bluuebunny/crossref_metadata_2025_split huggingface dataset:
PanTE: A Comprehensive Framework for Transposable Element Discovery in Graph-based Pangenomes
Authors: Wang Yiwen , Cao Shuo , Liu Zhenya , Liu Yuting , Liu Zhongqi , Ma Wenqi , Lu Jianzhong , Xiao Hua , Chen Jinfeng , Ou Shujun , Garrison Erik , Zhou Yongfeng 
Published: February 2025

Abstract

Transposable element (TE) annotation is crucial for understanding genetics, genomics and evolution, yet current methods struggle to identify TEs in graph-based pangenomes. We developed a framework PanTE to construct accurate and representative TE libraries for both single genomes and graph pangenomes. PanTE is the first of its kind capable of being directly applied to graph-based pangenomes to build population-level TE libraries. By partially reimplementing RepeatModeler2 and integrating key innovations, including graph pangenome disassembly, alignment-free LTR structure detection, a machine learning-based classifier and efficiency-boosting strategies, PanTE outperformed RepeatModeler2 by efficiently handling large genomes, detecting high-abundance TEs and LTR-retrotransposons, and providing robust TE classification with superior computational efficiency. Compared to EDTA, it annotated ~ 26% more TEs in the grapevine genome and achieved up to 13 times faster runtimes in the wheat genome. PanTE represents a significant advancement in population-wide TE discovery, making it particularly valuable for pangenomic studies.
Structural flexibility in the ordered domain of the dengue virus strain 2 capsid protein is critical for chaperoning viral RNA replication
Authors: SHARMA Kamal Kant , Raghuvamsi Palur Venkata , Aik Daniel Y. K. , Marzinek Jan K , Bond Peter J. , Wohland Thorsten 
Published: February 2025

Abstract

Viral replication necessitates intricate nucleic acid rearrangements, including annealing and strand displacement to achieve the viral RNA functional structure. Often a single RNA chaperone performs these seemingly incompatible functions. This raises the question of what structural and dynamic features of such chaperones govern distinct RNA rearrangements. While cationic intrinsically disordered regions promote annealing by playing a charge-screening role, how the same chaperone mediates strand displacement remains elusive. Here, we investigate the annealing and strand displacement of the 5’ upstream AUG region (5UAR) as chaperoned by the Dengue virus strain 2 capsid protein (Denv2C) as a model RNA chaperone. Through single molecule analysis and molecular simulations, we demonstrate that Denv2C regulates nucleic acid melting, folding, annealing, and strand displacement via flexibility in its ordered region. A mutation that renders the Denv2C ordered region rigid, converts Denv2C into a mere annealer. Our findings underscore the role of Denv2C’s disordered region as a “macromolecular counterion” during RNA annealing, while a flexible ordered region is crucial for effective strand displacement.
H3K27me3 demethylases regulate flowering time response to low ambient temperature
Authors: Poza-Viejo Laura , Luna Ana , Olmo Iván del , Arikan Burcu , González-Bodí Sara , Yan Wenhao , Kaufmann Kerstin , Turck Franziska , Crevillén Pedro 
Published: February 2025

