ObjectiveTo investigate the ameliorating effect of Xiao Chaihutang combined with Erchen Tang （XAE） on metabolic-associated fatty liver disease （MAFLD） in mice and the influence of this therapy on the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α）/peroxisome proliferator-activated receptor α （PPARα） signaling pathway. MethodsForty-eight C57BL/6 mice were randomized into six groups： normal （CHOW）， atorvastatin （ATO， 0.05 g·kg^-1）， high-fat diet （HFD）， low-dose XAE （XAE-L， 10 g·kg^-1）， medium-dose XAE （XAE-M， 20 g·kg^-1）， and high-dose XAE （XAE-H， 40 g·kg^-1）. Each group contained 8 mice. Except the CHOW group， the other groups of mice were fed a HFD for the modeling of MAFLD. The experiment lasted for 20 weeks. Starting from the 13th week， mice were administered corresponding agents daily by gavage， and the mice in both the CHOW and HFD groups received equal volumes of purified water. At the end of the experiment， cardiac blood， liver， and adipose tissue samples were collected. Pathological staining was performed on the liver and adipose tissue separately. The levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， triglycerides （TG）， and total cholesterol （TC） in the serum， as well as TG and TC in the liver， were determined. Additionally， the mRNA levels of fatty acid synthetase （FASN）， stearoyl-CoA desaturase 1 （SCD1）， sterol regulatory element-binding protein 1c （SREBP-1c）， SIRT1， PPARα， PGC-1α， interleukin 6 （IL-6）， interleukin-1β （IL-1β）， and tumor necrosis factor-α （TNF-α） in the liver were measured by real-time PCR. The protein levels of SIRT1， PGC-1α， PPARα， and CPT1α in the mouse liver tissue were determined by Western blot. ResultsCompared with the CHOW group， the HFD group exhibited increased body weight， liver weight， and white adipose tissue weight （P<0.01）. After XAE intervention， these parameters were reduced compared with those in the HFD group （P<0.01）. Pathological section results showed that the morphology of hepatocytes and epididymal white adipocytes in the model mice was significantly improved after XAE intervention， with decreases in both the number and volume of lipid droplets. Furthermore， the XAE groups had lower levels of AST， ALT， HDL-C， LDL-C， TG， and TC in the serum and TG and TC in the liver than the HFD group （P<0.05，P<0.01）. Moreover， XAE administration downregulated the mRNA levels of lipid synthesis-related genes （FASN and SCD1） （P<0.05） and upregulated the mRNA levels of lipid oxidation-related genes （SIRT1， PPARα， and PGC-1α） （P<0.05，P<0.01）. Additionally， the protein levels of SIRT1， PGC-1α， PPARα， and CPT1α in the liver were upregulated after XAE treatment compared with those in the HFD group （P<0.05，P<0.01）. ConclusionXAE exerts a therapeutic effect on MAFLD by activating the SIRT1/PGC-1α/PPARα signaling pathway.

