bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying batch effects for individual genes in single-cell data
Authors: Jin Shuilin , Zhou Yang , Sheng Qiongyu 
Published: October 2024

Abstract

Batch effects significantly impede the comparison of multiple single-cell experiment batches. Existing batch effect removal methods primarily focus on aligning cells across batches, often overlooking gene-level batch effects. Here, we introduce group technical effects (GTE), a quantitative metric to assess batch effects on individual genes. Using GTE, we show that batch effects unevenly impact genes within the dataset. A portion of highly technical genes (HTGs) differ between datasets and dominate the batch effects. Removing these genes effectively integrates the dataset. We demonstrate that as few as three HTGs are sufficient to introduce substantial batch effects. Furthermore, we observe that biologically similar cell types undergo similar batch effects, informing the development of data integration strategies. The GTE method is versatile and applicable to various single-cell omics data types.
Comparison of asymmetric and symmetric centration strategies for photorefractive keratectomy in myopic astigmatism patients
Authors: Salari Farhad , Ghassemi Hamed , Samadi Mahsan , Montazerian Zahra , Atighehchian Mehrnaz , Abdi Parisa , Latifi Golshan , Mosquera Samuel Arba , Zarei-Ghanavati Mehran 
Published: October 2024

Abstract

Purpose:
To compare differences in clinical outcomes of symmetric offset (SO) and asymmetric offset (AO) centration strategies in photorefractive keratectomy (PRK) in patients with myopia or myopic astigmatism.
Methods:
Forty refractive surgery candidates who visited Farabi Eye Hospital’s refractive surgery clinic from May to August 2022 were enrolled in the study. We randomly assigned one of each patient’s eyes to the AO and the other one to the SO group using random blocks. Patients were followed for four months. Ablation profile, Visual acuity (VA), and higher order aberrations (HOA) were evaluated. Effective optical zone (EOZ) and its circularity index were calculated automatically by a MATLAB-based algorithm.
Results:
There was no significant difference between the two groups' total ablation volume and maximum and central ablation depth (all P > 0.05). The two groups showed significant differences in minimum ablation depth, with a higher value for SO than AO (0.03 ± 0.03 and 0.01 ± 0.01, respectively, P-value < 0.001). There wasn’t a significant difference between postoperative mean RMS of higher order aberrations (HOA) among AO and SO groups (all P > 0.05). The EOZ was 6.046 ± 0.63 in the SO group and 6.047 ± 0.68 in the AO group (P value = 0.61, paired t-test).
Conclusions:
In conclusion, symmetric and asymmetric offset centration strategies result in safe and effective refractive correction. There was no significant difference between the two groups' higher-order aberration, visual acuity, refraction, and postoperative total ablation volume.
What Do Patients Learn from the Internet? Evaluation of the Quality of Zygomatic Implant Therapy Information among the Turkish Population: Methodological Study
Authors: Pektaş Muhammet yasin , Topal Olgun 
Published: October 2024

Abstract

As a result of informatics and technological developments, the Internet has become the primary source of reference for accessing information, including about health issues. This study uses the DISCERN instrument to evaluate the quality of Internet-based information Turkish patients use to learn about dental implant therapy. The key phrases “zygomatic implant therapy,” “zygomatic implant,” and “zygomatic screwed tooth” were searched using popular search engines, such as Google (www.google.com.tr), Yandex (www.yandex.com.tr), Yahoo (www.yahoo.com), and Bing (www.bing.com), on September 12–18, 2023. The top ten websites obtained from each search term were determined; 93 of the 120 websites included in the evaluation were measured using the DISCERN instrument, comprising 16 questions. Among the evaluated websites, 57 were dentists or dental clinics, 15 were general or dental health, 6 were news, and 15 were hospitals. The DISCERN score of the evaluated websites ranged from 18 to 52 (mean, 28.62), and the mean DISCERN rating score was 1.93. None of the sites was rated as “excellent,” and three were rated as “good.” The quality of information resources on the Internet about zygomatic implant therapy in Turkey was generally low: the source of the given information was often not cited, the treatment options were not clarified, and contraindications and complications of the treatment were not explained.
Comparative Study on Caesarian and Normal Vaginal Delivery, Rajshahi Division, Bangladesh
Authors: Khatun Mst. Abeda , Najnin Monira , Parvin Rehana , Sayam Mohammad Abdun Nur , Rana Md. Masud 
Published: October 2024

