Forsythia suspensa is a traditional Chinese medicine and a commonly used landscaping plant. Its dried fruit is used in medicine for its functions of clearing heat, removing toxins, reducing swelling, dissipating masses, and dispersing wind and heat. It possesses extremely high medicinal and economic value. However, the genetic differentiation and diversity of its wild populations remain unclear. In this study, chloroplast genome sequences were obtained from 15 wild individuals of F. suspensa using high-throughput sequencing technology. The sequence characteristics and intraspecific variations were analyzed. The results were as follows:(1) The full length of the F. suspensa chloroplast genome ranged from 156 184 to 156 479 bp, comprising a large single-copy region, a small single-copy region, and two inverted repeat regions. The chloroplast genome encoded a total of 132 genes, including 87 protein-coding genes, 37 tRNA genes, and 8 rRNA genes.(2) A total of 166-174 SSR loci, 792 SNV loci, and 63 InDel loci were identified in the F. suspensa chloroplast genome, indicating considerable genetic variation among individuals.(3) Population structure analysis revealed that F. suspensa could be divided into five or six groups. Both the population structure analysis and phylogenetic reconstruction results indicated significant genetic variation within the wild populations of F. suspensa, with no obvious correlation between intraspecific genetic differentiation and geographical distribution. This study provides new insights into the genetic diversity and differentiation within F. suspensa species and offers additional references for the conservation of species diversity and the utilization of germplasm resources in wild F. suspensa.
Genome, Chloroplast ; Forsythia/classification* ; Phylogeny ; Genetic Variation ; Chloroplasts/genetics* ; Microsatellite Repeats

Traditional Chinese medicine(TCM) is the pillar for the development of motherland medicine, and animal medicine has a long history of application in China, characterized by wide resources, strong activity, definite efficacy, and great benefits. It has significant potential and important status in the consumption market of raw materials of TCM. In the context of global climate change, farming system alterations, and low renewability, the depletion of wild medicinal animal resources has accelerated. Accordingly, the conservation and sustainable utilization of wild resources of animal medicinal materials has become a problem that garners increasing attention and urgently needs to be solved. This paper summarizes the current situation of domestic and foreign medicinal animal breeding and research progress in industrial application in recent years and points out the issues related to standardized breeding, germplasm selection and breeding, and quality evaluation standards for medicinal animals. Furthermore, this paper discusses standardized breeding, quality standards, resource protection and utilization, and the search for alternative resources for rare and endangered medicinal animals. It proposes that researchers should systematically carry out in-depth basic research on animal medicine, improve the breeding scale and level of medicinal animals, employ modern technology to enhance the quality standards of medicinal materials, and strengthen the research and development of alternative resources. This approach aims to effectively address the relationship between protection and utilization and make a significant contribution to the sustainable development of medicinal animal resources and the animal-based Chinese medicinal material industry.
Animals ; Breeding ; China ; Medicine, Chinese Traditional ; Conservation of Natural Resources

Objective:To systematically evaluate studies validating the performance of the Global Leadership Initiative on Malnutrition (GLIM) in diagnosing malnutrition.Methods:Seven Chinese and English databases including Embase, Web of Science (WOS), PubMed, CINAHL, Cochrane Library, SinoMed, CNKI, Wanfang Data, and VIP Database were searched for articles on the validation of GLIM criteria published between September 2018 and September 2024. Two researchers independently performed literature screening and data extraction. The concurrent and predictive validity of the criteria was analyzed.Results:A total of 136 papers were included for analysis. The GLIM criteria for diagnosing malnutrition had a sensitivity of 77%, a specificity of 87%, and an area under the curve (AUC) of 0.90. Malnutrition diagnosed by the GLIM criteria predicted prolonged hospital and intensive care unit (ICU) stays, increased readmission and complication rates (both overall and infectious), reduced survivals (median, overall, and disease-free), and increased in-hospital and follow-up mortalities. Both moderate and severe malnutrition predicted decreased overall survival. However, only three studies analyzed the impact of nutritional therapy on the clinical outcomes of malnourished patients.Conclusions:The GLIM criteria accurately differentiate malnutrition and are a valid predictive tool of clinical outcomes. However, the validity criteria in these validation studies were questionable, along with high methodological heterogeneity. Furthermore, there is a lack of studies validating the role of nutritional therapy in improving the clinical outcomes of malnourished patients.

