bluuebunny/crossref_metadata_2025_split huggingface dataset:
Osteoporosis and chronic tendinopathy: a two-sample Bidirectional Mendelian randomization
Authors: Wu Hongfei , Cui Yushi , Gao Yun , Zhang Xingping , Zhang Shuai , Wang Mingyuan , Zhang Zhilong , Yang Shengping 
Published: October 2024

Abstract

BACKGROUND The incidence of osteoporosis rises with advancing age, and it has emerged as a significant global public health issue, often presenting clinically with symptoms such as pain, kyphosis, reduced height, and fractures.Chronic tendinopathy is a common orthopedic disease, which is mainly characterized by pain, delayed and difficult to heal, causing great pain to patients. Preliminary epidemiological studies have investigated the potential association between osteoporosis and chronic tendinopathy; however, a definitive causal relationship has yet to be established. With increasing life expectancy and an accelerating aging population, the burden of osteoporosis and chronic tendinopathy is expected to rise significantly, with important implications for morbidity and mortality.METHODS Instrumental variables were selected from the IEU GWAS database of summary statistics. Five different bone mineral density (BMD) sites—heel, total body, femoral neck, lumbar spine, and ultradistal forearm BMD—along with total body BMD across five age groups (0–15, 15–30, 30–45, 45–60, and over 60 years) were utilized as osteoporosis phenotypes. Achilles tendinitis, Bicipital tendinitis, Calcific tendinitis, Calcific tendinitis of shoulder, Gluteal tendinitis, Patellar tendinitis were selected, Peroneal tendinitis represent Chronic tendinopathy phenotypes. Multiple analytical methods were employed to comprehensively assess the causal relationship between chronic tendinopathy and osteoporosis. Sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, and 'leave-one-out' analysis, were conducted to verify the robustness of the findings.RESULTS Mendelian Randomization analysis revealed a significant causal relationship between five different sites of BMD and Calcific tendinitis of the shoulder; Additionally, MR demonstrated a significant causal relationship between Heel BMD, Lumbar spine BMD and Peroneal tendinitis. In the Mendelian Randomization analysis examining age-related bone mineral density (BMD) and chronic tendinopathy, significant causal relationships were identified between total body BMD in the age groups 0–15 years, 45–60 years, and over 60 years with calcific tendinitis of the shoulder.. In all inverse analyses, no significant causal association between chronic tendinopathy and osteoporosis was observed. The reliability of these results was confirmed through sensitivity analyses.CONCLUSION Osteoporosis may be a potential etiological factor for chronic tendinopathy, with a significant causal relationship observed between BMD and chronic tendinopathy, particularly in individuals over 45 years of age. This suggests that patients presenting with chronic tendinopathy may have an underlying issue of osteoporosis. Therefore, routine bone mineral density (BMD) screening is recommended for individuals over 45 years of age who present with chronic tendinopathy.
Interpretable Machine Learning Approaches for Children's ADHD Detection Using Clinical Assessment Data: An online web application deployment
Authors: Qin Han , Zhang lili , Wang Jianhong , Yan Weiheng , Wang Xi , Qu Xia , Peng Nan , Wang Ling 
Published: October 2024

