Quantitative assessment of retinal vasculature changes in systemic lupus erythematosus using wide-field OCTA and the correlation with disease activity.

Purpose: To assess the retinal vasculature changes quantitatively using wide-field optical coherence tomography angiography (OCTA) in systemic lupus erythematosus (SLE), and explore its correlation with systemic clinical features. Design: Prospective, cross-sectional, observational study. Participants and controls: Patients with SLE who presented to the Ophthalmology Department of Peking Union Medical College Hospital from November 2022 to April 2023 were collected. The subjects were divided into retinopathy and without retinopathy groups. Age and gender-matched healthy subjects were selected as controls. Methods: Patients with SLE and control subjects were imaged with 24×20 mm OCTA scans centered on the fovea and 6×6 mm OCTA scans centered on the optic disc. The sub-layers of OCTA images were stratified by the built-in software of the device and then the retinal thickness and vessel density were measured automatically. The characteristics of retinal OCTA parameters of SLE and its correlation with systemic clinical indicators of patients without retinopathy were analyzed. Main outcome measures: OCTA parameters, visual acuity, intraocular pressure, and systemic clinical indicators of patients such as disease activity index, autoimmune antibodies, and inflammatory marker levels were collected. Results: A total of 102 SLE patients were included, 24 of which had retinopathy, and 78 had unaffected retina. Wide-field OCTA could effectively detect retinal vascular obstruction, non-perfusion area, and morphological abnormalities in patients with lupus retinopathy. SLE patients without retinopathy had significantly higher retinal superficial vessel density (SVD) in foveal (P=0.02), para-foveal temporal (P=0.01), nasal (P=0.01), peripheral foveal temporal (P=0.02), and inferior areas (P=0.02), as well as subregion temporal (P=0.01) and inferior areas (P=0.03) when compared with healthy controls (n=65 eyes from 65 participants). The area under curve (AUC) value of subregion inferior SVD combined parafoveal temporal SVD was up to 0.70. There was a significantly positive correlation between SVD and disease activity in SLE without retinopathy group. Patients with severe activity had the most significant increase in SVD. Conclusion: Wide-field OCTA can provide a relatively comprehensive assessment of the retinal vasculature in SLE. In the absence of pathological changes of the retina, the SVD was significantly increased and was positively correlated with the disease activity of SLE.

Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China.

Objective: Insulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the "common soil" of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related disease. This study aims to develop and validate machine learning (ML)-augmented algorithms for insulin sensitivity assessment in the community and primary care settings. Methods: We analyzed the data of 9358 participants over 40 years old who participated in the population-based cohort of the Hubei center of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals). Three non-ensemble algorithms and four ensemble algorithms were used to develop the models with 70 non-laboratory variables for the community and 87 (70 non-laboratory and 17 laboratory) variables for the primary care settings to screen the classifier of the state-of-the-art. The models with the best performance were further streamlined using top-ranked 5, 8, 10, 13, 15, and 20 features. Performances of these ML models were evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPR), and the Brier score. The Shapley additive explanation (SHAP) analysis was employed to evaluate the importance of features and interpret the models. Results: The LightGBM models developed for the community (AUROC 0.794, AUPR 0.575, Brier score 0.145) and primary care settings (AUROC 0.867, AUPR 0.705, Brier score 0.119) achieved higher performance than the models constructed by the other six algorithms. The streamlined LightGBM models for the community (AUROC 0.791, AUPR 0.563, Brier score 0.146) and primary care settings (AUROC 0.863, AUPR 0.692, Brier score 0.124) using the 20 top-ranked variables also showed excellent performance. SHAP analysis indicated that the top-ranked features included fasting plasma glucose (FPG), waist circumference (WC), body mass index (BMI), triglycerides (TG), gender, waist-to-height ratio (WHtR), the number of daughters born, resting pulse rate (RPR), etc. Conclusion: The ML models using the LightGBM algorithm are efficient to predict insulin sensitivity in the community and primary care settings accurately and might potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.

Direct and indirect consumption activities drive distinct urban-rural inequalities in air pollution-related mortality in China.

