bluuebunny/crossref_metadata_2025_split huggingface dataset:
DNA and RNA from the same single nucleus reveals interactions between genomic and transcriptomic landscapes in human tumor samples
Authors: Li Siran , Alexander Joan , Kendall Jude , Andrews Peter , Rose Elizabeth , Orjuela Hope , Park Sarah , Podszus Craig , Shanley Liam , Ranade Nissim , Morris Patrick , Stauder Danielle , Bradford Daniel , Ronemus Michael , Rishi Arvind , Ma Rong , Donoho David L. , Goldberg Gary L. , Wigler Michael , Levy Dan 
Published: October 2023

AbstractTo deepen our understanding of cancer heterogeneity and uncover the dynamic interactions of tumor and host cells, we introduce hybrid BAG-seq: a high-throughput, multi-omic method that simultaneously captures DNA and RNA from tens of thousands of individual single nuclei. This method provides dual molecular layer information: DNA to distinguish tumor from stroma, identify tumor subclones, and detect mutant stromal sub-populations; and RNA to characterize distinct cell types, cell states, and signatures of aberrant expression. Additionally, we developed a suite of analysis tools to illuminate cluster phylogeny and connections between DNA identity and RNA expression. We applied this hybrid protocol to 65,499 single nuclei from samples of five uterine cancer patients, and validated the clustering using RNA-only and DNA-only protocols on 34,651 and 21,432 nuclei, respectively, from the same tissues. Multiple tumor genome or expression clusters were often present within a patient, with different tumor clones projecting into distinct or shared expression states, demonstrating nearly all possible genome-transcriptome correlations across the cohort. While tumor expression profiles were highly unique to each patient, the stromal cell types generally recurred across samples, but certain patients and tissues exhibited unique stromal sub-types characterized by aberrant expression. Moreover, we identified mutant stroma in various cell types from several patients with a significant loss of the X-chromosome. This study reveals the complex landscape of genome and transcriptome interactions at the resolution of single nuclei, providing new insights into mutant stroma and tumor heterogeneity.
Robust CNV detection using single-cell ATAC-seq
Authors: Moore Travis W. , Yardımcı Galip Gürkan 
Published: October 2023

AbstractCopy number variation (CNV) is a widely studied type of structural variation seen in the genomes of cancerous and other dysfunctional cells. CNVs can have direct and indirect effects on gene dosage, and are thought to drive cancer progression and other disorders. Advancements in single-cell assays such as sc-ATAC-seq and sc-RNA-seq, along with their ubiquitous use, allows for the identification of CNVs at single cell resolution. While there are a variety of available tools for CNV detection in sc-RNA-seq, development of sc-ATAC-seq based accurate and reliable CNV callers is in the early stages, with only two available algorithms so far. We present RIDDLER, a single-cell ATAC-seq CNV detection algorithm based on outlier aware generalized linear modeling. By utilizing tools from robust statistics, we developed an extensible model that is able to identify single-cell CNVs from sc-ATAC-seq data in an unsupervised fashion, while providing probabilistic justification for results. Our statistical approach also allows us to estimate when loss of signal is likely caused by drop-out or a true genome deletion event, as well as predict reliable CNVs without the need for normative reference cells. We demonstrate the effectiveness of our algorithm on cancer cell line models where it achieves better agreement with bulk WGS derived CNVs than competing methods. We also compare our approach on 10x multimone data, where it shows better agreement and integration with RNA derived CNV estimates.
Correlation of ECG and Cardiac MRI for Assessment of Ventricular Hypertrophy and Dilatation in Adults with Repaired Tetralogy of Fallot
Authors: Brar Shanjot , Kang Mehima , Sodhi Amit , Deyell Marc W. , Laksman Zachary , Andrade Jason G. , Bennett Matthew T. , Krahn Andrew D. , Yeung-Lai-Wah John , Bennett Richard G. , Barlow Amanda , Grewal Jasmine , Sathananthan Gnalini , Chakrabarti Santabhanu 
Published: October 2023

