[Objective] To establish a new scoring system to predict the perioperative outcomes (operation time, intraoperative blood loss, and trifecta achievement) in patients undergoing robot-assisted partial nephrectomy (RAPN) by integrating the RENAL and Mayo adhesive probability (MAP) scores. [Methods] Clinical data of 178 patients with renal cell carcinoma who underwent RAPN performed by the same surgeon in our hospital during Jan.2015 and Jan.2022 were retrospectively analyzed.The RENAL and MAP scores of all patients were calculated.Linear regression and logistic regression were used to evaluate the associations between the components of the RENAL and MAP scores (a total of 6 variables) and perioperative outcomes.The factors with significant associations were then included into logistic regression analysis to identify independent predictors for constructing an assessment system for perioperative outcomes, and the receiver operating characteristic (ROC) curve was plotted to calculate the area under the curve (AUC) to predict its efficacy. [Results] Multivariate linear regression analysis showed that tumor size (β=6.14, 95%CI: 1.93—10.34, P=0.004), exophytic rate (β=10.60, 95%CI: 3.44—17.76, P=0.004), and perinephric fat thickness (β=16.48, 95%CI: 8.52—24.45, P<0.001) were significantly associated with operation time.Tumor size (β=10.55 95%CI: 5.60—15.49, P<0.001) was associated with both intraoperative blood loss and trifecta achievement (OR=1.73, 95%CI: 1.26—2.36, P=0.001). Multivariate logistic regression analysis of these 3 factors identified tumor size (OR=9.07, 95% CI: 1.18—69.45, P=0.03) and perinephric fat thickness (OR=2.28, 95%CI: 1.86—6.04, P=0.01) as independent predictors of perioperative outcomes.Based on these findings, the tumor size and perinephric fat thickness (RP) scoring was constructed, which demonstrated better predictive ability than RENAL score or MAP score alone (RP vs.RENAL vs.MAP: 0.766 vs.0.548 vs.0.684). [Conclusion] The RP score includes fewer variables than the RENAL and MAP scores but outperforms them.

Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

Objective: To retrospectively analyze the early monitoring indicators before and after admission, the use of coagulation/anticoagulant medications, and the red blood cell transfusion within 24 hours in emergency trauma patients, and to identify the indicators related to the volume of red blood cells transfused during the first 24 hours of hopitalization, thereby assisting clinical judgment of the probability and required quantity of red blood cell transfusion. Methods: Data of 117 emergency trauma patients admitted to intensive care unit (ICU) from January 2022 to March 2024 were retrospectively analyzed. Patients were categorized according to whether the volume of red blood cells transfused within 24 hours exceeded specific quartile thresholds (Q1, Q2, Q3). Non-parametric tests were used for numerical variables and Chi-square tests were used for categorical variables to identify statistically significant single-factor indicators, which were subsequently incoporated into a binary logistic regression model to obtain a combined predictive probability. ROC curve analysis was performed on the multi-factor indicators and their combined predictive probability derived from the binary logistic regression model. Results: 1) The initial hemoglobin (Hb) and hematocrit (Hct) levle were independent influencing factors in the group with red blood cell transfusion volume exceeded Q1 (P<0.05), and the combined predictive probability demostrated by ROC curve analysis was AUC=0.858 (P<0.05). 2) In the group of red blood cell transfusion volume exceeding Q2, the initial Fib, transhulitic acid, human prothrombin complex, trauma category and primary trauma site were independent influencing factors (P<0.05), and the combined predictive probability of ROC curve analysis was AUC=0.966 (P<0.05). 3) Pulse pressure and trauma category were independent influencing factors in the group with red blood cell transfusion volume exceeding Q3 (P<0.05), and ROC curve analysis revealed that combined prediction probability was AUC=0.944 (P<0.05). Conclusion: Early monitoring indicators and the use of coagulation medications, before and after admission in emergency trauma patients show diagnostic value in predicting the amount of red blood cells transfused on the first day of admission. Early warning alerts established through patient monitoring indicators can reduce incidents of untimely blood supply from the blood transfusion department (blood bank) for emergency trauma patients with massive hemorrhage, especially for patients with rare blood types or during blood supply shortage.

