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Abstract The Druze are a distinct group known for their close community, traditions, and consanguineous marriages, dating back to the eleventh century. This practice has led to unique genetic variations, impacting both pathology and gene-associated phenotypes. Some Druze clans, particularly those with exceptional long-lived family heads (ELLI), attracted attention. Given that the bulk of these ELLI were men, the d3GHR polymorphism was the first obvious possibility. Among the 73 clan members, 8.2% carried the d3GHR isoform, with nearly 11% being males. There was a significant age-related increase (p = 0.04) in this isoform among males, leading to examination of potential environmental mediators affecting gene regulation among these carriers during life (namely epigenetic). We focused on DNA methylation due to its crucial role in gene regulation, development, and disease progression. We analyzed DNA samples from 14 clan members with different GHR genotypes, finding a significant (p

Abstract The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from pleiotropic segregating variants. We tracked allele frequency changes as a function of viability across different age bins and prioritized 34 variants with an immediate implication on lipid metabolism, body mass index (BMI), and cognitive performance, among other traits, revealed by PheWAS analysis in the UK Biobank. Given the highly complex and non-linear interactions between the genetic determinants of longevity, we reasoned that a composite polygenic score would approximate a substantial portion of the variance in lifespan and developed the integrated longevity genetic scores (iLGSs) for distinguishing exceptional survival. We showed that coefficients derived from our ensemble model could potentially reveal an interesting pattern of genomic pleiotropy specific to lifespan. We assessed the predictive performance of our model for distinguishing the enrichment of exceptional longevity among long-lived individuals in two replication cohorts (the Scripps Wellderly cohort and the Medical Genome Reference Bank (MRGB)) and showed that the median lifespan in the highest decile of our composite prognostic index is up to 4.8 years longer. Finally, using the proteomic correlates of iLGS, we identified protein markers associated with exceptional longevity irrespective of chronological age and prioritized drugs with repurposing potentials for gerotherapeutics. Together, our approach demonstrates a promising framework for polygenic modeling of additive liability conferred by ARTs in defining exceptional longevity and assisting the identification of individuals at a higher risk of mortality for targeted lifestyle modifications earlier in life. Furthermore, the proteomic signature associated with iLGS highlights the functional pathway upstream of the PI3K-Akt that can be effectively targeted to slow down aging and extend lifespan.

Abstract The emerging technique of neutral beam microscopy offers a non-perturbative way of imaging surfaces of various materials which cannot be studied using conventional microscopes. Current neutral beam microscopes use either diffractive focusing or pin-hole scanning to achieve spatial resolution, and are characterised by a strong dependence of the imaging time on the required resolution. In this work we introduce an alternative method for achieving spatial resolution with neutral atom beams which is based on manipulating the magnetic moments of the beam particles in a gradient field, and is characterised by a much weaker dependence of the imaging time on the image resolution. The validity of the imaging approach is demonstrated experimentally by reconstructing one dimensional profiles of the beam which are in good agreement with numerical simulation calculations. Numerical simulations are used to demonstrate the dependence of the signal to noise on the scan resolution and the topography of the sample, and assess the broadening effect due to the spread of velocities of the beam particles. The route towards implementing magnetic encoding in high resolution microscopes is discussed.

The Growth Hormone Receptor (GHR) gene encodes a protein that is essential for mediating the biological effects of growth hormone (GH). A series of molecular events are set off when GH binds to its receptor, resulting in a variety of physiological reactions linked to development, growth, and metabolism. Recently a particular genetic variation, within the GHR gene that is labeled as the “d3GHR,” which lacks exon 3 was associated with longevity. This specific deletion isoform was connected to changes in the structure of the GHR protein, which may have an impact on the GHR's function. To test in vitro the advantage of the d3 carrier that may link to longevity, we employed the CRISPR/Cas9 technique to produce two isoforms: the homozygotes isoform (d3/d3) and the heterozygotes isoform (d3/fl) using HEK293 cell line. The CRISPR editing effectiveness was >85 %, indicating that we had successfully built the Cas9-gRNA complex that is appropriate for the GHR gene. The viability of the resulted isoform cells was examined under three environmental stressors that mimic some aging processes. In addition, we examined the GHR signaling pathway by selecting potential downstream genes in the GHR signaling cascade. The results show that heterozygotes cells demonstrated higher survival rates under UV radiation compared with the WT cells (87 % compared with 67 % for the WT cells when exposed to 2 min of UV radiation), and in fasting conditions, the d3GHR cells showed a 15 % greater viability than the WT cells. Moreover, the baseline expression levels (without intervention) of the IGF1 and JAK/STAT genes signaling pathways significantly declined in the homozygotes cells compared with the WT (p

