bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recovery of complete genomes of canine parvovirus from clinical samples
Authors: de Araújo dos Santos Sara França , de Souza Ueric José Borges , Oliveira Martha Trindade , Jaime Jairo , Spilki Fernando Rosado , Franco Ana Cláudia , Roehe Paulo Michel , Campos Fabrício Souza 
Published: July 2023

AbstractCanine parvovirus (CPV) is a highly pathogenic virus that affects dogs, especially puppies. CPV is believed to have evolved from feline panleukopenia virus (FPV), eventually giving rise to three antigenic types, CPV-2a, 2b, and 2c. CPV-2 is recognized for its resilience in contaminated environments, ease of transmission among dogs, and pathogenicity for puppies. Despite the relevance of the virus, complete genome sequences of CPV available at GenBank, to date, are scarce. In the current study, we have developed a methodology to allow the recovery of complete CPV-2 genomes directly from clinical samples. For this, seven fecal samples from Gurupi, Tocantins, North Brazil, were collected from puppies with clinical signals of viral enteritis, and submitted to viral DNA isolation and amplification. Two multiplex PCR strategies were designed including primers targeting fragments of 400 base pairs (bp) and 1,000 bp along the complete genome. Sequencing was performed with the Nanopore®technology and results obtained with the two approaches were compared. Genome assembly revealed that the 400 bp amplicons generated larger numbers of reads, allowing a more reliable coverage of the whole genome than those attained with primers targeting the larger (1000 bp) amplicons. Nevertheless, both enrichment methodologies were efficient in amplification and sequencing. Viral genome sequences were of high quality and allowed more precise typing and subtyping of viral genomes compared to the commonly employed strategy relying solely on the analysis of the VP2 region, which is limited in scope. The CPV-2 genomes recovered in this study belong to the CPV2a and CPV-2c subtypes, closely related to isolates from the neighboring Amazonian region. In conclusion, the technique reported here may contribute to increase the number of full CPV genomes available, which is essential for understanding the genetic mechanisms underlying the evolution and spread of CPV-2.
Genomic signatures of strawberry domestication and breeding
Authors: Fan Zhen , Whitaker Vance M. 
Published: July 2023

AbstractCultivated strawberry (Fragaria × ananassa) has a brief history of less than 300 years, beginning with the hybridization of octoploidsF. chiloensisand F.virginiana. Here we explored the genomic signatures of this history using whole-genome sequences of 289 wild, heirloom and modern varieties. Four non-admixed wild octoploid populations were identified, with recurrent introgression among the sympatric populations. The proportion ofF. virginianaancestry increased by 20% in modern varieties over initial hybrids, and the proportion ofF. chiloensissubsp. pacifica rose from 0 to 3.4%. Effective population size rapidly declined during early breeding. Meanwhile, divergent selection for distinct environments reshaped wild allelic origins in 21 out 28 chromosomes. Despite 20 breeding cycles since the initial hybridization, more than half of loci underlying yield and fruit size are still not under selection. These insights add clarity to the domestication and breeding history of what is now the most widely cultivated fruit in the world.
Estimating person-specific neural correlates of mental rotation: A machine learning approach
Authors: Uslu Sinan , Tangermann Michael , Vögele Claus 
Published: July 2023

AbstractUsing neurophysiological measures to model how the brain performs complex cognitive tasks such as mental rotation is a promising way towards precise predictions of behavioural responses. The mental rotation task has frequently been used to monitor progressive neurological disorders. Up until now, research on neural correlates of mental rotation have largely focused on group analyses yielding models with features common across individuals. Here, we propose an individually tailored machine learning approach to identify person-specific patterns of neural activity during mental rotation. We trained ridge regressions to predict the reaction time of correct responses in a mental rotation task using task-related, non-invasive electrocortical activity of the same person. When tested on independent data of the same person, the regression model predicted the reaction times significantly more accurately than when only the average reaction time was used for prediction (bootstrap mean difference of 0.02, 95% CI: 0.01–0.03, p < .001). When tested on another person’s data, the predictions were significantly less accurate compared to within-person predictions. Further analyses revealed that considering person-specific reaction times and topographical activity patterns substantially improved a model’s generalizability. Our results indicate that a more individualized approach towards neural correlates can improve their predictive performance of behavioural responses, particularly when combined with machine learning.
Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments
Authors: Kulikov Nikita , Derakhshandeh Fatemeh , Mayer Christoph 
Published: July 2023

