bluuebunny/crossref_metadata_2025_split huggingface dataset:
Merkel cell carcinoma-derived macrophage migration inhibitory factor (MIF) may promote persistence of Chronic Lymphocytic Leukemia
Authors: Alencar Gabriel F. , Rodriguez Haroldo J. , Pulliam Thomas H. , Remington Allison J. , Gilmour Macy W. , Alam Rian , Jabbour Austin J. , Mullen Logan J. , DeBuysscher Blair L. , Nghiem Paul , Taylor Justin J. 
Published: September 2024

AbstractWhile concurrent diagnoses of Merkel cell carcinoma (MCC) and other cancers, like Chronic lymphocytic leukemia (CLL), are rare, patients with MCC have a 30-fold higher incidence of CLL. While these increases have been attributed to the ability of CLL to suppress immune responses allowing for the emergence of MCC, here we found evidence that MCC could support the persistence of CLL. Using single cell sequencing approaches and computational analyses of MCC and CLL from a patient where both cancers were present in the same lymph node, we found that production of macrophage migration inhibitory factor (MIF) by MCC could promote the persistence of CLL through stimulation of CD74 and CXCR4. These results may explain why blood cell counts rapidly normalized after treatment for MCC and were maintained at normal levels despite the absence of treatment for CLL.Abstract Figure
Beyond immunity: a transcriptomic landscape of Plasmodium’s modulation of mosquito metabolic pathways
Authors: García-Longoria L , Berthomieu A , Hellgren O , Rivero A 
Published: September 2024

AbstractThe focus of mosquito-Plasmodiuminteractions has predominantly been centered on mosquito immunity, revealing key mechanisms by which mosquitoes attempt to combatPlasmodiuminfection. However, recent evidence suggests that beyond immunity, a multitude of mosquito physiological and metabolic pathways play crucial roles in determining whether the parasite completes its development within the mosquito. We review which of these metabolic pathways are potentially modulated byPlasmodium, revealing a fragmented and occasionally contradictory state of knowledge. We then present a comprehensive transcriptomic analysis ofPlasmodium-infected and uninfected mosquitoes, examining gene expression of crucial genes across different stages of the parasite’s development. These genes range from key enzymes and proteins involved in gut structure and function, to genes involved in egg production and resorption, salivary gland invasion and mosquito behaviour. For this purpose, we use a non-model system consisting of the avian malaria parasitePlasmodium relictum, an invasive parasite threatening bird biodiversity across the world, and its natural vector, the mosquitoCulex pipiens. Our results reveal how at each stage of its development within the mosquito,Plasmodiummodulates a myriad of mosquito metabolic pathways, in ways that potentially favour its survival and the completion of its life cycle. We discuss whether this constitutes sufficient evidence of parasite-driven manipulation or whether the changes are simply the mosquito’s response to the infection, which the parasite may serendipitously exploit to enhance its fitness. Our study extends the comparative transcriptomic analyses of malaria-infected mosquitoes beyond human and rodent parasites, and provides insights into the degree of conservation of metabolic pathways and into the selective pressures exerted byPlasmodiumparasites on their vectors.
A unified model of hippocampal spatial and object cells involving bidirectionally coupled Lateral and Medial Entorhinal Cortical layers
Authors: Patil Bharat K. , Aziz Azra , Saka Manoj Kumar , Deshmukh Sachin S. , Chakravarthy V. Srinivasa 
Published: September 2024

