Association between physical activity and depression in adult prescription opioid users: A cross-sectional analysis based on NHANES 2007-2018.

OBJECTIVE: This study was designed to examine the association between physical activity (PA) and depression among adult prescription opioid users. METHOD: Data of adults who recently took prescription opioids were collected from NHANES 2007-2018. Participants were divided into two groups according to whether PA in each domain was ≥600 MET-min/week. According to weekly activity frequency, recreational physical activity (RPA) was divided into inactivity, insufficient activity, weekend warrior (WW), and regular activity. PHQ-9 scores ≥10 were identified as depression. RESULTS: RPA of ≥600 MET-min/week was associated with a 40% (OR: 0.60, 95%CI: 0.38-0.96, P = 0.032) reduction in the risk of depression. Restricted Cubic Spline plots found a nonlinear dose-response relationship between RPA and depression (P = 0.045), and the turning point of depression risk was around 600 MET-min/week. There was no significant difference in the risk of depression between the WW and inactivity groups (OR: 0.65, 95%CI: 0.25-1.72, P = 0.382). The regular activity group had an 45% (OR: 0.55, 95%CI: 0.31-0.99, P = 0.046)lower risk for depression than the inactivity group. CONCLUSION: Only regular RPA is associated with a reduced risk of depression, and RPA showed a nonlinear dose-response relationship. The antidepressant effect of the WW is not significant.

Intelligent multicast routing method based on multi-agent deep reinforcement learning in SDWN.

Multicast communication technology is widely applied in wireless environments with a high device density. Traditional wireless network architectures have difficulty flexibly obtaining and maintaining global network state information and cannot quickly respond to network state changes, thus affecting the throughput, delay, and other QoS requirements of existing multicasting solutions. Therefore, this paper proposes a new multicast routing method based on multiagent deep reinforcement learning (MADRL-MR) in a software-defined wireless networking (SDWN) environment. First, SDWN technology is adopted to flexibly configure the network and obtain network state information in the form of traffic matrices representing global network links information, such as link bandwidth, delay, and packet loss rate. Second, the multicast routing problem is divided into multiple subproblems, which are solved through multiagent cooperation. To enable each agent to accurately understand the current network state and the status of multicast tree construction, the state space of each agent is designed based on the traffic and multicast tree status matrices, and the set of AP nodes in the network is used as the action space. A novel single-hop action strategy is designed, along with a reward function based on the four states that may occur during tree construction: progress, invalid, loop, and termination. Finally, a decentralized training approach is combined with transfer learning to enable each agent to quickly adapt to the dynamic changes of network link information and accelerate convergence. Simulation experiments show that MADRL-MR outperforms existing algorithms in terms of throughput, delay, packet loss rate, etc., and can establish more intelligent multicast routes. Code and model are available at https://github.com/GuetYe/MADRL-MR_code.

High level of winter warming aggravates soil carbon, nitrogen loss and changes greenhouse gas emission characteristics in seasonal freeze-thaw farmland soil.

Changes in the soil environment caused by winter warming is affecting the carbon and nitrogen cycles of seasonal freeze-thaw farmland soil. A field experiment was conducted in a seasonal freeze-thaw farmland soil of northeast China to investigate the effects caused from different levels of warming (W1 + 1.77 °C, W2 + 0.69 °C and C + 0 °C) on soil carbon and nitrogen dynamics, microbial biomass and greenhouse gases fluxes. During the early and middle winter, the contents of all kinds of soil carbon and nitrogen (Ammonium, nitrate, total nitrogen, dissolved organic carbon, readily oxidizable organic carbon and soil organic carbon) tended to increase with the increase of warming level, while during the late winter, their contents under different temperature treatments roughly present trend of W2 ≥C > W1. Except for the late thawing period, warming increased the contents of soil microbial biomass carbon and nitrogen, during the late thawing period, with the increase of warming level, MBC and MBN decreased significantly. Warming would stimulate the release of greenhouse gases from soil. But due to the differences of soil environmental conditions in each period and soil nutrient dynamics under different treatments, which made the effects of different levels of warming on soil GHGs fluxes in different periods are different. Our study suggested that low-level warming improved the availability of soil carbon and nitrogen, increased the contents of microbial biomass and greenhouse gas emissions. However, although high-level winter warming showed a similar phenomenon in the early and middle winter to the low-level warming, during the late winter, high-level warming increased soil nutrients loss and broke the seasonal coupling relationship between crop nutrient acquisition and soil microbial nutrient supply, and even led to the adaptation of soil CO2 release to it. This is of great significance for exploring the carbon and nitrogen cycle mechanisms of global terrestrial ecosystem.

Feasibility of an Individualized mHealth Nutrition (iNutrition) Intervention for Post-Discharged Gastric Cancer Patients Following Gastrectomy: A Randomized Controlled Pilot Trial.

