Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation.

Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused by the rodent-transmitted orthohantaviruses (HVs), with China possessing the most cases globally. The virus hosts in China are Apodemus agrarius and Rattus norvegicus, and the disease spread is strongly influenced by global climate dynamics. To assess and predict the spatiotemporal trends of HFRS from 2005 to 2098, we collected historical HFRS data in mainland China (2005-2020), historical and projected climate and population data (2005-2098), and spatial variables including biotic, environmental, topographical, and socioeconomic. Spatiotemporal predictions and mapping were conducted under 27 scenarios incorporating multiple integrated representative concentration pathway models and population scenarios. We identify the type of magistral HVs host species as the best spatial division, including four region categories. Seven extreme climate indices associated with temperature and precipitation have been pinpointed as key factors affecting the trends of HFRS. Our predictions indicate that annual HFRS cases will increase significantly in 62 of 356 cities in mainland China. Rattus regions are predicted to be the most active, surpassing Apodemus and Mixed regions. Eighty cities are identified as at severe risk level for HFRS, each with over 50 reported cases annually, including 22 new cities primarily located in East China and Rattus regions after 2020, while 6 others develop new risk. Our results suggest that the risk of HFRS will remain high through the end of this century, with Rattus norvegicus being the most active host, and that extreme climate indices are significant risk factors. Our findings can inform evidence-based policymaking regarding future risk of HFRS.

No evidence for persistent natural plague reservoirs in historical and modern Europe.

Caused by Yersinia pestis, plague ravaged the world through three known pandemics: the First or the Justinianic (6th-8th century); the Second (beginning with the Black Death during c.1338-1353 and lasting until the 19th century); and the Third (which became global in 1894). It is debatable whether Y. pestis persisted in European wildlife reservoirs or was repeatedly introduced from outside Europe (as covered by European Union and the British Isles). Here, we analyze environmental data (soil characteristics and climate) from active Chinese plague reservoirs to assess whether such environmental conditions in Europe had ever supported "natural plague reservoirs". We have used new statistical methods which are validated through predicting the presence of modern plague reservoirs in the western United States. We find no support for persistent natural plague reservoirs in either historical or modern Europe. Two factors make Europe unfavorable for long-term plague reservoirs: 1) Soil texture and biochemistry and 2) low rodent diversity. By comparing rodent communities in Europe with those in China and the United States, we conclude that a lack of suitable host species might be the main reason for the absence of plague reservoirs in Europe today. These findings support the hypothesis that long-term plague reservoirs did not exist in Europe and therefore question the importance of wildlife rodent species as the primary plague hosts in Europe.

Country-specific determinants for COVID-19 case fatality rate and response strategies from a global perspective: an interpretable machine learning framework.

BACKGROUND: There are significant geographic inequities in COVID-19 case fatality rates (CFRs), and comprehensive understanding its country-level determinants in a global perspective is necessary. This study aims to quantify the country-specific risk of COVID-19 CFR and propose tailored response strategies, including vaccination strategies, in 156 countries. METHODS: Cross-temporal and cross-country variations in COVID-19 CFR was identified using extreme gradient boosting (XGBoost) including 35 factors from seven dimensions in 156 countries from 28 January, 2020 to 31 January, 2022. SHapley Additive exPlanations (SHAP) was used to further clarify the clustering of countries by the key factors driving CFR and the effect of concurrent risk factors for each country. Increases in vaccination rates was simulated to illustrate the reduction of CFR in different classes of countries. FINDINGS: Overall COVID-19 CFRs varied across countries from 28 Jan 2020 to 31 Jan 31 2022, ranging from 68 to 6373 per 100,000 population. During the COVID-19 pandemic, the determinants of CFRs first changed from health conditions to universal health coverage, and then to a multifactorial mixed effect dominated by vaccination. In the Omicron period, countries were divided into five classes according to risk determinants. Low vaccination-driven class (70 countries) mainly distributed in sub-Saharan Africa and Latin America, and include the majority of low-income countries (95.7%) with many concurrent risk factors. Aging-driven class (26 countries) mainly distributed in high-income European countries. High disease burden-driven class (32 countries) mainly distributed in Asia and North America. Low GDP-driven class (14 countries) are scattered across continents. Simulating a 5% increase in vaccination rate resulted in CFR reductions of 31.2% and 15.0% for the low vaccination-driven class and the high disease burden-driven class, respectively, with greater CFR reductions for countries with high overall risk (SHAP value > 0.1), but only 3.1% for the ageing-driven class. CONCLUSIONS: Evidence from this study suggests that geographic inequities in COVID-19 CFR is jointly determined by key and concurrent risks, and achieving a decreasing COVID-19 CFR requires more than increasing vaccination coverage, but rather targeted intervention strategies based on country-specific risks.

