OBJECTIVE: To explore the potential effects and mechanisms of Liang-Ge-San (LGS) for the treatment of acute respiratory distress syndrome (ARDS) through network pharmacology analysis and to verify LGS activity through biological experiments. METHODS: The key ingredients of LGS and related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. ARDS-related targets were selected from GeneCards and DisGeNET databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the Metascape Database. Molecular docking analysis was used to confirm the binding affinity of the core compounds with key therapeutic targets. Finally, the effects of LGS on key signaling pathways and biological processes were determined by in vitro and in vivo experiments. RESULTS: A total of LGS-related targets and 496 ARDS-related targets were obtained from the databases. Network pharmacological analysis suggested that LGS could treat ARDS based on the following information: LGS ingredients luteolin, wogonin, and baicalein may be potential candidate agents. Mitogen-activated protein kinase 14 (MAPK14), recombinant V-Rel reticuloendotheliosis viral oncogene homolog A (RELA), and tumor necrosis factor alpha (TNF-α) may be potential therapeutic targets. Reactive oxygen species metabolic process and the apoptotic signaling pathway were the main biological processes. The p38MAPK/NF-κ B signaling pathway might be the key signaling pathway activated by LGS against ARDS. Moreover, molecular docking demonstrated that luteolin, wogonin, and baicalein had a good binding affinity with MAPK14, RELA, and TNF α. In vitro experiments, LGS inhibited the expression and entry of p38 and p65 into the nucleation in human bronchial epithelial cells (HBE) cells induced by LPS, inhibited the inflammatory response and oxidative stress response, and inhibited HBE cell apoptosis (P<0.05 or P<0.01). In vivo experiments, LGS improved lung injury caused by ligation and puncture, reduced inflammatory responses, and inhibited the activation of p38MAPK and p65 (P<0.05 or P<0.01). CONCLUSION LGS could reduce reactive oxygen species and inflammatory cytokine production by inhibiting p38MAPK/NF-κ B signaling pathway, thus reducing apoptosis and attenuating ARDS.
Drugs, Chinese Herbal/pharmacology* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Humans ; Male ; Network Pharmacology ; Apoptosis/drug effects* ; Mice

OBJECTIVE: To identify the underlying mechanism by which quercetin (Que) alleviates sepsis-related acute respiratory distress syndrome (ARDS). METHODS: In vivo, C57BL/6 mice were assigned to sham, cecal ligation and puncture (CLP), and CLP+Que (50 mg/kg) groups (n=15 per group) by using a random number table. The sepsisrelated ARDS mouse model was established using the CLP method. In vitro, the murine alveolar macrophages (MH-S) cells were classified into control, lipopolysaccharide (LPS), LPS+Que (10 μmol/L), and LPS+Que+acetylcysteine (NAC, 5 mmol/L) groups. The effect of Que on oxidative stress, inflammation, and apoptosis in mice lungs and MH-S cells was determined, and the mechanism with reactive oxygen species (ROS)/p38 mitogen-activated protein kinase (MAPK) pathway was also explored both in vivo and in vitro. RESULTS: Que alleviated lung injury in mice, as reflected by a reversal of pulmonary histopathologic changes as well as a reduction in lung wet/dry weight ratio and neutrophil infiltration (P<0.05 or P<0.01). Additionally, Que improved the survival rate and relieved gas exchange impairment in mice (P<0.01). Que treatment also remarkedly reduced malondialdehyde formation, superoxide dismutase and catalase depletion, and cell apoptosis both in vivo and in vitro (P<0.05 or P<0.01). Moreover, Que treatment diminished the release of inflammatory factors interleukin (IL)-1β, tumor necrosis factor-α, and IL-6 both in vivo and in vitro (P<0.05 or P<0.01). Mechanistic investigation clarifified that Que administration led to a decline in the phosphorylation of p38 MAPK in addition to the suppression of ROS expression (P<0.01). Furthermore, in LPS-induced MH-S cells, ROS inhibitor NAC further inhibited ROS/p38 MAPK pathway, as well as oxidative stress, inflammation, and cell apoptosis on the basis of Que treatment (P<0.05 or P<0.01). CONCLUSION Que was found to exert anti-oxidative, anti-inflammatory, and anti-apoptotic effects by suppressing the ROS/p38 MAPK pathway, thereby conferring protection for mice against sepsis-related ARDS.
Animals ; Sepsis/drug therapy* ; Quercetin/therapeutic use* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; Mice, Inbred C57BL ; Reactive Oxygen Species/metabolism* ; Apoptosis/drug effects* ; Male ; Oxidative Stress/drug effects* ; MAP Kinase Signaling System/drug effects* ; Lung/drug effects* ; Mice ; Lipopolysaccharides ; Macrophages, Alveolar/pathology* ; Inflammation/pathology* ; Protective Agents/therapeutic use*

