Tag: statistics

Sci Rep. 2025 Jul 2;15(1):23240. doi: 10.1038/s41598-025-06175-7.

ABSTRACT

Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder, yet its underlying molecular mechanisms remain puzzling. This study aimed to uncover the genes with a causal relationship to KOA using Mendelian randomization (MR), transcriptomic profiling, and machine learning methods. MR analysis was conducted utilizing expression quantitative trait loci (eQTL) data from the eQTLGen consortium alongside KOA-related GWAS summary statistics to identify candidate genes. Subsequently, differential expression analysis and WGCNA were applied to synovial tissue microarray datasets obtained from the GEO database. The intersecting genes were further refined using three machine learning algorithms: LASSO, random forest, and SVM-RFE. Diagnostic efficacy was assessed via ROC curve analysis and nomogram construction. Validation was ultimately performed using qPCR on clinical synovial tissue samples. Twelve genes with putative causal associations to KOA were identified, with MEG3 and MAPK3 emerging as the most diagnostically robust. Both exhibited high sensitivity and specificity in ROC analysis, and their differential expression was corroborated by qPCR. This study underscores the diagnostic utility of MEG3 and MAPK3 in KOA and offers a promising molecular framework for early disease detection. Nonetheless, validation in larger, independent cohorts and further mechanistic investigations are warranted to substantiate these findings.

PMID:40604047 | DOI:10.1038/s41598-025-06175-7

Sci Rep. 2025 Jul 2;15(1):23367. doi: 10.1038/s41598-025-06389-9.

ABSTRACT

It is important to highlight that infection with the human immunodeficiency virus (HIV) may trigger chronic inflammation in people living with HIV/AIDS (PLWHA), impacting to the key immune cells such B and T lymphocytes, leading to development of autoantibodies which might be potential to developed autoimmune phenomenon. This study represent the first investigation in Sudan designed to evaluate and determine the prevalence of Antinuclear autoantibody (ANA) among people living with HIV/AIDS by systematically charaterizing ANA staining patterns; distribution, frequency and their correlation with estimated endpoint titers and interplay of age -sex specific ANA patterns in the context of HIV infection post antiretroviral therapy era. Using Serum samples of one hundred and sixteen (116) HIV-infected patients admitted to two major Voluntary Testing and Counseling (VTC), of the HIV clinical centers at the Military Hospital and Bahri Hospital in Khartoum, Sudan, have been assessed for ANA screening. A total of 116 HIV confirmed cases, were screened for ANA autoantibodies using HEp-2 cell indirect immunofluorescent technique. out of 116 85/116 (73.3%) were showed positivity for ANA. the proportion of ANA positivity among the male group was higher than the female group, 49/65 (75.4%) and 36/51 (70.6%), respectively, but there are no significant statistical differences (p = 0.7). Interestingly, a high proportion of positivity for ANA were found in the older subject groups (aged 42-56 years and > 57 years), with rates of 80% for each. Furthermore, our study also showed that the predominant ANA patterns were nuclear fine-speckled (AC-4, 56.5%) followed by cytoplasmic fine granules (AC-20, 24.7%). This study suggests that HIV might induced chronic inflammation and trigger the production of autoantibodies with variable specificities, needing further studies to better understand the role of HIV-driven chronic inflammation in shaping autoimmune serological profiles in these patients.

PMID:40604026 | DOI:10.1038/s41598-025-06389-9

Sci Rep. 2025 Jul 2;15(1):23664. doi: 10.1038/s41598-025-07694-z.

