bluuebunny/crossref_metadata_2025_split huggingface dataset:
LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model
Authors: Pratyush Pawel , Bahmani Soufia , Pokharel Suresh , Ismail Hamid D , KC Dukka B 
Published: April 2024

Abstract

Motivation
Recent advancements in natural language processing have highlighted the effectiveness of global contextualized representations from protein language models (pLMs) in numerous downstream tasks. Nonetheless, strategies to encode the site-of-interest leveraging pLMs for per-residue prediction tasks, such as crotonylation (Kcr) prediction, remain largely uncharted.

Results
Herein, we adopt a range of approaches for utilizing pLMs by experimenting with different input sequence types (full-length protein sequence versus window sequence), assessing the implications of utilizing per-residue embedding of the site-of-interest as well as embeddings of window residues centered around it. Building upon these insights, we developed a novel residual ConvBiLSTM network designed to process window-level embeddings of the site-of-interest generated by the ProtT5-XL-UniRef50 pLM using full-length sequences as input. This model, termed T5ResConvBiLSTM, surpasses existing state-of-the-art Kcr predictors in performance across three diverse datasets. To validate our approach of utilizing full sequence-based window-level embeddings, we also delved into the interpretability of ProtT5-derived embedding tensors in two ways: firstly, by scrutinizing the attention weights obtained from the transformer’s encoder block; and secondly, by computing SHAP values for these tensors, providing a model-agnostic interpretation of the prediction results. Additionally, we enhance the latent representation of ProtT5 by incorporating two additional local representations, one derived from amino acid properties and the other from supervised embedding layer, through an intermediate fusion stacked generalization approach, using an n-mer window sequence (or, peptide/fragment). The resultant stacked model, dubbed LMCrot, exhibits a more pronounced improvement in predictive performance across the tested datasets.

Availability and implementation
LMCrot is publicly available at https://github.com/KCLabMTU/LMCrot.
District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach
Authors: Srivathsan Ariktha , Abdou Amza , Al-Khatib Tawfik , Apadinuwe Sue-Chen , Badiane Mouctar D , Bucumi Victor , Chisenga Tina , Kabona George , Kabore Martin , Kanyi Sarjo Kebba , Bella Lucienne , M’po Nekoua , Masika Michael , Minnih Abdellahi , Sitoe Henis Mior , Mishra Sailesh , Olobio Nicholas , Omar Fatma Juma , Phiri Isaac , Sanha Salimato , Seife Fikre , Sharma Shekhar , Tekeraoi Rabebe , Traore Lamine , Watitu Titus , Bol Yak Yak , Borlase Anna , Deiner Michael S , Renneker Kristen K , Hooper P J , Emerson Paul M , Vasconcelos Andreia , Arnold Benjamin F , Porco Travis C , Hollingsworth T Déirdre , Lietman Thomas M , Blumberg Seth 
Published: April 2024

Abstract
Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation–follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1–9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43–1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.
Proteomics couples electrical remodelling to inflammation in a murine model of heart failure with sinus node dysfunction
Authors: Kahnert Konstantin , Soattin Luca , Mills Robert W , Wilson Claire , Maurya Svetlana , Sorrentino Andrea , Al-Othman Sami , Tikhomirov Roman , van de Vegte Yordi J , Hansen Finn B , Achter Jonathan , Hu Wei , Zi Min , Smith Matthew , van der Harst Pim , Olesen Morten S , Boisen Olsen Kristine , Banner Jytte , Jensen Thomas H L , Zhang Henggui , Boyett Mark R , D’Souza Alicia , Lundby Alicia 
Published: April 2024

Abstract

Aims
In patients with heart failure (HF), concomitant sinus node dysfunction (SND) is an important predictor of mortality, yet its molecular underpinnings are poorly understood. Using proteomics, this study aimed to dissect the protein and phosphorylation remodelling within the sinus node in an animal model of HF with concurrent SND.