Clonal MAPK-pathway activating mutations in the MAP2K1 (MEK1) gene are present in approximately 9% of cutaneous melanomas. These mutations are divided into three classes: RAF-dependent, RAF-regulated, RAF-independent. Cell lines with class-2 or RAF-regulated MAP2K1-mutations are most responsive to MEK-inhibitors. We present a patient with a class-2 MAP2K1-mutant stage IV-M1d melanoma who experienced extra- and intracranial progressive disease following treatment with immune-checkpoint inhibitors. The patient was treated with the MEK-inhibitor trametinib (2 mg OD) to which a low-dose of dabrafenib (50 mg BID) was added to mitigate skin-toxicity. Following documentation of a partial response (PR), she developed one new, and increase in volume of two pre-existing brain metastases that were treated with stereotactic radiosurgery (SRS) while continuing trametinib and dabrafenib. Thereafter, a deep partial radiologic and metabolic response both extra-and intra-cranially was achieved and is ongoing 88 weeks after initiating trametinib. She experienced no grade > 2 adverse events. Focal post-radiation necrosis at site of an irradiated brain metastasis developed 9 months after SRS and is successfully being treated with low-dose bevacizumab. This is the first published case of a durable intracranial disease control with the MEK-inhibitor trametinib of a stage IV-M1d class-2 MAP2K1-mutant melanoma. This illustrates the utility of NGS profiles that include class-1/2 MAP2K1-mutations in patients with melanoma and other malignancies to provide valuable information on a potentially active individualized treatment option. A prospective clinical trial that further evaluates the efficacy of MEK-inhibitor therapies in MAP2K1-mutated tumors is justified.

The increasing capabilities of AI pose new risks and vulnerabilities for organizations and decision makers. Several trustworthy AI frameworks have been created by U.S. federal agencies and international organizations to outline the principles to which AI systems must adhere for their use to be considered responsible. Different trustworthy AI frameworks reflect the priorities and perspectives of different stakeholders, and there is no consensus on a single framework yet. We evaluate the leading frameworks and provide a holistic perspective on trustworthy AI values, allowing federal agencies to create agency-specific trustworthy AI strategies that account for unique institutional needs and priorities. We apply this approach to the Department of Veterans Affairs, an entity with largest health care system in US. Further, we contextualize our framework from the perspective of the federal government on how to leverage existing trustworthy AI frameworks to develop a set of guiding principles that can provide the foundation for an agency to design, develop, acquire, and use AI systems in a manner that simultaneously fosters trust and confidence and meets the requirements of established laws and regulations.

BACKGROUND AND OBJECTIVE:. To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validated while incorporating a Veteran sample. DERIVATION COHORT:. Adults (age ≥ 18 yr) hospitalized outside the ICU with a diagnosis of COVID-19 for model development to the Veterans Health Administration (VHA) (n = 80 hospitals). VALIDATION COHORT:. External validation occurred in a VHA cohort of 34 hospitals, as well as six non-Veteran health systems for further external validation (n = 21 hospitals) between 2020 and 2023. PREDICTION MODEL:. eXtreme Gradient Boosting machine learning methods were used, and performance was assessed using the area under the receiver operating characteristic curve and compared with the National Early Warning Score (NEWS). The primary outcome was transfer to the ICU or death within 24 hours of each new variable observation. Model predictor variables included demographics, vital signs, structured flowsheet data, and laboratory values. RESULTS:. A total of 96,908 admissions occurred during the study period, of which 59,897 were in the Veteran sample and 37,011 were in the non-Veteran sample. During external validation in the Veteran sample, the model demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.88. This was significantly higher than NEWS (0.79; p < 0.01). In the non-Veteran sample, the model also demonstrated excellent discrimination (0.86 vs. 0.79 for NEWS; p < 0.01). The top three variables of importance were eosinophil percentage, mean oxygen saturation in the prior 24-hour period, and worst mental status in the prior 24-hour period. CONCLUSIONS:. We used machine learning methods to develop and validate a highly accurate early warning score in both Veterans and non-Veterans hospitalized with COVID-19. The model could lead to earlier identification and therapy, which may improve outcomes.

