bluuebunny/crossref_metadata_2025_split huggingface dataset:
Frequency coding of multisensory integration in the local field potentials of the medial pulvinar
Authors: Vittek Anne-Laure , Juan Cécile , Gaillard Corentin , Mercier Manuel , Girard Pascal , Ben Hamed Suliann , Cappe Céline 
Published: July 2024

AbstractThe pulvinar is a posterior thalamic nucleus, with a heterogeneous anatomo-functional organization. It is divided into four parts, including the medial pulvinar, which is densely connected with primary unisensory and multisensory cortical regions, and subcortical structures, including the superior colliculus. Based on this connectivity, the medial pulvinar may play an important role in sensory processing and multisensory integration. However, its contribution to multisensory integration has rarely been directly investigated. To fill this knowledge gap, two macaque monkeys were trained on a fixation task, during which auditory, visual and audiovisual stimuli were presented. We characterize local field potentials of the medial pulvinar associated with these stimuli. In the temporal domain, we describe an early and a late period showing multisensory integration, both dominated by sub-additive processes (the audiovisual response is inferior to the sum of the unisensory responses). In the frequency domain, multisensory integration, mostly sub-additive, is predominant in the lower frequencies (90% of recorded signals in 4.5-8.5Hz and 96% in 8.5-20Hz). Prevalence largely decreases in high frequencies (54% in 35-60Hz, 37% in 60-120Hz). This suggests that the medial pulvinar is a multisensory hub, integrating visual and auditory information in different frequency bands and contributing to cortico-pulvino-cortical multisensory computational loops.
Adolescent choices and caregiver roles: Understanding individual and interpersonal influences on sexual decision-making in South Africa
Authors: Makkan Heeran , Machira Yvonne Wangui , Mthembu Funeka , Masibi Omphile , Molefe Thuso , Maenetje Pholo , Muturi-Kioi Vincent , Price Matt A. , Edward Vinodh Aroon , Chetty-Makkan Candice 
Published: July 2024

AbstractSouth African adolescents are at-risk for HIV infection. Understanding the factors influencing sexual decision-making is crucial for developing effective HIV prevention strategies. We conducted a qualitative study with adolescents and caregivers in Rustenburg, South Africa to explore individual and interpersonal factors that influence adolescent sexual decision-making. Focus Group Discussions (FGDs) were conducted in English and Setswana with 17 adolescents (13 females and 4 males) and 19 caregivers (17 females and 2 males) between April and July 2018. Thematic analysis revealed that while adolescents had access to sexual education from various sources, where the knowledge does not translate into healthy sexual decision-making. A contributing barrier was the lack of effective communication and support between caregivers and adolescents in discussing topics related to sexual activity. Although adolescents expressed a strong need to be understood and supported by caregivers regarding their sexual activity, there was perceived distrust, judgemental attitude from caregivers, poor role models of a father figure, and the traditional taboo of having these discussions with caregivers. While female adolescents and female caregivers discussed sensitive matters, this type of communication was limited with adolescent males. Male adolescents were uncomfortable communicating with either caregiver, fearing caregiver judgemental attitudes and being misunderstood. Female caregivers perceived male caregiver roles to be absent and non-engaging when it came to adolescent education and support in sexual matters. Caregivers desired to support their children, yet they seemed to doubt their skills. Communication tools and guidance on how adolescents and caregivers could communicate about sensitive matters could create enabling environments for adolescents to make informed, healthy decisions regarding their risky sexual behaviours. To address adolescent intention-behaviour gap, future interventions could consider gain-framed messaging within intervention packages to promote healthy sexual choices.
Fecal microbiome predicts treatment response after the initiation of semaglutide or empagliflozin uptake
Authors: Klemets Annabel , Reppo Ingrid , Krigul Kertu Liis , Volke Vallo , Aasmets Oliver , Org Elin 
Published: July 2024

