bluuebunny/crossref_metadata_2025_split huggingface dataset:
A laboratory framework for ongoing optimisation of amplification based genomic surveillance programs
Authors: Lam Connie , Johnson-Mackinnon Jessica , Basile Kerri , Fong Winkie , Suster Carl J.E. , Gall Mailie , Agius Jessica , Chandra Shona , Draper Jenny , Martinez Elena , Drew Alexander , Wang Qinning , Chen Sharon C , Kok Jen , Dwyer Dominic E , Sintchenko Vitali , Rockett Rebecca J. 
Published: July 2023

ABSTRACTConstantly evolving viral populations affect the specificity of primers and quality of genomic surveillance. This study presents a framework for continuous optimisation of sequencing efficiency for public health surveillance based on the ongoing evolution of the COVID-19 pandemic. SARS-CoV-2 genomic clustering capacity based on three amplification based whole genome sequencing schemes was assessed using decreasing thresholds of genome coverage and measured against epidemiologically linked cases. Overall genome coverage depth and individual amplicon depth were used to calculate an amplification efficiency metric. Significant loss of genome coverage over time was documented which was recovered by optimisation of primer pooling or implementation of new primer sets. A minimum of 95% genome coverage was required to cluster 94% of epidemiologically defined SARS-CoV-2 transmission events. Clustering resolution fell to 70% when only 85% of genome coverage was achieved. The framework presented in this study can provide public health genomic surveillance programs a systematic process to ensure an agile and effective laboratory response during rapidly evolving viral outbreaks.
Deep mutational scanning of whole SARS-CoV-2 spike in an inverted infection system
Authors: Taminishi Shunta , Li Songling , Higuchi Yusuke , Kirita Yuhei , Motooka Daisuke , Ozaki Yuki , Arimori Takao , Ikemura Nariko , Itoh Yumi , Matoba Satoaki , Okamoto Toru , Takagi Junichi , Standley Daron M , Hoshino Atsushi 
Published: July 2023

SummaryIn order to investigate SARS-CoV-2 mutations and their impact on immune evasion and infectivity, we developed a Deep Mutational Scanning (DMS) platform utilizing an inverted infection assay to measure spike expression, ACE2 affinity, and viral infectivity in human cells. Surprisingly, our analysis reveals that spike protein expression, rather than ACE2 affinity, is the primary factor affecting viral infectivity and correlated with SARS-CoV-2 evolution. Notably, within the N-terminal domain (NTD), spike expression and infectivity-enhancing mutations are concentrated in flexible loops. We also observed that Omicron variants BA.1 and BA.2 exhibit immune evasion through receptor binding domain (RBD) mutations, although these mutations reduce structural stability. Interestingly, the NTD has evolved to increase stability, compensating for the RBD instability and resulting in heightened overall infectivity. Our findings, available in SpikeScanDB, emphasize the importance of spike expression levels and compensatory mutations in both the NTD and RBD domains for shaping Omicron variant infectivity.
Assessing generalizability of a dengue classifier across multiple datasets
Authors: Lu Bingqian , Li Yanni , Evans Ciaran 
Published: July 2023