Abstract

Background
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent mental disorder characterized by hyperactivity, impulsivity, and inattention. This study aims to develop a verifiable and interpretable machine learning model to identify ADHD and its subtypes in children using clinical Assessment scales data.
Methods
This study utilized the ADHD-200 dataset, including demographic data, Behavioral Rating Scale, and Wechsler Intelligence Scale assessments, to train and validate our models. The model's performance was evaluated using 10-fold cross-validation within the internal dataset, and the best model will be used for external validation. Seven machine learning models were evaluated. The SHapley Additive exPlanations (SHAP) method was employed for model interpretation. Finally, a web application will deploy the prediction model to provide ADHD probabilities based on user input.
Results
The Random Forest (RF) model performing best in identifying ADHD and the Support Vector Machine (SVM) model excelling in distinguishing ADHD subtypes. The RF model achieved an AUC of 0.99 in 10-fold cross-validation and an AUC of 0.99 in external validation, and the SVM model achieved a micro-average AUC of 0.96 and an accuracy of 0.83 in internal validation and a micro-average AUC of 0.96 and an accuracy of 0.85 in external validation. We used SHAP to interpret the models, revealing that higher ADHD Index pushed the model towards ADHD classification. Additionally, lower IQ scores were correlated with a higher likelihood of ADHD, consistent with previous studies. The dependency analysis found that the model can identify different behavioral scales. We deployed the final model online using a web application and showed users how the model made decisions.
Conclusions
Our findings highlight the potential of using machine learning and clinical assessment scales to support the diagnosis and subtype identification of ADHD in children, offering a practical solution for improving diagnostic accuracy and efficiency in clinical settings.
The burden of Gastric Cancer and possible risk factors from 1990 to 2021，and projections until 2035: findings from the Global Burden of Disease Study 2021
Authors: Fan Yangyan , Qin Niping , Yang Zhiping , Fan Daiming 
Published: October 2024

Abstract

Background
Gastric cancer exhibit high morbidity and mortality rate in China, resulting in substantial disease burdens. A comprehensive evaluation of the burden is crucial to improve strategies for gastric cancer prevention and treatment.
Methods
We collected incidence, deaths, disability-adjusted life-years (DALYs), age-standardized incidence rate(ASIR), age-standardized death rate (ASDR), age-standardized DALY rate (ASR) of gastric cancer at the global, regional, and national levels in all 204 countries and territories from 21 regions during 1990 to 2021. The Bayesian age-period-cohort model was applied to project future trends until 2035.
Results
In 2021, The new cases, deaths and DALYs of gastric cancer increased. More than 1.23 million incident cases of gastric cancer were reported worldwide, which caused 954373.60 deaths and 22786633.10 DAYLs. The age-standardized rates for incidence, death and DALYs decreased by-42%(-49% to -35%),-49%(-55% to -43%) and − 53%(-58% to -47%) from 1990 to 2021, respectively. The highest age-standardized incidence and death rates in 2021 were observed in the High-middle SDI quintile. Both the age-standardized death, incidence and DALYs rate among males were all higher than those among females. In 2021, East Asia and High-income North America had the highest disease burden related to smoking, and Central Europe had the highest disease burden related to diet high in sodium. Furthermore, projections suggest that the ASIR and ASDR of gastric cancer will likely follow steady downward trends by 2035.
Conclusions
Gastric cancer continued to cause a heavy burden globally and in different countries and regions, with significant decreased in the incidence and mortality. Death and DALY rates attributable to high sodium diet and smoking have generally declined. There are still significant differences between age groups and regions. Targeted preventive measures, such as controlling smoking and increasing intake of fresh vegetables and fruits, should be taken in the future to reduce the risk of gastric cancer
Identification of the citrus GRF gene family and its expression in fruit peel thickening mediated by gibberellin
Authors: Liu Xin , Chen Yuewen , Yuan Bo , Peng Miao , Zhao Yushuang , Chen Tong , Lu Jiawei , Li Feifei , Lu Xiaopeng , Yang Junfeng 
Published: October 2024

Abstract

Background
Growth-regulating factors (GRFs) play a crucial role in plant growth and development, particularly in cell division and expansion. Citrus fruit cracking, a prevalent issue, adversely impacts both yield and fruit quality. Gibberellins (GAs) are known to ameliorate citrus fruit cracking by inducing thicker peel formation, which is attributed to cell division and expansion. However, the mechanistic link between gibberellins and citrus peel thickening, and whether this process is mediated by GRF genes regulation, has not been definitively established.
Results
In this study, 8 CsGRFs (Citrus sinensis), 11 CcGRFs (Citrus clementina), and 8 CgGRFs (Citrus grandis) were identified from the citrus genome which divided into six clusters, with the genes of the same cluster sharing similar gene structures. Cis-elements analysis revealed that the promoter regions of GRF genes contained numerous hormone-responsive elements. Tissue expression profiles showed that CsGRF genes had higher expression levels in young tissues, including early fruit tissues, one-year-leaf, ovules, and root tips. RNA-seq and qPCR analyses revealed that the expression levels of CsGRF3, 4, 7, and 8 were significantly regulated in response to GA3 treatment. Notably, CsGRF8 was the most significantly induced by GA3 and highly expressed in the early stages of peel development. These findings indicate gibberellins may exert regulatory effects on peel development through the induction of CsGRF genes.
Conclusion
This study systematically analyzed the characteristics of the citrus GRF gene family, as well as the changes in citrus peel thickness and the expression patterns of CsGRF genes under gibberellin treatment. These findings provide valuable insights for advancing research on the role of CsGRF genes in regulating citrus peel development, which could help reduce the occurrence of fruit cracking.
A deep learning-based approach for Multiple Sclerosis Lesion Segmentation
Authors: Abdelali Hanene Ben , Sahnoun Mouna , Sakka Salma , Damak Mariem , Siarry Patrick , Kallel Fathi 
Published: October 2024