AbstractPhylogenetic tree reconstruction with molecular data is important in many fields of life science research. The gold standard in this discipline is the phylogenetic tree reconstruction based on the Maximum Likelihood method. In this study, we explored the utility of neural networks to predict the correct model of sequence evolution and the correct topology for four sequence alignments. We trained neural networks with different architectures using simulated nucleotide and amino acid sequence alignments for a wide range of evolutionary models, model parameters and branch lengths. By comparing the accuracy of model and topology prediction of the trained neural networks with Maximum Likelihood and Neighbour Joining methods, we show that for quartet trees, the neural network classifier outperforms the Neighbour Joining method and is in most cases as good as the Maximum Likelihood method to infer the best model of sequence evolution and the best tree topology. These results are consistent for nucleotide and amino acid sequence data. Furthermore, we found that neural network classifiers are much faster than the IQ-Tree implementation of the Maximum Likelihood method. Our results show that neural networks could become a true competitor for the Maximum Likelihood method in phylogenetic reconstructions.
Increased Karyopherin Alpha Levels Attenuate Mutant Ataxin-1-Induced Neurodegeneration
Authors: Ruff Elena K , Timperman Dylan Lawrence , Amador Adulfo Anaya , Aguirre-Lamus Isabella , de Haro Maria , Al-Ramahi Ismael 
Published: July 2023

AbstractNeurodegenerative diseases are characterized by the abnormal accumulation of disease-driving proteins. Emerging evidence suggests that nucleocytoplasmic transport (NCT) components play a critical role in neurodegeneration. This study investigates the impact of modulating Karyopherin alpha (KPNA) levels on neurodegeneration induced by mutant Ataxin-1 (ATXN1) using aDrosophilamodel of Spinocerebellar Ataxia Type 1 (SCA1). Our findings reveal that ATXN1 (82Q) interacts with KPNAs in the nucleus and cytoplasm of neurons. Increasing KPNA levels alleviates ATXN1 (82Q)-induced neurodegeneration and progressive neuronal dysfunction. Surprisingly, mechanistic analyses demonstrate that elevated KPNA levels retain mutant ATXN1 in the cytoplasm, reducing its nuclear accumulation in theDrosophilacentral nervous system. Moreover, elevated KPNA levels lead to a decrease in soluble oligomeric ATXN1. These results indicate that KPNAs may act as chaperones for mutant ATXN1, preventing its nuclear translocation and reducing its pathological effects. Importantly, they also constitute a proof of principle that retaining mutant ATXN1 in the cytoplasm represents an attractive and viable therapeutic option. Given the dysregulation of Karyopherins in many neurodegenerative diseases and their emerging role as chaperones, the results presented here may extend beyond SCA1 into other disorders like Alzheimer’s or Parkinson’s disease.
TheEscherichia colichromosome moves to the replisome
Authors: Gras Konrad , Fange David , Elf Johan 
Published: July 2023

AbstractThe replisome, a large multi-subunit assembly, carries out the process of chromosome replication, connecting the unwrapping of the parental DNA with the creation of new daughter strands. InEscherichia coli, it is debated whether the two replisomes move independently along the two chromosome arms during replication or if they remain in close proximity, with the DNA being pulled toward the replisomes as replication progresses. Here, we use fluorescence microscopy to determine the location and diffusivity of the replisome and various chromosomal loci throughout the cell cycle of the model organismE. coli. We find that (i) the two replisomes are confined to a region of 250 nm and 120 nm along the cell long and short axis respectively, and the chromosomal loci move through this region sequentially based on distance from the origin of replication. (ii) When a locus is being replicated, its diffusivity slows down. (iii) There is no indication that replication initiation occurs close to the cell membrane as has been proposed in a few previous studies. In conclusion, our data supports a model with DNA moving towards stationary replisomes at replication.
Environmental Surface Monitoring as a Noninvasive Method for SARS-CoV-2 Surveillance in Community Settings: Lessons from a University Campus Study
Authors: Ali Sobur , Cella Eleonora , Johnston Catherine , Deichen Michael , Azarian Taj 
Published: July 2023

