An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

Rhodanese-Fold Containing Proteins in Humans: Not Just Key Players in Sulfur Trafficking.

The Rhodanese-fold is a ubiquitous structural domain present in various protein subfamilies associated with different physiological functions or pathophysiological conditions in humans. Proteins harboring a Rhodanese domain are diverse in terms of domain architecture, with some representatives exhibiting one or several Rhodanese domains, fused or not to other structural domains. The most famous Rhodanese domains are catalytically active, thanks to an active-site loop containing an essential cysteine residue which allows for catalyzing sulfur transfer reactions involved in sulfur trafficking, hydrogen sulfide metabolism, biosynthesis of molybdenum cofactor, thio-modification of tRNAs or protein urmylation. In addition, they also catalyse phosphatase reactions linked to cell cycle regulation, and recent advances proposed a new role into tRNA hydroxylation, illustrating the catalytic versatility of Rhodanese domain. To date, no exhaustive analysis of Rhodanese containing protein equipment from humans is available. In this review, we focus on structural and biochemical properties of human-active Rhodanese-containing proteins, in order to provide a picture of their established or putative key roles in many essential biological functions.

Mapping the landscape of genetic dependencies in chordoma.

Identifying the spectrum of genes required for cancer cell survival can reveal essential cancer circuitry and therapeutic targets, but such a map remains incomplete for many cancer types. We apply genome-scale CRISPR-Cas9 loss-of-function screens to map the landscape of selectively essential genes in chordoma, a bone cancer with few validated targets. This approach confirms a known chordoma dependency, TBXT (T; brachyury), and identifies a range of additional dependencies, including PTPN11, ADAR, PRKRA, LUC7L2, SRRM2, SLC2A1, SLC7A5, FANCM, and THAP1. CDK6, SOX9, and EGFR, genes previously implicated in chordoma biology, are also recovered. We find genomic and transcriptomic features that predict specific dependencies, including interferon-stimulated gene expression, which correlates with ADAR dependence and is elevated in chordoma. Validating the therapeutic relevance of dependencies, small-molecule inhibitors of SHP2, encoded by PTPN11, have potent preclinical efficacy against chordoma. Our results generate an emerging map of chordoma dependencies to enable biological and therapeutic hypotheses.

The impact of the early stages of COVID-19 on mental health in the United States, Germany, and the United Kingdom.

The impact of COVID-19 on people's physical health is well documented. But how did COVID-19-with all the uncertainty and disruption of daily life it entailed-impact people's mental health? We used ecologically momentary assessments from 22,562 individuals (largely young adults) across the United States, Germany, and the United Kingdom to study the impact of the early stages of COVID-19 on mental health. Exploring within-person trajectories of mood (4,471,810 observations) and depression (274,911 observations) between January 1 and September 30 of 2020, and comparing them to those observed for the same time period in 2019, we provide evidence that people-on average-show high levels of resilience. While the United States saw momentary decreases in mood and increases in depression that quickly returned to baseline, Germany and the United Kingdom did not experience observable negative effects on mental health. In a small subsample of U.S. users, we show that the mental health trajectories appear to be relatively consistent across different sociodemographics groups. Investigating the impact of social distancing on people's mental health within-person, we demonstrate that social distancing-on average-was associated with a decline in mental health. However, our findings also highlight that not all COVID-19 experiences were created equal. While individuals who experienced social distancing as burdensome reported lower levels of mental health, those who did not, indicated normal or even elevated levels of mental health. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Metal-chelating activity of soy and pea protein hydrolysates obtained after different enzymatic treatments from protein isolates.

Soy and pea proteins are two rich sources of essential amino acids. The hydrolysis of these proteins reveals functional and bioactive properties of the produced small peptide mixtures. In our study, we employed the hydrolysis of soy and pea protein isolates with the endopeptidases Alcalase® and Protamex®, used alone or followed by the exopeptidase Flavourzyme®. The sequential enzyme treatments were the most efficient regarding the degree of hydrolysis. Then, soy and pea protein hydrolysates (SPHs and PPHs, respectively) were ultrafiltrated in order to select peptides of molecular weight ≤ 1 kDa. Whatever the protein source or the hydrolysis treatment, the hydrolysates showed similar molecular weight distributions and amino acid compositions. In addition, all the ultrafiltrated hydrolysates possess metal-chelating activities, as determined by UV-spectrophotometry and Surface Plasmon Resonance (SPR). However, the SPR data revealed better chelating affinities in SPHs and PPHs when produced by sequential enzymatic treatment.

