bluuebunny/crossref_metadata_2025_split huggingface dataset:
The oral-gut microbiota relationship in healthy humans: identifying shared bacteria between environments and age groups
Authors: Costa Carolina F. F. A. , Correia-de-Sá Teresa , Araujo Ricardo , Barbosa Fernando , Burnet Philip W. J. , Ferreira-Gomes Joana , Sampaio-Maia Benedita 
Published: October 2024

IntroductionAlthough the oral cavity and the gut are anatomically continuous regions of the gastrointestinal tract, research on the relationship between oral and gut microbiota remains sparse. Oral-gut bacterial translocation is mostly studied in pathological contexts, thus evidence of translocation in healthy conditions is still scarce. Studying the oral-gut microbiota relationship in humans in different life stages is necessary in order to understand how these microbial communities might relate throughout life.MethodsIn this study, saliva and fecal samples were collected from healthy participants (39 children, 97 adults). Microbiota analysis was carried out by sequencing the V4 region of the 16S ribosomal RNA gene, followed by amplicon sequence variant (ASV) analysis.Results and discussionAlthough the oral and gut microbiota are vastly different, a subset of 61 ASVs were present in both the oral cavity and gut of the same individual, and represented 1.6% of all ASVs detected. From these, 26 ASVs (classified into 18 genera: Actinomyces, Rothia, Bacteroides, Porphyromonas, Prevotella, Alistipes, Fusobacterium, Neisseria, Haemophilus, Akkermansia, Solobacterium, Granulicatella, Streptococcus, Gemella, Mogibacterium, Dialister, Veillonella, Christensenellaceae R-7 group) were present in both children and adults, suggesting the possibility of persistent colonization of both habitats by these microorganisms, initiating in childhood. Additionally, 62% of shared ASVs were more abundant in the oral cavity, indicating that oral-to-gut translocation may be the main route of translocation between environments, and highlighting that this phenomenon might be more common than previously thought in healthy individuals of all ages.
Nutritional intervention in end-stage renal disease: a clinical trial study
Authors: Tao Xueting , Qian Jiaolin , Hu Yongwei 
Published: October 2024

ObjectiveChronic kidney disease is a global health problem, and end-stage renal disease (ESRD) has a major impact on patients' quality of life and prognoses. However, studies on individualized nutritional therapy for patients with ESRD need more complementary evidence.MethodsA clinical study was conducted based on a small population. It included patients with ESRD who underwent dialysis treatment in the Taicang Hospital Department of Nephrology, Soochow University, China, between January 2019 and December 2021. According to the randomized number table method, patients were divided into the nutritional treatment group (NIG) and the non-nutritional intervention control group (NNIG). There were 84 patients in the NIG and 92 patients in the NNIG. This study analyzed the changes in residual renal function (RRF) and indicators of blood and kidney function in ESRD with personalized nutritional therapy.ResultsThe results show that nutritional interventions for ESRD are effective in reducing the rate of decline in RRF and improving indicators of blood and kidney function in patients with ESRD. It was also found that patients with diabetes mellitus gained fewer health benefits per unit of RRF improvement with individualized nutritional therapy.ConclusionThis study provides important information about the treatment effects and factors associated with individual nutritional interventions in a population with ESRD. These results contribute to a better understanding of the effects of nutritional therapy in ESRD and provide a basis for managing it. Further studies should focus on specific populations and potential interventions to improve patient prognosis.
Relationship between relative fat mass and low-carbohydrate diet scores and sleep disorders in United States: a real-world cross-sectional study
Authors: Cao Cheng , Yu Keyi , Lin Fuquan , Xu Aie , Zhou Miaoni 
Published: October 2024

