Certain micronutrients exhibit immunomodulatory effects. However, no intervention has yet investigated the effect of an individualized supplementation on the severity of upper respiratory tract infections (URI). Therefore, we investigated whether a personalized supplementation moderates the incidence and severity of URI. Selenium, zinc, and vitamin D was measured from 59 healthy participants ) in dried blood spots. Accordingly, a personalized supplement was provided with or without the respective micronutrients. We used WURSS-21 questionnaires to assess the disease status. The blood values converged during the intervention and micronutrients no longer differed at the end of the intervention period between treated and untreated volunteers. The incidence and severity of the illness did not significantly differ between the groups. However, when analyzing the WURSS-21 score by the intention to treat, the initially randomized treatment arm revealed a significantly higher score than the placebo arm. Upon acute administration, individualized combination of selenium, zinc and vitamin D does not reduce the number or contribute to a milder course of URIs. Therefore, supplementation in acute infectious situations seems questionable. Further studies must address the habitual diet in more detail to better understand the impact of individual micronutrient status on the prevention of URI.

This article examines the diagnosis of the Agricultural Innovation System (SIA) in the department of Tolima, Colombia, as part of a project led by the Colombian Ministry of Agriculture and Rural Development and the Technological University of Pereira (TUP), which also evaluated the National Agricultural Innovation System (NAIS) in regions such as Chocó, Bolívar, and Meta. A methodology was used that involved a survey with 58 questions on a Likert scale to 300 participants, evaluated with congruence and relevance indexes, identifying key variables in the operation of the Agricultural Innovation System (AIS). A survey was also applied to actors of the National Innovation System for Higher Education in Agriculture, A survey was also applied to map the participating actors in the regional agricultural innovation systems of Tolima to identify gaps in extension, innovation, development, sustainability, ICT, education and training. Among the conclusions, it stands out that the associativity subsystem presents the lowest lag and is close to a score of two on the scale of gaps, evaluation carried out among the five subsystems including extension, ICT, environmental aspects, and pub-lic policy. The department of Tolima shows low performance in innovation and ICT, while the extension is less lagging. In Chaparral there is a general lag, with innovation being the worst evaluated subsystem. Rovira obtains high scores in most subsystems, although innovation and ICT have lower scores. At the national and regional levels, innovation is low, and articulation among NARS actors is insufficient, which highlights the need to promote good practices, strategies, and projects.

This research emphasizes a meta-heuristic Modified Ant Lion Optimizer (MALO) optimization approach for simultaneous utilization of DSTATCOM devices and distributed Photovoltaic (PV) sources with network reconfiguration in a radial power distribution scheme. In a radial power distribution network with network reconfiguration majority of the research is based on Constant Power model analysis. However, it is noticed that load models have a substantial impact on the distributed PV sources and the D-STATCOM device's optimal size and position. The effect of the Constant Power (CP) and Polynomial (ZIP) with load growth load models for the simultaneous insertion of distributed PV sources and DSTATCOM devices with network reconfiguration examined in this research work for power system planning. The penetration levels of distributed PV sources considered for the investigation are 25%, 50%, 75%, and 100%. The principal objective of this research is to reduce network total power losses, enhance the voltage magnitude profile at all buses, and reduce the overall operating cost while adhering to equality and inequality constraints. The proposed algorithm verified on 118-node test systems. The investigation is carried out for planning network upgradation to a High Voltage Distribution System(HVDS) on 317 nodes in the rural Bangalore Electricity Supply Company Limited(BESCOM) radial distribution scheme. Simulated results obtained by this method are validated with the BAT algorithm and available techniques in the literature.

Multiple Sclerosis (MS) is a neurodegenerative disease that mainly affects young adults. The high prevalence of the disease and its impact on patients' quality of life led to priority being given to the etiopathogenesis of the disease to identify possible modifiable factors and consequent effective intervention strategies. Recent hypotheses suggest that the etiopathogenesis of MS is multifactorial and includes factors related to the immune system, neuroinflammation and neuro-degeneration. In this scenario, sleep has a close - although indirect - relationship with MS, through its relationship with each of those factors. In particular, the role of cytokines in immune system impairment and neuroinflammation, mitochondrial dysfunction and oxidative stress in neurodegeneration all are associated with sleep in different forms. Furthermore, melatonin in relation with vitamin D has a potential therapeutic effect in MS sleep-related problems. Given the growing interest of research in the mechanisms underlying MS and therapies able to alleviate MS-related symptoms at all stages of the disease, a more in-depth study of the role of sleep disturbances and the factors intrinsically related to sleep and MS could be useful both to investigate the etiopathogenetic factors of MS and to develop potential non-invasive intervention strategies for MS treatment.

DNA double-strand breakage is the most lethal damage to chromosomal DNA. It activates a series of cellular DNA damage response pathways, including DNA damage sensing, control of cell cycle arrest and apoptosis, and DNA repair. DNA damage response pathways are regulated by complex signaling machineries. Of the intracellular signaling cascades, diacylglycerol kinase (DGK) phosphorylates diacylglycerol (DG) to generate phosphatidic acid (PA). Because both DG and PA serve as second messengers, DGK activity induces a shift of signaling pathways from DG-mediated to PA-mediated cascades, thereby implicating DGK in the regulation of widely various functions. Reportedly, one member of the DGK family, DGKζ, is intimately involved in the regulation of stress responses through p53 and NF-κB. Stresses such as ischemia and infarction cause DGKζ downregulation. Experimental DGKζ depletion renders cells and mice vulnerable to various stressors such as chemotherapeutic agents and ionizing irradiation. Nevertheless, how DGKζ is involved in DNA repair, a critical event of DNA damage response for survival remains unknown. For this study, we examined how DGKζ depletion affects DNA repair mechanisms. We demonstrated that DGKζ depletion causes attenuation of Akt activation and DNA-PK protein expression upon DNA damage, which might engender downregulated BRCA1 protein synthesis and stability. Results suggest that DGKζ depletion attenuates BRCA1-mediated DNA repair machinery, thereby conferring vulnerability to DNA damage.

The post-hoc analysis presented here aimed to address the influence of endogenous vitamin D in the immunological mechanism underlying effective mite allergoid-immunotherapy (AIT). Previously, we have shown that one subpopulation of T regulatory cells results in phenotypically identifiable as functionally potentiated and memory cells in allergic children after 12 months of this immunoactive treatment. Indeed, AIT is the only known treatment able to reshape the detrimental immune response against the allergen into a not noxious one. Besides, VD is widely considered an immunoregulatory molecule endogenously produced and exogenously provided with foods and supplements that might interact with AIT mechanism and affect its outcome. Therefore, a post-hoc analysis of the clinical and immunological data of three different cohorts of allergic patients was performed. One cohort (N=70) was on standard symptoms-controlling pharmacological treatment while the other two (N=60 and N=35, respectively) were treated with AIT for 12 months. Among the first were observed a lower mean endogenous VD level (<22 ng/ml) along with worse symptoms and higher use of medications. Remarkably, the comparison between two sub-cohorts of patients with serum VD above (N=32) or below (N=28) a cut-off value set at mean value (27 ng/ml) revealed that optimal improvement of all clinical and immune parameters was achieved (as expected by effective AIT), irrespective of the VD level. Notably, the third analysis, carried out on one cohort of AIT patients also taking concomitantly VD3 as food supplement (N=19), was distinguished by uppermost overall treatment outcome (amelioration of symptoms, lowest medications requirement, and reduction of total and allergen-specific IgE) as well as the increase of allergen-specific tolerogenic memory T regulatory cells. These findings suggest that endogenous VD level affects allergy severity and allergen immunotherapy effectiveness. Also, VD3 might be investigated as an add-on supplement to get the best out of immunotherapy in VD deficient/insufficient allergic patients. The immunogenic but low-allergenic mite allergoid used as bioactive agent might have contributed to minimize allergic and highlight immunological effects described here.

Background: Nutritional rickets is still considered as a global health problem especially in low-resource countries and immigrant societies of developed countries. Generalized skeletal deformities including angular knee deformities as genu varum and genu valgum are prominent features of nutritional rickets. Angular knee deformities can cause gait difficulties. However, the true remodelling potential of the healed knee deformities is largely unknown to the pediatric and orthopedic community. Aims: The primary objective of this study protocol is to investigate the natural history of disease in regard to the remodelling potential of angular knee deformities in children and adolescents with healed nutritional rickets. And determine the potential patient- and deformity-related factors that are associated with a favorable deformity remodelling as age and sex of patients and type, severity, laterality of deformities etc. Methods: This will be a prospective observational analytical cohort natural history of disease study. A minimum of at least 140 knees with healed nutritional rickets and angular knee deformities will be observed at regular three-monthly intervals over a period of at least one year. We will report two outcome variables namely; clinical and radiological tibio-femoral angle. And independent patient and deformity-related variables as age, sex, deformity type, severity and laterality. Inferential statistics namely bivariate and multivariate analysis will be employed accordingly to identify the relation between outcome variables and the different independent variables. Ethics and dissemination: This protocol study has been approved by the institutional research ethics committee. Results will be presented at conferences and submitted to relevant international and society publications. Authors will also communicate the results to their scholarly networks and post them on scholarly networking sites. Conclusions: This study has the potential for improving the decision-making process as to which patients deserve conservative treatment and which deserve surgical deformity correction. Results are expected to have an impact on the clinical practice of pediatricians, orthopedic surgeons and family physicians alike.

Abstract: A primary action of vitamin D is regulation of gene transcription. Many cell types possess genes that make antimicrobial peptides (AMPS) (endogenous antibiotics), recently discovered to be regulated by vitamin D. Two examples are cathelicidin and beta defensins, both bioactive against many different bacteria, fungi, mycobacteria, parasites and viruses. The signal transduction pathway is triggered by sensing microorganisms via cell surface receptors, causing intracellular production of calcitriol (1,25(OH)2D) and vitamin D receptors, leading to upregulation of AMP production. Serum 25(OH)D concentrations required to sustain adequate AMP production to eradicate infections are unknown. Vitamin D3 is photosynthesized in skin in amounts ranging from 10,000 (250 mcg) to 25,000 (625 mcg) International Units (IU) from 7-dehydrocholesterol after whole-body exposure to one minimal erythemal dose (MED) of ultraviolet B (UVB) radiation, and is impacted by many factors including geographic localities, seasonal changes and skin pigmentation. We and others have reported extended daily oral dosing with these amounts of vitamin D3 safe. We routinely observe serum 25(OH)D concentrations below 20ng/ml on new admissions, which have been reported insufficient to sustain AMP production. In contrast serum 25(OH)D concentrations above 100ng/ml have been reported after serial UVB treatments for psoriasis. Little vitamin D naturally occurs in food, and insufficient sun exposure may be causing worldwide deficiency. We review evidence suggesting that higher daily intakes of vitamin D3 than the currently recommended 600 (15 mcg) IU/day may be necessary to sustain AMP production in the face of an overwhelming infection, particularly in non-Hispanic blacks, a high risk population suffering the worst outcomes from COVID-19. We propose that increased vitamin D supplementation could provide a safe and cost-effective way to protect all populations from infections, in particular those from pandemic COVID-19.

In this paper, we observe that if X is a set and (Bin(X), □) is the semigroup of binary systems on X, then its center ZBin(X) consists of the locally-zero-semigroups and that these can be modeled as (simple) graphs and conversely. Using this device we show that we may obtain many results of interest concerning groupoids by reinterpreting graph theoretical properties and at the same time results on graphs G may be obtained by considering them as elements of centers of the semigroups of binary systems (Bin(X), □) where X = V(G), the vertex set of G.

This paper proposed three-dimensional numerical simulation method by coupling of electrostatic and fluid fields to evaluating the performance of electrical sensor in the concentration measurement of gas/solid two-phase flow. Compared with the static numerical simulation, this real-time dynamic 3-D simulation method can research on a designed capacitance sensor combining the dynamic characteristics of the two-phase flows for concentration measurement. Several fluid-electrostatic models of transmission pipes with different sensor structures are built. Under different test positions and different particle concentrations, the flow characteristics and the corresponding electric signals can be obtained, and the correlation coefficient between the concentration values and the capacitance values are used for performance evaluation of the sensors. The effects of flow regimes on concentration measurement are also been investigated in this paper. To validate the results of simulation, an experimental platform with horizontal straight pipe for phase volume concentration measurement of solid/air two-phase flow is built, and the experimental results agree well with simulation conclusions. The simulation and test results show that the coupling models can give constructive reference opinions for the sensor design and collection of installation position in different transmission pipelines, which are very important for the practical process of pneumatic conveying system.

