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Shallow lakes are an important natural source of atmospheric methane (CH 4), and the input of autochthonous organic matter (OM) into their sediments encourages methanogenesis. Although algal- and macrophytic-originated OM in these lakes are expected to have different impacts on methanogenesis and methanogenic archaeal communities in lake sediments owing to their various properties, their specific influence and role in sediment remain unclear. In this study, a 148-day incubation was carried out by adding algal- and macrophytic-OM to the sediments of shallow eutrophic Lake Chaohu and Lake Taihu in China. CH 4 was periodically monitored, while the methanogens were examined via qPCR and high-throughput sequencing at the end of incubation. Algal-OM stimulated CH 4 production more than macrophytic-OM in both sediments, with the rates initially increasing and then decreasing before reaching a relative constant. Macrophytic-OM promoted CH 4 production to a comparable extent in both lakes, while algal-OM promoted greater CH 4 in Lake Chaohu than in Lake Taihu. However, algal-OM did not significantly increase mcrA gene copies, while macrophytic-OM did by 17.0–20.1-fold. Algal-OM potentially promoted the methylotrophic pathway in Lake Taihu but did not change the methanogenic structure in Lake Chaohu. Comparatively, macrophytic-OM promoted CH 4 production mainly by acetoclastic methanogen proliferation in both lakes. More CH 4 release with algal-OM compared to macrophytic-OM deserves further attention owing to the prevailing increasing algal blooms and the declining macrophyte population in lakes. [Display omitted] • Algal-OM and macrophytic-OM promoted methanogenesis in sediments. • Algal-OM promoted more methane than macrophytic-OM in sediments. • Algal-OM did not significantly increase mcr A gene copies but macrophytic-OM did. • Algal-OM increased the methylotrophic archaea in sediment from Lake Taihu. • Macrophytic-OM stimulated acetoclastic methanogen proliferation in both lakes. [ABSTRACT FROM AUTHOR]

Introduction: The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China., Methods: EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs., Results: The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2 th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6 th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90 th percentile, 41.90°C) and extreme high temperature (99 th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs., Conclusion: High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yin, Jingesi, Yin, Chen, Huang, Cheng, Li, Liu, Wang, Yin and Jiang.)

Cold spells have been associated with specific diseases. However, there is insufficient scientific evidence on the effects of cold spells on out-of-hospital cardiac arrest (OHCA). Data on OHCA cases and on meteorological factors and air pollutants were collected between 2013 and 2020. We adopted a quasi-Poisson generalized additive model with a distributed lag nonlinear model (DLNM) to estimate the effect of cold spells on daily OHCA incidence. Backward attributable risk within the DLNM framework was calculated to quantify the disease burden. We compared the effects and OHCA burden of cold spells using nine definitions. The risks of different cold spells on OHCA increased at higher intensities and longer durations. Based on Akaike's information criterion for the quasi-Poisson regression model and the attributable risk, the optimal cold spell was defined as a period in the cold month when the daily mean temperature was below the 10th percentile of the temperature distribution in the study period for at least 2 days. The single-day effect of the optimal cold spell on OHCA occurred immediately and lasted for approximately 1 week. The maximum single-day effect was 1.052 (95% CI: 1.018-1.087) at lag0, while the maximum cumulative effect was 1.433 (95% CI:1.148-1.788) after a 14-day lag. Men were more susceptible to cold spells. Young and middle-aged people were affected by cold spells similar to the elderly. Cold spells can increase the risk of OHCA with an approximately 1-week lag effect. Health regulators should take more targeted measures to protect susceptible populations during cold weather., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Composite temperature-related indices have been utilized to comprehensively reflect the impact of multiple meteorological factors on health. We aimed to evaluate the predictive ability of temperature-related indices, choose the best predictor of stroke morbidity, and explore the association between them., Methods: We built distributed lag nonlinear models to estimate the associations between temperature-related indices and stroke morbidity and then applied two types of cross-validation (CV) methods to choose the best predictor. The effects of this index on overall stroke, intracerebral hemorrhage (ICH), and ischemic stroke (IS) morbidity were explored and we explained how this index worked using heatmaps. Stratified analyses were conducted to identify vulnerable populations., Results: Among 12 temperature-related indices, the alternative temperature-humidity index (THIa) had the best overall performance in terms of root mean square error when combining the results from two CVs. With the median value of THIa (25.70 °C) as the reference, the relative risks (RRs) of low THIa (10th percentile) reached a maximum at lag 0-10, with RRs of 1.20 (95%CI:1.10-1.31), 1.49 (95%CI:1.29-1.73) and 1.12 (95%CI:1.03-1.23) for total stroke, ICH and IS, respectively. According to the THIa formula, we matched the effects of THIa on stroke under various combinations of temperature and relative humidity. We found that, although the low temperature (<20 °C) had the greatest adverse effect, the modification effect of humidity on it was not evident. In contrast, lower humidity could reverse the protective effect of temperature into a harmful effect at the moderate-high temperature (24 °C-27 °C). Stratification analyses showed that the female was more vulnerable to low THIa in IS., Conclusions: THIa is the best temperature-related predictor of stroke morbidity. In addition to the most dangerous cold weather, the government should pay more attention to days with moderate-high temperature and low humidity, which have been overlooked in the past., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)