Search

Abstract. Background:. Clinical opportunistic screening is a cost-effective cancer screening modality. This study aimed to establish an easy-to-use diagnostic model serving as a risk stratification tool for identification of individuals with malignant gastric lesions for opportunistic screening. Methods:. We developed a questionnaire-based diagnostic model using a joint dataset including two clinical cohorts from northern and southern China. The cohorts consisted of 17,360 outpatients who had undergone upper gastrointestinal endoscopic examination in endoscopic clinics. The final model was derived based on unconditional logistic regression, and predictors were selected according to the Akaike information criterion. External validation was carried out with 32,614 participants from a community-based randomized controlled trial. Results:. This questionnaire-based diagnostic model for malignant gastric lesions had eight predictors, including advanced age, male gender, family history of gastric cancer, low body mass index, unexplained weight loss, consumption of leftover food, consumption of preserved food, and epigastric pain. This model showed high discriminative power in the development set with an area under the receiver operating characteristic curve (AUC) of 0.791 (95% confidence interval [CI]: 0.750–0.831). External validation of the model in the general population generated an AUC of 0.696 (95% CI: 0.570–0.822). This model showed an ideal ability for enriching prevalent malignant gastric lesions when applied to various scenarios. Conclusion:. This easy-to-use questionnaire-based model for diagnosis of prevalent malignant gastric lesions may serve as an effective prescreening tool in clinical opportunistic screening for gastric cancer.

Abstract Evidence for the treatment of patients with mild-to-moderate chronic obstructive pulmonary disease (COPD) is limited. The efficacy of N-acetylcysteine (an antioxidant and mucolytic agent) for patients with mild-to-moderate COPD is uncertain. In this multicentre, randomised, double-blind, placebo-controlled trial, we randomly assigned 968 patients with mild-to-moderate COPD to treatment with N-acetylcysteine (600 mg, twice daily) or matched placebo for two years. Eligible participants were 40-80 years of age and had mild-to-moderate COPD (forced expiratory volume in 1 second [FEV1] to forced vital capacity ratio

In order to meet the demand for dual-temperature heating in production and life, a dual-temperature heat pump system based on refrigerant leakage was proposed. By establishing and verifying the mathematical model and system model of the scroll compressor based on refrigerant leakage for numerical simulation, the system was calculated and analyzed under different discharge outlet positions, discharge outlet sizes, evaporation temperatures, high-temperature condensation temperatures, and medium-temperature condensation temperatures. The changing trends of performance parameters were compared with traditional dual-temperature heat pump systems. The results show that the sooner the middle discharge port of the compressor is opened, the less power the compressor consumes, and the larger the discharge port is, the more obvious the energy-saving effect of the system is; Compared with the traditional dual-temperature heat pump system, the heating performance coefficient is significantly improved under different working conditions, with the highest of 16%. The model proposed in the study provides a more effective method for the theoretical analysis of refrigerant leakage dual-temperature heat pumps and air-supplemented enthalpy-increasing heat pump systems, and the research results provide a theoretical basis for the optimization of scroll compressor performance, and the research, design and system performance improvement of dual-temperature heat pump systems.

PURPOSESurvival from esophageal cancer (EC) is poor, partly reflecting the delay in diagnosis. To inform the potential measures for downstaging the disease, we estimated diagnosis delay, that is, the length of interval from symptom-to-diagnosis (STD), and investigated its correlates among patients with EC in a high-risk resource-limited rural area in China.METHODSPatients newly diagnosed with EC (N = 411) were recruited in a secondary hospital in Henan province in China between August 1, 2018, and October 21, 2020. A face-to-face structured questionnaire was used to collect patient-level and health-seeking data from patients and/or proxies. Association between the length of STD interval and stage at diagnosis was examined using logistic regression. Correlates of the length of the STD interval were identified using negative binomial regression.RESULTSThe median STD interval was 61 (IQR, 24-155) days, with the time from symptom onset to first health care contact representing 90.1% (IQR, 7.8%-100%) of its length. The odds of being diagnosed at stages III-IV increased by 3% (age- and sex-adjusted odds ratio, 1.03 [95% CI, 0.99 to 1.08]) for every 2-month increase in the STD interval. Higher awareness of EC risk factors was associated with shorter STD intervals (incidence rate ratio [95% CI] for awareness score ≥2 v ≤0: 0.65 [0.46 to 0.93]), whereas patients who first visited secondary or tertiary/cancer hospitals had much longer STD intervals than those who first visited a primary health care facility (1.69 [1.19 to 2.40]; 2.22 [1.24 to 3.97]).CONCLUSIONThe median length of the STD interval was 2 months, but with considerable interindividual variability. Improving EC awareness, coupled with effective referral pathways, may promote timely diagnosis of this disease.

