bluuebunny/crossref_metadata_2025_split huggingface dataset:
Habitat selection during dispersal reduces the energetic cost of transport when making large displacements
Authors: de Boer Tullio , Farine Damien R. , Klarevas-Irby James A. 
Published: November 2023

AbstractWhen dispersing, individuals typically have to make large displacements. While previously thought to be costly, recent work has suggested that individuals can largely mitigate these costs by expressing distinct movement strategies—moving faster and straighter—during dispersal. Several studies have also found that individuals express differences in their habitat preferences during dispersal. These preferences often involve an increased use of open habitats relative to their non-dispersing habitat selection, within which individuals typically achieve larger displacements per unit of time. As a result, it has been suggested, but never explicitly tested, that changes in habitat selection could reflect an increased preference for habitats that facilitate greater energetic efficiency in terms of movement. Here, we combine step-selection analysis with models of the energetics of movement to determine whether actively dispersing vulturine guineafowl (Acryllium vulturinum) select different habitats relative to their non-dispersing counterparts, and whether their habitat preferences correspond to a decrease in the cost of transport. Our results confirm that fine-scale differences in habitat preferences expressed when making large displacements during the transient stage of dispersal correspond with an increase in the energetic efficiency of movement. These findings highlight the ability for animals to exhibit adaptive movement strategies across different axes of decision-making (e.g., where and how to move) to overcome different ecological challenges.
AptaDiff: de novo design and optimization of aptamers based on diffusion models
Authors: Wang Zhen , Liu Ziqi , Zhang Wei , Li Yanjun , Feng Yizhen , Lv Shaokang , Diao Han , Luo Zhaofeng , Yan Pengju , He Min , Li Xiaolin 
Published: November 2023

AbstractAptamers are single-stranded nucleic acid ligands, featuring high affinity and specificity to target molecules. Traditionally they are identified from large DNA/RNA libraries using in vitro methods, like Systematic Evolution of Ligands by Exponential Enrichment (SELEX). However, these libraries capture only a small fraction of theoretical sequence space, and various aptamer candidates are constrained by actual sequencing capabilities from the experiment. Addressing this, we proposed AptaDiff, the first in silico aptamer design and optimization method based on the diffusion model. Our Aptadiff can generate aptamers beyond the constraints of high-throughput sequencing data, leveraging motif-dependent latent embeddings from variational autoencoder, and can optimize aptamers by affinity-guided aptamer generation according to Bayesian optimization. Comparative evaluations revealed AptaDiff’s superiority over existing aptamer generation methods in terms of quality and fidelity across four high-throughput screening data targeting distinct proteins. Moreover, Surface Plasmon Resonance (SPR) experiments were conducted to validate the binding affinity of aptamers generated through Bayesian optimization for two target proteins. The results unveiled a significant boost of 87.9% and 60.2% in RU values, along with a 3.6-fold and 2.4-fold decrease in KD values for the respective target proteins. Notably, the optimized aptamers demonstrated superior binding affinity compared to top experimental candidates selected through SELEX, underscoring the promising outcomes of our AptaDiff in accelerating the discovery of superior aptamers.Key PointsWe proposed AptaDiff, the first in silico aptamer design method based on the diffusion model. Aptadiff can generate aptamers beyond the constraints of high-throughput sequencing data.Aptadiff can optimize aptamers through affinity-guided generation via Bayesian optimization within a motif-dependent latent space, and the affinity of the optimized aptamers to the target protein is better than the best experimental candidate from traditional SELEX screening.Aptadiff consistently outperforms the current state-of-the-art method in terms of quality and fidelity across high-throughput screening data targeting distinct proteins.
Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach
Authors: Addo Gideon , Yeboah Bismark Amponsah , Obuobi Michael , Doh-Nani Raphael , Mohammed Seidu , Amakye David Kojo 
Published: November 2023