AbstractEarly diagnosis of dengue fever is important for individual treatment and monitoring disease prevalence in the population. To assist diagnosis, previous studies have proposed classification models to detect dengue from symptoms and clinical measurements. However, there has been little exploration of whether existing models can be used to make predictions for new populations. We trained logistic regression models on five publicly available dengue datasets from previous studies, using three explanatory variables identified as important in prior work: age, white blood cell count, and platelet count. These five datasets were collected at different times in different locations, with a variety of disease rates and patient ages. A model was trained on each dataset, and predictive performance and model calibration was evaluated on both the original (training) dataset, and the other (test) datasets from different studies. We further compared performance with larger models and other classification methods. In-sample area under the receiver operating characteristic curve (AUC) values for the logistic regression models ranged from 0.74 to 0.89, while out-of-sample AUCs ranged from 0.55 to 0.89. Matching age ranges in training/test datasets increased AUC values and balanced the sensitivity and specificity. Adjusting the predicted probabilities to account for differences in dengue prevalence improved calibration in 20/28 training-test pairs. Results were similar when other explanatory variables were included and when other classification methods (decision trees and support vector machines) were used. The in-sample performance of the logistic regression model was consistent with previous dengue classifiers, suggesting the chosen model is a good choice in a variety of settings and has decent overall performance. However, adjustments are required to make predictions on new datasets. Practitioners can use existing dengue classifiers in new settings but should be careful with different patient ages and disease rates.
Is biomedical research self-correcting? Modeling insights on the persistence of spurious science
Authors: Grimes David Robert 
Published: July 2023

ABSTRACTThe reality that volumes of published research are not reproducible has been increasingly recognised in recent years, notably in biomedical science. In many fields, spurious results are common, reducing trustworthiness of reported results. While this increases research waste, a common response is that science is ultimately self-correcting, and trustworthy science will eventually triumph. While this is likely true from a philosophy of science perspective, it does not yield information on how much effort is required to nullify suspect findings, nor factors that shape how quickly science may be correcting in the publish-or-perish environment scientists operate. There is also a paucity of information on how perverse incentives of the publishing ecosystem, which reward novel positive findings over null results, shaping the ability of published science to self-correct. Precisely what factors shape self-correction of science remain obscure, limiting our ability to mitigate harms. This modelling study illuminates these questions, introducing a simple model to capture dynamics of the publication ecosystem, exploring factors influencing research waste, trustworthiness, corrective effort, and time to correction. Results from this work indicate that research waste and corrective effort are highly dependent on field-specific false positive rates and the time delay before corrective results to spurious findings are propagated. The model also suggests conditions under which biomedical science is self-correcting, and those under which publication of correctives alone cannot stem the propagation of untrustworthy results. Finally, this work models a variety of potential mitigation strategies, including researcher and publication driven interventions.Significance statementIn biomedical science, there is increasing recognition that many results fail to replicate, impeding both scientific advances and trust in science. While science is self-correcting over long time-scales, there has been little work done on the factors that shape time to correction, the scale of corrective efforts, and the research waste generated in these endeavours. Similarly, there has been little work done on quantifying factors that might reduce negative impacts of spurious science. This work takes a modeling approach to illuminate these questions, uncovering new strategies for mitigating the impact of untrustworthy research.
PhageScanner, a flexible machine learning pipeline for automated bacteriophage genomic and metagenomic feature annotation
Authors: Albin Dreycey , Alistar Mirela 
Published: July 2023

AbstractEven though bacteriophages are the most plentiful organisms on Earth, many of their genomes and assemblies from metagenomic sources lack protein sequences with identified functions. Most proteins in bacteriophages are structural, known as Phage Virion Proteins (PVPs), but a considerable number remain unclassified. Complicating matters further, conventional lab-based methods for PVP identification are time-consuming and tedious. To expedite the process of identifying PVPs, machine-learning models are increasingly being employed. While existing tools have developed models for predicting PVPs from protein sequences as input, none of these efforts have built software allowing for genomic and metagenomic as input. In addition, there isn’t a framework available for easily curating data and creating new types of models. In response, we introduce PhageScanner, an open-source platform that streamlines data collection, model training and testing, and includes a prediction pipeline for annotating genomic and metagenomic data. PhageScanner also features a graphical user interface (GUI) for visualizing annotations on genomic and metagenomic data. We also introduce a BLAST-based classifier that outperforms ML-based models (achieving an F1 score of 94% for multiclass PVP detection and 97% for binary PVP detection) and an efficient Long Short-Term Memory (LSTM) classifier. We showcase the capabilities of PhageScanner by predicting PVPs in six previously uncharacterized bacteriophage genomes. In addition, showing the utility of the framework, we create a new model that predicts phage-encoded toxins within bacteriophage genomes.
Exploring Gene Expression Patterns and Evolutionary Responses in Host-Parasite inteactions: Insights from theSchistocephalus solidus– Threespine stickleback System
Authors: Wohlleben Anika M. , Tabima Javier F. , Meyer Néva P. , Steinel Natalie C. 
Published: July 2023

