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The Indian Ocean Dipole (IOD) strongly influences Indo-Pacific climate extremes, yet its drivers remain incompletely understood. Using satellite observations, reanalysis, and climate model experiments, we identify Middle East dust emissions as a major external driver of IOD variability. Observational evidence shows that dust over the 1980-2020 period account for ~36% of interannual IOD variance, surpassing El Niño-Southern Oscillation as the main driver during boreal autumn. Climate simulations confirm that reduced dust enhances warming in the western Indian Ocean and inducing easterly winds that shoal the eastern thermocline. These anomalies trigger Bjerknes and wind–evaporation–sea surface temperature feedbacks, amplifying a positive IOD pattern, and vice versa. Our findings reveal a powerful dust–IOD teleconnection, highlighting the need to incorporate aerosol forcing into seasonal forecasts and climate projections. Multipole datasets and targeted sensitivity simulations reveal interannual variability in Middle Eastern dust accounts for ~36 % of the Indian Ocean Dipole variance during boreal autumn, surpassing the influence of El Niño-Southern Oscillation.

The height of the atmospheric mixed layer is a critical parameter controlling the vertical dispersion of pollutants. Here we calculate daily maximum mixed layer height (MMLH) using operational radiosonde and surface meteorological measurements made at 219 carefully selected WMO weather stations and analyze their long-term trends from 1973 to 2018. We found that 74 stations showed significant increases in MMLH, whereas 48 sites showed negative trends. Positive trends are mainly found in Central US, Europe, Africa, East and Southeast Asia and East Australia. Stations over the coastal US, India and West Australia generally exhibit negative trends. The trends can be attributed to changes in vertical temperature gradient ∇ θ v between 950 and 700 hPa and diurnal temperature range (DTR). ∇ θ v in general decreased and caused positive MMLH trends over the majority of the regions. DTR decreases globally, causing negative MMLH trends (corresponding to decreased DTR), and plays a more important role over India and Central Asia.

Background Cell subsets differentially modulate host immune responses to Mycobacterium tuberculosis (MTB) infection. However, the nature and functions of these subsets against osteoarticular tuberculosis (OTB) are unclear. Here, we aimed to understand the phenotypes and functions of immune cell subsets in patients with OTB using single-cell RNA sequencing (scRNA-Seq). Methods Pathological and healthy adjacent tissues were isolated from patients with OTB and subjected to scRNA-Seq. Unsupervised clustering of cells was performed based on gene expression profiles, and uniform manifold approximation and projection was used for clustering visualization. Results Thirteen cell subsets were identified in OTB tissues. scRNA-seq datasets of patients and healthy controls (HCs) showed that infection changed the frequency of immune cell subsets in OTB tissues. Myeloid cell examination revealed nine subsets. The frequency of macrophage-RGS1 high subsets decreased in OTB tissues; this increased MTB susceptibility in an SLC7A11/ferroptosis-dependent manner. Immunohistochemistry assays and flow cytometry for patients with OTB and osteoarticular bacterial infection (OBI) and HCs verified that the frequency of macrophage-RGS1 high subset decreased in OTB tissues and blood samples, thereby distinguishing patients with OTB from HCs and patients with OBI. Conclusion The macrophage-RGS1 high subset levels were decreased in patients with OTB, and would be up-regulated after effective treatment. Therefore, the clinical significance of this study is to discover that macrophage-RGS1 high subset may serve as a potential biomarker for OTB diagnosis and treatment efficacy monitoring.

Fires are a major source of air pollutants in Southeast Asia. Over the past few decades, there has been an increase in fire activities in this region, and the causes are not entirely clear. By analyzing multiple observational and reanalysis datasets, as well as conducting climate model simulations, we uncover a distinct positive impact of Arctic sea ice loss on Southeast Asian fire weather. There is a possibility that the fall in the autumn Sea Ice Concentration (SIC) over the Beaufort Sea the year prior contributes to the increase in boreal spring fire activity in Southeast Asia. This sea ice reduction generates a local low warm anomaly, triggering an upper atmosphere Rossby wave train that propagates from the tropical Pacific to Southeast Asia and arrives in Southeast Asia as a high-pressure anomaly with descending air. Moreover, two meridional cells originating from equatorial and polar regions intensify the sinking airflow. This Arctic-driven teleconnection causes high pressure with warmer and dryer surfaces in Southeast Asia, creating favorable conditions for fire ignition and expansion. Based on the fire weather classification criteria, a negative change in SIC of one standard deviation below the climatological mean will expose over 500 million people to very high levels of fire pollution across Southeast Asia, and the number of people exposed to extreme fires will be 1000 times greater than in the present scenario. The above-mentioned mechanism has great implications for projecting decadal air quality and developing relevant health policies to cope with climate change in Southeast Asia.

