Tag: pubmed

Sci Rep. 2025 Jul 20;15(1):26327. doi: 10.1038/s41598-025-12163-8.

ABSTRACT

Snow water equivalent (SWE) is a critical variable for understanding water availability and snowmelt-driven streamflow in mountainous regions. Yet, its spatial and temporal estimation is constrained by scarce in situ measurements and the inherent challenges of deriving SWE directly from satellite observations. Thus, accurate SWE assessment is essential for predicting the spatial distribution of snowpack and its temporal contributions to downstream outflow, particularly in semi-arid snow-fed basins like Morocco’s High Atlas regions. In this study, we simulate the local and spatial distribution of SWE and outflow at 500 m using Snow17 model, ERA5-Land and satellite-derived fractional Snow Cover Area (fSCA) from Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2000-2022. The reanalysis data was downscaled and bias corrected using machine learning models (e.g. random forest). To validate results, we compared simulated snow cover area (fSCA) (transformed from SWE simulation) with fSCA issued from MODIS. The methodology was tested in the Rheraya sub-basin (Tensift basin) and applied in Ait Ouchene and Tillouguite sub-basins (Oum Er Rbia basin) in Morocco’s High Atlas Mountains. Statistical analysis shows strong model performance, with Nash-Sutcliffe Efficiency (NSE) values exceeding 0.84 for snow depth (SD) simulations. Moreover, spatio-temporal analysis revealed that SWE and snow depth are significantly higher above 2,500 m elevation, with SWE exceeding 300 mm and SD surpassing 60 cm in Tillouguite and Rheraya sub-basins. Findings also demonstrated that snowmelt contributions to outflow varied significantly with elevation, accounting for 40-46% of annual outflow above 2,500 m and playing a dominant role during spring (55-57% of seasonal outflow). Our research provides a framework for enhancing SWE/outflow estimation and understanding snowpack dynamics in semi-arid mountainous regions, highlighting the vital role of high-altitude snowpacks in water resource sustainability and management under climate change.

PMID:40685453 | DOI:10.1038/s41598-025-12163-8

Sci Rep. 2025 Jul 20;15(1):26322. doi: 10.1038/s41598-025-11610-w.

ABSTRACT

Investigation of antibiotic use in the pediatric population is crucial, in particular in the hospital setting. Measures of antibiotic consumption, such as Duration-Of-Therapy (DOT) and Length-Of-Therapy (LOT) are recommended as indicators of use in pediatrics. This study is aimed to estimate DOT and LOT in hospitalized children using data from electronic medical records (EMRs). We included all patients hospitalized in a tertiary care children’s hospital in Italy, from January to December 2022. Measures DOT and LOT were derived from data recorded in patient EMRs. DOT/1000 patient-days was estimated by patient characteristics, antibiotic molecule prescribed and type of inpatient ward. The time trend of antimicrobial consumption in hospitalized children was also estimated. At least one antibiotic was prescribed in 8,518 out of 21,787 children (39.1%). Overall, DOT and LOT/1000 patient-days were 539 and 354, with a DOT/LOT ratio of 1.5. The molecule with the highest DOT/1000 patient-days was piperacillin/tazobactam followed by meropenem (81.3 and 59.6 DOT/1000 patient-days). Oncohematology and Intensive Care Units were the type of wards with highest DOT/1000 patient-days (1112 and 944, respectively) and LOT/1000 patient-days (591 and 547, respectively). EMRs enhances data accessibility to measure antibiotic use in hospitalized children and their integration into pediatric antibiotic stewardship programs.

PMID:40685445 | DOI:10.1038/s41598-025-11610-w

Odontology. 2025 Jul 20. doi: 10.1007/s10266-025-01157-7. Online ahead of print.

ABSTRACT

Non-coding RNAs (ncRNAs) regulate inflammatory responses and bone resorption in periodontitis. This systematic review and meta-analysis aimed to evaluate the diagnostic value of ncRNA in periodontitis. Studies were selected from PubMed, EMBASE, and Web of Science. Heterogeneity was assessed using the Q test and I² statistic. Diagnostic value was determined by pooled sensitivity, specificity, and area under the curve (AUC) of the summary receiver operating characteristic (SROC). Subgroup analysis was performed to explore heterogeneity sources. Thirteen articles (38 tests, 820 controls, 948 cases) were included. The overall sensitivity of ncRNAs for diagnosing periodontitis was 0.79 (95% CI: 0.73-0.84), specificity was 0.83 (95% CI: 0.78-0.86), and AUC was 0.88 (95% CI: 0.85-0.90), indicating good diagnostic performance. The positive likelihood ratio was 4.53 (95% CI: 3.64-5.65), and the negative likelihood ratio was 0.26 (95% CI: 0.20-0.33), indicating limited clinical applicability of the pooled results. The diagnostic score was 2.88 (95% CI: 2.50-3.26), and the DOR was 17.75 (95% CI: 12.12-26.00), suggesting significant diagnostic accuracy for dysregulated ncRNAs in periodontitis. Dysregulated ncRNAs can distinguish periodontitis from healthy controls, highlighting their potential as diagnostic biomarkers.

