Objective To explore the safety and effects of alpha-lipoic acid (ALA) in patients with ischemic heart failure (IHF). Methods A randomized, double-blind, placebo-controlled trial was designed (ClinicalTrial.gov registration number NCT03491969). From January 2019 to January 2023, 300 patients with IHF were enrolled in four medical centers in China, and were randomly assigned at a 1∶1 ratio to receive ALA (600 mg daily) or placebo on top of standard care for 24 months. The primary outcome was the composite outcome of hospitalization for heart failure (HF) or all-cause mortality events. The second outcome included non-fatal myocardial infarction (MI), non-fatal stroke, changes of left ventricular ejection fraction (LVEF) and 6-minute walking distance (6MWD) from baseline to 24 months after randomization. Results Finally, 138 patients of the ALA group and 139 patients of the placebo group attained the primary outcome. Hospitalization for HF or all-cause mortality events occurred in 32 patients (23.2%) of the ALA group and in 40 patients (28.8%) of the placebo group (HR＝0.753, 95%CI 0.473-1.198, P＝0.231; Figure 1A-1C). The absolute risk reduction (ARR) was 5.6%, the relative risk reduction (RRR) associated with ALA therapy was approximately 19.4% compared to placebo, corresponding to a number needed to treat (NNT) of 18 patients to prevent one event. In the secondary outcome analysis, the composite outcome of the major adverse cardiovascular events (MACE) including the hospitalization for HF, all-cause mortality events, non-fatal MI or non-fatal stroke occurred in 35 patients (25.4%) in the ALA group and 47 patients (33.8%) in the placebo group (HR＝0.685, 95%CI 0.442-1.062, P＝0.091; Figure 1D). Moreover, greater improvement in LVEF (β＝3.20, 95%CI 1.14-5.23, P＝0.002) and 6MWD (β＝31.7, 95%CI 8.3-54.7, P＝0.008) from baseline to 24 months after randomization were observed in the ALA group as compared to the placebo group. There were no differences in adverse events between the study groups. Conclusions These results show potential long-term beneficial effects of adding ALA to IHF patients. ALA could significantly improve LVEF and 6MWD compared to the placebo group in IHF patients.

Liver transplantation (LT) has become a standard treatment for end-stage liver diseases, and graft injury is intricately associated with poor prognosis. Granzyme B (GZMB) plays a vital role in natural killer (NK) cell biology, but whether NK-derived GZMB affects graft injury remains elusive. Through the analysis of single-cell RNA-sequencing data obtained from human LT grafts and the isolation of lymphocytes from mouse livers following ischemia-reperfusion injury (IRI), we demonstrated that 2NK cells with high expression of GZMB are enriched in patients and mice. Both systemically and liver-targeted depletion of NK cells led to a notable reduction in GZMB⁺ cell infiltration, subsequently resulting in diminished graft injury. Notably, the reconstitution of Il2rg ^-/- Rag2 ^-/- mice with purified Gzmb-KO NK cells demonstrated superior outcomes compared to those with wild-type NK cells. Crucially, global knockout of GZMB and pharmacological inhibition exhibited remarkable improvements in liver function in both mouse IRI and rat LT models. Moreover, a phosphorylated derivative of FDA-approved vidarabine was identified as an effective inhibitor of mouse GZMB activity by molecular dynamics, which could provide a potential avenue for therapeutic intervention. Therefore, targeting NK cell-derived GZMB during the LT process suggests potential therapeutic strategies to improve post-transplant outcomes.

