bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of motor unit discharges from ultrasound images: Analysis of in silico and in vivo experiments
Authors: Rohlén Robin , Lubel Emma , Farina Dario 
Published: January 2024

AbstractObjectiveUltrasound (US) images during a muscle contraction can be decoded into individual motor unit (MU) activity, i.e., trains of neural discharges from the spinal cord. However, current decoding algorithms assume a stationary mixing matrix, i.e. equal mechanical twitches at each discharge. This study aimed to investigate the accuracy of these approaches in non-ideal conditions when the mechanical twitches in response to neural discharges vary over time and are partially fused in tetanic contractions.MethodsWe performed an in silico experiment to study the decomposition accuracy for changes in simulation parameters, including the twitch waveforms, spatial territories, and motoneuron-driven activity. Then, we explored the consistency of the in silico findings with an in vivo experiment on the tibialis anterior muscle at varying contraction forces.ResultsA large population of MU spike trains across different excitatory drives, and noise levels could be identified. The identified MUs with varying twitch waveforms resulted in varying amplitudes of the estimated sources correlated with the ground truth twitch amplitudes. The identified spike trains had a wide range of firing rates, and the later recruited MUs with larger twitch amplitudes were easier to identify than those with small amplitudes. Finally, the in silico and in vivo results were consistent, and the method could identify MU spike trains in US images at least up to 40% of the maximal voluntary contraction force.ConclusionThe decoding method was accurate irrespective of the varying twitch-like shapes or the degree of twitch fusion, indicating robustness, important for neural interfacing applications.
Identification of CK2α’ selective inhibitors by the screening of an allosteric-kinase-inhibitor-like compound library
Authors: Mudaliar Deepti , Mansky Rachel H. , White Angel , Baudhuin Grace , Hawkinson Jon , Wong Henry , Walters Michael A. , Gomez-Pastor Rocio 
Published: January 2024

AbstractProtein Kinase CK2 is a holoenzyme composed of two regulatory subunits (CK2β) and two catalytic subunits (CK2α and CK2α’). CK2 controls several cellular processes including proliferation, inflammation, and cell death. However, CK2α and CK2α’ possess different expression patterns and substrates and therefore impact each of these processes differently. Elevated CK2α participates in the development of cancer, while increased CK2α’ has been associated with neurodegeneration, especially Huntington’s disease (HD). HD is a fatal disease for which no effective therapies are available. Genetic deletion of CK2α’ in HD mouse models has ameliorated neurodegeneration. Therefore, pharmacological inhibition of CK2α’ presents a promising therapeutic strategy for treating HD. However, current CK2 inhibitors are unable to discriminate between CK2α and CK2α’ due to their high structural homology, especially in the targeted ATP binding site. Using computational analyses, we found a potential Type IV (“D” pocket) allosteric site on CK2α’ that contained different residues than CK2α and was distal from the ATP binding pocket featured in both kinases. With this potential allosteric site in mind, we screened a commercial library containing ∼29,000 allosteric-kinase-inhibitor-like compounds using a CK2α’ activity-dependent ADP-GloTMKinase assay. Obtained hits were counter-screened against CK2α revealing two CK2α’ selective compounds. These two compounds might serve as the basis for further medicinal chemistry optimization for the potential treatment of HD.
The transcriptional and translational landscape of HCoV-OC43 infection
Authors: Bresson Stefan , Sani Emanuela , Armatowska Alicja , Dixon Charles , Tollervey David 
Published: January 2024