AbstractContextThe gut microbiome has been shown to be in a bidirectional interaction with type 2 diabetes medications that have been in clinical use for several decades. However, the bidirectional effects of novel type 2 diabetes drugs semaglutide, empagliflozin, and the gut microbiome have yet to be clearly described.ObjectiveWe investigate the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, we analyze whether the pre-treatment gut microbiome can predict the treatment efficacy.MethodsGut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis. Subjects additionally donated plasma and urine samples for quantitative measurement of clinical markers before treatment initiation and at Months 3 and 12. Repeated measures ANOVA paired with paired t-tests were used to analyze the effects of drug initiation on the gut microbiome. Pearson correlation was used to identify microbial features associated with the change in clinical parameters.ResultsSemaglutide and empagliflozin use is associated with changes in the gut microbiome after treatment initiation, but changes in microbial diversity were not detected. The baseline gut microbiome predicted changes in glycohemoglobin for semaglutide and empagliflozin users.ConclusionOur findings suggest that semaglutide and empagliflozin impact the gut microbial community during treatment. In addition, the baseline gut microbiome can predict semaglutide treatment effects.
Introduction of Dengue Virus Serotype 3 in the Afar Region, Ethiopia
Authors: Mekonnen Feleke , Khan Bilal A. , Nibret Endalkachew , Munshea Abaineh , Tsega Daniel , Endalamaw Demeke , Tadesse Senait , Yismaw Gizachew , Lankir Damtie , Ali Jemal , Ulinici Mariana , Orsini Emanuele , Susnjar Ursa , Carletti Tea , Licastro Danilo , Bitew Molalegne , Giovanetti Marta , Marcello Alessandro 
Published: July 2024

AbstractThe genetic analysis of the Dengue virus circulating in Ethiopia’s Afar region, in 2023, identified three distinct introductions with spatiotemporal clustering linked to genomes from Asia and Italy. These findings are crucial for enhancing prevention and control strategies, reinforcing the necessity to provide sustainable tools for genomic epidemiology in Africa.
Automated, Objective Speech and Language Markers of Longitudinal Changes in Psychosis Symptoms
Authors: Tang Sunny X. , Spilka Michael J. , John Majnu , Birnbaum Michael L. , Saito Ema , Berretta Sarah A. , Behbehani Leily M. , Liberman Mark Y. , Malhotra Anil K. , Simpson William , Kane John M. 
Published: July 2024

AbstractBackground and HypothesesWe sought to evaluate the ability of automated speech and language features to track fluctuations in the major psychosis symptoms domains:Thought Disorder, Negative Symptoms, andPositive Symptoms.Study DesignSixty-six participants with psychotic disorders were longitudinally assessed soon after inpatient admission, at discharge, and at 3- and 6-months. Psychosis symptoms were measured with semi-structured interviews and standardized scales. Recordings were collected from paragraph reading, fluency, picture description, and open-ended tasks. Longitudinal relationships between psychosis symptoms and 357 automated speech and language features were analyzed using a single component score and as individual features, using linear mixed models.Study ResultsAll three psychosis symptom domains demonstrated significant longitudinal relationships with the single component score.Thought Disorderwas particularly related to features describing more subordinated constructions, less efficient identification of picture elements, and decreased semantic distance between sentences.Negative Symptomswas related to features describing decreased speech complexity.Positive Symptomsappeared heterogeneous, withSuspiciousnessrelating to greater use of nouns, andHallucinationsrelated to decreased semantic distances. These relationships were largely robust to interactions with gender and race. However, interactions with timepoint revealed variable relationships during different phases of illness (acute vs. stable).ConclusionsAutomated speech and language features show promise as scalable, objective markers of psychosis severity. The three symptom domains appear to be distinguishable with different features. Detailed attention to clinical setting and patient population is needed to optimize clinical translation; there are substantial implications for facilitating differential diagnosis, improving psychosis outcomes and enhancing therapeutic discovery.
Evaluating the Potential of Wearable Technology in Early Stress Detection: A Multimodal Approach
Authors: Darwish Basil A. , Salem Nancy M. , Kareem Ghada , Mahmoud Lamees N. , Sadek Ibrahim 
Published: July 2024

