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Summary: Background: Previous conventional epidemiological studies found a J-shape relationship between alcohol consumption and dementia, but this result was subject to confounding biases and reverse causation. Therefore, we aimed to investigate the potential linear or non-linear causal association between alcohol consumption and the incident risk of dementia in current drinkers. Methods: This study used data from the UK Biobank to investigate the relationship between alcohol consumption and dementia risk. 313,958 White British current drinkers, who were free of dementia during 2006–2010, were followed up until 2021. Alcohol consumption was self-reported and calculated according to the National Health Service guideline. The primary outcome was all-cause dementia identified through hospital and mortality records. We used multivariable Cox models with restricted cubic splines for conventional analysis and both non-linear and linear Mendelian Randomization (MR) analyses to assess causal relationships, employing a genetic score based on 95 SNPs identified from a meta-genome-wide association study of 941,280 people from Europe. Findings: 313,958 current drinkers consumed an average of 13.6 [IQR: 7.1–25.2] units/week alcohol (men averaged 20.2 [11.1–33.9] units/week and women 9.5 [5.3–16.7] units/week). During a mean follow-up of 13.2 years, 5394 (1.7%) developed dementia. Multivariable Cox model with restricted cubic spline functions identified a J-shaped relationship between alcohol consumption and dementia risk, with the lowest risk at 12.2 units/week. The non-linear MR failed to identify a significant non-linear causal relationship (p = 0.45). Both individual-level (HR: 2.22 95%CI [1.06–4.66]) and summary-level (1.89 [1.53–2.32]) linear MR analyses indicated that higher genetically predicted alcohol consumption increased dementia risk. Interpretation: This study identified a positive linear causal relationship between alcohol consumption and dementia among current drinkers. The J-shaped association found in conventional epidemiological analysis was not supported by non-linear MR analyses. Our findings suggested that there was no safe level of alcohol consumption for dementia. Funding: The Shenzhen Science and Technology Program and the Strategic Priority Research Program of Chinese Academy of Sciences.

Summary: Background: How often hypertensive patients could achieve remission to normal blood pressure (BP) (i.e.,

Abstract Background Chronic inflammation and insulin resistance are highly prevalent in patients on maintenance haemodialysis (MHD) and are strongly associated with protein energy wasting. We conducted a pilot, randomized, placebo‐controlled trial of recombinant human interleukin‐1 receptor antagonist (IL‐1ra) and pioglitazone to explore the safety, feasibility and efficacy for insulin‐mediated protein metabolism in patients undergoing MHD. Methods Twenty‐four patients were randomized to receive IL‐1ra, pioglitazone or placebo for 12 weeks. Changes in serum inflammatory markers and insulin‐mediated protein synthesis, breakdown and net balance in the whole‐body and skeletal muscle compartments were assessed using hyperinsulinaemic–hyperaminoacidemic clamp technique at baseline and Week 12. Results Among 24 patients, median (interquartile range) age was 51 (40, 61), 79% were African American and 21% had diabetes mellitus. All patients initiated on intervention completed the study, and no serious adverse events were observed. There was a statistically significant decrease in serum high‐sensitivity C‐reactive protein in the pioglitazone group compared with placebo, but not in the IL‐1ra group. No significant differences in the changes of whole‐body or skeletal muscle protein synthesis, breakdown and net balance were found between the groups. Conclusions In this pilot study, there were no statistically significant effects of 12 weeks of IL‐1ra or pioglitazone on protein metabolism in patients on MHD. Clinicaltrials.gov registration: NCT02278562.

