Tag: pubmed

Sci Rep. 2025 Feb 9;15(1):4844. doi: 10.1038/s41598-025-89287-4.

ABSTRACT

Exercise Self-Efficacy Scale (ESES) is widely used to assess individuals’ exercise self-efficacy through self-reporting. It includes one factor and 18 items that gauge one’s confidence in exercising under various conditions, such as when tired, stressed, or in unfavourable weather. Evidence indicates that differences in the original factor structure and psychometric properties were observed across different populations, including school-age students, university students, and adults. This study examined the factor structure, reliability, convergent validity, and measurement invariance of the Chinese version of the ESES among secondary school students. Data from 856 students (age: M = 13.80, SD = 0.94) were analysed using exploratory and confirmatory factor analyses to identify the best-fitting factor structure. The reliability and convergent validity were tested using the collected data. Configural, metric, and scalar invariances, as well as the likelihood ratio test, were tested for measurement invariance. A 14-item, two-factor structure of the ESES, consistently demonstrated the best fit among secondary school students. The two-factor structure showed strong internal consistency reliability (McDonald’s Omega of 0.921 and 0.843) and satisfactory convergent validity (average variance extracted values of 0.582 and 0.478, composite reliability values of 0.917 and 0.845). Multi-group confirmatory factor analysis (likelihood ratio test, p > 0.01) revealed scalar measurement invariance across sex, ethnic backgrounds, grades, and school locations. These findings suggest that the 14-item, two-factor Chinese version of the ESES is suitable for use with secondary-school students. Future studies could confirm these findings by examining the 14-item, two-factor ESES in diverse samples, considering ethnicity, socioeconomic status, and age range.

PMID:39924573 | DOI:10.1038/s41598-025-89287-4

Sci Rep. 2025 Feb 10;15(1):4848. doi: 10.1038/s41598-025-89482-3.

ABSTRACT

Ensemble learning can effectively mitigate the risk of model overfitting during training. This study aims to evaluate the performance of ensemble learning models in predicting tumor deposits in rectal cancer (RC) and identify the optimal model for preoperative clinical decision-making. A total of 199 RC patients were analyzed, with radiomic features extracted from T2-weighted and apparent diffusion coefficient images and selected through advanced statistical methods. After that, the bagging-ensemble learning model (random forest), boosting-ensemble learning model (XGBoost, AdaBoost, LightGBM, and CatBoost), and voting-ensemble learning model (integrating 5 classifiers) were applied and optimized using grid search with tenfold cross-validation. The area under the receiver operator characteristic curve, calibration curve, t-distributed stochastic neighbor embedding (t-SNE), and decision curve analysis were adopted to evaluate the performance of each model. The voting-ensemble learning model (VELM) performs best in the testing cohort, with an AUC of 0.875 and an accuracy of 0.800. Notably, Calibration plots confirmed VELM’s stability and t-SNE visualization illustrated clear clustering of radiomic features. Decision curve analysis further validated the VELM’s superior net benefit across a range of clinical thresholds, underscoring its potential as a reliable tool for clinical decision-making in RC.

PMID:39924571 | DOI:10.1038/s41598-025-89482-3

Sci Rep. 2025 Feb 10;15(1):4855. doi: 10.1038/s41598-025-89536-6.

ABSTRACT

Apple scab disease causes significant losses in apple crop production. In the north western Himalayas of India, the indiscriminate use of triazole fungicides to manage apple scab has led to the emergence of triazole-resistant strains of V. inaequalis. To investigate the resistance profile in three Venturia inaequalis populations collected from North, South and Central Kashmir, baseline sensitivity assays were conducted on 30 V. inaequalis isolates unexposed to any fungicides. The mean ED₅₀ value and discriminatory dose of difenoconazole and flusilazole were determined to be 0.584, 0.15 µg ml^-1 and 0.018, 0.02 µg ml^-1 respectively. The assessment at these discriminatory doses revealed a major shift in sensitivity against both fungicides. The sequencing of conserved region-2 of CYP51A1 revealed that the resistant isolates have TTT (Phenylalanine) instead of TAT (Tyrosine) codon at position 133. Moreover, the same mutation was observed in some shifted isolates which confirmed that this mutation is not solely responsible for the development of resistance. From linear mixed-model regression analyses, the fitness parameters of resistant isolates were assessed which revealed that except for oxidative stress at 1 mm H₂O₂ (wherein a decreased micro colony growth linearly increases with resistance), there is no fitness cost associated with the development of resistance against difenoconazole and flusilazole. Meanwhile, the resistance against both fungicides is phenotypically stable. Consequently, it is speculated that these populations are unlikely to regain their sensitivity even in the absence of these frequently used fungicides.

