Tag: nevin manimala

Syst Rev. 2025 Dec 12. doi: 10.1186/s13643-025-03015-7. Online ahead of print.

ABSTRACT

BACKGROUND: Sarcopenia is a clinical syndrome characterized by a significant reduction in muscle mass and strength, typically associated with the ageing process. In recent years, an increasing number of studies have shown that sarcopenia not only affects functional health in the elderly but may also be closely associated with the onset of cardiovascular diseases, particularly atrial fibrillation. However, the association between sarcopenia and atrial fibrillation has not yet been adequately systematically evaluated. Therefore, this study aims to investigate the relationship between sarcopenia and atrial fibrillation through a systematic review and meta-analysis.

METHODS: The study will adhere to the PRISMA-P guidelines to ensure a transparent and rigorous methodology and will conduct a comprehensive literature search using databases PubMed, Embase, the Cochrane Library, and Web of Science, with the search period spanning from the establishment of the databases to 15 May 2025. Included will be clinical observational studies that meet the criteria, including prospective cohort studies, and case-control studies. The included studies must explicitly assess the association between sarcopenia and the occurrence of atrial fibrillation. We will assess the risk of bias of all included studies using the Newcastle-Ottawa Scale (NOS) and the AHRQ quality assessment tool. The data for this study will be analyzed using Stata 15. We will employ random-effects models for statistical analysis, along with subgroup analysis, to further explore the potential influence of factors such as age, gender, and disease status on the results.

DISCUSSION: The primary objective of this study is to assess the impact of sarcopenia on atrial fibrillation and to analyze their potential association. This study is expected to reveal the potential association between sarcopenia and atrial fibrillation and provide evidence-based support for clinical prevention and treatment. The study results will help promote early identification and intervention for sarcopenia, thereby reducing the risk of atrial fibrillation and improving health outcomes for the elderly population.

SYSTEMATIC REVIEW REGISTRATION: Prospero CRD420251054023.

PMID:41388557 | DOI:10.1186/s13643-025-03015-7

Vet Res. 2025 Dec 12. doi: 10.1186/s13567-025-01686-7. Online ahead of print.

ABSTRACT

Goats represent a significant reservoir for tuberculosis (TB) in animals, contributing notably to public and animal health challenges, causing economic repercussions. Ante mortem diagnosis of TB is hindered by the limited sensitivity of available techniques and false-positive results from other mycobacterial infections, such as paratuberculosis (PTB). Nuclear Magnetic Resonance (NMR)-based metabolomics provides unique fingerprinting of the disease’s metabolic status, making it a promising diagnostic tool. However, conventional high-resolution NMR has limitations in veterinary practice, where high costs and large equipment size are major constraints. Benchtop NMR spectrometer is proposed as a compact, cost-effective alternative for livestock farms. The study aimed to evaluate NMR-based metabolomics as a diagnostic tool and transfer it from high-resolution to benchtop NMR spectrometers in an animal setting. Serum samples from TB-infected, PTB-infected (n = 16), and healthy control goats (HC) were analyzed by both high-resolution and benchtop NMR spectroscopy. Multivariate statistical analysis successfully differentiated groups on the basis of their metabolic profiles with both spectrometers. We identified that betaine, glucose, glycerol, and lactate are significantly capable of distinguishing between the three groups. Additionally, 3-hydroxybutyrate, creatine, glutamate, leucine, lysine, phenylalanine, threonine, and tyrosine further differentiate TB from HC. Acetate, creatine, glutamate, isoleucine, leucine, and lysine distinguish TB from PTB, while 3-hydroxybutyrate and phenylalanine serve to differentiate PTB from HC. Analyses with both high-resolution and benchtop spectrometers demonstrated high sensitivity and accuracy and reliable metabolite identification. These findings highlight NMR’s spectroscopy potential to identify biomarkers associated with TB and PTB infection, improving health management in livestock.

