bluuebunny/crossref_metadata_2025_split huggingface dataset:
Density Spectral Array EEG for Sleep Staging in Pediatric Patients
Authors: Rudock Robert J. , Turner Ashley D. , Binkley Michael , Landre Rebekah , Morrissey Michael J. , Tomko Stuart R. , Guerriero Réjean M. 
Published: October 2024

Purpose:
Sleep is an essential physiologic process, which is frequently disrupted in children with illness and/or injury. Accurate identification and quantification of sleep may provide insights to improve long-term clinical outcomes. Traditionally, however, the identification of sleep stages has relied on the resource-intensive and time-consuming gold standard polysomnogram. We sought to use limited EEG data, converted into density spectrum array EEG, to accurately identify sleep stages in a clinical pediatric population.

Methods:
We reviewed 87 clinically indicated pediatric polysomnographic studies with concurrent full montage EEG, between March 2017 and June 2020, of which 11 had normal polysomnogram and EEG interpretations. We then converted the EEG data of those normal studies into density spectral array EEG trends and had five blinded raters classify sleep stage (wakefulness, nonrapid eye movement [NREM] 1, NREM 2, NREM 3, and rapid eye movement) in 5-minute epochs. We compared the classified sleep stages from density spectral array EEG to the gold standard polysomnogram.

Results:
Inter-rater reliability was highest (κ = 0.745, P < 0.0001) when classifying state into wakefulness, NREM sleep, and rapid eye movement sleep. Agreement between group classification and polysomnogram was highest (κ = 0.873, [0.819, 0.926], P < 0.0001) when state was classified into wakefulness and sleep and was lowest (κ = 0.674 [0.645, 0.703], P < 0.0001) when classified into wakefulness, NREM 1, NREM 2, NREM 3, and rapid eye movement. The most common error that raters made was overscoring of NREM 1.

Conclusions:
Density spectral array EEG can be used to identify sleep stages in clinical pediatric patients without relying on traditional polysomnography.
Targeting Neuropilin-1 to Enhance Immunotherapy in Melanoma: Reducing Peripheral Treg-Mediated Immunosuppression and Tumour Progression
Authors: Khamaru Somlata , Tung Kshyama Subhadarsini , Chattopadhyay Subhasis 
Published: October 2024

AbstractMelanoma, the most aggressive type of skin cancer with a high mutation rate, is the fifth most common cancer among Caucasians. Despite advancements in treatments like immune checkpoint inhibitors and targeted therapies, over 40% of patients experience immune-related side effects, presenting significant challenges. Neuropilin-1 (NRP1) has become an essential target in cancer therapy due to its overexpression in various cancers, where it enhances regulatory T cell (Treg) function and supports tumor growth, often leading to poor outcomes.This study investigated the effects of NRP1 inhibition in B16-F10 melanoma and its impact on immune responses regulated by Tregs. NRP1 was overexpressed in several cancers, including B16-F10 cells, compared to non-cancerous NIH-3T3 cells. Inhibiting NRP1 selectively caused apoptosis in B16-F10 cells without affecting NIH-3T3 cells. It also reversed the immunosuppression of splenic T cells induced by B16-F10-conditioned media, reducing Treg markers (NRP1, NKG2A, FOXP3), Treg activity, and the production of immunosuppressive cytokines (IL-10, IL-17A). Furthermore, NRP1 inhibition increased T cell proliferation and boosted the release of effector cytokines (TNF, IFN-γ, IL-6, IL-2). NRP1 inhibition also suppressed the STAT, ERK MAPK, and Smad2/3 pathways while activating the PI3K/AKT pathway. In splenic T cells from B16-F10 tumor-bearing mice treated with an NRP1 inhibitor, there was a decrease in Treg markers and activity, along with enhanced T cell proliferation. Additionally, NRP1 inhibitor treatment reduced lung metastasis, decreased tumor size, and improved survival in these mice.This study shows that inhibiting NRP1 may slow B16-F10 melanoma progression and reduce Treg-mediated immunosuppression. This suggests its potential as a promising approach in future cancer immunotherapies, especially in combination with other treatments.
Unwrapping the ciliary coat: high-resolution structure and function of the ciliary glycocalyx
Authors: Hoepfner Lara M. , Nievergelt Adrian P. , Matrino Fabrizio , Scholz Martin , Foster Helen E. , Rodenfels Jonathan , von Appen Alexander , Hippler Michael , Pigino Gaia 
Published: October 2024