PMID:39924568 | DOI:10.1038/s41598-025-89536-6

Sci Rep. 2025 Feb 10;15(1):4856. doi: 10.1038/s41598-025-88730-w.

ABSTRACT

The pore structure of porous media directly affects its permeability characteristics and fluid flow properties, making the accurate reconstruction of these structures of great significance. In recent years, multi-point statistics (MPS) methods have been widely used in pore structure modeling. Among them, the SNESIM algorithm, as an advanced MPS technique, has been extensively applied in the study of porous media pore structures. This paper aims to investigate the use of the SNESIM algorithm for reconstructing pore structures on 2D core slices with varying porosities, all taken from the same core. It also analyzes the effectiveness, limitations, and applicable conditions of the algorithm. This study utilizes CT scan images to construct digital core technology and applies the SNESIM algorithm to reconstruct pore structures of core slices with different porosities. By analyzing performance parameters such as porosity, pore throat ratio, average grain radius, coordination number, and permeability, the study shows that the reconstructed images(RI) from most samples maintain a trend similar to that of the training images(TI), demonstrating the good applicability and reliability of the SNESIM algorithm in pore structure reconstruction. However, the core slices used in this study were all taken from the same core. Effectively transferring the pore structures from the 2D plane to the 3D pore space and restoring the pore structures to the greatest extent still requires further research. In particular, when dealing with complex pore structures, the accuracy and performance of the SNESIM algorithm need further improvement. Future research will focus on optimizing the algorithm to handle more diverse pore structures and exploring 3D reconstruction methods to more comprehensively describe and analyze the pore characteristics in actual porous media.

PMID:39924565 | DOI:10.1038/s41598-025-88730-w

Sci Rep. 2025 Feb 9;15(1):4819. doi: 10.1038/s41598-025-89065-2.

ABSTRACT

Science holds high prestige in society and understanding public perception of what is considered scientific is essential. The scientificity of a profession is the degree of scientific legitimacy and is determined by the quality of its scientific procedures. Higher levels of scientificity are achieved when scientific results are more objective, impartial, and neutral. In this work, we first estimate the scientificity levels attributed to various professions using a logistic regression model. Then, we explore ways to simultaneously improve their scientific perception by means of multiobjective optimization techniques. To this aim, the statistical results are used to formulate a multiobjective optimization model that maximizes the scientific perception of all the professions considered. The findings provide insights into science policy measures to optimize resource allocation in order to increase the scientific perception of the professions.

PMID:39924535 | DOI:10.1038/s41598-025-89065-2

Sci Rep. 2025 Feb 9;15(1):4818. doi: 10.1038/s41598-025-88961-x.

ABSTRACT

Fatigue is a common health complaint in older adults, but its prevalence varies widely among studies due to differences in populations and assessment tools. The objective of this review is to systematically evaluate the prevalence of fatigue and perceived fatigability in older adults with PRISMA 2020. Four databases-PubMed, Embase, Web of Science (WoS), and Cochrane Library-were systematically searched as of December 27, 2023. Cochrane Q tests and the I² statistic were used using Stata16.0 to assess between-study heterogeneity. A total of 21 studies involving 17843 participants were included in this study. The prevalence of fatigue in older adults was 42.6%, and the prevalence of perceived physical fatigability and mental fatigability was 58.2% and 24.0%. Meta-analysis showed that the prevalence of perceived physical fatigability among older adults was very high. This prevalence varied with regional economic development level, age of the subjects, sample size, and representativeness of the subjects. Fatigue is a health dilemma faced by most older adults. To improve quality of life, early and regular fatigue assessment should be part of routine health screening for older adults.