AbstractEnvironmental testing of high-touch objects is a potential noninvasive approach for monitoring population-level trends of SARS-CoV-2 and other respiratory viruses within a defined setting. We aimed to determine the association between SARS-CoV-2 contamination on high-touch environmental surfaces, community level case incidence, and university student health data. Environmental swabs were collected from January 2022 to November 2022 from high-touch objects and surfaces from five locations on a large university campus in Florida, USA. RT-qPCR was used to detect and quantify viral RNA, and a subset of positive samples was analyzed by viral genome sequencing to identify circulating lineages. During the study period, we detected SARS-CoV-2 viral RNA on 90.7% of 162 tested samples. Levels of environmental viral RNA correlated with trends in community-level activity and case reports from the student health center. A significant positive correlation was observed between the estimated viral gene copy number in environmental samples and the weekly confirmed cases at the university. Viral sequencing data from environmental samples identified lineages contemporaneously circulating in the local community and state based on genomic surveillance data. Further, we detected emerging variants in environmental samples prior to their identification by clinical genomic surveillance. Our results demonstrate the utility of viral monitoring on high-touch environmental surfaces for SARS-CoV-2 surveillance at a community level. In communities with delayed or limited testing facilities, immediate environmental surface testing may considerably inform epidemic dynamics.Graphical Abstract
Booster dose of self-amplifying SARS-CoV-2 RNA vaccine vs. mRNA vaccine: a phase 3 comparison of ARCT-154 with Comirnaty®
Authors: Oda Yoshiaki , Kumagai Yuji , Kanai Manabu , Iwama Yasuhiro , Okura Iori , Minamida Takeshi , Yagi Yukihiro , Kurosawa Toru , Greener Benjamin , Zhang Ye , Walson Judd L. 
Published: July 2023

