Tag: nevin manimala

Sci Rep. 2025 Jul 28;15(1):27481. doi: 10.1038/s41598-025-12723-y.

ABSTRACT

The deep-sea comprises diverse habitats and species whose characterisation provides crucial insights into the health and resilience of our oceans. Whereas direct sampling enables investigation of the vertical variability of the seafloor at small spatial scales, optical imaging allows for multi-scale assessment of the spatial distribution of (mega)benthos and substrates. However, modern seafloor imaging surveys typically generate thousands of images that are infeasible to manual annotation. Consequently, transforming these terabyte-scale datasets into actionable insights requires automated workflows. Here, we deployed two A.I workflows to automate the annotation of substrates and megafaunal taxa in seafloor images from the tropical North Atlantic. Clustering, feature space visualisation and multivariate statistical analysis techniques were used to classify the seafloor into habitats, estimate megafaunal distribution patterns, and to identify environmental drivers that influence observed patterns. We found that the seabed here formed seven clearly distinct clusters, with visible sub-partitions observed in each cluster. Investigations revealed a gradient of sediment disturbance due to biogenic activity, with images showing little-to-no sediment disturbance mapping to one half of the feature space, whereas images exhibiting visibly vigorous sediment reworking mapping to the other half of the feature space. Also, megafaunal abundances were 14 times higher in the shallower Eastern region of the seabed, potentially due to higher Particulate Organic Carbon flux and relatively warmer temperatures. Moreover, geographic clustering of megafauna was observed in topographically complex features such as slopes of submarine canyons and on top of seamounts, where heterogeneity created diverse microhabitats and unique niches that megafauna could exploit.

PMID:40721850 | DOI:10.1038/s41598-025-12723-y

Sci Rep. 2025 Jul 28;15(1):27432. doi: 10.1038/s41598-025-13177-y.

ABSTRACT

Multi-level trend analysis of extreme climate variables is an efficient method for in-depth investigation of the climate change impacts on ecohydrology. However, most of existing statistical methods do not reveal potential trends in different levels of data. In this study, a new approach namely Fuzzy Innovative Trend Analysis (FITA) was introduced that takes the advantages of fuzzy logic to improve and facilitate Innovative Trend Analysis (ITA) abilities to multilevel trend detection at Extreme Climate Indices (ECIs). Regarding the graphical nature of the proposed method, two new indices, namely Grow Percent (GP) and Total Grow Percent (TGP) were suggested for quantifying the power of trend at distinct levels. The FITA was utilized for trend detection at three levels of four important ECIs related to precipitation and temperature. To this end, long-term (1960-2021) daily temperature and precipitation observations at six meteorology stations across diverse climatic zones of Iran were used. The multilevel trends attained by the FITA were further compared to those of ITA, Mann-Kendall (M-K), and Sen’s slope (SS) tests. The results indicated that the FITA provides promising results with higher interpretability and reliability than its counterparts at all stations. The underlying high-resolution trends detected at certain stations also pointed out that the M-K and SS tests may yield in misleading interpretations when they are used for identifying trends in ECIs.

PMID:40721846 | DOI:10.1038/s41598-025-13177-y

Adv Rheumatol. 2025 Jul 28;65(1):34. doi: 10.1186/s42358-025-00468-1.

ABSTRACT

INTRODUCTION: Systemic sclerosis (SSc) often leads to decreased muscle strength and mass, impairing physical performance and causing disability. Interventions with resistance exercise (RE) is an effective non-pharmacological approach to mitigate these issues. This systematic review aims to evaluate the effects of interventions with RE on muscle strength, muscle mass, physical performance, physical disability, and quality of life (QOL) in SSc patients, as well as to assess its adherence and safety.

METHODS: A systematic review and meta-analysis were conducted based on a PICOS framework: Patient = Systemic Sclerosis; Intervention = Resistance exercise; Study design = Randomized clinical trials. Searches were performed across MEDLINE (PubMed), PMC, Web of Science, Cochrane Library, LILACS, and EMBASE up to January 2025.

