This study aims to investigate the mechanism of Qingrun Decoction in alleviating hepatic insulin resistance in type 2 diabetes mellitus(T2DM) rats through the reprogramming of amino acid metabolism. A T2DM rat model was established by inducing insulin resistance through a high-fat diet combined with intraperitoneal injection of streptozotocin. The model rats were randomly divided into five groups: model group, high-, medium-, and low-dose Qingrun Decoction groups, and metformin group. A normal control group was also established. The rats in the normal and model groups received 10 mL·kg~(-1) distilled water daily by gavage. The metformin group received 150 mg·kg~(-1) metformin suspension by gavage, and the Qingrun Decoction groups received 11.2, 5.6, and 2.8 g·kg~(-1) Qingrun Decoction by gavage for 8 weeks. Blood lipid levels were measured in different groups of rats. Pathological damage in rat liver tissue was assessed by hematoxylin-eosin(HE) staining and oil red O staining. Transcriptome sequencing and untargeted metabolomics were performed on rat liver and serum samples, integrated with bioinformatics analyses. Key metabolites(branched-chain amino acids, BCAAs), amino acid transporters, amino acid metabolites, critical enzymes for amino acid metabolism, resistin, adiponectin(ADPN), and mammalian target of rapamycin(mTOR) pathway-related molecules were quantified using quantitative real-time polymerase chain reaction(qRT-PCR), Western blot, and enzyme-linked immunosorbent assay(ELISA). The results showed that compared with the normal group, the model group had significantly increased serum levels of total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), and resistin and significantly decreased ADPN levels. Hepatocytes in the model group exhibited loose arrangement, significant lipid accumulation, fatty degeneration, and pronounced inflammatory cell infiltration. In liver tissue, the mRNA transcriptional levels of solute carrier family 7 member 2(Slc7a2), solute carrier family 38 member 2(Slc38a2), solute carrier family 38 member 4(Slc38a4), and arginase(ARG) were significantly downregulated, while the mRNA transcriptional levels of solute carrier family 1 member 4(Slc1a4), solute carrier family 16 member 1(Slc16a1), and methionine adenosyltransferase(MAT) were upregulated. Furthermore, the mRNA transcription and protein expression levels of branched-chain α-keto acid dehydrogenase E1α(BCKDHA) and DEP domain-containing mTOR-interacting protein(DEPTOR) were downregulated, while mRNA transcription and protein expression levels of mTOR, as well as ribosomal protein S6 kinase 1(S6K1), were upregulated. The levels of BCAAs and S-adenosyl-L-methionine(SAM) were elevated. The serum level of 6-hydroxymelatonin was significantly reduced, while imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid levels were significantly increased. Compared with the model group, Qingrun Decoction significantly reduced blood lipid and resistin levels while increasing ADPN levels. Hepatocytes had improved morphology with reduced inflammatory cells, and fatty degeneration and lipid deposition were alleviated. Differentially expressed genes and differential metabolites were mainly enriched in amino acid metabolic pathways. The expression levels of Slc7a2, Slc38a2, Slc38a4, and ARG in the liver tissue were significantly upregulated, while Slc1a4, Slc16a1, and MAT expression levels were significantly downregulated. BCKDHA and DEPTOR expression levels were upregulated, while mTOR and S6K1 expression levels were downregulated. Additionally, the levels of BCAAs and SAM were significantly decreased. The serum level of 6-hydroxymelatonin was increased, while those of imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid were decreased. In summary, Qingrun Decoction may improve amino acid metabolism reprogramming, inhibit mTOR pathway activation, alleviate insulin resistance in the liver, and mitigate pathological damage of liver tissue in T2DM rats by downregulating hepatic BCAAs and SAM and regulating key enzymes involved in amino acid metabolism, such as BCKDHA, ARG, and MAT, as well as amino acid metabolites and transporters.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Insulin Resistance ; Diabetes Mellitus, Type 2/genetics* ; Male ; Liver/drug effects* ; Amino Acids/metabolism* ; Rats, Sprague-Dawley ; Humans ; Metabolic Reprogramming

