OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Objective To analyze the characteristics of postoperative hospital-acquired infections and drug sensitivity in lung transplant recipients over the past 5 years in a single center. Methods A total of 724 lung transplant recipients at Wuxi People's Hospital from January 2019 to December 2023 were selected. Based on the principles of hospital-acquired infection diagnosis, a retrospective analysis was conducted on the hospital infection situation and infection sites of lung transplant recipients, and an analysis of the distribution of hospital-acquired infection pathogens and their antimicrobial susceptibility test status was performed. Results Among the 724 lung transplant recipients, 275 cases of hospital-acquired infection occurred, with an infection rate of 38.0%. The case-time infection rate decreased from 54.2% in 2019 to 22.8% in 2023, showing a downward trend year by year (Z=30.98, P<0.001). The main infection site was the lower respiratory tract, accounting for 73.6%. The pathogens were mainly Gram-negative bacteria, with the top four being Acinetobacter baumannii (37.1%), Pseudomonas aeruginosa (17.3%), Klebsiella pneumoniae (13.7%), and Stenotrophomonas maltophilia (13.4%), with imipenem resistance rates of 89%, 53%, 58% and 100%, respectively. Gram-positive bacteria were mainly Staphylococcus aureus (3.6%), with a methicillin resistance rate of 67%. Conclusions Over the past 5 years, the hospital-acquired infections in lung transplant recipients have shown a downward trend, mainly involving lower respiratory tract infections, with the main pathogens being Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae, all of which have high resistance rates to imipenem.

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 report a case of hepatitis B virus （HBV） reactivation induced by iparomlimab and tuvonralimab， summarize the clinical characteristics and potential mechanisms of such adverse reactions induced by immune-checkpoint inhibitors （ICIs）， and provide references for clinical application. METHODS From the perspective of a clinical pharmacist， a retrospective analysis was conducted on the treatment course of a patient with metastatic cervical cancer who experienced HBV reactivation after receiving iparomlimab and tuvonralimab. Additionally， an analysis of the correlation with adverse reactions was performed， and the clinical characteristics， risk factors， potential mechanisms， key points of treatment approaches and pharmaceutical care associated with HBV reactivation induced by ICIs were summarized. RESULTS & CONCLUSIONS The patient developed HBV reactivation and severe liver injury after using iparomlimab and tuvonralimab. The condition improved following drug discontinuation， and symptomatic treatment such as glucocorticoids. According to Naranjo’s Assessment Scale and China’s Measures for the Reporting and Monitoring of Adverse Drug Reactions， the association between iparomlimab and tuvonralimab and HBV reactivation was judged as “highly probable”， and it was identified as a new adverse reaction； the correlation between iparomlimab and tuvonralimab， paclitaxel and liver injury was “highly probable”. HBV reactivation in hepatitis B patients receiving standardized antiviral therapy is very rare after ICIs treatment； HBV reactivation is related to the overactivation of the immune system and disruption of immune balance induced by ICIs. For such patients， glucocorticoids should be administered for treatment， accompanied by pharmaceutical care， including pre- medication risk assessment and monitoring of relevant indicators during treatment.

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

OBJECTIVES: To investigate the neuroprotective effects of electroacupuncture (EA) preconditioning against cerebral ischemia-reperfusion injury (CIRI) mediated by gut microbiota modulation, Nrf2/HO-1 pathway activation, and ferroptosis suppression. METHODS: Adult male SD rats were divided into sham operation group, CIRI model group, and EA preconditioning group. In the latter two groups, rat models of CIRI were established by middle cerebral artery occlusion (MCAO), and in EA preconditioning group, EA was applied at Baihui (DU20) and Zusanli (ST36) for 3 days before modeling. Neurological deficits, cerebral infarction, and hippocampal pathology of the rats were evaluated using behavioral tests, TTC staining, and Nissl and HE staining, and the oxidative stress markers (MDA, ROS, and SOD), apoptosis/ferroptosis-related proteins (Bax, Bcl-2, GPX4, and SLC7A11), and changes in gut microbiota were analyzed. RESULTS: EA preconditioning significantly reduced neurological deficits, decreased infarct volume, promoted hippocampal neuronal survival, and improved structural integrity of the hippocampal neurons in MCAO rats. EA preconditioning also significantly lowered MDA and ROS and increased SOD levels, upregulated Bcl-2, GPX4, and SLC7A11 expressions, and downregulated Bax expression in the hippocampal tissue of the rats, causing also activation of Nrf2/HO-1 signaling and improvement of gut microbiota composition. CONCLUSIONS EA preconditioning alleviates CIRI in rats by suppressing ferroptosis and apoptosis, enhancing antioxidant defenses via activating Nrf2/HO-1 signaling, and regulating the gut-brain axis.
Animals ; Electroacupuncture ; NF-E2-Related Factor 2/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction ; Reperfusion Injury/therapy* ; Ferroptosis ; Male ; Rats ; Brain Ischemia ; Gastrointestinal Microbiome ; Heme Oxygenase (Decyclizing)/metabolism* ; Brain/metabolism* ; Oxidative Stress ; Heme Oxygenase-1/metabolism* ; Apoptosis

