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Abstract Background Depression is a prevalent disorder with significant health impacts. Physical activity is known to protect against depression, but its effects may vary in populations with disrupted sleep patterns, such as weekend catch-up sleepers, which refers to participants who sleep longer on weekends than on weekdays. This study examines the dose-response relationship between physical activity and depression in this population. Methods Data from 1,906 participants in the National Health and Nutrition Examination Survey (2021–2023) were analyzed. Physical activity was measured in MET-minutes per week, and depression was assessed using the PHQ-9. Multivariate linear regression, restricted cubic spline, and two-part linear regression models were employed. Results In the adjusted model, physical activity showed a negative trend with depression, though this association did not reach statistical significance in the fully adjusted model. Stratified analyses revealed stronger associations in women (OR = 0.86, 95% CI: 0.75, 0.99, P = 0.0329) and individuals aged 40–60 years (OR = 0.79, 95% CI: 0.65, 0.97, P = 0.0237). A threshold effect was observed, with physical activity below 2.48 MET-min/1000-wk showing a negative association with depression (OR = 0.69, 95% CI: 0.56, 0.85, P = 0.0006). Beyond this threshold, the relationship changed. Conclusion A nonlinear relationship between physical activity and depression was identified in weekend catch-up sleepers, with moderate activity levels (2.48 MET-min/1000-wk) offering the greatest mental health benefits, particularly in women and individuals aged 40–60 years. Clinical trial number Not applicable. Graphical Abstract

Background We aimed to examine the effect of physical activity (PA) and weekend catch-up sleep (WCS) on depressive symptoms by evaluating their effects on high-sensitivity C-reactive protein (hsCRP) levels.Methods Data were collected from 10,715 adults aged ≥19 years. PA and depressive symptoms were assessed using self-report scales. The WCS was calculated by subtracting self-reported average weekday sleep hours from weekend sleep hours, and serum hsCRP levels were measured using immunoturbidimetric methods. Given that depressive symptoms are characterized by their multifaceted nature, we identified specific symptoms associated with hsCRP levels. Path analysis was used to investigate the association between PA, WCS, hsCRP, and depressive symptoms, and that between PA, WCS, hsCRP, and specific symptoms related to hsCRP.Results Higher levels of PA and WCS were associated with a decreased risk of depressive symptoms through lowering hsCRP levels. Among various depressive symptoms, sleep problems and appetite changes were associated with hsCRP. In pathway analyses using them as dependent variables, higher levels of PA and WCS were also associated with a decreased risk of sleep problems and appetite changes through lowering hsCRP levels.Limitations The current study employed a cross-sectional design, and WCS and PA were based on participants' self-reports rather than objective measurements.Conclusions Increased levels of PA and WCS may help alleviate depressive symptoms, particularly sleep problems and appetite changes, by mitigating chronic inflammation. Therefore, ensuring adequate exercise time and compensating for inadequate weekday sleep during weekends are crucial for maintaining mental well-being.

The high spatial-temporal variability in fishing effort, combined with the difficulty of monitoring individual activities, hampers effective management of recreational fisheries. Angler smartphone applications (apps) offer a promising digital tool for self-reporting of fishing effort (E) and catch per unit of effort (CPUE). However, despite their growing use for data collection in recreational fisheries, the existing literature on their performance remains limited, raising concerns about potential biases in the data. Since 2019, daily trips inside the 12 partially protected Marine Protected Areas (MPAs) of the Balearic Islands (Spain) must be self-reported via the “Diari de Pesca Recreativa” app (the App), recording fishing E and CPUE. This study aimed to evaluate the App’s performance in reporting recreational fisheries data over a six-year period. Data obtained via the App (3672 trip self-reports) were compared to data collected through a standard method (360 on-site creel surveys). Importantly, the App represents complete fishing trips, whereas creel surveys record only partial trips, as they are conducted mid-activity. This methodological difference in trip duration reporting was expected to influence estimates of E (hours · angler · trip) and possibly CPUE (catch · E⁻¹). These estimates were compared across datasets overall, as well as stratified by month, fishing type, MPA, and for key target species. Data from the App tended to overestimate E, while creel surveys underestimated it, and significant differences were observed between whole datasets for E and CPUE. However, when stratified, most groups showed no statistically significant differences in E and CPUE estimates. With these generally comparable results, and given that the limitations of one are offset by the strengths of the other, combining both data sources will improve reliability. The App not only generates a higher volume of trip data but also digitizes data collection through a user-friendly platform for self-reporting, enabling automation and analytics for fisheries monitoring and management of recreational fisheries. Because reporting was mandatory in this case, biases commonly associated with voluntary apps (e.g. avidity, age bias) are unlikely to apply, making this study particularly relevant for assessing the utility of mandatory app-based data in fisheries management.