ObjectiveTo investigate the relationship between relative fat mass (RFM) and low-carbohydrate diet (LCD) scores and sleep disorders in the U.S. population.MethodsData were collected from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2014. A total of 5,394 respondents participated in the study. Univariate and multivariate linear regression analyses were used to investigate the relationship between RFM and LCD scores, and univariate and multivariate logistic regression analyses were used to investigate the relationship between RFM and LCD scores and sleep disorders. Restricted cubic spline (RCS) analyses were conducted to test for nonlinear associations between RFM and LCD scores and sleep disorders.ResultsA total of 5,394 participants were included in the statistical analysis, including 5,080 healthy participants and 314 with sleep disorders. Univariate and multivariate linear regression showed a bivariate positive correlation between RFM and LCD scores (p &lt; 0.05), and logistic regression analysis showed a significant positive correlation between RFM (95% CI: 1.02–1.07, p = 0.005) LCD scores (95% CI: 1.00–1.03, p = 0.044) and sleep disturbances. Subgroup analyses showed robust effects of RFM and LCD score on sleep disorders.ConclusionRFM was positively and bi-directionally associated with LCD scores, both of which resulted as risk factors for sleep disorders. This study emphasizes that an LCD and lowering RFM can prevent and ameliorate the risk of sleep disorders.
Diagnostic efficacy of data mining method based on multimodal ultrasound for papillary thyroid carcinoma
Authors: Xu Changyu , Zhang Liwei , Zhang Qiming , Wang Tianqi , Wu Yuqing , Yao Jinlai , Dong Xiaoqiu 
Published: October 2024

ObjectiveThe incidence of papillary thyroid caracinoma (PTC) is increasing year by year. Logistic regression model and Chi-squared automatic interaction (CHAID) decision tree based on multimodal ultrasound were established, and the diagnostic efficiency of the two models in PTC was compared.MethodsThe findings, features and data of routine ultrasound, shear wave elastography (SWE) and contrast-enhanced ultrasonography (CEUS) were prospectively collected in 203 patients. Including: echogenicity, aspect ratio, maximum diameter of tumor, boundary, morphology, focal hyperecho, blood flow grading, maximum elasticity (Emax), minimum elastcity (Emin), mean elasticity (Emean), enhancement degree, enhanced characteristics, distribution of contrast agent, contrast medium arrival time. According to the pathological results, they were divided into PTC group and non-PTC group. CHAID decision tree model and binary Logistic regression model were established, receiver operator characteristic (ROC) curves of the two models were drawn, and diagnostic effectiveness was evaluated by comparing area under curve (AUC).ResultsLogistic regression showed that hypoechoic or very hypoechoic, aspect ratio ≥1, microcalcification and high SWE value were risk factors for PTC (OR 8.604, 2.154, 2.297, 1.067, respectively, P &lt; 0.05). The CHAID decision tree showed echo, aspect ratio, Emax, contrast agent distribution and infusion time combined to diagnose PTC. ROC curve showed that the AUC of PTC predicted by Logistic regression model and CHAID decision tree model was 0.878 and 0.883, respectively, with no statistical significance (z=0.325, P=0.7456).ConclusionBoth Logistic regression model and CHAID decision tree model can play a good role in the diagnosis of PTC based on multi-modal ultrasound, but the diagnostic efficiency of both models is comparable. In conclusion, these two models provide new insights and ideas for PTC diagnosis.
Prognostic value of neutrophil to lymphocyte ratio for patients with bladder cancer undergoing radical cystectomy: a systematic review and meta-analysis
Authors: Chen Zhan , Zhang Yao , Chen Telei 
Published: October 2024

