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Bisphenol F (BPF) has been used in the syntheses of polymers, which are widely used in coatings, varnishes, adhesives, and other plastics. During the past decades, BPF contamination in the aquatic environment has dramatically increased due to its release from manmade products. Concerns have driven much attention to whether it may adversely impact aquatic lives or human beings. The present study performed an acute toxic exposure experiment and a 15 d developmental exposure of BPF at environmental concentrations (20, 200, and 2000 ng/L) using Chinese medaka (Oryzias sinensis). In the acute toxic exposure, the LC50 of BPF to Chinese medaka is 87.90 mg/L at 96 h. Developmental exposure induced a significant increase in the frequency of larvae with abnormalities in the 2000 ng/L BPF group compared to the control group. Transcriptomic analysis of the whole larvae revealed 565 up-regulated and 493 down-regulated genes in the 2000 ng/L BPF exposure group. Analysis of gene ontology and KEGG pathways enrichments indicated endocrine disorders to be associated with BPF-induced developmental toxicity. The present results suggest that BPF is developmentally toxic at 2000 ng/L concentration in Chinese medaka and causes endocrine-related aberrations in the transcriptional network of genes.

Highly pathogenic avian influenza virus (HPAIV) A H5 clade 2.3.4.4 has caused worldwide outbreaks in domestic poultry, occasional spillover to humans, and increasing deaths of diverse species of wild birds since 2014. Wild bird migration is currently acknowledged as an important ecological process contributing to the global dispersal of HPAIV H5. However, it is unclearhow seasonal bird migration facilitates global virus dispersal, andwhich avian species are exposed to HPAI H5 clade 2.3.4.4 viruses and where. To shed light on ongoing global outbreaks, we sought to explore these questions through phylodynamic analyses based on empirical data of bird movement tracking and virus genome sequences. First, based on viral phylogeography and bird migration networks, we demonstrate that seasonal bird migration can explain salient features of the global dispersal of clade 2.3.4.4. Second, we detect synchrony between the seasonality of bird annual cycle phases and virus lineage movements. We reveal the differing vulnerable bird orders at geographical origins and destinations of HPAIV H5 lineage movements. Notably, we highlight the potential importance of relatively under-discussed Suliformes and Ciconiiformes, in addition to Anseriformes and Charadriiformes, in virus lineage movements. Our study provides a phylodynamic framework that links the bird movement ecology and genomic epidemiology of avian influenza; it highlights the importance of integrating bird behaviour and life history in avian influenza studies.

Migratory birds play a critical role in the rapid spread of highly pathogenic avian influenza (HPAI) H5N8 virus clade 2.3.4.4 across Eurasia. Elucidating the timing and pattern of virus transmission is essential therefore for understanding the spatial dissemination of these viruses. In this study, we surveyed >27,000 wild birds in China, tracked the year-round migration patterns of 20 bird species across China since 2006, and generated new HPAI H5N8 virus genomic data. Using this new data set, we investigated the seasonal transmission dynamics of HPAI H5N8 viruses across Eurasia. We found that introductions of HPAI H5N8 viruses to different Eurasian regions were associated with the seasonal migration of wild birds. Moreover, we report a backflow of HPAI H5N8 virus lineages from Europe to Asia, suggesting that Europe acts as both a source and a sink in the global HPAI virus transmission network. ispartof: MOLECULAR BIOLOGY AND EVOLUTION vol:40 issue:2 ispartof: location:United States status: published

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications such as companion diagnostics and prognostics. However, there is a lack of certified RNA reference materials and the corresponding reference datasets of differential expression for assessing the reliability of RNAseq for its intended use in detecting intrinsically small biological differences in clinical settings such as molecular subtyping of diseases. As part of the Quartet Project for quality control and data integration of multiomics profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets between two reference samples, providing "ground truth" for cross-platform and cross-lab proficiency test. Moreover, Quartet-sample-based quality metrics were developed for assessing the reliability of RNAseq technology in terms of intra-batch measurement and cross-batch data integration. The small intrinsic biological differences among the Quartet samples enabled sensitive assessment of performance of transcriptomic measurements and their cross-batch integration at the ratio level. The Quartet RNA reference materials combined with the ratio-based reference datasets can serve as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