SUMMARYBackgroundLicensed mRNA vaccines demonstrated initial effectiveness against COVID-19 but require booster doses to broaden the anti-SARS-CoV-2 response. There is an unmet need for novel highly immunogenic and broadly protective vaccines. We compared immunogenicity and tolerability of ARCT-154, a novel self-amplifying mRNA vaccine with the mRNA vaccine, Comirnaty®.MethodsWe compared immune responses to ARCT-154 and Comirnaty booster doses in healthy 18– 77-year-old Japanese adults initially immunised with two doses of mRNA COVID-19 vaccine (Comirnaty or Spikevax®) then a third dose of Comirnaty at least 3 months previously. Neutralising antibodies were measured before and 28 days after booster vaccination. The primary objective was to demonstrate non-inferiority of the immune response against Wuhan-Hu-1 SARS-CoV-2 virus as geometric mean titre (GMT) ratios and seroresponse rates (SRR) of neutralising antibodies; key secondary endpoints included the immune response against the Omicron BA.4/5 variant and vaccine tolerability assessed using participant-completed electronic diaries.FindingsBetween December 13, 2022 and February 25, 2023 we enrolled 828 participants randomised 1:1 to receive ARCT-154 (n = 420) or Comirnaty (n = 408) booster doses. Four weeks after boosting, ARCT-154 induced higher Wuhan-Hu-1 neutralising antibodies GMTs than Comirnaty (5641 [95% CI: 4321, 7363] and 3934 [2993, 5169], respectively), a GMT ratio of 1·43 (95% CI: 1·26–1·63), with SRR of 65·2% (60·2–69·9) and 51·6% (46·4–56·8) meeting the non-inferiority criteria. Respective anti-Omicron BA.4/5 GMTs were 2551 (1687–3859) and 1958 (1281–2993), a GMT ratio of 1·30 (95% CI: 1·07–1·58), with SRR of 69·9% (65·0–74·4) and 58·0% (52·8–63·1), meeting the superiority criteria for ARCT-154 over Comirnaty. Booster doses of either ARCT-154 or Comirnaty were equally well-tolerated with no causally-associated severe or serious adverse events; 94·8% and 96·8% of ARCT-154 and Comirnaty vaccinees reported local reactions and 65·7% and 62·5% had solicited systemic adverse events. Events were mainly mild in severity, occurring and resolving within 3–4 days of vaccination.InterpretationImmune responses four weeks after an ARCT-154 booster dose in mRNA-immunised adults were higher than after a Comirnaty booster, meeting non-inferiority criteria against the prototype Wuhan-Hu-1 virus, and superiority criteria against the Omicron BA.4/5 variant.FundingThe study was funded by the Japanese Ministry of Health, Labour, and Welfare following a public invitation to bid for an urgent improvement project for vaccine manufacturing systems, fourth invitation, Grant number: 1212-3.Clinical Trials registration and identifierThe study was registered on the Japan Registry for Clinical Trials (jRCT 2071220080).
On the limitations of large language models in clinical diagnosis
Authors: Reese Justin T , Danis Daniel , Caufield J Harry , Groza Tudor , Casiraghi Elena , Valentini Giorgio , Mungall Christopher J , Robinson Peter N 
Published: July 2023

AbstractObjectiveLarge Language Models such as GPT-4 previously have been applied to differential diagnostic challenges based on published case reports. Published case reports have a sophisticated narrative style that is not readily available from typical electronic health records (EHR). Furthermore, even if such a narrative were available in EHRs, privacy requirements would preclude sending it outside the hospital firewall. We therefore tested a method for parsing clinical texts to extract ontology terms and programmatically generating prompts that by design are free of protected health information.Materials and MethodsWe investigated different methods to prepare prompts from 75 recently published case reports. We transformed the original narratives by extracting structured terms representing phenotypic abnormalities, comorbidities, treatments, and laboratory tests and creating prompts programmatically.ResultsPerformance of all of these approaches was modest, with the correct diagnosis ranked first in only 5.3-17.6% of cases. The performance of the prompts created from structured data was substantially worse than that of the original narrative texts, even if additional information was added following manual review of term extraction. Moreover, different versions of GPT-4 demonstrated substantially different performance on this task.DiscussionThe sensitivity of the performance to the form of the prompt and the instability of results over two GPT-4 versions represent important current limitations to the use of GPT-4 to support diagnosis in real-life clinical settings.ConclusionResearch is needed to identify the best methods for creating prompts from typically available clinical data to support differential diagnostics.
Automated Pipeline for Comparing Protein Conformational States in the PDB to AlphaFold2 Predictions
Authors: Ellaway Joseph I. J. , Anyango Stephen , Nair Sreenath , Zaki Hossam A. , Nadzirin Nurul , Powell Harold R. , Gutmanas Aleksandras , Varadi Mihaly , Velankar Sameer 
Published: July 2023

AbstractProteins, as molecular machines, are necessarily dynamic macromolecules that carry out essential cellular functions. Recognising their stable conformations is important for understanding the molecular mechanisms of disease. While AI-based computational methods have enabled protein structure prediction, the prediction of protein dynamics remains a challenge. Here, we present a deterministic pipeline that clusters experimentally determined protein structures to comprehensively recognise conformational states across the Protein Data Bank. Our approach clusters protein chains based on a GLObal CONformation (GLOCON) difference score, which is computed from pairwise C-alpha distances. By superposing the clustered structures, differences and similarities in conformational states can be observed. Additionally, we offer users the ability to superpose predicted models from the AlphaFold Database to the clusters of PDB structures. This clustering pipeline significantly advances researchers’ ability to explore the conformational landscape within the PDB. All clustered and superposed models can be viewed in Mol* on the PDBe Knowledge Base website, or accessed in as raw annotations via our GraphAPI and FTP server. The clustering package is made available as an open-source Python3 package under the Apache-2.0 license.
The Endogenous Opioid Met-Enkephalin Modulates Thalamo-Cortical Excitation Inhibition Balance in a Medial Thalamus-Anterior Cingulate Cortex Circuit
Authors: Arias Hervert Erwin , Birdsong William 
Published: July 2023

