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Target biomarkers for H2 at both the protein and genome levels are still unclear. In this study, quantitative proteomics acquired from a mouse model were first analyzed. At the same time, functional pathway analysis helped identify functional pathways at the protein level. Then, bioinformatics on mRNA sequencing data were conducted between sepsis and normal mouse models. Differential expressional genes with the closest relationship to disease status and development were identified through module correlation analysis. Then, common biomarkers in proteomics and transcriptomics were extracted as target biomarkers. Through analyzing expression quantitative trait locus (eQTL) and genome-wide association studies (GWAS), colocalization analysis on Apoa2 and sepsis phenotype was conducted by summary-data-based Mendelian randomization (SMR). Then, two-sample and drug-target, syndrome Mendelian randomization (MR) analyses were all conducted using the Twosample R package. For protein level, protein quantitative trait loci (pQTLs) of the target biomarker were also included in MR. Animal experiments helped validate these results. As a result, Apoa2 protein or mRNA was identified as a target biomarker for H2 with a protective, causal relationship with sepsis. HDL and type 2 diabetes were proven to possess causal relationships with sepsis. The agitation and inhibition of Apoa2 were indicated to influence sepsis and related syndromes. In conclusion, we first proposed Apoa2 as a target for H2 treatment.

Global warming and human activities are complicating the spatial and temporal relationships between basin hydrologic processes and ecosystem quality (EQ), especially in arid and semi-arid regions. Knowledge of the synergy between hydrological processes and ecosystems in arid and semi-arid zones is an effective measure to achieve ecologically sustainable development. In this study, the inland river basin Ulagai River Basin (URB), a typical arid and semi-arid region in Northern China, was used as the study area; based on an improved hydrological model and remote-sensing and in situ measured data, this URB-focused study analyzed the spatial and temporal characteristics of hydrological process factors, such as precipitation, evapotranspiration (ET), surface runoff, lateral flow, groundwater recharge, and EQ and the synergistic relationships between them. It was found that, barring snowmelt, the hydrological process factors such as precipitation, ET, surface runoff, lateral flow, and groundwater recharge had a rising trend in the URB, since the 20th century. The rate of change was higher in the downstream areas when compared with what it was in the upstream and midstream areas. The multi-year average of EQ in the basin is 53.66, which is at a medium level and has an overall improving trend, accounting for 95.14% of the total area, mainly in the upstream, downstream southern, and downstream northern areas of the basin. The change in relationship between the hydrological process factors and EQ was found to have a highly synergistic effect. Temporally, EQ was consistent with the interannual trends of precipitation, surface runoff, lateral flow, and groundwater recharge. The correlation between the hydrological process factors and EQ was found to be higher than 0.7 during the study period. Spatially, the hydrological process factors had a synergistic relationship with EQ from strong to weak upstream, midstream, and downstream, respectively. In addition, ecosystem improvements were accelerated by government initiatives such as the policy of Returning Grazing Land to Grassland Project, which has played an important role in promoting soil and water conservation and EQ. This study provides theoretical support for understanding the relationship between hydrological processes and ecological evolution in arid and semi-arid regions, and it also provides new ideas for related research.

In the post-COVID-19 era, significant changes have taken place regarding the epidemic, the economy, family and social life. However, it remains unclear how these changes encompass the psychological symptoms of college students. We carried out a cross-sectional study to investigate anxiety, depression, and post-traumatic stress disorder (PTSD) symptoms among college students from 10 November 2020, to 16 November 2020. The questionnaire included a self-designed canvas, Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), and Impact of Event Scale (IES-R). Factors associated with psychological symptoms were estimated by ordered and non-conditional logistic regression analysis. Of 4754 participants, 25.0%, 29.7%, 3.4%, 15.3%, 17.1%, and 2.9% reported anxiety, depression, PTSD symptoms, one, any two, and all three, respectively. In cases with anxiety or depression symptoms, there was a 9.11% comorbidity with PTSD. Factors associated with fears of being infected, social, family, and economic changes increased the risk of psychological symptoms in college students caused by COVID-19. Female college students, identified with anxiety or depression symptoms, were at a lower risk of developing PTSD symptoms (OR, 0.61, 95% CI: 0.43–0.86). Non-medical majors at university, rural residence, higher educational background, fear of taking public transport, and deterioration of family relationships increased the risk for PTSD symptoms among male respondents with anxiety or depression symptoms due to COVID-19. Factors correlated with psychological symptoms had expanded from the fear of being infected to extensive social, family, and economic changes caused by COVID-19. Therefore, screening and interventions for psychological symptoms should be consistently strengthened and more targeted to college students in the post-COVID-19 era.

