bluuebunny/crossref_metadata_2025_split huggingface dataset:
A newly developed whole genome sequencing protocol enables early tracking of Enterovirus D68 molecular evolution
Authors: Giardina Federica AM , Romano Greta , Ferrari Guglielmo , Pellegrinelli Laura , Seiti Arlinda , Galli Cristina , Pariani Elena , Piralla Antonio , Baldanti Fausto 
Published: October 2024

ABSTRACTBackground Human enterovirus D68 (EV-D68) has been associated with an increase in mild-to-severe pediatric respiratory diseases worldwide. The rate of circulation of this virus is largely underestimated in the population and genetic evolutionary data are usually available only for partial sequences (e.g VP1 region). To achieve a timely genomic surveillance, a reliable, high-throughput EV-68 sequencing assay is required. Here we report an improved high-throughput EV-D68 whole-genome sequencing (WGS) assay performed directly on clinical samples that is suitable for short-read sequencing platforms. Between June and December 2022, a total 37 (1.9%) respiratory samples were EV-D68 positive and together with 52 additional samples with a median cycle threshold of 28.3, ranging from 18 to 36.8 were included in the validation analyses. Overall, all the primers had good performance and no mismatches were detected in more than 85% of sequences (932 WGS dataset). Using a cut-off of Cq <32 in at least 85.5% of samples a WG or PG was obtained, confirming an acceptable positive sequencing rate for the designed method. A total of 65 WGS were obtained and have a mean coverage of 98.4% across the genome, with a median depth of 6158x (range 2815x-7560x). Based on the obtained data, this method is cost effective resulting in an easy-to-perform protocol helpful for tracing the evolution of EV-D68 in protein different from VP1. EV-D68 could become a significant pathogen for public health in the next future, and thus this protocol for whole genome sequencing could help clinical and molecular virologists to be ready for molecular epidemiology surveillance.
Spatial and Spectral Changes in Cortical Surface Potentials during Pinching versus Thumb and Index Finger Flexion
Authors: Kerezoudis Panagiotis , Jensen Michael A , Huang Harvey , Ojemann Jeffrey G. , Klassen Bryan T. , Ince Nuri F. , Hermes Dora , Miller Kai J 
Published: October 2024

ABSTRACTElectrocorticographic (ECoG) signals provide high-fidelity representations of sensorimotor cortex activation during contralateral hand movements. Understanding the relationship between independent and coordinated finger movements along with their corresponding ECoG signals is crucial for precise brain mapping and neural prosthetic development. We analyzed subdural ECoG signals from three adult epilepsy patients with subdural electrode arrays implanted for seizure foci identification. Patients performed a cue-based task consisting of thumb flexion, index finger flexion or a pinching movement of both fingers together. Broadband power changes were estimated using principal component analysis of the power spectrum. All patients showed significant increases in broadband power during each movement compared to rest. We created topological maps for each movement type on brain renderings and quantified spatial overlap between movement types using a resampling metric. Pinching exhibited the highest spatial overlap with index flexion, followed by superimposed index and thumb flexion, with the least overlap observed for thumb flexion alone. This analysis provides practical insights into the complex overlap of finger representations in the motor cortex during various movement types, and may help guide more nuanced approaches to brain-computer interfaces and neural prosthetics.SIGNIFICANCE STATEMENTThis study measured brain activity actively during finger movement and found that pinching movements show higher cortical overlap with index finger flexion and uniquely engage parietal regions, advancing our understanding of motor control hierarchy and sensorimotor integration, while suggesting improvements for more naturalistic brain-computer interfaces through prioritized index finger decoding and integration of parietal lobe measurements.
scGNN+: Adapting ChatGPT for Seamless Tutorial and Code Optimization
Authors: Jiang Yi , Wang Shuang , Feng Shaohong , Wang Cankun , Wu Weidong , Huang Xiaopei , Ma Qin , Wang Juexin , Ma Anjun 
Published: October 2024

