bluuebunny/crossref_metadata_2025_split huggingface dataset:
A simple model of population dynamics with beneficial and harmful interaction networks for empirical applications
Authors: Bimler Malyon D. , Pascal Luz Valerie , Adams Matthew P. , Baker Chris 
Published: October 2024

AbstractPopulation dynamic models can forecast changes in the abundances of multiple interconnected species, which makes them potentially powerful tools for managing ecological communities, yet they remain largely under-utilised in applied settings. High data requirements and the ability to only model a narrow range of ecological interactions and/or trophic levels together limits their usefulness when faced with complex and data-poor systems, where beneficial (e.g. mutualism) and harmful (e.g. competition) interactions may operate simultaneously within and between species.We present a model of population dynamics that can describe a wide range of ecological interaction outcomes with a simple, unified structure. Species growth rates are constrained by a maximum growth rate parameter which prevents the risk of population explosions even in the case of mutualism. Species interactions are defined by two, not mutually-exclusive interactions matrices that describe the effects of beneficial and harmful interactions respectively, together providing the potential for the net effect of interactions between one species and another to switch from beneficial to harmful as population density increases.This model recreates classic dynamics in two-species mutualistic, competitive, and predator-prey scenarios, allowing us to model a wide range of trophic levels and interaction types together within the same equation. The maximum growth rate parameter, theoretically based in intrinsic constraints on reproduction, can be parameterised from a wide range of sources including natural history, historical data, and breeding programs. We illustrate the potential of this model with a data-poor case study of a threatened species and two interacting predators.This new model is generaliseable to a wide range of natural ecological communities. Its model structure lowers data requirements whilst remaining intuitive and biologically realistic, making it an accessible option for predicting community-wide population changes in applied contexts where data is sparse and/or uncertain.
Design, rationale, and baseline characteristics of the SONIC-HF multicenter registry
Authors: Kagiyama Nobuyuki , Kamiya Kentaro , Toki Misako , Saito Hiroshi , Iwata Kentaro , Matsue Yuya , Yoshioka Kenji , Saito Kazuya , Murata Azusa , Hayashida Akihiro , Ako Junya , Kitai Takeshi , Maekawa Emi 
Published: October 2024

AbstractBackgroundSkeletal muscle mass and function are crucial for assessing physical frailty, sarcopenia, and cachexia, which significantly impact the prognosis of geriatric patients with heart failure (HF). Ultrasound-based assessment of skeletal muscles offers a non-invasive, real-time alternative to traditional methods. ThecompariSON of various methods In evaluatIon of sarCopenia in patients with Heart Failurestudy (SONIC-HF) aimed to evaluate the feasibility and prognostic impact of ultrasound-based muscle assessment in geriatric patients with HF.MethodsThis multicenter, prospective cohort study enrolled HF patients aged ≥65 years who could ambulate independently at discharge. Certified observers assessed muscle thickness (biceps, quadriceps, rectus femoris, and diaphragm) using ultrasound at rest and during contraction. The primary endpoint was all-cause mortality. Secondary endpoints included HF hospitalization, unplanned hospital visits, and cardiovascular and non-cardiovascular mortality.ResultsOf the 692 enrolled patients (median age 81 (IQR 74–86) years, 57.6% female, left ventricular ejection fraction 45% (32%–60%)), ultrasound-based muscle assessments were completed in 606 patients. Interobserver reliability was excellent (intraclass correlation coefficient 0.84–0.99). Median muscle thicknesses at rest and during contraction were: diaphragm 1.9 (1.6–2.3) mm and 2.9 (2.3–3.8) mm; biceps 19.6 (15.9–23.1) mm and 25.3 (21.3–29.5) mm; quadriceps 19.0 (15.0–23.5) mm and 24.8 (19.9–29.5) mm; rectus femoris 9.7 (7.1–12.3) mm and 12.1 (9.6–15.0) mm. The median follow-up time was 733.5 (438–882) days.ConclusionsThe SONIC-HF registry will provide valuable insights into the feasibility and prognostic implications of ultrasound-based muscle assessment in geriatric patients with HF.
Imaging, Pulmonary Function, and Histopathologic Findings of Persistent Fibrosis in a Longitudinal Cohort Three Years after Severe COVID-19 Infection
Authors: Murphy Scarlett O. , McGroder Claire F. , Salvatore Mary M. , D’Souza Belinda M. , Capaccione Kathleen M. , Saqi Anjali , Shaikh Faisal , Benesh Shannon , Zhang David , Baldwin Matthew R. , Garcia Christine Kim 
Published: October 2024

