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.

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.

Biochemical and functional characterization of a periplasmic disulfide oxidoreductase from Neisseria meningitidis essential for meningococcal viability.

TlpAs (thioredoxin-like proteins) are bacterial thioredoxin-like periplasmic disulfide oxidoreductases generally involved in cytochrome c maturation (Ccm) process. They contain a characteristic CXXC active site motif involved in disulfide exchange reaction. In the human pathogenic Neisseria meningitidis species, no TlpA has been characterized so far. In the present study, using an in silico analysis, we identified a putative periplasmic TlpA, called TlpA2. Biochemical and kinetic characterizations of the soluble form of TlpA2, tTlpA2 (truncated TlpA2), were performed. A reduction potential of -0.230 V at pH 7 was calculated, suggesting that TlpA2 acts as a reductant in the oxidative environment of the periplasm. Using a second-order reactive probe, high pKapp (apparent pKa) values were determined for the two cysteines of the SCXXC motif. The tTlpA2 was shown to be efficiently reduced by the N-terminal domain of the DsbD, whereas tTlpA2 reduced a mimetic peptide of cytochrome c' with a catalytic efficiency similar to that observed with other disulfide oxidoreductase like ResA. Moreover, the corresponding gene tlpA2 was shown to be essential for the pathogen viability and able to partially complement a Bordetella pertussis CcsX mutant. Together, these data support an essential role of TlpA2 in the Ccm process in N. meningitidis.

Kinetic evidence that methionine sulfoxide reductase A can reveal its oxidase activity in the presence of thioredoxin.

The mouse methionine sulfoxide reductase A (MsrA) belongs to the subclass of MsrAs with one catalytic and two recycling Cys corresponding to Cys51, Cys198 and Cys206 in Escherichia coli MsrA, respectively. It was previously shown that in the absence of thioredoxin, the mouse and the E. coli MsrAs, which reduce two mol of methionine-O substrate per mol of enzyme, displays an in vitro S-stereospecific methionine oxidase activity. In the present study carried out with E. coli MsrA, kinetic evidence are presented which show that formation of the second mol of Ac-L-Met-NHMe is rate-limiting in the absence of thioredoxin. In the presence of thioredoxin, the overall rate-limiting step is associated with the thioredoxin-recycling process. Kinetic arguments are presented which support the accumulation of the E. coli MsrA under Cys51 sulfenic acid state in the presence of Trx. Thus, the methionine oxidase activity could be operative in vivo without the action of a regulatory protein in order to block the action of Trx as previously proposed.

Methionine sulfoxide reductase: chemistry, substrate binding, recycling process and oxidase activity.

Three classes of methionine sulfoxide reductases are known: MsrA and MsrB which are implicated stereo-selectively in the repair of protein oxidized on their methionine residues; and fRMsr, discovered more recently, which binds and reduces selectively free L-Met-R-O. It is now well established that the chemical mechanism of the reductase step passes through formation of a sulfenic acid intermediate. The oxidized catalytic cysteine can then be recycled by either Trx when a recycling cysteine is operative or a reductant like glutathione in the absence of recycling cysteine which is the case for 30% of the MsrBs. Recently, it was shown that a subclass of MsrAs with two recycling cysteines displays an oxidase activity. This reverse activity needs the accumulation of the sulfenic acid intermediate. The present review focuses on recent insights into the catalytic mechanism of action of the Msrs based on kinetic studies, theoretical chemistry investigations and new structural data. Major attention is placed on how the sulfenic acid intermediate can be formed and the oxidized catalytic cysteine returns back to its reduced form.

Quantifying structure and performance diversity for sets of small molecules comprising small-molecule screening collections.

Using a diverse collection of small molecules we recently found that compound sets from different sources (commercial; academic; natural) have different protein-binding behaviors, and these behaviors correlate with trends in stereochemical complexity for these compound sets. These results lend insight into structural features that synthetic chemists might target when synthesizing screening collections for biological discovery. We report extensive characterization of structural properties and diversity of biological performance for these compounds and expand comparative analyses to include physicochemical properties and three-dimensional shapes of predicted conformers. The results highlight additional similarities and differences between the sets, but also the dependence of such comparisons on the choice of molecular descriptors. Using a protein-binding dataset, we introduce an information-theoretic measure to assess diversity of performance with a constraint on specificity. Rather than relying on finding individual active compounds, this measure allows rational judgment of compound subsets as groups. We also apply this measure to publicly available data from ChemBank for the same compound sets across a diverse group of functional assays. We find that performance diversity of compound sets is relatively stable across a range of property values as judged by this measure, both in protein-binding studies and functional assays. Because building screening collections with improved performance depends on efficient use of synthetic organic chemistry resources, these studies illustrate an important quantitative framework to help prioritize choices made in building such collections.

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).

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).

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.

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.

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.

Structural and biochemical characterization of free methionine-R-sulfoxide reductase from Neisseria meningitidis.

A new family of methionine-sulfoxide reductase (Msr) was recently described. The enzyme, named fRMsr, selectively reduces the R isomer at the sulfoxide function of free methionine sulfoxide (Met-R-O). The fRMsrs belong to the GAF fold family. They represent the first GAF domain to show enzymatic activity. Two other Msr families, MsrA and MsrB, were already known. MsrA and MsrB reduce free Met-S-O and Met-R-O, respectively, but exhibit higher catalytic efficiency toward Met-O within a peptide or a protein context. The fold of the three families differs. In the present work, the crystal structure of the fRMsr from Neisseria meningitidis has been determined in complex with S-Met-R-O. Based on biochemical and kinetic data as well as genomic analyses, Cys(118) is demonstrated to be the catalytic Cys on which a sulfenic acid is formed. All of the structural factors involved in the stereoselectivity of the l-Met-R-O binding were identified and account for why Met-S-O, DMSO, and a Met-O within a peptide are not substrates. Taking into account the structural, enzymatic, and biochemical information, a scenario of the catalysis for the reductase step is proposed. Based on the thiol content before and after Met-O reduction and the stoichiometry of Met formed per subunit of wild type and Cys-to-Ala mutants, a scenario of the recycling process of the N. meningitidis fRMsr is proposed. All of the biochemical, enzymatic, and structural properties of the N. meningitidis fRMsr are compared with those of MsrA and MsrB and are discussed in terms of the evolution of function of the GAF domain.

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).

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.

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.

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.

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.

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.