This research aims to construct a stable epithelial cell senescence model for screening and e-valuation of senolytics.We explored the optimal conditions for doxorubicin-induced senescence of non-transformed epithelial cells MCF 10A,including the optimal induction concentration,the optimal inter-vention time,and the optimal senescence duration,and confirmed the feasibility of MCF 10A as an epi-thelial senescence model by multiple ways.The optimal condition for Doxorubicin-induced senescence of MCF 10A cells was treatment with 0.6 μmol/L Doxorubicin for 16 h to achieve the best senescence state on the 8th day.Under the optimal induction conditions,the positive rate of senescence-associated β-gal-actosidase(SA-β-gal)staining in the treated group reached 97％.At the same time,biochemical results of detecting the expression of mRNA,proteins,and immunofluorescence demonstrated that the expression levels of senescence-associated secretory phenotype(SASP),p16,p21 and p53 in the treated group were significantly higher than those in the control cells,and Lamin B1 was significantly decreased(P＜0.001),which were consistent with the specific characteristics of senescence.In summary,an epithelial senescence model was successfully induced in MCF 10A cells by Doxorubicin in this study,which will promote the screening of senolytics for senescent epithelial cells.

Objective:To develop and validate a clinical prediction model for assessing the risk of postoperative pulmonary complications (PPCs) in elderly patients undergoing surgery with general anesthesia.Methods:This prospective observational study enrolled patients aged ≥65 years who underwent general anesthesia with mechanical ventilation duration >3 hours across six tertiary hospitals between December 2022 and August 2023. Based on follow-up outcomes (until discharge or postoperative day 7), patients were categorized into a non-PPCs group and a PPCs group. Detailed records included baseline patient characteristics, preoperative comorbidities, surgical information (type, duration), and bedside lung ultrasound scores (LUS) assessed within 24 hours postoperatively using a standardized 12-zone protocol. Predictor selection was performed using LASSO regression. Significant predictors identified were incorporated into a multivariate logistic regression analysis to build the prediction model, visualized as a nomogram. Internal validation was conducted via bootstrap resampling (1 000 repetitions). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves for calibration accuracy, and decision curve analysis (DCA) for clinical utility.Results:A total of 130 eligible elderly surgical patients were included. PPCs occurred in 17 patients (incidence rate: 13.1%). Multivariate analysis identified LUS ( OR=1.248, 95% CI: 1.099-1.417, P=0.001) and elective surgery type ( OR=0.206, 95% CI: 0.043-0.988, P=0.048) as independent predictors of PPCs. The nomogram model demonstrated an AUC of 0.867 (95% CI: 0.775-0.959) upon initial testing. Internal validation confirmed good discrimination (AUC=0.863, 95% CI: 0.778-0.972). Calibration curves indicated excellent agreement between predicted probabilities and observed outcomes. Decision curve analysis demonstrated significant clinical net benefit across a wide range of threshold probabilities (0.03-0.89). Conclusions:The clinical prediction model, developed using early postoperative LUS scores and surgical type, effectively predicts the risk of postoperative pulmonary complications in elderly patients following surgery under general anesthesia. The model exhibits strong discrimination, calibration, and clinical utility, providing clinicians with a reliable tool for individualized risk assessment to support clinical decision-making and potentially reduce PPC incidence.

Objective:To systematically evaluate studies validating the performance of the Global Leadership Initiative on Malnutrition (GLIM) in diagnosing malnutrition.Methods:Seven Chinese and English databases including Embase, Web of Science (WOS), PubMed, CINAHL, Cochrane Library, SinoMed, CNKI, Wanfang Data, and VIP Database were searched for articles on the validation of GLIM criteria published between September 2018 and September 2024. Two researchers independently performed literature screening and data extraction. The concurrent and predictive validity of the criteria was analyzed.Results:A total of 136 papers were included for analysis. The GLIM criteria for diagnosing malnutrition had a sensitivity of 77%, a specificity of 87%, and an area under the curve (AUC) of 0.90. Malnutrition diagnosed by the GLIM criteria predicted prolonged hospital and intensive care unit (ICU) stays, increased readmission and complication rates (both overall and infectious), reduced survivals (median, overall, and disease-free), and increased in-hospital and follow-up mortalities. Both moderate and severe malnutrition predicted decreased overall survival. However, only three studies analyzed the impact of nutritional therapy on the clinical outcomes of malnourished patients.Conclusions:The GLIM criteria accurately differentiate malnutrition and are a valid predictive tool of clinical outcomes. However, the validity criteria in these validation studies were questionable, along with high methodological heterogeneity. Furthermore, there is a lack of studies validating the role of nutritional therapy in improving the clinical outcomes of malnourished patients.