ABSTRACTThe coronavirus HCoV-OC43 circulates continuously in the human population and is a frequent cause of the common cold. Here, we generated a high-resolution atlas of the transcriptional and translational landscape of OC43 during a time course following infection of human lung fibroblasts. Using ribosome profiling, we quantified the relative expression of the canonical open reading frames (ORFs) and identified previously unannotated ORFs. These included several short upstream ORFs and a putative ORF nested inside the M gene. In parallel, we analyzed the cellular response to infection. Endoplasmic reticulum (ER) stress response genes were transcriptionally and translationally induced beginning 12 and 18 hours post infection, respectively. By contrast, conventional antiviral genes mostly remained quiescent. At the same time points, we observed accumulation and increased translation of noncoding transcripts normally targeted by nonsense mediated decay (NMD), suggesting NMD is suppressed during the course of infection. This work provides resources for deeper understanding of OC43 gene expression and the cellular responses during infection.
Aggregation ofrecount3RNA-seq data improves inference of consensus and tissue-specific gene co-expression networks
Authors: Ravichandran Prashanthi , Parsana Princy , Keener Rebecca , Hansen Kaspar D. , Battle Alexis 
Published: January 2024

AbstractBackgroundGene co-expression networks (GCNs) describe relationships among expressed genes key to maintaining cellular identity and homeostasis. However, the small sample size of typical RNA-seq experiments which is several orders of magnitude fewer than the number of genes is too low to infer GCNs reliably.recount3, a publicly available dataset comprised of 316,443 uniformly processed human RNA-seq samples, provides an opportunity to improve power for accurate network reconstruction and obtain biological insight from the resulting networks.ResultsWe compared alternate aggregation strategies to identify an optimal workflow for GCN inference by data aggregation and inferred three consensus networks: a universal network, a non-cancer network, and a cancer network in addition to 27 tissue context-specific networks. Central network genes from our consensus networks were enriched for evolutionarily constrained genes and ubiquitous biological pathways, whereas central context-specific network genes included tissue-specific transcription factors and factorization based on the hubs led to clustering of related tissue contexts. We discovered that annotations corresponding to context-specific networks inferred from aggregated data were enriched for trait heritability beyond known functional genomic annotations and were significantly more enriched when we aggregated over a larger number of samples.ConclusionThis study outlines best practices for network GCN inference and evaluation by data aggregation. We recommend estimating and regressing confounders in each data set before aggregation and prioritizing large sample size studies for GCN reconstruction. Increased statistical power in inferring context-specific networks enabled the derivation of variant annotations that were enriched for concordant trait heritability independent of functional genomic annotations that are context-agnostic. While we observed strictly increasing held-out log-likelihood with data aggregation, we noted diminishing marginal improvements. Future directions aimed at alternate methods for estimating confounders and integrating orthogonal information from modalities such as Hi-C and ChIP-seq can further improve GCN inference.
Exploring the Impact of Probiotic Route of Administration on Its Protective Effects against Pathogenic Infection inGalleria mellonella
Authors: Menta Lakshmi Naga Kavya , Law Soffi Kei Kei , Tan Hock Siew 
Published: January 2024

AbstractIn probiotic research, identifying promising candidates for further development remains challenging. Traditional mammalian models are invaluable for assessing efficacy, but limitations such as high cost, ethical considerations, and lengthy reproductive cycles can slow the preliminary screening process. TheGalleria mellonellalarvae have emerged as a powerfulin vivo-like screening model. Most studies onG. mellonellaoften use intra-hemocelic injection, bypassing the natural gut entry point for probiotics, which is analogous to introducing probiotics into the mammalian blood. Despite their advantages, discrepancies exist betweenG. mellonellaand mammalian models, particularly regarding the route of probiotic administration. This study bridges this gap by investigating the differential effects of oral and intra-hemocelic administration of a probiotic,Escherichia coliNissle 1917 (EcN1917), on its protective efficacy against a gastrointestinal pathogen,SalmonellaTyphimurium ATCC 14028 (ST14028). The larvae were challenged with varying doses of EcN1917 and ST14028 through both routes. Survivability, health index, and bacterial burden in the gut and hemolymph were assessed. This study demonstrated that oral EcN1917 pre-treatment significantly increased survivability against ST14028 infection compared to the control group and alleviated the pathogen gut burden. Notably, injection pre-treatment decreased survivability. This discrepancy is attributed to the dual nature of probiotics, exhibiting beneficial effects in the gut but acting as pathogens in non-native locations like the hemolymph. This study concludes that the route of probiotic administration inG. mellonellasignificantly impacts the protective effects of probiotics.
Facilitating clinical trials in Polycythemia vera (PV) by identifying patient cohorts at high near-term risk of thrombosis using rich data and machine learning
Authors: Abu-Zeinah Ghaith , Krichevsky Spencer , Erdos Katie , Silver Richard T. , Scandura Joseph M. 
Published: January 2024