ABSTRACTBackgroundSurgically repaired Tetralogy of Fallot (rTOF) is associated with progressive right ventricular hypertrophy (RVH) and dilation (RVD). Accurate estimation of RVH/ RVD is vital for the ongoing management of this patient population. The utility of the ECG in evaluating patients with rTOF with pre-existing right bundle branch block (RBBB) has not been studied. We aimed to determine the sensitivity/specificity of currently established ECG criteria in detecting RVH/RVD in this patient population.MethodsWe included consecutive patients diagnosed with rTOF who underwent CMR performed at our regional referral centre between January 2012 and December 2019. Each CMR was assessed for LVH, LVD, RVH or RVD diagnosis. The ECG corresponding to the CMR was then used to determine RVH/LVH for specificity and sensitivity analysis.ResultsOur study included 163 consecutive rTOF patients. The specificity for ECG-based criteria for LVH was 100.00% (95% C.I. (87.75, 100.00)), and the sensitivity was 7.19% (95% C.I. (3.15, 12.83)). When RBBB was present, specificity for RVH was 100.00% (95% C.I. (84.56, 100.00)), and sensitivity was 7.69% (95% C.I. (3.75, 13.69)). When RBBB was absent, specificity for RVH was 100.00% (95% C.I. (15.81, 100.00)), and sensitivity was 0.00% (95% C.I. (0.00, 33.63)). A regression model with the entire group of 163 ToF patients, based on the Sokolow-Lyon criterion (sum of R in V1 + S in V5/V6), produced a new suggested criterion for the diagnosis of RVH in patients with rTOF, which was a sum of R in V1 + S in V5/V6 greater than 13.25 mm. This model’s sensitivity for RVH detection was 69.1%, and specificity was 36.8%.ConclusionsStandard ECG voltage criteria have poor sensitivity for detecting right and left ventricular chamber hypertrophy and dilatation in patients with rTOF, so current ECG criteria should not be used to monitor RVH/RVD in this patient population.
Microenvironment changes in basal ganglia region correlates with hypertension at 7T MRI
Authors: Liang Hongqin , Meng Shan , Li Yue , Yi Xiaoqi , Zhang Haipeng , Wang Jian , Lv Fajin 
Published: October 2023

ABSTRACTBACKGROUNDHypertension, a major risk factor for stroke, is associated with the changes of microenvironment in basal ganglia region, including microstructural characteristics and mapping relationship of blood flow and peripheral nerve tissue.MATERIALS AND METHODSThe morphological characteristics of the lenticulostriate arteries (LSA) and peripheral nerve nuclei were compared by 7T time-of-Flight MRA between 32 hypertensive patients (mean age: 47.1±9.6 years) and 48 age-matched healthy subjects (mean age: 47.7±8.1 years) from September 2022 to February 2023. The ITK-SNAP software was used to measure the morphological characteristics of the LSA and the volume of the nuclei.RESULTSThe average stems number and length of LSA was significantly higher in healthy people than those in hypertension patients (p<0.05). The volumes of the peripheral nerve nuclei in healthy subjects were significantly larger than those in hypertensive patients (p<0.05). There was a positive correlation between the volume of putamen and the length of LSA in the left hemisphere (r = 0.23, p < 0.05). The number of stems was found to be positively correlated with Globus pallidus volume (r = 0.27, p < 0.05) and internal capsule volume (r = 0.25, p < 0.05) in the right hemisphere. For older adults (>45 year old), the average stems number of LSA and the volume of nuclei were significantly different (P <0.05).CONCLUSIONThe microstructure of the basal ganglia has changed obviously in patients with hypertension compared to healthy individuals when observed by 7T MRA.NOVELTY AND RELEVANCEWhat Is New?Previously studies on basal ganglia of hypertension using 7T MRI mainly focused on the imaging of LSA, but have not identified significant associations between the LSA and peripheral nerve tissue. However, the occurrence of hypertension adverse events such as intracerebral hemorrhage is closely related to the microenvironment formed by the lenticular artery and peripheral nerve tissue. Once the potential correlation is taken into account, the treatment and follow-up plan related to hypertension may be changed to effectively reduce the adverse.What Is Relevant?The rupture of LSA is a recognized cause of stroke in the basal ganglia of hypertensive patients, and the change of the microenvironment of peripheral nerve tissue is closely related to the rupture of LSA. The current findings confirm this notion and identify a potential association between the LSA and peripheral nerve nuclei in hypertensive patients, reinforcing the causal relationship between changes in follow-up strategies for lifelong hypertension and disease risk.Clinical/Pathophysiological Implications?Consider early and active assessment of basal ganglia blood flow and peripheral nerve tissue changes in all hypertensive patients to help reduce the risk of adverse events (such as cerebral hemorrhage, cerebral infarction, cognitive impairment, etc.) in individuals.
Multi-donor human cortical Chimeroids reveal individual susceptibility to neurotoxic triggers
Authors: Bolaños Noelia Antón , Faravelli Irene , Faits Tyler , Andreadis Sophia , Trattaro Sebastiano , Kastli Rahel , Adiconis Xian , Di Bella Daniela J. , Tegtmeyer Matthew , Nehme Ralda , Levin Joshua Z. , Regev Aviv , Arlotta Paola 
Published: October 2023