ObjectiveTo explore the changes in volatile components， total polysaccharides， enzyme activity， and chromaticity value of Myristicae Semen Koji（MSK） during the fermentation process， and conduct correlation analysis. MethodsBased on gas chromatography-mass spectrometry（GC-MS）， the changes of volatile components in MSK at different fermentation times were identified. The phenol sulfuric acid method， dinitrosalicylic acid method（DNS）， and carboxymethyl cellulose sodium salt method（CMC-Na） were used to investigate the total polysaccharide content， amylase activity， and cellulase activity during the fermentation process. Visual analysis technology was used to explore the changes in chromaticity values， revealing the fermentation process of MSK and the dynamic changes of various measurement indicators， partial least squares-discriminant analysis（PLS-DA） was used to explore the differential compounds of MSK at different fermentation degrees， and Pearson correlation analysis was used to explore the correlation between volatile components of MSK and total polysaccharides， enzyme activity， and chromaticity values. ResultsA total of 60 volatile compounds were identified from MSK， the relative contents of components such as （+）-α-pinene， β-phellandrene， β-pinene， （+）-limonene， and p-cymene obviously increased， while the relative contents of components such as safrole， methyl isoeugenol， methyleugenol， myristicin， and elemicin significantly decreased. During the fermentation process， the total polysaccharide content showed an upward trend， while the activities of amylase and cellulase showed an initial increase followed by a decrease， and reached their maximum value at 40 h. the overall brightness（L^*） and total color difference（ΔE^*） gradually increased， while the changes in red-green value（a^*） and yellow-blue value（b^*） were not obvious. PLS-DA results showed that MSK could be clearly distinguished at different fermentation times， and 13 differential biomarkers were screened out. Pearson correlation analysis results showed that the contents of α-terpinene， β-phellandrene， methyleugenol， β-cubebene and myristic acid had an obvious correlation with chromaticity values. ConclusionAfter fermentation， the volatile components， total polysaccharides， amylase activity， and cellulase activity of MSK undergo significant changes， and there is a clear correlation between them and chromaticity values， which reveals the dynamic changes in the fermentation process and related indicators of MSK， laying a foundation for the quality control.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To investigate the diagnostic value of 4 novel inflammatory markers related to routine blood tests,namely neutrophil-to-lymphocyte ratio(NLR),red blood cell distribution width(RDW),hemoglobin-to-RDW ratio(HRR)and systemic immune-inflammation index(SII),in elderly patients with chronic cardiovascular disease(CVD)complicated with frailty.Methods Retrospectively analyze 110 patients with chronic stable CVD who were hospitalized in the cadre ward of cardiovascular medicine at the Air Force Characteristic Medical Center from January 2022 to June 2023.According to the assessment results of the Fried scale,they were divided into three groups:non-frailty group(Fried score=0,n=30),the pre-frailty group(Fried score 1 or 2,n=40)and frailty group(Fried score≥3,n=40).The differences in general information,the impairment rate of daily living activities,miniature nutritional assessment-short form(MNA-SF)scores,mini-mental state examination(MMSE)scores,and the indicators such as NLR,RDW,HRR,and SII among the three groups were compared.Spearman rank correlation was used to analyze the correlation between NLR,RDW,HRR,SII and frailty scores as well as each frailty indicator.Multivariate logistic regression analysis was performed to identify the independent risk factors for frailty in elderly patients with chronic CVD,and the receiver operating characteristic(ROC)curve was used to assess the clinical diagnostic value of NLR and HRR in elderly patients with chronic CVD complicated with frailty.Results Compared with non-frailty group and pre-frailty group,patients in frailty group were older,with higher impaired rates of daily living activities,NLR,RDW,and SII,and lower MNA-SF scores,MMSE scores,and HRR,and differences were statistically significant(P<0.05).Spearman rank correlation analysis showed that the frailty score was positively correlated with NLR(rs=0.354,P<0.001),and RDW(rs=0.448,P<0.001),negatively correlated with HRR(rs=-0.232,P=0.024),and had no significant correlation with SII(rs=0.144,P=0.167).Further analysis of the correlation between the above novel inflammatory markers and the 5 components of frailty showed that NLR was positively correlated with fatigue(rs=0.228,P=0.017),slowed walking speed(rs=0.299,P<0.001),and low physical function(rs=0.319,P<0.001);RDW was positively correlated with decreased grip strength(rs=0.321,P<0.001),slowed walking speed(rs=0.422,P<0.001),and low physical function(rs=0.246,P=0.001);and HRR was negatively correlated with slowed walking speed(rs=-0.230,P=0.025),and low physical function(rs=-0.299,P=0.003).Multivariate logistic regression analysis showed that MNA-SF score(OR=0.577,95%CI 0.342-0.973)was an independent protective factor for pre-frailty in elderly patients with chronic CVD(P<0.05);NLR(OR=7.866,95%CI 1.101-56.185)was an independent risk factor for frailty,while HRR(OR=0.344,95%CI 0.120-0.983)and MNA-SF score(OR=0.292,95%CI 0.146-0.580)were independent protective factors for frailty in elderly CVD patients(P<0.05).The area under the ROC curve of NLR and HRR for diagnosing frailty in elderly patients with chronic CVD were 0.778 and 0.749,respectively.Conclusion NLR and HRR have high clinical diagnostic value for frailty in elderly patients with chronic CVD,and are expected to become effective inflammatory markers for screening elderly patients with chronic CVD complicated with frailty.