Regional personality differences predict variation in early COVID-19 infections and mobility patterns indicative of social distancing.

The early stages of the COVID-19 pandemic revealed stark regional variation in the spread of the virus. While previous research has highlighted the impact of regional differences in sociodemographic and economic factors, we argue that regional differences in social and compliance behaviors-the very behaviors through which the virus is transmitted-are critical drivers of the spread of COVID-19, particularly in the early stages of the pandemic. Combining self-reported personality data that capture individual differences in these behaviors (3.5 million people) with COVID-19 prevalence and mortality rates as well as behavioral mobility observations (29 million people) in the United States and Germany, we show that regional personality differences can help explain the early transmission of COVID-19; this is true even after controlling for a wide array of important sociodemographic, economic, and pandemic-related factors. We use specification curve analyses to test the effects of regional personality in a robust and unbiased way. The results indicate that in the early stages of COVID-19, Openness to experience acted as a risk factor, while Neuroticism acted as a protective factor. The findings also highlight the complexity of the pandemic by showing that the effects of regional personality can differ (a) across countries (Extraversion), (b) over time (Openness), and (c) from those previously observed at the individual level (Agreeableness and Conscientiousness). Taken together, our findings support the importance of regional personality differences in the early spread of COVID-19, but they also caution against oversimplified answers to phenomena as complex as a global pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Lipolysis-Stimulated Lipoprotein Receptor Acts as Sensor to Regulate ApoE Release in Astrocytes.

Astroglia play an important role, providing de novo synthesized cholesterol to neurons in the form of ApoE-lipidated particles; disruption of this process can increase the risk of Alzheimer's disease. We recently reported that glia-specific suppression of the lipolysis-stimulated lipoprotein receptor (LSR) gene leads to Alzheimer's disease-like memory deficits. Since LSR is an Apo-E lipoprotein receptor, our objective of this study was to determine the effect of LSR expression modulation on cholesterol and ApoE output in mouse astrocytes expressing human ApoE3. qPCR analysis showed that siRNA-mediated lsr knockdown significantly increased expression of the genes involved in cholesterol synthesis, secretion, and metabolism. Analysis of media and lipoprotein fractions showed increased cholesterol and lipidated ApoE output in HDL-like particles. Further, lsr expression could be upregulated when astrocytes were incubated 5 days in media containing high levels (two-fold) of lipoprotein, or after 8 h treatment with 1 µM LXR agonist T0901317 in lipoprotein-deficient media. In both conditions of increased lsr expression, the ApoE output was repressed or unchanged despite increased abca1 mRNA levels and cholesterol production. We conclude that LSR acts as a sensor of lipoprotein content in the medium and repressor of ApoE release, while ABCA1 drives cholesterol efflux, thereby potentially affecting cholesterol load, ApoE lipidation, and limiting cholesterol trafficking towards the neuron.

Anti-Inflammatory Activity of Bryophytes Extracts in LPS-Stimulated RAW264.7 Murine Macrophages.

Bryophytes produce rare and bioactive compounds with a broad range of therapeutic potential, and many species are reported in ethnomedicinal uses. However, only a few studies have investigated their potential as natural anti-inflammatory drug candidate compounds. The present study investigates the anti-inflammatory effects of thirty-two species of bryophytes, including mosses and liverworts, on Raw 264.7 murine macrophages stimulated with lipopolysaccharide (LPS) or recombinant human peroxiredoxin (hPrx1). The 70% ethanol extracts of bryophytes were screened for their potential to reduce the production of nitric oxide (NO), an important pro-inflammatory mediator. Among the analyzed extracts, two moss species significantly inhibited LPS-induced NO production without cytotoxic effects. The bioactive extracts of Dicranum majus and Thuidium delicatulum inhibited NO production in a concentration-dependent manner with IC50 values of 1.04 and 1.54 µg/mL, respectively. The crude 70% ethanol and ethyl acetate extracts were then partitioned with different solvents in increasing order of polarity (n-hexane, diethyl ether, chloroform, ethyl acetate, and n-butanol). The fractions were screened for their inhibitory effects on NO production stimulated with LPS at 1 ng/mL or 10 ng/mL. The NO production levels were significantly affected by the fractions of decreasing polarity such as n-hexane and diethyl ether ones. Therefore, the potential of these extracts to inhibit the LPS-induced NO pathway suggests their effective properties in attenuating inflammation and could represent a perspective for the development of innovative therapeutic agents.

Electrically Switchable Nanolever Technology for the Screening of Metal-Chelating Peptides in Hydrolysates.

