Primary ciliary dyskinesia (PCD) is caused by pathologic variants in over 50 different genes that affect the structure and function of motile cilia. Low nasal NO (nNO) is a biomarker for diagnosis in patients with features of PCD; but the reason why it is low is unclear. At the cellular level, a characteristic feature shared by most PCD patients is that antigens and other particles are not cleared from the epithelial surface. Poor antigen clearance results in pro-oxidant pathway activation and airway epithelial damage and may predispose PCD patients to DUOX1- and IL33- mediated asthma. Secondary ciliary dysfunction, such as that caused by viruses or by smoking, can also contribute to asthma development. Variants in genes underlying the function of cilia, can be associated with poor lung function, even in the absence of PCD. Single nucleotide polymorphisms in PCD – related genes can be associated with increased asthma severity. The role of cilia and antigen stasis is the pathophysiology of asthma is an important area for research, because specific airway clearance techniques and other therapeutic interventions, such as antioxidants, could be of value in preventing the development of asthma and asthma-like symptoms.

Transient receptor potential melastatin-8 (TRPM8) is a cation channel that is activated by cold and “cooling agents” such as menthol and icilin, which induce a cold sensation. Stimulation of TRPM8 activates an intracellular signaling cascade that ultimately leads to a change in the gene expression pattern of the cells. Here, we investigated the TRPM8-induced signaling pathway that links TRPM8 channel activation to gene transcription. Using a pharmacological approach, we show that inhibition of phosphatidylinositol 4-phosphate 5 kinase alpha (PIP5K), an enzyme essential for the biosynthesis of phosphatidylinositol 4,5-bisphosphate, attenuated TRPM8-induced gene transcription. Analyzing the link between TRPM8 and Gq proteins, we show that pharmacological inhibition of the beta gamma subunits impairs TRPM8 signaling. In addition, genetic studies showed that TRPM8 requires an activated Galpha subunit for signaling. In the nucleus, the TRPM8-induced signaling cascade triggers an activation of the transcription factor AP-1, a complex consisting of a dimer of basic region leucine zipper (bZIP) transcription factors. Here, we identified the bZIP protein c-Jun as an essential component of AP-1 within the TRPM8-induced signling cscade. In summary, with PIP5K, Gq subunits and c-Jun we have identified key molecules in the TRPM8-induced signaling from the plasma membrane to the nucleus.

Colorectal cancer (CRC) remains a major global health issue. Although chemotherapy is the first-line treatment, its effectiveness is limited due to drug resistance developed in CRC. To overcome resistance and improve the prognosis of CRC patients, investigation for new therapeutic approaches is necessary. Using human colorectal adenocarcinoma (HT29) and metastatic CRC (SW620) cell lines, the potential anticancer properties of a newly synthesized compound 1-(Isobutyl)-3-(4-methylbenzyl) benzimidazolium chloride (IMBZC) were evaluated by performing MTT cytotoxicity, cell migration, and colony formation assays, as well as by monitoring apoptosis-related protein and gene expression using Western blot and reverse transcription-quantitative polymerase chain reaction technologies. Tested at various concentrations, the half-maximal inhibitory concentrations (IC50) of IMBZC on HT29 and SW620 cell growth were determined to be 6.97 μg/mL and 4.89 μg/mL, respectively. IMBZC did not alter cell growth of normal cells HEK293. In addition, IMBZC inhibited cell migration and significantly decreased colony formation, suggesting its promising role in suppressing cancer metastasis. Mechanistic analyzes revealed that IMBZC treatment increased the expression of pro-apoptotic proteins p53 and Bax, while decreasing the expression of anti-apoptotic proteins Bcl-2 and Bcl-xL, thus indicating the induction of apoptosis in IMBZC-treated CRC cells, compared to untreated cells. Additionally, the addition of IMBZC to conventional chemotherapeutic drugs (i.e., 5-fluorouracil, irinotecan, and oxaliplatin) resulted in an increase in the cytotoxic potential of the drugs. In conclusion, the study suggests that IMBZC has substantial anticancer effects against CRC cells through its ability to induce apoptosis, inhibit cancer cell migration and colony formation, and enhance the cytotoxic effects of conventional chemotherapeutic drugs. These findings indicate that IMBZC could be a promising chemotherapeutic drug for the treatment of CRC. Further research should be conducted using in vivo models to confirm the anti-CRC activities of IMBZC.

Aim/Purpose: This study aims to assess the influence of integrating ChatGPT on enhancing the academic writing performance and engagement of English as a Foreign Language (EFL) undergraduate students at Delhi, India, who are enrolled in Academic Writing during the first semester of the academic year 2024/2025. Given the unique challenges within the Indian undergraduate education system, innovative technological interventions are essential to improve writing skills and increase engagement among EFL learners.

Carbapenemase-producing Enterobacter spp. Serratia marcescens, Citrobacter freundii, Providencia spp. and Morganella morganii (CP-ESCPM) are increasingly identified as causative agents of nosocomial infections but are still not under systematic genomic surveillance. In this study, using a combination of whole genome sequencing and conjugation experiments, we sought to elucidate the genomic characteristics and transferability of resistance genes in clinical CP-ESCPM isolates from Bulgaria. Among the 36 sequenced isolates, NDM-1 (12/36), VIM-4 (11/36), VIM-86 (8/36) and OXA-48 (7/36) carbapenemases were identified; two isolates carried both NDM-1 and VIM-86. The majority of carbapenemase genes were found on self-conjugative plasmids. IncL plasmids were responsible for the spread of OXA-48 among E. hormaechei, C. freundii and S. marcescens. IncM2 plasmids were generally associated with the spread of NDM-1 in C. freundii and S. marcescens, and also of VIM-4 in C. freundii. IncC plasmids were involved in the spread of the recently described VIM-86 in P. stuartii isolates. IncC plasmids carrying blaNDM-1 and blaVIM-86 have been observed too. blaNDM-1 was also detected on IncX3 in S. marcescens and on IncT plasmid in M. morganii. The significant resistance transfer rates highlight the role of the ESCPM group as a reservoir of resistance determinants and stress the need for strengthening the infection control measures.

Thrombosis after severe acute respiratory syndrome coronavirus 2 vaccination is a serious complication in patients who have a thrombophilic predisposition. In this case, a female patient with no family history of thrombophilia who had pediatric antiphospholipid syndrome (APS) developed deep vein thrombosis (DVT) when she was 6 years old; 6 months after receiving a second dose of the BNT162b2 vaccine, DVT reoccurred. The original thrombi were found in the right common iliac vein and the inferior vena cava, with concomitant left pulmonary infarction. The patient was treated with anticoagulants for 6 years after DVT onset, with subsequent treatment cessation for 5 years without recurrence. She received the BNT162b2 vaccine at 17 years of age, 1 week before a routine outpatient visit. Platelet factor 4 elevation was detected 14 days after the first vaccination, persisting for 5 months without thrombotic symptoms. Six months after the second vaccine dose, the DVT recurred and was treated with a direct oral anticoagulant. The vaccine exacerbated the patient’s APS by activating coagulation, causing thrombosis recurrence. Platelet factor 4 levels may indicate coagulation status. When patients predisposed to thrombosis are vaccinated, coagulation status and platelet activation markers should be monitored to prevent DVT development.

ChatGPT, a Large Language Model (LLM) utilizing Natural Language Processing (NLP), has caused concerns about its impact on job sectors, including cybersecurity. In this study, we assessed ChatGPT’s impacts in non-managerial cybersecurity roles using the NICE Framework and Technological Displacement theory. We also explored its potential in passing top cybersecurity certification exams. Findings revealed ChatGPT’s promise in streamlining some jobs, especially those requiring memorization. Moreover, we highlighted ChatGPT’s challenges and limitations, such as ethical implications, LLM limitations, and Artificial Intelligence (AI) security. The study suggests that LLMs like ChatGPT could transform the cybersecurity landscape, causing job losses, skill obsolescence, labor market shifts, and mixed socioeconomic impacts. We recommend a shift in focus from memorization to critical thinking, and collaboration between LLM developers and cybersecurity professionals.

Sentence stimuli pervade psycholinguistics research. Yet limited attention has been paid to the automatic construction of sentence stimuli. Given their linguistic capabilities, this study investigated the efficacy of ChatGPT/AI tools in generating sentence stimuli. In three psycholinguistic experiments, this study examined the acceptability and validity of AI-formulated auditory sentences and written sentences in two languages: English and Arabic. Participants gave English AI-generated stimuli similar to or higher acceptability ratings than human-composed stimuli, but the opposite was observed for Arabic AI-generated stimuli. The validity of AI-developed stimuli relied on the study design, with only Experiment 2 demonstrating the target psycholinguistic effect (L1/L2 morphosyntactic prediction). These results highlight the promising role of AI as a stimuli developer which could facilitate psycholinguistic research and increase its diversity. Implications for psycholinguistic research were discussed.

.Bacground: Sepsis remains a major health challenge worldwide, characterized by a dysre-gulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. Method: This study retrospectively analyzed 309 sepsis patients admitted to the Internal Me-dicine and Anaesthesia ICUs between December 12, 2021, and December 15, 2023, to inves-tigate the relationship between FIB-4 levels, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) and clinical outcomes. Results: The study found that higher FIB-4 measurements were statistically significantly asso-ciated with increased 28-day mortality, with a cut-off value of 4.9 providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated Conclusion:FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients.

Background: This study addresses the burgeoning impact of Large Language Models (LLMs) such as ChatGPT on the integrity of online examinations and seeks to demonstrate latent and advanced LLM reasoning capabilities. The research devises an iterative self-reflective strategy for invoking critical thinking and higher-order reasoning in LLMs based on multimodal exam questions using visuals and text. Methods: The proposed strategy was demonstrated and evaluated on real exam questions by subject experts and the performance of ChatGPT (GPT-4) with vision was estimated on an additional dataset of 600 text descriptions of multimodal exam questions, focusing on its response to complex, visual, and textual prompts. Results: The results indicate that latent multi-hop reasoning capabilities can be invoked using the proposed self-reflective strategy, which can effectively steer ChatGPT towards correct answers by integrating critical thinking from each modality into the final response. Meanwhile, ChatGPT demonstrated considerable proficiency in being able to answer multimodal exam questions across 12 subjects. Conclusions: This work challenges findings from recent studies which claim that existing LLMs are unable to reason on complex multimodal tasks, and therefore this study underscores the need for enhanced online exam security measures like proctoring software, that can mitigate the potential misuse of AI technologies in educational settings.

Background: Classical Hodgkin's lymphoma (cHL) is a lymph node disease, however, extranodal involvement is present in about 10% of affected individuals. Various forms of direct central nervous system (CNS) involvement have been reported, including intracranial, epidural, leptomeningeal, and intramedullary spinal cord cHL (Table 1). We hereby describe the clinical presentation, work up, and outcomes of two distinctive cases of cHL with intracranial extra-axial spread in patients receiving novel combination and traditional chemotherapy. Methods: This case series (n=2) was conducted following the CARE guidelines. Institutional review board (IRB) approved protocol #24-015 for HIPPA waiver of subjects in our retrospective study. Results: Patients with cHL exhibiting CNS symptoms or relapse refractory cases benefit from neuroimaging and excluding infectious etiologies. Suspicious lesions include iso- to hypointensity on T1 weighted and iso- to hyperintensity on T2 MR scans. Diagnosis is confirmed with biopsy. Treatment with A-AVD has shown more benefit than traditional ABVD chemotherapy. There has been shown progression free survival with nivolumab-AVD (N-AVD) over brentuximab-AVD (B-AVD). Conclusion: cHL with CNS involvement is rare and requires comprehensive workup to exclude infectious and other malignancies. Diagnosis relies on neuroimaging and subsequent brain biopsy. Treatment with novel N-AVD has shown greater PFS in patients with advanced cHL.

