Tag: statistics

Sci Rep. 2025 Sep 30;15(1):34044. doi: 10.1038/s41598-025-13004-4.

ABSTRACT

As a total ankle replacement (TAR) prosthesis has been developed and improved in terms of design and surgical technique, it could be expected to lead to a successful functional outcome in the ankle joint. However, several complications of the TAR procedure may be often caused by an incomplete understanding of the abnormal biomechanics of the ankle joint and the prosthesis design of the TAR. This study was performed to suggest a novel approach to determine the TAR prosthesis size by using an orthopedic digital templating software based on a comparison between X-ray and CT images. This study was examined in a novel approach to determine the prosthesis size by using an orthopedic digital templating software (Orthoview™, Florida, USA) based on the comparison between X-ray and CT images. A total 6 types of clinical foot and ankle images were obtained from x-ray and CT of 55 subjects in the coronal and sagittal plane. The x-ray images magnified as 100% and 115% based on the CT images. All subjects were diagnosed to the ankle osteoarthritis with stage 2-4 according to Takakura’s ankle OA classification. To predict the appropriate component sizes of the TAR prosthesis, the same TAR prosthesis (HINTEGRA, Newdeal, France) was chosen, and the tibial and the the talar component sizes were selected until by adapting to the osteotomized range of the tibia and talus. The unskilled surgeons predicted the sizes of the TAR components before procedure by using the orthopedic digital templating software. These predicted sizes were then compared with the selected sizes by the specialist surgeon during the procedure. The Cohen’s Kappa correlation coefficient was applied to statistically analyze the agreement between the predicted and selected sizes of the TAR components for unskilled and specialist surgeons, respectively. On the CT images, the average agreement rate was relatively higher than on the x-ray images at over 77%. Especially, highest agreement rate was shown at the tibial component in the coronal plane with almost 80%, followed by over 75% in the sagittal plane. In the talar part, the agreement rate was shown to be over 76% in the coronal and sagittal plane, respectively. Overall, the predicted size from the CT image was more consistent with the size selected by the specialist surgeon than the X-ray image. In conclusion, the application of the orthopedic digital templating software based on CT images may expect to provide more complete and detailed visualization to predict the appropriate size of the TAR components than conventional X-ray images which would be limited by relatively lower sensitivity and specificity as well as overlapping the adjacent bones.

PMID:41028141 | DOI:10.1038/s41598-025-13004-4

Sci Rep. 2025 Sep 30;15(1):33984. doi: 10.1038/s41598-025-12134-z.

ABSTRACT

Healthcare governance is essential for ensuring quality service delivery, accountability, and transparency within health systems. However, challenges such as resource limitations, political interference, and inexperienced management hinder effective governance in many regions, including the South Wollo Zone of Northeast Ethiopia. Therefore, this study assessed the healthcare governance practices and their determinants among public hospital managers in South Wollo Zone, Northeast Ethiopia, in 2024. A facility-based cross-sectional study using a mixed-method approach was conducted. Quantitative data were collected from 182 randomly selected hospital managers using simple random sampling. For the qualitative component, purposive sampling was employed to select 10 key informants for in-depth interviews. In this study, good governance was defined as the ability of hospital managers to uphold accountability, transparency, participation, responsiveness, and rule of law in their managerial roles, based on principles adapted from the World Health Organization’s (WHO) health system governance framework. The WHO framework and the UNDP governance principles were used as reference frameworks to guide measurement and analysis of good governance among healthcare managers. For the quantitative analysis, good governance was treated as a single dependent variable, classified dichotomously as good governance or poor governance based on a predefined scoring system. Variables with a p-value < 0.2 in the bivariable logistic regression were considered candidates for multivariable logistic regression, and those with a p-value < 0.05 were considered statistically significant. Quantitative analysis revealed that only 41.20% of the managers demonstrated good healthcare governance practices. Key factors significantly associated with good governance included having governance-related training, access to structured feedback systems, opportunities for peer learning, and freedom from political interference. The qualitative findings supported these results, emphasizing the role of training, feedback, collaboration, and managerial autonomy in strengthening governance practices. To improve governance in public hospitals, strengthening managerial training programs, establishing regular feedback mechanisms, promoting peer-learning opportunities, and minimizing political interference are recommended.

PMID:41028140 | DOI:10.1038/s41598-025-12134-z

Sci Rep. 2025 Sep 30;15(1):34103. doi: 10.1038/s41598-025-19820-y.

