bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure of the T=13 capsid of infectious pancreatic necrosis virus (IPNV) - a salmonid birnavirus
Authors: Munke Anna , Ahmed Abdelrahim Gamil Amr , Mikalsen Aase B. , Wang Han , Evensen Øystein , Okamoto Kenta 
Published: August 2024

AbstractBirnaviruses infect a broad range of vertebrate hosts, including fishes and birds, and cause substantial economic losses in the fishery and livestock industries. The infectious pancreatic necrosis virus (IPNV), an aquabirnavirus, specifically targets salmonids. While structures on T=1 subviral particles of the birnaviruses, including IPNV, have been studied, structural insights into the infectious T=13 particles have been limited to the infectious bursal disease virus (IBDV), an avibirnavirus. Determining the capsid structure of the T=13 particle of IPNV is crucial for advancing knowledge of its antigenicity, capsid assembly, and possible functional structures. Here, the capsid structure of the IPNV L5 strain has been determined at a resolution of 2.75 Å. The overall structure resembles the T=13 IBDV structure, with notable differences in the surface loops on the P domain of the VP2 capsid protein, essential for antigenicity and virulence. Additionally, previously undescribed structural features have been identified, including the C-terminal regions of the VP2 subunits within the pentagonal assembly unit at each 5-fold axis, which interlock with adjacent VP2 subunits. This interlocking, together with class-averaged projections of triangular and pentagonal units, suggests that the pentagonal unit formation could be important for correct T=13 particle assembly, preventing the formation of T=1 subviral particles. Furthermore, positively charged residues in obstructed capsid pores at each 5-fold axis are speculated to facilitate intraparticle genome synthesis of IPNV.ImportanceAquabirnaviruses cause deadly infectious diseases in salmonid fish, posing significant challenges for both wild and farmed fish populations. The most prevalent aquabirnavirus worldwide is the infectious pancreatic necrosis virus, whose multifunctional capsid is critical to its infection, replication, and maturation. Previously, research has focused on the structure of the virus’s non-infectious subviral capsid. In this study, however, the first structure of the large, infectious, and functional form of the capsid has been determined. This new capsid structure reveals functional motifs that were previously unclear in the non-infectious capsid. These motifs are believed to be essential for the virus’s replication and particle assembly, making them promising targets for developing strategies to control virus proliferation.
Tree nursery environments and their effect on early trait variation
Authors: Perry Annika , Beaton Joan K. , Stockan Jenni A. , Iason Glenn R. , Cottrell Joan E. , Cavers Stephen 
Published: August 2024

AbstractDespite the major role of nurseries in raising young plants and trees prior to transplantation, not enough is known about how the nursery climate impacts the growth and development of plants from germination through to maturity. It is important for forestry practitioners to understand the effect that different nursery environments may have on early stage growth as these may exceed differences due to genetic variation and can confound the use of early stage traits for selection. Here, a replicated progeny-provenance experiment of the economically and ecologically important species Scots pine (Pinus sylvestrisL.) was established in three environmentally distinct nurseries in Scotland and traits including survival, growth, form and phenology were measured. Temperature variation and photoperiod were the only uncontrolled environmental variables during this period, and their effect on measured traits was found to be significant among nurseries from the first growing season onwards. Trait interactions were not consistent between nurseries, indicating that the effectiveness of using proxy traits to select for desirable characteristics may depend on the environment in which the trees are grown. This study is the first in a series that will examine trait variation in Scots pine from seedlings to mature trees and highlights the importance of carefully considering and accounting for the nursery environment when growing trees for subsequent transplantation.
Genomic loci for sclerotinia stem rot resistance and chlorophyll stability inBrassica napus: integrating GWAS with microbiome insights
Authors: Chawade Aakash , Thuraga Vishnukiran , Sepp Siim Samuel , Ghosh Samrat , Ghadamgahi Farideh , Odilbekov Firuz , Muthusamy Saraladevi , Vetukuri Ramesh R , Abreha Kibrom B. 
Published: August 2024

