Category: Statistics

Sci Rep. 2025 Apr 27;15(1):14726. doi: 10.1038/s41598-025-98795-2.

ABSTRACT

The prevention of osteoarthritis through controlling body measurements has received increasing attention in recent years, but the relationship between lean body mass (LBM) and osteoarthritis remains unclear. Hence, we explored this association through the data from the National Health and Nutrition Examination Survey (2007-2018). The present study enrolled 31,172 participants. To explore the correlation between LBM and osteoarthritis, we utilized logistic regression equations to explore associations between covariates, exposures, and outcomes. We used multivariate regression models to further control confounding factors. Restricted cubic splines were employed to investigate non-linear relationships. And the inflection point was identified by recursive algorithm. Furthermore, stratified analyses of gender and age were conducted. Osteoarthritis was negatively correlated with LBM [0.74 (0.67, 0.80)] in the model adjusting for all confounders. Based on the restricted cubic spline curve, an inflection point of 52.26 kg was found to confirm the non-linear relationship. LBM was negatively correlated with osteoarthritis at 0.56 (0.48, 0.64) before the inflection point, and the association was not statistically significant afterward. This large-scale study revealed that LBM was non-linearly correlated with osteoarthritis in the general American population. Differences in age and gender were further identified.

PMID:40289200 | DOI:10.1038/s41598-025-98795-2

Sci Rep. 2025 Apr 27;15(1):14703. doi: 10.1038/s41598-025-98435-9.

ABSTRACT

Environmental Health Literacy (EHL) focuses on significant impact of environmental factors on human health and emphasizes the importance of public awareness and engagement in identifying and mitigating environmental health risks. This paper presents a study in the Distrito Federal, Brazil, aimed at evaluating EHL and identify the main socioeconomic characteristics capable of predicting EHL levels. Using the EHL Scale, which assesses knowledge, attitudes, and behaviors toward environmental health, this research applies a questionnaire to 397 respondents. Through descriptive statistics and confirmatory and exploratory factor analyses, the study validates the scale for the Brazilian context and offers structural adjustments for the air scale. Using the socioeconomic data we implemented a predictive Random Forest algorithm to forecast EHL levels on each of the scales. By extracting the Shapley values from the model, we established the most relevant variables to predict EHL, offering valuable insights for policymakers, health and environmental professionals to enhance public engagement with environmental health issues. The results indicate that social vulnerability features are predictive of EHL, including education, income, age, ethnicity, presence of disability and use of continuous medication. This study identifies factors that bolster policy strategies to communicate environmental health risks and promote behavior change regarding the environment and self-care.

PMID:40289196 | DOI:10.1038/s41598-025-98435-9

Sci Rep. 2025 Apr 27;15(1):14720. doi: 10.1038/s41598-025-98155-0.

ABSTRACT

Distinguishing the luminal subtypes of breast cancer (BC) remaining challenging. Thus, the aim of this study was to investigate the feasibility of radiomic signature using intratumoral and peritumoral features obtained from dynamic contrast-enhanced MRI (DCE-MRI) in preoperatively discriminating the luminal from non-luminal type in patients with BC. A total of 305 patients with pathologically confirmed BC from three hospitals were retrospectively enrolled. The LASSO method was then used for selecting features, and the radiomic score (radscore) for each patient was calculated. Based on the radscore, Radiomic signature of intratumoral, peritumoral, and combined intratumoral and peritumoral were established, respectively. The performances of the radiomic signatures were validated with receiver operator characteristic (ROC) curve and decision curve analysis. For predicting molecular subtypes, the AUC for intratumoral radiomic signature was 0.817, 0.838, and 0.883 in the training set, internal validation set, and external validation set, respectively. AUC for the peritumoral radiomic signature was 0.863, 0.895, and 0.889 in the training set, internal validation set, and external validation set, respectively. The AUC for combined intratumoral and peritumoral radiomic signature was 0.956, 0.945, and 0.896 in the training set, internal validation set, and external validation set, respectively. Additional contributing value of combined intratumoral and peritumoral radiomic signature to the intratumoral radiomic signature was statistically significant [NRI, 0.300 (95% CI: 0.117-0.482), P = 0.001 in internal validation set; NRI, 0.224 (95% CI: 0.038-0.410), P = 0.018 in external validation set]. These results indicated that the radiomic signature combining intratumoral and peritumoral features showed good performance in predicting the luminal type of breast cancer.