ABSTRACT

Soil saturated hydraulic conductivity (Ks) is a critical parameter for modeling water and solute transport in soils. Conventional laboratory measurements of Ks are labor-intensive, costly, and susceptible to measurement errors, underscoring the need for more reliable estimation techniques. This study systematically compares the performance of Ordinary Kriging (OK), Ordinary Co-Kriging (OCK), and Response Surface Methodology (RSM) for Ks estimation, thereby integrating geostatistical and statistical optimization frameworks. Soil samples were collected from 135 locations within the surface layer (0-30 cm), and Ks along with key soil physicochemical properties were determined. In the geostatistical domain, OK based on a spherical semivariogram (R² = 0.81; nugget/sill = 10.19%) yielded moderate predictive ability (R² = 0.70, RMSE = 3.62 mm day^-1, MAE = 10.02 mm day^-1), whereas OCK employing an exponential cross-semivariogram (R² = 0.91; nugget/sill = 0.45%) substantially improved accuracy (R² = 0.85, RMSE = 3.21 mm day^-1, MAE = 9.43 mm day^-1). By contrast, RSM achieved the highest predictive performance, with a quadratic model producing R² = 0.94 and Adeq Precision = 49.2. Optimization within the experimental range indicated a maximum Ks of 137.18 mm day^-1 at 8.9% clay and 86% sand. Collectively, these findings demonstrate that while OK and OCK provide valuable insights into the spatial dependence of Ks, RSM offers superior predictive accuracy and practical applicability for optimizing soil hydraulic functions in water resources and agricultural management.

PMID:41028130 | DOI:10.1038/s41598-025-19820-y

Sci Rep. 2025 Sep 30;15(1):34077. doi: 10.1038/s41598-025-14375-4.

ABSTRACT

Sustainable construction materials are one of the major solutions to combat climate change and reduce its impact on the global economy. This research study aimed to optimise the quaternary blend of cement, fly ash, pumice and rice husk ash using factorial experiments and elastic modulus tests, followed by their empirical modelling. Keeping the quantities of fly ash and rice husk ash per unit volume of concrete constant, it was observed that the compressive strength decreased with the increase in quantity of pumice per unit volume of concrete due to its lower specific surface area. Similarly, the highest value of elastic modulus was observed for the sample containing 10% fly ash, 15% rice husk ash, and 5% pumice, as it was approximately 14.2% and 13.9% higher than the control group at 28 days and 120 days, respectively. Novel equations for estimating elastic modulus and flexural strength as a function of compressive strength were developed and found to be statistically reliable. Lastly, in comparison to Random Forest model, the Extreme Gradient Boosting model successfully predicted the compressive strength of quaternary blended concrete as evident from its higher R² values of 0.999 and 0.921 and lower RMSE values of 0.419 and 4.96 during the training and testing phases, respectively, and the results were confirmed using the paired t-test.

PMID:41028118 | DOI:10.1038/s41598-025-14375-4

Sci Rep. 2025 Sep 30;15(1):33972. doi: 10.1038/s41598-025-11076-w.

ABSTRACT

This study investigated the effectiveness of a resistance and aerobic training model among 71 middle-aged participants aged 30-60 (mean age 44.27 ± 8.67 years; mean BMI 27.94 ± 3.92 kg/m²) with obesity, comprising 36 males and 35 females (male/female ratio ≈ 1.03:1). Participants were categorized into four groups based on their self-reported training regimens: dietary-only (Group C), aerobic fat oxidation (Group F), high-intensity interval training (Group H), and resistance training (Group R). Subjects followed their specialized routines through online and offline sources for at least 12 weeks. Groups F, H, and R demonstrated statistically lower body weight as well as waist-to-hip ratio and body fat percent levels, when assessed against Group C (P < 0.01). The combination of resistance training with specific benefits produced larger reductions in waist-to-hip ratio, together with android fat mass, primarily observed among male participants (P < 0.01). The participants in Group H demonstrated the greatest decrease in body fat percentage among female subjects (P < 0.01), even though Group R participants achieved beneficial results, although their adherence level was less than ideal. Participants from all experimental groups maintained similar levels of muscle mass. The hybrid online and offline approach effectively enhanced adherence and engagement, demonstrating its scalability and potential for managing obesity.

PMID:41028117 | DOI:10.1038/s41598-025-11076-w

Sci Rep. 2025 Sep 30;15(1):33923. doi: 10.1038/s41598-025-08813-6.

