bluuebunny/crossref_metadata_2025_split huggingface dataset:
XBB.1.5 Spike Protein COVID-19 Vaccine Induces Broadly Neutralizing and Cellular Immune Responses Against EG.5.1 and Emerging XBB Variants
Authors: Patel Nita , Trost Jessica F. , Guebre-Xabier Mimi , Zhou Haixia , Norton Jim , Jiang Desheng , Cai Zhaohui , Zhu Mingzhu , Marchese Anthony M. , Greene Ann M. , Mallory Raburn M. , Kalkeri Raj , Dubovsky Filip , Smith Gale 
Published: September 2023

AbstractMonovalent SARS-CoV-2 Prototype (Wuhan-Hu-1) and bivalent (Prototype + BA.4/5) COVID-19 vaccines have demonstrated a waning of vaccine-mediated immunity highlighted by lower neutralizing antibody responses against SARS-CoV-2 Omicron XBB sub-variants. The reduction of humoral immunity due to the rapid evolution of SARS-CoV-2 has signaled the need for an update to vaccine composition. A strain change for all authorized/approved vaccines to a monovalent composition with Omicron subvariant XBB.1.5 has been supported by the WHO, EMA, and FDA. Here, we demonstrate that immunization with a monovalent recombinant spike protein COVID-19 vaccine (Novavax, Inc.) based on the subvariant XBB.1.5 induces cross-neutralizing antibodies against XBB.1.5, XBB.1.16, XBB.2.3, EG.5.1, and XBB.1.16.6 subvariants, promotes higher pseudovirus neutralizing antibody titers than bivalent (Prototype + XBB.1.5) vaccine, induces SARS-CoV-2 spike-specific Th1-biased CD4+ T-cell responses against XBB subvariants, and robustly boosts antibody responses in mice and nonhuman primates primed with a variety of monovalent and bivalent vaccines. Together, these data support updating the Novavax vaccine to a monovalent XBB.1.5 formulation for the 2023-2024 COVID-19 vaccination campaign.
Online Bayesian Optimization of Nerve Stimulation
Authors: Wernisch Lorenz , Edwards Tristan , Berthon Antonin , Tessier-Lariviere Olivier , Sarkans Elvijs , Stoukidi Myrta , Fortier-Poisson Pascal , Pinkney Max , Thornton Michael , Hanley Catherine , Lee Susannah , Jennings Joel , Appleton Ben , Garsed Phillip , Patterson Bret , Buttinger Will , Gonshaw Samuel , Jakopec Matjaž , Shunmugam Sudhakaran , Mamen Jorin , Tukiainen Aleksi , Lajoie Guillaume , Armitage Oliver , Hewage Emil 
Published: September 2023

AbstractObjectiveIn bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs modifying their function. Stimulation devices, capable of triggering exogenous neural signals using electrical wave forms, require a complex and multi-dimensional parameter space in order to control such wave forms. Determining the best combination of parameters (wave form optimization, or dosing) for treating a particular patient’s illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting, due to the size of the parameter space. Restricting this space, however, may lead to sub-optimal therapeutic results, reduced responder rates, and adverse effects.ApproachAs an alternative to a full parameter search, we present a flexible machine learning, data acquisition and processing framework for optimizing neural stimulation parameters requiring as few steps as possible using Bayesian optimization. Such optimization builds a model of the neural and physiological responses to stimulations enabling it to optimize stimulation parameters and to provide estimates of the accuracy of the response model. The vagus nerve innervates, among other thoracic and visceral organs, the heart, thus controlling heart rate and is therefore ideal for demonstrating the effectiveness of our approach.Main results.The efficacy of our optimization approach was first evaluated on simulated neural responses, then applied to vagus nerve stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target heart rates and optimizing neural B-fibre activations despite high intersubject variability.SignificanceAn optimized stimulation waveform was achieved in real time with far fewer stimulations than required by alternative optimization strategies, thus minimizing exposure to side effects. Uncertainty estimates helped avoiding stimulations outside a safe range. Our approach shows that a complex set of neural stimulation parameters can be optimized in real-time for a patient to achieve a personalized precision dosing.
Regulating Cell Orientation with a Femtosecond Laser-Induced Macro Stripe Design on Metallic Culture Surfaces
Authors: Imashiro Chikahiro , Ezura Atsushi , Yamada Takahiro G. , Akiyama Yoshikatsu , Komotori Jun 
Published: September 2023