The classification of fetuses as Small for Gestational Age (SGA) and Large for Gestational Age (LGA) is a critical aspect of neonatal health assessment. SGA and LGA, terms used to describe fetal weights that fall below or above the expected weights for Appropriate for Gestational Age (AGA) fetuses, indicate intrauterine growth restriction and excessive fetal growth, respectively. Early prediction and assessment of latent risk factors associated with these classifications can facilitate timely medical interventions, thereby optimizing the health outcomes for both the infant and the mother. This study aims to leverage first-trimester data to achieve these objectives. This study analyzed data from 7943 pregnant women, including 424 SGA, 928 LGA, and 6591 AGA cases, collected from 2015 to 2021 at the Third Affiliated Hospital of Sun Yat-sen University in Guangzhou, China. We propose a novel algorithm, named the Weighted Inheritance Voting Ensemble Learning Algorithm (WIVELA), to predict the classification of fetuses into SGA, LGA, and AGA categories based on biochemical parameters, maternal factors, and morbidity during pregnancy. Additionally, we proposed algorithms for relevance determination based on the classifier to ascertain the importance of features associated with SGA and LGA. The proposed classification solution demonstrated a notable average accuracy rate of 92.12% on 10-fold cross-validation over 100 loops, outperforming five state-of-the-art machine learning algorithms. Furthermore, we identified significant latent maternal risk factors directly associated with SGA and LGA conditions, such as weight change during the first trimester, prepregnancy weight, height, age, and obstetric factors like fetal growth restriction and birthing LGA baby. This study also underscored the importance of biomarker features at the end of the first trimester, including HDL, TG, OGTT-1h, OGTT-0h, OGTT-2h, TC, FPG, and LDL, which reflect the status of SGA or LGA fetuses. This study presents innovative solutions for classifying and identifying relevant attributes, offering valuable tools for medical teams in the clinical monitoring of fetuses predisposed to SGA and LGA conditions during the initial stage of pregnancy. These proposed solutions facilitate early intervention in nutritional care and prenatal healthcare, thereby contributing to enhanced strategies for managing the health and well-being of both the fetus and the expectant mother.

Summary: Background: Constipation is generally considered a common physical symptom of depression or a side effect of antidepressant treatments. However, according to the gut-brain axis hypothesis, the association between depression and constipation might be bi-directional. This study investigated the association between premorbid constipation and depression. Methods: We conducted a retrospective cohort study using data from UK Biobank. Individuals free of depression between 2006 and 2010 were included. Constipation status was determined using diagnostic codes from electronic health records or a baseline questionnaire. Data on covariates, including socio-demographic characteristics, lifestyle factors, health conditions, and regular medication use, were also collected through a baseline questionnaire. The primary outcome is incident depression, which was extracted from hospital inpatient admissions, primary care, self-report, and death data from baseline to 2022. The secondary outcome is depressive symptoms, which was assessed by Patient Health Questionnaire–9 (PHQ-9) from an online survey in 2016. Cox proportional hazard regression models were employed to assess the prospective association between constipation and incident depression. Logistic regression models were used to assess its association with depressive symptoms. Findings: Among the 449,459 participants included in the study, 18,596 (4.1%) experienced constipation at baseline, and 18,576 (4.1%) developed depression over a median follow-up period of 12.3 years. Premorbid constipation is associated with a 2.28-fold higher risk of depression. After adjusting the covariates, we found those with constipation still had a 48% higher risk of developing depression (adjusted hazard ratio [aHR] 1.48; 95% CI, 1.41–1.56) than those without constipation. Self-reported and diagnosed constipation were both associated with a higher risk of depression, with the aHR being 1.42 (95% CI: 1.34–1.51) and 1.66 (95% CI: 1.51–1.82), respectively. Participants with constipation were more likely to report depressive symptoms than people without (adjusted odds ratio 2.18; 95% CI, 1.97–2.43). These findings remained consistent in sensitivity analyses. Interpretation: Diagnosed and self-reported constipation are both prospectively associated with an elevated risk of depression. These explorative findings suggest that constipation may be an independent risk factor or a prodromal symptom of depression. Gastroenterologists and primary care physicians should pay more attention to the depressive symptoms of their constipation patients. Funding: The Shenzhen Science and Technology Program and the Strategic Priority Research Program of Chinese Academy of Sciences.

The significant differences in data domains between SAR images and the expensive and time-consuming process of data labeling pose significant challenges to terrain classification. Current terrain classification methodologies face challenges in addressing domain disparities and detecting uncommon terrain effectively. Based on Style Transformation and Domain Metrics (STDMs), we propose an unsupervised domain adaptive framework named STDM-UDA for terrain classification in this paper, which consists of two steps: image style transfer and domain adaptive segmentation. As a first step, image style transfer is performed within the image space to mitigate the differences in low-level features between SAR image domains. Subsequently, leveraging this process, the segmentation network extracts image features, employing domain metrics and adversarial training to enhance alignment between domain gaps in the semantic feature space. Finally, experiments conducted on several pairs of SAR images, each exhibiting varying degrees of differences in key imaging parameters such as source, resolution, band, and polarization, demonstrate the robustness of the proposed method. It achieves remarkably competitive classification accuracy, particularly for unlabeled, high-resolution broad scenes, effectively overcoming the domain gaps introduced by the diverse imaging parameters under studies.