Climate factors and the East Asian summer monsoon may drive large outbreaks of dengue in China.

OBJECTIVE: To investigate the relationship between climate variables, East Asian summer monsoon (EASM) and large outbreaks of dengue in China. METHODS: We constructed ecological niche models (ENMs) to analyse the influence of climate factors on dengue occurrence and predict dengue outbreak areas in China. Furthermore, we formulated a generalised additive model (GAM) to quantify the impact of the EASM on dengue occurrence in mainland China from 1980 to 2016. RESULTS: Mean Temperature of Coldest Quarter had a 62.6% contribution to dengue outbreaks. Southern China including Guangdong, Guangxi, Fujian and Yunnan provinces are more vulnerable to dengue emergence and resurgence. In addition, we found population density had a 68.7% contribution to dengue widely distribution in China using ENMs. Statistical analysis indicated a dome-shaped association between EASM and dengue outbreak using GAM, with the greatest impact in the South-East of China. Besides, there was a positive nonlinear association between monthly average temperature and dengue occurrence. CONCLUSION: We demonstrated the influence of climate factors and East Asian summer monsoon on dengue outbreaks, providing a framework for future studies on the association between climate change and vector-borne diseases.

Scaled-Up Synthesis of Amorphous NiFeMo Oxides and Their Rapid Surface Reconstruction for Superior Oxygen Evolution Catalysis.

The anode oxygen evolution reaction (OER) is known to largely limit the efficiency of electrolyzers owing to its sluggish kinetics. While crystalline metal oxides are promising as OER catalysts, their amorphous phases also show high activities. Efforts to produce amorphous metal oxides have progressed slowly, and how an amorphous structure benefits the catalytic performances remains elusive. Now the first scalable synthesis of amorphous NiFeMo oxide (up to 515 g in one batch) is presented with homogeneous elemental distribution via a facile supersaturated co-precipitation method. In contrast to its crystalline counterpart, amorphous NiFeMo oxide undergoes a faster surface self-reconstruction process during OER, forming a metal oxy(hydroxide) active layer with rich oxygen vacancies, leading to superior OER activity (280 mV overpotential at 10 mA cm-2 in 0.1 m KOH). This opens up the potential of fast, facile, and scale-up production of amorphous metal oxides for high-performance OER catalysts.

Spatial distribution and ecological risk assessment of trace metals in urban soils in Wuhan, central China.

Surface soil samples from 467 sample sites were collected in urban area of Wuhan City in 2013, and total concentrations of five trace metals (Pb, Zn, Cu, Cr, and Cd) were measured. Multivariate and geostatistical analyses showed that concentrations of Pb, Zn, and Cu are higher along Yangtze River in the northern area of Wuhan, gradually decrease from city center to suburbs, and are mainly controlled by anthropogenic activities, while those of Cr and Cd are relatively spatially homogenous and mainly controlled by soil parent materials. Pb, Zn, Cu, and Cd have generally higher concentrations in roadsides, industrial areas, and residential areas than in school areas, greenbelts, and agricultural areas. Areas with higher road and population densities and longer urban construction history usually have higher trace metal concentrations. According to estimated results of the potential ecological risk index and Nemero synthesis pollution index, almost the whole urban area of Wuhan is facing considerable potential ecological risk caused by soil trace metals. These results reveal obvious trends of trace metal pollution, and an important impact of anthropogenic activities on the accumulation of trace metals in soil in Wuhan. Vehicular emission, industrial activities, and household wastes may be the three main sources for trace metal accumulation. Increasing vegetation cover may reduce this threat. It should be pointed out that Cd, which is strongly accumulated in soil, could be the largest soil pollution factor in Wuhan. Effective measures should be taken as soon as possible to deal with Cd enrichment, and other trace metals in soil should also be reduced, so as to protect human health in this important large city.