ABSTRACT

The current manuscript deals with the analytical study of the generalized Benjamin-Ono (BO) equation. The underlying model has numerous applications in scientific fields like wave propagation effect and study of the plasma dynamics and complicated modeling of physical systems. The Jacobi elliptic function (JEF) expansion method is employed for employed for the solitary wave and soliton solutions for the underlying model. This technique provides dark, bright and dark periodic solitary wave solutions. Different solutions are chosen to draw their physical behavior. 2D, 3D and their corresponding contours are drawn and their physical behavior is explained in the context of real-life application. The stability analysis, chaotic behavior, sensitivity and bifurcation analysis is derived to analyze its various dynamics and simulations are plotted for various choices of the parameters. These results will create an impact in the existing literature.

PMID:41028092 | DOI:10.1038/s41598-025-08813-6

Sci Rep. 2025 Sep 30;15(1):34027. doi: 10.1038/s41598-025-12847-1.

ABSTRACT

The COVID-19 pandemic has caused over 7 million deaths worldwide, with age, underlying conditions, and immunosuppression increasing the incidence of severe outcomes. Despite vaccination, immunocompromised (IC) individuals show lower vaccine response, probably leading to more breakthrough infections. The objective of our study was to evaluate the overall occurrence of intensive care admission and/or death during hospitalisation, stratified by COVID-19 severity and immunological status (IC vs. non-IC individuals). Our study used a nationwide database to compare COVID-19 hospitalisations and outcomes in IC versus non-immunocompromised individuals (non-IC). This is a longitudinal cohort study analysed de-identified COVID-19 data from Brazil’s DATASUS system (02 March 2020-31 December 2023). The study included 361,898 subjects, identifying 7484 (2.07%) IC individuals. IC individuals showed higher rates of chronic liver, neurological, and lung diseases, while non-IC individuals had higher obesity rates. Intensive care unit (ICU) admissions (42.6% vs. 38.5%) and mortality (51.1% vs. 35.9%) were greater in IC compared to non-IC individuals. Therefore, IC individuals consistently experienced more ICU admissions and higher mortality across the COVID-19 pandemic years (odds ratios rising from 1.68 in 2020 to 2.39 in 2023), influenced by the prevalence of SARS-Cov-2 variants. Our study shows higher morbidity and mortality in IC individuals during the COVID-19 pandemic, underscoring the need for targeted strategies like early interventions, reinforcing the need for sustained surveillance, targeted vaccination strategies, and prioritised care.

PMID:41028085 | DOI:10.1038/s41598-025-12847-1

Sci Rep. 2025 Sep 30;15(1):33928. doi: 10.1038/s41598-025-09801-6.

ABSTRACT

Cycling safety at intersections is a growing concern as both cycling activity and motor vehicle traffic continue to rise. Intersections pose heightened risks for cyclists due to complex traffic patterns, ambiguous right-of-way rules, and insufficient signaling, often leading to collisions. This study investigates how intersection control types and operational characteristics influence driver failure-to-yield behavior toward cyclists. Using ten years of Michigan crash data involving single motor vehicle-cyclist collisions, we apply a Mixed Logit Model to account for unobserved heterogeneity in driver behavior. The analysis focuses on three types of intersection control: traffic signals, stop/yield signs, and uncontrolled intersections, examining their impact on various driver-cyclist interaction scenarios. Key findings indicate that driver age, day of the week, vehicle type, and speed limit consistently affect yielding behavior across all control types. Impairment due to alcohol or drugs significantly increases the likelihood of hazardous driver actions. Drivers are more prone to fail to yield in straight-ahead scenarios, though they are less likely to be deemed at fault in non-yield crashes. Intersection control effectiveness also varies by maneuver type; signalized intersections reduce failure rates in straight-travel scenarios, while stop/yield signs are more effective during left turns. This research addresses a critical gap by linking infrastructure features with driver yielding performance, offering evidence-based insights for improving intersection safety. The findings support targeted interventions in roadway design, driver education, and the integration of advanced technologies such as cyclist detection systems and vehicle-to-vehicle communication to enhance cyclist protection.

PMID:41028078 | DOI:10.1038/s41598-025-09801-6

Sci Rep. 2025 Sep 30;15(1):34101. doi: 10.1038/s41598-025-19539-w.