AbstractThe glycocalyx, a highly heterogeneous glycoprotein layer of cilia regulates adhesion and force transduction, and is involved in signalling. The high-resolution molecular architecture of this layer is currently not understood. We describe the structure of the ciliary coat in the green algaChlamydomonas reinhardtiiby cryo-electron tomography and proteomic approaches and present the high-resolution cryoEM structure of the main component, FMG1B. We describe FMG1B as a mucin orthologue which lacks the majorO-glycosylation of mammalian mucins, but isN-glycosylated. FMG1A, a previously undescribed isoform of FMG1B is expressed inC. reinhardtii. By microflow-based adhesion assays we observe increased surface adhesion in the glycocalyx deficient double-mutantfmg1a-fmg1b. We find this mutant to be capable of surface-gliding, with neither isoform required for extracellular force transduction by intraflagellar transport. Our results find FMG1 to form a protective layer with adhesion-regulative instead of adhesion-conferring properties and an example of an undescribed class of mucins.
Association between SARS-CoV-2 and Stroke: Perspectives from a metaumbrella-review
Authors: Baldo de Souza Andreza Maria Luzia , de Araújo Enoque Fernandes , Carvas Nelson , Raimundo Augusto César , Pereira Antonio Carlos , de Castro Meneghim Marcelo 
Published: October 2024

AbstractIn the face of the global COVID-19 pandemic, the need arose to investigate potential complications associated with SARS-CoV-2, including the risk of Stroke.ObjectiveThis study aimed to verify the association between SARS-CoV-2 and the risk of Stroke, based on systematic reviews and meta-analyses, in order to assess the inclusion of the virus as a new risk factor for cerebrovascular diseases.MethodsA metaumbrella was conducted, which included 34 systematic reviews, of which 4 were selected for the final analysis based on methodological quality and consistency. The analysis aggregated the results of 70 primary studies, considering different stroke subtypes and outcomes associated with COVID-19. Study heterogeneity was assessed using the I² index, and significance bias was verified using Egger’s test.ResultsThe analysis showed that the severity of COVID-19 is significantly associated with an increased risk of stroke (eOR = 2.48; 95%CI: 1.55 – 3.95), particularly for ischemic stroke (eOR = 1.76; 95%CI: 1.11 – 2.80) and hemorrhagic stroke (eOR = 3.86; 95%CI: 1.79 – 8.33). Additionally, patients with cerebrovascular comorbidities had higher mortality (eOR = 2.48; 95%CI: 2.48 – 19.63), as did those who had previously suffered a stroke (eOR = 6.08; 95%CI: 3.73 – 9.91).ConclusionThe association between SARS-CoV-2 and stroke was consistent and significant, suggesting that COVID-19 should be considered a new risk factor for cerebrovascular diseases. However, the high heterogeneity among the studies analyzed reinforces the need for further research to consolidate this relationship.
Causal links between mitophagy and Alzheimer’s disease: a Mendelian randomization study
Authors: Zhang Weijian , Chen Wenjia , Guo Zhendong , Li Hui 
Published: October 2024

BackgroundEmerging evidence highlights the dysregulation of mitophagy, the process of clearing damaged mitochondria, as a potential contributor to Alzheimer’s disease (AD) pathology. However, the precise mechanisms linking mitophagy to AD remain poorly understood. This study utilized summary-data-based Mendelian Randomization (SMR) combined with multi-omics data to explore the causal relationships between them, and to uncover potential epigenetic mechanisms of gene regulation.MethodsMitophagy-related genes were identified through the integration of three databases, and transcriptomic data of AD patients were obtained from the Gene Expression Omnibus (GEO) database. A meta-analysis was conducted to recognize differentially expressed genes (DEGs) associated with mitophagy in AD. Through SMR tools, genome-wide association study (GWAS) summary data of AD from the GWAS Catalog (n=487,511) were separately integrated with expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) from blood and brain tissues to identify potentially causal genes and methylation sites. The findings from primary analysis were validated with data from the UK Biobank (n=301,478).ResultsIn total, 111 mitophagy-related genes were found to be differentially expressed in AD. The three-step SMR analysis identified two genes, PARL and BCL2L1, from blood tissues and three genes, ATG13, TOMM22, and SPATA33, from brain tissues as causal candidate genes associated with AD. The analysis pinpointed the possible epigenetic mechanisms, where specific methylation sites regulate the expression of these genes, potentially contributing to their association with AD. All findings were successfully replicated in UK Biobank cohorts.ConclusionsThe study emphasized the putatively causal relationships of mitophagy-related gene with AD. These underlying pathogenic mechanisms could pave the way for new approaches in early detection and therapeutic intervention for AD.
Soft X-ray tomography reveals variations inB.subtilisbiofilm structure upontasAdeletion
Authors: Chatzimpinou Anthoula , Diehl Anne , Harhoff A. Tobias , Driller Kristina , Vanslembrouck Bieke , Chen Jian-Hua , Kairiss Kristaps , Loconte Valentina , Le Gros Mark A , Larabell Carolyn , Turgay Kürşad , Oschkinat Hartmut , Weinhardt Venera 
Published: October 2024

