bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Confounder Controlled Machine Learning Approach: Group Analysis and Classification of Schizophrenia and Alzheimer’s Disease using Resting-State Functional Network Connectivity
Authors: Hassanzadeh Reihaneh , Abrol Anees , Pearlson Godfrey , Turner Jessica A. , Calhoun Vince D. 
Published: October 2023

AbstractResting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer’s disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it is also of interest to directly compare AD and SZ patients with each other to identify potential biomarkers shared between the disorders. However, comparing patient groups collected in different studies can be challenging due to potential confounds, such as differences in the patient’s age, scan protocols, etc. In this study, we compared and contrasted resting-state functional network connectivity (rs-FNC) of 162 patients with AD and late mild cognitive impairment (LMCI), 181 schizophrenia patients, and 315 cognitively normal (CN) subjects. We used confounder-controlled rs-FNC and applied machine learning algorithms (including support vector machine, logistic regression, random forest, and k-nearest neighbor) and deep learning models (i.e., fully-connected neural networks) to classify subjects in binary and three-class categories according to their diagnosis labels (e.g., AD, SZ, and CN). Our statistical analysis revealed that FNC between the following network pairs is stronger in AD compared to SZ: subcortical-cerebellum, subcortical-cognitive control, cognitive control-cerebellum, and visual-sensory motor networks. On the other hand, FNC is stronger in SZ than AD for the following network pairs: subcortical-visual, subcortical-auditory, subcortical-sensory motor, cerebellum-visual, sensory motor-cognitive control, and within the cerebellum networks. Furthermore, we observed that while AD and SZ disorders each have unique FNC abnormalities, they also share some common functional abnormalities that can be due to similar neurobiological mechanisms or genetic factors contributing to these disorders’ development. Moreover, we achieved an accuracy of 85% in classifying subjects into AD and SZ where default mode, visual, and subcortical networks contributed the most to the classification and accuracy of 68% in classifying subjects into AD, SZ, and CN with the subcortical domain appearing as the most contributing features to the three-way classification. Finally, our findings indicated that for all classification tasks, except AD vs. SZ, males are more predictable than females.
Macroevolutionary drivers of morphological disparity in the avian quadrate
Authors: Kuo Pei-Chen , Navalón Guillermo , Benson Roger B. J. , Field Daniel J. 
Published: October 2023

AbstractIn birds, the quadrate bone acts as a hinge between the lower jaw and the skull, playing an important role in cranial kinesis. As such, the evolution of avian quadrate morphology may plausibly be assumed to have been influenced by selective pressures related to feeding ecology. However, variation in quadrate morphology across living birds and its potential relationship with ecology have never been quantitatively characterised. Here, we used three-dimensional geometric morphometrics and phylogenetic comparative methods to quantify morphological variation of the quadrate and its relationship with an array of key ecological features across 200 bird species covering all major extant lineages. We found non-significant associations between quadrate shape and several aspects of feeding and foraging ecology across different scales of phylogenetic comparison. By contrast, allometry and phylogeny exhibit stronger relationships with quadrate shape than other ecological features. We show that the avian quadrate evolves as an integrated unit and exhibits strong associations with the morphologies of neighbouring bones. Our results collectively suggest a macroevolutionary scenario in which the shape of the quadrate evolved jointly with other elements of the avian kinetic system, with the major lineages of birds exploring alternative quadrate morphologies—highlighting the potential diagnostic value of quadrate morphology in investigations of fossil bird systematics.
Ocelli: an open-source tool for the visualization of developmental multimodal single-cell data
Authors: Rutkowski Piotr , Tabaka Marcin 
Published: October 2023