Some asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19. Here, we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate the relationship between asymptomatic proportion and age. Epidemiological data obtained before mass vaccination provide valuable insights into the nature of pathogenicity of SARS-CoV-2. The data were collected by multiple rounds of city-wide PCR testing with contact tracing, where each patient was monitored for symptoms through the whole course of infection. The clinical endpoint (asymptomatic or symptomatic) for each patient was recorded (the pre-symptomatic patients were classified as symptomatic). We find that the proportion of infections that are asymptomatic declines with age (coefficient = −0.006, 95% CI: −0.008 to −0.003,p< 0.01), falling from 42% (95% CI: 6–78%) in age group 0–9 years to 11% (95% CI: 0–25%) in age group greater than 60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern, together with the distribution of cases by age, can explain most of the reported variation in asymptomatic proportions among cities. Our analysis suggests that SARS-CoV-2 surveillance strategies should take account of the variation in asymptomatic proportion with age.

In recent years, the single-stage detectors have been developed rapidly; however, compared with the multi-stage detectors, their detection precision is still relatively low. Single-stage detectors and multi-stage detectors are analyzes and compared in detail in this paper, which reveals that single-stage detectors suffer from some problems, including feature loss and inaccurate feature extraction. Therefore, this paper proposes a novel detection model, dubbed Optimized Network (OptNet), to alleviate these deficiencies. OptNet consists of three modules: pyramid of attention features, feature alignment and consistency supervision (CS). The pyramid of attention features, based on feature pyramid networks (FPNs), introduces a novel branch named attention FPN (AtFPN), which aggregates the multi-layer features of the backbone network and optimizes the object features by using lightweight attention modules. AtFPN alleviates the loss of the feature pyramid information and the blocking of feature transmission between adjacent layers. Meanwhile, it provides global information for the model. The feature alignment module aligns the anchor box to the feature by using the object location information to guide the network to extract precise object features. Finally, CS accelerates network optimization and reduces semantic differences between the features on different layers. In the detection stage, OptNet optimizes the prediction of the model with the first detection result to improve the accuracy. Experiments on the MS COCO 2017 dataset demonstrate that OptNet yields significant improvement in the detection precision.

BACKGROUND: The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America.METHODS: We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports).FINDINGS: We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01-0·17, pINTERPRETATION: In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options.FUNDING: National Key Research and Development Program of China and the Medical Research Council.

Asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19, but it is not yet clear how the proportion of asymptomatic infections varies by age and geographic location. Here we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate this question. Data were collected by multiple rounds of city-wide PCR test with detailed contact tracing, where each patient was monitored for symptoms through the whole course of infection. We find that the proportion of asymptomatic infections declines with age (coefficient =-0.006, P60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern together with the age distribution of overall cases can explain most of the geographic differences in reported asymptomatic proportions. Combined with demography and contact matrices from other countries worldwide, we estimate that a maximum of 22%–55% of SARS-CoV-2 infections would come from asymptomatic cases in an uncontrolled epidemic based on asymptomatic proportions in China. Our analysis suggests that flare-ups of COVID-19 are likely if only adults are vaccinated and that surveillance and possibly control measures among children will be still needed in the future to contain epidemic resurgence.

With the continuous development of “Internet + ”, big data, cloud computing and other intelligent scientific and technological concepts, it brings opportunity and challenge to the construction of university informatization. Information transmission will determine the decision-making, so the construction of universities financial information is an urgent matter. At the same time, with the introduction of the government accounting system, higher requirements have been put up for the accounting of administrative institutions. At present, the system of financial accounting in colleges and universities in China is still not perfect enough, the information platform construction still has some shortages, however, the university financial accounting check and calculates is the important constituent of university development, strengthening and consummating the university finance is imminent in the information construction. On the basis of analyzing the current situation and problems of college informatization, this paper puts forward the theoretical framework of financial informatization sharing platform based on cloud computing environment to meet the needs of college teaching, scientific research and management, some thoughts on the financial transformation of colleges and universities in the later period.

Brown-Vialetto-Van Laere syndrome-2 is a rare neurological disorder characterized by sensory neuronopathy and pontobulbar palsy, caused by variations in SLC52A2 and SLC52A3 genes, encoding the riboflavin transporters. By reprogramming with SOX2, KLF4, c-MYC and OCT3/4, we generated an iPSC cell line from peripheral blood mononuclear cells (PBMCs) collected from a three-year-old Chinese female individual to be used as a disease model. By fully examination, the resulting iPSCs expressed pluripotency-associated stem cell markers, maintained the normal karyotype and proliferative potential for three-germ layer differentiation.

