bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scalable CNN-based classification of selective sweeps using derived allele frequencies
Authors: van den Belt Sjoerd , Zhao Hanqing , Alachiotis Nikolaos 
Published: September 2024

Abstract

Motivation
Selective sweeps can successfully be distinguished from neutral genetic data using summary statistics and likelihood-based methods that analyze single nucleotide polymorphisms (SNPs). However, these methods are sensitive to confounding factors, such as severe population bottlenecks and old migration. By virtue of machine learning, and specifically convolutional neural networks (CNNs), new accurate classification models that are robust to confounding factors have been recently proposed. However, such methods are more computationally expensive than summary-statistic-based ones, yielding them impractical for processing large-scale genomic data. Moreover, SNP data are frequently preprocessed to improve classification accuracy, further exacerbating the long analysis times.

Results
To this end, we propose a 1D CNN-based model, dubbed FAST-NN, that does not require any preprocessing while using only derived allele frequencies instead of summary statistics or raw SNP data, thereby yielding a sample-size-invariant, scalable solution. We evaluated several data fusion approaches to account for the variance of the density of genetic diversity across genomic regions (a selective sweep signature), and performed an extensive neural architecture search based on a state-of-the-art reference network architecture (SweepNet). The resulting model, FAST-NN, outperforms the reference architecture by up to 12% inference accuracy over all challenging evolutionary scenarios with confounding factors that were evaluated. Moreover, FAST-NN is between 30× and 259× faster on a single CPU core, and between 2.0× and 6.2× faster on a GPU, when processing sample sizes between 128 and 1000 samples. Our work paves the way for the practical use of CNNs in large-scale selective sweep detection.

Availability and implementation
https://github.com/SjoerdvandenBelt/FAST-NN
Multi-task deep latent spaces for cancer survival and drug sensitivity prediction
Authors: Rintala Teemu J , Napolitano Francesco , Fortino Vittorio 
Published: September 2024

Abstract

Motivation
Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has driven many developments in drug development, however, there are important aspects crucial to precision medicine that are often overlooked, namely the inherent differences between tumours in patients and the cell-lines used to model them in vitro. Recent developments in transfer learning methods for patient and cell-line data have shown progress in translating results from cell-lines to individual patients in silico. However, transfer learning can be forceful and there is a risk that clinically relevant patterns in the omics profiles of patients are lost in the process.

Results
We present MODAE, a novel deep learning algorithm to integrate omics profiles from cell-lines and patients for the purposes of exploring precision medicine opportunities. MODAE implements patient survival prediction as an additional task in a drug-sensitivity transfer learning schema and aims to balance autoencoding, domain adaptation, drug-sensitivity prediction, and survival prediction objectives in order to better preserve the heterogeneity between patients that is relevant to survival. While burdened with these additional tasks, MODAE performed on par with baseline survival models, but struggled in the drug-sensitivity prediction task. Nevertheless, these preliminary results were promising and show that MODAE provides a novel AI-based method for prioritizing drug treatments for high-risk patients.

Availability and implementation
https://github.com/UEFBiomedicalInformaticsLab/MODAE.
Polyphest: fast polyploid phylogeny estimation
Authors: Yan Zhi , Cao Zhen , Nakhleh Luay 
Published: September 2024

Abstract

Motivation
Despite the widespread occurrence of polyploids across the Tree of Life, especially in the plant kingdom, very few computational methods have been developed to handle the specific complexities introduced by polyploids in phylogeny estimation. Furthermore, methods that are designed to account for polyploidy often disregard incomplete lineage sorting (ILS), a major source of heterogeneous gene histories, or are computationally very demanding. Therefore, there is a great need for efficient and robust methods to accurately reconstruct polyploid phylogenies.