ABSTRACT

This study introduces new approach which combines the geometrical theory of diffraction (GTD) and the ray tracing (RT) method to analyze the produced scattering pattern due to a striking plane wave on a rough surface with random attributes regarding electromagnetic and statistical properties. The Fresnel equation-based model is utilized to determine the distribution of scattered power for both reflection from the region above the surface and transmission into the region beneath the surface. The polarization (direction of electric field) of the incident optical wave is also considered. The proposed algorithm addresses multi-bounce of striking ray, making it an advanced higher-order GTD-RT approach. The precision of the findings is validated by comparing them with scattering pattern data from empirical observations produced by a Radiant beam striking paper sheets with different roughness properties and different probabilistic characteristics. This study’s numerical results explore how the scattering pattern is influenced by surface degree of granularity, incidence angle, and light refraction coefficient of the rough surface. Additionally, first and second order scattering are calculated and compared. The second-order GTD-RT method provides slightly improved accuracy over the first-order method, especially for highly rough surfaces, but the enhancement remains marginal. Given its low average error (< 2.5%) and significantly lower computational cost, the first-order GTD-RT method offers a more practical and efficient solution for optical scattering analysis in rough surface scenarios. To validate the accuracy and reliability of the proposed model, a subset of the numerical results obtained in this study has been systematically compared with previously published findings derived using alternative analytical approaches, specifically the Geometrical Optics (GO) method and the second-order Kirchhoff approximation. These comparisons serve to highlight the consistency of the presented approach with established theoretical models and underscore its capability to accurately characterize the scattering behavior from rough surfaces under similar conditions.

PMID:40604003 | DOI:10.1038/s41598-025-07694-z

Sci Rep. 2025 Jul 2;15(1):23323. doi: 10.1038/s41598-025-07031-4.

ABSTRACT

Industrial development has caused significant environmental pollution by discharging chromium (Cr) contaminated hazardous effluents into the ecosystem. The main goal of this study was to isolate, characterize, and assess the Cr(VI) resistance potential of indigenous naturally occurring chromate-resistant bacteria from the Uttar Dinajpur region of West Bengal. Based on the maximum tolerable concentration (MTC) to Cr(VI), a potent indigenous bacterial isolate with an MTC of 400 µg mL^{– 1} was selected for a detailed assessment of its Cr(VI) tolerance and reducing abilities. Molecular identification and phylogenetics revealed the isolate as a strain of Bacillus wiedmannii. Cr(VI) resistance ability of the isolate in different pH was analyzed, and a Fourier-transform infrared spectroscopy analysis under different pH in the presence of Cr(VI) was performed to capture the preliminary variation in the metabolic fingerprints. The isolate demonstrated Cr(VI) removal efficiency of 70.27% Cr(VI) at pH 8. The expression of chromate reductase enzyme in constitutive and Cr(VI) induced conditions was measured using different electron donors, and a detailed statistical analysis was performed to determine whether there exists a significant difference in the specific activity of chromate reductase in constitutive and induced conditions. The extracellular chromate reductase had a 98.42% Cr(VI) reduction rate using glucose as an electron donor and it was significantly higher than that of other electron donors, indicating glucose as the preferred electron source for Cr(VI) reduction. The genes responsible for coding enzymes responsible for chromate reduction viz., azoreductase, FMN-dependent NADH-azoreductase type1, and chromate reductase were also detected in the studied isolate. The findings of this study may contribute to the pool of indigenous isolates in countering chromate toxicity and their efficient utilization in chromate detoxification and bioremediation.

PMID:40603995 | DOI:10.1038/s41598-025-07031-4

Sci Rep. 2025 Jul 2;15(1):23622. doi: 10.1038/s41598-025-06714-2.

ABSTRACT

To investigate the genetic etiology of ventriculomegaly (VM) in fetuses by analyzing chromosomal aberrations and genetic variations through high-throughput sequencing. Clinical data and samples (amniotic fluid or miscarriage tissue) were collected from fetuses with ventricular width >10 mm, diagnosed at Shanxi Children’s Hospital between 2020 and 2023. All samples underwent copy number variation sequencing (CNV-seq), and those with negative CNV-seq result were further analyzed by whole exome sequencing (WES) to identify single-gene variants. Chromosomal abnormalities and monogenic variants were classified according to the American College of Medical Genetics and Genomics guidelines. Statistical analysis was performed using SPSS 26.0, and pregnancy outcomes were tracked. Among 73 VM fetuses, 23 (31.5%) cases exhibited chromosomal aberrations via CNV-seq, including 4 aneuploidies, 12 pathogenic CNVs, 2 likely pathogenic CNVs, and 8 variants of unknown significance. The incidence of chromosomal abnormalities was significantly higher in non-isolated VM fetuses compared to isolated VM (p < 0.05). WES analysis of 33 CNV-negative cases identified single-gene defects in 16 (48.5%) fetuses, including SPATA5, PDHA1, TRIM71, PIK3R2, TUBB, CRB2, PIDD1, RTTN, FGFR3, AIMP1, POGZ, MYH7, CNOT3, MACF1, and PURA gene, with 10 novel variants reported. Fetal VM is associated with heterogeneous neurodevelopmental outcomes, and genetic etiology plays an important role in its pathogenesis. WES enhances the efficiency of diagnosis, particularly for VM fetuses without detectable aneuploidy or CNVs. Identifying the genetic etiology of fetal VM is is crucial for informing birth defect prevention strategies and improving the overall health of the newborn population.