ABSTRACTHelminth parasites pose a significant threat to host survival and reproductive success, imposing strong selection pressure on hosts to evolve countermessures (e.g., immune responses and behavioral changes). To gain insights into the underlying mechanisms of host-parasite co-evolution, we examined differences in gene expression in immune tissues of two Alaskan stickleback (Gasterosteus aculeatus) populations with varying susceptibility to infection by the cestodeSchistocephalus solidus. Our analyses revealed distinct patterns of immune gene expression at the population-level in response to infection. Infected fish from the high infection population displayed signs of immune manipulation by the parasite, whereas this phenomenon was absent in fish from the low infection population. Notably, we found significant differences in immune gene expression between the populations, with uninfected Rocky Lake fish showing up-regulation of innate immune genes associated with inflammation compared to uninfected Walby Lake fish. These findings highlight the divergent evolutionary paths taken by different stickleback populations in their response to the same parasite.
Dimension reduction of microbiome data linkedBifidobacteriumto allergic rhinitis
Authors: Komaki Shohei , Sahoyama Yukari , Hachiya Tsuyoshi , Koseki Keita , Ogata Yusuke , Hamazato Fumiaki , Shiozawa Manabu , Nakagawa Tohru , Suda Wataru , Hattori Masahira , Kawakami Eiryo 
Published: July 2023

AbstractDimension reduction has been used to visualise the distribution of multidimensional microbiome data, but the composite variables calculated by the dimension reduction methods have not been widely used to investigate the relationship of the human gut microbiome with lifestyle and disease. In the present study, we applied several dimension reduction methods, including principal component analysis (PCA), principal coordinate analysis (PCoA), non-metric multidimensional scaling (NMDS), and non-negative matrix factorization (NMF), to a microbiome dataset from 186 subjects with symptoms of AR and 106 controls. All the dimension reduction methods supported that the enterotype clusters were overlapped in the dimension reduction plots, and that the distribution of microbial data points appeared to be continuous rather than discrete. Comparison of the composite variables calculated from the different dimension reduction methods showed that the characteristics of the composite variables differed between the dimension reduction methods. The second composite variable calculated from PCoA was significantly associated with the intake of several nutrients, including omega-3 polyunsaturated fatty acids, and the risk of AR. The composite variable was also correlated with the relative abundance ofBifidobacterium, and thus,Bifidobacteriumwas related to the risk of AR and intake of several nutrients through dimension reduction. Our results highlight the usefulness of the dimension reduction methods for investigating the association of microbial composition with lifestyle and disease in clinical research.
Pax37 gene function inOikopleura dioicasupports a neuroepithelial-like origin for its house-making Fol territory
Authors: Lagman David , Leon Anthony , Cieminska Nadia , Deng Wei , Chatzigeorgiou Marios , Henriet Simon , Chourrout Daniel 
Published: July 2023

