bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultra-resolution Deconvolution of Spatial Transcriptomics Unveils Spatiotemporal Cellular Dynamics in Complex Microenvironments
Authors: Xu Yin , Huang Zurui , Zhang Yawei , Wang Zhenghang , Guo Peijin , Zhang Feifan , Gong Wenxuan , Liang Guanghao , Mei Boyuan , Dong Lihui , Chang Renbao , Gong Minghui , Xia Yu , Ni Haochen , Yang Jing , Gao Yuan , Liu Zhaoqi , Shen Lin , Li Jian , Xu Meng Michelle , Han Dali 
Published: July 2024

AbstractThe current challenge in analyzing sequencing-based spatial transcriptomics (ST) is to precisely resolve the spatial distribution of cell subpopulations with low abundance and detect context-dependent variation in cell states within complex tissue microenvironments. Here, we introduce an ultra-resolution ST deconvolution algorithm (UCASpatial) that improves the resolution of mapping cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to murine wound healing, we recapitulate known spatiotemporal dynamics of multiple cell subpopulations involved in wound healing and reveal the spatial segregation of distinct macrophage subpopulations embedded within different cellular communities at the wound center. In human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME within the same tumor. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic endogenous retrovirus silencing and impaired type I interferon response. Our findings present UCASpatial as a versatile tool for deciphering ultra-resolution cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.
SOFisher: Reinforcement Learning-Guided Experiment Designs for Spatial Omics
Authors: Li Zhuo , Wu Weiran , Cui Yan , Sun Jian , Yuan Zhiyuan 
Published: July 2024

AbstractSpatial omics technologies enable the precise detection of proteins and RNAs at high spatial resolution. Designing spatial omics experiments requires careful consideration of “what” targets to measure and “where” to position the field of views (FOVs). Current FOV sampling strategies often involve acquiring densely sampled FOVs and stitching them together, which is time-consuming, resource-intensive, and sometimes impossible. To optimize FOV sampling strategies, we developed SOFisher, a reinforcement learning-based framework that harnesses the knowledge gained from the sequence of previously sampled FOVs to guide the selection of the next FOV position, to improve the efficiency of capturing more regions of interest. We rigorously evaluated SOFisher’s performance using comprehensive simulations based on real spatial datasets, and our results clearly demonstrated that SOFisher consistently outperformed the conventional approach across various metrics. SOFisher’s robustness and generalizability were further validated through cross-domain generalization tests and its adaptability to varying FOV sizes. On a real Alzheimer’s Disease (AD) dataset, SOFisher successfully guided the selection of FOVs containing neurofibrillary tangles and amyloid-β plaques in both single and dual target tissue landmark scenarios. Remarkably, SOFisher-guided experiment design of spatial single-omics on limited tissue areas yielded insights into AD-related cell states, subtypes, and gene programs previously obtained through extensive spatial multi-omics experiments. SOFisher has the potential to revolutionize the experiment design of spatial biology.
Novel single-cell preservation and RNA sequencing technology unlocks field studies forPlasmodiumnatural infections
Authors: Sauve Erin , Monsieurs Pieter , Guetens Pieter , de Moraes Barros Roberto Rudge , Rosanas-Urgell Anna 
Published: July 2024

