bluuebunny/crossref_metadata_2025_split huggingface dataset:
BrainCellR: A Precise Cell Type Nomenclature R Package for Comparative Analysis Across Brain Single-Cell Datasets
Authors: Chi Yuhao , Marini Simone , Wang Guang-Zhong 
Published: November 2023

AbstractSingle-cell studies in neuroscience require precise cell type classification and consistent nomenclature that allows for meaningful comparisons across diverse datasets. Current approaches often lack the ability to identify fine-grained cell types and establish standardized annotations at the cluster level, hindering comprehensive understanding of the brain’s cellular composition. To facilitate data integration across multiple models and datasets, we designed BrainCellR. This package provides researchers with a powerful and user-friendly tool for efficient cell type classification and nomination from single-cell transcriptomic data. BrainCellR goes beyond conventional classification approaches by incorporating a standardized nomenclature system for cell types at the cluster level. This feature enables consistent and comparable annotations across different studies, promoting data integration and providing deeper insights into the complex cellular landscape of the brain.Contactsimone.marini@ufl.eduorguangzhong.wang@picb.ac.cn
A small-molecule TrkB ligand improves dendritic spine phenotypes and atypical behaviors in female Rett syndrome mice
Authors: Medeiros Destynie , Ayala-Baylon Karen , Egido-Betancourt Hailey , Miller Eric , Chapleau Christopher , Robinson Holly , Phillips Mary L. , Yang Tao , Longo Frank M. , Li Wei , Pozzo-Miller Lucas 
Published: November 2023

SUMMARYRett syndrome (RTT) is a neurodevelopmental disorder caused by mutations in methyl-CpG-binding protein-2 (MECP2), encoding a transcriptional regulator of many genes, including brain-derived neurotrophic factor (Bdnf). BDNF mRNA and protein levels are lower in RTT autopsy brains and in multiple brain regions ofMecp2-deficient mice, and experimentally increasing BDNF levels improve atypical phenotypes inMecp2mutant mice. Due to the low blood-brain barrier permeability of BDNF itself, we tested the effects of a brain penetrant, small molecule ligand of its TrkB receptors. Appliedin vitro, LM22A-4 increased dendritic spine density in pyramidal neurons in cultured hippocampal slices from postnatal day (P) 7 maleMecp2knockout (KO) mice as much as recombinant BDNF, and both effects were prevented by the TrkB receptor inhibitors K-252a and ANA-12. Consistent with its partial agonist activity, LM22A-4 did not affect spine density in CA1 pyramidal neurons in slice cultures from male wildtype (WT) mice, where typical BDNF levels outcompete its binding to TrkB. To identify neurons of known genotypes in the ‘mosaic’ brain of femaleMecp2heterozygous (HET) mice, we treated 4–6-month-old female MeCP2-GFP WT and HET mice with peripheral injections of LM22A-4 for 4 weeks. Surprisingly, mutant neurons lacking MeCP2-GFP showed dendritic spine volumes comparable to that in WT controls, while MeCP2-GFP-expressing neurons showed larger spines, similar to the phenotype we described in symptomatic maleMecp2KO mice where all neurons lack MeCP2. Consistent with this non-cell-autonomous mechanism, a 4-week systemic treatment with LM22A-4 had an effect only in MeCP2-GFP-expressing neurons in femaleMecp2HET mice, bringing dendritic spine volumes down to WT control levels, and without affecting spines of MeCP2-GFP-lacking neurons. At the behavioral level, we found that femaleMecp2HET mice engaged in aggressive behaviors significantly more than WT controls, which were reduced to WT levels by a 4-week systemic treatment with LM22A-4. Altogether, these data revealed differences in dendritic spine size and altered behaviors inMecp2HET mice, in addition to provide support to the potential usefulness of BDNF-related therapeutic approaches such as the partial TrkB agonist LM22A-4.
Brain-wide Disruptions of Anatomical Connectivity in Antipsychotic-Naïve First Episode Psychosis
Authors: Chopra Sidhant , Levi Priscila T. , Holmes Alexander , Orchard Edwina R. , Segal Ashlea , Francey Shona M. , O’Donoghue Brian , Cropley Vanessa L. , Nelson Barnaby , Graham Jessica , Baldwin Lara , Yuen Hok Pan , Allott Kelly , Alvarez-Jimenez Mario , Harrigan Susy , Pantelis Christos , Wood Stephen J , McGorry Patrick , Fornito Alex 
Published: November 2023

