bluuebunny/crossref_metadata_2025 huggingface dataset:
Decoding dynamic visual scenes across the brain hierarchy
Authors: Chen Ye , Beech Peter , Yin Ziwei , Jia Shanshan , Zhang Jiayi , Yu Zhaofei , Liu Jian K.
Published: June 2024

Understanding the computational mechanisms that underlie the encoding and decoding of environmental stimuli is a paramount investigation within the domain of neuroscience. Central to this pursuit is the exploration of how the brain represents visual information across its hierarchical architecture. A prominent challenge resides in discerning the neural underpinnings of the processing of dynamic natural visual scenes. Although considerable research efforts have been made to characterize individual components of the visual pathway, a systematic understanding of the distinctive neural coding associated with visual stimuli, as they traverse this hierarchical landscape, remains elusive. In this study, we leverage the comprehensive Allen Visual Coding dataset and utilize the capabilities of deep learning neural network models to study the question of neural coding in response to dynamic natural visual scenes across an expansive array of brain regions. We find that our decoding model adeptly deciphers visual scenes from neural spiking patterns exhibited within each distinct brain area. A compelling observation arises from the comparative analysis of decoding performances, which manifests as a notable encoding proficiency within both the visual cortex and subcortical nuclei, in contrast to a relatively diminished encoding activity within hippocampal neurons. Strikingly, our results reveal a robust correlation between our decoding metrics and well-established anatomical and functional hierarchy indexes. These findings not only corroborate existing knowledge in visual coding using artificial visual stimuli but illuminate the functional role of these deeper brain regions using dynamic natural scenes. Consequently, our results proffer a novel perspective on the utility of decoding neural network models as a metric for quantifying the encoding of dynamic natural visual scenes, thereby advancing our comprehension of visual coding within the complex hierarchy of the brain.
Compartmental structure in the secondary lymphoid tissue can slow downin vivoHIV-1 evolution in the presence of strong CTL responses
Authors: Chung Wen-Jian , Wodarz Dominik
Published: June 2024

Human immunodeficiency virus (HIV-1) replicates in the secondary lymphoid tissues, which are characterized by complex compartmental structures. While Cytotoxic T lymphocytes (CTL) readily access infected cells in the extrafollicular compartments, they do not home to follicular compartments, which thus represent an immune-privileged site. Using mathematical models, we have previously shown that this compartmental tissue structure can delay the emergence of CTL escape mutants. Here, we show computationally that the compartmental structure can have an impact on the evolution of advantageous mutants that are not related to CTL recognition: (i) Compartmental structure can influence the fixation probability of an advantageous mutant, with weakened selection occurring if CTL responses are of intermediate strength. (ii) Compartmental structure is predicted to reduce the rate mutant generation, which becomes more pronounced for stronger CTL responses. (iii) Compartmental structure is predicted to slow down the overall rate of mutant invasion, with the effect becoming more pronounced for stronger CTL responses. Altogether, this work shows thatin vivovirus evolution proceeds slower in models with compartmental structure compared to models that assume equivalent virus load in the absence of compartmental structure, especially for strong CTL-mediated virus control. This has implications for understanding the rate of disease progression.
EnVhog: an extended view of the viral protein families on Earth through a vast collection of HMM profiles
Authors: Rubén Pérez-Bucio , Enault François , Galiez Clovis
Published: June 2024

Over the last twenty years, hundreds of metagenomic studies have generated millions of viral genomic sequences from a wide variety of ecosystems. Despite this, the overall genetic diversity of viruses remains elusive, both in terms of the number of protein families they encode and the diversity of these families. Indeed, even if it is recognized that the organization of the viral protein sequence space requires sensitive homology detection methods, such methods have never been applied at a large scale. To produce a more realistic and comprehensive view of the protein diversity in the viral world, we have (i) collected thousands of viromes and identified viral contigs and proteins within them, (ii) retrieved viral proteins available in different public databases, and (iii) applied sensitive similarity searches to cluster all these proteins into families and (iv) annotate the protein clusters produced. More than 46 million deduplicated proteins were clustered into less than 2.3 million protein families. After further removing genomic sequences likely of cellular origin using an iterative procedure, the remaining 2,203,457 clusters were coined enVhogs (for environmental Viral homologous groups). Their multiple sequence alignments have been transformed into HMMs to constitute the EnVhog database. Even if only a small proportion of enVhogs were annotated (15.9 %), they encompass almost half of the protein dataset (44.8 %). Applied to the annotation of four recently published viromes from diverse environments (sulfuric soil, grassland, surface seawater and human gut), enVhog HMMs doubled the number of viral sequences characterized, and increased by 54%-74% the number of proteins functionally annotated. EnVhog, the largest comprehensive compilation of viral protein information to date, is a resource that will thus further help to determine the functions of proteins encoded in newly sequenced viral genomes, and help to improve the accuracy of viral sequence detection tools.