RESULTS: Ten randomized clinical trials, including 422 participants (~85% female), were eligible for analysis. Participants’ ages ranged from 42 to 64 years, with body mass indices between 22.5 and 28.0 kg/m². The intervention period was standardized to 12 weeks. Interventions with RE significantly improved muscle strength (SMD = 2.76 kg; 95% CI, 1.32 to 4.20; p = 0.0002) and functional disability (SMD = -0.47; 95% CI, -0.93 to -0.00; p = 0.05) compared to controls. Interventions with RE also showed superiority in the physical component of QOL (SMD = 0.42; 95% CI, 0.04 to 0.81; p = 0.03). Although enhanced physical performance was observed, statistical pooling was not possible due to limited data. Interventions with RE had a low incidence of adverse events, but data on disease progression and adherence were insufficient.

CONCLUSION: Interventions with RE benefits muscle strength, physical function, and QOL in SSc patients, though optimal protocols and adherence strategies need further investigation. More robust studies are required to refine training methods and enhance clinical trial designs.

PMID:40721843 | DOI:10.1186/s42358-025-00468-1

BMC Psychol. 2025 Jul 28;13(1):841. doi: 10.1186/s40359-025-03204-y.

ABSTRACT

BACKGROUND: Body dysmorphic disorder (BDD) is a prevalent concern among adolescent girls. Childhood experiences of security or insecurity are recognized as significant foundational factors influencing body image and, consequently, the development of BDD. Adolescents with a history of childhood trauma may face an elevated risk of developing psychiatric conditions, including obsessive-compulsive disorder and BDD. This study, therefore, aimed to predict BDD symptoms based on childhood trauma, with self-compassion acting as a mediating factor. This framework integrates principles from cognitive-behavioral theory and attachment theory. Specifically, cognitive distortions stemming from cognitive-behavioral patterns, coupled with diminished self-esteem and self-worth as conceptualized by attachment theory, are believed to contribute to lower self-compassion, subsequently leading to a higher incidence of BDD symptoms.

METHODS: A cross-sectional design employing structural equation modeling (SEM) was utilized to construct an optimal model for BDD symptoms, where the mediating role of self-compassion was tested in the relationship between childhood trauma and BDD symptoms. The study population comprised female students aged 16 to 22 in the cities of Meybod and Ardakan during the 2023-2024 academic year. A non-random convenience sample of 300 participants was selected. Data were collected using the Childhood Trauma Questionnaire (CTQ), the Yale-Brown Obsessive Compulsive Scale-Modified for BDD (BDD-YBOCS), and the Self-Compassion Scale (SCS). Statistical analyses, including Pearson’s correlation coefficient and stepwise multiple regression, were performed using SPSS-26 software. SEM analyses were conducted using AMOS-24 software.

RESULTS: The study’s results indicated several significant relationships among the variables. Childhood trauma was found to have a significant negative direct effect on self-compassion (β=-0.704, p < 0.001), suggesting that higher levels of trauma are associated with lower self-compassion and vice versa. Conversely, childhood trauma exhibited a significant positive direct effect on BDD symptoms (β = 0.321, p < 0.001), indicating that increased trauma predicts more severe BDD symptoms. Furthermore, self-compassion demonstrated a considerable negative direct impact on BDD symptoms (β=-0.765, p < 0.001), implying that low self-compassion is linked to increased BDD symptomatology and vice versa. Crucially, the Sobel test statistic of 3.216 (exceeding the critical value of 1.96) confirmed that self-compassion significantly mediated the relationship between childhood trauma and BDD symptoms (β = 0.538, p < 0.001). This mediation model suggests that self-compassion plays a vital role in explaining how childhood trauma contributes to the development of BDD symptoms.

