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BACKGROUND: Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources. RESULTS: We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues. CONCLUSIONS: These findings suggest DRAGON-AIs potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

A key component of green hydrogen production technologies is the fabrication of large-scale porous transport layer (PTL) for use in anion electrolyte membrane water electrolysers (AEMWEs). One strategy to achieve that goal is to manufacture Ni-based 3D electrode skeletons that can be further catalyzed to achieve high current densities at low overpotentials. In the present work, shock-wave induced spray (SWIS) and cold spray (CS) deposition techniques were used to prepare 20 cm2 Ni-based electrode skeletons. In our experimental conditions, the porosity of coatings prepared using the SWIS deposition system and Ni powders with particle sizes D50 = 32 and 75 μm never exceeded 28%. Higher porosity could only be achieved using the CS deposition system and a spheroidal Ni–Al powder, whose particles consist of an aluminum core encapsulated in a nickel shell. After Al leaching in an alkaline solution, the resulting electrodes showed good mechanical and structural integrity with up to 41% porosity. The electrochemical active surface area of the most porous electrodes is a factor of 2100 larger than a polished Ni plate, and it has superaerophobic properties with a captive air bubble contact angle of 151°. During 1 h of electrolysis, the overpotential at 100 mA cm−2 of the most active leached Ni–Al cold spray deposited electrode was 330 mV, compared to 380 mV for a Ni foam electrode.

Abstract Background Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources. Results We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues. Conclusions These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Abstract Background Activation of innate immunity is a first line of host defense during acute critical illness (ACI) that aims to contain injury and avoid tissue damages. Aberrant activation of innate immunity may also participate in the occurrence of organ failures during critical illness. This review aims to provide a narrative overview of recent advances in the field of innate immunity in critical illness, and to consider future potential therapeutic strategies. Main text Understanding the underlying biological concepts supporting therapeutic strategies modulating immune response is essential in decision-making. We will develop the multiple facets of innate immune response, especially its cellular aspects, and its interaction with other defense mechanisms. We will first describe the pathophysiological mechanisms of initiation of innate immune response and its implication during ACI. We will then develop the amplification of innate immunity mediated by multiple effectors. Our review will mainly focus on myeloid and lymphoid cellular effectors, the major actors involved in innate immune-mediated organ failure. We will third discuss the interaction and integration of innate immune response in a global view of host defense, thus considering interaction with non-immune cells through immunothrombosis, immunometabolism and long-term reprogramming via trained immunity. The last part of this review will focus on the specificities of the immune response in children and the older population. Conclusions Recent understanding of the innate immune response integrates immunity in a highly dynamic global vision of host response. A better knowledge of the implicated mechanisms and their tissue-compartmentalization allows to characterize the individual immune profile, and one day eventually, to develop individualized bench-to-bedside immunomodulation approaches as an adjuvant resuscitation strategy.

High school teachers often struggle to engage students who have little or no motivation to learn. We argue that improving students' perceptions of affective relationships with teachers may have the potential to positively influence their motivation, and vice versa. This study looks at reciprocal associations between students' perceptions of the teacher-student relationship climate (PTSRC) and three components of academic motivation (autonomous, controlled, and amotivation), measured at two time points, over a 12-month period. We recruited 328 students (on average 15 years of age, 65% girls) from public high schools in disadvantaged areas of a Canadian suburb. We found that students' autonomous motivation predicted an increase in positive PTSRC. In contrast, we did not find evidence that PTSRC predicted either autonomous or controlled motivation. Nonetheless, a positive PTSRC predicted a decrease in students' amotivation. This finding suggests that high school students' positive PTSRC can help them find purpose in their schooling. Knowing that motivation typically declines during the high school years, this study is important because it suggests that promoting positive teacher-student relationships can contribute to ward off such decline.