Methods and results
We acquired deep sinus node proteomes and phosphoproteomes in mice with heart failure and SND and report extensive remodelling. Intersecting the measured (phospho)proteome changes with human genomics pharmacovigilance data, highlighted downregulated proteins involved in electrical activity such as the pacemaker ion channel, Hcn4. We confirmed the importance of ion channel downregulation for sinus node physiology using computer modelling. Guided by the proteomics data, we hypothesized that an inflammatory response may drive the electrophysiological remodeling underlying SND in heart failure. In support of this, experimentally induced inflammation downregulated Hcn4 and slowed pacemaking in the isolated sinus node. From the proteomics data we identified proinflammatory cytokine-like protein galectin-3 as a potential target to mitigate the effect. Indeed, in vivo suppression of galectin-3 in the animal model of heart failure prevented SND.

Conclusion
Collectively, we outline the protein and phosphorylation remodeling of SND in heart failure, we highlight a role for inflammation in electrophysiological remodelling of the sinus node, and we present galectin-3 signalling as a target to ameliorate SND in heart failure.
The role of rhizosphere phages in soil health
Authors: Wang Xiaofang , Tang Yike , Yue Xiufeng , Wang Shuo , Yang Keming , Xu Yangchun , Shen Qirong , Friman Ville-Petri , Wei Zhong 
Published: April 2024

Abstract
While the One Health framework has emphasized the importance of soil microbiomes for plant and human health, one of the most diverse and abundant groups—bacterial viruses, i.e. phages—has been mostly neglected. This perspective reviews the significance of phages for plant health in rhizosphere and explores their ecological and evolutionary impacts on soil ecosystems. We first summarize our current understanding of the diversity and ecological roles of phages in soil microbiomes in terms of nutrient cycling, top-down density regulation, and pathogen suppression. We then consider how phages drive bacterial evolution in soils by promoting horizontal gene transfer, encoding auxiliary metabolic genes that increase host bacterial fitness, and selecting for phage-resistant mutants with altered ecology due to trade-offs with pathogen competitiveness and virulence. Finally, we consider challenges and avenues for phage research in soil ecosystems and how to elucidate the significance of phages for microbial ecology and evolution and soil ecosystem functioning in the future. We conclude that similar to bacteria, phages likely play important roles in connecting different One Health compartments, affecting microbiome diversity and functions in soils. From the applied perspective, phages could offer novel approaches to modulate and optimize microbial and microbe–plant interactions to enhance soil health.
An opportunistic pathogen under stress: how Group B Streptococcus responds to cytotoxic reactive species and conditions of metal ion imbalance to survive
Authors: Goh Kelvin G K , Desai Devika , Thapa Ruby , Prince Darren , Acharya Dhruba , Sullivan Matthew J , Ulett Glen C 
Published: April 2024

Abstract
Group B Streptococcus (GBS; also known as Streptococcus agalactiae) is an opportunistic bacterial pathogen that causes sepsis, meningitis, pneumonia, and skin and soft tissue infections in neonates and healthy or immunocompromised adults. GBS is well-adapted to survive in humans due to a plethora of virulence mechanisms that afford responses to support bacterial survival in dynamic host environments. These mechanisms and responses include counteraction of cell death from exposure to excess metal ions that can cause mismetallation and cytotoxicity, and strategies to combat molecules such as reactive oxygen and nitrogen species that are generated as part of innate host defence. Cytotoxicity from reactive molecules can stem from damage to proteins, DNA, and membrane lipids, potentially leading to bacterial cell death inside phagocytic cells or within extracellular spaces within the host. Deciphering the ways in which GBS responds to the stress of cytotoxic reactive molecules within the host will benefit the development of novel therapeutic and preventative strategies to manage the burden of GBS disease. This review summarizes knowledge of GBS carriage in humans and the mechanisms used by the bacteria to circumvent killing by these important elements of host immune defence: oxidative stress, nitrosative stress, and stress from metal ion intoxication/mismetallation.
AcMYB266, a key regulator of the red coloration in pineapple peel: a case of subfunctionalization in tandem duplicated genes
Authors: Zhang Wei , Wu Jing , He Junhu , Liu Chaoyang , Yi Wen , Xie Jingyao , Wu Ya , Xie Tao , Ma Jun , Zhong Ziqin , Yang Mingzhe , Chen Chengjie , Luan Aiping , He Yehua 
Published: April 2024