AbstractBacterial biofilms are complex communities of cells within a self-produced extracellular matrix. They play crucial roles in healthcare, nutrition, agriculture and environmental research, yet an analysis of their elaborate 3D architecture remains challenging. Understanding mechanisms of biofilm formation, particularly the effects of chemical, physical, and genetic influences or modifications, is crucial but requires structural information at subcellular resolution to enable a community-level analysis of biofilms. In this work, we developed a “biofilm-in-capillary” growth method compatible with full-rotation soft X-ray tomography, providing high-resolution 3D imaging of bacterial cells and their surrounding extracellular matrix during biofilm formation, without drying or fixation steps. This approach offers 50 nm isotropic spatial resolution, rapid imaging time, and quantitative native analysis of biofilm structure. We demonstrate the potential of our method usingBacillus subtilisbiofilms, detecting coherent alignment and chaining of wild-type cells while they are travelling towards the oxygen-rich capillary tip region. In stark contrast, the genetic knock-out ΔtasAshows a loss of cellular orientation, including changes in the extracellular matrix in volume and chemical density. Notably, we show that the addition of TasA protein to a culture of a ΔtasAstrain restores the extracellular matrix density and leads to a compaction of cell assemblies, yet no chaining is observed as for the wildtype. Our approach to imaging biofilms is scalable and transferable, opening new avenues for examining biofilm structure and function across various species, including mixed biofilms, and observing 3D reorganization in response to genetic and environmental factors.
Partially Shared Multi-Modal Embedding Learns Holistic Representation of Cell State
Authors: Zhang Xinyi , Shivashankar GV , Uhler Caroline 
Published: October 2024

AbstractExperimental technologies for jointly measuring different data modalities at the single-cell level offer different windows into cell state. To obtain a holistic understanding of cell state, computational methods are needed that carefully integrate the different views to capture shared information as well as tease apart modality-specific information. We present a computational framework that automatically learns partial information sharing between multiple modalities by using anAutoencoder with aPartiallyOverlappingLatent space learned throughLatentOptimization (APOLLO). On paired scRNA-seq and scATAC-seq data (SHARE-seq) and paired scRNA-seq and surface protein data (CITE-seq), we demonstrate that APOLLO comprehensively and automatically identifies and distinguishes between information captured by both modalities, in the shared latent space, and modality-specific information. Beyond sequencing modalities, large-scale multiplexed single-cell imaging datasets, such as the Human Protein Atlas, are becoming available that allow studying how protein localization relates to function. While chromatin, microtubules or ER are standardly stained as a reference, little is known about the information shared between these stains. We found that APOLLO enables the prediction of missing modalities, such as unmeasured protein stains, and allows disentangling which modality or cellular compartment is linked with a specific phenotype, such as the variability in protein localization observed across single cells. Collectively, APOLLO enables explicit learning of shared and modality-specific information leading to a more holistic understanding of cell state and the underlying regulatory mechanisms. APOLLO is a general framework that can be applied to any multi-modal data well beyond the single-cell domain including, for example, large-scale medical biobanks.
ADrosophilascreen of schizophrenia-related genes highlights the requirement of neural and glial matrix metalloproteinases for neuronal remodeling
Authors: Keret Shir , Meltzer Hagar , Marmor-Kollet Neta , Schuldiner Oren 
Published: October 2024

