ObjectiveQi deficiency and phlegm dampness syndrome is a common type of clinical traditional Chinese medicine（TCM） syndrome. However， there is no standard， scientific， and accurate report on the construction of animal models of Qi deficiency and phlegm dampness syndrome. This study aims to construct a mouse model of Qi deficiency and phlegm dampness syndrome by using a multi-factor composite modeling method and to evaluate the model. MethodsTwenty-one C57BL/6 mice were randomly divided into three groups with seven mice in each group， which were the normal group， model group， and Shenling Baizhusan （SLBZ） group. The control group was fed with ordinary diet and kept in a normal environment. The model group and SLBZ group were fed with a high-fat diet in a high-humidity environment. Swimming with heavy weights until exhaustion and gavage with cold water or lard were used to establish the mouse model of Qi deficiency and phlegm dampness syndrome. In order to test the syndrome by prescription， mice in the SLBZ group were treated with SLBZ for 14 days after model construction. The exhaustive swimming time， body weight， serum lipid levels， tongue changes， "Qi deficiency and phlegm dampness" assessment scale score， and cecal index of mice in each group were measured. The feces of each group of mice were sent for metagenomics and metabolome sequencing， and the changes in intestinal flora and metabolites were analyzed. ResultsAfter the modeling of Qi deficiency and phlegm dampness syndrome， the exhaustive swimming time of mice was obviously shortened （P<0.01）. The serum total cholesterol， low density lipoprotein cholesterol， and non-high density lipoprotein cholesterol of mice were significantly increased （all P<0.01）. The tongue of mice was significantly different from that of the normal group， and the score of the assessment scale was significantly higher than that of the control group （P<0.01）. Cecal index decreased significantly （P<0.01）. The serum lipid level， tongue image， assessment scale score， and cecal index were reversed in the SLBZ group. Metagenomic and metabolome sequencing results showed that intestinal flora and fecal metabolites were significantly changed in mice with Qi deficiency and phlegm dampness syndrome. Akkermansia_muciniphila， Faecalibaculum_rodentium， Eubacterium_plexicaudatum， Eubacterium sp 14_2， Candida glabrata， Romboutsia_ilealis， Turicibacter sp TS3， and other bacteria had significant changes， and the expressions of intestinal metabolites such as chenodeoxycholic acid， choline， L-phenylalanine betaine， and 2-phenylbutyric acid were significantly changed. Related metabolic pathways such as linoleic acid metabolism， primary bile acid biosynthesis， lysine degradation， arginine biosynthesis， and alpha-linolenic acid metabolism were affected. ConclusionThe Qi deficiency and phlegm dampness model of mice can be constructed by the multi-factor composite modeling method of high-fat diet feeding， high-humidity environment feeding， exhaustive swimming with heavy weight， and intragastric administration with cold water or lard. The blood lipid level， tongue change， score of "Qi deficiency and phlegm dampness assessment scale"， cecal index， and changes in related intestinal flora and metabolites of mice can be used as key indicators for model evaluation.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Objective To investigate the cognition level and behavior compliance of blood pressure measurement in community residents and analyze the related influencing factors, and to provide evidence for community health management and blood pressure control. Methods A questionnaire survey was conducted to investigate 4470 community patients. Questionnaires included basic personal information，blood pressure measurement cognition, and blood pressure measurement behavior related issues. SPSS 19.0 was used to analyze the basic information, blood pressure measurement cognition, and pressure measurement behavior of the survey subjects. Logistic regression was performed to analyze relevant factors affecting blood pressure measurement cognition and behavior compliance. Results The overall cognitive compliance rate for blood pressure measurement among the visiting community patients was 31.52%. Age, education level, and chronic disease had a statistically significant impact on the cognitive knowledge (P<0.05). The overall behavior compliance rate of blood pressure measurement among the community patients was 23.69%. The cognition, age and education had a statistically significant impact on the overall behavior compliance rate of blood pressure measurement (P<0.05). Conclusion The cognitive level and standardized behavior of blood pressure measurement of community patients need to be improved. More attention should be paid to the elderly, low education level residents and community residents without chronic diseases, to promote community residents to form correct and standardized behavior of blood pressure measurement through health education.