Effective features play an important role in synthetic aperture radar (SAR) image interpretation. However, since SAR images contain a variety of terrain types, it is not easy to extract effective features of different terrains from SAR images. Deep learning methods require a large amount of labeled data, but the difficulty of SAR image annotation limits the performance of deep learning models. SAR images have inevitable geometric distortion and coherence speckle noise, which makes it difficult to extract effective features from SAR images. If effective semantic context features cannot be learned for SAR images, the extracted features struggle to distinguish different terrain categories. Some existing terrain classification methods are very limited and can only be applied to some specified SAR images. To solve these problems, a jigsaw puzzle self-supervised learning (JPSSL) framework is proposed. The framework comprises a jigsaw puzzle pretext task and a terrain classification downstream task. In the pretext task, the information in the SAR image is learned by completing the SAR image jigsaw puzzle to extract effective features. The terrain classification downstream task is trained using only a small number of labeled data. Finally, fully connected conditional random field processing is performed to eliminate noise points and obtain a high-quality terrain classification result. Experimental results on three large-scene high-resolution SAR images confirm the effectiveness and generalization of our method. Compared with the supervised methods, the features learned in JPSSL are highly discriminative, and the JPSSL achieves good classification accuracy when using only a small amount of labeled data.

The theoretical innovation of adapting Marxism to the Chinese context has put forth a novel concept of green development, signifying a new phase of adapting Marxism to the Chinese contest and needs of the times. Currently, there is a pressing need for in-depth research and understanding of the inherent essence and connotations of green development. Capitalizing on a macroscopic and forward-thinking strategy is essential to explore the new trends, characteristics, and tendencies of green development in the new era. Identifying the objective existence of practical issues in the field of green development, conducting a thorough analysis of the root causes, and proposing corresponding measures are imperative for more effective implementation of the green development concept. This effort aims to contribute to realizing the dream of the great rejuvenation of the Chinese nation in Contemporary Times.

In the biomedical field, the time interval from infection to medical diagnosis is a random variable that obeys the log-normal distribution in general. Inspired by this biological law, we propose a novel back-projection infected–susceptible–infected-based long short-term memory (BPISI-LSTM) neural network for pandemic prediction. The multimodal data, including disease-related data and migration information, are used to model the impact of social contact on disease transmission. The proposed model not only predicts the number of confirmed cases, but also estimates the number of infected cases. We evaluate the proposed model on the COVID-19 datasets from India, Austria, and Indonesia. In terms of predicting the number of confirmed cases, our model outperforms the latest epidemiological modeling methods, such as vSIR, and intelligent algorithms, such as LSTM, for both short-term and long-term predictions, which shows the superiority of bio-inspired intelligent algorithms. In general, the use of mobility information improves the prediction accuracy of the model. Moreover, the number of infected cases in these three countries is also estimated, which is an unobservable but crucial indicator for the control of the pandemic.

Directly linked porphyrin dimers show intriguing electronic features but emphasis has been placed on planar monomeric units. Here, the authors report a Twisted-Planar-Twisted framework which can undergo a cis-trans transformation accompanied by a colour change in presence of methanol, making this framework applicable as a methanol sensor.

Summary: Background: Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. Methods: We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. Findings: We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4–65·1) million cases globally in 2019 to 152·8 (130·8–175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [–7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64–1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52–1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41–67]) and western Europe (74% [58–90]), and the largest in north Africa and the Middle East (367% [329–403]) and eastern sub-Saharan Africa (357% [323–395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia. Interpretation: Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia. Funding: Bill & Melinda Gates Foundation and Gates Ventures.

