A Study on the Historical Development of China’s Sports Dream

China’s sports dream was profoundly influenced by traditional Chinese culture in ancient China. At that time, the primary purpose of sports was bodybuilding, health preserving and entertainment. The ruling class never advocated even suppressed the phenomenon of emphasizing literacy and military force for the need of their ruling. In semi-colonial and semi-feudal old China, with the foreign invasion and inside corruption, modern sports were introduced to China and the China’s sports dream had a strong sense of survival and participation. However, sports level as a whole was not high. At present, with the rejuvenation of Chinese nation’s “Chinese Dream”, combining with Chinese excellent traditional culture, China plays a vital role in realizing China’s sports dream,  promoting Chinese sports soft power, shaping China’s international sporting image, eliminating alienation in modern sports and establishing new international sports order

N-(4-Chloro­phen­yl)-4-meth­oxy-3-(propanamido)­benzamide cyclo­hexane hemisolvate

The title compound, C17H17ClN2O3·0.5C6H12, was prepared by the condensation reaction of 4-meth­oxy-3-(propanamido)­benzoic acid with 4-chloro­aniline. The Cl atom, the propionyl CH3 group and the cyclo­hexyl CH2 group are disordered over two sets of sites of equal occupancy in both mol­ecules. The cyclo­hexane solvent mol­ecule is disordered over two orientations which were modelled with relative occupancies of 0.484 (4) and 0.516 (4). In the crystal, there are a number of N—H⋯O hydrogen bonds, forming layers perpendicular to (001)

Time-varying effect in the competing risks based on restricted mean time lost

Patients with breast cancer tend to die from other diseases, so for studies that focus on breast cancer, a competing risks model is more appropriate. Considering subdistribution hazard ratio, which is used often, limited to model assumptions and clinical interpretation, we aimed to quantify the effects of prognostic factors by an absolute indicator, the difference in restricted mean time lost (RMTL), which is more intuitive. Additionally, prognostic factors may have dynamic effects (time-varying effects) in long-term follow-up. However, existing competing risks regression models only provide a static view of covariate effects, leading to a distorted assessment of the prognostic factor. To address this issue, we proposed a dynamic effect RMTL regression that can explore the between-group cumulative difference in mean life lost over a period of time and obtain the real-time effect by the speed of accumulation, as well as personalized predictions on a time scale. Through Monte Carlo simulation, we validated the dynamic effects estimated by the proposed regression having low bias and a coverage rate of around 95%. Applying this model to an elderly early-stage breast cancer cohort, we found that most factors had different patterns of dynamic effects, revealing meaningful physiological mechanisms underlying diseases. Moreover, from the perspective of prediction, the mean C-index in external validation reached 0.78. Dynamic effect RMTL regression can analyze both dynamic cumulative effects and real-time effects of covariates, providing a more comprehensive prognosis and better prediction when competing risks exist

Learning Agility and Adaptive Legged Locomotion via Curricular Hindsight Reinforcement Learning

Agile and adaptive maneuvers such as fall recovery, high-speed turning, and sprinting in the wild are challenging for legged systems. We propose a Curricular Hindsight Reinforcement Learning (CHRL) that learns an end-to-end tracking controller that achieves powerful agility and adaptation for the legged robot. The two key components are (I) a novel automatic curriculum strategy on task difficulty and (ii) a Hindsight Experience Replay strategy adapted to legged locomotion tasks. We demonstrated successful agile and adaptive locomotion on a real quadruped robot that performed fall recovery autonomously, coherent trotting, sustained outdoor speeds up to 3.45 m/s, and tuning speeds up to 3.2 rad/s. This system produces adaptive behaviours responding to changing situations and unexpected disturbances on natural terrains like grass and dirt

Synthesis and antiviral activities of a novel class of thioflavone and flavonoid analogues