AbstractStress can adversely impact health, leading to issues like high blood pressure, heart diseases, and a compromised immune system. Consequently, using wearable devices to monitor stress is essential for prompt intervention and effective management. This study investigates the efficacy of wearable devices in the early detection of psychological stress, employing both binary and five-class classification models. Significant correlations were observed between stress levels and physiological signals, including Electrocardiogram (ECG), Electrodermal Activity (EDA), and Respiration (RESP), establishing these modalities as reliable biomarkers for stress detection. Utilizing the publicly available Wearable Stress and Affect Detection (WESAD) dataset, we employed two ensemble methods, Majority Voting (MV) and Weighted Averaging (WA), to integrate these signals, achieving maximum accuracies of 99.96% for binary classification and 99.59% for five-class classification. This integration significantly enhances the accuracy and robustness of the stress detection system. Furthermore, ten different classifiers were evaluated, and hyperparameter optimization and K-fold cross-validation ranging from 3-fold to 10-fold were applied. Both time-domain and frequency-domain features were examined separately. A review of commercially available wearable devices supporting these modalities was also conducted, resulting in recommendations for optimal configurations for practical applications. Our findings highlight the potential of multimodal wearable devices in advancing the early detection and continuous monitoring of psychological stress, with significant implications for future research and the development of improved stress detection systems.
Accurate Predictions of Liquid-Liquid Phase Separating Proteins at Single Amino Acid Resolution
Authors: Monti Michele , Fiorentino Jonathan , Miltiadis-Vrachnos Dimitrios , Bini Giorgio , Cotrufo Tiziana , de Groot Natalia Sanchez , Armaos Alexandros , Tartaglia Gian Gaetano 
Published: July 2024

AbstractLiquid-liquid phase separation (LLPS) is a molecular mechanism that leads to the formation of membraneless organelles inside the cell. Despite recent advances in the experimental probing and computational prediction of proteins involved in this process, the identification of the protein regions driving LLPS and the prediction of the effect of mutations on LLPS are lagging behind.Here, we introduce catGRANULE 2.0 ROBOT (R - Ribonucleoprotein, O - Organization, in B - Biocondensates, O - Organelle, T - Types), an advanced algorithm for predicting protein LLPS at single amino acid resolution. Integrating physico-chemical properties of the proteins and structural features derived from AlphaFold models, catGRANULE 2.0 ROBOT significantly surpasses traditional sequence-based and state-of-the-art structure-based methods in performance, achieving an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.76 or higher. We present a comprehensive evaluation of the algorithm across multiple organisms and cellular components, demonstrating its effectiveness in predicting LLPS propensities at the single amino acid level and the impacts of mutations on LLPS. Our results are robustly supported by experimental validations, including immunofluorescence microscopy images from the Human Protein Atlas.catGRANULE 2.0 ROBOT’s potential in protein design and mutation control can improve our understanding of proteins’ propensity to form subcellular compartments and help develop strategies to influence biological processes through LLPS. catGRANULE 2.0 ROBOT is freely available athttps://tools.tartaglialab. com/catgranule2.
ALS molecular subtypes are a combination of cellular, genetic, and pathological features learned by deep multiomics classifiers
Authors: O’Neill Kathryn , Shaw Regina , Bolger Isobel ,   NYGC ALS Consortium, Tam Oliver , Phatnani Hemali , Hammell Molly Gale 
Published: July 2024