Abstract Systemic sclerosis (SSc), also known as scleroderma, is an autoimmune-related connective tissue disease with a complex and unknown pathophysiological mechanism with genes association. Several articles have reported a high prevalence of thyroid disease in SSc patients, while one study suggested a potential contribution of appendicitis to the development of SSc. To investigate this causal association, we conducted Mendelian randomization (MR) analysis using instrumental variables (IVs) to assess exposure and outcome. In the MR study involving two cohorts, all analyses were conducted using the TwoSampleMR package in R (version 4.3.0). Single nucleotide polymorphisms (SNPs) meeting a statistically significant threshold of 5E−08 were included in the analysis. Multiple complementary approaches including MR-IVW, MR-Egger, weighted median, simple mode, and weighted mode were employed to estimated the relationship between the exposure and outcome. Leave-one-out analysis and scatter plots were utilized for further investigation. Based on the locus-wide significance level, all of the MR analysis consequences manifested no causal association between the risk of appendicitis with SSc (IVW OR 0.319, 95% CI 0.063–14.055, P = 0.966). Negative causal effects of autoimmune thyroiditis (AT) on SSc (IVW OR 0.131, 95% CI 0.816–1.362, P = 0.686), Graves’ disease (GD) on SSc (IVW OR 0.097, 95% CI 0.837–1.222, P = 0.908), and hypothyroidism on SSc (IVW OR 1.136, 95% CI 0.977–1.321, P = 0.096) were derived. The reverse MR revealed no significant causal effect of SSc on thyroid disease. According to the sensitivity analysis, horizontal pleiotropy was unlikely to distort the causal estimates. The consequences indicated no significant association between AT, GD, and hypothyroidism with SSc. Similarly, there was no observed relationship with appendicitis.

The sports service supply chain faces various potential risks, such as market fluctuations, logistics issues, and partner uncertainties. To address these risks effectively, this study employs a combination of fuzzy comprehensive evaluation (FCE) methods and intelligent neural networks to create an innovative risk management framework. By considering diverse uncertainties and leveraging the analytical power of intelligent neural networks, this study aims to optimize the operation of the sports service supply chain and explore the risk factors within the public service supply chain of stadiums. This framework provides policy references to promote the healthy and sustainable development of the sports service industry. The main empirical findings, based on a representative survey of experts in China, are as follows: (1) When determining the weights of risk indicators for managing the public service supply chain of stadiums using the FCE method, the customer risk indicator is of paramount importance, with a weight of 0.286, accounting for 95.2 % of the total significance; and (2) In evaluating various risk indicators of the public service supply chain of stadiums through the neural network method, the customer risk indicator scores the highest, achieving a score of 76.02. Notably, the customer complaint risk indicator scores slightly higher at 79.33. Based on these findings, the study recommends focusing on enhancing customer experience within risk management strategies. Additionally, it suggests strengthening the supervision of platforms and third-party activities to ensure the stability and efficient operation of the stadium service supply chain. This study aims to provide theoretical support and reference indicators for evaluating the public service capabilities of stadiums.

Summary: Using noninvasive biomarkers to identify high-risk individuals prior to endoscopic examination is crucial for optimization of screening strategies for esophageal squamous cell carcinoma (ESCC). We conducted a nested case-control study based on two community-based screening cohorts to evaluate the warning value of serum metabolites for esophageal malignancy. The serum samples were collected at enrollment when the cases had not been diagnosed. We identified 74 differential metabolites and two prominent perturbed metabolic pathways, and constructed Metabolic Risk Score (MRS) based on 22 selected metabolic predictors. The MRS generated an area under the receiver operating characteristics curve (AUC) of 0.815. The model performed well for the within-1-year interval (AUC: 0.868) and 1-to-5-year interval (AUC: 0.845) from blood draw to diagnosis, but showed limited ability in predicting long-term cases (>5 years). In summary, the MRS could serve as a potential early warning and risk stratification tool for establishing a precision strategy of ESCC screening.