The coronavirus disease 2019 (COVID-19), instigated by the zoonotic Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), rapidly transformed from an outbreak in Wuhan, China, into a widespread global pandemic. A significant post-infection condition, known as ‘long- COVID’, emerges in a substantial subset of patients, manifesting with a constellation of over 200 reported symptoms that span multiple organ systems. This condition, also known as 'post-acute sequelae of SARS-CoV-2 infection' (PASC), presents a perplexing clinical picture with far-reaching implications, often persisting long after the acute phase. While initial research focused on the immediate pulmonary impact of the virus, the recognition of COVID-19 as a multiorgan disruptor has unveiled a gamut of protracted and severe health issues. This review provides a summary of the primary effects of long COVID on the cardiovascular, nervous, and respiratory systems. It also delves into the mechanisms underlying these impacts and underscores the critical need for a comprehensive understanding of long COVID's pathogenesis.

We recently reported the isolation and characterization of an anti-SARS-CoV-2 antibody, called IgG-A7, that protected transgenic mice expressing the human angiotensin-converting enzyme 2 (hACE-2) from the infection with SARS-CoV-2 Wuhan. We show here that IgG-A7 protected 100% of the transgenic mice infected with Delta (B.1.617.2) and Omicron (B.1.1.529) at doses of 0.5 and 5 mg/kg, respectively. In addition, we studied the pharmacokinetic (PK) profile and Toxicology (Tox) of IgG-A7 in CD-1 mice at single doses of 100 and 200 mg/kg. PK parameters at those high doses were proportional to the dose, with the half-life in serum of ~10.5 days. IgG-A7 was well tolerated with no signs of toxicity in urine and blood samples, nor in histopathology analyses. Tissue Cross-reactivity (TCR) with a panel of mouse and human tissues showed no evidence of IgG-A7 interaction with tissues of these species, supporting the PK/Tox results in vivo and suggesting that while IgG-A7 has a broad efficacy profile it is not toxic in humans. The information generated in CD-1 mouse as PK/Tox model, complemented with the mouse and human TCR, could be of relevance as alternatives to NHPs in rapidly emerging viral diseases and/or quickly evolving viruses such as SARS-CoV-2.

To control the COVID-19 pandemic, many countries implemented vaccination and imposed societal restrictions both at the national level and for international travel. As a check of the corona status, a COVID pass has been issued. A COVID pass could be obtained when fully vaccinated against COVID-19, having recovered from a documented COVID-19 episode, or a recent (24-48 hours) negative SARS-CoV-2 antigen test. A global analysis of SARS-CoV-2 immune status (determined by past infection and/or vaccination), vaccination rates, as well as societal restrictions in controlling the COVID-19 pandemic is presented.

The Puuc Biocultural State Reserve (PBSR is an unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on the mainte-nance of low impact productive activities coordinated by multiple communal and private land-owners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and its relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000-2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (+19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000-2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing has changed over the years after the creation of the PBSR in 2011. An emergent hotspot analysis shows, however, that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012-2021 pe-riod was less common than prior to 2011 and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, results show that land owners outside the PBSR often clear forests with lower carbon density and species diversity than land owners inside the PBSR. This suggests that, compared to land owners outside the PBSR, land owners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012-2021 period minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend the continuation of efforts for providing alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. The combination of these models with contin-uous change detection datasets will allow to reveal underlying ecological processes and generate information better adapted to forest governance scales.

Background & aims. The fourth dose of anti-SARS-CoV-2 vaccine slightly improved the humoral response among previously seronegative liver transplant (LT) recipients. Mycophenolate (MMF) treatment worsens the vaccination response. This study aimed to evaluate whether temporary MMF interruption might improve immunogenicity of the fourth anti-SARS-CoV-2 BNT16b2 vaccine dose in nonresponsive LT recipients. Methods. LT recipients negative for anti-spike glycoprotein-specific immunoglobulin G receptor-binding domain (s-RBD) antibodies after the third vaccine dose were enrolled. Anti-SARS-CoV-2 spike-specific T cell responses were measured before and two months following the fourth vaccine dose, and anti-SARS-CoV-2-s-RBD antibodies also 6 months thereafter. MMF was suspended two weeks before and after vaccination. Results. Five LT recipients were enrolled. After a mean of 78 days after vaccination, all patients tested positive for anti-SARS-CoV-2-s-RBD antibodies. The mean antibody titer was 8944 UI/ml. The positive antibody response was maintained during a mean of 193 days of follow-up. Three patients developed a positive T cell response. Two patients (one positive for T cell response) developed a self-limited SARS-CoV-2 infection. Conclusions. Suspending MMF prior to the fourth dose of anti-SARS-CoV-2 mRNA vaccine seems feasible and safe. This procedure could restore vaccine-induced immunogenicity in a large portion of previously nonresponsive LT recipients.

This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. In this case, the mutation parameter is dynamically moved during the evolution process by using a shadowed and general type-2 fuzzy systems. The main idea of this work is to make a performance comparison between using shadowed and general type 2 fuzzy systems as controllers of the mutation parameter in differential evolution. The performance is compared with the problem of optimizing fuzzy controllers for a D.C. Motor. Simulation results show that general type-2 fuzzy systems are better when higher levels of noise are considered in the controller.

The gastrointestinal (GI) tract is innervated by the enteric nervous system (ENS), an extensive neuronal network that traverses along its walls. Due to local reflex circuits, the ENS is capable of functioning with and without input from the central nervous system. The functions of the ENS range from the propulsion of food to nutrient handling, blood flow regulation and immunological defense. Records of it first being studied emerged in the early 19th century when the submucosal and myenteric plexuses were discovered. This was followed by extensive research and further delineation of its development, anatomy, and function during the next two centuries. The morbidity and mortality associated with the underdevelopment, infection or inflammation of the ENS highlights its importance and the need for us to completely understand its normal function. This review will provide a general overview of the ENS to date and connect specific GI disorders such as short bowel syndrome with neuronal pathophysiology. Exciting opportunities in which the ENS could be used as a therapeutic target for common GI diseases will also be highlighted, as the further unlocking of such mechanisms could open the door to more therapy-related advances, and ultimately change our approach to GI disorders.

SARS-CoV-2, the causal agent of the globally spreading COVID-19, is capable of infecting variable animals besides human being. We evaluated the potential susceptibility of important livestock, pets and aquatic mammals by performing a multi-species sequence analysis of ACE2 based on the reported affected and unaffected animals. We identified a triple amino acid pattern of ACE2, at position 30, 31 and 34, that might be associated with SARS-CoV-2 infection and H34 might be an indicator of the susceptibility to COVID-19.

SARS-CoV-2 (CoV-2) is a coronavirus which is causing the actual COVID-19 pandemic. The disease caused by 2019 new coronavirus (2019-nCoV) was named coronavirus disease-19 (COVID-19) by the World Health Organization in February 2020. Primary non-specific reported symptoms of 2019-nCoV infection at the prodromal phase are malaise, fever, and dry cough. The most commonly reported signs and symptoms are fever (98%), cough (76%), dyspnea (55%), and myalgia or fatigue (44%). Nonetheless, recent reports suggest an association between COVID-19 and altered olfactory and taste functions, although smell seems to be more affected than taste. These associations of smell and taste dysfunctions and CoV-2 are consistent with case reports describing a patient with SARS with long term anosmia after recovery from respiratory distress, with the observation that olfactory function is commonly altered after infection with endemic coronaviruses, and with data demonstrating that intentional experimental infection of humans with CoV-299 raises the thresholds at which odors can be detected. Post-viral anosmia and is one of the leading causes of loss of sense of smell in adults, accounting for up to 40% cases of anosmia. Viruses that give rise to the common cold are well known to cause post-infectious loss, and over 200 different viruses are known to cause upper respiratory tract infections. I reviewed the possible mechanisms of smell and taste loss in COVID-19. I concluded that since the existence of such a relationship is likely, it is highly recommended that those patients who experience complications such as smell and/or taste loss, even as unique symptoms, should be considered as potential SARS-CoV-2 virus carriers.

SARS-CoV-2, the newly identified human coronavirus causing severe pneumonia epidemic, was probably originated from Chinese horseshoe bats. However, direct transmission of the virus from bats to humans is unlikely due to lack of direct contact, implying the existence of unknown intermediate hosts. Angiotensin converting enzyme 2 (ACE2) is the receptor of SARS-CoV-2, but only ACE2s of certain species can be utilized by SARS-CoV-2. Here, we evaluated and ranked the receptor-utilizing capability of ACE2s from various species by phylogenetic clustering and sequence alignment with the currently known ACE2s utilized by SARS-CoV-2, predicting potential intermediate hosts of SARS-CoV-2.

Despite significant research efforts, the question of whether rising atmospheric CO₂ concentrations (C_a) affect leaf respiration remains unanswered. Here, I reanalyse published hydrogen isotope abundances in starch glucose of sunflower leaves. I report that, as C_a increases from 450 to 1500 ppm, respiration by the oxidative pentose phosphate pathway in chloroplasts increases from 0 to ≈ 5% relative to net carbon assimilation. This is consistent with known regulatory properties of the pathway. Summarising recent reports of metabolic fluxes in plant leaves, a picture emerges in which mitochondrial processes are distinctly less important for overall respiration than the oxidative pentose phosphate pathways in chloroplasts and the cytosol. Regulatory properties of these pathways are consistent with observations of lower-than-expected stimulations of photosynthesis in response to increasing C_a. Reported advances in understanding leaf respiratory mechanisms may enable modelling and prediction of respiration effects (inter alia) on biosphere-atmosphere CO₂ exchange and plant performance under climate change.

Pregnant women are especially vulnerable to respiratory diseases. We aimed to study seroconversion rate during pregnancy in a cohort of consecutive pregnancies tested in the first and third trimesters and to compare maternal and obstetric complications between women who seroconverted in the first versus the third trimester. This is an observational, cohort study carried out at Hospital Universitario de Torrejón, in Madrid, Spain, during the first peak of the COVID-19 pandemic. All consecutive singleton pregnancies with a viable fetus attending their 11-13 weeks scan between January 1st and May 15th, 2020, were included and monthly follow up until delivery. Antibodies against SARS-CoV-2 (IgA and IgG) were analyzed on stored serum samples obtained from the first and third trimester routine antenatal bloods in 470 pregnant women. Antibodies against SARS-CoV-2 were detected in 31 (6.6%) women in the first trimester and in 66 (14.0%) in the third trimester, including 48 (10.2%) that were negative in the first trimester (seroconversion during pregnancy). Although the rate of infection was significantly higher in the third versus the first trimester (p = 0.003), no significant differences in maternal or obstetric complications were observed in women testing positive in the first versus the third trimester.

Despite the remarkable success of SARS CoV-2 vaccines, the rise of variants, some of which are more resistant to the effects of vaccination, highlights the potential need for additional COVID-19 vaccines. We used the Multiple Antigen Presenting System (MAPS) technology, in which proteins are presented on a polysaccharide polymer to induce antibody, Th1, Th17 and CD8+ T cell responses, to engineer a novel vaccine targeting SARS CoV-2. This vaccine contains a fragment of the spike (S) protein receptor-binding domain (RBD) sequence of the original D614G strain and was used to immunize nonhuman primates (NHP) for assessment of immunological responses and protection against SARS CoV-2 challenge. The SARS CoV-2 MAPS vaccine generated robust neutralizing antibodies as well as Th1, Th17 and cytotoxic CD8 T-cell responses in NHPs. Furthermore, MAPS-immunized NHPs had significantly lower viral loads in the nasopharynx and lung compared to control animals. Taken together, these findings support the use of the MAPS platform to make a SARS CoV-2 vaccine. The nature of the platform also could enable its use for the inclusion of different variants in a single vaccine.

Wastewater surveillance for SARS-CoV-2 has garnered extensive public attention during the COVID-19 pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, it is necessary to bridge the communication and knowledge gaps between researchers and public health responders. Here we describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethical consideration for monitoring. Overall, while wastewater surveillance to assess community infections is not a new idea, by addressing these barriers, the COVID-19 pandemic may be the initiating event that turns this emerging public health tool into a sustainable nationwide surveillance system.