PMID:41388555 | DOI:10.1186/s13567-025-01686-7

BMC Med Ethics. 2025 Dec 13. doi: 10.1186/s12910-025-01344-9. Online ahead of print.

ABSTRACT

BACKGROUND: Lately, the misconduct in research among scientist has been escalating. The use of artificial intelligence has been converted in a double ace card, on one side it has simplificated the way of obtaining valious data for researchers in an easy way, but in the other hand, has promoted that researchers became careless about the scientific method. This situation has become a problem among university teachers since the students are tempt to obtain results in an easy way, leaving ethics aside. The objective of the study was to determine the knowledge and practices regarding scientific integrity among university students in Peru.

METHODS: A descriptive cross-sectional quantitative study was conducted, applying a validated survey on knowledge and practices regarding scientific integrity to 1,420 university students in the Southern Region of Peru, with 60.85% being women. The questionnaire consisted of 21 questions, and data were analysed using descriptive and inferential statistics. Robust statistics were applied, and comparisons were made based on gender, age, and region. Ages ranged from 17 to 29 years (M = 21.14, SD = 2.72).

RESULTS: The majority demonstrated high levels of knowledge and regular levels of practices regarding scientific integrity. Statistically significant differences were found based on gender (women > men), age (older than 23 years > younger than 22 years), and region. Inappropriate practices were identified in the use of artificial intelligence in academic work.

CONCLUSIONS: It was concluded that university students have high levels of knowledge regarding scientific integrity; however, they exhibit regular and low levels of application in research projects.

PMID:41388540 | DOI:10.1186/s12910-025-01344-9

Endocr Regul. 2025 Dec 12;59(1):217-226. doi: 10.2478/enr-2025-0025. Print 2025 Jan 1.

ABSTRACT

Objective. Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes mellitus (T2DM) that substantially impairs quality of life. This study aimed to assess the relationship between metabolic parameters and DPN severity in T2DM patients. Methods. A prospective observational study was conducted at PSG Institute of Medical Sciences and Research (Peelamedu, Coimbatore, India) from August 2023 to August 2024, enrolling 90 adults with T2DM on oral hypoglycemic agents after ethical approval and informed consent. Blood samples were analyzed for fasting glucose, HbA1c, lipid profile, and plasma insulin. The LDL/HDL ratio and HOMA-IR were calculated to evaluate metabolic status. DPN severity was measured using a biothesiometer. Results. The higher HbA1c levels significantly correlated with increased neuropathy severity (severe: 12.1±1.3% vs. mild: 8.4±2.0%; p=0.002). LDL/HDL ratio was elevated in patients with severe DPN (3.6±1.8) compared to mild DPN cases (2.5±1.0), but this difference was not significant (p=0.12). Severe DPN cases also showed higher HOMA-IR (10.2±2.8) suggesting a possible link to insulin resistance though not statistically significant (p=0.23). Conclusion. HbA1c strongly associates with DPN severity, while LDL/HDL ratio and HOMAIR showed no significant correlation. Further research is needed to clarify these metabolic relationships and their clinical relevance.

PMID:41388536 | DOI:10.2478/enr-2025-0025

Sci Rep. 2025 Dec 12. doi: 10.1038/s41598-025-31174-z. Online ahead of print.

ABSTRACT

Control charts are widely used in manufacturing and quality management to monitor process variability. Although easy to implement, the Shewhart control chart lacks sensitivity to small process shifts. The exponentially weighted moving average (EWMA) control chart is effective in detecting minor shifts, but responds slowly to sudden changes. To enhance the detection capability, this study adopts the adaptive EWMA (AEWMA) control chart, which features dynamic adjustment mechanisms to improve the monitoring performance. This is applicable for skewed process data, particularly those following a Gamma distribution such as lifetime data, waiting times, and current stability indicators in semiconductor manufacturing. The Wilson-Hilferty transformation was applied to approximate the normality before constructing the AEWMA control chart. Monte Carlo simulations were employed to design and evaluate both the fixed sampling interval (FSI) and variable sampling interval (VSI) schemes under various combinations of shapes, scale parameters, and smoothing constants. To address the limitations of the traditional average run length (ARL) in reflecting the differences in sampling schemes, this study also adopted the average time-to-signal (ATS) as a performance metric. The simulation results demonstrated that the AEWMA VSI chart outperformed both the AEWMA FSI and EWMA charts in terms of sensitivity and stability when detecting small process shifts.