AbstractA novel class of thioflavone and flavonoid derivatives has been prepared and their antiviral activities against enterovirus 71 (EV71) and the coxsackievirus B3 (CVB3) and B6 (CVB6) were evaluated. Compounds 7d and 9b showed potent antiviral activities against EV71 with IC50 values of 8.27 and 5.48μM, respectively. Compound 7f, which has been synthesized for the first time in this work, showed the highest level of inhibitory activity against both CVB3 and CVB6 with an IC50 value of 0.62 and 0.87μM. Compounds 4b, 7a, 9c and 9e also showed strong inhibitory activities against both the CVB3 and CVB6 at low concentrations (IC50=1.42−7.15μM), whereas compounds 4d, 7c, 7e and 7g showed strong activity against CVB6 (IC50=2.91–3.77μM) together with low levels of activity against CVB3. Compound 7d exhibited stronger inhibitory activity against CVB3 (IC50=6.44μM) than CVB6 (IC50>8.29μM). The thioflavone derivatives 7a, 7c, 7d, 7e, 7f and 7g, represent a new class of lead compounds for the development of novel antiviral agents

Bioassessment of a Drinking Water Reservoir Using Plankton: High Throughput Sequencing vs. Traditional Morphological Method

Drinking water safety is increasingly perceived as one of the top global environmental issues. Plankton has been commonly used as a bioindicator for water quality in lakes and reservoirs. Recently, DNA sequencing technology has been applied to bioassessment. In this study, we compared the effectiveness of the 16S and 18S rRNA high throughput sequencing method (HTS) and the traditional optical microscopy method (TOM) in the bioassessment of drinking water quality. Five stations reflecting different habitats and hydrological conditions in Danjiangkou Reservoir, one of the largest drinking water reservoirs in Asia, were sampled May 2016. Non-metric multi-dimensional scaling (NMDS) analysis showed that plankton assemblages varied among the stations and the spatial patterns revealed by the two methods were consistent. The correlation between TOM and HTS in a symmetric Procrustes analysis was 0.61, revealing overall good concordance between the two methods. Procrustes analysis also showed that site-specific differences between the two methods varied among the stations. Station Heijizui (H), a site heavily influenced by two tributaries, had the largest difference while station Qushou (Q), a confluence site close to the outlet dam, had the smallest difference between the two methods. Our results show that DNA sequencing has the potential to provide consistent identification of taxa, and reliable bioassessment in a long-term biomonitoring and assessment program for drinking water reservoirs

The Polar Wind Modulated by the Spatial Inhomogeneity of the Strength of the Earth's Magnetic Field

When the geomagnetic field is weak, the small mirror force allows precipitating charged particles to deposit energy in the ionosphere. This leads to an increase in ionospheric outflow from the Earth's polar cap region, but such an effect has not been previously observed because the energies of the ions of the polar ionospheric outflow are too low, making it difficult to detect the low‐energy ions with a positively charged spacecraft. In this study, we found an anticorrelation between ionospheric outflow and the strength of the Earth's magnetic field. Our results suggest that the electron precipitation through the polar rain can be a main energy source of the polar wind during periods of high levels of solar activity. The decreased magnetic field due to spatial inhomogeneity of the Earth's magnetic field and its effect on outflow can be used to study the outflow in history when the magnetic field was at similar levels.publishedVersio

Performance of artificial intelligence in diabetic retinopathy screening: a systematic review and meta-analysis of prospective studies

AimsTo systematically evaluate the diagnostic value of an artificial intelligence (AI) algorithm model for various types of diabetic retinopathy (DR) in prospective studies over the previous five years, and to explore the factors affecting its diagnostic effectiveness.Materials and methodsA search was conducted in Cochrane Library, Embase, Web of Science, PubMed, and IEEE databases to collect prospective studies on AI models for the diagnosis of DR from January 2017 to December 2022. We used QUADAS-2 to evaluate the risk of bias in the included studies. Meta-analysis was performed using MetaDiSc and STATA 14.0 software to calculate the combined sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of various types of DR. Diagnostic odds ratios, summary receiver operating characteristic (SROC) plots, coupled forest plots, and subgroup analysis were performed according to the DR categories, patient source, region of study, and quality of literature, image, and algorithm.ResultsFinally, 21 studies were included. Meta-analysis showed that the pooled sensitivity, specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, area under the curve, Cochrane Q index, and pooled diagnostic odds ratio of AI model for the diagnosis of DR were 0.880 (0.875-0.884), 0.912 (0.99-0.913), 13.021 (10.738-15.789), 0.083 (0.061-0.112), 0.9798, 0.9388, and 206.80 (124.82-342.63), respectively. The DR categories, patient source, region of study, sample size, quality of literature, image, and algorithm may affect the diagnostic efficiency of AI for DR.ConclusionAI model has a clear diagnostic value for DR, but it is influenced by many factors that deserve further study.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42023389687