AbstractSchizophrenia (SCZ) is a multifactorial neuropsychiatric disorder of complex and mostly unknown etiology, affected by genetic, developmental and environmental factors. Neuroanatomical abnormalities, such as loss of grey matter, are apparent prior to the onset of symptoms, suggesting neurodevelopmental origin. Indeed, it has been hypothesized, and recently experimentally supported, that SCZ is associated with dysregulation of developmental synaptic pruning. Here, we explore the molecular link between SCZ-associated genes and developmental neuronal remodeling, focusing on theDrosophilamushroom body (MB), which undergoes stereotypic remodeling during metamorphosis. We conducted a loss-of-function screen in which we knocked downDrosophilahomologs of human genes that genomic studies have associated with SCZ. Out of our ‘positive hits’, we focused on matrix metalloproteinases (MMPs), mostly known for their role in remodeling of the extracellular matrix. We found that both Mmp1 and Mmp2, which are closely-related to mammalian MMPs, are required in neurons and in glia for the pruning of MB axons. Our combinatorial loss-of-function experiments suggest that Mmp2 secretion from glia is the most important promoter of axon pruning. Our results shed new light on potential molecular players underlying neurodevelopmental defects in SCZ and highlight the advantage of genetically tractable model organisms in the study of human neurodevelopmental disorders.
LINE-1 ribonucleoprotein complexes bind DNA to enable nuclear entry during mitosis
Authors: Zernia Sarah , Ettefa Farida , Sil Srinjoy , Koeman Cas , Deplazes-Lauber Joëlle , Freitag Marvin , Holt Liam J. , Stigler Johannes 
Published: October 2024

SummaryLong Interspersed Nuclear Element-1 (LINE-1) is an autonomous retrotransposon that makes up a significant portion of the human genome, contributing to genetic diversity and genome evolution. LINE-1 encodes two proteins, ORF1p and ORF2p, both essential for successful retrotransposition. ORF2p has endonuclease and reverse transcription activity, while ORF1p binds RNA. Many copies of ORF1p assemble onto the LINE-1 RNA to form a ribonucleoprotein complex (RNP). However, the functional role of RNPs in the LINE-1 life cycle is unclear. Using reconstitution assays on DNA curtains, we show that L1 RNPs gain DNA binding activity only when RNA is super-saturated with ORF1p. In cells, L1 RNPs bind to chromosomes during mitosis. Mutational analysis reveals that DNA binding is crucial for nuclear entry and LINE-1 retrotransposition activity. Thus, a key function of ORF1p is to form an RNP that gains access to the genome through DNA binding upon nuclear envelope breakdown.
Advancing Noninvasive Mechanical Ventilation: Simulating Techniques for Improved Respiratory Care
Authors: Tahmid Md Toki , Bappa Mrinmoy Nandi 
Published: October 2024

AbstractRespiratory failure is a critical condition that often requires mechanical ventilation to support or restore normal breathing. While invasive mechanical ventilation (IMV) is commonly used for severe cases, noninvasive mechanical ventilation (NIMV) offers a less intrusive alternative that reduces complications and can be applied in moderate cases. The COVID-19 pandemic highlighted the global shortage of ventilators, particularly in low- and middle-income countries (LMICs), where limited access to life-saving equipment exacerbated the crisis. In response to these challenges, this paper presents a simplified, compartmental-based simulation model for NIMV. This model provides a practical and accessible tool for simulating respiratory system behavior under various ventilation modes, using the analogy between electrical circuits and lung physiology. By simulating key parameters such as airway resistance and lung compliance, the model allows clinicians and researchers to evaluate ventilator performance and optimize treatment strategies. Furthermore, the simulation offers a blueprint for developing cost-effective, easy-to-use NIMV systems that can be deployed in resource-constrained environments. Our contribution seeks to address the ventilator shortage by enabling better design and understanding of noninvasive ventilation, ultimately improving respiratory care for patients with moderate respiratory failure.
The Specification Game: Rethinking the Evaluation of Drug Response Prediction for Precision Oncology
Authors: Codicè Francesco , Pancotti Corrado , Rollo Cesare , Moreau Yves , Fariselli Piero , Raimondi Daniele 
Published: October 2024