This study aimed to identify circulating exosomal microRNAs for early detection of coronary microvascular dysfunction (MD) and stratification of myocardial injury risk in type 2 diabetes, and to test whether miR-550a-5p derived from endothelial cell models mechanistically links endothelial stress to cardiomyocyte vulnerability via Hippo-eNOS signaling and vesicular transfer. We combined Gene Expression Omnibus (GEO)-guided discovery and compendium prioritization with clinical and mechanistic validation. Plasma exosomal miR-550a-5p/miR-665 were quantified in a well-phenotyped Type 2 Diabetes Mellitus (T2DM) cohort and related to MD and myocardial injury. , miR-550a-5p was modulated in human cardiac microvascular endothelial cells under high glucose to profile Hippo-YAP/eNOS signaling, and its exosomal transfer effects on human cardiomyocytes were evaluated, with Hippo inhibition applied as a rescue strategy. Exosomal miR-550a-5p and miR-665 were elevated in MD and further increased with myocardial injury, showing useful diagnostic performance and independent associations. miR-550a-5p inhibition restored endothelial viability, migration, tube formation and p-eNOS/eNOS, reduced MST1/LATS1 activation, and increased Yes-associated protein (YAP) activity. Endothelial exosomes delivered miR-550a-5p to cardiomyocytes, aggravating apoptosis and oxidative stress; donor-cell miR-550a-5p suppression and Hippo inhibition mitigated these effects. Exosomal miR-550a-5p, together with miR-665, functions as a dual-utility signal, serving as an accessible biomarker for coronary MD and as a mechanistic mediator in endothelial-to-cardiomyocyte exosomal signaling. These findings support earlier detection, risk stratification, and mechanism-guided intervention in T2DM. Future priorities include external validation, longitudinal kinetic assessment, and target-network mapping.

Background Candida auris infections pose a threat to public health, necessitating increased awareness in China. This study aimed to analyze the strains of C. auris, assess the infection status, and investigate clinical characteristics and risk factors for mortality. Methods A retrospective analysis was conducted on 18 patients with Candida auris infection. We focused on evaluating basic characteristics, strain sources, and antibacterial susceptibility test results. Statistical methods were used to determine clinical features and identify risk factors for death. Results The strain type, composition ratio, and specimen source of C. auris were not associated with mortality. Neither the infection index nor the length of hospitalization showed an association with the prognosis. However, significant risk factors for mortality included cerebral infarction, cardiac disease, renal dysfunction, hypoproteinemia, and anemia (all p < 0.05). Conclusions Cerebral infarction, cardiac disease, renal dysfunction, hypoproteinemia, and anemia are significant risk factors for death in C. auris infections. These findings indicate the importance of recognizing and addressing these factors in the clinical management of C. auris infection. This research investigates the strains of C. auris, assesses the infection situation, and investigates clinical characteristics and risk factors for mortality. The significant risk factors for death in C. auris infections include (1) cerebral infarction (2) cardiac disease (3) renal dysfunction (4) hypoproteinemia (5) anemia.