Household consumption in China is associated with substantial PM2.5 pollution, through activities directly (i.e., fuel use) and/or indirectly (i.e., consumption of goods and services) causing pollutant emissions. Urban and rural households exhibit different consumption preferences and living areas, thus their contributions to and suffering from air pollution could differ. Assessing this contrast is crucial for comprehending the environmental impacts of the nation's ongoing urbanization process. Here we quantify Chinese urban and rural households' contributions to ambient PM2.5 pollution and the health risks they suffer from, by integrating economic, atmospheric, and health models and/or datasets. The national premature deaths related to long-term exposure to PM2.5 pollution contributed by total household consumption are estimated to be 1.1 million cases in 2015, among which 56% are urban households and 44% are rural households. For pollution contributed indirectly, urban households, especially in developed provinces, tend to bear lower mortality risks compared with the portions of deaths or pollution they contribute. The opposite results are true for direct pollution. With China's rapid urbanization process, without adequate reduction in emission intensity, the increased indirect pollution-associated premature deaths could largely offset that avoided by reduced direct pollution, and the indirect pollution-associated urban-rural inequalities might become severer. Developing pollution mitigation strategies from both production and consumption sides could help with reducing pollution-related mortality and associated urban-rural inequality.

Activation of persulfate with natural organic acids (ascorbic acid/catechin hydrate) for naproxen degradation in water and soil: Mechanism, pathway, and toxicity assessment.

In this study, we investigated the effects of different natural organic acids (NOAs), L-ascorbic acid (AA) and (+)-catechin hydrate (CAT), on the activation of persulfate (PDS) for the oxidation of naproxen (NAP) in water and soil. We found that only AA-activated PDS process had a significant degradation efficiency of NAP in water. High AA concentration (500 µM) inhibited the degradation of NAP, whereas high levels of PDS (7.5 mM) and acidic conditions (pH=3-7) were beneficial for NAP degradation. In soil, both CAT and AA promoted PDS activation and NAP degradation. Low soil organic matter and high Fe/Mn-mineral contents were favorable for NAP degradation by AA-activated PDS. Column experiments confirmed that NAP was readily transported and degraded under porous medium conditions using AA-activated PDS. Moreover, we revealed that SO4•- and HO• were the dominant reactive species for NAP degradation by AA-activated PDS. Intermediate products of NAP in the AA-activated PDS process were analyzed and the reactive sites of NAP were predicted. E. coli growth tests verified that the intermediate products in the AA-activated PDS process were less toxic than NAP. Our results highlight the high potential of NOAs-activated PDS process for the remediation of NAP-contaminated water and soil.

Quantitative chest CT assessment of pulmonary alveolar proteinosis with deep learning: a real-world longitudinal study.

Background: High-resolution computed tomography (HRCT) plays an important role in accessing the severity of pulmonary alveolar proteinosis (PAP). Visual evaluation of changes between two HRCT scans is subjective. This study was conducted to quantitatively evaluate lung burden changes in patients with PAP using HRCT-based automated deep-learning method following 12 months of statin therapy. Methods: In this prospective real-world observational study, patients with PAP who underwent chest HRCT were evaluated from November 28, 2018, to April 12, 2021. Oral statin administration was initiated as therapy for these PAP patients with 12 months of follow-up. HRCT-derived lung ground-glass opacification percentage of the whole lung and 5 lobes and the percentage of different densities of ground glass were automatically quantified with deep-learning software. Longitudinal changes of the HRCT quantitative parameter were also compared. Results: The study enrolled 50 patients with PAP, including 25 mild-moderate PAP cases and 25 severe PAP cases. The percentage of lung ground-glass opacification of the whole lung and 5 lobes and the percentage of different densities of ground glass were significantly different among the 2 different clinical types at baseline (all P values <0.05). Overall, the percentage of whole-lung ground-glass opacification significantly decreased between the baseline HRCT and the HRCT results after 12 months of follow-up (P=0.023; 95% CI: 1.384-18.684). Changes in the total opacification of the whole lung were positively correlated with changes in partial pressure of arterial oxygen (PaO2; r=0.716; P<0.001) and percentage of predicted diffusion capacity for carbon monoxide (DLCO%pred; r=0.664; P<0.001). Conclusions: A quantitative image parameter automatically generated by a deep-learning tool from chest HRCT scans may be used to evaluate the severity of PAP and may help to evaluate and quantify the response to statin therapy.