AbstractOBJECTIVEDisruptions of axonal connectivity are thought to be a core pathophysiological feature of psychotic illness, but whether they are present early in the illness, prior to antipsychotic exposure, and whether they can predict clinical outcome remains unknown.METHODSWe acquired diffusion-weighted MRI to map axonal connectivity between each pair of 319 parcellated brain regions in 61 antipsychotic-naive individuals with First Episode Psychosis (FEP; 15-25 years, 46% female) and a demographically matched sample of 27 control participants, along with clinical follow-up data in patients 3 months and 12 months after the scan. We used connectome-wide analyses to map disruptions of inter-regional pairwise connectivity coupled with connectome-based predictive modelling to predict longitudinal change in symptoms and functioning.RESULTSIndividuals with FEP showed disrupted connectivity in a brain-wide network linking all brain regions when compared with controls (pFWE=.03). Baseline structural connectivity significantly predicted change in functioning over 12 months (r =.44;pFWE=.041), such that lower connectivity within fronto-striato-thalamic systems predicted worse functional outcomes.CONCLUSIONSBrain-wide reductions of structural connectivity exist during the early stages of psychotic illness and cannot be attributed to antipsychotic medication. Moreover, baseline measures of structural connectivity can predict change in patient functional outcomes up to one year after engagement with treatment services.
Multi-voxel neuro-reinforcement changes resting-state functional connectivity: A pilot study
Authors: Wang Shawn , Cushing Cody A. , Lau Hakwan , Craske Michelle G. , Taschereau-Dumouchel Vincent 
Published: November 2023

AbstractBackgroundMulti-voxel neuro-reinforcement has been shown to selectively reduce amygdala reactivity in response to feared stimuli, but the precise mechanisms supporting these effects are still unknown. The current pilot study seeks to identify potential intermediaries of change using functional brain connectivity at rest.MethodsIndividuals (N = 11) diagnosed with at least two animal subtype specific phobias took part in a double-blind multi-voxel neuro-reinforcement clinical trial targeting one of two phobic animals, with the untargeted animal as placebo control. Changes in whole-brain resting state functional connectivity from pre-treatment to post-treatment were measured using group ICA. These changes were tested to see if they predicted the previously observed decreases in amygdala reactivity in response to images of target phobic animals.ResultsA common functional connectivity network overlapping with the visual network was identified in resting state data pre-treatment and post-treatment. Significant increases in functional connectivity in this network from pre-treatment to post-treatment were found in higher level visual and cognitive processing regions of the brain. Increases in functional connectivity in these regions also significantly predicted decreases in task-based amygdala reactivity to targeted phobic animals following multi-voxel neuro-reinforcement. Specifically, greater increases of functional connectivity pre-treatment to post-treatment were associated with greater decreases of amygdala reactivity to target phobic stimuli pre-treatment to post-treatment.ConclusionsThese findings provide preliminary evidence that multi-voxel neuro-reinforcement can induce persisting functional connectivity changes in the brain. Moreover, these changes in functional connectivity were not limited to the direct area of neuro-reinforcement, suggesting neuro-reinforcement may change how the targeted region interacts with other brain regions. Identification of these brain regions represent a first step towards explaining the underlying mechanisms of change in previous multi-voxel neuro-reinforcement studies. Future research should seek to replicate these effects in a larger sample size to further assess their role in the effects observed from multi-voxel neuro-reinforcement.
Fetal sexual dimorphism and preeclampsia among twin pregnancies
Authors: Brown Rebekah E. , Noah Akaninyene I. , Hill Ashley V. , Taylor Brandie DePaoli 
Published: November 2023

