This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

This study investigated the effects and underlying mechanisms of vanillic acid(VA) against cardiac fibrosis(CF) induced by isoproterenol(ISO) in mice. Male C57BL/6J mice were randomly divided into control group, VA group(100 mg·kg~(-1), ig), ISO group(10 mg·kg~(-1), sc), ISO + VA group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig), ISO + dynamin-related protein 1(Drp1) inhibitor(Mdivi-1) group(10 mg·kg~(-1), sc + 50 mg·kg~(-1), ip), and ISO + VA + Mdivi-1 group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig + 50 mg·kg~(-1), ip). The treatment groups received the corresponding medications once daily for 14 consecutive days. On the day after the last administration, cardiac functions were evaluated, and serum and cardiac tissue samples were collected. These samples were analyzed for serum aspartate aminotransferase(AST), lactate dehydrogenase(LDH), creatine kinase-MB(CK-MB), cardiac troponin I(cTnI), reactive oxygen species(ROS), interleukin(IL)-1β, IL-4, IL-6, IL-10, IL-18, and tumor necrosis factor-α(TNF-α) levels, as well as cardiac tissue catalase(CAT), glutathione(GSH), malondialdehyde(MDA), myeloperoxidase(MPO), superoxide dismutase(SOD), total antioxidant capacity(T-AOC) activities, and cytochrome C levels in mitochondria and cytoplasm. Hematoxylin-eosin, Masson, uranium acetate and lead citrate staining were used to observe morphological and mitochondrial ultrastructural changes in the cardiac tissues, and myocardial injury area and collagen volume fraction were calculated. Flow cytometry was applied to detect the relative content and M1/M2 polarization of cardiac macrophages. The mRNA expression levels of macrophage polarization markers [CD86, CD206, arginase 1(Arg-1), inducible nitric oxide synthase(iNOS)], CF markers [type Ⅰ collagen(Coll Ⅰ), Coll Ⅲ, α-smooth muscle actin(α-SMA)], and cytokines(IL-1β, IL-4, IL-6, IL-10, IL-18, TNF-α) in cardiac tissues were determined by quantitative real-time PCR. Western blot was used to detect the protein expression levels of Coll Ⅰ, Coll Ⅲ, α-SMA, Drp1, p-Drp1, voltage-dependent anion channel(VDAC), hexokinase 1(HK1), NOD-like receptor protein 3(NLRP3), apoptosis-associated speck-like protein(ASC), caspase-1, cleaved-caspase-1, gasdermin D(GSDMD), cleaved N-terminal gasdermin D(GSDMD-N), IL-1β, IL-18, B-cell lymphoma-2(Bcl-2), B-cell lymphoma-xl(Bcl-xl), Bcl-2-associated death promoter(Bad), Bcl-2-associated X protein(Bax), apoptotic protease activating factor-1(Apaf-1), pro-caspase-3, cleaved-caspase-3, pro-caspase-9, cleaved-caspase-9, poly(ADP-ribose) polymerase-1(PARP-1), and cleaved-PARP-1 in cardiac tissues. The results showed that VA significantly improved cardiac function in mice with CF, reduced myocardial injury area and cardiac index, and decreased serum levels of AST, CK-MB, cTnI, LDH, ROS, IL-1β, IL-6, IL-18, and TNF-α. VA also lowered MDA and MPO levels, mRNA expressions of IL-1β, IL-6, IL-18, and TNF-α, and mRNA and protein expressions of Coll Ⅰ, Coll Ⅲ, and α-SMA in cardiac tissues, and increased serum levels of IL-4 and IL-10, cardiac tissue levels of CAT, GSH, SOD, and T-AOC, and mRNA expressions of IL-4 and IL-10. Additionally, VA ameliorated cardiac pathological damage, inhibited myocardial cell apoptosis, inflammatory infiltration, and collagen fiber deposition, reduced collagen volume fraction, and alleviated mitochondrial damage. VA decreased the ratio of F4/80~+CD86~+ M1 cells and the mRNA expressions of CD86 and iNOS in cardiac tissue, and increased the ratio of F4/80~+CD206~+ M2 cells and the mRNA expressions of CD206 and Arg-1. VA also reduced protein expressions of p-Drp1, VDAC, NLRP3, ASC, caspase-1, cleaved-caspase-1, GSDMD, GSDMD-N, IL-1β, IL-18, Bad, Bax, Apaf-1, cleaved-caspase-3, cleaved-caspase-9, cleaved-PARP-1, and cytoplasmic cytochrome C, and increased the expressions of HK1, Bcl-2, Bcl-xl, pro-caspase-3, pro-caspase-9 proteins, as well as the Bcl-2/Bax and Bcl-xl/Bad ratios and mitochondrial cytochrome C content. These results indicate that VA has a significant ameliorative effect on ISO-induced CF in mice, alleviates ISO-induced oxidative damage and inflammatory response, and its mechanism may be closely related to the inhibition of Drp1/HK1/NLRP3 and mitochondrial apoptosis signaling pathways, suppression of myocardial cell inflammatory infiltration and collagen fiber deposition, reduction of collagen volume fraction and CollⅠ, Coll Ⅲ, and α-SMA expressions, thus mitigating CF.
Animals ; Isoproterenol/adverse effects* ; Male ; Mice ; Signal Transduction/drug effects* ; Vanillic Acid/administration & dosage* ; Dynamins/genetics* ; Mice, Inbred C57BL ; Fibrosis/genetics* ; Apoptosis/drug effects* ; Mitochondria/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Myocardium/metabolism* ; Humans

