Background: Chikungunya virus (CHIKV) diagnosis have become a challenge for primary care physicians in areas where zika virus and/or dengue virus are present. Case definitions for the three arboviral infections are overlapping. Methods: A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analyzed in multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance. Results: 295 patients with confirmed CHIKV infection were included. A screening tool was made using symmetric arthritis (4 points), fatigue (3 points), rash (2 points) and ankle joint pain (1 point). The ROC curve identified a cut-off value and a score ≥ 5.5 was considered positive to identify CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%. Conclusion: We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.

The use of machine learning (ML) approaches to target clinical problems is called to revolutionize clinical decision-making. The success of these tools is subjected to the understanding of the intrinsic processes being used during the classical pathway by which clinicians make decisions. In a parallelism with this pathway, ML can have an impact at four levels: for data acquisition, predominantly by extracting standardized, high-quality information with the smallest possible learning curve; for feature extraction, by discharging healthcare practitioners from performing tedious measurements on raw data; for interpretation, by digesting complex, heterogeneous data in order to augment the understanding of the patient status; and for decision support, by leveraging the previous step to predict clinical outcomes, response to treatment or to recommend a specific intervention. This paper discusses the state-of-the-art, as well as the current clinical status and challenges associated with each of these tasks, together with the challenges related to the learning process, the auditability/traceability, the system infrastructure and the integration within clinical processes.

During the Renaissance, Leonardo Da Vinci was the first person to successfully detail the anatomy of the aortic root and its adjacent structures. Ever since, novel insights into morphology, function and their interplay have accumulated resulting in advanced knowledge on complex functional characteristics of the aortic valve (AV) and root. This shifted the vision from the AV as being a static structure towards that of a dynamic interconnected apparatus within the aortic root as a functional unit, exhibiting a complex interplay with adjacent structures via both humoral and mechanical stimuli. This paradigm shift has stimulated surgical treatment strategies of valvular disease that seek to recapitulate healthy AV function, whereby AV disease can no longer be seen as an isolated morphological pathology which needs to be replaced. As prostheses still cannot reproduce the complexity of human nature, treatment of diseased AVs, whether stenotic or insufficient, has tremendously evolved with a similar shift towards treatments options that are more hemodynamically centered such as the Ross procedure and valve-conserving surgery. Native AV and root components allow for an efficient Venturi effect over the valve to allow for optimal opening during the cardiac cycle, while also alleviating the left ventricle. Next to that, several receptors are present on native AV leaflets, enabling messenger pathways based on their interaction with blood and other shear-stress related stimuli. Many of these physiological and hemodynamical processes are under acknowledged but may hold important clues for innovative treatment strategies, or as potential novel targets for therapeutic agents that halt or reverse the process of valve degeneration. A structured overview of these pathways and their implications for cardiothoracic surgeons and cardiologists is lacking. As such, we provide an overview on embryology, hemodynamics, and messenger pathways of the healthy and diseased AV and its implications for clinical practice, by relating this knowledge to current treatment alternatives and clinical decision-making.

Patient value is an important factor in clinical decision-making, but conventionally, it is not incorporated in the decision processes. In this paper, a value-based therapy recommendation comprehensive model is proposed. A literature analysis is conducted to collect value-based evidence. Categorized values and candidate therapies are used in combination as filtering keywords to build this evidence. Then a formalism model is put forward to integrate the value-based evidence with clinical evidence. The relative importance of two evidence can be adjusted dynamically by decision-makers during the decision-making processes. A prototype system was implemented using a case study for breast cancer and validated for feasibility and effectiveness.

This study focused on the development and implementation of an educational simulation program based on Korean Triage and Acuity Scale (KTAS) for nurses in emergency medical centers who completed KTAS training. We also examined its educational effects based on the evaluation of clinical decision-making ability, job satisfaction, and customer orientation. The study participants were 30 nurses in the emergency medical center of a general hospital. Data were collected from May 3 to 24, 2017, and analyzed using SPSS 22.0. There was a significant difference in the mean scores in clinical decision-making ability, job satisfaction, and customer orientation before and after simulation education. In other words, emergency nurses who received KTAS-based simulation education program improved their clinical decision making ability, job satisfaction, and customer orientation. Based on the results of this study, it is expected that it can be used for KTAS education, and it was found that simulation-based education is a useful learning method for triage nurses in emergency medical center.

Admission and discharge diagnoses of in-hospital patients are often in discord. Incorrect admission diagnoses are related to increased cost of care and patient safety. Additionally, due to the seasonality of many conditions, this discord may vary across the year. In this paper, we used medical claims data to develop a methodological framework that examines these differences, for Medicare beneficiaries. We provide examples for pneumonia, a condition with seasonal implications, and aneurysm, where early detection can be life-saving. Following a Bayesian approach, our work quantifies and visualizes with time series plots the degree that any clinical condition is correctly diagnosed upon admission. We examined differences in weekly intervals, during a calendar year. The mean length of stay and hospital charges were furthermore compared between matching and non-matching {admission, discharge Dx} pairs, and 95% confidence intervals of the difference of means were estimated. We applied Statistical Process Control methods and then visualized differences, for the hospital charges and the length of stay, per week, with time series plots. Our methodology and the visualizations underline the importance of a rigorous and non-delayed diagnostic process upon admission since there are significant implications in terms of hospital outcomes and cost of care.

Comorbidities can have a cumulative effect on hospital outcomes of care, such as the length of stay (LOS), and hospital mortality. This study examines patients hospitalized with Congestive Heart Failure (CHF), a life-threatening condition, which, when it coexists with a burdened disease profile, the risk for negative hospital outcomes increases. Since coexisting conditions co-interact, with a variable effect on outcomes, clinicians should be able to recognize these joint effects. In order to study CHF comorbidities, we used medical claims data from CMS. After extracting the most frequent cluster of CHF comorbidities, we: (i) Calculated, step-by-step, the conditional probabilities for each disease combination inside this cluster (ii) Estimated the cumulative effect of each comorbidity combination on the LOS and hospital mortality (iii) Constructed (a) Bayesian, scenario-based graphs and (b) Bayes-networks to visualize results. Results show that, for CHF patients, different comorbidity constructs have variable effect on the LOS and hospital mortality. Therefore, dynamic comorbidity risk assessment methods should be implemented for informed clinical decision making in any ongoing effort for quality of care improvements.

Knowledge of clinical approaches and barriers in managing childhood myopia is limited. This study explores optometrists' knowledge, attitude, and practice towards childhood myopia. A 26-item survey was circulated online among practising optometrists in India. The questionnaire assessed the demographics, knowledge, self-reported clinical practice behaviour, barriers, source of information guiding their management, and extent of adult caregiver engagement for childhood myopia. Of 393 responses, a significant proportion of respondents (32.6%–92.4%) were unaware of the ocular complications associated with high myopia, with less than half (46.5%) routinely measuring axial length in clinical practice. Despite the improved awareness of emerging myopia management options, the uptake remains generally poor, with single-vision distance full correction spectacles (70.3%) being the most common mode of vision correction. Barriers to adopting emerging evidence are medico-legal concerns and the absence of clinical practice guidelines. Original research articles were the primary source of information supporting clinical practice. Most (>70%) respondents considered involving the adult caregiver in their child's clinical decision-making process. While practitioner knowledge, perspective, and practice are improving, childhood myopia management evidence is constantly evolving and remains inconclusive. Evidence-based practice guidelines and continuing education on myopia control might be helpful for practitioners in improving their clinical decision-making skills.

Background: Media coverage of Lyme disease (LD) has led to an increase in consultations for presumed LD in Europe. However, LD is confirmed in only 10-20% of patients, with a significant number remaining in a diagnostic dead-end. Objectives: To reach a deeper understanding of how patients themselves contribute to the diagnostic process. To describe the genesis of the LD hypothesis in care pathways. Methods: In 2019, 30 patients from a prospective cohort consulting in the infectious diseases department at University Hospital in Marseille for presumed LD were recruited for semi-structured interviews. The inclusion criteria were : suffering from subjective symptoms for 6 months, no clinical or paraclinical argument suggesting current LD. The patients’ medical trajectories were collected using a biographical approach. Results: The diagnosis of Lyme disease was primarily triggered by identification with personal testimonies found on the internet. Most of patients were leading their own diagnostic investigation. The majority of participants were convinced they had LD despite the lack of medical evidence and the scepticism of their referring GP. Conclusion: GPs should first systematically explore patients’ etiologic representations in order to improve adherence to the diagnosis especially in the management of medically unexplained symptoms. Long COVID-19 syndrome challenge offers an opportunity to promote active patient involvement in diagnosis.

Optoacoustic imaging is an emerging technology that holds great promise for improving general clinical practice since it offers a unique combination of optical absorption contrast, high resolution, and high penetration depth. This combination of factors provides a distinct advantage over alternative imaging modalities in oncology, cardiology, dermatology, or endocrinology among other medical fields. Optoacoustic technology affords the medical practitioner the possibility of visualizing light-absorbing biomolecules like water, lipids, oxy/deoxy hemoglobin, or melanin in deep tissue with relatively cheap and small form factor instruments, without the need of contrast agents or ionizing radiation. Moreover, exogenous fluorescent contrast agents like indocyanine green or methylene blue can also be observed. Driven by its potential for new applications in the clinic, the field has experienced intense changes in the last 20 years. Continuous technological advancements in instrumentation, image formation methods, or acquisition geometries, have led to the development of numerous clinical devices also motivating the creation of several startup companies that aim to translate the technology from the lab to the clinic. Thus, the question arises: how far are we from clinical adoption? In this article, we aim to shed light on such question by reviewing the clinical studies that have been performed in the last 10 years. Our intention is to go beyond the classical review format by providing a brief general overview of the steps that new imaging methods undergo on their journey from the lab to clinical adoption. Then we examine the progress that optoacoustic technology has made on such a journey.

Background: Good clinical practice (GCP) training is the industry standard for ensuring the quality conduct of registrational clinical trials. However, concerns have been raised about whether the current structure and delivery of GCP training sufficiently prepares clinical investigators and their delegates to conduct clinical trials. Methods: We conducted qualitative semi-structured interviews with 13 clinical investigators and 10 research sponsors to 1) examine characteristics of the quality conduct of sponsored clinical trials, including critical tasks and concerns perceived as essential for trial quality, 2) identify key knowledge and skills required to perform critical tasks, and 3) identify gaps and redundancies in GCP training and areas of improvement to ensure the quality conduct of clinical trials. We used applied thematic analysis to analyze the data. Results: The top three tasks identified as critical for the quality conduct of clinical trials were obtaining informed consent, ensuring protocol compliance, and protecting participants’ health and safety. Respondents acknowledged that GCP principles address each of these critical tasks; however, they described many challenges and burdens of GCP training, including high training frequency and repetitive content. Respondents suggested moving beyond GCP training as a mere check-box activity by making it more effective, engaging, and interactive. They also emphasized that applying GCP principles in a real-world, skills-based environment would increase the relevance of GCP training to investigators and their delegates. Conclusion: Our findings indicate that although investigators and sponsors recognize that GCP training addresses critical tasks necessary to the quality conduct of clinical trials, they articulated the need for significant improvement in the design, content, and presentation of GCP training.

Obstructive Sleep Apnea (OSA) is nowadays one of the respiratory pathologies with a higher in-cidence globally in developed countries. This situation led to an increase in the demand for medical appointments and diagnostic studies related to that condition, especially those based on poly-somnographies and cardiorespiratory polygraphies. These studies are limited in resources, causing long waiting lists with the subsequent impact on the patients’ health. Furthermore, it is necessary to mention that OSA’s symptomatology is not very specific, and it is typically present in the general population (excessive sleepiness, snore, etc.). In this regard, this paper proposes a novel intelligent clinical decision support system for the diagnosis of OSA which could be used to help medical teams, both in primary care settings and in units specialized in respiratory pathologies. The aim of the proposed system is to help discriminate the patients suspected of suffering from the pathology from those who are not. To this end, two types of information sets of heterogeneous nature are consid-ered. The first one encompasses objective data, related to the patient's health profile with infor-mation usually available in electronic health records. The second type comprises subjective data, referred to the symptomatology reported by the patient in a previous interview. To process the first group of information, a Machine Learning classification algorithm is used, Bagged Trees in this case. For processing the second information set, related with the symptomatology of the patient, a col-lection of expert systems based on fuzzy inferential systems arranged in cascade are employed. As a result, the system is able to determine two risk indicators related to the patient's risk of suffering from OSA: the Statistical Risk and the Symbolic Risk respectively. Subsequently, by interpreting both risk indicators mentioned it will be possible to determine the severity of the patients’ health, proposing a preliminary evaluation on their condition. For the initial tests of the system, a software artifact has been built using a dataset with 4,978 selected patients, suspected of suffering from OSA, from the Álvaro Cunqueiro Hospital in Vigo. The results obtained are promising, demonstrating the potential usefulness of this type of tools in medical diagnosis. Once the system has been validated with new data from clinical environments, it is considered as possible to obtain a relevant improvement in the quality of the healthcare services, and a reduction in the associated costs.