PMID:40289183 | DOI:10.1038/s41598-025-98155-0

Sci Rep. 2025 Apr 27;15(1):14700. doi: 10.1038/s41598-025-95207-3.

ABSTRACT

The combination of autonomous recording units (ARUs) and machine learning enables scalable biodiversity monitoring. These data are often analysed using occupancy models, yet methods for integrating machine learning outputs with these models are rarely compared. Using the Yucatán black howler monkey as a case study, we evaluated four approaches for integrating ARU data and machine learning outputs into occupancy models: (i) standard occupancy models with verified data, and false-positive occupancy models using (ii) presence-absence data, (iii) counts of detections, and (iv) continuous classifier scores. We assessed estimator accuracy and the effects of decision threshold, temporal subsampling, and verification strategies. We found that classifier-guided listening with a standard occupancy model provided an accurate estimate with minimal verification effort. The false-positive models yielded similarly accurate estimates under specific conditions, but were sensitive to subjective choices including decision threshold. The inability to determine stable parameter choices a priori, coupled with the increased computational complexity of several models (i.e. the detection-count and continuous-score models), limits the practical application of false-positive models. In the case of a high-performance classifier and a readily detectable species, classifier-guided listening paired with a standard occupancy model provides a practical and efficient approach for accurately estimating occupancy.

PMID:40289178 | DOI:10.1038/s41598-025-95207-3

Sci Rep. 2025 Apr 27;15(1):14725. doi: 10.1038/s41598-025-98865-5.

ABSTRACT

The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where such modeling proceeds is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of the temporal structure of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain automatically and continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Our work provides a comprehensive picture of the neural correlates of automatic encoding of implicit structure that can be the crucial substrate for the swift detection of patterns and unexpected events in the environment.

PMID:40289162 | DOI:10.1038/s41598-025-98865-5

Light Sci Appl. 2025 Apr 27;14(1):175. doi: 10.1038/s41377-025-01865-3.

ABSTRACT

Links and knots are exotic topological structures that have garnered significant interest across multiple branches of natural sciences. Coherent links and knots, such as those constructed by phase or polarization singularities of coherent light, have been observed in various three-dimensional optical settings. However, incoherent links and knots-knotted or connected lines of coherence singularities-arise from a fundamentally different concept. They are “hidden” in the statistic properties of a randomly fluctuating field, making their presence often elusive or undetectable. Here, we theoretically construct and experimentally demonstrate such topological entities of incoherent light. By leveraging a state-of-the-art incoherent modal-decomposition scheme, we unveil incoherent topological structures from fluctuating light speckles, including Hopf links and Trefoil knots of coherence singularities that are robust against coherence and intensity fluctuations. Our work is applicable to diverse wave systems where incoherence or practical coherence is prevalent, and may pave the way for design and implementation of statistically-shaped topological structures for various applications such as high-dimensional optical information encoding and optical communications.

PMID:40289134 | DOI:10.1038/s41377-025-01865-3

Ital J Pediatr. 2025 Apr 27;51(1):129. doi: 10.1186/s13052-025-01972-2.

ABSTRACT

BACKGROUND: Molar incisor hypomineralisation (MIH) is a developmental dental condition that causes defects in the enamel of the first molars and permanent incisors. The aim of the present study was to assess possible causal correlations between the mother-child dyad medical history and MIH.

