Prediction of Treatment Effect of SLE-ITP Patients Based on Cost-Sensitive Neural Network and Variational Autoencoder.

OBJECTIVE: The aim of the study was to examine the factors influencing the therapeutic effect of patients with systemic lupus erythematosus combined with immune thrombocytopenia (SLE-ITP) and develop a prediction model to predict the therapeutic effect of SLE-ITP. METHODS: Three hundred twenty-four SLE-ITP patients were retrieved from the electronic health record database of SLE patients in Jiangsu Province according to the latest treatment response criteria for ITP. We adopted the Cox model based on the least absolute shrinkage and selection operator to explore the impact factors affecting patient therapeutic effect, and we developed neural network model to predict therapeutic effect, and in prediction model, cost-sensitivity was introduced to address data category imbalance, and variational autoencoder was used to achieve data augmentation. The performance of each model was evaluated by accuracy and the area under the receiver operator curve. RESULTS: The results showed that B-lymphocyte count, H-cholesterol level, complement-3 level, anticardiolipin antibody, and so on could be used as predictors of SLE-ITP curative effect, and abnormal levels of alanine transaminase, immunoglobulin A, and apolipoprotein B predicted adverse treatment response. The neural network treatment effect prediction model based on cost-sensitivity and variational autoencoder was better than the traditional classifiers, with an overall accuracy rate closed to 0.9 and a specificity of more than 0.9, which was useful for clinical practice to identify patients at risk of ineffective treatment response and to achieve better individualized management. CONCLUSIONS: By predicting the curative effect of SLE-ITP, the severity of patients can be determined, and then the best treatment strategy can be planned to avoid ineffective treatment.

Salmonellosis outbreak archive in China: data collection and assembly.

Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.

Clonal Propagation and Assessment of Biomass Production and Saponin Content of Elite Accessions of Wild Paris polyphylla var. yunnanensis.

Paris polyphylla var. yunnanensis is an endangered medicinal plant endemic to China with great economic importance for the pharmaceutical industry. Two significant barriers to its commercial development are the long duration of its seed germination and the frequency of interspecific hybridization. We developed a method for clonal propagation of Paris polyphylla var. yunnanensis and successfully applied it to selected elite wild plants, which could become cultivar candidates based on their biomass production and saponin content. In comparison to the traditional method, somatic embryogenesis produced an average of 63 somatic embryos per gram of callus in just six weeks, saving 12 to 15 months in plantlet production. The produced in vitro plantlets were strong and healthy and 94% survived transplanting to soil. Using this method, four candidate cultivars with diverse morphologies and geographic origins were clonally reproduced from selected elite wild accessions. In comparison to those obtained with the traditional P. polyphylla propagation technique, they accumulated higher biomass and polyphyllin levels in rhizomes plus adventitious roots during a five-year period. In conclusion, somatic embryogenesis-based methods offer an alternate approach for the rapid and scaled-up production of P. polyphylla, as well as opening up species conservation options.

Analysis of factors affecting nonalcoholic fatty liver disease in Chinese steel workers and risk assessment studies.

BACKGROUND: The global incidence of nonalcoholic fatty liver disease (NAFLD) is rapidly escalating, positioning it as a principal public health challenge with significant implications for population well-being. Given its status as a cornerstone of China's economic structure, the steel industry employs a substantial workforce, consequently bringing associated health issues under increasing scrutiny. Establishing a risk assessment model for NAFLD within steelworkers aids in disease risk stratification among this demographic, thereby facilitating early intervention measures to protect the health of this significant populace. METHODS: Use of cross-sectional studies. A total of 3328 steelworkers who underwent occupational health evaluations between January and September 2017 were included in this study. Hepatic steatosis was uniformly diagnosed via abdominal ultrasound. Influential factors were pinpointed using chi-square (χ2) tests and unconditional logistic regression analysis, with model inclusion variables identified by pertinent literature. Assessment models encompassing logistic regression, random forest, and XGBoost were constructed, and their effectiveness was juxtaposed in terms of accuracy, area under the curve (AUC), and F1 score. Subsequently, a scoring system for NAFLD risk was established, premised on the optimal model. RESULTS: The findings indicated that sex, overweight, obesity, hyperuricemia, dyslipidemia, occupational dust exposure, and ALT serve as risk factors for NAFLD in steelworkers, with corresponding odds ratios (OR, 95% confidence interval (CI)) of 0.672 (0.487-0.928), 4.971 (3.981-6.207), 16.887 (12.99-21.953), 2.124 (1.77-2.548), 2.315 (1.63-3.288), 1.254 (1.014-1.551), and 3.629 (2.705-4.869), respectively. The sensitivity of the three models was reported as 0.607, 0.680 and 0.564, respectively, while the precision was 0.708, 0.643, and 0.701, respectively. The AUC measurements were 0.839, 0.839, and 0.832, and the Brier scores were 0.150, 0.153, and 0.155, respectively. The F1 score results were 0.654, 0.661, and 0.625, with log loss measures at 0.460, 0.661, and 0.564, respectively. R2 values were reported as 0.789, 0.771, and 0.778, respectively. Performance was comparable across all three models, with no significant differences observed. The NAFLD risk score system exhibited exceptional risk detection capabilities with an established cutoff value of 86. CONCLUSIONS: The study identified sex, BMI, dyslipidemia, hyperuricemia, occupational dust exposure, and ALT as significant risk factors for NAFLD among steelworkers. The traditional logistic regression model proved equally effective as the random forest and XGBoost models in assessing NAFLD risk. The optimal cutoff value for risk assessment was determined to be 86. This study provides clinicians with a visually accessible risk stratification approach to gauge the propensity for NAFLD in steelworkers, thereby aiding early identification and intervention among those at risk.