Introduction The current study determined the level and trends associated with the incidence, death and disability rates for bladder cancer and its attributable risk factors in 204 countries and territories, from 1990 to 2019, by age, sex and sociodemographic index (SDI; a composite measure of sociodemographic factors).Methods Various data sources from different countries, including vital registration and cancer registries were used to generate estimates. Mortality data and incidence data transformed to mortality estimates using the mortality to incidence ratio (MIR) were used in a cause of death ensemble model to estimate mortality. Mortality estimates were divided by the MIR to produce incidence estimates. Prevalence was calculated using incidence and MIR-based survival estimates. Age-specific mortality and standardised life expectancy were used to estimate years of life lost (YLLs). Prevalence was multiplied by disability weights to estimate years lived with disability (YLDs), while disability-adjusted life years (DALYs) are the sum of the YLLs and YLDs. All estimates were presented as counts and age-standardised rates per 100 000 population.Results Globally, there were 524 000 bladder cancer incident cases (95% uncertainty interval 476 000 to 569 000) and 229 000 bladder cancer deaths (211 000 to 243 000) in 2019. Age-standardised death rate decreased by 15.7% (8.6 to 21.0), during the period 1990–2019. Bladder cancer accounted for 4.39 million (4.09 to 4.70) DALYs in 2019, and the age-standardised DALY rate decreased significantly by 18.6% (11.2 to 24.3) during the period 1990–2019. In 2019, Monaco had the highest age-standardised incidence rate (31.9 cases (23.3 to 56.9) per 100 000), while Lebanon had the highest age-standardised death rate (10.4 (8.1 to 13.7)). Cabo Verde had the highest increase in age-standardised incidence (284.2% (214.1 to 362.8)) and death rates (190.3% (139.3 to 251.1)) between 1990 and 2019. In 2019, the global age-standardised incidence and death rates were higher among males than females, across all age groups and peaked in the 95+ age group. Globally, 36.8% (28.5 to 44.0) of bladder cancer DALYs were attributable to smoking, more so in males than females (43.7% (34.0 to 51.8) vs 15.2% (10.9 to 19.4)). In addition, 9.1% (1.9 to 19.6) of the DALYs were attributable to elevated fasting plasma glucose (FPG) (males 9.3% (1.6 to 20.9); females 8.4% (1.6 to 19.1)).Conclusions There was considerable variation in the burden of bladder cancer between countries during the period 1990–2019. Although there was a clear global decrease in the age-standardised death, and DALY rates, some countries experienced an increase in these rates. National policy makers should learn from these differences, and allocate resources for preventative measures, based on their country-specific estimates. In addition, smoking and elevated FPG play an important role in the burden of bladder cancer and need to be addressed with prevention programmes.

Abstract Background Cystinuria is an inherited disorder of renal amino acid transport that causes recurrent nephrolithiasis and significant morbidity in humans. It has an incidence of 1 in 7000 worldwide making it one of the most common genetic disorders in man. We phenotypically characterized a mouse model of cystinuria type A resultant from knockout of Slc3a1. Methods Knockout of Slc3a1 at RNA and protein levels was evaluated using real-time quantitative PCR and immunofluorescence. Slc3a1 knockout mice were placed on normal or breeder chow diets and evaluated for cystine stone formation over time suing x-ray analysis, and the development of kidney injury by measuring injury biomarkers. Kidney injury was also evaluated via histologic analysis. Amino acid levels were measured in the blood of mice using high performance liquid chromatography. Liver glutathione levels were measured using a luminescent-based assay. Results We confirmed knockout of Slc3a1 at the RNA level, while Slc7a9 RNA representing the co-transporter was preserved. As expected, we observed bladder stone formation in Slc3a1 −/− mice. Male Slc3a1 −/− mice exhibited lower weights compared to Slc3a1 +/+. Slc3a1 −/− mice on a regular diet demonstrated elevated blood urea nitrogen (BUN) without elevation of serum creatinine. However, placing the knockout animals on a breeder chow diet, containing a higher cystine concentration, resulted in the development of elevation of both BUN and creatinine indicative of more severe chronic kidney disease. Histological examination revealed that these dietary effects resulted in worsened kidney tubular obstruction and interstitial inflammation as well as worsened bladder inflammation. Cystine is a precursor for the antioxidant molecule glutathione, so we evaluated glutathione levels in the livers of Slc3a1 −/− mice. We found significantly lowered levels of both reduced and total glutathione in the knockout animals. Conclusions Our results suggest that that diet can affect the development and progression of chronic kidney disease in an animal model of cystinuria, which may have important implications for patients with this disease. Additionally, reduced glutathione may predispose those with cystinuria to injury caused by oxidative stress. Word count: 327.