To date, uncertainty remains about how long the protective immune responses against SARS-CoV-2 persists and reports of suspected reinfection began to be described in recovered patients months after the first episode. Viral evolution may favor reinfections, and the recently described spike mutations, particularly in the receptor binding domain (RBD) in SARS-CoV-2 lineages circulating in the UK, South Africa, and most recently in Brazil, have raised concern on their potential impact in infectivity, immune escape and reinfection. We report a case of reinfection from distinct SARS-CoV-2 lineages presenting the E484K mutation in Brazil, a variant associated with escape from neutralizing antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as the current coronavirus pandemic is an infectious disease that initially confirmed in China in late December 2019. In this study, we analyzed 131 complete sequences of SARS-CoV-2 from Asia. Our results show that there are fifteen major mutations in Asia which most of them are co-evolved. There were five groups based on co-mutations which three of them resulted in clade G including (241C>T, 3037C>T, 14408C>T, and 23403A>G), (28881G>A, 28882G>A, 28883G>C and 23403A>G) and (25563G>T and 23403A>G). Co-mutations in (8782C>T and 28144T>C) and (1397G>A, 28688T>C, 29742G>T and 11083G>T) were clustered in clade S and a new clade outside of GISAID classification, respectively. Sequences with a mutation in 26144G>T had low variability without any co-mutation which formed clade V. In this study, we showed that Most of the circulated viruses in Asia collected in five co-mutation groups which may affect the transmissibility and vaccine designing strategies.

Coronaviruses (CoVs) are a well-known group of viruses in veterinary medicine. We currently know four genera of Coronavirus, alfa, beta, gamma and delta. Wild, farmed and pet animals are infected with CoVs belonging to all four genera. Seven human respiratory coronaviruses have still been identified, four of which cause upper respiratory tract diseases, specifically, the common cold, and the last three that have emerged cause severe acute respiratory syndromes, SARS-CoV-1, MERS-CoV and SARS-CoV-2. In this review we briefly describe animal coronaviruses and what we actually know about SARS-CoV-2 infection in farm and domestic animals.

The outbreak of COVID-19 has caused a global public health crisis. The spread of SARS-CoV-2 by contact is widely accepted, but the relative importance of aerosol transmission for the spread of COVID-19 is controversial. Here we characterize the distribution of SARA-CoV-2 in 123 aerosol samples, 63 masks, and 30 surface samples collected at various locations in Wuhan, China. The positive percentages of viral RNA included 21% of the aerosol samples from an intensive care unit and 39% of the masks from patients with a range of conditions. A viable virus was isolated from the surgical mask of one critically ill patient while all viral RNA positive aerosol samples were cultured negative. The SARS-CoV-2 detected in masks from patients, ambient air, and respirators from health workers compose a chain of emission, transport, and recipient of the virus. Our results indicate that masks are effective in protecting against the spread of viruses, and it is strongly recommended that people throughout the world wear masks to break the chain of virus transmission and thus protect themselves and others from SARS-CoV-2.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

Angiogenesis mediated by proteins such as Fibroblast Growth Factor – 2 (FGF-2) is a vital component of normal physiological processes and has also been implicated in contributing to disease state associated with various microbial infections. Previous studies by our group and others have shown that Candida albicans, a common agent of candidiasis, induces FGF-2 expression in vitro, and angiogenesis in brains and kidneys during systemic infections. However, the underlying mechanism(s) via which the fungus increases FGF-2 expression and the role(s) that FGF-2/angiogenesis plays in C. albicans disease remain unknown. Here we show, for the first time, that C. albicans hyphae (and not yeast cells) increase the FGF-2 response in human endothelial cells. Moreover, candidalysin, a toxin secreted exclusively by C. albicans in the hyphal state is required to induce this response. Our in vivo studies show that, in the systemic C. albicans infection model, mice treated with FGF-2 exhibit significantly higher mortality rates when compared to untreated mice not given the angiogenic growth factor. Even treatment with fluconazole could not fully rescue infected animals that were administered FGF-2. Our data suggest that the increase of FGF-2 production/angiogenesis induced by candidalysin contributes to the pathogenicity of C. albicans.

Retroviruses perpetuate their survival by incorporating a copy of their genome into the host cell, a critical step catalyzed by the virally encoded integrase. The viral capsid plays an important role during the viral life-cycle, including nuclear importation in case of lentiviruses and integration targeting events, hence, targeting the integrase and the viral capsid is a favorable therapeutic strategy. While integrase strand transfer inhibitors (INSTIs) are recommended as first-line regimens given their high efficacy and tolerability, lenacapavir is the first capsid inhibitor and the newest addition to the HIV treatment arsenal. These inhibitors are however designed for treatment of HIV-1 infection, and their efficacy against HIV-2 remains widely understudied and inconclusive, supported only by few limited phenotypic susceptibility studies. We therefore carried out inhibition profiling of a panel of second-generation INSTIs and lenacapavir against HIV-2 in cell culture, utilizing pseudovirion inhibition profiling assays. Our results show that the tested INSTIs and lenacapavir exerted excellent efficacy against ROD-based HIV-2 integrase, and interestingly, raltegravir also showed modest antiviral activity against the SARS-CoV-2 Omicron variant in antiviral assays carried out in Vero E6 cells.

Background and Objectives: Cardiovascular events are the leading cause of morbidity and mortal-ity in hemodialysis (HD) patients. Identifying risk factors can help in the effort to reduce cardi-ovascular risk and improve life expectancy. The purpose of this study was to evaluate the ability of CHA2DS2-VASc score [risk index of stroke in atrial fibrillation (AF)] in patients with end stage kidney disease, to predict stroke, major cardiovascular events and mortality. Materials and Meth-ods: CHA2DS2-VASc and HAS-BLED (bleeding risk from use of anticoagulation in AF) scores were calculated in 237 HD patients, [99 women, median age 76 (15) years], at time they com-menced on HD. The scores’ ability to predict long term cardiovascular morbidity and mortality was estimated, both in those with and without AF. Results: CHA2DS2-VASc score was signifi-cantly increased in AF (n=69) compared to non-AF (n=168) patients, 5 (2.5) versus 4 (2), p<0.0001, respectively. Increased CHA2DS2-VASc score was associated with heart failure (p=0.007, p=0.024), stroke (p<0.0001, p<0.0001) and risk of all-cause mortality (p<0.0001, p<0.0001), in both groups, respectively. C statistics indicated that CHA2DS2-VASc score performed modest discrimination in this HD population with and without AF for heart failure, stroke, and all-cause mortality, but for cardiovascular mortality in AF group only. Conclusions: Increased CHA2DS2-VASc score at time starting on HD, can predict stroke, heart failure and all-cause mortality in HD patients in-dependent of the presence of AF. Risk of cardiovascular mortality could be predicted only on patients with AF.

We have developed a simple, rapid, high-throughput RBD-based ELISA to assess the humoral immunity against emerging SARS-CoV-2 virus variants. The cDNAs of the his-tagged RBD proteins of the virus variants were stably engineered into HEK cells secreting the protein into the supernatant, and RBD purification was performed by Ni-chromatography and buffer exchange by membrane filtration. The simplified assay uses single dilutions of sera from finger-pricked native blood samples, purified RBD in 96-well plates, and a chromogenic dye for development. The results of this RBD-ELISA were confirmed to correlate with those of a commercial immunoassay measuring antibodies against the Wuhan strain, as well as direct virus neutralization assays assessing the cellular effects of the Wuhan and the Omicron (BA.5) variants. Here we document the applicability of this ELISA to assess the variant-specific humoral immunity in vaccinated and convalescent patients, as well as to follow the time course of selective vaccination response. This simple and rapid assay, easily modified to detect humoral immunity against emerging SARS-CoV-2 virus variants, may help to assess the level of antiviral protection after vaccination or infection.

Oral diseases remain a major health problem worldwide, with the World Health Organisation reporting that oral health neglect affects almost half of the world’s population. Quorum sensing molecules (QSMs) influence oral biofilms in various ways with knowledge of direct oral QSM-host interaction being limited, and such studies could provide more insight into the cross-kingdom communication occurring during oral disease development. This review aims to explore the literature on oral QSM-host interaction and to highlight areas of advancement in this field. QSM CSP-1 produced by Gram-positive oral bacteria was found to interact with T2R receptors, activating NF-kB signalling and leading to remodeling of the cytoskeleton. AI-2 in the oral cavity was found in various studies to elicit an inflammatory response in specific oral cells. Overall AHL detection methods remain an area for development, through which greater understanding of oral QSMs’ influence on host cells can be achieved. In conclusion, from the current literature it can be inferred that that QSMs are utilised by host cells to detect bacterial presence and in the majority of cases elicit an immune response towards the environmental QSMs. This may provide a base to target QSMs as novel treatment of oral diseases.

More than 3 years have passed since the emergence of COVID-19. On May 8, 2023, COVID-19 in Japan was downgraded to Category 5 by the Infectious Disease Control Law. In Japan, at the beginning of the COVID-19 pandemic in 2020, cases of infection and deaths from severe disease were few compared with those of Western countries. However, in the medical field, screening for COVID-19 was given top priority, resulting in confusion and proving disadvantageous for many patients, also the overreaction to COVID-19 as the most important issue in society can be attributed largely to statements by infectious disease experts. In addition, the mRNA vaccine emerged in 2021, and most of the population was vaccinated up to two times within a short period of less than 1 year because infectious disease experts strongly promoted vaccination. After 2022, when vaccination progressed, and the Omicron strain, which is an attenuated strain, became the mainstay of the SARS-CoV-2, the number of severe cases of COVID-19 decreased significantly; however, the number of infected people increased dramatically instead. A significant portion of the population is thought to have hybrid immunity due to vaccination plus natural infection and maintains high antibody titers. Henceforth, additional vaccination should be given preferentially to those who will benefit most from it. Conversely, measures against COVID-19 caused serious damage to the economy and society. Policies that not only address countermeasures against infection, but also those that encompass the economy and society as a whole are necessary.

Mammalian seminal plasma contains a multitude of bioactive components, including lipids, glucose, mineral elements, metabolites, proteins, cytokines and growth factors, with various functions during insemination and fertilization. The seminal plasma protein PDC-109 is one of the major soluble components of the bovine ejaculate and is crucially important for sperm motility, capacitation and acrosome reaction. A hitherto underappreciated function of seminal plasma is its anti-microbial and anti-viral activity, which may limit sexual transmission of infectious diseases during intercourse. We have recently discovered that PDC-109 inhibits the membrane fusion activity of influenza virus particles and significantly impairs viral infections at micromolar concentrations. Here we investigated whether the antiviral activity of PDC-109 is restricted to Influenza or if other mammalian viruses are similarly affected. We focused on Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 19 (COVID-19), thoroughly assessing PDC-109 inhibition with SARS-CoV-2 Spike (S)-pseudotyped reporter virus particles, but also live-virus infections. Consistent with our previous publications we found significant virus inhibition, albeit accompanied by substantial cytotoxicity. Using time-of-addition experiments however, we discovered treatment regimen that enable virus suppression without affecting cell viability. We furthermore demonstrated that PDC-109 is also able to impair infections mediated by the VSV glycoprotein (VSVg) thus indicating a broad pan-antiviral activity against multiple virus species and families.

The COVID-19 pandemic had profound negative effects on millions of couples affected by infertility and in need to resort to assisted reproductive technologies. There is no consensus over the optimal way and moment of screening triage-negative asymptomatic patients and staff. We present SARS-CoV-2 antibodies’ (IgM, IgG) seroprevalence in 516 triage-negative patients and 30 fertility care providers. The sampling for SARS-CoV-2 serological assays took place from the lockdown release throughout the second half of 2020 (17.05 - 01.12.2020). It revealed an increased seroprevalence of antibodies that closely followed the local epidemiology of COVID-19, with the highest rate of seropositivity coincident with the peak of the second wave. From 546 triage-negative individuals whose blood samples were assessed for SARS-CoV-2 antibodies, 6% yielded positive results. The overall seroconversion rate was 2.8% for IgG and 5.1% for IgM. In the group with positive IgM, we observed a negative predictive value for IgM of 98.36% (95% CI: 88.79 – 99.78%), which is clinically meaningful. Serological testing of triage-negative patients up to seven days prior to the actual fertility procedure might avoid the more expensive and not more sensitive molecular testing currently being used for patient screening in most fertility units.