Objective To analyze the influencing factors for postoperative anastomotic leak (AL) in carcinoma of the esophagus and gastroesophageal junction and construct a nomogram predictive model. Methods The patients who underwent radical esophagectomy at Jinling Hospital Affiliated to Nanjing University School of Medicine from January 2018 to June 2020 were included in this study. Relevant variables were screened using univariate and multivariate logistic regression analyses. A nomogram was then developed to predict the risk factors associated with postoperative AL. The predictive performance of the nomogram was validated using the receiver operating characteristic (ROC) curve. Results A total of 468 patients with carcinoma of the esophagus and gastroesophageal junction were included in the study, comprising 354 males and 114 females, with a mean age of (62.8±7.2) years. The tumors were predominantly located in the middle or lower esophagus, and 51 (10.90%) patients experienced postoperative AL. Univariate logistic regression analysis indicated that age, body mass index (BMI), tumor location, preoperative albumin levels, diabetes mellitus, anastomosis technique, anastomosis site, and C-reactive protein (CRP) levels were potentially associated with AL (P<0.05). Multivariate logistic regression analysis identified age, BMI, tumor location, diabetes mellitus, anastomosis technique, and CRP levels as independent risk factors for AL (P<0.05). A nomogram was developed based on the findings from the multivariate logistic regression analysis. The area under the receiver operating characteristic (ROC) curve was 0.803, indicating a strong concordance between the actual observations and the predicted outcomes. Furthermore, decision curve analysis demonstrated that the newly established nomogram holds significant value for clinical decision-making. Conclusion The predictive model for postoperative AL in patients with carcinoma of the esophagus and gastroesophageal junction demonstrates strong predictive validity and is essential for guiding clinical monitoring, early detection, and preventive strategies.

In recent years, robot-assisted esophagectomy has become increasingly widespread, but the esophagogastric anastomosis step remains relatively complex and cumbersome. Currently, commonly used gastrointestinal reconstruction anastomosis techniques include end-to-end anastomosis, end-to-side anastomosis, and side-to-side anastomosis. Depending on the anastomosis method, they can be further divided into manual anastomosis and mechanical anastomosis, with common instruments including circular staplers and linear staplers. In esophageal cancer surgery, the choice of esophagogastric anastomosis technique is typically based on the tumor’s location and size as well as the surgeon’s preference. Each anastomosis technique has its advantages and disadvantages. With continuous improvements in anastomosis techniques and updates in stapling instruments, the incidence of complications after esophagogastric anastomosis has been effectively reduced. However, safely and efficiently completing gastrointestinal reconstruction during surgery remains a significant challenge. Scholars have made extensive explorations in this field, actively proposing and achieving various reconstruction methods, leading to significant progress. This article reviews the research progress of robot-assisted esophagogastric anastomosis techniques from both the anastomosis techniques and methods perspectives.

Objective:To analyze the risk factors of cardiac arrest during pre-hospital emergency treatment,and to construct the corresponding nomogram model.Methods:A retrospective analysis was performed on 159 patients who were dispatched by our center and received pre-hospital emergency treatment from Jan 2021 to Jan 2023.As the modeling group,these patients were divided into the occurrence group(n=54)and the non-occurrence group(n=105)according to whether they had cardiac arrest.According to the ratio of modeling group∶validation group=1.2∶1.0,132 patients who were dispatched and received pre-hospital emergency treatment by our center from Feb 2023 to Oct 2024 were selected as the validation group.They were divided into the occurrence group(n=45)and the non-occurrence group(n=87).Multivariable Logistic regression analysis was employed to investigate the factors influencing pre-hospital cardiac arrest and to construct a predictive model.The value of the predictive model was evaluated using receiver operating characteristic(ROC)curve,calibration curve,and decision curve.Results:Multivariate Logistic regression analysis showed that age＞59 years old(OR=0.658,95%CI:0.559-0.773),rescue arrival time＞10 min(OR=7.699,95%CI:3.013-19.675)and non-standard pre-hospital emergency measures(OR=2.807,95%CI:1.150-6.853)were independent risk factors for pre-hospital emergency cardiac arrest(P＜0.05).The nomogram model constructed according to the above factors was verified,and the C-index of the modeling group and verification group model was 0.798(95%CI:0.749-0.847)and 0.794(95%CI:0.740-0.848),respectively,which proved that the prediction efficiency of this model was good,and the decision curve showed good clinical benefit.Conclusion:Age＞59 years old,rescue arrival time＞10 min,and non-standard pre-hospital emergency measures are independent risk factors for pre-hospital emergency cardiac arrest,and the constructed prediction model has good clinical application.