Abstract Background The decreasing suicide rate in China has been regarded as a major contributor to the decline of global suicide rate in the past decade. However, previous estimations on China’s suicide rates might not be accurate, since often they were based on the data from the Ministry of Health’s Vital Registration (“MOH-VR”) System, which is biased towards the better-off population. This study aims to compare suicide data extracted from the MOH-VR System with a more representative mortality surveillance system, namely the Center for Disease Control and Prevention’s Disease Surveillance Points (“CDC-DSP”) System, and update China’s national and subnational suicide rates in the period of 2004–2014. Methods The CDC-DSP data are obtained from the National Cause-of-Death Surveillance Dataset (2004–2014) and the MOH-VR data are from the Chinese Health Statistics Yearbooks (2005–2012) and the China Health and Family Planning Statistics Yearbooks (2013–2015). First, a negative binomial regression model was used to test the associations between the source of data (CDC-DSP/MOH-VR) and suicide rates in 2004–2014. Joinpoint regression analyses and Kitagawa’s decomposition method are then applied to analyze the trends of the crude suicide rates. Results Both systems indicated China’s suicide rates decreased over the study period. However, before the two systems merged in 2013, the CDC-DSP System reported significantly higher national suicide rates (IRR = 1.18, 95% Confidence Interval [CI]: 1.13–1.24) and rural suicide rates (IRR = 1.29, 95% CI: 1.21–1.38) than the MOH-VR System. The CDC-DSP System also showed significant reversing points in 2011 (95% CI: 2006–2012) and 2006 (95% CI: 2006–2008) on the rural and urban suicide trends. Moreover, the suicide rates in the east and central urban regions were reversed in 2011 and 2008. Conclusions The biased MOH-VR System underestimated China’s national and rural suicide rates. Although not widely appreciated in the field of suicide research, the CDC-DSP System provides more accurate estimations on China’s suicide rates and is recommended for future studies to monitor the reversing trends of suicide rates in China’s more developed areas.

We here report a new CO2 capture and storage method that converts CO2 into a novel alkyl carbonate salt, denoted as CO2SM, by a system consisting of equimolar 1,4-butanediol (BDO) and 1,2-ethylenediamine (EDA). This novel CO2SM was then used to prepare BaCO3 crystals through a simple and fast hydrothermal synthesis under mild conditions. The CO2SM was both the source of CO2 and the modifier to regulate the nucleation and growth of BaCO3 crystals. The morphology of the BaCO3 crystals could be tuned from rod to shuttle by adjusting the key influencing factors, including CO2SM concentration, mineralization temperature, and mineralization time. A possible mechanism for the synthesis of BaCO3 crystals from the CO2SM was also presented. After the BaCO3 crystals were isolated, the filtrate of the hydrothermal reaction could be recycled to again absorb CO2 and prepare BaCO3 crystals of the same polymorph. This novel approach appears promising for preparing well-formed metal carbonates. Keywords: BaCO3, CO2-storage material, Morphology control, CO2 capture and utilization

Previous investigations of geographic concentration of urban poverty indicate the contribution of a variety of factors, such as economic restructuring and class-based segregation, racial segregation, demographic structure, and public policy. However, the models used by most past research do not consider the possibility that poverty concentration may take different forms in different locations across a city, and most studies have been conducted in Western settings. We investigated the spatial patterning of neighborhood poverty and its correlates in Hong Kong, which is amongst cities with the highest GDP in the region, using the city-wide ordinary least square (OLS) regression model and the local-specific geographically weighted regression (GWR) model. We found substantial geographic variations in small-area poverty rates and identified several poverty clusters in the territory. Factors found to contribute to urban poverty in Western cities, such as socioeconomic factors, ethnicity, and public housing, were also mostly associated with local poverty rates in Hong Kong. Our results also suggest some heterogeneity in the associations of poverty with specific correlates (e.g. access to hospitals) that would be masked in the city-wide OLS model. Policy aimed to alleviate poverty should consider both city-wide and local-specific factors.