Results
We introduce Polyphest (POLYploid PHylogeny ESTimation), a new method for efficiently and accurately inferring species phylogenies in the presence of both polyploidy and ILS. Polyphest bypasses the need for extensive network space searches by first generating a multilabeled tree based on gene trees, which is then converted into a (uniquely labeled) species phylogeny. We compare the performance of Polyphest to that of two polyploid phylogeny estimation methods, one of which does not account for ILS, namely PADRE, and another that accounts for ILS, namely MPAllopp. Polyphest is more accurate than PADRE and achieves comparable accuracy to MPAllopp, while being significantly faster. We also demonstrate the application of Polyphest to empirical data from the hexaploid bread wheat and confirm the allopolyploid origin of bread wheat along with the closest relatives for each of its subgenomes.

Availability and implementation
Polyphest is available at https://github.com/NakhlehLab/Polyphest.
GGTyper: genotyping complex structural variants using short-read sequencing data
Authors: Mirus Tim , Lohmayer Robert , Döhring Clementine , Halldórsson Bjarni V , Kehr Birte 
Published: September 2024

Abstract

Motivation
Complex structural variants (SVs) are genomic rearrangements that involve multiple segments of DNA. They contribute to human diversity and have been shown to cause Mendelian disease. Nevertheless, our abilities to analyse complex SVs are very limited. As opposed to deletions and other canonical types of SVs, there are no established tools that have explicitly been designed for analysing complex SVs.

Results
Here, we describe a new computational approach that we specifically designed for genotyping complex SVs in short-read sequenced genomes. Given a variant description, our approach computes genotype-specific probability distributions for observing aligned read pairs with a wide range of properties. Subsequently, these distributions can be used to efficiently determine the most likely genotype for any set of aligned read pairs observed in a sequenced genome. In addition, we use these distributions to compute a genotyping difficulty for a given variant, which predicts the amount of data needed to achieve a reliable call. Careful evaluation confirms that our approach outperforms other genotypers by making reliable genotype predictions across both simulated and real data. On up to 7829 human genomes, we achieve high concordance with population-genetic assumptions and expected inheritance patterns. On simulated data, we show that precision correlates well with our prediction of genotyping difficulty. This together with low memory and time requirements makes our approach well-suited for application in biomedical studies involving small to very large numbers of short-read sequenced genomes.

Availability and implementation
Source code is available at https://github.com/kehrlab/Complex-SV-Genotyping.
Graspot: a graph attention network for spatial transcriptomics data integration with optimal transport
Authors: Gao Zizhan , Cao Kai , Wan Lin 
Published: September 2024

Abstract

Summary
Spatial transcriptomics (ST) technologies enable the measurement of mRNA expression while simultaneously capturing spot locations. By integrating ST data, the 3D structure of a tissue can be reconstructed, yielding a comprehensive understanding of the tissue’s intricacies. Nevertheless, a computational challenge persists: how to remove batch effects while preserving genuine biological structure variations across ST data. To address this, we introduce Graspot, a graph attention network designed for spatial transcriptomics data integration with unbalanced optimal transport. Graspot adeptly harnesses both gene expression and spatial information to align common structures across multiple ST datasets. It embeds multiple ST datasets into a unified latent space, facilitating the partial alignment of spots from different slices. Demonstrating superior performance compared to existing methods on four real ST datasets, Graspot excels in ST data integration, including tasks that require partial alignment. In particular, Graspot efficiently integrates multiple ST slices and guides coordinate alignment. In addition, Graspot accurately aligns the spatio-temporal transcriptomics data to reconstruct human heart developmental processes.

Availability and implementation
Graspot software is available at https://github.com/zhan009/Graspot.
Establishing the size and configuration of the imaging support workforce: a census of national workforce data in England
Authors: Nightingale Julie , Etty Sarah , Snaith Beverley , Sevens Trudy , Appleyard Rob , Kelly Shona 
Published: September 2024

Abstract

Objectives
The imaging support workforce is a key enabler to unlock imaging capacity and capability, yet no evidence exists of the workforce size and configuration. This research provides the first comprehensive analysis of workforce data to explore the deployment of the support workforce within National Health Service (NHS) imaging services in England.