EnVhog database is available athttp://envhog.u-ga.fr/envhog.
CelEsT: a unified gene regulatory network for estimating transcription factor activities inC. elegans
Authors: Perez Marcos Francisco
Published: June 2024

Transcription factors (TFs) play a pivotal role in orchestrating the intricate patterns of gene regulation critical for development and health. Although gene expression is complex, differential expression of many genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships inC. elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging.

Here I introduceCelEsT, a unified gene regulatory network (GRN) designed to estimate the activity of 487 distinctC. elegansTFs - ∼58% of the total - from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, different GRNs were benchmarked against a comprehensive set of TF perturbation RNA-seq experiments and identified optimal processing of each data type. Moreover, I showcase how leveraging conservation of TF binding motifs in the promoters of candidate target orthologues across genomes of closely-related species can distil targets into a select set of highly informative interactions, a strategy which can be applied to many model organisms. Combined analyses of multiple datasets from commonly-studied conditions including heat shock, bacterial infection and male-vs-female comparison validatesCelEsT’s performance and highlights previously overlooked TFs that likely play major roles in co-ordinating the transcriptional response to these conditions.

CelEsT can be used to infer TF activity on a standard laptop computer within minutes. Furthermore, anR Shinyapp is provided for the community to perform rapid analysis with minimal coding experience required. I anticipate that widespread adoption ofCelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation inC. elegansand beyond.
A Cry For Kelp: Evidence for Polyphenolic Inhibition of Oxford Nanopore Sequencing of Brown Algae
Authors: Pearman William S. , Arranz Vanessa , Carvajal Jose I. , Whibley Annabel , Liau Yusmiati , Johnson Katherine , Gray Rachel , Treece Jackson M. , Gemmell Neil J. , Liggins Libby , Fraser Ceridwen I. , Jensen Evelyn L. , Green Nicholas J.
Published: June 2024

Genomic resources for macroalgae are increasingly important for conservation and commercial management, however the generation of such resources continues to be hampered by difficulties in the isolation of suitable DNA. Even when DNA has been isolated that otherwise appears high quality, such samples may not perform well during the sequencing process. We here compare Oxford Nanopore long-read sequencing results for three species of macroalgae to those of non-macroalgal species and find that macroalgal samples tend to lead to rapid decline in the number of available sequencing pores resulting in reduced sequencing yield. LC-MS analysis of macroalgal DNA that would be considered suitable for sequencing reveals that DNA derived from dried macroalgae is enriched for polyphenol-DNA adducts – which may lead to sequencing inhibition. Our findings have wide-ranging implications for the generation of genomic resources from macroalgae, for example long read sequencing of dried herbarium specimens, and suggest a need to use fresh tissue wherever possible for genome sequencing.
A causal framework for the drivers of animal social network structure
Authors: Kawam Ben , Ostner Julia , McElreath Richard , Schülke Oliver , Redhead Daniel
Published: June 2024

Abstract

A major goal of behavioural ecology is to explain how phenotypic and ecological factors shape the networks of social relationships that animals form with one another. This inferential task is notoriously challenging. The social networks of interest are generally not observed, but must be approximated from behavioural samples. Moreover, these data are highly dependent: the observed network edges correlate with one another, due to biological and sampling processes. Failing to account for the resulting uncertainty and biases can lead to dysfunctional statistical procedures, and thus to incorrect results. Here, we argue that these problems should be understood—and addressed—as problems of causal inference. For this purpose, we introduce a Bayesian causal modelling framework that explicitly defines the links between the target interaction network, its causes, and the data. We illustrate the mechanics of our framework with simulation studies and an empirical example. First, we encode causal effects of individual-, dyad-, and group-level features on social interactions using Directed Acyclic Graphs and Structural Causal Models. These quantities are the objects of inquiry, ourestimands. Second, we developestimatorsfor these effects—namely, Bayesian multilevel extensions of the Social Relations Model. Third, we recover the structural parameters of interest, map statistical estimates to the underlying causal structures, and compute causalestimatesfrom the joint posterior distribution. Throughout the manuscript, we develop models layer by layer, thereby illustrating an iterative workflow for causal inference in social networks. We conclude by summarising this workflow as a set of seven steps, and provide practical recommendations.
Biofilm formation inStreptococcus suis:In vitroimpact of serovar and assessment of coinfections with other porcine respiratory disease complex bacterial pathogens
Authors: Miguélez-Pérez Rubén , Mencía-Ares Oscar , Gutiérrez-Martín César B. , González-Fernández Alba , Petrocchi-Rilo Máximo , Delgado-García Mario , Martínez-Martínez Sonia
Published: June 2024