The efficacy and safety of Gukang Capsule for primary osteoporosis: a systematic review and meta-analysis of randomized clinical trial.

Background: Gukang Capsule has been used as a complementary and alternative medicine (CAM) for the treatment of primary osteoporosis (POP) in China. The primary aim of this study was to assess the clinical effectiveness and safety of Gukang Capsule in POP patients. Methods: A systematic search was conducted across multiple academic databases including PubMed, Web of science, Cochrane Library, China National Knowledge Infrastructure, Chongqing VIP Information, and Wanfang database to identify randomized controlled trials investigating the Gukang Capsule in the treatment of POP. The screening process, data extraction, and assessment of methodological quality were conducted independently by two reviewers. Statistical analysis was performed using the Rev Man 5.3 software. Subgroup analysis was carried out through the combination of OPF. Subgroup analysis was performed according to whether OPF were combined. Stata 12.0 was used for sensitivity and bias analysis. Results: Nineteen studies were assessed that included 1804 participants. It was found that compared with the control group, the total effective rate (RR = 1.26, 95% CI, 1.20, 1.33), the Medical Outcomes Study Short-form 36 [RR = 1.26, 95% CI(1.20, 1.33)], the bone mineral density (BMD) of lumbar vertebra (SMD = 0.77, 95% CI, 0.48, 1.07), the BMD of femoral neck [SMD = 0.84, 95% CI(0.53, 1.14)], and the BMD of Ward's triangle (SMD = 0.64, 95% CI, 0.44, 0.85) of the Gukang Capsule experimental group were higher. Compared with the control group, the fracture healing time (SMD = -2.14, 95% CI, -2.45, -1.84), the bone specific alkaline phosphatase (BALP) levels in serum (SMD = -2.00, 95% CI, -2.83, -1.17), the tartrate resistant acid phosphatase 5b (TRACP-5b) levels in serum (SMD = -2.58, 95% CI, -3.87, -1.29) of the Gukang Capsule experimental group were lower. The bone glaprotein (BGP) levels in serum (SMD = -0.22, 95% CI, -1.86, 1.43) and the adverse events (RR = 0.80, 95% CI, 0.40, 1.63) of the experimental group and the control group have no difference. Conclusion: Gukang Capsule, as a CAM for the management of POP, exhibits the potential to enhance BMD and quality of life, expedite the healing time of OPF, diminish levels of BALP and TRACP-5b, and improve the total effective rate without increasing the adverse events. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023477774, PROSPERO CRD42023477774.

A Multi-Modal Classification Method for Early Diagnosis of Mild Cognitive Impairment and Alzheimer's Disease Using Three Paradigms With Various Task Difficulties.

Alzheimer's Disease (AD) accounts for the majority of dementia, and Mild Cognitive Impairment (MCI) is the early stage of AD. Early and accurate diagnosis of dementia plays a vital role in more targeted treatments and effectively halting disease progression. However, the clinical diagnosis of dementia requires various examinations, which are expensive and require a high level of expertise from the doctor. In this paper, we proposed a classification method based on multi-modal data including Electroencephalogram (EEG), eye tracking and behavioral data for early diagnosis of AD and MCI. Paradigms with various task difficulties were used to identify different severity of dementia: eye movement task and resting-state EEG tasks were used to detect AD, while eye movement task and delayed match-to-sample task were used to detect MCI. Besides, the effects of different features were compared and suitable EEG channels were selected for the detection. Furthermore, we proposed a data augmentation method to enlarge the dataset, designed an extra ERPNet feature extract layer to extract multi-modal features and used domain-adversarial neural network to improve the performance of MCI diagnosis. We achieved an average accuracy of 88.81% for MCI diagnosis and 100% for AD diagnosis. The results of this paper suggest that our classification method can provide a feasible and affordable way to diagnose dementia.