PMID:40603987 | DOI:10.1038/s41598-025-06714-2

Sci Rep. 2025 Jul 2;15(1):23645. doi: 10.1038/s41598-025-00176-2.

ABSTRACT

The association between neutrophil-to-lymphocyte ratio (NLR), an inflammatory marker, and all-cause mortality among individuals with obstructive sleep apnea (OSA) remains unclear. This study aimed to evaluate the association of NLR with all-cause mortality among individuals with OSA. A total of 4,085 participants with OSA were selected from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2008, with follow-up data collected until December 31, 2019. Weighted Cox regression analyses were used to explore the association between the NLR and all-cause mortality. Nonlinear associations were detected using restricted cubic splines (RCS). Subgroup analyses were further performed to explore these relationships. The mean follow-up time for the entire cohort was 137.7 months. There was a clear trend of increasing mortality risk with higher NLR quartiles, rising from 11.86% in Q1, 13.41% in Q2, 14.81% in Q3, to 29.22% in Q4. The Cox regression analysis revealed that lnNLR was associated with an increased risk of all-cause mortality after full adjustment (hazard ratio [HR] = 1.81, 95% CI 1.43-2.30, p < 0.001). RCS showed a J-shaped relationship between lnNLR with all-cause mortality (p-non-linear < 0.001). The interaction tests found that coronary heart disease (CHD) influenced the association between lnNLR and all-cause mortality, with a HR of 3.98 for those with CHD and 1.62 for those without CHD (p = 0.008). There was a nonlinear correlation between elevated NLR and increased risk of all-cause mortality among OSA individuals. The association was more pronounced among CHD subgroups. Future research should explore the underlying mechanisms and evaluate whether therapies targeting inflammation can lower mortality risk in OSA patients.

PMID:40603961 | DOI:10.1038/s41598-025-00176-2

Sci Rep. 2025 Jul 2;15(1):23363. doi: 10.1038/s41598-025-03173-7.

ABSTRACT

Research on the relationship between socioeconomic status (SES), the prevalence of disability, and the use of healthcare services by people with disabilities is limited. The aim of this study is to identify socioeconomic predictors of disability and examine the utilization of healthcare services among people with disabilities in Bangladesh. We used the first national representative, the National Household Survey on Persons with Disabilities (NSPD) 2021 survey data. The data utilized in our analysis came from 100,859 people who were at least 18 years old. Standard of living (henceforth referred to as wealth) was our proxy indicator of SES. The variables of interest for the outcome were the respondents’ disability status and frequency of use of healthcare services. Adjusted odds ratio, relative, and slope inequality index are three regression-based techniques we utilized to evaluate different aspects of SES disparities in use of healthcare services and disability status. The prevalence of disability of our study sample was 3.40% and about 74.06% of people with disabilities have used healthcare services in the past three months. When compared to people in the poor SES group, people in the rich and middle SES group had 0.69 (95% CI 0.60-0.78) and 0.80 (95% CI 0.78-0.95) times lower chance of developing disability. When compared to individuals in the poor SES group, those in the rich and middle SES groups were 2.12 times (95% CI 1.55-2.89) and 1.39 times (95% CI 1.12-1.72) more likely to use of healthcare services. SES should be a key consideration in designing public health programs aimed at improving healthcare access and reducing disability prevalence in Bangladesh.