AbstractPopularly referred to as the GPS of the brain, the hippocampus has a variety of neurons that encode spatial properties of the environment. These spatial cells of the hippocampus may be broadly placed under two categories – those that encode spatial locations (e.g. place cells, grid cells etc) and those that encode spatial objects (eg. Object-sensitive cells. Object-trace cells etc). There are computational models that explain emergence of specific types of spatial cells, but it is challenging to construct integrative models that can demonstrate the emergence of the complete range of spatial cells both space and object type. We present a simple, unified computational model that explains the emergence of a wide variety of object- and spatially-sensitive neurons in the hippocampus. The model is essentially a deep neural network that combines visual and path integration information. The visual information is received by a part of the model that is analogous to Lateral Entorhinal Cortex (LEC) and path integration information is received by a layer analogous to Medial Entorhinal Cortex (MEC). In order to arrive at a consistent estimate of position, LEC and MEC in the model are connected laterally using a Graph Neural Network. The model is trained to predict position, orientation and reward of a simulated agent. The agent explores a box-like environment with colored walls and objects on the floor and is rewarded based on its encounters with objects. The model demonstrates the emergence of the following 7 types of spatial and object cells - place, grid, border, object, object-sensitive, object-vector and, object-trace cells. The model findings compare favorably with a large body of experimental literature on hippocampal spatial cells.
Overcoming the limitations of motion sensor models by considering dendritic computations
Authors: Luna Raúl , Serrano-Pedraza Ignacio , Bertalmío Marcelo 
Published: September 2024

AbstractThe estimation of motion is a fundamental process for any sighted animal. Computational models for motion sensors have a long and successful history but they still suffer from fundamental shortcomings, as they disagree with physiological evidence and each model is dedicated to a specific type of motion, which is controversial from a biological standpoint. In this work we propose a new approach for modeling motion sensors that considers dendritic computations, a key aspect for predicting single-neuron responses that had previously been absent from motion models. We show how, by taking into account the dynamic and input-dependent nature of dendritic nonlinearities, our motion sensor model is able to overcome the fundamental limitations of standard approaches.
A benchmarking study of copy number variation inference methods using single-cell RNA-sequencing data
Authors: Chen Xin , Fang Li Tai , Chen Zhong , Chen Wanqiu , Zhu Bin , Wu Hongjin , Moos Malcolm , Farmer Andrew , Zeng Feng , Song Lijuan , Zhang Xiaowen , Xiong Wei , Gong Shusheng , Jones Wendell , Mason Christopher E , Wu Shixiu , Xiao Chunlin , Wang Charles 
Published: September 2024

AbstractSingle-cell RNA-sequencing (scRNA-seq) has emerged as a powerful tool for cancer research, enabling in-depth characterization of tumor heterogeneity at the single-cell level. Recently, scRNA-seq copy number variation (scCNV) inference methods have been developed, expanding the application of scRNA-seq to study genetic heterogeneity in cancer using transcriptomic data. However, the fidelity of these methods has not been investigated systematically. In this study, we benchmarked five commonly used scCNV inference methods, HoneyBADGER, CopyKAT, CaSpER, inferCNV, and sciCNV. We evaluated their performance across four different scRNA-seq platforms derived data from a multicenter study. We further evaluated the scCNV performance using scRNA-seq datasets derived from mixed samples consisting of five human lung adenocarcinoma cell lines and generated a clinical scRNA-seq dataset from a human small cell lung cancer patient to validate our findings. Our evaluation criteria included sensitivity and specificity of CNV detection, and subclone identification from mixed cancer samples. We found that the sensitivity and specificity of the five scCNV inference methods varied, depending on the selection of reference data, sequencing depths, and read lengths. Overall, CopyKAT and CaSpER exhibited superior performance to other methods, while inferCNV, sciCNV, and CopyKAT outperformed other methods in subclone identification accuracy. Remarkably, inferCNV achieved high accuracy in subclone identification when using data from a “single scRNA-seq protocol”, however, when applying these methods to a dataset derived from multiple scRNA-seq platforms from the mixed samples, we found that batch effects significantly affected the performance of subclone identification for most methods, except for HoneyBADGER. Our benchmarking study revealed the strengths and weaknesses of each of the five scCNV inference methods and provided guidance for selecting the optimal CNV inference method using scRNA-seq data.
Colora: A Snakemake Workflow for Complete Chromosome-scaleDe NovoGenome Assembly
Authors: Obinu Lia , Booth Timothy , De Weerd Heleen , Trivedi Urmi , Porceddu Andrea 
Published: September 2024

