bluuebunny/crossref_metadata_2025_split huggingface dataset:
The relationship between major depression and migraine: A bidirectional two-sample Mendelian randomization study
Authors: Lv Xiaofeng , Xu Bojun , Tang Xiurong , Liu Shanshan , Qian Jun-Hui , Guo Julan , Luo Jian 
Published: April 2023

BackgroundPrevious epidemiological and other studies have shown an association between major depressive disorder (MDD) and migraine. However, the causal relationship between them remains unclear. Therefore, this study aimed to investigate the causal relationship between MDD and migraine using a bidirectional, two-sample Mendelian randomization (MR) approach.MethodsData on MDD and migraine, including subtypes with aura migraine (MA) and without aura migraine (MO), were gathered from a publicly available genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) utilized as instrumental variables (IVs) were then screened by adjusting the intensity of the connection and removing linkage disequilibrium. To explore causal effects, inverse variance weighting (IVW) was used as the primary analysis method, with weighted median, MR-Egger, simple mode, and weighted mode used as supplementary analytic methods. Furthermore, heterogeneity and pleiotropy tests were carried out. Cochran’s Q-test with IVW and MR-Egger was used to assess heterogeneity. Pleiotropy testing was carried out using the MR-Egger intercept and MR-PRESSO analysis methods. A leave-one-out analysis was also used to evaluate the stability of the findings. Finally, we used migraine (MA and MO) levels to deduce reverse causality with MDD risk.ResultsRandom effects IVW results were (MDD-Migraine: odds ratio (OR), 1.606, 95% confidence interval (CI), 1.324–1.949, p = 1.52E-06; MDD-MA: OR, 1.400, 95%CI, 1.067–1.8378, p = 0.015; MDD-MO: OR, 1.814, 95%CI, 1.277–2.578, p = 0.0008), indicating a causal relationship between MDD levels and increased risk of migraine (including MA and MO). In the inverse MR analysis, the findings were all negative, while in sensitivity analyses, the results were robust except for the study of MA with MDD.ConclusionOur study confirms a causal relationship between MDD levels and increased risk of migraine, MA, and MO. There was little evidence in the reverse MR analysis to suggest a causal genetic relationship between migraine (MA and MO) and MDD risk levels.
Temperature variability increases the onset risk of ischemic stroke: A 10-year study in Tianjin, China
Authors: Chen Zhuangzhuang , Liu Peilin , Xia Xiaoshuang , Wang Lin , Li Xin 
Published: April 2023

BackgroundEpidemiological evidence suggests a correlation between ambient temperature and ischemic stroke. However, evidence on the impact of daily temperature variability on the onset of ischemic stroke is lacking and limited.ObjectiveWe aimed to investigate the short-term association between temperature variability and ischemic stroke occurrence in Tianjin.MethodsWe performed a 10-year analysis of ischemic stroke patients hospitalized in two affiliated hospitals of Tianjin Medical University from 2011 to 2020. Daily meteorological data were collected from the Tianjin Meteorological Bureau. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. A quasi-Poisson generalized linear regression combined with distributed lag non-linear model (DLNM) was used to estimate the effect of temperature variability on daily stroke onset, while controlling for daily mean temperature, relative humidity, long-term trend and seasonality, public holiday, and day of the week.ResultsTemperature variability was positively associated with ischemic stroke. A 1°C increase in temperature variability at 0–1 days (TV0–1) was associated with a 4.1% (1.9–6.3%) increase of ischemic stroke onset. In a stratified analysis, men, people aged ≤65 years, and individuals with pre-existing hypertension, hyperlipidemia, hyperhomocysteinemia were more susceptible to temperature variability. Furthermore, the influence pattern of temperature variability on ischemic stroke was different in the cold season (November–April) and the warm season (May–October).ConclusionOur findings suggested that short-term temperature variability exposure could increase the risk of ischemic stroke, which may provide new insights into the impact of climate change on health.
Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched controls
Authors: Somaskandhan Pranavan , Leppänen Timo , Terrill Philip I. , Sigurdardottir Sigridur , Arnardottir Erna Sif , Ólafsdóttir Kristín A. , Serwatko Marta , Sigurðardóttir Sigurveig Þ. , Clausen Michael , Töyräs Juha , Korkalainen Henri 
Published: April 2023