ABSTRACTFibrotic-like abnormalities are present in 60% of a single-center, longitudinal, multi-ethnic cohort 3-years after severe COVID-19. They are independently associated with male sex, low BMI, shorter telomere length, increased severity of illness, and mechanical ventilation; Black race and asthma are protective. Participants with fibrotic-like abnormalities are more likely to have reduced diffusion capacity and 6-minute walk distance. Fibrotic-like abnormalities persist but modestly improve over time. Transbronchial biopsies show small airways histopathology, consistent with high prevalence of air trapping in expiration, and infrequent interstitial thickening. This study highlights the need for continued monitoring of patients with persistent fibrosis after severe COVID-19.
Incidence and prevalence of euthanasia in Belgium. A study using administrative data on all cases of euthanasia reported between 2002 and 2023
Authors: Wels Jacques , Hamarat Natasia 
Published: October 2024

SummaryBackgroundReported assisted dying cases have increased in countries with such legislation. In Belgium, where euthanasia was legalized in 2002, cases rose from 236 in 2003 to 3,423 in 2023. While most studies focus on occurrence rates, this study examines the magnitude of increase and the contribution of demographic changes observed over the period.MethodsWe analysed complete data from the Belgian Federal Commission for the Control and Evaluation of Euthanasia (FCCEE) from 2002-2023 (N=33,604). Using Poisson regression, we calculated Rate Ratios (RR) by age, gender, region, and euthanasia characteristics. We compared estimates with a model that included demographic offsets to calculate Prevalence Rates (PR) and explored interaction effects across sub-categories.ResultsThe yearly RR is 1.070, while the PR is 1.054, indicating that demographic changes significantly influence the observed increase. The PR for euthanasia among females has slightly risen (PR: 1.034), while psychiatric cases remained a small proportion (PR: 1.002). Cases citing multimorbidity have increased (RR: 1.029), whereas cases related to psychiatric disorders (PR: 0.949) and deaths in care homes (PR: 0.998) have not shown significant increases. Higher prevalence is observed in the Flemish region (PR: 1.983) but the gap has narrowed over the years.InterpretationA substantial part of the increase in euthanasia cases is attributed to demographic changes, particularly population ageing. Early increases were mainly due to the regulatory onset, while recent trends reflect a growing influence of demographic factors and regional adjustments. Considering demographic shifts is essential and long-term trends should be monitored.FundingERC (UHealth), FNRS-CQ
Pipeline to explore information on genome editing using large language models and genome editing meta-database
Authors: Suzuki Takayuki , Bono Hidemasa 
Published: October 2024

ABSTRACTGenome editing (GE) is widely recognized as an effective and valuable technology in life sciences research. However, certain genes are difficult to edit depending on some factors such as the type of species, sequences, and GE tools. Therefore, confirming the presence or absence of GE practices in previous publications is crucial for the effectively design and establishment of research using GE. Although the Genome Editing Meta-database (GEM:https://bonohu.hiroshima-u.ac.jp/gem/) aims to provide as comprehensive GE information as possible, it does not indicate how each registered gene is involved in GE. In this study, we developed a systematic method for extracting essential GE information using large language models from the information based on GEM and GE-related articles. This approach allows for a systematic and efficient investigation of GE information that cannot be achieved using the current GEM alone. In addition, by converting the extracted GE information into metrics, we propose a potential application of this method to prioritize genes for future research. The extracted GE information and novel GE-related scores are expected to facilitate the efficient selection of target genes for GE and support the design of research using GE.Database Tool URLs:https://github.com/szktkyk/extract_geinfo,https://github.com/szktkyk/visualize_geinfo
Skin Hydration By Natural Moisturizing Factors, A Story Of H-Bond Networking
Authors: Martin Marving , Chantemargue Benjamin , Trouillas Patrick 
Published: October 2024