Streptococcus suisis a worldwide pathogen that impacts swine industry, causing severe clinical signs in postweaning piglets, including meningitis and arthritis. Biofilm formation is a major virulence mechanism inS. suis, enhancing its persistence and resistance. Here, we assessed thein vitrobiofilm formation of 240S. suisisolates from Spanish swine farms and evaluated the effects of serovars (SVs) and coinfections with other porcine respiratory disease complex (PRDC) pathogens. Our study revealed significant heterogeneity in biofilm formation amongS. suisSVs. Notably, SV2 exhibited the lowest biofilm formation, contrasting with the high biofilm-forming capacities of SV1, SV7, and SV9. Virulence factorsepf,mrp, andslywere associated (p< 0.05) with reduced biofilm formation. Other PRDC pathogens, includingActinobacillus pleuropneumoniae,Glaesserella parasuis, andPasteurella multocida, formed biofilms, though generally less robust than those ofS. suis(except for SV2), contrasting the high biofilm formation ofStaphylococcus hyicus. Coinfections demonstrated enhanced biofilm formation in mixed cultures ofS. suis, particularly withP. multocida. Other coinfections revealed variable results in pathogen interactions, suggesting the potential of biofilms for increased persistence and pathogenicity in coinfections. In conclusion, this study underscores the importance of serovar-specific differences in biofilm formation amongS. suisisolates, with significant implications for pathogenicity and persistence. The heterogeneous biofilm formation observed in coinfections with other PRDC pathogens reveals a complex interplay that could exacerbate disease severity. These findings provide a foundation for further research on biofilm mechanisms to mitigate the impact of PRDC in the swine industry.
Discovery of a Heparan Sulfate Binding Domain in Monkeypox Virus H3 as an Anti-poxviral Drug Target Combining AI and MD Simulations
Authors: Zheng Bin , Duan Meimei , Huang Yifen , Wang Shangchen , Qiu Jun , Lu Zhuojian , Liu Lichao , Tang Guojin , Cheng Lin , Zheng Peng
Published: June 2024

Viral adhesion to host cells is a critical step in infection for many viruses, including monkeypox virus (MPXV). In MPXV, the H3 protein mediates viral adhesion through its interaction with heparan sulfate (HS), yet the structural details of this interaction have remained elusive. Using AI-based structural prediction tools and molecular dynamics (MD) simulations, we identified a novel, positively charged α-helical domain in H3 that is essential for HS binding. This conserved domain, found acrossorthopoxviruses, was experimentally validated and shown to be critical for viral adhesion, making it an ideal target for antiviral drug development. Targeting this domain, we designed a protein inhibitor, which disrupted the H3-HS interaction, inhibited viral infectionin vitroand viral replicationin vivo, offering a promising antiviral candidate. Our findings reveal a novel therapeutic target of MPXV, demonstrating the potential of combination of AI-driven methods and MD simulations to accelerate antiviral drug discovery.
Custom Biomedical FAIR Data Analysis in the Cloud Using CAVATICA
Authors: Berke Seth R , Kanchan Kanika , Marazita Mary L , Tobin Eric , Ruczinski Ingo
Published: June 2024

The historically fragmented biomedical data ecosystem has moved towards harmonization under the findable, accessible, interoperable, and reusable (FAIR) data principles, creating more opportunities for cloud-based research. This shift is especially opportune for scientists across diverse domains interested in implementing creative, nonstandard computational analytic pipelines on large and varied datasets. However, executing custom cloud analyses may present difficulties, particularly for investigators lacking advanced computational expertise. Here, we present an accessible, streamlined approach for the cloud compute platform CAVATICA that offers a solution. We outline how we developed a custom workflow in the cloud, for analyzing whole genome sequences of case-parent trios to detect sex-specific genetic effects on orofacial cleft risk, which required several programming languages and custom software packages. The approach involves just three components: Docker to containerize software environments, tool creation for each analysis step, and a visual workflow editor to weave the tools into a Common Workflow Language (CWL) pipeline. Our approach should be accessible to any investigator with basic computational skills, is readily extended to implement any scalable high-throughput biomedical data analysis in the cloud, and is applicable to other commonly used compute platforms such as BioData Catalyst. We believe our approach empowers versatile data reuse and promotes accelerated biomedical discovery in a time of substantial FAIR data.
Transcriptome- and proteome-wide Mendelian randomization to prioritize therapeutic targets for coronary heart disease
Authors: Gaziano Liam , Allara Elias , Giambartolomei Claudia , Stacey David , Zhao Jing Hua , Dashti Hesam , Jiang Tao , Ritchie Scott C. , Ferolito Brian R , Rasooly Danielle , Peloso Gina M. , Di Angelantonio Emanuele , Wheeler Eleanor , Pietzner Maik , Assimes Themistocles L , Wilson Peter WF , Cho Kelly , Aragam Krishna G , Burgess Stephen , Danesh John , Langenberg Claudia , Casas Juan Pablo , Michael Gaziano J , Pereira Alexandre C , Butterworth Adam S
Published: June 2024