AbstractInter-individual genetic variation affects the susceptibility to and progression of many diseases. Efforts to study the molecular mechanisms mediating the impact of human genetic variation on normal development and disease phenotypes are limited, however, by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple individuals. Here, we present human brain “Chimeroids”, a highly reproducible, multi-donor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid, while maintaining fidelity to endogenous tissue. By reaggregating cells from multiple single-donor organoids at the neural stem or committed progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We leveraged Chimeroids to investigate inter-individual variation in susceptibility to neurotoxic stressors that exhibit high clinical phenotypic variability: ethanol and the anti-epileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results show that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of the contribution of human genetic variation to brain development and disease.
A topographical atlas of αSyn dosage and cell-type expression in the mouse brain and periphery
Authors: Geertsma Haley M. , Fisk Zoe A. , Sauline Lillian , Prigent Alice , Kurgat Kevin , Callaghan Steve M. ,   aSCENT-PD consortium, Henderson Michael X. , Rousseaux Maxime W.C. 
Published: October 2023

AbstractParkinson’s disease (PD) is the second most common neurodegenerative disease worldwide and presents pathologically with Lewy pathology and dopaminergic neuron loss. Lewy pathology contains aggregated αSynuclein (αSyn), a protein encoded by theSNCAgene which is also mutated or duplicated in a subset of familial PD cases. Due to its predominant presynaptic localization, immunostaining for the protein results in diffuse signal, providing little insight into the types of cells expressing αSyn. As a result, insight into αSyn expression-driven cellular vulnerability has been difficult to ascertain. Using a combination of knock-in mice that target αSyn to the nucleus of cells (SncaNLS) andin situhybridization ofSncain wild-type mice, we systematically map the topography and cell types expressing αSyn in the mouse brain, spinal cord, retina, and gut. We find a high degree of correlation between αSyn protein and RNA levels across multiple brain regions and further identify cell types with low and high αSyn. We found that αSyn is highly expressed in neurons, particularly those involved in PD and to a lower extent in non-neuronal cell types, notably those of oligodendrocyte lineage. We also find that αSyn is devoid in certain neuron types (e.g. ChAT-positive motor neurons), and that all enteric neurons express αSyn to a certain degree. Taken together, this atlas provides much-needed insight into the cellular topography of αSyn, and provides a quantitative map to test assumptions about the role of αSyn in network vulnerability in PD and other αSynucleinopathies.
Beyond human-likeness: Socialness is more influential when attributing mental states to robots
Authors: Jastrzab Laura E. , Chaudhury Bishakha , Ashley Sarah A. , Koldewyn Kami , Cross Emily S. 
Published: October 2023