AbstractSingle-cell RNA sequencing (scRNA-seq) is a powerful technology used to investigate cellular heterogeneity. When applied to unicellular eukaryotes such asPlasmodiumparasites, scRNA-seq provides a single-cell resolution particularly valuable to study complex infections which are often comprised of mixed life stages and clones. Until now, the application of scRNA-seq has been mainly limited toin vitroand animal malaria models, despite known transcriptional differences as compared to circulating parasite populations. This is primarily due to the challenges of working withPlasmodiumnatural infections in endemic settings. We validated sample preparation methods and a novel single-cell RNA sequencing technology for the first time inP. knowlesiparasites which can be effectively implemented to analyze natural infections in low-resource settings. We recovered 22,345P. knowlesisingle-cell transcriptomes containing all asexual blood stages from 6in vitroculture samples, with conditions mimicking natural infections, and generated the most extensiveP. knowlesisingle-cell dataset to date. All 6 samples produced reproducible circular UMAP projections with consistent cluster localization and high gene expression correlation, regardless of the sample preparation methods used. Biomarker expression and life stage annotation using the Malaria Cell AtlasP. knowlesireference dataset further confirmed these results. In conclusion, the combination of adaptable sample preparation methods with novel preservation and scRNA-seq technology has the potential to fundamentally transform the study of natural infections. This approach unlocks the use of scRNA-seq in field studies which will lead to new insights intoPlasmodiumparasite biology.ImportanceSequencing unicellular organisms, such as malaria parasites, at the single-cell level is important to understand the diversity present in cell populations. Until now, single-cell sequencing of malaria has been primarily limited to laboratory models. While these models are key to understanding biological processes, there are known differences between lab models and parasite populations circulating in natural human infections. This study presents sample preparation methods and a new single-cell RNA sequencing technology that enables sample collection from natural infections in low-resource settings. Using a mock natural infection, we validated this new single-cell RNA sequencing technology using marker genes with known expression patterns and a reference dataset from the Malaria Cell Atlas. We demonstrate that high-quality single-cell transcriptomes with consistent expression patterns can be recovered using various sample preparation methods, thereby unlocking single-cell sequencing for field studies and leading to additional insights into parasite biology in the future.
Organizational principles of the primate cerebral cortex at the single-cell level
Authors: Chen Renrui , Nie Pengxing , Ma Liangxiao , Wang Guang-Zhong 
Published: July 2024

AbstractThe primate cerebral cortex, the major organ for cognition, consists of an immense number of neurons. However, the organizational principles governing these neurons remain unclear. By accessing the single-cell spatial transcriptome of over 25 million neuron cells across the entire macaque cortex, we discovered that the distribution of neurons within cortical layers is highly non-random. Strikingly, over three-quarters of these neurons are located in distinct neuronal clusters. Within these clusters, different cell types tend to collaborate rather than function independently. Typically, excitatory neuron clusters mainly consist of excitatory-excitatory combinations, while inhibitory clusters primarily contain excitatory-inhibitory combinations. Both cluster types have roughly equal numbers of neurons in each layer. Importantly, most excitatory and inhibitory neuron clusters form spatial partnerships, indicating a balanced local neuronal network and correlating with specific functional regions. These findings suggest that different brain regions of the primate cortex may exhibit similar mechanisms at the neuronal population level.
Concurrent optogenetic motor mapping of multiple limbs in awake mice reveals cortical organization of coordinated movements
Authors: Khanal Nischal , Padawer-Curry Jonah , Voss Trevor , Schulte Kevin , Bice Annie , Bauer Adam 
Published: July 2024

AbstractBackgroundMotor mapping allows for determining the macroscopic organization of motor circuits and corresponding motor movement representations on the cortex. Techniques such as intracortical microstimulation (ICMS) are robust, but can be time consuming and invasive, making them non-ideal for cortex-wide mapping or longitudinal studies. In contrast, optogenetic motor mapping offers a rapid and minimally invasive technique, enabling mapping with high spatiotemporal resolution. However, motor mapping has seen limited use in tracking 3-dimensonal, multi-limb movements in awake animals. This gap has left open questions regarding the underlying organizational principles of motor control of coordinated, ethologically relevant movements involving multiple limbs.ObjectiveOur first objective was to develop Multi-limb Optogenetic Motor Mapping (MOMM) to concurrently map motor movement representations of multiple limbs with high fidelity in awake mice. Having established MOMM, our next objective was determine whether maps of coordinated and ethologically relevant motor output were topographically organized on the cortex.MethodsWe combine optogenetic stimulation with a deep learning driven pose-estimation toolbox, DeepLabCut (DLC), and 3-dimentional triangulation to concurrently map motor movements of multiple limbs in awake mice.ResultsMOMM consistently revealed cortical topographies for all mapped features within and across mice. Many motor maps overlapped and were topographically similar. Several motor movement representations extended beyond cytoarchitecturally defined somatomotor cortex. Finer articulations of the forepaw resided within gross motor movement representations of the forelimb. Moreover, many cortical sites exhibited concurrent limb coactivation when photostimulated, prompting the identification of several cortical regions harboring coordinated and ethologically relevant movements.ConclusionsThe cortex appears to be topographically organized by motor programs, which are responsible for coordinated, multi-limbed, and behavioral-like movements.
Inhibitory neurons marked by a connectivity molecule regulate memory precision
Authors: Tuñon-Ortiz Arnulfo , Tränkner Dimitri , Brockway Sarah N. , Raines Olivia , Mahnke Abbey , Grega Matthew , Zelikowsky Moriel , Williams Megan E. 
Published: July 2024