Baveno-VII criteria to predict decompensation and initiate non-selective beta-blocker in compensated advanced chronic liver disease patients

Background/Aims The utility of Baveno-VII criteria of clinically significant portal hypertension (CSPH) to predict decompensation in compensated advanced chronic liver disease (cACLD) patient needs validation. We aim to validate the performance of CSPH criteria to predict the risk of decompensation in an international real-world cohort of cACLD patients. Methods cACLD patients were stratified into three categories (CSPH excluded, grey zone, and CSPH). The risks of decompensation across different CSPH categories were estimated using competing risk regression for clustered data, with death and hepatocellular carcinoma as competing events. The performance of “treating definite CSPH” strategy to prevent decompensation using non-selective beta-blocker (NSBB) was compared against other strategies in decision curve analysis. Results One thousand one hundred fifty-nine cACLD patients (36.8% had CSPH) were included; 7.2% experienced decompensation over a median follow-up of 40 months. Non-invasive assessment of CSPH predicts a 5-fold higher risk of liver decompensation in cACLD patients (subdistribution hazard ratio, 5.5; 95% confidence interval, 4.0–7.4). “Probable CSPH” is suboptimal to predict decompensation risk in cACLD patients. CSPH exclusion criteria reliably exclude cACLD patients at risk of decompensation, regardless of etiology. Among the grey zone, the decompensation risk was negligible among viral-related cACLD, but was substantially higher among the non-viral cACLD group. Decision curve analysis showed that “treating definite CSPH” strategy is superior to “treating all varices” or “treating probable CSPH” strategy to prevent decompensation using NSBB. Conclusions Non-invasive assessment of CSPH may stratify decompensation risk and the need for NSBB in cACLD patients

Novel hypoxia-related gene signature for predicting prognoses that correlate with the tumor immune microenvironment in NSCLC

Background: Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. The global influence of hypoxia-related genes (HRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response is unclear in patients with non-small cell lung cancer (NSCLC).Method: RNA-seq and clinical data for NSCLC patients were derived from The Cancer Genome Atlas (TCGA) database, and a group of HRGs was obtained from the MSigDB. The differentially expressed HRGs were determined using the limma package; prognostic HRGs were identified via univariate Cox regression. Using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, an optimized prognostic model consisting of nine HRGs was constructed. The prognostic model’s capacity was evaluated by Kaplan‒Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis in the TCGA (training set) and GEO (validation set) cohorts. Moreover, a potential biological pathway and immune infiltration differences were explained.Results: A prognostic model containing nine HRGs (STC2, ALDOA, MIF, LDHA, EXT1, PGM2, ENO3, INHA, and RORA) was developed. NSCLC patients were separated into two risk categories according to the risk score generated by the hypoxia model. The model-based risk score had better predictive power than the clinicopathological method. Patients in the high-risk category had poor recurrence-free survival in the TCGA (HR: 1.426; 95% CI: 0.997–2.042; p = 0.046) and GEO (HR: 2.4; 95% CI: 1.7–3.2; p < 0.0001) cohorts. The overall survival of the high-risk category was also inferior to that of the low-risk category in the TCGA (HR: 1.8; 95% CI: 1.5–2.2; p < 0.0001) and GEO (HR: 1.8; 95% CI: 1.4–2.3; p < 0.0001) cohorts. Additionally, we discovered a notable distinction in the enrichment of immune-related pathways, immune cell abundance, and immune checkpoint gene expression between the two subcategories.Conclusion: The proposed 9-HRG signature is a promising indicator for predicting NSCLC patient prognosis and may be potentially applicable in checkpoint therapy efficiency prediction