AbstractControlling cell orientation is paramount in bioengineering processes. While several surface modification techniques have emerged to guide cell alignment, they often involve complex, repetitive procedures for each experiment. A streamlined approach for cell orientation is thus necessary. In this study, we present a reusable metallic culture surface that induces an anisotropic cell orientation, attributed to its unique geometric morphology. By employing a femtosecond laser, periodic nanostructures were produced on the metallic culture surface, leading to a distinctive macro-stripe design composed of both laser-treated and mirrored areas. Myoblast cells cultured on this surface displayed a pronounced orientation. Initial random cell adherence was followed by migration towards the mirror surface, culminating in the desired orientation. This shift can be credited to the mirrored sections offering superior cell adhesion and reduced wettability compared to the laser-treated sections. This innovative culture surface holds significant potential for advancing bioengineering endeavors, especially in the realm of tissue engineering.
All-optical reporting of inhibitory receptor driving force in the nervous system
Authors: Selfe Joshua S. , Steyn Teresa J. S. , Shorer Eran F. , Burman Richard J. , Düsterwald Kira M. , Abdelfattah Ahmed S. , Schreiter Eric R. , Newey Sarah E. , Akerman Colin J. , Raimondo Joseph V. 
Published: September 2023

AbstractIonic driving forces provide the net electromotive force for ion movement across receptors, channels, and transporters, and are a fundamental property of all cells. In the brain for example, fast synaptic inhibition is mediated by chloride permeable GABAA receptors, and single-cell intracellular recordings have been the only method for estimating driving forces across these receptors (DFGABAA). Here we present a new tool for quantifying inhibitory receptor driving force named ORCHID: all-Optical Reporting of CHloride Ion Driving force. We demonstrate ORCHID’s ability to provide accurate, high-throughput measurements of resting and dynamic DFGABAA from genetically targeted cell types over multiple timescales. ORCHID confirms theoretical predictions about the biophysical mechanisms that establish DFGABAA, reveals novel differences in DFGABAA between neurons and astrocytes, and affords the firstin vivomeasurements of intact DFGABAA. This work extends our understanding of inhibitory synaptic transmission and establishes a precedent for all-optical methods to assess ionic driving forces.
Growth/differentiation factor 15 controls primary cilia morphology in the murine ventricular-subventricular zone thereby affecting progenitor proliferation
Authors: Baur Katja , Şan Şeydanur , Hölzl-Wenig Gabriele , Mandl Claudia , Hellwig Andrea , Ciccolini Francesca 
Published: September 2023

AbstractGrowth/differentiation factor 15 (GDF15) and its receptor GDNF Family Receptor Alpha-Like (GFRAL) are expressed from embryonic development onwards in the germinal epithelium of the ganglionic eminence (GE), regulating proliferation and number of apical progenitors. However, the mechanisms underlying this regulation are not yet clear. We here show that GDF15 exerts this regulation by affecting ciliary signalling. Not only was GFRAL localized to primary cilia but, constitutive GDF15 ablation also led to shorter and thicker primary cilia. Lack of GDF15 affected the expression of histone deacetylase 6 (HDAC6) and ciliary adenylate cyclase 3 (ADCY3), thereby modifying acetylation of microtubules and endogenous Sonic Hedgehog (SHH) activation in neural progenitors. Application of exogenous GDF15 or pharmacological antagonism of HDAC6 or ADCY3 all increased cilia length and rescued proliferation and SHH signalling in mutant but not WT progenitors. Notably, HDAC6 expression and cilia length were changed only in the GE, were ciliary GFRAL localization was observed. In contrast, GFRAL was absent from primary cilia of hippocampal progenitors where GDF15 affected ADCY3 and SHH signalling, but not HDAC6 expression or cilia morphology. We conclude that ciliary GDF15 signalling regulates HDAC6 thereby affecting primary cilia elongation and proliferation in apical progenitors.
How antisense transcripts can evolve to encode novel proteins
Authors: Iyengar Bharat Ravi , Grandchamp Anna , Bornberg-Bauer Erich 
Published: September 2023