AbstractDry skin is a common condition experienced by many. Besides being particularly present during the cold season, various diseases exist all year round, leading to localized xerosis. To prevent it, the skin is provided with natural moisturizing factors (NMFs). They are small amino acids or derivatives found in the outermost layer of the skin, thestratum corneum(SC). They are often claimed to be highly efficient humectants, increasing the water content to maintain the fluidity of the skin. However, alternative mechanisms have been proposed, suggesting that NMFs themselves may act as lipid mobility amplifiers. This work aims at investigating the role of three NMFs, namely urea (URE), glycerol (GLY) and urocanic acid / urocanate (UCA/UCO) in SCin silicomodels, considering two different levels of humidity. Molecular dynamic simulations showed an increase in the diffusion of different lipid components, mainly free fatty acids (FFAs) and ceramides acyl chain moieties, in the presence of either high water content or NMFs. The membrane properties were modified, as seen by an increased thickness and a greater lateral stiffness. All NMFs exhibited a similar impact, whereas UCA revealed slight differences according to its charged state. By studying NMF-water intermolecular interactions, we highlighted the role of NMF as a regulator of membrane perturbations, while insuring membrane fluidity. This role allows NMFs to prevent destabilization of the skin membrane in the presence of high-water content. This study, performed at an atomistic resolution, highlighted a strong H-bond network between lipids, involving mainly ceramides but also all other components. This network can be modified in the presence of high-water concentration or NMFs, resulting in modifications of membrane properties, rationalizing hydration effects.
ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncoverin vitro-enriched cell types
Authors: Dolgos Robin , Parmentier Romuald , Wang Jing , Servant Raphaëlle , Templeton Arnoud J. , Zellweger Tobias , Lamb Alastair D. , Mertz Kirsten D. , Subotic Svetozar , Vlajnic Tatjana , Seifert Helge , Mortezavi Ashkan , Rentsch Cyrill A. , Bubendorf Lukas , Le Magnen Clémentine 
Published: October 2024

AbstractPatient-derived organoids (PDOs) offer new opportunities to model various cancers. However, their application in prostate cancer (PCa) has been hampered by poor success rates and overgrowth of cell types which are not representative of the patient samples. By exploiting a cohort of 164 PCa patient samples and tuning several culture parameters, we show that an extracellular matrix-free (ECM)-free culture system increases the take-rate of PDOs with luminal-like and PCa features. Single-cell RNA sequencing (scRNA-seq) reveals that ECM-free PDOs comprise cell populations associated with known PCa signatures and exhibit transcriptomic resemblance with their respective parental tumors. In addition, we define organoid-associated cell type signatures and identify markers discriminating tumorsversusbenign cellsex vivoandin situ. Furthermore, we generate the first prostate PDO single-cell atlas integrating previously-published scRNA-seq datasets and our newly- generated data. We show that Matrigel-based organoid cultures derived from primary PCa are essentially composed of benign-like epithelial cells, irrespective of the dataset or the malignant nature of the tissue of origin. In contrast, ECM-free conditions maintain heterogenous patient-specific luminal tumor cell populations and enrich in intermediate cell types. Ultimately, our work will significantly enhance the potential of PDOs in basic and translational PCa research.
Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC
Authors: Chang-Gonzalez Ana C. , Akitsu Aoi , Mallis Robert J. , Lang Matthew J. , Reinherz Ellis L. , Hwang Wonmuk 
Published: October 2024