Metabolomics profiling for accurate and reliable quantification of organic acids that carry a carboxylic acid functional group in complex biological samples, remains a major analytical challenge in clinical chemistry research. Several procedural barriers associated with quantification of clinically important carboxylic containing metabolites (CCMs) including spontaneous decarboxylation during ionization, poor chromatographic resolution, and retention on a reverse-phase column, limit the sensitivity, specificity, and reproducibility of multiple-reaction monitoring (MRM) based LC-MS assay development. We report a targeted metabolomics-based analytical method for the quantification of CCMs using phenylenediamine derivatization. Accurate and sensitive quantification of CCMs is successfully demonstrated in an array of biological matrices. Recovery of metabolites from different matrices (plasma, serum, urine, saliva, tissues, and cell extracts), ranged from 90% to 105%, with all the CVs ≤ 10%. The method showed linearity over a broad dynamic range from 0.1 ng/mL to 10 µg/mL with linear regression coefficients of 0.99 for most of the metabolites tested herein, that covers broad-based applicability with the analysis of biological samples. In most cases the LODs were as low as 0.01 ng/mL. The phenylenediamine-based derivatization of carboxyl acid library consisting of more than 70 endogenous metabolites was constructed for metabolite identification, which spanned more than 40 biological pathways. The library included a wide-variety of structurally variant CCMs such as amino acids/conjugates, short to medium chain organic acids, di/tri-carboxylic acids/conjugates, fatty acids and some ring-containing CCMs. We compared the CCMs profiles of pancreatic cancer cells with normal pancreatic epithelial cells to test and validate the biological utility of this method. The comparative profiling between cancerous and normal cells resulted in the identification of potential biomarkers in pancreatic cancer, and their correlation with several key metabolic pathways such as central carbon energy metabolism, protein metabolism, including TCA cycle, glycolysis, Gln-Glu pathway, and biosynthesis of amino acids and unsaturated fatty acids was established. The method, described herein, for the first time enables the sensitive and highly specific quantification of CCMs on small sample size with high reproducibility in a high throughput manner. Given the biological and functional significance of this class of metabolites, this mass spectrometry based targeted quantitative assay, fills an important gap and is likely to support a wide range of applications for basic, clinical, and translational research.

This study proposes an innovative pharmacovigilance approach, VIGI-4, leveraging ChatGPT Teams Pro version. Our method involves aggregating data from all phase 4 studies published in February 2024 to identify adverse reactions. These results are categorized by disease state alphabetically, demonstrating the method's capacity to generate structured and easily navigable outputs. The results section is tailored to exemplify the valuable, actionable insights attainable through our workflow. This research emphasizes the game-changing potential of integrating advanced technologies such as ChatGPT into pharmacovigilance, signaling a new era in safeguarding drug safety.

In an era where dietary habits significantly impact health, technological interventions can offer personalized and accessible food choices. This paper introduces Chef Dalle, a recipe recommen-dation system that leverages multimodal human-computer interaction (HCI) techniques to pro-vide personalized cooking guidance. The application integrates voice-to-text conversion via Whisper, ingredient image recognition through GPT-Vision, and employs TF-IDF vectorization alongside cosine similarity for personalized recipe recommendations. These methods enable users to interact with the system using voice, text, or images, accommodating various dietary re-strictions and preferences. Furthermore, the utilization of DALL-E 3 for generating recipe images enhances user engagement. User feedback mechanisms allow for the refinement of future rec-ommendations, demonstrating the system's adaptability. Chef Dalle showcases potential appli-cations ranging from home kitchens to grocery stores and restaurant menu customization, ad-dresses accessibility, promoting healthier eating habits. This paper underscores the significance of multimodal HCI in enhancing culinary experiences, setting a precedent for future developments in the field.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

Background: With its impressive natural language processing and comprehension skills, ChatGPT-4 (Chat Generative Pre-Trained Transformer) is a technology that shows great promise for use in a number of medical fields. This article provides a thorough description of the possible uses of OpenAI's state-of-the-art language model, ChatGPT-4, in musculoskeletal imaging. Purpose for review: MSK Radiologists need to evolve about their knowledge and understanding of the roles of ChatGPT and its implications in daily practice. We aim to emphasize the advantages of ChatGPT-4 on the musculoskeletal imaging field and its potential to enhance radiologist working checklist review items, and the overall productivity of radiology reports. Recent findings: The fact of that specialists in radiology, rheumatology, orthopedic surgery, and other fields are conversant with ChatGPT. Furthermore, opinions are generally well, despite the fact that many people have reservations about the new technology, which is still developing ^[1]. Compared to GPT-4V based ChatGPT, GPT-4 based ChatGPT showed noticeably better diagnostic accuracy. Although ChatGPT, which is based on GPT-4, performed diagnostically on par with radiology residents, however, it demonstrated lower performance than a musculoskeletal radiologist ^[2].

Background: Open AI developed ChatGPT, a language model based on the GPT architecture, designed for text-based communication. Trained on diverse internet texts, ChatGPT generates contextually appropriate responses using machine learning. It understands input through analysis and context interpretation, generating coherent and contextually relevant responses. Interaction is possible through messaging platforms. Materials and Methods: In November 2023, we utilized ChatGPT 3.5, the default version at that time, to answer questions from the Italian National Residency Program Admission Tests (SSMs) of 2021, 2022, and 2023. The questions cover clinical, diagnostic, analytical, therapeutic, and epidemiological scenarios, sometimes accompanied by images. The study compared ChatGPT's answers to the official corrections on the Italian Ministry of University and Research (MUR) website. The scoring method used for evaluation was 1 point for correct answers, 0 points for unanswered questions, and -0.25 points for incorrect answers, reflecting the SSM test scoring system. Results: In summary, ChatGPT was tested with a total of 420 questions, 140 for each test. It achieved an overall accuracy of 80.48%, providing correct answers for 338 questions and incorrect answers for 82 questions. When faced with questions containing both text and images, it answered 55% correctly and 45% incorrectly. The model's performance varied over time, with an 82.14% accuracy rate in 2021 and 2022 (115 correct out of 140) and a 77.14% accuracy rate in 2023 (108 correct out of 140). Applying thisscoring method to the SSM test, ChatGPT would have scored 105 points in 2021 and 2022, and 100 points in 2023. Conclusions: ChatGPT has exhibited above-average performance in the last three SSM tests, highlighting its robust capability to interpret clinical scenarios and offer precise diagnostic and therapeutic guidance. Despite this, some limitations persist, notably the software's inability to interpret non-textual information.

Additive manufacturing (AM) or 3D printing of metals is gaining popularity due to its flexibility in fabricating parts with highly complex designs, as well as simplifying manufacturing steps and optimizing process times. In this investigation, 17-4 PH stainless steel was additively manufactured using Laser-Powder Bed Fusion (L-PBF), followed by functionalization through a DUPLEX treatment. This treatment involved a plasma-assisted nitriding process, followed by deposition of an arc-PVD c-Al0.7Cr0.3N hard coating. The microstructural modifications resulting from plasma nitriding (such as the formation of Fe2,3N and Fe4N, and the αN or expanded martensite phases), and the surface improvements with the c-Al0.7Cr0.3N coating on the 3D-printed 17-4 PH steel, are evaluated in comparison to conventionally manufactured 17-4 PH steel. These microstructural characteristics are correlated with the mechanical response of the treated surfaces. As a result of the plasma nitriding process, the hardness of the 3D-printed 17-4 PH SS increased by approximately 260%. The wear, measured through dynamic and static scratch-testing, was reduced by approximately 31%. This improvement was attributed to the modification of adhesive failure mechanisms, leading to a reduction in wear volume, improved coating adhesion, and enhanced scratch resistance.

Artificial intelligence methods, especially artificial neural networks (ANNs), have recently been successfully used more and more frequently in the mathematical description of physical phenomena in the processing of metallic materials. Results based on measured data of phenomena in real production are often, at least locally, different or more complex than the results of established theories. In general, ANN models, which mostly work as "black boxes", allow us to improve production efficiency by themselves. The fact is, however, that a better understanding of the phenomena under consideration, which is otherwise enabled by classical mathematical approaches in the form of explicit mathematical formulas, could ensure even greater efficiency. In this article, therefore, a general concept is proposed to explain the discussed phenomena in metallic materials. The application of the concept is illustrated on the example of hot extrusion of aluminum alloy 6082, where CAE is used as an artificial neural network to model the phenomenon and predict the key parameters of the phenomenon. ChatGPT is used to explain the results according to the proposed concept. The basic idea is to enable practicing engineers to better understand the considered phenomena and results obtained by ANNs.

Human Immunodeficiency Virus (HIV) infection and its latent recurrent infection make vaccine development a significant challenge for traditional vaccines; however, the mRNA delivery of multiepitope antigens capable of creating antibodies against the surface proteins of HIV-1 and HIV-2 along with their respective Nef proteins, responsible for the latent infection can bring a most effective, as well as affordable solution to the unresolved epidemics of HIV. In this paper, we present the complete design of a multiepitope vaccine to prevent acute infections and inactivate Nef proteins that block the MHC-1 and MHC-2 pathways to hide the virus for later reinfection.

This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

Artificial Intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use ChatGPT holds a prom-inent position using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for gen-erating human-like responses to queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT in-tegration, with pilot studies and trials revealing each field's potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex data sets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs.

Introduction: In recent years, generative Artificial Intelligence models, such as ChatGPT, have been increasingly utilized in healthcare. Despite acknowledging the high potential of AI models in terms of quick access to sources and formulating a response to a clinical question, the results obtained using these models still require validation through comparison with established clinical guidelines. This study compares the responses of the AI model to eight clinical questions with the Italian Association of Medical Oncology (AIOM) guidelines for ovarian cancer. Materials and Methods: The authors used the Delphi method to evaluate responses from ChatGPT and the AIOM guidelines. An expert panel of healthcare professionals assessed responses based on clarity, consistency, comprehensiveness, usability, and quality using a 5-point Likert scale. The GRADE methodology assessed the evidence quality and the recommendations' strength. Results: A survey involving 14 physicians revealed that the AIOM guidelines consistently scored higher averages compared to the AI models with a statistically significant difference. Post-hoc tests showed that AIOM guidelines significantly differed from all AI models, with no significant difference among the AI models. Conclusions: While AI models can provide rapid responses, they must match established clinical guidelines regarding clarity, consistency, comprehensiveness, usability, and quality. These findings underscore the importance of relying on expert-developed guidelines in clinical decision-making and highlight potential areas for AI model improvement.

The reactivity of 3,5-di-(pyridin-4-yl)-1,2,4-thiadiazole (L1) with 1,4-diiodotetrafluorobenzene (1,4-DITFB) was explored and the halogen-bonded 1:1 co-crystal (1) was successfully isolated and structurally characterized.

This is a brief critique of the functions—particularly olfactory functions—specified for the “Chemosensory Protein” (CSPs) molecule family. On the basis of these proteins’ presence in the sensory antennal lymph of locusts, odor chemosensory ligand binding functions have been hypothesized. According to this hypothesis, the entire protein molecule superfamily is referred to as “CSPs”. However, new information and developments in the field of CSP molecular research, such as the expression of CSP genes in the gut, brain, fat body, wings, epidermis, and pheromone gland, as well as gene expression profiling from most early developmental stages—that is, CSP expression well in advance of the appearance of chemical sense nerve cells—strongly suggest that the protein molecule has other roles that are unrelated to chemosensing. Moreover, CSPs are found in bacterial microbial prokaryote organisms in addition to insects and all other arthropods. Thus, we examine the molecule’s name, definition, RNA editing, protein structure, lipid binding properties, DNA interaction, and evolutionary characteristics in brief before referring to this protein family as “Chemosensory Proteins”. As a means of renaming this protein family, this review article discusses the latest findings (“CSP” is attached to the tail of bigger intracellular proteins) and attempts to compel all the data. Because of its highly conserved molecular distinctive feature (four adjacent cysteines), we propose renaming “CSPs” as “4CSPs” (4 Cysteines Soluble Proteins) and use at least for abbreviations for distinctive animal proteins the common peptide 5-letter code, such as “Bommo-4CSPs”.

Predatory research field in science is when an emerging scientific topic destroys current topics and characterizes a main scientific change. Predatory research field can be a basic driver of scientific and technological change that generates a 'creative destruction' in science and society in contexts of knowledge-based competition and rapid changes. The prediction of proposed theory of predatory research fields is that it destroys with a fast growth other research fields. The theoretical approach is tested here in research fields of large language models (LLM) by analyzing the transformers (a deep learning architecture based on the multi-head attention mechanism) proposed in 2017 and from November 2022 started main applications in generative artificial intelligence with innovations of BERT, ChatGPT, Microsoft Copilot (launched on February 7, 2023) and other natural language processing tools driven by AI technology for engaging conversations, gain insights, automate tasks, etc., etc. Statistical evidence suggests that growth rate of transformer technologies is 80.58%, a high level compared to all other research fields in machine learning (having a growth rate of 13.83%). Moreover, predatory research field of transformers has a destructive power such that all other domains in LLM from 2021 to 2023 have a general reduction of scientific growth. The impact of transformers is much more drastic of previous radical technologies such as CNN having a temporal growth rate of 0.16%, lower than 0.38% by transformers, ceteris paribus. These analysis reveals that transformers have characteristics to generate a radical scientific and technological change in a not-too-distant future. Overall, then, the study suggests that predatory research field on emerging topics and technologies can generate path-breaking innovations and the examination here can clarify the essential elements of the science dynamics for a better theory of scientific and technological change, providing also main implications for knowledge policy to support promising research fields and technologies to guide economic and social change.