AbstractSclerotinia Stem Rot (SSR) disease is one of the most serious diseases affecting the yield and quality of oilseed rape (Brassica napus). Understanding the genetic basis of the resistance trait in oilseed rape to SSR and microbiome composition for enhanced resistance is crucial for developing resistant varieties and sustainably mitigate the impact of the disease. In this study, in a panel of 168 oilseed rape accessions, most resistant (NGB 13503 and NGB 13834) and susceptible (NGB 13497 and NGB 13897) accessions are identified. A Genome-wide association study (GWAS) identified 47 SNPs linked to the SSR lesion length, lesion area, and lesion relative to the leaf area. Among the SNPs significantly linked to lesion length were Bn-A04-p10555408, Bn-A07-p12487549, Bn-A09-p4652268, Bn-A09-p4916858 and to our knowledge, these SNPs have not been previously linked to SSR resistance in oilseed rape. Moreover, the study identified 24 SNPs linked with chlorophyll content before SSR inoculation (SPADH), after the SSR inoculation (SPADI), and chlorophyll index (CI). Maintaining the chlorophyll level is correlated with the SSR resistance. Furthermore, bacterial taxa (e.g.Pseudomonas,Methylobacterium, andAquabacterium) and fungal taxa (e.g.Mycosphaerellales,Thelebolales, andAkanthomyces) were enriched in the resistant compared to in the susceptible oilseed rape accessions. The SNPs linked to lesion length showed consistent haplotype variation between these selected accessions. Given the absence of complete resistance against SSR, the study provides insights into the significance of maintaining chlorophyll levels and considering microbiome composition for enhancing the level of existing partial resistance to SSR in oilseed rape.
APPROACHES TO DIMENSIONALITY REDUCTION FOR ULTRA-HIGH DIMENSIONAL MODELS
Authors: Kotlarz Krzysztof , Słomian Dawid , Szyda Joanna 
Published: August 2024

ABSTRACTThe rapid advancement of high-throughput sequencing technologies has revolutionised genomic research by providing access to large amounts of genomic data. However, the most important disadvantage of using Whole Genome Sequencing (WGS) data is its statistical nature, the so-called p>>n problem. This study aimed to compare three approaches of feature selection allowing for circumventing the p>>n problem, among which one is a novel modification of Supervised Rank Aggregation (SRA). The use of the three methods was demonstrated in the classification of 1,825 individuals representing the 1000 Bull Genomes Project to 5 breeds, based on 11,915,233 SNP genotypes from WGS. In the first step, we applied three feature (i.e. SNP) selection methods: the mechanistic approach(SNP tagging)and two approaches considering biological and statistical contexts by fitting a multiclass logistic regression model followed by either 1-dimensional clustering(1D-SRA)or multi-dimensional feature clustering(MD-SRA)that was originally proposed in this study. Next, we perform the classification based on a Deep Learning architecture composed of Convolutional Neural Networks. The classification quality of the test data set was expressed by macro F1-Score. The SNPs selected bySNP taggingyielded the least satisfactory results (86.87%). Still, this approach offered rapid computing times by focussing only on pairwise LD between SNPs and disregarding the effects of SNP on classification.1D-SRAwas less suitable for ultra-high-dimensional applications due to computational, memory and storage limitations, however, the SNP set selected by this approach provided the best classification quality (96.81%).MD-SRAprovided a very good balance between classification quality (95.12%) and computational efficiency (17x lower analysis time and 14x lower data storage), outperforming other methods. Moreover, unlikeSNP tagging, both SRA-based approaches are universal and not limited to feature selection for genomic data. Our work addresses the urgent need for computational techniques that are both effective and efficient in the analysis and interpretation of large-scale genomic datasets. We offer a model suitable for the classification of ultra-high-dimensional data that implements fusing feature selection and deep learning techniques.
Plasma Membrane Remodelling in GM2 Gangliosidoses Drives Synaptic Dysfunction
Authors: Nicholson Alex S. , Priestman David A. , Antrobus Robin , Williamson James C. , Bush Reuben , Barrow Henry G. , Smith Emily , Dobrenis Kostantin , Bright Nicholas A. , Platt Frances M. , Deane Janet E. 
Published: August 2024