IntroductionVisual sleep scoring has several shortcomings, including inter-scorer inconsistency, which may adversely affect diagnostic decision-making. Although automatic sleep staging in adults has been extensively studied, it is uncertain whether such sophisticated algorithms generalize well to different pediatric age groups due to distinctive EEG characteristics. The preadolescent age group (10–13-year-olds) is relatively understudied, and thus, we aimed to develop an automatic deep learning-based sleep stage classifier specifically targeting this cohort.MethodsA dataset (n = 115) containing polysomnographic recordings of Icelandic preadolescent children with sleep-disordered breathing (SDB) symptoms, and age and sex-matched controls was utilized. We developed a combined convolutional and long short-term memory neural network architecture relying on electroencephalography (F4-M1), electrooculography (E1-M2), and chin electromyography signals. Performance relative to human scoring was further evaluated by analyzing intra- and inter-rater agreements in a subset (n = 10) of data with repeat scoring from two manual scorers.ResultsThe deep learning-based model achieved an overall cross-validated accuracy of 84.1% (Cohen’s kappa κ = 0.78). There was no meaningful performance difference between SDB-symptomatic (n = 53) and control subgroups (n = 52) [83.9% (κ = 0.78) vs. 84.2% (κ = 0.78)]. The inter-rater reliability between manual scorers was 84.6% (κ = 0.78), and the automatic method reached similar agreements with scorers, 83.4% (κ = 0.76) and 82.7% (κ = 0.75).ConclusionThe developed algorithm achieved high classification accuracy and substantial agreements with two manual scorers; the performance metrics compared favorably with typical inter-rater reliability between manual scorers and performance reported in previous studies. These suggest that our algorithm may facilitate less labor-intensive and reliable automatic sleep scoring in preadolescent children.
Impact of Donepezil on Brain Glucose Metabolism Assessed Using [18F]2-Fluoro-2-deoxy-D-Glucose Positron Emission Tomography Imaging in a Mouse Model of Alzheimer’s Disease Induced by Intracerebroventricular Injection of Amyloid-Beta Peptide
Authors: Hugon Gaëlle , Goutal Sébastien , Sarazin Marie , Bottlaender Michel , Caillé Fabien , Droguerre Marine , Charvériat Mathieu , Winkeler Alexandra , Tournier Nicolas 
Published: April 2023

Graphical Abstract[18F]2-fluoro-2-deoxy-D-glucose ([18F]FDG) PET imaging was performed in a mouse model of Alzheimer’s disease to investigate the impact of donepezil on brain glucose metabolism.
Energy minimization segmentation model based on MRI images
Authors: Wang Xiuxin , Yang Yuling , Wu Ting , Zhu Hao , Yu Jisheng , Tian Jian , Li Hongzhong 
Published: April 2023

IntroductionMedical image segmentation is an important tool for doctors to accurately analyze the volume of brain tissue and lesions, which is important for the correct diagnosis of brain diseases. However, manual image segmentation methods are time-consuming, subjective and lack of repeatability, it needs to develop automatic and reliable methods for image segmentation.MethodsMagnetic Resonance Imaging (MRI), a non-invasive imaging technique, is commonly used to detect, characterize and quantify tissues and lesions in the brain. Partial volume effect, gray scale in homogeneity, and lesions presents a great challenge for automatic medical image segmentation methods. So, the paper is dedicated to address the impact of partial volume effect and multiple sclerosis lesions on the segmentation accuracy in MRI. The objective function of the improved model and the post-processing method of lesion filling are researched based on the fuzzy clustering space and energy model.ResultsIn particular, an energy-minimized segmentation algorithm is proposed. Through experimental verification, the AR-FCM algorithm can better overcome the problem of low segmentation accuracy of the RFCM algorithm for tissue boundary voxels and improve the segmentation accuracy of this algorithm. Meanwhile, a multi-channel input energy-minimization segmentation method with lesion filling and anatomical mapping is further proposed.DiscussionThe feasibility of the lesion filling strategy using post-processing can be confirmed and the segmentation accuracy is increased by comparison experiments.
Candidate Chinese Herbal Medicine Alleviates Methamphetamine Addiction via Regulating Dopaminergic and Serotonergic Pathways
Authors: Ru Qin , Xiong Qi , Tian Xiang , Xu Congyue , Li Can , Chen Lin , Wu Yuxiang 
Published: April 2023