PMID:40685444 | DOI:10.1007/s10266-025-01157-7

Sci Rep. 2025 Jul 20;15(1):26317. doi: 10.1038/s41598-025-88745-3.

ABSTRACT

Metaheuristics, which are general-purpose algorithms, are commonly used to solve complex optimization problems. These algorithms manipulate multiple potential solutions to converge on the optimum, balancing the exploration and exploitation phases. A recent algorithm, the Parrot Optimizer (PO), is inspired by the behavior of domestic parrots to improve the diversity of solutions. However, while promising, the PO may encounter difficulties such as convergence to sub-optimal solutions or slow convergence speed. This paper proposes an improvement to the PO algorithm by integrating chaotic maps to solve complex optimization problems. The improved algorithm, called Chaotic Parrot Optimizer (CPO), is characterized by a better ability to avoid local minima and reach globally optimal solutions thanks to a dynamic diversification strategy based on chaotic maps. The effectiveness of the CPO algorithm has been rigorously evaluated through in-depth statistical analysis, using 23 benchmark functions as well as IEEE CEC 2019 and CEC 2020 benchmarks, covering a wide range of optimization challenges. The results show that CPO outperforms not only the original PO algorithm, but also six recent metaheuristics in terms of convergence speed and solution quality. In addition, it has been successfully applied to three complex engineering illustrating its ability to solve real-world, multi-constraint problems. Its integration with Kapur entropy also enabled precise segmentation of medical images, underlining its strong potential for critical biomedical applications. The CPO source code will be available on the Github account: [email protected] after acceptance.

PMID:40685431 | DOI:10.1038/s41598-025-88745-3

Sci Rep. 2025 Jul 20;15(1):26320. doi: 10.1038/s41598-025-12086-4.

ABSTRACT

Plant disease management based on pesticide use has numerous detrimental effects on health and the environment. As a result, the adoption of environment-friendly disease management options is the best alternative to pesticide use. Therefore, the identification of locally available bio-agents like Trichoderma species using morpho-cultural and molecular approaches specifically targeting the internal transcribed spacer (ITS) region, translation elongation factor 1-alpha (TEF 1-α) and RNA polymerase B subunit II (RPB2) is necessary. In this study, we characterized 24 Trichoderma strains isolated from the apple rhizosphere. Significant variations were observed in the morpho-cultural characteristics of Trichoderma isolates and categorized them into four groups (I-IV) that were identified as T. harzianum complex, T. koningiopsis, T. viride, and T. hamatum, comprising 4, 4, 6 and 10 isolates, respectively. The concatenated sequence data set derived from the ITS region, TEF 1-α and RPB2 grouped 24 Trichoderma isolates into 03 independent clades. Specifically, the sequencing based on ITS region grouped them into four sub-clades, which were identified as T. harzianum complex, T. viride, T. asperelloides, and T. koningiopsis, comprising 4, 6, 5 and 7 isolates, respectively, and two independent lineages, each represented by a single isolate. In contrast, sequencing of the TEF 1-α and RPB2 genes grouped 24 Trichoderma isolates into two distinct clades and six sub-clades that were identified as T. asperelloides, T. asperellum, T. hamatum, T. viride, T. koningiopsis and T. harzianum complex, comprising 5, 5, 3, 4, 3 and 4 isolates, respectively. Thus, the final identification of 24 Trichoderma strains was achieved through a combined morpho-cultural and molecular approach, resulting in the identification of six species viz., T. koningiopsis, T. viride, T. asperellum, T. asperelloides, T. hamatum and T. harzianum complex comprising 5, 5, 3, 4, 3 and 4 isolates, respectively in accordance with the reference sequences retrieved from NCBI. Notably, to our knowledge, this is the first report of T. koningiopsis, T. viride, T. asperellum, T. asperelloides, and T. hamatum from the apple rhizosphere.

PMID:40685429 | DOI:10.1038/s41598-025-12086-4

Sci Rep. 2025 Jul 20;15(1):26343. doi: 10.1038/s41598-025-10704-9.