AbstractProtein coding features can emergede novoin non coding transcripts, resulting in emer- gence of new protein coding genes. Studies across many species show that a large frac- tion large fraction of evolutionarily novel non-coding RNAs have an antisense overlap with protein coding genes. The open reading frames (ORFs) in these antisense RNAs could also overlap with existing ORFs. In this study, we investigate how the evolution an ORF could be constrained by its overlap with an existing ORF in three different read- ing frames. Using a combination of mathematical modeling and genome/transcriptome data analysis in two different model organisms, we show that antisense overlap can increase the likelihood of ORF emergence and reduce the likelihood of ORF loss, es- pecially in one of the three reading frames. In addition to rationalising the repeatedly reported prevalence ofde novoemerged genes in antisense transcripts, our work also provides a generic modeling and an analytical framework that can be used to under- stand evolution of antisense genes.
Role of NUMTs (Nuclear mitochondrial DNA) genes in affecting disease resistance in duck against Pasteurellosis
Authors: Sahu Jyoti , Pal Aruna , Chakraborty Argha , Banerjee Samiddha , Debnath Manti , Samanta Rajarshi 
Published: September 2023

AbstractDucks are mostly resistant to common avian diseases, but frequent occurrence of duck pasteurellosis, commonly kown as Duck Cholera, caused byPasteurella multocidamay cause a loss. In our earlier studies, we have identified certain immune response genes of nuclear origin as well as mitochondrial genes in duck, conferring resistance against duck cholera. In our current study, we have detected certain NUMT (Nuclear mitochondrial) genes in duck with certain role in disease resistance in case of duck cholera. NUMT genes are basically nuclear genes, but they act through mitochondria. Identified NUMT genes (Thymidine phosphorylase/ endothelial cell growth factor1 gene, TFAM Transcription factor A, mitochondrial, TK2 Thymidine kinase 2) were characterized and certain important domains were identified. Differential mRNA expression profiling revealed upregulation of the genes in healthy ducks compared to that of infected ducks. Exploitation of the identified genes may lead to development of ducks resistant to duck Cholera.
Machine learning general transcriptional predictors of plant disease
Authors: Sia Jayson , Zhang Wei , Cheng Mingxi , Bogdan Paul , Cook David E. 
Published: September 2023

AbstractPlants utilize an innate immune system to defend against all classes of microbial invaders. While we understand specific genetic determinants of host-pathogen interactions, it remains less clear how generalized the immune response is to diverse pathogens. Using a data-driven approach, and utilizing feature selection based on network science and topology, we developed machine learning models that could predict host disease development across diverse pathosystems. These machine learning models identified early transcriptional responses predictive of later disease development, regardless of pathogen class, using a fraction of the host transcriptome. The identified gene sets were not enriched for canonical defense genes, but where statistically enriched for genes previously identified from independent data sets, including those described as representing a general plant stress response. These results highlight novel components of a general plant immune response, and demonstrate the application of machine learning to address biological hypotheses of a complex multigenic outcome.TeaserA machine learning approach can predict plant disease development caused by diverse microbial invaders, and newly identified genes may represent novel components of a general plant response to infection.
SenePy: Unveiling the Cell-Type Specific Landscape of Cellular Senescence through Single-Cell Analysis in Living Organisms
Authors: Sanborn Mark A. , Wang Xinge , Gao Shang , Dai Yang , Rehman Jalees 
Published: September 2023