OBJECTIVE:This present study aims to estimate the structural validity, internal consistency reliability of the LSNS-6 and examine the associations between the LSNS-6 and suicidal outcomes among mainland Chinese older adults. METHODS:This validation study used a big representative sample (N = 2819) of older adults in Beijing from the Sample Survey on Aged Population in Urban/Rural China. Confirmatory factor analyses (CFA) were applied to examine the factor structures of the Chinese version of LSNS-6. Internal consistency reliability of the LSNS-6 was examined by Cronbach's alpha coefficient and the corrected item-total correlation. Logistic regression analyses were used to explore the associations between the LSNS-6 and late-life death wishes, suicidal ideation in mainland Chinese. FINDINGS:This present study showed good internal consistency and consistent factor structure of the LSNS-6 as well as its subscales. The present data demonstrated the LSNS-6 could be a useful tool for assessing social networks among older mainland Chinese. Interestingly, among the mainland Chinese, late-life suicidality was highly associated with the LSNS-6 family subscale, rather than the friends subscale. CONCLUSION:The LSNS-6 could be a useful tool for assessing social networks among older mainland Chinese. In addition, suggestion is made to improve social networks, especially in family bonds and support, as a promising strategy in reducing late-life suicide risks in mainland China.

Homogeneous CaCO3 microspheres were controllably synthesized via a simple hydrothermal method without using extraneous additives by Ca(OH)2 saturated solution reacted with CO2 storage material (CO2SM), which was obtained by absorbing CO2 gas in a system containing equimolar ethylenediamine (EDA) and polyethylene glycol 400 (PEG). Specifically, homogeneous pure vaterite spheres were obtained by using 160 g/L CO2SM solution at 100 °C and a reaction time of two hours. It is noteworthy that the EDA and PEG, which are released from CO2SM, have dual functions as a CO2 absorber and crystal regulator in the process of controlling the crystallization of CaCO3 crystals.

Academic research trends involving public health education may reflect a certain degree of talent construction status. This study systematically reviews the data for published literature on graduate public health education, aiming to provide evidence for the optimization of public health postgraduate training mechanisms in China. Keyword cooccurrence analysis was performed based on high-frequency keywords. From 1992 to 2008, the annual number of publications in this field was relatively low in China, averaging fewer than 5 articles. The number of publications showed a steep increase after 2009. The publications were mostly from single research institutions, including comprehensive universities and military medical universities, concentrated in Beijing and Shanghai. The high-frequency keywords were public health and preventive medicine, postgraduate training, professional degree, MPH, curriculum, and teaching reform. Hotspots consisted of practical teaching research, training, educational reform and comparative education research. Research on public health postgraduate education has not reached scale and has insufficient support. Moreover, many problems in graduate public health education still cannot be solved by existing studies: authentic and practical learning, a unified approach to cultivate graduate students, organizational change of graduate public health education, and international cooperation and public health education.

China's Clinical Medicine Level Test (CMLT) was designed to evaluate the key factors that affect the learning outcome of medical students prior to entering clinical practice. In this study, we systemically analyzed the performance of a cohort of medical students at Jinan University School of Medicine participating in the recent CMLT. The analytical results of the medical students' written and objective structured clinical examination (OSCE) scores showed that their academic performance was predominantly associated with students' internship allocations, although other demographic characteristics such as sex, age, geographical origin of students, and grade point average (GPA) might be sporadically related to the students' OSCE performance at different OSCE stations. To explore the inherent reasons behind this, a survey was implemented among the medical students who participated in the examination to further interpret the factors influencing the students' learning outcome. The findings of this questionnaire manifested that intrinsic motivation and identified regulation acted as the major motivational profiles for the medical students from three different internship sites, whereas external regulation emerged as the crucial factor to make the students perform well academically in the CMLT. The result of this study suggested that strengthening the quality control of the clinical learning environment and improving medical administration may still be the most effective approaches to ensure the quality of clinical medical education.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (-1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic's effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. This paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions. [ABSTRACT FROM AUTHOR]

Megacities are major sources of anthropogenic fossil fuel CO2 (FFCO2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km2 or more with complex topography and changing landscapes. We present a high-resolution land-atmosphere modelling system for urban CO2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO2 emission product, Hestia-LA, to simulate atmospheric CO2 concentrations across the LA megacity at spatial resolutions as fine as ∼ 1 km. We evaluated multiple WRF configurations, selecting one that minimized errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May-June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO2 emission products to evaluate the impact of the spatial resolution of the CO2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO2 concentrations. We find that high spatial resolution in the fossil fuel CO2 emissions is more important than in the atmospheric model to capture CO2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO2 emissions monitoring in the LA megacity requires FFCO2 emissions modelling with ∼ 1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.