Metal-chelating peptides (MCP) are considered as indirect antioxidants due to their capacity to inhibit radical chain reaction and oxidation. Here, we propose a new proof of concept for the screening of MCPs present in protein hydrolysates for valorizing their antioxidant properties by using the emerging time-resolved molecular dynamics technology, switchSENSE. This method unveils possible interactions between MCPs and immobilized nickel ions using fluorescence and electro-switchable DNA chips. The switchSENSE method was first set up on synthetic peptides known for their metal-chelating properties. Then, it was applied to soy and tilapia viscera protein hydrolysates. Their Cu2+-chelation capacity was, in addition, determined by UV-visible spectrophotometry as a reference method. The switchSENSE method has displayed a high sensitivity to evidence the presence of MCPs in both hydrolysates. Hence, we demonstrate for the first time that this newly introduced technology is a convenient methodology to screen protein hydrolysates in order to determine the presence of MCPs before launching time-consuming separations.

Depression predictions from GPS-based mobility do not generalize well to large demographically heterogeneous samples.

Depression is one of the most common mental health issues in the United States, affecting the lives of millions of people suffering from it as well as those close to them. Recent advances in research on mobile sensing technologies and machine learning have suggested that a person's depression can be passively measured by observing patterns in people's mobility behaviors. However, the majority of work in this area has relied on highly homogeneous samples, most frequently college students. In this study, we analyse over 57 million GPS data points to show that the same procedure that leads to high prediction accuracy in a homogeneous student sample (N = 57; AUC = 0.82), leads to accuracies only slightly higher than chance in a U.S.-wide sample that is heterogeneous in its socio-demographic composition as well as mobility patterns (N = 5,262; AUC = 0.57). This pattern holds across three different modelling approaches which consider both linear and non-linear relationships. Further analyses suggest that the prediction accuracy is low across different socio-demographic groups, and that training the models on more homogeneous subsamples does not substantially improve prediction accuracy. Overall, the findings highlight the challenge of applying mobility-based predictions of depression at scale.

Coexpression network architecture reveals the brain-wide and multiregional basis of disease susceptibility.

Gene networks have yielded numerous neurobiological insights, yet an integrated view across brain regions is lacking. We leverage RNA sequencing in 864 samples representing 12 brain regions to robustly identify 12 brain-wide, 50 cross-regional and 114 region-specific coexpression modules. Nearly 40% of genes fall into brain-wide modules, while 25% comprise region-specific modules reflecting regional biology, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. Schizophrenia and autism genetic risk are enriched in brain-wide and multiregional modules, indicative of broad impact; these modules implicate neuronal proliferation and activity-dependent processes, including endocytosis and splicing, in disease pathophysiology. We find that cell-type-specific long noncoding RNA and gene isoforms contribute substantially to regional synaptic diversity and that constrained, mutation-intolerant genes are primarily enriched in neurons. We leverage these data using an omnigenic-inspired network framework to characterize how coexpression and gene regulatory networks reflect neuropsychiatric disease risk, supporting polygenic models.

Feelings of shame and guilt are associated with distinct neural activation in youth.

Shame and guilt are moral emotions that play an important role in social functioning. There is limited knowledge about the neural underpinnings of these emotions, particularly in young people. In the current study, 36 healthy females (mean age 18.8 ± 1.9 years) underwent functional Magnetic Resonance Imaging, during which they reflected on their decisions about social moral dilemmas, and subsequently received negative or positive peer feedback. Ratings of shame and guilt were used as parametric modulators of brain activity. Shame was associated with decreased activity in the superior temporal sulcus and precentral gyrus during reflection. Guilt was associated with decreased activity in the precuneus during positive feedback, and in the hippocampus and supramarginal gyrus during negative feedback. Results suggest that shame and guilt are associated with activity in brain regions involved in social cognition and emotion regulation; however, they have distinct underlying neural circuitry that may be differentiated based on social evaluation.

Spending reflects not only who we are but also who we are around: The joint effects of individual and geographic personality on consumption.