SUMMARYThe CA3 region is central to hippocampal function during learning and memory and has a unique connectivity. CA3 pyramidal neurons are the targets of huge, excitatory mossy fiber synapses from DG axons and have a high degree of excitatory recurrent connectivity. Thus, inhibition likely plays an outsized importance in constraining excitation and shaping CA3 ensembles during learning and memory. Here, we investigate the function of a never-before studied set of dendrite-targeting, GABAergic neurons defined by expression of the synaptic adhesion molecule, Kirrel3. We discovered that activating Kirrel3-expressing GABAergic neurons specifically impairs memory discrimination and inhibits CA3 pyramidal neurons in novel contexts. Kirrel3 is required for DG-to-GABA synapse formation and variants in Kirrel3 are strong risk factors for neurodevelopmental disorders. Thus, our work suggests that Kirrel3-GABA neurons are a critical source of feed-forward inhibition from DG to CA3 during the encoding and retrieval of contextual memories, a function which may be specifically disrupted in some brain disorders.
Global Perspectives on Returning Genetic Research Results in Parkinson’s Disease
Authors: Tan Ai Huey , Saffie-Awad Paula , Schumacher Schuh Artur F , Lim Shen-Yang , Madoev Harutyun , Ahmad-Annuar Azlina , Solle Justin , Wegel Claire Ellen , Doquenia Maria Leila , Dey Sumit , Periñan Maria Teresa , Makarious Mary B , Fiske Brian , Morris Huw R , Noyce Alastair J , Alcalay Roy N. , Kumar Kishore R. , Klein Christine ,   the Global Parkinson’s Genetics Program (GP2)
Published: July 2024

AbstractIn the era of precision medicine, genetic test results have become increasingly relevant in the care of patients with Parkinson’s disease (PD) and their families. While large PD research consortia are performing widespread genetic testing to accelerate discoveries, debate continues about whether, and to what extent, the results should be returned to patients. Ethically, it is imperative to keep participants informed, especially when findings are potentially actionable. However, research testing may not hold the same standards required from clinical diagnostic laboratories. The absence of universally recognized protocols complicates the establishment of appropriate guidelines. Aiming to develop recommendations on return of research results (RoR) practice within the Global Parkinson’s Genetics Program (GP2), we conducted a global survey to gain insight on GP2 members’ perceptions, practice, readiness, and needs surrounding RoR. GP2 members (n=191), representing 147 institutions and 60 countries across six continents, completed the survey. Access to clinical genetic testing services was significantly higher in high-income countries compared to low– and middle-income countries (96.6% vs. 58.4%), where funding was predominantly covered by patients themselves. While 92.7% of the respondents agreed that genetic research results should be returned, levels of agreement were higher for clinically relevant results relating to pathogenic or likely pathogenic variants in genes known to cause PD or other neurodegenerative diseases. Less than 10% offered separate clinically-accredited genetic testing before returning genetic research results. 48.7% reported having a specific statement on RoR policy in their ethics consent form, while 53.9% collected data on participants’ preferences on RoR prospectively. 24.1% had formal genetic counselling training. Notably, the comfort level in returning incidental genetic findings or returning results to unaffected individuals remains low. Given the differences in resources and training for RoR, as well as ethical and regulatory considerations, tailored approaches are required to ensure equitable access to RoR. Several identified strategies to enhance RoR practices include improving informed consent processes, increasing capacity for genetic counselling including providing counselling toolkits for common genetic variants, broadening access to sustainable clinically-accredited testing, building logistical infrastructure for RoR processes, and continuing public and healthcare education efforts on the important role of genetics in PD.
Identification of Causal Risk Factors for Pan-Cancers: a Mendelian Randomization Study
Authors: Du Bowen , Fan Li , Tang Chaopeng , Xu Song , Ge Jingping , Shang Xuejun 
Published: July 2024