ABSTRACTSenescent cells accumulate in tissues with organismal age and contribute causally to multiple chronic diseases.In vivosenescent cell phenotypes are heterogeneous because cellular context and stressors vary by cell type and tissue. Due to the variability of senescence programs, there is no universal method to identify senescent cells and even widely used markers, such asCDKN2A, are not ubiquitous. Therefore, we interrogated theTabula Muris Senismouse single-cell aging atlas and an array of single-cell datasets from human donors that spanned many ages to find cell-specific signatures of cellular senescence. We derived 75 mouse and 65 human senescence signatures from individual cell populations.CDKN2Aand other markers of senescence were overrepresented in these signatures but there were many novel senescence genes present at higher rates. Within individual cell populations, we observed multiple programs of senescence with distinct temporal and transcriptional characteristics. We packaged the signatures along with a single-cell scoring method into an open-source package:SenePy. SenePysignatures better recapitulate cellular senescence than available methods when tested on multiplein vivoRNA-seq datasets and a p16ink4areporter single-cell dataset. We usedSenePyto map the kinetics of senescent cell accumulation across 97 cell types from humans and mice.SenePyalso generalizes to disease-associate senescence and we used it to identify an increased burden of senescent cells in COVID-19 and myocardial infarction. This work provides a significant advancement towards our ability to identify and characterizein vivocellular senescence.
Genomic Epidemiologic Investigation of a Multispecies Hospital Outbreak of NDM-5-Producing Enterobacterales Infections
Authors: Raabe Nathan J. , Valek Abby L. , Griffith Marissa P. , Mills Emma , Waggle Kady , Srinivasa Vatsala Rangachar , Ayres Ashley M. , Bradford Claire , Creager Hannah , Pless Lora L. , Sundermann Alexander J. , Tyne Daria Van , Snyder Graham M. , Harrison Lee H. 
Published: September 2023

ABSTRACTBackgroundNew Delhi metallo-β-lactamase (NDM) represents an emergent mechanism of carbapenem resistance associated with high mortality and limited antimicrobial treatment options. Because theblaNDMresistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods like speciation, antimicrobial resistance testing, and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks.MethodsInitial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance, which was performed weekly using the Illumina platform. To resolve NDM-encoding plasmids, we performed long-read Oxford Nanopore sequencing and constructed hybrid assemblies using Illumina and Nanopore sequencing data. Reports of relatedness between NDM-producing organisms and reactive WGS for suspected outbreaks were shared with the IP&C team for assessment and intervention.FindingsWe observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included seven bacterial species and each encoded the same NDM-5 plasmid, which showed high homology to NDM plasmids previously observed in Asia. WGS surveillance and epidemiologic investigation characterized ten horizontal plasmid transfer events and six bacterial transmission events between patients housed in varying hospital units. Transmission prevention focused on enhanced observation and adherence to basic infection prevention measures.InterpretationOur investigation revealed a complex, multispecies outbreak of NDM that involved multiple plasmid transfer and bacterial transmission events, increasing the complexity of outbreak identification and transmission prevention. Our investigation highlights the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks.FundingThis work was funded in part by the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH) (R01AI127472) (R21AI1783691).5.SummaryWe investigated a multispecies outbreak of Enterobacterales harboring the same New-Delhi metallo-β-lactamase-encoding plasmid using both traditional infection prevention and genomic approaches. Our investigation revealed a complex outbreak involving 7 bacterial species, including both bacterial transmission and plasmid transfer events.
Patterns of Crimean-Congo haemorrhagic fever virus seroprevalence in human and livestock populations in northern Tanzania
Authors: Hughes Ellen C , de Glanville William , Kibona Tito , Mmbaga Blandina Theophil , Rostal Melinda K , Swai Emanuel , Cleaveland Sarah , Lankester Felix , Willett Brian J , Allan Kathryn J 
Published: September 2023

AbstractResults from a cross-sectional study of Crimean-Congo haemorrhagic fever virus (CCHFV) in northern Tanzania demonstrated high seroprevalence in humans and ruminant livestock with high levels of spatial heterogeneity. CCHFV may represent an unrecognised human health risk in this region and drivers of exposure need further investigation.
Systematic review of genome wide association studies (GWAS) of epilepsy identifies common risk variants and associated genes
Authors: Jacobs S. , Wootton O. , Ives-Deliperi V , Tucker L.M , Stein D.J , Dalvie S. 
Published: September 2023