(1) Background: A major challenge for post-discharged gastric cancer patients following gastrectomy is the impact of the anatomy change on decreased oral intake, nutritional status, and, ultimately, quality of life. The purpose of this study is to examine the feasibility and preliminary effects of an individualized mHealth nutrition (iNutrition) intervention in post-discharged gastric cancer patients following gastrectomy. (2) Methods: A mixed-method feasibility study with a parallel randomized controlled design was conducted. Patients were randomly assigned to either the iNutrition intervention group (n = 12) or the control group (n = 12). Participants completed measures at baseline (T0), four (T1), and twelve weeks (T2) post-randomization. (3) Results: Recruitment (33%) and retention (87.5%) rates along with high adherence and acceptability supported the feasibility of the iNutrition intervention for post-discharged gastric cancer patients following gastrectomy, echoed by the qualitative findings. The iNutrition intervention significantly improved participants' nutritional behavior (p = 0.005), energy intake (p = 0.038), compliance with energy requirements (p = 0.006), and compliance with protein requirements (p = 0.008). (4) Conclusions: The iNutrition intervention is feasible and potentially benefits post-discharged gastric cancer patients following gastrectomy. A larger trial is required to establish the efficacy of this approach. Trial Registration: 19 October 2022 Chinese Clinical Trial Registry, ChiCTR2200064807.

[Simulation and Regulation of Sustainable Utilization of Water Resources in China Based on Improved Water Resources Ecological Footprint Model].

The original ecological footprint model of water resources was improved here to explore the rational policy of water resources development and utilization. Aiming to address the problems of high complexity, weak applicability, and insufficient systematicness and dynamics of the existing water resources ecological footprint model, the grey water footprint was introduced into the model to quantify the water for decontamination. In the calculation of the water resources ecological footprint index, the rainwater collection project, seawater desalination, and water resources regeneration, unconventional water sources were considered, and when combined with the system dynamics simulation technology, the SD model of water resources sustainable utilization in China was established. We carried out research on the regulation and control of sustainable utilization of water resources in China. The results showed that the development and utilization of water resources in China remained within the ecological carrying capacity as a whole from 2000 to 2017, and the development of water resources still had potential, but the supply and demand of water resources were unbalanced. Given this, from the perspective of throttling, open-source, and pollution control, six control schemes for sustainable utilization of water resources in China were set up, including the continuation of the current situation, green throttling, pollution control, strict planning for water source development, and comprehensive treatment. Among them, the comprehensive coordination plan for 2018-2050 could properly solve the problem of water resources supply and demand under the conditions of meeting the ecological sustainability of water resources and reasonable water resources load and was the best regulation plan to realize the sustainable utilization of water resources in China. At present, the development of water resources in China lags, which does not match the growth rate of social and economic development on water resources consumption. It is necessary to further strengthen the efforts of open-source, water-saving, and pollution control based on the original policies, so as to alleviate the ecological stress of water resources.

[Effects of Climate Warming on the Key Process and Index of Black Soil Carbon and Nitrogen Cycle During Freezing Period].

As an critical part of the global biogeochemical cycle, the winter soil carbon and nitrogen cycles are extremely sensitive to climate warming. Furthermore, the black soil in northeast China is fertile and rich in organic matter and is a vital production base of commodity grains in China. For as long as half a year, the black soil is in a freezing-thawing state. Climate warming will change the snow cover thickness and soil freezing degree on the surface of the black soil in the winter and affect the freezing-thawing cycle frequency and timing of the soil, thus exerting a profound influence on the fixation, transformation, and release of soil carbon and nitrogen during the freezing period and throughout the year. To better understand the effects of climate warming on the black soil carbon and nitrogen dynamics during the freezing period, an experiment was conducted with two warming levels (W1 and W2) using an infrared radiometer to simulate soil warming. The warming increased the surface soil temperature (0 cm soil temperature) by 1.54℃ (W1) and 4.10℃ (W2), respectively, and significantly increased the soil moisture content compared with the control (C) during the freezing period, most likely because of the melting snow. The snow cover thickness, soil freezing depth, soil organic carbon (SOC), and labile organic carbon (LC) content were reduced by both warming treatments. However, the effect of the temperature increase during the freezing period on the key processes and indicators of the nitrogen cycle in black soil was relatively more complicated. With the increase in temperature, the content of nitrate nitrogen (NO3--N) decreased significantly, and the content of total nitrogen (TN) and net nitrogen nitrification rate increased significantly, while the ammonium nitrogen (NH4+-N), total inorganic nitrogen (TIN) content, and the net nitrogen mineralization rate exhibited a significant increase first and then decreased. In summary, climate warming will bring a warmer and more humid environment to the black soil during the freezing period, and the resulting changes in the soil carbon and nitrogen content and transformation processes will have a profound impact on the structure, productivity of the plants and microbial communities, and carbon and nitrogen cycles in the subsequent growing season. The results provide a scientific basis for studying the carbon and nitrogen cycle mechanisms of the northeast black soil during the freezing period.