Despite widespread use of drugs targeting traditional cardiovascular risk factors such as lipids and blood pressure, a high burden of coronary heart disease (CHD) remains, hence novel therapeutics are needed for people who harbor residual risk. Using transcriptomic and proteomic data to instrument 15,527 genes or proteins, we conducted systematiccis-Mendelian randomization (MR) and conditional colocalization analyses with a genetic meta-analysis involving nearly 300,000 CHD cases. We identified 567 targets with putative causal relevance to CHD, of which 69 were not identified in previous genetic discovery or MR studies and were the sole causal signal in that genomic region. To aid translation of our findings, we annotated results with up-to-date information on drugs acting on these targets. Our results revealed opportunities for drug repurposing and development prioritization. For example, we provide evidence that cilostazol, a drug that targetsPDE3Aand is currently used for claudication, could be repurposed for prevention of CHD.
The impact of ethical implications intertwined with tuberculosis household contact investigation: a qualitative study
Authors: Mlambo LM , Milovanovic M , Hanrahan CF , Motsomi KW , Morolo MT , Mohlamonyane MP , Albaugh NW , Ahmed K , Martinson NA , Dowdy DW , West NS.
Published: June 2024

Background

Household contact investigation (HCI) is an effective and widely used approach to identify persons with tuberculosis (TB) disease and infection, globally. Despite widespread recommendations for the use of HCI, there remains poor understanding of the impact on and value of contact investigation for participants. Further, how HCI as a practice impacts psychosocial factors, including stigma and possible unintended disclosure of illness among persons with TB, their families, and communities, is largely unknown.

Methods

This exploratory qualitative study nested within a randomized trial (ClinicalTrials.gov:NCT04520113, 17 August 2020) was conducted in South Africa to understand the impacts of HCI on index patients living with TB and their household contact persons in two rural districts in the Limpopo province (Vhembe and Capricorn) and Soshanguve, a peri-urban township in Gauteng province. People with TB and household members of people with TB were recruited to participate in in-depth interviews and focus group discussions using semi-structured guides. We explored individual, interpersonal, and community-level perceptions of potential impacts of household contact investigation to elucidate their perceptions of HCI. Thematic analysis identified key themes.

Results

Twenty-four individual interviews and six focus group discussions (n=39 participants) were conducted. Participants viewed HCI as an effective approach to finding TB cases, helpful in educating households about TB symptoms and reducing barriers to health-related services. At the interpersonal level, HCI aided people with TB in safely disclosing their TB status to family members and facilitated family and social support for accountability. The introduction of HIV testing during HCI was reported by some participants as making household members slightly uncomfortable, decreasing interest in household members being tested for TB. HCI negatively impacted community-level TB and HIV-related stigma due to healthcare worker visibility at home.

Conclusion

Our data suggests varying impacts of HCI on people with TB, their families and interpersonal relationships, and communities, highlighting the importance of considering approaches that address concerns about community stigma and HIV testing to enhance acceptance of HCI.
Estimating the lives that could be saved by expanded access to weight-loss drugs
Authors: Pandey Abhishek , Ye Yang , Wells Chad R. , Singer Burton H. , Galvani Alison P.
Published: June 2024

Obesity is a major public health crisis in the United States (US) affecting 42% of the population, exacerbating a spectrum of other diseases and contributing significantly to morbidity and mortality overall. Recent advances in pharmaceutical interventions, particularly glucagon-like peptide-1 (GLP-1) receptor agonists (e.g., semaglutide, liraglutide) and dual gastric inhibitory polypeptide and glucagon-like peptide-1 (GIP/GLP-1) receptor agonists (e.g., tirzepatide), have shown remarkable efficacy in weight loss. However, limited access to these medications due to high costs and insurance coverage issues restricts their utility in mitigating the obesity epidemic. We quantify the annual mortality burden directly attributable to limited access to these medications in the US. By integrating hazard ratios of mortality across body mass index categories with current obesity prevalence data, combined with willingness to take the medication, observed adherence to and efficacy of the medications, we estimate the impact of making these medications accessible to all those eligible. Specifically, we project that with expanded access, over 43,000 deaths could be averted annually, including more than 12,000 deaths among people with type 2 diabetes. These findings underscore the urgent need to address barriers to access and highlight the transformative public health impact that could be achieved by expanding access to these novel treatments.
Mapping Of The Sino-European Science And Technology Collaborations On Personalized Medicine: An Updated Overview
Authors: Pontoriero Letizia , Mazzoni Andrea , de Santis Giovanni , Gentili Matteo , Moltzen Ejner , Puch Sabine , Lange Carolin , Frosini Andrea , D’Errico Gianni
Published: June 2024