PMID:40603941 | DOI:10.1038/s41598-025-03173-7

Sci Rep. 2025 Jul 2;15(1):23182. doi: 10.1038/s41598-025-03188-0.

ABSTRACT

The combined method for interval forecasting (CMIF) is proposed for improved real-time prediction of wind speed uncertainty to facilitate wind turbine operation and power grid dispatching. Time-varying filtering for empirical mode decomposition and phase space reconstruction are used to decompose and reconstruct the original wind speed sequence to solve chaotic phenomena and eliminate noise. Statistical and machine learning models are considered as candidates, and models with excellent performances are selected. Finally, the selected models are combined by a multi-objective optimizer to obtain the final prediction. Experiments were performed using data from the Gansu wind tower, and the results showed that CMIF improved the accuracy of the predicted wind speed interval by 1.07-55.37% compared with single models. The prediction interval had a narrow width while maintaining a high coverage rate, which facilitated accurate quantification of the wind speed uncertainty.

PMID:40603938 | DOI:10.1038/s41598-025-03188-0

Sci Rep. 2025 Jul 2;15(1):23287. doi: 10.1038/s41598-025-04287-8.

ABSTRACT

The space-borne gravitational wave observatory is to detect low-frequency gravitational wave signals in the range of 0.1-100 mHz. The inertial sensors of space gravitational wave require very high accuracy for acceleration noise, and the interaction of the space magnetic field with the test mass can generate magnetic moment forces and Lorentz forces, which lead to acceleration noise. Here, we obtain space magnetic field data from OMNI during 25 years from 1998 to 2022. And accordingly, we calculate the acceleration noise of space magnetic field of a heliocentric gravitational wave observatory, LISA, in more than 2 solar activity cycles. Then, we obtain the amplitude spectral densities of the acceleration noise for each day of the 25 years. We find that the median of the space magnetic field acceleration noise of LISA at 1 mHz is about 1 × 10 – 17 m s – 2 H z – 1 / 2 . We compare the space magnetic field acceleration noise of LISA and a geocentric gravitational wave observatory, TianQin, and find that the acceleration noise of the space magnetic field is of comparable magnitude for TianQin and LISA, and neither of them exceeds the respective acceleration noise requirements. Based on the statistical result of space magnetic field acceleration noise in more than 2 solar cycles, we give the χ – ξ parameters map of the TM for LISA and TianQin, and find that TianQin has a more stringent requirement of the parameters design than that of LISA.

PMID:40603937 | DOI:10.1038/s41598-025-04287-8

Sci Rep. 2025 Jul 2;15(1):23351. doi: 10.1038/s41598-025-06111-9.

ABSTRACT

Motion Capture (MoCap) is rapidly growing in the sports, biomechanics, healthcare, and medicine segments, where accuracy is crucial. Current research studies are concurrently confirming that the accuracy can be determined only for the specific analyzed configuration and thus recommending performing your own accuracy verification on your specific setup. However, it is often hard to perform since it requires significant effort, time, knowledge of statistical data analysis and often equipment and tools that are not commonly available. This paper deals with this by creating a standardized setup with carefully evaluated accuracy, substituting the on-site validation process (in case of using such a setup) or providing the worst-case accuracy (when a more advanced setup is used). The setup is designed to be low-cost, easily reproducible and cover a wide range of applications – thus VICON setup with five VERO v1.3 cameras is used. The accuracy was evaluated using the robotic manipulator EPSON C3, determining that the absolute positioning accuracy of such a standardized setup is 0.65 mm on average (SD = 0.48, with maximal error of 2.47 mm) and rotation accuracy 0.40° (SD = 0.35, with maximal error of 2.0°), which is negligible considering the experimental diameter of 1.4 m and full angular span. The major source of error was specific to particular spatial and rotational positions; other systematic and other random errors were noticeably smaller. If the standardized setup is used and all its requirements are met, a similar accuracy as validated above can be expected without the need to explicitly validate the specific configuration, which is time-consuming and resource-intensive.

PMID:40603931 | DOI:10.1038/s41598-025-06111-9