Abstract

Purpose: Multiple Sclerosis (MS) is a chronic disease of the Central Nervous System (CNS), characterized by the presence of disseminated lesions in the brain and Spinal Cord (SC). Magnetic Resonance Imaging (MRI) has become an essential tool for studying the anatomy and functions of the CNS in vivo, enabling not only the identification of brain structures but also the detection of damaged tissue in various neurodegenerative diseases, including MS. The segmentation of lesions on MR images is a crucial step in the diagnosis and monitoring of the disease. However, manual segmentation of MS lesions is a complex and time-consuming task requiring considerable expertise.
Methods: This paper proposes a fully automated method for MS lesion segmentation based on a Convolutional Neural Network (CNN) architecture. The model was trained on datasets from the MICCAI 2016 and ISBI 2015 international challenges. FLAIR images from these databases were used as input to the CNN.
Results: The results show a significant improvement in the accuracy and robustness of the model, resulting in high-quality segmentation of MS lesions. The model achieved remarkable performance, with a Dice Similarity Coefficient (DSC) of over 89%, outperforming recent methods.
Conclusion: These promising results underline the considerable potential for future advances in the automated segmentation of MS lesions.
GPU Accelerated Security Constrained Optimal Power Flow
Authors: Degleris Anthony , Gamal Abbas El , Rajagopal Ram 
Published: October 2024

Abstract

We propose a GPU accelerated proximal message passing algorithm for solving contingency-constrained DC optimal power flow problems (OPF). We consider a highly general formulation of OPF that uses a sparse device-node model and supports a broad range of devices and constraints, e.g., energy storage and ramping limits. Our algorithm is a variant of the alternating direction method multipliers (ADMM) that does not require solving any linear systems and only consists of sparse incidence matrix multiplies and vectorized scalar operations. We develop a pure PyTorch implementation of our algorithm that runs entirely on the GPU. The implementation is also end-to-end differentiable, i.e., all updates are automatic differentiation compatible. We demonstrate the performance of our method using test cases of varying network sizes and time horizons. Relative to a CPU-based commercial optimizer, our implementation achieves well over 100x speedups on large test cases, solving problems with over 500 million variables in under a minute on a single GPU.
Do floral traits and rewards effects floral visitation in Syzygium parameswaranii; An Endangered evergreen tree of the southern Western Ghats of India?
Authors: Reghunath Athira , Surendran Anjana , Ramasubbu Raju 
Published: October 2024

Abstract

Syzygium parameswaranii is a mass-blooming endangered tree species endemic to the Western Ghats of India. The reproductive phenoevents of S. parameswaranii were significantly correlated with temperature which indicated that the flowering phenoevents should be accelerated by a specific temperature. Due to its poor floral rewards (nectar) and advertisement, a limited number of floral visitors were drawn to the blossoms of S. parameswaranii. Since there were no attractive or colourful sepals or petals, the large number of stamens served as the major floral attractant and provided pollen grains as a major floral reward because the quantity of nectar was very low. The diversity of floral visitors in S. parameswaranii was relatively limited when compared to other species of Syzygium. The flowers were attracted and visited by only twelve species including ants, bees, beetles, butterflies, moths and wasps. Among these visitors, only seven of them served as efficient pollinators. Scolia dubia was recorded with higher visitation frequency (0.78 ± 0.11) and visitor activity index (0.89) than any other visitor. Due to their frequent visits and effective stigma contact, they were recorded as the most effective pollinators of S. parameswaranii.
Exploring the Effects of Cancer-Associated Mutations in Selected Cell Lines Using Online Computational Tools
Authors: Premkumar Rohid 
Published: October 2024