AbstractPrecision oncology plays a pivotal role in contemporary healthcare, aiming to optimize treatments for each patient based on their unique characteristics. This objective has spurred the emergence of various cancer cell line drug-response datasets, driven by the need to facilitate pre-clinical studies by exploring the impact of multi-omics data on drug response. Despite the proliferation of machine learning models for Drug Response Prediction (DRP), their validation remains critical to reliably assess their usefulness for drug discovery, precision oncology and their actual ability togeneralizeover the immense space of cancer cells and chemical compounds.This paper shows that the commonly used evaluation strategies for DRP methods learn solutions that optimize an unintended DRP score and fail to predict the proper drug-response activity (”specification gaming”). This problem hinders the advancement of the DRP field, and here we propose a new validation paradigm composed by three Aggregation Strategies (Global, Fixed-Drug, and Fixed-Cell Line) and three train-test Splitting Strategies to ensure a realistic assessment of the prediction performance. We also scrutinize the challenges associated with using IC50 as a prediction label, showing how its close correlation with the drug concentration ranges worsens the risk of misleading performance assessment. We thus propose also an alternative prediction label for DRP which is safer from this perspective.
Competitive exclusion, experience-based learning, and human fishing, influence activity patterns in Juvenile and Adult Brown Pelicans (Pelecanus occidentalis)
Authors: Plazas-Cardona Dennys , Ríos-Orjuela Juan Camilo , Wilches-Vega Juan D. 
Published: October 2024

AbstractThe activity patterns of young and adult individuals offer insights into exclusion and adaptation dynamics in seabirds. Juveniles often show differences in their daily behaviors compared to adults, especially in activities like feeding. We focus in two contrasting hypotheses to explain the age-related differences in activity patterns of Brown Pelicans (Pelecanus occidentalis): the “competitive exclusion” hypothesis and the “experience-based adaptation” hypothesis. The competitive exclusion hypothesis posits that adult pelicans, with superior foraging skills, actively exclude juveniles from prime feeding areas, leading to temporal segregation. In contrast, the experience-based adaptation hypothesis suggests that juveniles exhibit different activity patterns as they undergo a learning process, gradually improving their foraging efficiency through trial and error. Using continuous focal sampling, we analyzed the activity peaks of both juveniles and adults, revealing significant temporal segregation between age groups. Additionally, the impact of human fishing activity on pelican behavior was assessed, showing alterations in natural foraging patterns. These findings contribute to the understanding of resource use and competition dynamics in seabirds and highlight the importance of considering both biological and anthropogenic factors when analyzing seabird behavior.
CellEKT: A robust chemical proteomics workflow to profile cellular target engagement of kinase inhibitors
Authors: Rüegger Joel , Gagestein Berend , Janssen Antonius P. A. , Valeanu Alexandra , Mori Alger Lazo , van der Peet Marielle , Boutkan Michael S. , Florea Bogdan I. , Henneman Alex A. , Hochstrasser Remo , Wang Haiyan , Westwood Paul , Topp Andreas , Gomez Barila Patricia M. , Medema Jan Paul , Jimenez Connie R. , Woersdoerfer Bigna , Kirchner Stephan , Zhang Jitao David , Grether Uwe , Rufer Arne C. , van der Stelt Mario 
Published: October 2024

SummaryThe human genome encodes 518 protein kinases that are pivotal for drug discovery in various therapeutic areas such as cancer and autoimmune disorders. The majority of kinase inhibitors target the conserved ATP-binding pocket, making it difficult to develop selective inhibitors. To characterize and prioritize kinase-inhibiting drug candidates, efficient methods are desired to determine target engagement across the cellular kinome. In this study, we present CellEKT (Cellular Endogenous Kinase Targeting), an optimized and robust chemical proteomics platform for investigating cellular target engagement of endogenously expressed kinases using the sulfonyl fluoride-based probe XO44 and two new probesALX005andALX011. The optimized workflow enabled the determination of the kinome interaction landscape of covalent and non-covalent drugs across over 300 kinases, expressed as half maximum inhibitory concentration (IC50), which were validated using distinct platforms like phosphoproteomics and NanoBRET. With CellEKT, target engagement profiles were linked to their substrate space. CellEKT has the ability to decrypt drug actions and to guide the discovery and development of drugs.Graphical abstract