Network pharmacology combined with experimental validation to investigate the effect of Rongjin Niantong Fang on chondrocyte apoptosis in knee osteoarthritis.

Knee osteoarthritis (KOA) is a chronic degenerative disease that affects the quality of life of middle­aged and elderly individuals, and is one of the major factors leading to disability. Rongjin Niantong Fang (RJNTF) can alleviate the clinical symptoms of patients with KOA, but the molecular mechanism underlying its beneficial effects on KOA remains unknown. Using pharmacological analysis and in vitro experiments, the active components of RJNTF were analyzed to explore their potential therapeutic targets and mechanisms in KOA. The potential targets and core signaling pathways by which RJNTF exerts its effects on KOA were obtained from databases such as Gene Expression Omnibus, Traditional Chinese Medicine Systems Pharmacology and Analysis Platform. Subsequently, chondrocyte apoptosis was modeled using hydrogen peroxide (H2O2). Cell Counting Kit­8 assay involving a poly [ADP­ribose] polymerase­1 (PARP1) inhibitor, DAPI staining, reverse transcription­quantitative PCR, Annexin V­FITC/PI staining and flow cytometry, western blotting and co­immunoprecipitation analysis were used to determine the therapeutic efficacy of RJNTF on KOA and to uncover the molecular mechanism. It was found that PARP1­knockdown lentivirus, incubation with PARP1 inhibitor PJ34, medium and high doses of RJNTF significantly reduced H2O2­induced chondrocyte apoptosis. Medium and high doses of RJNTF downregulated the expression of cleaved caspase­3, cleaved PARP1 and PAR total proteins, as well as nucleus proteins of apoptosis­inducing factor (AIF) and migration inhibitory factor (MIF), and upregulated the expression of caspase­3, PARP1 total protein, as well as the cytoplasmic expression of AIF and MIF, suggesting that RJNTF may inhibit chondrocyte apoptosis through the PARP1/AIF signaling pathway.

Progress on Prevention and Treatment of Cerebral Small Vascular Disease Using Integrative Medicine.

Cerebral small vessel disease (CSVD) is a senile brain lesion caused by the abnormal structure and function of arterioles, venules and capillaries in the aging brain. The etiology of CSVD is complex, and disease is often asymptomatic in its early stages. However, as CSVD develops, brain disorders may occur, such as stroke, cognitive dysfunction, dyskinesia and mood disorders, and heart, kidney, eye and systemic disorders. As the population continues to age, the burden of CSVD is increasing. Moreover, there is an urgent need for better screening methods and diagnostic markers for CSVD, in addition to preventive and asymptomatic- and mild-stage treatments. Integrative medicine (IM), which combines the holistic concepts and syndrome differentiations of Chinese medicine with modern medical perspectives, has unique advantages for the prevention and treatment of CSVD. In this review, we summarize the biological markers, ultrasound and imaging features, disease-related genes and risk factors relevant to CSVD diagnosis and screening. Furthermore, we discuss IM-based CSVD prevention and treatment strategies to stimulate further research in this field.

The role of booster vaccination in decreasing COVID-19 age-adjusted case fatality rate: Evidence from 32 countries.