PMID:41388064 | DOI:10.1038/s41598-025-31174-z

Sci Rep. 2025 Dec 12. doi: 10.1038/s41598-025-29755-z. Online ahead of print.

ABSTRACT

Earthquake early warning systems (EEWS) aim to warn end-users of impending ground shaking. They can be most impactful in large earthquakes occurring close to large population centers, where exposure to strong ground shaking is extensive. However, such earthquakes are rare, and EEWS performance expectations remain uncertain. The February 2023 Kahramanmaraş, Türkiye sequence, including the M7.8 Pazarcık and M7.5 Elbistan events, exposed millions to strong ground shaking and produced a rich waveform dataset, offering a test case. We use this data to produce a realistic simulation of warning times. We use the EPIC point source algorithm for real-time earthquake characterization, and incorporate alert delivery latency using a statistical model driven by real-world alert delivery data from California, collected by the MyShake smartphone app. We show EPIC would produce solutions very quickly (4 s for Pazarcık, 10 s for Elbistan). Despite EPIC’s expected magnitude underestimation (peak M6.7 for Pazarcık, M7.2 for Elbistan), we show that its magnitude estimate grows large quickly enough to provide areas of MMI 6+ shaking with up to 20 s of warning time, even with alert delivery latencies included, provided that low alerting thresholds of MMI 3 or 4 are used.

PMID:41388057 | DOI:10.1038/s41598-025-29755-z

Sci Rep. 2025 Dec 12;15(1):43713. doi: 10.1038/s41598-025-27466-z.

ABSTRACT

The use of a plough is characterized by the presence of a turning moment acting in a clockwise direction. When placing the plough resistance center to the left of the tractor’s longitudinal symmetry axis, it becomes possible to use the plough with one landside placed on its last bottom. The article presents a new analytical dependence that allows determining the design and technological parameters of the plow using the transverse displacement of the center of resistance to the left of the tractor’s longitudinal axis of symmetry. Studies have shown that using a plough with one landside instead of five does not affect the ploughing depth and the operating width. At the statistical significance level of 0.05, the null hypothesis about the equality of the mean values and variances of these parameters’ oscillations is not rejected. The normalized correlation functions and spectral densities of these processes’ oscillations are approximately the same. Using a plough with one landside instead of five leads to a 10.3% decrease in draft resistance, accompanied by a 10% decrease in specific fuel consumption. This study fills a gap in the practical operation of plows, aimed at reducing their draft resistance, which is key in reducing fuel consumption.

PMID:41388049 | DOI:10.1038/s41598-025-27466-z

Sci Rep. 2025 Dec 12. doi: 10.1038/s41598-025-31610-0. Online ahead of print.

ABSTRACT

This study presents a multi-temporal geospatial modeling approach to identify and map land degradation and desertification hotspots in the aeolian-dominated semi-arid regions of Bommanahal, Beluguppa, and Kanekal Mandals of Anantapur District, Andhra Pradesh, India. Landsat 4-5 TM (1990), Landsat 7 ETM+ (2000, 2010), and Landsat 8 OLI/TIRS (2020) datasets were processed through a standardized workflow comprising radiometric calibration, atmospheric correction, LST retrieval, and spectral index computation. Three diagnostic indices: Normalized Difference Vegetation Index (NDVI), Topsoil Grain Size Index (TGSI), and Normalized Difference Salinity Index (NDSI), were integrated with Land Surface Temperature (LST) to quantify vegetation stress, soil texture variability, and salinity conditions. Correlation and regression analyses were employed to evaluate the relationships between LST and index-derived DN values, after which stratified sample extraction and buffer-based zonal statistics were used to delineate surface degradation intensity. A composite hotspot map was generated using mask extraction and cell statistics to merge the most degraded pixel clusters, identifying approximately 192 km² as severe degradation zones. Model performance was validated using ROC-AUC analysis, yielding an accuracy of 0.851. The study demonstrates a reproducible GIS workflow for semi-arid degradation assessment and provides a robust spatial framework for targeted land restoration, sustainable resource planning, and long-term environmental management in vulnerable dryland ecosystems.