Aim

Personalized medicine is part of the future frontier of public health and precision healthcare systems have been implemented for years, both within Europe and beyond. To establish the state of the art of Sino-EU science and innovation in Personalized medicine, we have mined the major dedicated databases globally. Here we present the updated mapping on the Sino-EU collaborations. Patents, scientific publications and preprints related to Personalized medicine have been mapped and analyzed after being extracted through databases mining. The integration of the previous mapping provides a more complete overview, which does not show relevant variations, confirming previous trends. In this work we complete the mapping by providing a digital tool for consulting the various data collected.
Integration of clinical, pathological, radiological, and transcriptomic data improves the prediction of first-line immunotherapy outcome in metastatic non-small cell lung cancer
Authors: Captier Nicolas , Lerousseau Marvin , Orlhac Fanny , Hovhannisyan-Baghdasarian Narinée , Luporsi Marie , Woff Erwin , Lagha Sarah , Salamoun Feghali Paulette , Lonjou Christine , Beaulaton Clément , Salmon Hélène , Walter Thomas , Buvat Irène , Girard Nicolas , Barillot Emmanuel
Published: June 2024

The survival of patients with metastatic non-small cell lung cancer (NSCLC) has been increasing with immunotherapy, yet efficient biomarkers are still needed to optimize patient care. In this study, we explored the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We leveraged a novel multimodal cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, collecting at baseline positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. Most integration strategies investigated yielded multimodal models surpassing both the best unimodal models and established univariate biomarkers, such as PD-L1 expression. Additionally, several multimodal combinations demonstrated improved patient risk stratification compared to models built with routine clinical features only. Our study thus provided new evidence of the superiority of multimodal over unimodal approaches, advocating for the collection of large multimodal NSCLC cohorts to develop and validate robust and powerful immunotherapy biomarkers.
Deep learning of protein energy landscape and conformational dynamics from experimental structures in PDB
Authors: Tang Yike , Yu Mendi , Bai Ganggang , Li Xinjun , Xu Yanyan , Ma Buyong
Published: June 2024

Protein structure prediction has reached revolutionary levels of accuracy on single structures, implying biophysical energy function can be learned from known protein structures. However apart from single static structure, conformational distributions and dynamics often control protein biological functions. In this work, we tested a hypothesis that protein energy landscape and conformational dynamics can be learned from experimental structures in PDB and coevolution data. Towards this goal, we develop DeepConformer, a diffusion generative model for sampling protein conformation distributions from a given amino acid sequence. Despite the lack of molecular dynamics (MD) simulation data in training process, DeepConformer captured conformational flexibility and dynamics (RMSF and covariance matrix correlation) similar to MD simulation and reproduced experimentally observed conformational variations. Our study demonstrated that DeepConformer learned energy landscape can be used to efficiently explore protein conformational distribution and dynamics.
Sex-specific effects of gut microbiome on shaping bile acid metabolism
Authors: Yang Yifei , Chi Liang , Hsiao Yun-Chung , Lu Kun
Published: June 2024

Gut microbiome is a group of microorganisms that plays important roles in contributing to health and diseases. These bacterial compositions have been demonstrated to impact bile acids (BAs) profiles, either by directly metabolizing primary BAs to secondary BAs or indirect ways through host metabolism by influencing BAs synthesis, transportation and conjugation in liver. It has been observed sexually dimorphic gut microbiome and bile acids composition, with variations in expression levels of bile acid metabolizing genes in the liver. However, associations betweensex-specific differences in gut microbiome and BAs profiles are not well understood. This study aimed to investigate whether gut microbiome could influence BAs profiles in host in a sex-specific manner. We transplanted cecum feces of male and female C57BL/6 mice to male mice and measured BAs concentrations in feces, serum and liver samples 7 days after fecal transplantation. We found different BAs profiles between mice with male and female gut microbiome, including altering levels and proportions of secondary BAs. We also observed varied expression levels of genes related to bile acid metabolism in the liver and distal ileum.Our results highlight sex-specific effects of gut microbiome on shaping bile acid metabolism through gut bacteria and regulation of host genes.
Yersiniaactively downregulates type III secretion and adhesion at higher cell densities
Authors: Ermoli Francesca , Spahn Christoph , Glatter Timo , Diepold Andreas
Published: June 2024