AbstractThe recent expansion of single-cell technologies has enabled simultaneous genome-wide measurements of multiple modalities in the same single cell. The potential to jointly profile such modalities as gene expression, chromatin accessibility, protein epitopes, or multiple histone modifications at single-cell resolution represents a compelling opportunity to study developmental processes at multiple layers of gene regulation. Here, we present Ocelli, a lightweight Python package for scalable visualization and exploration of developmental multimodal single-cell data. The core functionality of Ocelli focuses on diffusion-based modeling of developmental processes. Ocelli addresses common tasks in developmental single-cell data analysis, such as visualization of cells on a low-dimensional embedding that preserves the continuity of the developmental progression of cells, identification of rare and transient cell states, integration with trajectory inference algorithms, and imputation of undetected feature counts. Extensive benchmarking shows that Ocelli outperforms existing methods regarding computational time and quality of the reconstructed low-dimensional representation of developmental data.
Amniotic Fluid Organoids As Personalized Tools For Real-Time Modeling Of The Developing Fetus
Authors: Babosova Olga , Weisz Boaz , Rabinowitz Grace , Avnet Hagai , Shani Hagit , Schwartz Anat , Batsry Linoy , Pardo Noam , Elkan Tal , Stockheim David , Jubany Tammir , Frank Denise D. , Barshack Iris , Dotan Zohar A. , Levin-Klein Rena , Beckerman Pazit , Pleniceanu Oren 
Published: October 2023

ABSTRACTDespite biomedical advances, major knowledge gaps regarding human development remain, and many developmental disorders lack effective treatment, representing a huge clinical burden. This results from fetuses being largely inaccessible for analysis. Here, we employ fetal cells in human amniotic fluid (AF) to establish personalized fetal kidney and lung organoids (AFKO and AFLO, respectively), recapitulating fetal organs at single-cell resolution. AFKO harbor key fetal kidney cell populations, including nephrogenic, urothelial and stromal, endocytose albumin, and modelPAX2-related anomalies. Strikingly, upon injection into the nephrogenic cortex of human fetal kidney explants, AFKO-derived progenitors integrate into the host progenitor niche and contribute to developing nephrons. AFLO comprise alveolar cells and most airway cell types in a typical pseudostratified structure, upregulate surfactant expression upon corticosteroid treatment, and show functional CFTR channels. Overall, this platform represents a new personalized tool that can be applied to virtually any fetus in real-time, affording unprecedented options in studying development, uncovering mechanisms ofin uteropathologies (e.g., congenital anomalies, infections or chemical teratogens) deciphering the developmental origins of chronic diseases, and tailoring treatments for these pathologies, as well as for prematurity-related complications. Importantly, since AF contains cells from additional tissues (e.g., skin and gastrointestinal tract), and is derived in a procedure already performed in many patients, this platform may well become a broadly applicable tool in fetal medicine.
Transcriptional profiling of peripheral blood mononuclear cells identifies inflammatory phenotypes in ataxia telangiectasia
Authors: Michki Nigel S. , Singer Benjamin D. , Perez Javier V. , Thomas Aaron J. , Natale Valerie , Helmin Kathryn A. , Wright Jennifer , Cheng Leon , Young Lisa R. , Lederman Howard M. , McGrath-Morrow Sharon A. 
Published: October 2023

AbstractAtaxia telangiectasia (A-T) is an autosomal recessive neurodegenerative disease with widespread systemic manifestations and marked variability in clinical phenotypes. In this study, we sought to determine whether transcriptomic profiling of peripheral blood mononuclear cells defines subsets of individuals with A-T beyond mild and classic phenotypes, enabling identification of novel features for disease classification and treatment response to therapy.MethodsParticipants with stable A-T (n=90) were recruited and compared with unaffected controls (n=15). PBMCs were isolated and bulk RNAseq was performed. Plasma was also isolated in a subset of individuals. Affected individuals were designated mild or classic based onATMmutations and clinical and laboratory features.ResultsPeople with classic A-T were more likely to be younger and IgA deficient and to have higher alpha-fetoprotein levels and lower % forced vital capacity compared to individuals with mild A-T. In classic A-T, the expression of genes required for V(D)J recombination was lower, and the expression of genes required for inflammatory activity was higher. We assigned inflammatory scores to study participants and found that inflammatory scores were highly variable among people with classic A-T and that higher scores were associated with lowerATMmRNA levels. Using a cell type deconvolution approach, we inferred that CD4+ T cells and CD8+ T cells were lower in number in people with classic A-T. Finally, we showed that individuals with classic A-T exhibit higherSERPINE1(PAI-1) mRNA and plasma protein levels, irrespective of age, and higherFLT4(VEGFR3) andIL6ST(GP130) plasma protein levels compared with mild A-T and controls.ConclusionUsing an unbiased transcriptomic approach, we identified novel features and developed an inflammatory score to identify subsets of individuals with different inflammatory phenotypes in A-T. Findings from this study could be used to help direct treatment and to track treatment response to therapy.
Data-driven characterization and correction of the orientation dependence of magnetization transfer measures using diffusion MRI
Authors: Karan Philippe , Edde Manon , Gilbert Guillaume , Barakovic Muhamed , Magon Stefano , Descoteaux Maxime 
Published: October 2023