AbstractIncreasing evidence suggests that mechanical load on theαβT cell receptor (TCR) is crucial for recognizing the antigenic peptide-loaded major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination. To further examine the generality of the mechanism, we perform all-atom MD simulations of the B7 TCR under different conditions for comparison with our previous simulations of the A6 TCR. The two TCRs recognize the same pMHC and have similar interfaces with pMHC in crystal structures. We find that the B7 TCR-pMHC interface stabilizes under ∼15-pN load using a conserved dynamic allostery mechanism that involves the asymmetric motion of the TCR chassis. However, despite forming comparable contacts with pMHC as A6 in the crystal structure, B7 has fewer high-occupancy contacts with pMHC during the simulation. These results suggest that the dynamic allostery common to the TCRαβchassis can amplify slight differences in interfacial contacts into distinctive mechanical responses and potentially nuanced biological outcomes.
The body size and fitness match and its variability in plastic response to temperature
Authors: Żygadło Antoni , Burzawa Agata , Potera Katarzyna , Sierpowski Franek , Walczyńska Aleksandra 
Published: October 2024

AbstractThe ability of organisms to respond plastically to environmental change remains one of the most challenging areas of ecological studies. Reasons for this include the complex nature of environmental cues and responses at the organismal level, the costs that organisms face in performing phenotypic plasticity under different conditions, and the individual capacity to respond, which depends on many internal and external factors. The special case in this regard is an example of the plastic body size response to temperature, known as the Temperature-Size Rule (TSR). We used five clonal and three multiclonal experimental populations of theLecane inermisrotifer. We measured two traits over a wide thermal range: body size and population growth rater. We investigated (i) the thermal conditions under which different experimental populations perform the TSR or canalize (= no plasticity) their body size, (ii) how this response relates to a direct measure of fitness, and (iii) whether this response varies with the thermal preferences of the studied organisms. We found a relationship between body size and fitness, confirming that the TSR is only performed within a certain thermal range, beyond which body size is canalized. We did not find the expected relationship between the strength of the TSR and the range of thermal tolerance, but our results do not allow us to reject the existence of such a relationship. Additionally, we found a relatively high repeatability of thermal tolerance in experimental populations in comparison with the previous studies. Finally, we suggest the role of the level of genetic composition within a population in its ability to respond plastically to temperature. This is the first study to describe in detail the special case of plasticityversuscanalization, for body size response to optimal and suboptimal temperatures, in organisms that differ in their tolerance to temperature.
Exploring the Role of CottonCMFGenes in Salt Stress Tolerance: Insights from Phylogenetic, Expression, and Functional Analyses
Authors: Cui Yupeng , Shi Gongyao , Wang Shuai , Peng Xingyu , Zhou Xue-Rong , Ye Wuwei 
Published: October 2024

ABSTRACTSalt stress significantly limits cotton growth and development, making the improvement of salt tolerance critical.CMFgenes, containing a single CCT domain, are promising targets for breeding programs. We identified 101CMFgenes from four cotton species. Phylogenetic analysis grouped these genes into six clusters closely related toArabidopsis. Gene structure and motif analysis showed high conservation, while collinear analysis indicated segmental duplication as a key factor inCMFgene family expansion. Promoter analysis predicted involvement in light, abiotic stress, plant hormone responses, and growth. Expression analysis revealed differential expression ofGhCMFgenes across tissues, with some induced by abiotic stress. Co-expression network analysis indicatedGhCMF14interacts with other proteins to resist abiotic stress. Subcellular localization showed GhCMF14 in the nucleus. SilencingGhCMF14enhanced salt tolerance, with higher chlorophyll and proline content, and lower MDA and H2O2levels. This study provides insights intoCMFgene regulation and their role in cotton salt stress tolerance.
Simulation Insights on the Compound Action Potential in Multifascicular Nerves
Authors: Tharayil Joseph , Zinno Ciro , Agnesi Filippo , Lloyd Bryn , Farcito Silvia , Cassara Antonino M. , Kuster Niels , Reimann Michael , Micera Silvestro , Neufeld Esra 
Published: October 2024

