Category: Nevin Manimala

Foot Ankle Orthop. 2025 Sep 28;10(3):24730114251371722. doi: 10.1177/24730114251371722. eCollection 2025 Jul.

ABSTRACT

BACKGROUND: Ankle arthroscopy (AA) is a commonly used operative technique to diagnose and treat a variety of intraarticular pathologies of the ankle joint. In AA, 2 portals are commonly established to achieve visualization of the joint: the anteromedial (AM) and anterolateral (AL) portals. However, the superficial peroneal nerve (SPN) runs near the anterolateral portal site; thus, creation of the AL portal is associated with neuropraxic injuries to the SPN.When AA is combined with additional procedures, such as a Brostrom-Gould ligament repair or open reduction internal fixation (ORIF), the use of a direct lateral incision is required. We present a novel approach to combining AA with lateral adjunct procedures which avoids creation of the AL portal; the AM portal and lateral incision are used for instrumentation instead. The primary objective of this study is to compare complication rates, such as SPN injury, between the lateral incision (LI) approach and conventional arthroscopy plus a lateral incision approach.

METHODS: Following IRB approval, a retrospective chart review was conducted spanning a time frame from January 2020 to October 2024. Patients were included if they underwent AA plus either a Brostrom-Gould repair or ORIF (AA+) or if they underwent AA plus adjunct procedures using the lateral portal instrumentation method (LI). Ninety-four patients were initially identified; 2 were excluded per criteria. Demographic information, intraoperative details, and any postoperative complications or reoperations were recorded. Descriptive statistics were used to describe demographics and operative data, and 2-tailed Student t tests were used to identify statistical differences between group metrics.

RESULTS: Ninety-two patients were included in the study. No statistical differences were observed between cohorts in either of the intraoperative metrics considered (procedural duration and tourniquet duration; P = .44 and .89, respectively). In addition, complication and reoperation rates were not statistically different between the LI and AA+ groups (P = .94 and .40, respectively). The rate of SPN neuropathy or neurapraxia were also compared between groups, resulting in no statistical differences (P = .37).

CONCLUSION: In this retrospective cohort study, we observed no differences when only anteromedial and lateral portals are used for an ankle arthroscopy with adjunct procedures compared with the traditional 3-incision approach. We hypothesize that instances of infection or wound dehiscence would decrease given a large enough cohort because of the creation of 1 fewer portal. However, given the small, underpowered sample, we cannot determine whether the lateral approach alters complication risk; larger multicenter studies are needed.

LEVEL OF EVIDENCE: Level III, retrospective cohort study.

PMID:41031227 | PMC:PMC12477371 | DOI:10.1177/24730114251371722

NPJ Biodivers. 2025 Sep 30;4(1):36. doi: 10.1038/s44185-025-00101-w.

ABSTRACT

The role of intraspecific trait variability (ITV) in trait spaces is still overlooked. We outline the swapping procedure, which detects changes in the main properties of any trait space as a function of ITV. Building on the properties of eigendecomposition analysis, we propose a set of target parameters, statistical tests and related interpretations to stimulate further research on this topic. We also link R functions to perform the swapping procedure.

PMID:41028299 | DOI:10.1038/s44185-025-00101-w

Sci Rep. 2025 Sep 30;15(1):34117. doi: 10.1038/s41598-025-20663-w.