Lung cancer incidence and mortality rates are increasing worldwide, posing a significant public health challenge and an immense burden to affected families. Lung cancer encompasses distinct subtypes, namely, non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). In clinical investigations, researchers have observed that neuroendocrine tumors can be classified into four types: typical carcinoid, atypical carcinoid, small-cell carcinoma, and large-cell neuroendocrine carcinoma based on their unique features. However, there exist combined forms of neuroendocrine cancer. This study focuses specifically on combined pulmonary carcinomas with a neuroendocrine component. In this comprehensive review article, the authors provide an overview of combined lung cancers and present two pathological images to visually depict these distinctive subtypes.

Abstract With the continuous development of artificial intelligence technology, more and more computational models for generating new molecules are being developed. However, we are often confronted with the question of whether these compounds are easy or difficult to synthesize, which refers to synthetic accessibility of compounds. In this study, a deep learning based computational model called DeepSA, was proposed to predict the synthesis accessibility of compounds, which provides a useful tool to choose molecules. DeepSA is a chemical language model that was developed by training on a dataset of 3,593,053 molecules using various natural language processing (NLP) algorithms, offering advantages over state-of-the-art methods and having a much higher area under the receiver operating characteristic curve (AUROC), i.e., 89.6%, in discriminating those molecules that are difficult to synthesize. This helps users select less expensive molecules for synthesis, reducing the time and cost required for drug discovery and development. Interestingly, a comparison of DeepSA with a Graph Attention-based method shows that using SMILES alone can also efficiently visualize and extract compound’s informative features. DeepSA is available online on the below web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepsa/ ) of our group, and the code is available at https://github.com/Shihang-Wang-58/DeepSA .

Abstract Background Current guidelines recommend only severe dysplasia and above (SDA) lesions of the esophageal squamous epithelium for clinical intervention. However, the histopathologic diagnosis derived from tissue biopsies may be subject to underestimation of severity. Methods 1073 participants from whom biopsies were taken at baseline chromoendoscopic examination in a population‐based screening trial were enrolled in this study. The size of the Lugol‐unstained lesions (LULs) was mainly analyzed. The outcome was defined as SDA lesions either identified at baseline screening, or during follow‐up, collectively referred to as the cumulative risk of SDA. Multivariable logistic regression models were used to evaluate the cumulative risk of SDA. Results One hundred and forty‐six SDA cases were identified in the study period. Participants with large LULs had a high cumulative incidence of SDA (cumulative incidence16–20mm: 55.88%; cumulative incidence>20mm: 76.92%) in the median of 7‐year duration. LULs of large size were significantly associated with a higher cumulative risk of SDA, regardless of the pathologic diagnosis (adjusted OR16–20mmvs.≤5mm = 21.02, 95% CI: 7.56–58.47; adjusted OR>20mmvs.≤5mm = 33.62, 95% CI: 11.79–95.87). Conclusions Results from this study suggest physician–patient shared decision‐making regarding clinical treatment or intensive surveillance should be carried out for LULs >20 mm in the esophagus, regardless of the histologic diagnosis. For those with LULs of 16–20 mm, intensive surveillance would also best be considered.

This study aims to develop a cost-effective and reliable motion monitoring device capable of comprehensive fatigue analysis. It achieves this objective by integrating surface electromyography (sEMG) and accelerometer (ACC) signals through a feature fusion strategy. The study introduces a multi-level attention mechanism for classification, leveraging convolutional neural networks (CNNs). The preprocessing phase involves a local feature attention mechanism that enhances local waveform features using the amplitude envelope. A dual-scale attention mechanism, operating at both channel and neuron levels, is employed to enhance the model's learning from high-dimensional fused data, improving feature extraction and generalization. The local feature attention mechanism significantly improves the model's classification accuracy and convergence, as demonstrated in ablation experiments. The model, optimized with multi-level attention mechanisms, excels in accuracy and generalization, particularly in handling data with pseudo-artifacts. Computational analysis indicates that the proposed optimization algorithm has minimal impact on CNN's training and testing times. The study achieves recognition accuracies of 92.52%, 92.38%, and 92.30%, as well as F1-scores of 91.92%, 92.13%, and 92.29% for the three fatigue states, affirming its reliability. This research provides technical support for the development of affordable and dependable wearable motion monitoring devices.