Inequality in historical transboundary anthropogenic PM2.5 health impacts.

Atmospheric transport of fine particulate matter (PM2.5), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

The atmospheric lead emission, deposition, and environmental inequality driven by interprovincial trade in China.

Lead (Pb) as a hazardous air pollutant has raised widespread concerns due to its adverse and toxic effects on the ecological environment and human health. Here we integrated the multi-regional input-output (MRIO) model and an atmospheric transport model to examine regional environmental inequality (REI) index induced by Pb emission transfers, and to evaluate the impacts of interprovincial trade on regional atmospheric Pb concentrations and dry deposition fluxes in China in 2012. In 2012, approximately 57.4% ~ 72.6% of Pb emissions in well-developed eastern regions (Beijing-Tianjin, Yangtze River Delta (YRD)) and the southern seaboard of China were embodied in other regions in China subject to the demands from these well-developed regions to industrial products and services. Our results, based on the net virtual flows of Pb emission and value-added, indicate that most provinces in the eastern seaboard of China outsource Pb emission and benefit from the interprovincial trade by reducing their Pb emissions. REI indexes show that the well-developed Guangdong province outsources its Pb emission but has low economic gains. Many less-developed provinces in central China enhance virtual Pb emission inflow but have high economic gains. Whereas, inland provinces in western China not only experience Pb emission increase, but also suffer from indirect economic loss due to trade with well-developed provinces to meet their increasing demands to Pb emission abundant industrial products from these provinces in eastern China which are mostly provided by less-developed but energy and mineral product abundant provinces in western China. For example, the province pair with highest REI index was Jiangsu-Inner Mongolia (REI = 2.47), which revealed that Jiangsu was the largest beneficiary which exported 37.2 t of net Pb emission and gained value-added of 521.4 billion RMB through trade with Inner Mongolia which suffered from both virtual Pb inflow and economic loss in 2012. As a result of interprovincial trade, Pb dry deposition in central and eastern China was decreased but increased in western China. Overall, interprovincial trade reduced 17.6% of atmospheric Pb dry deposition in China.

Clinical management and treatment of obesity in China.

China has one of the largest populations with obesity in the world, and obesity has become a major challenge for the country's health-care system. Current guidelines for obesity management are not adequately supported by evidence from clinical studies in Chinese populations. Effective lifestyle interventions suitable for Chinese populations are scarce, insufficient weight-loss medications have been approved by regulatory bodies, and there is low acceptance of non-lifestyle interventions (ie, medications and surgery) among both health-care providers and the general public. Large, well designed, and well implemented clinical trials are needed to strengthen the evidence base for the clinical management of obesity in China. Obesity management can be improved through use of a tiered system involving health management centres, integrated lifestyle interventions and medical treatments, strengthened obesity education and training, and use of advanced electronic health technologies. Resource mobilisation, support from major stakeholders for people with overweight or obesity, and education and changes to social norms among the wider public are also needed. National health policies should prioritise both obesity prevention and improvement of the treatment and management of obesity.

Carbon and health implications of trade restrictions.

In a globalized economy, production of goods can be disrupted by trade disputes. Yet the resulting impacts on carbon dioxide emissions and ambient particulate matter (PM2.5) related premature mortality are unclear. Here we show that in contrast to a free trade world, with the emission intensity in each sector unchanged, an extremely anti-trade scenario with current tariffs plus an additional 25% tariff on each traded product would reduce the global export volume by 32.5%, gross domestic product by 9.0%, carbon dioxide by 6.3%, and PM2.5-related mortality by 4.1%. The respective impacts would be substantial for the United States, Western Europe and China. A freer trade scenario would increase global carbon dioxide emission and air pollution due to higher levels of production, especially in developing regions with relatively high emission intensities. Global collaborative actions to reduce emission intensities in developing regions could help achieve an economic-environmental win-win state through globalization.

Environmental taxation and regional inequality in China.