Metabolic engineering and synthetic biology approaches have been successfully implemented for construction of yeast platforms producing compounds with various applications.Bioengineered yeast is a promising nutritional supplement for the delivery of compounds with geroprotective activities.Yarrowia lipolytica is an efficient platform for the production of anti-inflammatory essential lipids 3-omega polyunsaturated fatty acids through either aerobic or anaerobic synthesis.Biosynthetic pathways of promising terpenoids, including astaxanthin, carnosic acid, and ginsenosides, can be reconstructed in the yeast Saccharomyces cerevisiae.Biosynthesis of intermediate substrates of several potent compounds, such as vitamin D3, fucoxanthin, or andrographolide, has been established in yeast. The aging process entails a multifaceted decline in the capacity to restore homeostasis in response to stress. A prevalent characteristic of many age-related diseases is the presence of low-grade chronic inflammation, a risk factor contributing significantly to morbidity and mortality in the elderly population. Specific lifestyle interventions, such as regular physical activity, targeted diet, and supplementation, can delay the accumulation of chronic age-associated conditions by mitigating inflammation processes. Bioengineered yeast-producing compounds with distinctive bioactivities, including anti-inflammatory properties, have the potential to provide rich dietary alternatives for the prevention of age-related diseases. This review highlights recent achievements in engineering effective yeast platforms, namely Saccharomyces cerevisiae and Yarrowia lipolytica, that hold promise in retarding the onset of aging and age-related ailments. The aging process entails a multifaceted decline in the capacity to restore homeostasis in response to stress. A prevalent characteristic of many age-related diseases is the presence of low-grade chronic inflammation, a risk factor contributing significantly to morbidity and mortality in the elderly population. Specific lifestyle interventions, such as regular physical activity, targeted diet, and supplementation, can delay the accumulation of chronic age-associated conditions by mitigating inflammation processes. Bioengineered yeast-producing compounds with distinctive bioactivities, including anti-inflammatory properties, have the potential to provide rich dietary alternatives for the prevention of age-related diseases. This review highlights recent achievements in engineering effective yeast platforms, namely Saccharomyces cerevisiae and Yarrowia lipolytica, that hold promise in retarding the onset of aging and age-related ailments.

The direct perturbation of anthropogenic aerosols on Earth’s energy balance [i.e., direct aerosol radiative forcing (DARF)] remains uncertain in climate models. These uncertainties critically depend on aerosol optical properties, primarily aerosol optical depth (AOD), single scattering albedo (SSA), and the asymmetry factor g. In this study, we investigate the intermodel spread of DARF across 14 global models within phase 6 of the Coupled Model Intercomparison Project (CMIP6), using unified radiative transfer calculation and aerosol optical parameter assumptions. The global mean DARF for clear sky in 2014 with respect to 1850 is estimated as −0.77 ± 0.52 W m−2 assuming an externally mixed state and −0.68 ± 0.53 W m−2 for an internally mixed state. We further conduct a quantitative analysis and find that globally, for the external mixing assumption, AOD is the dominant factor, whose intermodel spread results in 36% of the total DARF uncertainty. For the internal mixing assumption, SSA becomes the major factor, which also leads to 36% DARF uncertainty. The g parameter and aerosol vertical distribution combined contribute to ∼30% of the DARF uncertainty. Regionally, DARF uncertainty is typically more sensitive to SSA where the absorbing aerosol fraction is high, such as South Asia and central Africa. Substantial differences between model-averaged and observed aerosol optical parameters are still noticed, with external mixing in general yielding closer agreement with observations. Our results highlight the importance of aerosol scattering and absorption properties in DARF estimation.

The direct perturbation of anthropogenic aerosols on Earth’s energy balance [i.e., direct aerosol radiative forcing (DARF)] remains uncertain in climate models. In this study, we investigate the uncertainty of DARF associated with aerosol vertical distribution, using simulation results from 14 global models within phase 6 of the Coupled Model Intercomparison Project (CMIP6). The column mass loading for each aerosol species is first normalized to the multimodel average for each model, which is called the mass-normalization process. The unified radiative transfer model and aerosol optical parameter are used, so that the differences in the calculated DARF are solely attributed to the difference in aerosol vertical profiles. The global mean DARF values in 2014 with respect to 1850 before and after mass normalization are −0.77 ± 0.52 and −0.81 ± 0.12 W m−2 respectively, assuming external mixing, which indicates that the intermodel difference in aerosol vertical distribution accounts for ∼20% of the total DARF uncertainty. We further conduct two separate experiments by normalizing aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) profiles, respectively, and find that the vertical distribution of SSA results in larger DARF uncertainty (0.17 W m−2) than that of AOD (0.10 W m−2). Finally, compared with CALIPSO observation, CMIP6 models tend to produce higher aerosol layers. The bias in modeled aerosol profile with respect to CALIPSO leads to stronger DARF, especially for land regions.