SummaryWe sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. Replicating previous studies, we confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that beyond humanness, the perceivedsocialnessof an agent appeared to be as important, if not more so, for mind attribution. Our findings suggest that top-down knowledge cues are just as important, if not more so, than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents.
Integrating microbial abundance time series with fermentation dynamics of the rumen microbiomeviamathematical modelling
Authors: Davoudkhani Mohsen , Rubino Francesco , Creevey Christopher J. , Ahvenjärvi Seppo , Bayat Ali R. , Tapio Ilma , Belanche Alejandro , Muñoz-Tamayo Rafael 
Published: October 2023

AbstractThe rumen represents a dynamic microbial ecosystem where fermentation metabolites and microbial concentrations change over time in response to dietary changes. The integration of microbial genomic knowledge and dynamic modelling can enhance our system-level understanding of rumen ecosystem’s function. However, such an integration between dynamic models and rumen microbiota data is lacking. The objective of this work was to integrate rumen microbiota time series determined by 16S rRNA gene amplicon sequencing into a dynamic modelling framework to link microbial data to the dynamics of the volatile fatty acids (VFA) production during fermentation. For that, we used the theory of state observers to develop a model that estimates the dynamics of VFA from the data of microbial functional proxies associated with the specific production of each VFA. We determined the microbial proxies using CowPi to infer the functional potential of the rumen microbiota and extrapolate their functional modules from KEGG (Kyoto Encyclopedia of Genes and Genomes). The approach was challenged using data from anin vitroRUSITEC experiment and from anin vivoexperiment with four cows. The model performance was evaluated by the coefficient of variation of the root mean square error (CRMSE). For thein vitrocase study, the mean CVRMSE were 9.8% for acetate, 14% for butyrate and 14.5% for propionate. For thein vivocase study, the mean CVRMSE were 16.4% for acetate, 15.8% for butyrate and 19.8% for propionate. The mean CVRMSE for the VFA molar fractions were 3.1% for acetate, 3.8% for butyrate and 8.9% for propionate. Ours results show the promising application of state observers integrated with microbiota time series data for predicting rumen microbial metabolism.
Characterizing cell-type spatial relationships across length scales in spatially resolved omics data
Authors: dos Santos Peixoto Rafael , Miller Brendan F. , Brusko Maigan A. , Aihara Gohta , Atta Lyla , Anant Manjari , Atkinson Mark A. , Brusko Todd M. , Wasserfall Clive H. , Fan Jean 
Published: October 2023

AbstractSpatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we developed CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package with source code and additional documentation athttps://jef.works/CRAWDAD/.To demonstrate the utility of such multi-scale characterization, recapitulate expected cell-type spatial relationships, and evaluate against other cell-type spatial analyses, we applied CRAWDAD to various simulated and real SRO datasets of diverse tissues assayed by diverse SRO technologies. We further demonstrate how such multi-scale characterization enabled by CRAWDAD can be used to compare cell-type spatial relationships across multiple samples. Finally, we applied CRAWDAD to SRO datasets of the human spleen to identify consistent as well as patient and sample-specific cell-type spatial relationships. In general, we anticipate such multi-scale analysis of SRO data enabled by CRAWDAD will provide useful quantitative metrics to facilitate the identification, characterization, and comparison of cell-type spatial relationships across axes of interest.
A highly resolved network reveals the role of terrestrial herbivory in structuring aboveground food webs
Authors: Hale Kayla R. S. , Curlis John David , Auteri Giorgia G. , Bishop Sasha , French Rowan L. K. , Jones Lance E. , Mills Kirby L. , Scholtens Brian G. , Simons Meagan , Thompson Cody , Tourville Jordon , Valdovinos Fernanda S. 
Published: October 2023