AbstractBackgroundEvidence from observational studies and clinical trials suggests an association between plasma protein and metabolite levels and cancers. However, the causal relationship between them is still unclear.MethodsWe collected genome-wide association study (GWAS) summary statistics of plasma protein levels from the UK Biobank Pharma Proteomics Project (UKB-PPP, 9,216 to 34,090 participants) and plasma metabolites from the GWAS Catalog (3,441 to 8,299 participants), paired with summary statistics of 99 types of cancers from FinnGen database (131,348 to 412,181 participants). We conducted univariable and multivariable Mendelian randomization (MR) analyses to explore the causal association between plasma protein and metabolites and cancers.ResultsWe identified 175 plasma proteins and 28 metabolites causally associated with cancers (p < 1 × 10−5). Notably, BTN2A1 is causally associated with an increased risk of bone and articular cartilage cancer (OR = 1.776, 95% CI = 1.429 - 2.207), colorectal cancer (OR = 1.200, 95% CI = 1.129 - 1.275), eye and adnexa cancer (OR = 2.686, 95% CI = 1.943 - 3.714), lip cancer (OR = 3.004, 95% CI = 2.193 - 4.114), oral cancer (OR = 1.905, 95% CI = 1.577 - 2.302), ovary cancer (OR = 1.265, 95% CI = 1.143 - 1.400), and rectum cancer (OR = 1.393, 95% CI = 1.263 - 1.536). N6- carbamoylthreonyladenosine level is causally associated with various cancers including colorectal cancer (OR = 1.800, 95% CI = 1.444 – 2.243), head and neck cancer (OR = 2.423, 95% CI = 1.665 – 3.525), hepatocellular carcinoma (OR = 6.476, 95% CI = 2.841 – 14.762), oral cancer and skin cancer (OR = 1.271, 95% CI = 1.161 – 1.392). Additionally, all results are available at the online database (www.causal-risk.net).ConclusionsOur MR analysis reveals causal risk factors for cancers.
Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer’s disease dementia
Authors: Gaubert Sinead , Garces Pilar , Hipp Jörg , Bruña Ricardo , Lopéz Maria Eugenia , Maestu Fernando , Vaghari Delshad , Henson Richard , Paquet Claire , Engemann Denis 
Published: July 2024

AbstractIntroductionAlzheimer’s disease (AD) is the most common cause of dementia. Non-invasive, affordable, and largely available biomarkers that are able to identify patients at a prodromal stage of AD are becoming essential, especially in the context of new disease-modifying therapies. Mild cognitive impairment (MCI) is a critical stage preceding dementia, but not all MCI patients will progress to AD. This study explores the potential of non-invasive magnetoencephalography (MEG) to predict future cognitive decline from MCI to AD dementia.MethodsWe analyzed resting state MEG data from the BioFIND dataset including 117 MCI patients, of whom 64 progressed to AD dementia (AD progression) while 53 remained stable (stable MCI) using multivariate spectral analyses. The patients were followed-up between 2009 and 2018. Receiver operating characteristic curves obtained via logistic regression models were used to quantify separation of patients progressing to AD dementia from stable MCI.ResultsMEG beta power, particularly over parieto-occipital magnetometers, was significantly reduced in the AD progression group compared to stable MCI, indicative of future cognitive decline. Logistic regression models showed that MEG beta power outperformed conventional metrics like the Mini Mental Status Examination (MMSE) score and structural brain measures in predicting progression to AD dementia (AUC 0.81 vs 0.71 and AUC 0.81 vs 0.75, respectively). The combination of age, education, MMSE, MEG beta power and Hippocampal volume/Total grey matter ratio achieved a 0.83 AUC, 78% sensitivity and 76% specificity. Spectral covariance matrices analyzed with Riemannian methods exhibited significant differences between groups across a wider range of frequencies than spectral power.DiscussionThese findings highlight the potential of spectral power and covariance as robust non-invasive electrophysiological biomarkers to predict MCI progression that complement other diagnostic measures, including cognitive scores, structural magnetic resonance imaging (MRI) and biological biomarkers.
Erectile Dysfunction as a Novel Biomarker for The Onset of Cardiometabolic Vascular Disease Risk in the Aging Male: A Systematic Review and Meta-Analysis
Authors: Borges Julian Yin Vieira 
Published: July 2024

