Objective: To compare the intervention effects of sitagliptin combined with metformin and insulin aspart combined with metformin among patients with type 2 diabetes mellitus (T2DM), so as to provide the reference for optimizing blood glucose control strategies among patients with T2DM. Methods: T2DM patients admitted to the department of endocrinology of Jinhua Central Hospital from January 2018 to December 2024 were selected as the research objects. According to the propensity score matching, T2DM patients were divided into sitagliptin combined with metformin group and insulin aspart combined with metformin group at a ratio of 1∶1. The basic information, capillary blood glucose, glycosylated hemoglobin blood glucose (HbA1c), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), triglyceride (TG), body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP) of the two groups were collected by questionnaire survey, physical examination and laboratory test. The generalized estimating equation was used to analyze the changes of various indicators before and after treatment between the two groups of patients, and the intervention effect was compared. Results: There were 69 cases in the sitagliptin combined with metformin group. Among these 42 cases were males, accounting for 60.87%, and 27 cases were females, accounting for 39.13%.Forty-two cases were younger than 60 years, accounting for 60.87%. There were 69 cases in the insulin aspart combined with metformin group. Among these 47 cases were males, accounting for 68.12%, and 22 cases were females, accounting for 31.88%. Forty-five cases were younger than 60 years, accounting for 65.22%. There were no statistically significant differences in gender, age, education level, smoking, drinking, vegetable and fruit intake, and disease duration between the two groups (all P>0.05). After 6 months of treatment, there was an interaction between group and time in capillary blood glucose and HbA1c in the two groups (all P<0.05), and the reduction of capillary blood glucose and HbA1c in the sitagliptin combined with metformin group was greater than that in the insulin aspart combined with metformin group. There were no statistically significant differences between groups and time in TC, HDL-C, TG, BMI, SBP, and DBP, and no interaction effect was found between groups and time (all P>0.05). Conclusion Sitagliptin combined with metformin is more effective than insulin aspart combined with metformin in controlling blood glucose among patients with T2DM.

Objective Based on 25 indicators including immune factors, cell count classification, and smear results of the knee joint fluid, machine learning models were established to distinguish between osteoarthritis (OA) and rheumatoid arthritis (RA). Methods 100 OA and 40 RA patients scheduled for total knee arthroplasty were enrolled respectively. Each patient's knee joint fluid was collected preoperatively. Nucleated cells were counted and classified. The expression levels of immune factors, including tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), IL-6, IL-8, IL-15, matrix metalloproteinase 3 (MMP3), MMP9, MMP13, rheumatoid factor (RF), serum amyloid A (SAA), C-reactive protein (CRP), and others were measured. Smears and microscopic classification of all the immune factors were performed. Independent influencing factors for OA or RA were identified using univariate binary logistic regression, Lasso regression, and multivariate binary logistic regression. Based on the independent influencing factors, three machine learning models were constructed which are logistic regression, random forest, and support vector machine. Receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to evaluate and compare the models. Results A total of 5 indicators in the knee joint fluid were screened out to distinguish OA and RA, which were IL-1β(odds ratio(OR)=10.512, 95× confidence interval (95×CI) was 1.048-105.42, P=0.045), IL-6 (OR=1.007, 95×CI was 1.001-1.014, P=0.022), MMP9 (OR=3.202, 95×CI was 1.235-8.305, P=0.017), MMP13 (OR=1.002, 95× CI was 1-1.004, P=0.049), and RF (OR=1.091, 95×CI was 1.01-1.179, P=0.026). According to the results of ROC, calibration curve and DCA, the accuracy (0.979), sensitivity (0.98) and area under the curve (AUC, 0.996, 95×CI was 0.991-1) of the random forest model were the highest. It has good validity and feasibility, and its distinguishing ability is better than the other two models. Conclusion The machine learning model based on immune factors in the knee joint fluid holds significant value in distinguishing OA and RA. It provides an important reference for the clinical early differential diagnosis, prevention and treatment of OA and RA.
Humans ; Arthritis, Rheumatoid/metabolism* ; Machine Learning ; Male ; Female ; Middle Aged ; Aged ; Synovial Fluid/immunology* ; Osteoarthritis, Knee/metabolism* ; Knee Joint/metabolism* ; ROC Curve ; Diagnosis, Differential