The recording, reporting, and use of data on school attendance and absence (DSAA) play a crucial role in understanding attendance and addressing absence in educational systems worldwide. However, a comprehensive grasp of the diverse approaches adopted across and within different countries has remained elusive. To address this knowledge gap, the International Network for School Attendance (INSA) facilitated this special issue providing an in-depth investigation into DSAA practices in 13 countries. This opening paper serves two purposes. First, it lays the conceptual groundwork for readers before they delve into the recording, reporting, and use of DSAA in different countries. Second, it presents key insights that emerge from the diverse array of contributions and a discussion of challenges and opportunities for the field. These include the substantial inconsistencies within and across countries; the pressing need for standardised best practices for recording, reporting, and using data; and the importance of embracing technological advancements to enhance the use of data. We envisage that the collective effort of the 40 authors involved in this special issue will enrich knowledge, enhance collaboration, and create real-world impact by enabling interested parties to develop, use, and evaluate data-driven strategies related to attendance and absence. By working together to address challenges and seize opportunities related to DSAA, we help young people access the education they rightfully deserve.

Autism spectrum disorder (ASD) is a highly heritable complex disease that affects 1% of the population, yet its underlying molecular mechanisms are largely unknown. Here we study the problem of predicting causal genes for ASD by combining genome-scale data with a network propagation approach. We construct a predictor that integrates multiple omic data sets that assess genomic, transcriptomic, proteomic, and phosphoproteomic associations with ASD. In cross validation our predictor yields mean area under the ROC curve of 0.87 and area under the precision-recall curve of 0.89. We further show that it outperforms previous gene-level predictors of autism association. Finally, we show that we can use the model to predict genes associated with Schizophrenia which is known to share genetic components with ASD.

Abstract Quantifying imperfect symmetry of molecules can help explore the sources, roles and extent of structural distortion. Based on the established methodology of continuous symmetry and chirality measures, we develop a set of three-dimensional molecular descriptors to estimate distortion of large structures. These three-dimensional geometrical descriptors quantify the gap between the desirable symmetry (or chirality) and the actual one. They are global parameters of the molecular geometry, intuitively defined, and have the ability to detect even minute structural changes of a given molecule across chemistry, including organic, inorganic, and biochemical systems. Application of these methods to large structures is challenging due to countless permutations that are involved in the symmetry operations and have to be accounted for. Our approach focuses on iteratively finding the approximate direction of the symmetry element in the three-dimensional space, and the relevant permutation. Major algorithmic improvements over previous versions are described, showing increased accuracy, reliability and structure preservation. The new algorithms are tested for three sets of molecular structures including pillar[5]arene complexes with Li+, C100 fullerenes, and large unit cells of metal organic frameworks. These developments complement our recent algorithms for calculating continuous symmetry and chirality measures for small molecules as well as protein homomers, and simplify the usage of the full set of measures for various research goals, in molecular modeling, QSAR and cheminformatics.

