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Abstract Background The long-term survival in hepatocellullar carcinoma (HCC) patients after transarterial chemoembolization (TACE) remains dismal due to local and/or regional recurrence as well as distant metastasis. The efficacy of sorafenib in advanced HCC has been demonstrated and brought great hope. Recently, the use of sorafenib in combination with TACE for BCLC stage B and C HCC patients was recommended. However, data on this dual-modality treatment is little, and its advantage over TACE alone has not been addressed. The present study sought to understand the efficacy of the combination of TACE and sorafenib in the treatment of advanced HCC. Methods Between June 2008 and Feb 2011, 45 patients with advanced HCC were enrolled and treated with sorafenib in combination with TACE according to an institutional protocol of the Zhongshan hospital, Fudan University. The control group of 45 other HCC patients with similar characteristics treated with TACE alone in the same period of time in our institute were selected for retrospective comparison of the treatment outcomes especially overall survival time. Adverse reactions induced by sorafenib were observed and recorded. Results The median overall survival time of the combined treatment group was 27 (95% Confidence Interval: 21.9–32.1) months, and that of TACE alone group was 17 months (95% Confidence Interval: 8.9–25.0) months (P = 0.001). Patients required significantly less frequent TACE for their symptomatic treatment after the initiation of sorafenib therapy. The most common adverse events associated with sorafenib were hand-foot skin reaction, rash and diarrhea. Of CTCAE grade IV or V toxicity was observed. Conclusion TACE combined sorafenib significantly prolonged median overall survival time of patients with advanced HCC.

Accurate prediction of PM 10 concentration is important for effectively managing PM 10 exposure and mitigating health and economic risks posed to humans in dry bulk ports. However, accurately capturing the time-series nonlinear variation characteristics of PM 10 concentration is challenging owing to the specific intensity of port operation activities and the influence of meteorological factors. To address such challenges, a novel combined deep learning model （CLAF） was proposed, merging cascaded convolutional neural networks （CNN）, long short-term memory （LSTM）, and an attention mechanism （AM）. This integrated model aimed to forecast hourly PM 10 concentration in dry bulk ports. First, using the random forest characteristic importance algorithm, the distinct meteorological factors were identified among the selected five meteorological factors. These selected factors were incorporated into the prediction model along with the PM 10 concentration. Subsequently, the CNN layer was employed to extract high-dimensional time-varying features from the input variables, while the LSTM layer captured sequential features and long-term dependencies. In the AM layer, different weights were assigned to the output components of the LSTM layer to amplify the effects of important information. Finally, three evaluation metrics were applied to compare the performance of the CLAF model with three basic models and three commonly used prediction models. Real-case data was collected and used in this study. Comparison results demonstrated that considering the meteorological factors could improve the prediction accuracy and fitting performance of PM 10 concentration in ports. The CLAF model reduced the mean absolute error statistic by 13.92%-56.9%, decreased the mean square error statistic by 45.99%-81.02%, and improved the goodness-of-fit statistic by 3.2%-15.5%.

Objective To analyze the current situation of dietary diversity and caregiver self-efficacy for complementary feeding among infants and young children aged 6 to 23 months in rural Nanchong city,Sichuan province,and to explore the relationship between dietary diversity and caregiver self-efficacy. Methods Multi-stage randomized cluster sampling method was used to select infants and young children aged 6 to 23 months and their caregivers in rural areas of Nanchong city,Sichuan province as the subjects.A structured questionnaire was designed to collect the basic information of the subjects,dietary diversity,and caregiver self-efficacy for complementary feeding.Multivariate Logistic regression was adopted to analyze the relationship between the dietary diversity and caregiver self-efficacy for complementary feeding of infants and young children. Results A total of 770 pairs of infants and young children and their caregivers were included.The minimum pass rate of dietary diversity was 61.56%(474/770) for all the infants and young children and 45.00%(108/240),69.16%(287/415),and 68.70%(79/115) for the infants and young children aged 6 to 11,12 to 17,and 18 to 23 months,respectively.The results of regression analysis showed that the caregiver self-efficacy of complementary feeding was a contributing factor for qualified dietary diversity of infants and young children in the case of other confounders being controlled( OR =1.42,95% CI =1.17-1.73, P <0.001). Conclusion The dietary diversity for infants and young children in rural Nanchong city,Sichuan province needs to be improved,and caregivers with higher self-efficacy of complementary feeding are more likely to provide diversified complementary feeding for infants and young children.

Objective To analyze the prevalence of coronary heart disease among community residents over 18 years old in Jinjiang district of Chengdu city,Sichuan province,and explore its associated factors,so as to provide a reference for the prevention and control of coronary heart disease in communities.Methods From October 15 to November 10 in 2021,a total of 5220 adult residents from 33 communities in Jinjiang were selected by multi-stage stratified random sampling for face-to-face questionnaire survey,physical examination,and laboratory blood test.Binary Logistic regression was employed to predict the factors associated with coronary heart disease among adult residents in Jinjiang.Results The crude and standard prevalence rates of coronary heart disease among 5220 adult residents were 3.39% and 2.11%,respectively.Logistic regression analysis showed that age ( OR =1.068,95% CI =1.051-1.086, P <0.001),depressive symptoms ( OR =1.639,95% CI =1.037-2.591, P =0.034),regular exercise ( OR =0.584,95% CI =0.378-0.902, P =0.015),elevated blood pressure ( OR =3.529,95% CI =2.344-5.312, P <0.001),dyslipidemia ( OR =2.152,95% CI =1.291-3.587, P =0.003),and core knowledge score of chronic diseases ( OR =1.144,95% CI =1.066-1.228, P <0.001) were associated with coronary heart disease among adult residents in Jinjiang.Conclusions The prevalence of coronary heart disease is high among adult residents in Jinjiang district of Chengdu.The urban residents who are older,have depressive symptoms,lack of exercise,elevated blood pressure,dyslipidemia,and score higher on core knowledge of chronic diseases are prone to coronary heart disease.