AbstractBackgroundDe novoassembly creates reference genomes that underpin many modern biodiversity and conservation studies. Large numbers of new genomes are being assembled by labs around the world. To avoid duplication of efforts and variable data quality, we desire a best-practice assembly process, implemented as an automated portable workflow.ResultsHere we present Colora, a Snakemake workflow that produces chromosome-scalede novoprimary or phased genome assemblies complete with organelles using PacBio HiFi, Hi-C, and optionally ONT reads as input. The source code of Colora is available on GitHub:https://github.com/LiaOb21/colora. Colora is also available at the Snakemake Workflow Catalog (https://snakemake.github.io/snakemake-workflow-catalog/?usage=LiaOb21%2Fcolora).ConclusionColora is a user-friendly, versatile, and reproducible pipeline that is ready to use by researchers looking for an automated way to obtain high-qualityde novogenome assemblies.
Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults
Authors: Gong Qiuyu , Sharma Mehul , Kuan Emma L. , Glass Marla C. , Chander Aishwarya , Singh Mansi , Graybuck Lucas T. , Thomson Zachary J. , LaFrance Christian M. , Zaim Samir Rachid , Peng Tao , Okada Lauren Y. , Genge Palak C , Henderson Katherine E. , Dornisch Elisabeth M. , Layton Erik D. , Wittig Peter J. , Heubeck Alexander T. , Mukuka Nelson M. , Reading Julian , Roll Charles R. , Hernandez Veronica , Parthasarathy Vaishnavi , Stuckey Tyanna J. , Musgrove Blessing , Swanson Elliott , Lord Cara , Weiss Morgan D.A. , Phalen Cole G. , Mettey Regina R. , Lee Kevin J. , Johanneson John B. , Kawelo Erin K. , Garber Jessica , Krishnan Upaasana , Smithmyer Megan , Wherry E. John , Vella Laura , Henrickson Sarah E. , Kopp Mackenzie S. , Savage Adam K. , Becker Lynne A. , Meijer Paul , Coffey Ernest M. , Goronzy Jorg J. , Speake Cate , Bumol Thomas F. , Goldrath Ananda W. , Torgerson Troy R. , Li Xiao-jun , Skene Peter J. , Buckner Jane H. , Gustafson Claire E. 
Published: September 2024

SummaryThe generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults’ memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools athttps://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/to enhance data accessibility and further the understanding of immune health across age.
A Statistically-Robust Model Of The Axomyelin Unit Under Normal Physiologic Conditions With Application To Disease States
Authors: Gow Alexander , Dupree Jeffrey L , Feinstein Douglas L , Boullerne Anne 
Published: September 2024

ABSTRACTDespite tremendous progress in characterizing the myriad cellular structures in the nervous system, a full appreciation of the interdependent and intricate interactions between these structures is as yet unfulfilled. Indeed, few more so than the interaction between the myelin internode and its ensheathed axon. More than a half-century after the ultrastructural characterization of this axomyelin unit, we lack a reliable understanding of the physiological properties, the significance and consequence of pathobiological processes, and the means to gauge success or failure of interventions designed to mitigate disease. Herein, we highlight shortcomings in the most common statistical procedures used to characterize the axomyelin unit, with particular emphasis on the underlying principles of simple linear regression. These shortcomings lead to insensitive detection and/or ambiguous interpretation of normal physiology, disease mechanisms and remedial methodologies. To address these problems, we syndicate insights from early seminal myelin studies and use a statistical model of the axomyelin unit that is established in the accompanying article. Herein, we develop and demonstrate a statistically-robust analysis pipeline with which to examine and interpret axomyelin physiology and pathobiology in two disease states, experimental autoimmune encephalomyelitis and therumpshakermouse model of leukodystrophy. On a cautionary note, our pipeline is a relatively simple and streamlined approach that is not necessarily a panacea for allgratio analyses. Rather, it approximates a minimum effort needed to elucidate departures from normal physiology and to determine if more comprehensive studies may lead to deeper insights.
Rapid production of modified cattle and sheep from spermatid-like stem cells
Authors: Yang Lei , Di Anqi , Song Lishuang , Liu Xuefei , Wu Di , Wang Song , Hao Zhenting , Bu Lige , Bai Chunling , Su Guanghua , Wei Zhuying , Zhang Li , Liu Zhonghua , Gao Shaorong , Li Guangpeng 
Published: September 2024

