bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emotional exhaustion, academic self-efficacy, and academic procrastination as predictors of research motivation
Authors: Carranza Esteban Renzo Felipe , Mamani-Benito Oscar , Castillo-Blanco Ronald , Elguera Pajares Ana , Lingan Susana K. 
Published: March 2024

ObjectiveTo determine whether emotional exhaustion, academic self-efficacy, and academic procrastination predict research motivation in Peruvian university students.MethodsA cross-sectional predictive design was used and 1876 university students (59.9% female and 40.1% male), whose ages varied between 17 and 34 (M = 20.66; SD = 3.55), participated. The research motivation scale (RMS), academic self-efficacy scale (ASS), academic procrastination scale (APS), and the Single Item of Academic Emotional Exhaustion (SIAEE) scale were used to measure the variables.ResultsIt is evident that the proposed model had an acceptable fit χ2(2) = 0.5, p = 0.784, comparative fit index = 1.000, root mean square error of approximation = 0.000, standardized residual root mean square = 0.003, showing that academic self-efficacy (β = 0.26, p &lt; 0.001) and academic procrastination (β = −0.26, p &lt; 0.001) significantly predict research motivation, unlike emotional exhaustion, which does not predict research motivation (β = 0.03, p = 0.232).ConclusionAcademic self-efficacy and academic procrastination predict research motivation while emotional exhaustion does not, as reflected in the results.
Individual variation in undergraduate student metacognitive monitoring and error detection during biology model evaluation
Authors: Dauer Joseph , Behrendt Mei Grace , Elliott McKenna , Gettings Bethany , Long Tammy , Clark Caron 
Published: March 2024

IntroductionModels are a primary mode of science communication and preparing university students to evaluate models will allow students to better construct models and predict phenomena. Model evaluation relies on students’ subject-specific knowledge, perception of model characteristics, and confidence in their knowledge structures.MethodsFifty first-year college biology students evaluated models of concepts from varying biology subject areas with and without intentionally introduced errors. Students responded with ‘error’ or ‘no error’ and ‘confident’ or ‘not confident’ in their response.ResultsOverall, students accurately evaluated 65% of models and were confident in 67% of their responses. Students were more likely to respond accurately when models were drawn or schematic (as opposed to a box-and-arrow format), when models had no intentional errors, and when they expressed confidence. Subject area did not affect the accuracy of responses.DiscussionVariation in response patterns to specific models reflects variation in model evaluation abilities and suggests ways that pedagogy can support student metacognitive monitoring during model-based reasoning. Error detection is a necessary step towards modeling competence that will facilitate student evaluation of scientific models and support their transition from novice to expert scientists.
Impact of bariatric surgery on ovarian reserve markers and its correlation with nutritional parameters and adipokines
Authors: Andreu Alba , Flores Lilliam , Méndez Marta , Ibarzabal Ainize , Casals Gregori , Mercadé Imma , Borrás Aina , Barral Yasmina , Agustí Inés , Manau Dolors , Vidal Josep , Casals Gemma 
Published: March 2024

IntroductionA reduction in anti-müllerian hormone (AMH) levels at short-term after bariatric surgery (BS) has been previously described. However, an assessment of ovarian reserve at longer-follow up, and a comprehensive evaluation of the potentially implicated factors has not been reported.DesignProspective cohort study.Materials and methodsTwenty women aged 18-40 years with BMI 43.95 kg/m2 undergoing BS were studied at baseline (BS0), and at 1 month (BS1), 4 months (BS2), 12 months (BS3), and 24-36 months (BS4) after the surgery. Anthropometrics, reproductive hormones (AMH, FSH, LH, estradiol, testosterone, SHBG, androstenedione), metabolic parameters (adiponectin, leptin, ghrelin, insulin), and nutritional blood parameters (markers of nutritional status, vitamins, and minerals) were obtained at each study time point. Antral follicular count (AFC) was assessed by ultrasonography at BS0, BS3, and BS4. Mixed models were used for analysis of longitudinal data.ResultsThe mean AMH level was 3.88 ng/mL at BS0, decreased at BS3 (mean= 2.59 ng/mL; p=0.009), and remained stable between BS3 and BS4 (mean= 2.96 ng/mL; p=0.409). We also observed a non-significant decrease in AFC at BS3 (mean=26.14 at BS0, mean 16.81 at BS3; p=0.088) that remained stable at BS4 (mean= 17.86; p=0.731). Mixed models analysis showed: (a) a decrease in 10 kg of body weight was associated with an average decrease of 0.357 ng/mL in AMH (p=0.014); (b) a decrease in 1 BMI point was associated with an average decrease of 0.109 ng/mL in AMH (p=0.005); (c) an increase in 1 µg/mL of adiponectin was associated with an average decrease of 0.091 ng/ml in AMH (p=0.041) Significant positive correlations were found between the AMH levels after BS and plasma concentrations of testosterone, free androgen index, insulin and HOMA index. No significant correlations were detected between AMH levels and nutritional parameters.ConclusionsOur results were in line with previous observations, showing that AMH levels decreased significantly at 12 months after bariatric surgery, in parallel with a non-significant reduction in AFC. Both ovarian reserve markers showed a later stabilization up to the end of the study. Of note, postoperative AMH levels were positively correlated with key androgen and insulin resistance-related parameters.
Association between cognitive function and skeletal muscle in patients undergoing maintenance hemodialysis
Authors: Wang Lulu , Bian Xueqin , Liu Lilin , He Qingyun , Xu Jie , Chen Xue , Ye Hong , Yang Junwei , Jiang Lei 
Published: March 2024