Background Short sleep has been associated with metabolic syndrome (MetS). Weekend catch-up sleep (WCS) serves as a compensatory strategy for sleep deficits, yet its association with MetS in children and adolescents remains unclear. This study aimed to investigate whether WCS is related to a decreased risk for MetS in sleep-deprived individuals of this population.Methods A total of 8930 participants aged 7–17 years with weekday sleep insufficiency were selected from the China Nutrition and Health Surveillance of Children and Lactating Women (2017). Sleeping hours on weekdays/weekends and WCS duration were calculated based on self-reported weekday/weekend sleep schedules. MetS was defined using Cook's criteria. Logistic regression and restricted cubic spline (RCS) regression models adjusting for covariates were used to assess the relationships between WCS and MetS.Results WCS had a significantly protective association with the prevalence of MetS (p 

Enhancing the efficiency of small pelagic purse-seine fisheries is essential for promoting responsible fisheries management in the Persian Gulf. Therefore, this study forecasts the spatiotemporal catch variations of Sind sardinella (Sardinella sindensis) and Buccaneer anchovy (Encrasicholina punctifer) caught by double-boat purse seiners in the northern Persian Gulf, Qeshm Island. To achieve this, a dataset comprising fishing records from 314 purse seine operations, along with associated environmental parameters obtained from satellite imagery—including sea surface temperature (SST), chlorophyll-a concentration, photosynthetically active radiation (PAR), wind speed, wind direction, depth, and distance—was compiled and analyzed using an advanced machine learning methodology covering the period from September 2014 to October 2023. The evaluation of the regression models used to predict sardine and anchovy catches—including Random Forest (RF), Boosting, and Support Vector Regression (SVR)—revealed varying levels of predictive performance across both species and model types. In the case of sardine, the Boosting Regression model yielded the highest predictive accuracy, characterized by a relatively low error (RMSE = 395.5) and moderate explanatory power (R2 = 0.41). Conversely, for anchovies, the SVR model with a radial basis function (RBF) kernel demonstrated superior performance relative to the other models, with an RMSE of 437 and an R2 of 0.35. The results suggest that anchovy catch prediction was more challenging and potentially influenced by additional unmodeled variables. The CPUE of sardine increases with rising chlorophyll-a concentrations up to approximately 2 mg/m3, but declines beyond this point. The optimal SST range was between 22 °C and 26 °C, whereas sardine catches declined at temperatures exceeding 30 °C. Because anchovy was consistently present across all sampling sets, distance from the shoreline emerged as the most influential parameter contributing to successful net captures. A negative relationship was observed between this factor and anchovy CPUE. As the second most important variable, the optimal SST range for anchovy was similar to that of sardine. Given the substantial fishing effort in the northern Persian Gulf, the findings of this study may help enhance regional fishing strategies by promoting the integration of climate change considerations into operational planning.

Bottom towed gears can have severe and long-lasting effects on sensitive marine habitats and species. Diversification of gear types in fisheries using bottom towed gears to encompass low environmental impact methods, such as static gear, is one way to reduce dependency on damaging fishing methods. Here we report on trials investigating how the use of white Light Emitting Diodes (LEDs; Fishtek Marine PotLights) affect catch rates of northern shrimp (Pandalus borealis; normally caught using trawls) across three different pot designs off the west coast of Scotland. We also caught the valuable Norway lobster (Nephrops norvegicus) and valueless poor cod (Trisopterus minutus) and considered occurrences and catch rates of these species. Illuminated pots resulted in significant increases in catch per unit effort (CPUE; ind. pot−1 24 h−1) of northern shrimp for all pot types up to maximum mean of 4.6 ± 4.5 shrimp pot−1 24 h−1 (illuminated shrimp tubes specifically designed to catch shrimp; range =