OBJECTIVE: To investigate the effects of liriodendrin on the intestinal flora and the ferroptosis signaling pathway in renal tissue of rats with sepsis-induced acute kidney injury (AKI). METHODS: Thirty male Sprague-Dawley (SD) rats were randomly divided into sham operation group (Sham group), sepsis model induced by cecal ligation and puncture group (CLP group), and liriodendrin intervention group (CLP+LIR group), with 10 rats in each group. The CLP+LIR group was given 0.2 mL of 100 mg/kg liriodendrin by gavage 2 hours before modeling; Sham group and CLP group were given the same volume of normal saline by gavage. The samples were collected after anesthesia 24 hours after modeling. The pathological changes of renal tissue were observed by hematoxylin-eosin (HE) staining. The levels of inflammatory factors such as tumor necrosis factor-α (TNF-α), interleukins (IL-1β, IL-6) were detected by enzyme linked immunosorbent assay (ELISA). The levels of renal function indicators such as creatinine (Cr), and urea nitrogen (UREA) in peripheral blood, and the content of malondialdehyde (MDA) and Fe²⁺ in renal tissue were detected. Western blotting was used to detect the expressions of nuclear factor E2-related factor 2 (Nrf2), glutathione peroxidase 4 (GPX4) and heme oxygenase-1 (HO-1) in renal tissues. The changes of intestinal flora were detected by 16S rDNA high-throughput sequencing. RESULTS: Compared with the Sham group, the CLP group showed significantly enlarged glomeruli, noticeable renal interstitial edema, disorganized kidney tissue, and significantly increased pathological scores. The contents of TNF-α, IL-1β, IL-6, Cr, and UREA in peripheral blood and the levels of MDA and Fe²⁺ in renal tissue were significantly increased. The protein expressions of Nrf2, GPX4, and HO-1 in renal tissue were significantly down-regulated. The species richness of intestinal flora decreased significantly, and the relative abundances of pathogenic bacteria such as Morganella, Citrobacter, Proteus, Klebsiella, Shigella, Aggregatibacter, and Enterococcus increased significantly, while the relative abundances of beneficial bacteria such as Butyricimonas, Veillonella, Prevotella, Lactobacillus, Bifidobacterium, and Ruminococcus decreased significantly. Compared with the CLP group, CLP+LIR group could significantly reduce the pathological damage of renal tissue, the pathological score significantly decreased (1.80±0.84 vs. 4.20±1.30, P < 0.05), and improve the composition of intestinal flora, reduce the relative abundances of pathogenic bacteria such as Proteus, Klebsiella, Shigella, Aggregatibacter, and Enterococcus, and significantly increase the relative abundances of Lactobacillus, Bifidobacterium, and Ruminococcus, significantly reduce the contents of TNF-α, IL-1β, IL-6, Cr, and UREA in peripheral blood and the levels of MDA and Fe²⁺ in renal tissue [blood TNF-α (ng/L): 191.31±7.23 vs. 254.90±47.89, blood IL-1β (ng/L): 11.15±4.04 vs. 23.06±1.67, blood IL-6 (ng/L): 163.20±17.83 vs. 267.69±20.92, blood Cr (μmol/L): 24.14±4.25 vs. 41.17±5.43, blood UREA (mmol/L): 4.59±0.90 vs. 8.01±1.07, renal MDA (μmol/g): 9.67±0.46 vs. 16.05±0.88, renal Fe²⁺ (mg/g): 0.71±0.07 vs. 0.93±0.04, all P < 0.05], and increase the protein expressions of Nrf2, GPX4, and HO-1 (Nrf2/GAPDH: 1.21±0.01 vs. 0.39±0.01, GPX4/GAPDH: 0.74±0.04 vs. 0.48±0.04, HO-1/GAPDH: 0.91±0.01 vs. 0.41±0.02, all P < 0.05). CONCLUSIONS Liriodendrin has an obvious protective effect on sepsis-induced AKI. The mechanism may involve regulating the intestinal flora, increasing the activation of the Nrf2/HO-1/GPX4 signaling pathway in renal tissue, and reducing ferroptosis.
Animals ; Acute Kidney Injury/microbiology* ; Rats, Sprague-Dawley ; Sepsis/complications* ; Male ; Ferroptosis/drug effects* ; Gastrointestinal Microbiome/drug effects* ; Rats ; Signal Transduction ; Kidney/metabolism* ; Tumor Necrosis Factor-alpha/metabolism*