BackgroundPatients on hemodialysis have a higher burden of cognitive impairment than individuals of the same age in the general population. Studies have found a link between cognition and skeletal muscle function. However, few studies have investigated these associations and the underlying mechanisms in patients on hemodialysis.MethodsA total of 166 patients on hemodialysis were enrolled in this longitudinal study. Cognitive function was assessed by Montreal Cognitive Assessment (MoCA) scores. Skeletal muscle indicators were evaluated using Inbody S10. Plasma brain-derived neurotrophic factor (BDNF) concentrations were measured by enzyme-linked immunosorbent assay. The primary outcome was a change in the MoCA scores. A mediation analysis was performed to examine the indirect effect of skeletal muscle on cognitive decline through BDNF.ResultsAmong the 166 patients, the average age was 49.9 ± 11.2 years. Of these patients with a median follow-up of 1,136 days, 133 participated in the study. We defined MoCA scores decreased by ≥2 points at 3 years from the baseline measurement as cognitive decline (CD). Compared to the cognitively unchanged group, patients with CD had significantly lower fat-free mass, soft lean mass, skeletal muscle mass, and skeletal muscle index (all P&lt;0.05). After adjusting for potential confounders, skeletal muscle indicators were protective predictors of CD. A significant increase in plasma BDNF levels was observed in the CD group. Mediation analysis suggested that BDNF played a mediating role of 20-35% between cognitive impairment and skeletal muscle.ConclusionSkeletal muscle is a protective predictor of CD in patients undergoing dialysis. BDNF mediates the relationship between cognitive impairment and skeletal muscle function.
Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome
Authors: Huang Xinfeng , He Qing , Hu Haiping , Shi Huanhuan , Zhang Xiaoyang , Xu Youqiong 
Published: March 2024

ObjectiveTo identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods.MethodsPlasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups. Biomarkers were selected using support vector machine recursive feature elimination (SVM-RFE), random forest (rf), and least absolute shrinkage and selection operator (LASSO) regression, and the performance of two biomarker panels was compared across five machine learning models.ResultsIn the OPLS-DA models, 50 and 89 lipid metabolites were associated with pre-MetS and MetS patients, respectively. Further machine learning identified two sets of plasma metabolites composed of PS(38:3), DG(16:0/18:1), and TG(16:0/14:1/22:6), TG(16:0/18:2/20:4), and TG(14:0/18:2/18:3), which were used as biomarkers for the pre-MetS and MetS discrimination models in this study.ConclusionIn the initial lipidomics analysis of pre-MetS and MetS, we identified relevant lipid features primarily linked to insulin resistance in key biochemical pathways. Biomarker panels composed of lipidomics components can reflect metabolic changes across different stages of MetS, offering valuable insights for the differential diagnosis of pre-MetS and MetS.
Deep learning anomaly detection in AI-powered intelligent power distribution systems
Authors: Duan Jing 
Published: March 2024

Introduction: Intelligent power distribution systems are vital in the modern power industry, tasked with managing power distribution efficiently. These systems, however, encounter challenges in anomaly detection, hampered by the complexity of data and limitations in model generalization.Methods: This study developed a Transformer-GAN model that combines Transformer architectures with GAN technology, efficiently processing complex data and enhancing anomaly detection. This model’s self-attention and generative capabilities allow for superior adaptability and robustness against dynamic data patterns and unknown anomalies.Results: The Transformer-GAN model demonstrated remarkable efficacy across multiple datasets, significantly outperforming traditional anomaly detection methods. Key highlights include achieving up to 95.18% accuracy and notably high recall and F1 scores across diverse power distribution scenarios. Its exceptional performance is further underscored by achieving the highest AUC of 96.64%, evidencing its superior ability to discern between normal and anomalous patterns, thereby reinforcing the model’s advantage in enhancing the security and stability of smart power systems.Discussion: The success of the Transformer-GAN model not only boosts the stability and security of smart power distribution systems but also finds potential applications in industrial automation and the Internet of Things. This research signifies a pivotal step in integrating artificial intelligence into the power sector, promising to advance the reliability and intelligent evolution of future power systems.
Influence of intimate partner violence and male involvement on maternal healthcare services utilisation in Nigeria
Authors: Adetutu O. M. , Oyinlola F. F. , Oyelakin T. E. , Ofili F. L. 
Published: March 2024