PMID:39924533 | DOI:10.1038/s41598-025-88961-x

Sci Rep. 2025 Feb 9;15(1):4821. doi: 10.1038/s41598-025-89115-9.

ABSTRACT

Breast cancer, a complex global health concern, has predominantly been studied for nuclear DNA variations. However, the role of mitochondrial DNA (mtDNA) haplogroups in breast cancer susceptibility, especially in Pakistan, remains underexplored. This case-control study investigates the association between mtDNA haplogroups and breast cancer in Pakistan. The study reveals a significant abundance of haplogroup M in breast cancer cases by analyzing breast cancer patients and healthy controls through mitochondrial control region genome sequencing (p < 0.001). Increased frequencies of haplogroups M, H, and R in patients compared to controls suggest their potential role in breast cancer susceptibility. Triple-Negative Breast Cancer (TNBC) cases are also linked to haplogroup M, showing a statistically significant association with a p-value of 0.002. This suggests a potential meaningful association between haplogroup M and the occurrence of TNBC in the studied population. These findings emphasize the importance of mitochondrial genetics in breast cancer risk among the Pakistani population, offering insights for biomarker discovery and targeted interventions. Recognizing mitochondrial genetics in breast cancer risk assessment holds promise for tailored medicine strategies and may impact global breast cancer research and prevention efforts.

PMID:39924515 | DOI:10.1038/s41598-025-89115-9

Sci Rep. 2025 Feb 9;15(1):4809. doi: 10.1038/s41598-024-83657-0.

ABSTRACT

Asia is home to diverse hunter-gatherer populations characterized by significant morphological, anthropological, cultural, and linguistic diversity. Despite their importance in understanding ancestral human subsistence, little is known about the essential genetic adaptations of these groups. This study investigates the evolutionary pressures shaping the genome of the Maniq population, a nomadic hunter-gatherer group inhabiting the rainforests of southern Thailand. Using genome-wide approaches, including iHS, xp-EHH, PBE, and beta statistics, we identified signatures of positive and balancing selection. Genes under positive selection were enriched in pathways related to immunity, metabolic regulation, structural adaptation, cardiovascular performance, and neuromodulatory traits. Several genes associated with the Southeast Asian ‘negrito-like’ phenotype were also under positive selection. Balancing selection was primarily detected in immune-related genes, particularly within the HLA region, underscoring the critical role of genetic diversity in surviving pathogen-rich environments. Additionally, balancing selection in olfactory receptor genes highlights their importance in environmental sensing and adaptation. These results reveal the intricate interplay of positive and balancing selection in shaping the genetic landscape of the Maniq population and highlight their adaptations to the ecological and lifestyle challenges of life in the rainforest. This study contributes to our understanding of human evolutionary processes in tropical environments and hunter-gatherer societies.

PMID:39924514 | DOI:10.1038/s41598-024-83657-0

J Orthop Surg Res. 2025 Feb 9;20(1):153. doi: 10.1186/s13018-025-05543-3.

ABSTRACT

BACKGROUND: Previous studies have shown that hyaluronic acid can delay the progression of knee osteoarthritis. Existing research has extracted a bright red fluid called cell-free fat extract from human adipose tissue, which may play an important role in delaying the progression of osteoarthritis. By comparing with intra-articular injection of hyaluronic acid, this study aimed to evaluate the effects of intra-articular injection of CEFFE on both clinical efficacy and the reduction of bone marrow edema in patients with early to mid-stage knee osteoarthritis.