Improving the resolution of degraded radar echo images of weather radar systems can aid severe weather forecasting and disaster prevention. Previous approaches to this problem include classical super-resolution (SR) algorithms such as iterative back-projection (IBP) and a recent nonlocal self-similarity sparse representation (NSSR) that exploits the data redundancy of radar echo data, etc. However, since radar echoes tend to have rich edge information and contour textures, the textural detail in the reconstructed echoes of traditional approaches is typically absent. Inspired by the recent advances of faster and deeper neural networks, especially the generative adversarial networks (GAN), which are capable of pushing SR solutions to the natural image manifold, we propose using GAN to tackle the problem of weather radar echo super-resolution to achieve better reconstruction performance (measured in peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM)). Using authentic weather radar echo data, we present the experimental results and compare its reconstruction performance with the above-mentioned methods. The experimental results showed that the GAN-based method is capable of generating perceptually superior solutions while achieving higher PSNR/SSIM results.

Cadmium-contaminated soil significantly threatens global food security and human health. This scenario gives rise to significant worries regarding widespread environmental pollution. Biochar and arbuscular mycorrhizal fungi (AMF) can effectively immobilize cadmium in the soil in an environmentally friendly way. Existing studies have separately focused on the feasibility of each in remediating polluted soil. However, their association during the remediation of cadmium-polluted soils remains unclear. This review paper aims to elucidate the potential of biochar, in conjunction with AMF, as a strategy to remediate soil contaminated with cadmium. This paper comprehensively analyzes the current understanding of the processes in cadmium immobilization in the soil environment by examining the synergistic interactions between biochar and AMF. Key factors influencing the efficacy of this approach, such as biochar properties, AMF species, and soil conditions, are discussed. The influences of biochar–AMF interactions on plant growth, nutrient uptake, and overall ecosystem health in cadmium-contaminated environments are highlighted. This review indicates that combining biochar and AMF can improve cadmium immobilization. The presence of AMF in the soil can create numerous binding sites on biochar for cadmium ions, effectively immobilizing them in the soil. Insights from this review contribute to a deeper understanding of sustainable and eco-friendly approaches to remediate cadmium-contaminated soils, offering potential applications in agriculture and environmental management.

In the initial stages of restoring rocky desertification, the proliferation of nutrients strongly influences plant survival. The carbon–nitrogen doctrine in plants argues that a lower leaf carbon–nitrogen (C:N) ratio enhances the growth of plant nutrients. However, the mechanisms by which inoculation with arbuscular mycorrhizal fungi (AMF) can influence plants during the restoration of rocky desertification are not thoroughly understood. This study used mulberry as a suitable example of a mycorrhizal plant in desertification areas to examine changes in growth, leaf carbon, nitrogen accumulation, and the carbon–nitrogen ratio post inoculation using AMF. The correlation between leaf carbon–nitrogen ratio and root morphology following AMF inoculation was also examined. The results demonstrated that inoculating mulberry with the dominant strains Funneliformis mosseae (Fm) and Rhizophagus intraradices (Ri) not only enhanced above-ground growth and improved carbon and nitrogen nutrient absorption but also had a more pronounced effect on leaf nitrogen accumulation than on carbon accumulation, resulting in a potential decrease in the leaf C:N ratio by 42.13%. It also significantly improved root morphology by exponentially increasing the number of connections and crossings by 120.5% and 109.8%, respectively. Further analysis revealed a negative correlation between leaf C:N ratio and root morphology, as well as between root length and the number of connections. Plants with more developed root systems exhibited greater competitiveness for nitrogen, resulting in a lower leaf C:N ratio. This study suggests that the inoculation of AMF could enhance leaf nitrogen accumulation and reduce the leaf C:N ratio by expanding the spatial absorption range of the root through positive changes in root morphology, thereby promoting plant nutrient growth. This study forms a fundamental scientific basis for the successful management of desertification.

Recently, rampant eutrophication induced by phosphorus enrichment in water has been attracting attention worldwide. However, the mechanisms by which phosphate can be eliminated from the aqueous environment remain unclear. This study was aimed at investigating the adsorption performance and regulation mechanisms of the zeolite-biochar composite for removing phosphate from an aqueous environment. To do this, physicochemical properties of the zeolite-biochar composite were assessed by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET) specific surface area (SSA) analyzer, and transmission electron microscopy (TEM). Adsorption tests were performed to evaluate the adsorption ability of the composite material for mitigating excess phosphorus in the aqueous environment. The findings evinced that the phosphorus removed by PZC 7:3 (pyrolyzed zeolite and corn straw at a mass ratio of 7:3) can reach 90% of that removed by biochar. The maximum adsorption capacities of zeolite, biochar, and PZC 7:3 were 0.69, 3.60, and 2.41 mg/g, respectively. The main mechanism of phosphate removal by PZC 7:3 was the formation of thin-film amorphous calcium-magnesium phosphate compounds through ligand exchange. This study suggests that PZC 7:3 is a viable adsorbent for the removal of phosphate from aquatic systems.