ABSTRACTBackgroundDiabetes is a serious and progressive medical condition demanding efficient diagnostic methods, especially since its associated symptoms overlap with the symptoms of other medical conditions. While various studies have explored early detection of diabetes across different age groups, there is a notable gap in specific attention to middle-aged adults. This study explicitly focused on this demographic, aiming to assess associations between symptoms and diabetes status, investigate the relevance and relative influence of certain symptomatic and demographic features in the prediction of diabetes, and identify the most efficient machine learning (ML) model for predicting diabetes.MethodsUtilizing a dataset from a previous study conducted in the Sylhet Diabetes Hospital in Bangladesh, India, comprising 520 participants, including both diabetic and non-diabetic patients, we extracted and analyzed demographic and symptom-related information from 296 middle-aged adults aged from 40 to 60 years. Employing chi-square tests, we evaluated symptom-diabetes associations, while utilizing the Boruta algorithm to investigate symptom importance and influence. Seven ML models namely, K-Nearest Neighbor (KNN), Naïve Bayes (NB) classifier, Support Vector Machines with linear, polynomial, and radial basis function kernels, Random Forest (RF) classifier, and Logistic Regression were then assessed for optimal predictive performance.ResultsOut of the 296 participants of this study, 179 (60%) were diabetic. Significant associations were found between diabetes status in middle-aged adults and symptoms such as polyuria, polydipsia, weakness, sudden weight loss, partial paresis, polyphagia, and visual blurring, as confirmed by the p-values of their respective chi-square tests. All features studied, including demographics and symptoms, were confirmed as relevant for predicting diabetes in middle-aged adults. Notably, polyuria, polydipsia, gender, alopecia, irritability, and sudden weight loss were identified as the most influential features. Among the seven ML models, RF showed the highest sensitivity (98.59%), while KNN excelled in specificity (97.83%). RF demonstrated the best accuracy (96.58%) and area under the curve score (96.00%), making it the most efficient ML model for predicting diabetes among middle-aged adults.ConclusionThe findings of this study emphasize the importance of using diabetes-related symptoms for early detection of diabetes within the middle-aged adult population. The RF model demonstrated robust diagnostic capabilities, emphasizing its potential in predicting diabetes in middle-aged adults. Further exploration of genetic, lifestyle, and environmental factors is warranted to enhance the understanding and diagnostic accuracy in this demographic.
Obesity Prevention Efforts in France, Italy, and Japan - A Scoping Review Protocol
Authors: Hammad Nour M. , Tobias DeirDre K. 
Published: November 2023

AbstractBackgroundPopulation-level prevention efforts in the US have yet to correct the upward trends in increasing US obesity prevalence. Italy, France, and Japan are high-income countries that have employed approaches aimed at obesity prevention that may have contributed to their favorable obesity trends. It is plausible that these efforts could be culturally adapted with similar effectiveness to the US population. This paper outlines the protocol of a scoping review that will identify and characterize the range of obesity prevention efforts implemented in Italy, France, and Japan to inform potential strategies for obesity prevention in the US.Methods and analysisWe will conduct a systematic search in PubMed, Embase, and Cochrane. We will assess articles that describe any national, regional, or local public health and/or clinical guideline, recommendation, intervention, campaign, policy or other population-level effort targeting obesity prevention in Italy, France, and Japan. Two independent reviewers will screen the articles, and a third independent reviewer will resolve conflicts that arise upon screening. Descriptive synthesis will be performed to describe the country-specific prevention strategies and summarize the available evidence for their effectiveness.DiscussionThe purpose of this paper is to describe the study protocol for a scoping review that will provide a comprehensive summary of available evidence for obesity prevention strategies that have been implemented in Italy, France, and Japan. These strategies will inform potential prevention efforts for consideration in the US.Scoping review registration DOIhttps://doi.org/10.17605/OSF.IO/M35YX.
GMAC: A simple measure to quantify upper limb use from wrist-worn accelerometers
Authors: Balasubramanian Sivakumar 
Published: November 2023

AbstractVarious measures have been proposed to quantify upper-limb use through wrist-worn inertial measurement units. The two most popular traditional measures of upper-limb use – thresholded activity counts (TAC) and the gross movement (GM) score suffer from high sensitivity and specificity, respectively. We had previously proposed a hybrid version of these two measures – the GMAC – that showed better overall detection performance. However, the previously proposed GMAC used both accelerometer and gyroscope data and used the same parameter values from the TAC and GM measures. In this paper, we aim to answer two important questions to improve the usefulness of the GMAC measure: (a) can the GMAC measure be implemented using only the accelerometer data? (b) what are the optimal parameter values for the GMAC measure? We propose a modified version of the GMAC that works with only accelerometer data, and optimize this measure’s parameters. This optimized GMAC showed better detection performance than the previously proposed GMAC and surprisingly had comparable performance to that of the best-performing machine learning-based measure (random forest inter-subject model). Although intra-subject machine learning-based measures perform better than the optimized GMAC, the latter is simpler, well suited for real-time upper-limb use detection, and is the best option when a trained machine learning-based intra-subject model or labeled data is unavailable. The optimized GMAC measure can be a useful measure for either offline detection or for real-time detection and feedback of upper limb use.
SPECTRE: standardized global spatial data on terrestrial SPECies ThREats
Authors: Branco Vasco V. , Correia Luís , Cardoso Pedro 
Published: November 2023