We conducted a content analysis of the literature underlying the Centers for Disease Control and Prevention (CDC) Guideline on the Diagnosis and Management of Mild Traumatic Brain Injury Among Children (i.e., the Guideline) to determine the extent to which social determinants of health (SDoH) were examined or addressed. The systematic review forming the basis for the Guideline included 37 studies addressing diagnosis, prognosis, and treatment/rehabilitation. We examined those studies to identify SDoH domains derived from the U.S. Department of Health and Human Services Healthy People 2020 and 2030 websites. No study explicitly mentioned social determinants of health, by name, and few studies addressed SDoH domains as a primary focus (ranging from 0% to 27% of studies across SDoH domains). The most frequently represented SDoH domains, described in an inferential or a descriptive manner, were Education Access and Quality (29.7% of studies), Social and Community Context (27.0% of studies), and Economic Stability (21.6% of studies). Health Care Access (13.5% of studies) was less well represented and no studies (0%) examined Neighborhood and Built Environment. In terms of the CDC clinical questions, SDoH were only examined as predictors of outcome (prognosis) and no studies examined SDoH in relation to diagnosis or treatment/rehabilitation. The Guideline includes some commentary on health literacy and socioeconomic status. Overall, social determinants of health are largely unrepresented as important or meaningful variables influencing the Guideline on the Diagnosis and Management of Mild Traumatic Brain Injury Among Children, or in the studies that informed the Guideline.

Regulatory non-coding RNAs (ncRNAs) are increasingly recognized as integral to the control of biological processes. This is often through the targeted regulation of mRNA expression, but this is by no means the only mechanism through which regulatory ncRNAs act. The Gene Ontology (GO) has long been used for the systematic annotation of protein-coding and ncRNA gene function, but rapid progress in the understanding of ncRNAs meant that the ontology needed to be revised to accurately reflect current knowledge. Here, a targeted effort to revise GO terms used for the annotation of regulatory ncRNAs is described, focusing on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), small interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs). This paper provides guidance to biocurators annotating ncRNA-mediated processes using the GO and serves as background for researchers wishing to make use of the GO in their studies of ncRNAs and the biological processes they regulate.

TRP channels are important pharmacological targets in physiopathology. TRPV2 plays distinct roles in cardiac and neuromuscular function, immunity, and metabolism, and is associated with pathologies like muscular dystrophy and cancer. However, TRPV2 pharmacology is unspecific and scarce at best. Using in silico similarity-based chemoinformatics we obtained a set of 270 potential hits for TRPV2 categorized into families based on chemical nature and similarity. Docking the compounds on available rat TRPV2 structures allowed the clustering of drug families in specific ligand binding sites. Starting from a probenecid docking pose in the piperlongumine binding site and using a Gaussian accelerated molecular dynamics approach we have assigned a putative probenecid binding site. In parallel, we measured the EC50 of 7 probenecid derivatives on TRPV2 expressed in Pichia pastoris using a novel medium-throughput Ca2+ influx assay in yeast membranes together with an unbiased and unsupervised data analysis method. We found that 4-(piperidine-1-sulfonyl)-benzoic acid had a better EC50 than probenecid, which is one of the most specific TRPV2 agonists to date. Exploring the TRPV2-dependent anti-hypertensive potential in vivo, we found that 4-(piperidine-1-sulfonyl)-benzoic acid shows a sex-biased vasodilator effect producing larger vascular relaxations in female mice. Overall, this study expands the pharmacological toolbox for TRPV2, a widely expressed membrane protein and orphan drug target.

Background: Three-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings. Methods: We evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia. In part (1), we used a set of 108 MPRAGE reconstructed images derived from 12 healthy volunteers to systematically assess the effectiveness of SAMER in correcting varying degrees of motion corruption, ranging from mild to severe. In part (2), 29 patients who were scheduled for brain MRI with memory loss protocol and had motion corruption on their clinical MPRAGE scans were prospectively enrolled. Results: In part (1), SAMER resulted in effective correction of motion-induced cortical volume and thickness reductions. We observed systematic increases in the estimated cortical volume and thickness across all neuroanatomical regions and a relative reduction in percent error values compared to reference standard scans of up to 66 % for the cerebral white matter volume. In part (2), SAMER resulted in statistically significant volume increases across anatomical regions, with the most pronounced increases seen in the parietal and temporal lobes, and general reductions in percent error relative to reference standard clinical scans. Conclusion: SAMER improves the accuracy of morphometry through systematic increases and recovery of the estimated cortical volume and cortical thickness following motion correction, which may affect the evaluation of regional cortical atrophy in patients undergoing evaluation for dementia.