Graphical AbstractConditioned place preference (CPP) test was used to assess the potential therapeutic effects of CCHM on METH addiction. The active components and hub targets, which were screened by the network pharmacology analysis, were verified by further experiments.
Single and combined associations of blood lead and essential metals with serum lipid profiles in community-dwelling adults
Authors: Wan Heng , Wang Dongmei , Liang Yongqian , He Yajun , Ma Qintao , Li Tingting , He Yingbo , Guo Hanquan , Wang Jiachen , Li Zhao , Lin Xu , Liu Lan , Shen Jie 
Published: April 2023

BackgroundAlthough several studies have examined the relationships between lead (Pb) exposure and serum lipid profiles, the associations of the metal mixture, including lead (Pb) and essential metals with lipid profiles, remain unclear.ObjectiveTo investigate the associations of the metal mixture including Pb and essential metals [magnesium (Mg), manganese (Mn), copper (Cu), iron (Fe), zinc (Zn), and calcium (Ca)] with serum lipid profiles [total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C)], as well as the potential interactions among the metals.MethodsNine hundred and ninety-eight Chinese community-dwelling adults completed a questionnaire and underwent checkups of anthropometric parameters, serum lipid profile levels (TC, TG, LDL-C, and HDL-C), and blood metal concentrations (Pb, Mg, Mn, Cu, Fe, Zn, and Ca). The multivariable linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) were applied to evaluate the single and combined associations of blood Pb and essential metals with serum lipid profiles.ResultsIn the multivariable linear regression model, the blood Pb was positively associated with TC, LDL-C, and HDL-C (p &lt; 0.05, all), and the blood Mg were positively associated with serum TC, LDL-C, and Ln TG (p &lt; 0.05, all). In the WQS regression and BKMR models, the metal mixture of blood Pb and the essential metals was positively associated with all of the serum lipid profiles. In addition, an inverse U-shaped association of Pb with Ln TG and the positive interactive effect between blood Pb and Mg levels on TC and LDL-C were found.ConclusionThe levels of blood Pb, together with the essential metals, especially Mg levels, are suggested to be considered when assessing dyslipidemia risk. However, more evidence is still needed to validate the conclusions.
Chronic circadian desynchronization of feeding-fasting rhythm generates alterations in daily glycemia, LDL cholesterolemia and microbiota composition in mice
Authors: Trebucq Laura Lucía , Lamberti Melisa Luciana , Rota Rosana , Aiello Ignacio , Borio Cristina , Bilen Marcos , Golombek Diego Andrés , Plano Santiago Andrés , Chiesa Juan José 
Published: April 2023

IntroductionThe circadian system synchronizes behavior and physiology to the 24-h light– dark (LD) cycle. Timing of food intake and fasting periods provide strong signals for peripheral circadian clocks regulating nutrient assimilation, glucose, and lipid metabolism. Mice under 12 h light:12 h dark (LD) cycles exhibit behavioral activity and feeding during the dark period, while fasting occurs at rest during light. Disruption of energy metabolism, leading to an increase in body mass, was reported in experimental models of circadian desynchronization. In this work, the effects of chronic advances of the LD cycles (chronic jet-lag protocol, CJL) were studied on the daily homeostasis of energy metabolism and weight gain.MethodsMale C57 mice were subjected to a CJL or LD schedule, measuring IPGTT, insulinemia, microbiome composition and lipidemia.ResultsMice under CJL show behavioral desynchronization and feeding activity distributed similarly at the light and dark hours and, although feeding a similar daily amount of food as compared to controls, show an increase in weight gain. In addition, ad libitum glycemia rhythm was abolished in CJL-subjected mice, showing similar blood glucose values at light and dark. CJL also generated glucose intolerance at dark in an intraperitoneal glucose tolerance test (IPGTT), with increased insulin release at both light and dark periods. Low-density lipoprotein (LDL) cholesterolemia was increased under this condition, but no changes in HDL cholesterolemia were observed. Firmicutes/Bacteroidetes ratio was analyzed as a marker of circadian disruption of microbiota composition, showing opposite phases at the light and dark when comparing LD vs. CJL.DiscussionChronic misalignment of feeding/fasting rhythm leads to metabolic disturbances generating nocturnal hyperglycemia, glucose intolerance and hyperinsulinemia in a IPGTT, increased LDL cholesterolemia, and increased weight gain, underscoring the importance of the timing of food consumption with respect to the circadian system for metabolic health.
Diagnostic value of the apparent diffusion coefficient in differentiating malignant from benign endometrial lesions
Authors: Scepanovic Bojana , Andjelic Nikola , Mladenovic-Segedi Ljiljana , Kozic Dusko , Vuleta Dusan , Molnar Una , Nikolic Olivera 
Published: April 2023