AbstractAmyotrophic Lateral Sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this general heterogeneity, several common factors have been identified. For example, nearly all patients show pathological accumulations of phosphorylated TDP-43 protein in affected regions of the motor cortex and spinal cord. Moreover, large patient cohort studies have revealed that most patient samples can be grouped into a small number of ALS subtypes, as defined by their transcriptomic profiles. These ALS molecular subtypes can be grouped by whether postmortem motor cortex samples display signatures of: mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or dense TDP-43 pathology and associated transposable element de-silencing (ALS-TE). In this study, we have built a deep layer ALS neural network classifier (DANcer) that has learned to accurately assign patient samples to these ALS subtypes, and which can be run on either bulk or single-cell datasets. Upon applying this classifier to an expanded ALS patient cohort from the NYGC ALS Consortium, we show that ALS Molecular Subtypes are robust across clinical centers, with no new subtypes appearing in a cohort that has quadrupled in size. Signatures from two of these molecular subtypes strongly correlate with disease duration: ALS-TE signatures in cortex and ALS-Glia signatures in spinal cord, revealing molecular correlates of clinical features. Finally, we use single nucleus RNA sequencing to reveal the cell type-specific contributions to ALS subtype, as determined by our single-cell classifier (scDANCer). Single-cell transcriptomes reveal that ALS molecular subtypes are recapitulated in neurons and glia, with both ALS-wide shared alterations in each cell type as well as ALS subtype-specific alterations. In summary, ALS molecular subtypes: (1) are robust across large cohorts of sporadic and familial ALS patient samples, (2) represent a combination of cellular, genetic, and pathological features, and (3) correlate with clinical features of ALS.Abstract FigureFigure 0:Graphical Abstract - ALS molecular subtypes are a combination of cellular, genetic, and pathological features learned by deep multiomics classifiers.
Structures of TGF-β with betaglycan and the signaling receptors reveal the mechanism whereby betaglycan potentiates receptor complex assembly and signaling
Authors: Wieteska Łukasz , Taylor Alexander B. , Punch Emma , Coleman Jonathan A. , Conway Isabella O. , Lin Yeu-Farn , Byeon Chang-Hyeock , Hinck Cynthia S. , Krzysiak Troy , Ishima Rieko , López-Casillas Fernando , Cherepanov Peter , Bernard Daniel J. , Hill Caroline S. , Hinck Andrew P. 
Published: July 2024

AbstractBetaglycan (BG) is a transmembrane co-receptor of the transforming growth factor-β (TGF-β) family of signaling ligands. It is essential for embryonic development and tissue homeostasis and fertility in adults. It functions by enabling binding of the three TGF-β isoforms to their signaling receptors and is additionally required for inhibin A (InhA) activity. Despite its requirement for the functions of TGF-βs and InhA in vivo, structural information explaining BG ligand selectivity and its mechanism of action is lacking. Here, we determine the structure of TGF-β bound both to BG and the signaling receptors, TGFBR1 and TGFBR2. We identify key regions responsible for ligand engagement, which has revealed novel binding interfaces that differ from those described for the closely related co-receptor of the TGF-β family, endoglin, thus demonstrating remarkable evolutionary adaptation to enable ligand selectivity. Finally, we provide a structural explanation for the hand-off mechanism underlying TGF-β signal potentiation.
High-throughput method rapidly characterizes hundreds of novel antibiotic resistance mutations
Authors: Jago Matthew J. , Soley Jake K. , Denisov Stepan , Walsh Calum J. , Gifford Danna R. , Howden Benjamin P. , Lagator Mato 
Published: July 2024

AbstractA fundamental obstacle to tackling the antimicrobial resistance crsisis is identifying mutations that lead to resistance in a given genomic background and environment. We present a high-throughput technique – Quantitative Mutational Scan Sequencing (QMS-Seq) – that enables quantitative comparison of which genes are under antibiotic selection and captures how genetic background influences resistance evolution. We compared fourE. colistrains exposed to ciprofloxacin, cycloserine, or nitrofurantoin and identified 975 resistance mutations, many in genes and regulatory regions not previously associated with resistance. QMS-Seq revealed that multi-drug and antibiotic-specific resistance are acquired through categorically different types of mutations, and that minor genotypic differences significantly influence evolutionary routes to resistance. By quantifying mutation frequency with single base pair resolution, QMS-Seq informs about the underlying mechanisms of resistance and identifies mutational hotspots within genes. Our method provides a way to rapidly screen for resistance mutations while assessing the impact of multiple confounding factors.
Synthesis of K+channel radioligand [18F]5-methyl-3-fluoro-4-aminopyridine and PET imaging in mice
Authors: Sun Yang , Ramos-Torres Karla M. , Takahashi Kazue , Zhang Lauren L. , Brugarolas Pedro 
Published: July 2024