The T3SS injectisome is used by Gram-negative bacteria, including important pathogens, to manipulate eukaryotic target cells by injecting effector proteins. Some bacterial species display bimodal expression of the T3SS, allowing the T3SS-negative population to benefit from the activity of their T3SS-positive siblings without investing in the assembly and production of injectisomes. In contrast,Yersinia enterocolitica, a main T3SS model organism that uses the system to evade the host immune response, was thought to uniformly express and assemble injectisomes, which are then activated by target cell contact. In this study, we found that at higher local bacterial concentrations,Yersiniaactively downregulates T3SS expression, assembly and activity. This effect is reversible, highly specific, and distinct from stationary phase adaptation. A key player is the main T3SS transcription factor VirF, which is downregulated at the higher cell densities suppressing T3SS activity and whosein transexpression restores T3SS expression and assembly. Transcript analysis showed that this effect is mediated by increased levels of the regulatory RNAscsrBC, which sequester the regulatory protein CsrA and destabilize thevirFtranscript. Downregulation of the VirF-dependent adhesin YadA led to a drastic reduction in bacterial cell adhesion. We propose that the phenotype described in this study, active downregulation of cell attachment and T3SS secretion at higher local bacterial densities, is a strategy implemented to promote bacterial replication and dissemination at later stages of infection.
Functional protein mining with conformal guarantees
Authors: Boger Ron S. , Chithrananda Seyone , Angelopoulos Anastasios N. , Yoon Peter H. , Jordan Michael I. , Doudna Jennifer A.
Published: June 2024

1

Molecular structure prediction and homology detection provide a promising path to discovering new protein function and evolutionary relationships. However, current approaches lack statistical reliability assurances, limiting their practical utility for selecting proteins for further experimental and in-silico characterization. To address this challenge, we introduce a novel approach to protein search leveraging principles from conformal prediction, offering a framework that ensures statistical guarantees with user-specified risk and provides calibrated probabilities (rather than raw ML scores) for any protein search model. Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of new proteins with likely desirable functional properties.
Acceptability and feasibility of maternal screening for Group B Streptococcus: a rapid review
Authors: Constantinou Georgina , Webb Rebecca , Ayers Susan , Mitchell Eleanor J , Daniels Jane
Published: June 2024

Background

The risks and benefits of maternal screening for GBS during pregnancy or the intrapartum period are widely debated, since screen positive results trigger prophylactic antibiotic use. There is little known about women’s and health professional’s views regarding GBS screening.

Objectives

To conduct a rapid review to synthesise evidence on women and health professionals’: (1) knowledge and awareness of; (2) preferences for; and (3) acceptability of GBS screening programmes, and (4) how feasible they are to implement.

Method

Literature searches were conducted using online databases from their inception to 2023. Papers were included if they reported primary research from the perspectives of health professionals and women, about their knowledge and awareness, preferences, acceptability and feasibility of different types of GBS screening programmes. Data were assessed for confidence using GRADE- CERQual and analysed using a convergent synthesis approach.

Findings

42 papers were eligible for inclusion. A total of 16,306 women and professionals were included. Women generally did not have extensive knowledge about GBS. Health professionals had a higher level of knowledge than women. Women were generally (but not universally) positive about GBS testing procedures. Some women were concerned about the impact on their place of birth.

Discussion and Conclusion

Where GBS screening programmes are available, parents must be provided with high quality information about them. Health professionals and service managers need to weigh up the benefits and risks of screening for GBS with local feasibility and treatment options, and with women’s individual values and birth plans.

Statement of significance

Problem:Maternal GBS colonisation at birth can lead to invasive GBS disease. The risks and benefits of screening for GBS during pregnancy is widely debated.

What is already known:Different countries use different GBS screening strategies, such as the universal screening strategy vs risk based.

What this paper adds:The World Health Organization reviewed their GBS policy guidelines in 2024.

Resultsfrom this paper were used to ensure women and health professional’s views were considered. This paper found that women are generally (but not universally) positive about GBS testing procedures with some concerned about the impact on their birth choices.
Maternal Colonization, Perinatal Exposure, and Neonatal Acquisition of Resistant Enterobacterales
Authors: Mithal Leena B. , Sajwani Alima , Aron Abigail , Kremer Aspen , Sumner Jack T. , Castro Manzano Valeria C. , Donnelly Grayson , Watson Andrew D. , Shuai Weitao , Miller Emily S. , Fisher Joel B. , Hartmann Erica M. , Arshad Mehreen
Published: June 2024

Background

Multi-drug resistant Enterobacterales, in particular with ceftriaxone resistance (CefR-E), are globally prevalent. Pregnant people colonized with resistant Enterobacterales are at risk of perinatally transmitting to neonates; infections with CefR-E strains are associated with higher mortality, morbidity and health care costs. This study aimed to estimate the rate of gut colonization of AmpR-E (ampicillin resistant Enterobacterales) and CefR-E in a population of healthy mother-infant dyads in the Chicago area and investigate the genetic characteristics of CefR-E.

Methods

Pregnant persons anticipating vaginal birth at two Chicago area hospitals were enrolled. Patients with preterm delivery (<35 weeks), fever during labor, cesarean delivery, exposure to antibiotics in 3rd trimester, and neonatal intensive care were excluded. Pregnancy and birth history were obtained from parent and medical record. Maternal vaginal and rectal swabs, and infant stool samples were collected and screened for resistance by plating on MacConkey with ceftriaxone. Whole genome sequencing (WGS) and analysis was conducted on the CefR-E isolates.

