Prescription optimization is a crucial aspect in the study of traditional Chinese medicine （TCM） compounds. In recent years， the introduction of mathematical methods， data mining techniques， and artificial neural networks has provided new tools for elucidating the compatibility rules of TCM compounds. The study of TCM compounds involves numerous variables， including the proportions of different herbs， the specific extraction parts of each ingredient， and the interactions among multiple components. These factors together create a complex nonlinear dose-effect relationship. In this context， it is essential to identify methods that suit the characteristics of TCM compounds and can leverage their advantages for effective application in new drug development. This paper provided a comprehensive review of the cutting-edge optimization experimental design methods applied in recent studies of TCM compound compatibilities. The key technical issues， such as the optimization of source material selection， dosage optimization of compatible herbs， and multi-objective optimization indicators， were discussed. Furthermore， the evaluation methods for component effects were summarized during the optimization process， so as to provide scientific and practical foundations for innovative research in TCM and the development of new drugs based on TCM compounds.

Objective To investigate the predictive value of preoperative combined detection of neutrophil-to-lymphocyte ratio (NLR) and prothrombin time-international normalized ratio to albumin ratio (PTAR) for early abdominal infection after liver transplantation. Methods Clinical data of 287 recipients who underwent liver transplantation at the Liver Transplant Center of Beijing Friendship Hospital, Affiliated to Capital Medical University, from January 2020 to April 2024 were retrospectively analyzed. The patients were divided into infection group (n=60) and non-infection group (n=227) based on whether abdominal infection occurred within 30 days after surgery. The distribution characteristics of pathogens and infection time in infected patients were analyzed. Spearman correlation analysis was used to assess the correlation between NLR, PTAR, Child-Pugh score and preoperative model for end-stage liver disease (MELD) score. Univariate and multivariate logistic regression analyses were performed to identify risk factors for abdominal infection. Receiver operating characteristic (ROC) curves were plotted for NLR, PTAR, and the combined prediction model to evaluate their predictive efficacy for abdominal infection after liver transplantation. Based on the cutoff value of the combined model, recipients were divided into low-risk and high-risk groups, and Kaplan-Meier analysis was used to compare the cumulative incidence of abdominal infection within 30 days after surgery between the two groups. Results Among the 287 recipients who underwent liver transplantation, 60 developed bacterial or fungal abdominal infections postoperatively. A total of 86 strains were isolated from infected patients, with Gram-negative bacteria accounting for 58%, Gram-positive bacteria for 36%, and fungi for 5%. Preoperative NLR and PTAR were positively correlated with Child-Pugh and MELD scores (all 1 > r > 0, P < 0.05). Logistic regression analysis showed that preoperative NLR, preoperative PTAR, postoperative ICU stay duration and postoperative biliary leakage were risk factors for abdominal infection within 30 days after surgery. The area under the curve (AUC) for NLR, PTAR, Child-Pugh score and MELD score were 0.771, 0.735, 0.650 and 0.741, respectively. The AUC for the combined NLR and PTAR prediction model was 0.824 (95% confidence interval: 0.763-0.885, P < 0.001), with a cutoff value of 0.168. Kaplan-Meier analysis showed that the cumulative incidence of abdominal infection within 30 days after surgery was lower in the low-risk group than in the high-risk group, with statistically significant difference (P < 0.001). Conclusions Preoperative NLR and PTAR are independent risk factors for abdominal infection within 30 days after liver transplantation. The combined prediction model of NLR and PTAR may effectively identify high-risk recipients for early abdominal infection after liver transplantation, providing basis for early intervention.

Eag1(ether-à-go-go-1,also known as Kv10.1,KC-NH1)is a member of the KCNH gene family of voltage-gated potassiumion(K+)channels,which is mainly expressed in the central nervous system as well as in a variety of malignancies and plays an important role in tumor development.The study of the distribution and mechanism of action of Eag1 is of great impor-tance to reveal its physiological function and its association with pathological mechanisms.This paper reviews the current re-search progress on the physiological and pathological properties of Eag1,the relationship between Eag1 and tumor development and the anti-tumor application of Eag1 modulators.