Abstract

Background: One of the most important public health concerns is the marked rise in the number of caesarean sections (CS). The World Health Organization advises against CS rates that are more than 10% and lower than 5% since both of these ranges have the potential to negatively impact the health of expectant mothers and newborns.
Objective: The study aimed to investigate influencing factors for selective CS among pregnant mothers and to determine the association for selective CSamong mothers with selected socio-economic characteristics in Rajshahi Division, Bangladesh.
Methodology: It was a cross-sectional study was conducted. In this study, data were collected July 2024. A semi structured questionnaire was used for collecting data, a total number of 393 delivery mothers were participated in Rajshahi Division, Bangladesh. A descriptive analysis, the chi-square test, and binary logistic regression model were utilized in the present study.
Results: The prevalence of lower educated mothers with normal vigilant delivery (NVD) and CS delivery was 59% and 41%, respectively, and Naogaon district mothers delivered their child by cesarian section compared to other districts in Bangladesh. The women ≥30 years old (AOR = 74.934; 95% CI: 12.831-437.613) were more likely to have preferred CS delivery compared to younger women, and these factors were statistically significant (p<0.01). The educated subjects (AOR = 83.469; 95% CI: 2.554–2727.394) were more likely to have preferred CS delivery compared to their lower educated counterparts, and these factors were statistically significant (p<0.05).
Conclusions: The study revealed that a large number of women preferred CS deliveryespecially higher educated women were mostly. The main reasons for choosing CS were to take advantage of certain socioeconomic and demographic variables, ensure the safety of both mothers and their infants. This study strongly recommended health education. sessions, especially in electronic and print media, about the disadvantages of CS delivery.
Developing an online calculator to estimate the overall survival benefit from adjuvant radiotherapy in patients with early-stage type II endometrial carcinoma
Authors: Chen Xi , Du Junhong , Cheng Yuemei , Wang Fengfeng , Wang Wenhua , Lang Tingyu , Liu Xiaowei , Li Hongli , Yang Yongxiu , liang Xiaolei 
Published: October 2024

Abstract

Objective
The benefit of adjuvant radiotherapy (aRT) on overall survival (OS) in early-stage type II endometrial carcinoma (EC) is not well established. This study aimed to develop nomograms and a web-based calculator to identify these patients who might benefit from aRT.
Methods
Research projects were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, and divided into the developing and validation cohorts. LASSO Cox regression identified prognostic factors, and nomograms were constructed to predict 1-, 3-, and 5-year OS with/without aRT. The expected OS benefit from aRT was indicated by the difference in predicted OS between the two nomograms. Validation involved ROC analysis, calibration curves, and decision curve analysis. A web calculator was created for estimating aRT's net OS benefit.
Results
Among 6084 patients, aRT did not improve OS across all patients but showed benefits in specific subgroups, such as those with clear cell carcinoma and carcinosarcoma. Nomograms were built for patients with and without aRT to predict OS at 1-, 3-, and 5-year, and they can accurately forecast OS, and the web-based calculator was developed to estimate the net OS benefit of aRT.
Conclusions
The nomograms provide accurate OS estimates for early-stage type II-EC patients with/without aRT, supporting individualized treatment decisions. The web calculator offers a quantitative tool for optimizing aRT use based on clinicopathological features.
Electromyographic evaluation of patients with temporomandibular disorders and limited mouth opening Part I: Masseteric activity during maximum opening
Authors: Lin Xiaoyu , Takaoka Ryota , Moriguchi Daisuke , Morioka Shion , Ueda You , Yamamoto Rie , Ono Emi , Ishigaki Shoichi 
Published: October 2024