Background: until broad vaccination coverage is reached and effective therapeutics are available, controlling population mobility (ie, changes in the spatial location of a population that affect the spread and distribution of pathogens) is one of the major interventions used to reduce transmission of SARS-CoV-2. However, population mobility differs across locations, which could reduce the effectiveness of pandemic control measures. Here we assess the extent to which socioeconomic factors are associated with reductions in population mobility during the COVID-19 pandemic, at both the city level in China and at the country level worldwide. Methods: in this retrospective, observational study, we obtained anonymised daily mobile phone location data for 358 Chinese cities from Baidu, and for 121 countries from Google COVID-19 Community Mobility Reports. We assessed the intra-city movement intensity, inflow intensity, and outflow intensity of each Chinese city between Jan 25 (when the national emergency response was implemented) and Feb 18, 2020 (when population mobility was lowest) and compared these data to the corresponding lunar calendar period from the previous year (Feb 5 to March 1, 2019). Chinese cities were classified into four socioeconomic index (SEI) groups (high SEI, high–middle SEI, middle SEI, and low SEI) and the association between socioeconomic factors and changes in population mobility were assessed using univariate and multivariable linear regression. At the country level, we compared six types of mobility (residential, transit stations, workplaces, retail and recreation, parks, and groceries and pharmacies) 35 days after the implementation of the national emergency response in each country and compared these to data from the same day of the week in the baseline period (Jan 3 to Feb 6, 2020). We assessed associations between changes in the six types of mobility and the country's sociodemographic index using univariate and multivariable linear regression. Findings: the reduction in intra-city movement intensity in China was stronger in cities with a higher SEI than in those with a lower SEI (r=–0·47, pInterpretation: although COVID-19 outbreaks are more frequently reported in larger cities, our analysis shows that future policies should prioritise the reduction of risks in areas with a low socioeconomic level—eg, by providing financial assistance and improving public health messaging. However, our study design only allows us to assess associations, and a long-term study is needed to decipher causality. Funding: Chinese Ministry of Science and Technology, Research Council of Norway, Beijing Municipal Science & Technology Commission, Beijing Natural Science Foundation, Beijing Advanced Innovation Program for Land Surface Science, National Natural Science Foundation of China, China Association for Science and Technology.

A belt weigher is widely used in industrial production and trade settlement; however, it is difficult to maintain its nominal measuring accuracy in service. With the belt weigher indication, average speed of belt, variation in belt sag, running deviation of belt, environmental temperature, and humidity as inputs, and the control instrument indication as output, a BP neural network model to compensate the automatic weighing error of the belt weigher is built. We obtained the sample data depending on the test system for the type evaluation of the belt weigher in the Jiangsu Institute of Metrology, as well as supplemental relevant parameters for the monitoring devices. The BP model is trained and validated using MATLAB. The validation results show that the absolute value of the maximum relative automatic weighing error output by the BP model is less than 0.5%, significantly lower than the error before using the BP model for compensation. The BP model is effective, feasible, and practical for compensating the automatic weighing error of the belt weigher.

People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%–52.0%), 32.3% (95% CI: 22.5%–42.4%), and 14.2% (7.9%–20.5%) in the number of COVID-19 cases for every 10-μg/m3 increase in long-term exposure to NO2, PM2.5, and PM10, respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration., Graphical abstract Image 1, This research reported a national-level association with long-term exposure to air pollutants and COVID-19 cases covering 324 cities in China.

Surveillance of whooper swan migration is important for monitoring avian influenza transmission risk potential from east to west China between the East Asian--Australasian and Central Asian flyways. Here, we characterised the evolutionary and reasssortment history of H5N2 viruses isolated from 1866 fresh faeces samples of wintering whooper swans collected in the Sanmenxia Reservoir area, China. This was combined with information on the migration routes of whooper swans in Eastern Asia to elucidate the role of whooper swans in spreading the virus. All segments of the new H5N2 isolates belong to the Eurasian avian-like lineage and are closely related to wild-bird viruses from China, Korea and Mongolia covering the wintering, stopover and breeding grounds in migration routes of whooper swans. We further found that the temporal-spatial migration process of whooper swans was identical with the virus transmission and reassortment pathway in Eastern Asia particularly.