The study aimed to know the direct effect of strategic leadership on the quality of service represented by wireless communications services, in addition to knowing the indirect effect of strategic leadership on the quality of service when using performance as an intermediary variable. This research was conducted in government institutions in the Republic of Yemen. Represented by the offices of the Ministry of Communications and Information Technology in five Yemeni cities, it targeted senior management employees, boards of directors, and middle management concerned with strategic planning and strategic leadership. To measure and evaluate the factors of strategic leadership and service quality in Offices of the Yemeni Ministry of Communications Ministry of Communications and Information Technology of the Republic of Yemen. Moreover, performance. A questionnaire was formulated and distributed to the study sample, and data was collected through questionnaires for 150 individuals in some offices of the Yemeni Ministry of Communications. This study uses structural equation model analysis from the Partial Least Squares program through the Smart Plus 4 programs. The study reached a set of results, including that all models show a direct, positive and significant effect of strategic leadership on the quality of service represented by the quality of services in the offices of the Ministry of Communications. As well as the positive relationship between them, as well as the direct and positive impact of performance on the quality of service, as well as the positive and significant relationship between them. While the results indicated a positive and significant indirect effect of strategic leadership on service quality, there is also a positive and significant indirect relationship between strategic leadership on service quality when using performance as an intermediary variable.

Owing to their extensive biological potential, essential oils (EOs) and their bioactive phytochemicals have gained attention from the scientific community. Within this domain, Terpinen-4-ol (T-4-ol), a bioactive monoterpene alcohol and the major constituent of tea tree oil (TTO), has made its way into translational research. Recent literature on T-4-ol strongly indicates its diverse pharmacological properties, including but not limited to antimicrobial, antivirulent, antioxidant, anti-inflammatory, anti-hypertensive, and anti-cancer effects. Hence, this review provides a comprehensive overview of the multifaceted biological activities exhibited by T-4-ol, emphasizing its medicinal potential for widescale application. The antibacterial and antifungal effectiveness of T-4-ol has been discussed encompassing its role in combating a broad spectrum of bacterial and fungal pathogens, respectively. The review delves into the antivirulent prospects of T-4-ol, shedding light on its ability to attenuate virulence and mitigate bacterial pathogenesis. Scientific literature on the antioxidant and anti-inflammatory activity of T-4-ol highlighting its role in neutralizing reactive oxygen species and modulating inflammatory pathways has also been collated. Furthermore, the review elaborates on the cardioprotective and anti-hypertensive properties of T-4-ol and augments literature on its anti-cancer mechanism against various cancer cell lines. Overall, this review consolidates the existing knowledge on T-4-ol, providing a holistic understanding of its pharmacological abilities. The exploration of these diverse attributes positions T-4-ol as a promising candidate for further research and therapeutic repurposing in various biomedical applications.

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. Recent data highlight similarities between neurodegenerative diseases including PD and type 2 diabetes mellitus (T2DM) suggesting a crucial interplay between the gut–brain axis. GLP-1R agonists, known for their use in T2DM treatment, are currently extensively studied as novel PD modifying agents. For this narrative review article, we searched PubMed and Scopus databases for peer-reviewed research, review articles and clinical trials regarding GLP-1R agonists and PD, published in the English language with no time restrictions. We also screened the references of the selected articles for possible additional articles in order to include most of the key recent evidence. Our research was conducted between February 2023 and February 2024. We used the terms “GLP-1”, “GLP-1 receptor”, “GLP-1R agonists”, “PD”, “T2DM”, “insulin”, “neurodegenerative disease”, “glucose”, “animal models”, “clinical trials” in different combinations. Many data on animal models and preclinical studies show that GLP1-R agonists can restore dopamine levels, inhibit dopaminergic loss, attenuate neuronal degeneration and alleviate motor and non-motor features of PD. Evidence from clinical studies are also very promising enhancing the possibility of adding GLP1-R agonists in the current armamentarium of drugs available for PD treatment.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

The Distributed eLearning Center (DeLC) is a portal, providing extensive support in the day-to-day work when it comes to e-learning content – it helps students and teachers organize their learning materials, fill the gaps in knowledge (for students) and educational approaches (for teachers), organize and conduct exams, and overall, with providing proactive and personalized e-learning environment. The scope of DeLC as a project involves many extensions, covering the aspects of learning, teaching, exams, and collecting statistical information. Such extension is an agent-oriented environment, which enriches the functionalities with intelligent components, that are reactive and proactive, referred to as agents or assistants. This paper is focused on presenting the latest step in the evolution of FraudDetector software agent, which started with base functionality for fraud detection, and now it aims at usage of AI to accomplish its tasks, taking advantage not only from its knowledgebase, but from a much larger one, used by ChatGPT – through integration with it, which is the main contribution of this research, although the real results from production environment are still pending. In this process, agent’s architecture should stay open for collaboration with another external AI provider if necessary, trying to decouple the components, responsible for integration. As of now, the experiments show that involving ChatGPT in FraudDetector’s functionality enriches it and the agent’s precision could be improved this way.

Generative artificial intelligence tools are flourishing across various sciences, particularly in the educational domain. ChatGPT, with its versions 3.5 and 4.0, stands out for its multilingual capabilities, catering to both students and educators. This research aimed to evaluate the performance differences between these versions, and importantly, to compare the accuracy of ChatGPT's responses in English versus Arabic. In our study, we presented ChatGPT with 39 chemistry problems related to 6th-7th grade curriculum, including twenty-five open questions and fourteen multiple-choice questions. Each response was categorized as accurate, partially accurate, or inaccurate. Our analysis, focused on trends across versions and languages, revealed significant enhancements in version 4.0, particularly in its ability to process Arabic. However, despite these improvements, our findings indicate that responses in English consistently outperformed those in Arabic in terms of accuracy. In light of this discrepancy, we suggest that ChatGPT either incorporates additional Arabic databases into its training regimen or develops a code that adopts the following strategy to ensure more accurate responses in science education: questions should first be translated from Arabic to English, addressed, and then retranslated into Arabic before being presented to the user. This approach takes advantage of the greater accuracy of responses in English to benefit Arabic-speaking users, and it may also improve outcomes for speakers of other languages who experience less precise answers in the fields of chemistry or science education.

This report provides a comprehensive overview of occupational asthma and respiratory hypersensitivity, focusing on some chemicals used in the workplace Includes numerous case studies and research papers related to occupational exposure methacrylates, such as HEMA-HPMA, and respiratory hypersensitivity are discussed And the relationship is explored The book also examines asthma pathophysiology, emerging drug delivery systems used to treat asthma, and the potential of nanoparticles , dendrimers and micellar systems have to improve pulmonary drug delivery in detail The worldwide prevalence of asthma is highlighted, with higher rates in high-GDP countries. The book highlights the need to improve asthma diagnosis, treatment and biomarkers, particularly in rural and low-income countries where the disease is often underdiagnosed and inadequately treated, and discusses the role of inflammation in asthma, in particular secondary inflammation characterized by specific cytokines and inflammation cells In addition, the paper explores various drug delivery methods, such as parenteral and parenteral drugs, pressurized inhalers (pMDIs), dry powder inhalers ( DPIs), nebulizers, nanoparticles, liposomes, micellar systems, microparticles , dendrimers, and gene therapy . These systems aim to increase pulmonary delivery of drugs and improve clinical outcomes. The potential of dendrimer bilirubin-based nanoparticles and micellar systems in the treatment of asthma and lung inflammatory diseases, including asthma, has been discussed in summary, this paper provides an overview of occupational asthma and respiratory hypersensitivity, and this discussion highlights the association between methacrylate exposure and respiratory hypersensitivity.

The aim of this study was to determine the microbial stability, challenge to L. monocytogenes, and some physicochemical properties of turkey breast meat by alginate-based coating enriched with postbiotics (8% concentration, CFS) of Bifidobacterium bifidum DSM 20456 and Bifidobacterium bifidum BB12 strains. For this purpose, firstly, some antimicrobial and total phenolic matter, flavonoid, and DPPH activity values of postbiotics were determined. In addition, FTIR analysis was performed to see the intermolecular interactions of the biological coating agent. As a result of the study, alginate solution with postbiotic showed significant differences in pH, a*, b*, yeast-mold values of turkey meat during storage (7 days), while L* value, total aerobic mesophilic bacteria count (TMAP), psychrotrophic bacteria (PAB), lactic acid bacteria (LAB) and Listeria monocytogenes count were not effective (p>0.05).

With the aim to develop novel scaffolds for sustained release of drugs, we initially developed an easy approach for the synthesis of α,ω-homobifunctional mercaptoacyl poly(alkyl oxide)s. This was based on the esterification of the terminal hydroxyl groups of poly(alkyl oxide)s with suitably S-4-methoxytrityl (Mmt) protected mercapto acids, followed by removal of the acid labile S-Mmt group. This method allowed the efficient synthesis of the title compounds in high yield and purity, which were further used in the development a thioether cross-linked liposome scaffold, by thia-Michael reaction of the terminal thiol groups with preformed nano-sized liposomes bearing maleimide groups on their surface. The reaction process was followed by 1H-NMR, using a Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion NMR experiment (1H-NMR CPMG), which allowed real-time monitoring and optimization of the reaction process. The thioether cross-linked liposomal scaffold that was synthesized was proven to preserve the nanosized characteristics of the initial liposomes and allowed sustained release of calcein (which was used as a chromophore), providing evidence for the efficient synthesis of a novel drug release scaffold consisted of nanoliposome building blocks.

To accurately and non-destructively monitor the growth of spring wheat in the Hetao Irrigation Area, UAV remote sensing was employed during various fertility stages. Digital image indices from diverse fertilization treatments were calculated and compared with physiological indices to identify the most sensitive digital image indices corresponding to these indices. The study underscored the critical importance of the flowering stage in the growth of spring wheat, thus highlighting the necessity of focusing on this stage. This finding reiterated that the flowering stage was pivotal for spring wheat development in the Hetao Irrigation Area. Several digital image indices, such as GLA, R, G, INT, g, GRVI, MGRVI, RGBVI, EXG, and GRRI, exhibited a high frequency of significant correlations with physiological indices during the four primary reproductive stages of wheat. Consequently, these sensitive digital image indices during the flowering stage can more effectively characterize the physiological indices of spring wheat.

This study investigates the moderating effect of corporate governance on the associations of internal audit and quality of internal audit with quality of financial reporting among commercial banks in the Republic of Yemen. The final sample includes 210 internal auditors, heads of internal auditors, chairpersons, and members of audit committees. Using a survey-based methodology, the results of the Smart-PL4 analysis showed a positive association between internal audit and quality of internal audit and quality of financial reporting. Interestingly, the results showed an insignificant association between internal audit, quality of internal audit, and quality of financial reporting when considering the moderating effect of corporate governance. The findings of this study contributes valuable insights to the existing literature on the influence of internal audit, quality of internal audit, and corporate governance on quality of financial reporting in developing countries, specifically in Yemen.

The fast-paced evolution of artificial intelligence (AI), machine learning (ML), natural language processing (NLP), large language model (LLM) applications, and generative pre-trained transformer (GPT) have set the stage for improved and autonomous project scheduling models. This study demonstrates how project scheduling can be enhanced by employing building information modeling (BIM) to predict reliable schedules for each project element. The research is based on design science research (DSR) methodology and focus group discussion. The proposed system consists of six components: project analyzer, data warehouse, activity identifier and sequencing, activity magnitude and direct cost calculator, activity duration calculator, and schedule analyzer. Unlike other solutions, the proposed solution sequences activities based on an ML model rather than constraint matrices. The proposed solution thus enhances project performance through proactive planning and risk management. Integrating the autonomous project scheduling solution with the other components of an autonomous project management system would surmount schedule challenges and would result in greater cost efficiency and fewer delays.

Incorporating AI tools like ChatGPT into higher educational settings has been beneficial for education, yet the extent of user satisfaction with the information provided by these tools, known as user information satisfaction (UIS), remains underexplored. Our study introduces a UIS model specifically designed for ChatGPT's application in the educational sector. Drawing from established UIS theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide both educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. We gathered data from Indonesian university participants and applied Structural Equation Modeling using Smart-PLS 4.0 for our data analysis. The results reveal that completeness, precision, timeliness, convenience, and the format of information as the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings lead to a recommendation for a cautious approach to the integration of ChatGPT in higher education. We advocate for a strategic use that recognizes its innovative potential while also acknowledging its limitations, thus ensuring a responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.