IntroductionMagnetic resonance imaging (MRI) with its innovative techniques, such as diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), increases the diagnostic accuracy in distinguishing between malignant and benign lesions of the endometrium. The aim of the study was MRI differentiation between malignant and benign endometrial lesions and correlation with histopathological findings with a special emphasis on quantitative analysis. An additional aim was to correlate the ADC values and histological tumor grades.MethodsThe prospective study included 119 female patients with or without vaginal bleeding and pathological values of endometrial thickness, who underwent MRI examinations. According to MRI reports the patients were divided into 45 suspicious malignant and 74 suspicious benign endometrial lesions. The radiological diagnosis was compared to the histopathological evaluation, which confirmed 37 malignant lesions while the rest were benign.ResultsThe mean ADC value for malignant lesions was 0.761 ± 0.13×10−3 mm2/s and for benign lesions was 1.318 ± 0.20×10−3 mm2/s. The ADC values for malignant lesions were expectedly lower than those of benign lesions (p&lt;0.001). The ADC cut-off value was 1.007×10−3 mm2/s with a sensitivity of 100%, specificity of 92.7%, a positive predictive value of 60.3%, and a negative predictive value of 100%. In comparison with the histopathological findings, the sensitivity of MRI was 100%, specificity 90.2%, positive predictive value was 82.2%, and negative predictive value was 100%. Observing the histological grades 1, 2, and 3 of endometrial carcinoma, no statistically significant differences of mean ADC values were found. The mean ADC values for histological tumor grades 1,2 and 3 were 0.803 ± 0.13×10−3 mm2/s, 0.754 ± 0.12×10−3 mm2/s and 0.728 ± 0.13×10−3 mm2/s, respectively.ConclusionDWI and ADC values represent clinically useful tools for the differentiation between malignant and benign endometrial lesions with high sensitivity and good specificity, but the results failed to demonstrate their usefulness in differentiating histological grades of endometrial cancer.
Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma
Authors: Liu Yunxun , Jian Jun , Zhang Ye , Wang Lei , Liu Xiuheng , Chen Zhiyuan 
Published: April 2023

BackgroundThe ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.MethodsCAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression was used to build a risk signature. With microarray data from the GEO database, prognostic characteristics were externally verified. For high and low CAF-risk categories, immune cells and immunotherapy responses were analyzed. Finally, a nomogram model based on the risk signature and prospective chemotherapeutic drugs were examined.ResultsCombining scRNA-seq and bulk-seq data analysis yielded a total of 124 CAF-related genes. LRP1, ANXA5, SERPINE2, ECM1, RBP1, GJA1, and FKBP10 were the seven BLCA prognostic genes that remained after univariate Cox regression and LASSO regression analyses. Then, based on these genes, prognostic characteristics were created and validated to predict survival in BLCA patients. Additionally, risk signature had a strong correlation with known CAF scores, stromal scores, and certain immune cells. The CAF-risk signature was identified as an independent prognostic factor for BLCA using multifactorial analysis, and its usefulness in predicting immunotherapy response was confirmed. Based on risk classification, we projected six highly sensitive anticancer medicines for the high-risk group.ConclusionThe prognosis of BLCA may be accurately predicted using CAF-based risk signature. With a thorough understanding of the BLCA CAF-signature, it might be able to explain the BLCA patients’ response to immunotherapy and identify a potential target for BLCA treatment.
The diagnostic accuracy of diabetes retinopathy screening by ophthalmic clinical officers, ophthalmic nurses and county ophthalmologists against a retina specialist in 2 selected county referral hospitals, Kenya
Authors: Ong’ang’o Jane Rahedi , Mashedi Olga , Gichangi Micheal , Kiplimo Richard , Nyamori Joseph , Alwenya Kennedy 
Published: April 2023