AbstractObjectiveDevelop an efficient method for simulating evoked compound action potential (eCAP) signals from complex nerves to help optimize and interpret eCAP recordings; validate it through comparison with measured vagus nerve eCAP recordings; elucidate the subtle interplay giving rise to specific eCAP signal shapes and magnitudes.ApproachWe developed an extended reciprocity theorem approach to model neuron signals in heterogeneous environments, and use it to study analytically the single fibre action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model eCAP signals from complex nerves populated with heterogeneous fiber populations of fibers. A cuff electrode was used to measure activity induced by vagus nerve stimulation inin vivoporcine experiments; these measurements were compared with signals produced by the model.Main ResultsThe semi-analytic model produces signals that approximate the shape and amplitude ofin vivomeasurements. Partially activated fascicles contribute substantially to the signal, as eCAP contributions from smoothly varying fiber calibers in fully activated ones partially cancel. As a result, eCAP magnitude does not depend monotonically on the stimulation current and recruitment level. Because the eCAP is sensitive to the degree of activation in individual fascicles, and to the location of the recording electrodes with respect to individual fascicles, the contributions of different fascicles to the recorded eCAP signals vary significantly with changes in the shape and placement of the stimulus and the recording electrodes.SignificanceOur method can be used to rapidly assess new stimulation and recording setups involving complex nerves and neurovascular bundles, e.g., to maximize signal information content, for closed-loop control in bioelectronic medicine applications, and potentially to non-destructively reconstruct structural and functional nerve topologies through inverse problem solving.
BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions
Authors: Wang Xiangwen , Zhou Jiahui , Mueller Jane , Quinn Derek , Moody Thomas S. , Huang Meilan 
Published: October 2024

AbstractEnzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities and facilitating the discovery of novel biocatalysts. However, the limited availability of data for specific enzyme functions, such as conversion efficiency and stereoselectivity, presents challenges for prediction accuracy. In this study, we developed BioStructNet, a structure-based deep learning network that integrates both protein and ligand structural data to capture the complexity of enzyme-substrate interactions. Benchmarking studies with the different algorithms showed the enhanced predictive accuracy of BioStructNet. To further optimize the prediction accuracy for the small dataset, we implemented transfer learning in the framework, training a source model on a large dataset and fine-tuning it on a small, function-specific dataset, using the CalB dataset as a case study. The model performance was validated by comparing the attention heat maps generated by the BioStructNet interaction module, with the enzyme substrate interactions revealed by enzyme-substrate complexes revealed from molecular simulations. BioStructNet would accelerate the discovery of functional enzymes for industrial use, particularly in cases where the training datasets for machine learning are small.
BBATProt : A Framework Predicting Biological Function with Enhanced Feature Extraction via Explainable Deep Learning
Authors: Wang Youqing , Ye Xukai , Feng Yue , Wang Haoqian , Lin Xiaofan , Ma Xin , Zhang Yifei 
Published: October 2024

AbstractAccurately predicting the functions of peptides and proteins from their amino acid sequences is essential for understanding life processes and advancing biomolecule engineering. Due to the time-consuming and resource-intensive nature of experimental procedures, computational approaches, especially those based on machine learning frameworks, have garnered significant interest. However, many existing machine learning tools are limited to specific tasks and lack adaptability across different predictions. Here we propose a versatile framework BBATProt for the prediction of various protein and peptide functions. BBATProt employs transfer learning with a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model, to effectively capture high-dimensional features from amino acid sequences. The whole custom-designed network, integrating Bidirectional Long Short-Term Memory (Bi-LSTM) and Temporal Convolutional Networks (TCN), can align with the spatial characteristics of proteins. It combines local and global feature extraction through attention mechanisms for precise functional prediction. This approach ensures that key features are adaptively extracted and balanced across diverse tasks. Comprehensive evaluations show BBATProt outperforms state-of-the-art models in predicting functions like hydrolytic catalysis, activity of peptides, and post-translational modification sites. Visualizations of feature evolution and refinement via attention mechanisms validate the framework’s interpretability, providing transparency into the evolutional process and offering deeper insights into function prediction.