Background: The global COVID-19 pandemic is still ongoing, and cross-country and cross-period variation in COVID-19 age-adjusted case fatality rates (CFRs) has not been clarified. Here, we aimed to identify the country-specific effects of booster vaccination and other features that may affect heterogeneity in age-adjusted CFRs with a worldwide scope, and to predict the benefit of increasing booster vaccination rate on future CFR. Method: Cross-temporal and cross-country variations in CFR were identified in 32 countries using the latest available database, with multi-feature (vaccination coverage, demographic characteristics, disease burden, behavioral risks, environmental risks, health services and trust) using Extreme Gradient Boosting (XGBoost) algorithm and SHapley Additive exPlanations (SHAP). After that, country-specific risk features that affect age-adjusted CFRs were identified. The benefit of booster on age-adjusted CFR was simulated by increasing booster vaccination by 1-30% in each country. Results: Overall COVID-19 age-adjusted CFRs across 32 countries ranged from 110 deaths per 100,000 cases to 5,112 deaths per 100,000 cases from February 4, 2020 to Jan 31, 2022, which were divided into countries with age-adjusted CFRs higher than the crude CFRs and countries with age-adjusted CFRs lower than the crude CFRs (n = 9 and n = 23) when compared with the crude CFR. The effect of booster vaccination on age-adjusted CFRs becomes more important from Alpha to Omicron period (importance scores: 0.03-0.23). The Omicron period model showed that the key risk factors for countries with higher age-adjusted CFR than crude CFR are low GDP per capita and low booster vaccination rates, while the key risk factors for countries with higher age-adjusted CFR than crude CFR were high dietary risks and low physical activity. Increasing booster vaccination rates by 7% would reduce CFRs in all countries with age-adjusted CFRs higher than the crude CFRs. Conclusion: Booster vaccination still plays an important role in reducing age-adjusted CFRs, while there are multidimensional concurrent risk factors and precise joint intervention strategies and preparations based on country-specific risks are also essential.

Graph Reasoning Module for Alzheimer's Disease Diagnosis: A Plug-and-Play Method.

Recent advances in deep learning have led to increased adoption of convolutional neural networks (CNN) for structural magnetic resonance imaging (sMRI)-based Alzheimer's disease (AD) detection. AD results in widespread damage to neurons in different brain regions and destroys their connections. However, current CNN-based methods struggle to relate spatially distant information effectively. To solve this problem, we propose a graph reasoning module (GRM), which can be directly incorporated into CNN-based AD detection models to simulate the underlying relationship between different brain regions and boost AD diagnosis performance. Specifically, in GRM, an adaptive graph Transformer (AGT) block is designed to adaptively construct a graph representation based on the feature map given by CNN, a graph convolutional network (GCN) block is adopted to update the graph representation, and a feature map reconstruction (FMR) block is built to convert the learned graph representation to a feature map. Experimental results demonstrate that the insertion of the GRM in the existing AD classification model can increase its balanced accuracy by more than 4.3%. The GRM-embedded model achieves state-of-the-art performance compared with current deep learning-based AD diagnosis methods, with a balanced accuracy of 86.2%.

Comparing Multi-Dimensional fNIRS Features Using Bayesian Optimization-Based Neural Networks for Mild Cognitive Impairment (MCI) Detection.

The diagnosis of mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease (AD), is essential for initiating timely treatment to delay the onset of AD. Previous studies have shown the potential of functional near-infrared spectroscopy (fNIRS) for diagnosing MCI. However, preprocessing fNIRS measurements requires extensive experience to identify poor-quality segments. Moreover, few studies have explored how proper multi-dimensional fNIRS features influence the classification results of the disease. Thus, this study outlined a streamlined fNIRS preprocessing method to process fNIRS measurements and compared multi-dimensional fNIRS features with neural networks in order to explore how temporal and spatial factors affect the classification of MCI and cognitive normality. More specifically, this study proposed using Bayesian optimization-based auto hyperparameter tuning neural networks to evaluate 1D channel-wise, 2D spatial, and 3D spatiotemporal features of fNIRS measurements for detecting MCI patients. The highest test accuracies of 70.83%, 76.92%, and 80.77% were achieved for 1D, 2D, and 3D features, respectively. Through extensive comparisons, the 3D time-point oxyhemoglobin feature was proven to be a more promising fNIRS feature for detecting MCI by using an fNIRS dataset of 127 participants. Furthermore, this study presented a potential approach for fNIRS data processing, and the designed models required no manual hyperparameter tuning, which promoted the general utilization of fNIRS modality with neural network-based classification to detect MCI.

Monkeypox outbreaks in the context of the COVID-19 pandemic: Network and clustering analyses of global risks and modified SEIR prediction of epidemic trends.