Covid-19 pandemic has captivated scientists to investigate if this new disease can affect the central nervous system (CNS). The most challenging symptoms of Covid-19 are related to respiratory distress, and most patients admitted in intensive care units cannot breathe by their own. Therefore, a crucial question is if respiratory distress can be partially explained by the CNS affection. SARS-Cov-2 is a beta-coronavirus that shares high similarities with SARS-CoV. The infection of SARS‐CoV has been reported in the brains from both patients and experimental animals, where the brainstem was heavily infected. Those coronaviruses have been able to invade the brainstem via a synapse‐connected route to the medullary respiratory center, where the infected regions included the nucleus of the solitary tract and nucleus ambiguous. The vagal afferent nerves from receptors in the lung communicate with the medulla and pons respiratory control centers to coordinate inspiration and expiration. This suggests that neuroinvasion of SARS‐CoV‐2 might play a role in the acute respiratory failure of Covid-19. Therefore, acute respiratory distress in Covid-19 can be partially explained by brainstem dysfunction, suggesting the needs of more specific and aggressive treatments with the direct participation of neurologists and neurointensivists.

SARS-CoV-2 causes severe pneumonia epidemics and probably originated in horseshoe bats, but the intermediate host is unknown. The interaction of SARS-CoV-2 spike protein and its acceptor protein ACE2 is an important issue in determining viral host range and cross-species infection, while the binding capacity of Spike protein to ACE2 of different species is unknown. Here, we used the atomic structure model of SARS-CoV-2 and human ACE2 to assess the receptor utilization capacity of ACE2s from different species including cats, chimpanzees, dogs, cattles. Our results show, domestic cats (Felis catusc) and dogs (Canis lupus familiaris) are more susceptible to infection by SARS-CoV-2 and that they can efficiently transmit the virus to previously uninfected animals that are housed with them. Especially, cats could be a choice of animal model for screening antiviral drugs or vaccine candidates against SARS-CoV-2.

This study investigated the neuroprotective effects of methyl 3,4-dihydroxybenzoate (MDHB) against t-butylhydroperoxide(TBHP) induced oxidative damage in SH-SY5Y (human neuroblastoma cells) and the underlying mechanisms. SH-SY5Y were cultured in DMEM+10% FBS for 24 hours and pretreated with different concentrations of MDHB or N-acetyl-L-cysteine (NAC) for 4 hours prior to the addition of 40 μM TBHP for 24 hours. Cell viability was analyzed using the methyl thiazolyl tetrazolium (MTT) and lactate dehydrogenase (LDH) assays. An annexin V-FITC assay was used to detect cell apoptosis rate. The 2',7'-dichlorofluorescin diacetate (DCFH-DA) assay was used to determine intracellular ROS levels. The activities of antioxidative enzymes (GSH-Px and SOD) were measured using commercially available kits. The oxidative DNA damage marker 8-OHdG was detected using ELISA. Western blotting was used to determine the expression of Bcl-2, Bax, caspase 3, p-Akt and Akt proteins in treated SH-SY5Y cells. Our results showed that MDHB is an effective neuroprotective compound that can mitigate oxidative stress and inhibit apoptosis in SH-SY5Y cells

Abstract: This article reports the results of an ecological study of cancer incidence rates by state in the US for the period 2016-2020. The goals of this study were to determine the extent to which solar UVB doses still reduced cancer risk compared to findings reported in 2006 for cancer mortality rates for the periods 1950–1969 and 1970-1794 as well as cancer incidence rates for the period 1998–2002 and to determine which factors were recently associated with cancer risk. The cancer data for non-Hispanic white (European American) men and women were obtained from the Centers for Disease Control and Prevention. Indices were obtained for solar UVB at the surface for July 1992, and alcohol consumption, and diabetes and obesity prevalence near the 2016–2020 period. Lung cancer incidence rates were also used in the analyses as a surrogate for smoking, diet, and air pollution. The cancers for which solar UVB is significantly associated with reduced incidence are bladder, brain (males), breast, corpus uteri, esophageal, gastric, non-Hodgkin’s lymphoma, pancreatic, and renal cancer. Lung cancer was significantly associated with colorectal, laryngeal, and renal cancer. Diabetes was also significantly associated with breast, liver, and lung cancer. Obesity prevalence was significantly associated with breast, colorectal and renal cancer. Alcohol consumption was associated with bladder and esophageal cancer. Thus diet has become a very important driver of cancer incidence rates. The role of solar UVB in reducing risk of cancer has been reduced due to people spending less time outdoors, wearing sunscreen that blocks UVB but not UVA radiation, and population increases in overweight and obesity, which lowers 25-hydroxyvitamin D concentrations and generates systemic inflammation, a risk factor for cancer. The dietary approach that would reduce the risk of diabetes, obesity, lung cancer, and, therefore cancer, would be one based mostly on whole-plants and restrictions on red and processed meats and ultraprocessed foods. Solar UVB exposure for a few minutes before applying sunscreen and taking vitamin D supplements would also help reduce risk of cancer.Keywords: alcohol consumption; cancer incidence;

In the current work, the stable queueuing system's Generalised Z-Entropy (GZE) of Rényian formalism is examined in its fractal dimension. Notably, fractal dimension’s resulting behaviour that corresponds to the GZE parameters is examined through numerical tests. This research makes a substantial generalization in the literature by fusing fractal geometry and information theory to shed light on how entropy and complexity interact. More fundamentally, the significant role of fractal dimension to advance Big Data Analytics(BDAs) is highlighted. Closing remarks combined with open problems and the next phase of research are provided.

In this paper, an intelligent blind guide system based on 2D LiDAR and RGB-D camera sensing is proposed, and the system is mounted on the smart cane. The intelligent guide system relies on 2D LiDAR, RGB-D camera, IMU, GPS, Jetson nano B01, STM32 and other hardware. The main advantage of the intelligent guide system proposed by us is that the distance between the smart cane and obstacles can be measured by 2D LiDAR based on Cartographer algorithm, thus achieving Simultaneous localization and mapping (SLAM). At the same time, through the improved yolov5 algorithm, pedestrians, vehicles, pedestrian crosswalks, traffic lights, warning posts, stone piers, tactile paving and other objects in front of the visually impaired can be quickly and effectively identified. Laser SLAM and improved yolov5 obstacle identification tests were carried out inside a teaching building on the campus of Hainan Normal University and on a pedestrian crossing on Longkun South Road in Haikou City, Hainan Province. The results show that the intelligent guide system developed by us can drive the wheels and omnidirectional wheels at the bottom of the smart cane, and give the smart cane a self-leading blind guide function like a "guide dog", which can effectively guide the visually impaired to avoid obstacles and reach the predetermined destination, and can quickly and effectively identify the obstacles on the way out. The laser SLAM speed of this system is 25~31FPS, which can realize the short-distance obstacle avoidance and navigation function both in indoor and outdoor envionments. The improved yolov5 helps to identify 86 types of objects, the recognition rate for pedestrian crosswalks and for vehicles are 84.6% and 71.8%, respectively; the overall recognition rate for 86 types of objects is 61.2%, and the obstacle recognition rate of the intelligent guide system is 25-26FPS.

We investigate the innovational determinants of “Patent Applications” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have a deeper positive association with “Patent Applications” are “Human Resources” and “Intellectual Assets”, while the variables that show a more intense negative relation with Patent Applications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”. A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has been realized. The results show the presence of two clusters. A network analysis with the distance of Manhattan has been performed and we find three different complex network structures. Finally, a comparison is made among eight machine learning algorithms for the prediction of the future value of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the best performing algorithm. Using PNN the results show that the mean future value of “Patent Applications” in the estimated countries is expected to decrease of -0.1%.

In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We use data from the EIS-European Innovation Scoreboard of the European Commission for 36 countries in the period 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that “New Doctorate Graduates” is positively associated, among others, with “Human Resources” and “Government Procurement of Advanced Technology Products” and negatively, associated among others, with “Total Entrepreneurial Activity” and “Innovation Index”. We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with the Elbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, we use the Network Analysis with the Distance of Manhattan, and we find the presence of seven network structures. Finally, we propose a confrontation among ten machine learning algorithms to predict the value of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD. Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while Linear Regression performs better for AD.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.

In this article we investigate the determinants of marketing or organizational innovators in Europe for 36 countries in the period 2010-2019. We have used data from the European Innovation Scoreboard-EIS of the European Commission. We perform different econometric models i.e. Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. Results show that the level of marketing or organizational innovators in positively associated, among others variables to “Innovation Index”, “Innovators” and “Knowledge Intensive Service Exports”, while is negatively associated with “Sales Impacts”, “Foreign Controlled Enterprises Share of Value Added” and “Government procurement of advanced technology products”.

In the following article, the value of the "Knowledge Intensive Services Exports in Europe" in 36 European countries is estimated. The data were analyzed through a set of econometric models or: Poled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. The results show that “Knowledge Intensive Services Exports” is negatively associated, among others, with "Buyer Sophistication", "Government Procurement of Advanced Technology Products", and positively associated with the following variables i.e. "Innovation Index", "Sales Impacts" and "Total Entrepreneurial Activity". Then a clusterization with k-Means algorithm was made with the Elbow method. The results show the presence of 3 clusters. A network analysis was later built and 4 complex network structures and three structures with simplified networks were detected. To predict the future trend of the variable, a comparison was made with eight different machine learning algorithms. The results show that prediction with Augmented Data-AD is more efficient than prediction with Original Data-AD with a reduction of the mean of statistical errors equal to 55,94%.

The following article indicates the determinants of “Internet User Skills” among European countries based on the application of the database deriving from the DESI-Index. The data were analyzed using the following econometric models, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS, WLS corrected for heteroskedasticity. The Elbow method and the Silouette coefficient method were compared for the optimization of the number of clusters obtained by the k-Means algorithm. The result shows the presence of 5 clusters. A network analysis was carried out using the Euclidean distance with the result of identifying two network structures between some analyzed countries. subsequently a comparison was made between six different machine learning algorithms for the prediction of the future value of the variable of interest. The result shows that the best predictor algorithm is Gradient Boosted Tree Regression with an expected value of the predicted variable increasing by a value of 1.75%. Later a further comparison was made by comparing 6 algorithms with the increased data. The result shows that the best predictor is Simple Regression Tree. The interest variable is predicted to decrease by an amount equal to -6.099%. Statistical errors improve on average by 32.43% in the transition between the original data and the increased data.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.

The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

The determinants of the presence of “Foreign Doctorate Students” among 36 European Countries for the period 2010-2019 are analyzed in this article. Panel Data with Fixed Effects, Random Effects, WLS, Pooled OLS, and Dynamic Panel are used to investigate the data. We found that the presence of Foreign Doctorate Students is positively associated to “Attractive Research Systems”, “Finance and Support”, “Rule of Law”, “Sales Impacts”, “New Doctorate Graduates”, “Basic School Entrepreneurial Education and Training”, “Tertiary Education” and negatively associated to “Innovative Sales Share”, “Innovation Friendly Environment”, “Linkages”, “Trademark Applications”, “Government Procurement of Advanced Technology Products”, “R&D Expenditure Public Sectors”. A cluster analysis was then carried out through the application of the unsupervised k-Means algorithm optimized using the Silhouette coefficient with the identification of 5 clusters. Finally, eight different machine learning algorithms were used to predict the value of the "Foreign Doctorate Students" variable. The results show that the best predictor algorithm is the "Tree Ensemble Regression" with a predicted value growing at a rate of 114.03%.

This paper proposes a new structure of the dual-rotor hybrid-excited axial-flux permanent magnet vernier machine (DR-HEAFPMVM) with the modular stator and the consequent-pole PM (CPM) rotor for low-speed, high torque density applications such as in-wheel electric vehicles. The tooth-wound non-overlapping armature windings and direct current (DC) excitation windings are respectively arranged in stator main-teeth and split-teeth to obtain the modulated and adjustable air-gap flux densities, which result in the high torque density and outstanding flux-weakening capability. First, the design consideration, operation principle, and the air-gap flux density distributions of the proposed machine are elaborated based on the air-gap permeance function. Then, the influence of the pole ratios (PRs) and the DC excitation currents on the main electromagnetic performances of the DR-HEAFPMVM, such as the flux-weakening capability, back-electromotive force (back-EMF), on-load electromagnetic torque, loss distribution, and efficiencies, is investigated using the 3-D finite-element method (FEM). Results verify the feasibility of the flux adjustment of the DC excitation windings equipped in the split-tooth, and the design with a pole ratio of 8/1 tends to have higher torque density, higher machine efficiency, and considerable flux-weakening capability compared with the other two PRs.