Abstract CD8+ T cell activation via immune checkpoint blockade (ICB) is successful in microsatellite instable (MSI) colorectal cancer (CRC) patients. By comparison, the success of immunotherapy against microsatellite stable (MSS) CRC is limited. Little is known about the most critical features of CRC CD8+ T cells that together determine the diverse immune landscapes and contrasting ICB responses. Hence, we pursued a deep single cell mapping of CRC CD8+ T cells on transcriptomic and T cell receptor (TCR) repertoire levels in a diverse patient cohort, with additional surface proteome validation. This revealed that CRC CD8+ T cell dynamics are underscored by complex interactions between interferon-γ signaling, tumor reactivity, TCR repertoire, (predicted) TCR antigen-specificities, and environmental cues like gut microbiome or colon tissue-specific ‘self-like’ features. MSI CRC CD8+ T cells showed tumor-specific activation reminiscent of canonical ‘T cell hot’ tumors, whereas the MSS CRC CD8+ T cells exhibited tumor unspecific or bystander-like features. This was accompanied by inflammation reminiscent of ‘pseudo-T cell hot’ tumors. Consequently, MSI and MSS CRC CD8+ T cells showed overlapping phenotypic features that differed dramatically in their TCR antigen-specificities. Given their high discriminating potential for CD8+ T cell features/specificities, we used the single cell tumor-reactive signaling modules in CD8+ T cells to build a bulk tumor transcriptome classification for CRC patients. This “Immune Subtype Classification” (ISC) successfully distinguished various tumoral immune landscapes that showed prognostic value and predicted immunotherapy responses in CRC patients. Thus, we deliver a unique map of CRC CD8+ T cells that drives a novel tumor immune landscape classification, with relevance for immunotherapy decision-making.

Abstract Objective Periodic fever, aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome is the most common periodic fever syndrome in children; by definition, episodes occur every 2 to 8 weeks. However, in a subset of our patients, we noticed a higher frequency of attacks, of less than 2 weeks, which we refer to as extreme PFAPA (ePFAPA). This group consisted of patients who were extreme upon presentation of PFAPA, and those who became extreme after initiation of abortive corticosteroid treatment. We aimed to characterize demographic and clinical features of ePFAPA, including the two groups, and to compare them to patients with non-extreme PFAPA (nPFAPA). Study design : The medical records of 365 patients with PFAPA who attended Schneider Children’s Medical Center of Israel from March 2014 to April 2021 were reviewed. Patients with concomitant familial Mediterranean fever were excluded. Characteristics of the ePFAPA (including subgroups) and nPFAPA groups were compared using Wilcoxon rank sum, Pearson’s chi-squared, and Fisher’s exact tests. Results Forty-seven patients (12.9%) were identified as having ePFAPA. Among patients with ePFAPA, compared to patients with nPFAPA, the median (interquartile range) age at disease onset was earlier: 1.5 years (0.7–2.5) vs. 2.5 years (1.5-4.0), P

The intriguing ability of C-phenyl-nitrilimine to co-exist as allenic and propargylic bond-shift isomers motivated us to investigate how substituents in the phenyl ring influence this behavior. Building on our previous work on the meta- and para-OH substitution, here we extended this investigation to explore the effect of the NH2 substitution. For this purpose, C-(4-aminophenyl)- and C-(3-aminophenyl)-nitrilimines were photogenerated in an argon matrix at 15 K by narrowband UV-light irradiation (λ = 230 nm) of 5-(4-aminophenyl)- and 5-(3-aminophenyl)-tetrazole, respectively. The produced nitrilimines were further photoisomerized to carbodiimides via 1H-diazirines by irradiations at longer wavelengths (λ = 380 or 330 nm). Combining IR spectroscopic measurements and DFT calculations, it was found that the para-NH2-substituted nitrilimine exists as a single isomeric structure with a predominant allenic character. In contrast, the meta-NH2-substituted nitrilimine co-exists as two bond-shift isomers characterized by propargylic and allenic structures. To gain further understanding of the effects of phenyl substitution on the bond-shift isomerism of the nitrilimine fragment, we compared geometric and charge distribution data derived from theoretical calculations performed for C-phenyl-nitrilimine with those performed for the derivatives resulting from NH2 (electron-donating group) and NO2 (electron-withdrawing group) phenyl substitutions.

We present the first records of Tropidurus chromatops Harvey & Gutberlet, 1998 from the Beni Department (Bolivia) and extend this species’ distribution to western Bolivia by approximately 256 km in a straight line to the Beni Floodplains ecoregion. Likewise, we contribute information on some aspects of the natural history, altitude of occurrence, and the geographic distribution of T. chromatops in the Department of Beni.