AbstractMotivationSPECTRE is an open-source database containing standardised spatial data on global environmental and anthropogenic variables that are potential threats to terrestrial species and ecosystems. Its goal is to allow users to swiftly access spatial data on multiple threats at a resolution of 30 arc-seconds for all terrestrial areas. Following the standard set by Worldclim, this data allows full comparability and ease of use under common statistical frameworks for global change studies, species distribution modelling, threat assessments, quantification of ecosystem services and disturbance, among multiple other uses. A web user interface, a persistent online repository, and an accompanying R package with functions for downloading and manipulating data are provided.Main types of variable containedSPECTRE is a GIS product with 24 geoTiff raster layers (with plans to expand in the near future) with an approximate 1 km2resolution.
De novoclustering of long-read amplicons improves phylogenetic insight into microbiome data
Authors: Hui Yan , Nielsen Dennis Sandris , Krych Lukasz 
Published: November 2023

AbstractLong-read amplicon profiling through read classification limits phylogenetic analysis of amplicons while community analysis of multicopy genes, relying on unique molecular identifier (UMI) corrections, often demands deep sequencing. To address this, we present a long amplicon consensus analysis (LACA) workflow employing multiplede novoclustering approaches based on sequence dissimilarity. LACA controls the average error rate of corrected sequences below 1% for the Oxford Nanopore Technologies (ONT) R9.4.1 and ONT R10.3 data, 0.2% for ONT R10.4.1, and 0.1% for high-accuracy ONT Duplex and Pacific Biosciences (PacBio) circular consensus sequencing (CCS) data in both simulated 16S rRNA and real 16-23S rRNA amplicon datasets. In high-accuracy PacBio CCS data, the clustering-based correction matched UMI correction, while outperforming 4×UMI correction in noisy ONT R10.3 and R9.4.1 data. Notably, LACA preserved phylogenetic fidelity in long operational taxonomic units and enhanced microbiome-wide phenotype characterization for synthetic mock communities and human vaginal samples.
Active microbial communities facilitate carbon turnover in brine pools found in the deep Southeastern Mediterranean Sea
Authors: Rubin-Blum Maxim , Makovsky Yizhaq , Rahav Eyal , Belkin Natalia , Antler Gilad , Sisma-Ventura Guy , Herut Barak 
Published: November 2023

AbstractDischarge of gas-rich brines fuels productive chemosynthetic ecosystems in the deep sea. In these salty, methanic and sulfidic brines, microbial communities adapt to specific niches along the physicochemical gradients. However, the molecular mechanisms that underpin these adaptations are not fully known. Using metagenomics, we investigated the dense (∼106cell ml-1) microbial communities that occupy small deep-sea brine pools found in the Southeastern Mediterranean Sea (1150 m water depth, ∼22°C, ∼60 PSU salinity, sulfide, methane, ammonia reaching millimolar levels, and oxygen usually depleted), reaching high productivity rates of 685 µg C L-1d-1ex-situ. We curated 266 metagenome-assembled genomes of bacteria and archaea from the several pools and adjacent sediment-water interface, highlighting the dominance of a singleSulfurimonas, which likely fuels its autotrophy using sulfide oxidation or inorganic sulfur disproportionation. This lineage may be dominant in its niche due to genome streamlining, limiting its metabolic repertoire, particularly by using a single variant of sulfide: quinone oxidoreductase. These primary producers co-exist with ANME-2c archaea that catalyze the anaerobic oxidation of methane. Other lineages can degrade the necromass aerobically (HalomonasandAlcanivorax), or anaerobically through fermentation of macromolecules (e.g., Caldatribacteriota, Bipolaricaulia, Chloroflexota, etc). These low-abundance organisms likely support the autotrophs, providing energy-rich H2, and vital organics such as vitamin B12.
General remarks of the secondary promoter element regulating the genome replication of paramyxo- and filoviruses
Authors: Ashida Shoichi , Kojima Shohei , Okura Takashi , Kato Fumihiro , Urata Shuzo , Matsumoto Yusuke 
Published: November 2023

