bluuebunny/crossref_metadata_2025_split huggingface dataset:
The collagen metabolism, disrupted endothelium, the endothelial progenitor cells and their microvesicles in acute rheumatic fever
Authors: Ramakrishnan Sivasubramanian , Sahu Parul , Jain Kshama , Bhattacharya Jashdeep , Das Barun , Iyer Srikanth , Shukla Anurag , Balaji Arvind , Gupta Saurabh Kumar , Kothari Shyam S , Saxena Anita , Upadhay Pramod 
Published: August 2023

AbstractBackgroundAcute rheumatic fever (ARF) and its chronic sequelae, rheumatic heart disease (RHD) contributes to valvular dysfunction and significant cardiovascular disability and endocardial damage is considered the primary pathophysiological mechanism underlying ARF. This study examined peripheral blood markers of endothelial injury and function in ARF and RHD patients and compared them to healthy controls.MethodIn this prospective observational study, the levels of collagen intermediates, matrix metalloproteinases, tissue inhibitors of matrix metalloproteinases, brain natriuretic peptide, Anti-DNaseB, VEGF, E-selectin, VCAM, and ICAM in circulation were estimated. The study also isolated hemangioblastic and monocytic endothelial progenitor cells and their respective microvesicles from the peripheral blood of patients and control samples.ResultsProcollagen type I carboxy-terminal propeptide, cross-linked c-telopeptide of type I, and procollagen III c-terminal propeptide levels were higher in RHD subjects compared to patients with ARF. The ARF patients had the highest levels of matrix metalloproteinases 10 (MMP-10) followed by chronic patients and healthy controls. The ratio of tissue inhibitors of matrix metalloproteinases TIMP-1 and MMP-10 was lowest in healthy controls.At the cellular level, there were higher number of monocytic endothelial progenitor cells (EPCs) in ARF subjects as compared to healthy controls. For hemangioblastic EPCs, there was no significant difference between chronic subjects and healthy controls, though their early subtype was higher in chronic subjects. The hemangioblastic EPCs microvesicles were more abundant in ARF compared to RHD patients.ConclusionThe greater number of EPCs and respective microvesicles confirm the continued disruption of the endothelium in ARF, and during the progression of the disease, the majority of EPCs undergo apoptosis.Obituary StatementThis study was conceived and designed by SR, PU, and Prof. Rajnish Juneja, Professor at AIIMS. Prof. Rajnish Juneja expired in April 2018 while the study was ongoing (1).Mr. Suran Nambisan, a research fellow at NII, was part of the team who initiated the experimental work. Dr. Suran Nambisan expired in January 2023.This paper is dedicated to both of them. It was the profound love for mankind and unwavering dedication to perfection by Prof. Rajnish Juneja that brought together a remarkable team to undertake this study. Dr. Suran Nambisan embarked on his professional research journey by successfully establishing and standardizing a few intricate protocols used in this study.
Autophagy protein Atg7 is essential and druggable for maintaining malaria parasite cellular homeostasis and organelle biogenesis
Authors: Mishra Akancha , Srivastava Pratik Narain , H Shabeer Ali , Mishra Satish 
Published: August 2023

AbstractPlasmodiumparasites have a complex life cycle that transitions between mosquito and mammalian hosts and undergoes continuous cellular remodeling to adapt to various drastic environments. Following hepatocyte invasion, the parasite discards superfluous organelles for intracellular replication, and the remnant organelles undergo extensive branching and mature into hepatic merozoites. Autophagy is a ubiquitous eukaryotic process that permits the recycling of intracellular components. Here, we show that theP. bergheiautophagy-related E1-like enzyme Atg7 is expressed in the blood and liver stages, localized to the parasite cytosol and is essential for the localization of Atg8 on the membrane and the development of parasite blood and liver forms. We found that depleting Atg7 abolishes exocytosis of micronemes, organelle biogenesis and the formation of merozoites during liver stage development. Furthermore, we identified the compounds from the Maybridge library with a high docking score againstPfAtg7. We show that these compounds inhibit apicoplast biogenesis and parasite development in both blood and liver stages. Overall, this study establishes the essential functions of autophagy inPlasmodiumblood and liver stages and highlights the potential of using Atg7 as a drug target against malaria.
Noncoding genetic variation in ISPD distinguishes gamecocks from nongame chickens
Authors: Bendesky Andres , Brew Joseph , Francis Kerel X. , Corbetto Enrique F. Tello , Ariza Antonio González , Baena Sergio Nogales , Shimmura Tsuyoshi 
Published: August 2023