Amidst the rapid advancements in artificial intelligence (AI) applications, determining the alignment between AI evaluations and human judgment remains crucial, especially in sectors like finance, healthcare, and education. This study delves into a unique scenario—a teenage entrepreneur pitch competition, mirroring real-world challenges faced by these young innovators. The objective was to assess the congruence between evaluations by ChatGPT, an AI model, and human judges. The results indicate a remarkable alignment between AI and human evaluations across several criteria. The implications of this study are far-reaching, highlighting AI's potential in ensuring unbiased and reliable evaluations in pitch competitions and beyond. However, navigating the juncture of AI and human judgment mandates continued research and ethical considerations.

The sustainability of Indigenous Socioecological Systems (ISES) faces significant threats from global anthropogenic environmental changes, endangering Indigenous People (IP), who safeguard a substantial portion of the world's natural capital. Indigenous Traditional Food Systems (ITFS) are crucial within ISES, providing not only diverse and nutritious food but also holding cultural, spiritual, and economic significance. Despite embodying sustainable lifestyles, Indigenous voices remain underrepresented in climate and sustainability discussions. Addressing this gap, the research adopts the Political Ecological Theoretical Framework (PETF) to analyze the regulatory impact on the adaptability, resilience, and sustainability of ITFS. Two Indigenous communities, the Karen in Thailand and various groups in the Republic of Sakha (Yakutia) in Russia, serve as case studies. The study aims to establish a theoretical framework integrating Indigenous concerns into policies and regulations, emphasizing self-determination, cultural preservation, and land rights. Findings emphasize the necessity for comprehensive legal frameworks prioritizing Indigenous involvement in climate resilience and sustainability efforts, moving beyond symbolic gestures towards meaningful collaboration and decision-making power. Recognizing Indigenous vulnerability and engaging them as active partners is essential for navigating climate challenges within ISES and ITFS.

The introduction of ChatGPT in academia has raised significant concerns, particularly regarding issues like plagiarism and the ethical use of generative text for academic purposes. Existing literature has predominantly focused on ChatGPT adoption, leaving a notable gap in addressing the strategies users employ to mitigate these emerging challenges. To bridge this gap, this research utilizes the Uncertainty Reduction Theory (URT) to formulate user strategies for reducing uncertainty. These strategies include both interactive and passive approaches. Concurrently, the study identifies key sources of uncertainty, which include concerns related to transparency, information accuracy, and privacy. Additionally, it introduces the concepts of seeking clarification and consulting peer feedback as mediating roles to facilitate reduced uncertainty. We tested these hypotheses with a sample of Indonesian users (N = 566) using structural equation modeling via Smart-PLS 4.0 software. The results confirm that interactive Uncertainty Reduction Strategies (URS) are more effective in reducing uncertainty when using ChatGPT compared to passive URS. Transparency concerns, information accuracy, and privacy concerns are identified as factors that increase the level of uncertainty. In contrast, consulting peer feedback is the most effective strategy for reducing uncertainty compared to seeking clarification at the individual-system level. Insights from the mediating effects confirm that consulting peer feedback significantly mediates uncertainty sources to reduce uncertainty. The study discusses various strategies for the ethical use of ChatGPT by users in the educational context and contributes significantly to theoretical development.

(1) Background: The aim of study was to investigate the salt consumption by children and adolescents from the Silesian Province (Poland), taking into account the region’s dietary traditions and number of years of school education. (2) Methods : 300 students aged 10–18 from different types of schools, were enrolled in the study and divided into groups in terms of: school, sex, the state of nutrition. The survey questionnaire about dietary habits, including the frequency and serving size with respect to 12 salty products was used. On the basis of the frequency and the amount of consumed products, as well as the data on salt content, the amount of total daily intake of salt was estimated.; (3) Results: The mean daily intake of salt by children and adolescents was 1.083 g ( 0.433 g of sodium); children aged 10–12 consumed the highest amount of salt (1.296 g/day) compared to pupils aged 13–15 (1.131 g of sodium) and adolescents aged 16–18 (0.863 g/day); (4) Conclusions: With age, as a result of various factors, the consumption of salt declines. The parents impact and the familial socio-environmental factors begin to wane, and other factors start to have influence, e.g. school education of healthy lifestyle, health behavior of peers.

Antipsychotic drug (APD) medication can lead to metabolic dysfunctions and weight gain, which together increase morbidity and mortality. Metabolically active visceral adipose tissue (VAT) in particular plays a crucial role in the etiopathology of these metabolic dysregulations. Here we studied the effect of 12 weeks drug medication by daily oral feeding of clozapine and haloperidol on the perirenal fat tissue as part of VAT of male and female Sprague Dawley rats in the context of complex former investigations on brain, liver, and blood. Adipocyte area values were determined as well as triglycerides, non-esterified fatty acids (NEFAs), glucose, glycogen, lactate, malondialdehyde equivalents, ferric iron and protein levels of Perilipin-A, hormone-sensitive-lipase (HSL), hepcidin, glucose transporter-4 (Glut-4) and insulin receptor-ß (IR-ß). We found increased adipocyte mass in males with slightly higher adipocyte area values in both males and females under clozapine medication. Triglycerides, NEFAs, glucose and oxidative stress in the medicated groups were unchanged or slightly decreased. In contrast to controls and haloperidol medicated rats, perirenal adipocyte mass and serum leptin levels were not correlated under clozapine. Protein expressions of perilipin-A, Glut-4 and HSL were decreased under clozapine medication. IR-ß expression changed sex-specifically in the clozapine medicated groups associated with higher hepcidin levels in the perirenal adipose tissue of clozapine-medicated females. Taken together, clozapine and haloperidol have a smaller effect than expected on perirenal adipose tissue. The perirenal adipose tissue shows only weak changes in lipid and glucose metabolism. The main changes can be seen in the proteins examined and probably in their effect on liver metabolism.

Chronic lymphocytic leukemia (CLL) is characterized by dysfunctional B cells. Immune checkpoint molecules such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and programmed death-1 (PD-1) are upregulated in patients with CLL and may correlate with prognostic markers such as beta-2 microglobulin (B2M). The aim of this study was to evaluate the levels of immune checkpoints on B-cell subsets and to further correlate them with B2M levels in patients with CLL. We recruited 21 patients with CLL and 12 controls. B cell subsets and the levels of immune checkpoint expression were determined using conventional multi-color flowcytometry. Basal levels of B2M in patients with CLL were measured using an Enzyme-linked immunosorbent assay. Patients with CLL had increased levels of activated B cells when compared to the control group, p< 0.001. The expression of PD-1 and CTLA-4 were increased on activated B cells and memory B cells, p< 0.05. There were no associations between B2M levels and the measured immune checkpoints on B cell subsets, after adjusting for sex and age. African patients with CLL express elevated levels of PD-1 and CTLA-4 immune checkpoints on activated and memory B cell subsets. However, there is no correlation between these immune checkpoint expressions and B2M levels.

Nucleic acid delivery through extracellular vesicles (EVs) is a well-preserved evolutionary mechanism in all life kingdoms including eukaryotes, prokaryotes, and plants. EVs naturally allow horizontal transfer of native as well as exogenous functional mRNA, that once incorporated in EVs is protected from enzymatic degradation. The possible use of EVs as carriers for vaccine has been investigated showing that EVs expressing recombinant SARS-CoV-2 S protein induced an immune response. Moreover, EV-based vaccines presenting the natural configuration of viral antigens have advantages in conferring long lasting immunization and lower toxicity than synthetic nanoparticles. To overcome the manufacturing limitations of EVs derived from eukaryotic cells, edible plant-derived EVs have been studied as an attractive alternative for vaccine delivery, especially for mucosal administration. We recently showed that EVs obtained from orange juice (oEVs) loaded with SARS-CoV-2 mRNAs protected their cargo from enzymatic degradation and were stable at room temperature for one year. Lyophilized oEVs containing the S1 mRNA were administered to rats by gavage and they induced a specific humoral immune response with generation of blocking antibodies, including IgA, that are the first mucosal barrier in the adaptive immune response. Moreover, a Th1 cytokine secretion occurred, suggesting a specific lymphocyte activation. In conclusion, mRNA-containing oEVs could be used for developing new oral vaccines due to optimal mucosal absorption, resistance to stress conditions, and the ability to stimulate a humoral and cellular immune response.

In ore regions impacted by mining and metal smelting emissions, distinguishing between geogenic anoma-lies and anthropogenic contamination poses a significant challenge. In a study from two areas with different mining histories in the Ore Mountains, Czech Republic, we demonstrate that targeted sampling of topsoils and subsoils respecting local geology and correct soil data treatment respecting soil textural variability effects are indispensable to correctly construct and interpret geochemical maps and identify anthropogenic contam-ination by As, Cu, Pb, and Zn. The list of analysed elements must include both potentially toxic and lithogenic elements, otherwise natural controls of soil composition cannot be deciphered. By using empirical cumulative distribution functions, we found that local backgrounds for As/Fe and Pb/Ti are significantly naturally ele-vated (5.7 to 9.8 times and 2.1 to 2.7 times higher, respectively) compared to the global averages. We con-structed geochemical maps with topsoil minus subsoil concentrations to show the main directions of spreading anthropogenic contamination. The anthropogenic diffuse contamination contribution was calcu-lated (1.12·10-4 and 1.42·10-4 for As/Fe and 16.5·10-4 and 16.2·10-4 for Pb/Ti, respectively), which corresponds to topsoil enrichment by ca. 15 and 14 mg kg-1 for As and ca. 35 and 42 mg kg-1 for Pb in the two study areas. Our study thus provided the first published quantitative estimates of geogenic and anthropogenic contribution to this well-known montane area. The obtained estimates were comparable to the results obtained previously from the local peat archives. The approach we used is efficient in deciphering natural and anthropogenic controls of PTEs in geochemically complicated areas.

Human sepsis is one of the leading cause of death worldwide and is known to be a harmful damaging host inflammatory condition, primarily caused by endotoxin released by gram-negative bacteria. Despite antibiotics administration being widely used to treat disease, effective targeted therapeutic strategies for the sepsis are still lacking. Here, we demonstrate that CM1, a derivative of natural polyphenol chrysin, exerts anti-inflammatory activity by inducing the ubiquitin-editing protein TNFAIP3 and NAD-dependent deacetylase sirtuin 1 (SIRT1). We found that CM1 attenuated Toll-like receptor 4 (TLR4)-induced the generation of inflammatory cytokines by inhibiting the extracellular-signal-regulated kinase (ERK)/MAPK and nuclear factor kappa B (NF-κB) signaling pathway. In addition, the treatment of macrophages with CM1 induced the expression of TNFAIP3 and SIRT1 in TLR4-stimulated primary macrophages, however the anti-inflammatory properties of CM1 was disappeared by siRNA silencing of TNFAPI3 or by the genetic and pharmacologic inhibition of SIRT1. Importantly, intravenously administration of CM1 resulted in the decreased susceptibility to endotoxin-induced sepsis, leading to inhibition of the generation of proinflammatory cytokines and neutrophils infiltration into lung than control mice. Collectively, these findings suggest that CM1 has the potential to be a treatment candidate for diverse inflammatory diseases including sepsis.

Oncostatin M (OSM), an inflammatory cytokine belonging to interleukin-6 superfamily, is recognized as an essential factor secreted by osteal macrophages to orchestrate bone remodelling. Osteoprotegerin (OPG) produced by osteoblasts regulates osteoclastogenesis. We previously demonstrated that bone morphogenetic protein-4 (BMP-4) stimulates OPG synthesis in osteoblast-like MC3T3-E1 cells, and that SMAD1/5/8(9), p38 mitogen-activated protein kinase (MAPK), and p70 S6 kinase positively regulates the OPG synthesis. The present study is aimed to investigate the effect of OSM on BMP-4-stimulated OPG synthesis in osteoblasts. OSM suppressed the release and the mRNA expression of OPG upregulated by BMP-4 in MC3T3-E1 cells.  Neither the BMP-4-induced phosphorylation of SMAD1/5/9 nor that of p38 MAPK affected by OSM. On the other hand, the BMP-4-stimulated phosphorylation of p70 S6 kinase was considerably suppressed by OSM. These results strongly suggest that OSM suppresses the BMP-4-stimulated OPG synthesis via inhibition of the p70 S6 kinase-mediated pathway in osteoblasts.

Endothelial function is regulated by a myriad of complex pathways. In our previous study, the expression of miR-378a-3p was shown to inhibit endothelial autophagy and impair endothelial function. However, the mechanism underlying the effect of miR-378a-3p in endothelial cells remains to be elucidated. By employing an in silico approach, Protein Disulfide Isomerase 4 (PDIA-4) was identified as a target of miR-378-3p; however, its’ role in endothelial cells is not known. We here report that endothelial cell-specific loss of PDIA-4 leads to impaired autophagic flux accompanied by loss of endothelial function and apoptosis. Endothelial cell-specific loss of PDIA-4 also induced marked changes in endothelial cells’ architecture, accompanied with the loss of endothelial markers and gain of mesenchymal markers consistent with endothelial-to-mesenchymal transition (EndMT). Loss of PDIA-4 activates TGF-signaling, and inhibition of TGF-signaling inhibits EndMT in PDIA-4 silenced endothelial cells in vitro. Our findings help elucidate the role of PDIA-4 in endothelial autophagy and endothelial function and provide a potential target to modulate and/or limit autophagy and EndMT in (patho-)physiological conditions.