AbstractPurposeTo characterize the orientation dependence of magnetization transfer (MT) measures in white matter (WM) and propose a first correction method for such measures.MethodsA characterization method was developed using the fiber orientation obtained from diffusion MRI (dMRI) with diffusion tensor imaging (DTI) and constrained spherical deconvolution (CSD). This allowed for characterization of the orientation dependence of measures in all of WM, regardless of the number of fiber orientation in a voxel. Furthermore, a first correction method was proposed from the results of characterization, aiming at removing said orientation dependence. Both methods were tested on a 20-subject dataset and effects on tractometry results were also evaluated.ResultsPrevious results for single-fiber voxels were reproduced and a novel characterization was produced in voxels of crossing fibers, which seems to follow trends consistent with single-fiber results. Unwanted effects of the orientation dependence on MT measures were highlighted, for which the correction method was able to produce improved results.ConclusionEncouraging results of corrected MT measures showed the importance of such correction, opening the door for future research on the topic.
Mesoscale Ca2+imaging reveals networks of Purkinje cell dendritic and somatic modulation, with divergent roles of activity versus correlation during behavior
Authors: Streng M.L. , Carter R.E. , Kottke B.W. , Togneri K. , Wasserman E. , Rajendran V. , Kodandaramaiah S. B. , Krook-Magnuson E. , Ebner T.J. 
Published: October 2023

AbstractA major challenge in cerebellar physiology is determining how the stereotypic, conserved circuitry of the cerebellar cortex, with its dominant parasagittal and transverse architectures, underlies its fundamental computations and contributions to behavior. To interrogate Purkinje cell dynamics at this parasagittal and transverse spatial scale, we implemented a novel approach for awake, chronic, wide-field Ca2+imaging of the cerebellar cortex. We observe two functionally and spatially distinct Purkinje cell networks, reflecting their dendritic and somatic activities, respectively. Both dendritic and somatic networks exhibit bilateral, widespread activation during behavior, but with diverse patterns of spatial correlations occurring primarily along the parasagittal and transverse directions, consistent with the main geometry of the cerebellar cortex. Somatic network correlation dynamics are robustly modulated by prediction errors, and even reflect ultimate behavioral outcomes. These results provide a novel link between cerebellar structure and function, with the correlation dynamics of Purkinje cell activity a key feature.
Auditory Hair Cells and Spiral Ganglion Neurons Regenerate Synapses with Refined Release Properties In Vitro
Authors: Vincent Philippe F.Y. , Young Eric D. , Edge Albert S.B. , Glowatzki Elisabeth 
Published: October 2023

ABSTRACTRibbon synapses between inner hair cells (IHCs) and type I spiral ganglion neurons (SGNs) in the inner ear are damaged by noise trauma and with aging, causing ‘synaptopathy’ and hearing loss. Co-cultures of neonatal denervated organs of Corti and newly introduced SGNs have been developed to find strategies for improving IHC synapse regeneration, but evidence of the physiological normality of regenerated synapses is missing. This study utilizes IHC optogenetic stimulation and SGN recordings, showing that newly formed IHC synapses are indeed functional, exhibiting glutamatergic excitatory postsynaptic currents. When older organs of Corti were plated, synaptic activity probed by deconvolution, showed more mature release properties, closer to the highly specialized mode of IHC synaptic transmission that is crucial for coding the sound signal. This newly developed functional assessment of regenerated IHC synapses provides a powerful tool for testing approaches to improve synapse regeneration.
Mimetic butterfly wings through mimetic butterfly eyes
Authors: Dang Andrew , Bernard Gary D. , Yuan Furong , Macias-Muñoz Aide , Hill Ryan I. , Lawrence J. P. , Rangel Olguin Aline G. , Luis-Martínez Armando , Mullen Sean P. , Llorente-Bousquets Jorge , Briscoe Adriana D. 
Published: October 2023

