bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linoleic acid supplementation reverses microglial response to diet induced-obesity at hypothalamic, cortical and subcortical level in mice
Authors: Jantzen Lucas , Dumontoy Stéphanie , Ramadan Bahrie , Houdayer Christophe , Haffen Emmanuel , Hichami Aziz , Khan Naim , Van Waes Vincent , Cabeza Lidia 
Published: July 2023

AbstractObesity is a major risk factor for neuropsychiatric alterations. Fatty regimes lead to systemic and cerebral inflammation, the latest acting through lipotoxicity on hypothalamic structures controlling energy homeostasis. Since literature points to a protective effect of linoleic acid (LA) on mood disorders through the regulation of systemic inflammation, we investigated how five weeks of LA supplementation modulates emotional behaviour and microglia-related neuroinflammation. C57BL/6j mice were fed with either a high-fat (HFD) or a standard diet for 12 weeks, underwent a battery of behavioural tests and were subsequently sacrificed for immunofluorescence staining targeting microglia-specific calcium-binding proteins (IBA-1). Neuroinflammation severity was approximated in multiple hypothalamic, cortical and subcortical regions. Our results show an anxio-depressive-like effect of sustained HFD that neither was alleviated nor worsen with LA supplementation. Increased IBA-1 expression in the HFD group was substantially reversed with LA supplementation. Thus, our results suggest anti-neuroinflammatory properties of LA not restricted to hypothalamic areas, but also evident at the cortical and subcortical level. This study is therefore relevant in the frame of obesity and neuropsychiatric disorders with a neuroinflammatory basis. Further investigation may provide more information to justify dietary strategies aiming at reducing the impact of obesity associated comorbidities.
Neural network models for the evolution of associative learning
Authors: Salinas Emiliano Méndez , Weissing Franz J. , Kozielska Magdalena 
Published: July 2023

AbstractThe ability to learn from past experience is an important adaptation, but how natural selection shapes learning is not well understood. Here, we investigate the evolution of associative learning (the association of stimuli with rewards) by a modelling approach that is based on the evolution of neural networks (NNs) underlying learning. Individuals employ their genetically encoded NN to solve a learning task with fitness consequences. NNs inducing more efficient learning have a selective advantage and spread in the population. We show that in a simple learning task, the evolved NNs, even those with very simple architecture, outperform well-studied associative learning rules, such as the Rescorla-Wagner rule. During their evolutionary trajectory, NNs often pass a transitional stage where they functionally resemble Rescorla-Wagner learning, but further evolution shapes them to approximate the theoretically optimal learning rule. Networks with a simple architecture evolve much faster and tend to outperform their more complex counterparts on a shorter-term perspective. Also, on a longer-term perspective network complexity is not a reliable indicator of evolved network performance. These conclusions change somewhat when the learning task is more challenging. Then the performance of many evolved networks is not better than that of the Rescorla-Wagner rule; only some of the more complex networks reach a performance level close to the optimal Bayesian learning rule. In conclusion, we show that the mechanisms underlying learning influence the outcome of evolution. A neural-network approach allows for more flexibility and a wider set of evolutionary outcomes than most analytical studies, while at the same time, it provides a relatively straightforward and intuitive framework to study the learning process.
Computational Engineering of a Therapeutic Antibody to Inhibit Multiple Mutants of HER2 Without Compromising Inhibition of the Canonical HER2
Authors: Peled Sapir , Guez-Haddad Julia , Biton Nevet Zur , Nimrod Guy , Fischman Sharon , Fastman Yair , Ofran Yanay 
Published: July 2023

AbstractGenomic germline and somatic variations may impact drug binding and even lead to resistance. However, designing a different drug for each mutant may not be feasible. In this study, we identified the most common cancer somatic mutations from the Catalogue of Somatic Mutations in Cancer (COSMIC) that occur in structurally characterized binding sites of approved therapeutic antibodies. We found two HER2 mutations, S310Y and S310F, that substantially compromise binding of Pertuzumab, a widely used therapeutics, and lead to drug resistance. To address these mutations, we designed a multi-specific version of Pertuzumab, that retains original function while also bindings these HER2 variants. This new antibody is stable and inhibits HER3 phosphorylation in a cell-based assay for all three variants, suggesting it can inhibit HER2-HER3 dimerization in patients with any of the variants. This study demonstrates how a small number of carefully selected mutations can add new specificities to an existing antibody without compromising its original function, creating a single therapeutic antibody that targets multiple common variants, making a drug that is not personalized yet its activity may be.
Multilayer Label Free Non-Faradic Electrochemical Impedance Immunosensor for Cortisol Detection
Authors: Gupta Chinmay , Pattanayek Sudip Kumar , Mukherjee Biswarup , Kumar Sachin 
Published: July 2023