AbstractComparative studies suggest remarkable similarities among food webs across habitats, including systematic changes in their structure with diversity and complexity (scale-dependence). However, historic aboveground terrestrial food webs (ATFWs) have coarsely grouped plants and insects such that these webs are generally small, and herbivory is disproportionately underrepresented compared to vertebrate predator-prey interactions. Furthermore, terrestrial herbivory is thought to be structured by unique processes compared to size-structured feeding in other systems. Here, we present the richest ATFW to date, including ∼580,000 feeding links among ∼3,800 taxonomic species, sourced from ∼27,000 expert-vetted interaction records annotated as feeding upon one of six different resource types: leaves, flowers, seeds, wood, prey, and carrion. By comparison to historical ATFWs and null ecological hypotheses, we show that our temperate forest web displays a potentially unique structure characterized by two properties: a) a large fraction of carnivory interactions dominated by a small number of hyper-generalist, opportunistic bird and bat predators, and b) a smaller fraction of herbivory interactions dominated by a hyper-rich community of insects with variably-sized but highly-specific diets. We attribute our findings to the large-scale, even resolution of vertebrate, insect, and plant guilds in our food web.
AngoraPy: A Python Toolkit for Modelling Anthropomorphic Goal-Driven Sensorimotor Systems
Authors: Weidler Tonio , Goebel Rainer , Senden Mario 
Published: October 2023

AbstractGoal-driven deep learning is increasingly used to supplement classical modeling approaches in computational neuroscience. The strength of deep neural networks lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or hypothesis-driven connectivity patterns. Consequently, goal-driven models can generate hypotheses about the neurocomputations underlying cortical processing. Whereas goal-driven modeling is becoming increasingly common in perception neuroscience, its application to sensorimotor control is currently hampered by the complexity of the methods required to train models comprising the closed sensation-action loop. To mitigate this hurdle, we introduceAngoraPy, a modeling library that provides researchers with the tools to train complex recurrent convolutional neural networks that model sensorimotor systems.
Neither Williston nor Dollo: mandibular complexity from stem tetrapods to modern amphibians
Authors: Watt Emily C. , Felice Ryan N. , Goswami Anjali 
Published: October 2023

AbstractDirectional trends in evolution have long captured the attention of biologists, and are particularly interesting when they reflect fundamental developmental processes that underlie morphological change. Here, we apply deep time data and a phylogenetic comparative framework to assess two fundamental “laws” – Williston’s law of phenotypic simplification and Dollo’s law of irreversibility – in the tetrapod mandible, a structure that has sustained the same primary function of feeding for nearly 400 million years. In spite of this conserved function, the tetrapod mandible has undergone numerous morphological and compositional changes during and since the initial water-to-land transition around 390Ma. To quantify these shifts, we reconstructed the compositional ev olution of the mandible with 31 traits scored in 568 species from early tetrapods through to modern amphibians, thereby capturing immense developmental and ecological diversity as well as an excellent fossil record. Mandibular complexity and jaw disparity are highest at the base of the tetrapod tree and generally decrease through time, with stasis dominating over the last ~160M years. Nonetheless, we find a lack of support for Williston’s and Dollo’s laws, with loss and gain of jaw components equally likely throughout the course of early tetrapod and amphibian evolution. Combined, our results demonstrate that evolutionary patterns of mandibular complexity are more nuanced than either Williston’s or Dollo’s laws allow. Thus, laws of simplification are too crude to capture the evolutionary processes underlying the evolution of even a functionally conserved structure through deep time.SummaryThe lower jaw is a key innovation in vertebrate evolution with a unifying primary function: feeding. In spite of this conserved function, the jaw is extremely diverse in shape and composition. In limbed vertebrates (tetrapods), the jaw evolves from a complex structure comprising multiple elements and high numbers of teeth towards a simpler structure comprising few elements and generally fewer teeth. Superficially, this pattern suggests support for both Williston’s and Dollo’s laws of phenotypic simplification and irreversibility, respectively. However, we find a lack of support for either law in the jaw of the earliest tetrapods and amphibians, adding to growing literature refuting overly simplified “laws” governing organismal evolution.