AbstractHaploid androgenetic stem cells (haSCs) are revolutionary resources for studying animal traits and greatly impact livestock breeding, but livestock haSCs have yet to be obtained. Here, we report the derivation of cattle and sheep haSCs using a novel FACE medium, and these cells harbor formative pluripotency features. Notably, knockout cattle and sheep can be efficiently obtained upon injection of the protaminized haSCs with targeted gene mutations into oocytes.
Cholinergic feedback for context-specific modulation of sensory representations
Authors: Yu Bin , Yue Yuxuan , Ren Chi , Yun Rui , Lim Byungkook , Komiyama Takaki 
Published: September 2024

AbstractThe brain’s ability to prioritize behaviorally relevant sensory information is crucial for adaptive behavior, yet the underlying mechanisms remain unclear. Here, we investigated the role of basal forebrain cholinergic neurons in modulating olfactory bulb (OB) circuits in mice.Calcium imaging of cholinergic feedback axons in OB revealed that their activity is strongly correlated with orofacial movements, with little responses to passively experienced odor stimuli. However, when mice engaged in an odor discrimination task, OB cholinergic axons rapidly shifted their response patterns from movement-correlated activity to odor-aligned responses.Notably, these odor responses during olfactory task engagement were absent in cholinergic axons projecting to the dorsal cortex. The level of odor responses correlated with task performance. Inactivation of OB-projecting cholinergic neurons during task engagement impaired performance and reduced odor responses in OB granule cells. Thus, the cholinergic system dynamically modulates sensory processing in a modality-specific and context-dependent manner, providing a mechanism for a flexible and adaptive sensory prioritization.
EBAX-1/ZSWIM8 destabilizes miRNAs resulting in transgenerational memory of a predatory trait
Authors: Quiobe Shiela Pearl , Kalirad Ata , Röseler Waltraud , Witte Hanh , Wang Yinan , Rödelsperger Christian , Sommer Ralf J. 
Published: September 2024

AbstractEnvironmental influences on traits and associated transgenerational epigenetic inheritance have widespread implications, but remain controversial and underlying mechanisms poorly understood. We introduce long-term environmental induction experiments on alternative diets inPristionchus pacificus, a nematode exhibiting mouth-form plasticity including predation, by propagating 110 isogenic lines for 101 generations with associated food-reversal experiments. We found dietary induction and subsequent transgenerational memory of the predatory morph and identified a role of ubiquitin ligase EBAX-1/ZSWIM8 in this process.Ppa-ebax-1mutants have no memory andPpa-EBAX-1 destabilizes the clustered microRNA familymiR-2235a/miR-35.Deletions of a cluster of 44 identicalmiR-2235acopies resulted in precocious and extended transgenerational inheritance of the predatory morph. These findings indicate that EBAX-1/ZSWIM8 destabilizes miRNAs resulting in transgenerational memory, suggesting a role for target-directed miRNA degradation.
BST2 induces vascular smooth muscle cell plasticity and phenotype switching during cancer progression
Authors: Bell Caitlin F. , Baylis Richard A. , Lopez Nicolas G. , Ma Wei Feng , Gao Hua , Wang Fudi , Bamezai Sharika , Fu Changhao , Kojima Yoko , Adkar Shaunak S. , Luo Lingfeng , Miller Clint L. , Leeper Nicholas J. 
Published: September 2024