Abstract

This study aimed to identify the differences in masseteric activity during maximum mouth opening among healthy volunteers, patients with limited mouth opening (LMO) and myofascial pain, and patients with LMO and disc displacement. Thirty-seven patients with temporomandibular disorders and LMO (< 37 mm) and 27 healthy volunteers participated in this study. Patients were categorized into three groups based on magnetic resonance imaging (MRI) findings and clinical symptoms: disc displacement (DD), disc displacement with myofascial pain (DD + M), and myofascial pain (M). After a five-minute relaxation period, the participants were instructed to perform maximum opening (Omax) and maintain the Omax position for five seconds, and this was repeated three times. Subsequently, the participants were asked to perform maximum voluntary clenching for five seconds, which was repeated twice. At rest, no significant masseter potential differences were observed among the DD, DD + M, M, and healthy groups (p > .05). However, during Omax, the DD + M and M groups exhibited significantly higher masseteric potential than the healthy and DD groups (p < .001). Furthermore, the masseteric potential during Omax correlated with the pain level. Overall, there are distinct differences in masseteric activity levels between patients with LMO and with or without myofascial pain or disc displacement.
Comparative efficacy of biochar vs. cooking charcoal in urea-based soil fertility management: Impacts on soil quality, nutrient Retention, and maize performance
Authors: Oyeyiola Yetunde Bunmi , Ewetola Esther Abosede , Kolawole Gani Oladejo , Lawal Babatunde Akeem 
Published: October 2024

Abstract

Biochar stands out for its valuable properties in promoting sustainable agricultural practices. However, Nigerian farmers face significant challenges in adopting biochar due to the high costs associated with acquiring pyrolizers or fabricating local kilns. They are, however, familiar with charcoal production for domestic use. This screen house trial was a factorial combination of three black carbon types: biochar, charcoal, and no black carbon (NBC) with each applied at 5 t/ha and three urea levels: 0, 30 and 60 kg N/ha). Maize was grown on the amended soils for six weeks. The Fourier Transform Infrared scans revealed differences between the two black carbons, with biochar showing sharper peaks at wavelengths 1588, 1375, and 1100 nm. Soils amended with biochar significantly outperformed those treated with charcoal or no black carbon, showing higher levels of soil organic carbon (7.05 g/kg compared to 5.12 and 4.09 g/kg for charcoal and NBC, respectively), available phosphorus (135.57 mg/kg compared to 4.12 and 5.48 mg/kg for charcoal and NBC, respectively), exchangeable bases, maize nitrogen and phosphorus uptake, and total dry biomass yield. Paired T-tests revealed significant differences in the impact of biochar and charcoal on soil organic carbon and nutrient conditions, ultimately affecting maize performance. Therefore, cooking charcoal cannot substitute for biochar when the soil and environmental benefits associated with biochar are desired.
Assessment of Seasonality of Stream Water Quality: a Case Study of River Kaljani in Alipurduar Municipality, West Bengal, India
Authors: Roy Mousami 
Published: October 2024

Abstract

In this study an attempt was made to determine the seasonality of stream water quality: A case study of river Kaljani in Alipurduar Municipality, West Bengal, India. Monthly observations of 21 water quality parameters for the periods between January 2010 and December 2022 were used as the database which was generated by West Bengal Pollution Control Board in accordance with the guideline established by the Central Pollution Control Board, Govt. of India. The Hierarchical Cluster Analysis (HCA) was applied to assess the seasonal pattern in water quality status while Spearman’s Rank Correlation was used for determining the association between water quality parameters with seasonal and monthly normal rainfall to determine the impact of rainfall in controlling such seasonality. The result of HCA shows that stream water quality changes following two distinct hydrogeochemical seasons, November to April and May to October which are governed by local rainfall. The result of Spearman’s rho displays that geogenic parameters (e.g., TSS, TFS, Turbidity etc.) follow rainfall-based seasonality while anthropogenic parameters (e.g., BOD, COD, Na+ etc.) do not follow rainfall-based seasonality. Since rainfall cannot fully explain the whole complexity of hydrogeochemical season, the role of other factors like discharge needs to be incorporated in this context.
Prediction of COVID-19 Severity and Mortality in Hospitalized Children Using Machine Learning Tree-based Classifiers
Authors: Karimi Mehran , Nafei Zahra , Shamsi Farimah , Akbarian Elahe 
Published: October 2024