PMID:41388010 | DOI:10.1038/s41598-025-31610-0

J Clin Periodontol. 2025 Dec 12. doi: 10.1111/jcpe.70075. Online ahead of print.

ABSTRACT

AIM: Effective prevention of periodontitis requires addressing multiple modifiable health behaviours (MHBs). This study aimed to examine how MHBs interact and to identify the key behaviours that could serve as targets for intervention.

MATERIALS AND METHODS: We analysed data from a large, population-based survey using questionnaires conducted in China during 2021-2023. Logistic regression was used to examine associations between self-reported periodontitis and multiple MHBs. Network analysis was applied to assess interrelationships among MHBs and identify central MHBs.

RESULTS: Among 85,483 participants, 12.8% reported periodontitis. Ten MHBs were associated with self-reported periodontitis. Ever smoking, ever drinking, unhealthy bedtime, frequent consumption of sugar-sweetened snacks and beverages, insufficient vegetable or fruit intake and toothbrushing less than twice daily were linked to higher prevalence, while insufficient physical activity, no daily flossing and absence of annual dental checkups were linked to lower prevalence. Network analysis identified ever smoking, ever drinking, toothbrushing frequency and dental checkups as the most central behaviours, with variations observed across different subgroups.

CONCLUSION: This study identified key MHBs and revealed differences in central behaviours across subgroups. Ever smoking, ever drinking, toothbrushing frequency and annual dental checkups may represent priority targets for tailored prevention strategies. Future research is warranted to inform integrated interventions.

PMID:41387986 | DOI:10.1111/jcpe.70075

J Oral Rehabil. 2025 Dec 12. doi: 10.1111/joor.70136. Online ahead of print.

ABSTRACT

OBJECTIVE: To compare clinical examination findings, functional limitations, and psychological profiles between patients with subclinical temporomandibular disorders (TMD) and those with self-reported painful TMD.

MATERIALS AND METHODS: This cross-sectional study investigated 98 subclinical TMD patients and 262 self-reported painful TMD patients attending a specialised orofacial pain clinic. Subclinical TMD was defined as positive palpation findings without muscle or joint pain complaints. Self-reported painful TMD required both pain complaints and positive clinical findings. Validated questionnaires assessed jaw functional limitations (JFLS-20), depression (PHQ-9), stress (SPST-20), and oral behaviours (OBC). Statistical analysis used Mann-Whitney U tests and chi-square tests with Bonferroni correction.

RESULTS: Self-reported painful TMD patients were significantly older (median age 39 vs. 31 years, p = 0.003), showed greater jaw functional limitations (JFLS global score: 1.88 vs. 0.75, p < 0.001), and higher depression scores (PHQ-9: 1.0 vs. 0.0, p < 0.001). Sleep bruxism frequency differed significantly between groups (p < 0.001), with subclinical patients more commonly reporting frequent sleep bruxism. No significant differences were found in stress levels, overall oral behaviours, or daytime clenching frequency.

CONCLUSIONS: Patients with self-reported painful TMD demonstrate distinct clinical profiles characterised by greater functional impairment and psychological distress compared to subclinical cases.

CLINICAL RELEVANCE: These findings suggest different phenotypes within the TMD spectrum that may require tailored clinical approaches. Longitudinal studies are needed to determine whether subclinical TMD represents an early stage or a distinct entity.

PMID:41387980 | DOI:10.1111/joor.70136