AbstractParamyxo- and filovirus genomes are equipped with bipartite promoters at their 3’ ends to initiate RNA synthesis. The two elements, the primary promoter element 1 (PE1) and the secondary promoter element 2 (PE2), are separated by a spacer region that must be precisely a multiple of six nucleotides, indicating these viruses are related to the “rule of six”. However, our knowledge of PE2 has been limited to a narrow spectrum of virus species. In this study, a comparative analysis of 1,647 paramyxoviral genomes from a public database revealed that the paramyxovirus PE2 can be clearly categorized into two distinct subcategories: one marked by C repeats at every six bases (exclusive to the subfamilyOrthoparamyxovirinae), and another characterized by CG repeats every six bases (observed in the subfamiliesAvulavirinaeandRubulavirinae). This unique pattern collectively mirrors the evolutionary lineage of these subfamilies. Furthermore, we showed that the PE2 of theRubulavirinae, with the exception of mumps virus, serves as part of the gene-coding region. This may be due to the fact that theRubulavirinaeis the only paramyxovirus that cannot propagate without RNA editing occurring. Zaire ebolavirus has eight sequential uracil (U) repeats every six bases within its genomic promoter. We showed that a minimum of four sequential U-containing hexamer repeats is imperative for genome replication. This discovery led to the identification of such quadruplet U-containing hexamer repeats within the genomic and antigenomic promoters of other viruses within the familyFiloviridae.SignificanceThe genomic intricacies of paramyxo- and filoviruses are highlighted by the bipartite promoters—PE1 and PE2—at their 3’ termini. The spacer region between these elements follows the “rule of six”, crucial for genome replication. By a comprehensive analysis of paramyxoviral genome sequences, we identified distinct subcategories of PE2 based on C and CG repeats that were specific toOrthoparamyxovirinaeandAvulavirinae/Rubulavirinae, respectively, mirroring their evolutionary lineages. Notably, the PE2 ofRubulavirinaeis integrated in the gene-coding region, a unique trait potentially linked to its complete dependence on RNA editing for virus growth. This study also focused on the PE2 sequences in filovirus genomes. In filoviruses, four consecutive U-containing hexamer repeats appeared to be critical for their genome replication.
Loss of multi-level 3D genome organization during breast cancer progression
Authors: Rossini Roberto , Oshaghi Mohammadsaleh , Nekrasov Maxim , Bellanger Aurélie , Domaschenz Renae , Dijkwel Yasmin , Abdelhalim Mohamed , Collas Philippe , Tremethick David , Paulsen Jonas 
Published: November 2023

AbstractBreast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in anin vitromodel of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) are overall maintained, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing theMYConcogene is inserted into a highly active subcompartment on chromosome 10. This insertion is accompanied by the formation ofde novoenhancer contacts and activation ofMYC, illustrating how structural genomic variants can alter the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the loss of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.
Geographic variation in the songs of two closely related song-learning species, Anna’s and Costa’s hummingbird (Calypte anna, C. costae)
Authors: Berger A. N. , Ye W. Y. , Padilla A. S. , Gumbi B. C. , Clark C. J. , Campbell P. 
Published: November 2023

ABSTRACTIn species that learn their song, cultural transmission of song components can lead to the accumulation of variants that differ among populations, resulting in the formation of dialects. Three avian clades are thought to have independently evolved song learning – parrots, oscine passerines, and hummingbirds. Dialects have mainly been studied in passerines. We extend the study of dialects to the bee hummingbird clade, focusing on Anna’s and Costa’s hummingbirds (Calypte annaandC. costae). Both species are vocal learners. Anna’s produces complex, three phrase, multi-syllable songs and Costa’s produces simple, one phrase songs. We recorded 5-24 males per population (5 Costa’s and 6 Anna’s populations) across the species’ ranges in the Western United States and tested for evidence of geographic variation in song. We found minor population differences in frequency measures of Costa’s song, but song form was invariant across populations. Anna’s song was contrastingly variable with population differences in both syllable use and multiple spectral and temporal measures. The most strongly differentiated Anna’s population in our study, Seattle (Washington State), is the product of a recent northward range expansion facilitated by human activities that provide additional food sources for hummingbirds. The loss and modification of syllables in this population is suggestive of a founder effect on song. This study provides insight into song evolution in non-passerine vocal learners and contributes to understanding of how complex signals evolve.
Phytopathogenic cyclic glucohexadecaose from an inverting transglycosylase
Authors: Motouchi Sei , Komba Shiro , Nakai Hiroyuki , Nakajima Masahiro 
Published: November 2023

AbstractXanthomonasspecies contain numerous notoriously well-known plant pathogens. Among various pathogenic factors, the role of α-1,6-cyclized β-1,2-glucohexadecaose (CβG16α) produced byXanthomonas campestrispv.campestriswas shown previously to be vital for infecting model organismsArabidopsis thalianaandNicotiana benthamiana. However, enzymes responsible for biosynthesising CβG16α are essentially unknown, which limits the generation of agrichemicals that inhibit CβG16α synthesis. In this study, we discovered that OpgD fromX. campestrispv.campestrisconverts linear β-1,2-glucan to CβG16α. Structural and functional analyses revealed that OpgD fromX. campestrispv.campestrispossesses an anomer-inverting transglycosylation mechanism, which is unprecedented among carbohydrate-active enzymes. The discovery of this unprecedented glucan-generating mechanism reveals a new foundation for the enzymatic synthesis of carbohydrates. Furthermore, identifying CβG16α synthase highly conserved inXanthomonasprovides a broadly adaptable drug target for new-genre agrichemicals that overcome antimicrobial-resistant bacterial issues.