Methods
Using a census methodology, an anonymised Electronic Staff Record (ESR) data set extracted in December 2022 was analysed to identify support workers and their employment bandings at NHS Trust, regional and national (England) level. Support workforce proportions, median values and Spearman’s Rank correlations were calculated.

Results
Analysis of 137 NHS Trusts, comprising 100% of Acute Trusts (n = 124) and Specialist Trusts with imaging services (n = 13), identified that the support workforce (pay bands 2-4) constitutes 23.6% of the imaging staff base. Ranking Trusts into three categories based on the proportion of support workers in their imaging establishment, median values ranged from 30.7% (high), to 22.2% (medium) and 10.5% (low). Two opposing deployment models of Band 2 and Band 3 support workers were identified.

Conclusions
Comprising almost one quarter of the imaging establishment, models of deployment at Bands 2 and 3 are highly variable. Assistant practitioners (Band 4) are under-utilised, providing an opportunity to introduce innovations to address workforce demands.

Advances in knowledge
This census is the first to provide evidence of the size and structure of the support workforce, the first step in enabling effective workforce transformation. Further research is required to explain the two opposing deployment models.
Attract and kill trees? No simple solution for Anoplophora glabripennis (Coleoptera: Cerambycidae) control
Authors: Sun Zuo-Xiang , Sun Hui-Quan , Zhong Qiu-Mei , Shao Peng-Peng , Su Zhi , Wang Zhuo , Liu Yu-Ting , Wei Jian-Rong 
Published: September 2024

Abstract
Anoplophora glabripennis (Motschulsky), the Asian longhorned beetle, is a serious wood-boring pest of hardwood trees. There have been records that suggest Elaeagnus angustifolia L. (Elaeagnaceae) might be an “attract and kill” tree species for A. glabripennis, i.e., a tree that is attractive to A. glabripennis adults but kills their oviposited eggs. To evaluate the possibility of E. angustifolia as a control measure for A. glabripennis, we carried out a series of behavioral experiments in the laboratory and in the field. Results showed that: (i) A. glabripennis females preferred E. angustifolia branches and leaves over poplar tree species evaluated; the weight of feces from both female and male A. glabripennis feeding on E. angustifolia was significantly higher than from those feeding on Populus deltoides ‘Shalinyang’ or Populus alba. L. var. pyramidalis; (ii) the average lifespan of females and males feeding on E. angustifolia was significantly longer than those feeding on other host trees evaluated; (iii) in the laboratory oviposition choice experiment, there were significantly fewer egg notch grooves on E. angustifolia than on P. deltoides ‘Shalinyang‘, and those made in E. angustifolia were without eggs; (iv) in the field, the number of egg notch grooves on E. angustifolia was 43.6 ± 18.1 per stem, but the number of eggs laid was only 14.4 ± 6.4 per stem; and (v) Field surveys of existing mixed forests showed that when E. angustifolia was planted with P. alba. var. pyramidalis or Populus simonii × (Populus pyramidalis + Salix matsudana) ‘Poparis’ in the mixed forest, both poplar varieties suffered greater infestation than E. angustifolia. Therefore, E. angustifolia is not a suitable attract and kill tree to be extensively planted in mixed forests for control of A. glabripennis.
Rethinking AI: bias in speech-recognition chatbots for ELT
Authors: Jeon Jaeho , Lee Seongyong , Coronel-Molina Serafín M 
Published: September 2024

Abstract
Artificial intelligence (AI) technologies, particularly chatbots with speech-recognition, are gaining attention as tools for ELT. However, this frontline development in contemporary ELT seems to stand in stark contrast to the multilingual effort, another innovative trend, as chatbots’ speech recognition capabilities are primarily attuned to native English speaker pronunciation. Addressing this concern, this study adopted a Global Englishes (GE) perspective and examined students’ attitudes toward English after their use of a speech-recognition chatbot. Text-mining analysis of reflection papers from 38 students and thematic analysis of interviews with seven students revealed that the chatbot hindered the incorporation of diverse English use into ELT and students expressed a conception of English not as a language in flux but rather as a subject with specific content to be mastered. The findings are discussed concerning GE, AI ethics, and computer-assisted language learning, and implications for future chatbot use in ELT are provided.
Age structure and age heaping: solving Ireland’s post-famine digit preference puzzle
Authors: Colvin Christopher L , Henderson Stuart , Mclaughlin Eoin 
Published: September 2024