The rational design of PROTACs is difficult due to their obscure structure-activity relationship. Here the authors present a deep neural network model - DeepPROTACs - for predicting the degradation capacity of a proposed PROTAC molecule.

Abstract Background The association of early-life undernutrition and dyslipidemia found in previous studies may be confounded by the uncontrolled age difference between exposed and unexposed participants. The study aimed to investigate the association of early-life undernutrition and the risk of dyslipidemia in adulthood with good control of the age variable. Methods We took the Great Chinese Famine (1959–1961) as a natural experiment of severe undernutrition. This study was based on the baseline investigation of a population-based cohort in rural China. Undernutrition in early life was defined as being exposed to famine at younger than 3 years of age. Three approaches including Adjustment, Restriction, and Matching were applied to control the confounding effect of age. Logistic regression models were applied to evaluate the association between early-life famine and the presence of dyslipidemia. Stratified analysis by gender was also performed, and potential effect modification was tested by adding the interaction term of the famine exposure variable and gender into the model. Results Undernutrition in early life was associated with increased risk of borderline high and above (BHA) levels of total cholesterol (TC, ORAdjustment = 1.61; ORRestriction = 1.56; ORMatching = 1.87), triglycerides (TG, ORAdjustment = 1.33; ORRestriction = 1.30; ORMatching = 1.34), low-density lipoprotein cholesterol (LDL-C, ORAdjustment = 1.75; ORRestriction = 1.53; ORMatching = 1.77) and dyslipidemia (ORAdjustment = 1.52; ORRestriction = 1.45; ORMatching = 1.60), as well as high levels of TC, TG, LDL-C and dyslipidemia. An inverse association of undernutrition and risk of low high-density lipoprotein cholesterol (HDL-C) was found. Female participants with undernutrition experience had an increased risk of BHA TG and LDL-C (TG: ORAdjustment, female = 1.45; ORRestriction, female = 1.39; ORMatching, female = 1.51; LDL-C: ORAdjustment, female = 2.11; ORRestriction, female = 1.80; ORMatching, female = 2.15), but this association was not found in males. Conclusion Early-life undernutrition increased the risk of TC, TG, LDL-C, and dyslipidemia. Gender would significantly modify this effect for TG and LDL-C. These results emphasize the importance of nutritional conditions in the early stages of life to long-term health consequences.

BackgroundConventional universal endoscopic screening with pathology-based endoscopic re-examination for esophageal squamous cell carcinoma is in need of reform in China. We established a “two-step” precision screening strategy using two risk prediction models and have evaluated the cost-effectiveness of this precision strategy compared with the traditional strategy based on a large population-level randomized controlled trial from a healthcare provider’s perspective.MethodsFour precision screening strategies with different risk cutoffs at baseline screening and endoscopic surveillance were constructed, and then compared with traditional strategy through modeling using subjects from the screening cohort of the ESECC (Endoscopic Screening for Esophageal Cancer in China) trial. Total screening costs and the number of SDA (severe dysplasia and above in lesions of the esophagus) cases were obtained to calculate the average screening cost per SDA detected, the incremental cost-effectiveness ratio (ICER) and protection rates. Sensitivity analysis was conducted to evaluate uncertainties.ResultsCompared to traditional strategy, all precision screening strategies have much lower average costs for detection of one SDA case ($7,148~$11,537 vs. $14,944). In addition, precision strategies 1&2 (strategies 1,2,3,4 described below) achieved higher effectiveness (143~150 vs. 136) and higher protection rates (87.7%~92.0% vs. 83.4%) at lower cost ($1,649,727~$1,672,221 vs. $2,032,386), generating negative ICERs (-$54,666/SDA~-$25,726/SDA) when compared to the traditional strategy. The optimal strategies within different willingness-to-pay (WTP) ranges were all precision screening strategies, and higher model sensitivities were adopted as WTP increased.ConclusionsPrecision screening strategy for esophageal cancer based on risk stratification is more cost-effective than use of traditional screening strategy and has practical implications for esophageal cancer screening programs in China.