METHODS: A total of 48 patients with KOA (Kellgren-Lawrence grade II-III) symptoms were randomly divided into CEFFE group (24 cases) and HA group (24 cases). The patients in the CEFFE group received five injections of CEFFE (2 ml, 1 time/week), and the patients in the HA group received five injections of HA (2 ml, 1 ml/10 mg, 1 time/week). All the patients underwent clinical assessments using rating scales, including VAS, WOMAC and Lysholm Knee Score. These assessments were conducted at pre-treatment and at 3-week, 6-week, 3-month, and 6-month follow-up timepoints post-treatment. The clinical efficacy was evaluated at the 6-month follow-up after the treatment. The changes in subchondral bone marrow edema before and 6 months after treatment were assessed by grading BME on MRI of the affected knees.

RESULTS: A total of 52 knees from 46 patients were included in the final analysis. Comparison of VAS score, WOMAC score, and Lysholm score between the two groups revealed that the differences between pre-treatment and 3 weeks post-treatment were not statistically significant (P > 0.05). For the VAS score and WOMAC score at 6 weeks, 3 months, and 6 months post-treatment, the CEFFE group was lower than the HA group (P < 0.05). For the Lysholm score, the CEFFE group was higher than the HA group (P < 0.05). Compared with pre-treatment, VAS scores and WOMAC scores were lower and Lysholm scores were higher at all post-treatment time points (P < 0.05). At 6 months post-treatment, the clinical efficacy of the CEFFE group was significantly better than that of the HA group (P < 0.05). At 6 months post-treatment, MRI grading showed that subchondral BME was reduced to different degrees in both groups, with the reduction being more pronounced in the CEFFE group (P < 0.05).

CONCLUSION: This study demonstrated that intra-articular injection of CEFFE into the knee joint could enhance the durability of tissue-specific cells (especially chondrocytes) and improve cellular metabolic processes, preventing the continued progression of osteoarthritis. Both CEFFE and HA were found to improve clinical symptoms and reduced subchondral bone marrow edema in the treatment of early to mid-stage knee osteoarthritis. However, CEFFE was more effective than HA in achieving these outcomes.

PMID:39924508 | DOI:10.1186/s13018-025-05543-3

BMC Glob Public Health. 2025 Feb 10;3(1):12. doi: 10.1186/s44263-025-00130-4.

ABSTRACT

BACKGROUND: Income is associated with many health outcomes, but it is unclear how far this reflects a causal relationship. Mendelian randomisation (MR) uses genetic variation between individuals to investigate causal effects and may overcome some of the confounding issues inherent in many observational study designs.

METHODS: We used two-sample MR using data from unrelated individuals to estimate the effect of log occupational income on indicators of mental health, physical health, and health-related behaviours. We investigated pleiotropy (direct effects of genotype on the outcome) using robust MR estimators, CAUSE, and multivariable MR including education as a co-exposure. We also investigated demographic factors and dynastic effects using within-family analyses, and misspecification of the primary phenotype using bidirectional MR and Steiger filtering.

RESULTS: We found that a 10% increase in income lowered the odds of depression (OR 0.92 [95% CI 0.86-0.98]), death (0.91 [0.86-0.96]), and ever-smoking (OR 0.91 [0.86-0.96]), and reduced BMI (- 0.06 SD [- 0.11, – 0.003]). We found little evidence of an effect on alcohol consumption (- 0.02 SD [- 0.01, 0.05]) or subjective wellbeing (0.02 SD [- 0.003, 0.04]), or on two negative control outcomes, childhood asthma (OR 0.99 [0.87, 1.13]) and birth weight (- 0.02 SD, [- 0.01, 0.05]). Within-family analysis and multivariable MR including education and income were imprecise, and there was substantial overlap between the genotypes associated with income and education: out of 36 genetic variants significantly associated with income, 29 were also significantly associated with education.

CONCLUSIONS: MR evidence provides some limited support for causal effects of income on some mental health outcomes and health behaviours, but the lack of reliable evidence from approaches accounting for family-level confounding and potential pleiotropic effects of education places considerable caveats on this conclusion. MR may nevertheless be a useful complement to other observational study designs since its assumptions and limitations are radically different. Further research is needed using larger family-based genetic cohorts, and investigating the overlap between income and other socioeconomic measures.

PMID:39924502 | DOI:10.1186/s44263-025-00130-4