The most effective interventions By 23 January 2020, China had imposed a national emergency response to restrict travel and impose social distancing measures on its populace in an attempt to inhibit the transmission of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2). However, which measures were most effective is uncertain. Tian et al. performed a quantitative analysis of the impact of control measures between 31 December 2019 and 19 February 2020, which encompasses the Lunar New Year period when millions of people traveled across China for family visits. Travel restrictions in and out of Wuhan were too late to prevent the spread of the virus to 262 cities within 28 days. However, the epidemic peaked in Hubei province on 4 February 2020, indicating that measures such as closing citywide public transport and entertainment venues and banning public gatherings combined to avert hundreds of thousands of cases of infection. It is unlikely that this decline happened because the supply of susceptible people was exhausted, so relaxing control measures could lead to a resurgence. Science , this issue p. 638

Background Multidrug-resistant tuberculosis (MDR-TB) is on the rise in China. This study used a dynamic Markov model to predict the longitudinal trends of MDR-TB in China by 2050 and to assess the effects of alternative control measures. Methods Eight states of tuberculosis transmission were set up in the Markov model using a hypothetical cohort of 100 000 people. The prevalence of MDR-TB and bacteriologically confirmed drug-susceptible tuberculosis (DS-TB+) were simulated and MDR-TB was stratified into whether the disease was treated with the recommended regimen or not. Results Without any intervention changes to current conditions, the prevalence of DS-TB+ was projected to decline 67.7% by 2050, decreasing to 20 per 100 000 people, whereas that of MDR-TB was expected to triple to 58/100 000. Furthermore, 86.2% of the MDR-TB cases would be left untreated by the year of 2050. In the case where MDR-TB detection rate reaches 50% or 70% at 5% per year, the decline in prevalence of MDR-TB would be 25.9 and 36.2% respectively. In the case where treatment coverage was improved to 70% or 100% at 5% per year, MDR-TB prevalence in 2050 would decrease by 13.8 and 24.1%, respectively. If both detection rate and treatment coverage reach 70%, the prevalence of MDR-TB by 2050 would be reduced to 28/100 000 by a 51.7% reduction. Conclusions MDR-TB, especially untreated MDR-TB, would rise rapidly under China’s current MDR-TB control strategies. Interventions designed to promote effective detection and treatment of MDR-TB are imperative in the fights against MDR-TB epidemics.

People with chronic obstructive pulmonary disease, cardiovascular disease or hypertension have a high risk of severe coronavirus disease 2019 (COVID-19). Long-term exposure to air pollution, especially PM2.5, has also been associated with COVID-19 mortality. We collated individual-level data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average levels of air pollutants as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the time of emergency response. Other variables included census, smoking prevalence, climate, and socio-economic data from 324 cities in China. We adjusted for human mobility and socio-economic factors, and found that an increase in long-term NO2 or PM2.5 may correspond to an increase in the number of COVID-19 cases and severe infections. However, the linkage might also be affected by the confounding factor of population size because of the predefined correlation between population size and air pollution. The results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings of this paper (and other previous studies that have given ambiguous results) indicate that a more definitive analysis is needed of the link between COVID-19 and air pollution.

Respiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China.One sentence summaryTravel restrictions and the national emergency response delayed the growth and limited the size of the COVID-19 epidemic in China.