This paper formulates the performance evaluation of cloud services as a multicriteria group decision making problem, and presents a fuzzy multicriteria group decision making method for evaluating the performance of cloud services. Interval-valued intuitionistic fuzzy numbers are used to model the inherent subjectiveness and imprecision of the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to ideal solution method and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented to demonstrate the applicability of the proposed fuzzy multicriteria group decision making method for solving the multicriteria group decision making problem in real world situations.

Objectives: This study aims to identify, report, and analyze registered and published clinical trials and observational studies for the pharmacological treatment of COVID-19 conducted in China. Methods: A strategic search was conducted via the Chinese Clinical Trial Registry to identify and extract clinical trials and observational studies registered and conducted in China for the pharmacological treatment of COVID-2019 between January 1^st, 2020 and March 21^st, 2020. This was further supplemented by searches conducted via the China National Knowledge Infrastructure (CNKI) database, the MEDLINE database, the World Health Organization (WHO) database, and MedRxiv and BioRxiv electronic platforms for preprint articles, published up until April 8^th, 2020. Studies available in Chinese and English were included in the searches and extracted. A primary descriptive analysis was performed for registered clinical trials and observational studies identified in the Chinese Clinical Trial Registry based on the extraction of the following clinical study information: trial ID, planned date of enrollment, recruitment status, study design, population, sample size, intervention/exposure group, control /reference group, dosage, and primary outcomes. A secondary descriptive analysis was performed for published clinical trials and observational studies identified from the supplementary databases based on the extraction of the following published clinical study information: study design, population, intervention/exposure group, control /reference group and main results as appropriate. Results: A total of 221 clinical trials and observational studies were included from all databases searched. From the Chinese Clinical Trial Registry, 195 registered clinical studies including 170 clinical trials and 25 observational studies were identified and included for primary analysis. From the supplementary databases, 26 published clinical studies including 8 clinical trials and 18 observational studies were included for secondary analysis. Of these 26 published clinical studies, 18 studies, including 3 clinical trials and 15 observational studies were identified from CNKI, 2 studies including 1 clinical trial and 1 observational study from MEDLINE, 2 including 1 clinical trials and 1 observational studies from the WHO database, and 4 including 3 clinical trials and 1 observational studies from MedRxiv and BioRxiv platforms. In the primary analysis, among the 170 clinical trials included from the Chinese Clinical Trial Registry, 101 investigated western medicines (WMs), while 15 investigated Traditional Chinese Medicines (TCMs), and 54 investigated a combination of TCMs and WMs. Among the 25 included observational studies from the Chinese Clinical Trial Registry, 2 investigated WMs, 2 investigated TCMs, and 21 investigated a combination of TCMs and WMs. The total number of exposed patients in all 195 clinical studies from the Chinese Clinical Trial Registry amounted to 24,500. In the secondary analysis, treatment with Lopinavir-ritonavir and treatment with Hydroxychloroquine was not associated with a difference from standard of care in the rate of RT-PCR negativity; treatment with a combination of Lopinavir-ritonavir, interferon α, and Lian-Hua-Qing-Wen capsule was found to significantly improve the effective rate of treatment compared with Interferon α combined with Lian-Hua-Qing-Wen capsule. Conclusions: China is generating a massive source of evidence that is critical for defeating the COVID-19 pandemic. Not only the clinical experience, but also the scientific evidence should be shared with the global scientific community.

The Clinical Trials Transformation Initiative (CTTI) Investigator Qualification Project addresses the need for a more efficient and effective means of identifying qualified clinical investigators and delegates. Selection of investigators and delegates who are qualified by training and experience to conduct clinical trials is essential to safeguarding protections for study participants and ensuring data quality and integrity. Sponsors generally document investigator qualification through training on the principles of good clinical practice (GCP), as defined by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), adopted by regulatory authorities in the US, Japan and the European Union. Although these GCP principles provide an important foundation for promoting the conduct of quality clinical trials, the industry standard “one-size-fits-all” GCP training may not fully prepare investigators and delegates for conducting quality clinical trials. Routine GCP training alone may not be sufficient to prepare an inexperienced member of a site team, while repeating such training is unlikely to enhance the qualifications of an experienced researcher. The CTTI project team used findings from qualitative research activities, as well as input from an expert meeting with multiple stakeholders, to identify gaps and redundancies in the current training of investigators and their delegates and recommend practical, action-based solutions. CTTI provides recommendations on how to implement a more efficient and effective means of qualification for investigators and delegates, determine whether a site team is a good fit for a particular protocol, and improve the quality of clinical trial conduct.

Multicompartment compliance aids (MCAs) are devices with each discrete section denoting a single dosing occasion. The purpose of an MCA is to maximize patient adherence and thereby optimize the treatment benefits. These devices are widely employed throughout western Europe and UK and use appears to be rapidly increasing (2) although the RPS as moved away from these devices as a means to improve adherence. We analysed MCAs from various pharmacies over a wide geographic area in England and North Wales. We concluded that most MCA users are elderly patients. Also, most of the patients suffer of combined cardiovascular disease. However, a significant proportion of patients falls in the mental/ neurological disease category. Additionally, most of the externals added to MCAs are inhalers and painkillers. Moreover, SDIs are more frequent in female patients and these SDI are mainly related with mental health medication, cardiovascular disease medication and neurological medication. In conclusion, a directive for dispensing of MCAs in pharmacies by pharmacists through an enhanced service should be elaborated having in consideration PIMs, SDIs, drug stability and use of externals and MCA design and brand.

This study aimed to determine clinical instructors’ perceptions of the assessments used to evaluate the clinical knowledge of undergraduate nursing students. This study uses a descriptive phenomenological approach. Purposive sampling was used to recruit sixteen clinical instructors for semi-structured interviews between August to December 2019. All interviews were audio-recorded and transcribed verbatim. Data were analyzed using Colaizzi’s seven-step method. Four criteria were used to ensure the study’s validity: credibility, transferability, dependability, and confirmability. Three themes were identified in the clinical instructors’ views on evaluating the clinical performance of student nurses: familiarity with students, patchwork clinical learning, and differing perceptions of the same scoring system. Study results suggest the need for a reliable, valid, and consistent approach to evaluating students’ clinical knowledge. If the use of patchwork clinical internships for student nurses is unavoidable, a method for assessing student nurses’ clinical performance that requires instructor consensus is necessary.

Background: Consciousness is usually interpreted as a state of being aware of one’s environment as well as self. According to the trilogy paradigm of consciousness (or simply “trilogy”), it is primarily guided by two new mental functions—awareness-based choice selection (ABCS) and discretionary selection of information for awareness (DSIA) or intentional attention—which may play a role in the choice selection during decision making. Method: To test whether ABCS and DSIA could improve the choice selection efficiency, 204 subjects were recruited using social media platforms to complete an anonymous online survey. The survey was designed to examine the role of subtle hints and cues in guiding participants’ attention toward a particular subject of awareness and this in return would increase the likelihood of selecting a correct choice among the proposed options, thereby enhancing the decision-making efficacy. Results: The participants’ attention could be successfully swayed to a particular subject matter (DSIA) in 59−73% of occasions. In addition, using ABCS increased the efficiency of selecting a correct choice among presented options. The analyses further revealed a gap between the selecting a choice during decision-making process and its execution, which is indicative of an appropriation process. Conclusion: The present study shows that sheer knowledge of facts may not be sufficient for selecting a correct choice among presented options effectively. However, as ABCS improves the choice selection efficiency, it plays an instrumental role in determining the subject of awareness, indirectly supporting the notion of DSIA.

Nowadays the freedom to make choices is considered of vital importance for decision-makers. Researchers investigating the psychological effects of choice provided empirical evidence about the many advantages of choice (i.e., increased intrinsic motivation, greater perception of self-determination, better performance, and greater life satisfaction). However, more recent studies demonstrated the downsides of choice. When the decision task difficulty exceeds the natural cognitive resources of human mind, the possibility to choose becomes more a source of unhappiness and dissatisfaction than an opportunity for a greater well-being. We here discuss in a detailed fashion the main findings of research in psychology and consumer behavior showing the bright sides and the downsides of choice.

Lymphoma diagnoses in the U.S. are substantial, with an estimated 89,380 new cases in 2023, necessitating innovative treatment approaches. Phase 1 clinical trials play a pivotal role in this context. We developed a binary predictive model to assess trial adherence to expected average durations, analyzing 1,089 completed Phase 1 lymphoma trials from clinicaltrials.gov. Using machine learning, the Random Forest model demonstrated high efficacy with an accuracy of 0.7248 and ROC-AUC of 0.7701 for lymphoma trials. Importantly, this model maintained an accuracy of 0.7405 when applied to lung cancer trials, showcasing its versatility. A key insight is the correlation between higher predicted probabilities and extended trial durations, offering nuanced insights beyond binary predictions. Our research contributes to enhanced clinical research planning and potential improvements in patient outcomes in oncology.

Genome-based testing in oncology is a rapidly expanding area of health care which is the basis of the emerging area of precision medicine. Efficient and considered adoption of novel genomic medicine testing is hampered in Canada by the fragmented nature of health care oversight as well as by lack of clear and transparent processes to support rapid evaluation, assessment and implementation of genomic tests. This article provides an overview of some key barriers and proposes approaches to addressing these challenges as a potential pathway to developing a national approach to genomic medicine in oncology.

Worldwide, the cesarean section rate has steadily increased from 6.7% in 1990 to 21.1% in 2018 and is expected to rise even more. World Health Organization propose the adoption of the Robson classification system as a global standard for monitoring, evaluating, and comparing delivery rates. The purpose of the current study is to use the Robson classification system to investigate how, independently of medical factors, the day of the week and time of delivery may affect the mode of birth. In the sample analysis, we included the records of 8572 women giving birth in one private health facility in Greece. Over 60% of deliveries during the study period were performed by a cesarean section and 8.5% of deliveries were performed by operative vaginal delivery. The results of this study indicate that the lowest birth rates are observed on Monday, Saturday, and Sunday. In Robson category 1 women are 73% more likely to deliver by cesarean section between 08:00 a.m. - 03:59 p.m. compared to those who give birth between 12:00 a.m. - 07:59 a.m. Also, women in group 5.1 are 16.7 times more likely to deliver by cesarean section in the morning compared to overnight deliveries. These result point out two non-clinical variables that influences the CS rate. The Robson classification system was a useful tool for the above comparisons.

Rare diseases are characterized by a wide diversity of signs and symptoms and vary not only from disease to disease, but also from person to person, and living with a disease leads patients to peculiar experiences and treatments, without limits of time and space, as they extend to various environments and relationships of their lives. The objective of this study is the theoretical interaction between Value Co-creation (VC) and the Stakeholder Theory (ST) with the Shared Decision Making (SDM) health care theory. It is configured as a multiparadigmatic proposal by enabling the analysis of multiple perspectives of different stakeholders in health care. Thus, Co-created Decision Making (CDM) emerges in a logic dominated by service, with emphasis on intangible aspects and the interactivity of the relationships. It goes beyond the clinical office and the doctor-patient relationships, as studied in SDM, extending to all environments and interactions that add value to the patient's treatment. It was concluded that the essence of this new theory proposed here is neither in patient-centered care nor in patient self-care, but in co-created relationships with and between stakeholders in both directions, including non-health care environments that are important to the patient, such as relationships with friends, family, other patients with the same disease, social media, public policies, and the practice of pleasurable activities.

Clinical trials, by contributing to the development of diagnostics and to the search for modern, more effective, and safer therapies, have become one of the most important elements of the healthcare system. The aim of this study was to assess Poles' knowledge and beliefs about clinical trials. Methods: The survey was conducted among Poles aged 18 and over with the help of external company, Ariadna, which is an independent research panel. The questionnaire contained 22 questions, of which 13 questions concerned beliefs and attitudes towards clinical trials. Results: One thousand and seventy-nine participants took part in the study (N = 1079). The mean age of respondents was 44.96 years (SD = 16.30). Slightly more women (N = 568, 52.6%) than men (N = 511, 47.4%) took part in the study. Among the respondents, 86.5% (N = 933) were aware of clinical trials. The main sources of information about clinical trials were the media (53.8%) including the Internet (N= 355, 32.9%), TV (N = 175, 16.2%), press (N = 30, 2.8%) and radio (N = 21, 1.9%). 43.2% (N = 466) of respondents reported little knowledge of clinical trials, while more than three quarters (N = 805, 75.2%) said they would like to learn more about clinical trials. Most respondents (N = 879, 81.4%) agreed with the statement that participation in a clinical trial is completely voluntary, and more than half (N = 580, 53.7%) agreed with the statement that hospitals participating in clinical trials provide better healthcare. The statement that the results of clinical trials are made available to the public was disagreed with by 37.2% (N = 402) of participants. Only 30.3% (N = 327) of participants agreed that clinical trials should be conducted with children. Conclusions: Poles rate their knowledge of clinical trials as low and would like to learn more. To reach the largest possible group of Polish patients, parallel educational activities on multiple levels may have the best effect. Poles' knowledge of clinical trials is mainly based on commercial sources. Further studies in different groups, i.e., clinical trial patients and investigators, are needed.