Therapeutic Area: Pharmacologic Therapy Background: Homozygous familial hypercholesterolemia (HoFH) is a rare genetic disorder characterized by severely elevated low-density lipoprotein cholesterol (LDL-C) and increased risk of early-onset atherosclerotic cardiovascular disease. Despite treatment with multiple lipid-lowering therapies (LLTs), most patients with HoFH do not attain guideline-recommended LDL-C treatment goals. In a phase 3 trial (NCT03409744), evinacumab, an angiopoietin-like 3 inhibitor, substantially reduced mean LDL-C by 43.6% from baseline to Week 24. Here, we report on the long-term LDL-C lowering efficacy of evinacumab analyzed by patient subgroups from the open-label treatment period (OLTP) of this phase 3 trial. Methods: This single-arm, open-label, phase 3 study (NCT03409744) comprised patients with HoFH aged ≥12 years who were evinacumab-naïve or had previously received evinacumab in other trials. The study included a run-in period (≤10 weeks), a screening period (2 weeks), an OLTP (≤192 weeks), and a follow-up period (24 weeks). In the OLTP, all patients received intravenous evinacumab 15 mg/kg every 4 weeks alongside optimized LLT. Results: Overall, 116 patients were enrolled with a mean (standard deviation [SD]) age of 38.8 (15.9) years. The proportion of male and female patients was similar (50.9% vs 49.1%, respectively). Most patients were White (69.0%) or Asian (10.3%). At baseline, mean (SD) LDL-C was 261.0 (160.1) mg/dL. Evinacumab reduced mean (SD) LDL-C from baseline to Week 96 by 57.6% (16.7%), 36.4% (54.6%), and 38.0% (52.9%) in patients

Abstract Background and Aims Endocan is a marker of endothelial damage. Data regarding the association of this proteoglycan and acute respiratory distress syndrome (ARDS) is discrepant. Hence, this study sought to investigate the possible correlation between serum/plasma endocan concentration and ARDS. Methods A systematic review and meta‐analysis of international online databases was conducted following PRISMA guidelines. PubMed, SCOPUS, Embase, and Web of Science were searched in March 2023, with the leading search terms being “ARDS” OR “respiratory distress” AND “endocan” and other associated terms. Studies that measured endocan levels in patients with ARDS and compared it with non‐ARDS controls or within different severities of ARDS were included. We performed a random‐effect meta‐analysis for pooling the differences using standardized mean difference (SMD) and 95% confidence interval (CI). Results We included 14 studies involving 1,058 patients. Those developing ARDS had significantly higher levels of endocan compared to those without ARDS (SMD: 0.47, 95% CI: 0.10–0.84, p = 0.01). Our meta‐analysis of three studies found that endocan levels in ARDS nonsurvivors were significantly higher than in survivors (SMD: 0.31, 95% CI: 0.02–0.60, p = 0.03). Three studies investigated endocan levels in different severities of ARDS. Only one of these studies reported significantly higher endocan levels in patients with worsening acute respiratory failure at Day 15. The other two reported no significant association between ARDS severity and circulating endocan levels. Conclusion Blood endocan levels were significantly higher in patients with ARDS than those without. Additionally, among patients with ARDS, blood endocan values were significantly elevated in nonsurvivors compared to survivors. These findings could help researchers design future studies and solidify these findings and finally, clinicians to take advantage of measuring endocan in clinical settings for assessment of patients with ARDS.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

School motivation is key to promoting optimal educational pathways. Some studies suggest that parental monitoring behaviors foster school motivation among adolescents; however, they did not examine the potential role of adolescents' motivation in shaping parental monitoring behaviors. This longitudinal study aimed to examine the bidirectional associations between three types of school motivation (autonomous, controlled, and amotivation) and two types of perceived parental monitoring behaviors (solicitation and control). The sample consisted of 328 adolescents (212 girls, 116 boys; M = 15.78 years), assessed at the end of their third or fourth year of secondary school, and again, 1 year later. Path analyses revealed that over a 1-year period, bidirectional associations were found between autonomous motivation and perceived parental solicitation. Moreover, parental solicitation as perceived by the adolescents was associated with a decrease in amotivation during the following year. Findings provide support for the dynamic nature of the parent-child relationships and highlight the need to consider child-to-parent effects to promote positive school-related outcomes.