Abstract

Background
Children make up a large percentage of Coronavirus Disease 2019 (COVID-19) hospital admissions, but there is little information available about the features to predict the severity status of the illness or mortality in pediatrics. Logistic regression, supporting vector machine and ensemble machine learning algorithms were used to develop predictive models and identify prognostic factors for severity and mortality of COVID-19 in hospitalized children.
Methods
A total of 183 children with COVID-19 under the age of 18 years hospitalized in a referral hospital in Yazd province, Iran, from March 1, 2020 to August 1, 2021 were considered for this study. Logistic regression, and machine learning classifiers including supporting vector machine, decision tree, random forest, Bagging classifier trees, Gradient boosted decision trees, and Adaptive boost classifier trees were employed to predict the development of mild/severe or critical COVID-19 and death occurrence during hospitalization. Each model performance was assessed through five-fold cross-validation method, with evaluation metrics and area under the curve. In addition, the best clinical predictive models were used to identify significant factors between severe and non-severe groups, as well as between survivors and non-survivors.
Results
Seven predictive models were developed using the medical files of 183 hospitalized children, consisting of 94 and 89 (48.6%) in non-severe and severe groups, respectively, as well as 159 survivors and 24 (13%) non-survivors. In prediction of severity status, both decision tree and random forest algorithms had the highest accuracy of 73.3% and 68.7% to predict severity status in balanced data, respectively. Based on decision tree, respiratory distress and cough at the time of admission could be regarded as the as the key factors to estimate the likelihood of severity status. The results also showed that Gradient boosted decision trees, and Adaptive boost classifier trees had the best performance for mortality prediction in balanced data considering the accuracy of 88.8% and 87.7%, respectively. Cough at the time of admission, age group of 1–13 years old, and non-normal WBC could be considered as predictive factors for death occurrence.
Conclusions
This study indicated that tree-based classifiers were the best machine learning approaches for predicting severity status and mortality in hospitalized children with COVID-19. Clinical symptoms at the time of admission identified as the most predictive features though optimal algorithms.
Comparative effectiveness of Statins for Chronic Obstructive Pulmonary Disease Patients with Pulmonary Hypertension: systematic review and network meta-analysis
Authors: Xu Guobo , Huang Wenrui , Fang Xingzi , Ou Xingyan , Chen Lei , Tang Xiaoxuan , Du Xuelian 
Published: October 2024