Abstract

Flowering time is an important crop trait, as premature or delayed flowering can significantly reduce yields. Plants flower in response to a defined set of endogenous and environmental cues. The effect of ambient temperature on flowering time is extensively studied, but the role of epigenetic modifiers on the floral thermosensory pathway remains largely unexplored. Here we describe that the histone demethylases EARLY FLOWERING 6 (ELF6) and JUMONJI 13 (JMJ13) fine-tune temperature-dependent flowering. We found that the elf6-3 jmj13-1 double mutant is hyposensitive to the effect of low ambient temperature on flowering time. Genetic analyses demonstrate that ELF6 and JMJ13 function requires the cold-responsive floral repressors FLOWERING LOCUS C (FLC) and FLOWERING LOCUS M (FLM). ELF6 and JMJ13 bind to the chromatin of FLC and FLM loci at both temperature regimes, with increased binding to FLM observed at low ambient temperatures. Interestingly, we also detected increased levels of H3 lysine 27 trimethylation (H3K27me3) in the elf6-3 jmj13-1 double mutant at low ambient temperature in FLC and FLM. Our work demonstrates that ELF6 and JMJ13 are required to modulate FLC and FLM gene expression in response to ambient temperature fluctuations, revealing H3K27me3 demethylases as novel players in the floral thermosensory pathway.
Pattern and predictors of lepra reactions among patients treated for leprosy in southeast Nigeria: A mixed methods Study
Authors: Okoh Emeka E. , Ojule Inumanye N. , Amah Linda O. , Okoh Joel C. , Sibeudu Nnaemeka E. , Oduwegwu Stella I. 
Published: February 2025

Abstract

Background
Lepra reactions occur among patients treated for leprosy. This study aimed to assess the pattern and predictors of lepra reactions in southeast Nigeria.
Methods
This is a convergent parallel mixed-methods study that determined the pattern and explored the experiences of leprosy patients. Participants were recruited by cluster sampling technique. Chi-square test and binary logistic regression analysis were performed with statistical significance level of </=0.05. In addition, in-depth and key informant interviews were conducted.
Results
There were 71 participants in total, comprising 35 males (49.3%) and 36 females (50.7%) with a mean age of 60.39±16.327. The prevalence of type 1 and type 2 lepra reactions were 59.2% (95% CI 47.14 – 70.17), and 35.2% (95% CI 27.30 – 50.07) respectively. Type 1 lepra reaction (LR) was significantly associated with gender (P< 0.023) and farming (p<0.044). Furthermore, Paucibacillary leprosy (PB) was significantly associated with both types 1(p< 0.022) and 2(p< 0.011) lepra reactions. Type of diagnosis (PB) was a significant predictor of type 1 LR 5.89 (95% CI 1.58 - 21.99) and type 2 LR 8.76 (95% CI 1.67 - 46.15). Worsening and new lesions led to discrimination and stigmatization for leprosy survivors.
Conclusions
Lepra reactions are common among leprosy patients in southeast Nigeria. Male gender, farming and PB leprosy were found to be predictors of leprosy reactions.
PRECISE-RA: Predicting Remission and StratifyingRisk in Rheumatoid Arthritis Patients Treated withbDMARDs—A Robust Machine Learning Approach
Authors: Salehi Fatemeh , Eskofier Bjoern M. , Salin Emmanuelle , Bayat Sara , Schett Georg , Kleyer Arnd , Smarr Benjamin , Fritsch-Stork Ruth 
Published: February 2025

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are costly, and up to 40% of patients do not achieve remission within six months. Accurate prediction of treatment response is crucial for optimizing care, minimizing side effects, and enhancing cost efficiency.
This study proposes a robust machine learning framework for predicting six-month remission in RA patients using baseline routine clinical data. The framework also integrates risk stratification and explainability to enhance its clinical applicability. We evaluated multiple machine learning models, AdaBoost, Random Forest, XGBoost, and Support Vector Machines, using data from Austrian RA patients. We externally validated the results on an independent dataset from the Erlangen Hospital. To improve the reliability of probability estimates for actionable risk stratification, we employed calibration techniques, including Platt scaling, Isotonic regression, Beta calibration, and Spline calibration. We generated calibration curves to assess and visualize the alignment between predicted probabilities and observed outcomes. In addition, we used SHapley Additive exPlanations (SHAP) to analyze the contributions of different patient characteristics to the prediction of RA remission.
AdaBoost demonstrated stronger performance than the other models, achieving an accuracy of 85.71% and a Brier score of 0.13 with isotonic regression calibration. SHAP identified DAS28, visual analog scales (VAS), age, and swollen joint count (SJC) as important characteristics for the prediction of RA remission. We also stratified patients into low-, medium-, and high-risk categories based on model predictions to support follow-up scheduling and treatment prioritization.
Our framework predicts RA remission before the initiation of bDMARD therapy. It enables personalized care, actionable risk stratification, and optimized resource allocation. Its robustness was validated on two different individual cohort datasets, which highlights its potential for integration into routine clinical workflows.
The Adjusted Ferritin Inflammation Index: A Novel Metric for Predicting Mortality in Heart Failure
Authors: ALAK Çetin , Çiriş Şükrü , Yurdalan Furkan Fatih , Hunutlu Fazil Çağrı , Kumral Zeynep , Şentürk Tunay 
Published: February 2025

