Background and aims As a ferroptosis inducer, sorafenib, a first-line treatment for hepatocellular carcinoma (HCC), has a significant antitumor effect. Nonetheless, HCC patients frequently develop sorafenib resistance. Here, we investigated the impacts of progestagen-associated endometrial protein (PAEP), which controls sorafenib resistance and tumorigenesis in HCC. Furthermore, we investigated the function of PAEP and the underlying molecular mechanisms that cause HCC ferroptosis when sorafenib is applied. Methods Western blot analysis, cell proliferation, colony formation and animal experiments were performed to investigate the function of PAEP in sorafenib resistance and tumorigenesis in HCC. We detected the levels of reactive oxygen species, iron, and malondialdehyde and preformed transmission electron microscopy to investigate the relationship between PAEP and ferroptosis. Co-immunoprecipitation (co-IP) assay was performed to investigate the underlying molecular mechanisms of PAEP that cause HCC ferroptosis. Results PAEP was significantly overexpressed in HCC tissues, and this was associated with a poor clinical prognosis. PAEP silencing dramatically reduced HCC cells’ malignant phenotype. We found that sorafenib-induced ferroptosis was more sensitive to HCC cells with PAEP knockdown. Furthermore, the orthotopic cell line-derived xenograft mouse model results showed that sorafenib sensitivity can be effectively increased in vivo by PAEP knockdown. We determined that transferrin (TF) was a PAEP target using the String database, and we further supported this finding with Co-IP analysis. Additionally, on sorafenib-induced ferroptosis in HCC cells, TF partially reversed the effects of PAEP knockdown. Conclusions Our research indicates that PAEP may be a potential biomarker for predicting sorafenib resistance in HCC and disruption of PAEP expression may be a potential cancer-directed therapeutic option for HCC.

Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (https://hlse.cn/), with the aim of synthesizing, evaluating, translating, and applying lifestyle-related evidence resources. This paper aims to introduce the functional module design of the evidence translation system, the system development process and testing, introduce the interface design and function demonstration, and explain the significance of constructing the HLSE.

  Objective   To systematically assess the applicability of the clinical practice guidelines (CPGs) integrating Chinese and western medicine, thereby providing reference for enhancing their future usability.   Methods   PubMed, Web of Science, Embase, SinoMed, WanFang Data, and CNKI databases were searched for guidelines for the integration of Chinese and western medicine. Supplementary searches of Chinese Medical Association, Chinese Medicine Administration, MedSci websites, Website of China Association of Chinese Medicine, Medlive, Website of Dangdang, Chinese Association of Integrative Medicine and World Federation of Traditional Chinese Medicine Societies were conducted. The search time frame was from inception of the databases to December 31, 2022. Four reviewers independently evaluated the implementability of clinical practice guidelines by using "Clinical Practice Guideline (CPG) implementation evaluation tool".   Results   A total of 61 integrative Chinese and western medicine guidelines were included. Of the guidelines assessed, 9 guidelines(14.75%) exhibited strong implementability, 40(65.57%) demonstrated average implementability, and 12 (19.67%) demonstrated poor implementability. Among the 5 domains, the dimensions of "accessibility" and "implementability" were found to be of high quality, while those of "communication", "ease of identification" and "applicability" were relatively poor. Notably, compared to guidelines published between 2006—2016, those published between 2017—2022 showed improvements in the areas of "identification" and "application".   Conclusions   The implementabilityof the existing clinical practice guidelines of the integrative Chinese and western medicine is average and needs to be improved. In the future, emphasis should be placed on the integration of medical education and research, publicity of the guidelines, continuous medical education and training, a more concise form of recommendations, application of the guidelines by clinicians, and the implementability of the integrative Chinese and western medicine guideline.

Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (https://hlse.cn/), with the aim of synthesizing, evaluating, translating, and applying lifestyle-related evidence resources. This paper aims to introduce the functional module design of the evidence translation system, the system development process and testing, introduce the interface design and function demonstration, and explain the significance of constructing the HLSE.

Objective:To develop the method based on deep learning to predict the dose distribution of breast-conserving postoperative intensity-modulated radiotherapy(IMRT) for breast cancer, and to evaluate accuracy of the prediction model.Methods:The data of 110 left-sided breast-conserving postoperative IMRT for breast cancer patients were reviewed, among them, 80 cases were randomly selected for training set, 10 cases for validation set and the remaining 20 cases were used as test set.Firstly, the four-channel characteristics of the patients′ computed tomography(CT) images, regions of interest, distances between voxel and planning target volume(PTV), and corresponding dose distributions were taken as input data.The established U-Net was used for training and obtaining prediction model which was utilized to perform dose prediction on the test set, in order to verify the influence of the features of distance between voxel and PTV in dose prediction, and to compare the dose prediction result with the actual manual planned dose.Results:By incorporating the features of distance between voxel and PTV, the model achieved higher accuracy in predicting the dose distribution.The dose scores and dose volume histogram(DVH) scores of the testing set, consisting of 20 patients, were 2.10±0.18 and 2.28±0.08, respectively, and the predicted dose distribution was closer to the manually planned distribution( t=2.52, 2.40, P<0.05). The deviation between the predicted doses of the PTV and the organ at risk (OAR) and the manually planned doses were within 4%, the average dose to the contralateral breast was increased by 13 cGy, all of them within the clinically acceptable range. Except for the statistically significant differences in D2, D98( Di represents the dose received by i%of the PTV volume), Dmean(mean dose) of PTV 60 and V5( Vi was the volume percentage of OAR receiving i Gy dose.), Dmeanof the ipsilateral lung ( t=3.74, 2.91, 2.99, 3.47, 2.29, P < 0.05), there were no statistically significant differences in other parameters. Conclusions:The deep learning-based method can accurately predict the dose distribution of breast-conserving postoperative IMRT for breast cancer, and it has been proven through experiments that by incorporating the features of distance between voxel and PTV can effectively improve the prediction accuracy, which helps physicists to improve the quality and consistency of treatment planning.

Objective To study the method of treatment of esophageal stricture and ulcer in children caused by corrosive injury using esophageal stent.Methods The stent made of stainlees steel Z type covered with thin membrane or Ni-Ti shape memory wire mesh-like stent was used and placed through mouth by the transport of tracheal stent in 12 cases.Results Symptoms of the dysphagia in all 12 cases treated with 18 sets of Z stents were alleviated remarkably.Following up study from 6 month to 6 years,the stents were regulated or replaced one or more times in 9 cases,the stents were removed in 5 cases,and food-taking was normal following up from 6 to 36 months.Surgical operation was done in one case.The stents were retained in 6 cases,but ordinary and soft food could be taken without problem.One case was treated with 2 stes of Ni-Ti shape memory wire mesh-like stent,the esophageal stricture reappeared one month later and operation was done 6 years later.Conclusion Stent of the Z type is safe and effective in treating esophageal stricture and ulcer in children caused by corrosive injury.