AbstractFoundation models have transformed AI by leveraging large-scale data to efficiently perform diverse tasks, and their applications in bioinformatics are primarily focused on data-centric tasks like cell type annotation and gene expression analysis. However, their potential extends beyond data analysis, offering significant opportunities in software development and optimization, such as code refinement, tutorial generation, and advanced visualization. For example, models like OpenAI Codex can suggest optimized code snippets and generate well-documented, reproducible workflows, enhancing accessibility and reducing computational complexity. Despite these advantages, the use of foundation models for improving computational tool engineering in single-cell research remains underutilized. To address this gap, we developed scGNN+, a web-based platform that combines the power of graph neural networks with the capabilities of ChatGPT to enhance reproducibility, code optimization, and visualization. scGNN+ further simplifies the process for users by generating standardized, well-annotated code, making complex procedures more accessible to non-programmers. Additionally, ChatGPT integration allows users to create high-quality, customizable visualizations through natural language prompts, improving data interpretation and presentation. Ultimately, scGNN+ offers a user-friendly, reproducible, and optimized solution for single-cell research, leveraging the full potential of foundation models in bioinformatics. scGNN+ is publicly available at https://bmblx.bmi.osumc.edu/scgnn+.
Capturing the Hierarchically Assorted Protein-protein Interaction Modules of Mammalian Cell
Authors: Dai Shuaijian , Zhang Yage , Yu Weichuan , Li Ning 
Published: October 2024

AbstractProteins are organized into modules by both functions and physical interactions within compartments of an eukaryotic cell. Thein vivochemical crosslinking mass spectrometry (XL-MS) data collected from organelles, the whole cells and tissues are able to provide unique information about both protein-protein interaction (PPI) and the intensity of PPI. In the present study, we have retrieved 55,982 crosslinked peptides (XL-peptides) from the XL-MS databases, out of which 6,356in vivoPPIs were identified. Introduction of the MONET software into analysis of 4,526 hetero PPIs revealed a total of 402 protein modules, including 15, 58 and 163 stable protein complex(s), condensate-forming protein module(s) and intrinsically disordered region (IDR)-containing protein module(s), respectively. The application of ChatGPT in analysis of these modules unexpectedly identified 4 vesicle-related modules. Together, these modules were assorted into 6 communities (module of modules) and 3 systems (module of communities) hierarchically. The bioinformatic analysis found that the three systems are corresponding to three compartments of eukaryotic cell: nuclei, mitochondria, endoplasmic reticulum (ER), respectively. This study presents a novel and comprehensive biomolecular modulome of a mammalian cell, which captures putative protein compositions of protein complexes, protein condensates and vesicles and provides a hierarchical protein organization and function within compartments of mammalian cell.
Oddball evoked deviant responses reflect complex context dependent expectations in mouse V1
Authors: Knudstrup Scott G. , Martinez Reyes Catalina , Jensen Cambria M. , Schecter Rachel W. , Frank Mac Kenzie , Gavornik Jeffrey P. 
Published: October 2024

AbstractEvoked responses in the mouse primary visual cortex can be modulated by the temporal context in which visual inputs are presented. Oddball stimuli embedded in a sequence of regularly repeated visual elements have been shown to drive relatively large deviant responses, a finding that is generally consistent with the theory that cortical circuits implement a form of predictive coding. These results can be confounded by short-term adaptation effects, however, that make interpretation difficult. Here we use various forms of the oddball paradigm to disentangle temporal and ordinal components of the deviant response, showing that it is a complex phenomenon affected by temporal structure, ordinal expectation, and event frequency. Specifically, we use visually evoked potentials to show that deviant responses occur over a large range of time, lead to long-term plasticity in some cases, cannot be explained by a simple adaptation model, scale with predictability, and are modulated by violations of both first and second-order sequential expectations.Significance StatementVisual experience and temporal context can modulate evoked responses in mouse V1. There remains disagreement about whether this reflects predictive coding in visual circuits and if visual mismatched negativity, which has important cross-over implications for human clinical work, constitutes evidence supporting this theory or simple neural adaptation. This work strongly supports the former interpretation by demonstrating complex experience-dependent deviant responses that cannot be easily explained by a simple adaptation model. We use statistically rigorous analysis of the local field potential to show that oddball evoked deviance signals reflect relative timing, event frequency, 1stand 2ndorder sequence expectations and scale as a function of event probability.
Relating GPCR domains with functionality: receptor helix-bundle and C-terminus differentially influence GRK-specific functions and β-arrestin-mediated regulation
Authors: Matthees Edda S. F. , Haider Raphael S. , Klement Laura , Reichel Mona , Blum Nina K. , Weitzel Verena , Trüpschuch Thimea , Ziegler Carla , Drube Julia , Schulz Stefan , Hoffmann Carsten 
Published: October 2024