AbstractCortisol, a well-known psychological stress biomarker, produced by the hypothalamic-pituitary-adrenal system, tends to intensify with stressors. Prolonged overexpression of cortisol leads to chronic stress that causes disparities in the proper functioning of the human body. Thus, there is a huge demand for developing a rapid cortisol detection system. Several point-of-care diagnostic techniques are available for rapid cortisol detection, such as electrochemical sensing, which works on changes in the electrical properties due to the binding of an analyte with a biorecognition element. Researchers have used different electrochemical methodologies such as cyclic voltammetry (CV), chronoamperometry, and faradic electrochemical impedance spectroscopy (EIS) for the detection of cortisol, but usage of external redox active reagents, low sensitivity, limited dynamic range, and electrode fouling nature limits their use. Hence, we reported a label-free and non-invasive cortisol detection using non-faradic EIS. A novel multilayer immunosensor was fabricated on PEDOT: PSS coated ITO glass by functionalizing with cortisol antibodies. Specific and rapid detection of cortisol was measured by monitoring the change in impedance in a dynamic range from 50-200 ng/mL. We envision the developed immunosensor has the potential for new developments in stress monitoring, disease prognosis, and enable personalized care.HighlightsNovel PEDOT: PSS based multilayer immunosensor for cortisol detectionImpedance based label free detection of cortisol using non-faradic EISPresentation of detailed multilayer immunosensor fabrication, experimental detection, and equivalent circuit model with working mechanismCortisol detection in a dynamic range of 50-200 ng/mLGraphical Abstract
Non-additive genetic components contribute significantly to population-wide gene expression variation
Authors: Tsouris Andreas , Brach Gauthier , Schacherer Joseph , Hou Jing 
Published: July 2023

SummaryGene expression variation, an essential step between genomic variation and phenotypic landscape, is collectively controlled by local (cis) and distant (trans) regulatory changes. Nevertheless, how these regulatory elements differentially influence the heritability of expression traits remains unclear. Here, we bridge this gap by analyzing the transcriptomes of a large diallel panel consisting of 323 unique hybrids originated from genetically divergent yeast isolates. We estimated the broad- and narrow-sense heritability across 5,087 transcript abundance traits and showed that non-additive components account for 36% of the phenotypic variance on average. By comparing allelic expression ratios in the hybrid and the corresponding parental pair, we identified regulatory changes in 25% of all cases, with a majority acting intrans. We further showed thattrans-regulation could underlie coordinated expression variation across highly connected genes, resulting in significantly higher non-additive variance and most likely in some of the missing heritability of gene expression traits.HighlightsDiallel panel for dissecting genetic components underlying gene expression variationNon-additive components account for 36% of gene expression trait heritabilityMostcis-regulatory variation is buffered by additionaltrans-acting variantsGenes undertrans-regulation show high non-additive variance and functional coherence
Discovering Immunoreceptor Coupling and Organization Motifs (ICOMs)
Authors: Reth Michael 
Published: July 2023

AbstractThe recently determined cryo-EM structures of the T cell antigen receptor (TCR) and B cell antigen receptor (BCR) show in molecular details the interactions of the ligand-binding part with the signaling subunits but they do not reveal the signaling mechanism of these antigen receptors. Without knowing the molecular basis of antigen sensing by these receptors, a rational design of optimal vaccines is not possible. The existence of conserved amino acids (AAs) that are not involved in the subunit interaction suggests that antigen receptors form higher complexes and/or have lateral interactors that control their activity. Here, I describe evolutionary conserved leucine zipper (LZ) motifs within the transmembrane domains (TMD) of antigen and coreceptor components that are likely to be involved in the oligomerization and lateral interaction of antigen receptor complexes on T and B cells. These immunoreceptor coupling and organization motifs (ICOMs) are also found within the TMDs of other important receptor types and viral envelope proteins. This discovery suggests that antigen receptors do not function as isolated entities but rather as part of an ICOM-based interactome that controls their nanoscale organization on resting cells and their dynamic remodeling on activated lymphocytes.
One-Shot Random Forest Model Calibration for Hand Gesture Decoding
Authors: Jiang Xinyu , Ma Chenfei , Nazarpour Kianoush 
Published: July 2023