AbstractLarvacean tunicates feature a spectacular innovation not seen in other animals - the trunk oikoplastic epithelium (OE). This epithelium produces a house, a large and complex extracellular structure used for filtering and concentrating food particles. Previously we have shown that several homeobox transcription factors may play a role in patterning the OE. Among these are twoPax3/7duplicates that we namedPax37AandPax37B. The vertebrate homologs,PAX3andPAX7, are involved in developmental processes related to neural crest and muscles. In the ascidian tunicateCiona robusta,Pax3/7has been given a role in development of cells deriving from the neural plate border including trunk epidermal sensory neurons and tail nerve cord neurons as well as in neural tube closure. Here we have investigated the roles ofPax37AandPax37Bin the development of the OE using CRISPR-Cas9, analyzing scRNA-seq data from wild-type animals that were compared with scRNA-seq data fromC. robusta. We revealed thatPax37Bbut notPax37Ais essential for the differentiation of cell fields that produce the food concentrating filter of the house: the anterior Fol, giant Fol and Nasse cells. Lineage analysis supports that expression ofPax37is under influence of Wnt signaling and that Fol cells have a neuroepithelial-like transcriptional signature. We propose that the highly specialized secretory epithelial cells of the Fol region either maintained or evolved neuroepithelial features as do “glue” secreting collocytes of ascidians. Their development seems to be controlled by a GRN that also operates in some ascidian neurons.
An aiHumanoid Simulation of Gram-Negative Sepsis: A Comprehensive Multi-Organoid Platform for Advanced Disease Modeling, Drug Discovery, and Personalized Medicine
Authors: Danter Wayne R 
Published: July 2023

AbstractOrganoids are three-dimensional cellular structures resembling human organs, which have emerged as valuable tools for studying organ development, disease modeling, and drug discovery. Integrating multiple organoid systems allows for the examination of complex interactions between different organs. In this study, we present the development and initial validation of the aiHumanoid simulation, an advanced AI-based computational framework that integrates 18 individual organoid simulations through a common cardiovascular system. Our aim is to investigate the systemic effects of gram-negative sepsis, a life-threatening condition that affects multiple organ systems.In this study, we evaluated the impact of gram-negative sepsis on the organoid systems that make up the aiHumanoid simulation. Our findings indicate significant alterations in cardiovascular, nervous system, respiratory, renal, hepatic, hematologic, gastrointestinal, musculoskeletal, immune, and endocrine parameters in both male and female sepsis-affected organoids. Notably, markers of inflammation, coagulation, renal dysfunction, liver damage, immune response, and endocrine regulation were significantly affected by sepsis. While some parameters showed gender-specific differences in response, such as hormonal changes, the overall impact of gram-negative sepsis was observed in both sexes.This study demonstrates the potential of the aiHumanoid to accurately simulate the systemic effects of diseases on various organ systems. The integration of computational simulations with organoid systems offers a powerful approach for understanding disease mechanisms and evaluating potential therapies. By providing a more efficient and physiologically relevant platform for drug testing, the aiHumanoid simulation has the potential to accelerate the drug development process, reduce costs, and minimize the need for animal testing. Further research and ongoing validation will be crucial to fully exploit the capabilities of this revolutionary computational framework for advancing disease modeling and therapeutic interventions.
The impact of late Pleistocene mammal extinctions on pathogen richness in extant hosts
Authors: Prys-Jones Tomos O. , Abraham Andrew J. , Mihaljevic Joseph R. , Murray Kris A. , Doughty Christopher E. 
Published: July 2023