Abstract

Introduction and objectives: Statins may effectively treat PH-COPD, but current guidelines do not endorse their use. This study aims to assess the comparative effectiveness and safety of Statins in adult patients with pulmonary hypertension associated with chronic obstructive pulmonary disease (PH-COPD) through a systematic review and network meta-analysis.
Material and methods: We searched 8 databases for randomized controlled trials (RCTs) involving Statins in individuals with PH-COPD from inception to July 1, 2024. We assessed bias using the ROB 2.0 tool and evaluated evidence quality with the CINeMA framework. We employed a Bayesian network meta-analysis approach to assess outcomes including pulmonary artery pressure, exercise tolerance, lung function, oxygenation parameters, inflammatory markers, and vasoactive substances. Using RStudio and other software, we generated forest plots, league tables, and SUCRA curves to evaluate both direct and indirect comparisons.
Results: We analyzed data from 41 RCTs involving 3,606 participants. Our analysis revealed that all 5 statins were effective in reducing Systolic Pulmonary Artery Pressure (sPAP) compared to standard treatment(ST). Rosuvastatin was the most effective, significantly lowering sPAP(MD=-8.8; (95%CI -11.68, -5.85)) and IL-6(MD=-16.41; 95%Cl -29.64, -3.04) and improving the 6-Minute Walk Distance (6MWD)(MD=67.03; 95%Cl 2.77, 130.86). Atorvastatin 20 mg was the most effective in improving lung function, increasing PO2, reducing inflammatory markers such as TNF-α and hs-CRP, and lowering ET-1. Finally, Simvastatin 20 mg+ST was identified as the most effective regimen for reducing PCO2 and increasing NO levels.
Conclusions: Our study demonstrates that statins are more effective than standard treatment for adults with PH-COPD. Rosuvastatin is the most effective at reducing sPAP. It also improves the 6MWD and lowers IL-6 levels. Additionally, statins have significantly enhanced lung function, oxygenation parameters, and inflammatory markers in PH-COPD patients, with Atorvastatin showing the best performance in these areas.
Building and validation based on machine learning methods: Predictive model for falls risk among community patients with chronic obstructive pulmonary disease in China
Authors: Chen Yong , Yu Yonglin , Yang Dongmei , Chen Xiaoju 
Published: October 2024

Abstract

Background
Falls in patients with chronic obstructive pulmonary disease (COPD) can have potentially devastating consequences; however, there is still a lack of accurate fall risk prediction models for community-dwelling patients with COPD in China. The aim of this study was to develop a risk prediction model for falls in COPD patients applicable to the Chinese community.
Methods
The clinical data of 809 Community COPD patients were analyzed by using the 2020 China Health and Retirement Longitudinal Study (CHARLS) database. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to analyze predictors. Multiple machine learning (ML) classification models are integrated to analyze and identify the optimal model, and Shapley Additive exPlanations (SHAP) interpretation was developed for personalized risk assessment.
Results
The following eight variables: Memory_disease, Cardiology, Hyperlipidemia, Hypertension, Gender, Sleeping_time_at_night, ADL_score, and Age are predictors of falls in community-based COPD patients. Logistic classification model was the optimal model, test set area under curve (AUC) (95% confidence interval, CI): 0.693 (0.621–0.765), accuracy: 0.638, sensitivity: 0.627, and specificity: 0.642.
Conclusions
The model constructed in this study has relatively reliable predictive performance, which helps clinical doctors identify high-risk populations of community COPD patients prone to falls at an early stage.
A real-world pharmacovigilance study of Ocrelizumab based on FAERS database
Authors: Liang Haiping , Wu Junlin , Chen Lili , Shen Yonggang 
Published: October 2024

Abstract

Ocrelizumab is a humanized monoclonal antibody targeting CD20 for the treatment of multiple sclerosis (MS). The analysis of the FDA Adverse Event Reporting System database (FAERS) provides critical insights into the safety profile of Ocrelizumab. Signal detection and analysis for Ocrelizumab-related AEs were performed using disproportionality analysis techniques. Of 30622295 reports collected from the FAERS database, 143788 AE reports associated with Ocrelizumab were identified, involving 42301 patients. Among these reports, 427 preferred terms (PTs) met the criteria across four algorithms for signal detection, encompassing a total of 27 System Organ Classes (SOCs). The most frequently reported AEs included respiratory infections, urinary tract infections, Herpes virus infection, and infusion-related reactions, aligning with those documented in the drug label and clinical trials. Novel and unexpected AE signals were also detected, such as COVID-19, positive JC polyomavirus test, dental disease, cystitis, cellulitis, etc., with most adverse reactions occurring within the first month of dosing. Our study indicates that Ocrelizumab demonstrates a favorable safety profile, consistent with findings from existing clinical trials. This study has identified the adverse reactions associated with Ocrelizumab, providing valuable insights for its clinical use.