Abstract
Red fruit peel is an attractive target for pineapple breeding. Various pineapple accessions with distinct red coloration patterns exist; however, the precise molecular mechanism accounting for these differences remains unknown, which hinders the pineapple breeding process from combining high fruit quality with red peel. In this study, we characterized a transcription factor, AcMYB266, which is preferentially expressed in pineapple peel and positively regulates anthocyanin accumulation. Transgenic pineapple, Arabidopsis, and tobacco plants overexpressing AcMYB266 exhibited significant anthocyanin accumulation. Conversely, transient silencing of this gene led to decreased anthocyanin accumulation in pineapple red bracts. In-depth analysis indicated that variations of AcMYB266 sequences in the promoter instead of the protein-coding region seem to contribute to different red coloration patterns in peels of three representative pineapple varieties. In addition, we found that AcMYB266 was located in a cluster of four MYB genes exclusive to and conserved in Ananas species. Of this cluster, each was proved to regulate anthocyanin synthesis in different pineapple tissues, illustrating an interesting case of gene subfunctionalization after tandem duplication. In summary, we have characterized AcMYB266 as a key regulator of pineapple red fruit peel and identified an MYB cluster whose members were subfunctionalized to specifically regulate the red coloration of different pineapple tissues. The present study will assist in establishing a theoretical mechanism for pineapple breeding for red fruit peel and provide an interesting case for the investigation of gene subfunctionalization in plants.
Performance and emission characteristics of novel biodiesel-diesel blends: an RSM and ANN approach
Authors: Al Zubi Mohammad A , Penmetsa Ravi Varma , Kumar P Satish , Patil Pravin P , Singh Bharat , Alsubih Majed , Islam Saiful , Khan Wahaj Ahmad 
Published: April 2024

Abstract
In this paper, the impact of different input variables on the performance and emission features of a pongamia pinnata and rapeseed oil biodiesel with n-Butanol additive were investigated, statistically analyzed, and optimized by employing the powerful response surface methodology (RSM) based design of experiment (DOE) techniques. The vegetable oils (pongamia pinnata and rapeseed oils) were transesterified and their corresponding methyl esters were blended with diesel and n-Butanol at blend ratios 10:84:6, 10:78:12, 20:74:6 and 20:68:12. The samples were tested on a direct injection CI engine at a rated speed of 1500 rpm and standard CR of 17.5:1 at different loads. In each test, performance and emission parameters were measured. Expert machine learning (ML) methods were used to forecast these features. In addition, polynomial equations were developed for each blend using regression techniques and compared with an artificial intelligence technique. It was observed that the engine performance increased as biodiesel and additive weight percentage increased. Regardless of the loads placed on the engine and the blend ratios, the use of PPME and RSME combined with n-Butanol blends demonstrated a clear decrease in NOx compared to diesel (7.07% for P20B12 and 6.58% for R20B12). As per the trend, it is seen that the percentage reduction in CO2 emissions is greater with high percentage increase of n-Butanol in the tested sample irrespective of loads applied on the engine (2.95% more P20B12 for as compared to P20B6). For the emission characteristics, ANN demonstrated a range of 87.92% to 98.83% prediction accuracy while that of regression varies from 81.4% to 98.8% for all the samples of PPME blended biodiesel.
Jeddah strategic approaches to sustainable urban development and vision 2030 alignment
Authors: Alhubashi Haytham , Alamoudi Mohammed , Imam Ayman , Abed Ahmad , Hegazy Ibrahim 
Published: April 2024