ObjectivesThis study evaluated the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for survival outcomes in bladder cancer patients treated with radical cystectomy.MethodsStudies assessing NLR’s prognostic significance for bladder cancer after radical cystectomy were identified from PubMed, Embase, Web of Science, and Cochrane databases until April 2024. Survival outcomes analyzed included overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), cancer-specific survival (CSS), and progression-free survival (PFS).ResultsThe meta-analysis comprised 15 cohort studies with 8,448 patients. Multivariate analysis showed significantly shorter OS, CSS, DFS, and RFS in the high NLR group compared to the low NLR group. However, no significant difference in PFS was observed between the groups.ConclusionsNLR serves as an independent prognostic indicator for bladder cancer patients undergoing radical cystectomy, with elevated NLR associated with poorer survival. Further large-scale, prospective studies are warranted to validate the relationship between NLR and prognosis in bladder cancer.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024549573.
Incidence of prolonged transitional neonatal hypoglycemia and associated factors among neonatal admissions in South Gondar public hospitals, North-Central Ethiopia: a prospective cross-sectional study
Authors: Kebede Solomon Demis , Aytenew Tigabu Munye , Agmas Kindu , Asferie Worku Necho , Moges Natnael 
Published: October 2024

BackgroundUnlike in developed countries, neonatal morbidity and mortality are the leading challenges associated with easily preventable and treatable disorders during the neonatal period in low- and middle-income countries. However, evidence-based data about prolonged transitional hypoglycemia and associated factors are highly limited in Ethiopia and resource-limited countries.MethodsAn institution-based prospective cross-sectional study was conducted at public hospitals in South Gondar in neonatal intensive care units (NICUs). The data were entered and analyzed using SPSS version 23. Descriptive statistics were used to summarize maternal characteristics. Multivariate binary logistic regression at a p value &lt;0.05 was used.ResultsA total of 400 neonates, admitted to NICUs in public hospitals within 48–72 h of birth between October 2, 2021, and June 30, 2022, were included in the study. The incidence of prolonged transitional neonatal hypoglycemia (PTHG) was 23.5% (19.3%–28%). The factors associated with PTHG were hypothermia (AOR = 4.41; 95% CI = 2.72–10.92), preterm birth (AOR = 3.5; 95% CI = 1.69–11.97), perinatal asphyxia (AOR = 2.5; 95% CI = 1.34–9.67), and pathological jaundice (AOR = 2.3; 95% CI = 1.21–10.34). In contrast, spontaneous vaginal delivery (SVD) was a protective factor (AOR = 0.72; 95% CI = 0.35–0.88).ConclusionsThe incidence of (PTHG) was nearly one-fifth. Factors increasing the risk of PTHG were hypothermia, preterm birth, perinatal asphyxia (PNA), early onset of sepsis (EONS), and pathological jaundice. Spontaneous vaginal delivery (SVD) was also a protective factor. Preventing neonatal hypothermia was the main measure used to reduce PTHG in the study area. Special attention could be given to neonates with prematurity, early onset neonatal sepsis (EONS), birth asphyxia, and pathological jaundice, as monitoring their RBS could lead to a significant change in reducing PTHG.
Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm
Authors: Sun Maojin , Sun Luyi 
Published: October 2024

IntroductionThe development of science and technology has driven rapid changes in the social environment, especially the rise of the big data environment, which has greatly increased the speed at which people obtain information. However, in the process of big data processing, the allocation of information resources is often unreasonable, leading to a decrease in efficiency. Therefore, optimizing task scheduling algorithms has become an urgent problem to be solved.MethodsThe study optimized task scheduling algorithms using artificial intelligence (AI) methods. A task scheduling algorithm optimization model was designed using support vector machine (SVM) and K-nearest neighbor (KNN) combined with fuzzy comprehensive evaluation. In this process, the performance differences of different nodes were considered to improve the rationality of resource allocation.Results and DiscussionBy comparing the task processing time before and after optimization with the total cost, the results showed that the optimized model significantly reduced task processing time and total cost. The maximum reduction in task processing time is 2935 milliseconds. In addition, the analysis of query time before and after optimization shows that the query time of the optimized model has also been reduced. The experimental results demonstrate that the proposed optimization model is practical in handling task scheduling problems and provides an effective solution for resource management in big data environments. This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.
Leukocyte telomere length and lung function: a mendelian randomization study in European population
Authors: Zhu Shenyu , Zheng Wenlong , Rao Dingyu , Tang Zhixian , Liao Xinhui 
Published: October 2024