Abstract

This research aimed to investigate the mutations in selected cancer-related genes across three different cell lines: A549, NCI-H23, and NCI-H460. The genes of interest included HSP90AA1, TBL1XR1, ZFHX3, DDR2, LIFR, and MYH11, with a focus on their mutation profiles and potential impacts on cancer development. Various online programs, including PolyPhen-2, Mutation Master, and DynaMut, were employed to analyze the functional effects of mutations on the proteins encoded by these genes. Results indicated that HSP90AA1 and DDR2 had high Mutation Master scores, suggesting a strong association with disease. PolyPhen results showed that HSP90AA1 and ZFHX3 mutations were predicted to be probably damaging, while TBL1XR1 was classified as benign. The DynaMut analysis revealed significant changes in flexibility and stability for most mutations, particularly highlighting the destabilizing effects of TBL1XR1 and ZFHX3. The Swiss-Model results showed full green structures upon superposition of wild-type and mutant proteins, indicating minimal structural differences. However, the absence of results for ZFHX3 in Mutation Master due to missing transcript data emphasizes the challenges faced in mutation research. The findings provide insights into the mutation landscape of these genes, suggesting potential avenues for further investigation in cancer research.
A prospective randomized comparative analysis of bipolar TURP and high-power Thulium vapoenucleation in the management of benign prostatic hyperplasia.
Authors: Paighan Nitin , Goel Hemant , Saini Abhishek , Akhil Shrrey , Makkar Arun 
Published: October 2024

Abstract

Background:
Benign prostatic hyperplasia is on the rise as the life expectancy has been increased due to medical advancements. TURP once a gold standard is now slowly been replaced by lasers. As patients continue seeking less invasive and more efficient treatment options, they must be provided with evidence-based treatment options. Studies using 200-watt thulium lasers are scant and have a mixed population of small and large prostates. This study focuses mainly on large prostates(>60 cc) avoiding the biases in operating time and hospital stay and intends to to compare efficacy and outcomes of bipolar transurethral resection of the prostate (TURP) vs High power thulium vapoenucleation of the prostate (ThuVEP) in benign enlargement of the prostate.
Methods:
A total of 68 patients were included in our study of which 34 were randomly divided in 2 arms viz Bipolar TURP group V/s ThuVEP with a prostate size of more than 60 ccs..
An analytical between-group comparison was made of preoperative and perioperative data including operation time, intraoperative blood loss by measuring spothemoglobin on postoperative day 1, hospital stay, intra-operative and perioperative complications like capsular perforation, bleeding requiring transfusion, urinary tract infections, etc. Postoperative data was collected at 2 weeks, 6 weeks, and 3 months after surgery on IPSS, uroflowmetry with PVR, and residual prostate size at 3 months. Post-operative complications like SUI, urethral strictures, bladder neck stenosis, and the need for surgery for residual adenoma, were also compared.
Results:
ThuVEP was associated with statistically significant shorter resection time, lesser requirement of irrigation fluid in the postoperative period, less blood loss, & shorter hospital stay. IPSS, PVR, and voiding time were comparable between the 2 groups. The ThuVEP group had better Qmax and Qavg and residual prostate size at all times during follow-up. The two groups were similar in terms of complications.
Conclusion:
Both procedures could be performed with equal safety in larger prostates. However, ThuVEP outperformed Bipolar TURP in terms of blood loss, hospital stay , post-operative uroflow parameters, and residual prostate size.
Synthesis of self-curing bio-based eugenol-epoxy resin an application to metal surface coating
Authors: Patil Arunkumar , Pawar N S , Mali Pundalik , Tayade Madhukar , Borse Kundan , Patil Vikas 
Published: October 2024

