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The increase in extreme precipitation (EP) may pose a serious threat to the health and safety of population in arid and semi-arid regions. The current research on the impact of EP on population in Central Asia (CA) is insufficient and there is an urgent need for a comprehensive assessment. Hence, we opted for precipitation and temperature data under two Shared Socioeconomic Pathways (SSP2–4.5 and SSP5–8.5) from ten Global Climate Models (GCMs), which were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). By integrating population data in 2020 and 2050 (SSP2 and SSP5), we investigated the future changes in EP and population exposure in CA under 1.5 °C and 2 °C global warming scenarios (GWSs). Our analysis indicates that EP in CA is projected to increase with global warming. Under the SSP5–8.5, the maximum daily precipitation (Rx1day) exhibits an average response rate to global warming of 3.58 %/K (1.99–4.06 %/K). With rising temperatures, an increasing number of areas and populations in CA will be impacted by EP, especially in the Fergana valley. Approximately 25% of the population (land area) in CA is exposed to Rx1day with increases of more than 8.31% (9.32%) under 1.5 °C GWS and 14.18% (13.25%) under 2 °C GWS. Controlling temperature rise can be effective in reducing population exposures to EP. For instance, limiting the temperature increase to 1.5 °C instead of 2 °C results in a 2.79% (1.75%–4.59%) reduction in population exposure to Rx1day. Finally, we found that climate change serves as the predominant factor influencing the population exposure to EP, while the role of population redistribution, although relatively minor, should not be disregarded. Particularly for prolonged drought, the role of population redistribution manifests negatively.

ABSTRACT: Objectives: We aimed to determine the clinical impact of inappropriate empirical antibiotic treatment (IEAT) compared with appropriate empirical antibiotic treatment (AEAT) in hospitalised patients with urinary tract infections (UTIs) caused by Escherichia coli (E. coli). Methods: This retrospective cohort study included adult patients with a primary diagnosis of UTI who were treated with empirical antibiotics at a tertiary hospital in southern China over a 2-year period. Clinical data of patients who received IEAT were compared with those of patients receiving AEAT. We used multivariable logistic regression to identify the predictors for receiving IEAT and the risk factors affecting clinical outcomes. Results: A total of 213 patients were enrolled (median age, 61 years), of whom 103 (48.4%) received IEAT. IEAT was associated with empirical use of fluoroquinolones, male sex and age-adjusted Charlson comorbidity index (aCCI) score >6. Hospital length of stay (LOS) was longer for patients who received IEAT than for those who received AEAT (13.6 ± 8.6 days vs. 10.8 ± 7.9 days; P = 0.008). IEAT was an independent risk factor for longer LOS along with aCCI score ≥2, lung disease and cardiac disease. Conclusion: Empirical use of fluoroquinolones for UTIs should be avoided, especially in male patients with aCCI score >6. Improved empirical antimicrobial therapy may have a beneficial impact in reducing bacterial resistance and healthcare costs by decreasing the LOS. Therefore, interventions to promote in-depth antibiotic stewardship programmes in China are needed.

Summary: Although hydroxychloroquine (HCQ) has long been used to treat autoimmune diseases, its mechanism of action remains poorly understood. In CD4 T-cells, we found that a clinically relevant concentration of HCQ inhibited the mitochondrial antioxidant system triggered by TCR crosslinking, leading to increased mitochondrial superoxide, impaired activation-induced autophagic flux, and reduced proliferation of CD4 T-cells. In antigen-presenting cells, HCQ also reduced constitutive activation of the endo-lysosomal protease legumain and toll-like receptor 9, thereby reducing cytokine production, but it had little apparent impact on constitutive antigen processing and peptide presentation. HCQ's effects did not require endo-lysosomal pH change, nor impaired autophagosome-lysosome fusion. We explored the clinical relevance of these findings in patients with celiac disease—a prototypic CD4 T-cell-mediated disease—and found that HCQ limits ex vivo antigen-specific T cell responses. We report a T-cell-intrinsic immunomodulatory effect from HCQ and suggest potential re-purposing of HCQ for celiac disease.

This mini review identifies several thermogravimetric analysis (TGA)-based methods for the identification and quantification of different microplastics in both proof-of-concept studies and environmental samples, and highlights method-specific limitations associated with their application. Well-separated and non-overlapping melting peaks are a conditional requirement for the identification and quantification of microplastics using thermogravimetric analysis-differential scanning calorimetry (TGA-DSC). Other TGA-based methods, such as coupled Fourier transform infrared spectroscopy (TGA-FTIR) or mass spectrometry (TGA-MS), as well as thermal extraction desorption-gas chromatography-mass spectrometry (TED-GC-MS), are dependent on the presence of at least one unique thermal degradation product for use as a marker in the identification and quantification process. Varying degrees of time expenditure and complexity of analysis are present within the reviewed methods, with one consistent factor underlying the evaluation: an underutilization of information extracted from the TGA signal itself. As such, in this mini-review, we advocate the development of methods in which stand-alone TGA can be applied towards the chemical identification of microplastics. Although the main hindrance to this is the presence of overlapping thermal transitions, stand-alone TGA has long been used as a routine and robust method for the analysis of polymers, and methods for optimizing the resolution of complex mixtures are available. Current results in literature emphasize the complementarity of analysis methods, and TGA has potential to play a role as a rapid and facile method that can guide the chemical identification of polymers and address needs of current methods.

Liver cancer is one of the most common malignancies, with severe morbidity and mortality. While considerable progress has been made in liver cancer treatment, the 5-year overall survival (OS) of patients has not improved significantly. Reasons include the inadequate capability of early screening and diagnosis, a high incidence of recurrence and metastasis, a high degree of tumor heterogeneity, and an immunosuppressive tumor microenvironment. Therefore, the identification and validation of specific and robust liver cancer biomarkers are of major importance for early screening, timely diagnosis, accurate prognosis, and the prevention of tumor progression. In this review, we highlight some of the latest research progress and potential applications of liver cancer biomarkers, describing hotspots and prospective directions in biomarker discovery.