IntroductionLow maternal health care services utilisation, especially antenatal care attendance and skilled birth attendance, has been documented to be responsible for maternal mortality and morbidity in Nigeria. While available evidence suggests mixed findings on uptake of maternal health care services in the context of abusive spousal relationships, male involvement in household and health decision-making has been established to promote uptake of maternal health care services. Yet, studies which consider mediating influence of intimate partner violence on male involvement and maternal health care services uptake are sorely missing in Nigeria. We hypothesised that maternal health care services uptake in abusive marital unions has implications for male involvement in pregnancy care and this has been largely overlooked in Nigeria.Materials and methodsThis study extracted data from the 2018 Nigeria Demographic and Health Survey (NDHS). The 2018 NDHS is a nationally representative secondary data which collected population, demographic and health information on women, men and households in Nigeria. The secondary data used a two-stage stratified and multistage sampling technique to collect information from the respondents. In this study, data were extracted for women who were sexually active, within the reproductive age (15–49 years) and not pregnant in five years prior the survey (n = 7,847).ResultsThe results indicated (77%) antenatal care attendance and (47%) skilled delivery. The mediating influence of IPV on male involvement resulted in women who experienced sexual violence more likely to use heath facility for antenatal care (OR = 3.20; C.I: 1.20–8.50). Women whose partners were involved in health decision making had lower odds of antenatal care attendance (OR = 0.64; C.I: 0.44–0.94). Also, women whose partners were involved in spending their earnings had lower probability of antenatal care attendance (OR = 0.72; C.I: 0.55–0.96). Yet, the mediating influence of intimate partner violence on male involvement resulted in a lower likelihood of use of skilled delivery for emotionally abused women (OR = 0.58; C.I: 0.39–0.85). Women whose partners were involved in spending their earnings had higher odds of using skilled delivery (OR = 2.15; C.I: 1.79–2.56). Yet, women whose partners were involved in their health decision-making had lower odds of using skilled delivery (OR = 0.46; C.I: 0.34–0.62).ConclusionThis study held the philosophical stance that intimate partner violence mediated the influence of male involvement on maternal health care uptake while intimate partner violence had an inconsistent influence on maternal health care uptake. Policies and interventions should aim at addressing deep-rooted gender norms which promote IPV and limit male involvement in pregnancy care in Nigeria. Programme and policy interventions should focus on enhancing socioeconomic status of women.
Multi-omics analyses reveal interactions between the skin microbiota and skin metabolites in atopic dermatitis
Authors: Huang Kaikai , Li Fang , Liu Yingyao , Liang Baoying , Qu Pinghua , Yang Linlin , Han Shanshan , Li Wenjun , Mo Xiumei , Dong Lei , Lin Ying 
Published: March 2024

IntroductionAtopic dermatitis (AD) is one of the most common inflammatory skin diseases. Skin microecological imbalance is an important factor in the pathogenesis of AD, but the underlying mechanism of its interaction with humans remains unclear.Methods16S rRNA gene sequencing was conducted to reveal the skin microbiota dynamics. Changes in skin metabolites were tracked by LC–MS metabolomics. We then explored the potential mechanism of interaction by analyzing the correlation between skin bacterial communities and metabolites in corresponding skin-associated samples.ResultsSamples from 18 AD patients and 18 healthy volunteers (HVs) were subjected to 16S rRNA gene sequencing and LC–MS metabolomics. AD patients had dysbiosis of the skin bacterial community with decreased species richness and evenness. The relative abundance of the genus Staphylococcus increased significantly in AD, while the abundances of the genera Propionibacterium and Brevundimonas decreased significantly. The relative abundance of the genera Staphylococcus in healthy females was significantly higher than those in healthy males, while it showed no difference in AD patients with or without lesions. The effects of AD status, sex and the presence or absence of rashes on the number of differentially abundant metabolites per capita were successively reduced. Multiple metabolites involved in purine metabolism and phenylalanine metabolism pathways (such as xanthosine/xanthine and L-phenylalanine/trans-cinnamate) were increased in AD patients. These trends were much more obvious between female AD patients and female HVs. Spearman correlation analysis revealed that the genus Staphylococcus was positively correlated with various compounds involved in phenylalanine metabolism and purine metabolic pathways. The genera Brevundimonas and Lactobacillus were negatively correlated with various compounds involved in purine metabolism, phenylalanine metabolism and sphingolipid signaling pathways.DiscussionWe suggest that purine metabolism and phenylalanine metabolism pathway disorders may play a certain role in the pathogenic mechanism of Staphylococcus aureus in AD. We also found that females are more likely to be colonized by the genus Staphylococcus than males. Differentially abundant metabolites involved in purine metabolism and phenylalanine metabolism pathways were more obvious in female. However, we should notice that the metabolites we detected do not necessarily derived from microbes, they may also origin from the host.
MRI brain structural and functional networks changes in Parkinson disease with REM sleep behavior disorders
Authors: Wang Fang , Zhu Zhigang , Zhou Chuanbin , Zhu Yongyun , Zhu Yangfan , Liang Chunyu , Chen Jieyu , Liu Bin , Ren Hui , Yang Xinglong 
Published: March 2024