The noble metals palladium and silver find use in many high performance applications, and their alloys (PdAg), known for more than sixty years, are industrially important, finding use in many fields including hydrogen purification and separation, numerous facets of catalysis, and in fuel cells. In recent years, interest in these materials has grown significantly, particularly in energy generating applications and due to their performance as solid-state chemical sensors for a range of small molecules. PdAg thin films can be prepared using traditional physical methods such as cold rolling, or more modern and controllable chemical or physical deposition techniques such as electrodeposition or chemical vapour deposition. Despite the wide-reaching uses of PdAg, several recent advancements in materials preparation, such as additive manufacturing, better known as 3-D printing, remain unexplored for this material due to the differing chemistries of the two elements. In this review, we explore the manufacturing methods commonly employed for the preparation of PdAg thin films, the common and niche applications of these materials, and opportunities for the future development of these two aspects, with an emphasis on how preparation of thin films can utilise additive manufacturing approaches.

Although distributed additive manufacturing can provide high returns on investment the current markup on commercial filament over base polymers limits deployment. These cost barriers can be surmounted by eliminating the entire process of fusing filament by 3-D printing products directly from polymer granules. Fused granular fabrication (FGF) (or fused particle fabrication (FPF)) is being held back in part by the accessibility of low-cost pelletizers and choppers. An open-source 3-D printable invention disclosed here provides for precise controlled pelletizing of both single thermopolymers as well as composites for 3-D printing. The system is designed, built and tested for its ability to provide high tolerance thermopolymer pellets from a number of sizes capable of being used in a FGF printer. In addition, the chopping pelletizer is tested for its ability to chop multi-materials simultaneously for color mixing and composite fabrication as well as precise fractional measuring back to filament. The US$185 open-source 3-D printable pelletizer chopper system was successfully fabricated and has a 0.5 kg/hr throughput with one motor, and 1.0 kg/hr throughput with two motors using only 0.24 kWh/kg during the chopping process. Pellets were successfully printed directly via FGF and indirectly after being converted into high-tolerance filament in a recyclebot.

Leptin is the archetypal adipokine that promotes a negative whole-body energy balance largely through its action on brain leptin receptors. As such, the sustained weight loss and food intake suppression induced by Roux-en-Y gastric bypass (RYGB) surgery have been attributed to enhancement of leptin receptor signalling. We formally revisited this idea in Zucker Fatty fa/fa rats, an established genetic model of leptin receptor deficiency, and carefully compared their body weight, food intake and oral glucose tolerance after RYGB with that of sham-operated fa/fa (obese) and sham-operated fa/+ (lean) rats. We found that RYGB rats sustainably lost body weight, which converged with that of lean rats and was 25.5 % lower than that of obese rats by the end of the 4 week study period. Correspondingly, daily food intake of RYGB rats was similar to that of lean rats from the second postoperative week, while it was always at least 33.9 % lower than that of obese rats. Further, oral glucose tolerance of RYGB rats was normalized at the forth postoperative week. These findings assert that leptin is not an essential mediator of the sustained weight loss and food intake suppression as well as the improved glycemic control induced by RYGB, and instead point to additional circulating and/or neural factors.

Liver related diseases are the 3rd leading causes (9.3%) of mortality in type 2 diabetes mellitus (T2DM) in Japan. T2DM is closely associated with nonalcoholic fatty liver disease (NAFLD) which is the most prevalent chronic liver disease worldwide. Nonalcoholic steatohepatitis (NASH), a severe form of NAFLD, can lead to hepatocellular carcinoma (HCC) and hepatic failure. There are no established pharmacotherapies for NASH patients with T2DM. Though vitamin E is established as a 1st line agent in NASH without T2DM, its efficacy was recently denied in NASH with T2DM. The effects of pioglitazone on NASH histology with T2DM have extensively been established, but several concerns exist such as body weight gain, fluid retention, cancer incidence, and bone fracture. Glucagon-like peptide 1 (GLP-1) receptor agonists and sodium/glucose cotransporter 2 (SGLT2) inhibitors are expected to ameliorate NASH　(LEAN study, LEAD trial, and E-LIFT study). Among a variety of SGLT2 inhibitors, dapagliflozin have already entered phase 3 trials (DEAN study). A key clinical question is what kinds of anti-diabetic drugs are the most appropriate for the treatment of NASH to prevent progression of hepatic fibrosis resulting in HCC/liver-related mortality without increasing risk at cardiovascular or renal events. The combination therapies such as glucagon receptor agonist/GLP-1 or gastrointestinal peptide /GLP-1 will be under development. This review focuses on antidiabetic agents and future perspectives on the view of the treatment of NAFLD with T2DM.

Fiber-rich green river Aonori alga is mass-cultivated in Japan; it has been reported to reduce inflammation and improve metabolic health in humans. Peroxisome proliferation-activated receptor (PPARs) are associated with metabolic disorders such as obesity and type 2 diabetes (T2DM). We evaluated the effects of supplementation with NBF2, a formula made of algal and junos citrus biomaterials, on metabolic markers in obese and diabetic rats. An experimental study was performed using 18 obese and hyperglycemic Otsuka Long-Evans Tokushima Fatty (OLETF) rats randomly assigned to high dose NBF2 (20mg/kg; n=6), low dose (10mg/kg; n=6) NBF2 drink for 6 weeks, whereas OLETF control rats received similar amount of tap water (vehicle; n=6). LETO rats were used as normal controls (n=8). Biospecimens were taken for ELISA and real-time PCR. Both high dose and low dose NBF2 increased brown adipose tissue (BAT) mass and adiponectin (APN), improved insulin sensitivity, and significantly improved glycemic and lipid (TG, LDL-c) profiles in NBF2-supplemented OLETF rats after a 6-week supplementation with NBF2 (vs. OLETF controls), as well as LDL-c (p<0.05). During the glucose tolerance test (OGTT), both NBF2 groups and LETO rats had normal glycemia by 90-minute time-point (vs. OLETF controls; p<0.01). Furthermore, intake of NBF2 up-regulated PPARa/g-mRNA and Sirt2-mRNA gene expressions in BAT, and improved blood pressure profile in OLETF rats. Findings from this research suggest that intake of NBF2 formula induces dual PPAR-a/g and Sirt2 activation, providing insights on beneficial prophylactic and therapeutic effects of this NB2 formula on dyslipidemia and hyperglycemia in T2DM.

(1) Background: SARS-CoV-2 infection is mostly accompanied by mild COVID-19 symptoms in children. However, the multisystem inflammatory syndrome (MIS-C) and long-term sequelae are often severe complications. Therefore, the protection of the pediatric population against SARS-CoV-2 with effective vaccines is particularly important. Here we compare the humoral and cellular immune responses elicited in children (n=15) aged 5-11 years vaccinated with RBD-based vaccines combined in a heterologous scheme of SOBERANA® 02 and SOBERANA® Plus with those from children (n=10) aged 4-11 years who recovered from mild symptomatic COVID-19. (2) Methods: Blood samples were taken 14 days after last dose for vaccinated and 45-60 days after the infection diagnosis for COVID-19 recovered children. Anti-RBD IgG and ACE2-RBD inhibition were assessed by ELISA; IgA, cytokine and cytotoxic related proteins profile were determined by multiplex assays. Total B and T cell subpopulations and IFN-γ release were measured by multiparametric flow cytometry using a large panel of antibodies after in vitro stimulation with S1 peptides. (3) Results: Significant higher levels of specific anti-RBD IgG and IgA and ACE2-RBD inhibition capacity were found in vaccinated children in comparison to COVID-19 recovered children. Th1-like and Th2-like CD4+ T cells were also significantly higher in vaccinated subjects. IFN-γ secretion were higher in central memory CD4+ T cells of COVID-19 recovered children, but no differences between both groups were found in CD4+ and CD8+ T cells effector, terminal and naïve T cell subpopulations. High levels of IL-2, IL-6, IFN-γ and IL-10 in contrast to low levels of IL-4 suggesting a predominant Th1 cell polarization. Cytotoxic-related proteins granzyme A and B, perforin and granulin were also found in the supernatant after S1 stimulation in both vaccinated and recovered children. (4) Conclusions: Vaccination with the heterologous scheme of SOBERANA® 02/ SOBERANA® Plus induces strong antibody and cellular immune response compared to natural infections of young children.

β-cyclodextrin (CD) derivatives containing aromatic triazole ring were studied as potential carriers of drugs containing an anthraquinone moiety in the structure: anthraquinone-2-sulfonic acid (AQ2S), anthraquinone-2-carboxylic acid (AQ2CA) and a common anthracycline, daunorubicin (DNR). UV-Vis and voltammetry measurements were carried out to determine the solubilities and stability constants of the complexes formed and revealed the unique properties of the chosen CDs as effective pH dependent drug complexing agents. The stability constants of the drug complexes with the CDs containing triazole: βCDLip and βCDGAL were significantly larger than with the native βCD. The AQ2CA and AQ2S drugs are ill-soluble and their solubilities increased as the result of complex formation with βCDLip and βCDGAL ligands. AQ2CA, AQ2S were negatively charged at pH 7.4 and therefore they were less prone to form inclusion complex with the hydrophobic CD cavity than at pH 3 (characteristic of gastric juices) when they were protonated. βCDTriazole and βCDGAL ligands were found to form weaker inclusion complexes with the positively charged drug DNR at acidic pH (pH 5.5) than in the neutral medium (pH 7.4) when the drug dissociates to the neutral, uncharged form. This pH dependence is favorable for anti-tumor applications.

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the chief concern of the international community in almost no time. As of May 9th, 2021, more than 150 million cases and 3.2 million deaths have been recorded. Considering the early struggle in treating COVID-19 patients, the researchers and clinicians have decided to try the previously available drugs according to their mechanisms of action. Hence, many antivirals, antibiotics, antiparasitics, and antipyretics have been proposed. Pregnant women, fetuses, and infants are known high-risk populations that are threatened during disease outbreaks. Therefore, this article reviews the safety of potential drugs for COVID-19 patients during pregnancy and breastfeeding.

The role of the Renin-Angiotensin-Aldosterone System (RAAS) in Corona Virus Disease 2019 (COVID-19) infection has become a controversial topic of discussion. RAAS inhibitors, such as Angiotensin Converting Enzyme (ACE) inhibitors and Angiotensin II receptor blockers (ARBs), which are used to treat cardiovascular diseases, have been implicated in potentially increasing cell surface levels of ACE2. ACE2 is the host receptor for COVID-19 that was discovered in Wuhan, China in December 2019. Since December, COVID-19 has transmitted rapidly across the world and has become a global pandemic. COVID-19 is similar to the Middle East respiratory syndrome coronavirus (MERS-CoV) with the first case reported in Saudi Arabia in September 2012. COVID-19, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is also similar to SARS-CoV, which first infected humans in the Guangdong province of southern China in 2002, and caused an epidemic between November 2002 and July 2003. Both SARS-CoV and COVID-19 use ACE2 to enter host cells. ACE2 is primarily expressed in the mouth, lung, heart, esophagus, kidney, bladder, and intestines, and is a component of RAAS, which serves to maintain vascular tone and blood volume. Inhibition or activation of other components of RAAS has been shown to directly increase or decrease the expression and/or activity of ACE2. Furthermore, RAAS-targeting therapeutics, such as ACE inhibitors and ARBs, have also been shown to regulate the expression and/or activity of ACE2, albeit in animal models. Although these changes in ACE2 have been demonstrated only in animal models, there is no evidence that administration of RAAS-targeting therapeutics to humans for the treatment of hypertension, diabetes, and other cardiovascular diseases (e.g., myocardial infarction and heart failure) causes changes in ACE2 expression. Nor is there clinical evidence that RAAS-targeting therapeutics augment COVID-19 infection, morbidity, or mortality. However, clinical evidence does suggest that ACE2 expression may protect against respiratory distress caused by a variety of noxious agents. This review attempts to provide a balanced overview of the potential role of RAAS in regulating ACE2, and the role of ACE2 during COVID-19 infection. Evidence is provided to show that the expression of ACE2 may mediate both positive and negative outcomes, depending on the timing of ACE2 expression.

The aim of this research is to apply artificial intelligence (AI) methods, specifically artificial immune systems (AIS), in order to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD (Integral-Proportional Derivative) and PI-D (Proportional-Integral Derivative) control. The study results in a novel solution to the control synthesis problem for the industrial system. In particular, the research addresses the synthesis of I-P control for a two-loop system in the technological process of a distillation column. This synthesis is accomplished using the AIS algorithm, making it the first application of this technique to this specific context. Methodological approaches are proposed to enhance the performance of industrial multivariable control systems through effective utilization of optimization algorithms by establishing modified quality criteria. The problem of synthesis of multi-input multi-output (MIMO) control system is solved, taking into account the interconnections due to the decoupling procedure.

