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Currently, no specific treatment exists to alleviate metabolic dysfunction-associated fatty liver (MAFLD). Previously, Poria cocos (PC) effectively relieved MAFLD, but its bioactive components are still unknown. The bioactive substances in PC that regulate mitochondria function to alleviate MAFLD were thus determined. The L02 hepatocyte model induced by fat emulsion and the MAFLD rat model induced by a high-fat diet (HFD) were developed to explore the efficacy of PC against MAFLD. The activity of PC-derived components in the liver mitochondria of HFD-fed rats was evaluated using the L02 hepatocyte model. Additionally, the PC-derived components from the liver mitochondria were identified by ultra-high performance liquid chromatography/mass spectrometry. Finally, the anti-steatosis ability of PC-derived monomers and monomers groups was evaluated using the adipocyte model. PC maintained the mitochondrial ultrastructure, alleviated mitochondrial oxidative stress, and regulated the energy metabolism and the fatty acid β oxidation to relieve lipid emulsion-induced cellular steatosis and HFD-induced MAFLD. PC-derived components entering the liver mitochondria inhibited oxidative stress injury and improved the energy metabolism to fight cellular steatosis. Additionally, 15 chemicals were identified in the PC-treated rat liver mitochondria. These identified chemical molecules and molecule groups in the mitochondria prevented cellular steatosis by regulating mitochondrial oxidative stress and energy metabolism. PC restores mitochondrial structure and function, alleviating MAFLD, which is related to oxidative stress, energy metabolism, and fatty acid β oxidation. The identified 15 components may be the main effective PC components regulating mitochondria function to alleviate MAFLD. Thus, PC may be a promising mitochondrial regulator to prevent MAFLD.

To achieve sustainable development goals in Huangshui River Basin (HRB), strengthening adaptive water resources management under the dual impact of climate change (CC) and human interventions (HI) is of great significance. Multiple mathematical and statistical methods were employed to determine the runoff trend and breakpoint in HRB. The elasticity of CC and HI on the runoff decline and their contributions were quantitatively discerned based on the Budyko hypothesis, complementary method, and SWAT hydrological model. The results show that (1) the runoff showed a decreasing trend, with a runoff breakpoint in 1990; (2) the elasticity coefficients indicated a 1% increase in P, ET0, and n, leading to a 2.19% increase, a 1.19% decrease, and a 1.52% decrease in the runoff, respectively; (3) the Budyko framework determined the contribution of CC and HI to runoff decline in HRB to be 37.98–41.86% and 58.14–62.02%, respectively, and that estimated by SWAT hydrological model to be 38.72 and 61.28%, respectively; (4) HI were the primary factor for runoff decline in HRB, where direct anthropogenic disturbances such as water withdrawals and water conservancy project construction were the main drivers. The findings have important scientific significance for water resources planning and management in HRB. HIGHLIGHTS We determined the change trend and breakpoint of annual runoff from 1959 to 2014.; The runoff elasticity was estimated theoretically based on the Budyko hypothesis for 20 mountainous catchments and 5 hydrographic cross-sections in HRB.; The complementary method calculated the contribution threshold of climate change and human interventions to runoff changes.; SWAT models were used to discern runoff change attributions.;

High-intensity human activities have changed land use/land cover (LULC) patterns in the Huangshui River Basin (HRB), which has brought significant challenges to ecosystems sustainable development. Discerning ecosystem service dynamic characteristics and responses under different land use/cover change (LUCC) scenarios are necessary to increase the public willingness to pay for the ecosystem and guide the decision-making process. We examined LULC spatiotemporal dynamics in the HRB from 2000 to 2020 and coupled Markov-chain, multi-objective programming (MOP), and patch-generating land use simulation (PLUS) models to optimize and simulate LULC spatial pattern for five scenarios: natural development scenario (NDs), city expansion scenario (CEs), ecological protection scenario (EPs), economic development scenario (EDs), ecological and economic balance scenario (EEBs). Given regional differences, a spatially modified ecosystem service value (ESV) assessment model was proposed to evaluate ESV. Factors driving ESV spatial stratified heterogeneity were identified using geographic detectors. Ecosystem service value sensitivity in response to LUCC was discriminated against using the elasticity model. The study area was dominated by 56.86–60.40 % grassland and 33.11–36.27 % cropland. Grassland and cropland area decreased by 579.75 km2 and 423.87 km2 over the period 2000–2020, while the other areas such as forestland, water area, construction land, and barren land increased by 289.81 km2, 140.77 km2, 489.10 km2, and 83.96 km2, respectively. Land conversion mainly occurred among grassland, cropland, and construction land. Total ESV was 39,665 million yuan in 2020, an increase of 2.25 % compared to 2000. Total ESV of NDs, EPs, EDs, and EEBs increased by 0.34 %, 1.04 %, 2.01 %, and 7.78 %, respectively compared to 2020, while that of CEs decreased by 0.17 %. ESV sensitivity coefficient response to LUCC was 0.43 during 2010–2020, indicating that LULC conversion of 1 % would result in average changes of 0.43 % in ESV. Ecosystem services response to LUCC was not very marked in the HRB. Elevation was the dominant driver of LULC and ESV stratified spatial heterogeneity in the HRB. The effects of elevation on LUCC and ESV should receive more attention in management. Multi-objective optimization and multi-scenario analysis effectively guided land-use planning and decision-making involved in ecosystem uncertainty, complexity, and interaction. The EPs and EEBs may be more suitable for future HRB development.