AbstractBackgroundIn singleton pregnancies, fetal sexual dimorphism has been observed in hypertensive disorders of pregnancy (HDP), particularly preeclampsia, a morbid syndrome that increases risk of adult onset cardiovascular disease for mothers and their offspring. However, few studies have explored the effect of fetal sex on HDP among twin pregnancies.MethodsWe conducted a retrospective cohort study of 1,032 twin pregnancies between 2011 - 2022 using data from a perinatal database that recruits participants from three hospitals in Houston, TX. We categorized pregnancies based on fetal sex pairings into female/female, male/male, and female/male. Pregnancies with a female/female fetal sex were used as our reference group. Our primary outcomes included gestational hypertension, preeclampsia, superimposed preeclampsia, and preeclampsia subtyped by gestational age of delivery. A modified Poisson regression model with robust error variance was used to calculate the relative risk (RR) and 95% confidence interval (CI) for the association between fetal sex pairs and HDP.ResultsAdjusted models of female/male fetal sex pairs were associated with preterm preeclampsia (RR 2.01, 95% CI 1.15-3.53) relative to those with female/female fetuses. No associations with other HDP were observed among pregnancies with male/male fetal sex compared to those with female/female fetal sex pairs.ConclusionsWe found some evidence of sexual dimorphism for preterm preeclampsia among female/male twin pairs. Additional research is needed to understand what biological mechanisms could explain these findings.
E2F transcription factors promote tumorigenicity in pancreatic ductal adenocarcinoma
Authors: Bertonnier-Brouty Ludivine , Andersson Jonas , Kaprio Tuomas , Hagström Jaana , Bsharat Sara , Asplund Olof , Hatem Gad , Haglund Caj , Seppänen Hanna , Prasad Rashmi B , Artner Isabella 
Published: November 2023

AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with limited treatment options, illustrating an urgent need to identify new drugable targets in PDACs. Using the similarities between tumor development and normal embryonic development, which is accompanied by rapid cell expansion, we identified embryonic signalling pathways that were reinitiated during tumor formation and expansion. Here, we report that the transcription factors E2F1 and E2F8 are potential key regulators in PDAC. E2F1 and E2F8 RNA expression is mainly localized in proliferating cells in the developing pancreas and in malignant ductal cells in PDAC. Silencing of E2F1 and E2F8 in PANC-1 pancreatic tumor cells inhibited cell proliferation and impaired cell spreading and migration. Moreover, loss of E2F1 also affected cell viability and apoptosis with E2F expression in PDAC tissues correlating with expression of apoptosis and mitosis pathway genes, suggesting that E2F factors promote cell cycle regulation and tumorigenesis in PDAC cells. In conclusion, our findings show that E2F1 and E2F8 transcription factors regulate cell proliferation, survival, and migration during pancreatic carcinogenesis.
Holistic in silico developability assessment of novel classes of small proteins using publicly available sequence-based predictors
Authors: Pais Daniel A. M. , Mayer Jan-Peter A. , Felderer Karin , Batalha Maria B. , Eichner Timo , Santos Sofia T. , Kumar Raman , Silva Sandra D. , Kaufmann Hitto 
Published: November 2023

