bluuebunny/crossref_metadata_2025_split huggingface dataset:
Catalysis in Motion: Large-Scale Domain Alternation Enables Co(III)-C Bond Homolysis in Lysine 5,6-Aminomutase
Authors: Tian Shiliang , Pham Khai , Voss Peter , Poore Andrew , Liu Mingxin , Zuercher Eli , Birthright Caitlin , Toba David , Das Natasha , Yachuw Stephen , Denault Christian , Kim Maggie , Klose Thomas , Uyeda Christopher 
Published: November 2024

Abstract

Lysine 5,6-aminomutase (LAM) is a radical-based enzyme that catalyzes the reversible migration of an amino group between the C5 and C6 positions of lysine. This reaction is mediated by the coenzymes adenosylcobalamin (AdoCbl) and pyridoxal 5’-phosphate (PLP). Our study investigated the activation mechanism of AdoCbl in LAM. Using cryo-electron microscopy (cryo-EM), we resolved structures of LAM in both its ‘Open’ and ‘Closed’ states, revealing a substantial 64.1-degree rotation of the Rossmann domain upon substrate binding, which shifts the AdoCbl cofactor 25.5 Å towards PLP. This large conformational shift enables Co(III)-C homolysis and adenosine radical (Ado•) formation. Following domain alternation, adenosine is stabilized by a key hydrogen bond network composed of Lys371α, Asp299α, and Glu412α, while PLP is anchored by hydrogen bonds and electrostatic interactions with two Tyr and two Arg residues, securing the substrate lysine in place. The enzyme pocket is precisely designed to ensure the proper orientation and positioning of Ado• and PLP-substrate complex, facilitating efficient hydrogen abstraction from the substrate after the formation of the highly reactive Ado• radical, which is crucial for maintaining catalytic efficiency. This study provided the first structural information supporting the long-existing hypothesis of Rossmann domain rotation as part of the LAM activation process, shedding light on the enzymes' conformational dynamics and illustrating how nature employs domain movements to activate metallocofactors and control radical chemistry.
An Interpretable Framework for Gastric Cancer Classification Using Multi-Channel Attention Mechanisms and Transfer Learning Approach on Histopathology Images
Authors: Zubair Muhammad , Owais Muhammad , Hassan Taimur , Bendechache Malika , Hussain Muzammil , Hussain Irfan , Werghi Naoufel 
Published: November 2024

Abstract

The importance of gastric cancer and the role of deep learning techniques in categorizing gastric cancer histopathology images have recently increased. Identifying the drawbacks of traditional deep learning models, including lack of interpretability, inability to capture complex patterns, lack of adaptability, and sensitivity to noise. We suggest a multi-channel attention mechanism-based framework that can overcome the limitations of conventional deep learning models by dynamically focusing on relevant features, enhancing extraction, and capturing complex relationships in medical data. The proposed framework uses three different attention mechanism channels and convolutional neural networks to extract multichannel features during the classification process. The proposed framework’s strong performance is confirmed by comparative experiments conducted on a publicly available Gastric Histopathology Sub-size Image Database, which yielded remarkable classification accuracies of 99.07% and 98.48% on the validation and testing sets, respectively. Additionally, on the HCRF dataset, the framework achieved high classification accuracy of 99.84% and 99.65% on the validation and testing sets, respectively. The effectiveness and interchangeability of the three channels are further confirmed by ablation and interchangeability experiments, highlighting the remarkable performance of the framework in gastric cancer histopathological image classification tasks. This offers an advanced and pragmatic artificial intelligence solution that addresses challenges posed by unique medical image characteristics for intricate image analysis. The proposed approach in artificial intelligence medical engineering demonstrates significant potential for enhancing diagnostic precision by achieving high classification accuracy and treatment outcomes.
New technology to utilise and suppress weeds for sustainable maize production
Authors: Wu Kaixian , Zhou Shiyong , Zeng Guang , Yang Hongli , Wu Bozhi 
Published: November 2024