ABSTRACT

The present study investigated the tissue reaction of platelet rich fibrin and chitosan hydrogel as internal matrices in repairing furcal perforations in mature dogs’ teeth. Seventy-two teeth in six mongrel dogs were experimented in this study. After access opening, root canal preparation was completed and obturation was done using gutta percha/resin sealer. Furcation perforations were done, and the experimental teeth were classified according to the perforation repair protocol to three experimental groups and a positive control group (18 teeth each). Group 1: Platelet-rich fibrin matrix with premixed calcium silicate-based bioceramic putty (BC putty), Group 2: Chitosan hydrogel matrix with BC putty, Group 3: BC putty alone and Group 4: a positive control group where no repair material was utilized. Access openings were restored with composite filling. The experimented teeth and the supporting bone were sectioned into blocks and histologically examined for tissue reaction at one and three months. Statistical analysis was performed using Chi-square test, where the significance level was set at P ≤ 0.05. BC putty and BC putty with PRF matrix exhibited less bone loss, epithelial proliferation and inflammatory reaction compared to chitosan hydrogel at one and three months intervals, also they showed more hard tissue deposition compared to chitosan hydrogel at 3-month interval. Although BC putty presented higher sealing ability with great area of newly formed hard tissue compared to chitosan hydrogel, BC putty with PRF can be considered as a successful management option for furcal perforation repair. Management of perforation is considered a challenging procedure especially when located in the furcation area, however histological evaluation of the tissue reaction to different internal matrices materials could provide favorable clinical outcomes concerning the perforation repair procedures.

PMID:41028290 | DOI:10.1038/s41598-025-20663-w

Sci Rep. 2025 Sep 30;15(1):33792. doi: 10.1038/s41598-025-99177-4.

ABSTRACT

Graduates from medical schools are expected to be ready for demanding professional roles. Previous studies have indicated that medical students frequently experience anxiety and depression, which affect their academic and personal lives. This study aims to identify factors associated with anxiety and depression among medical students at universities in Ethiopia. This cross-sectional study was conducted at three Ethiopian medical colleges-Gondar University in northern Ethiopia, Jimma University in southern Ethiopia, and Hawasa University in southern Ethiopia-from November 1, 2023, to March 30, 2024. A total of 450 medical students participated in the survey, which utilized the Beck Depression Inventory, Beck Anxiety Inventory, and Satisfaction with Life Scale. Various demographic, academic, and social factors were analyzed via descriptive statistics, chi-square tests, and logistic regression. The prevalence of depression was 52%, while the prevalence of anxiety was 59.1%. Compared to males, females had higher rates of depression (63.93%) and anxiety (65.02%). Additionally, nonlocal students exhibited greater anxiety levels (68.28%). Living alone, poor peer relationships, and poor academic performance were significantly associated with increased anxiety and depression. Logistic regression revealed significant associations between sex, living arrangements, peer relationships, year of study, academic performance, and life satisfaction and anxiety and depression symptoms. Anxiety and depression are prevalent among medical students and are influenced by various demographic, academic, and social factors. Addressing these issues through targeted interventions, enhanced support services, and curriculum adjustments is crucial for improving the mental health and academic success of medical students.

PMID:41028282 | DOI:10.1038/s41598-025-99177-4

Sci Rep. 2025 Sep 30;15(1):34086. doi: 10.1038/s41598-025-14641-5.

ABSTRACT

The accumulation of mineral deposits on industrial equipment surfaces poses a major concern in a variety of processes. Gypsum (CaSO₄·2H₂O) is one of the most widely produced minerals in both natural and industrial environments. Currently, intelligent white-box models can serve as a suitable alternative to time-consuming and high-priced experiments, enabling the identification of possible gypsum scaling issues in the chemical and petroleum industries. In this regard, the current study focused on the development of robust mathematical correlations to estimate the solubility of gypsum in aqueous electrolyte solutions. For this purpose, three rigorous techniques of Genetic Programming (GP), Gene Expression Programming (GEP), and Group Method of Data Handling (GMDH) were implemented on two distinct data banks, including 2288 experimental data-points taken from previously published literature. Solution temperature (T), solution molecular weight (MW), and molal concentrations of monovalent, divalent, and trivalent compounds (m_I, m_II, and m_III) were the input/independent variables employed in the first data bank, whereas solution temperature (T), solution molecular weight (MW), and solution ionic strength (I) were included in the second data bank. The performance and accuracy of correlations were evaluated using various statistical indicators such as Mean Bias Error (MBE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²). Following multiple statistical and graphical analyses on the novel correlations’ outcomes, it was found that the correlation established by implementing the GMDH technique onto the first data bank (i.e., GMDH-1) performed significantly better than all other correlations, with MAE = 0.01095, RMSE = 0.01482, and R² = 0.8508. The correlations obtained by applying the GEP and GMDH techniques to the second data bank (i.e., GEP-2 and GMDH-2) also revealed a satisfactory level of performance. By comparing the new correlations developed in this study with models reported in previous studies, a reasonable level of agreement was found.