BackgroundThe telomere has long been regarded as a dependable biomarker for cellular senescence. The lung function can reflect the function and status of the lungs. As individuals age beyond adulthood, there is a gradual decline in lung function. However, the existence of a associated between leukocyte telomere length (LTL) and lung function remains uncertain.MethodsA two-sample Mendelian randomization (MR) analysis was used. The Single-nucleotide polymorphisms (SNPs) of LTL from the genome-wide association (GWAS) study were used as exposure instruments variable, and the lung function indicator including Forced expiratory volume in 1-s (FEV1), FEV1 Best measure, FEV1 predicted and Forced vital capacity (FVC) from the Neale Lab and MRC-IEU were used as outcomes. The associated between the exposures and outcomes was assessed using inverse-variance weighted (IVW), MR-Egger, and weighted median methods. Sensitivity analysis was conducted using Cochran’s Q-test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis, and Steriger test.ResultsUsing the IVW method, a significant association was identified between genetically determined telomere length extension and enhanced lung function in FEV1, with ukb-a-336 (P = 0.127, OR = 1.028,95CI% = 1.003–1.042) and ukb-b-19657 (P = 7.26E-05, OR = 1.051,95CI% = 1.025–1.077),in FEV1 predicted, ukb-a-234 (P = 0.013, OR = 1.029,95CI% = 1.003–1.042), ukb-b-8428 (P = 0.001, OR = 1.032,95CI% = 1.012–1.052), in FEV1 best measure, ukb-a-231 (P = 7.24E-05, OR = 1.050,95CI% = 1.025–1.075), ukb-b-11141 (P = 1.40E-09, OR = 1.067,95CI% = 1.045–1.090).The sensitivity analysis did not reveal heterogeneity or horizontal pleiotropy.Meanwhile, the Steriger test results also indicate that the directionality between exposure and outcome is correct. Therefore, the results indicated robustness.ConclusionThere is a correlation between longer LTL and better lung function in the European dataset.
Lipid metabolic profiling and diagnostic model development for hyperlipidemic acute pancreatitis
Authors: Ren Dongmei , Li Yong , Zhang Guangnian , Li Tiantian , Liu Zhenglong 
Published: October 2024

IntroductionHyperlipidemic acute pancreatitis (HLAP) is a form of pancreatitis induced by hyperlipidemia, posing significant diagnostic challenges due to its complex lipid metabolism disturbances.MethodsThis study compared the serum lipid profiles of HLAP patients with those of a healthy cohort using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify distinct lipid metabolites. Logistic regression and LASSO regression were used to develop a diagnostic model based on the lipid molecules identified.ResultsA total of 393 distinct lipid metabolites were detected, impacting critical pathways such as fatty acid, sphingolipid, and glycerophospholipid metabolism. Five specific lipid molecules were selected to construct a diagnostic model, which achieved an area under the curve (AUC) of 1 in the receiver operating characteristic (ROC) analysis, indicating outstanding diagnostic accuracy.DiscussionThese findings highlight the importance of lipid metabolism disturbances in HLAP. The identified lipid molecules could serve as valuable biomarkers for HLAP diagnosis, offering potential for more accurate and early detection.
Expertise-dependent visuocognitive performance of chess players in mating tasks: evidence from eye movements during task processing
Authors: Küchelmann Thomas , Velentzas Konstantinos , Essig Kai , Schack Thomas 
Published: October 2024