Results

Between July 2020 and April 2022, 261 mother-infant dyads were enrolled with 184 maternal samples and 157 infant stool samples analyzed. Rate of maternal AmpR-E gut colonization was 97% (179/184). Rate of maternal and infant CefR-E gut colonization was 14% (26/184) and 7% (11/157) respectively. Perinatal transmission of CefR-E was 50% (11 of 22) positive mothers with available infant sample). No clinical variables were significantly associated with maternal CefR-E colonization or perinatal transmission. Type of infant nutrition (breastmilk) was significantly associated with decreased perinatal transmission of AmpR-E to infant (p=0.015). WGS of the CefR-E showed that 19/42 isolates wereE. coli, and transmission primarily occurred from mothers colonized withE. coli.

Conclusions

This study demonstrates that a sizable minority of pregnant persons are colonized with CefR-E in the U.S., a higher burden than previously reported for developed countries. Enterobacterales appear adept in perinatal transmission, with half of infants born to colonized pregnant persons harboring CefR-E in first week of life.
Genetic analysis implicatesERAP1and HLA as risk factors for severe Puumala virus infection
Authors: Haapaniemi Hele , Strausz Satu , Tervi Anniina ,   FinnGen, Jones Samuel E. , Kanerva Mari , Fors-Connolly Anne-Marie , Ollila Hanna M.
Published: June 2024

Puumala virus (PUUV) infections can cause severe illnesses such as Hemorrhagic Fever with Renal Syndrome in humans. However, human genetic risk factors contributing to disease severity are still poorly understood. Our goal was to elucidate genetic factors contributing to PUUV infections and understand the biological mechanisms underlying individual vulnerability to the disease. Leveraging data from the FinnGen study, we conducted a genome-wide association study on severe Hemorrhagic Fever with Renal Syndrome caused by PUUV with 2,227 cases. We identified associations at the Human Leukocyte Antigen (HLA) locus andERAP1with severe PUUV infection. HLA molecules are canonical mediators for immune recognition and response.ERAP1facilitates immune system recognition and activation by cleaving viral proteins into smaller peptides which are presented to the immune system via HLA class I molecules. Notably, we identified that the lead variant (rs26653, OR = 0.84, p = 2.93×10-8) in theERAP1gene was a missense variant changing amino acid arginine to proline. From the HLA region, we showed independent and significant associations with both HLA class I and II genes. Furthermore, we showed independent associations with nine HLA alleles and severe PUUV infection using conditional HLA fine-mapping. The strongest association was found with theHLA-C*07:01allele (OR = 1.5, p = 4.0×10−24) followed by signals atHLA-B*13:02, HLA-DRB1*01:01, andHLA-DRB1*11:01alleles (p<5×10−8). Our findings suggest that viral peptide processing withERAP1and antigen presentation through HLA alleles contribute to the development of severe PUUV disease.
Conformational disorder in the crystal structure of methyl 2-acetamido-2-deoxy-β-D-glucopyranosyl-(1→4)–2-acetamido-2-deoxy-β-D-glucopyranoside (methyl β-chitobioside) methanol monosolvate
Authors: Shit Pradip , Tetrault Timothy , Zhang Wenhui , Yoon Mi-Kyung , Oliver Allen G. , Serianni Anthony S.
Published: June 2024

Methyl 2-acetamido-2-deoxy-β-D-glucopyranosyl-(1→4)-2-acetamido-2-deoxy-β-D-glucopyranoside (methyl β-chitobioside), (IV), crystallizes from aqueous methanol at room temperature to give a structure (C17H30N2O22·CH3OH) containing conformational disorder in the exocyclic hydroxymethyl group of one of its βGlcNAc residues. As observed in other X-ray structures of disaccharides containing β-(1→4) O-glycosidic linkages, inter-residue hydrogen bonding between O3H of the βGlcNAc bearing the OCH3 aglycone and O5 of the adjacent βGlcNAc is observed based on the 2.79 Å internuclear distance between the O atoms. The structure of (IV) was compared to that determined previously for 2-acetamido-2-deoxy-β-D-glucopyranosyl-(1→4)-2-acetamido-2-deoxy-β-D-glucopyranose (β-chitobiose), (III). The O-glycosidic linkage torsion angles, phi (ϕ) and psi (ψ), in (III) and (IV) differ by 6–8°. The N-acetyl side chain conformation in (III) and (IV) shows some context dependence, with the C1—C2—N—Ccar torsion angle 10–15° smaller for the βGlcNAc residue involved in the internal O-glycosidic linkage. In (IV), conformational disorder is observed in the exocyclic hydroxymethyl (–CH2OH) group in the βGlcNAc residue bearing the OCH3 aglycone, and a fitting of the electron density indicates an approximate 50:50 distribution of the gauche–gauche (gg) and gauche–trans (gt) conformers in the lattice. Similar behavior is not observed in (III), presumably due to the different packing structure in the vicinity of the –CH2OH substituent that affects its ability to hydrogen bond to proximal donors/acceptors. Unlike (IV), a re-examination of the previously reported electron density of (III) revealed conformational disorder in the N-acetyl side chain attached to the reducing-end βGlcNAc residue caused by rotation about the C2—N bond.
trans-Diaquatetrakis(tetrahydrofuran-κO)iron(II) μ-carbonyl-tetradecacarbonyltetrachlorido-μ-dimethylsilanediolato-tetragalliumtetrairon(7 Ga–Fe)(Fe–Fe) tetrahydrofuran tetrasolvate
Authors: Demmin Mary Elizabeth , Bauer Cary , Ruf Michael , Harakas George N.
Published: June 2024