Abstract

Iron deficiency (ID) is common in heart failure (HF) patients and associated with poorer outcomes. However, traditional markers like ferritin and transferrin saturation (TSAT) may fail to accurately assess ID due to the confounding effects of inflammation. In this study, we introduce the Adjusted Ferritin Inflammation Index (AFII), a composite score combining ferritin/CRP ratio and albumin levels, designed to improve the precision of ID assessment in HF patients. A total of 322 HF patients with reduced ejection fraction were included in the analysis, following the application of specific inclusion and exclusion criteria. Multivariate analysis identified AFII as an independent predictor of mortality (HR: 2.155, 95% CI: 1.361–3.412, p = 0.001), demonstrating strong discriminatory power (AUC: 0.713). Survival analysis showed that patients with AFII ≥ 2.1 had significantly lower survival rates across all subgroups. These findings suggest that AFII could be a valuable tool for risk stratification in HF, offering a more comprehensive measure of mortality risk compared to traditional iron markers. Further validation in multi-center studies is needed to confirm its clinical utility.
Enhancing Doxorubicin Efficacy in Non-Small Cell Lung Cancer: The Synergistic Role of Curcumin in Modulating p21 and p53
Authors: Chai Haiqiang , Liu Huixia 
Published: February 2025

Abstract

Lung cancer is one of the most lethal type of malignancy in the world. Polyphenolic compounds such as curcumin, which are found in certain plant foods, are considered as chemotherapeutic agents that induce their effect through their anti-proliferative, anti-estrogenic, and pro-oxidant properties associated with cancer. In this study, we investigated the effects of curcumin on the chemosensitivity of A549 cells to doxorubicin (DOX). A549 and A549/DOX cancer cells treated with DOX and curcumin and MTT assay was applied to investigate the cell viability. Western blot and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) were applied to investigate the protein and mRNA expression levels of P-glycoprotein (p-gp), apoptosis mediators, p21 and p53. P-gp activity was assessed by rhodamine 123 accumulation assay. Apoptosis was measured by annexin V flow cytometry. Curcumin potentiated the anticancer effects of DOX in A549/DOX cells. In other words, combinational treatment of resistant cells with DOX and curcumin reversed resistant phenotype in NSCLC via downregulating P-gp and p21 and upregulating p53. In addition, cells exposed to curcumin showed higher levels of apoptosis and higher expression levels of pro-apoptotic mediators. In conclusion, our findings demonstrated the possible effective roles of curcumin in the reversing DOX resistance via targeting p21 and p53 in NSCLC.
Dynamic Pothole Detection: A Six-Month Study of Depth Variation and Characterization Using Scatter Plot Techniques
Authors: Bhatt Arpit Kumar , Hrituraj Hrituraj , Sharma Vinamra Bhushan , Sharma Ankit , Biswas Susham 
Published: February 2025