Objectives: Data sharing has become a requirement of many funding bodies and is becoming a scientific standard in many disciplines. In medical research, however, data sharing can conflict with clinicians’ obligation to protect patients’ privacy. General recommendations on data sharing exist also for clinical research, but so far lack practical and Swiss-specific aspects. The objective of this document is to provide practical recommendations for all relevant aspects of data sharing in agreement with legislation in Switzerland. Methods: This document was written by members of the Swiss CTU Network, a network of academic clinical trial units. The process did not follow a formalized Delphi process. After an internal consensus round, this report is now published as pre-print for external review. A second version will incorporate external comments. We plan to publish this document as a text in progress, as we expect relevant changes in related fields such as the development of further dedicated medical repositories or methodological advances in anonymization techniques. Results: We developed principles and practical recommendations with respect to informed consent, data management plan, anonymization, data structure and format, coding of variables, metadata and documentation, version control, selection of repository, requesting and use of data. We also provide a summary of legal aspects relevant for the Swiss context. Conclusions: The intension to share data has an impact not only after a clinical trial or an observational study is completed, but also during the planning period, the conduct and the analysis phase. Clinical researchers need to be aware at the beginning of a study on how to inform patients and at least the amount of work related to preparing data for sharing, metadata, and any further documentation. This report provides details of aspects to be considered, suggests decision criteria, and provides examples and checklists, in order to support data sharing in practice.

Clinical education is a method that is applied to formal nurse education as a step to provide real and direct learning experiences in the nursing environment correctly and effectively. The success of education in a clinical setting certainly requires the support of teaching nurses (clinical instructors) who have credibility and competence in terms of knowledge, attitudes and skills and are actively involved in professional activities. The diversity of backgrounds of nurses and students, including patients, certainly contributes to a shift in paradigms and perspectives for the nursing environment both in education and in clinical settings in health services. Responding to this cultural diversity, it is important to prepare knowledge and understanding related to transcultural nursing issues, intercultural communication and clinical education which explores the socio-cultural elements in the implementation of staff, students and patients. Purpose: The purpose of this literature review is to identify the extent to which nurse educators play a role by including socio-cultural and transcultural aspects in efforts to develop the quality of education in clinical practice environments in the millennium era. Method: The method of writing this article uses 11 literature review, the publication year period 2019,2020 and 2021 with sources from 4 databases such as science Direct, Scopus, ProQues and Elsevier. The review guidelines used are based on Prisma and the Joanna Briggs Institutute. The level of eligibility is identified through the title, abstract, research methodology as well as the type of scholarly journal and full text. Results: The results of the reviews found are presented in a narrative form. The results of the review study found that there were 11 articles explaining the competence of clinical education based on the socio-cultural approach, which is an educational strategy in the clinical area that integrates transcultural elements of nursing, intercultural communication, collaboration, self-directed with the principles of openness, honesty, and mutual respect in the implementation of team interaction and collaboration. The development of interpersonal relationships is also an important role that educators must have in helping to introduce the nurse orientation process to the organizational environment and other professional teams so that the achievement of satisfaction with clinical education is able to improve the performance of nurses and students perfectly. Conclusion: Clinical education which is supported by the competence of nurse educators (clinical instructors) who have individual and professional competences has a role to play in improving clinical learning outcomes by both students and nurses with a socio-cultural and transcultural strategic approach that will create satisfaction with the achievement of clinical competence and performance effectively.

This article offers a pragmatic ‘epistemology of wargaming’ which views wargames as immersive ‘thought experiments’ in which the human players involved use their experiential, empirical, and theoretical knowledge – together with whatever cognitive models they are able to deploy, or develop anew – to generate a conceptual, operational understanding of the adversarial scenario in which they are immersed; and exploit this understanding to craft tactical decisions designed to optimise the likelihood they will achieve their strategic objectives. From this perspective, contemporary interest in the use of ‘AI’-enabled tools to augment the validity of wargaming outputs – where these outputs constitute the decisions players make and the insights such decisions reveal – might most purposefully focus on: the design and implementation of wargames (to strengthen the architecture these provide to support immersive decision-making); and the analysis of players’ decisions (to better understand the cognitive models these involve and reflect). While the focus we suggest might disappoint those keen to replace human players with (semi-) autonomous decision-making machines, as long as the principal objectives of wargaming are to assess and enhance the decision-making capabilities of human players and human personnel, ‘AI’-enabled applications can only ever play a supporting role (albeit a potentially invaluable one) in the design, presentation, implementation, and analysis of wargames. As Irving Berlin might have it: ‘AI’ might soon be able to do most things better than us, but it can never replace humans when only a human will do.

Safety is very important in aviation since a loss of safety frequently results in both fatalities and financially damaging situations that are typically unrecoverable. Thus, achieving safety as much as possible is the primary goal of practically all aviation technology work. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based classifier is created to estimate the fault risk factor of airplanes. Five categories of real fleet data belonging to structure, electrical, avionic, motor systems, and incident statistics of the planes have been used for classifier development. A risk factor determination for each plane is the output of the developed intelligent classifier, and it can be used to identify general overhaul candidate planes and stop defects and crashes before they happen. The obtained results show that using ANFIS provides a great capability in processing many inputs and outputs depending on different types and classes in the aviation industry and thus predicting the failure risk of the airplane efficiently.

This thesis presents findings from an online experiment aimed at evaluating individuals' attitudes towards their own cognitive biases that lead to objective mistakes. In a number of incentivized decision problems, a participant in the experiment might make a mistake and choose a dominated lottery (FOSD lottery), which is likely to result from a particular heuristic or cognitive bias. In this case, she is then confronted with her error under one of two treatments: a confrontation with an explanation only regarding the mistake or one with the addition of the supposed mechanism (bias). Following this explanation, her comfort level with her choice is measured. A bias that acted as a mechanism for the observed error could be considered advantageous (i.e., useful given alternative costs) or disadvantageous (i.e., mostly harmful) in other decision-making scenarios encountered during one's lifetime. Consequently, the perception of cognitive biases is subjective and may vary among decision makers, who may emphasize either the positive or negative aspects of such biases. The proposed methodology allows to determine whether these biases are perceived as useful rules of thumb, despite leading to a dominated lottery choice in that particular context, or unfavorable.Results revealed significant differences between the two treatments and across five different decision problems. Interestingly, the results showed that in only 60% of the cases, the participants felt uneasy about their mistakes. In the remaining instances, the participants demonstrated either indifference or a sense of comfort with their choice of a dominated lottery. The net effect of providing information on the cognitive biases that presumably lead to the mistakes, measured as the difference between treatments, revealed a negative perception of the mechanism behind the error in one problem, contentment with the mechanism for another, and no significant effect for the remaining biases.

Little is known about fertility preservation within the TGD community. Few receive adequate counseling placing them at risk for decision regret. The goal of this project was to develop, and pilot test the Transgender Fertility Preservation Knowledge Scale (TFPKS) to support the development and evaluation of health education resources. A community engaged; cross sectional retrospective design was used. Participants (n=189) provided information describing demographics, healthcare decision-making preferences, experiences/knowledge of fertility preservation, and treatment decision regret. The sample included 189 TGD adults. Most were white and aged 26-35 (33.3%) and not offered a consultation (73.0%). Many (41.2%) report they would have participated if offered. Knowledge regarding fertility preservation to support this desire was low. Most participants identified a patient-centered (69.4%) decision making preference. Much remains to address the healthcare inequities within the TGD population regarding fertility preservation. Overall participants had low levels of knowledge to support decision making. Further, healthcare system and individual barriers to fertility preservation remain prevalent. A foundational step towards addressing these disparities, is the identification of a valid and reliable instrument to measure TGD knowledge of fertility preservation.

Re-creation of the past of historical buildings sits at the intersection of the spatio-temporal manifestation of cultural memories, socio-cultural meanings, values and identity re-moulds and refines the existing understanding and sense of place. Digital technologies have become a popular tool in re-creation of the past by creating a new body of knowledge and historical discourse based on identifying the gaps within our written histories. Designers and policymakers around the world have been exploring various tools and technologies such as diachronic modelling yet there is a gap in evidence-based understanding regarding the actual functioning and success of application for place making. This paper, therefore, sets out to scrutinise the role of digital technologies in facilitating digital place making. To do so, it investigates the potential of a new “digital heritage” narrative in the revival of the lost architectural narrative of the Dennys Lascelles Wool Store, Geelong. The proposed paper aims to investigate the potential of a new “digital heritage” narrative and story-telling as a means towards digital place making framework. While exploring the new and unique capabilities provided by the digital narrative in capturing, simulating and disseminating ‘lost’ heritage it will further imbue a sense of place by connecting the everyday city dweller.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. It is commonly diagnosed in advanced stages and therapeutic interventions are typically constrained to systemic chemotherapy, which yields only modest clinical outcomes. In this review, we examine recent developments in targeted therapy tailored to address distinct molecular pathway alteration required for PDAC. Our review delineates the principal signaling pathways and molecular mechanisms implicated in the initiation and progression of PDAC. Subsequently, we provide an overview of prevailing guidelines, ongoing investigations, and prospective research trajectories related to targeted therapeutic interventions, drawing insights from randomized clinical trials and other pertinent studies. This review focus on a comprehensive examination of preclinical and clinical data substantiating the efficacy of these therapeutic modalities, emphasizing the potential of combinatorial regimens and novel therapies to enhance the quality of life for individuals afflicted with PDAC. Lastly, the review delves into the contemporary application and ongoing research endeavors concerning targeted therapy for PDAC. This synthesis serves to bridge the molecular elucidation of PDAC with its clinical implications, the evolution of innovative therapeutic strategies, and the changing landscape of treatment approaches.

Background The coronavirus pandemic has led to the creation of clinical guidelines by a large number of professional medical communities. However, the quality and methodology of development of Russian clinical guidelines has been little studied. The continued relevance of studying the use of DOACs in patients with COVID-19 was the basis for conducting this study. Aim The objective of this study was to assess DOACs consumption and expenditures in Russian Federation during COVID-19 pandemic and to analyse domestic evidence base for the use of DOACs in COVID-19 patients through identifying all publicly available Russian-produced CPGs for the treatment of COVID-19 and assessing their quality as the source of recommendations for the use of oral anticoagulants for the prevention of thrombotic complications in COVID-19 patients. Methods We searched Russian databases for CPGs, published between 2020 and 2023. We identified 7 relevant documents that met our inclusion criteria. Three authors analyzed Russian clinical guidelines using a AGREE II questionnaire. We calculated DOACs DDD consumption according to Russian clinical guidelines and DDD consumption in patients with COVID-19 for the period 2020-2022. Results 7 clinical CPGs were analyzed with the AGREE II tool, it was revealed that experts gave the highest scores for the sections scope and purpose (from 62.98% to 100%), clarity of presentation (from 96.30% to 100%). The lowest scores were given for the sections stakenholder involment (33.33% to 64.81%), rigour of development (from 0% to 49.31%), applicability (from 23.61% to 50%), editory independence ( from 0% to 50%). When comparing the total score, it was found that two clinical guidelines received the highest scores - ROPNIZ (Livzan), ROPNIZ (Drapkina). The minimum score is registered with the NIIOZMM (Khripun) clinical guideline. No guideline received a total score of more than 70%. According to clinical recommendations, the consumption of apixaban and rivaroxaban is 15 DDD (30-day course of therapy), 22.5 DDD (45-day course of therapy). Consumption of apixaban in the Russian Federation in 2020 and 2021 corresponds to the indicators presented in clinical recommendations (in 2020 – 26.59 DDD per patient with COVID-19; in 2021 – 15.75 DDD per patient with COVID-19), and in 2022 – 10.67 DDD, which is below the recommended values. In 2020, consumption of rivaroxaban in the Russian Federation was 26.59 which corresponds to data from clinical recommendations; in 2021, consumption decreased to 7.87 DDD; in 2022 – 5.48 DDD, which is 2.74 times less than recommended.

The transition from undergraduate dental student to the actual practicing dentist is a crucial phase and ensuring the preparedness of graduates for the complexity and demands of contempo-rary dental practice is a challenging task. This study aimed to evaluate the self-perceived prepar-edness of undergraduate dental students and house officers in the dental colleges of Pakistan. Cross-sectional national study was planned to collect the information from dental students and new graduates in Pakistan. The pre-validated Dental Undergraduates Preparedness Assessment Scale (DU-PAS) was used. Purposive sampling technique was utilized to recruit house officers and undergraduate dental students from 27 dental schools in Pakistan. The data analysis was car-ried out using the R statistical environment for Windows (R Core Team, 2015). The total of 862 responses with 642 females and 219 males were analyzed in the study. Overall, clinical skills score was 30.56+9.08 and score for soft skills was 30.54+10.6. The mean age of the participants was 23.42+1.28. Deficiencies were reported in various soft skills and clinical skills attributes.The results highlighted the strengths and weaknesses of dental students and new graduates in Pakistani den-tal institutions. The findings may be used to further develop and strengthen teaching and training of dental students in Pakistan.