BackgroundRapid eye movement sleep behavior disorder (RBD) is common in individuals with Parkinson’s disease (PD). In spite of that, the precise mechanism underlying the pathophysiology of RBD among PD remains unclear.ObjectiveThe aim of the present study was to analyze gray matter volumes (GMVs) as well as the changes of functional connectivity (FC) among PD patients with RBD (PD-RBD) by employing a combination of voxel-based morphometry (VBM) and FC methods.MethodsA total of 65 PD patients and 21 healthy control (HC) subjects were included in this study. VBM analyses were performed on all subjects. Subsequently, regions with significant different GMVs between PD patients with and without RBD (PD-nRBD) were selected for further analysis of FC. Correlations between altered GMVs and FC values with RBD scores were also investigated. Additionally, receiver operating characteristic (ROC) curves were employed for the evaluation of the predictive value of GMVs and FC in identifying RBD in PD.ResultsPD-RBD patients exhibited lower GMVs in the left middle temporal gyrus (MTG) and bilateral cuneus. Furthermore, we observed higher FC between the left MTG and the right postcentral gyrus (PoCG), as well as lower FC between the bilateral cuneus (CUN) and the right middle frontal gyrus (MFG) among PD-RBD patients in contrast with PD-nRBD patients. Moreover, the GMVs of MTG (extending to the right PoCG) was positively correlated with RBD severity [as measured by REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ) score]. Conversely, the FC value between the bilateral CUN and the right MTG in PD-RBD patients was negatively correlated with RBDSQ score.ConclusionThis study revealed the presence replace with GMV and FC changes among PD-RBD patients, which were closely linked to the severity of RBD symptoms. Furthermore, the combination of basic clinical characteristics, GMVs and FC values effectively predicted RBD for individuals with PD.
Clinical course of five patients definitively diagnosed with idiopathic perilymphatic fistula treated with transcanal endoscopic ear surgery
Authors: Kubota Toshinori , Ito Tsukasa , Furukawa Takatoshi , Matsui Hirooki , Goto Takanari , Shinkawa Chikako , Matsuda Han , Ikezono Tetsuo , Kakehata Seiji 
Published: March 2024

ObjectivesAn idiopathic perilymphatic fistula (PLF) can be difficult to diagnose because patients present with sudden sensorineural hearing loss (SSHL) and/or vestibular symptoms without any preceding events. In such cases, we currently test for cochlin-tomoprotein (CTP) to confirm the diagnosis of idiopathic PLF because CTP is only detected in the perilymph. In this study, we report the clinical course of five patients definitively diagnosed with idiopathic PLF who underwent PLF repair surgery using transcanal endoscopic ear surgery (TEES).Patients and methodsFive patients were initially treated with intratympanic dexamethasone for SSHL, at which time a CTP test was also performed (preoperative CTP test). Due to refractory hearing loss and/or fluctuating disequilibrium, PLF repair surgery using TEES was performed to seal the oval and round windows using connective tissue and fibrin glue. These patients were diagnosed with definite idiopathic PLF based on pre- or intra-operative CTP test results (negative, &lt; 0.4 ng/mL; intermediate, 0.4–&lt; 0.8 ng/mL; and positive, &gt; 0.8 ng/mL). We evaluated pre- and intra-operative CTP values, intraoperative surgical findings via a magnified endoscopic view, and pre- and post-operative changes in averaged hearing level and vestibular symptoms.ResultsPre- and intra-operative CTP values were positive and intermediate in three patients, positive and negative in one patient, and negative and positive in one patient. None of the patients had intraoperative findings consistent with a fistula between the inner and middle ears or leakage of perilymph. Only two patients showed a slight postoperative recovery in hearing. Four patients complained of disequilibrium preoperatively, of whom two had resolution of disequilibrium postoperatively.ConclusionA positive CTP test confirms PLF in patients without obvious intraoperative findings. The CTP test is considered more sensitive than endoscopic fistula confirmation. We consider that CTP test results are important indicators to decide the surgical indication for idiopathic PLF repair surgery. In our experience with the five cases, two of them showed improvements in both hearing and vestibular symptoms.