Abstract

Potholes represent a significant threat to road infrastructure, contributing to road safety risks and escalating maintenance costs. This research investigates dynamic pothole detection and depth variation over a six-month period, employing a combination of RGB value analysis, pothole depth measurements, scatter plot visualization with the help of terrestrial laser Scanner, and artificial intelligence (AI) techniques. The study aims to develop an automated model that characterizes potholes not only in terms of their spatial location but also by assessing their depth and temporal progression. RGB values from high-resolution images of road surfaces are analyzed to detect pothole features, while depth measurements are recorded using advanced sensors. AI algorithms, including image processing and machine learning, are applied to process the data, detect potholes, and analyze their development over time. Scatter plot techniques are utilized to visualize the correlation between pothole depth, location, and environmental factors, providing deeper insights into the conditions that drive pothole formation and expansion. The results highlight the potential of integrating image processing and AI in proactive road maintenance strategies, offering an innovative approach to early pothole detection and characterization. This model could significantly enhance predictive maintenance, reduce road repair costs, and improve overall road safety.
Microplastics in FLOW: Seasonal Patterns in Major Latvian Rivers
Authors: Barone Marta , Svipsta Sanda , Bikše Jānis , Dimante-Deimantovica Inta 
Published: February 2025

Abstract

Rivers are considered key pathways for microplastics, transporting these pollutants from inland sources to marine environments. In this study, we investigated the seasonal fluctuations of microplastics in the surface waters of four major Latvian rivers (Daugava, Lielupe, Gauja, and Salaca) that flow into the Gulf of Riga. Sampling was conducted from spring 2022 to summer 2023 to represent distinct seasonal and environmental conditions. Using a Manta net (100 µm mesh size) samples were collected in triplicate and analysed for microplastic concentration, shape, size, colour, and polymer composition. Microplastic concentrations ranged from 0.63 to 132.88 particles/m³, with the highest levels observed in the River Salaca. Fibres and fragments were the predominant microplastic shapes, with polyethylene, polypropylene, and ethylene propylene diene monomer being the most abundant polymers. We found significant spatial and seasonal variations in microplastic concentrations in some rivers, with the River Salaca showing the most extreme seasonal fluctuations. However, overall, no significant correlation was observed between the suspended material and river discharge variables. Replicate sampling revealed variability between samples, highlighting the need to include replicas. These findings highlight the complexity of microplastic pollution dynamics and the need for careful consideration of seasonal factors when assessing environmental contamination. This article is the first to contribute data from Latvian rivers on the growing pool of information on microplastics contamination in waterways.
Assessing the Interplay of Religious Coping, Cravings, and Readiness for Change in Individuals with Opioid and Alcohol Dependence: A Prospective Study
Authors: Kumar Amit , Bhattacharjee Dipanjan , Khanra Sourav 
Published: February 2025

Abstract

Introduction: Globally, alcohol dependence is affecting approximately 6.5% of men and 1.5% of women. It often develops in early adulthood but can start at any age after repeated continued exposure to alcoholic beverages. Opioid dependence develops after regular use of opioids, a necessary but not sufficient condition for developing opioid dependence. In view of the alarming increase of these substances, there is a need to understand the religious coping and religious attitudes among individuals with opioid dependence syndrome and alcohol dependence syndrome.
Methods: The study aimed to assess the religious attitude and coping and their interaction with craving and readiness to change among Opioid dependence syndrome (ODS) and Alcohol dependence syndrome (ADS). The study was a prospective study. A total of 40 respondents, 20 respondents were diagnosed with ODS, and 20 were diagnosed with ADS. The data was collected through the religious attitude scale and brief religious cope, severity of dependence, Desire for Drug Questionnaire (DDQ), and the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES) (8D and 8A) and repeated on days 7 and 14. Statistics procedures were used and tested with the SPSS 25 version.
Results: The main results evidenced in this study were that patients with alcohol dependence have higher positive religious coping than opioid-dependent patients. The ADS group uses more positive coping comparing the ODS Group. The positive religious coping in the ADS group has led to better outcomes in craving reduction and readiness to change compared to the ODS group.
Predicting composition of a functional food product using computer simulation
Authors: Nikitina M. A. , Chernukha I. M. , Artamonova M. P. , Qusay A. T. 
Published: February 2025