Scientific, technical and bioinformatics advances have made it possible to establish analytics-based molecular biosimilarity for the approval of biosimilars. If the molecular structure and other product- and process-related attributes are comparable within the limits of testing then a biosimilar candidate would have safe safety and efficacy as its reference products. The current model of animal and human testing becomes redundant since all of these studies have much lower sensitivity and reproducibility in confirming biosimilarity. The recent AI-based protein structure prediction model has confirmed that the 3D structure can be predicted from the amino acid sequence, reducing the need for structural analysis; however, the new test methods based on MS are millions of times more sensitive and accurate. While the regulatory agencies have begun waiving animal testing and, in some cases, clinical efficacy testing, removing clinical pharmacology profiling brings a dramatic paradigm shift, reducing development costs without compromising safety and efficacy. Also shared is a list of 160+ products ready to enter as biosimilars. Major actions from regulatory agencies and developers are required to make this paradigm shift.

COVID-19 is causing major turmoil around the globe, and the clinical trial industry is likely to face unprecedented challenges to health and business sectors. In an effort to find a suitable treatment and prevention options for COVID-19, several COVID-19 clinical trials are being planned and initiated, while a large number of clinical trials for non- COVID-19 indications are suffering delays. With over more than 1000 trials being disrupted and more trials being added to this category daily, there is a direct impact on trial site activation and patient enrolment. This analysis deals with the specific impacts of the COVID-19 pandemic on the clinical trial and pharmaceutical industry. The objective of this study is to provide an updated information of the disrupted clinical trials and its impact on various therapeutic areas and different drugs. Among the severely affected clinical trials, oncology and CNS trials are the hardest hit therapy areas.This article will certainly emphasize the need for advanced and innovative approaches to maintain the health of the clinical trial ecosystem by continuing the existing trials and the start of the new studies. We have to take and follow necessary actions to guarantee that the initiatives will not be locked during the COVID-19 pandemic, both for the treatment of patients and for the researchers to conduct decision-relevant clinical trials.

Machine safety is not only a prerequisite for successful production, but also the foundation for sustainability and growth of any manufacturing organisation. The latest approaches in this rapidly developing field are the integration of effective risk management tools and strategies into occupational health and safety (OHS) systems. In this article, using a specific example from practice, we will show how using multi-criteria decision making (AHP) support Machinery Safety Decision Making (MSDM) from the point of reducing losses. Using Classification and Regression Tree Analysis (CART), we estimated the efficiency, cost-effectiveness and thus the sustainability level of the relevant safety measures. These were proposed risk reduction measures that typically raised uncertainty among managers regarding the estimation of cost-effectiveness. The advantage of application decision trees approach is possibility to identify and establish relatively homogeneous groups of undesirable events and their impact on the organisation's objectives. A comprehensive model has been developed to support management decision making in manufacturing organizations in implementing and improving safety measures in line with manufacturing sustainability goals.

Investment management is a common process and practice used for achieving a desirable investment goal or outcome. Investment assessment should be carried out at various stages of project realization in accordance with capital investment volume. Investment risk management implies the effective control of all procedures and monitoring of risks in all phases of the investment project. Because of the reason that a single indicator in probability calculation of achieving optimal return from the investment does not exist, performing sufficiently reliable estimates of the quality of investments becomes a tedious task. There are many indicators, factors, and criteria required for consideration to reach the effective solution of the investment problem. Unfortunately, the systematic variation of economic situations in the marketplace stipulates the continuous and frequent changes of investment conditions and environment in which the investor should act and operate. Hence, the rules required for providing a reasonable quality of investment projects can be based only on investor’s management strategy and rely on investor’s intuition and practice. The importance of classification in investment management and decision making process is undeniable. The objects to be classified are described using assessments in accordance with various criteria which can be both quantitative and qualitative. With a competent formulation of the investment process, both methods are used in parallel. There exist various decision making approaches for the investment management, and simple additive weighting (SAW) is one of the well-known multi-criteria decision making (MCDM) methods aiming to provide an optimal decision for decision maker when solving various real-life problems, and particularly, investment problem. In this paper, fuzzy simple additive weighting (FSAW) method in group decision making is applied to undertake the capital investment expenditure for purchasing cars with the purpose of renting them to the public. The development of existing FSAW method is accomplished and this process involves the sensibility of outcomes to changes in the rate of fuzziness represented with decisions taken. Eventually, the degree of fuzziness involved in an analysis that directly attempts to model the immanent vagueness and imperfectness in particular precedency judgments made, is determined. A numerical example illustrates the importance and effectiveness of the suggested approach with the aim of ranking alternatives and hence, determining the most preferred alternative in MCDM problem.

Clinical pharmacists are employed at many hospital departments in Denmark, but not yet on the Faroe Islands. The purpose of this study was to test feasibility of a clinical pharmacist-led medication review service at the surgical ward of the National Hospital on the Faroe Islands. Hospitalised surgical patients were offered a medication review service by a clinical pharmacist. Identified drug related problems (DRPs) were classified according to the Pharmaceutical Care Network Europe (PCNE) model. The qualitative inputs from the ward’s staff were collected. In total, 42 patients with 171 identified DRPs were included. The majority of the DRPs concerned suboptimal effect and the safety of the drug treatment. The 49.6 % of the proposed medication changes were accepted by the ward physicians. According to the qualitative inputs, the interest for the service was greater among the younger physicians compared to the older ones, and among nurses compared to physicians. Identified barriers for the optimal service implementation were an absence of medication ordinations and poor visibility of pharmacist’s notes in electronic health records. For a successful implementation of the service, work on the physicians’ interest in an interdisciplinary cooperation and optimization of the electronic health records are warranted.

Pharmacogenomics may improve patient care by guiding drug selection and dosing, however this requires prior knowledge of the pharmacogenomics of drugs commonly used in a specific setting. The aim of this study was to identify a preliminary set of pharmacogenetic variants important in Southern Africa. We describe co-morbidities in 3997 patients from Malawi, South Africa, and Zimbabwe. These patient cohorts were included in pharmacogenomic studies of anticoagulation, dyslipidemia, hypertension, HIV, and breast cancer. The 20 topmost prescribed drugs in this population were identified. Using literature, a list of pharmacogenes vital in disposition of the top 20 drugs was constructed leading to drug-gene pairs potentially informative in translation of pharmacogenomics. The most reported morbidity was hypertension (58.4%), making antihypertensives the most prescribed drugs, particularly amlodipine. Dyslipidemia occurred in 31.5% of the participants and statins were frequently prescribed cholesterol lowering drugs. HIV was reported in 20.3% of the study participants with lamivudine/stavudine/efavirenz being the most prescribed antiretroviral combination. Based on these data, pharmacogenes of immediate interest in Southern African populations include ABCB1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLC22A1, SLCO1B1 and UGT1A1. Variants in these genes are a good starting point for pharmacogenomic translation programs in Southern Africa.

In recent years, the consumption of over-the-counter probiotics used to promote health has grown rapidly worldwide and become an industry. In medicine, various studies have proven that probiotics can help improve the immune system and intestinal health. They are usually safe, but in some rare cases, they may cause concerning adverse reactions. Although the use of probiotics has been widely popularized in the public, the results of many probiotics clinical trials are contradictory. Especially for the cancer patients, the feasibility of probiotics management to provide benefits by targeting cancer and lessening anti-cancer side effects requires further investigations. And this review summarizes the interactions between probiotics and the host and current pros and cons of applying probiotics in the cancer patients.

Background: Fertility is a crucial component of population maintenance and growth. A declin-ing fertility trend has been observed over the past two decades, and it continues. Objective: The aim of this research was to examine the level of fertility knowledge, factors in-fluencing fertility knowledge, and the relationship between fertility knowledge and the decision to have a child. Methods: A cross-sectional study was conducted on a sample of mothers in five hospitals on the Adriatic coast of the Republic of Croatia, involving 1541 mothers from September 2021 to De-cember 2023. The Cardiff Fertility Knowledge Scale was used for the research. Results: The participants were divided into two groups based on fertility status in women, spe-cifically the period of declining fertility in women. Group 1 included participants aged 18-31 with sustained fertility, and Group 2 included participants aged 32 and older experiencing de-clining fertility. Fertility knowledge was 58.9%. Women with higher educational status showed better results (62.3%). The most common sources of fertility knowledge were the healthcare sys-tem and the internet. Factors associated with the level of fertility knowledge included higher education, marital status, and higher economic status. Conclusion: The research results reveal a lack of fertility knowledge among participants, as well as an intention to have a child in later stages of life. The lack of formal education on this topic leads to information gathering from unreliable sources.

Preconception or prenatal carrier screening for hereditary deafness is an effective early intervention strategy to reduce the incidence of newborn deafness, but current research is limited. This study aimed to investigate the carrier frequencies of common deafness genes in the Chinese population and to follow up on pregnancy outcomes in high-risk couples. Carrier screening for common deafness genes in the Chinese population, including the GJB2 and SLC26A4 genes, was performed using next-generation sequencing technology. Of the 9,993 subjects screened, the carrier rate was 2.86% for the GJB2 gene and 2.63% for the SLC26A4 gene. Of the six high-risk couples, four made alternative reproductive decisions (three with prenatal diagnosis and one with preimplantation genetic testing), with consequent successful termination of the birth of two affected fetuses. The frequencies of preconception or prenatal carrier screening for the deafness genes GJB2 and SLC26A4 in 9,993 subjects from China in this study were 2.86% and 2.63%, respectively. In addition, four out of six high-risk couples made alternative reproductive decisions, followed by the successful prevention of the birth of two affected fetuses. These findings confirmed the clinical utility of preconception or prenatal carrier screening for hereditary deafness.

The goal of this study is to categorize stakeholders in Internet of Things (IoT) security based on their roles in order to address the challenges associated with managing the large amount of data generated by IoT devices. With the increasing number of connected devices, the security risks also escalate, necessitating skilled stakeholders to mitigate these risks and prevent potential attacks. This study proposes a two-part approach that involves clustering stakeholders according to their responsibilities and determining relevant features to enhance decision-making. By grouping stakeholders into shared categories, the study aims to provide a more efficient and effective method for managing IoT security. The insights gained from this research will not only benefit stakeholders involved in IoT security but also assist policymakers and regulators in developing effective strategies.

Finding a suitable support is a key process in the life history of climbing plants. Climbers that find a suitable support have greater performance and fitness than those that remain prostrate. Numerous studies on climbing plant behavior have elucidated the mechanistic details of support searching and attachment. Far fewer studies have addressed the ecological significance of support-searching behavior and the factors that affect it. Among these, the diameter of supports influences their suitability for twining plants. When support diameter increases beyond some point climbing plants are unable to maintain tensional forces and therefore lose attachment to the trellis. Here we further investigate this issue by putting pea plants in the situation to choose between supports of different diameters while their movement was recorded by means of a three-dimensional motion analysis system. The results indicate that the way climbing plants move can vary depending on whether they are presented with one or two potential supports. Furthermore, when presented with a choice between a thin and a thick support, the plants showed a distinct preference for the former than the latter. The present findings shed further light on how climbers make decisions as far as support search is concerned, and provide evidence that plants adopt one of several alternative plastic responses in a way that optimally corresponds to environmental scenarios.

Transformation studies have been leaning towards the more practical aspects of change processes and have not yet dealt sufficiently with their personal and political dimensions. They are arguably constrained in doing so if they are either overly focussed on systems and how to control them or on individualistic values and behaviours. In this study we show how the actually-occurring societal transformations that people face can be usefully approached through the lenses of dialogical sense-making and critical phenomenology. While distinct, these approaches share a concern with aspects missed when transformation is abstracted and alienated from people’s lives; namely people’s lived experiences during times of change, and the conditions of possibility for these experiences. Dialogical sense-making explores how people create meaning around transformations, through interactions with other people, with different lines of arguments, and as part of broader public discourse. Critical phenomenology engages with subjectivity and lived experience, and with the role of foundational as well as socio-culturally dominant yet contingent structures in shaping our ways of perceiving, experiencing and knowing the world. Through a discussion of insights from these approaches, we show how they offer tools that enable new questions about transformative change as it is experienced and made sense of. Situating analyses of tranformation from within a focus on experience brings us closer to understanding the significance of change processes in people’s lives, and allows for an inquiry into the conditions of experience, including transformative experiences.

Decision making is a complex process involving various parts of the brain which are active during different times. It is challenging to measure externally the exact instance when any given region becomes active during the decision-making process. Here we try to extract and visualize the dynamic functional brain activation information from the observed fMRI data. We propose the use of a regularized deconvolution model to simultaneously map various activation regions within the brain and track how different activation regions changes with time. Thus, providing both spatial and temporal brain activation information. The activation information can then be further analyzed as per need and requirements. The proposed technique was validated using simulated data and then applied to a simple decision-making task for identification of various brain regions involved in different stages of decision making. The visualization aspect of the algorithm allows us to actually see the flow of activation (and deactivation) in form of a motion picture. The dynamic estimate may aid in understanding the causality of activation between various brain regions in a better way.