This is a brief critique of the functions—particularly olfactory functions—specified for the “Chemosensory Protein” (CSPs) molecule family. On the basis of these proteins’ presence in the sensory antennal lymph of locusts, odor chemosensory ligand binding functions have been hypothesized. According to this hypothesis, the entire protein molecule superfamily is referred to as “CSPs”. However, new information and developments in the field of CSP molecular research, such as the expression of CSP genes in the gut, brain, fat body, epidermis, and pheromone gland, as well as gene expression profiling from most early developmental stages—that is, CSP expression well in advance of the appearance of chemical sense nerve cells—strongly suggest that the protein molecule has other roles that are unrelated to chemosensing. Moreover, CSPs are found in bacterial microbial prokaryote organisms in addition to insects. Thus, we examine the molecule’s name, definition, RNA editing, protein structure, lipid binding properties, DNA interaction, and evolutionary characteristics in brief before referring to this protein family as “Chemosensory Proteins”. This article tries to compel and discuss the most recent information as a way to rename this protein family. Because of its highly conserved molecular distinctive feature (four adjacent cysteines), we propose renaming “CSPs” as “4CSPs” (4 Cysteines Soluble Proteins).

The integration of AI in educational settings, particularly through Large Language Models (LLMs), is accelerating, reshaping pedagogical approaches due to students' interactions with new learning tools. This study assesses the impact of generative AI on the educational experiences of computer and data science students at the Center for Informatics, University of Paraíba (CI/UFPB), Brazil. Through Exploratory Factorial Analysis (EFA) of five psychometric scales, the research examines students' acceptance of LLMs, their associated burnout levels, technology anxiety, and the prevalence of metacognitive and dysfunctional learning strategies associated with LLMs. Results indicate significant adoption of AI technologies among students, accompanied by a low incidence of technology anxiety, manifesting as fears of losing jobs to AI. However, a significant correlation was observed between academic burnout and dysfunctional learning strategies, which could likely be attributed to the rigorous academic environment. Additionally, the employment of metacognitive strategies in conjunction with LLMs reflects an advanced learning approach, yet challenges with functional learning strategies persist. This study contributes to the discourse on AI in education, highlighting the need for educational frameworks that support effective AI adoption while addressing the psychological demands on students.

Results showed that mulberry leaves could significantly reduce backfat thickness (P&lt;0.05) and increase intramuscular fat (IMF) content (P&lt;0.05). Lipidomics analysis showed that mulberry leaves improved lipid profile composition and increased the proportion of triglycerides (TG). Interestingly, IMF content was positively correlated with acyl C18:2 and negatively correlated with C18:1 of differential TGs. In addition, cecal microbiological analysis showed that mulberry leaves could increase the abundance of bacteria such as UCG−005, Muribaculaceae_norank, Prevotellaceae_NK3B31_group, Limosilactobacillus, and so on. At the same time improve the L-tyrosine-baton rouge ester, Oleic acid methyl ester, 21-deoxycortisol, N-acetyldihydrosphingosine, Mulberrin relative abundance. In this study, we found that mulberry leaves could extremely significantly increasing the mRNA relative expression of lipoprotein lipase (LPL), fatty acid-binding protein 4 (FABP4) and peroxisome proliferators-activated receptor γ (PPARγ) in muscle (P＜0.01), significantly increasing mRNA relative expression of diacylglycerol acyltransferase 1 (DGAT1) (P＜0.05) and significantly decreasing the mRNA relative expression of acetyl CoA carboxylase (ACC) (P＜0.05), and aignificantly upregulated hormone-sensitive triglyceride lipase (HSL), peroxisome proliferators-activated receptor α (PPARα) mRNA relative expression (P＜0.05) in backfat. In addition mulberry leaves could increased serum leptin and adiponectin (P＜0.01). Ultimately lead to up-regulation of IMF and down-regulation of backfat.

We analyzed mineralogical characteristics, and major as well as rare earth element concentrations from a cryptotephra layer in sediments of the infilled maar of Auel (Eifel, Germany). The results of detailed geochemical analyses of clinopyroxenes and their glassy rim of the specific layer are most similar to those from the Campanian Ignimbrite (CI) Tephra occurrence in a loess section at Urluia (Romania). Both records show idiomorphic green clinopyroxenes and formation of twisted minerals up to millimeter scale. The cryptotephra in the Auel core has an age of around 39,940 yr b2k in the ELSA-20 chronology, almost identical to the latest Ar/Ar dates for the Campanian Ignimbrite/Y5 eruption. These observations suggest that parts of the CI ash cloud were transported also northwestward into Central Europe, whereas the main branch of the CI ash plume was transported from southern Italy towards the NE, E and SE.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but severe adverse event that was first observed during the global vaccination campaign against SARS-CoV-2 infection, specifically in those receiving adenoviral vector-based vaccines for Coronavirus disease 2019 (COVID-19). VITT develops 4 to 42 days post-vaccination and is characterized by the development of platelet-activating anti-platelet factor 4 (PF4) antibodies, leading to thrombocytopenia and thrombosis at unusual sites. The rise in awareness and subsequent prompt recognition of VITT was paramount in reducing mortality. Moreover, as vaccination campaigns around the world continue, a better understanding of VITT not only has important clinical implications but is also crucial for future vaccine development. In this review, we summarize the clinical features, pathophysiology, and incidence rates of VITT as well as highlight other anti-PF4 antibody-mediated disorders of growing clinical significance.

This paper outlines the evolution of a learning technology interface from a Beta version to launch with educators and its alignment to pedagogical theory, designed to maximise collaboration between teacher and student. It explores how the “co-creation” of curricula via textual sources that underpin teaching and learning can be enhanced through interactive e-books and outlines the challenges involved in this praxis. With a number of stakeholders involved in the live use of the platform (including teachers, students, HE educators, course instructors, curriculum designers and software developers), iterative feedback loops informed real-time design improvements to both the interface and the-ory. This collaboration utilised a design-based research (DBR) approach (Wang and Hannafin, 2005), which is outlined here as explanation of how the tool developed and how iterative feedback helped to reconsider the challenges educators face in implementing pedagogical innovation across differing contexts. We propose how speculative design (Lukens and DiSalvo, 2012) and Activity Theory (Engeström, 1987) workshops can methodologically enhance the planning and evaluation phases inherent to DBR approaches, which involve students to prepare for educators’ innovation. Finally, we conclude with how educators can utilise these design principles using stratified approaches to help prepare organisational approaches for innovation.

Alzheimer's disease (AD) is characterized by abnormal amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-PET or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n=88) and some volunteers (n=66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.

The superficial quality of the strip is a very important issue in steel production; the profile, flat-ness, and geometry of strip are indicators of supreme quality. Considering the dimensions, the thickness is one of the most important variables in the production of strip. In the present study the elastic curve of Back Up Rolls (BUR) is analyzed, considering them as simply supported beams as well as the effect of rolls on the profile of the strip, specifically in the strip edge pro-ducing edge drop. The analysis is simulated with a model in 3D using a Finite Element Method (FEM) considering +0.039mm crown on Back Up Roll and +0.101mm crown on Work Roll (WR). The results showed that there is an instability zone of 76mm in the strip edge, this geometry is symmetrical in both ends of the strip, it was validated with the results of compact X-ray thick-ness gauge from a 4-high cold mill. This study not only provides a theoretical basis for the edge drop, but also provides the basis for the understanding of deformation on rolls used in rolling mill processes and their effect on the thickness, profile, shape, and dimensional quality of strips.

Cinnamate 4-hydroxylase (C4H) is a cytochrome P450-dependent monooxygenase enzyme that catalyzes a key step in phenylpropanoid metabolism in plants. However, there is very limited information on the function of C4H in medicinal plants. In the present study, the C4H gene from the Ferula pseudalliacea genome (named FpC4H) was cloned and characterized. In addition, the expression levels of FpC4H in the roots, stems, leaves, flowers and seeds were investigated via real-time PCR. FpC4H showed the most similarity with C4H proteins from Daucus carota. The results predicted that FpC4H, as well as its orthologs, is an unstable and hydrophilic protein. A high genetic distance was observed between FpC4H and C4H from monocots based on evolutionary analysis. Moreover, a variable region related to the variable function of C4H was detected in conserved domain region of C4H proteins. Protein structure analysis revealed that isoleucine and leucine residues are frequently present in the binding region of FpC4H, and two ion binding regions, cysteine258 and asparagine217, were identified in the 3D structure of FpC4H. Expression analysis revealed that the FpC4H gene is expressed in all organs of F. pseudallicea. A low expression level of FpC4H was recorded in leaves, and a high expression level was observed in flower tissues. Based on the expression profile, FpC4H seems to be linked to a high content of phenolic compounds in flowers.

Online artificial intelligence (AI) tools have recently gained in popularity. So-called “generative AI” chatbots unlock new opportunities to access vast realms of knowledge when being prompted by users. Here, we test the capabilities of two such AIs in order to determine the benefits for plastic surgery while also assessing potential risks. Future developments are outlined. We used the online portals of OpenAI’s ChatGPT(version 3.5) and Google’s Bard to ask a set of questions and give specific commands. Results provided by the two tools were compared and analyzed by a committee. For professional plastic surgeons, we found that ChatGPT and Bard can be of help when it comes to conducting scientific reviews and helping with scientific writing but are of limited use due to the superficiality of their answers in specific domains. For medical students, in addition to the above, they provide useful educational material with respect to surgical methods and exam preparation. For patients, they can help when it comes to preparing for an intervention, weighing in risks and benefits, while providing guidance on optimal post-operative care. ChatGPT and Bard open widely accessible data to every internet user. While they might create a sense of “magic” due to their chatbot interfaces, they nonetheless can help to increase productivity. For professional surgeons, they produce superficial answers - for now - albeit providing help with scientific writing and literature reviews. For medical students, they are great tools to deepen their knowledge about specific topics such as surgical methods and exam preparation. For patients, they can help in translating complicated medical jargon into understandable lingo and provide support for pre-operative as well as post-operative care. Such AI tools should be used cautiously as answers are not always precise nor accurate and should always be used in combination with expert medical guidance.

A Staudinger reaction on solid phase between an electronodeficit organic azide such as sulfonyl azide, and the phosphite triester formed upon phosphoramidite coupling is a convenient method for chemical modification of oligonucleotides at the internucleotidic phosphate position. In this work, 4-carboxybenzenesulfonyl azide either with a free carboxy group or in the form of an activated ester such as pentafluorophenyl, 4-nitrophenyl, or pentafluorobenzyl ester were used to introduce a carboxylic acid function to the terminal or internal internucleotidic phosphate of an oligonucleotide via Staudinger reaction. A subsequent treatment with excess primary alkyl amine followed by usual work-up, after prior activation with a suitable peptide coupling agent such as HBTU/HOBt in the case of a free carboxyl, afforded amide-linked oligonucleotide conjugates in good yields including multiple conjugations of up to the exhaustive modification at each phosphate position for a weakly activated pentafluorobenzyl ester, whereas more strongly activated and, thus, more reactive aryl esters provided only single conjugations at the 5′-end. The conjugates synthesized include those with di- and polyamines that introduce a positively charged side-chain to potentially assist intracellular delivery of the oligonucleotide.

A single Cancer immunotherapy has ushered in a transformative era in oncology, bringing forth unprecedented promise and opportunities. However, even with its significant breakthroughs, the domain faces the continual issue of treatment resistance. Such resistance not only restricts the broad effectiveness of these pioneering treatments but also highlights the imperative need for further research. Delving into the complex world of cancer immunotherapy resistance, we identify a range of mechanisms, from primary and secondary resistance to the notable effects of genetic and epigenetic variables, and the pivotal importance of the tumor microenvironment (TME). Additionally, we emphasize the need for innovative strategies to mitigate this resistance, including combination treatments, customized immune checkpoints, and instantaneous monitoring. By advocating for these cutting-edge methods, we foresee a direction that incorporates personalized healthcare, enhanced treatment options, and a steadfast dedication to the welfare of patients. Through a comprehensive and diverse approach, we aim to address the hurdles posed by resistance, elevating cancer immunotherapy as a symbol of hope for patients worldwide.