Sterile alpha and TIR motif-containing 1 (SARM1) is a protein involved in programmed death of injured axons. Following axon injury or a drug-induced insult, the TIR domain of SARM1 degrades the essential molecule nicotinamide adenine dinucleotide (NAD+), leading to a form of axonal death called Wallerian degeneration. Degradation of NAD+ by SARM1 is essential for the Wallerian degeneration process, but accumulating evidence suggest that other activities of SARM1, beyond the mere degradation of NAD+, may be necessary for programmed axonal death. In this study we show that the TIR domains of both human and fruit fly SARM1 produce 1''-2' and 1''-3' glycocyclic ADP-ribose (gcADPR) molecules as minor products. As previously reported, we observed that SARM1 TIR domains mostly convert NAD+ to ADPR (for human SARM1) or cADPR (in the case of SARM1 from Drosophila melanogaster). However, we now show that human and Drosophila SARM1 additionally convert ~0.1-0.5% of NAD+ into gcADPR molecules. We find that SARM1 TIR domains produce gcADPR molecules both when purified in vitro and when expressed in bacterial cells. Given that gcADPR is a second messenger involved in programmed cell death in bacteria and likely in plants, we propose that gcADPR may play a role in SARM1-induced programmed axonal death in animals.

This work aimed to show which treatments showed efficacy against coronavirus disease 2019 (COVID-19); therefore, the results of 37 clinical trials started in 2020 and completed in 2021 are reviewed and discussed here. These were selected from databases, excluding vaccines, computational studies, in silico, in vitro, and those with hyperimmune sera from recovered patients. We found 34 drugs, one vitamin, and one herbal remedy with pharmacological activity against symptomatic COVID-19. They reduced mortality, disease progression, or recovery time. For each treatment, the identifier and type of trial, the severity of the disease, the sponsor, the country where the trial was conducted, and the trial results are presented. The drugs were classified according to their mechanism of action. Several drugs that reduced mortality also reduced inflammation in the most severe cases. These include some that are not considered anti-inflammatory, such as Aviptadil, pyridostigmine bromide, anakinra, imatinib, baricitinib, and bevacizumab, as well as the combination of ivermectin, aspirin, dexamethasone, and enoxaparin. Nigella sativa seeds with honey have also been reported to have therapeutic activity. On the other hand, tofacitinib, novaferon with ritonavir, and lopinavir were also effective, as well as in combination with antiviral therapies such as danoprevir with ritonavir. The natural products colchicine and Vitamin D3 were only effective in patients with mild-to-moderate COVID-19, as was hydroxychloroquine. Drug repositioning has been the main tool in the search for effective therapies by expanding the pharmacological options available to patients.

Abstract Background The Constant-Murley Score (CMS) is a relatively unique shoulder assessment tool because it combines patient-reported outcomes (pain and activity), performance measurement and clinician-reported outcomes (strength and mobility). With these characteristics, the effect of patient-related psychological factors on the CMS remains debated. We aimed to investigate which parameters of the CMS are influenced by psychological factors by assessing the CMS before and after rehabilitation for chronic shoulder pain. Methods This retrospective study screened all patients (18–65 years old) who were admitted for interdisciplinary rehabilitation for chronic shoulder pain (≥ 3 months) between May 2012 and December 2017. Patients with unilateral shoulder injuries were eligible. Exclusion criteria were shoulder instability, concomitant neurological injuries, complex regional pain syndrome (including Steinbrocker syndrome), heavy psychiatric issues, and missing data. The Hospital Anxiety and Depression Scale, Pain Catastrophizing scale, and Tampa Scale of Kinesiophobia were administered before and after treatment. Regression models were used to estimate associations between psychological factors and the CMS. Results We included 433 patients (88% male, mean age 47±11 years) with a median duration of symptoms of 392.2 days (interquartile range: 266.5-583.5). Rotator cuff issue was present in 71% of patients. During interdisciplinary rehabilitation, patients were followed for a mean of 33.6±7.5 days. The mean CMS at entry was 42.8 ±15.5. The mean gain in CMS after treatment was 10.6 ±10.9. Before treatment, psychological factors were significantly associated with only the pain CMS parameter: -0.37 (95% CI: -0.46 to -0.28), p