Sumoylation is a newly discovered post-translational modification, in which a small ubiquitin-like modifier (SUMO) is covalently conjugated to a lysine residue in a target protein. This provides an efficient way to modulate the activity, stability and subcellular localization of a wide variety of substrates. Sumoylation plays a key role in the occurrence and development of type 2 diabetes mellitus (T2DM). This paper addresses the relationship between sumoylation and T2DM in regulation of pancreatic β-cell function, the metabolic order in skeletal muscles, liver and other organs and diabetes-associated complications. A deeper knowledge of sumoylation may enable us to better understand the pathogenesis of T2DM and sumoylation system at the molecular level, which can help provide new ideas for the early diagnosis and subsequent treatment of T2DM and its associated complications.

This study aims to investigate the ameliorating effect of Corni Fructus(CF) on the myocardial ischemic injury and the pharmacokinetic properties of characteristic components of CF. The mouse model of isoproterenol-induced myocardial ischemia was established and administrated with the aqueous extract of CF. The general efficacy of CF in ameliorating the myocardial ischemic injury was evaluated based on the cardiac histopathology and the levels of myocardial injury markers: creatine kinase isoenzyme(CK-MB) and cardiac troponin I(cTn-I). The metabolomics analysis was carried out for the heart and serum samples of mice to screen the biomarkers of CF in ameliorating the myocardial ischemic injury and then the predicted biomarkers were submitted to metabolic pathway enrichment. The pharmacokinetic analysis was performed for morroniside, loganin, and cornuside Ⅰ in mouse heart and serum samples to obtain the pharmacokinetic parameters of these components. The pharmacokinetic parameters were then integrated on the basis of self-defined weighting coefficients to simulate an integrated pharmacokinetic profile of CF iridoid glycosides in the heart and serum of the mouse model of myocardial ischemia. The results indicated that CF reduced the pathological damage to cardiac cells and tissue(hematoxylin-eosin staining) and lowered the levels of CK-MB and cTn-I in the serum of the mouse model of myocardial ischemia(P<0.01). Metabolomics analysis screed out 31 endogenous metabolites in the heart and 35 in the serum as biomarkers of CF in ameliorating the myocardial ischemic injury. These biomarkers were altered by modeling and restored by CF. Six metabolic pathways in the heart and 5 in the serum were enriched based on these metabolic markers. The main integrated pharmacokinetic parameters of CF iridoid glycosides were T_(max)=1 h, t_(1/2)=(1.52±0.05) h in the heart and T_(max)=1 h, t_(1/2)=(1.56±0.50) h in the serum. Both concentration-time curves showed a double-peak phenomenon. In conclusion, CF demonstrated the cardioprotective effect by regulating metabolic pathways such as taurine and hypotaurine metabolism, and pantothenic acid and coenzyme A biosynthesis. The integrated pharmacokinetics reflect the general pharmacokinetic properties of characteristic components in CF.
Animals ; Cornus/chemistry* ; Mice ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Myocardial Ischemia/metabolism* ; Humans ; Troponin I/metabolism* ; Myocardium/pathology* ; Disease Models, Animal ; Biomarkers/metabolism* ; Creatine Kinase, MB Form/metabolism*