CONCLUSION: The finding demonstrates a robust model fit, confirming self-compassion’s mediating role in the association between childhood trauma and BDD symptoms. Consequently, interventions aimed at enhancing self-compassion, such as group education programs and therapeutic approaches grounded in self-compassion therapy delivered in established treatment centers, could effectively mitigate the impact of childhood trauma. Such interventions are anticipated to lead to a reduction in BDD symptomatology, particularly by decreasing cognitive distortions related to body image and fostering greater self-acceptance.

PMID:40721837 | DOI:10.1186/s40359-025-03204-y

Neurol Res Pract. 2025 Jul 28;7(1):53. doi: 10.1186/s42466-025-00409-9.

ABSTRACT

BACKGROUND: In Germany, multidisciplinary care for people with Parkinson’s disease (PwP, PD) is mainly provided in the inpatient setting. Differences in user groups between established and effective interventions like PD Multimodal Complex Therapy (PD-MCT) and Geriatric Complex Therapy (GCT) have not been investigated.

METHODS: This real-world bicenter prospective observational study involved PwP undergoing 14-day inpatient multidisciplinary therapies at two German university hospitals providing either PD-MCT or GCT. Demographic and clinical variables were recorded before and device-based gait variables before and after therapy. Non-parametric and parametric tests including ANCOVA with age as covariate were conducted to compare groups at baseline, and an exploratory binomial logistic regression (LR) to identify predictors of ‘therapy response’ concerning gait speed.

RESULTS: Between 09/2017 and 09/2022, 100 (41% female) and 102 (34.3% female) PwP received GCT or PD-MCT, with significant (p < 0.003) mean or median differences (GCT vs. PD-MCT) in age (74.7 vs. 65.6 years), disease duration (9.9 vs. 7.4 years), and HY stage (3 vs. 2.5). The GCT group showed significantly reduced lower extremity (SPPB), global cognitive (MoCA) and executive function (TMT), lower quality of life, and higher fear of falling (FES-I). There were significant (p < 0.004) between-group differences in gait parameters at both normal and fast pace, e.g., reduced gait speed and step length among GCT users. After age-adjustment, differences in gait speed, fast-pace step length, lower extremity and executive function, fear of falling and quality of life persisted. The exploratory LR model was statistically significant (p < 0.05, R² = 0.312) and revealed lower fear of falling and gait speed as predictors of ‘therapy response’, independent of therapy type, age, sex, disease duration or stage.

CONCLUSION: GCT users show higher age and severity, particularly concerning mobility impairments independent of age. It is unclear if, on a national level, actual PD-MCT/GCT user groups align with intended target groups. Health insurance data analyses could help refine clinical recommendations and public health policies for more targeted multidisciplinary PD care.

TRIAL REGISTRATION: Park Move Study: DRKS, DRKS00020948. Registered 30 March 2020-retrospectively registered, https://drks.de/search/de/trial/DRKS00020948/details.

PMID:40721836 | DOI:10.1186/s42466-025-00409-9

BMC Psychol. 2025 Jul 28;13(1):844. doi: 10.1186/s40359-025-03210-0.

ABSTRACT

BACKGROUND: Sleep problems faced by college students have become an important global health issue that requires immediate attention. This study investigates the relationship between dysfunctional beliefs and attitudes about sleep (DBAS) and sleep quality among college students, with a focus on examining the mediating effects of anxiety, stress, and depression in this relationship.

METHODS: A cross-sectional design was employed, with data collected through a survey conducted from January to March 2024 among Chinese university students. The survey evaluated DBAS, anxiety, depression, stress, and sleep quality. Descriptive statistics and correlation analysis were performed using SPSS 27.0, subsequently applying PROCESS models (Model 4 and Model 6) to develop parallel and chain mediation models.