Background: Ninety-eight percent of documented cases of the zoonotic disease human monkeypox (MPX) were reported after 2001, with especially dramatic global spread in 2022. This longitudinal study aimed to assess spatiotemporal risk factors of MPX infection and predict global epidemiological trends. Method: Twenty-one potential risk factors were evaluated by correlation-based network analysis and multivariate regression. Country-level risk was assessed using a modified Susceptible-Exposed-Infectious-Removed (SEIR) model and a risk-factor-driven k-means clustering analysis. Results: Between historical cases and the 2022 outbreak, MPX infection risk factors changed from relatively simple [human immunodeficiency virus (HIV) infection and population density] to multiple [human mobility, population of men who have sex with men, coronavirus disease 2019 (COVID-19) infection, and socioeconomic factors], with human mobility in the context of COVID-19 being especially key. The 141 included countries classified into three risk clusters: 24 high-risk countries mainly in West Europe and Northern America, 70 medium-risk countries mainly in Latin America and Asia, and 47 low-risk countries mainly in Africa and South Asia. The modified SEIR model predicted declining transmission rates, with basic reproduction numbers ranging 1.61-7.84 in the early stage and 0.70-4.13 in the current stage. The estimated cumulative cases in Northern and Latin America may overtake the number in Europe in autumn 2022. Conclusions: In the current outbreak, risk factors for MPX infection have changed and expanded. Forecasts of epidemiological trends from our modified SEIR models suggest that Northern America and Latin America are at greater risk of MPX infection in the future.

Yersinia pestis and Plague: some knowns and unknowns.

Since its first identification in 1894 during the third pandemic in Hong Kong, there has been significant progress of understanding the lifestyle of Yersinia pestis, the pathogen that is responsible for plague. Although we now have some understanding of the pathogen's physiology, genetics, genomics, evolution, gene regulation, pathogenesis and immunity, there are many unknown aspects of the pathogen and its disease development. Here, we focus on some of the knowns and unknowns relating to Y. pestis and plague. We notably focus on some key Y. pestis physiological and virulence traits that are important for its mammal-flea-mammal life cycle but also its emergence from the enteropathogen Yersinia pseudotuberculosis. Some aspects of the genetic diversity of Y. pestis, the distribution and ecology of plague as well as the medical countermeasures to protect our population are also provided. Lastly, we present some biosafety and biosecurity information related to Y. pestis and plague.

Dendrobium mixture ameliorates hepatic injury induced by insulin resistance in vitro and in vivo through the downregulation of AGE/RAGE/Akt signaling pathway.

Dendrobium mixture (DM) is a patented Chinese herbal medicine which has been shown to ameliorate type 2 diabetes mellitus (T2DM) with non-alcoholic fatty liver disease (NAFLD) in vivo and in vitro. We aimed to investigate the underlying mechanism of DM as a therapeutic agent in attenuating liver steatosis in relation to type 2 diabetes mellitus (T2DM). DM (16.2 g/kg/d) was administered to db/db mice for 4 weeks. The db/m mice and db/db mice in the control and model groups were given normal saline. Additionally, DM (11.25 g/kg/d) was administered to Sprague-Dawley (SD) rats, and the serum was collected and used in an experiment involving palmitic acid (PA)-induced human liver HepG2 cells with abnormal lipid and glucose metabolism. In db/db mice, the administration of DM significantly alleviated liver steatosis, including histological damage and cell apoptosis. DM was found to prevent the upregulation of the RAGE and AKT1 proteins in liver tissues. The underlying mechanism of DM was further studied in PA-induced HepG2 cells. Post-DM administration serum from SD rats reduced lipid accumulation and regulated glucose metabolism in HepG2 cells. Consequently, it inhibited RAGE/AKT signaling and restored autophagy activity. The upregulated autophagy was associated with the mTOR-AMPK signaling pathway. Furthermore, post-DM administration serum reduced apoptosis of hepatocytes in PA-induced HepG2 cells. Our study supports the potential use of DM as a therapeutic agent for the treatment of NAFLD in T2DM. The mechanism underlying this therapeutic potential is associated with the downregulation of the AGE/RAGE/Akt signaling pathway.