AbstractThe development of novel therapeutic proteins is a lengthy and costly process, with an average attrition rate of 91% (Thomas et al., 2021). To increase the probability of success and ensure robust drug supply beyond approval, it is essential to assess the developability profile of new potential drug candidates as early and broadly as possible in development (Jain et al., 2023). Predicting these propertiesin silicois expected to be the next leap in innovation as it would enable significantly reduced development timelines combined with broader screens at lower costs. However, developing predictive algorithms typically requires substantial datasets generated under very defined conditions, a limiting factor especially for new classes of therapeutic proteins that hold immense clinical promise.Here we describe a strategy for assessing the developability of a novel class of small therapeutic Anticalin® proteins using machine learning in conjunction with a knowledge-driven approach. The knowledge-driven approach considers developability attributes such as aggregation propensity, charge variants, immunogenicity, specificity, thermal stability, hydrophobicity, and potential post-translational modifications, to calculate a holistic developability score. Based on sequence-derived descriptors as input parameters we established novel statistical models designed to predict the developability scores for Anticalin proteins. The best models yielded low root mean square errors across the entire dataset and were further validated by removing input data from individual screening campaigns and predicting developability scores for those drug candidates.The adoption of the described workflow will enable significantly streamlined preclinical development of Anticalin drug candidates and could potentially be applied to other therapeutic protein scaffolds.
Lateral inhibition in V1 controls neural & perceptual contrast sensitivity
Authors: Del Rosario Joseph , Coletta Stefano , Kim Soon Ho , Mobille Zach , Peelman Kayla , Williams Brice , Otsuki Alan J , Del Castillo Valerio Alejandra , Worden Kendell , Blanpain Lou T. , Lovell Lyndah , Choi Hannah , Haider Bilal 
Published: November 2023

SummaryLateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with anatomy and direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.
In vivo evaluation of a novel compliance-matching vascular graft
Authors: Rovas G. , Reymond P. , van Steenberghe M. , Diaper J. , Bikia V. , Cikirikcioglu M. , Habre W. , Huber C. , Stergiopulos N. 
Published: November 2023

AbstractBackgroundThe mismatch of elastic properties between the arterial tissue and the vascular grafts, commonly called compliance mismatch, is responsible for many deleterious post-operative complications. Currently, there is an absence of prostheses that conform with the compliance of healthy aortas.ObjectivesWe proposed a novel compliance-matching graft design, composed of a standard aortic graft surrounded by an optimized Nickel-Titanium compliance-augmenting layer. We aimed to evaluate the in vivo performance of the novel grafts in a swine model and compare it to the native aorta and to gold-standard aortic grafts.MethodsWe replaced the thoracic aorta of six domestic pigs with compliance-matching grafts under cardiopulmonary bypass. We removed the compliance-regulating layer of the compliant grafts, so that gold-standard grafts remained implanted.ResultsThe compliance-matching grafts were implanted without surgical complications and without inducing post-operative hypertension by maintaining systolic pressure (11% increase), aortic pulse wave velocity (17% decrease) and aortic distensibility (40% increase) at healthy levels. The gold-standard grafts caused a significant rise in systolic pressure (47%), pulse pressure (126%) and pulse wave velocity (64%).ConclusionsOur novel compliant grafts could diminish the complications caused by compliance-mismatch and they could surpass the clinical performance of existing prostheses. The proposed grafts comprise a step towards optimized treatment and improved life expectancy of patients subjected to aortic replacement.
CGCom: a framework for inferring Cell-cell Communication based on Graph Neural Network
Authors: Wang Honglin , Zhang Chenyu , Hong Seung-Hyun , Maye Peter , Rowe David , Shin Dong-Guk 
Published: November 2023

AbstractCell-cell communication is crucial in maintaining cellular homeostasis, cell survival and various regulatory relationships among interacting cells. Thanks to recent advances of spatial transcriptomics technologies, we can now explore if and how cells’ proximal information available from spatial transcriptomics datasets can be used to infer cell-cell communication. Here we present a cell-cell communication inference framework, called CGCom, which uses a graph neural network (GNN) to learn communication patterns among interacting cells by combining single-cell spatial transcriptomic datasets with publicly available ligand-receptor information and the molecular regulatory information down-stream of the ligand-receptor signaling. To evaluate the performance of CGCom, we applied it to mouse embryo seqFISH datasets. Our results demonstrate that CGCom can not only accurately infer cell communication between individual cell pairs but also generalize its learning to predict communication between different cell types. We compared the performance of CGCom with two existing methods, CellChat and CellPhoneDB, and our comparative study revealed both common and unique communication patterns from the three approaches.Commonly found communication patterns include three sets of ligand-receptor communication relationships, one between surface ectoderm cells and spinal cord cells, one between gut tube cells and endothelium, and one between neural crest and endothelium, all of which have already been reported in the literature thus offering credibility of all three methods. However, we hypothesize that CGCom is superior in reducing false positives thanks to its use of cell proximal information and its learning between specific cell pairs rather than between cell types. CGCom is a GNN-based solution that can take advantage of spatially resolved single-cell transcriptomic data in predicting cell-cell communication with a higher accuracy.
Insulin and Exercise-induced Phosphoproteomics of Human Skeletal Muscle Identify REPS1 as a New Regulator of Muscle Glucose Uptake
Authors: Kjærgaard Larsen Jeppe , Lindqvist Cecilie B. , Jessen Søren , García-Ureña Mario , Ehrlich Amy M. , Schlabs Farina , Quesada Júlia Prats , Schmalbruch Johann H. , Small Lewin , Thomassen Martin , Lemminger Anders Krogh , Eibye Kasper , Gonzalez-Franquesa Alba , Stidsen Jacob V. , Højlund Kurt , Kilpeläinen Tuomas O. , Bangsbo Jens , Treebak Jonas T. , Hostrup Morten , Deshmukh Atul S. 
Published: November 2023