RESULTS: A total of 864 valid responses were retained, comprising 629 male participants (72.8%) and 235 female participants (27.2%), with ages ranging from 16 to 23 years (M = 18.8, SD = 1.0). The findings demonstrated that DBAS negatively predicted sleep quality (B = – 0.15, 95% CI [- 0.20, – 0.09]). Anxiety (B = – 0.03, 95% CI [- 0.06, – 0.01]) and stress (B = – 0.05, 95% CI [- 0.08, – 0.02]) performed as parallel mediators in the association between DBAS and sleep quality. Furthermore, DBAS influenced sleep quality indirectly through the chain mediation of anxiety and stress (β = -0.04, 95% CI [- 0.07, – 0.02]).

CONCLUSIONS: DBAS has a direct negative impact on sleep quality and affects it indirectly through the parallel mediation of anxiety and stress. Additionally, DBAS may indirectly influence sleep quality through the chain-mediating effects of anxiety and stress. The study highlights the significance of addressing DBAS, as it directly affects students’ emotional well-being and sleep quality. Future research should concentrate on creating targeted interventions to reduce DBAS, thus enhancing emotional health and sleep quality in university students.

PMID:40721835 | DOI:10.1186/s40359-025-03210-0

BMC Sports Sci Med Rehabil. 2025 Jul 28;17(1):217. doi: 10.1186/s13102-025-01262-8.

ABSTRACT

OBJECTIVE: This study aimed to examine the injury profile of a professional football team over five consecutive seasons and assess the predictive value of the Functional Movement Screen (FMS), offering insights to optimize injury prevention strategies in professional football.

DESIGN: Injury data for 169 players between the 2016-2017 and 2020-2021 seasons were recorded, including the number of missed training sessions, injury severity, and injury types. Descriptive statistics were used to analyze these factors. The relationship between preseason FMS composite scores, asymmetry findings, and injury profiles was assessed using Variance Inflation Factor (VIF) and Logistic Regression Analysis.

RESULTS: Over the five seasons, the injury incidence was 7.76 injuries per 1,000 training hours (95% CI: 7.59-7.93), 15.47 injuries per 1,000 match hours (95% CI: 15.23-15.71), and 8.9 injuries per 1,000 combined hours (95% CI: 8.72- 9.0). Injury data, including severity, type, and training or match absence, were meticulously recorded and analyzed. The study established an injury profile for players over five consecutive seasons but found that FMS was ineffective in predicting injuries, either within individual seasons or across the entire period. This suggests that the FMS may not be a reliable tool for forecasting injury risk in high-performance football.

CONCLUSION: The injury frequency was 8.9 per 1,000 h of exposure, with 26% of injuries classified as severe, leading to over 28 missed training days per injury. Given that the FMS test battery alone did not reliably predict injury risk, we recommend its use in combination with other multifactorial screening methods to enhance the accuracy of injury risk assessment. Hamstring injuries were the most common, while goalkeepers primarily experienced back issues. Factors such as age, height, and body mass may influence injury risk. These findings underscore the need for multifaceted injury prevention programs that consider a wider range of risk factors beyond FMS scores, including age, height, and body mass, to effectively manage and reduce the risk of injuries in professional football. Additionally, these insights can assist technical staff in managing training absences and planning player availability more effectively.

PMID:40721830 | DOI:10.1186/s13102-025-01262-8

BMC Pharmacol Toxicol. 2025 Jul 28;26(1):138. doi: 10.1186/s40360-025-00973-5.