Ulcerative colitis (UC) is a chronic and non-specific inflammatory bowel disease (IBD). Huanglian Ganjiang decoction (HGD), derived from ancient book Beiji Qianjin Yao Fang, has demonstrated efficacy in treating UC patients traditionally. Previous research established that the compatibility of cold herb Coptidis Rhizoma + Phellodendri Chinensis Cortex (CP) and hot herb Angelicae Sinensis Radix + Zingiberis Rhizoma (AZ) in HGD synergistically improved colitis mice. This study investigated the compatibility mechanisms through which CP and AZ regulated inflammatory balance in colitis mice. The experimental colitis model was established by administering 3% dextran sulphate sodium (DSS) to mice for 7 days, followed by CP, AZ and CPAZ treatment for an additional 7 days. M1/M2 macrophage polarization levels, glucose metabolites levels and pyruvate dehydrogenase kinase 4 (PDK4) expression were analyzed using flow cytometry, Western blot, immunofluorescence and targeted glucose metabolomics. The findings indicated that CP inhibited M1 macrophage polarization, decreased inflammatory metabolites associated with tricarboxylic acid (TCA) cycle, and suppressed PDK4 expression and pyruvate dehydrogenase (PDH) (Ser-293) phosphorylation level. AZ enhanced M2 macrophage polarization, increased lactate axis metabolite lactate levels, and upregulated PDK4 expression and PDH (Ser-293) phosphorylation level. TCA cycle blocker AG-221 and adeno-associated virus (AAV)-PDK4 partially negated CP's inhibition of M1 macrophage polarization. Lactate axis antagonist oxamate and PDK4 inhibitor dichloroacetate (DCA) partially reduced AZ's activation of M2 macrophage polarization. In conclusion, the compatibility of CP and AZ synergistically alleviated colitis in mice through M1/M2 macrophage polarization balance via PDK4-mediated glucose metabolism reprogramming. Specifically, CP reduced M1 macrophage polarization by restoration of TCA cycle via PDK4 inhibition, while AZ increased M2 macrophage polarization through activation of PDK4/lactate axis.
Animals ; Drugs, Chinese Herbal/chemistry* ; Mice ; Macrophages/immunology* ; Glucose/metabolism* ; Pyruvate Dehydrogenase Acetyl-Transferring Kinase/genetics* ; Male ; Mice, Inbred C57BL ; Humans ; Colitis/drug therapy* ; Disease Models, Animal ; Colitis, Ulcerative/drug therapy* ; Metabolic Reprogramming

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

OBJECTIVE To explore the effect of fluconazole on proteomics of Trichosporon asahii so as to reveal the responding process of T.asahii to fluconazole stress and the resistance mechanisms to azoles on the protein level.METHODS T.asahii AS 2.2174 was chosen as the research subject,the minimum inhibitory concentration(MIC)of fluconazole was determined by broth microdilution assay.The protein abundance of T.asahii was detec-ted by means of tandem mass tag(TMT)technique combined with liquid chromatography-tandem mass spectrom-etry(LC-MS/MS)before and after the treatment with fluconazole(1× MIC).The differentially expressed pro-teins(DEPs)were identified based on the screening standards of fold change ≥1.20 or ≤0.83 and P＜0.05.Gene ontlogy(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis were performed for the DEPs so as to understand the biological property of the DEPs and the major biological pathways that the DEPs in-volved in.Finally,the targeted validation was carried out for the targeted differentially expressed proteins by using multiple reaction monitoring(MRM).RESULTS The MIC of fluconazole to T.asahii AS 2.2174 was 8 μg/ml.Totally 196 DEPs were identified,including 93 upregulated DEPs and 103 downregulated DEPs.The function en-richment analysis showed that the DEPs mainly participated in synthesis and metabolism of sterols,drug metabo-lism,stress response,energy metabolism and intertranslation.The targeted DEPs showed the consistent expres-sion trends in MRM target validation and TMT-LC-MS/MS.CONCLUSIONS The protein abundance of T.asahii has remarkable change under the fluconazole stress.The bioinformatics analysis reveals the complicated molecular mechanisms of T.asahii in response to the fluconazole stress,which may offer valuable ideas for understanding the drug resistance to azoles and developing new drug targets.