Multi-objective optimization (MOO) is an optimization involving minimization or maximization of several objective functions more than the conventional one objective optimization, which is useful in many fields. Many of the current methodologies addresses challenges and solutions that attempt to solve simultaneously several Objectives with multiple constraints subjoined to each. Often MOO are generally subjected to linear inequality, equality and or bounded constraint that prevent all objectives from being optimized at once. This paper reviews some recent articles in area of MOO and presents deep analysis of Random and Uniform Entry-Exit time of objectives. It further break down process into sub-process and then provide some new concepts for solving problems in MOO, which comes due to periodical objectives that do not stay for the entire duration of process lifetime, unlike permanent objectives which are optimized once for the entire process duration. A methodology based on partial optimization that optimizes each objective iteratively and weight convergence method that optimizes sub-group of objectives are given. Furthermore, another method is introduced which involve objective classification, ranking, estimation and prediction where objectives are classified based on their properties, and ranked using a given criteria and in addition estimated for an optimal weight point (pareto optimal point) if it certifies a coveted optimal weight point. Then finally predicted to find how far it deviates from the estimated optimal weight point. A Sample Mathematical Tri-Objectives and Real world Optimization was analyzed using partial method, ranking and classification method, the result showed that an objective can be added or removed without affecting previous or existing optimal solutions. Therefore suitable for handling time governed MOO. Although this paper presents concepts work only, it’s practical application are beyond the scope of this paper, however base on analysis and examples presented, the concept is worthy of igniting further research and application.

SIGNIFICANCE Putting worth on research and selection of studies by importance are crucial in medical innovation. Practical applications include choosing personal study topics, publication review, study grant selection, and decisions of spending or misspending billions in public health. Multiple studies raised alarm that current methods perform poorly in reproducibility, prediction of best research and objectivity. I propose using the metrics how much disease burden is reduced and calculating objective, numerical research value. The concept is that worth of medical research is not subjective but can be reproducible and numerically quantified. The method increases transparency by giving decision makers an externally accountable proof, and frees peer reviewers to check scientific integrity. Its numerical form can capture small differences important in competition between studies. ABSTRACT Finding value and selecting knowledge by importance are crucial in medical innovation. Applications include individuals designing research, funding organizations selecting grants, journals – publications, institutions – priorities in public health and health policy, and decision makers spending or misspending billions of research funds. Currently finding value of knowledge is done by peer review together with checking scientific integrity. Multiple studies raised alarm that it performs poorly in prediction of highest citations, bias, transparency and quality. The resulting problems include perception of slow medical progress and wasting funds and time. I introduce a standard, objective and numerical method for finding value of medical research. It measures disease burden prevented by new knowledge contained in a study or a publication. In its simple form, it is calculated by multiplying disease prevalence, disease burden, and efficacy of the therapy. It can be modified for risk of failure, multi-disease effect and for ethical considerations. The process is described step-by-step in terms common in medical practice. A quick estimate is often sufficient. The advantage is objectivity, since it is calculated from real world data. This gives transparency and externally accountability of decision making. The second advantage is a numerical form. This can measure small differences in research value which, in sharp competition, determine which studies are selected. A researcher can calculate the value of own future effort. Institutions might ask to provide it at submission. The method is also applicable to broad policy analysis, objective evaluation of scientific achievement and bibliometric studies.

The rapid and extensive loss of biodiversity globally has resulted in an increased urgency to capture and conserve the diversity which is present, including genetic diversity within species. However, for many species there is currently no detailed genetic data available to inform the collection and use of material held in ex situ collections and this can hamper the consideration of genetic issues and reduce the likelihood collection represent the diversity present. Even in the absence of direct genetic data, however, it is possible to consider genetic issues using the existing theoretical and empirical evidence-based and biological, ecological and demographic data for a given species. Here a framework to facilitate the consideration of genetic diversity and genetic issues, even where genetic data is lacking, is presented.

The current discussion about a “risk culture” in financial services was triggered by the recent series of crisis (from the US subprime mortgage crisis to the lock-in trap of central banks in the aftermath of the sovereign debt crisis). The last decade saw a long list of hybris, misconduct and criminal activities by human beings on a single or even a collective basis in banks, in the industry or in the whole economy. As a counter-reaction, financial authorities called for a guidance by a “new” risk culture in financial institutions based on a set of abstract, formal and normative governance processes. In the humanities, culture is a paraphrase for the behaviour in collectives and dynamics of organization found in human societies. Therefore, a “risk culture” should be a link between those normative guidelines and the positive “real-world” decision-making in financial services. This paper will focus on “risk culture” from the perspective of human beings interacting in dynamical and intertemporal commercial relations. In this context, “risk” is perceived by economic agents ex-ante as the consequence of the time-lag between the present and the uncertain future development (compared to a probability distribution calculated by observers ex-post). For all those individual decisions – to be made under uncertainty – future “risk” includes the so-called “normal accidents”, i.e. failures that will happen at some uncertain point in time but inevitable, and it is only the questions, when failure will happen and how to maintain function in the first line of defence. Finally, the sum of all decisions with individual responsibility for things to come is the positive economical context of a “risk culture” in the sense of the (rational) behaviour of an honourable merchant in long-term and repeated commercial relations in a merchant community, as this is a heritage of European business culture.

Background: Measuring vital signs has always been a central task for Critical Care Nurse´s (CCNs) and Registered Nurse Anesthetist`s (RNAs) providing care in the post-anesthesia care unit (PACU) and a prerequisite for their decision-making. Properly measuring and understanding pediatric vital signs is a challenge in younger pediatric patients up to 36 months old. Purpose: gain a greater understanding of CCNs' and RNAs' perceptions of decision-making regarding the level of vital sign monitoring children require in the PACU. Method: A qualitative study design involving the critical-incident technique was used. Interviews were carried out with a purposeful sample of CCNs and RNAs (n=17) from two different hospitals. Findings: According to the nurses' experience, grounds for decisions concerning children’s need of vital-sign monitoring were both adequate and inadequate. They used actions to adjust the monitoring of vital signs to optimise conditions for assessment and the prospects of a safe recovery for the child. Conclusions: Evidence-based care and safety are compromised when the technology has limitations and is not adapted for children. Its use means that experience and clinical assessment are relied on to a greater extent. This not only makes experience important for reliable assessment, but also means that greater risks are accepted.

Lung cancer is the leading cause of global cancer-related mortality resulting in ~1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or biobanked sections/biopsy of lung tumors, PDXs, and pleural affusion. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and immune therapy agents. PDOs mainly recapitulated the genomic alterations, transcriptomic landscape and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remained, PDOs showed promise to screen novel therapy drugs. With the technical advance of high throughput, tumor-on-chip, combined microenvironment, and air-liquid interface (ALI), the drug screening using PDOs would serve better for precision care of lung cancer patients.

Comparing to males, females require much more morphine to produce comparable levels of analgesia, suggesting a difference in the endogenous hyperalgesia and analgesia modulation between sexes. Aside from hormones, emerging evidence suggests sex-differential intrinsic neural regulation of pain generation and maintenance. According to the International Association for the Study of Pain (IASP) and American College of Gastroenterology (ACG), up to 25 % of the population having visceral pain at any one time, and in the United States 10-15 percent of adults suffering from irritable bowel syndrome (IBS). Here we analyzed literatures on clinical reports of sex differences in visceral pain focusing on IBS, other form of bowel dysfunction and comorbidities, and summarized animal models that provided means to investigate the underlying molecular mechanisms in sexual dimorphism of visceral pain. Neurons and nonneuronal cells (glia and immune cells) in the peripheral and central nervous systems all contribute to sex-dependent nociception and nociplasticity in the painful signal processing. Emotion is another factor in pain perception and appears to have sexual dimorphism.

Ketamine as an old - new drug has variety of clinical implications. In the last 30 years, ketamine has become popular for acute use in humans. Ketamine at standard doses is principally utilized for the induction and maintenance in surgical procedures. Beside its use in anesthesia and analgesia, recently studies had shown that ketamine find the place in the treatment of asthma, epilepsy, depression, bipolar affective disorders, alcohol and heroin addiction. Its mechanism of action is complex, but it mostly acts as a noncompetitive antagonist at the N-methyl-D-aspartate (NMDA) receptor. Ketamine is generally considered relatively secure and does not result in serious adverse effects when used at low doses and for short periods- Also, ketamine is known as a powerful psychostimulant. During the past decade, ketamine has been one of the commonly abused drug.

Antibody-drug conjugates (ADCs) have provided new therapeutic options and significant promise for patients with cancers, particularly where existing treatments are limited. Substantial effort in ADC development is underway globally, with 13 ADCs currently approved and many more in development [1]. Therapeutic benefits of ADCs leverage the ability to selectively target cancer cells through antibody binding, resultant relative sparing of non-malignant tissues, and the targeted delivery of a cytotoxic payload. Consequently, this drug class has demonstrated activity in multiple malignancies refractory to standard therapeutic options [1-4]. Despite this, limitations exist, including narrow therapeutic windows, unique toxicity profiles, development of therapeutic resistance, and appropriate biomarker selection [5-7]. This review will describe the development of ADCs, their mechanisms of action, pivotal trials, and approved indications and identify common themes. Current challenges and opportunities will be discussed for this drug class in cancer therapeutics at a time when significant developments in antibody therapies, immunotherapy and targeted agents are occurring.

Background: Transient Hypogammaglobulinemia of Infancy (THI) is a primary immunodeficiency caused by a temporary decline of serum levels of immunoglobulin G (IgG) greater than 2 standard deviations below the mean age-specific reference values in an infant between 5 and 24 months of age. Preterm infants are particularly susceptible to THI, as, in the third trimester of pregnancy, IgG is transferred across the placenta from mother to infant.Objective: To systematically review the diagnostic criteria of Transient Hypogammaglobulinemia of infants.Design & Methods: Systematic Review. Manual searching of 3 electronic databases (PubMed, Medline, & Google Scholar) from September 2021 – April 2022. Abstracts were screened to assess fit to the inclusion criteria. Data was extracted from the selected studies by using an adapted extraction tool from Cochrane.org. Studies were then assessed for bias by using an assessment tool also adapted from Cochrane.org.Results: Of the 215 articles identified, 16 were eligible for examining the diagnostic criteria of THI. These studies were also assessed for bias in 6 domains. 5 studies (31%) had a low risk of bias, while 4 studies (25%) had a high risk of bias, & 7 studies (44%) were unclear for bias.Conclusion: We can conclude that THI is only definitively diagnosed after the abnormal IgG levels have normalized, hence THI is mostly a benign condition, but must be monitored for subsequent recurrent infections. The diagnostic criterion also includes vaccine & isohaemagglutinin responses to differentiate against other immunological disorders in infants.

Colorectal cancer (CRC) is the third most common type of cancer and the second leading cause of cancer deaths worldwide. Surgery or surgery plus radiotherapy and/or chemotherapy for patients with metastatic CRC (mCRC) were accepted as the main therapeutic strategies until the early 2000s, when targeted drugs, like cetuximab and bevacizumab were developed. The use of targeted drugs in clinical practice has significantly increased patients’ overall survival. To date, the emergence of several types of targeted drugs has opened new possibilities and revealed new prospects for mCRC treatment. Therapeutic strategies are continually being updated to select the most suitable targeted drugs based on the results of clinical trials that are currently underway. This review discusses the up-to date molecular evidence of targeted therapy for mCRC and summarizes the Food and Drug Administration-approved targeted drugs including the results of clinical trials. We also explain their mechanisms of action and how these affect the choice of a suitable targeted therapy.

Background: Mucormycosis is a worldwide angio-invasive fungal infection that is associated with high morbidity and mortality. A few European studies have focused on the epidemiology. Methodology: A retrospective longitudinal descriptive study was performed with inpatients diagnosed with mucormycosis (ICD-9-CM, code 117.7, cases 1997-2015; and ICD-10, code B46, cases 2016-2018; along with length of hospital stay) in Spanish public hospitals between 1 January 1997 and 31 December 2018. Data were obtained from the Minimum Basic Data Set (CMBD in Spanish). Principal findings: A total of 962 patients were recorded; 665 were men. The mean age (±SD) was 55±18.8 years. The annual incidence rate increased from 0.74 to 1.24 cases per million person-years. The lethality rate was 31.3%. Renal failure (41.6%) and hematological malignancy (36.3%) were the main factors involved. Conclusions: Mucormycosis is a rare infectious disease in Spain, but it has had a significantly increased incidence in the last two decades. Being an adult male and having diabetes, neoplasm or renal failure are the main factors associated. High mortality is usually associated mainly with hematological malignancy and renal failure. CMBD studies could be an efficient tool for assessing changes in the epidemiology of mucormycosis.

The treatment of peptides has played an important role in clinical practice since the discovery of insulin therapy in the 1920s. Over 60 peptide drugs are approved in the United States (US and other regional mar-kets, and peptides continue to undergo drug discovery steadily. Peptide research and development has lev-eraged a wider range of structures known from other plant sources, via pharmacology and medicinal molecular biology, beyond its conventional focus on individual endogenous peptides. We build a comprehensive database of peptides that have met scientific studies with more than 150 constantly evolving peptides. Here we provide a simple overview of the peptide-based drug therapy environment, comprising evolutionary points of view, structural properties, operational thresholds, and explanation of the therapeutic area.