In order to combat environmental pollution, China enacted the Environmental Protection Tax Law in early 2018. Yet the impacts of the environmental tax on individual regions with different socioeconomic statuses, which are crucial for social justice and public acceptance, remain unclear. Based on a Multi-Regional Input-Output (MRIO) table and a nationally regulated tax payment calculation method, this study analyzes the distributional impacts of an environmental tax based upon province's consumption from both inter-provincial and rural-urban aspects. The national tax revenue based on the current levy mechanism is estimated to be only one seventh of the economic loss from premature mortality caused by ambient particulate matter (PM2.5). The taxation may slightly alleviate urban-rural inequality but may not be helpful with reducing inter-provincial inequality. We further analyze two alternative levy mechanisms. If each province imposes taxes to products it consumes (rather than produces, as in the current mechanism), with the tax rate linearly dependent on its per capita consumption expenditure, this would moderately increase the national tax revenue and significantly reduce inter-provincial inequality. To better compensate for the economic costs of air pollution and reduce regional inequality, it would be beneficial to increase the tax rate nationwide and implement a levy mechanism based on provincially differentiated levels of consumption and economic status.

Not performing an OGTT results in underdiagnosis, inadequate risk assessment and probable cost increases of (pre)diabetes in Han Chinese over 40 years: a population-based prospective cohort study.

OBJECTIVE: To explore the influence by not performing an oral glucose tolerance test (OGTT) in Han Chinese over 40 years. DESIGN: Overall, 6682 participants were included in the prospective cohort study and were followed up for 3 years. METHODS: Fasting plasma glucose (FPG), 2-h post-load plasma glucose (2h-PG), FPG and 2h-PG (OGTT), and HbA1c testing using World Health Organization (WHO) or American Diabetes Association (ADA) criteria were employed for strategy analysis. RESULTS: The prevalence of diabetes is 12.4% (95% CI: 11.6-13.3), while the prevalence of prediabetes is 34.1% (95% CI: 32.9-35.3) and 56.5% (95% CI: 55.2-57.8) using WHO and ADA criteria, respectively. 2h-PG determined more diabetes individuals than FPG and HbA1c. The testing cost per true positive case of OGTT is close to FPG and less than 2h-PG or HbA1c. FPG, 2h-PG and HbA1c strategies would increase costs from complications for false-positive (FP) or false-negative (FN) results compared with OGTT. Moreover, the least individuals identified as normal by OGTT at baseline developed (pre)diabetes, and the most prediabetes individuals identified by HbA1c or FPG using ADA criteria developed diabetes. CONCLUSIONS: The prevalence of isolated impaired glucose tolerance and isolated 2-h post-load diabetes were high, and the majority of individuals with (pre)diabetes were undetected in Chinese Han population. Not performing an OGTT results in underdiagnosis, inadequate developing risk assessment and probable cost increases of (pre)diabetes in Han Chinese over 40 years and great consideration should be given to OGTT in detecting (pre)diabetes in this population. Further population-based prospective cohort study of longer-term effects is necessary to investigate the risk assessment and cost of (pre)diabetes.

Detection of Sources in Non-Negative Blind Source Separation by Minimum Description Length Criterion.

While non-negative blind source separation (nBSS) has found many successful applications in science and engineering, model order selection, determining the number of sources, remains a critical yet unresolved problem. Various model order selection methods have been proposed and applied to real-world data sets but with limited success, with both order over- and under-estimation reported. By studying existing schemes, we have found that the unsatisfactory results are mainly due to invalid assumptions, model oversimplification, subjective thresholding, and/or to assumptions made solely for mathematical convenience. Building on our earlier work that reformulated model order selection for nBSS with more realistic assumptions and models, we report a newly and formally revised model order selection criterion rooted in the minimum description length (MDL) principle. Adopting widely invoked assumptions for achieving a unique nBSS solution, we consider the mixing matrix as consisting of deterministic unknowns, with the source signals following a multivariate Dirichlet distribution. We derive a computationally efficient, stochastic algorithm to obtain approximate maximum-likelihood estimates of model parameters and apply Monte Carlo integration to determine the description length. Our modeling and estimation strategy exploits the characteristic geometry of the data simplex in nBSS. We validate our nBSS-MDL criterion through extensive simulation studies and on four real-world data sets, demonstrating its strong performance and general applicability to nBSS. The proposed nBSS-MDL criterion consistently detects the true number of sources, in all of our case studies.