ABSTRACTGlycosphingolipids (GSL) are important bioactive components of cellular membranes. Complex GSLs, containing sialic acid residues are known as gangliosides and are highly abundant in the brain. Diseases of ganglioside metabolism often result in severe, early-onset neurodegeneration. The ganglioside GM2 is the substrate of the hydrolytic lysosomal β- hexosaminidase A (HexA) enzyme and when subunits of this enzyme are non-functional, GM2 lipid accumulates in cells leading to the GM2 gangliosidoses, Tay-Sachs and Sandhoff diseases. We have developed high-quality i3Neuron-based models of Tay-Sachs and Sandhoff diseases, that demonstrate storage of GM2, formation of membrane whorls and accumulation of endolysosomal proteins consistent with disease phenotypes. Importantly, in addition to lysosomal dysfunction, the composition of the plasma membrane (PM) is significantly impacted in these diseases with changes in the abundance of both lipids and proteins. The changes to the PM proteome are driven in part by exocytosis of lysosomal material resulting in the aberrant accumulation of lysosomal proteins and lipids on the cell surface. The altered abundance of GM2 at the PM was striking, bringing the abundance of this precursor lipid up to that of the common neuronal gangliosides. Furthermore, the PM profiling identifies significant changes in synaptic protein abundances with direct functional impact on neuronal activity including rapid electrical firing consistent with neuronal hyperactivity. This work provides mechanistic insights into neuronal dysfunction in the GM2 gangliosidoses and highlights that these are also severe PM disorders. This work has broad implications for other lysosomal storage disorders and late-onset neurodegenerative diseases involving sphingolipid dysregulation.
Temperate phage-antibiotic synergy is widespread, but varies by phage, host, and antibiotic pairing
Authors: Fatima Rabia , Hynes Alexander P. 
Published: August 2024

AbstractWith a decline in antibiotic effectiveness, there is a renewed interest in bacteriophage (phage) therapy. Phages are bacterial-specific viruses that can be used alone or with antibiotics to reduce bacterial load. Most phages are unsuitable for therapy because they are ‘temperate’ and can integrate into the host genome, forming a lysogen which is protected from subsequent phage infections. However, integrated phages can be awakened by stressors such as antibiotics. This interaction was previously reported to result in a potent synergy between antibiotic classes and a modelE. colitemperate phage, which can readily eradicate the bacterium at sub-lethal concentrations of antibiotics, despite the poor effectiveness of the phage alone. Here we explore the generalizability of this synergy to a clinically relevant pathogen:Pseudomonas aeruginosa. Thirty-six temperate phages isolated from clinical strains were screened for synergy with six antibiotics (ciprofloxacin, levofloxacin, meropenem, piperacillin, tobramycin, polymyxin B), using checkerboard assays. Interestingly, our screen identified phages that can synergize with each antibiotic, despite their widely differing targets - however, these are highly phage-antibiotic and phage-host pairing specific. Screening the strongest pairings across multiple clinical strains reveal that these phages can reduce the antibiotic minimum inhibitory concentration up to 32-fold, even in a resistant isolate, functionally re-sensitizing the bacterium to the antibiotic. When meropenem and tobramycin were effective synergistic agents, they did not reduce the frequency of lysogens, suggesting a mechanism of action independent of the temperate nature of the phages. In contrast, ciprofloxacin and piperacillin were able to reduce the frequency of lysogeny, the former by inducing phages – as previously reported inE. coli. Curiously, synergy with piperacillin reduced the frequency of lysogeny, but not by inducing the phages, and therefore likely acts by biasing the phage away from lysogeny in the initial infection. Overall, our findings indicate that temperate phages can act as adjuvants to antibiotics in clinically relevant pathogens, even in the presence of antibiotic resistance, thereby drastically expanding their therapeutic potential.
Severe deviation in protein fold prediction by advanced AI: a case study
Authors: López-Sagaseta Jacinto , Urdiciain Alejandro 
Published: August 2024