Background: Multidrug-resistant tuberculosis (MDR-TB) is emerging in China. We used a dynamic Markov model to predict the longitudinal trends of MDR-TB in China by 2050, and assess the effects of alternative control measures. Methods Eight states of TB transmission were set up in the Markov model using a hypothetical cohort of 100,000 people. Prevalence of MDR-TB and bacteriological confirmed drug-susceptible TB (DS-TB+) were simulated. MDR-TB was stratified into being treated with the recommended regimen or not. Findings: Under the current China’s TB control conditions, by 2050, prevalence of DS-TB+ could be estimated to decrease to 39 per 100,000 people, a 37·1% reduction from 2019 , whereas MDR-TB would increase by three times to 58/100,000. Furthermore, by the year of 2050, 86·2% of the MDR-TB cases would be left untreated. If the detection rate of MDR-TB could reach 50% or 70% at 5% per year, the decline of MDR-TB prevalence would be 25·9% and 36·2% respectively. If treatment coverage was improved to 70% or 100% by 5% yearly , MDR-TB prevalence in 2050 would gain a reduction of 13·8% and 24·1%, respectively. If both detection rate and treatment coverage could reach 70%, the prevalence of MDR-TB would be reduced to 28/100, 000, a 51·7% reduction by 2050. Interpretation: MDR-TB, especially untreated MDR-TB, would rise rapidly under current MDR-TB control strategies in China. Interventions on promoting effective detection and treatment of MDR-TB are imperative in the fights against MDR-TB epidemics. Funding Statement: The Sweden-China (VR-NSFC) joint project (PI, Biao Xu, 81361138019 and Sven Hoffner, 540-2013-8797). Declaration of Interests: The authors stated: "None declared." Ethics Approval Statement: Not required.

A lanthanum-modified magnetic oyster shell (La-Fe-OSP) was prepared by magnetization and lanthanum loading, and then its properties and phosphorus removal capability were studied. The results showed that La-Fe-OSP was magnetic, and the specific surface area and porosity increased remarkably compared with those before modification. La-Fe-OSP achieved a removal rate greater than 90% for various phosphate solutions (10-100 mg·L-1) and could be successfully recycled by applying a magnetic field. The phosphorus adsorption process of La-Fe-OSP could be characterized by a pseudo-second order model and Langmuir model and displayed intraparticle diffusion properties. La-Fe-OSP could maintain the novel adsorption performance within the pH range of 3.0-8.0, and its adsorption capability was negligibly affected by coexisting ions and dissolved organic matter (DOM) in water. Moreover, the maximum phosphorus removal rates of La-Fe-OSP for the overlying water and the pore water were 96.4% and 41%, respectively. In addition, La-Fe-OSP application also slightly changed the order of various phosphorus forms in sediment and promoted the transformation of easily released iron-bound P (Fe-P) to hardly released occluded P (Oc-P). After five successive cycles, La-Fe-OSP still obtained 85.1% phosphate removal efficiency and thus showed excellent application prospects.

Epithelial-mesenchymal transition (EMT) is a morphological process in which epithelial cells transform into mesenchymal cells via a specific procedure. EMT plays an important role in the cancer invasion-metastasis cascade and the current treatment of metastatic cancer, influences the migration, polarity, and adhesion of tumor cells, promotes their migration, invasiveness, anti-apoptotic ability. It contributes to the changes of the tumor microenvironment and suppresses the sensitivity of tumor cells to chemotherapy, causing cancer metastasis and worse, hindering the control and therapy of it. This paper reviews the mechanisms, detection, and treatments of cancer metastasis that have been identified and applied to date, summarizes the EMT-related biological molecules, providing a reference for EMT-targeted research and therapy. As EMT is significant in the progress of tumor metastasis, it is meaningful for the therapy and control of metastatic cancer to understand the mechanism of EMT at the molecular level. We summarized the mechanisms, detection and therapeutic implications of EMT, listed the research progress of molecules like genes, miRNAs, signaling pathways in EMT. We also discussed the prospects of EMT-targeted treatment in cancer metastasis interventions and the challenges the treatment and researches are facing. The summary is conducive to the treatment and further research of EMT and metastatic cancer.

Prediction performance of a risk scoring system needs to be carefully assessed before its adoption in clinical practice. Clinical preventive care often uses risk scores to screen asymptomatic population. The primary clinical interest is to predict the risk of having an event by a pre-specified future time t(0). Accuracy measures such as positive predictive values have been recommended for evaluating the predictive performance. However, for commonly used continuous or ordinal risk score systems, these measures require a subjective cut-off threshold value that dichotomizes the risk scores. The need for a cut-off value created barriers for practitioners and researchers. In this paper, we propose a threshold-free summary index of positive predictive values that accommodates time-dependent event status and competing risks. We develop a nonparametric estimator and provide an inference procedure for comparing this summary measure between two risk scores for censored time to event data. We conduct a simulation study to examine the finite-sample performance of the proposed estimation and inference procedures. Lastly, we illustrate the use of this measure on a real data example, comparing two risk score systems for predicting heart failure in childhood cancer survivors.