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To investigate the relationship between the expression levels of serum microRNA(miR-138-5p)and long non-coding RNA(LncRNA)NEAT1 in patients with colorectal cancer(CRC)and clinical pathological features and prognosis.Methods:Totally 163 CRC patients admitted to our hospital from May 2019 to August 2021 were used as the CRC group,and were assigned into a survival group(n=104)and a death group(n=47)based on 3-year prognosis.Another 175 patients with benign colorectal lesions were as the control group.Real-time fluorescence quantitative PCR was used to measure serum miR-138-5p and LncRNA NEAT1.K-M curve was used to analyze the relationship between serum miR-138-5p and LncRNA NEAT1 expression and prognosis of CRC.Multivariate Cox re-gression was used to analyze the influencing factors of prognosis of CRC.ROC was used to analyze the predictive value of serum miR-138-5p and LncRNA NEAT1 for prognosis of CRC.Results:Compared with the control group,the serum miR-138-5p in the CRC group was lower(t=12.802,P<0.05),and the LncRNA NEAT1 was higher(t=13.752,P<0.05).The serum miR-138-5p was related to the differentiation degree,T stage,and N stage of CRC patients(χ2=4.780,6.557,8499,P<0.05);and the serum LncRNA NEAT1 was associated with T stage and N stage in CRC patients(χ2=8.352,9.642,P<0.05).There were obvious differences between the survival group and the death group in T stage and N stage(χ2=6.801,7.580,P<0.05),and the serum miR-138-5p in the survival group was lower than that in the death group(t=8.290,P<0.05),while the serum LncRNA NEAT1 was higher than that in the death group(t=10.008,P<0.05).K-M curve showed that patients with high miR-138-5p expression had a higher 3-year survival rate than those with low miR-138-5p expression(Log Rank χ2=6.661,P=0.010);and the 3-year survival rate of patients with high ex-pression of LncRNA NEAT1 was lower than that of patients with low expression of LncRNA NEAT1(Log Rank χ2=10.620,P=0.001).Multivariate Cox regression analysis showed that T stage(HR=3.516),N stage(HR=2.983),serum miR-138-5p(HR=0.927),and LncRNA NEAT1(HR=1.659)were all factors affecting the prognosis of CRC(P<0.05).ROC results showed that the AUC for predicting poor prognosis in CRC by combining serum miR-138-5p and LncRNA NEAT1 was 0.716,which was obviously higher than that predicted by miR-138-5p(Z=3.173,P=0.002)and LncRNA NEAT1(Z=3.253,P=0.001)alone.Conclusion:Serum miR-138-5p is lower and LncRNA NEAT1 is higher in CRC pa-tients.Moreover,the levels of both are closely related to the clinical pathological features and prognosis.

Objective To establish a rapid,sensitive,and specific multiplex PCR detection method for the simultaneous detection of Cryptosporidium,Eimeria,and bovine parvovirus.Methods Specific primers targeting the SSU rRNA genes of Cryptosporidium and Eimeria,as well as the VP2 gene of bovine parvovirus were designed and the corresponding recombinant plasmid standards were constructed.To establish the multiplex PCR method,the reaction conditions were optimized using temperature gradient PCR and single-variable control methods.The sensitivity,specificity,reproducibility,and clinical application of the protocol were evaluated.Results The optimal annealing temperature was found to be 60.5℃,and the forward and reverse primer concentrations were determined to be 0.2 μmol/L for Eimeria,and 0.4 μmol/L for Cryptosporidium and bovine parvovirus.The assay demonstrated high sensitivity,with detection limits of 243,260,and 3 110 copies for the recombinant plasmid standards of Cryptosporidium,Eimeria,and bovine parvovirus,respectively.Specificity testing showed no cross-reactivity with ten common bovine pathogens,including Salmonella,bovine viral diarrhea virus,and bovine rotavirus.Consistent intra-and inter-batch results confirmed the strong reproducibility of the method.Clinical application to 81 diarrhea samples from various regions in the Ganzi Prefecture,Sichuan,revealed positivity rates of 18.52%(15/81)for Cryptosporidium,34.57%(28/81)for Eimeria,and 18.52%(15/81)forbovineparvovirus,withamixedinfectionrateof3.7%(3/81).Conclusions Themultiplex PCR method established in this study offers a reliable tool for differential diagnosis and epidemiological investigation of the three common diarrheal pathogens in yaks.