Summary: Background: Previous risk prediction models taking esophageal malignant lesions detected during endoscopy as the primary outcome are not always sufficient to identify prevalent cases which are “overlooked” at screening. We aimed to update and externally validate our previous risk prediction model for malignant esophageal lesions by redefining the predicted outcome. Methods: 15,192 individuals from the Endoscopic Screening for Esophageal Cancer in China randomized controlled trial (ESECC trial, NCT01688908) were included as the training set, and 4576 participants from another population-based esophageal squamous cell carcinoma (ESCC) screening cohort (Anyang Esophageal Cancer Cohort Study, AECCS) served as the external validation set. Lesions with severe dysplasia or worse diagnosed at chromoendoscopy or identified via follow-up within 1 year after screening were defined as main outcome. Logistic regressions were applied to reconstruct the questionnaire-based prediction model using information collected before screening, with Akaike Information Criterion to determine the model structure. Findings: The final prediction model included age and its quadratic term, family history of ESCC, low body mass index (≤22 kg/m2), use of coal or wood as main fuel for cooking, eating rapidly, and ingestion of leftover food. The area under the curve was 0·77 (95% CI: 0·73–0·80) and 0·71 (95% CI: 0·65–0·78) in the training and validation set. When screening the top 50% or 10% of high-risk individuals within population, the detection rates can be increased in both cohorts, as compared to universal screening. Interpretation: The described tool may promote the efficiency of current national screening programs for ESCC and contribute to a precision screening strategy in high-risk regions in China. Funding: This work was supported by the National Natural Science Foundation of China (82073626, 81773501), the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), the National Key R&D Program of China (2021YFC2500405), the Beijing-Tianjin-Hebei Basic Research Cooperation Project (J200016), the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority (XXZ0204) and the Beijing Nova Program (Z201100006820093). Sponsors had no role in the study design, data collection, analysis, and interpretation of data.

Abstract Background This study aims to compare the performance of the recently developed Chinese (city) tariff of the EQ-5D-3L against the UK, US, Japanese and Korean tariffs in a general rural population in China. Methods From November 2015 to September 2016, 12,085 permanent residents aged 45–69 from 257 villages randomly selected from Hua County, Henan Province, China, were interviewed using EQ-5D-3L, and a one-on-one questionnaire investigation was used to collect data on factors associated with HRQOL. The health utility scores were calculated using the UK, US, Japanese, Korean and Chinese (city) tariffs. The agreement, known-groups validity and sensitivity of these five tariffs were evaluated. Transition scores for pairs of observed EQ-5D-3L health states were calculated and compared. Results The Korean tariff yielded the highest mean health utility score (0.963), followed by the Chinese (city) (0.948), US (0.943), UK (0.930) and Japanese (0.921) tariffs, but the differences in the scores of any two tariffs did not exceed the MCID. The Chinese (city) tariff showed higher ICC values (ICCs> 0.89, 95% CI:0.755–0.964) and narrower limits of agreement (0.099–0.167) than the Korean tariff [(ICCs> 0.71, 95% CI:0.451–0.955); (0.146–0.253)]. The Chinese (city) tariff had a higher relative efficiency and effect size statistics in 10 out of 11 variables as compared to the UK, US and Japanese tariffs. The Chinese (city) tariff (0.215) was associated with moderate mean absolute transition scores compared with the UK (0.342), US (0.230), Japanese (0.149) and Korean (0.189) tariffs for 1485 observed pairs of the EQ-5D-3L health states. Conclusions Health utility scores derived from the five tariffs differed. The Chinese (city) tariff was the most suitable of these tariffs and was without obvious weakness. We recommend adopting the Chinese (city) tariff when applying EQ-5D-3L to assess quality of life among the elderly in China’s agricultural region with socio-economic status similar to Hua County. Results of this study had provided a crucial basis for health surveys, health promotion projects, health intervention trials, and health economic evaluation taking HRQOL as a target in rural areas of China.