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

The gut microbiota regulates intestinal nutrient absorption, participates in modulating host glucolipid metabolism, and contributes to ameliorating glucolipid metabolism disorder. Dysbiosis of the gut microbiota can compromise the integrity of the intestinal mucosal barrier, induce inflammatory responses, and exacerbate insulin resistance and abnormal lipid metabolism in the host. Dangua Humai Oral Liquid, a hospital-developed formulation for regulating glucolipid metabolism, has been granted a national invention patent and demonstrates significant clinical efficacy. This study aimed to investigate the effects of Dangua Humai Oral Liquid on gut microbiota and the intestinal mucosal barrier in a mouse model with glucolipid metabolism disorder. A glucolipid metabolism disorder model was established by feeding mice a high-glucose and high-fat diet. The mice were divided into a normal group, a model group, and a treatment group, with eight mice in each group. The treatment group received a daily gavage of Dangua Humai Oral Liquid(20 g·kg~(-1)), while the normal group and model group were given an equivalent volume of sterile water. After 15 weeks of intervention, glucolipid metabolism, intestinal mucosal barrier function, and inflammatory responses were evaluated. Metagenomics and untargeted metabolomics were employed to analyze changes in gut microbiota and associated metabolic pathways. Significant differences were observed between the indicators of the normal group and the model group. Compared with the model group, the treatment group exhibited marked improvements in glucolipid metabolism disorder, alleviated pathological damage in the liver and small intestine tissue, elevated expression of recombinant claudin 1(CLDN1), occluding(OCLN), and zonula occludens 1(ZO-1) in the small intestine tissue, and reduced serum levels of inflammatory factors lipopolysaccharides(LPS), lipopolysaccharide-binding protein(LBP), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α). At the phylum level, the relative abundance of Bacteroidota decreased, while that of Firmicutes increased. Lipid-related metabolic pathways were significantly altered. In conclusion, based on the successful establishment of the mouse model of glucolipid metabolism disorder, this study confirmed that Dangua Humai Oral Liquid effectively modulates gut microbiota and mucosal barrier function, reduces serum inflammatory factor levels, and regulates lipid-related metabolic pathways, thereby ameliorating glucolipid metabolism disorder.
Animals ; Gastrointestinal Microbiome/drug effects* ; Mice ; Intestinal Mucosa/microbiology* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred C57BL ; Humans ; Glycolipids/metabolism* ; Lipid Metabolism/drug effects* ; Administration, Oral ; Disease Models, Animal

OBJECTIVE: To explore the epidemiological characteristics of knee osteoarthritis (KOA) among the elderly in the community, and its correlation with bone mass loss. METHODS: A cross-sectional study was conducted on elderly community population over 50 year old from 12 community health service centers in Zhejiang province. Their gender, age, body mass index (BMI), T value and KOA diagnosis were collected using face to face questionnaire survey. Univariate regression was used to analyze the influence of age, gender, BMI and bone loss on KOA. Logistic multivariate regression model was used to analyze the independent effect of bone mass loss on KOA. RESULTS: Among 4 173 subjects in this study, 1 710 of them were had a KOA. The prevalence rate was 40.9%. The mean age, the proportion of females and the mean BMI in KOA patients were (65.5±3.8) years old, 67.7%(1 158/1 710) and(24.59±1.28) kg·m^-2, respectively, which were significantly higher than (58.5±3.2) years old, 51.3%(1 263/2 463), and (23.48±1.25) kg·m^-2 in non-KOA subjects (P<0.001). In the population aged from 60 to 69 years old, the influence of osteopenia and osteoporosis on the prevalence of KOA was[OR=1.21, 95%CI(1.00, 1.46), P=0.053 2], [OR=1.42, 95%CI(1.14, 1.78), P=0.002 2]. The influence of male and female osteoporosis on the prevalence of KOA was [OR=1.52, 95%CI(1.16, 1.99), P=0.002 7] and [OR=1.87, 95%CI(1.51, 2.32), P<0.000 1], respectively. In the population of 24 kg·m^-2≤BMI<28 kg·m^-2, the influence of osteopenia and osteoporosis on the prevalence of KOA was [OR=1.47, 95%CI(1.21, 1.80), P=0.000 1], [OR=2.69, 95%CI(2.11, 3.42), P<0.000 1], respectively. After controlling the confounding factors of age, gender and BMI, compared with people with normal bone mass, the effect of osteopenia on the prevalence of KOA was [OR=1.34, 95%CI(1.08, 1.67), P=0.009 2], and the effect of osteoporosis on the prevalence of KOA was [OR=1.38, 95%CI(1.06, 1.79), P=0.017 9]. CONCLUSION Elderly overweight women are more likely to develop KOA. Bone mass loss is an independent risk factor for KOA, which will significantly increase the prevalence of KOA in people overweight or aged 60 to 69 years old.
Humans ; Female ; Male ; Aged ; Osteoarthritis, Knee/etiology* ; Middle Aged ; Cross-Sectional Studies ; Bone Density ; Aged, 80 and over ; Incidence ; Body Mass Index ; China/epidemiology* ; Osteoporosis/epidemiology*