AbstractThrombosis remains the leading cause of morbidity and mortality for patients (pts) with polycythemia vera (PV), yet PV clinical trials are not powered to identify interventions that improve thrombosis-free survival (TFS). Such trials are infeasible in a contemporary PV cohort, even when selecting “high-risk” pts based on Age >60 and thrombosis history, because thousands of patients would be required for a short-term study to meet TFS endpoint. To address this problem, we used artificial intelligence and machine learning (ML) to dynamically predict near-term (1-year) thrombosis risk in PV pts with high sensitivity and positive predictive value (PPV) to enhance pts selection. Our automation-driven data extraction methods yielded more than 16 million data elements across 1,448 unique variables (parameters) from 11,123 clinical visits for 470 pts. Using the AutoGluon framework, the Random Forest ML classification algorithm was selected as the top performer. The full (309-parameter) model performed very well (F1=0.91, AUC=0.84) when compared with the current ELN gold-standard for thrombosis risk stratification in PV (F1=0.1, AUC=0.39). Parameter engineering, guided by Gini feature importance identified the 21 parameters (top-21) most important for accurate prediction. The top-21 parameters included known, suspected and previously unappreciated thrombosis risk factors. To identify the minimum number of parameters required for the accurate ML prediction, we tested the performance of every possible combination of 3-9 parameters from top-21 (>1.6M combinations). High-performing models (F1> 0.8) most frequently included age (continuous), time since dx, time since thrombosis, complete blood count parameters, blood type, body mass index, and JAK2 mutant allele frequency. Having trained at tested over 1.6M practical ML models with a feasible number of parameters (3-9 parameters in top-21 most predictive), it is clear that study cohorts of patients with PV at high near-term thrombosis risk can be identified with high enough sensitivity and PPV to power a clinical trial for TFS. Further validation with external, multicenter cohorts is ongoing to establish a universal ML model for PV thrombosis that would facilitate clinical trials aimed at improving TFS.
Plasma proteomic associates of infection mortality in UK Biobank
Authors: Drozd Michael , Hamilton Fergus , Cheng Chew W , Lillie Patrick J , Brown Oliver I , Chaddock Natalie , Savic Sinisa , Naseem Khalid , Iles Mark M , Morgan Ann W , Kearney Mark T , Cubbon Richard M 
Published: January 2024

AbstractBackgroundInfectious diseases are a major cause of mortality in spite of existing public health, anti-microbial and vaccine interventions. We aimed to define plasma proteomic associates of infection mortality and then apply Mendelian randomisation (MR) to yield biomarkers that may be causally associated.MethodsWe used UK Biobank plasma proteomic data to associate 2,923 plasma proteins with infection mortality before 31stDecember 2019 (240 events in 52,520 participants). Since many plasma proteins also predict non-infection mortality, we focussed on those associated with >1.5-fold risk of infection mortality in an analysis excluding survivors. Protein quantitative trait scores (pQTS) were then used to identify whether genetically predicted protein levels also associated with infection mortality. To conduct Two Sample MR, we performed a genome-wide association study (GWAS) of infection mortality using UK Biobank participants without plasma proteomic data (n=363,953 including 984 infection deaths).FindingsAfter adjusting for clinical risk factors, 1,142 plasma proteins were associated with risk of infection mortality (false discovery rate <0.05). 259 proteins were associated with >1.5-fold increased risk of infection versus non-infection mortality. Of these, we identified genetically predicted increasing MERTK concentration was associated with increased risk of infection mortality. GWAS for infection mortality revealed no SNPs achieving genome-wide statistical significance (p<5×10-8). However, MR supported a causal association between increasing plasma MERTK protein and infection mortality (odds ratio 1.46 per unit; 95% CI 1.15-1.85; p=0.002).InterpretationPlasma proteomics demonstrates many proteins are associated with infection mortality. MERTK warrants exploration as a potential therapeutic target.
Diagnosis in children with prolonged or recurrent cough: findings from the Swiss Paediatric Airway Cohort
Authors: Mallet Maria Christina , Elmiger Annina , Glick Sarah , Krasnova Tayisiya , de Jong Carmen CM , Kern Barbara , Moeller Alexander , Regamey Nicolas , Sutter Oliver , Usemann Jakob ,   SPAC Study Team, Pedersen Eva SL , Kuehni Claudia E 
Published: January 2024