Abstract Background Heterogeneity should be carefully addressed to facilitate establishment of effective population-level blood lipid management. The primary aim of the study was to investigate gender heterogeneity in prevalence of dyslipidemia, including trends with age and associated factors in middle age rural Chinese. Methods This is a cross-sectional study based on a baseline investigation of a population-based randomized controlled trial in rural China, involving 26,378 permanent residents of age 45–69. The age-specific prevalence of dyslipidemia was estimated for men and women, and the trends of prevalence with age were compared. Logistic regression was used to explore the factors associated with prevalent risk of dyslipidemia. Results The overall prevalence of dyslipidemia was significantly higher in females than in males for borderline high and above (BHA) total cholesterol (TC ≥ 200 mg/dL), BHA triglycerides (TG ≥ 150 mg/dL) and BHA low-density lipoprotein cholesterol (LDL-C ≥ 130 mg/dL), but was lower for low high-density lipoprotein cholesterol (HDL-C

Abstract Objective To investigate the risk factors for osteonecrosis of the femoral head (ONFH) after the treatment of femoral neck fracture in patients under 60 years old. Methods A total of 250 cases of femoral neck fracture treated at 3 hospitals in Xuzhou from January 2002 to January 2016 were studied. The patients were followed up for 1~15 years, and the clinical data on femoral head necrosis after the femoral neck operation were analysed retrospectively. Risk factors were recorded, including age, gender, preoperative traction, time from injury to operation, reduction method, type of reduction, BMI, ASA classification, and quality of reduction. Logistic regression analysis was used to evaluate the independent risk factors for ONFH after treatment of femoral neck fracture. Results The duration of follow-up was 1~15 years, with an average of 7.5 years. None of the 250 patients had fracture non-union, but 40 (16%) had necrosis of the femoral head. The time to necrosis of the femoral head was 1~7 years after the operation, with an average of 3.8 years. Univariate analysis showed that the type of fracture, the quality of reduction, the removal of internal fixation, BMI and ASA classification were risk factors affecting necrosis of the femoral head in patients with femoral neck fracture, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that internal fixation, fracture type (displacement), reduction quality (dissatisfaction), BMI (> 25), and ASA grade (III + IV) were independent risk factors affecting femoral head necrosis in patients with femoral neck fracture. Conclusion A variety of high-risk factors for femoral head necrosis are present after surgery with hollow compression screws for femoral neck fracture in adults. Removal of internal fixation, type of fracture, quality of reduction, BMI, and ASA classification were the most important risk factors influencing the development of femoral head necrosis. During treatment, there should be some targeted measures to reduce the incidence of necrosis of the femoral head.

A numerical model is established based on the plasticity theory and a thermomechanical coupled finite element method (FEM) to simulate the hot isostatic pressing (HIP) process of atomized and milled Ti6Al4V powders and is then experimentally verified. Key material parameters related to the simulation are obtained by experimental and calculation methods. The HIP densification mechanism for two types of Ti6Al4V powders are clarified through the analysis of the powder flow and relative density distribution of compacts using the proposed model. The results indicate that the densification trends of the two powders are not much different under the same working conditions and that milled powder with a higher energy is more conducive to densification and can better overcome the “corner effect” compared to atomized powder. The equiaxed microstructure of the milled powder sintered body contributes to increasing its strength, whereas the lamellar microstructure of the atomized powder sintered body contributes to increasing its plasticity.