Inverse design of chiral functional films by a robotic AI-guided system.

Artificial chiral materials and nanostructures with strong and tuneable chiroptical activities, including sign, magnitude, and wavelength distribution, are useful owing to their potential applications in chiral sensing, enantioselective catalysis, and chiroptical devices. Thus, the inverse design and customized manufacturing of these materials is highly desirable. Here, we use an artificial intelligence (AI) guided robotic chemist to accurately predict chiroptical activities from the experimental absorption spectra and structure/process parameters, and generate chiral films with targeted chiroptical activities across the full visible spectrum. The robotic AI-chemist carries out the entire process, including chiral film construction, characterization, and testing. A machine learned reverse design model using spectrum embedded descriptors is developed to predict optimal structure/process parameters for any targeted chiroptical property. A series of chiral films with a dissymmetry factor as high as 1.9 (gabs ~ 1.9) are identified out of more than 100 million possible structures, and their feasible application in circular polarization-selective color filters for multiplex laser display and switchable circularly polarized (CP) luminescence is demonstrated. Our findings not only provide chiral films with the highest reported chiroptical activity, but also have great fundamental value for the inverse design of chiroptical materials.

Jiangu granule ameliorated OVX rats bone loss by modulating gut microbiota-SCFAs-Treg/Th17 axis.

BACKGROUND: Postmenopausal osteoporosis (PMOP) is a common disease that has decreased bone strength as its main symptom after menopause. Effective treatment for PMOP remains lacking, but traditional Chinese medicine has some advantages in delaying bone loss. Jiangu granule is a traditional Chinese medicine prescription commonly used to treat PMOP. Previous studies have demonstrated its efficacy, but the mechanism of action remains uncharacterized. PURPOSE: This study aims to observe and discuss the mechanism of Jiangu granule to ameliorate bone loss in OVX rats by regulating the gut microbiota (GM)-short-chain fatty acids (SCFAs)- Treg/Th17 axis. METHODS: Female SD rats were divided into the sham operation (S), Jiangu granule (J), and model group (M). Bilateral ovaries were surgically removed from the rats in the J and M groups. After 6 and 12 weeks, rats were sacrificed, and femur, tibia, vertebrae, serum, spleen, colon, and feces samples were collected. We detected the strength of bones, gut microbiota structure, and SCFAs in feces, the Treg and Th17 cell levels in the spleen, and cytokine levels in the serum. RESULT: Jiangu granule restored the abundance of gut microbiota, increased the content of SCFAs, reduced the permeability of colon epithelium, increased the proportion of Treg cells in the spleen, changed the osteoimmunomodulation-related cytokines, effectively prevented bone loss, and enhanced bone strength. CONCLUSION: Jiangu granule can effectively improve bone loss in OVX rats, possibly by regulating the "GM-SCFAs-Treg/Th17″ axis.

Abundance and characteristics of microplastics in the surface water and sediment of parks in Xi'an city, Northwest China.

Microplastics (MPs), as a new type of pollutants, have attracted wide attention especially in recent years, but there was insufficient research on the distribution and characteristics of MPs in urban park water body. In this study, the pollution of MPs in water and sediment of Xi'an, the largest city in northwest China, was investigated. The MPs concentration in the surface water and sediment was 2900-6970 items/m3 and 940-3560 items/kg, respectively. According to the urban functions, the parks were divided into residential areas, commercial areas, tourism areas and industrial areas, and the highest abundance of MPs was observed in the tourism and residential areas, suggesting the impacts of human activities. MPs in these parks were mainly in four kinds of shapes, namely fiber, pellet, fragment and film, and dominated by fibers and fragments. Most of the extracted MPs were small in size, and 63-92% of them were smaller than 0.5 mm. Polypropylene and polyethylene terephthalate were the main polymer types in surface water and sediments, respectively. This study showed that the park water and sediment can be used as an important "sink" in MPs, which is of great significance for monitoring and alleviating the pollution of urban MPs. This study provided important reference for better understanding MPs levels in inland freshwaters.