The title compound, [Fe(C4H8O)4(H2O)2][Fe4Ga4(C2H6O2Si)Cl4(CO)15]·4C4H8O, consists of an iron(II) cation octahedrally coordinated by two water molecules (trans) with four tetrahydrofurans (THF) at equatorial sites. Two additional THF molecules are hydrogen bonded to each of the water molecules. The dianion of the title compound is an organometallic butterfly complex with a dimethyl siloxane core and two iron-gallium fragments. The lengths of the iron to gallium metal–metal bonds range from 2.3875 (6) to 2.4912 (6) Å.
Prediction of flexural strength in FRP bar reinforced concrete beams through a machine learning approach
Authors: Manan Aneel , Zhang Pu , Ahmad Shoaib , Ahmad Jawad
Published: June 2024

Purpose

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

Design/methodology/approach

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R2, root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

Findings

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Originality/value

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.
Influence of scanning speed on titanium alloy processed with TC4+Ni60/hBN composite powder by laser metal deposition coating technology
Authors: Miah Md Helal , Singh Chand Dharmahinder , Singh Malhi Gurmail , Wang Gongdong
Published: June 2024

Purpose

Regarding the broadening of the titanium alloy application field, the surface treatment coating of TC4 alloy has become an essential global research topic. This study aims to illustrate the titanium-based composite coating is created by laser cladding TC4+Ni60/hBN composite powder onto the surface of the TC4 alloy.

Design/methodology/approach

Different laser scanning speeds were initially selected to prepare TC4+Ni60/hBN titanium-based composite coating on the surface of TC4 alloy using RFL-C1000 Raycus fiber laser. Second, the cladding layers with different laser scanning speeds are composed of Ti2Ni, TiN0.3, TiC, TiB, α-Ti and other phases. Finally, precision balances, friction and wear testing machines were used to analyze and test the structure, phase, hardness, wear amount and friction coefficient of the composite coating and to study the effect of laser scanning speed on the microstructure and properties of the titanium-based composite coating.

Findings

It is evident that at the low laser scanning speed, the reinforcing phase agglomeration area is distributed in the substrate as a network. Increasing the laser scanning speed can reduce the cladding layer's friction coefficient and improve the cladding layer's hardness and wear resistance. But too high a laser scanning speed will cause defects such as pores and cracks in the cladding layer and also affect the cladding layer. The bonding performance of the layer and the substrate is optimal in this research at a laser scanning speed of 10 mm/s.

Originality/value

This research has practical value in improving the quality of surface treatment coating in modern aerospace and automotive companies.
Approach for sizing by optimization of an electrical drive considering a multiphysics and multidynamics behaviour
Authors: Thomas Robin , Gerbaud Laurent , Chazal Herve , Garbuio Lauric
Published: June 2024

Purpose

This paper aims to describe a modelling and solving methodology of a (static converter–electric motor–control) system for its sizing by optimization, considering the dynamic thermal heating of the machine.

Design/methodology/approach

The electrical drive sizing model is composed of two simulators (electrical and thermal) that are co-simulated with a master−slave relationship for the time step management. The computation is stopped according to simulation criteria.

Findings

This paper details a methodology to represent and size an electrical drive using a multiphysics and multidynamics approach. The thermal simulator is the master and calls the electrical system simulator at a fixed exchange time step. The two simulators use a dedicated dynamic time solver with adaptive time step and event management. The simulation automatically stops on pre-established criteria, avoiding useless simulations.

Research limitations/implications

This paper aims to present a generic methodology for the sizing by optimization of electrical drives with a multiphysics approach, so the precision and computation time highly depend on the modelling method of each components. A genetic multiobjective optimization algorithm is used.

Practical implications

The methodology can be applied to size electrical drives operating in a thermally limited zone. The power electronics converter and electrical machine can be easily adapted by modifying their sub-model, without impacting the global model and simulation principle.

Originality/value

The approach enables to compute a maximum operating duration before reaching thermal limits and to use it as an optimization constraint. These system considerations allow to over constrain the electrical machine, enabling to size a smaller machine while guaranteeing the same output performances.