ObjectiveTo observe the inhibitory effect of the Weiliuan mixture （WLAHJ） on the subcutaneous xenograft tumor of MKN-74 gastric cancer cells， and explore the potential anti-gastric cancer mechanism of WLAHJ by using transcriptomic sequencing technology to reveal related genes and pathways. Methods30 Balb/c nude mice were randomly divided into model， low-， medium-， and high-dose（15，30，45 g·kg^-1） WLAHJ and 5-FU （0.025 g·kg^-1） groups to build a subcutaneous xenograft tumor model with MKN-74 human gastric cancer cells. After modeling，each group was continuously treated with the corresponding drugs for 28 days. During the treatment period， the body weight and tumor size of the mice were observed and recorded every 2 days. At the end of the treatment， the mice were sacrificed， and required samples were collected to calculate the tumor inhibition rate of WLAHJ on the subcutaneous xenograft tumor. High-throughput transcriptomic sequencing （RNA-seq） technology was used to analyze the differentially expressed genes in the subcutaneous tumor tissues of the model group and the medium-dose WLAHJ group， thus exploring the potential mechanism of WLAHJ in gastric cancer intervention. Immunofluorescence experiments were conducted to detect the protein expression levels of glutathione peroxidase 4 （GPX4）， solute carrier family 7 member 11 （SLC7A11）， transferrin receptor protein-1 （TFR-1）， and acyl-CoA synthetase long-chain family member 4 （ACSL4） in subcutaneous xenograft tumors of each group. Cell counting kit-8（CCK-8） and colony formation assays were used to detect the viability and anti-proliferative ability of human gastric cancer AGS and MKN-74 cells at different concentrations of WLAHJ. Kits were used to detect the levels of Fe²⁺， reactive oxygen species （ROS）， malondialdehyde （MDA）， and superoxide dismutase （SOD） activity in cells. Western blot was used to detect the expression levels of GPX4， SLC7A11， TRF-1， ACSL4， spermidine/spermine N1-acetyltransferase 1 （SAT1）， arachidonic acid 15-lipoxygenase （ALOX15）， and key proteins in the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR） signaling pathway. ResultsThe mechanism of WLAHJ in gastric cancer intervention may be related to ferroptosis and the PI3K/Akt /mTOR signaling pathway. The growth of subcutaneous xenograft tumors in nude mice of the WLAHJ and 5-FU groups（P<0.05，P<0.01）， GPX4， and SLC7A11 dropped significantly（P<0.01）， while TFR-1， ACSL4， SAT1， and ALOX15（P<0.05，P<0.01）increased significantly compared with those in the model group. The levels of ROS， Fe²⁺， and MDA increased in the WLAHJ and 5-FU groups and the proliferation of gastric cancer cells， SOD activity， the ratios of phosphorybation （p）-mTOR/mTOR， p-PI3K/PI3K， and p-Akt/Akt protein expressions（P<0.05，P<0.01）decreased compared with those in the blank group. ConclusionThe mechanism of WLAHJ in treating gastric cancer may be related to the regulation of the PI3K/ Akt /mTOR signaling pathway to intervene in ferroptosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

ObjectiveTo establish a subcutaneous xenograft model of gastric cancer in nude mice and to identify differentially expressed genes （DEGs） affected by Jianpi Yangzheng Xiaozheng formula （JPYZXZ） in diffuse gastric cancer （DGC） using transcriptome sequencing. The study aims to identify potential key prognostic factors and preliminarily elucidate the therapeutic mechanism of JPYZXZ. MethodsSubcutaneous tumor tissues were collected from nude mice treated with JPYZXZ （6 g·kg^-1）and from the untreated traditional Chinese medicine control group. High-throughput RNA sequencing was performed to extract and analyze total RNA and identify DEGs， followed by functional enrichment analysis. DEGs were intersected with cancer-associated fibroblast （CAF）-related genes identified from single-cell RNA sequencing （scRNA-seq） data. A Cox proportional hazards regression model （Cox model） was constructed to identify potential key targets， among which DAZ interacting protein 1 （DZIP1） was selected. The role of DZIP1 in DGC progression was further verified through in vitro and in vivo experiments. ResultsTranscriptome sequencing revealed that DEGs regulated by JPYZXZ were significantly enriched in biological processes such as focal adhesion， phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway， and vascular development （P<0.05）. Intersection analysis with CAF marker genes identified ten potential common target genes. Cox regression analysis combined with the Cancer Genome Atlas （TCGA） dataset for stomach adenocarcinoma （STAD） confirmed that DZIP1 is an independent prognostic factor significantly associated with poor outcomes. Transcriptome and immunohistochemical analyses showed that DZIP1 expression was significantly higher in gastric cancer tissues than in adjacent tissues， while JPYZXZ treatment downregulated DZIP1 expression in a dose-dependent manner. Clinical data further demonstrated that serum DZIP1 levels in patients treated with JPYZXZ were significantly lower than those in the control group. ConclusionJPYZXZ may inhibit the malignant progression of DGC by downregulating DZIP1 expression， thereby suppressing CAF activation and epithelial-mesenchymal transition （EMT）. These findings provide experimental evidence and identify DZIP1 as a potential therapeutic target in DGC treatment.