AbstractObjectiveMost existing machine learning models for myoelectric control require a large amount of data to learn user-specific characteristics of the electromyographic (EMG) signals, which is burdensome. Our objective is to develop an approach to enable the calibration of a pre-trained model with minimal data from a new myoelectric user.ApproachWe trained a random forest model with EMG data from 20 people collected during the performance of multiple hand grips. To adapt the decision rules for a new user, first, the branches of the pre-trained decision trees were pruned using the validation data from the new user. Then new decision trees trained merely with data from the new user were appended to the pruned pre-trained model.ResultsReal-time myoelectric experiments with 18 participants over two days demonstrated the improved accuracy of the proposed approach when compared to benchmark user-specific random forest and the linear discriminant analysis models. Furthermore, the random forest model that was calibrated on day one for a new participant yielded significantly higher accuracy on day two, when compared to the benchmark approaches, which reflects the robustness of the proposed approach.SignificanceThe proposed model calibration procedure is completely source-free, that is, once the base model is pre-trained, no access to the source data from the original 20 people is required. Our work promotes the use of efficient, explainable, and simple models for myoelectric control.
Imperceptible gamma-band sensory stimulation enhances episodic memory retrieval
Authors: Griffiths Benjamin J. , Weinert Daniel E. , Jensen Ole , Staudigl Tobias 
Published: July 2023

AbstractEnhanced gamma activity (30-100Hz) coincides with the successful recall of episodic memories, but it remains unknown whether this oscillatory activity is a cause or a consequence of the retrieval process. To address this question, we asked human participants to complete a paired associates memory task while undergoing sensory stimulation (at 65Hz, 43.3Hz and 32.5Hz). We observed that 65Hz and 32.5Hz sensory stimulation enhances recall compared to a baseline condition without stimulation. No similar effect was observed following 43.3Hz stimulation. Notably, while almost all participants could perceive 32.5Hz and 43.3Hz sensory stimulation, only a small proportion of participants (∼10%) could perceive the 65Hz visual flicker, suggesting 65Hz sensory stimulation acts as an imperceptible intervention to enhance recall. To understand the dual action of 65Hz and 32.5Hz sensory stimulation on recall, we built three pyramidal-interneuronal network gamma (PING) models and drove them using the same stimulation protocols as in the behavioural task. The behavioural results could be reproduced by stimulating an endogenous ∼32Hz oscillation, but not by stimulating an endogenous ∼65Hz oscillation nor by stimulating a network without an endogenous oscillation. These results suggest that imperceptible 65Hz sensory stimulation enhances recall by harmonically entraining an endogenous ∼32.5Hz oscillation. Based on these findings, we propose that “slow” gamma oscillations play a causal role in episodic memory retrieval.
Human primary motor cortex indexes the onset of subjective intention in brain-machine-interface mediated actions
Authors: Noel Jean-Paul , Bockbrader Marcia , Colachis Sam , Solca Marco , Orepic Pavo , Ganzer Patrick D. , Haggard Patrick , Rezai Ali , Blanke Olaf , Serino Andrea 
Published: July 2023

AbstractSelf-initiated behavior is accompanied by the experience of willing our actions. Here, we leverage the unique opportunity to examine the full intentional chain – from will (W) to action (A) to environmental effects (E) - in a tetraplegic person fitted with a primary motor cortex (M1) brain machine interface (BMI) generating hand movements via neuromuscular electrical stimulation (NMES). This combined BMI-NMES approach allowed us to selectively manipulate each element of the intentional chain (W, A, and E) while performing extra-cellular recordings and probing subjective experience. Our results reveal single-cell, multi-unit, and population-level dynamics in human M1 that encode W and may predict its subjective onset. Further, we show that the proficiency of a neural decoder in M1 reflects the degree of W-A binding, tracking the participant’s subjective experience of intention in (near) real time. These results point to M1 as a critical node in forming the subjective experience of intention and demonstrate the relevance of intention-related signals for translational neuroprosthetics.
Genomic Characterization and Gene Bank Curation ofAegilops: The Wild Relatives of Wheat
Authors: Adhikari Laxman , Raupp John , Wu Shuangye , Koo Dal-Hoe , Friebe Bernd , Poland Jesse 
Published: July 2023

AbstractGenetic diversity found in crop wild relatives is critical to preserve and utilize for crop improvement to achieve sustainable food production amid climate change and increased demand. We genetically characterized a large collection of 1,041Aegilopsaccessions distributed among 23 different species using more than 45K single nucleotide polymorphisms identified by genotyping-by-sequencing (GBS). The Wheat Genetics Resource Center (WGRC)Aegilopsgermplasm collection was curated through the identification of misclassified and redundant accessions. There were 49 misclassified and 28 sets of redundant accessions within the four diploid species. The curated germplasm sets now have improved utility for genetic studies and wheat improvement. We constructed a phylogenetic tree and PCA cluster for allAegilopsspecies together, giving one of the most comprehensive views ofAegilops. TheSitopsissection and the U genomeAegilopsclade were further scrutinized with in-depth population analysis. The genetic relatedness among the pair ofAegilopsspecies provided strong evidence for the species evolution, speciation and diversification. We inferred genome symbols for two speciesAe.neglectaandAe.columnarisbased on the sequence read mapping and the presence of segregating loci on the pertinent genomes as well as genetic clustering. The high genetic diversity observed amongAegilopsspecies indicated that the genus could play an even greater role in providing the critical need for untapped genetic diversity for future wheat breeding and improvement. To fully characterize theseAegilopsspecies, there is an urgent need to generate reference assemblies for these wild wheats, especially for the polyploidAegilops.One-sentence summaryGenotypingAegilopsspecies, the wild relatives of wheat, has revealed high genetic diversity and unique evolutionary relationships among theAegilopsand with wheat, giving insight into the effective use of these germplasms for bread wheat improvement.
Optogenetic Stimulation of Single Ganglion Cells in the Living Primate Fovea
Authors: Murphy Peter J. , McGregor Juliette E. , Xu Zhengyang , Yang Qiang , Merigan William , Williams David R. 
Published: July 2023