Objective To evaluate the changes in postoperative plasma β-endorphin(β-EP)levels in patients who had received perioperative electroacupuncture(EA)treatment in 10 randomized controlled trials(RCTs)and examine the impact of EA on postoperative pain.Methods This meta-analysis evaluated the changes in plasma β-EP levels and visual analog scale(VAS)12,24 and 48 hours after surgery in patients receiving perioperative EA.It also assessed the changes in plasma serotonin(5-hydroxytryptamine,5-HT)and prostaglandin E2(PGE2)levels at 24 hours postsurgery.A comprehensive search was conducted in the China National Knowledge Infrastructure(CNKI),Wanfang,Chongqing VIP database,Chinese Biomedical Database(CBM),Web of Science,and PubMed databases.RCTs on perioperative EA and β-EP published from the inception of the websites up to July 25,2023,were retrieved.Effect size aggregation,literature quality assessment,and bias analysis were performed using RevMan 5.3 software,and sensitivity analysis was conducted via R 4.3.1.Results A total of 10 RCTs involving 706 patients were included.EA in conjunction with conventional anesthesia significantly increased plasma β-EP levels at 12 hours postsurgery[standard mean difference(SMD)=2.79,95%CI(1.85,3.72),Z=5.81,P＜0.00001],24hours postsurgery[SMD=1.87,95%CI(0.9,2.83),Z=3.79,P=0.0001],and 48 hours postsurgery[SMD=2.02,95%CI(1.49,2.54),Z=7.50,P＜0.00001].EA reduced plasma PGE2 levels at 24 hours postsurgery and plasma 5-HT levels at 24 hours postsurgery,and the VAS at 12,24 and 48 hours after surgery also decreased.Conclusion These findings suggest that perioperative EA markedly elevates plasma β-EP levels,reduces pain-inducing factors in plasma,and effectively alleviates acute postoperative pain.

Objective To explore the molecular mechanism by which SOS Ras/Rac guanine nucleotide exchange factor 1-intronic transcript 1(SOS1-IT1)affects enhancer of zeste homolog 2(EZH2)protein expression in endometrial cancer cells Ishikawa and RL95-2.Methods Lentiviral transfection of short hairpin RNA(shRNA)and overexpression plasmid were used in Ishikawa and RL95-2 cell lines to knock down and overexpress SOS1-IT1.The mechanism of EZH2 expression regulation was studied using Real-time PCR,Western blotting,and chromatin immunoprecipitation.Results The expression of SOS1-IT1 and EZH2 genes was positively correlated in endometrial cancer tissues.Knocking down SOS1-IT1 significantly reduces the expression of EZH2,inhibited the proliferation and migration of Ishikawa and RL95-2 cells,and could reduced the acetylation of histone H3 at position 27(H3K27)and the enrichment of CREB binding protein(CBP)in the EZH2 gene promoter region.Overexpression of SOS1-IT1 could increased the expression of EZH2 and enhance the acetylation of H3K27 and the enrichment of CBP.CBP could bind to SOS1-IT1 RNA,and this binding ability was weakened when CBP was knocked down.Conclusion SOS1-IT1 can promote the expression level of EZH2 in endometrial cancer cells Ishikawa and RL95-2 by regulating the acetylation modification level of the EZH2 gene promoter region,thereby affecting the proliferation and migration ability of endometrial cancer cells.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

The tumor microenvironment is a crucial factor in tumor occurrence and progression. The hypoxic microenvironment is widely present in tumor tissue and is a key endogenous factor accelerating tumor deterioration. The "blood stasis toxin" theory, as an emerging perspective in tumor research, is regarded as the unique "soil" in tumor progression from the perspective of traditional Chinese medicine(TCM) due to its dynamic evolution mechanism, which closely resembles the formation of the hypoxic microenvironment. Scientifically integrating TCM theories with the biological characteristics of tumors and exploring precise syndrome differentiation and treatment strategies are key to achieving comprehensive tumor prevention and control. This article focused on the hypoxic microenvironment of the tumor, elucidating its formation mechanisms and evolutionary processes and carefully analyzing the internal relationship between the "blood stasis toxin" theory and the hypoxic microenvironment. Additionally, it explored the interaction among blood stasis, toxic pathogens, and hypoxic environment and proposed micro-level prevention and treatment strategies targeting the hypoxic microenvironment based on the "blood stasis toxin" theory, aiming to provide TCM-based theoretical support and therapeutic approaches for precise regulation of the hypoxic microenvironment.