Objective： To analyze the symptoms, diagnosis and treatment of upper urinary tract calculi patients combined with mild and moderate benign prostatic hyperplasia (BPH) after ureteral stent implantation. Methods： One hundred and six BPH patients who were hospitalized for upper urinary tract calculi and had ureteral stents retained from January 2019 to December 2022 were selected and divided into 2 weeks group and 4 weeks group according to the time of removal of ureteral stents after surgery. Their general clinical data were analyzed and compared. International Prostatic Symptom Scale (IPSS), postoperative ureteral Stent Symptom Questionnaire (USSQ), and incidence of adverse events after ureteral stent removal were recorded before and after removal. Results： The scores of IPSS were significantly increased in all patients, and symptoms in urinary tract had improved significantly after discharge (P<0.05). Compared with the 2 weeks group, the USSQ score of the 4 weeks group was significantly increased (P<0.05). And no significant adverse event was observed in the 2 weeks group after the removal of ureteral sten. Conclusion： IPSS score and USSQ score increased significantly during stent implantation in BPH patients with lithiasis. And complications increased significantly over time. Following thorough clinical assessment, early ureteral stent removal demonstrates both safety and efficacy, representing an optimal therapeutic approach in selected cases.
Humans ; Male ; Prostatic Hyperplasia/surgery* ; Stents ; Ureter/surgery* ; Aged ; Middle Aged ; Urinary Calculi/surgery* ; Ureteral Calculi/surgery*

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

Objective To construct a diagnostic and prognostic model for malignant pleural effusion (MPE) in patients with non-M1b stage (AJCC 7th edition) non-small cell lung cancer (NSCLC) by machine learning. Methods Retrospective analysis was conducted on patients diagnosed with NSCLC in the Surveillance, Epidemiology, and End Results database from 2010 to 2015, excluding those in the M1b stage. Two sets of data were collected: data 1 (patients with non-M1b stage NSCLC, n=47 392) was used to construct the MPE diagnostic model; and data 2 (patients with M1a stage NSCLC and MPE, n=2 422) was used to construct a prognostic model. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen feature variables, with a training set and validation set ratio of 7:3. Models were built using eight machine learning algorithms, with evaluation metrics including accuracy, precision, recall, F1 score, area under the ROC curve (AUC), decision curve, calibration curve, and precision recall curve (PR), with ROC-AUC as the main evaluation metric. Results The incidence of MPE in patients with non-M1b stage NSCLC was 5.12%, and the 1-year survival rate of patients with MPE was 32.5%. LASSO regression identified nine diagnostic-related variables and 12 prognostic-related variables. The AUC values of the models constructed by eight machine learning algorithms all exceeded 0.70. The random forest model performed the best in the diagnostic model (training set AUC=0.908, validation set AUC=0.897), and the XGBoost model showed the best performance in the prognostic model (training set AUC=0.905, validation set AUC=0.875). Other evaluation indicators showed good results and balanced distribution. SHAP feature importance analysis showed that tumor size, lymph node metastasis, and histological type were important influencing factors for the occurrence of MPE, and chemotherapy intervention was the most remarkably prognostic factor. Conclusion The random forest diagnostic model constructed in this study can effectively predict the risk of MPE in patients with non-M1b stage NSCLC, and the XGBoost prognostic model can predict the prognosis of M1a-stage NSCLC patients with concurrent MPE.