Interactionist theories are considered to have resolved the classic person-situation debate by demonstrating that human behavior is most accurately described as a function of both personal characteristics as well as environmental cues. According to these theories, personality traits form part of the personal characteristics that drive behavior. We suggest that psychological theory stands to gain from also considering personality traits as an important environmental characteristic that shapes sociocultural norms and institutions, and, in turn, behavior. Building on research in geographical psychology, we support this proposition by presenting evidence on the relationship of individual and regional personality with spending behavior. Analyzing the spending records of 111,336 participants (31,915,942 unique transactions) across 374 Local Authority Districts (LAD) in the United Kingdom, we first show that geographic regions with higher aggregate scores on a given personality trait collectively spend more money on categories associated with that trait. Shifting the focus to individual level spending as our behavioral outcome (N = 1,716), we further demonstrate that regional personality of a participant's home LAD predicts individual spending above and beyond individual personality. That is, a person's spending reflects both their own personality traits as well as the personality traits of the people around them. We use conditional random forest predictions to highlight the robustness of these findings in the presence of a comprehensive set of individual and regional control variables. Taken together, our findings empirically support the proposition that spending behaviors reflect personality traits as both personal and environmental characteristics. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Remodeling of brain morphology in temporal lobe epilepsy.

BACKGROUND: Mesial temporal lobe epilepsy (TLE) is one of the most widespread neurological network disorders. Computational anatomy MRI studies demonstrate a robust pattern of cortical volume loss. Most statistical analyses provide information about localization of significant focal differences in a segregationist way. Multivariate Bayesian modeling provides a framework allowing inferences about inter-regional dependencies. We adopt this approach to answer following questions: Which structures within a pattern of dynamic epilepsy-associated brain anatomy reorganization best predict TLE pathology. Do these structures differ between TLE subtypes? METHODS: We acquire clinical and MRI data from TLE patients with and without hippocampus sclerosis (n = 128) additional to healthy volunteers (n = 120). MRI data were analyzed in the computational anatomy framework of SPM12 using classical mass-univariate analysis followed by multivariate Bayesian modeling. RESULTS: After obtaining TLE-associated brain anatomy pattern, we estimate predictive power for disease and TLE subtypes using Bayesian model selection and comparison. We show that ipsilateral para-/hippocampal regions contribute most to disease-related differences between TLE and healthy controls independent of TLE laterality and subtype. Prefrontal cortical changes are more discriminative for left-sided TLE, whereas thalamus and temporal pole for right-sided TLE. The presence of hippocampus sclerosis was linked to stronger involvement of thalamus and temporal lobe regions; frontoparietal involvement was predominant in absence of sclerosis. CONCLUSIONS: Our topology inferences on brain anatomy demonstrate a differential contribution of structures within limbic and extralimbic circuits linked to main effects of TLE and hippocampal sclerosis. We interpret our results as evidence for TLE-related spatial modulation of anatomical networks.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics.

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

Chromatographic separation simulation of metal-chelating peptides from surface plasmon resonance binding parameters.

Some metal-chelating peptides have antioxidant properties, with potential nutrition, health, and cosmetics applications. This study aimed to simulate their separation on immobilized metal ion affinity chromatography from their affinity constant for immobilized metal ion determined in surface plasmon resonance, both technics are based on peptide-metal ion interactions. In our approach, first, the affinity constant of synthetic peptides was determined by surface plasmon resonance and used as input data to numerically simulate the chromatographic separation with a transport-dispersive model based on Langmuir adsorption isotherm. Then, chromatographic separation was applied on the same peptides to determine their retention time and compare this experimental tR with the simulated tR obtained from simulation from surface plasmon resonance data. For the investigated peptides, the relative values of tR were comparable. Hence, our study demonstrated the pertinence of such numerical simulation correlating immobilized metal ion affinity chromatography and surface plasmon resonance.

Converging patterns of aging-associated brain volume loss and tissue microstructure differences.

Given the worldwide increasing socioeconomic burden of aging-associated brain diseases, there is pressing need to gain in-depth knowledge about the neurobiology of brain anatomy changes across the life span. Advances in quantitative magnetic resonance imaging sensitive to brain's myelin, iron, and free water content allow for a detailed in vivo investigation of aging-related changes while reducing spurious morphometry differences. Main aim of our study is to link previous morphometry findings in aging to microstructural tissue properties in a large-scale cohort (n = 966, age range 46-86 y). Addressing previous controversies in the field, we present results obtained with different approaches to adjust local findings for global effects. Beyond the confirmation of age-related atrophy, myelin, and free water decreases, we report proportionally steeper volume, iron, and myelin decline in sensorimotor and subcortical areas paralleled by free water increase. We demonstrate aging-related white matter volume, myelin, and iron loss in frontostriatal projections. Our findings provide robust evidence for spatial overlap between volume and tissue property differences in aging that affect predominantly motor and executive networks.

Neuro-Clinical Signatures of Language Impairments after Acute Stroke: A VBQ Analysis of Quantitative Native CT Scans.