ObjectivesUpper gastrointestinal (G.I.) cancer screening has been conducted in China for decades. However, the economic burden for treatment “intensively” occurred in advance due to screening in resource-limited communities remain unclear.MethodsWe compared the treatment costs for upper G.I. cancers from the screening and control arms of a population-based randomized trial in a high-risk area for esophageal cancer (EC) in China based on claims data from the health insurance system in the local area which included whole population coverage.ResultsThe average out-of-pocket cost per treatment of EC in the screening arm was lower than that in the control arm ($5,972 vs. $7,557). This difference was a consequence of down-staging from screening which resulted in lower cost therapy for earlier stage cancers. Moreover, this result is similar for cardial and non-cardial gastric cancer in the two study arms ($7,933 vs. $10,605). However, three times as many (103 vs. 36) families in the screening arm suffered catastrophic health expenditure for all cancer types. The overall treatment cost for all EC patients in the screening arm ($1,045,119) was 2.44 times that in the control arm ($428,292), and the ratio for cardial and non-cardial gastric cancer was 1.12 ($393,261 vs. $351,557).ConclusionCancer treatment secondary to screening may triple the likelihood of catastrophic patient medical expenditure, and sharply increase the economic pressure on the local community, particularly for cancer types which are of high prevalence. Financial support for patients and the health insurance system should be taken into consideration when planning budgets for cancer screening programs in communities which are resource-limited.

BackgroundMuscle fatigue is a crucial indicator to determine whether training is in place and to protect trainers.PurposeTo make full use of morphological information of surface EMG and ECG signals in the time domain, a new idea and method for the fatigue assessment of exercise muscles based on data fusion is proposed in this paper.MethodssEMG and ECG time series with the same length were obtained by signal preprocessing and sequence normalization, feature extraction of sequence tenses was realized by a deep learning network based on sequential convolution and signal fusion model of muscle fatigue evaluation was established by D-S evidence theory.ExperimentThirty volunteers were recruited and divided into three groups. ECG signals and sEMG signals at the biceps brachii of the right upper limb were monitored in a 20-minute exercise cycle.ResultsThe prediction result of TCN based on time domain signal is better than the commonly used KNN and SVM recognition algorithm, and the recognition accuracy of relaxed, excessive and fatigue by D-S fusion was 89%, 86%, 88.5%. The accuracy was 0.9055, 0.9494 and 0.9269, respectively. The recall rates of the three conditions were 0.9303, 0.9570 and 0.9435. The F-score of the three conditions was 0.8911, 0.8764 and 0.8837, respectively.ConclusionBased on time series and time series convolutional network, sEMG and ECG fusion of motor muscle recognition method can better distinguish different state information and has certain practical value in the fields of muscle evaluation, clinical diagnosis, wearable devices and so on.

Aiming at solving the problems of small fault data samples and insufficient remaining useful life (RUL) prediction accuracy of nuclear power machinery, a method based on an exponential degradation model is proposed to predict the RUL of equipment after the failure warning system alarm. After data preprocessing, time-domain feature extraction, selection, and dimensionality reduction fusion of multiple degradation variables, the exponential degradation model is constructed based on the Bayesian process, and prior information is used. As an application, the RUL of a nuclear power turbine was calculated based on actual monitoring data, the α−λ precision curve was used to evaluate the prediction effect, and the RUL prediction results verified the effectiveness of the proposed method.

The simultaneous need for energy efficiency and indoor comfort may not be met by existing air source heat pump (ASHP) technology. The novelty of this study lies in the use of a new gravity-driven radiator as the indoor heating terminal of ASHPs, aiming to provide an acceptable indoor comfort with improved energy efficiency. To confirm and quantify the performance improvement due to the proposed system retrofit, a field test was conducted to examine the system performance under real conditions. In the tests, measurements were made on the refrigerant- and air-side of the system to characterize its operational characteristics. Results showed that the proposed radiator has a rapid thermal response, which ensures a fast heat output from the system. The proposed system can create a stable and uniform indoor environment with a measured air diffusion performance index of 80%. The energy efficiency of the proposed system was also assessed based on the test data. It was found that the system’s first law efficiency is 42.5% higher than the hydraulic-based ASHP system. In terms of the second law efficiency, the compressor contributes the most to the overall system exergy loss. The exergy efficiency of the proposed system increases with the outdoor temperature and varies between 35.02 and 38.93% in the test period. The research results and the analysis methodology reported in this study will be useful for promoting the technology in search of energy efficiency improvement in residential and commercial buildings.

Chronic hepatitis B virus (HBV) infection is a risk factor for hepatocellular carcinoma (HCC) and is associated with immune tolerance to HBV. Here the authors show, in a transgenic mouse model, that rescuing T cells function via inhibition of co-inhibitory receptor TIGIT results in HCC development via supporting inflammation.