AbstractArtificial intelligence (AI) and deep learning are making groundbreaking strides in protein structure prediction. AlphaFold is remarkable in this arena for its outstanding accuracy in modelling proteins fold based solely on their amino acid sequences. In spite of these remarkable advances, experimental structure determination remains critical. Here we report severe deviations (>30 Å) between the experimental structure of a two-domain protein and its equivalent AI-prediction. These observations are particularly relevant to the relative orientation of the domains within the global protein scaffold. Significant divergence between experimental structures and AI-predicted models echoes the presence of unusual conformations, insufficient training data and high complexity in protein folding that can ultimately lead to current limitations in protein structure prediction.
Re-evaluating the relationship between female social bonds and infant survival in wild baboons
Authors: Creighton Maria J.A. , Lerch Brian A. , Lange Elizabeth C. , Silk Joan B. , Tung Jenny , Archie Elizabeth A. , Alberts Susan C. 
Published: August 2024

ABSTRACTOver the past few decades studies have provided strong evidence that the robust links between the social environment, health, and survival found in humans also extend to non-human social animals. A number of these studies emphasize the early life origins of these effects. For example, in several social mammals, more socially engaged mothers have infants with higher rates of survival compared to less socially engaged mothers, suggesting that positive maternal social relationships causally improve offspring survival. Here we show that the relationship between infant survival and maternal sociality is confounded by previously underappreciated variation in female social behavior linked to changes in reproductive state and the presence of a live infant. Using data from a population of wild baboons living in the Amboseli basin of Kenya – a population where high levels of maternal sociality have previously been linked to improved infant survival – we find that infant- and reproductive state-dependent changes in female social behavior drive a statistically significant relationship between maternal sociality and infant survival. After accounting for these state-dependent changes in social behavior, maternal sociality is no longer positively associated with infant survival in this population. Our results emphasize the importance of considering multiple explanatory pathways—including third-variable effects—when studying the social determinants of health in natural populations.
Archaic introgression and the distribution of shared variation under stabilizing selection
Authors: Ragsdale Aaron P. 
Published: August 2024

AbstractMany phenotypic traits are under stabilizing selection, which maintains a population’s mean phenotypic value near some optimum. The dynamics of traits and trait architectures under stabilizing selection have been extensively studied for single populations at steady state. However, natural populations are seldom at steady state and are often structured in some way. Admixture and introgression events may be common, including over human evolutionary history. Because stabilizing selection results in selection against the minor allele at a trait-affecting locus, alleles from the minor parental ancestry will be selected against after admixture. We show that the site-frequency spectrum can be used to model the genetic architecture of such traits, allowing for the study of trait architecture dynamics in complex multi-population settings. We use a simple deterministic two-locus model to predict the reduction of introgressed ancestry around trait-contributing loci. From this and individual-based simulations, we show that introgressed-ancestry deserts are enriched around such loci. When introgression between two diverged populations occurs in both directions, as has been inferred between humans and Neanderthals, the locations of introgressed-ancestry deserts will tend to be shared across populations. We argue that stabilizing selection for shared phenotypic optima may explain recent observations in which regions of depleted human-introgressed ancestry in the Neanderthal genome overlap with Neanderthal-ancestry deserts in humans.
PHeP: TrustAlert Open-Source Platform for Enhancing Predictive Healthcare with Deep Learning
Authors: Contaldo Sandro Gepiro , Pietropaolo Emanuele , Bosio Lorenzo , Pernice Simone , Terrone Irene , Baccega Daniele , Wang Yuting , Sahoo Rahul Kumar , Rizzo Giuseppe , Visconti Alessia , Berchialla Paola , Beccuti Marco 
Published: August 2024