AbstractG protein-coupled receptors (GPCRs) orchestrate diverse physiological responses via intracellular signaling through G proteins, GPCR kinases (GRKs), and arrestins. While the role of G proteins in receptor signaling is well-established, the contributions of GRKs and arrestins remain incompletely understood. Here, we investigate the influence of arrestin-interacting GPCR domains (helix-bundle/C-terminus) on β-arrestin conformations and functions using refined biosensors and advanced cellular knockout systems. By focusing on prototypical class A (b2AR) and B (V2R) receptors and their chimeras (b2V2/V2b2), we can now characterize differential β-arrestin conformational changes as primarily mediated by the receptor C-terminus or helix-bundle. Moreover, we demonstrate that some β-arrestin-supported processes are governed by distinct receptor domains, such as ERK1/2 activation (helix-bundle) and arrestin co-internalization (C-terminus), while others depend on the overall GPCR configuration, such as receptor internalization. Our findings elucidate how individual GPCR domains dictate downstream signaling events, shedding light on the structural basis of receptor-specific signaling and regulation.
Acid excretion is impaired in calcium oxalate stone formers
Authors: Imenez Silva Pedro H , Dhayat Nasser A. , Fuster Daniel G. , Seeger Harald , Ritter Alexander , Ernandez Thomas , Buchkremer Florian , Roth Beat , Bonny Olivier , Rubio-Aliaga Isabel , Wagner Carsten A. 
Published: October 2024

ABSTRACTBackgroundUrine pH is a key factor in kidney stone formation. We aimed to identify whether acid excretion capacity is disturbed in calcium oxalate (CaOx) or calcium phosphate (CaP) stone formers.MethodUrinary, serum, clinical, and anthropomorphic baseline data were obtained from the Swiss Kidney Stone Cohort, a prospective, longitudinal, and multi-centric observational study. We included in this study 193 non-stone formers (NSF, confirmed by negative CT scan), and 309 CaOx and 28 CaP stone formers. Titratable acids, net acid excretion (NAE), NAE capacity (NAEC) and acid-base (AB) score were calculated. Logistic regression analyses were used to estimate the potential associations of various acid-base variables with the occurrence of CaOx kidney stones.ResultsCaOx stone formers showed a disturbed capacity to excrete acids in comparison to NSF (NAEC NSF = 3.49±12.6 mmol/24h; CaOx = −1.06±13.10; CaP = 0.97±14.70 and AB score NSF = 20.5±6.36 mmol/24h; CaOx = 17.9± 6.53; CaP = 18.8±6.10). The correlation between urine calcium and urine pH was altered in CaOx stone formers and between urine calcium and NAE was stronger in CaP stone formers. Logistic models showed that urinary ammonium was negatively associated with CaOx stone formation (unadjusted model, odds ratio 0.43[0.32-0.58], p< 0.001 for CaOx). Urine calcium was positively associated with CaOx kidney stones (2.85 [2.11-3.92], p<0.001). Similar results were obtained after adjusting for age, sex, and BMI. Replacing urine ammonium, pH, and phosphate with NAEC or ammonium and pH with AB score in our logistic regression models showed that NAEC and AB score are strongly associated with CaOx kidney stone formation.ConclusionAmmonium excretion, NAEC and AB score are associated with the occurrence of CaOx kidney stones suggesting a potential role of proximal tubule dysfunction in their formation. CaP stone formers exhibit a disproportionately higher calcium excretion when acid excretion increases.Key learning pointsWhat was knownUrine pH is a strong determinant in the formation of various urologically relevant crystals. Impaired urine acidification capacity has been observed in individuals who form calcium phosphate and uric acid stones.This study addsWhen compared to non-stone formers, calcium oxalate stone formers are marked by a reduced capacity of excreting acids when urine pH becomes more acidic.Potential impactThe calculation of net acid excretion capacity and acid-base score are novel tools to identify those under potential higher risk of developing calcium oxalate stones.
Dissociable after-effects of prosocial acts: Effort is costly for others but valued for self
Authors: Zheng Ya , Tang Rumeng 
Published: October 2024