AbstractColor vision is thought to play a key role in the evolution of animal coloration, while achromatic vision is rarely considered as a mechanism for species recognition. Here we test the hypothesis that brightness vision rather than color vision helpsAdelpha fessoniabutterflies identify potential mates while their co-mimetic wing coloration is indiscriminable to avian predators. We examine the trichromatic visual system ofA. fessoniaand characterize its photoreceptors using RNA-seq, eyeshine, epi- microspectrophotometry and optophysiology. We model the discriminability of its wing color patches in relation to those of its co-mimic,A. basiloides, throughA. fessoniaand avian eyes. Visual modeling suggests that neitherA. fessonianor avian predators can readily distinguish the co-mimics’ coloration using chromatic or achromatic vision under natural conditions. These results suggest that mimetic colors are well-matched to visual systems to maintain mimicry, and that mate avoidance between these two look-alike species relies on other cues.
An in vivo drug screen reveals that cyclooxygenase 2-derived prostaglandin D2promotes spinal cord neurogenesis
Authors: Laura González-Llera , Daniel Sobrido-Cameán , Ana Quelle-Regaldie , Laura Sánchez , Antón Barreiro-Iglesias 
Published: October 2023

AbstractThe study of neurogenesis is essential to understand fundamental developmental processes and for the development of cell replacement therapies for central nervous system disorders. Here, we designed an in vivo drug screening protocol in developing zebrafish to find new molecules and signalling pathways regulating neurogenesis in the ventral spinal cord. This unbiased drug screen revealed that 4 cyclooxygenase (COX) inhibitors reduce the generation of serotonergic interneurons in the developing spinal cord. These results fitted very nicely with available single cell RNAseq data revealing that the floor plate cells show differential expression of 1 of the 2 COX2 zebrafish genes (ptgs2a). Indeed, several selective COX2 inhibitors and 2 different morpholinos againstptgs2aalso caused a significant reduction in the number of serotonergic neurons in the ventral spinal cord and led to locomotor deficits. Single cell RNAseq data and different pharmacological manipulations further revealed that COX2-floor plate-derived prostaglandin D2promotes neurogenesis in the developing spinal cord by promoting mitotic activity in progenitor cells. Rescue experiments using a phosphodiesterase-4 inhibitor suggest that intracellular changes in cAMP levels underlie the effects of COX inhibitors on neurogenesis and locomotion. Our study provides compelling in vivo evidence showing that prostaglandin signalling promotes neurogenesis in the ventral spinal cord.
Understanding SARS-CoV-2 Spike glycoprotein clusters and their impact on immunity of the population from Rio Grande do Norte, Brazil
Authors: Teixeira Diego Gomes , Rodrigues-Neto João Firmino , Severiano da Cunha Dayse Caroline , Jeronimo Selma Maria Bezerra 
Published: October 2023