AbstractChickens were domesticated >4,000 years ago, probably first for fighting them and only later as a source of food. Fighting chickens, commonly known as gamecocks, continue to be bred throughout the world, but the genetic relationships among geographically diverse gamecocks and with nongame chickens are not known. Here, we sequenced the genomes of 44 geographically diverse gamecocks and of 62 nongame chickens representing a variety of breeds. We combined these sequences with published genomes to generate the most diverse chicken genomes dataset yet assembled, at 307 samples. We found that gamecocks do not form a homogeneous group, yet they share genetic similarities that distinguish them from nongame chickens. Such similarities are likely the result of a common origin before their local diversification into, or mixing with, nongame chickens. Particularly noteworthy is a variant in an intron of ISPD, an extreme outlier present at a frequency of 90% in gamecocks but only 4% in nongame chickens. The ISPD locus has the strongest signal of selection in gamecocks, suggesting it is important for fighting performance. Because ISPD variants that are highly prevalent in gamecocks are still segregating in nongame chickens, selective breeding may help reduce its frequency in farm conditions in which aggression is not a desired trait. Altogether, our work provides genomic resources for agricultural genetics, uncovers a common origin for gamecocks from around the world and what distinguishes them genetically from chickens bred for purposes other than fighting, and points to ISPD as the most important locus related to fighting performance.
KDM6A facilitates Xist upregulation at the onset of X inactivation
Authors: Lin Josephine , Zhang Jinli , Ma Li , Fang He , Ma Rui , Groneck Camille , Filippova Galina N. , Deng Xinxian , Ma Wenxiu , Disteche Christine M. , Berletch Joel B. 
Published: August 2023

AbstractX chromosome inactivation (XCI) is a female-specific process in which one X chromosome is silenced to balance X-linked gene expression between the sexes. XCI is initiated in early development by upregulation of the lncRNAXiston the future inactive X (Xi). A subset of X-linked genes escape silencing and thus have higher expression in females, suggesting female-specific functions. One of these genes is the highly conserved geneKdm6a, which encodes a histone demethylase that removes methyl groups at H3K27 to facilitate gene expression. Here, we investigate the role of KDM6A in the regulation ofXist. We observed impaired upregulation ofXistduring early stages of differentiation in hybrid mouse ES cells following CRISPR/Cas9 knockout ofKdm6a. This is associated with reducedXistRNA coating of the Xi, suggesting diminished XCI potency. Indeed,Kdm6aknockout results in aberrant overexpression of genes from the Xi after differentiation. KDM6A binds to theXistpromoter and knockout cells show an increase in H3K27me3 atXist. These results indicate that KDM6A plays a role in the initiation of XCI through histone demethylase-dependent activation ofXistduring early differentiation.
Multi-Site Statistical Mapping of Along-Tract Microstructural Abnormalities in Bipolar Disorder with Diffusion MRI Tractometry
Authors: Nabulsi Leila , Chandio Bramsh Q. , McPhilemy Genevieve , Martyn Fiona M. , Roberts Gloria , Hallahan Brian , Dannlowski Udo , Kircher Tilo , Haarman Benno , Mitchell Philip , McDonald Colm , Cannon Dara M. , Andreassen Ole A. , Ching Christopher R. K. , Thompson Paul M. 
Published: August 2023

AbstractInvestigating alterations in brain circuitry associated with bipolar disorder (BD) may offer a valuable approach to discover brain biomarkers for genetic and interventional studies of the disorder and related mental illnesses. Some diffusion MRI studies report evidence of microstructural abnormalities in white matter regions of interest, but we lack a fine-scale spatial mapping of brain microstructural differences along tracts in BD. We also lack large-scale studies that integrate tractometry data from multiple sites, as larger datasets can greatly enhance power to detect subtle effects and assess whether effects replicate across larger international datasets. In this multisite diffusion MRI study, we used BUndle ANalytics (BUAN, Chandio 2020), a recently developed analytic approach for tractography, to extract, map, and visualize profiles of microstructural abnormalities on 3D models of fiber tracts in 148 participants with BD and 259 healthy controls from 6 independent scan sites. Modeling site differences as random effects, we investigated along-tract white matter (WM) microstructural differences between diagnostic groups. QQ plots showed that group differences were gradually enhanced as more sites were added. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic, interhemispheric, and posterior pathways; higher FA was also noted in posterior bundles, relative to controls. By integrating tractography and anatomical information, BUAN effectively captures unique effects along white matter (WM) tracts, providing valuable insights into anatomical variations that may assist in the classification of diseases.
Prenatal environment is associated with the pace of cortical network development over the first three years of life
Authors: Tooley Ursula A. , Latham Aidan , Kenley Jeanette K. , Alexopoulos Dimitrios , Smyser Tara , Warner Barbara B. , Shimony Joshua S. , Neil Jeffrey J. , Luby Joan L. , Barch Deanna M. , Rogers Cynthia E. , Smyser Chris D. 
Published: August 2023

AbstractEnvironmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n= 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.
Anomalous networks under the multispecies coalescent: theory and prevalence
Authors: Ané Cécile , Fogg John , Allman Elizabeth S. , Baños Hector , Rhodes John A. 
Published: August 2023

AbstractReticulations in a phylogenetic network represent processes such as gene flow, admixture, recombination and hybrid speciation. Extending definitions from the tree setting, ananomalousnetwork is one in which some unrooted tree topology displayed in the network appears in gene trees with a lower frequency than a tree not displayed in the network. We investigate anomalous networks under the Network Multispecies Coalescent Model with possible correlated inheritance at reticulations. Focusing on subsets of 4 taxa, we describe a new algorithm to calculate quartet concordance factors on networks of any level, faster than previous algorithms because of its focus on 4 taxa. We then study topological properties required for a 4-taxon network to be anomalous, uncovering the key role of 32-cycles: cycles of 3 edges parent to a sister group of 2 taxa. Under the model of common inheritance, that is, when each gene tree coalesces within a species tree displayed in the network, we prove that 4-taxon networks are never anomalous. Under independent and various levels of correlated inheritance, we use simulations under realistic parameters to quantify the prevalence of anomalous 4-taxon networks, finding that truly anomalous networks are rare. At the same time, however, we find a significant fraction of networks close enough to the anomaly zone to appear anomalous, when considering the quartet concordance factors observed from a few hundred genes. These apparent anomalies may challenge network inference methods.
Capturing dynamic fear experiences in naturalistic contexts: An ecologically valid fMRI signature integrating brain activation and connectivity
Authors: Zhou Feng , Zhang Ran , Yao Shuxia , Dong Debo , Feng Pan , Kranz Georg , Feng Tingyong , Becker Benjamin 
Published: August 2023

AbstractEnhancing our understanding of how the brain constructs conscious emotional experiences within dynamic real-life contexts necessitates ecologically valid neural models. Here, we present evidence delineating the constraints of current fMRI activation models in capturing naturalistic fear dynamics. To address this challenge, we fuse naturalistic fMRI with predictive modeling techniques to develop an ecologically valid fear signature that integrates activation and connectivity profiles, allowing for accurate prediction of subjective fear experience under highly dynamic close-to-real-life conditions. This signature arises from insights into the crucial role of distributed brain networks and their interactions in emotion modulation, and the potential of network-level information to improve predictions in dynamic contexts. Across a series of investigations, we demonstrate that this signature predicts stable and dynamic fear experiences across naturalistic scenarios with heightened sensitivity and specificity, surpassing traditional activation- and connectivity-based signatures. Notably, the integration of affective connectivity profiles enables precise real-time predictions of fear fluctuations in naturalistic settings. Additionally, we unearth a distributed yet redundant brain-wide representation of fear experiences. Subjective fear is encoded not only by distributed cortical and subcortical regions but also by their interactions, with no single brain system conveying substantial unique information. Our study establishes a comprehensive and ecologically valid functional brain architecture for subjective fear in dynamic environments and bridges the gap between experimental neuroscience and real-life emotional experience.
Two determinants of dynamic adaptive learning for magnitudes and probabilities
Authors: Foucault Cedric , Meyniel Florent 
Published: August 2023