ABSTRACT

To address the problems of centralized attribute authority, inefficient encryption and invalid access control strategy in the data sharing scheme based on attribute-based encryption technology, a smart grid data sharing scheme that supports policy update and traceability is proposed. The smart contract of the blockchain is used to generate the user’s key, which does not require a centralized attribute authority. Combined with attribute-based encryption and symmetric encryption technology, the confidentiality of smart grid data is protected and flexible data access control is achieved. In addition, online/offline encryption and outsourced computing technologies complete most of the computing tasks in the offline stage or cloud server, which greatly reduces the computing burden of data owners and data access users. By introducing the access control policy update mechanism, the data owner can flexibly modify the key ciphertext stored in the cloud server. Finally, the analysis results show that this scheme can protect the privacy of smart grid data, verify the integrity of smart grid data, resist collusion attacks and track the identity of malicious users who leak private keys, and its efficiency is better than similar data sharing schemes.

PMID:40685425 | DOI:10.1038/s41598-025-10704-9

Sci Rep. 2025 Jul 20;15(1):26330. doi: 10.1038/s41598-025-11601-x.

ABSTRACT

The construction sector is proactively working to minimize the environmental impact of cement manufacturing by adopting alternative cementitious substances and cutting carbon emissions tied to concrete. This study investigates the viability of using waste industrial materials as a replacement of cement in concrete mixes. The primary goal is to predict the compressive strength of waste-incorporated concrete by evaluating the effects of materials such as cement, fly ash (FA), silica fume (SF), ground granulated blast furnace slag (GGBFS), metakaolin (MK), water usage, aggregate levels, and superplasticizer dosages. A total of 441 data entries were sourced from various publications. Multiple machine learning techniques, such as light gradient boosting (LGB), extreme gradient boosting (XGB), and decision trees (DT), along with hybrid approaches like XGB-LGB and XGB-DT, were utilized to study how these variables influence compressive strength. The dataset was partitioned into training and testing, and statistical tools were employed to assess the correlation between input variables and strength. Model accuracy was gauged using metrics such as mean absolute percentage error (MAPE), root mean square error (RMSE), and the coefficient of determination (R²). Among the models, the XGB and DT approach delivered the highest precision, with an R² of 0.928 in the training stage. Among hybrid models, XGB-DT exhibited a balanced performance having R² value of 0.907 and 0.785 for training and testing phase. Additionally, SHAP (SHapley Additive exPlanations) and partial dependence plots (PDP) were employed to pinpoint the optimal ranges for each variable’s contribution to the improvement of compressive strength. SHAP and PDP analyses identified coarse aggregate, superplasticizers, water and cement content have high influence on model’s output. Additionally, 150-200 kg/m³ of GGBFS as key factors for optimizing compressive strength. The study concludes that the hybrid models along with the single models, can effectively forecast the compressive strength of concrete incorporating industrial byproducts, assisting the construction industry in efficiently evaluating material properties and understanding the influence of various input factors.

PMID:40685423 | DOI:10.1038/s41598-025-11601-x

Sci Rep. 2025 Jul 20;15(1):26342. doi: 10.1038/s41598-025-11849-3.

ABSTRACT

Mastering the deformation and air leakage patterns of gob-side retained roadway in fully mechanized mining faces, as well as the distribution characteristics of the gas flow field, is of great significance for the comprehensive prevention and control of gas in the goaf. Taking the 20,107 fully mechanized mining face of Qincheng Coal Mine in Shanxi Province as a case study, this paper employs fracture mechanics and plate-beam theory to analyze the impact of the roof fracture position on stress concentration and deformation failure of the roadway wall. It is found that when the fracture line is located outside the wall, the supporting stress can be effectively transferred and pressure can be relieved. Based on this, a calculation method for the critical position of roof-cutting and pressure-relief is proposed. Through field measurements and statistical analysis, the quantitative characteristics of the air leakage flow field and gas concentration distribution in the gob-side retained roadway goaf area were obtained. Consequently, a comprehensive gas prevention and control technology for gob-side retained roadway was proposed, which primarily includes directional drilling with staged hydraulic fracturing for roof cutting and pressure relief, along with enhanced coordinated gas extraction. Additionally, it incorporates auxiliary measures such as silicate composite material spraying for leakage sealing, optimization of ventilation pipe parameters in retained roadway, and airflow regulation for pressure reduction. The proposed approach was validated through field practice. The research results indicate that: (1) The air leakage flow field in the 20,107 goaf is characterized by positive-pressure leakage from the intake airflow of the belt roadway and high-concentration gas accumulation on the retained roadway side, which then enters the return airflow. The positive-pressure air leakage volume in the inclined section of the working face (0-36 m) is 332.84 m³/min, accounting for 58.17% of the total, while the air leakage volume in the retained roadway section (36-108 m along the strike) is 408.45 m³/min, accounting for 87.09%. (2) After optimization, the average pure gas extraction rate of directional drilling boreholes (fracturing and extraction boreholes) in the fractured zone reaches 7.46 m³/min, while the average gas concentration in the gob-side retained roadway gradually decreases from 0.59 to 0.34%. These findings provide a theoretical and practical basis for controlling the deformation of gob-side retained roadway walls, reducing air leakage in the goaf, and improving gas extraction efficiency, thereby guiding the safe and efficient production of fully mechanized mining faces.