γδ T cells are major producers of IL-17A in response to microbial infection. Here the authors show that a high load of commensal microbes can maintain homeostasis of IL-17A+γδ T cells in the liver via CD1d antigen presentation, with implications for liver diseases.

The ability of the host to clear hepatitis B virus (HBV) is closely correlated to the establishment of commensal microbiota. However, how microbiota affects anti-HBV immunity is still unclear. Using a well-known hydrodynamical HBV transfection mouse model and treatment with antibiotics (Atb), we explored the change in adaptive immunity (CD4+ cells, germinal center B cells and anti-HBs Ab). In our setting, normal mice exhibited complete clearance of HBV within 6 weeks post-hydrodynamic injection (HDI) of HBV-containing plasmid, whereas Atb-treated mice lost this capacity, showing high serum level of hepatitis B surface antigen (HBsAg) without hepatitis B surface antibodies (anti-HBs), similar as what happened in Rag1−/− mice or CD4−/− mice, suggesting that microbiota may influence the function of CD4+ T cells. Furthermore, the numbers of splenic and hepatic effector CD4+ T cells (CD44hiCD62L−CD4+ T cells) both decreased with impaired function (IFN-γ synthesis), resulting in lower frequency of germinal center B cells and CD4+ follicular helper T cells, and impaired anti-HBs production. We further tried to find the bacterial species responsible for maintaining anti-HBV immunity, and found that each antibiotic alone could not significantly influence HBV clearance compared to antibiotic combination, suggesting that global commensal microbial load is critical for promoting HBV clearance. We also confirmed that TLRs (e.g., TLR2, 4, 9) are not major players in immune clearance of HBV using their agonists and knock-out mice. These results suggest that commensal microbiota play an important role in maintaining CD4+ T cell immunity against HBV infection.

A Bayesian framework-based approach is proposed for the quantitative validation and calibration of the kriging metamodel established by simulation and experimental training samples of the injection mechanism in squeeze casting. The temperature data uncertainty and non-normal distribution are considered in the approach. The normality of the sample data is tested by the Anderson−Darling method. The test results show that the original difference data require transformation for Bayesian testing due to the non-normal distribution. The Box−Cox method is employed for the non-normal transformation. The hypothesis test results of the calibrated kriging model are more reliable after data transformation. The reliability of the kriging metamodel is quantitatively assessed by the calculated Bayes factor and confidence. The Bayesian factor and the confidence level results indicate that the kriging model demonstrates improved accuracy and is acceptable after data transformation. The influence of the threshold ε on both the non-normally and normally distributed data in the model is quantitatively evaluated. The threshold ε has a greater influence and higher sensitivity when applied to the normal data results, based on the rapid increase within a small range of the Bayes factors and confidence levels.

If a traditional ideal-gas ejector model is used to evaluate the performance of a wet vapor ejector, large deviations from the experimental results will be unavoidable. Moreover, the model usually fails to assess the ejector performance at subcritical mode. In this paper, we proposed a novel model to evaluate the performance of both dry and wet vapors ejectors over the entire operational range at critical or subcritical modes. The model was obtained by integrating the linear characteristic equations of ejector with critical and breakdown points models, which were developed based on the assumptions of constant-pressure mixing and constant-pressure disturbing. In the models, the equations of the two-phase speed of sound and the property of real gas were introduced and ejector component efficiencies were optimized to improve the accuracy of evaluation. It was validated that the proposed model for the entire operational range can achieve a better performance than those existing for R134a, R141b and R245fa. The critical and breakdown points models were further used to investigate the effect of operational parameters on the performance of an ejector refrigeration system (ERS). The theoretical results indicated that decreasing the saturated generating temperature when the actual condensing temperature decreases, and/or increasing the saturated evaporating temperature can improve the performance of ERS significantly. Moreover, superheating the primary flow before it enters the ejector can further improve the performance of an ERS using R134a as a working fluid.

Nature Communications 8 Article number:13839 (2017); Published 9 January 2017; Updated 10 April 2017 The HTML version of this Article previously published had an incorrect volume number of 7; it should have been 8. This has now been corrected in the HTML; the PDF version of the paper was correct from the time of publication.