The trends in death of primary liver cancer caused by specific etiologies worldwide: results from the Global Burden of Disease Study 2019 and implications for liver cancer management.

BACKGROUND: Over past decades, epidemiological patterns of liver cancer (LC) have changed dramatically. The Global Burden of Disease (GBD) study provides an opportunity for tracking the progress in cancer control with its annual updated reports at national, regional and global level, which can facilitate the health decision-making and the allocation of health resources. Therefore, we aim to estimate the global, regional and national trends of death caused by liver cancer due to specific etiologies and attributable risks from 1990 to 2019. MATERIALS AND METHODS: Data was collected from the GBD study 2019. Estimated annual percentage changes (EAPC) were used to quantify the trends of age-standardized death rate (ASDR). We applied a linear regression for the calculation of estimated annual percentage change in ASDR. RESULTS: From 1990 to 2019, the ASDR of liver cancer decreased globally (EAPC = - 2.23, 95% confidence interval [CI]: - 2.61 to - 1.84). Meanwhile, declining trends were observed in both sexes, socio-demographic index (SDI) areas, and geographies, particularly East Asia (EAPC = - 4.98, 95% CI: - 5.73 to - 4.22). The ASDR for each of the four major etiologies fell globally, while liver cancer caused by hepatitis B had the largest drop (EPAC = - 3.46, 95% CI: - 4.01 to - 2.89). China has had dramatic decreases in death rates on a national scale, particularly when it comes to the hepatitis B etiology (EAPC = - 5.17, 95% CI: - 5.96 to - 4.37). However, certain nations, such as Armenia and Uzbekistan, saw a rise in liver cancer mortality. Controlling smoking, alcohol, and drug use contributed to a drop in LC-related mortality in the majority of socio-demographic index areas. Nevertheless, the excessive body mass index (BMI) was portrayed as the underlying cause for LC fatalities. CONCLUSION: From 1990 to 2019, there was a worldwide decrease in deaths caused by liver cancer and its underlying causes. However, rising tendencies have been observed in low-resource regions and countries. The trends in drug use- and high BMI-related death from liver cancer and its underlying etiologies were concerning. The findings indicated that efforts should be increased to prevent liver cancer deaths through improved etiology control and risk management.

Longitudinal assessment of cardiac parameters through MRI in breast cancer patients treated with anti-HER2 therapy.