AbstractSkeletal muscle regulates glucose uptake in response to insulin and exercise which is critical for maintaining metabolic health. We conducted a comprehensive phosphoproteomic analysis of skeletal muscle from healthy people in response to an acute bout of exercise or insulin stimulation by a hyperinsulinemic euglycemic clamp. Our analysis revealed 233 phosphosites regulated by both exercise and insulin of which most phosphosites were regulated in opposite directions. However, 71 phosphosites on 55 proteins displayed regulation in the same direction, indicating a potential convergence of signaling pathways. We identified the vesicle-associated protein, REPS1, to be phosphorylated at Ser709 in response to both insulin and exercise. REPS1 protein level and Ser709 phosphorylation were closely related to insulin-stimulated glucose uptake in skeletal muscle and required for maximal insulin-stimulated glucose uptake. Furthermore, we observed that insulin triggered phosphorylation of REPS1 Ser709 via P90S6 kinase (RSK) and is impaired in mice and humans with insulin resistance. Collectively, REPS1 is a convergence point for insulin and exercise signaling and a promising therapeutic target in insulin resistance.
Larval swimming in the sea anemoneNematostella vectensisis sensitive to a broad light spectrum and exhibits a wavelength-dependent behavioral switch
Authors: Payne Meghan , Lilly Emma , Sharkey Camilla R , McCulloch Kyle J 
Published: November 2023

AbstractIn nearly all animals, light sensing mediated by opsin visual pigments is important for survival and reproduction. Eyeless light-sensing systems, though vital for many animals, have received relatively less attention than forms with charismatic or complex eyes. Despite no single light sensing organ, the sea anemoneNematostella vectensis, has 29 opsin genes and multiple light-mediated behaviors throughout development and reproduction, suggesting a deceptively complex light-sensing system. To characterize one aspect of this light-sensing system, we analyzed larval swimming behavior at high wavelength resolution across the ultraviolet and visual spectrum.N. vectensislarvae respond to light at least from 315 to 650 nm, which is a broad sensitivity range even compared to many animals with complex eyes. Swimming in the water column is induced by ultraviolet (UV) and violet wavelengths until 420 nm. Between 420 and 430 nm a behavioral switch occurs where at wavelengths longer than 430 nm, larvae respond to light by swimming down. Swimming down toward the substrate is distinct from light avoidance, as animals do not exhibit positive or negative phototaxis at any wavelength tested. At wavelengths longer than 575 nm, animals in the water column take increasingly longer to respond and this behavior is more variable until 650 nm where larval response is no different from the dark, suggesting these longer wavelengths lie outside of their sensitivity range. Larval swimming is the only motile stage in the life history ofN. vectensis, and increased swimming activity in the water column could lead to greater dispersal range in potentially damaging shallow environments with short-wavelength light exposure. Longer wavelength environments may indicate more suitable substrates for metamorphosis into the polyp stage, where the individual will remain for the rest of its life. Future work will test whether this robust behavior is mediated by multiple opsins.