ABSTRACTSARS-CoV-2 genome underwent mutations since it started circulating intensively within the human populations. The aim of this study was to understand the fluctuation of the spike clusters concomitant to high rate of population immunity either due to natural infection and/or vaccination in a state of Brazil that had high rate of infection and vaccination coverage. A total of 1715 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and correlate with circulating variants. From March 2020 to June 2022, Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma [P1]) dominated the first half of 2021. Late 2021 had Clusters 2 (Omicron) and 3 (Omicron sublineages) with the most unique epitopes, while Cluster 4 (Delta sublineages) emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome.IMPORTANCEIdentification of epitopes of emerging or endemic pathogens is of importance to estimate population responses and predict clinical outcomes and contribute to vaccine improvement. In the case of SARS-CoV-2, the virus within 6 months of circulation transitioned from the wild-type to novel variants leading to distinct clinical outcomes. Immunoinformatics analysis of viral epitopes of isolates from the Brazilian state of Rio Grande do Norte was performed using a clustering method. This analysis aimed to clarify how the introduction of novel variants in a population characterized by high infection and/or vaccination rates resulted in immune evasion and distinct clinical disease. Our analysis showed that the epitope profiles of each variant explained the respective potential for cytokine production, including the variants that were more likely to cause cytokine storms. Finally, it serves as a mean to explain the multi-wave patterns observed during SARS-CoV-2 pandemics.
SmartEM: machine-learning guided electron microscopy
Authors: Meirovitch Yaron , Park Core Francisco , Mi Lu , Potocek Pavel , Sawmya Shashata , Li Yicong , Chandok Ishaan Singh , Athey Thomas L. , Karlupia Neha , Wu Yuelong , Berger Daniel R. , Schalek Richard , Pfister Hanspeter , Schoenmakers Remco , Peemen Maurice , Lichtman Jeff W. , Samuel Aravinthan D.T. , Shavit Nir 
Published: October 2023

SummaryConnectomics provides essential nanometer-resolution, synapse-level maps of neural circuits to understand brain activity and behavior. However, few researchers have access to the high-throughput electron microscopes necessary to generate enough data for whole circuit or brain reconstruction. To date, machine-learning methods have been used after the collection of images by electron microscopy (EM) to accelerate and improve neuronal segmentation, synapse reconstruction and other data analysis. With the computational improvements in processing EM images, acquiring EM images has now become the rate-limiting step. Here, in order to speed up EM imaging, we integrate machine-learning into real-time image acquisition in a single-beam scanning electron microscope. This SmartEM approach allows an electron microscope to perform intelligent, data-aware imaging of specimens. SmartEM allocates the proper imaging time for each region of interest – scanning all pixels equally rapidly, then re-scanning small subareas more slowly where a higher quality signal is required to achieve accurate segmentability, in significantly less time. We demonstrate that this pipeline achieves a 7-fold acceleration of image acquisition time for connectomics using a commercial single-beam SEM. We apply SmartEM to reconstruct a portion of mouse cortex with the same accuracy as traditional microscopy but in less time.
Competition between stacking and divalent cation mediated electrostatic interactions determines the conformations of short DNA sequences
Authors: Mondal Balaka , Chakraborty Debayan , Hori Naoto , Nguyen Hung T. , Thirumalai D. 
Published: October 2023

AbstractInteractions between divalent cations (Mg2+and Ca2+) and highly charged single stranded DNA (ssDNA) and double stranded DNA (dsDNA), as well as stacking interactions, are important in a variety of problems, including nucleosome stability and phase separation in nucleic acids. Quantitative techniques accounting for ion-DNA interactions are needed to obtain insights into these and related problems. Towards this end, we created a computational model that explicitly takes into account monovalent and divalent ions, within the framework of the sequence-dependent coarse-grained Three Interaction Site (TIS) model for DNA. Molecular simulations of the rigid 24 base-pair (bp) dsDNA and flexible ssDNA sequences, dT30and dA30, in a buffer containing Na+and Cl−, with varying amounts of the divalent cations, are used to show that the calculated excess number of ions around the dsDNA and ssDNAagree quantitatively with ion-counting experiments. Using an ensemble of all-atom structures generated from coarse-grained simulations, we calculated the Small Angle X-ray Scattering (SAXS) profiles, which are also in excellent agreement with experiments. Strikingly, recapitulation of all the experimental findings was achieved without adjusting any of the parameters in the energy function to fit the data. At a molecular level, we find that Mg2+and Ca2+sense the differences between the major and minor grooves in dsDNA even though they are masked in ion-counting and SAXS experiments. The smaller Mg2+binds predominantly to the minor grooves and phosphate groups whereas Ca2+binds specifically only to the minor groove. The dA30conformations are dominated by stacking interactions, resulting in structures with considerable helical order. In contrast, the near cancellation of the favorable stacking and unfavorable electrostatic interactions leads to dT30populating an ensemble of heterogeneous conformations.