AbstractIntroductionProlonged or recurrent cough is a common reason for referral to pediatric pulmonologists, yet few studies have assessed its causes. We examined records of children visiting respiratory outpatient clinics in Switzerland and assessed how diagnoses vary by age.MethodsWe analyzed data from the multicenter Swiss Paediatric Airway Cohort study. We included 363 children (median age 6 years, range 0–16) referred for prolonged or recurrent cough. From outpatient records, we extracted information on diagnostic investigations, final diagnoses proposed by pediatric pulmonologists, and treatments prescribed.ResultsAsthma and asthma-like conditions (cough variant asthma, episodic viral wheeze, and recurrent obstructive bronchitis) was diagnosed in 132 (36%) of 363 children, respiratory tract infections (RTI) including protracted bacterial bronchitis (PBB) in 51 (14%), upper airway cough syndrome (UACS) in 48 (13%), postinfectious cough in 36 (10%); other diagnoses including gastroesophageal reflux disease (GERD) and somatic cough syndrome or tic cough were found in 23 (6%). No etiology was found in 73 children (20%). Asthma was diagnosed 3.5 times more often in schoolchildren while RTI including PBB was diagnosed 3 times more often in preschoolers. Inhaled corticosteroids were prescribed for 84% of children diagnosed with asthma and asthma-like conditions, antibiotics for 43% of children with RTI, and nasal corticosteroids for 83% of those with UACS.ConclusionCoughing children received a wide spectrum of diagnoses that differed between preschool and schoolchildren. Asthma accounted for 36% of diagnoses, which emphasizes the importance of comprehensive investigation beyond asthma in children with prolonged or recurrent cough.
Constraints on the Emergence of RNA through Non-Templated Primer Extension with Mixtures of Potentially Prebiotic Nucleotides
Authors: Jia Xiwen , Zhang Stephanie J. , Zhou Lijun , Szostak Jack W. 
Published: January 2024

ABSTRACTThe emergence of RNA on the early Earth is likely to have been influenced by a series of chemical and physical processes that acted to filter out various alternative nucleic acids. For example, UV photostability is thought to have favored the survival of the canonical nucleotides. In a recent proposal for the prebiotic synthesis of the building blocks of RNA, ribonucleotides share a common pathway with arabino- and threo-nucleotides. We have therefore investigated non-templated primer extension with 2-aminoimidazole-activated forms of these alternative nucleotides to see if the synthesis of the first oligonucleotides might have been biased in favor of RNA. We show that non-templated primer extension occurs predominantly through 5ʹ-5ʹ imidazolium bridged dinucleotides, echoing the mechanism of template-directed primer extension. Ribo- and arabino-nucleotides exhibited comparable rates and yields of non-templated primer extension, whereas threo-nucleotides showed lower reactivity. Competition experiments with mixtures of nucleotides confirmed the bias against the incorporation of threo-nucleotides into oligonucleotides. This bias, coupled with selective prebiotic synthesis and templated copying favoring ribonucleotides, provides a plausible model for the exclusion of threo-nucleotides from primordial oligonucleotides. In contrast, the exclusion of arabino-nucleotides may have resulted primarily from biases in synthesis and in template-directed primer extension.
MagIC-Cryo-EM: Structural determination on magnetic beads for scarce macromolecules in heterogeneous samples
Authors: Arimura Yasuhiro , Konishi Hide A. , Funabiki Hironori 
Published: January 2024