BACKGROUND: We evaluated the early changes in left ventricular (LV) volumetric, functional, and tissue characteristics in human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients treated with trastuzumab and/or pertuzumab at cardiac magnetic resonance imaging (MRI). METHODS: HER2-positive breast cancer patients undergoing planned anti-HER2 therapy and nonanthracycline-based chemotherapy were enrolled and subdivided into dual anti-HER2 (trastuzumab plus pertuzumab) group and trastuzumab group. Cardiac MRI was performed before treatment and three months after starting, covering ventricular volumes, cardiac function, systolic myocardial strain, myocardial oedema, and T1 and T2 relaxation times. Cardiac dysfunction was primarily defined as a > 10% reduction in LV ejection fraction (LVEF) to < 55% and/or a > 15% global longitudinal strain (GLS) change at the follow-up MRI examination. RESULTS: Twenty-four HER2-positive patients were evaluated (16 in the dual anti-HER2 group, 8 in the trastuzumab group). Six patients developed cardiac dysfunction at follow-up, five of them in the dual anti-HER2 group. One patient developed symptomatic heart failure, and five patients developed asymptomatic cardiac dysfunction. Patients displayed significantly decreased systolic function and increased T1 and T2 relaxation time at follow-up (p ≤ 0.031). Systolic dysfunction remained significant in the dual anti-HER2 group. The decrease in GLS in the trastuzumab group was not significant (p = 0.169). T1 and T2 relaxation times tended to increase, but this was not significant at subgroup analysis. CONCLUSIONS: Cardiac MRI scans showed frequent signs of subclinical cardiotoxicity after short-term anti-HER2 therapy and nonanthracycline-based chemotherapy; the effect was slightly stronger in patients treated with dual therapy. KEY POINTS: • A frequent subclinical cardiotoxicity was detected by cardiac magnetic resonance imaging after short-term anti-human epidermal growth factor receptor 2 (HER2) therapy. • The change in myocardial strain was more marked in patients treated with dual (trastuzumab plus pertuzumab) than with trastuzumab only anti-HER2 therapy. • Cardiotoxicity surveillance through MRI is an interesting option particularly in patients treated with dual anti-HER2 therapy.

Assessment of left heart dysfunction to predict doxorubicin cardiotoxicity in children with lymphoma.

Objectives: The objectives of this study were to assess the changes in the left myocardial function after chemotherapy for childhood lymphoma and observe the predictive or monitor value for cancer treatment-related cardiac dysfunction (CTRCD) by speckle-tracking echocardiography. Methods: A total of 23 children with histopathological diagnoses of lymphoma were included, with age-matched normal controls. Comparative analysis of clinical serological tests and left heart strain parameters in children with lymphoma, including left ventricular global longitudinal strain (LVGLS); global myocardial work (GMW) indices, which include global work index (GWI), global constructive work (GCW), global wasted work, and global work efficiency; and the LS of subendocardial, middle, and subepicardial layer myocardium during left ventricular systole were measured: left atrial strain of reservoir phase (LASr), left atrial strain of conduit phase (LAScd), and left atrial strain of contraction phase (LASct). Results: One-way ANOVA showed that GLS, GWI, GCW, LASr, and LAScd were closely associated with CTRCD and multivariate logistic regression analysis showed that GLS was the most sensitive predictor for detecting patients at lofty risk of anthracycline-related cardiotoxicity. Both before and after chemotherapy, GLS in the left ventricle showed a pattern of basal segment < middle segment < apical segment and subepicardial < middle < subendocardial layer (p < 0.05), and the degree of decrease also showed a regular pattern of epicardial layer < middle layer < subendocardial layer while the difference was not significant (p > 0.05). After chemotherapy, maximum flow rate in early mitral relaxation/left atrial systolic maximum flow rate (E/A) and left atrial volume index of each group were in the normal range, and the values of LASr, LAScd, and LASct slightly increased in the second cycle and decreased significantly in the fourth cycle after chemotherapy, reaching the lowest level; LASr and LAScd were positively correlated with GLS. Conclusion: LVGLS is a more sensitive and earlier indicator to predict CTRCD compared with conventional echocardiography-related parameters and serological markers, and GLS of each myocardial layer showed a certain regularity. Left atrial strain can be used for early monitoring of cardiotoxicity in children with lymphoma after chemotherapy.

Development and Internal Validation of Risk Assessment Models for Chronic Obstructive Pulmonary Disease in Coal Workers.

Coal workers are more likely to develop chronic obstructive pulmonary disease due to exposure to occupational hazards such as dust. In this study, a risk scoring system is constructed according to the optimal model to provide feasible suggestions for the prevention of chronic obstructive pulmonary disease in coal workers. Using 3955 coal workers who participated in occupational health check-ups at Gequan mine and Dongpang mine of Hebei Jizhong Energy from July 2018 to August 2018 as the study subjects, random forest, logistic regression, and convolutional neural network models are established, and model performance is evaluated to select the optimal model, and finally a risk scoring system is constructed according to the optimal model to achieve model visualization. The training set results show that the logistic, random forest, and CNN models have sensitivities of 78.55%, 86.89%, and 77.18%; specificities of 85.23%, 92.32%, and 87.61%; accuracies of 81.21%, 85.40%, and 83.02%; Brier scores of 0.14, 0.10, and 0.14; and AUCs of 0.76, 0.88, and 0.78, respectively, and similar results are obtained for the test set and validation set, with the random forest model outperforming the other two models. The risk scoring system constructed according to the importance ranking of random forest predictor variables has an AUC of 0.842; the evaluation results of the risk scoring system shows that its accuracy rate is 83.7% and the AUC is 0.827, and the established risk scoring system has good discriminatory ability. The random forest model outperforms the CNN and logistic regression models. The chronic obstructive pulmonary disease risk scoring system constructed based on the random forest model has good discriminatory power.