ABSTRACTMany species of large mammals were driven to extinction during the late Pleistocene and early Holocene (approx. 10,000 – 50,000 years ago), with cascading effects on the physical structure of ecosystems and the dispersal of seeds, nutrients, and microbes. However, it remains uncertain whether the parasites associated with these extinct hosts also disappeared or persisted in surviving (extant) mammals. We hypothesize that if some parasites endured, extant mammals sharing their ranges with phylogenetically similar extinct mammals would have a greater pathogen richness than expected based on current levels of host diversity. We find that the inclusion of variables related to these extinctions account for an additional 5% of deviance when modelling per-host viral and bacterial richness, compared to models run without these variables. Partial dependence plots show a positive correlation between the number of extinct mammals lost and per-host viral and bacterial richness (p < 0.001 and p = 0.03, respectively). Additionally, decreasing phylogenetic distance between the extinct and extant species is associated with an increasing viral richness (p < 0.001). We discuss four mechanisms that may be driving these patterns and highlight future research to distinguish between them. Next, we use the models and IUCN range maps to identify geographic regions where viral and bacterial richness differs due to the inclusion of extinction variables. Notably, the richness of both pathogen types is increased in South America (viruses: +6.8%; bacteria: +3.1%) and decreased in Africa (viruses: −2.6%; bacteria: −13.6%), two continents known to have high and low levels of historical mammal extinctions, respectively. Viral richness is also elevated in North America (+8.6%), Europe (+5.1%), Oceania (+3.3%), and Asia (+2.3%). These results support the inclusion of extinction variables in future models of pathogen richness and may allow for improved targeting of future surveillance efforts.
Profiling human hypothalamic neurons reveals a candidate combination drug therapy for weight loss
Authors: Chen Hsiao-Jou Cortina , Yang Andrian , Mazzaferro Simone , Mali Iman , Cahn Olivier , Kentistou Katherine , Rowley Christine , Stewart Natasha , Seah Jun Wen Eugene , Pisupati Venkat , Kirwan Peter , Aggarwal Sanya , Toyohara Takafumi , Florido Mary H.C. , Cowan Chad A. , Quambusch Lena , Hyvönen Marko , Livesey Matthew R. , Perry John R.B. , Marioni John C. , Merkle Florian T. 
Published: July 2023

AbstractObesity substantially increases the risk of type 2 diabetes, cardiovascular disease, and other diseases, making it a leading preventable cause of death in developed countries. It has a strong genetic basis, with obesity-associated genetic variants preferentially acting in the brain. This includes the hypothalamic pro-opiomelanocortin (POMC) neurons that inhibit food intake and are stimulated by drugs that agonise glucagon-like 1 peptide receptor (GLP1R) including Semaglutide (Ozempic/Wegovy). We therefore hypothesised that drugs which selectively activate human POMC neurons would suppress appetite and promote weight loss, and that focusing on drugs already approved for use would facilitate rapid clinical translation. We therefore generated POMC neurons from human pluripotent stem cells (hPSCs) and identified enriched genes that were genetically associated with obesity and targeted by approved drugs. We found that human POMC neurons are enriched in GLP1R, reliably activated by Semaglutide, and their responses are further increased by co-administration of Ceritinib, an FDA-approved drug potently and selectively inhibiting anaplastic lymphoma kinase (ALK). Ceritinib reduced food intake and body weight in obese but not lean mice, and upregulated the expression of GLP1R in the mouse hypothalamus and hPSC-derived human hypothalamic neurons. These studies reveal a new potential therapeutic strategy for reducing food intake and body weight, and demonstrate the utility of hPSC-derived hypothalamic neurons for drug discovery.
Stem cell transcriptional profiles from mouse subspecies revealcis-regulatory evolution at translation genes
Authors: Simon Noah M. , Kim Yujin , Bautista Diana M. , Dutton James R. , Brem Rachel B. 
Published: July 2023

AbstractA key goal of evolutionary genomics is to harness molecular data to draw inferences about selective forces that have acted on genomes. The field progresses in large part through the development of advanced molecular-evolution analysis methods. Here we explored the intersection between classical sequence-based tests for selection and an empirical expression-based approach, using stem cells fromMus musculussubspecies as a model. Using a test of directional,cis-regulatory evolution across genes in pathways, we discovered a unique program of induction of translation genes in stem cells of the Southeast Asian mouseM. m. castaneusrelative to its sister taxa. We then mined population-genomic sequences to pursue underlying regulatory mechanisms for this expression divergence, finding robust evidence for alleles unique toM. m. castaneusat the upstream regions of the translation genes. We interpret our data under a model of changes in lineage-specific pressures acrossMus musculusin stem cells with high translational capacity. Our findings underscore the rigor of integrating expression and sequence-based methods to generate hypotheses about evolutionary events from long ago.