Abstract

Across the agricultural chronicle, mankind has relentlessly pursued myriad strategies to vanquish weeds and avert yield diminishment. Yet, a pragmatic technology adept at leveraging weeds as a beneficial biological resource, without compromising crop yields, has remained elusive. Our study unveils an innovative Integrated Technology to Utilise and Suppress Weeds (ITUSW) for sustainable maize cultivation. ITUSW ingeniously harnesses inter-row weed biomass and curtails intra-row weeds, attaining sustainable maize yields without sacrifice, outshining conventional global weed management practices. This technology amalgamates a spectrum of non-chemical weed suppression tactics into a practical system, harmonizing with globally recognized sustainable agricultural principles. By championing ITUSW, this research propels agriculture towards enhanced sustainability, redefining weeds from foes to allies, safeguarding yields and the environment.
Association between high-sensitivity C-reactive protein and diabetes mellitus
Authors: Yuan Jianxu , Zhou Dalin , Yu Shengjie 
Published: November 2024

Abstract

Background: The objective of this research endeavor was to delve into the interplay between high-sensitivity C-reactive protein (hs-CRP) levels and the risk of diabetes mellitus (DM).
Methods: This study examined the correlation between hs-CRP levels and DM risk by analyzing a sample of 7,614 adults from the United States, drawn from the National Health and Nutrition Examination Survey (NHANES) between 2017 and 2020. Employing multivariable logistic regression models, the research delved into the intricate relationship. Furthermore, to gain insights into potential variations across diverse populations, we incorporated subgroup and interaction analyses. Finally, Mendelian randomization (MR) was used for validation.
Results: In this study, 1,214 people were diagnosed with DM, and 6,400 people did not have DM. Utilizing a weighted multivariate logistic regression model that accounted for various covariates, the findings revealed that hs-CRP levels emerged as a significant risk factor for DM, with an odds ratio (OR) of 1.020 and a 95% confidence interval (CI) ranging from 1.005 to 1.034 (P < 0.05). Subgroup analyses consistently demonstrated a robust positive association across diverse categories, underscoring the universality of this relationship. Interaction tests further validated the consistency of this positive link, remaining unaffected by factors such as gender, age, race, education levels, body mass index (BMI), or diet behavior (DB), as evidenced by all interaction P-values exceeding 0.05. However, as the study observed that individual characteristics like triglyceride (TG) levels mediated the strength of this connection, with interaction P-values falling below 0.01, indicating its potential role in modulating the risk posed by hs-CRP on DM. The results of MR also indicated a positive correlation.
Conclusion: Our research showed that elevated hs-CRP levels increased the risk of DM, and improving its levels might help prevent and treat DM.
3D Printing of High-strength, Degradable and Antibacterial PLA/TPU/PMF composites
Authors: Chen Yinpeng , Niku Guge , He Meiyi , Fan Xiaoxi , Wang Shuang , Zheng Wen Jiang 
Published: November 2024

Abstract

This study investigates the 3D printing strategy for preparing polylactic acid/polyurethane elastomer/phosphorus-magnesium fiber (PLA/TPU/PMF) composites with biocompatibility, mechanical strength and antibacterial properties. The magnesium phosphate whisker PMF significantly enhances the antibacterial performance of the composite and remains stable against environmental oxidation, even after 24 hours in a 20% H2O2 solution at 37°C. Compared to hot-pressing, the 3D printed composite exhibits better mechanical properties, including higher Young's modulus (500 Mpa) and tensile strength (8 Mpa), as well as reduced stress relaxation. The compatibility of 3D printing with composites allows for versatile shapes and structures, such as curved nails, round rings, and more complex shapes like Christmas trees. In addition, the interactions between PLA, TPU and PMF accelerate degradation, allowing complete degradation within 15 days in an oxidative environment at 37°C with 20% H2O2.
Experimental research on the behavior of circular SFRC columns reinforced longitudinally by GFRP rebars
Authors: Saffarian Iman , Atefatdoost Gholam Reza 
Published: November 2024