In the process of seeking new strategies to improve the efficacy of antidepressants,traditional Chinese medicine inter-vention has gradually revealed its unique prevention and treat-ment advantages.The dopamine reward system is closely in-volved in the pathological occurrence and development of depres-sion.Currently,research has mostly focused on the functional mechanism of a specific nucleus in the dopamine reward system,and there is less research focused on the functional mechanism of the neural circuit.In the current micro research on reward cir-cuits,the association between abnormal reward circuits and neg-ative emotions such as anxiety and depression has been widely recognized.Traditional Chinese medicine intervention can exert antidepressant effects by influencing reward circuits.This article provides a review on the loop mechanism of dopamine reward system involvement in depression and research on traditional Chinese medicine intervention.

Aim To investigate the intracellular up-take and target protein binding characteristics of two Bruton's tyrosine kinase inhibitors(BTKi)with differ-ent selectivities to provide further insights into the mechanisms of drug off-target-related bleeding risk.Methods Ibrutinib(non-selective BTKi)and za-nubrutinib(selective BTKi)were used as study drugs.After incubation of MEC-1 cells and human platelets with drugs,the cellular thermal shift assay(CETSA)was combined with Western blot to obtain the melting curve and isothermal curve to analyze the binding char-acteristics of the two drugs with the target protein BTK.After incubation of MEC-1 cells and human platelets with drugs,the concentrations of the two drugs were detected by liquid chromatography-tandem mass spectrometry(LC-MS/MS)to analyze the intracellular uptake of the two drugs.Results CETSA analysis confirmed that zanubrutinib was more selective for the target protein BTK compared to ibrutinib.LC-MS/MS analysis showed that both drugs were uptaken intracel-lularly by MEC-1 cells and platelets in a concentration-dependent manner.Conclusions While BTKi targe-ting BTK to B lymphocytes exerts therapeutic effects,off-target effects on platelets due to differences in their intracellular uptake,and target-binding characteristics may be one of the reasons for the differences in bleed-ing risk across selective BTKi.

Objective:To explore effect of miR-125a-3p on skin injury and inflammatory response in psoriasis rats and its mechanism.Methods:SD rats were randomly divided into control group,psoriasis group,miR-NC group and miR-125a-3p group.Psoriasis Area and Severity Index(PASI)score and Baker score were measured on rats;levels of IL-6,IL-1β and TNF-α in rat skin tissue were detected by ELISA;qRT-PCR was used to detect miR-125a-3p expression;mRNA and protein expressions of forkhead box protein M1(FOXM1)in rat skin tissue were detected by qRT-PCR and Western blot.Keratinocytes from psoriasis rats were isolated and cultured,targeting relationship between miR-125a-3p and FOXM1 was verified by dual-luciferase reporter gene assay.Inhibiting or overexpressing miR-125a-3p and FOXM1 was overexpressed on basis of overexpressing miR-125a-3p,respectively.miR-125a-3p,FOXM1 mRNA and protein expressions in cells and IL-6,IL-1β,TNF-α levels in cell culture supernatants were detected,CCK-8 method was applied to detect cell viability,and flow cytometry was used to detect apoptosis rate.Results:Compared with control group,miR-125a-3p expression in skin tissue of rats in psoriasis group was decreased,PASI score,Baker score,IL-6,IL-1β,TNF-α levels,and FOXM1 mRNA and protein expressions were increased(P<0.05);compared with psoriasis group and miR-NC group,expression of miR-125a-3p in skin tissue of rats in miR-125a-3p group was increased,PASI score,Baker score,IL-6,IL-1β,TNF-α levels,and expressions of FOXM1 mRNA and protein were decreased(P<0.05).There was a targeting relationship between miR-125a-3p and FOXM1.After inhibiting miR-125a-3p expression,FOXM1 mRNA and protein expressions in cells,cell viability and IL-6,IL-1β,TNF-α levels in cell culture supernatant were increased,and apoptosis rate was decreased(P<0.05),while overexpression of miR-125a-3p had opposite effect.Overexpression of FOXM1 attenuated effects of overexpression of miR-125a-3p on cell viability,apopto-sis rate and inflammatory response.Conclusion:miR-125a-3p is lowly expressed in skin lesions of psoriasis rats,whose overexpression may inhibit proliferation of keratinocytes and promote apoptosis by targeting FOXM1,improve skin injury and reduce inflammatory response in psoriasis rats.