Abstract

Eugenol an active reagent extracted from the plant are being used as one of the composite materials for the preparation of monomer. In a course of successive reaction eugenol was reacted with the 1,4-butandiol diglycidyl ether yields the reactive species 3,3'-(butane-1,4-diylbis (oxy) bis(1-(4-allyl-2-methoxyphenoxy) propane-2-ol). It contains the two alcoholic hydroxy which further reacted with the epichlorohydrin gives the 2,2'-(3,12-bis((4-allyl-2-methoxyphenoxy) methyl)-2,5,10,13-tetraoxatetradecane-1,14-diyl) bis (oxirane) (BMTO). BMTO is an active monomer consisting of two epoxy functionals at terminal. In the next series of experiments the combination of epoxy acrylate resin with BMTO in presents of fixed amount of triethyl tetraamine formulated give the polymer composite material. The polymer material formed has an active bio-ingredient eugenol known for its antimicrobial activity over the coating to metal substrate. The final polymer has the tested with the various tests such as X-ray diffraction (XRD), gel content analysis, water absorption testing, thermogravimetric analysis (TGA), and a differential scanning calorimeter (DSC) study. The results showed effective nature of eugenol-based epoxy (BMTO). The functionality of the eugenol-based epoxy (BMTO) and structural properties were evaluated by gas chromatography-mass spectrometry (GC-MS), proton nuclear magnetic resonance (1H-NMR), and infrared (IR) spectra. The study examined the properties of cured epoxy, focusing on its thermal, mechanical, and anti-corrosion characteristics.
A high-efficient artificial bee colony algorithm with random neighborhood search and population state evaluation
Authors: Cao Yang , Wang Junlei 
Published: October 2024

Abstract

Artificial bee colony(ABC) algorithm performs well in the exploration process, but develops poorly in the exploitation process. How to balance the exploration and development of the algorithm during the evolution process has always been a challenge for the ABC algorithm.At the same time, for complex problems, the ABC algorithm may experience premature convergence or stagnation during the evolution process. To overcome these challenges, this paper proposes an effective variant of the ABC algorithm (random Neighborhood search Artificial Bee Colony with Population State Evaluation), referred to as NABC-PSE. In the NABC-PSE algorithm, a random neighborhood method is introduced, and different search strategies are designed for the employed bees and onlooker bees phases based on the best solution within the neighborhood. Additionally, a population state evaluation mechanism is added during the onlooker bee phase to allocate appropriate evolutionary strategies for the population when it becomes stagnant or converges prematurely. To address the issue of the roulette wheel mechanism where individual fitness becomes less distinct in the later stages of evolution, a selection strategy based on sorting is employed. Finally, to make more effective use of dimensional information, a greedy selection method is used to choose the dimensions for improvement.To validate the effectiveness of the algorithm, the NABC-PSE algorithm was tested on a set of 22 benchmark functions and compared with some other ABCs and several state-of-the-art algorithms. The results show that the proposed algorithm has high solution quality, fast global convergence rate.
Proposed Method of Acquiring Train Data for Early-Modern Japanese Printed Character Recognizers
Authors: Koiso Norie , Takemoto Yuki , Ishikawa Yu , Takata Masami 
Published: October 2024

Abstract

The National Diet Library's digital collection contains approximately 400,000 valuable books from the Meiji period to the early Showa period. These books are stored as image data and have not been converted into text. Therefore, the use of information is limited. Manual and automatic methods exist for texting early-modern Japanese printed books, but manual methods cost a fortune. Optical character recognition is used for automation, but the characteristics of early-modern Japanese printed characters and the differences in shape between early-modern Japanese printed characters and printed characters reduce the recognition rates. Therefore, developing a character recognition method specific to early-modern Japanese printed books is necessary. Collecting early-modern Japanese printed characters is also manual, and collecting several characters evenly is difficult. In this study, we propose a method to improve the accuracy of early-modern Japanese printed character recognition accuracy using images generated from early-modern Japanese printed characters. CycleGAN is used to generate images from early-modern Japanese printed characters. The generated image is incorporated into training data to create a character recognition model. The experiment demonstrated that the recognition rate improved using the generated images in the training data.