Objective To explore the molecular mechanism by which SOS Ras/Rac guanine nucleotide exchange factor 1-intronic transcript 1(SOS1-IT1)affects enhancer of zeste homolog 2(EZH2)protein expression in endometrial cancer cells Ishikawa and RL95-2.Methods Lentiviral transfection of short hairpin RNA(shRNA)and overexpression plasmid were used in Ishikawa and RL95-2 cell lines to knock down and overexpress SOS1-IT1.The mechanism of EZH2 expression regulation was studied using Real-time PCR,Western blotting,and chromatin immunoprecipitation.Results The expression of SOS1-IT1 and EZH2 genes was positively correlated in endometrial cancer tissues.Knocking down SOS1-IT1 significantly reduces the expression of EZH2,inhibited the proliferation and migration of Ishikawa and RL95-2 cells,and could reduced the acetylation of histone H3 at position 27(H3K27)and the enrichment of CREB binding protein(CBP)in the EZH2 gene promoter region.Overexpression of SOS1-IT1 could increased the expression of EZH2 and enhance the acetylation of H3K27 and the enrichment of CBP.CBP could bind to SOS1-IT1 RNA,and this binding ability was weakened when CBP was knocked down.Conclusion SOS1-IT1 can promote the expression level of EZH2 in endometrial cancer cells Ishikawa and RL95-2 by regulating the acetylation modification level of the EZH2 gene promoter region,thereby affecting the proliferation and migration ability of endometrial cancer cells.

[Objective] To analyse and predict the tendencies of using erythrocyte blood in Changsha based on the autoregressive integrated moving average (ARIMA) model, long short-term memory (LSTM) and ARIMA-LSTM combination model, so as to provide reliable basis for designing a feasible and effective blood inventory management strategy. [Methods] The data of erythrocyte usage from hospitals in Changsha between January 2012 and December 2023 were collected, and ARIMA model, LSTM model and ARIMA-LSTM combination model were established. The actual erythrocyte consumption from January to May 2024 were used to assess and verify the prediction effect of the models. The extrapolation prediction accuracy of the models were tested using two evaluation indicators: mean absolute percentage error (MAPE) and root mean square error (RMSE), and then the prediction performance of the model was compared. [Results] The RMSE of LSTM model, optimal model ARIMA(1,1,1)(1,1,1)12 and ARIMA-LSTM combination model were respectively 5 206.66, 3 096.43 and 2 745.75, and the MAPE were 18.78%,11.54% and 9.76% respectively, which indicated that the ARIMA-LSTM combination model was more accurate than the ARIMA model and LSTM model, and the prediction results was basically consistent with the actual situation. [Conclusion] The ARIMA-LSTM model can better predict the clinical erythrocyte consumption in Changsha in the short term.

Objective:To evaluate the efficacy and safety of percutaneous nephrolithotomy (PCNL) in the treatment of severe acute pancreatitis (SAP) with infected pancreatic necrosis (IPN).Methods:A retrospective analysis was conducted on the clinical data of 113 patients with SAP and IPN admitted to Qingdao Municipal Hospital between January 2018 and June 2023. The cohort included 66 males and 47 females, aged (46.2±13.6) years. Based on the treatment approach, patients were divided into two groups: those who underwent percutaneous catheter drainage (PCD) alone were assigned to the PCD group ( n=60), and those who received PCNL were assigned to the PCNL group ( n=53). Clinical parameters such as age, sex, number of debridement procedures, and postoperative complications were recorded. Results:Compared with the PCD group, the PCNL group had a higher CT severity index [8(6, 9) vs. 7(6, 8)], a greater proportion of patients with multiloculated abscesses [71.7%(38/53) vs. 41.7%(25/60)], and a higher percentage of patients with IPN involving >50% necrosis [56.6%(30/53) vs. 33.3%(20/60)]. These differences were statistically significant (all P<0.05). The PCNL group also showed a higher proportion of patients with post-treatment IPN necrosis involving <30% [91.4%(49/53) vs. 70.8%(42/60)], a lower rate of requiring step-up laparoscopic or open surgery [3.8%(2/53) vs. 10.0%(6/60)], fewer debridement sessions [2(1, 4) vs. 4(2, 6)], and a shorter total hospital stay [45(35, 58) d vs. 54(23, 72) d]. These differences were statistically significant (all P<0.05). Additionally, the PCNL group had lower rates of postoperative complications, including enteric fistula [3.8%(2/53) vs. 11.7%(7/60)], intra-abdominal bleeding [5.7%(3/53) vs. 13.3%(8/60)], and pancreatic fistula [15.1%(8/53) vs. 20.0% (12/60)]. These differences were also statistically significant (all P<0.05). The recurrence rate of abscesses was significantly lower in the PCNL group [11.3%(6/53) vs. 16.7%(10/60), χ2=4.14, P=0.042]. Conclusion:PCNL is an effective treatment for SAP complicated by IPN. Compared with PCD, it improves the clearance of necrotic tissue, reduces the number of debridement procedures, shortens the total hospital stay, and lowers the risk of postoperative complications.