ABSTRACTActivation of opioid receptors in the anterior cingulate cortex (ACC) mediates aspects of analgesia induced by both exogenous and endogenous opioids. We have previously shown that opioid signaling disrupts both afferent excitatory and indirect inhibitory synaptic transmission from the medial thalamus (MThal) to the ACC, but the effects of endogenous opioids within this circuit remain poorly understood. The goal of the current study was to understand how the endogenous opioid, [Met]5-enkephalin (ME), modulates thalamic-driven excitatory and inhibitory synaptic transmission onto layer V pyramidal neurons in the ACC. We used pharmacology, brain slice electrophysiology and optogenetic stimulation to study opioid-mediated modulation of optically evoked glutamatergic and GABAergic transmission. The results revealed that ME inhibited both AMPA-mediated excitatory and GABA-mediated inhibitory synaptic transmission in the ACC. However, inhibitory transmission was more potently inhibited than excitatory transmission by ME. This preferential reduction in GABAA-mediated synaptic transmission was primarily due to the activation of delta opioid receptors by ME and resulted in a net disinhibition of MThal-ACC excitatory pathway. These results suggest that moderate concentrations of ME can lead to net excitation of ACC circuitry and that analgesia may be associated with disinhibition rather than inhibition of ACC subcircuits.
A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2
Authors: Terbot John W , Cooper Brandon S. , Good Jeffrey M. , Jensen Jeffrey D. 
Published: July 2023

AbstractThe global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs.Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.Significance StatementDespite its tremendous impact on human health, a comprehensive evolutionary baseline model has yet to be developed for studying the within-host population genomics of SARS-CoV-2. Importantly, such modeling would enable improved analysis and provide insights into the key evolutionary dynamics governing SARS-CoV-2 evolution. Given this need, we have here quantified a set of plausible baseline models via large-scale simulation. The commonly shared features of these relevant models - including severe infection bottlenecks, low levels of progeny skew, and a high rate of strongly deleterious mutations - lay the foundation for sophisticated analyses of SARS-CoV-2 evolution within patients using these baseline models.
LactoSpanks: a collection of IPTG inducible promoters for the commensal lactic acid bacteriaLactobacillus gasseri
Authors: Fristot Elsa , Cambray Guillaume , Bonnet Jerome 
Published: July 2023

ABSTRACTLactic acid bacteria (LAB) are important for many biotechnological applications, such as bioproduction and engineered probiotics for therapy. Inducible promoters are key gene expression control elements, yet those available in LAB are mainly based on bacteriocin systems and have many drawbacks, including large gene clusters, costly inducer peptides and little portability toin vivosettings. UsingLactobacillus gasseri, a model commensal bacteria from the human gut, we report the engineering of Lactospanks promoters (Pls), a collection of variable strength inducible promoters controlled by theLacIrepressor fromB. subtilisand induced by isopropyl β-D-1-thiogalactopyranoside (IPTG). We first show that the Phyper-spank promoter fromBacillus subtilisis functional inL. gasseri, albeit with substantial leakage. We then construct and screen a semi-rational library of Phyper-spank variants to select a set of four IPTG-inducible promoters that span a range of expression levels and exhibit reduced leakages and operational dynamic ranges (from ca. 9 to 28 fold-change). With their low genetic footprint and simplicity of use, Lactospanks will support many applications inL. gasseri, and potentially other lactic acid and gram-positive bacteria.