AbstractBackgroundEpilepsy is one of the most prevalent neurological disorders, affecting 50 million individuals worldwide. The aetiology of epilepsy is known to have genetic contributions, yet headline results obtained from genome-wide association studies (GWAS) of epilepsy have not always been consistent. We undertook a systematic review of all the findings from this work in order to identify risk variants for epilepsy.MethodsThis systematic review was conducted in accordance with the updated PRISMA protocol. EbscoHost, PubMed, Scopus, Web of Science and Primo were searched between the years 2010 – 2024. The quality of each of the studies was evaluated using the Q-Genie tool.Results11 studies were included for full extraction, analysis, and quality assessment. Across the identified studies, 79 SNPs, located in 64 genes, were significantly associated with epilepsy at the genome-wide level. The majority of the variants were intronic and intergenic, with the well documentedSCN1Athe most widely reported gene involved across studies. Two SNPs, rs2292096 and rs149212747, linked respectively to focal epilepsy (FE) and status epilepticus, were exclusively identified in individuals of Asian ancestry, alongside an Asian-exclusive synonymous variant (rs3782886) inBRAPand a missense variant (rs671) inALDH2.ConclusionsGenes which encode for ion and transport channels, transcription factors, ubiquitin ligase and transporter proteins were identified as potentially involved in the aetiology of epilepsy disorders. The review identified one missense and one synonymous variant which deserve further exploration. Future research should also include populations of more diverse ancestries as this may reveal unique and important epilepsy-associated genes.
Impact of health systems interventions in primary health settings on type 2 diabetes care and health outcomes among adults in West Africa: a systematic review protocol
Authors: Bondzie Eugene Paa Kofi , Jahan Yasmin , Balabanova Dina , Danso-Appiah Tony , Mirzoev Tolib , Antwi Edward , Ayepong Irene 
Published: September 2023

AbstractType 2 diabetes remains a major global public health challenge particularly in the African region. Though evidence exists on pharmacological agents and non-pharmacological interventions in maintaining blood glucose concentration, the health systems ability in meeting patients’ needs may be inadequate. However, the management of non-communicable diseases particularly diabetes, have been postulated to depend largely on functioning health systems. This systematic review will therefore, summarize the current evidence on existing health systems interventions in primary health settings for type 2 diabetes care and health outcomes in West Africa and would explore the impact of these system-level interventions on service availability, accessibility and quality, as well as individualized outcomes such as glycemic control, disease awareness and treatment adherence.The review will be conducted in accordance with the reporting guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). The health system framework by Witter et al, 2019 will guide the system-level interventions and the search strategy to be explored in this review. This framework was designed to integrate the six building blocks of the World health’s organization (WHO) health systems framework and delineates how they work synergistically to improve specific health outcomes. We will search the following databases PubMed, Google scholar and Cumulated Index to Nursing and Allied Health Literature (CINAHL) between January 2000 to June 2023 and Car.info from inception to June 2023. The Cochrane Collaboration tool for assessing Risk of Bias will be implemented on each included study to assess for risk of bias.We will conduct a narrative synthesis and make comparisons across findings using Excel generated tables.The main limitation of this study is that we are likely to miss out on studies not conducted in English or French since our search would be conducted in English and French only.In Conclusion,this systematic review will outline the existing system-level interventions that aim to or already improve type 2 diabetes services in primary health facilities in West Africa and would allow for strengthening and co-production of successful interventions that can be generalized to the entire sub-region.
Efficient Edge-AI Models for Robust ECG Abnormality Detection on Resource-Constrained Hardware
Authors: Huang Zhaojing , Herbozo Contreras Luis Fernando , Leung Wing Hang , Yu Leping , Truong Nhan Duy , Nikpour Armin , Kavehei Omid 
Published: September 2023

AbstractThis study introduces two models, CLTC and CCfC, designed for abnormality identification using ECG data. Trained on the TNMG subset dataset, both models were evaluated for their performance, generative capacity, and resilience. They demonstrated comparable results in terms of F1 scores and AUROC values. The CCfC model achieved slightly higher accuracy, while the CLTC model showed better handling of empty channels. Remarkably, the models were successfully deployed on a resource-constrained microcontroller, proving their suitability for edge device applications. Generalization capabilities were confirmed through the evaluation of the CPSC dataset. The models’ efficient resource utilization, occupying 70.6% of total storage and 9.4% of flash memory, makes them promising candidates for real-world healthcare applications. Overall, this research advances abnormality identification in ECG data, contributing to the progress of AI in healthcare.