AbstractPredictive healthcare, a field revolutionized by the availability of large medical datasets and computational advancements, plays a pivotal role in enhancing patient care and healthcare system performance. Despite its significance, the training and deployment of predictive healthcare models present substantial challenges. To address these, we introduce the Predictive Healthcare Platform (PHeP), an open-source platform that simplifies the use of pretrained models. PHeP, developed under the TrustAlert project, offers an intuitive web-based graphical interface, making advanced predictive healthcare accessible to users without extensive computational skills or expensive computational resources. This paper presents the design and functionality of PHeP, demonstrating its effectiveness in predictive healthcare tasks, such as predicting re-hospitalization at three months using pre-trained BERT models.
Examining the impact of outdoor walk group attendance on health among older adults with mobility limitations in the Getting Older Adults Outdoors (GO-OUT) randomized trial
Authors: Su Tai-Te , Barclay Ruth , Moineddin Rahim , Salbach Nancy M. 
Published: August 2024

AbstractObjectiveThe Getting Older Adults Outdoors randomized trial showed a 10-week outdoor walk group (OWG) program was not superior to 10 weekly phone reminders on increasing physical and mental health; however, OWG attendance varied. This study examined whether a dose-response relationship existed between OWG attendance and improvement in physical and mental health among older adults with mobility limitations.MethodsWe analyzed data from 98 older adults randomized to a 10-week park-based OWG program. Participants were classified as attending 0–9, 10–15, and 16–20 OWG sessions based on attendance tertiles. Outcomes included change in scores on measures of walking endurance, comfortable and fast walking speed, balance, lower extremity strength, walking self-efficacy, and emotional well-being pre- to post-intervention.ResultsSeventy-nine older adults with complete information on the seven health outcomes were included (age=74.7±6.6 years, 72% female). Compared to those who attended 0–9 OWG sessions, participants attending 16–20 sessions exhibited a 52.7-meter greater improvement in walking endurance (95% CI:12.3, 93.1); 0.15-meter/second greater improvement in comfortable walking speed (95% CI:0.00, 0.29); and 0.17-meter/second greater improvement in fast walking speed (95% CI:0.02, 0.33). Higher attendance was also associated with higher odds of experiencing an improvement in walking self-efficacy (OR=4.03; 95% CI:1.05, 16.85) and fast walking speed (OR=9.00, 95% CI:1.59, 61.73). No significant dose-response relationships for balance, lower extremity strength, and emotional well-being were observed.ConclusionsHigher attendance in outdoor walking interventions is associated with greater improvements in walking endurance, walking speed, and walking self-efficacy among older adults with mobility limitations.
Evaluating Anti-LGBTQIA+ Medical Bias in Large Language Models
Authors: Chang Crystal T. , Srivathsa Neha , Bou-Khalil Charbel , Swaminathan Akshay , Lunn Mitchell R. , Mishra Kavita , Daneshjou Roxana , Koyejo Sanmi 
Published: August 2024

AbstractFrom drafting responses to patient messages to clinical decision support to patient-facing educational chatbots, Large Language Models (LLMs) present many opportunities for use in clinical situations. In these applications, we must consider potential harms to minoritized groups through the propagation of medical misinformation or previously-held misconceptions. In this work, we evaluate the potential of LLMs to propagate anti-LGBTQIA+ medical bias and misinformation. We prompted 4 LLMs (Gemini 1.5 Flash, Claude 3 Haiku, GPT-4o, Stanford Medicine Secure GPT (GPT-4.0)) with a set of 38 prompts consisting of explicit questions and synthetic clinical notes created by medically trained reviewers and LGBTQIA+ health experts. The prompts explored clinical situations across two axes: (i) situations where historical bias has been observed vs. not observed, and (ii) situations where LGBTQIA+ identity is relevant to clinical care vs. not relevant. Medically trained reviewers evaluated LLM responses for appropriateness (safety, privacy, hallucination/accuracy, and bias) and clinical utility. We find that all 4 LLMs evaluated generated inappropriate responses to our prompt set. LLM performance is strongly hampered by learned anti-LGBTQIA+ bias and over-reliance on the mentioned conditions in prompts. Given these results, future work should focus on tailoring output formats according to stated use cases, decreasing sycophancy and reliance on extraneous information in the prompt, and improving accuracy and decreasing bias for LGBTQIA+ patients and care providers.