PMID:40685412 | DOI:10.1038/s41598-025-11849-3

Sci Rep. 2025 Jul 20;15(1):26331. doi: 10.1038/s41598-025-11701-8.

ABSTRACT

Low urinary flow rates are frequently observed following tubularized incised plate urethroplasty. The underlying cause is not yet fully understood and may be associated with low urethral compliance. The purpose of this study is to non-invasively evaluate the urethral compliance in a rabbit model. Ten male New Zealand rabbits were randomly divided into a control group and a urethroplasty group for tubularized incised plate urethroplasty. Seven weeks post-operatively, ex vivo urethral compliance was evaluated using both the Jesus invasive measurement and the non-invasive method. The Jesus measurement involved measuring urethral volume and pressure by air insufflation, and the non-invasive method utilized ultrasound and uroflowmetry to assess the urethral anterior-posterior diameter and flow data, respectively. Curve regression analysis was applied to calculate urethral compliance. Curve regression analysis revealed that the median urethral compliance measured by non-invasive method in the control group was 0.247 (0.241, 0.257) mm•s/ml, and it was 0.269 (0.263, 0.270) mm•s/ml in the urethroplasty group, with no significant difference between the two groups. The Jesus method indicated median urethral compliance was 0.141 (0.137, 0.149) ml/cmH₂O for the control group and 0.182 (0.173, 0.192) ml/cmH₂O for the urethroplasty group, showing no significant statistical difference. In the rabbit model, urinary flow rate and anterior-posterior diameter serve as non-invasive indicators that can effectively reflect urethral compliance, and TIP surgery has no significant impact on urethral compliance.

PMID:40685409 | DOI:10.1038/s41598-025-11701-8

Sci Rep. 2025 Jul 20;15(1):26340. doi: 10.1038/s41598-025-11194-5.

ABSTRACT

SD Solar drying is increasingly recognized as a sustainable and energy-efficient solution for preserving agricultural products, offering a practical alternative to fossil fuel-dependent methods and traditional open sun drying (OSD). However, its overall performance is highly influenced by environmental variability and system design. This study provides a detailed evaluation of a newly developed direct solar dryer (DDSD) for tomato dehydration, conducted under real and fluctuating climatic conditions in Aswan, Egypt, from February 22 to 27, 2025. During the trial period, solar irradiance ranged widely from 88 to 826 W/m² due to intermittent cloud cover, while ambient temperatures fluctuated between 22 and 34 °C-conditions representative of actual field environments. Tomato samples were prepared in three physical forms-halves, quarters, and 6 mm slices-and subjected to two pretreatment methods (salted and unsalted) to assess their effects on drying kinetics. The DDSD demonstrated significantly better performance than OSD, reducing drying durations by 25-39.6%. The most efficient results were achieved for salted 6 mm slices, which dried in just 9 h-substantially faster than the 29 h for unsalted halves in DDSD and 48 h in OSD. These samples also exhibited the highest effective moisture diffusivity (D_eff) (5.92 × 10⁻⁹ m²/s), reflecting enhanced internal moisture transport. Among 12 drying models evaluated, the Logistic model most accurately described the drying behavior in the DDSD, with an excellent statistical fit (R² = 0.999524, χ² = 6.74 × 10⁻⁵, RMSE = 0.006868). Economically, the DDSD, integrated with a photovoltaic (PV) system, required a modest initial investment of $520 and achieved a payback period of just 1.82 years for salted slices due to faster processing and increased throughput. From an environmental perspective, the system is projected to offset approximately 105.68 metric tons of CO₂ emissions over a 20-year lifespan, with an energy payback time of only 1.10 years and potential revenue of $1321.04 from carbon credits. These findings underscore the DDSD’s potential as a cost-effective, environmentally sustainable, and technically efficient solution for agricultural drying in solar-rich regions.

PMID:40685404 | DOI:10.1038/s41598-025-11194-5