Artificial intelligence (AI) tools, such as OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have great potential in various fields, such as healthcare, education, and industry. This review highlights the applications and challenges of the ChatGPT versions 3.5 and 4.0 in radiology. ChatGPT can process medical texts, analyze medical images, and generate reports and summaries for different audiences. ChatGPT can also answer patients' questions and translate complex medical information into a plain language. ChatGPT has shown impressive results in medical tests and quizzes, indicating its potential to enhance diagnostic accuracy and medical education. These models show promise for reducing diagnosis times and healthcare costs. However, ChatGPT also faces challenges and limitations, such as a lack of visual content, ethical and legal issues, data quality, and error detection. This review highlights the benefits and future directions of ChatGPT and artificial intelligence (AI) in radiology.

Neuromyelitis Optica Spectrum Disorder (NMOSD) is a rare immune-mediated relapsing-remitting disease of the central nervous system. The usage of rituximab, to prevent NMOSD relapses, is common in Sweden, but the knowledge on long-term efficacy and risk for severe infections are limited. We performed a retrospective cohort study with medical chart review of rituximab-treated NMOSD patients at the Karolinska University Hospital, Sweden, to assess the occurrence of relapses and severe infectious events (SIE). Furthermore, we collected data on CD19+ lymphocyte, and IgG levels during therapy. A total of 42 NMOSD patients; 24 with aquaporin -4 antibodies (AQP4+), eight with myelin oligodendrocyte glycoprotein antibodies (MOG+) and 10 with absence of antibodies (double-seronegative) were included. During a mean treatment time of 4.4 years, 37% AQP4+, 75% MOG+, and 60% double-seronegative patients experienced 1 relapse. SIEs were common with 46% of AQP4+, 25% of MOG+, and 40% of double-seronegative patients affected. Incomplete CD19+ lymphocyte suppression did not predict a relapse and there was no correlation between IgG levels and SIEs. In conclusion, our data demonstrated a high risk for both relapses and SIEs in rituximab-treated NMOSD patients highlighting the need for close clinical vigilance of disease activity and infections during treatment.

Banana is one of the most important fruits in the world due to its status as a major food source for more than 400 million people. Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) causes substantial losses of banana crops every year, and molecular host resistance mechanisms are currently unknown. We here performed a genome-wide analysis of the autophagy related protein 8 (ATG8) family in a wild banana species. The banana genome was found to contain 10 MaATG8 genes. Four MaATG8s formed a gene cluster in the distal part of chromosome 4. Phylogenetic analysis of ATG8 families in banana, Arabidopsis thaliana, Citrus, rice, and ginger revealed five major phylogenetic clades shared by all of these plant species, demonstrating evolutionary conservation of the MaATG8 families. The transcriptomic analysis of plants infected with Foc TR4 showed that almost all of the MaATG8 genes were more highly induced in resistant cultivars than in susceptible cultivars. Finally, MaATG8F was found to interact with MaATG4B in vitro (with yeast two-hybrid assays), and MaATG8F and MaATG4B all positively regulated banana resistance to Foc TR4. Our study provides novel insights into the structure, distribution, evolution, and expression of the MaATG8 family in bananas. Furthermore, the discovery of interactions between MaATG8F and MaATG4 could facilitate future researches of disease resistance genes for genetic improvement of bananas.

We successfully fabricated Ag@Cu2O core-shell decorated on reduced graphene oxide (rGO) nanocomposites (ACRN) by a simple and convenient in situ substitution method. The properties of these ACRN with heterostructure layers were characterized by scanning and transmission electron microscopies and absorption spectroscopy. We used p-nitrophenol (4-NP) as a probe molecule to determine the chemical catalytic activity of the ACRN. Upon introduction of rGO, a high electron transfer efficiency was achieved; thus, the catalytic activity was improved significantly. Therefore, the ACRN exhibited significantly improved catalytic activity for the reduction of 4-NP and showed the high application value in the removal of toxic and harmful substances from water. In addition, the fabricated ACRN was used for the reduction of organic dyes and explosive pollutants to generate nontoxic products. Furthermore, the high charge redistribution and transfer among Ag, Cu2O and rGO in the ACRN induced the high catalytic reduction of organic pollutants, indicating the excellent potential of these materials for applications in water pollution treatment.

Background: This study retrospective evaluates patients with stage IV melanoma treated with Nivolumab and Ipilimumab combination therapy from two regional oncology centers from Romania between the years of 2019 up to the end of 2022. Methods: The data were analyzed in SAS for Windows, V9.4. The survival curves were estimated using the Kaplan-Meier method, and survival distributions were compared with log-rank test. The effects of the main clinical and pathological variables on OS and PFS were investigated with Cox regression. Results: Kaplan-Meier curve of OS in all evaluable patients enrolled in the study resulted in a median OS of 346 days (95% CI: 150-NA) and a median PFS of 211 days (95% CI: 113-430). 45.3% of the patients experienced adverse events during the Nivolumab + Ipilimumab treatment with some of them having multiple organ systems involved. Discussion: The OS values were lower than that reported in approval clinical trials, but the results show a marked improvement when comparing to results obtained by chemotherapy regimens previously used in these scenarios. Conclusion: This study provides real-world insights into the survival data and safety profiles of combination therapy with anti-PD-1 antibodies and anti-CTLA-4 antibodies.

The Chat Generative Pre-training Transformer (GPT), also known as ChatGPT, is a powerful generative AI model that can simulate human-like dialogues across a variety of domains. However, this popularity has attracted the attention of malicious actors who exploit ChatGPT to launch cyberattacks. This paper examines the tactics that adversaries use to leverage ChatGPT in a variety of cyberattacks. Attackers pose as regular users and manipulate ChatGPT’s vulnerability to malicious interactions, particularly in the context of cyber assault. The paper presents illustrative examples of cyberattacks that are possible with ChatGPT and discusses the realm of ChatGPT-fueled cybersecurity threats. The paper also investigates the extent of user awareness of the relationship between ChatGPT and cyberattacks. A survey of 253 participants was conducted, and their responses were measured on a three-point Likert scale. The results provide a comprehensive understanding of how ChatGPT can be used to improve business processes and identify areas for improvement. Over 80% of the participants agreed that cyber criminals use ChatGPT for malicious purposes. This finding underscores the importance of improving the security of this novel model. Organizations must take steps to protect their computational infrastructure. This analysis also highlights opportunities for streamlining processes, improving service quality, and increasing efficiency. Finally, the paper provides recommendations for using ChatGPT in a secure manner, outlining ways to mitigate potential cyberattacks and strengthen defenses against adversaries.

Boeremia exigua var. exigua is a recurrent pathogen causing root rot in industrial chicory. Currently, there is no chemical or varietal control for this disease, and thus management strategies need to be developed. This study determined the biocontrol effect of strains of Pseudomonas protegens bacteria with antimicrobial compounds on the fungus B. exigua var. exigua under in vitro, in vivo and field conditions. In addition, root colonization by these bacteria was estimated by molecular analysis. Eighteen isolates of Pseudomonas spp were evaluated and the strains that showed the greatest in vitro inhibition of fungal mycelial growth (mm), Ca10A and ChB7, were selected. Inoculation with the strain ChB7 showed less severity (necrotic area) under in vivo conditions (root trials) compared to the control inoculated with the pathogen (P≤0.05). The molecular analysis revealed that root colonization of plants grown in pots was equal or greater than 70%. Similar levels were observed in the field trials conducted in Selva Negra and Canteras experimental stations (2015-16 season), with values ranging from 85.7 to 70.5% and from 75.0 to 79.5%, respectively. Regarding yield (ton ha-1), values were higher in the treatments inoculated with strains Ca10A and ChB7 (P≤0.05) in both experimental sites, while a lower incidence and severity of root rot were observed in Selva Negra. These results suggest that the Chilean strains of P. protegens are a promising tool for the control of root diseases in industrial chicory.

Effective therapeutics for Alzheimer's disease (AD) are in great demand worldwide. In our previous work, we responded to this need by synthesizing novel drug candidates consisting of 4-amino-2,3-polymethylenequinolines conjugated with butylated hydroxytoluene via fixed-length alkylimine or alkylamine linkers (spacers) and studying their bioactivities pertaining to AD treatment. Here, we report significant extensions of these studies, including the use of variable-length spacers and more detailed biological characterizations. Conjugates were potent inhibitors of acetylcholinesterase (AChE, minimum IC50 15.1±0.2 nM) and butyrylcholinesterase (BChE, minimum IC50 5.96±0.58 nM), with weak inhibition of off-target carboxylesterase. Conjugates with alkylamine spacers were more effective cholinesterase inhibitors than alkylimine analogs. Optimal inhibition for AChE was exhibited by cyclohexaquinoline and for BChE by cycloheptaquinoline. Increasing spacer length elevated potency against both cholinesterases. Structure-activity relationships agreed with docking results. Mixed-type reversible AChE inhibition, dual docking to catalytic and peripheral anionic sites, and propidium iodide displacement suggested the potential of hybrids to block AChE-induced β-amyloid (Aβ) aggregation. Hybrids also exhibited inhibition of Aβ self-aggregation in the thioflavin test; those with a hexaquinoline ring and C8 spacer were the most active. Conjugates demonstrated high antioxidant activity in ABTS and FRAP assays as well as inhibition of luminol chemiluminescence and lipid peroxidation in mouse brain homogenates. Quantum-chemical calculations explained antioxidant results. Computed ADMET profiles indicated favorable blood-brain barrier permeability suggesting CNS activity potential. Thus, the conjugates could be considered promising multifunctional agents for potential treatment of AD.

Reactions of picolinamides with 1,3-propanesultone in methanol followed by the treatment with ketones led to a series of previously unknown chemical transformations, yielding first pyridinium salts (2a-f) with a protonated endocyclic nitrogen atom and then heterocyclic salts (3a-j) containing a 4-imidazoline ring. The structures of intermediate and final products were determined by IR and 1H, 13C NMR spectroscopy and X-ray study. The effects of the ketone and alcohol structures on the product yield were studied by quantum-chemical calculations. The stability of salts 3a-j towards hydrolysis and alcoholysis makes them excellent candidates for the search of new types of biologically active compounds.

(1) Background: The aim of this study was to analyze the relationship between the serum levels of soluble transferrin receptor (sTfR) and interleukin 4 (IL-4), and disease activity and organ mani-festations in SLE patients. (2) Methods: We studied 200 SLE patients and 50 controls. We analyzed disease activity, organ involvement, serum sTfR, IL-4, and interleukin-6 (IL-6) levels, and antinu-clear and antiphospholipid antibody profiles. (3) Results: The median serum levels of sTfR (p>0.000001) and IL-4 (p<0.00001) were higher in the study group than in the controls. SLE patients, compared to the controls, had significantly lower HGB levels (p<0.0001), a lower iron concentration (p=0.008), a lower value of total iron-binding capacity (TIBC) (p=0.03), and lower counts of RBC (p=0.004), HCT (p=0.0004), PLT (p=0.04), neutrophil (p=0.04), and lymphocyte (p<0.0001). Serum sTfR levels were negatively correlated with lymphocyte (p=0.0005), HGB (p=0.0001) and HCT (p=0.008), and positively correlated with IL-4 (p=0.01). Elevated serum sTfR >2.14 mg/dL was associated with an increased risk of myocardial infarction (OR: 10.6 95 CI 2.71–464.78; p=0.001), ischemic heart disease (OR: 3.25 95 CI 1.02–10.40; p=0.04), lung manifestations (OR: 4.48 95 CI 1.44–13.94; p=0.01), and hematological manifestations (OR: 2.07 95 CI 1.13–3.79; p=0.01), and with a reduced risk of neuropsychiatric manifestations (OR: 0.42 95 CI 0.22–0.80; p=0.008). Serum IL-4 was negatively correlated with CRP (p=0.003), and elevated serum IL-4 levels > 0.17 mg/l were associated with a reduced risk of mucocutaneous manifestations (OR: 0.48 95 CI 0.26–0.90; p=0.02). (4) Conclusions: In SLE patients, elevated serum levels of sTfR were associated with an increased risk of cardiovascular, pulmonary, and hematological manifestations, and with a decreased risk of neuropsychiatric manifestations. In contrast, elevated serum IL-4 levels were associated with a decreased risk of mucocutaneous manifestations.