IntroductionVisuocognitive performance is closely related to expertise in chess and has been scrutinized by several investigations in the last decades. The results indicate that experts’ decision-making benefits from the chunking process, perception and visual strategies. Despite numerous studies which link these concepts, most of these investigations have employed common research designs that do not use real chess play, but create artificial laboratory conditions via screen-based chess stimuli and obtrusive stationary eye tracking with or without capturing of decision-making or virtual reality settings.MethodsThe present study assessed the visuocognitive performance of chess novices, intermediates and experts in a real chess setting. Instead of check detection, find-the-best-move tasks or to distinguish between regions of a chessboard that were relevant or irrelevant to the best move in previous studies, we introduced n-mate tasks and sequentially manipulated their difficulty. Due to the complexity of the tasks, we monitored players’ visual strategies in a fine-graded initial phase (different time intervals instead of analysing a fixed number of first fixations) of task-solving and for complete trials, employing non-obtrusive mobile eye tracking, multi-sensor observation and full-automatic annotation of decision-making.ResultsThe results revealed significant expertise-dependent differences in visuocognitive performance based on a circumstantial spatial and temporal analysis. In order to provide more detailed results, for the first time the analyses were performed under the special consideration of different time intervals and spatial scalings. In summary, experts showed a significantly higher number of fixations on areas of interest and empty squares between pieces in the task processing than less-skilled players. However, they had a strikingly low total number of fixations on the whole board and in complete trials.DiscussionAs a conclusion, experts apply different visual search strategies in problem-solving. Moreover, experts’ visuocognitive processing benefits from stored chunks of mating constellations.
In the shoes of junior doctors: a qualitative exploration of job performance using the job-demands resources model
Authors: Chua Jia Long , Mougammadou Zeenathnisa , Lim Raymond Boon Tar , Tung Joshua Yi Min , Sng Gerald Gui Ren 
Published: October 2024

BackgroundThis qualitative study aimed to explore the factors affecting job performance amongst junior doctors working for public healthcare institutions in Singapore. Within these institutions, junior doctors experience challenges with maintaining a balance in job demands and resources, leading to strain. Exploring the lived experiences of these junior doctors is essential when reviewing workplace and organizational factors that contribute to stress on an individual level, providing valuable insights to address these challenges effectively.MethodSemi-structured interviews were conducted with 20 junior doctors in Singapore, ranging from house officers to senior residents. Framework analysis was performed on transcribed de-identified interviews to identify themes deductively based on the Job Demands-Resources (JD-R) Model.ResultsThemes were identified and contextualized based on the exiting JD-R model. These themes shed light on how work demands, resources and personal factors influence the job performance of junior doctors and job satisfaction.ConclusionThe study offers valuable insights into the specific issues disrupting the job demands and resource balance in Singapore Public Healthcare Institutions and their correlation with job performance. Our data suggests that job performance may be associated with job satisfaction. By understanding these factors, targeted efforts can be developed to improve working conditions for junior doctors, fostering their growth and engagement within the public healthcare system.
Multilevel modeling of technology use, student engagement, and fitness outcomes in physical education classes
Authors: Cui Zhaohang , Song Yifan , Du Xiaojuan 
Published: October 2024

IntroductionThe integration of technology in educational settings, particularly in physical education, has shown potential in enhancing learning experiences and improving physical health outcomes. This study aims to investigate the effects of technology use on student engagement and fitness outcomes, considering the mediating role of student engagement and the moderating influence of personal attributes.MethodsUtilizing a time-lagged design, the research collected data from 513 Chinese undergraduate students (52% male and, 48% female) aged between 18 and 24 years over three waves using structured questionnaires rated on a 5-point Likert scale.ResultsResults revealed a significant positive relationship between technology use and both student engagement (β = 0.68, p &lt; 0.01) and fitness outcomes (β = 0.60, p &lt; 0.01). Student engagement significantly mediated the relationship between technology use and fitness outcomes (β = 0.57, p &lt; 0.01). Personal attributes moderated the effects of technology use on student engagement (β = 0.54, p &lt; 0.01) and fitness outcomes (β = 0.52, p &lt; 0.01), indicating varied benefits among students based on individual characteristics.DiscussionThese findings highlight the importance of tailoring technological applications in physical education to individual needs, suggesting that personalized approaches can significantly enhance the effectiveness of technology in improving fitness and engagement.