PMID:41028254 | DOI:10.1038/s41598-025-14641-5

Sci Rep. 2025 Sep 30;15(1):34043. doi: 10.1038/s41598-025-14273-9.

ABSTRACT

Accurate estimation of water acidity is essential for characterizing acid mine drainage (AMD) and designing effective remediation strategies. However, conventional approaches, including titration and empirical estimation methods based on iron speciation, often fail to account for site-specific geochemical complexity. This study introduces a high-accuracy, site-specific empirical model for predicting acidity in AMD-impacted waters, developed from field data collected at the Trimpancho mining complex in the Iberian Pyrite Belt (Spain). Using multiple linear regression (MLR), a robust predictive relationship was established based on Cu, Al, Mn, Zn, and pH, achieving a coefficient of determination (R²) of 99.2%. The model significantly outperforms the standard Hedin method, with a lower mean absolute percentage error (13% vs. 29%). Results also reveal strong spatial and seasonal hydrochemical variability, underscoring the limitations of generalized acidity models in such environments. This work demonstrates the applicability of site-calibrated multivariate models as practical tools for enhancing acidity prediction in complex AMD systems.

PMID:41028253 | DOI:10.1038/s41598-025-14273-9

Sci Rep. 2025 Sep 30;15(1):33791. doi: 10.1038/s41598-025-97562-7.

ABSTRACT

Mango is a fruit of great economic importance in India. India is the top mango-producing nation in the world, accounting for over half of global mango output. In order to determine the production capability of the insured orchards, a complete inventory is carried out in situ every three years. The inventory includes counting number of trees, grouping them into yield categories, and assessing damaged ones. Satellite Remote Sensing proves to be a vital tool for estimating ecological parameters such as population density, tree health, volume, biomass, and carbon sequestration rates. The significance of tree counting extends beyond orchard evaluations, playing a vital role in environmental protection, agricultural planning, and crop yield forecast. unfortunately, conventional tree counting methods often require very expensive feature engineering, which leads to more errors as well as lower overall optimization. In order to overcome these obstacles, deep learning-based methods have been used to count trees, exhibiting cutting-edge results in this crucial activity. This paper introduces a novel approach employing deep learning for Image-Based Mango Tree counting in high-resolution satellite imagery data. The proposed model, named Bi-directional Feature Pyramid Network (BiFPN)-YOLOv8m an improved version of YOLOv8, employs object detection to effectively separate, locate, and count mango trees with in orchards. A dataset of 1700 training and 300 testing images of mango orchards with trees of various ages is used to evaluate the various YOLOv8 variants, YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x, including YOLOv9, YOLOv10, and BiFPN-YOLOv8m, with a focus on computational efficiency, accuracy, and speed. Experimental findings show that, even under difficult circumstances, the proposed method continuously outperforms state-of-the-art techniques.

PMID:41028215 | DOI:10.1038/s41598-025-97562-7

Sci Rep. 2025 Sep 30;15(1):34069. doi: 10.1038/s41598-025-14204-8.