Background: Kawasaki disease (KD) is a form of vasculitis that primarily affects children under the age of 5 years old. Patients may be missed diagnosis when initial clinical symptoms do not fulfill the traditional criteria. We aimed to analyze factors that clinicians could use to differentiate febrile children suspected of KD. Method: We retrospectively enrolled a total of 83 febrile children who were initially suspected of KD, but they did not meet the American Heart Association (AHA) criteria for a diagnosis. However, some of these patients were diagnosed with KD during their second visit. We analyzed patients' characteristics, clinical symptoms, and laboratory data. Results: In total, 50 patients were enrolled in the study. Of those, ten patients were diagnosed with KD on their second visit (group 1), while the other 40 patients still did not fit a KD diagnosis (group 2). A patient with a neutrophil to lymphocyte ratio greater than 1.33 combined with a C-reactive protein more than 33 mg/L was more likely to have KD. Conclusion: Among patients suspected of KD that did not initially meet the criteria, clinicians should pay special attention to elevated neutrophil-to-lymphocyte ratios and CRP levels and closely follow up such patients.

Clinical training in medical schools in Spain is performed by rotations in university hospitals. During these internships, students are expected to acquire and master basic procedural skills. However, the assessment tools available rarely check whether these skills are completely acquired by the students. We have used an e-portfolio to determine the optimal number of times the students need to repeat a procedure to be able to perform it independently. The results were compared with the actual performance during the internships. An e-portfolio collected qualitative information about the internships. Quantitative information was also requested about the number of times each clinical skill was performed. Later, a survey asked these students and their teachers the optimal number of times each skill should be repeated before it could be considered fully acquired. The questionnaire was answered by 98.6% of the students and 70.3% of their teachers. Out of the 21 clinical skills and procedures selected, both students and their tutors agreed in a similar optimal value in 16 of them; only in five of them, teachers thought that students needed a greater number of times than that selected by the students. When these optimal values were compared with the actual values recorded in the portfolio during the internships, it was found that about half of the clinical skills were carried out less frequently than expected, thus providing an important feedback about the internships. Quantitative information collected in portfolios reveals a moderate mismatch between students and tutors perceptions of their training needs.

The emergence of Distributed Ledger Technology (DLT) in the past decade has challenged our imagination to discover new, innovative and disruptive solutions to problems in domains ranging from finance and healthcare to supply chain and smart cities. However, the enormous energy consumption that has been observed in some of the most successful DLT applications raises the question of their long term sustainability. This article reviews the standardization efforts of the International Telecommunications Union (ITU) to provide guidelines to regulators and policy makers for making informed decisions on the applicability and sustainability of DLT architectures from the point of view of energy consumption.

Oxytocin is well known for its role in relationships and social cognition and has more recently been implicated in pain relief and pain perception. Connections between prosocial feelings and pain relief are also well documented, however, effects of exogenous oxytocin on social cognition and pain have not been explored. The current study tested whether intranasally-delivered oxytocin affects pain perception through prosocial behaviors. Additionally, moderation of the effects of oxytocin by life history or genetic polymorphisms are examined. Young adults (n=43; 65% female) were administered intranasal oxytocin (24 IU) or placebo in a crossover design on two visits separated by a one-week washout period. Pain was delivered via cold-pressor. Baseline measures for decision-making and social cognition were collected, as well as pain sensitivity and medication history. Saliva samples were collected for analysis of genetic markers, and urine samples were collected to assess oxytocin saturation. Following oxytocin administration, participants reported increased prosocial cognition and decision-making. Pain perception appeared to be adaptive, with procedural order and expectation affecting perception. Finally, behavioral trust and cooperation responses were significantly predicted by genetic markers. Oxytocin may increase a patient’s trust and cooperation and reduce pain sensitivity while having fewer physiological side effects than current pharmaceutical options.

Smartphone Addiction is a social issue caused by excessive smartphone use, affecting decision-making processes. Current research on the risky decision-making abilities of smartphone addicts is limited. This study used the fNIRS brain imaging technique and a Sequential Risk-Taking Task experimental paradigm to investigate the decision-making behavior and brain activity of smartphone addicts under varying risk levels. Using a mixed experimental design, the research assessed decision-making ability and brain activation levels as dependent variables across two groups (addiction and control), two risk amounts (high and low), and two outcomes (gain and loss). The study included 42 participants, with 25 in the addiction group and 17 in the control group. Results indicated that risk level significantly impacted the decision-making ability of smartphone addicts, with high-risk levels leading to weaker decision-making ability and increased risk-taking. However, at low risk levels, decision-making abilities between addicts and healthy individuals showed no significant difference. Furthermore, brain imaging results using fNIRS revealed stronger brain activation in the dlPFC region for smartphone addicts under loss outcome conditions, with no significant differences between the two groups in terms of brain activation at varying risk volumes. These findings are critical in promoting healthy smartphone use, guiding clinical treatment, and advancing brain mechanism research.

Type I contextuality or inconsistent connectedness is a fundamental feature of both the classical as well as the quantum realms. Type II contextuality (true contextuality or CHSH type contextuality) is frequently asserted to be specific to the quantum realm. Nevertheless, evidence for Type II contextuality in classical settings is slowly emerging (at least in the psychological realm). An example is given here of Type II contextuality involving a simple cooperative game. This arises due to the cooperative nature of the game which results in sign intransitivity for expectation values while individual random variables remain consistently connected. This shows that the conditions attributed uniquely to quantum systems may occur in classical settings as well. Sign intransitivity can be observed in preference relations in the setting of decision making and so intransitivity in decision making may also yield examples of Type II contextuality. Previously it was suggested that a fruitful setting in which to search for such contextuality is that of decision making by collective intelligence systems. An experiment was conducted using a detailed simulation of nest emigration by workers of the ant Temnothorax albipennis. In spite of intransitivity, these simulated colonies came close to but failed to violate Dzhafarov’s inequality for a 4-cyclic system. Further research using more sophisticated simulations and experimental paradigms is required

When following a prescribed route, we need to decide at each intersection which way to proceed. The present work addressed several factors that might influence the difficulty of this decision making process. Participants repeatedly followed a route through a virtual maze with twelve or eighteen intersections, and with two or three choices per intersection. One group performed task S, which promoted decision making by the serial order strategy since all intersections looked alike. Another group performed task SA, which allowed the use of the serial order and the associative cue strategy since unique visual cues were presented at each intersection. We found that in both tasks, participants were more accurate in making decisions on routes with twelve rather than eighteen intersections, and more accurate by a similar amount on routes with two rather than three choices. Reaction time in task SA was reciprocal to accuracy; reaction time in task S was generally lower and route-independent. Accuracy in task SA was similar for participants who experienced smooth transport across intersections and those who experienced abrupt transport, while accuracy in task S was lower for participants who experienced smooth rather than abrupt transport across intersections. We conclude that the number of intersections and the number of choices were equivalent determinants of route following difficulty. We further conclude that optic flow during turns at intersections interfered with anticipatory decision making in task S; hence natural (smooth) transport across intersections did not enhance route following performance.

The pace of implementation of renewable electricity storage in Europe is disappointingly slow. Several factors influence it, but there is a need to speed up the rate and increase the volumes in order to promote a 100% transition to renewable energy resources, expand the practice of using renewable energy, and contribute to the improvement of the user's quality of life. Also, an important factor is significantly reducing the global impact on the environment and climate change. Electricity from renewable energy sources such as solar and wind has a seasonal nature that cannot provide the necessary electricity consumption and cover peak loads. Also, the so-called "energy resource crisis" is a very topical problem at the moment, which reinforces the global need to increase the share of renewable energy resources in the overall balance of primary energy resources. It is precisely the wider integration of renewable electricity storage in practice that can help stimulate this. The availability of renewable electricity is constantly increasing and the level of technological innovation is rapidly developing, therefore it is valuable to analyze, look for connections and at the same time the main differences in the ways of accumulation in order to promote its availability from a private house to the national and European scale as a whole. Therefore, this article analyses and compares the different options for renewable electricity storage, from small batteries to large storage systems, arriving at the best solution according to needs, using analysis methods such as multicriteria decision analysis (MCDA) and TOPSIS. After comparing nine criteria, such as the amount of investment required, existing power density, efficiency, duration of operation and others, in both groups, it was concluded that lithium-ion batteries are currently the best solution among batteries, while in the group of large accumulation systems – pumped hydro storage.

This article is a theoretical contribution to mental model research, which currently has different threads. Whereas some researchers focus on the perceived causal structure, others also include decision policies and decisions. We focus on the link between recognized causal structure (“mental models of dynamic systems”) and policies, proposing Johnson-Laird’s theory of mental models as the link. The resulting framework hypothesizes two types of systematic mental model errors: (1) misrepresentation of the system’s structure and (2) failure to deploy relevant mental models of possibilities. Examination of three experiments through this lens reveals errors of both types. Therefore, we propose that the cognitive theory of mental models opens a path to better understand how people construct their decision policies and develop interventions to reduce such mental model errors. The article closes by raising several questions for empirical studies of the reasoning process leading from mental models of dynamic systems to decision policies.

Petrochemicals, which convert oil and gas into products such as plastics, are fundamental to modern societies. Chemists recognize their role in the design of materials and the adverse effects that these may have on the environment, preventing sustainable development. Several methodological frameworks and sustainability assessment approaches have been developed to evaluate the resources used in the petrochemical sector in terms of environmental costs. A combination of Life Cycle Assessment and Emergy Accounting - to assess the environmental support for resource use - is applied in this study of the PET production chain in Europe. The Unit Emergy Values of several intermediates are calculated or updated to facilitate discernment of the quality of energy used and the processes' efficiency. Several routes for synthesizing renewable para-xylene and ethylene glycol from biomass are discussed and confronted with the efforts focused on recycling and recovering the final product providing concurrently a procedure and a valuable data set for future CP actions. The results show that understanding the efficiencies changing across the production chain may help stakeholders make wise choices as to where and when interventions to promote a circular economy are most effective along a petrochemical production chain.

We are of the opinion that during the design of a binary classifier one ought to consider adding an “I don’t know” answer. We provide the case for the introduction of this third category when a human needs to make a decision based on the answer from a binary classifier. We discuss the costs and potential benefits of its introduction. Colloquially, we have used the term “I don’t know”, but formally we refer to it as NotAvailable. A procedure to define NotAvailable predictions in binary classifiers, called all leave-one-out models (ALOOM), is presented as proof of the concept. Furthermore, we discuss the potential benefits of applying ALOOM in real life applications.

Multi-criteria decision-making (MCDM) methods and techniques have been applied to many real-world problems in different fields of engineering science and technology. The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method. The aim of this study is to propose a modification to address two exceptional cases in which the EDAS method fails to solve an MCDM problem.

This research article presents the integration of participatory modeling and system dynamics as a novel methodology for the consolidation of social dynamic models for the subsequent evaluation and prioritization of green projects in Colombian post-conflict communities. In the first instance, through participatory work carried out along with the community, it was possible to identify, evaluate and systematize citizen factors in relation to the problems and needs of the region. Second, based on the results obtained, to calibrate a simulation model based on system dynamics that facilitates decision making with regard to the evaluation of green projects. The proposed methodology leads to the conclusion that, with the participation of the community and with a model based on the dynamics of variables such as supply and demand for natural resources of water and land, it is possible to warn decision makers about the variables that can lead to the maximization of investments and thus prioritize and select the most appropriate environmental, social or economic initiatives, that certainly meet the needs or expectations of the involved community. In the future, the model could be used to facilitate the management, administration and control of water and land resources by creating alerts called reserve margins.

The performance of choice-reaction tasks during athletic movement has been demonstrated to evoke unfavorable lower limb biomechanics. However, the mechanism of this observation is unknown. We conducted a systematic review examining the association between 1) the biomechanical and functional safety of unplanned sports-related movements (e.g. jumps/runs with spontaneously indicated landing leg/cutting direction) and 2) markers of perceptual-cognitive function (PGF). A literature search in three databases (Pubmed, ScienceDirect, Google Scholar) identified five relevant articles. Study quality, rated by means of a modified Downs & Black checklist, was moderate to high (average: 13.5/16 points). Four of five papers, in at least one parameter, found either an association of lower PGF and reduced task safety or significantly reduced task safety in low vs. high PGF performers. Yet, as a) the outcomes, populations and statistical methods of the included trials were highly heterogeneous and b) only two out of five studies had an adequate control condition (pre-planned movement task), evidence was classified as conflicting. In sum, PGF may represent a factor increasing injury risk during unplanned sports-related movements but future research strengthening the evidence of this association is warranted.

Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R1) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

Recent findings show that preferences for food items can be modified without external-reinforcements using the cue-approach task. In the task, the mere association of food item images with a neutral auditory cue and a speeded button press, resulted in enhanced preferences for the associated stimuli. Here, in a series of 10 independent samples with a total of 255 participants, we show we can enhance preferences using this non-reinforced method for faces, fractals and affective images as well as snack foods, using auditory, visual and even aversive cues. This change was highly durable in follow-up sessions performed one to six months after training. Preferences were successfully enhanced for all conditions, except for negative valence items. These findings promote our understanding of non-reinforced change, suggest a boundary condition for the effect and lay the foundation for development of novel applications.

The purposes of this study were to identify clinician’s characteristics associated with higher prescription rates of long-acting injectable (LAI) antipsychotics, as well as the information sources influencing medical decision-making about treatment of schizophrenia. We surveyed 202 psychiatrists during 6 regional French conferences (Bordeaux, Lyon, Marseille, Nice, Paris, Strasbourg). Data on the characteristics of practice, prescription rates of antipsychotic and information sources about their clinical decisions were collected. Most of psychiatrists used second-generation antipsychotic (SGA), and preferentially an oral formulation, in the treatment of schizophrenia. SGA LAI was prescribed to 30.4% of schizophrenic patients. The duration and the type of practice did not influence the class or formulation of antipsychotics used. The clinicians following the higher percentage of schizophrenic patients were associated with the higher use of LAI antipsychotics and the lower use of oral SGA. Personal experience, government regulatory approval and guidelines for the treatment of schizophrenia were the 3 main contributing factors guiding the clinical decision-making of clinicians about treatment of schizophrenia. The more clinicians follow schizophrenic patients, the more they use LAI antipsychotic. The development of specialised programmes with top specialists should lead to better use of LAI in the treatment of schizophrenia.

Glioblastoma (GBM) is the most lethal form of brain tumor, characterized by rapid growth and surrounding tissue invasion. The current standard treatment is surgery followed by radiotherapy, and concurrent chemotherapy, typically with temozolomide. Although extensive research has been performed over the past years to develop an effective therapeutic strategy for the treatment of GBM, efforts have not provided major improvements in the overall survival of patients with GBM. Thus, new therapeutic approaches are urgently needed. A major challenge in the development of therapies for central nervous system (CNS) disorders is overcoming the blood–brain barrier (BBB). In this context, the intranasal (IN) route of drug administration has been proposed as a non-invasive alternative route to directly targeting the CNS. In fact, this route of drug administration may bypass the blood-brain barrier and reduce systemic side effects. Recently, formulations have been developed to further enhance nose-to-brain transport, mainly with the use of nano-sized and nanostructured drug delivery systems. The focus of this review will be on the strategies developed to deliver a number of anticancer compounds for the treatment of GBM using the nasal administration. In particular, the specific properties of nanomedicines proposed for the nose-to-brain delivery will be critically evaluated. The number of preclinical and clinical data reviewed support the idea that nasal delivery of anticancer drugs might represent a breakthrough advancement in the fight against GBM.

Despite all scientific efforts and many protracted and expensive clinical trials, no new drug has been approved by FDA for treatment of Alzheimer disease (AD) since 2003. Indeed, more than 200 investigational programs have failed or have been abandoned in the last decade. The most probable explanations for failures of disease-modifying treatments (DMTs) for AD may include late initiation of treatments during the course of AD development, inappropriate drug dosages, erroneous selection of treatment targets, and mainly an inadequate understanding of the complex pathophysiology of AD, which may necessitate combination treatments rather than monotherapy. Clinical trials’ methodological issues have also been criticized. Current drug-development research for AD is aimed to overcome these drawbacks. Preclinical and prodromal AD populations, as well as traditionally investigated populations representing all the clinical stages of AD, are included in recent trials. Systematic use of biomarkers in staging preclinical and prodromal AD and of a single primary outcome in trials of prodromal AD are regularly integrated. The application of amyloid, tau, and neurodegeneration biomarkers, including new biomarkers—such as Tau positron emission tomography, neurofilament light chain (blood and CSF biomarker of axonal degeneration) and neurogranin (CSF biomarker of synaptic functioning)—to clinical trials allows more precise staging of AD. Additionally, use of the Bayesian statistics, modifiable clinical trial designs, and clinical trial simulators enrich the trial methodology. Besides, combination therapy regimens are currently assessed in clinical trials. The abovementioned diagnostic and statistical advances, which have been recently integrated in clinical trials, are consequential to the recent failures of studies of disease-modifying treatments. Their experiential rather than theoretical origins may better equip potentially successful drug-development strategies.

The new Post Accelerating Data and Knowledge Online Society, or ‘Padkos’ requires a new model of decision making. This introductory paper proposes a model where decision making and learning are a single symbiotic process, incorporating man and machine, as well as the AADD (ánthrōpos, apparatus, decider, doctrina) diamond model of individual and organizational decision-making and learning processes. The learning is incorporated by using a newly proposed quadruple loop learning model. This model allows for controlled changes of identity, the process of creating and the sense making of new mental models and assumption, and reflections. The model also incorporates the recently proposed model of quantum decision-making, where time collapse of the opted past and the anticipated future (explicitly including its time horizon) into the present play a key role in the process, leveraging decision-making and learning by human as well as Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The paper closes with conclusions.

Although child-centred care is increasingly referred to within the nursing literature, a clear definition of child-centred care and clarity around the concept is yet to be achieved. The objectives of this review were to examine: 1) What constitutes the concept of child-centred care in healthcare? 2) How has the concept of child-centred care developed? 3) What is the applicability of child-centred care and what are its limitations? and 4) How does the concept of child-centred care benefit and inform children’s healthcare? In total, 2984 papers were imported for screening, following removal of duplicates and screening, 21 papers were included in the scoping review.The findings suggest that child-centred care is an emerging, ambiguous, poorly defined concept; no clear consensus exists about what constitutes child-centred care. Although it seems antithetical to argue against child-centred care, little robust evidence was identified that demonstrates the impact of, and benefit from, child-centred care. If child-centred care is to be a sustainable, convincing model to guide practice and compete with other models of care it needs to establish robust evidence of its effectiveness, impact on children and their families as well as the wider impacts on the healthcare system.

The wastewater circular economy (WW-CE) promises a solution to improve water and sanitation management worldwide. However, the transition from conventional to circular wastewater treatment plants (WWTPs) requires facilitation to aid in decision makers understanding of integral sustainability impacts of alternative WW-CE configurations. This research implemented Life Cycle Sustainability Assessment (LCSA), combining Life Cycle Assessment, Social Life Cycle Assessment and Life Cycle Costing with a Multi-criteria Decision Making (MCDM) model to quantify environmental, socio-cultural, and economic impacts of conventional WWTPs with the WW-CE. Two real WWTPs in Chile have embraced the WW-CEs and adopting the title of Biofactories. These were considered as case studies, compared under three scenarios to demonstrate the sustainability trade-offs of the transition from no sanitation to conventional WWTPs and Biofactory WW-CE configurations. Results demonstrated that the transition to WW-CEs improved integral sustainability according to the LCSA model implemented in both WWPTs. This study highlights the urgent need to adopt sustainable decision-making models to not only improve sanitation coverage, but also improve sustainability performance of the sanitation industry across the globe.

This study addresses the motivations behind Generation Z's attendance at conferences and aims to contribute to a better understanding of their conference participation behavior. The study identified six latent factors that influence conference attendance motivation: Green and Digital Conference Experience, Educational and professional opportunities, Conference costs, Destination and conference stimuli, Stimulating factors, and Conference accessibility. These factors align with Generation Z's unique characteristics and preferences, such as their environmental consciousness, reliance on digital technologies, desire for continuous learning, career advancement, and experiences. The study also found that destination characteristics and educational and professional opportunities are significant motivators for Generation Z's conference attendance across different cultural contexts. Additionally, Generation Z's strong interest in sustainability and financial challenges highlights the need for eco-friendly practices and affordable registration fees to make conferences more appealing and accessible. The study further explores the impact of socio-demographic characteristics, revealing the gender and past conference attendance differences in motivation. Finally, the study discusses the implications for the conference industry and suggests areas for future research to enhance the understanding of conference attendance motivation among Generation Z.

Purpose: To clarify the mechanism of state anxiety on intertemporal decision-making, two studies were conducted to investigate the role of trait anxiety and inhibitory control. Study 1 examined the moderating effect of trait anxiety. Study 2 continued to investigate the mediating effect of inhibition control on the basis of study 1. Methods: A total of 266 Chinese college students participated. Participants’ state anxiety, trait anxiety and intertemporal decision-making were measured by questionnaires (scales) respectively. And inhibition control was evaluated by two-choice oddball paradigm. Results: The results of Study 1 indicated that state anxiety could predict intertemporal decision-making and that the moderating effect of trait anxiety on this relationship was significant. Study 2 found that inhibitory control could completely moderate the relationship between state anxiety and intertemporal decision-making and that this indirect effect was affected by trait anxiety. Conclusion: 1)Individuals with higher trait anxiety are more inclined to make more impulsive and intertemporal decisions when they have a high level of state anxiety; 2)state anxiety allows inhibitory control ability to have a further effect on intertemporal decision-making; and 3)the higher trait anxiety in individuals, the stronger mediating effect of inhibitory control on the relationship between state anxiety and intertemporal decision-making.

This research aimed to determine salient factors affecting the decision to become a beginning organic farmer. New and beginning organic farmers have unique characteristics, showcasing their dedication to environmental justice and social justice at the expense of their own businesses. This research employed a multiple-case case study design. We conducted semi-structured interviews with 40 first-generation farmers who operate organic farms in Arkansas, Florida, or Georgia. We analyzed interview transcripts using the qualitative analysis approach of coding. Our results revealed the reasons that people with little practical knowledge start farms. They are inspired by those around them who succeed and encouraged by influential characters in the field who assure them they can do something they love and be profitable. This research showed that first-generation farmers find inspiration and develop values rooted in food justice. Our findings have implications for developing and implementing current and future programmatic activities that aim to enhance beginning farmer training and workforce development. Identifying sources of inspiration will help researchers and service providers target newer and beginning farmers to support a vibrant food system, including a burgeoning market opportunity, developing strong communities around food, and building grassroots solutions.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

The notion of free will seems so intuitive to us that it would be hard, even impossible, to imagine that we live in a world without ever exerting any willpower. This view of reality is not only hindrance to inspiration, it poses a serious threat to our moral and social responsibilities. Nonetheless, many scientific and philosophical schools of thought such as determinism purport free will as a mere illusion. As an attempt to rescue free will put forward by libertarianism, compatibilism or physical indeterminism that either exempts our mind from the universal rules of cause and effect by offering our minds a metaphysical status or substitute free will with random will rooted in the laws of quantum mechanics. This manuscript offers an alternative perspective under a new paradigm of consciousness called physical libertarianism that explicates true free will through the unwavering laws of cause and effect. Based on this paradigm, consciousness is the result of interaction of awareness and decision-making process. By applying awareness to the process of decision-making awareness-based choice selection or true free will is conceived. In return, by assigning the power of decision making to the process of awareness discretionary selection of information for attention or intentional attention is emerged. Through integration of these two mental functions, an independent entity called “I” is formed that differentiates natural intelligence from artificial intelligence. While determinism can aptly describe the world of inanimate objects and artificial intelligence, because of “I,” determinism has no jurisdiction over the realm of natural intelligence.

Urban flood risk mapping is an important tool for the mitigation of flooding in view of human activities and climate change. Many developing countries, however, lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can improve urban flood risk management in regions with scarce hydrological data. Given this, we estimated the flood risk map for Rasht City (Iran), applying a composition of decision-making and machine learning methods. Flood hazard maps were produced applying six state-of-the-art machine learning methods such as classification and regression trees (CART), random forest (RF), boosted regression trees (BRT), multivariate adaptive regression splines (MARS), multivariate discriminant analysis (MDA), and support vector machine (SVM). Flood conditioning parameters applied in modeling were elevation, slope angle, aspect, rainfall, distance to river (DTR), distance to streets (DTS), soil hydrological group (SHG), curve number (CN), distance to urban drainage (DTUD), urban drainage density (UDD), and land use. In total, 93 flood location points were collected from the regional water company of Gilan province combined with field surveys. We used the Analytic Hierarchy Process (AHP) decision-making tool for creating an urban flood vulnerability map, which is according to population density (PD), dwelling quality (DQ), household income (HI), distance to cultural heritage (DTCH), distance to medical centers and hospitals (DTMCH), and land use. Then, the urban flood risk map was derived according to flood vulnerability and flood hazard maps. Evaluation of models was performed using receiver-operator characteristic curve (ROC), accuracy, probability of detection (POD), false alarm ratio (FAR), and precision. The findings showed that the CART method is most accurate method (AUC = 0.947, accuracy = 0.892, POD = 0.867, FAR = 0.071, and precision = 0.929). The results also demonstrated that DTR, UDD, and DTUD played important roles in flood hazard modeling; whereas, the population density was the most significant parameter in vulnerability mapping. These findings indicated that machine learning methods can improve urban flood risk management significantly in regions with limited hydrological data.