This research aims to construct a stable epithelial cell senescence model for screening and e-valuation of senolytics.We explored the optimal conditions for doxorubicin-induced senescence of non-transformed epithelial cells MCF 10A,including the optimal induction concentration,the optimal inter-vention time,and the optimal senescence duration,and confirmed the feasibility of MCF 10A as an epi-thelial senescence model by multiple ways.The optimal condition for Doxorubicin-induced senescence of MCF 10A cells was treatment with 0.6 μmol/L Doxorubicin for 16 h to achieve the best senescence state on the 8th day.Under the optimal induction conditions,the positive rate of senescence-associated β-gal-actosidase(SA-β-gal)staining in the treated group reached 97％.At the same time,biochemical results of detecting the expression of mRNA,proteins,and immunofluorescence demonstrated that the expression levels of senescence-associated secretory phenotype(SASP),p16,p21 and p53 in the treated group were significantly higher than those in the control cells,and Lamin B1 was significantly decreased(P＜0.001),which were consistent with the specific characteristics of senescence.In summary,an epithelial senescence model was successfully induced in MCF 10A cells by Doxorubicin in this study,which will promote the screening of senolytics for senescent epithelial cells.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

ObjectiveSorafenib is a first-line only drug approved for the treatment of advanced hepatocellular carcinoma (HCC). Resistance to sorafenib means that treatment outcomes are often unsatisfactory. Although the mechanism underlying sorafenib resistance remains unclear, resistance may occur through Akt signaling pathway activation in HCC. Dihydrotanshinone (DHT), a lipophilic component of traditional Chinese medicine Salvia miltiorrhiza Bunge, has multiple anti-tumor activities and inhibits Akt activation. The effect and mechanism of DHT combined with sorafenib on HCC have not been investigated. In this study, we investigate whether DHT potentiates the anti-cancer activities of sorafenib against HCC. MethodsIn this study, the effects of sorafenib and DHT on the viability, apoptosis and drug sensitivity of Huh7 and HepG2 cells were verified by Cell Counting Kit-8 (CCK-8) and flow cytometry. Akt, P-Akt, Caspase3, GSK-3β, P-GSK-3β, ribosomal protein S6 kinase (S6K), P-S6K, Cyclin D1, Bcl-xl, Bcl-2, and Bax expression levels were analyzed via Western blot. All data were statistically compared using one-way analysis of variance (ANOVA) and Dunnett test. Statistical analysis using SPSS 20.0 statistical software. ResultsDHT inhibit proliferation and promote apoptosis in HCC cells by reducing Akt activation. DHT inhibits the expression and activation of Akt downstream factors, including GSK-3β and S6K, which regulate the apoptotic response and are activated and upregulated by sorafenib treatment. Both sorafenib and DHT downregulate cyclin D1 expression and DHT upregulates Bax expression and downregulates Bcl-2 and Bcl-xl expression. However, sorafenib had little influence on Bcl-2 family protein expression. ConclusionDHT may enhance the proliferation inhibition and apoptosis induction of sorafenib in HCC cells by inhibiting the activation of Akt signaling pathway, thus enhancing the anticancer effect of sorafenib.

Parkinson's disease (PD) is a chronic neurodegenerative disease. At present, levodopa and other drugs are mainly used for dopamine supplementation therapy. However, the absorption of levodopa in the gastrointestinal tract is unstable and its half-life is short, and long-term use of levodopa will lead to the end-of-dose deterioration, dyskinesia, the "ON-OFF" phenomenon and other symptoms. Therefore, new preparations need to be developed to improve drug efficacy, reduce side effects or improve compliance of patients. Based on the above clinical needs, this review briefly introduced the preparation modification strategies for the treatment of PD through case analysis, in order to provide references for the research and development of related preparations.