Abstract

This research presents the experimental and theoretical evaluations on circular steel-fiber-reinforced-concrete (SFRC) columns reinforced by glass-fiber-reinforced-polymer (GFRP) rebar under the axial compressive loading. Test programs were designed to investigate and compare the effect of different parameters on the structural behavior of columns by performing tests. Theses variables included conventional concrete (CC), fiber concrete (FC), steel/GFRP longitudinal rebars, and transversal rebars configurations. A total of 16 specimens were constructed and categorized into four groups in terms of different rebarconcrete configurations, including GFRP-rebar-reinforced-CC columns (GRCC), GFRP-rebar-reinforced-FC columns (GRFC), steel-rebar-reinforced-CC columns (SRCC) and steel-rebar- reinforced-FC columns (SRFC). Experimental observations displayed that failure modes and cracking patterns of four groups of columns were similar, especially in pre-peak branches of load-deflection curves. Although the average ultimate axial load of columns with longitudinal GFRP rebars was obtained by 17.9% less than the average ultimate axial load of columns with longitudinal steel rebars, the average axial ductility index (DI) of them was gained by 10.2% higher than their counterpart columns. Adding steel fibers (SFs) into concrete led to the increases of 7.7% and 6.7% of the axial peak load and the DI of columns than their counterpart columns with CC. The volumetric ratio had greater efficiency on peak loads and DIs of columns than the type of transversal reinforcement. A simple analytical equation was proposed to predict the axial compressive capacity of columns by considering the axial involvement of longitudinal GFRP rebars, volumetric ratio, and steel spiral/hoop rebar. There was a good correlation between test results and predictions of the proposed equation.
Study of medical students' knowledge about the effect of energy drink and nutritional supplement consumption on pulse and blood pressure, a comparative study between males and females.
Authors: Almshhad Falak Mouhamad , alkhoja Rouaa , Hammoud Taghreed 
Published: November 2024

Abstract

Background
Energy drink consumption has increased dramatically in the past two decades, especially among young adolescents. Energy drinks are heavily marketed with the claim that these products provide a boost of energy to improve physical and cognitive performance, however, studies supporting these claims are limited. Dietary supplements (minerals/vitamins) also play a pivotal role in regulating blood pressure because they help in the function of macronutrients and also improve the functions of some blood pressure-lowering factors. Our aim was to study the knowledge of medical students about the effect of consuming energy drinks and dietary supplements on pulse and blood pressure.
Methods
A cross-sectional descriptive study was conducted at the Syrian Private University (Daraa Governorate) during the period 23/9/2024 to 4/10/2024. The responses of participating medical students were studied through a questionnaire distributed in paper and electronic form on the university campus.
Results
Our study included 300 students, with a percentage of males (51%) and females (49%). The largest percentage of participants were fourth-year students (43.7%). The most participating age group was “22 − 18” (79.7%). More than half of the students (60.7%) were aware of the common ingredients found in energy drinks. The majority of students (97.7%) responded that excessive consumption of energy drinks has a clear effect on pulse and blood pressure. The frequency of their consumption of energy drinks was as follows: never (40%), rarely (less than once a month) (29%), daily 16 (5.3%).
Conclusion
Energy drinks and nutritional supplements may have positive beneficial effects on academic performance or exercise and in various other activities, however, potential harmful health problems have been documented, especially among young people and adolescents. We found that the participating students had an acceptable level of awareness about the consumption of energy drinks and nutritional supplements and their potential effect on pulse and blood pressure. We also found that a small percentage of them had consumed these drinks and experienced some of their effects.
Experiment-driven Simplification of Johnson-Champoux-Allard-Lafarge Model for Fibrous Materials
Authors: Yang Tao , Eser Martin , Xiong Xiaoman , Groby Jean-Philippe , Maeder Marcus , Chang Yu-Hao , Marburg Steffen 
Published: November 2024

Abstract

Widely used empirical and semi-phenomenological models lack practicality due to unstable predictions or reliance on numerous parameters that are not directly measurable. This paper presents an experiment-driven method to simplify the Johnson–Champoux–Allard–Lafarge (JCAL) model by utilizing and relying on a two-microphone impedance tube only. Inverse characterization is applied to determine the non-acoustical parameters (i.e., tortuosity, airflow resistivity, viscous and thermal characteristic lengths, and static thermal permeability), and the regression method is then used to correlate porosity with these non-acoustical parameters. The simplified JCAL model is validated against the original model and experimental results for acrylic, silk, and wool fibers. The models perform well for porosities between 92% - 98% but underestimated sound absorption at 99% due to frame vibration effects. This experiment-driven simplification method reduces the JCAL model to a single parameter, porosity, enhancing efficiency, enabling faster predictions, and making the model more applicable to optimization strategies and broader applications.
Drug Evaluation Based on Multiple Criteria for Dry Eye Disease: A QSPR-Enhanced VIKOR and TOPSIS Approach Utilizing Degree-Based Topological indices
Authors: Shanmukha M C , Kirana B , Usha A , Shilpa K C 
Published: November 2024