ABSTRACT

Improving the machinability of nickel-based superalloys remains a significant challenge in modern manufacturing, particularly for aerospace and high-performance engineering applications. Excessive friction and elevated temperatures during machining often result in rapid tool wear and reduced efficiency. This study investigates the potential of eco-friendly hybrid nanofluids-engineered by combining nanoparticles with complementary thermal and lubricating characteristics-as a sustainable solution to enhance machining performance. Specifically, the performance of three hybrid nanofluid combinations-hexagonal boron nitride/graphite (hBN/Gr), hBN/molybdenum disulfide (MoS₂), and Gr/MoS₂-was evaluated during the milling of Inconel 601 under varied cutting speeds (30-60 m/min) and feed rates (0.05-0.15 mm/rev). Key machining responses such as cutting force, surface roughness, tool wear, temperature, and tool life were analyzed. Among the tested combinations, the hBN/Gr nanofluid demonstrated superior performance, achieving reductions in cutting force (4.17%), surface roughness (21.05%), cutting temperature (8.57%), and tool wear (19.25%), along with an 11.17% improvement in tool life compared to Gr/MoS₂. These enhancements are attributed to the fluid’s optimal viscosity and exceptional tribological behavior at the tool-chip interface. The study offers a novel, environmentally responsible approach to machining Inconel 601, emphasizing the promising role of hybrid nanofluids-particularly hBN/Gr-as next-generation lubricants in sustainable manufacturing.

PMID:41028203 | DOI:10.1038/s41598-025-14204-8

Sci Rep. 2025 Sep 30;15(1):34095. doi: 10.1038/s41598-025-14696-4.

ABSTRACT

The low-frequency variability of the mid-latitude atmosphere involves complex nonlinear and chaotic dynamical processes posing predictability challenges. It is characterized by sporadically recurring, often long-lived patterns of atmospheric circulation of hemispheric scale known as weather regimes. The evolution of these circulation regimes in addition to their link to large-scale teleconnections can help to extend the limits of atmospheric predictability. They also play a key role in sub- and inter-seasonal weather forecasting. Their identification and modeling remains an issue, however, due to their intricacy, including a clear conceptual picture. In recent years, the concept of metastability has been developed to explain regimes formation. This suggests an interpretation of circulation regimes as communities of states in the neighborhood of which the atmospheric system remains abnormally longer than typical baroclinic timescales. Here we develop a new and effective method to identify such communities by constructing and analyzing an operator of the system’s evolution via hidden Markov model (HMM). The method makes use of graph theory and is based on probabilistic approach to partition the HMM transition matrix into weakly interacting blocks – communities of hidden states – associated with regimes. The approach involves nonlinear kernel principal component mapping to consistently embed the system state space for HMM building. Application to northern winter hemisphere using geopotential heights from reanalysis yields four persistent and recurrent circulation regimes. Statistical and dynamical characteristics of these circulation regimes and surface impacts are discussed. In particular, unexpected high correlations are obtained with EL-Niño Southern Oscillation and Pacific decadal oscillation with lead times of up to one year.

PMID:41028162 | DOI:10.1038/s41598-025-14696-4

Sci Rep. 2025 Sep 30;15(1):34061. doi: 10.1038/s41598-025-14465-3.

ABSTRACT

This cross-sectional study aimed to investigate the correlation between the neutrophil-lymphocyte ratio (NLR) and all-cause mortality and cardiovascular mortality in osteoarthritis (OA) patients. We involved 3549 adults with OA from the National Health and Nutrition Examination Survey (NHANES) database (1999-2018). The optimal NLR threshold (2.53) was determined using maximally selected rank statistics. Kaplan-Meier (KM), weighted Cox regression, and restricted cubic spline (RCS) analyses were employed to assess the relationship between the NLR and mortality outcomes, with subgroup and sensitivity analyses evaluating the stability of the observed associations. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to evaluate the NLR prognostic accuracy for mortality across time points. During the 91-month median follow-up period, 843 patients died (256 from cardiovascular disease). Elevated NLR (≥ 2.53) was associated with increased risks of all-cause mortality (HR = 1.82) and cardiovascular mortality (HR = 2.50). Nonlinear correlations of the NLR with mortality outcomes were observed. ROC analysis demonstrated superior NLR predictive capability for all-cause and cardiovascular mortality compared to individual blood cell types. Elevated NLR is independently associated with increased risks of all-cause mortality and cardiovascular mortality in OA patients.

PMID:41028161 | DOI:10.1038/s41598-025-14465-3