BackgroundDiabetes is rapidly becoming a major cause of blindness among Kenyans, with the prevalence of any form of diabetes retinopathy (DR) ranging from 36% to 41%. Globally DR leads as a cause of vision loss in working age adults. In Kenya, specialized examinations are only available at national and some county referral hospitals through retina specialists, ophthalmologists or trained technicians. Thus, low coverage of retinal assessment and inadequate access to this service. An innovative DR fundus camera screening service run by ophthalmic nurses (ONs), ophthalmic clinical officers (OCOs) and county ophthalmologists was established since 2018.ObjectivesThe purpose of this study was to investigate the diagnostic accuracy of DR digital retinal camera screening by ONs, OCOs and county ophthalmologist against that of a retina specialist measured by sensitivity and specificity as the primary outcomes.MethodsCross sectional study conducted at 2 referral hospitals in Kenya. Using a Canon CR-2AF digital retinal camera patients with diabetes had a standard single shot of 45 degree view of the retina captured as image in each eye. This was graded for DR using the International Clinical Diabetic Retinopathy (ICDR) severity scale. All photos taken by the first graders (ON/OCO) were later assessed by the county hospital ophthalmologist who was blinded to their readings. The third grader (retina specialist) similarly was blinded to the readings of the first and second graders and assessed all the images from the 2 hospitals also using ICDR.ResultsA total of 308 patients with diabetes (median age 58 IQR 56-60, 53% female) were enrolled in the study. Sensitivity to identify any DR was (81.3%, 80.6%, and 81.54% for the OCO, ON and county ophthalmologist respectively). The corresponding specificities were 92.7%, 92.8% and 92.59%. Analysis of diagnostic accuracy of non-sight threatening DR against sight threatening DR revealed lower sensitivity for the three cadre groups although specificity remained high.ConclusionsIn this study, ON and OCO with basic training in DR screening and photo grading performed screening of DR with high specificity. However, the sensitivity to detect sight threatening DR was generally low by all the cadres which may leave severe forms of DR undetected.
Mesenchymal stem cells therapy for acute kidney injury: A systematic review with meta-analysis based on rat model
Authors: Wanyan Pingping , Wang Xin , Li Nenglian , Huang Yong , She Yali , Zhang Li 
Published: April 2023

Objective: To systematically evaluate the efficacy of mesenchymal stem cells (MSCs) for acute kidney injury (AKI) in preclinical studies and to explore the optimal transplantation strategy of MSCs by network meta-analysis with the aim of improving the efficacy of stem cell therapy.Methods: Computer searches of PubMed, Web of Science, Cochrane, Embase, CNKI, Wanfang, VIP, and CBM databases were conducted until 17 August 2022. Literature screening, data extraction and quality evaluation were performed independently by two researchers.Results and Discussion: A total of 50 randomized controlled animal studies were included. The results of traditional meta-analysis showed that MSCs could significantly improve the renal function and injured renal tissue of AKI rats in different subgroups. The results of network meta-analysis showed that although there was no significant difference in the therapeutic effect between different transplant routes and doses of MSCs, the results of surface under the cumulative ranking probability curve (SUCRA) showed that the therapeutic effect of intravenous transplantation of MSCs was better than that of arterial and intrarenal transplantation, and the therapeutic effect of high dose (&gt;1×106) was better than that of low dose (≤1×106). However, the current preclinical studies have limitations in experimental design, measurement and reporting of results, and more high-quality studies, especially direct comparative evidence, are needed in the future to further confirm the best transplantation strategy of MSCs in AKI.Systematic Review Registration: identifier https://CRD42022361199, https://www.crd.york.ac.uk/prospero.