Background: The immunomodulatory role of 1,25-Dihydroxy vitamin D3 (1,25(OH)2D3) is exerted through its interaction with the Vitamin D receptor (VDR) present on pancreatic and immune cells. While a deficiency in Vitamin D has been linked to Type 1 Diabetes Mellitus (T1DM), the exact molecular mechanism driving this down-regulation in T1DM is yet to be fully understood. This study aimed to decipher differences in the expression of genes associated with Vitamin D metabolism in T1DM patients and to ascertain if there is a correlation between serum 1,25(OH)2D3 levels and the expression of these genes. We also sought to understand the influence of specific microRNAs (miRNAs) on the expression of Vitamin D metabolism genes in peripheral blood mononuclear cells (PBMCs) of T1DM patients. Furthermore, the study delved into the potential implications of altered Vitamin D metabolism genes and miRNAs on autoimmune processes. Methods: Utilizing real-time PCR, we assessed the expression profiles of genes encoding for 1-hydroxylases (CYP27B1) and 24-hydroxylases (CYP24A1), as well as related miRNAs, in PBMCs from 30 T1DM patients and 23 healthy controls. ELISA tests facilitated the measurement of 1,25(OH)2D3, GAD65, and IA-2 levels. Results: Our findings showcased down-regulated CYP27B1 mRNA levels, while CYP24A1 expression remained stable compared to healthy subjects (CYP27B1, p = 0.0005; CYP24A1, p = 0.205, respectively). In T1DM patients, the levels of has-miR-216b-5p were found to be increased, while the levels of has-miR-21-5p were decreased in comparison to the control group. Notably, no correlation was identified between the expression of CYP27B1 in T1DM patients and the levels of has-miR-216b-5p, has-miR-21-5p, and 1,25(OH)2D3. A significant negative correlation was identified between CYP27B1 mRNA levels in PBMCs of T1DM and IA2, but not with GAD65. Conclusions: The study highlights there were reduced levels of both CYP27B1 mRNA and has-miR-21-5p, along with elevated levels of has-miR-216b-5p in the PBMCs of T1DM. However, the absence of a correlation between the expression of CYP27B1, levels of has-miR-216b-5p, and the status of 1,25(OH)2D3 suggests the possible existence of other regulatory mechanisms. Additionally, the inverse relationship between IA2 autoantibodies and CYP27B1 expression in T1DM patients indicates a potential connection between this gene and the autoimmune processes inherent in T1DM.

Open-source 3-D printing has played a pivotal role in revolutionizing the additive manufacturing (AM) landscape, by making distributed manufacturing economic, democratizing access, and fostering far more rapid innovation than antiquated proprietary systems. Unfortunately, some 3-D printing manufacturing companies began deviating from open-source principles and violating licenses for the detriment of the community. To determine if a pattern has emerged of companies patenting clearly open-source innovations, this study presents three case studies from the three primary regions of open-source 3-D printing development (EU, U.S. and China) as well as three aspects of 3-D printing technology (AM materials, an open-source 3-D printer, and core open-source 3-D printing concepts used in most 3-D printers). The results of this review have shown that non-inventing entities called patent parasites are patenting open-source inventions already well-established in the open source community and in the most egregious cases commercialized by one (or several) firms at the time of the patent filing. Patent parasites are able to patent open-source innovations by using a different language, vague patent titles and broad claims that encompass enormous swaths of widely diffused open-source innovation space. This practice poses a severe threat to innovation and several approaches to irradicate the threat are discussed.

Plant-based diets are increasingly popular for health as well as financial, ethical, and religious reasons. The medical literature clearly demonstrates that plant-based diets can be both nutritionally sufficient and medically beneficial. However, any person on an intentionally restrictive but poorly-informed diet may predispose themselves to clinically-relevant nutritional deficiencies. For persons on a poorly-informed plant-based diet, deficiencies are possible in both macronutrients (protein, essential fatty acids) and micronutrients (vitamin B12, iron, calcium, zinc and vitamin D). Practitioner evaluation of symptomatic patients on a plant-based diet requires special consideration of 7 key nutrient concerns for plant-based diets. This article translates these concerns into 7 practical questions that all practitioners can introduce into their patient assessments and clinical reasoning. Ideally, persons on plant-based diets should be able to answer these 7 questions. Each serves as a heuristic prompt for both clinician and patient attentiveness to a complete diet. As such, these 7 questions support increased patient nutrition knowledge and practitioner capacity to counsel, refer, and appropriately focus clinical resources.

Cryptosporidiosis is a major human health concern globally. Despite well-established methods, misdiagnosis remains common. Our understanding of the cryptosporidiosis biochemical mechanism remains limited, compounding the difficulty of clinical diagnosis. Here, we used a systems biology approach to investigate the underlying biochemical interactions in C57BL/6J mice infected with Cryptosporidium parvum. Faecal samples were collected daily following infection. Blood, liver tissues and luminal contents were collected 10 days post infection (dpi). High-resolution liquid chromatography and low-resolution gas chromatography coupled with mass spectrometry were used to analyse the proteomes and metabolomes of these samples. Faeces and luminal contents were additionally subjected to 16S rRNA gene sequencing. Univariate and multivariate statistical analysis of the acquired data illustrated altered host and microbial energy pathways during infection. Glycolysis/citrate cycle metabolites were depleted, while short-chain fatty acids and D-amino acids accumulated. An increased abundance of bacteria associated with a stressed gut environment was seen. Host proteins involved in energy pathways and Lactobacillus glyceraldehyde-3-phosphate dehydrogenase were upregulated during cryptosporidiosis. Liver oxalate also increased during infection. Microbiome-parasite relationships were observed to be more influential than the host-parasite association in mediating major biochemical changes in the mouse gut during cryptosporidiosis. Defining this parasite-microbiome interaction is the first step towards building a comprehensive cryptosporidiosis model towards biomarker discovery, and rapid and accurate diagnostics.

Age-related hearing loss (ARHL) is the most common sensory disorder in the elderly. It is associated with aging and hair cell death due to oxidative stress-induced mitochondrial dysfunction. Although transgenic mice and long-term cultures for induction of aging have been used to study ARHL, there are presently no ARHL animal models stimulated by intermittent environmental change for aging. In this study, an ARHL animal model was established by inducing continuous oxidative stress to promote short-term aging of cells, determined based on the expression of the hearing loss-induced phenotype and aging related factors in the short term. The incidence of hearing loss was significantly different among the groups subjected to intermittent hypoxic environment, high-fat diet (HFD), and injection with D-galactose. Continuous oxidative stress and HFD were factors that accelerated cellular aging. Increase in UCP2 affected oxidative stress and mitochondrial dysfunction. CDH23, SLC26A4, KCNQ4, Myo7a, and Myo6, which are ARHL-related factors, were modified by oxidative stress in cells of the hearing organ. We found that intermittent hypoxic, HFD, and galactose injection accelerated cellular aging in the short term. Thus, we anticipate that the development of this hearing loss animal model, which reflects intermittent environmental changes, will benefit future research on ARHL.

Public health practices including handwashing and vaccinations help reduce the spread and impact of infections. Nevertheless, the global burden of infection is high, and additional measures are necessary. Acute respiratory tract infections, for example, are responsible for approximately 2.65 million deaths per year. The role nutrition plays in supporting the immune system is well-established. A wealth of mechanistic and clinical data show that vitamins, including vitamins A, B6, B12, C, D, E, and folate; trace elements, including zinc, iron, selenium, magnesium, and copper; and the omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid play important and complementary roles in supporting the immune system. Inadequate intake and status of these nutrients are widespread, leading to a decrease in resistance to infections and as a consequence an increase in disease burden. Against this background the following conclusions are made: 1) Supplementation with the above micronutrients and omega-3 fatty acids is a safe, effective, and low-cost strategy to help support optimal immune function; 2) Supplementation above the RDA, but within recommended upper safety limits, for specific nutrients such as vitamins C and D is warranted; and 3) Public health officials are encouraged to include nutritional strategies in their recommendations to improve public health.

Diabetes and mental disorders have been recognized as two significant public health concerns globally. Recent research indicates that there is a bidirectional relationship between these two conditions, with each influencing the other's course and outcomes. Nutrition plays an essential role in the prevention and treatment of both mental disorders and diabetes. A comprehensive review of existing literature was conducted to examine the impact of anxiety and depression on the development of diabetes and the influence of diabetes on the occurrence of mental health disorders such as anxiety and depression. Additionally, the effects of nutrition on the prevention and management of mental disorders, diabetes, and related complications in at risk individuals were assessed. Our findings show that mental disorders, such as depression and anxiety increase the risk of developing type 2 diabetes and are associated with poorer glycemic control, increased diabetes-related complications, and higher mortality rates. Conversely, diabetes is also linked with an increased risk of developing mental health disorders, including depression, anxiety, and cognitive decline. The biological, psychological, and social factors that contribute to the comorbidity between these two conditions are complex and multifaceted. Therefore, an integrated approach to the management of both conditions is critical for improving patient outcomes and reducing the overall burden of disease. Nutritional interventions should be utilized to reduce the risk of diabetes in patients with anxiety and depression as well as enhance mental health in patients with diabetes.

Background: Obesity among pregnant women is common, and their offspring are predisposed to obesity, insulin resistance, and diabetes. Circulating metabolites that are related to insulin resistance and are associated with this decreased tissue-specific uptake are unknown. Here, we assessed metabolite profiles in elderly women and who were either female offspring from obese mothers (OOM) or offspring of lean mothers (OLM). Metabolic changes were tested for associations with metrics for insulin resistance. Methods: 37 elderly women were separated into an elderly offspring from obese mothers (OOM; n = 17) and elderly offspring from lean/normal weight mothers (OLM; n = 20) groups. We measured plasma metabolites using 1H-NMR and also insulin-dependent tissue specific glucose uptake in skeletal muscle were assessed. Associations were made between metabolites and glucose uptake. Results: Compared to the OLM group, we found that the 22:6 docosahexaenoic acid percentage of the total long chain n-3 fatty acids (DHA/FA) was significantly lower in OOM (P = 0.015). DHA/FA associated significantly to skeletal muscle GU (P = 0.031) and M-value in the OLM group only (P = 0.050). Conclusions: DHA/FA is associated with insulin-dependent skeletal muscle glucose uptake and that this association is significantly weakened in the offspring of obese mothers.

The pandemic caused by SARS-CoV-2 is still a major health problem. Newly emerging variants and long-COVID-19 represent a challenge for the global health system. In particular, individuals in developing countries with insufficient health care need easily accessible, affordable and effective treatments of COVID-19. Previous studies have demonstrated the efficacy of functional inhibitors of acid sphingomyelinase (FIASMA) against infections with various viruses, including early variants of SARS-CoV-2. This work investigated whether the acid sphingomyelinase inhibitors fluoxetine and sertraline, usually used as antidepressant molecules in clinical practice, can inhibit the replication of the former and recently emerged SARS-CoV-2 variants in vitro. Fluoxetine and sertraline potently inhibited the infection with pseudotyped virus like particles and SARS-CoV-2 variants D614G, alpha, delta, omicron BA.1 and omicron BA.5. These results highlight fluoxetine and sertraline as priority candidates for large-scale phase 3 clinical trials at different stages of SARS-CoV-2 infections, either alone or in combination with other medications.

New antiviral agents are essential to improving treatment and control of SARS-CoV-2 infections that can lead to the disease COVID-19. Antimicrobial peptoids are sequence-specific oligo-N-substituted glycine peptidomimetics that emulate the structure and function of natural antimicrobial peptides but are resistant to proteases. We demonstrate antiviral activity of a new peptoid (TM9) against the coronavirus, murine hepatitis virus (MHV), as a closely related model for the structure and antiviral susceptibility profile of SARS-CoV-2. This peptoid mimics the human cathelicidin LL-37, which has also been shown to have antimicrobial and antiviral activity. In this study TM9 was effective against three murine coronavirus strains, demonstrating the therapeutic window is large enough to allow use of TM9 for treatment. All three isolates of MHV generated infection in mice after 15 min of exposure by aerosol using the Madison aerosol chamber and all three viral strains could be isolated from the lungs throughout the 5-day observation period post-infection, with the peak titers on day 2. MHV-A59 and MHV-A59-GFP were also isolated from liver, heart, spleen, olfactory bulbs, and brain. These data demonstrate that MHV serves as a valuable natural murine model of coronavirus pathogenesis in multiple organs, including the brain.