Abstract
This research article provides an in-depth look into the urban development trajectory of Jeddah, a historic port city in Saudi Arabia, which has developed into a vibrant urban center that reflects its rich past and ambitious future. The study systematically explores Jeddah’s journey through different lenses—its strategic geographical location as a maritime and pilgrimage gateway, its historical development dating back to the seventh century and its transformation influenced by diverse cultural and economic interactions. It comprehensively analyzes Jeddah’s social and economic fabric, demographic trends and the impact of these factors on the city’s urban landscape. This article examines the governance and regulatory frameworks that shape development policies in Jeddah and addresses how these frameworks are designed to meet the challenges of modern urbanization, including rapid population growth, infrastructure requirements and environmental sustainability. The research also examines the city’s response to these challenges, focusing on strategic planning, infrastructure development and sustainable urban initiatives that align with the goals of Saudi Vision 2030. This article provides an in-depth understanding of urban dynamics in Jeddah, presenting it as a case study for managing growth and modernization in rapid urban environments.
Estimation of stationary optimal transport plans
Authors: O’Connor Kevin , Nobel Andrew , McGoff Kevin 
Published: April 2024

Abstract
We study optimal transport for stationary stochastic processes taking values in finite spaces. In order to reflect the stationarity of the underlying processes, we restrict attention to stationary couplings, also known as joinings. The resulting optimal joining problem captures differences in the long-run average behavior of the processes of interest. We introduce estimators of both optimal joinings and the optimal joining cost, and establish consistency of the estimators under mild conditions. Furthermore, under stronger mixing assumptions we establish finite-sample error rates for the estimated optimal joining cost that extend the best known results in the iid case. We also extend the consistency and rate analysis to an entropy-penalized version of the optimal joining problem. Finally, we validate our convergence results empirically as well as demonstrate the computational advantage of the entropic problem in a simulation experiment.
A scoping review of the methodological approaches used in retrospective chart reviews to validate adverse event rates in administrative data
Authors: Connolly Anna , Kirwan Marcia , Matthews Anne 
Published: April 2024

Abstract
Patient safety is a key quality issue for health systems. Healthcare acquired adverse events (AEs) compromise safety and quality; therefore, their reporting and monitoring is a patient safety priority. Although administrative datasets are potentially efficient tools for monitoring rates of AEs, concerns remain over the accuracy of their data. Chart review validation studies are required to explore the potential of administrative data to inform research and health policy. This review aims to present an overview of the methodological approaches and strategies used to validate rates of AEs in administrative data through chart review. This review was conducted in line with the Joanna Briggs Institute methodological framework for scoping reviews. Through database searches, 1054 sources were identified, imported into Covidence, and screened against the inclusion criteria. Articles that validated rates of AEs in administrative data through chart review were included. Data were extracted, exported to Microsoft Excel, arranged into a charting table, and presented in a tabular and descriptive format. Fifty-six studies were included. Most sources reported on surgical AEs; however, other medical specialties were also explored. Chart reviews were used in all studies; however, few agreed on terminology for the study design. Various methodological approaches and sampling strategies were used. Some studies used the Global Trigger Tool, a two-stage chart review method, whilst others used alternative single-, two-stage, or unclear approaches. The sources used samples of flagged charts (n = 24), flagged and random charts (n = 11), and random charts (n = 21). Most studies reported poor or moderate accuracy of AE rates. Some studies reported good accuracy of AE recording which highlights the potential of using administrative data for research purposes. This review highlights the potential for administrative data to provide information on AE rates and improve patient safety and healthcare quality. Nonetheless, further work is warranted to ensure that administrative data are accurate. The variation of methodological approaches taken, and sampling techniques used demonstrate a lack of consensus on best practice; therefore, further clarity and consensus are necessary to develop a more systematic approach to chart reviewing.
Effect of different feeding strategies and dietary fiber levels on energy and protein retention in gestating sows
Authors: Wisbech Sigrid J , Nielsen Tina S , Bach Knudsen Knud E , Theil Peter K , Bruun Thomas S 
Published: April 2024