Objective(s): Metabolic syndrome is associated with the development of chronic kidney disease. Bursera simaruba “chaca” is a medicinal plant used in Mexico for hypertension and empirical therapy. In this study, were examined the effects of ethanol extract of B. simaruba on metabolic syndrome.Materials and Methods: For induction of metabolic syndrome, 20% fructose was used, and it was administered in the water and food to male Wistar rats for 12 weeks, after administering ethanol extract of B. simaruba intragastrically (100 and 200 mg/kg/day) for 6 weeks, blood pressure was determined. In plasma, glucose, cholesterol, triglycerides, angiotensin II, oxide nitric, and angiotensin 1-7 were quantified. In the kidney was performed histological study and the activity of anti-oxidant enzymes was quantified. Results: Rats with metabolic syndrome developed obesity, arterial hypertension, dyslipidemia, and kidney damage characterized by proliferative glomerulonephritis, necrosis, and reduced activity of anti-oxidant enzymes. These alterations were significantly ameliorated by ethanol extract of B. simaruba.Conclusion: The ethanolic extract of B. simaruba showed antidyslipidemic, antihypertensive, anti-oxidant, and renoprotective effects.

IntroductionThe rapid expansion of artificial intelligence (AI) has produced many opportunities, but also new risks that must be actively managed, particularly in the health care sector with clinical practice to avoid unintended health, economic, and social consequences.MethodsGiven that much of the research and development (R&D) involving human subjects is reviewed and rigorously monitored by institutional review boards (IRBs), we argue that supplemental questions added to the IRB process is an efficient risk mitigation technique available for immediate use. To facilitate this, we introduce AI supplemental questions that provide a feasible, low-disruption mechanism for IRBs to elicit information necessary to inform the review of AI proposals. These questions will also be relevant to review of research using AI that is exempt from the requirement of IRB review. We pilot the questions within the Department of Veterans Affairs–the nation's largest integrated healthcare system–and demonstrate its efficacy in risk mitigation through providing vital information in a way accessible to non-AI subject matter experts responsible for reviewing IRB proposals. We provide these questions for other organizations to adapt to fit their needs and are further developing these questions into an AI IRB module with an extended application, review checklist, informed consent, and other informational materials.ResultsWe find that the supplemental AI IRB module further streamlines and expedites the review of IRB projects. We also find that the module has a positive effect on reviewers' attitudes and ease of assessing the potential alignment and risks associated with proposed projects.DiscussionAs projects increasingly contain an AI component, streamlining their review and assessment is important to avoid posing too large of a burden on IRBs in their review of submissions. In addition, establishing a minimum standard that submissions must adhere to will help ensure that all projects are at least aware of potential risks unique to AI and dialogue with their local IRBs over them. Further work is needed to apply these concepts to other non-IRB pathways, like quality improvement projects.

Perinatal depression is the onset of depressive symptoms during pregnancy and up to one year after childbirth. Migrant women are at higher risk of experiencing perinatal depression due to numerous psychosocial stressors related to their experiences. This qualitative review aims to aggregate the experiences and barriers to care faced by immigrant and refugee women in Canada who have perinatal depression. Qualitative research can elucidate the barriers to treatment and culturally-impacted experiences of Canadian migrant women with perinatal depression. Following PRISMA and Joanna Briggs Institute (JBI) guidelines for conducting qualitative systematic reviews, 13 eligible studies representing 10 samples (N = 262 participants) were identified and included in this review. Participants included service providers, immigrant women, and refugee women. Three synthesized themes were identified by this review using the JBI meta-aggregative approach: (1) culture-related challenges; (2) migration-related challenges; and (3) service accessibility and quality. Within these themes were experiences of migrant women that encompass six categories: (1) conceptualization of perinatal depression; (2) childbirth-specific challenges; (3) migration-related challenges; (4) social isolation; (5) accessibility of services; and (6) quality of care. The role of family, cultural differences, financial challenges, and the effects of these on service accessibility are impactful in the experiences of migrant women. A greater understanding of the role of both culture and migration in the delivery of care, especially regarding service provider attitudes in more representative samples, is recommended.