Diabetes mellitus, a chronic metabolic disorder characterized by hyperglycemia, presents a formidable global health challenge with its associated complications. Adiponectin, an adipocyte-derived hormone, has emerged as a significant player in glucose metabolism and insulin sensitivity. Beyond its metabolic effects, adiponectin exerts anti-inflammatory, anti-oxidative, and vasoprotective properties, making it an appealing therapeutic target for mitigating diabetic complications. The molecular mechanisms by which adiponectin impacts critical pathways implicated in diabetic nephropathy, retinopathy, neuropathy, and cardiovascular problems are thoroughly examined in this study. In addition, we explore possible treatment options for increasing adiponectin levels or improving its downstream signaling. The multifaceted protective roles of adiponectin in diabetic complications suggest its potential as a novel therapeutic avenue. However, further translational studies and clinical trials are warranted to fully harness the therapeutic potential of adiponectin in the management of diabetic complications. This review highlights adiponectin as a promising target for the treatment of diverse diabetic complications and encourages continued research in this pivotal area of diabetes therapeutics.

COVID-19 pandemic outbreak challenged the global public health in last couple of years. Throughout the pandemic period, numbers of mutant strains of SARS- CoV-2 created challenges for the infected patients with diverse pathophysiology and immune response. Variant of Concern (VOC) alpha (B.1.1.7), delta (B.1.617.2) and omicron (B.1.1.529) grew most notable for causing the epidemiological manifestations, which eventually caused elevated infectivity resulting in significant mortality. This review indicates the comparative analysis of the immune-pathophysiological mechanisms in respect to the aforementioned strains of SARS-CoV-2.

Accurate fuel mapping plays a crucial role in fire detection and management strategies. This paper presents a method for discriminating between wildfire fuel types by exploiting together remote sensing data and Convolutional Neural Networks (CNN). Specially, a CNN-based classification approach that leverages Sentinel-2 imagery is exploited to accurately classify fuel types into seven preliminary main classes (conifers, broadleaf, shrubs, grass, bare soil, urban areas, and water bodies) with an high accuracy of 0.99$\%$. To further refine the fuel mapping results, subclasses were generated from the seven principals by using biomass and bioclimatic maps. These additional maps provide complementary information about vegetation density and climatic conditions, respectively. By incorporating this information, we align our fuel type classification with the widely used Scott/Burgan fuel classification system. This refinement step allows for a more detailed and comprehensive assessment of fuel types, enhancing the accuracy and effectiveness of fire management efforts, which can be utilized by fire management agencies, policymakers, and researchers for improved fire behavior prediction and mitigation practices. The proposed approach presents a valuable tool for enhancing fire management, contributing to more effective wildfire prevention and mitigation efforts.

A large population has been infected by COVID-19 (Coronavirus disease-19) and it has been necessary a rapid and simple diagnostic method to detect the SARS-CoV-2and control its spread. We developed a colorimetric reverse transcription-loop-mediated isothermal amplification (RT-LAMP) kit that allow the detection of SARS-CoV-2 from nasopharyngeal swab samples without the need of RNA extraction. The kit utilizes three sets of LAMP primers targeting two regions of ORF1ab and one region in the E gene. The results are reported using colorimetric change of hydroxynaphthol blue, enabling visual interpretation without the need for expensive instrument. The kit demonstrated sensitivity to detect between 50 and 100 copies of the viral genome per reaction. The kit was authorized by the National Administration of Drugs, Food and Technology (ANMAT) of Argentina after validation using samples previously analyzed by gold standard RT-qPCR. The results showed sensitivity of 90,6 % and specificity of 100%, consistent with conventional RT-qPCR. In silico analysis confirmed the recognition of SARS-CoV-2 Variants of Concern (VOCs) B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.427, B.1.429and lineages of variant Omicron (B.1.1.529) with 100% homology. This rapid, simple, and sensitive RT-LAMP method paves a way for a large screening strategy to be carried out at locations lacking sophisticated-instrumental and trained-staff, as particularly happen at regional hospitals and medical centers from rural areas.

We provide a summary of various epidemiological parameters related to COVID-19 such as incubation period, serial interval and other parameters. Understanding these parameters is important for developing prevention strategies. SARS-CoV-2 can be transmitted by droplets and close contact, but there is evidence of airborne transmission. Aerosol-generating procedures have been identified as one of the specific risk factors for healthcare workers. Super-spreading events refer to situations where a small number of individuals cause the majority of infections. The basic reproductive number (R0) and the spread parameter (k) are used to characterise the transmissibility of the disease. Estimated values for R0 range from 2 to 3 and the estimated value for k is 0.1.The duration of infectiousness depends on viral load and shedding. Viral load varies according to factors such as clinical spectrum, type of variant and vaccination status. The relationship between viral load and infectivity is not fully understood.With regard to the frequency of symptoms and signs of COVID-19, fever, cough, fatigue and dyspnoea are common. The prevalence of olfactory and gustatory dysfunction (OGD) varies between studies and countries. Age and comorbidities are factors associated with olfactory dysfunction.Estimates of the proportion of asymptomatic patients range from 6% to 96%. Asymptomatic transmission is considered likely and is important for control measures.We reviewed the quantitative semiology of COVID-19 is reported on sensitivity, specificity and likelihood ratios of signs.Finally, we also review risk factors for COVID-19 (including health care workers), co-infections, and epidemiology of variants..

SARS-CoV-2 pandemic caused an increase in Intensive Care Unit (ICU) hospitalizations with rise in morbidity and mortality; nevertheless, there is still little evidence of pandemic impact on antibiotic resistance in ICU. Retrospective monocentric epidemiological study. All microorganisms isolated from all patients admitted to E.O. Galliera ICU from January 2018 to December 2022 were included. Antibiotic resistance (AR) profiles were evaluated. Aim of the study was to describe and analyze the impact of SARS-CoV-2 pandemic on ICU microorganisms resistance patterns. 1,771 microorganisms identified, 221 (12.47%) had resistant pattern (Resistant Organisms; ROs) isolated from 1,679 patients during 12,030 hospitalization days. The majority of ROs were Gram-negative (79.66% 2018, 77.29% 2019, 61.83% 2020, 62.56% 2021, 60.75% 2022), but increase of Gram-positive microorganisms was observed (20.34% to 39.25% between 2018-2022). Prevalence of AR was: 19.44% 2018, 11.54% 2019, 38.04% 2020, 34.15% 2021, 39.29% 2022 for Gram-positives; 19.86%, 13.56%, 18.12%, 12.41%, 12.31% for Gram-negatives. Incidence of Ros showed COVID-related rise in 2020-2021, followed by a lowering trend since 2021, with new rise in 2022. Possible explanations are antibiotic overtreatment and drop of containing measures. Interesting finding is the cumulative lowering trend of carbapenem resistant K. pneumoniae and P. aeruginosa probably due to different patient features.

Introduction SARS-CoV-2 infection normally damages respiratory system but may likewise impair endocrine organs’ function. Thyroid dysfunction and hyperglycemia are common endocrine complications of SARS-CoV-2 infection. Onset of T1D and associated complications including DKA, hospitalization and death, are thought to be increased during the COVID-19 pandemic. The aim of this study is to review the available data about the incidence rate of T1D and accompanying complications since the beginning of the COVID-19 pandemic. Methods: A systematic review was conducted using electronic databases PubMed and Google Scholar. The keywords “T1D, T1DM, Type 1 DM or Type 1 Diabetes”, “Coronavirus, SARS-CoV-2 or COVID-19” were used to search these databases. Titles and abstracts were screened for selection, and then relevant studies were reviewed in full text. Result: we selected 21 manuscripts out of 296 identified studies. Data about the incidence rate of T1D, hospitalization and death are not consistent across countries, but DKA incidence and severity seem to be higher during the COVID-19 pandemic. Conclusion: Our data collection demonstrated that COVID-19 may or may not increase the incidence of type 1 diabetes. Nevertheless, it is associated with higher incidence and severity of DKA in T1D patients. Antivirals are not fully protective against endocrine complications of SARS-CoV-2 infection. Combining medications that reduce SARS-CoV-2 entry into the cells and modulate the immune response to infection is an alternative practical approach to treating COVID-19.

The recent global emergence of the SARS-CoV-2 pandemic has accelerated research in several areas of science whose valuable outputs and findings can help to address future health challenges in the event of emerging infectious agents. We performed a multifocus shotgun analysis to compare differences in bacterial spectrum and viral presence through culture-independent RNA sequencing. We compared the microbiome of healthy people versus those with varying degrees of COVID-19 severity. We observed a significant increase in the diversity of microbial species in patients with COVID-19 regardless of disease severity. Some bacterial phyla, such as Actinobacteria, are significantly more abundant in healthy people than in infected people, whereas Bacteroides are less abundant in the latter. Infected people, regardless of severity and symptoms, have the same proportional representation of Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteriales the same. In addition to SARS-CoV-2 and numerous phage groups, we identified sequences of clinically significant viruses such as Human Herpes Virus 1, Human Mastadenovirus D, Molluscum Contagiosum Virus, and Rhinovirus A in several samples. Analyses were performed retrospectively, therefore, in the case of SARS-CoV-2 various WHO variants such as Alpha (B.1.1.7), Delta (B.1.617.2), Omicron (B.1.1.529), and 20C strains are represented. Additionally, the presence of specific virus strains has a certain effect on the distribution of individual microbial taxa.

The Mont-Saint-Michel is known worldwide for its unique combination of the natural site and the Medieval abbey at the top of the rocky islet. But the Mont is also located within an estuarine complex, which is considerably silting up. For two decades, large-scale works were planned to prevent the Mont from being surrounded by the expanding salt meadows. The construction of a new dam over the Couesnon River, the digging of two new channels, and the destruction of the causeway were the main operations carried out between 2007 and 2015. The remote sensing approach is fully suitable for evaluating the real impact of the engineering project in both time and space, particularly the expected large-scale hydrosedimentary effects, for reestablishing the maritime landscape around the Mont. Sentinel-2 satellite data have been used for the period from 2015 to 2023. Aster data were used for the previous period covering 2000 to 2017. Aerial photographs and an ALOS scene have been also used. The remote sensing approach is based on time-series images. It allows identifying local or regional consequences and temporary or permanent effects. The migration of the different channels (especially for the new west and east Couesnon river courses) and the erosion-progradation balance of the vegetation through space and time are the main features to study. Between 2007 and 2023, the erosion of the salt meadows is significant to the south-west of the Mont (− 150 ha) but more limited to the south-east (− 65 ha). The erosion effect is limited to the immediate environment because the vegetation fringe of the uppermost tidal flat along the main dike is slightly increasing (+ 35 ha) to the west and to the east (+ 40 ha). During the same period, the sedimentation considerably increased to the north-east of the Bay, between the Bec d’Andaine, the Grouin du Sud and Tombelaine islet, which seems now facing the same silting-up problem. At this stage, the remote-sensing survey indicates mixed results for the engineering project.

Among cross-sectional imaging modalities, computed tomography (CT) is more available and faster; however, magnetic resonance (MR) performs better in terms of sensitivity and specificity, due to its higher contrast resolution. The appearance of peritoneal deposits on CT and MR depends mainly on the primary tumour histology: in case of unknown primary tumour (3-5% of cases), their behaviour at imaging may provide insights on the tumour origin. The time-point of tumour evolution, previous or ongoing treatments and the peritoneal spaces where they occur, also play an important role in determining the appearance of peritoneal deposits. Thus, knowledge of peritoneal anatomy and fluid circulation is mandatory in detection and characterization of peritoneal deposits. Several benign and malignant conditions may show similar imaging features that overlap those of PC, making the differential diagnosis challenging. Clinical history, laboratory findings and previous imaging examinations must be considered to achieve the correct diagnosis.

The COVID-19 pandemic has had a major impact on health systems around the globe and Romania is no exception. The impact on healthcare expense for pregnant women has been considerable, especially in COVID-only tertiary centers, where specialized care is being provided .The aim of this study is to analyze the impact of SARS-CoV-2 infection on healthcare costs, in particular by managing cases in COVID-only maternity. Material and Methods: The objective of the study was to analyze if the model adopted by the health system consisting in complete separation of delivering obstetrical care for covid and non-covid patients was efficient. We conducted an observational study in which we compared a group of pregnant women infected with SARS-CoV-2 (study group) with a control group in which we included uninfected pregnant women. The patients were recruited from Bucur Maternity Hospital, declared a COVID-only center in march 2020. We compared the two groups in terms of expenses over the entire period of hospitalization, i.e. expense on hospitalization, medicines, medical supplies, and medical investigations.