AbstractProsocial behavior requires effort, yet people are often reluctant to exert effort for others’ benefit. However, the manner in which effort exertion affects subsequent reward evaluation during prosocial acts remains elusive. Here, we leveraged the temporal precision of electroencephalography, along with a paradigm that independently manipulated effort and reward for self and another person, to uncover the neural mechanism underlying the reward after-effect of effort expenditure during prosocial acts. We found a dissociable reward after-effect between self-benefitting and other-benefitting effort. When the beneficiary was oneself, the reward positivity (RewP) became more positive as effort increased, indicating an effort-enhancement effect. In contrast, when the beneficiary was others, the RewP became less positive as effort increased, demonstrating an effort-discounting effect. Moreover, this dissociation occurred only when reward system was activated and was independent of performance evaluation. Our finding provides novel insights into how prior effort expenditure shape reward evaluation during prosocial behavior.
Experience shapes the transformation of olfactory representations along the cortico-hippocampal pathway
Authors: Schiltz Eleonore , Broux Martijn , Aydin Cagatay , Goncalves Pedro , Haesler Sebastian 
Published: October 2024

ABSTRACTPerception relies on the neural representation of sensory stimuli. Primary sensory cortical representations have been extensively studied, but how sensory information propagates to memory-related multisensory areas has not been well described. We studied this question in the olfactory cortico-hippocampal pathway in mice. We recorded single units in the anterior olfactory nucleus (AON), the anterior piriform cortex (aPCx), lateral entorhinal cortex (LEC), the hippocampal CA1 subfield, and the subiculum (SUB) while animals performed a non-associative learning paradigm involving novel and familiar stimuli. Novel stimuli evoked larger responses than familiar stimuli in the AON, whereas in hippocampal areas, novelty was reflected by the number of responsive neurons. In parallel, odorant selectivity increased along the pathway. While both stimulus identity and experience were thus reflected in all regions, their neural representations gradually separated. Our findings provide a potential mechanism for how sensory representations are transformed to support stimulus identification and implicit memories.
Scalable Fabrication of an Array-Type Fixed-Target Device for Automated Room Temperature X-ray Protein Crystallography
Authors: Saha Sarthak , Chen Yaozu , Russi Silvia , Marchany-Rivera Darya , Cohen Aina , Perry Sarah L. 
Published: October 2024

1.AbstractX-ray crystallography is one of the leading tools to analyze the 3-D structure, and therefore, function of proteins and other biological macromolecules. Traditional methods of mounting individual crystals for X-ray diffraction analysis can be tedious and result in damage to fragile protein crystals. Furthermore, the advent of serial crystallography methods explicitly require the mounting of large numbers of crystals. To address this need, we have developed a device that facilitates the straightforward mounting of protein crystals for diffraction analysis, and that can be easily manufactured at scale. Inspired by grid-style devices that have been reported in the literature, we have developed an X-ray compatible microfluidic device that can be used to trap protein crystals in an array configuration, while also providing excellent optical transparency, a low X-ray background, and compatibility with the robotic sample handling and environmental controls used at synchrotron macromolecular crystallography beamlines. At the Stanford Synchrotron Radiation Lightsource (SSRL), these capabilities allow for fully remote-access data collection at controlled humidity conditions. Furthermore, we have demonstrated continuous manufacturing of these devices via roll-to-roll fabrication to enable cost-effective and efficient large-scale production.
Benchmarking a foundational cell model for post-perturbation RNAseq prediction
Authors: Csendes Gerold , Szalay Kristóf Z. , Szalai Bence 
Published: October 2024