Abstract and Graphical abstract[18F]3-fluoro-4-aminopyridine ([18F]3F4AP) is the first positron emission tomography (PET) radioligand that targets voltage-gated potassium (K+) channels in the brain for imaging demyelination. [18F]3F4AP exhibits high brain penetration, favorable kinetics for PET imaging, and high sensitivity to demyelinating lesions. However, recent studies in awake human subjects indicate lower metabolic stability than in anesthetized animals, resulting in reduced brain uptake. Therefore, there is a need for novel radioligands for K+channels with suitable pharmacological properties and enhanced metabolic stability. Recentin vitrostudies demonstrate that 5-methyl-3-fluoro-4-aminopyridine (5Me3F4AP) exhibits comparable binding affinity to K+channels, pKa, logD, and membrane permeability as 3F4AP, and a slower enzymatic metabolic rate, suggesting its potential as a K+channel PET tracer. In this study, we describe the radiochemical synthesis of [18F]5Me3F4AP using an isotope exchange method from the corresponding 3-fluoro-5-methyl-4-nitropyridine N-oxide, followed by a palladium on carbon mediated hydrogenation of the nitro and N-oxide groups. This method yielded [18F]5Me3F4AP with high purity and acceptable molar activity. PET/CT studies using naïve mice demonstrate that [18F]5Me3F4AP effectively crosses the blood-brain barrier and has comparable kinetics to [18F]3F4AP. These findings strongly suggest that [18F]5Me3F4AP is a promising candidate for neuroimaging applications and warrant further studies to investigate its sensitivity to lesions andin vivometabolic stability.Abstract Figure
Basis of Glucose and Fructose Selectivity in Sugar Transport Proteins
Authors: Andersen Camilla Gottlieb , Bavnhøj Laust , Brag Søren , Driller Jan Heiner , Pedersen Bjørn Panyella 
Published: July 2024

ABSTRACTThe distribution of sugars is crucial for plant energy, signaling, and defense mechanisms. Sugar Transport Proteins (STPs) are Sugar Porters that mediate proton-driven cellular uptake of glucose. Some STPs transport fructose, while others remain highly selective only glucose. What determines this selectivity, distinguishing between compounds with highly similar chemical composition remains unknown. Here, we present the structure ofArabidopsis thalianaSTP6 in an inward occluded conformational state with glucose bound and demonstrate its role as both a glucose and fructose transporter. We perform a comparative analysis of STP6 with the glucose-selective STP10 usingin-vivoandin-vitrosystems, demonstrating how different experimental setups strongly influence kinetic transport properties. Finally, we show that the position of a single methyl group in the binding site is sufficient to shuffle glucose and fructose specificity, providing detailed insights into the fine-tuned dynamics of affinity-induced specificity for sugar uptake. Altogether these findings enhance our understanding of sugar trafficking by Sugar Transport Proteins and lay the groundwork for the future advancements need to support plant engineering and enhance resistance towards pathogens.
Structural characterization of two full length γδ TCR/CD3 complexes
Authors: Hoque Mohammed , Grigg John Benji , Ramlall Trudy , Jones Jennifer , McGoldrick Luke L. , Olson William C. , Lin John C. , Smith Eric , Franklin Matthew C. , Zhang Tong , Saotome Kei 
Published: July 2024

AbstractThe T-cell receptor (TCR)/CD3 complex plays an essential role in the immune response and is a key player in cancer immunotherapies. There are two classes of TCR/CD3 complexes, defined by their TCR chain usage (αβ or γδ). Recently reported structures have revealed the organization of the αβ TCR/CD3 complex, but similar studies regarding the γδ TCR/CD3 complex have lagged behind. Here, we report cryoelectron microscopy (cryoEM) structural analysis of two full-length γδ TCRs, G115 (Vγ9Vδ2) and 9C2 (Vγ5Vδ1), in complex with CD3 subunits. Our results show that the overall subunit organization of the γδ TCR-CD3 complexes is similar to αβ TCRs. However, both γδ TCRs display highly mobile extracellular domains (ECDs), unlike αβ TCRs, which have TCR ECDs that are rigidly coupled to its transmembrane (TM) domains. We corroborate this finding in cells by demonstrating that a γδ T-cell specific antibody can bind a site that would be inaccessible in the more rigid αβ TCR/CD3 complex. Furthermore, we observed that a Vγ5Vδ1 complex forms a TCR γ5-chain mediated dimeric species whereby two TCR/CD3 complexes are assembled. Collectively, these data shed light on γδ TCR/CD3 complex formation and may aid the design of γδ TCR-based therapies.