METHODS: An observational, retrospective, case‒control pilot study was carried out at the Dental Clinic of the University of Salamanca. This study was conducted between November 2023 and May 2024. Data on potential aetiological factors were collected through personal interviews, and the children’s parents were asked aetiological questions. Statistical analysis was performed with Student’s t test and the chi-square test.

RESULTS: A total of 140 children were enrolled in the study. The case group included 70 children with MIH (31 boys and 39 girls; mean age: 9.1 ± 2.32 years), while the control group comprised 70 children without MIH (32 boys and 38 girls; mean age: 9.57 ± 3.09 years). Among the factors assessed, maternal drug allergies during pregnancy and childhood asthma were identified as potential aetiological contributors to MIH, both showing statistically significant associations (p < 0.01).

CONCLUSIONS: Within the limitations of this pilot case-control study, a potential association was observed between MIH and both maternal drug allergies during pregnancy and childhood asthma. These findings support the need for further investigation into prenatal and early-life factors that may contribute to enamel developmental disturbances. Larger prospective studies are recommended to confirm these associations and better understand the underlying mechanisms.

PMID:40289126 | DOI:10.1186/s13052-025-01972-2

BMC Neurol. 2025 Apr 28;25(1):186. doi: 10.1186/s12883-024-03989-2.

ABSTRACT

OBJECTIVE: Based on the near-infrared functional brain imaging system, this research studied the hemoglobin concentration signal in resting state and task state. The purpose of this research was to analyze the activated brain regions and functional connections by exploring the changes in hemoglobin concentration and the differences in brain network functional connections between healthy people and mild to moderate AD patients. So as to identify the cognitive dysfunction of patients at an early stage. By accurately locating the area of cognitive impairment in patients, it provides a basis for precise neural regulation of physical therapy.

METHODS: Patients who came to our hospital from January 2022 to December 2022 were recruited and selected according to the exclusion criteria. After receiving their informed consent, MMSE scale examination and near-infrared brain function imaging examination were performed in a relatively quiet environment.

RESULT: A total of 24 subjects were included in this study, including 7 in the control group (age: 72.57 ± 7.19) and 17 (age: 76.88 ± 9.29) in the AD group. The average cognitive scores were (28.00 ± 1.16), (19.24 ± 4.89), respectively. There were no statistically significant differences in gender, years of education, age, and past medical history between the AD group and the control group (P > 0.05). In the verbal fluency test (VFT) task, there was a significant difference in the activation values of the two groups in channels 01, 06, 07, 09, 13, 14, 15, 16, 19, 21, 22, 23, 27, 29, 31, 35, 38, 40, 43, 44, 45, 51, and 52II (p < 0.05), and the activation values of the normal group were greater than those of the AD group. There was a significant difference in the mean oxygenated hemoglobin concentration in channels 01, 07, 15, 16, 21, 22, 23, 31, 35, 40, 41, 44, and 48 (p < 0.05), and the average oxygenated hemoglobin concentration in the AD group was lower than that in the normal group. There was no significant difference in activation speed between the two groups. In the resting state, the number of total network edges, DLPFC-L to PreM and SMC-L, DLPFC-L to FEF-L, DLPFC-L to DLPFC-L, FPA-L to PreM and SMC-L, FPA-L to FPA-L, FPA-R to FPA-L, DLPFC-L to DLPFC-R, FEF-R to PreM and There was a statistically significant difference in the number of network edges in SMC-L (p < 0.05). Among the different groups, the number of network edges in the AD group was smaller than that in the normal group. Correlation analysis showed that T14, T31, T16, T23, T27, M16, M22, M41 (T: represents activation value, M: represents mean hemoglobin concentration, and number represents channel number). There was a positive correlation between the total number of network edges, DLPFC-L to PreM and SMC-L, DLPFC-L to DLPFC-L, FPA-L to PreM and SMC-L, FPA-L to FPA-L, DLPFC-L to DLPFC-R, FEF-R to PreM and SMC-L, and MMSE scores (p < 0.05).