Epidemiological and clinical studies have uniformly reported an overrepresentation of females with very-late-onset schizophrenia-like psychotic disorder (VLOS), in stark contrast to the sex distribution of early-onset schizophrenia. Various explanatory models have been proposed to account for these sex differences, including (a) antidopaminergic effects of estrogen, (b) differential vulnerability to subtypes, (c) neurodegenerative differences between the sexes, and (d) and sex differences in age-related psychosocial and neurological risk factors; however, these models have not yet been critically evaluated for their validity. Keywords related to VLOS symptomatology, epidemiology, and sex/gender were entered into the PubMed, MEDLINE, and Google Scholar databases spanning all years. Through a narrative review of symptomatology and pathophysiology of VLOS, we examine the strengths and limitations of the proposed models. We present a comprehensive biopsychosocial perspective to integrate the above models with a focus on the role of neuroinflammation. There is significant room for further research into the mechanisms of VLOS that may help to explain the female preponderance; the effects of estrogen and menopause, neuroinflammation, and dopaminergic transmission; and their interaction with age-related and lifetime psychosocial stressors and underlying biological vulnerabilities.

Abstract Bacterial swarms are a highly-researched example of natural active matter. In particular, the interplay between biological interactions and the physics underlying the swarming dynamics is of both biological and physical interest. In this paper, we study mixed swarms of Bacillus subtilis and Pseudomonas aeruginosa. We find intricate interactions between the species, showing both cooperation and segregation across different spatial and temporal scales. On one hand, even though axenic colonies grow on disparate time scale, an order of magnitude apart, the two-species swarm together, forming a single, combined colony. However, the rapidly moving populations are locally segregated, with different characteristic speeds and lengths (or cluster sizes) that depend on the ratio between the species. Comparison with controlled mutant strains suggest that both the physical and known biological differences in species characteristics may not be enough to explain the segregation between the species in the mixed swarm. We hypothesize that the heterogeneous spatial distribution is due to some mechanism that enables bacteria to recognize their own kind, whose precise origin we could not identify.

In order to address a long standing challenge for internal medicine physicians we developed artificial intelligence (AI) models to identify patients at risk of increased mortality. After querying 2,425 records of patients transferred from non-intensive care units to intensive care units from the Veteran Affairs Corporate Data Warehouse (CDW), we created two datasets. The former used 22 independent variables that included “Length of Hospital Stay” and “Days to Intensive Care Transfer,” and the latter lacked these two variables. Since these two variables are unknown at the time of admission, the second set is more clinically relevant. We trained 16 machine learning models using both datasets. The best-performing models were fine-tuned and evaluated. The LightGBM model achieved the best results for both datasets. The model trained with 22 variables achieved a Receiver Operating Characteristics Curve-Area Under the Curve (ROC-AUC) of 0.89 and an accuracy of 0.72, with a sensitivity of 0.97 and a specificity of 0.68. The model trained with 20 variables achieved a ROC-AUC of 0.86 and an accuracy of 0.71, with a sensitivity of 0.94 and a specificity of 0.67. The top features for the former model included “Total length of Stay,” “Admit to ICU Transfer Days,” and “Lymphocyte Next Lab Value.” For the latter model, the top features included “Lymphocyte First Lab Value,” “Hemoglobin First Lab Value,” and “Hemoglobin Next Lab Value.” Our clinically relevant predictive mortality model can assist providers in optimizing resource utilization when managing large caseloads, particularly during shift changes.

Literature on the effect of religion and religiosity on corruption has failed to distinguish between direct and mediated effect and to determine the different roles of two alternative mediation channels—the personal versus the cultural channel. Using a data set of 102 countries, we found that hierarchical religions have significant positive associations with corruption levels, while the non-hierarchical Protestant Christianity has significant negative associations with corruption levels. Most of the effect is mediated by the cultural channel. However, some hierarchical religions (particularly Sunni Islam and Orthodox Christianity) have both an indirect mediated effect and a direct unmediated effect, suggesting an additional dissociative parameter besides the hierarchical/non-hierarchical parameter, which we suggest is the status of a formal/informal state religion. The findings are closely linked to the modern view of economic development that although institutions give rise to economic growth, it is culture that shapes institutions.