Objective:To screen risk factors for ICU-acquired weakness in patients with mechanical ventilation and construct a predictive model, so as to provide a basis for the health management of patients with mechanical ventilation.Methods:Convenience sampling was used to select 312 ICU patients with mechanical ventilation admitted to the Tenth People's Hospital of Tongji University from October 2019 to August 2020 for the study. Patients were divided into training set ( n=220) and test set ( n=92) in a 7∶3 ratio. Based on machine learning algorithms, decision random forest (DRF), extremely-randomized trees (XRT) and generalized linear model (GLM) were used to construct three ICU-acquired weakness risk prediction models for patients with mechanical ventilation, respectively. The performance of the prediction model was evaluated using the area under the receiver operating characteristic curve ( AUC), the area under the precision-recall curve ( AUPRC), and the root mean square error ( RMSE) . Results:There were 7 predictors of risk of ICU-acquired weakness in patients with mechanical ventilation, including age, gender, braking, duration of mechanical ventilation, blood glucose, lactic acid, and parenteral nutrition. Test set and training set validation showed that AUC and AUPRC of GLM prediction model were greater than those of DRF, XRT prediction model. Test set validation indicated that the RMSE, logarithmic loss of GLM prediction model was less than those of DRF, XRT prediction model. Conclusions:Machine learning algorithm based GLM prediction model has good prediction performance. Healthcare professionals can construct evidence-based decisions for interventions in areas such as braking, duration of mechanical ventilation, and blood glucose management.

Objective:To analyze the risk factors of cardiac arrest during pre-hospital emergency treatment,and to construct the corresponding nomogram model.Methods:A retrospective analysis was performed on 159 patients who were dispatched by our center and received pre-hospital emergency treatment from Jan 2021 to Jan 2023.As the modeling group,these patients were divided into the occurrence group(n=54)and the non-occurrence group(n=105)according to whether they had cardiac arrest.According to the ratio of modeling group∶validation group=1.2∶1.0,132 patients who were dispatched and received pre-hospital emergency treatment by our center from Feb 2023 to Oct 2024 were selected as the validation group.They were divided into the occurrence group(n=45)and the non-occurrence group(n=87).Multivariable Logistic regression analysis was employed to investigate the factors influencing pre-hospital cardiac arrest and to construct a predictive model.The value of the predictive model was evaluated using receiver operating characteristic(ROC)curve,calibration curve,and decision curve.Results:Multivariate Logistic regression analysis showed that age＞59 years old(OR=0.658,95%CI:0.559-0.773),rescue arrival time＞10 min(OR=7.699,95%CI:3.013-19.675)and non-standard pre-hospital emergency measures(OR=2.807,95%CI:1.150-6.853)were independent risk factors for pre-hospital emergency cardiac arrest(P＜0.05).The nomogram model constructed according to the above factors was verified,and the C-index of the modeling group and verification group model was 0.798(95%CI:0.749-0.847)and 0.794(95%CI:0.740-0.848),respectively,which proved that the prediction efficiency of this model was good,and the decision curve showed good clinical benefit.Conclusion:Age＞59 years old,rescue arrival time＞10 min,and non-standard pre-hospital emergency measures are independent risk factors for pre-hospital emergency cardiac arrest,and the constructed prediction model has good clinical application.

Objective:To screen risk factors for ICU-acquired weakness in patients with mechanical ventilation and construct a predictive model, so as to provide a basis for the health management of patients with mechanical ventilation.Methods:Convenience sampling was used to select 312 ICU patients with mechanical ventilation admitted to the Tenth People's Hospital of Tongji University from October 2019 to August 2020 for the study. Patients were divided into training set ( n=220) and test set ( n=92) in a 7∶3 ratio. Based on machine learning algorithms, decision random forest (DRF), extremely-randomized trees (XRT) and generalized linear model (GLM) were used to construct three ICU-acquired weakness risk prediction models for patients with mechanical ventilation, respectively. The performance of the prediction model was evaluated using the area under the receiver operating characteristic curve ( AUC), the area under the precision-recall curve ( AUPRC), and the root mean square error ( RMSE) . Results:There were 7 predictors of risk of ICU-acquired weakness in patients with mechanical ventilation, including age, gender, braking, duration of mechanical ventilation, blood glucose, lactic acid, and parenteral nutrition. Test set and training set validation showed that AUC and AUPRC of GLM prediction model were greater than those of DRF, XRT prediction model. Test set validation indicated that the RMSE, logarithmic loss of GLM prediction model was less than those of DRF, XRT prediction model. Conclusions:Machine learning algorithm based GLM prediction model has good prediction performance. Healthcare professionals can construct evidence-based decisions for interventions in areas such as braking, duration of mechanical ventilation, and blood glucose management.