Aim Mouse model of myocardial hypertro-phy was established via intraperitoneal injection of iso-proterenol(ISO)in mice.This approach allows for an in-depth investigation into the pharmacological effects and mechanisms of action of emodin,offering novel in-sights and directions for the improvement of myocardial hypertrophy.Methods The mice were randomly di-vided into the following groups:control group(CON),emodin group(EMO),MAPK activator control group(EMO+Ani),model group(ISO),treatment group(ISO+EMO),and activator intervention group(ISO+EMO+Ani).After treatment with emodin and inter-vention with MAPK activator,the heart weight ratio and cardiac size of each group were observed.Hematoxy-lin-eosin(HE)staining was used to observe the patho-logical changes in cardiac tissue,and kits were utilized to measure the levels of GSH,LDH,and MDA in the serum.Western blot was employed to detect the protein expression levels of inflammatory and oxidative factors,as well as p-p38,p-ERK,p38,and ERK in cardiac tis-sue.Results Emodin can significantly inhibit the production of myocardial inflammatory and oxidative factors induced by ISO,thereby effectively alleviating the degree of myocardial hypertrophy and fibrosis.Af-ter the p38/ERK signaling pathway was specifically ac-tivated by farnesol,the improvement effect of emodin on myocardial hypertrophy was weakened.Further comparison revealed that,compared with the myocardi-al hypertrophy pathological model group,the pathologi-cal protein expression levels in the farnesol-treated group showed no significant difference,and were even higher in some indicators.Conclusion Emodin can effectively inhibit the release of inflammatory factors and improve the state of oxidative stress by modulating the p38/ERK signaling pathway,thereby exerting an ameliorative effect on myocardial hypertrophy.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]

Allergic diseases,also known as hypersensitivity diseases,are a systemic disorder affecting nearly 40%of the global population.Although they vary in affected sites and clinical manifestations,they share many common features.For example,allergic diseases are the same type Ⅰ hypersensitivity reaction;the disease mechanism is based on the inability of the positive deficiency to resist the evil,and the allergens induce the onset of the disease;the course of the disease is similar to the patient's physique;the onset of the disease is closely related to the taiyin meridian of the hand and the foot;and the disease locations in traditional Chinese medicine can be categorized as the"orifices",so that the different diseases can be treated with the same treatment.Chinese medicine believes that spleen deficiency is the initiating factor of immune dysfunction,and lung deficiency is the key to the occurrence of allergic diseases,and regulating the lung and spleen is the key point of treatment for allergic diseases.The method of"cultivating the earth and generating gold"is good at adjusting the spleen and stomach and restoring the function of the lungs,which is the key to"same treatment for different diseases"of allergic diseases.Therefore,the purpose of this article is to explore the commonalities of allergic diseases and the role of the method of"cultivating the earth and generating gold"in the treatment of allergic diseases under the perspective of"same treatment for different diseases".

Allergic diseases,also known as hypersensitivity diseases,are a systemic disorder affecting nearly 40%of the global population.Although they vary in affected sites and clinical manifestations,they share many common features.For example,allergic diseases are the same type Ⅰ hypersensitivity reaction;the disease mechanism is based on the inability of the positive deficiency to resist the evil,and the allergens induce the onset of the disease;the course of the disease is similar to the patient's physique;the onset of the disease is closely related to the taiyin meridian of the hand and the foot;and the disease locations in traditional Chinese medicine can be categorized as the"orifices",so that the different diseases can be treated with the same treatment.Chinese medicine believes that spleen deficiency is the initiating factor of immune dysfunction,and lung deficiency is the key to the occurrence of allergic diseases,and regulating the lung and spleen is the key point of treatment for allergic diseases.The method of"cultivating the earth and generating gold"is good at adjusting the spleen and stomach and restoring the function of the lungs,which is the key to"same treatment for different diseases"of allergic diseases.Therefore,the purpose of this article is to explore the commonalities of allergic diseases and the role of the method of"cultivating the earth and generating gold"in the treatment of allergic diseases under the perspective of"same treatment for different diseases".

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]