One of the frontiers of science is the development of a digital twin for a food product to predict composition and properties of a future product. Today, however, computer simulation (modeling) is used for predicting the composition of a food product. The aim of our research is to compare the levels of the nutritional value parameters from a digital model and a real food product and to assess adequacy of the obtained data. The objects of the research were the emulsified meat-and-plant product based on the traditional meal “Mukhamar” and a digital model (computer simulator) of the recipe of the emulsified meat-andplant product. By the example of the development of the emulsified meat-and-plant product based on the traditional meal “Mukhamar”, stages of the development of a digital twin of a food product are shown. It was demonstrated that it is incorrect to use a digital model without supporting it with data (numerical values) obtained from apparatus, sensors. The calculated parameters were compared with the data obtained empirically (as a result of the laboratory experiment) in three blocks: physicochemical indicators, vitamins and minerals. Simulation and calculation of the absolute and relative errors were performed in the program environment R Studio. Differences between the calculated and empirical data can be explained, firstly, by the average values of parameters in food product databases. As for now, databases contain averaged data, which do not take into account individual characteristics of animal and plant raw materials. Secondly, it is necessary to take into consideration the coefficient of losses (or coefficient of preservation) of food nutrients during thermal treatment of food. It has been established that only the development of the precise digital twin with regard to all parameters will help to trace quality parameters at each stage of the production, which will allow reacting timely to deviations and improving quality of the final product.
Biotechnological aspects of the technology of preparation of grain-fruit wort from wheat grain and blackcurrant cake
Authors: Serba E. M. , Sokolova E. N. , Rimareva L. V. , Ionov V. V. , Ignatova N. I. , Overchenko M. B. 
Published: February 2025

For the development of competitive alcoholic beverages with interesting sensory characteristics, it is promising to introduce fruit and berry raw materials into the grain wort, which allows distillates to be given an original taste and aroma. However, in the process of processing fruit and berry raw materials, difficulties arise due to its high acidity and high content of fiber and pectin substances, which require additional research to develop efficient technologies. The purpose of this work was to study the conditions for the preparation of grain-fruit wort using biotechnological methods for the conversion of polymers of wheat and blackcurrant raw materials. The objects of the study were berries and blackcurrant cake; wheat grain; enzyme preparations — sources of amylases, hemicellulases, proteases and pectinases; wort samples. The possibility of complex processing of black currant berries to obtain fermented juice as an additional product, and cake for use in grain–fruit wort has been substantiated. It was shown that as a result of the biocatalytic destruction of the protein-pectin complex of berry raw materials, the main part of fiber passed into the cake. The concentration of amine nitrogen was 315 mg%, soluble carbohydrates — 6.8%, phenolic substances — 94.75 mg%, pH — 3.0. It was found that with the combined hydrodynamic and enzymatic processing of grain and fruit raw materials, the introduction of blackcurrant cake into the composition of raw ingredients had a negative effect on the rheological properties of the wort, the viscosity of which increased almost three times. Rational conditions for the preparation of wort from mixed wheat raw materials and blackcurrant cake when used together have been selected: the hydromodule of the wort is 1:3; the dosage of hemicellulase enzymes is 0.3 units /g (может быть units KS/g) of raw materials; the content of the raw components of the cake is not more than 30%. The advantage of separate preparation of the raw components (wheat batch and fermented cake) of wort followed by combination at the stage of saccharification and proteolysis was revealed. With this method, the viscosity of the wort was significantly reduced. The concentration of total and soluble carbohydrates increased. Analysis of the carbohydrate profile showed that in wheat wort glucose was prevalent (8.1%). In grain-fruit wort, glucose and fructose were present in almost equal proportions. A block diagram has been developed for the separate preparation of raw materials (grain and blackcurrant cake) in the technology of grain-fruit distillates.