AbstractThough the responses of the rich variety of retinal ganglion cells (RGCs) reflect the totality of visual processing in the retina and provide the sole conduit for those processed responses to the brain, we have much to learn about how the brain uses these signals to guide behavior. An impediment to developing a comprehensive understanding of the role of retinal circuits in behavior is the paucity of causal studies in the intact primate visual system. Here we demonstrate the ability to optogenetically activate individual RGCs with flashes of light focused on single RGC somasin vivo, without activation of neighboring cells. The ability to selectively activate specific cells is the first step toward causal experiments that directly link retinal circuits to visual experience and behavior.
Identification of a botulinum neurotoxin-like gene cluster inBacillus toyonensis
Authors: Wei Xin , Lobb Briallen , Wang Kang , Dong Min , Doxey Andrew C. 
Published: July 2023

AbstractClostridial neurotoxins, which include botulinum neurotoxins (BoNTs) and tetanus neurotoxin (TeNT) are the most potent toxins known, and are the causative agents of the neuroparalytic diseases, botulism and tetanus. Until recently, the clostridial neurotoxin family was restricted to the genusClostridium, but members of this protein family have been found in a growing number of non-Clostridiumspecies includingWeissella, Enterococcus, andParaclostridium. Here, we report the bioinformatic identification and analysis of a novel clostridial neurotoxin homolog in aBacillus toyonensisgenome recently deposited into the NCBI Genbank database. This putative toxin shares 26-29% identity with its closest BoNT relatives, suggesting that it is likely a novel BoNT-like toxin. It possesses key functional motifs (e.g., HExxH) indicative of toxin protease activity, contains the four characteristic BoNT domains, and is located in a BoNT-like genomic neighborhood containing the upstream non-toxic non-hemagglutinin (NTNH) gene as well as several P47-related genes. Phylogenetically, the toxin clusters as a divergent member of the recently discovered lineage of BoNT-like toxins that includes BoNT/X, BoNT/En, and the insecticidal PMP1. Genomic analysis of theB. toyonensisisolate CH177 revealed additional virulence factors and toxin genes indicative of potential pathogenicity targeting an unknown host species. TheBacillus toyonensisBoNT-like protein (BTNT) adds to a growing number of non-clostridial BoNT-like toxins, adding further information on the intriguing phylogenetic distribution and evolutionary history of the most potent toxins known.
Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model
Authors: Sisk Thomas , Robustelli Paul 
Published: July 2023

AbstractA central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long-time scale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAILreversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We do not, however, find evidence for the existence of canonical conformational selection or induced fit binding pathways. We observe four kinetically separated native-like bound states that interconvert on time scales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAILhelices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or “fuzzy”, protein complex.
Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses
Authors: Song Dongyuan , Chen Siqi , Lee Christy , Li Kexin , Ge Xinzhou , Li Jingyi Jessica 
Published: July 2023

AbstractDouble dipping is a well-known pitfall in single-cell and spatial transcriptomics data analysis: after a clustering algorithm finds clusters as putative cell types or spatial domains, statistical tests are applied to the same data to identify differentially expressed (DE) genes as potential cell-type or spatial-domain markers. Because the genes that contribute to clustering are inherently likely to be identified as DE genes, double dipping can result in false-positive cell-type or spatial-domain markers, especially when clusters are spurious, leading to ambiguously defined cell types or spatial domains. To address this challenge, we propose ClusterDE, a statistical method designed to identify post-clustering DE genes as reliable markers of cell types and spatial domains, while controlling the false discovery rate (FDR) regardless of clustering quality. The core of ClusterDE involves generating synthetic null data as anin siliconegative control that contains only one cell type or spatial domain, allowing for the detection and removal of spurious discoveries caused by double dipping. We demonstrate that ClusterDE controls the FDR and identifies canonical cell-type and spatial-domain markers as top DE genes, distinguishing them from housekeeping genes. ClusterDE’s ability to discover reliable markers, or the absence of such markers, can be used to determine whether two ambiguous clusters should be merged. Additionally, ClusterDE is compatible with state-of-the-art analysis pipelines like Seurat and Scanpy.