Comparison of the caecal microbial community structure and physiological indicators of healthy and infection Eimeria tenella chickens during peak of oocyst shedding.

Eimeria tenella (E. tenella), an important intestinal parasite of chicken caeca, causes coccidiosis and brings large economic losses to the poultry industry annually. Gut microorganismal alterations directly affect the health of the body. To understand how E. tenella affects its host, we analysed the changes in caecal microbial diversity and the physiological and morphological changes during the peak of oocyst shedding. Infected and healthy chickens differed significantly in caecal pathology and blood indicators. At the genus level, the abundances of Faecalibacterium, Clostridium, Lachnoclostridium, Gemmiger, Flavonifractor, Pseudoflavonifractor and Oscillibacter were significantly decreased in the infected samples, whereas Escherichia, Nocardia and Chlamydia were significantly increased. Functional gene pathways related to replication, recombination and repair, and transcription were significantly decreased, and functional genes related to metabolism were highly significantly reduced in the infected samples. Furthermore, in the infected samples, E. tenella reduced the haemoglobin levels and red blood cell counts, greatly reduced the beneficial bacteria and increased the potentially pathogenic bacteria. This study provides a research basis for further understanding the pathogenic mechanisms of E. tenella and provides insight for potential new drug development.RESEARCH HIGHLIGHTS First simultaneous description of caecal microbiota and physiological indicators during E. tenella infection.Metagenomics used to explore functional properties of chicken caecal microbiota during E. tenella infection.Caecal microbial compositions and functional genes altered significantly after infection.Blood indicators and caecal morphology were significantly altered in the infected group.

Burden of pancreatic cancer along with attributable risk factors in China from 1990 to 2019, and projections until 2030.

OBJECTIVES: Understanding epidemiology trends and patterns of pancreatic cancer in China from 1990 to 2019 and predicting the burden to 2030 will provide foundations for future policies development. METHODS: We collected incidence, mortality, and disability-adjusted life-years (DALYs) data of pancreatic cancer in China from 1990 to 2019 based on the Global Burden of Disease Study 2019. We calculated the estimated annual percentage change (EAPC) to depict the trends of pancreatic cancer burden and predicted the incidence and mortality in the next decade by using a Bayesian age-period-cohort analysis. RESULTS: The number of incident cases sharply increased from 26.77 thousand in 1990 to 114.96 thousand in 2019, the age-standardized incidence rate (ASIR) nearly doubled from 3.17 per 100,000 in 1990 to 5.78 per 100,000 in 2019, with an EAPC of 2.32 (95% confidence interval [CI]: 2.12, 2.51). The mortality and DALYs presented a similar pattern with incidence. The dominant risk factor for pancreatic cancer was smoking, but the contribution of high body-mass index increased from 1990 to 2019. We projected that the incident cases and deaths of pancreatic cancer would increase to 218.79 thousand and 222.97 thousand, respectively, in 2030 with around 2 times growth. CONCLUSIONS: During the past three decades, the incidence, mortality and DALYs of pancreatic cancer gradually increased in China, and the absolute number and rate of pancreatic cancer burden would continue to rise over the next decade. Comprehensive policies and strategies need to be implemented to reduce the incidence and mortality.

Global magnitude and temporal trends of idiopathic developmental intellectual disability attributable to lead exposure from 1990 to 2019: Results from Global Burden of Disease Study.

As an important environmental pollutant, lead exposure can result in idiopathic developmental intellectual disability (IDII). However, the latest spatiotemporal patterns across the world are unclear. Therefore, in this study, the global burden of lead exposure-related IDII was assessed using the Global Burden of Disease (GBD) study (2019). The data were downloaded from the Institute for Health Metrics and Evaluation (IHME), and the estimated annual percentage change (EAPC) was calculated to assess the changing trend of the age-standardized disability-adjusted life-years (DALYs) rates (ASDR) of global IDII attributed to lead exposure. In 2019, the number of global DALYs of IDII attributed to lead exposure was 2.72 million, the corresponding ASDR was 35.70 per 100,000. The ASDR was highest in children and adolescents, and low- and middle-income countries. From 1990 to 2019, the global number of DALYs of IDII attributable to lead exposure increased by 7.89%, while the ASDR of IDII decreased by 19.19% [EAPC = -0.78, 95% confidence interval (CI): (-0.90, -0.66)]. The downward trends were seen in most GBD regions and countries, especially in high-income countries, but 11 countries presented an upward trend. Therefore, it is important to continue to improve primary mental healthcare globally, especially in low- and middle-income countries. Meanwhile, the implementation of effective strategies to reduce lead exposure should be continually strengthened.

