Sepsis is a systemic inflammatory response syndrome caused by the invasion of pathogenic microorganisms such as bacteria. In addition to the manifestations of systemic inflammatory response syndrome and primary infection lesions， critical cases often have manifestations of organ hypoperfusion. The morbidity and mortality of sepsis have remained high in recent years， which seriously affect the quality of life of the patients. The pathogenesis of sepsis is complicated， in which uncontrollable inflammation is a key mechanism. The phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway plays a key role in mediating inflammation in sepsis. The available therapies of sepsis mainly include resuscitation， anti-infection， vasoactive drugs， intensive insulin therapy， and organ support， which show limited effects of reducing the mortality. Therefore， finding new therapeutic drugs is a key problem to be solved in the clinical treatment of sepsis. In recent years， studies have shown that traditional Chinese medicine （TCM） can regulate the PI3K/Akt pathway via multiple pathways， multiple effects， and multiple targets to inhibit inflammation and curb the occurrence and development of sepsis， which has gradually become a hot spot in the prevention and treatment of sepsis. Moreover， studies have suggested that TCM has unique advantages in the treatment of sepsis. TCM can regulate the PI3K/Akt signaling pathway to inhibit inflammation， reduce oxidative stress， and control apoptosis in the prevention and treatment of sepsis. Despite the research progress， a systematic review remains to be performed regarding the TCM treatment of sepsis by regulating the PI3K/Akt signaling pathway. After reviewing relevant papers published in recent years， this study systematically summarizes the relationship between PI3K/Akt pathway and sepsis and the role of TCM in the treatment of sepsis， aiming to provide new ideas for the potential treatment of sepsis and the development of new drugs.

Ribosomal protein(RP)is an important part of ribosome,which is very important for the assembly and function of ribosome.Recent studies have shown that RP is closely related to the processes of growth,senescence,apoptosis,invasion and drug resistance of tumor cells.The drug resistance of tumors is one of the main reasons for the low cure rate of tumors.RP can affect the drug resistance of tumor cells through a variety of mechanisms,such as changes in signal pathway,epithelial-mesenchymal transformation,cancer stem cells and tumor microenvironment,resulting in a poor prognosis of cancer patients.Ribosome tar-geting therapy is a promising method for the treatment of cancer patients.This review summarizes the mecha-nism of RP and many kinds of cancer drug resistance,provides new ideas for elucidating the mechanism of tumor drug resistance,and then provides new strategies for clinical prevention and reduction of tumor drug re-sistance.

Objective To compare the segmenting efficacy of automatic segmentation models for advanced gastric cancer(AGC)on CT virtual monoenergetic images(VMI),non-linear blending images(NLBI)and mixed-energy images(MEI)based on 3D-nnU-Net.Methods Totally 216 cases of AGC were retrospectively enrolled,among them 185 cases were used to construct,train and validate models and divided into training set(n=154)and test set(n=31)at the ratio of 5∶1,while the other 31 cases were used as validation set to evaluate the generalization of the models.The 70 keV energy level VMI(VMI70 keV),NLBI and MEI were reconstructed with whole-abdominal dual-energy mode venous CT,and automatic segmentation models of AGC,including VMI70 keV,NLBI and MEI models were constructed using 3D-nnU-Net,respectively.Taken manually segmented results as golden standards,the efficacy of each model for segmenting all lesions and T2 stage lesions in test set and validation set were evaluated using Dice similarity coefficient(DSC),intersection over union(IoU)and average symmetric surface distance(ASSD).Results For all lesions in test and validation sets,DSC of 3 models were all＞0.80.DSC and IoU of VMI70 keV and NLBI models were both higher,while their ASSD was lower than those of MEI model(all P＜0.05).For T2 stage AGC in both test set and validation set(each n=5),DSC of MEI model was lower than that of VMI70 keV and NLBI models(both P＜0.05),while IoU of MEI model was lower than that of VMI70 keV model(P＜0.05),and its ASSD was higher than that of NLBI model(P＜0.05).Conclusion All 3D-nnU-Net-based VMI70 keV,NLBI and MEI models could effectively segment AGC on dual-energy CT images,and the segmentation efficacy of the former two were better.

Objective To compare the segmenting efficacy of automatic segmentation models for advanced gastric cancer(AGC)on CT virtual monoenergetic images(VMI),non-linear blending images(NLBI)and mixed-energy images(MEI)based on 3D-nnU-Net.Methods Totally 216 cases of AGC were retrospectively enrolled,among them 185 cases were used to construct,train and validate models and divided into training set(n=154)and test set(n=31)at the ratio of 5∶1,while the other 31 cases were used as validation set to evaluate the generalization of the models.The 70 keV energy level VMI(VMI70 keV),NLBI and MEI were reconstructed with whole-abdominal dual-energy mode venous CT,and automatic segmentation models of AGC,including VMI70 keV,NLBI and MEI models were constructed using 3D-nnU-Net,respectively.Taken manually segmented results as golden standards,the efficacy of each model for segmenting all lesions and T2 stage lesions in test set and validation set were evaluated using Dice similarity coefficient(DSC),intersection over union(IoU)and average symmetric surface distance(ASSD).Results For all lesions in test and validation sets,DSC of 3 models were all＞0.80.DSC and IoU of VMI70 keV and NLBI models were both higher,while their ASSD was lower than those of MEI model(all P＜0.05).For T2 stage AGC in both test set and validation set(each n=5),DSC of MEI model was lower than that of VMI70 keV and NLBI models(both P＜0.05),while IoU of MEI model was lower than that of VMI70 keV model(P＜0.05),and its ASSD was higher than that of NLBI model(P＜0.05).Conclusion All 3D-nnU-Net-based VMI70 keV,NLBI and MEI models could effectively segment AGC on dual-energy CT images,and the segmentation efficacy of the former two were better.

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.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.

In the era of evidence-based medicine, it is necessary to explore the unique advantages of traditional Chinese medicine (TCM) based on standardized technical methods and operating procedures in order to achieve the modernization and internationalization of TCM and benefit all humanity. The proposal of a three-pronged evidence system combining TCM theory, human experience and experimental evidence marks an important progress in the thinking method of the TCM evaluation system. The multi-evidence body integrated through appropriate methods provides a strong support for the clinical guideline recommendations and evidence-based health decision-making in TCM. Based on the current methodological progress of international evidence synthesis and grading, this paper proposes a novel approach for integrating multi-evidence in TCM: the MERGE framework. The aim is to establish a solid foundation for the development of this methodology and provide guidance for the advancement of evidence-based medicine framework in TCM.

The aims of developing rapid and living guidelines is to keep the recommendations in the guideline up-to-date. Compared with the conventional guideline, the rapid and living guideline can make better use of the existing evidence and apply and transform the evidence in a timely manner. This paper introduces the advantages and usage of rapid and living guidelines, the development process and existing challenges, and offers some insights, in order to provide reference for domestic organizations and scholars engaged in guideline development.

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.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.