CD44 is a type I transmembrane glycoprotein, and possesses various isoforms which are largely classified into CD44 standard and CD44 variant (CD44v) isoforms. Some variant-encoded regions play critical roles in tumor progression. However, the function of CD44 variant 4 (CD44v4)-encoded region has not been fully understood. Using peptide immunization, we developed an anti-CD44v4 mAb, C₄₄Mab-108, which is useful for flow cytometry, western blotting, and immunohistochemistry. In this study, we determined the critical epitope of C₄₄Mab-108 by enzyme-linked immunosorbent assay (ELISA). We used the alanine (or glycine)-substituted peptides of the CD44v4-encoded region (amino acids 271-290 of human CD44v3-10), and found that C₄₄Mab-108 did not recognize the alanine-substituted peptides of D280A and W281A. Furthermore, these peptides could not inhibit the recognition of C₄₄Mab-108 in flow cytometry and immunohistochemistry. The results indicate that the critical binding epitope of C₄₄Mab-108 includes Asp280 and Trp281 of CD44v3-10.

Superficial discolored spots on Atlantic salmon (Salmo salar) fillets are a serious quality problem for commercial seafood farming. Previous reports proposed that the black spots (called melanized focal changes (MFC)) may be melanin, but no convincing evidence has been reported. In this study, we performed chemical characterization of MFC, and also of red pigment (called red focal changes (RFC)), of salmon fillets using alkaline hydrogen peroxide oxidation and hydroiodic acid hydrolysis. This revealed that the MFC contain 3,4-dihydroxyphenylalanine (DOPA)-derived eumelanin whereas the RFC only contain trace amounts of eumelanin. Therefore, probably, the black color of MFC can be explained by the presence of eumelanin from accumulated melanomacrophages. For the red pigment, we could not find a significant signature of either eumelanin or pheomelanin, and the red color is probably predominantly hemorrhagic in nature. However, we found that in RFC the level of pigmentation did increase together with some melanogenic metabolites. Comparison with a “mimicking experiment,” in which a mixture of a salmon homogenate + DOPA was oxidized with tyrosinase, suggested that the RFC include conjugations of DOPAquinone and/or DOPAchrome with salmon muscle tissue proteins. In short, the results suggest that melanogenic metabolites in MFC and RFC derive from different chemical pathways, which would agree with the two different colorations deriving from distinct cellular origins, namely melanomacrophages and red blood cells, respectively.

This mixed-methods research article explores the influence of ChatGPT, a state-of-the-art AI language model, on the development of maladaptive learning habits in users. The study combines quantitative and qualitative data to provide a comprehensive understanding of how engaging with ChatGPT may inadvertently foster detrimental learning behaviors. Findings suggest that while ChatGPT can be a valuable learning tool, it has the potential to exacerbate or create bad learning habits if not used mindfully.

The migration from MATLAB to Python (M-to-PY) has gained significant traction in recent computational research. While MATLAB has long served as a linchpin in myriad scientific endeavors, there's an emerging trend to rejuvenate these projects using Python's extensive AI tools and libraries. This study presents a semi-automated process for M-to-PY conversion, using a detailed case study of an image skeletonization project comprising fifteen MATLAB files and a 1404-image dataset. Skeletonization is foundational for ongoing 3D motion detection research using AI transformers, predominantly developed in Python. The utilization of ChatGPT-4, acting as an AI co-programmer, is pivotal in this conversion. By leveraging the public OpenAI API, we developed an M-to-PY converter prototype, evaluated its efficacy using test cases from the Bard bot, and subsequently employed the converted code in an AI application. The dual contributions encompass a well-tested M-to-PY converter and a Skeleton App capable of sketching and skeletonizing any given image, enriching the AI toolset. This study accentuates how AI resources, like ChatGPT-4, can simplify code transitions, opening doors for innovative AI implementations using primarily MATLAB-coded scientific research.

This study investigates the therapeutic potential of new compound, potassium 2-[2-(2-oxo-4-phenylpyrrolidin-1-yl) acetamido]ethanesulfonate (Compound I), in depression. Willner's chronic unpredictable mild stress model of depression in 48 male Wistar rats was used a depression model. The rats were randomized into four groups, including an intact group, a Compound I group, a Fluoxetine group, and a control group receiving saline. Behavioral tests, such as the Porsolt forced swim test, hole-board test, elevated plus maze test, and light-dark box, were used to assess the animals' conditions. Our results demonstrated that Compound I effectively reduced the immobilization time of rats in the forced swim test, increased orientation and exploratory behavior, and decreased the latency period of going into the dark compartment compared to the control group. Hippocampal and striatal serotonin concentrations were increased in the Compound I group, and the compound also reduced the level of corticosterone in the blood plasma of rats compared to intact animals. These results suggest that Compound I has a reliable antidepressant activity, comparable to that of the reference antidepressant Fluoxetine.

The advent of artificial intelligence has ushered in a new era of digital tools, including chatbots and virtual assistants, for educational purposes. ChatGPT, an advanced language model, has gained popularity as an educational aid. However, concerns have emerged regarding its potential negative impact on student learning behavior. This experimental research study investigates the influence of ChatGPT on student learning behavior and offers insights into its potential drawbacks.

The craft guilds have been at the core of important historiographical debates on the economic, social and political history of medieval cities for twenty years. The aim of this article is to examine the seamen’s guilds in the town ports of Northern Peninsula in the late Middle Ages. This study analyzes fundamental aspects of the social assistance, labour organization and social identity of the town ports, located on the maritime border of the Kingdom of Castile. In contrast to the more classical view of the craft guilds as protectionist institutions, which only served the interests of a privileged group of masters, this analysis highlights the contribution of the seamen craft guilds to the organization of labor at sea, the training of sea workers, the ability to negotiate with merchants and avoid labor exploitation, the provision of social assistance to the most vulnerable population, and the ability to lead the social protest for the guilders’ representation in the urban government. In summary, it is concluded that the seafarers’ guilds were constituted as networks of mutual help between individuals in the labor, welfare and political spheres of the population of the town ports of Northern Iberia in the late Middle Ages.

Large language models have proliferated across multiple domains in as short period of time. There is however hesitation in the medical and healthcare domain towards their adoption because of issues like factuality, coherence, and hallucinations. Give the high stakes nature of healthcare, many researchers have even cautioned against its usage until these issues are resolved. The key to the implementation and deployment of LLMs in healthcare is to make these models trustworthy, transparent (as much possible) and explainable. In this paper we describe the key elements in creating reliable, trustworthy, and unbiased models as a necessary condition for their adoption in healthcare. Specifically we focus on the quantification, validation, and mitigation of hallucinations in the context in healthcare. Lastly, we discuss how the future of LLMs in healthcare may look like.

The need of research is often a complex issue. The standardization of methodologies, deeply rooted in the scientific method, has allowed humanity to progress. Since the fashion industry represents one of the most problematic industries globally, it is paramount to investigate the handicaps of fashion research practice. The goal of this systematic review is to outline the most used methodologies in the fashion research field that are being explored to achieve sustainability goals. The findings highlight the fragmentation of the literature in fashion research methodologies in relation to sustainability. Interviews and case studies are the most used methods while other less conventional, like Social Life Cycle Assessment, have been also tried. Finally, it is tested how ChatGPT can discuss and inform future routes to incorporate the findings. Together, this work reveals the handicaps of the fashion research methodologies and show an example on how ChatGPT can be assessed to help the fashion practitioners define research plans to achieve sustainable goals.

Introduction: This empirical study investigates the impact of two distinct mathematical problem-solving methods – the Algebraic Formula Method and the Newton Sum Method – on enhancing ChatGPT's competence in effectively solving quadratic root functions. The integration of Artificial Intelligence (AI) into mathematical problem-solving has paved the way for innovative approaches. In this study, we delve into the Algebraic Formula Method and the Newton Sum Method, essential techniques for solving quadratic root functions. We aim to showcase the profound influence of these methods on ChatGPT's capacity to excel in solving quadratic equations. Evidence Through concrete evidence, we demonstrate ChatGPT's adept utilization of the Newton Sum Method for quadratic root function calculations. While ChatGPT can compute quadratic root functions of the form α^15 + β^15 using this method, its proficiency in using algebraic formula methods typically extends only up to α^4 + β^4. This marked discrepancy underscores the pivotal role that different methods play in amplifying the AI system's mathematical capabilities Result The results of this study provide concrete evidence of ChatGPT's superior utilization of the Newton Sum Method for calculating quadratic root functions. The model adeptly computes expressions of the form α^15 + β^15 using this method, while its proficiency using algebraic formula methods is generally limited to α^4 + β^4. This striking discrepancy underscores the transformative impact that different methods can have on elevating the AI system's mathematical prowess. Conclusion :Pushing Boundaries: Pioneering Novel Maths Approaches for Overcoming Limitations in AIThis study serves as an illuminating testament to the significance of pioneering innovative methodologies, rules, theorems, or formulas to surmount the current limitations in AI systems like ChatGPT. These innovative pursuits hold the key to unlocking the untapped potential that lies within, propelling AI systems to greater heights of proficiency. In essence, they offer a strategic pathway towards expanding the capabilities of AI and pushing the boundaries of what can be achieved. Discussion The outcomes derived from this study underscore the significant influence wielded by the method selection in augmenting the mathematical competencies of ChatGPT. Particularly noteworthy is the application of the Newton Sum Method, which surfaces as a compelling exemplar. This method serves as a pivotal conduit through which the model surpasses its prior constraints, allowing it to venture into the realm of calculations entailing higher exponents. Implications and Future Research: These findings not only contribute to AI's mathematical competencies but also emphasize the need for pioneering new methods, rules, theorems, or formulas to further enhance AI systems like ChatGPT. Future research could explore the development of novel mathematical techniques tailored to AI systems, thus expanding their capabilities across diverse problem-solving domains.

Current neural network models can demonstrate reasonable-looking behavior, considered by some developers and researchers human-like. For example, a large language model GPT-3 is susceptible to human-like cognitive biases. Yet there is no data of such models solving emotional intelligence (EI) tasks. They are connected to the abilities that has been previously considered as specifically human EI is an important aspect of human communication. The ability to understand and respond to emotional cues is essential for effective communication. Therefore, it is crucial to determine the ways AI models such as ChatGPT demonstrate EI. The present research aims to measure the EI of GPT-4, a large language model trained by OpenAI. Russian version of the Mayer–Salovey–Caruzo Emotional Intelligence Test sections B, C, D, F, G and H were used in this research. High points were obtained in Understanding emotions scale and Strategic EI. Mean points are obtained in Managing emotions scale. Low and less reliable values are obtained in Using emotions to facilitate thought scale. Thus, GPT-4 seems already capable of identifying emotions in text and describing techniques for managing them. However, complex cases and irregular situations requiring emotions qualitative analysis would be a hard task for GPT-4.

Immune checkpoint inhibitors (ICIs), including anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and anti-programmed death-1 (PD-1) antibodies, have initiated a new era in the treatment of malignant melanoma. ICIs can be used in various settings, including as first-line, adjuvant, and neoadjuvant therapy. In the scope of this review, we examined clinical studies utilizing ICIs in the context of treating oral mucosal melanoma, a rare disease albeit with an extremely poor prognosis, with a specific focus on unraveling the intricate web of resistance mechanisms. The absence of a comprehensive review focusing on ICIs in oral mucosal melanoma is notable. Therefore, this review seeks to address this deficiency by offering a novel and thorough analysis of the current status, potential resistance mechanisms, and future prospects of applying ICIs specifically to oral malignant melanoma. Clarifying and thoroughly understanding these mechanisms will facilitate the advancement of effective therapeutic approaches and enhance the prospects for patients suffering from oral mucosal melanoma.

Load shifting is one of the demand side management (DSM) strategies to support the efficiency in the electricity grid during the peak hours demand. Load shifting at the appliance level is interesting to review since the appliance usage is one of the main inputs in the load profile analysis. More review studies in load shifting at the appliance level are required as it is a specific issue of load profile research body, and still limited studies are available at this moment. It is also essential to focus on the appliance usage patterns to better understand the impacts and characteristics of the individual appliance. The existing studies in load shifting have applied common structured literature reviews, and our study addresses the transparency of each stage and sub-stage of the selection of the final list studies. The finding shows that efficiency has been achieved in the installed capacity reduction, cost including emission reductions, and peak consumption reduction. The most applied method in the load shifting at the appliance level is by developing the load shifting optimisation algorithms. This work contributes to provide a transparent process of applying a systematicity literature review, where it becomes a source of knowledge and grounded theory. It contributes to a limited and specific research of load shifting at the appliance level by highlighting and discussing the key findings for the readers. In specific, it contributes to improve energy efficiency by presenting the load shifting methods at the appliance level and identifying the controllable and uncontrollable appliances. This detail review study at the appliance level can make valuable contributions to support decision and policy-making by illuminating new dynamic system in load shifting area in specific, and demand side management in general for energy efficiency.