Abstract

A healthy human tear film constitutes proteins, electrolytes, water, lipids, mucins, and vitamins. The lack of production of tear in the eye leads to dry eye disease(DED) which is also termed as “Sjögren’s syndrome”. Utilizing degree-based topological indices on molecular graphs reveal insights into the physicochemical properties of these drugs, such as polar surface area, polarizability, boiling point, enthalpy, molar refraction, molar volume, molecular weight and complexity are crucial in predicting their efficacy in the treatment. Various studies have been carried out in QSPR/QSAR analysis using linear regression and curvilinear regression. In this article, multiple linear regression is applied to find the correlation between seven physicochemical properties and 11 topological indices for dry eye disease drugs. For the considered properties of drugs under the study, Polarizability has shown significant results with high correlation and least RMSE (R=0.996 & RMSE=1.419) using various significant topological indices. The study is extended to evaluate and rank 22 dry eye disease drugs using Multi-Criteria Decision-Making (MCDM) techniques such as TOPSIS and VIKOR. The analysis revealed that Tacrolimus and Cyclosporine being ranked number 1 and number 22 respectively as identified by TOPSIS and VIKOR.
Resolving the conflict between the need for electricity generation upstream and the water supply for economic development downstream in the Ca River Basin, Vietnam
Authors: Nguyen Thien Dung , Luong Chung Ngoc 
Published: November 2024

ABSTRACT
Vietnam has vigorously developed hydroelectric reservoirs in main river basins with hydroelectricity reserves to produce electricity and exploit and use water resources efficiently and minimally – risks to meet socio-economic development requirements – in the downstream area. The study has shown evidence that the water level's daily mean value of the Ca River is increasingly reduced. However, the number of occurrences of the daily minimum flow was more than that of the period when it was not hydropower reservoirs and was affected by climate change. The study calculated and built five scenarios for water use in the downstream areas. These scenarios are calculated based on the water demand for domestic, industry, irrigation, and water sea level. A simulation model was developed for optimal hydropower generation of reservoir system upstream and forced to discharge downstream with five scenarios. This study's results demonstrated that four upstream reservoirs could operate with scenario 3 corresponding HNam Dan = 0.7 m. The results suggested options for the operation of hydroelectric reservoirs and simultaneously developed scenarios for taking water for agricultural irrigation downstream of the Ca River Basin with water level for irrigation drains and domestic water factories. The benefit of electricity in four reservoirs in scenario 3 reached 1,009 billion Vietnamese Dong (VND).
An Ayurveda approach for managing Geriatric Sleep Disturbances: A Comprehensive Review
Authors: Pooja Lekhak  , Ram Kishor Joshi  
Published: November 2024

Background: Ageing is defined as the progressive deterioration in structure and function of the body organs. In Ayurveda literature ageing (Jara) has been given importance since Vedic period as the natural, progressive phenomenon. In Ayurveda, Sleep (Nidra) is one of the Upasthambha (Sub-Pillar) which is essential for overall health. Ageing causes multiple changes in sleep patterns, and various diseases can further disrupt sleep. Ayurveda describes the physiological increase of Vata Dosha in old age which causes Vata Prakopa in body leading to degeneration of Dhatu (Dhatukshaya) which alter the sleep patterns. Aim: The paper aims to review common sleep disturbances seen in ageing and their prevention and management through Ayurveda. The study discusses various patterns of sleep during ageing and their possible management through Ayurveda. Primary sleep disorders common in the geriatric population such as; insomnia, obstructive sleep apnea, restless leg syndrome, circadian rhythm sleep-wake disorder was discussed and their management through Ayurveda was reviewed. The selection of Ayurvedic treatment and procedures which nourishes Dhatu and pacify Vata Dosha are effective in managing sleep disturbances. Result: The study finds that Vatashamak Chikitsa, regulation of Agni, Dincharya, Ritucharya, Vegdharan, use of Rasayana, Panchakarma, Yogasana are beneficial for the management of sleep disturbances. Conclusion: Sleep disturbances are common in ageing and can be managed efficiently through Ayurveda.
Comportamiento de la tuberculosis entre individuos en condición de vulnerabilidad. Córdoba. Colombia
Authors: Lozano -M Emily Andrea , Tejada -V Beatriz Elena , Valencia -J Nydia Nina 
Published: November 2024