ABSTRACT

The prediction and management of water quality are critical to ensure Sustainable water resources, particularly in regions like Odisha, where rivers face increasing pollution from industrialization, agriculture, and urban expansion. The Brahmani River, located in the Odisha State, is the 2nd largest watershed in the province, by which its water quality is affected by natural and anthropogenic changes. In this research, water samples were gathered throughout the monsoon season for four years (2020-2024) from previously selected 7 sampling stations. Geographical Information System (GIS) techniques were used to find out the distribution of surface water quality on land use pattern. A particular focus is given to hybrid models that integrate multiple approaches to improve predictive accuracy and robustness. Therefore, the study was undertaken by incorporating Weighted Arithmetic (WA) Water Quality Index (WQI), Synthetic Pollution Index (SPI), Nemerow Pollution Index (NPI), Overall Index of Pollution (OIP), multivariate statistical method, namely Factor Analysis (FA) or Principal Component Analysis (PCA), and Multi-Criteria Decision-Making (MCDM) approaches like Evaluation based on Distance from Average Solution (EDAS). The goal of this investigation is to evaluate the water’s purity and whether it is Suitable for consumption. Fifteen physicochemical parameters were tested from 7 observation stations. Referring to the present research, the obtained order of anionic abundance was SO₄^2- > Cl^– > NO₃^– >F^– > PO₄^3–. However, the order of cationic abundance was Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. The calculated WA-WQI values ranged between 49 and 72. Toxic heavy metals, nutrients, and microorganisms were the major pollutants influencing water quality, as stated by WA-WQI. In addition, the data was interpreted using pollution indices such as SPI (0.31-0.68), NPI (6-29.91), and OIP (0.45-4.40). By results, it is concluded that mainly 4 sites are unsuitable for drinking and irrigation purposes, due to long-term use of waste water, anthropogenic activities, over-extraction of Surface water and changes in land use pattern. Using the multivariate technique, the PCA method was useful to identify two latent pollution sources, that correctly assign 89% of the total variance in the dataset. During the first component, the major loadings on parameters: TDS, EC, alkalinity, Na⁺, Ca²⁺, Mg²⁺, K⁺, F^–, Cl^–, NO₃^–, and SO₄^2–. It indicates that locations were primarily Harmed by oxygen-consuming organic and Hazardous contamination. Furthermore, the EDAS score fluctuated between 0.01 and 0.97. The results revealed that Y-(1) mentioned high polluted water, followed by Y-(2) and Y-(7). This signifies the existence of dissolving biological material; nitrogen was the major pollutant, originating primarily from anthropogenic local contamination. Later on, the outcomes of water quality parameters on the different indexing methods were evaluated, and the obtained outcomes indicate that the highest mean effective weight value belongs to the TDS, EC, Cl^–, SO₄^2- and PO₄^3–, respectively. Notably, effective control of point source pollution and upper river ecological restoration should be done to improve the water quality and protect the reservoir. This research identifies key research gaps and proposes future directions for developing transparent, adaptive, and accurate models. The findings can also guide researchers and policymakers towards the development of smart water quality management systems that enhance decision-making and ecological sustainability.

PMID:41028073 | DOI:10.1038/s41598-025-19539-w

Sci Rep. 2025 Sep 30;15(1):33896. doi: 10.1038/s41598-025-08809-2.

ABSTRACT

This study investigates the efficacy of Astaxanthin and Quercetin as potential therapeutic agents for mitigating chloramphenicol-induced liver toxicity. Despite chloramphenicol’s broad-spectrum antibiotic properties, its clinical utility is hampered by hepatotoxic side effects. This research assesses the impact of chloramphenicol-induced mitochondrial toxicity, reactive oxygen species (ROS) production, and gene expression alterations in HepG2 liver cells. To enhance mitochondrial sensitivity, cells were cultured in galactose-containing media and exposed to chloramphenicol (up to 3000 µmol/L) for 48 h, with or without Astaxanthin (5-15 µM) or Quercetin (10-30 µM). Untreated and DMSO vehicle controls were included. Mitochondrial toxicity was evaluated using ATP content, ROS levels (ROS-Glo™ assay), and gene expression profiling. Expression of five mitochondrial-related genes SOD2, UCP2, NRF1, SURF1, and TFAM were analyzed due to their roles in oxidative stress, membrane potential regulation, biogenesis, and respiratory complex assembly. Antioxidant treatments resulted in significant reductions in ROS levels (p < 0.005) and restoration of mitochondrial gene expression patterns (p < 0.05, n = 3), alongside improved ATP retention. IC50 values and statistical comparisons were derived using GraphPad Prism with one-way ANOVA and appropriate post hoc tests. These findings suggest that Astaxanthin and Quercetin confer mitochondrial protection through modulation of oxidative stress and gene expression.

PMID:41028070 | DOI:10.1038/s41598-025-08809-2