Abstract
The quality of age reporting in Ireland worsened in the years after the 1845–1852 Great Irish Famine, even as measures of educational attainment improved. We show how Ireland’s age structure partly accounts for this seemingly conflicting pattern. Specifically, we argue that a greater propensity to emigrate typified the youngest segment (23–32-year-olds) used in conventional indices of age heaping. Any quantification of age heaping patterns must therefore be interpreted considering an older underlying population which is inherently more likely to heap. We demonstrate how age heaping indices can adjust for such demographic change by introducing age standardization.
Genomic Diversity Illuminates the Environmental Adaptation of Drosophila suzukii
Authors: Feng Siyuan , DeGrey Samuel P , Guédot Christelle , Schoville Sean D , Pool John E 
Published: September 2024

Abstract
Biological invasions carry substantial practical and scientific importance and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pest Drosophila suzukii using whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of the D. suzukii genome, its diversity and its evolution, and we identify an appropriate genotype–environment association pipeline for our dataset. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as the prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.
A Systematic Review and Meta-Analysis of the Association Between Physical Capability, Social Support, Loneliness, Depression, Anxiety, and Life Satisfaction in Older Adults
Authors: Sulandari Santi , Coats Rachel O , Miller Amy , Hodkinson Alexander , Johnson Judith 
Published: September 2024

Abstract

Background and Objectives
Physical capability, social support, loneliness, depression, and anxiety predict life satisfaction in older adults. Currently, no systematic review and meta-analysis have been conducted to investigate the strength of these associations globally. Therefore, this study quantified the strength of these associations.

Research Design and Methods
A systematic literature search was conducted using MEDLINE, EMBASE, APA PsycINFO, Web of Science, and Scopus. We included observational studies assessing the association between physical capability, social support, loneliness, depression, and anxiety with life satisfaction in adults aged 65+.

Results
In total, 10,552 articles were identified, of which 78 studies in 164,478 participants were included in the systematic review and 57 were included in the meta-analysis. Greater life satisfaction was significantly associated with greater physical capabilities (odds ratio [OR] = 2.64; 95% confidence interval [CI]: 2.01–3.45; p &lt; .001, k = 35, n = 33,732), higher social support (OR = 3.27; 95% CI: 2.59–4.13, k = 20 studies, n = 13,228), reduced loneliness (OR = 3.30; 95% CI: 2.53–4.30, k = 11, n = 33,638), depression (OR = 4.76; 95% CI: 3.10–7.32, k = 24, n = 64,097), and anxiety (OR = 5.10; 95% CI: 2.21–11.78, k = 5, n = 43,368). The strength of associations did not vary between Western and Eastern countries, year of publication, or quality. Gender was a moderator: Loneliness was more strongly associated with life satisfaction in females. Age was also a moderator; the association between social support and life satisfaction weakened with increasing age.

Discussion and Implications
Improving the physical capabilities of older individuals, fostering social support, and alleviating feelings of loneliness, depression, and anxiety may help build life satisfaction in older individuals, which policy-makers and healthcare professionals should prioritize when implementing strategies.
Investigation in yeast of novel variants in mitochondrial aminoacyl-tRNA synthetases WARS2, NARS2, and RARS2 genes associated with mitochondrial diseases
Authors: Figuccia Sonia , Izzo Rossella , Legati Andrea , Nasca Alessia , Goffrini Paola , Ghezzi Daniele , Ceccatelli Berti Camilla 
Published: September 2024