AbstractBackground and ObjectiveVascular Erectile dysfunction (ED) is considered a sentinel marker for underlying cardiovascular and metabolic disorders. This systematic review and meta-analysis aim to quantify the predictive value of ED for cardiometabolic vascular diseases (CVD) in young adults as well as aging males and to explore the temporal relationship between ED onset and the development of these diseases.MethodsA comprehensive search of databases including PubMed, EMBASE, and Cochrane Library was conducted to identify relevant studies. Inclusion criteria were studies assessing the association between ED and CVD, with effect sizes reported as odds ratios (ORs) or hazard ratios (HRs). Data were extracted and pooled using random-effects meta-analysis. Sensitivity analyses, including leave-one-out analysis, and Egger’s test for publication bias, were performed.Key Findings and LimitationsThe pooled analysis of 39 studies revealed a significant association between ED and CVD with an OR of 1.42 (95% CI: 1.28-1.57).The temporal relationship indicates that ED precedes the onset of CVD by approximately 2 to 5 years.Endothelial dysfunction, a common pathway in ED and CVD, was highlighted through biomarkers such as flow-mediated dilation (FMD), nitric oxide (NO) levels, and C-reactive protein (CRP).Limitations include heterogeneity among study designs and the potential for residual confounding.Conclusions and Clinical ImplicationsED is a robust predictive biomarker for CVD in aging males, with significant implications for early detection and preventive strategies. Clinicians should consider cardiovascular risk assessment in patients presenting with ED to facilitate timely intervention and improve long-term outcomes.
The rhythmic transcriptional landscape inCaenorhabditis elegans: daily, circadian and novel 16-hour cycling gene expression revealed by RNA-sequencing
Authors: Munns Jack , Newling Katherine , James Sally R. , Gilbert Lesley , Davis Seth J. , Chawla Sangeeta 
Published: July 2024

AbstractThe nematodeCaenorhabditis elegansis an unconventional model in chronobiology, reported to exhibit physiological and behavioural circadian rhythms while lacking a defined transcriptional oscillator. The extent and importance of circadian rhythms inC. elegansremain uncertain, given a probable lack of functional conservation of key circadian proteins, relatively non-robust reported rhythms and an ambiguous diel ecology. Here, we investigated the temporal coordination of gene expression inC. eleganspost-development using RNA sequencing. Over a circadian time series, in which we synchronised nematodes to combined light and temperature cycles, we found clear evidence of daily oscillations in 343 genes using JTK_Cycle. However, rhythms were not well-sustained in constant conditions, with only 13 genes remaining significantly rhythmic. Reanalysis of previous transcriptomic data echoed this finding in identifying far fewer rhythmic genes in constant conditions, while also identifying a greater number of rhythmic genes overall. Weighted gene co-expression network analysis (WGCNA), a hierarchical clustering approach, further confirmed prevalent environmentally driven daily oscillations in the RNA-seq data. This analysis additionally revealed a novel co-expression trend in which over 1000 genes exhibited hitherto unreported 16-hour oscillations, highlighting a new facet of temporal gene expression coordination inC. elegans.