The distribution of Ixodes and Ana plasma carried by Ixodes ticks in Anhui Province was clarified as reference for prevention and control of anaplasmosis.In total,630 hard ticks were collected from Jinzhai County,Hanshan County,Jing-de County and Chaohu City in Anhui Province from April to August 2023.Ticks were identified by morphological analysis and 16S rRNA sequencing.Nested PCR with Anaplasma species-specific primers were used to detect 16S rRNA of Anaplasma spe-cies carried by ticks.A phylogenetic tree was constructed using MEGA11.0 software.Of the identified ticks,18.8％(18/96)were Rhipicephalus microplus and 81.2％(78/96)were Haemaphysalis longicorni in Jinzhai County of Anhui Province,all were H.longicorni in Hanshan County and Chaohu City,while the main species in Jingde County was R.microplus.The posi-tive rate of Anaplasma carried by H.longicornis was 30.9％(102/330),which included A.bovis at 1.8％(6/330),A.phagocytophilum at 21.8％(72/330)and uncultured Anaplasma species at 7.3％(24/330).R.microplus was positively cor-related to A.bovis(13.6％,18/132).The uncultured Anaplasma species was mainly detected in host-free ticks.A.phagocy-tophilum was detected in 24.4％of parasitic ticks and 15.8％of host-free ticks.The positive rates of host-free and parasitic ticks were 19.9％and 17.8％,respectively.These results show that H.longicornis and R.microplus were the dominant ticks in several counties of Anhui Province.H.longicornis and R.microplus as well as free and parasitic ticks all carried Anaplas-ma.

Objective:This study aims to analyze the clinical characteristics of elderly patients with lung adenocarcinoma and to construct a predictive model for assessing their survival.Methods:We conducted a retrospective analysis of clinical data sourced from the SEER database for patients aged 60 years or older who were diagnosed with lung adenocarcinoma between 2013 and 2018.Cox regression analysis was employed to identify independent prognostic factors affecting the survival of elderly lung adenocarcinoma patients, leading to the development of a nomogram model.The discriminative ability and calibration of the nomogram were assessed using the C-index and calibration curve.Each patient's total risk score was calculated based on the predictive model, and patients were stratified according to the quartiles of their total risk scores.The Kaplan-Meier method and Log-rank test were utilized to evaluate survival differences among the identified risk groups.Results:Among 38, 852 lung adenocarcinoma patients, 17, 200 were males and 21, 652 were females.Significant differences in survival rates were observed among lung adenocarcinoma patients based on age, gender, marital status, histological grade, TNM stage, tumor size, and the presence of bone, brain, or liver metastases, as well as the type of treatment received, including surgical treatment, radiation therapy, and chemotherapy(all P<0.001).The C-index of the training model was 0.815(95% CI: 0.811-0.819), while the validation model yielded a C-index of 0.810(95% CI: 0.804-0.816).The prediction model demonstrated higher Area Under Curve(AUC)values of 0.746, 0.768, and 0.775 for 1-year, 3-year, and 5-year survival in the modeling dataset, respectively, and 0.747, 0.770, and 0.777 in the validation dataset.Furthermore, the risk stratification model effectively distinguished patients at varying levels of risk( P<0.001). Conclusions:Age, gender, marital status, histological grade, TNM stage, tumor size, and the presence of bone, brain, and liver metastases, along with treatment modalities such as surgery, radiotherapy, and chemotherapy, were identified as independent prognostic factors for elderly patients with lung adenocarcinoma.The risk prediction model developed in this study effectively differentiates between patients at varying levels of risk, which holds significant implications for predicting treatment responses in elderly lung adenocarcinoma patients and advancing the practice of precision medicine.

For two young female patients with extramedullary recurrence of reproductive system after allogeneic hematopoietic stem cell transplantation for acute myeloid leukemia. And the characteristics of extramedullary relapse of reproductive system are summarized for exploring possible effective treatments.

China prospective multicenter birth cohort (Prospective Omics Health Atlas birth cohort, POHA birth cohort) study was officially launched in 2022. This study, in collaboration with 12 participating units, aims to establish a high-quality, multidimensional cohort comprising 20 000 naturally conceived families and assisted reproductive families. The study involves long-term follow-up of parents and offspring, with corresponding biological samples collected at key time points. Through multi-omics testing and analysis, the study aims to conduct multi-omics big data research across the entire maternal and infant life cycle. The goal is to identify new biomarkers for maternal and infant diseases and provide scientific evidence for risk prediction related to maternal diseases and neonatal health.