OBJECTIVES: Ischemic stroke affects language production and/or comprehension and leads to devastating long-term consequences for patients and their families. Previous studies have shown that neuroimaging can increase our knowledge of the basic mechanisms of language recovery. Currently, models for predicting patients' outcomes have limited use in the clinic for the evaluation and optimization of rehabilitative strategies mostly because that are often based on high-resolution magnetic resonance imaging (MRI) data, which are not always possible to carry out in the clinical routine. Here, we investigate the use of Voxel-Based Morphometry (VBM), multivariate modelling and native Computed Tomography (nCT) scans routinely acquired in the acute stage of stroke for identifying biological signatures that explicate the relationships between brain anatomy and types of impairments. METHODS: 80 stroke patients and 30 controls were included. nCT-scans were acquired in the acute ischemia stage and bedside clinical assessment from board-certified neurologist based on the NIH stroke scale. We use a multivariate Principal Component Analyses (PCA) to identify the brain signatures group the patients according to the presence or absence of impairment and identify the association between local Grey Matter (GM) and White Matter (WM) nCT values with the presence or absence of the impairment. RESULTS: Individual patient's nCT scans were compared to a group of controls' with no radiological signs of stroke to provide an automated delineation of the lesion. Consistently across the whole group the regions that presented significant difference GM and WM values overlap with known areas that support language processing. CONCLUSION: In summary, the method applied to nCT scans performed in the acute stage of stroke provided robust and accurate information about brain lesions' location and size, as well as quantitative values. We found that nCT and VBQ analyses are effective for identifying neural signatures of concomitant language impairments at the individual level, and neuroanatomical maps of aphasia at the population level. The signatures explicate the neurophysiological mechanisms underlying aetiology of the stroke. Ultimately, similar analyses with larger cohorts could lead to a more integrated multimodal model of behaviour and brain anatomy in the early stage of ischemic stroke.

Sensing sociability: Individual differences in young adults' conversation, calling, texting, and app use behaviors in daily life.

Sociability as a disposition describes a tendency to affiliate with others (vs. be alone). Yet, we know relatively little about how much social behavior people engage in during a typical day. One challenge to documenting social behavior tendencies is the broad number of channels over which socializing can occur, both in-person and through digital media. To examine individual differences in everyday social behavior patterns, here we used smartphone-based mobile sensing methods (MSMs) in four studies (total N = 926) to collect real-world data about young adults' social behaviors across four communication channels: conversations, phone calls, text messages, and use of messaging and social media applications. To examine individual differences, we first focused on establishing between-person variability in daily social behavior, examining stability of and relationships among daily sensed social behavior tendencies. To explore factors that may explain the observed individual differences in sensed social behavior, we then expanded our focus to include other time estimates (e.g., times of the day, days of the week) and personality traits. In doing so, we present the first large-scale descriptive portrait of behavioral sociability patterns, characterizing the degree to which young adults engaged in social behaviors and mapping these behaviors onto self-reported personality dispositions. Our discussion focuses on how the observed sociability patterns compare to previous research on young adults' social behavior. We conclude by pointing to areas for future research aimed at understanding sociability using mobile sensing and other naturalistic observation methods for the assessment of social behavior. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Trajectories of brain remodeling in temporal lobe epilepsy.

Temporal lobe epilepsy has been usually associated with progressive brain atrophy due to neuronal cell loss. However, recent animal models demonstrated a dual effect of epileptic seizures with initial enhancement of hippocampal neurogenesis followed by abnormal astrocyte proliferation and neurogenesis depletion in the chronic stage. Our aim was to test for the hypothesized bidirectional pattern of epilepsy-associated brain remodeling in the context of the presence and absence of mesial temporal lobe sclerosis. We acquired MRIs from a large cohort of mesial temporal lobe epilepsy patients with or without hippocampus sclerosis on radiological examination. The statistical analysis tested explicitly for common and differential brain patterns between the two patients' cohorts and healthy controls within the computational anatomy framework of voxel-based morphometry. The main effect of disease was associated with continuous hippocampus volume loss ipsilateral to the seizure onset zone in both temporal lobe epilepsy cohorts. The post hoc simple effects tests demonstrated bilateral hippocampus volume increase in the early epilepsy stages in patients without hippocampus sclerosis. Early age of onset and longer disease duration correlated with volume decrease in the ipsilateral hippocampus. Our findings of seizure-induced hippocampal remodeling are associated with specific patterns of mesial temporal lobe atrophy that are modulated by individual clinical phenotype features. Directionality of hippocampus volume changes strongly depends on the chronicity of disease. Specific anatomy differences represent a snapshot within a progressive continuum of seizure-induced structural remodeling.