AbstractHumans face a dynamic world that requires them to constantly update their knowledge. Each observation should influence their knowledge to a varying degree depending on whether it arises from a stochastic fluctuation or an environmental change. Thus, humans should dynamically adapt their learning rate based on each observation. Although crucial for characterizing the learning process, these dynamic adjustments have only been investigated empirically in magnitude learning. Another important type of learning is probability learning. The latter differs from the former in that individual observations are much less informative and a single one is insufficient to distinguish environmental changes from stochasticity. Do humans dynamically adapt their learning rate for probabilities? What determinants drive their dynamic adjustments in magnitude and probability learning? To answer these questions, we measured the subjects’ learning rate dynamics directly through real-time continuous reports during magnitude and probability learning. We found that subjects dynamically adapt their learning rate in both types of learning. After a change point, they increase their learning rate suddenly for magnitudes and prolongedly for probabilities. Their dynamics are driven differentially by two determinants: change-point probability, the main determinant for magnitudes, and prior uncertainty, the main determinant for probabilities. These results are fully in line with normative theory, both qualitatively and quantitatively. Overall, our findings demonstrate a remarkable human ability for dynamic adaptive learning under uncertainty, and guide studies of the neural mechanisms of learning, highlighting different determinants for magnitudes and probabilities.Significance statementIn a dynamic world, we must constantly update our knowledge based on the observations we make. However, how much should we update our knowledge after each observation? Here, we have demonstrated two principles in humans that govern their updating and by which they are capable of dynamic adaptive learning. The first principle is that when they observe a highly surprising event indicating a likely change in the environment, humans reset their knowledge and perform one-shot learning. The second principle is that when their knowledge is more uncertain, humans update it more quickly. We further found that these two principles are differentially called upon in two key learning contexts that could be associated with different brain mechanisms: magnitude learning (which primarily requires adaptation to surprise, under the first principle) and probability learning (which primarily requires adaptation to uncertainty, under the second principle). Our findings advance understanding of the mechanisms of human learning, with implications for the brain and the development of adaptive machines.
Genetic and brain similarity independently predict childhood anthropometrics and socioeconomic markers
Authors: Dahl Andreas , Eilertsen Espen M. , Rodriguez-Cabello Sara F. , Norbom Linn B. , Tandberg Anneli D. , Leonardsen Esten , Lee Sang Hong , Ystrom Eivind , Tamnes Christian K. , Alnæs Dag , Westlye Lars T. 
Published: August 2023

AbstractLinking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ a novel approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance, with the assumption that similarity in cortical thickness may in part be driven by similarity in genetic variants. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, significant associations between cortical thickness similarity and traits were limited to anthropometrics such as height (r2= 0.11, SE = 0.01), weight (r2= 0.12, SE = 0.01), and birth weight (r2= 0.19, SE = 0.01), as well as markers of socioeconomic status such as local area deprivation (r2= 0.06, SE = 0.01). Analyses of the contribution from common genetic variants to traits revealed contributions across included outcomes, albeit somewhat lower than previous reports, possibly due to the young age of the sample. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as socioeconomic factors and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample. The approach provides a promising framework for analyses of neuroimaging genetics cohorts, which can be further expanded by including imaging derived phenotypes beyond cortical thickness.
The Significance and Limited Influence of Cerebrovascular Reactivity on Age and Sex Effects in Task- and Resting-State Brain Activity
Authors: Chen Donna Y. , Di Xin , Yu Xin , Biswal Bharat B. 
Published: August 2023

AbstractFunctional MRI (fMRI) measures the blood-oxygen-level dependent (BOLD) signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state BOLD activity and may confound inter-individual effects observed in BOLD-based measures, such as those related to aging and biological sex. To investigate this, we examined a large open-access fMRI dataset containing a breath-holding task, checkerboard task, and resting-state scans. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and from the resting-state data, we quantified the resting-state amplitude of low-frequency fluctuations (ALFF), and resting-state regional homogeneity (ReHo). We hypothesized that cerebrovascular reactivity would be correlated with BOLD measures and that accounting for these correlations would result in better estimates of age and sex effects. Our analysis showed that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with ALFF and ReHo in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in ALFF and ReHo scores. Finally, we demonstrated that correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.
Multiplex imaging of localized prostate tumors reveals changes in mast cell type composition and spatial organization of AR-positive cells in the tumor microenvironment
Authors: Ak Cigdem , Sayar Zeynep , Thibault Guillaume , Burlingame Erik A. , Eng Jennifer , Chitsazan Alex , Adey Andrew C. , Boniface Christopher , Spellman Paul T. , Thomas George V. , Kopp Ryan P. , Demir Emek , Chang Young Hwan , Stavrinides Vasilis , Eksi Sebnem Ece 
Published: August 2023

ABSTRACTMapping spatial interactions of cancer, immune and stromal cells present novel opportunities for patient stratification and for advancing immunotherapy. While single-cell studies revealed significant molecular heterogeneity in prostate tumors, there is currently no understanding of how immune cell heterogeneity impacts spatial coordination between tumor and stromal cells in localized tumors. Here, we used cyclic immunofluorescent imaging on whole-tissue sections to uncover novel spatial associations between cancer and stromal cells in low- and high-grade prostate tumors and tumor-adjacent normal tissues. Our results provide a spatial map of 699,461 single-cells that show epigenetic and molecular differences in distinct clinical grades. We report unique populations of mast cells that differentially express CD44, CD90 and Granzyme B (GZMB) and demonstrate GZMB+ mast cells are spatially associated with M2 macrophages in prostate tumors. Finally, we uncover recurrent neighborhoods that are primarily driven by androgen receptor positive (AR+) stromal cells and identify transcriptional networks active in AR+ prostate stroma.