Objective To explore the risk factors for healthcare-associated infection(HAI)in lung transplant re-cipients(LTRs),and construct a predictive nomogram model.Methods Clinical data of patients who underwent lung transplant in Wuxi People's Hospital from January 2019 to December 2023 were analyzed retrospectively.The patients were divided into a training set(n=506)and a validation set(n=218).Independent risk factors were screened through LASSO regression,and multivariate logistic regression was included to construct a nomogram pre-diction model.The discrimination,calibration,and clinical applicability of the model were evaluated using receiver operating characteristic(ROC)curves,Hosmer-Lemeshow goodness-of-fit,and decision curves.Results Among the 506 LTRs,201 developed HAIs,with an incidence of 39.72％.The major infection site was lower respiratory tract,and the major pathogen were Gram-negative bacilli(Acinetobacter baumannii).Older age,use of extracorpo-real membrane oxygenation(ECMO),double-lung transplant,surgery duration＞3 hours,long duration of contin-uous fever,frequent abnormal blood routine examination,and long duration of combined use of antimicrobial agents were identified as independent risk factors for HAI after lung transplant.The ROC curve analysis results showed that the areas under the curve(AUCs)of the training set and the validation set were 0.74(95％CI:0.70-0.78)and 0.71(95％CI:0.64-0.78),respectively.The Hosmer-Lemeshow test results showed that there was no sta-tistically significant difference between the predictive and actual probability of HAI(P＞0.05).The clinical decision curve results indicated that the model had clinical benefits at a threshold probability value of 7％-71％.Conclusion The nomogram prediction model constructed in this study can effectively evaluate the risk of postoperative infection in LTRs.The model is stable and has high clinical application value,providing scientific reference for postoperative infection prevention and control.

Objective To investigate the clinical application of ceftazidime/avibactam(CAZ/AVI)in lung trans-plant recipients with pulmonary infection caused by carbapenem-resistant Gram-negative bacilli(CRGNB),and ana-lyze the factors affecting the prognosis.Methods Lung transplant recipients who had CRGNB pulmonary infection and were treated with CAZ/AVI were included in the analysis.Based on 14-day clinical response,14-day microbial response,and 30-day survival status,the recipients were divided into a clinical response group and a clinical failure group,a microbial response group and a microbial failure group,as well as a survival group and a death group,re-spectively.Univariate analysis was conducted on various data from the two groups.Factors affecting therapeutic ef-ficacy and survival were included in a binary logistic regression model.Independent risk factors for CAZ/AVI anti-infective efficacy and all-cause mortality outcomes were analyzed.Results A total of 43 recipients were included.After 14-day anti-infective treatment,32 recipients(74.42％)achieved clinical response,and 30 recipients(69.77％)achieved microbial response.34 recipients(79.07％)survived 30 days after CAZ/AVI treatment.The Charlson comorbidity index(CCI),proportion of renal dysfunction,and incidence of shock in recipients in the clini-cal response group were all lower than those in the clinical failure group(P＜0.05),while the serum albumin(ALB)level was higher(P＜0.05).The incidence of shock in recipients in the microbial response group was lower than that in the microbial failure group(P＜0.05).CCI,proportion of renal dysfunction,and incidence of shock in recipients in the survival group were all lower than those in the death group(all P＜0.05),while ALB level was higher during treatment period(P＜0.05).Multivariate analysis of 14-day clinical response and 30-day survival showed that higher CCI was an independent risk factor affecting 14-day clinical response of recipients(OR=2.22,95％CI:1.07-4.63),while lower ALB levels(OR=0.72,95％CI:0.54-0.98)and higher CCI(OR=5.27,95％CI:1.18-23.58)were independent risk factors for 30-day all-cause mortality in recipients with pulmonary in-fection after lung transplant.Conclusion CAZ/AVI may be an effective drug for treating pulmonary infection caused by CRGNB in lung transplant recipients.Higher CCI is an independent risk factor for 14-day clinical failure in recipients after CAZ/AVI treatment.Lower ALB level and higher CCI are independent risk factors for increased 30-day mortality in recipients.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.

Objective To investigate the patterns of syndrome changes and their possible material basis in mouse models of chronic psychological stress during the modeling process.Methods A chronic unpredictable mild stress(CUMS)method was employed to prepare a model of chronic psychological stress in mice.After 2 weeks of modeling,Xiaoyao powder(XYS group)and Sini powder(SNS group)were administered concurrently with the modeling process.General conditions,behavioral,and biochemical indicators were compared between the modeling mice(M4 and M6 group)and the mice treated for 2 weeks(S4 and X4 group)and 4 weeks(S6 and X6 group)after chronic psychological stress.Results Compared with M4 group mice,body mass,total distance and central distance in the open field test,serum NE concentration,and gastric Ghrelin expression were increased in S4 group and X4 group mice,and sugar water preference rate and serum D-xylose concentration were increased in S4 group mice.Compared with X4 group mice,total distance in the open field test and serum D-xylose concentration were increased in the S4 group mice.Compared with M6 group mice,body mass,serum NE concentration,serum D-xylose concentration,and gastric Ghrelin expression were increased in group S6 and X6 group mice;sugar water preference rate,total distance in the open field test,and active avoidance counts in the shuttle box test were increased in X6 group mice,while their serum CORT concentration was decreased.Compared with S6 group mice,body mass,total distance in the open field test,serum D-xylose concentration,and gastric Ghrelin expression in X6 group mice were increased.Conclusions During the process of modeling chronic psychological stress in mice,the traditional Chinese medicine syndrome evolved from liver qi stagnation to liver qi stagnation with spleen deficiency.The biological bases of the syndrome changes may be the combined changes in serum CORT and NE concentrations and the decrease in gastric Ghrelin levels.