In this study, a composite film was developed for electrochemical sensing of tryptophan (Trp). Porous reduced graphene oxide (PrGO) was utilized as the electron transfer layer, and a C-undecylcalix[4] resorcinarene Langmuir-Blodgett (CUCR-LB) film served as the molecular recognition layer. Atomic force microscopy (AFM), transmission electron microscopy (TEM), Raman spectroscopy, scanning electron microscopy (SEM), and electrochemical experiments were employed to analyze the characteristics of the CUCR-LB/PrGO composite film. The electrochemical behavior of Trp on the CUCR-LB/PrGO composite film was investigated, revealing a linear response range of Trp was 1.0×10-7 to 3.0×10-5 mol L-1 and a detection limit of 3.0×10-8 mol L-1. Furthermore, the developed electroanalytical method successfully determined Trp content in an amino acid injection samples. This study not only introduces a rapid and reliable electrochemical method for determination of Trp but also presents a new strategy for constructing high-performance electrochemical sensing platforms.

Background Candida auris is an emerging multidrug-resistant fungal pathogen that represents a serious threat to healthcare settings currently. Objective: Its objective was to determine the prevalence of C. auris in the hospital since its initial detection in late 2019. Methods: Using an adapted risk assessment tool, we reviewed the charts. and medical files of all suspected? and confirmed cases of C. auris cases reported at King Khalid University Hospital, Riyadh between November 2019 and December 2022. Anonymized data were retrieved in a pre-established datasheet and analyzed to determine the epidemiological characteristics of C. auris infection in our facility. We established our initial prevalence by age, gender, risk factors, and according to sampling source. Results: Of the 53 confirmed cases positive for C. auris during the study period, 33 (62%) were males. Their ages ranged between 15 and 98; most positive cases occurred in 50 and above. Only one of the confirmed cases was hospital-acquired. All patients had at least one risk factor, and Urine samples yielded the greatest number of positive cases while admission to healthcare facilities constituted the highest risk in our study. Conclusion: Establishing a local prevalence could serve as our baseline/benchmark to compare with regional and international benchmarks.

We report on recent experimental results on β decay into self-conjugate (N=Z) nuclei with mass number 58≤A≤70. Super-allowed β decays from the Jπ=0+ ground state of a Z=N+2 parent nucleus are to the isobaric analogue state, through so-called Fermi transitions, and to Jπ=1+ states, by way of Gamow–Teller (GT) transitions. The operator of the latter decay is a generator of Wigner’s SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spin–orbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin–orbit splitting can be small in nuclei with 58≤A≤70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT β decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A=70.

The prevalent pathogens associated with bovine uterine infections are bacteria that appear to increase the host's susceptibility to secondary infections with other bacteria or viruses, among which BoHV-4 is the most frequently found. In this work, the study of the pathways of apoptosis induction was carried out on an experimental model of primary culture of endometrial cells, in order to know the implication of BoHV-4 and the presence of bacterial LPS in the pathogenesis of the bovine reproductive tract. For this, different staining techniques and molecular analysis by RT-PCR were used. The results obtained allowed us to conclude that the level of cell death observed in the proposed primary culture is directly related to the time of viral infection and the presence of LPS in BoHV-4 infection. The apoptosis indices in cells infected with BoHV-4, BoHV-4 + LPS presented a maximum that correlates with the appearance of the cytopathic effect, and the maximum viral titers in the model studied. However, morphological, biochemical and molecular changes were evident during both early and late stages of apoptosis. These findings provide information on the factors that may influence the pathogenesis of BoHV-4 and help to better understand the mechanisms involved in virus infection.

Norovirus (NoV) is recognised as a major cause of epidemic and sporadic acute gastroenteritis (AGE) in all age groups. Information on the genetic diversity of the NoVs circulating in the 1980s and 1990s, before the development and adoption of dedicated molecular assays, is limited compared to the last decades. In the period 1986-2020, uninterrupted viral surveillance was conducted in symptomatic children hospitalized for AGE in Palermo, Italy, providing a unique time capsule for exploring the epidemiological and evolutionary dynamics of enteric viruses. In this 35-year long time span NoVs of genogroup II (GII) were detected in 15.6% of AGE requiring hospitalization, whilst GI NoVs in 1.4%. Overall, the predominant NoV capsid (Cap) genotype was GII.4 (60.8%), with temporal replacement of the GII.4 Cap variants and associated polymerase (Pol) types. The chronology of emergence and circulation of the different GII.4 variants were consistent with the data available in literature. Also, for GII.3 and GII.2 NoVs the circulation of different lineages/strains, differing in either the Cap or Pol genes or in both, was observed. This long-term study revealed the ability of NoVs to modify continuously and rapidly their genomic makeup and highlights the importance of surveillance activities for vaccine design.

Cardiovascular and cerebrovascular disease incidence has risen mainly due to poor control of preventable risk factors and still constitutes a significant financial and health burden worldwide. ChatGPT is an artificial intelligence language-based model developed by OpenAI. Due to the model’s unique cognitive capabilities beyond data processing and the production of high-quality text, there has been a surge of research interest concerning its role in the scientific community and contemporary clinical practice. To fully exploit ChatGPT's potential benefits and reduce its possi-ble misuse, extreme caution must be taken to ensure its implications ethically and equitably. In this article, we explore the language model's possible applications and limitations while empha-sizing its potential value for diagnosing, managing, and prognosis cardiovascular and cerebro-vascular disease.

Looking for effective synthetic methods for 1H-pyrazolo[3,4-b]quinolines preparation, we came across a procedure where in a three component reaction catalyzed by L-proline, 4-aryl-4,9-dihydro-1H-pyrazolo[3,4-b]quinolines are formed. These compounds can be easily oxidized to a fully aromatic system, which gave hope for a synthetic method that could replace e.g. Friedländer condensation, often used for this purpose, although severely limited by the availability of suitable substrates. However, after careful repetition of the procedures described in the publication, it turned out that the compounds described therein do not form at all. The actual compounds turned out to be 4,4-(phenylmethylene)-bis-(3-methyl-1-phenylpyrazol-5-oles). 4-Aryl-4,9-dihydro-1H-pyrazolo[3,4-b]quinolines were prepared by another method and used as standards to compare the products formed in the original procedure.

Introduction: The objective of the study is to assess the failure of therapies with HFNO (High-Flow Nasal Oxygen), CPAP, Bilevel or combined therapy in patients with hypoxemic acute respiratory failure due to SARS-CoV-2 during their hospitalization. Methods: Retrospective and observational study of SARS-CoV-2 positive patients who required non-invasive respiratory support (NIRS), at the Reina Sofía General University Hospital of Murcia between March 2020 and May 2021. Results: Of 7355 patients, 197 (11,8%) were included. 95 of them failed this therapy (48,3%). We objectivated that during hospitalization in the ward the combined therapy with HFNO and CPAP had a lower failure rate overall and the highest treatment purely with Bilevel (p = 0,005). In the comparison of failure in therapy without two levels of airway pressure, HFNO, CPAP and combined therapy of HFNO with CPAP, (35,6% of patients) presented a 24,2% failure compared to those who did have two levels of pressure with Bilevel and combined therapy of HFNO with Bilevel (64,4% of patients) with 75,8% associated failure (OR: 0, 374; CI 95%: 0,203-0,688. p=0,001).Conclusions: The use of NIRS in conventional hospitalization is safe and effective in patients with respiratory failure secondary to SARS-CoV-2 infection. The therapeutic strategy with Bilevel increases the probability of failure, with the combined therapy strategy with CPAP and HFNO being the most promising option.

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent Based Models and Simulation consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Agents generate large volumes of data over time and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents’ perspectives on key events by providing natural language narratives. However, these narratives need to be factual, transparent, and reproducible. To this end, we present a structured narrative prompt for sending queries to LLMs. Chi-square tests and Fisher’s Exact tests are applied to assess statistically significant difference in sentiment scores of the narrative messages between simulation generated narratives, ChatGPT-generated narratives, and real tweets. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. This structure is expected to be extensible across LLMs. In 14 out of 44 categories, ChatGPT generated narratives which has sentiment scores that were not discernibly different, in terms of statistical significance (alpha level of 0.05), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of a LLM based on simulated agents’ information; and (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect simulated agent’s experiences with real people.

We define a spinor-Minkowski metric for SL(4,C). It is not a trivial generalization of the SL(2,C) metric and it involves the Minkowskian one. We define 4x4 version of the Pauli matrices and eight 4-component associated generalized eigenvectors that can be regarded as undotted covariant spinors. The 4-component spinors can be grouped into four categories. Each category transforms in its own way. The outer products of pairwise combinations of 4-component spinors can be associated with 4-vectors. Including the dotted covariant, undotted and dotted contravariant forms totally we have sixteen pairs of spinors. Eight of them live in the conjugate space which has no countepart in SL(2,C).

AI (Artificial Intelligence) chatbots has been widely applied. AI (Artificial Intelligence) chatbots has been widely applied. ChatGPT could enhance individual learning capabilities and clinical reasoning skills, facilitate students' understanding of complex concepts in healthcare education: (1) Background: There is currently less emphasis on its application in nursing education. The application of ChatGPT in nursing education needs to be verified; (2) Methods: A descriptive study is used to analyze the scores of ChatGPT on the registered nurse license exam(RNLE) and compare to the pass rate of candidates in Taiwan; (3) Results: The average score of four exams were around 51.6 to 63.75 by ChatGPT, and pass the RNLE in 2022 1st and 2023 2nd. However, ChatGPT may generate misleading or inaccurate explanations, or it could lead to hallucinations; (4) Conclusions: ChatGPT may have potentially to assist with nursing education. Although AI can simulate human behavior in context, it still cannot replace human creativity, critical thinking, and clinical reasoning.

This study continued the analysis of immunization with the receptor binding domain (RBD) associated with the adjuvants Dimethyldioctadecylammonium bromide (DDA) and Saponin (Sap) (RBD+DDA/Sap) or Aluminum hydroxide (AH) and outer membrane vesicles (OMVs) of Neisseria meningitidis (RBD+AH/OMV); from adult to old age and assessed maternal-fetal transference of antibodies. Outbred Swiss mice were immunized with 2 intramuscular (IM) doses with the antigenic preparations RBD+DDA/Sap, RBD+AH/OMV or RBD alone. The humoral immune response was evaluated using ELISA, avidity-ELISA, Immunoblotting and a Omicron-surrogate-neutralization assay (BA.1), while the cellular immune response was analyzed by ELISpot. Our previous work studied the IgG response; here, we verified that IgM levels were higher right after the immunization doses, but, as IgG, it persisted until 368 days after the immunization. The avidity of IgM increased from low to intermediate-to-high after the booster dose. RBD+DDA/Sap presented neutralizing indexes against Omicron at days 47 and 176, while RBD+AH/OMV showed neutralization on days 21, 47 and 176. Cellular response, measured 465 days after immunization, revealed IFN-Y and IL-4 secretion. The offspring of RBD+DDA/Sap had detectable antibodies, which decreased around 45 days after birth, the last point we analyzed. The results suggested that DDA/Sap is a promising adjuvant mixture to enhance humoral and cellular immune response against SARS-CoV-2, improving maternal-fetal transference of antibodies; cross-reactivity with Omicron variant; and the maintenance of antibodies for a long period.

This paper examines the potential of large language models, specifically ChatGPT, BingChat, and Bard, in enhancing the work of teachers in various educational settings. These models, powered by cutting-edge artificial intelligence, offer a wide range of applications that can aid educators in curriculum development, personalized instruction, student engagement, and administrative tasks. By harnessing the capabilities of these language models, teachers can not only streamline their workload but also improve the overall quality of education. This paper explores the ways in which these models can empower educators and revolutionize teaching practices.

Various 4-aminotetrahydropyridinylidene salts were treated with aldehydes in alkaline medium. Their conversion to 5-substituted -hydroxyketones in a one-step reaction succeeded only with an aliphatic aldehyde. Instead, aromatic aldehydes gave 5-substituted -aminoketones or a single -diketone. The new compounds were characterized by spectroscopic methods and a single crystal structure analysis. Some of them showed anticancer and antibacterial properties.

Generative artificial intelligence (AI), in particular large language models such as ChatGPT have reached public consciousness with a wide-ranging discussion of their capabilities and suitability for various professions. Following the printing press and internet, generative AI language models are the third transformative technological invention with truly cross-sectoral impact on knowledge transmission. While the printing press allowed for the transmission of knowledge that is independent of the physical presence of the knowledge holder with publishers acting as gatekeepers, the internet added levels of democratization allowing anyone to publish, along with global immediacy. The development of social media resulted in an increased fragmentation and tribalization of on-line communities on their ways of knowing, resulting in alternative truths propagated in echo chambers. It is against this background that generative AI language models have entered public consciousness. Using strategic foresight methodology, this paper will examine the polemic proposition that the age of generative AI will emerge as an age of public ignorance.