DISCUSSION: In this study, we found hemodynamic changes in the prefrontal lobes of AD patients under the VFT task, and the decrease in the functional connectivity of the prefrontal brain network in AD patients in the resting state, and these changes were associated with cognitive decline in patients. Our findings suggest that fNIRS may be used as a tool for future clinical screening for cognitive impairment, and may also be used to develop personalized preventive measures and treatment plans through accurate assessment.

PMID:40289104 | DOI:10.1186/s12883-024-03989-2

BMC Microbiol. 2025 Apr 27;25(1):250. doi: 10.1186/s12866-025-03953-1.

ABSTRACT

Synbiotic interventions have gained increasing attention for modulating gut microbiota and metabolic functions in obesity-related disorders. This study evaluated the effects of Limosilactobacillus reuteri KUB-AC5 (10⁸ CFU) and Wolffia globosa powder (6 g/day) using an in vitro continuous human gastrointestinal model. Fecal samples from obese donors were used to simulate the ascending and descending colon, with microbial viability, diversity, and metabolite production assessed over 14 days via culture-dependent and culture-independent methods. Synbiotic supplementation increased anaerobic bacterial counts by 2.6 log CFU/mL in the ascending colon and 2.2 log CFU/mL in the descending colon, with notable increases in lactic acid bacteria and reductions in Enterobacteriaceae. Metagenomic analysis revealed an increasing trend in microbial diversity and evenness after 7 days of treatment, though the changes were not statistically significant. PERMANOVA analysis confirmed significant shift in microbial community composition between stabilization, treatment, and washout periods (p < 0.05). Additionally, butyrate levels significantly increased (p < 0.05), while p-cresol, a deleterious metabolite, significantly decreased (p < 0.05). Bile acid composition was modulated, with increased tertiary bile acid 3-oxo-LCA and enhanced bile acid deconjugation, suggesting improved lipid metabolism and potential weight management benefits. These findings highlight the potential of synbiotic supplementation to enhance beneficial bacterial populations, improve microbial diversity, and support metabolic health in obesity management.

PMID:40289100 | DOI:10.1186/s12866-025-03953-1

BMC Gastroenterol. 2025 Apr 27;25(1):302. doi: 10.1186/s12876-025-03860-9.

ABSTRACT

BACKGROUND: Gastrointestinal (GI) cancers, including gastric, colorectal, and esophageal cancers, pose a significant global health burden. Despite advancements in diagnostic tools, early detection remains challenging, particularly in low-resource settings. Emerging evidence highlights the platelet-to-high-density lipoprotein ratio (PHR) as a novel biomarker integrating systemic inflammation and lipid metabolism. However, its association with GI cancer risk remains underexplored.

METHODS: This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2010 to 2018, comprising 19,388 participants, including 230 with GI cancers. PHR was calculated as the ratio of platelet count to high-density lipoprotein cholesterol levels and categorized into quartiles. Weighted logistic regression models, restricted cubic spline analysis, and subgroup analyses were employed to evaluate the association between PHR and GI cancer risk, adjusting for demographic, socioeconomic, lifestyle, and clinical factors.

RESULTS: Elevated PHR was independently associated with an increased risk of GI cancers. Participants in the highest PHR quartile exhibited a significantly higher risk (adjusted OR = 3.09; 95% CI: 2.16-4.43) compared to the lowest quartile. A dose-response relationship was observed, with two critical inflection points at PHR values of 3.2 and 4.5. Subgroup analyses revealed stronger associations among older adults, males, and obese individuals. The findings suggest that PHR may reflect the dynamic balance of systemic inflammation and lipid metabolism, contributing to tumorigenesis.

CONCLUSION: This study identifies PHR as a promising, cost-effective biomarker for early detection and risk stratification of GI cancers. Its integration into screening programs could improve precision medicine strategies by identifying high-risk individuals for early intervention. Further longitudinal and mechanistic studies are warranted to confirm these findings and explore the underlying biological mechanisms.

PMID:40289098 | DOI:10.1186/s12876-025-03860-9