OBJECTIVE: To study the impacts of varicocele (VC) and varicocelectomy (VCT) on the proteomics of rat testis tissue, and to analyze the differential proteins and signaling pathways, and observe the microstructural changes of the testis tissue. METHODS: We selected 60 male SD rats and divided them into a sham operation (SO), a VC model control, and a VCT group. We harvested the testis tissues from the rats at 4 weeks after modeling for determination of the differential protein expressions by mass spectrometry, analysis of the changes in the protein signaling pathways by KEGG pathway repolarization, and observation of the microstructural changes in the spermatogenic cells under the transmission electron microscope (TEM). RESULTS: A total of 15 clinically significant proteins were effectively identified, among which RPS24, KIFAP3, HPX, RPL38, TOP2A, PRPF19, TRPM3, RPL32, CNBP and AHSG were upregulated, while RPS9, TKFC, SH3BGRL3, ACAA2 and FABP3 downregulated. The differential pathways found included the Type-I 4-aminobutyrate degradation pathway, eIF2 signaling pathway, and Type-III glutamate degradation pathway, which were all related to the pathogenesis of testicular growth arrest. Compared with the rats in the VCT group, those of the VC group rats showed ultrastructural changes in the testis tissue under the TEM, such as mitochondrial vacuolar degeneration, dense nucleoli, invagination of cell nuclear membranes, and irregularity, which were detrimental to the survival of testicular cells. CONCLUSION VCT affects the development and growth of the testis by altering the expressions of relevant proteins and influencing the changes of the gene pathways in the testicular cells, which may be one of the causes of VC inducing testis injury and testicular spermatogenic dysfunction. The changes in these molecular pathways can provide some theoretical evidence for an insight VC as well as potential therapeutic targets for its treatment.
Male ; Animals ; Varicocele/pathology* ; Rats ; Testis/ultrastructure* ; Rats, Sprague-Dawley ; Proteomics ; Signal Transduction ; Proteome

OBJECTIVE: To evaluate the clinical efficacy and safety of Wuziyuye Decoction in the treatment of type-II diabetes mellitus (DM) with qi-yin deficiency complicated by asthenospermia. METHODS: We selected 100 cases of type-II DM with qi-yin deficiency complicated by asthenospermia treated in the First Hospital Affiliated to Ningbo University from January 2023 to March 2024, and randomly assigned them to receive Wuziyuye Decoction (the trial group, n = 50) and oral L-carnitine solution (the control group, n = 50) in addition to Western medicine to reduce fasting blood glucose to normal in both groups. After 12 weeks of medication, we followed up the patients for 24 weeks, obtained their semen parameters, traditional Chinese medicine (TCM) syndrome scores and levels of reproductive hormones, and the clinical pregnancy outcomes of their partners, followed by comparison of the data collected between the two groups before and after treatment. RESULTS: After 12 weeks of treatment, the trial group showed significant improvement over the baseline in the percentage of progressive motility (PR%) (［35.5±6.1］% vs ［18.0±4.2］%, P<0.05), sperm concentration (［54.0±33.4］ vs ［40.0±36.1］ × 10⁶/ml, P<0.05), and TCM syndrome score (4.5±2.3 vs 18.5±5.2, P<0.05), but no statistically significant difference in the semen volume (［2.85±0.36］ vs ［2.84±0.59］ ml, P>0.05), while the controls exhibited markedly improved percentage of PR% (［29.5±6.2］% vs ［18.5±4.5］%, P<0.05) and sperm concentration (［45.0±34.1］ vs ［42.0±38.3］ × 10⁶/ml, P<0.05), but no statistically significant difference in the semen volume (［3.04±0.89］ vs ［2.90±0.78］ ml, P>0.05) and TCM syndrome score (17.2±4.5 vs 17.8±4.8, P>0.05). The patients treated with Wuziyuye Decoction achieved even more significant improvement than the controls in the percentage of PR%, sperm concentration and TCM syndrome score (P<0.05), but there were no statistically significant differences in the reproductive hormone levels and clinical pregnancy outcomes between the two groups of patients after treatment (P>0.05). And no severe adverse reactions were observed in either group. CONCLUSION Wuziyuye Decoction is safe and effective for the treatment of type-II DM with qi-yin deficiency complicated by asthenospermia by improving the sperm motility and concentration of the patient.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Asthenozoospermia/complications* ; Diabetes Mellitus, Type 2/drug therapy* ; Yin Deficiency/complications* ; Adult ; Medicine, Chinese Traditional ; Sperm Motility ; Qi ; Female ; Pregnancy