Objective:To investigate the relationship between the expression levels of serum microRNA(miR-138-5p)and long non-coding RNA(LncRNA)NEAT1 in patients with colorectal cancer(CRC)and clinical pathological features and prognosis.Methods:Totally 163 CRC patients admitted to our hospital from May 2019 to August 2021 were used as the CRC group,and were assigned into a survival group(n=104)and a death group(n=47)based on 3-year prognosis.Another 175 patients with benign colorectal lesions were as the control group.Real-time fluorescence quantitative PCR was used to measure serum miR-138-5p and LncRNA NEAT1.K-M curve was used to analyze the relationship between serum miR-138-5p and LncRNA NEAT1 expression and prognosis of CRC.Multivariate Cox re-gression was used to analyze the influencing factors of prognosis of CRC.ROC was used to analyze the predictive value of serum miR-138-5p and LncRNA NEAT1 for prognosis of CRC.Results:Compared with the control group,the serum miR-138-5p in the CRC group was lower(t=12.802,P<0.05),and the LncRNA NEAT1 was higher(t=13.752,P<0.05).The serum miR-138-5p was related to the differentiation degree,T stage,and N stage of CRC patients(χ2=4.780,6.557,8499,P<0.05);and the serum LncRNA NEAT1 was associated with T stage and N stage in CRC patients(χ2=8.352,9.642,P<0.05).There were obvious differences between the survival group and the death group in T stage and N stage(χ2=6.801,7.580,P<0.05),and the serum miR-138-5p in the survival group was lower than that in the death group(t=8.290,P<0.05),while the serum LncRNA NEAT1 was higher than that in the death group(t=10.008,P<0.05).K-M curve showed that patients with high miR-138-5p expression had a higher 3-year survival rate than those with low miR-138-5p expression(Log Rank χ2=6.661,P=0.010);and the 3-year survival rate of patients with high ex-pression of LncRNA NEAT1 was lower than that of patients with low expression of LncRNA NEAT1(Log Rank χ2=10.620,P=0.001).Multivariate Cox regression analysis showed that T stage(HR=3.516),N stage(HR=2.983),serum miR-138-5p(HR=0.927),and LncRNA NEAT1(HR=1.659)were all factors affecting the prognosis of CRC(P<0.05).ROC results showed that the AUC for predicting poor prognosis in CRC by combining serum miR-138-5p and LncRNA NEAT1 was 0.716,which was obviously higher than that predicted by miR-138-5p(Z=3.173,P=0.002)and LncRNA NEAT1(Z=3.253,P=0.001)alone.Conclusion:Serum miR-138-5p is lower and LncRNA NEAT1 is higher in CRC pa-tients.Moreover,the levels of both are closely related to the clinical pathological features and prognosis.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To investigate the association of serum levels of tumor necrosis factor receptor-related factor 6(TRAF6)and histone deacetylase 3(HDAC3)with severity of coronary artery disease and prognosis in patients with acute myocardial infarction(AMI).Methods:A total of 122 AMI patients admitted Macheng Traditional Chinese Medicine Hospital between July 2019 and December 2020 were selected,divided into low score group(n=73,＜20 points)and high score group(n=49,≥20 points)according to Gensini score.Association of serum levels of TRAF6 and HDAC3 with Gensini score was analyzed by Pearson method.According to survival condition during hospitalization within 28d,they were divided into survival group(n=85)and death group(n=37).Cox regression model was used to analyze the influencing factors for death within 28d in AMI patients;receiver operating charac-teristic(ROC)curve was used to analyze the predictive efficacy of TRAF6 and HDAC3 for death within 28d in AMI patients.Results:Patients in high score group had significant higher serum levels of TRAF6[(6.01±2.39)μg/ml vs.