ABSTRACT

Although considered safe and widely used, some natural remedies are responsible for health ailments to their users that deserve to be investigated. SAYE PLUS is one of the most widely used traditional recipes as antimalaria for decades and recently against Covid-19 in Burkina Faso and beyond, and is commonly regarded as safe to use. In the present study, sub-chronic toxicity tests were performed orally in Wistar rats at daily doses of 250, 500, and 1000 mg/kg for 90 days, following the guidelines of the Organization for Economic Cooperation and Development (OECD). The results revealed neither symptoms of toxicity nor mortality. Depending on the dose, time frame, or animal sex, compared with the control, SAYE PLUS powder caused a statistically significant reduction in the water and food consumption of the treated rats. Significantly increases in serum creatinine, total protein, hydrogen phosphate ion (PO₄²), and potassium ion (K⁺) levels were detected in females at all doses. Compared to control values, the male rats’ glucose decreased while its PO₄^2- increased significantly at the daily dose of 1000 mg/kg of SAYE PLUS. Histopathological analysis revealed that the rat heart, lungs, liver, kidneys, and spleen histostructure were unaffected by sub-chronic exposure to SAYE PLUS up to 1000 mg/kg/d. The Findings provide some scientific information on the toxicological profile of the phytomedicine SAYE PLUS when administered in repeated doses for 90 days. However, they are limited by the absence of analysis of the animals’ hematological parameters. Nevertheless, results show that for patient safety, it is not advisable to use SAYE PLUS for more than two consecutive weeks. Furthermore, herbal remedies need careful evaluation before or during their human use, especially when a new form of use other than the traditional one is proposed. Further long-term studies focusing on the hematological parameters and certain kidney and liver functional indicators will add the scientific merit and interest of the present work.

PMID:40721828 | DOI:10.1186/s40360-025-00973-5

J Eat Disord. 2025 Jul 28;13(1):156. doi: 10.1186/s40337-025-01259-1.

ABSTRACT

BACKGROUND: Nomothetic (i.e., on average) eating disorder interventions generally provide insufficient guidance for managing suicidality. The present proof-of-concept study demonstrates how idiographic network models can be used to inform a modular, highly personalized approach to treatment for individuals experiencing suicidality in the context of Anorexia Nervosa spectrum disorders (ANSD).

METHODS: Using 21 days of ecological momentary assessment data (105 assessment points), contemporaneous and temporal idiographic symptom networks were generated for three patients with unique clinical presentations of ANSD. For each patient, we identify the most central symptoms in their network, as well as potentially important bridge symptoms linking eating pathology and suicidality. We then provide guidelines for using this information to guide the delivery of evidence-based intervention strategies.

RESULTS: Intervention strategies may vary substantially depending upon which network statistics are used to guide treatment target selection. Bridge symptoms, or symptoms that serve as links between eating pathology and suicidality, may represent particularly promising intervention targets for individuals experiencing these conditions concurrently. Interventions which target the symptoms with the highest strength centrality may also yield symptom improvement throughout the entire network.

CONCLUSIONS: Although the viability of network-informed, personalized treatment is contingent upon continued intervention development research, this approach has the potential to improve treatment outcomes for individuals with co-occurring eating disorders and suicidality.

PMID:40721825 | DOI:10.1186/s40337-025-01259-1

Sci Rep. 2025 Jul 28;15(1):27389. doi: 10.1038/s41598-025-12746-5.

ABSTRACT

This study examines long-term air temperature trends in Bhubaneswar, a rapidly urbanizing coastal city in eastern India, using data from 1901 to 2023. By analyzing maximum, minimum, and mean temperatures, we assess both natural climate variability and anthropogenic influences, including urban expansion. Statistical techniques such as homogenization, persistence analysis, and low-pass filtering reveal a pronounced warming trend, particularly in minimum temperatures, as an indication of an intensifying urban heat island effect. A weak but positive correlation between minimum temperature and population growth supports the role of urbanization in shaping local climate. These findings contribute to understanding urban climate evolution in tropical coastal settings where natural and human factors interact. Our results underscore minimum temperatures compared to maximum temperatures, indicating a warming trend likely driven by anthropogenic activities. Regression analysis between population growth and minimum temperature affirms a weak but notable positive correlation, indicating the gradual intensification of Bhubaneswar’s local microclimate due to urban development. This study contributes to understanding climate dynamics in tropical, coastal, and urban regions, where natural and human factors converge, shaping distinct local climate patterns. Nonetheless, the climatic trends are less pronounced than the interannual fluctuations in temperature measurements. The little climatic differences across several generations are unlikely to have influenced human activities compared to the substantial impacts of interannual temperature variability.

PMID:40721820 | DOI:10.1038/s41598-025-12746-5