Abstract
The aim of the study was to investigate whether increased inclusion of sugar beet pulp (SBP) alters retention of fat, protein, and energy when backfat (BF) is restored in early- and mid-gestation. In total, 46 sows were fed one of four dietary treatments with increasing inclusion of SBP providing dietary fiber (DF) levels of 119, 152, 185, and 217 g/kg; sows were assigned to one of three feeding strategies (FS; high, medium, and low) depending on BF thickness at mating and again at day 30 for the following month. On days 0, 30, 60, and 108, body weight (BW) and BF thickness were measured and body pools of protein and fat were estimated using the deuterium oxide technique. On days 30 and 60, urine, feces, and blood samples were collected to quantify metabolites, energy, and nitrogen (N) balances. On days 15 and 45, heart rate was recorded to estimate heat energy. At farrowing, total born and weight of the litter were recorded. In early gestation, BW gain (P &lt; 0.01) and body protein retention increased (P &lt; 0.05) with increasing fiber inclusion, while body fat retention increased numerically by 59%. The increase in BF was greatest for sows fed the high FS, intermediate when fed the medium strategy, and negligible for sows fed the lowest FS (P &lt; 0.001). Nitrogen intake, N loss in feces, and N balance increased linearly, whereas N loss in urine tended to decrease with increasing inclusion of fibers in early gestation. Concomitantly, fecal energy output and energy lost as methane increased linearly (P &lt; 0.001), while energy output in urine declined linearly. Total metabolizable energy (ME) intake therefore increased from 36.5 MJ ME/d in the low fiber group to 38.5 MJ ME/d in the high fiber group (P &lt; 0.01). Changing the ME towards more ketogenic energy was expected to favor fat retention rather than protein retention. However, due to increased intake of ME and increased N efficiency with increasing fiber inclusion, the sows gained more weight and protein with increasing fiber inclusion. In conclusion, increased feed intake improved both fat and protein retention, whereas increased DF intake increased protein retention.
Gene expression of free fatty acids-sensing G protein-coupled receptors in beef cattle
Authors: Durand Guillaume , Charrier Pierre , Bes Sébastien , Bernard Laurence , Lamothe Valérie , Gruffat Dominique , Bonnet Muriel 
Published: April 2024

Abstract
Many physiological functions are regulated by free fatty acids (FFA). Recently, the discovery of FFA-specific G protein-coupled receptors (FFARs) has added to the complexity of their actions at the cellular level. The study of FFAR in cattle is still in its earliest stages focusing mainly on dairy cows. In this study, we set out to map the expression of genes encoding FFARs in 6 tissues of beef cattle. We also investigated the potential effect of dietary forage nature on FFAR gene expression. To this end, 16 purebred Charolais bulls were fed a grass silage ration or a maize silage ration (n = 8/group) with a forage/concentrate ratio close to 60:40 for 196 d. The animals were then slaughtered at 485 ± 42 d and liver, spleen, ileum, rectum, perirenal adipose tissue (PRAT), and Longissimus Thoracis muscle were collected. FFAR gene expression was determined by real-time quantitative PCR. Our results showed that of the five FFARs investigated, FFAR1, FFAR2, FFAR3, and GPR84 are expressed (Ct &lt; 30) in all six tissues, whereas FFAR4 was only expressed (Ct &lt; 30) in PRAT, ileum, and rectum. In addition, our results showed that the nature of the forage, i.e., grass silage or maize silage, had no effect on the relative abundance of FFAR in any of the tissues studied (P value &gt; 0.05). Taken together, these results open new perspectives for studying the physiological role of these receptors in beef cattle, particularly in nutrient partitioning during growth.