Objective To examine of Ye Tianshi's approach to managing internal wind through herbal remedies.Methods A comprehensive search was conducted for medical cases pertaining to internal wind,liver wind,dizziness,head wind,deficiency labor,liver fire,insomnia,convulsions,epilepsy,and headache within the Clinical Guidelines in Medical Cases.Statistical analysis of symptom elements,target locations of symptom elements,frequency of Chinese medicinal substances,their properties,and meridian affiliations was performed using Excel.Prescription patterns were further analyzed through association rules and high-frequency drug clustering.Results The study included a total of 167 medical cases,from which 241 symptom elements and 333 target locations were extracted.A total of 183 prescriptions were analyzed,comprising 132 medicinal substances with an overall frequency of 1309 occurrences.The five most frequently used Chinese medicines were Sheng Di Huang,Fu Shen,E Jiao,Fu Ling,and Shu Di Huang.The predominant property observed was cold,followed by warm and neutral;the most common flavor was sweet,succeeded by bitter and warm.The leading meridian affiliations identified were liver,kidney,lung,heart,and spleen.The drug association rule analysis revealed 14 items,while high-frequency drug clustering resulted in 9 distinct categories.Conclusion Ye Tianshi's therapeutic approach to internal wind emphasizes the concept of"yang transforming into internal wind."The core principles of this treatment strategy involve nourishing bodily fluids to mitigate wind,addressing excess conditions in the upper body while rectifying deficiencies in the lower body,and promoting tranquility in the liver and stomach.Additionally,the use of pungent and sweet flavors is employed to facilitate the transformation of wind,to clear the liver and dispel heat,to eliminate wind and resolve phlegm,to tonify qi and enhance defensive qi,and to clear heat in order to soothe the spirit.This methodology seeks to achieve harmony among the organs and meridians while pacifying internal wind.

OBJECTIVE To explore the effect of fluconazole on proteomics of Trichosporon asahii so as to reveal the responding process of T.asahii to fluconazole stress and the resistance mechanisms to azoles on the protein level.METHODS T.asahii AS 2.2174 was chosen as the research subject,the minimum inhibitory concentration(MIC)of fluconazole was determined by broth microdilution assay.The protein abundance of T.asahii was detec-ted by means of tandem mass tag(TMT)technique combined with liquid chromatography-tandem mass spectrom-etry(LC-MS/MS)before and after the treatment with fluconazole(1× MIC).The differentially expressed pro-teins(DEPs)were identified based on the screening standards of fold change ≥1.20 or ≤0.83 and P＜0.05.Gene ontlogy(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis were performed for the DEPs so as to understand the biological property of the DEPs and the major biological pathways that the DEPs in-volved in.Finally,the targeted validation was carried out for the targeted differentially expressed proteins by using multiple reaction monitoring(MRM).RESULTS The MIC of fluconazole to T.asahii AS 2.2174 was 8 μg/ml.Totally 196 DEPs were identified,including 93 upregulated DEPs and 103 downregulated DEPs.The function en-richment analysis showed that the DEPs mainly participated in synthesis and metabolism of sterols,drug metabo-lism,stress response,energy metabolism and intertranslation.The targeted DEPs showed the consistent expres-sion trends in MRM target validation and TMT-LC-MS/MS.CONCLUSIONS The protein abundance of T.asahii has remarkable change under the fluconazole stress.The bioinformatics analysis reveals the complicated molecular mechanisms of T.asahii in response to the fluconazole stress,which may offer valuable ideas for understanding the drug resistance to azoles and developing new drug targets.