The introduction of social commerce ushered in a new era in business-consumer interaction. As a result, more power has passed from the vendor to the buyer, primarily fueling e-commerce acceptance. As a result, understanding consumer behaviour in the context of social commerce adoption has become essential for businesses looking to persuade customers by using the power of social ties and support.Furthermore, such social ties will facilitate trust as the most promising benefit while reducing perceived risk, which has always been a critical problem with online commerce. This study proposes a paradigm for understanding the impact of social commerce on the stages of the consumer decision-making process: need recognition, information search, alternative evaluation, purchase decision, and post-purchase behaviour, with a focus on social support. In this respect, relevant literature in the subject of social commerce either (1) lacks an adequate explanatory model, (2) has a solid theoretical base, or (3) contains practically complex theories with insufficient empirical data. The research model applies the Social Commerce Constructs (SCC): recommendations and referrals, forums and communities, and ratings and reviews to study the respective influence on the consumer decision-making process phases. This paper aims to understand the influence of social commerce on an integrative model that incorporates all customer choice phases while expecting new knowledge. Furthermore, it is advised that this conceptual model be empirically verified to evaluate the practical consequences.

With the revolution of computing and biology technology, data sets containing information could be huge and complex that sometimes are difficult to handle. Dynamic computing is an efficient approach to solve some of the problems. Since neighborhood multigranulation rough sets(NMGRS) were proposed, few papers focused on how to calculate approximations in NMGRS and how to update them dynamically. Here we propose approaches for computing approximations in NMGRS and updating them dynamically. First, static approaches for computing approximations in NMGRS are proposed. Second, search region in data set for updating approximations in NMGRS is shrunk. Third, matrix-based approaches for updating approximations in NMGRS while decreasing or increasing neighborhood classes are proposed. Fourth, incremental algorithms for updating approximations in NMGRS while decreasing or increasing neighborhood classes are designed. Finally, the efficiency and validity of the designed algorithms are verified by experiments.

In considering the question of machine as artist, the art object can be analytically separated from its making, and its making can be dualistically conceptualized as process on one hand and experience on the other. One of the reasons we value art is that there was an experience of its making. To better understand what is meant by the experience of art-making, this paper presents results from a qualitative, phenomenological study of a group of artists. These results appear in three groups: feeling, intention and lifeworld. Machines cannot experience art-making, at least not in the same way as humans, and thus they cannot create art but only art-like objects. Even so, in the present century, we should not be asking whether machines can be artists, but rather how machines can help more people experience art-making for themselves.

Background/Objectives:The first attempts of posterior lumbar interbody fusion can be traced back to the 1940s, where their performance was marked by animosity due to high rates of failure. Nowadays, the use of interbody fusion involves a much more complicated consideration of factors such as global alignment, disc height, fusion rates, and operative risk, all combined at once.Our study aims to examine all these effects using Flarehawk 9 as a means of interbody fusion.Materials and methods: A total of 58 patients underwent open posterior lumbar surgery using Flarehawk 9 between September 2021 and February 2023 with a mean follow up of 1 year.The mean age was 59.8 years old ( range between 33 and 79 years old), 36 of them are males while 22 of them are females. The diagnostic groups included spinal canal stenosis (n=40), failed back surgery syndrome-revision surgery (n=5),spondylolisthesis with slip percentage 25% (n=4),recurrent herniated disc (n=7) and adjacent segment disease (n=2). Results: The majority of patients demonstrated remarkable improvement based on ODI scores.The rate of union varied based on the fused levels and whether the patients had previous surgery or not.The amount of lordosis postoperatively is increased by 2±0.4 degrees.Conclusions: Even though anterior approaches become more and more popular and advanced nowadays, posterior fusion with interbody cage still remains a safe and effective method to treat various spine surgical pathologies with optimal results.

This study investigates the pivotal areas where Artificial Intelligence (AI) integration in healthcare warrants further exploration, leveraging insights from Boston Specialists, a forefront healthcare provider in AI adoption. Employing a qualitative case study approach, enriched by in-depth interviews and comprehensive literature reviews, we identify three main domains for potential AI expansion: scheduling efficiency, clinical documentation, and AI-driven medical research. Our results underscore the substantial enhancements AI brings to operational workflows and patient care, notably through improved scheduling systems, accuracy in medical documentation, and the facilitation of data-driven research methodologies. These findings suggest a critical need for healthcare institutions to further invest in AI technologies, focusing on these key areas to harness AI's full potential in personalizing care, optimizing efficiency, and advancing medical knowledge. The study concludes with a call for continued investigation into AI's integration within healthcare settings, emphasizing the importance of a supportive organizational infrastructure, ethical considerations, and data security in realizing AI's transformative impact on healthcare delivery and patient outcomes.

Cacipacoré virus (CPCV) was discovered in 1977 deep in the Amazon rainforest, from the blood of a black-faced ant thrush (Formicarius analis). As a member of the family Flaviviridae, genus orthoflavivirus, CPCV's intricate ecological association with vectors and hosts raises profound questions. CPCV’s transmission cycle may involve birds, rodents, equids, bovines, marsupials, non-human primates and bats as potential vertebrate hosts, whereas Culex and Aedes spp mosquitoes, have been implicated as potential vectors of transmission. The virus' isolation across diverse biomes, including urban settings suggests its adaptability as well as presents challenges for its accurate diagnosis and thus its impact on veterinary and human health. With no specific treatment or vaccine, prevention hinges on traditional arbovirus control measures. Here we provide an overview of the ecology, transmission cycles, epidemiology, pathogenesis and prevention, aiming in improving our ability to better understand this neglected arbovirus.

Blood-based biomarkers for early detection of recurrence have a significant clinical impact on the improved management of breast cancer patients, as cancer recurrence results in poor prognosis. This study aimed to investigate if the measurement of blood endocan in breast cancer patients with high ESM1 expression could be an effective tool to detect postoperative recurrence compared with existing tumor markers. Blood was collected before and after the tumor resection from the mouse models of breast cancer, and endocan levels were measured while visualizing metastatic recurrence with noninvasive luminescence imaging. In clinical settings, blood was withdrawn from 16 breast cancer patients before and after the tumor resection, and the effect of lumpectomy on blood endocan level was evaluated. Additionally, the blood endocan from 20 patients diagnosed with postoperative recurrence was measured, and their positivity rate for endocan was compared with that for serum carcinoembryonic antigen (CEA) or cancer antigen 15-3 (CA15-3). Our preclinical and clinical experiments revealed that blood endocan levels reflected tumor burden. Furthermore, over 60% of patients suffering from postoperative recurrence who tested negative for CEA or CA15-3 were positive for endocan. Our results support the clinical significance of endocan in breast cancer patients for detecting breast cancer recurrence.

Dietzia natronolimnaea C79793-74 has emerged as a potential probiotic strain with implications for managing Crohn's disease. This study evaluates the safety profile of D. natronolimnaea C79793-74 as a probiotic sup-plement. Genotypic characterization involved a 16S rRNA gene and genomic sequencing and genome an-notation. The safety assessment included interrogation of the assembled genome for antibiotic resistance genes and virulence factors, utilizing the CARD and VFDB databases. Notably, the analysis revealed an ab-sence of antibiotic resistance or virulence factors in Dietzia natronolimnaea C79793-74. The safety and tol-erability of D. natronolimnaea C79793-74 were further investigated in an 8-week double-blind, place-bo-controlled clinical trial involving healthy adult participants. A daily dose of 5 x 109 CFU of the probiotic strain was administered. This clinical trial represents the first assessment of the safety of D. natronolimnaea C79793-74 in human subjects. Results demonstrated that participants in both the Dietzia and Placebo groups maintained clinical and hematologic markers within the normal range throughout the study. More-over, the probiotic strain was well-tolerated, with nearly all participants experiencing no severe or medium adverse events. Collectively, the comprehensive data obtained in this study support the inference that Dietzia natronolimnaea C79793-74 is safe and well-tolerated as a nutritional supplement for human con-sumption

This review explores the complex interrelationships between emotion, attention, and behavior, drawing upon empirical evidence from psychological, neuroscientific, and clinical studies. It delves into the neural mechanisms that underlie these interactions, with a focus on key brain regions such as the prefrontal cortex and amygdala. Clinical cases involving stroke and attention-deficit/hyperactivity disorder (ADHD) are examined to illustrate the real-world implications of these cognitive interactions. The review also discusses the impact of effective emotion regulation strategies and the role of attention as a cognitive mechanism that influences both emotion and behavior. Neuroimaging studies, particularly functional MRI, are highlighted for their role in providing a deeper understanding of these intricate relationships. The review concludes by emphasizing the importance of this triadic relationship in adaptive functioning and its broader implications for mental health, interpersonal relationships, and quality of life.

Post operative recurrence (POR) is the rule in patients with Crohn’s disease (CD), mitigated with prophylactic therapy. The evidence for therapeutic choice and timing of intervention is lacking. We aimed to compare rates of POR in patients treated early with prophylactic 6-mercaptopurine (6-MP) or adalimumab. We conducted a prospective single center randomized open label clinical study, in which patients in surgical remission following their first ileocecectomy were randomized to receive early treatment with 6-MP or adalimumab. Patients were followed up clinically every 3 months and underwent endoscopy at weeks 32 and 58 post-operatively. The primary endpoint was endoscopic recurrence (ePOR) at 1 year (week 58), defined as a Rutgeerts score≥i2. We enrolled 35 patients (25 males, mean age 35±1.4 years, median disease duration 5±6.1 years) following ileocecectomy. Of these, 7(20%) were current smokers and 9(26%) biologics experienced. Patients allocated to adalimumab had significantly less ePOR than patients treated with 6MP at week 32 (21% vs 69%, p=0.004) and 58 (47% vs 75%), (p=0.03, HR=0.39, 95% CI=0.16-0.93). POR was associated with increased diameter of the resected small bowel surgical specimen, lower baseline body mass index (BMI), increased week 18 fecal calprotectin and serum alanine aminotransferase and decreased week 18 hemoglobin level. Adalimumab is more effective than 6-MP in preventing ePOR. Increased operative small bowel diameter and lower post-operative BMI were associated with ePOR. Eighteen weeks serum hemoglobin and ALT, and fecal calprotectin levels were predictive of endoscopic disease recurrence. (ClinicalTrials.gov ID NCT01629628).

The emergence of M. tuberculosis strains resistant to Isoniazid (INH) and Rifampicin (RIF), the two most potent drugs of first-line anti-TB therapy is termed multidrug drug-resistant TB (MDR-TB). Multidrug-resistant tuberculosis has been a serious medical and epidemic problem all over the world. We present here a series of clinical cases consist of two patients diagnosed with isoniazid resistant tuberculosis. Histopathological examination supports the diagnosis of tuberculous granulomas. And the pathology molecular examination revealed the presence of Isoniazid-resistant Mycobacterium tuberculosis1,2 via the following mutation c.947G>A; p.Gly316Asp. Isoniazid-resistance is associated with mutations in the furA-katG and fabG1-inhA operons, as well as mutations in the ahpC gene. 64% of the isoniazid-resistance phenotypes were associated with the katG315 mutation worldwide. The second most common mutation is inhA-15, and it has been reported in 19% of the Isoniazid-resistant isolates. The significant association between the two mutations, inhA c-15 and katG 315 respectively, and the high-level resistance is of interest in the interpretation of current and future molecular diagnostic testing, as an early prediction of the level of Isoniazid-resistance is essential to decide the benefit of high-dose Isoniazid use.

BACKGROUND: Retinoblastoma is a malignant tumour that develops from the immature cells of the retina. It is the most frequent type of paediatric intraocular cancer and is curable. Clinical and histological findings after enucleation of the affected eye dictate not only the patient's secondary care but also their prognosis. We assessed the clinical and histopathologic predictors of survival among children with retinoblastoma from two tertiary health facilities in Uganda. METHODS: This retrospective research utilized archived formalin fixed & paraffin embedded blocks of eye specimens enucleated between 2014 to 2016 at Mbarara University, pathology department and Ruharo Eye Centre. The specimens were then processed and stained with haematoxylin and eosin. The confirmation of retinoblastoma was made to include histologic stage and features of the tumor. Biographic data of the patients and the clinical features such as leukocoria, proptosis, phthisis, staphyloma, buphthalmos were retrieved from the records.RESULTS: Males (55.1%) dominated the study population (N=78). The median age was 31 months. The commonest clinical sign was leukocoria (69.2%) and the most abundant histopathological stage was stage 1 (41%). Optic nerve invasion 39.5%, choroidal invasion 29.5%, scleral invasion 7.7% and orbital extension 16.7% were seen. Flexner-Wintersteiner rosettes were seen in 24.6%. Necrosis was a prominent feature (71.2%). The two-year survival was estimated to be 62%. Leukocoria (RR 1.1), female gender (RR 1.4), intralaminar optic nerve invasion (RR 7.6) and a lack of orbital extension (RR- 7) were significant predictors of survival.CONCLUSION: Leukocoria and proptosis are noticeable clinical signs of retinoblastoma. Most patients present while in stage one although stage four presentation is also common. Leukocoria, optic nerve invasion, orbital extension, and gender are significant factors predictive of survival in patients with retinoblastoma.