AbstractBackgroundSmooth muscle cell (SMC) plasticity and phenotypic switching play prominent roles in the pathogenesis of multiple diseases, but their role in tumorigenesis is unknown. We investigated whether and how SMC diversity and plasticity plays a role in tumor angiogenesis and the tumor microenvironment.Methods and ResultsWe use SMC-specific lineage-tracing mouse models and single cell RNA sequencing to observe the phenotypic diversity of SMCs participating in tumor vascularization. We find that a significant proportion of SMCs adopt a phenotype traditionally associated with macrophage-like cells. These cells are transcriptionally similar to ‘resolution phase’ M2b macrophages, which have been described to have a role in inflammation resolution. Computationally predicted by the ligand-receptor algorithm CellChat, signaling from BST2 on the surface of tumor cells to PIRA2 on SMCs promote this phenotypic transition; in vitro SMC assays demonstrate upregulation of macrophage transcriptional programs, and increased proliferation, migration, and phagocytic ability when exposed to BST2. Knockdown of BST2 in the tumor significantly decreases the transition towards a macrophage-like phenotype, and cells that do transition have a comparatively higher inflammatory signal typically associated with anti-tumor effect.ConclusionAs BST2 is known to be a poor prognostic marker in multiple cancers where it is associated with an M2 macrophage-skewed TME, these studies suggest that phenotypically switched SMCs may have a previously unidentified role in this immunosuppressive milieu. Further translational work is needed to understand how this phenotypic switch could influence the response to anti-cancer agents and if targeted inhibition of SMC plasticity would be therapeutically beneficial.
Operant conditioning of cortical waves through a brain-machine interface
Authors: Dogadov Anton A. , Shulz Daniel E. , Ferezou Isabelle , Ego-Stengel Valérie , Estebanez Luc 
Published: September 2024

ABSTRACTAt the surface of the cerebral cortex, activity dynamics measured at a mesoscopic (about 0.1 to 1 mm in mouse cortex) scale are characterized by both spontaneous and behavior-related dynamical waves of synchronized neuronal activity. These waves are thought to participate in information propagation and processing, but remain poorly understood.To assess if such mesoscopic coordinated neuronal dynamics can be controlled in a goal-directed manner, we implemented a task in which mice are trained to generate waves with specific trajectories in order to obtain rewards. We tracked propagating waves at the surface of the somatosensory-motor cortex of head-fixed mice in real time by means of wide field calcium imaging, and conditioned the delivery of rewards to the detection of wave trajectories responding to specific spatiotemporal criteria.We found that the majority of the trained mice significantly increased their performance, mainly by increasing the frequency of rewardable waves. As the mice learned to achieve this task, we observed changes in the spatiotemporal patterns of the cortical waves. By revealing that, upon learning, neuronal activity can be shaped at the mesoscopic scale to generate specific waves patterns, our work opens up new perspectives for brain-machine interfacing.
Prediction of Protein Half-lives from Amino Acid Sequences by Protein Language Models
Authors: Sagawa Tatsuya , Kanao Eisuke , Ogata Kosuke , Imami Koshi , Ishihama Yasushi 
Published: September 2024

AbstractWe developed a protein half-life prediction model, PLTNUM, based on a protein language model using an extensive dataset of protein sequences and protein half-lives from the NIH3T3 mouse embryo fibroblast cell line as a training set. PLTNUM achieved an accuracy of 71% on validation data and showed robust performance with an ROC of 0.73 when applied to a human cell line dataset. By incorporating Shapley Additive Explanations (SHAP) into PLTNUM, we identified key factors contributing to shorter protein half-lives, such as cysteine-containing domains and intrinsically disordered regions. Using SHAP values, PLTNUM can also predict potential degron sequences that shorten protein half-lives. This model provides a platform for elucidating the sequence dependency of protein half-lives, while the uncertainty in predictions underscores the importance of biological context in influencing protein half-lives.