Prediction of diagnosis results of rheumatoid arthritis patients based on autoantibodies and cost-sensitive neural network.

OBJECTIVES: To analyze and evaluate the effectiveness of the detection of single autoantibody and combined autoantibodies in patients with rheumatoid arthritis (RA) and related autoimmune diseases and establish a machine learning model to predict the disease of RA. METHODS: A total of 309 patients with joint pain as the first symptom were retrieved from the database. The effectiveness of single and combined antibodies tests was analyzed and evaluated in patients with RA, a cost-sensitive neural network (CSNN) model was used to integrate multiple autoantibodies and patient symptoms to predict the diagnosis of RA, and the ROC curve was used to analyze the diagnosis performance and calculate the optimal cutoff value. RESULTS: There are differences in the seropositive rate of autoimmune diseases, the sensitivity and specificity of single or multiple autoantibody tests were insufficient, and anti-CCP performed best in RA diagnosis and had high diagnostic value. The cost-sensitive neural network prediction model had a sensitivity of up to 0.90 and specificity of up to 0.86, which was better than a single antibody and combined multiple antibody detection. CONCLUSION: In-depth analysis of autoantibodies and reliable early diagnosis based on the neural network could guide specialized physicians to develop different treatment plans to prevent deterioration and enable early treatment with antirheumatic drugs for remission. Key Points • There are differences in the seropositive rate of autoimmune diseases. • This is the first study to use a cost-sensitive neural network model to diagnose RA disease in patients. • The diagnosis effect of the cost-sensitive neural network model is better than a single antibody and combined multiple antibody detection.

Spatio-temporal multi-task network cascade for accurate assessment of cardiac CT perfusion.

The assessment of myocardial perfusion has become increasingly important in the early diagnosis of coronary artery disease. Currently, the process of perfusion assessment is time-consuming and subjective. Although automated methods by threshold processing have been proposed, they cannot obtain an accurate perfusion assessment. Thus, there is a great clinical demand to obtain a rapid and accurate assessment of myocardial perfusion through a standard procedure using an automated algorithm. In this work, we present a spatio-temporal multi-task network cascade (ST-MNC) to provide an accurate and robust assessment of myocardial perfusion. The proposed network captures patch-based spatio-temporal representations for each pixel through a spatio-temporal encoder-decoder network. Then the multi-task network cascade uses spatio-temporal representations as shared features to predict various perfusion parameters and myocardial ischemic regions. Extensive experiments on CT images of 232 subjects demonstrate ST-MNC could produce a good approximation for perfusion parameters and an accurate classification for ischemic regions. These results show that our proposed method can provide a fast and accurate assessment of myocardial perfusion.

The Mixed Effect of China's New Health Care Reform on Health Insurance Coverage and the Efficiency of Health Service Utilisation: A Longitudinal Approach.

In 2009, China launched a new health care reform as it endeavoured to develop a tiered system of disease diagnosis and treatment to promote the integration of medical resources. This was important for improving service capacity and building medical alliances that would eventually lead to improved health service utilisation efficiency. However, while the 2009 reform aimed to provide universal health insurance coverage to all citizens, its overall effect on health service utilisation efficiency remains unclear. We aimed to examine the new health care reform's mixed effect by applying a longitudinal study using China Health and Nutrition Survey (CHNS) data and the difference-in-difference (DID) method to estimate the health reform's impact on health insurance coverage rate. Then, we studied whether the increase in health insurance coverage rate affected health service utilisation efficiency in China. Our results showed that the increase in insurance coverage rate has indeed made expensive medical services available to low-income individuals. However, it also increased the likelihood of use of hospitals rather than primary care facilities, since there is more insurance cover for outpatient visits, which has led to an increased demand for quality services. This effect has generated a negative impact on health care utilisation which directly pertains to systemic inefficiency. This study thus indicates that China's latest health reform requires further policies to improve its overall efficiency.