The statements of sneeze-inducing nasal application therapy recorded in the ancient traditional Chinese medicine(TCM)books were sorted out and analyzed.The sneeze-inducing nasal application therapy is one of the external treatment methods of TCM.The therapy can heal the disease through dredging orifices and inducing sneeze with Chinese medicine acting on the nasal cavity.The therapeutic TCM mechanism of sneeze-inducing nasal application therapy is related with the nose which is one of the channels for expelling the pathogenic qi,and the sneeze-inducing mechanism of the therapy is similar to emetic method,and both of them have the actions of unblocking the stagnation,driving out pathogens,elevating qi,and releasing muscles.In the ancient TCM books,the sneeze-inducing nasal application therapy is most commonly used for the treatment of acute diseases such as trismus,unconsciousness,stroke and sudden death.Secondly,the therapy is indicated for the medical diseases,the diseases of obstetrics and gynecology,pediatrics,ophthalmology,and rhinolaryngology,and infectious diseases such as headache,jaundice,uterus-prolapse parturition(i.e.,prolapse or uterus during childbirth),fetal transfer(i.e.,malposition of fetus),infantile convulsion,nasosinusitis,ocular pannus,and plague.Commonly-used drugs for neeze-inducing nasal application therapy include Gleditsiae Fructus,Phaseoli Semen,Centipedae Herba,Pedicellus Melo,Pinelliae Rhizoma,Asari Radix et Rhizoma,Moschus,Piperis Longi Fructus,Veratri Nigri Radix et Rhizoma,Ricini Semen,Chuanxiong Rhizoma,and Raphani Semen.The investigation on the statements of sneeze-inducing nasal application therapy recorded in the ancient TCM books will provide reference for the modern clinical application of the therapy.

Objective To analyze the influencing factors of pancreatic fat deposition in patients with type 2 diabetes mellitus(T2DM),and to explore the relationship between pancreatic fat deposition and islet function.Methods A survey on diabetes prevalence was conducted among 548 residents in the Nicheng community of Pudong New Area from October 2015 to December 2016,including 301 patients with T2DM and 247 subjects with normal glucose tolerance(NGT).General information of the subjects were recorded,blood biochemical and insulin indexes were measured,body composition was measured by dual-energy X-ray absorptiometry,and insulin resistance index(HOMA-IR)and islet cell sensitivity index(HOMA-β)were calculated.Fatty liver and pancreatic fat deposition were detected by ultrasound.Both the T2DM group and NGT group were further divided into two subgroups according to the pancreatic fat deposition.Differences in general demographic information,biochemical and body fat indices among the groups were compared.Multivariate logistic regression was used to analyze the influencing factors of pancreatic fat deposition.Results In the NGT group,the subgroup with pancreatic fat deposition showed higher levels of age,waist circumference,waist-to-hip ratio(WHR),body mass index(BMI),fasting insulin levels(FINS),2-hour postprandial insulin levels(2 h INS),triglycerides(TG),uric acid(UA),alanine aminotransferase(ALT),fatty liver prevalence,abdominal fat percentage,and abdomen-to-hip ratio(AHR),compared with the subgroup without pancreatic fat deposition.High-density lipoprotein cholesterol(HDL-C)and limb fat percentage were lower in the subgroup with pancreatic fat deposition.In the T2DM group,the subgroup with pancreatic fat deposition showed higher levels of waist circumference,BMI,FINS,2 h INS,TG,UA,ALT,aspartate aminotransferase(AST),fatty liver prevalence,and abdominal fat percentage,compared with the subgroup without pancreatic fat deposition,with statistically significant differences(P<0.05).The HOMA-IR and HOMA-β in both NGT and T2DM groups with pancreatic fat deposition were significantly higher than those in the groups without pancreatic fat deposition.The prevalence of insulin resistance also significantly increased,with statistically significant differences(P<0.05).The results of multivariate logistic regression analysis showed that HDL-C,HOMA-β,abdominal fat percentage,age and fatty liver were the influencing factors for pancreatic fat deposition in NGT.Conclusion Elderly individuals with abdominal obesity and fatty liver are more prone to developing pancreatic fat deposition,which can affect islet function and aggravate the insulin resistance.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective:To investigate the effects of selinexor,a inhibitor of nuclear export protein 1(XPO1)on the proliferation inhibition and apoptosis of Kasumi-1 cells in acute myeloid leukemia(AML).Methods:MTS method was used to detect the inhibitory effect of different concentrations of selinexor on the proliferation of Kasumi-1 cells at different time points.The apoptosis rate and cell cycle changes after treatment with different concentration of selinexor were detected by flow cytometry.Results:Selinexor inhibited the growth of Kasumi-1 cells at different time points in a concentration-dependent manner(r24 h=0.7592,r48 h=0.9456,and r72 h=0.9425).Selinexor inhibited Kasumi-1 cells growth in a time-dependent manner(r=0.9057 in 2.5 μmol/L group,r=0.9897 in 5 μmol/L group and r=0.9994 in 10 μmol/L group).Selinexor could induce apoptosis of Kasumi-1 cells in a dose-dependent manner(r=0.9732),and the apoptosis of Kasumi-1 cells was more obvious with the increase of drug concentration.The proportion of G0/G1 phase was significantly increased and the proportion of S phase was significantly decreased after the treatment of Kasumi-1 cells by selinexor.With the increase of drug concentration,the proportion of Kasumi-1 cells cycle arrest in G0/G1 phase was increased and the cell synthesis was decreased.Conclusion:Selinexor can promote the death of tumor cells by inhibiting Kasumi-1 cells proliferation,inducing apoptosis and blocking cell cycle.