SummaryCryo-EM single-particle analyses typically require target macromolecule concentration at 0.05∼5.0 mg/ml, which is often difficult to achieve. Here, we deviseMagnetic Isolation andConcentration (MagIC)-cryo-EM, a technique enabling direct structural analysis of targets captured on magnetic beads, thereby reducing the targets’ concentration requirement to < 0.0005 mg/ml. Adapting MagIC-cryo-EM to a Chromatin Immunoprecipitation protocol, we characterized structural variations of the linker histone H1.8-associated nucleosomes that were isolated from interphase and metaphase chromosomes inXenopusegg extract. CombiningDuplicatedSelectionToExcludeRubbish particles (DuSTER), a particle curation method that excludes low signal-to-noise ratio particles, we also resolved the 3D cryo-EM structures of nucleoplasmin NPM2 co-isolated with the linker histone H1.8 and revealed distinct open and closed structural variants. Our study demonstrates the utility of MagIC-cryo-EM for structural analysis of scarce macromolecules in heterogeneous samples and provides structural insights into the cell cycle-regulation of H1.8 association to nucleosomes.
Cryo-EM structure of a blue-shifted channelrhodopsin fromKlebsormidium nitens
Authors: Wang Yuzhu Z. , Natsume Koki , Tanaka Tatsuki , Hososhima Shoko , Tashiro Rintaro , Sano Fumiya K. , Akasaka Hiroaki , Tsunoda Satoshi P. , Shihoya Wataru , Kandori Hideki , Nureki Osamu 
Published: January 2024

AbstractChannelrhodopsins (ChRs) are light-gated ion channels and invaluable tools for optogenetic applications. Recent developments in multicolor optogenetics, in which different neurons are controlled by multiple colors of light simultaneously, have increased the demand for ChR mutants with more distant absorption wavelengths. Here we report the 2.9 Å-resolution cryo-electron microscopy structure of a ChR fromKlebsormidium nitens(KnChR), which is one of the most blue-shifted ChRs. The structure elucidates the 6-s-cisconfiguration of the retinal chromophore, indicating its contribution to a distinctive blue shift in action spectra. The unique architecture of the C-terminal region reveals its role in the allosteric modulation of channel kinetics, enhancing our understanding of its functional dynamics. Based on the structure-guided design, we developed mutants with blue-shifted action spectra. Finally, we confirm that UV or deep-blue light can activate KnChR-transfected precultured neurons, expanding its utility in optogenetic applications. Our findings contribute valuable insights to advance optogenetic tools and enable refined capabilities in neuroscience experiments.
Early release of the expanded atlas of the sky in continuous gravitational waves
Authors: Dergachev Vladimir , Papa Maria Alessandra 
Published: January 2024

We present the early release of the atlas of continuous gravitational waves covering frequencies from 20 Hz to 1500 Hz and spindowns from −5×10−10 to 5×10−10  Hz/s. Compared to the previous atlas release we have greatly expanded the parameter space, and we now also provide polarization-specific data—both for signal-to-noise ratios and for the upper limits. Continuous wave searches are computationally difficult and take a long time to complete. The atlas enables new searches to be performed using modest computing power. To allow new searches to start sooner, we are releasing this data early, before our followup stages have completed.

Published by the American Physical Society
2024
Trade-offs between precision and fluctuations in charging finite-dimensional quantum batteries
Authors: Bakhshinezhad Pharnam , Jablonski Beniamin R. , Binder Felix C. , Friis Nicolai 
Published: January 2024

Within quantum thermodynamics, many tasks are modeled by processes that require work sources represented by out-of-equilibrium quantum systems, often dubbed quantum batteries, in which work can be deposited or from which work can be extracted. Here we consider quantum batteries modeled as finite-dimensional quantum systems initially in thermal equilibrium that are charged via cyclic Hamiltonian processes. We present optimal or near-optimal protocols for N identical two-level systems and individual d-level systems with equally spaced energy gaps in terms of the charging precision and work fluctuations during the charging process. We analyze the trade-off between these figures of merit as well as the performance of local and global operations.

Published by the American Physical Society
2024