Objetivo: Analizar el comportamiento de la Tuberculosis (TB) teniendo en consideración las condiciones de vulnerabilidad social. Materiales y métodos: Estudio descriptivo retrospectivo que contó con la información disponible en 27 registros de pacientes con diagnósticos de tuberculosis entre 2017 y 2018. Resultados: La gran mayoría de pacientes (96,3%) contaban con seguridad social subsidiada, exhibiendo una diferencia estadísticamente significativa respecto a aquellos sin afiliación (p<0,05). La ocupación predominante fue agricultora (33,3%), seguida de amas de casa (22,2%) y desempleados (29,6%), con diferencias significativas entre las proporciones (p=0,043). En cuanto a la pertenencia étnica, 74,1% no pertenecía a comunidades indígenas (p=0,05). El 77,8% de los casos correspondió a nuevos ingresos, siendo esta condición mayoritaria con diferencias significativas (p<0,05). El diagnóstico se realizó principalmente mediante baciloscopia (96,3%) con diferencia significativa respecto a histopatología (p<0,001). La tuberculosis pulmonar (88,9%) predominó sobre la extra pulmonar (p<0,05), y solo 11,1% presentaba VIH como comorbilidad (p<0,05). Se evidenció que las condiciones de vulnerabilidad social inciden negativamente en la adherencia al tratamiento supervisado. Conclusión: Las condiciones de vulnerabilidad social por pobreza, edad o por etnia favorecen la circulación del agente de TB en las comunidades desfavorecidas; tal situación indica la necesidad de fortalecer los programas de prevención, seguimiento y control de la tuberculosis mediante estrategias focalizadas e intervenciones efectivas en este grupo poblacional.
Machine Learning–Based Prediction for Incident Hypertension Based on Regular Health Checkup Data: Derivation and Validation in 2 Independent Nationwide Cohorts in South Korea and Japan
Authors: Hwang Seung Ha , Lee Hayeon , Lee Jun Hyuk , Lee Myeongcheol , Koyanagi Ai , Smith Lee , Rhee Sang Youl , Yon Dong Keon , Lee Jinseok 
Published: November 2024

Background
Worldwide, cardiovascular diseases are the primary cause of death, with hypertension as a key contributor. In 2019, cardiovascular diseases led to 17.9 million deaths, predicted to reach 23 million by 2030.

Objective
This study presents a new method to predict hypertension using demographic data, using 6 machine learning models for enhanced reliability and applicability. The goal is to harness artificial intelligence for early and accurate hypertension diagnosis across diverse populations.

Methods
Data from 2 national cohort studies, National Health Insurance Service-National Sample Cohort (South Korea, n=244,814), conducted between 2002 and 2013 were used to train and test machine learning models designed to anticipate incident hypertension within 5 years of a health checkup involving those aged ≥20 years, and Japanese Medical Data Center cohort (Japan, n=1,296,649) were used for extra validation. An ensemble from 6 diverse machine learning models was used to identify the 5 most salient features contributing to hypertension by presenting a feature importance analysis to confirm the contribution of each future.

Results
The Adaptive Boosting and logistic regression ensemble showed superior balanced accuracy (0.812, sensitivity 0.806, specificity 0.818, and area under the receiver operating characteristic curve 0.901). The 5 key hypertension indicators were age, diastolic blood pressure, BMI, systolic blood pressure, and fasting blood glucose. The Japanese Medical Data Center cohort dataset (extra validation set) corroborated these findings (balanced accuracy 0.741 and area under the receiver operating characteristic curve 0.824). The ensemble model was integrated into a public web portal for predicting hypertension onset based on health checkup data.

Conclusions
Comparative evaluation of our machine learning models against classical statistical models across 2 distinct studies emphasized the former’s enhanced stability, generalizability, and reproducibility in predicting hypertension onset.