Objective To examine of Ye Tianshi's approach to managing internal wind through herbal remedies.Methods A comprehensive search was conducted for medical cases pertaining to internal wind,liver wind,dizziness,head wind,deficiency labor,liver fire,insomnia,convulsions,epilepsy,and headache within the Clinical Guidelines in Medical Cases.Statistical analysis of symptom elements,target locations of symptom elements,frequency of Chinese medicinal substances,their properties,and meridian affiliations was performed using Excel.Prescription patterns were further analyzed through association rules and high-frequency drug clustering.Results The study included a total of 167 medical cases,from which 241 symptom elements and 333 target locations were extracted.A total of 183 prescriptions were analyzed,comprising 132 medicinal substances with an overall frequency of 1309 occurrences.The five most frequently used Chinese medicines were Sheng Di Huang,Fu Shen,E Jiao,Fu Ling,and Shu Di Huang.The predominant property observed was cold,followed by warm and neutral;the most common flavor was sweet,succeeded by bitter and warm.The leading meridian affiliations identified were liver,kidney,lung,heart,and spleen.The drug association rule analysis revealed 14 items,while high-frequency drug clustering resulted in 9 distinct categories.Conclusion Ye Tianshi's therapeutic approach to internal wind emphasizes the concept of"yang transforming into internal wind."The core principles of this treatment strategy involve nourishing bodily fluids to mitigate wind,addressing excess conditions in the upper body while rectifying deficiencies in the lower body,and promoting tranquility in the liver and stomach.Additionally,the use of pungent and sweet flavors is employed to facilitate the transformation of wind,to clear the liver and dispel heat,to eliminate wind and resolve phlegm,to tonify qi and enhance defensive qi,and to clear heat in order to soothe the spirit.This methodology seeks to achieve harmony among the organs and meridians while pacifying internal wind.

Objective To investigate the effect of Galangin on pyroptosis of bone marrow derived macrophages(BMDMs).Methods BMDMs were cultured in vitro and divided into blank control group,model group and Galangin group with different concentrations.Lipopolysaccharide(LPS)and adenosine triphosphate(ATP)were used to construct the pyroptosis model.The effect of different concentrations of Galangin on the proliferation of BMDMs was detected by cell counting Kit-8(CCK-8).The level of cysteinyl aspartate specific proteinase-1 p10 subunit(caspase-1 p10),interleukin-1β(IL-1β)in supernatant and intracellular nucleotide NOD-like receptor protein 3(NLRP3)were detected by Western blotting.IL-1β in supernatant was detected by enzyme-linked immunosorbent assay(ELISA).The cell death was observed by propidium iodide(PI)staining.High-throughput sequencing was used to compare the gene expression in the model group and Galangin groups at 20 μmol/L.Results There was no statistically significant difference between the 5,10,20,40,60,80 μmol/L Galangin groups on the proliferation level of BMDMs(all P>0.05),indicating that no significant effect of Galangin at 5,10,20,40,60,80 μmol/L was observed on the proliferation of BMDMs.So we selected Galangin at 5,10,20 μmol/L and treatment for 1,2 and 4 hours as the effects of different concentrations and time on the pyroptosis of BMDMs.Compared with blank control group,the expression of caspase-1 p10 and mature IL-1β protein and IL-1β in supernatant in model group were significantly increased(all P<0.05).Compared with model group,the expression of caspase-1 p10 and mature IL-1β protein and IL-1β in supernatant of Galangin at 5,10 and 20 μmol/L were significantly decreased[IL-1β protein expression(gray value):0.155±0.006,0.113±0.006,0.111±0.007 vs.1.000±0.000,caspase-1 p10 protein expression(gray value):0.207±0.044,0.160±0.008,0.082±0.008 vs.1.000±0.000,IL-1β(μg/L):99.80±10.36,85.21±8.78,26.53±4.56 vs.494.10±35.47,all P<0.05].There was no significant difference between the different concentration groups(all P>0.05),but with the extension of treatment time of Galangin,the inhibitory effect was enhanced.The inhibitory effect of Galangin at 20 μmol/L for 4 hours was the most obvious[IL-1β protein expression(gray value):0.186±0.004 vs.1.000±0.000,caspase-1 p10 protein expression(gray value):0.247±0.009 vs.1.000±0.000,IL-1β(μg/L):173.80±10.56 vs.653.80±76.02,all P<0.05].Treatment with 20 μmol/L Galangin for 4 hours could reduce the number of pyroptotic cell deaths(number of view:23.00±3.61 vs.67.67±15.63,P<0.05)and inhibited the expression of NLRP3 protein(gray value:0.178±0.025 vs.0.406±0.066,P<0.05).High-throughput sequencing showed that,compared with the model group,Galangin down-regulated the genes of Nlrp3,Nod2,IL-1β and up-regulated genes of Skp2(also known as Fbxl1),Fbxl20,Fbxl4,Fbxo32 and Fbxw7.Conclusion Galangin inhibited pyroptosis mediated by NLRP3 inflammasome in macrophages.