AbstractAccurately predicting cellular responses to perturbations is essential for understanding cell behaviour in both healthy and diseased states. While perturbation data is ideal for building such predictive models, it is considerably sparser than baseline (non-perturbed) cellular data. To address this limitation, several foundational cell models have been developed using large-scale single-cell gene expression data. These models are fine-tuned after pre-training for specific tasks, such as predicting post-perturbation gene expression profiles, and are considered state-of-the-art for these problems. However, proper benchmarking of these models remains an unsolved challenge.In this study, we benchmarked a recently published foundational model, scGPT, against baseline models. Surprisingly, we found that even the simplest baseline model - taking the mean of training examples - outperformed scGPT. Furthermore, machine learning models that incorporate biologically meaningful features outperformed scGPT by a large margin. Additionally, we identified that the current Perturb-Seq benchmark datasets exhibit low perturbation-specific variance, making them suboptimal for evaluating such models.Our results highlight important limitations in current benchmarking approaches and provide insights into more effectively evaluating post-perturbation gene expression prediction models.
CalTrig: A GUI-based Machine Learning Approach for Decoding Neuronal Calcium Transients in Freely Moving Rodents
Authors: Lange Michal A. , Chen Yingying , Fu Haoying , Korada Amith , Guo Changyong , Ma Yao-Ying 
Published: October 2024

ABSTRACTAdvances inin vivoCa2+imaging using miniature microscopes have enabled researchers to study single-neuron activity in freely-moving animals. Tools such as MiniAN and CalmAn have been developed to convertCa2+visual signalsto numerical data, collectively referred to as CalV2N. However, substantial challenges remain in analyzing the large datasets generated by CalV2N, particularly in integrating data streams, evaluating CalV2N output quality, and reliably and efficiently identifying Ca2+transients. In this study, we introduce CalTrig, an open-source graphical user interface (GUI) tool designed to address these challenges at the post-CalV2N stage of data processing. CalTrig integrates multiple data streams, including Ca2+imaging, neuronal footprints, Ca2+traces, and behavioral tracking, and offers capabilities for evaluating the quality of CalV2N outputs. It enables synchronized visualization and efficient Ca2+transient identification. We evaluated four machine learning models (i.e., GRU, LSTM, Transformer, and Local Transformer) for Ca2+transient detection. Our results indicate that the GRU model offers the highest predictability and computational efficiency, achieving stable performance across training sessions, different animals and even among different brain regions. The integration of manual, parameter-based, and machine learning-based detection methods in CalTrig provides flexibility and accuracy for various research applications. The user-friendly interface and low computing demands of CalTrig make it accessible to neuroscientists without programming expertise. We further conclude that CalTrig enables deeper exploration of brain function, supports hypothesis generation about neuronal mechanisms, and opens new avenues for understanding neurological disorders and developing treatments.
Circulatory proteins shape microglia state and boost phagocytosis
Authors: Lu Nannan , Moran-Losada Patricia , Hahn Oliver , Saksena Aryaman , Tapp Emma , Chadarevian Jean Paul , Dong Wentao , Shi Sophia M. , Shuken Steven R. , Guldner Ian , Zeng Wenshu , To Ning-Sum , Wong Pui Shuen , Hasselmann Jonathan , Davtyan Hayk , Sun Jerry , Li Lulin , Luo Jian , Yang Andrew C. , Li Qingyun , Cheung Tom H. , Abu-Remaileh Monther , Blurton-Jones Mathew , Wyss-Coray Tony 
Published: October 2024

SummaryMicroglia, the brain’s immune cells, are highly responsive to their local environment. Given that circulatory proteins can enter the brain, we asked whether microglia are responsive to such proteins. Here, we identify a stable population of microglia specialized to take up circulatory proteins in a region-specific manner under physiological conditions; human hematopoietic stem cell-derived microglia replacing endogenous microglia in chimeric mice show similar regional specialization. Plasma-positive microglia are characterized by prominent expression of genes related to innate immunity and antigen presentation and exhibit high metabolic and phagocytic activity. This activity is dependent, in part, on microglial uptake and accumulation of circulatory Apolipoprotein AI (ApoA-I). Our findings thus identify a new model of communication between brain and periphery through specialized microglia.