The COVID-19 pandemic has been challenging for society, especially for those residing in long-term care facilities (LTCF). This study aimed to describe rates of infection, hospitalization, and death due to COVID-19 among older people and staff of LTCF in a state of Southeastern Brazil and identify strategies to prevent and control the disease spread. This cross-sectional study was conducted with 164 LTCF (6,017 older people). Among the studied LTCF, 48.7% confirmed COVID-19 infection in older people, resulting in 39.6% hospitalization and 32.3% death among infected. Moreover, 68.9% of LTCF confirmed COVID-19 infection in the staff, with 7.3% hospitalization and 1.2% death. Preventive measures were identified and classified as organizational, infrastructure, hygiene items and personal protective equipment, and staff training against COVID-19. These measures showed strategies and barriers experienced in the daily routine of LTCF during the pandemic. LTCF in Brazil experienced challenges similar to observed worldwide.

Patients with COVID-19 demonstrate higher rates of cardiovascular complications, including thromboses and thromboembolism. One may suppose that the action of SARS-CoV-2 transforms stable atherosclerotic plaques into unstable status. Cardiovascular complications in COVID-19 may be caused by progressive viral alteration the blood vessels, including vasa vasorum. A lethal case of ischemic brain disease caused by cerebral atherosclerosis and exacerbated with a stroke during COVID-19 infection is briefly described. The results of autopsy showed perivascular lymphocytic infiltration and signs of vasa vasorum vasculitis with thrombi of adventitial microvasculature. The data discussed in the article are interpreted in context of the concept giving the important role in atherogenesis to vasa vasorum.

Background: Repeated SARS-CoV-2 infections are plausible and related published data are scarce. We aimed to identify factors associated with the risk of recurrent (three episodes) laboratory-confirmed symptomatic SARS-CoV-2 infections. Methods: A retrospective cohort study was conducted and 1,700 healthcare workers were enrolled. We used risk ratios (RR) and 95% confidence intervals (CI) to evaluate factors associated with symptomatic SARS-CoV-2 infections. Results: We identified 14 participants with recurrent illness episodes. Therefore, the incidence rate was 8.5 per 10,000 person-months. In multiple model, vaccinated adults (vs. unvaccinated, RR = 1.05 [1.03 - 1.06]) and those with a severe first illness episode (vs mild disease, RR = 1.05 [1.01 - 1.10]) were at increased risk for repeated symptomatic SARS-CoV-2 reinfections. Increasing age showed a protective effect (per each additional year of age: RR = 0.98 [0.97 - 0.99]). Conclusions: Our results suggest that recurrent SARS-CoV-2 infections are rare events in adults and they seem to be determined, partially, by vaccination status and age.

The COVID-19 pandemic has highlighted the importance and urgent need of rapid and accurate diagnostic tests for detection and screening of this infection. In our proposal, a biosensor based on the ELISA immunoassay was developed for monitoring antibodies against SARS-CoV-2 in human serum samples. The SARS-CoV-2 nucleocapsid protein (N-protein) was selected as a specific receptor for the detection of SARS-CoV-2 nucleocapsid immunoglobulin G. Thus, the N-protein was immobilized on surface of screen-printed carbon electrode (SPCE) modified with carboxylated graphene (CG). The IgG-SARS-CoV-2 nucleocapsid concentration was quantified using a secondary antibody labelled with horseradish peroxidase (HRP) (anti-IgG-HRP) catalyzed by 3,3’,5,5’-tetramethylbenzidine (TMB) mediator by chronoamperometry. A linear response was obtained in the range of 1:1000-1:200 v/v in phosphate buffer solution (PBS) and the limit of detection calculated was of 1:4947 v/v. The chronoamperometric method showed electrical signals directly proportional to antibody concentrations due to Ag-Ab specific and stable binding reaction.

Viral variant analysis is a bedrock of the disease surveillance. When combined with temporospatial analysis variant analysis can further the knowledge of disease spread in a study area. This paper suggests a method to perform the analysis in an operational setting which will allow for real-time surveillance of viral variants and allow local public health professionals to rapidly respond to changes in the evolution of the disease. This method includes three main subprocesses: preprocessing, analysis, and rendering. This method can be performed across multiple software platforms. A use case is given in which it was found that this method helped a hospital system understand the spread of SARS-CoV-2 in Northeast, Ohio.

The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), etiological agent of the novel coronavirus disease 2019 (COVID-19), has spread since December 2019, resulting in massive health and economic crisis worldwide. While efforts to stop the pandemic are crucial, collecting epidemiological data to help manage current and future pandemics will be important. In addition to humans, serological and molecular based studies have demonstrated SARS CoV-2 exposure in several wild, domestic and farmed animals. For examples Shriner and the team showed serologically an exposure of 40% to the white deer living in close proximity to urban centers. Additional reports have also emerged of susceptibility of animal’s species like cats, ferrets, raccoon dogs, cynomolgus macaques, rhesus macaques, white-tailed deer, rabbits, Egyptian fruit bats, and Syrian hamsters to SARS-CoV-2 infection.. It’s worth emphasizing that these reports are based on experimental data mostly derived from Europe, USA, South America and parts of Asia. In limited instances natural infections of SARS-CoV-2 have been reported in pet dogs, cats, tigers, lions, snow leopards, pumas, gorillas at zoos and farmed mink and ferrets. The presence of the virus in animal species and an understanding of whether these are natural or recent human to animal transmissions is important. It’s possible that such transmission could passage the virus or subject the virus to a different immunological pressure thereby helping with the development of viral variants in addition to being a host for future reservoirs of the virus. In Kenya SARS-CoV-2 was first detected on March 12th 2020 from imported human cases of persons who had travelled from the United States. This was followed by detection of imported cases majorly from China, Sweden and United Kingdom. Later infections were confirmed in Nairobi and Mombasa suggesting further cases of disease importations through the major ports of entry. However, no comparable data on animal exposure have hitherto been generated in Kenya. To address this key concern, we focused on three objectives; 1) development of a robust antibody ELISA based on crude SARS-CoV-2 lysate. 2) SARS-CoV-2 serology of domestic animals in Kenya. 3) Corroboration of the crude lysate based seroprevalence data and a commercial ELISA kit based on the Spike receptor binding domain (RBD) antigen. Our sample set included camel sera (both pre- & post outbreak sera), as well as sera from cats and dogs collected at the peak of the pandemic. Our results using the ELISA based on crude SARS-CoV-2 lysate indicated SARS-CoV-2 antibodies in camels (71%, N=145), cats 11% (N=16) and dogs (81%, N=36) with varying titer levels. These findings were comparable to those obtained using the commercial ELISA kit based on the spike RBD antigens. In summary, the data warrants two key conclusions: (i) we have demonstrated that the crude lysate ELISA allows for SARS-CoV-2 antibody detection, and given its potential to offer robust detection could be applied for initial mass screening (ii) although the current study cannot disentangle the relative contributions of antigenic cross-reactivity, pre-pandemic exposure to SARS-CoV-2 or human-animal transmission, it nonetheless demonstrates for the first time the prevalence of SARS-CoV-2 like antibodies in domestic and wild animals in Kenya. Our findings set the scene for further research into the prevalence of SARS-CoV-2 in domestic and wild animals to understand their potential epidemiological implications.

Background: The isoflurane minimum alveolar concentration (MAC) was measured in rats chronically treated with WIN 55,212-2. Methods: The isoflurane MAC was determined in 24 male rats from the end expiratory samples at time of tail clamping under the following conditions: without treatment (MACISO), in rats treated for 21 days with WIN 55,212-2 (MACISO+WIN55) and other group 8 days after stopping treatment for 21 days with WIN 55,212-2 (MACISO+WIN55+8D). Results: The MACISO was 1.32 ± 0.06. In the MACISO+WIN55 group the MAC increase to 1.69 ± 0.09 (28%). After 8 days stopping treatment, MAC did not decrease significantly 1.67 ± 0.07 (26%). Conclusions: The administration for 21 days of WIN 55,212-2 increases the MAC of isoflurane in rats; this effect does not disappear after 8 days of discontinuing treatment with the synthetic cannabinoid.

Background The World Health Organization has recently recognized Long COVID, calling the international medical community to strengthen research and comprehensive care of patients with this condition. However, if Long COVID pertains to children as well is not yet clear. Methods An anonymous, online survey was developed by an organization of parents of children suffering from persisting symptoms since initial infection. Parents were asked to report signs and symptoms, physical activity and mental health issues. Only children with symptoms persisting for more than four weeks were included. Results 510 children were included (56.3% females) infected between January 2020 and January 2021. At their initial COVID-19 infection, 22 (4.3%) children were hospitalized. Overall, children had persisting COVID-19 for a mean of 8.2 months (SD 3.9). Most frequent symptoms were: Tiredness and weakness (444 patients, 87.1% of sample), Fatigue (410, 80.4%), Headache (401, 78.6%), Abdominal pain (387, 75.9%), Muscle and joint pain (309, 60.6%), Post-exertional malaise (274, 53.7%), rash (267, 52.4%). 484 (94.9%) children had had at least four symptoms. 129 (25.3%) children have suffered constant COVID-19 infection symptoms, 252 (49.4%) have had periods of apparent recovery and then symptoms returning, and 97 (19.0%) had a prolonged period of wellness followed by symptoms. Only 51 (10.0%) children have returned to previous levels of physical activity. Parents reported a significant prevalence of Neuropsychiatric symptoms. Conclusions Our study provides further evidence on Long COVID in children. Symptoms like fatigue, headache, muscle and joint pain, rashes and heart palpitations, and mental health issues like lack of concentration and short memory problems, were particularly frequent and confirm previous observations, suggesting that they may characterize this condition. A better comprehension of Long COVID is urgently needed..

Prevention practices have been extensively used to contain the spread of the SARS-CoV-2 virus. These include social distancing, wearing masks, disinfection of hands, and sanitization of contact surfaces. However, the excessive usage of chemical disinfectants pose long term adverse effects to human health and the environment. Development of effective and environmentally friendly biocides, or virucidal agents, will help mitigate the ill effects of chemical disinfectants. Enzymes are potential candidates for the preparation of biocides against bacteria and viruses. Exploration of the virucidal activity of commercial enzymes, will highlight prospective, readily available sources for research on enzyme based biocides. In this study, the virucidal effect of some com-mercial enzyme preparations has been investigated against the SARS-CoV-2 virus. Vida Defense (2000 µg/ml), Excellacor (1500 µg/ml), and SEBkinase (3000 µg/ml) reduced SARS-CoV-2 viral ti-ters by ≥1 log CCID50 (≥90%). ImmunoSEB (6000µg/ml) and Peptizyme SP (500µg/ml) reduced the SARS-CoV-2 viral titers by 0.8 log CCID50 (84.2%). The study indicates that enzyme prepara-tions offer the potential to be explored further for an anti-viral biocide against SARS‐CoV‐2 for reducing the risk of COVID‐19 transmission. However, further studies are mandated to improve efficacy and establish safety.

Background: Coronavirus disease (COVID-19) has caused more than 745,000 deaths worldwide. Vitamin D has been identified as a potential strategy to prevent or treat this disease. The purpose of the study was to measure vitamin D at hospital admission of COVID-19; Methods: We included critically ill patients with the polymerase chain reaction positive test for COVID-19, from March to April, 2020. Statistical significance was defined as P &lt; .05. All tests were 2-tailed; Results: A total of 35 patients (median age, 60 years; 26 [74.3%] male) were included. Vitamin D levels were categorized as deficient for 14 participants (40%). Vitamin D deficiency was associated with vitamin A (P= 0.003) and Zinc (P= 0.019) deficiency and lower levels of albumin (P= 0.026) and prealbumin (P= 0.009). Overall, none of the studied variables were associated with vitamin D status: mortality, intensive care unit (ICU) or hospital stay, necessity of vasoactive agents, intubation, prone position, C reactive protein (CRP), Dimer-D, Interleukin 6 levels (IL-6), ferritin levels, or bacterial superinfection; Conclusions: In this single-center, retrospective cohort study, deficient vitamin D status was found in 40% in COVID-19 critically ill patients. However, deficient vitamin D status was not associated with inflammation or outcome.