ObjectiveTo establish a subcutaneous xenograft model of gastric cancer in nude mice and to identify differentially expressed genes （DEGs） affected by Jianpi Yangzheng Xiaozheng formula （JPYZXZ） in diffuse gastric cancer （DGC） using transcriptome sequencing. The study aims to identify potential key prognostic factors and preliminarily elucidate the therapeutic mechanism of JPYZXZ. MethodsSubcutaneous tumor tissues were collected from nude mice treated with JPYZXZ （6 g·kg^-1）and from the untreated traditional Chinese medicine control group. High-throughput RNA sequencing was performed to extract and analyze total RNA and identify DEGs， followed by functional enrichment analysis. DEGs were intersected with cancer-associated fibroblast （CAF）-related genes identified from single-cell RNA sequencing （scRNA-seq） data. A Cox proportional hazards regression model （Cox model） was constructed to identify potential key targets， among which DAZ interacting protein 1 （DZIP1） was selected. The role of DZIP1 in DGC progression was further verified through in vitro and in vivo experiments. ResultsTranscriptome sequencing revealed that DEGs regulated by JPYZXZ were significantly enriched in biological processes such as focal adhesion， phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway， and vascular development （P<0.05）. Intersection analysis with CAF marker genes identified ten potential common target genes. Cox regression analysis combined with the Cancer Genome Atlas （TCGA） dataset for stomach adenocarcinoma （STAD） confirmed that DZIP1 is an independent prognostic factor significantly associated with poor outcomes. Transcriptome and immunohistochemical analyses showed that DZIP1 expression was significantly higher in gastric cancer tissues than in adjacent tissues， while JPYZXZ treatment downregulated DZIP1 expression in a dose-dependent manner. Clinical data further demonstrated that serum DZIP1 levels in patients treated with JPYZXZ were significantly lower than those in the control group. ConclusionJPYZXZ may inhibit the malignant progression of DGC by downregulating DZIP1 expression， thereby suppressing CAF activation and epithelial-mesenchymal transition （EMT）. These findings provide experimental evidence and identify DZIP1 as a potential therapeutic target in DGC treatment.

This study aims to investigate the antipyretic effects and mechanisms of ethanol extracts from Arisaematis Rhizoma fermented with bile from different sources on a rat model of fever induced by a dry-yeast suspension. The rat model of fever was established by subcutaneous injection of 20% dry-yeast suspension into the rat back. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6) in the serum, as well as prostaglandin E_2(PGE_2) and cyclic adenosine monophosphate(cAMP) in the hypothalamus, were determined by ELISA. Metabolomics analysis was then performed on serum and hypothalamus samples based on UPLC-Q-TOF MS to explore the potential biomarkers and metabolic pathways. The results showed that the body temperatures of rats significantly rose 4 h after modeling. After oral administration of high-dose ethanol extracts of Arisaematis Rhizoma fermented with bovine bile(NCH) and porcine bile(ZCH), the body temperatures of rats declined(P<0.05), and the NCH group showed better antipyretic effect than the ZCH group. Additionally, compared with the model group, the NCH and ZCH groups showed lowered levels of IL-1β, IL-6, TNF-α, PGE_2, and cAMP(P<0.01). The results of serum and hypothalamus metabolomics analysis indicated that both NCH and ZCH exerted antipyretic effects by regulating phenylalanine metabolism, sphingolipid metabolism, arachidonic acid metabolism, and steroid hormone biosynthesis. Collectively, both NCH and ZCH can play an obvious antipyretic role in the rat model of dry yeast-induced fever, and the underlying mechanism might be closely associated with inhibiting inflammation and regulating metabolic disorders. Moreover, NCH demonstrates better antipyretic effect.
Animals ; Rats ; Male ; Fermentation ; Rats, Sprague-Dawley ; Rhizome/metabolism* ; Drugs, Chinese Herbal/chemistry* ; Bile/chemistry* ; Antipyretics/chemistry* ; Fever/metabolism* ; Cattle ; Swine ; Tumor Necrosis Factor-alpha/metabolism* ; Ethanol/chemistry* ; Interleukin-6/blood* ; Interleukin-1beta/blood*