Humans ; Tumor Microenvironment/drug effects* ; Neoplasms/therapy* ; Animals ; Medicine, Chinese Traditional ; Disease Progression ; Drugs, Chinese Herbal

The aim of this study was to investigate the improvement effect of Wenpi Pills(WPP) on non-alcoholic fatty liver disease(NAFLD). The experiment was divided into two parts, using C57BL/6 mouse models induced by a high-fat diet(HFD) and a methionine and choline deficiency diet(MCD). The HFD-induced experiment lasted for 16 weeks, while the MCD-induced experiment lasted for 6 weeks. Mice in both parts were divided into four groups: control group, model group, low-dose WPP group(3.875 g·kg~(-1), WPP＿L), and high-dose WPP group(15.5 g·kg~(-1), WPP＿H). After sample collection from the HFD-induced mice, lipid content in the serum and liver, liver function indexes in the serum, and hepatic pathology were examined. Real-time fluorescent quantitative reverse transcription PCR(qRT-PCR) was used to detect the expression of lipid-related genes. After sample collection from the MCD-induced mice, serum liver function indexes and inflammatory factors were measured, and hepatic pathology and lipid changes were analyzed by hematoxylin-eosin(HE) staining and widely targeted lipidomic profiling, respectively. The results from the HFD-induced experiment showed that, compared with the HFD group, WPP administration significantly reduced the levels of aspartate aminotransferase(AST), alanine aminotransferase(ALT), triglyceride(TG), and total cholesterol(TC) in the serum, with the WPP＿H group showing the most significant improvement. HE staining results indicated that, compared with the HFD group, WPP treatment improved the morphology of white adipocytes, reducing their size, and alleviated hepatic steatosis and lipid droplet accumulation. The qRT-PCR results suggested that WPP might increase the mRNA expression of liver cholesterol-converting genes, such as liver X receptor α(LXRα) and cytochrome P450 family 27 subfamily A member 1(CYP27A1), as well as lipid consumption genes like peroxisome proliferator-activated receptor α(PPARα) and adenosine mono-phosphate-activated protein kinase(AMPK). Meanwhile, WPP decreased the mRNA expression of lipid synthesis genes, including fatty acid synthetase(FAS), stearoyl-CoA desaturase 1(SCD1), and sterol regulatory element-binding protein 1c(SREBP-1c), thereby reducing liver lipid accumulation. The results from the MCD-induced experiment showed that, compared with the MCD group, WPP administration reduced the levels of ALT, AST, and inflammatory factors in the serum, thereby alleviating liver injury and the inflammatory response. HE staining of liver tissue indicated that WPP effectively improved hepatic steatosis. Non-targeted lipidomics analysis showed that WPP improved lipid metabolism disorders in the liver, mainly by affecting the metabolism of TG and cholesterol esters. In conclusion, WPP can improve hepatic lipid accumulation in NAFLD mice induced by both HFD and MCD. This beneficial effect is primarily achieved by alleviating liver injury and inflammation, as well as regulating lipid metabolism.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Lipid Metabolism/drug effects* ; Mice ; Mice, Inbred C57BL ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Diet, High-Fat/adverse effects* ; Liver/drug effects* ; Humans ; Disease Models, Animal ; Methionine