(5.06±1.74)μg/ml,P=0.012]and HDAC3[(4.14±1.94)ng/ml vs.(2.87±1.37)ng/ml,P＜0.001]compared with low score group.Pearson correlation analysis indicated that serum levels of TRAF6 and HDAC3 were positively correlated with Gensini score(r=0.879,0.837,P＜0.001 all).Patients in death group had significant higher serum levels of TRAF6[(6.89±1.67)μg/ml vs.(4.81±1.24)μg/ml,P＜0.001]and HDAC3[(5.37±1.77)ng/ml vs.(2.52±0.76)ng/ml,P＜0.001]compared with those in survival group.Cox regression analysis indicated that Gensini score[HR=1.857,95％CI 1.259～2.737,P=0.001],TRAF6[HR=1.659,95％CI 1.083～2.543,P=0.022],HDAC3[HR=1.779,95％CI 1.192～2.653,P=0.004]were independent risk factors for death within 28d in AMI patients.ROC curve analysis indicated that AUC of TRAF6,HDAC3 and their combina-tion predicting death within 28d in AMI patients was 0.862,0.859 and 0.971 respectively,and AUC of combination was significantly higher than those of TRAF6 and HDAC3 alone(Z=2.535,2.032,P=0.011,0.042).Conclu-sion:Serum levels of TRAF6 and HDAC3 are closely related to severity of coronary artery disease and prognosis in AMI patients,and dual combination possesses good predictive value for prognosis in AMI patients.

Extracting extracts of secondary metabolites from the karst cave fungus Metarhizium anisopliae NHC-M3-2 from the Yilingyan Scenic Area in Guangxi. Ten compounds were isolated and purified from fungal secondary metabolites using thin-layer chromatography and high-performance liquid chromatography. 7-Hydroxy-3-hydroxypropyl-5,6-dimethylisochrome-1-one (1) and 7-hydroxy-3,5,6-trimethyl-isochromen-1-one (2) were new isocoumarin compounds, N-acetyl phenylalanine (3), chaetosumin J (4), 2-one-13-hydroxy-3,5,8,7(11)-eudesmatetraen-12,8-olide (5), 1H-indole-3-carboxaldehyde (6), irpexolaceus B (7), irlactin L (8), cytochalasin K (9), and helvolic acid (10), a total of 8 known compounds. The structure of the compound was determined using methods such as NMR and mass spectrometry. The tumor cytotoxicity of the compound was evaluated using the CCK-8 method. The results showed that the IC₅₀ of compound 2 on HepG2 cells was 29.83 µmol·L^-1, and compound 9 on HCT116 cells was 27.44 µmol·L^-1.

Objective:To investigate the effect of sertraline hydrochloride combined with compound chamomile lidocaine gel in the treatment of premature ejaculation(PE).Methods:We selected 80 cases of PE treated in our hospital from June 2021 to May 2023 and equally randomized them into a control and an observation group,the former medicated with compound chamomile lidocaine gel while the latter with sertraline hydrochloride in addition,both for 6 weeks.We recorded and compared the intravaginal ejaculation latency time(IELT),the number of successful sexual intercourses per week,the Premature Ejaculation Diagnostic Tool(PEDT)scores,and the incidence of adverse reactions between the two groups of patients.Results:After the treatment,the IELT was signif-icantly longer([5.39±1.17]vs[2.49±0.73]min,P＜0.05),the weekly number of successful sexual intercourses remarkably higher(1.82±0.45 vs 0.93±0.19,P＜0.05)and the PEDT scores markedly lower(7.42±2.04 vs 9.85±2.36,P＜0.05)in the observation than in the control group,but no statistically significant differences were observed in the baseline PEDT scores or the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Sertraline hydrochloride combined with com-pound chamomile lidocaine gel is definitely effective in the treatment of PE,which can significantly improve the patients'quality of sexual life,with a high safety and low incidence of adverse reactions.