Abstract
Aminoacyl-transfer RiboNucleic Acid synthetases (ARSs) are essential enzymes that catalyze the attachment of each amino acid to their cognate tRNAs. Mitochondrial ARSs (mtARSs), which ensure protein synthesis within the mitochondria, are encoded by nuclear genes and imported into the organelle after translation in the cytosol. The extensive use of next generation sequencing (NGS) has resulted in an increasing number of variants in mtARS genes being identified and associated with mitochondrial diseases. The similarities between yeast and human mitochondrial translation machineries make yeast a good model to quickly and efficiently evaluate the effect of variants in mtARS genes. Genetic screening of patients with a clinical suspicion of mitochondrial disorders through a customized gene panel of known disease-genes, including all genes encoding mtARSs, led to the identification of missense variants in WARS2, NARS2 and RARS2. Most of them were classified as Variant of Uncertain Significance. We exploited yeast models to assess the functional consequences of the variants found in these genes encoding mitochondrial tryptophanyl-tRNA, asparaginyl-tRNA, and arginyl-tRNA synthetases, respectively. Mitochondrial phenotypes such as oxidative growth, oxygen consumption rate, Cox2 steady-state level and mitochondrial protein synthesis were analyzed in yeast strains deleted in MSW1, SLM5, and MSR1 (the yeast orthologues of WARS2, NARS2 and RARS2, respectively), and expressing the wild type or the mutant alleles. Pathogenicity was confirmed for most variants, leading to their reclassification as Likely Pathogenic. Moreover, the beneficial effects observed after asparagine and arginine supplementation in the growth medium suggest them as a potential therapeutic approach.
Thermal comfort in different building forms and operation conditions—case study of Ningbo dental treatment rooms
Authors: Ma Siyu , Lu Hanyue , Deng Wu , Lu Jun , Zhou Tongyu , Zhang Huayan 
Published: September 2024

Abstract
The research on indoor thermal comfort has extensively covered office, educational, and residential buildings, but healthcare facilities have been relatively overlooked. This study compared and analyzed the annual dynamic thermal comfort of six dental treatment rooms with different building forms and operation conditions through on-site surveys and EnergyPlus simulations. The results indicated that due to the significant internal heat gain of the dental equipment, treatment rooms with excellent insulation performance may paradoxically experience severe overheating issues during the cooling and free-running seasons. The findings can be used to provide empirical data to support dental treatment spaces design in Ningbo.
Lifeguard Pharmacy: the co-development of a new community pharmacy response service for people in danger from domestic abuse or suicidal ideation
Authors: Barcelos Ana Maria , Latham-Green Tracey , Barnes Rebecca , Gorton Hayley , Gussy Mark , Henderson Claire , Khatri Mahomed , Knapp Peter , Solomon Josie 
Published: September 2024

Abstract

Background
Domestic abuse (DA) and suicidal ideation (SI) are prevalent and often co-occur. Numerous practical and psychosocial barriers inhibit help-seeking, including accessibility and confidentiality concerns. Pharmacies are accessible and may be perceived as a discreet venue for a DA and SI response service.

Objective
To co-develop a community pharmacy response service for people experiencing domestic abuse or suicidal ideation.

Methods
Overall, 36 unique individuals contributed at least once to a series of focus groups, interviews or workshops to co-develop the service components. Participants had lived experience of DA/SI or were professionals from DA/SI support services or pharmacies. Audio recordings and field notes from events were thematically analysed. Specific themes were identified and informed the development of the service components.

Key findings
Participants supported the development of this new service and considered community pharmacies to be an ideal setting. They thought of the service as a lifeline, that would offer hope. Under this main concept of hope, five main themes were identified: Safety, Empathy, Empowerment, Equity, and Discretion. Participants’ practical considerations were incorporated into the service design, including the name choice of “Lifeguard Pharmacy”, the strapline “Bringing Hope to Life”, and the development of a “Client Flowchart” outlining how to welcome a client, arrange for a consultation, and then guide clients out of the pharmacy afterwards.

Conclusions
Overall, the findings supported the development and introduction of this pharmacy-based intervention, which may help overcome barriers to help-seeking for DA or SI due to its sense of hope, accessibility, and discretion.