The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

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 analyze the characteristics of adult anomalous aortic origin of coronary artery(AAOCA)and the causes of missed diagnosis by transthoracic echocardiography(TTE)so as to facilitate TTE in diagnosing adult AAOCA.Methods A total of 37 adult patients with AAOCA diagnosed by non-invasive coronary CT angiography(CCTA)and/or invasive coronary angiography(ICA)were selected as research samples at some hospital from January 2019 to December 2022,and their clinical symptoms and the findings of 12-lead electrocardiogram,cardiac enzymes and TTE were summarized;the patients were typed according to the site of origin of coronary artery anomalies,and the causes for the missed diagnosis of TTE were eplored.Chi-square test was used to compare the differences in TTE missed diagnoses.Results Of the 37 patients,31 ones had no or only mild symptoms;most ones had negative results in terms of 12-lead electrocardiography,cardiac enzymes,changes in the size of the cardiac chambers,segmental ventricular wall motion abnormalities and left ventricular systolic function.The patients with anomalous origin of the right coronary artery from left sinus(ARCA-L)gained the largest proportion of 59.45％(22/37);21 patients were diagnosed with anomalous origin of coronary artery arising from the opposite sinus(ACAOS)in the two examinations of TTE,of whom there were 19 cases of ARCA-L,and the detection rate of ACAOS by TTE was 87.5％;all the 13 patients origins in branches and high-grade openings were missed by TTE.The detection rate of ACAOS by TTE was significantly higher than that of coronary artery anomalies originating in branches and in high openings,and the difference was statistically significant(21/24 vs 0/13,P＜0.001).Conclusion Most adult AAOCA patients lack specificity in symptoms and related examination results.TTE has a high detection rate of ACAOS,while it is easy to miss the diagnosis of coronary artery anomalies originating from branches and high openings.Ultrasonographers have to identify false negative AAOCA by multi-section and multi-angle scanning and color Doppler flow imaging in order to reduce the rate of missed diagnosis.[Chinese Medical Equipment Journal,2024,45(1):71-75]

For the treatment of atrial fibrillation,Professor WU Wei innovatively put forward the theory of heart-blood-vessels trinity and the theory of stasis-toxin causing palpitation.It is believed that atrial fibrillation is caused by stasis and toxin,and affects the heart,blood and vessels.The core pathogenesis of atrial fibrillation is due to qi stagnation,blood stasis and toxin.The treatment for atrial fibrillation should be closely based on the pathogenesis,the therapeutic principles of treating from the perspective of stasis and together by removing toxin gradually is advocated.And the therapy of regulating qi,activating blood and removing stasis is also the way to remove toxin.The medication is based on the modified Taoren Honghua Decoction,which is mainly composed of Persicae Semen,Carthami Flos,Chuanxiong Rhizoma,Corydalis Rhizoma,Rehmanniae Radix,Paeoniae Radix Rubra,Salviae Miltiorrhizae Radix et Rhizoma,Jujubae Fructus,Puerariae Lobatae Radix,Nardostachyos Radix et Rhizoma,Ostreae Concha,Poria,and Polygonati Odorati Rhizoma.According to the characteristics of Lingnan climate and atrial fibrillation mostly being easy to affect the emotions,the pungent drugs in the prescription are usually removed,and the specific herbal pair of Puerariae Lobatae Radix-Nardostachyos Radix et Rhizoma is added to remove toxin according to the differentiation of disease.Moreover,for the treatment of atrial fibrillation,Professor WU Wei also adopts traditional Chinese medicine(TCM)external treatment such as foot bath,acupuncture and moxibustion,and physical-breathing exercise as well as health-care methods for comprehensive regulation,relieving the toxin and restoring the original qi.During the treatment atrial fibrillation,Professor WU Wei follows the principle of precise intervention and comprehensive regulation with Chinese medicine,so as to achieve the purpose of eliminating symptoms,restoring sinus rhythm and improving physical constitution.The thoughts of Professor WU Wei for the syndrome differentiation and treatment of atrial fibrillation will provide reference for the treatment of atrial fibrillation with TCM.

The pathogenesis of osteoarthritis (OA) is related to a variety of factors such as mechanical overload, metabolic dysfunction, aging, etc., and is a group of total joint diseases characterized by intra-articular chondrocyte apoptosis, cartilage fibrillations, synovial inflammation, and osteophyte formation. At present, the treatment methods for osteoarthritis include glucosamine, non-steroidal anti-inflammatory drugs, intra-articular injection of sodium hyaluronate, etc., which are difficult to take effect in a short period of time and require long-term treatment, so the patients struggle to adhere to doctor’s advice. Some methods can only provide temporary relief without chondrocyte protection, and some even increase the risk of cardiovascular disease and gastrointestinal disease. In the advanced stages of OA, patients often have to undergo joint replacement surgery due to pain and joint dysfunction. Mitochondrial dysfunction plays an important role in the development of OA. It is possible to improve mitochondrial biogenesis, quality control, autophagy balance, and oxidative stress levels, thereby exerting a protective effect on chondrocytes in OA. Therefore, compared to traditional treatments, improving mitochondrial function may be a potential treatment for OA. Here, we collected relevant literature on mitochondrial research in OA in recent years, summarized the potential pathogenic factors that affect the development of OA through mitochondrial pathways, and elaborated on relevant treatment methods, in order to provide new diagnostic and therapeutic ideas for the research field of osteoarthritis.

Objective To explore the efficiency of artificial intelligence and radiomics-assisted X-ray in diagnosis of lumbar osteoporotic vertebral compression fractures(OVCF).Methods The clinical data of 455 patients diagnosed as lumbar OVCF by MRI in our hospital were selected.The patients were divided into the training group(n=364)and the validation group(n=91),X-ray films were extracted,the image delineation,feature extraction and data analysis were carried out,and the artificial intelligence radiomics deep learning was applied to establish a diagnostic model for OVCF.After verifying the effectiveness of the model by receiver operating characteristic(ROC)curve,area under the curve(AUC),calibration curve,and decision curve analysis(DCA),the efficiencies of manual reading,model reading,and model-assisted manual reading of X-ray in the early diagnosis of OVCF were compared.Results The ROC curve,AUC and calibration curve proved that the model had good discrimination and calibration,and excellent diagnostic performance.DCA demonstrated that the model had a higher clinical net benefit.The diagnostic efficiency of the manual reading group:the accuracy rate was 0.89,the recall rate was 0.62.The diagnostic efficiency of the model reading group:the accuracy rate was 0.93,the recall rate was 0.86,the model diagnosis showed good predictive performance,which was significantly better than the manual reading group.The diagnostic efficiency of the model-assisted manual reading group:the accuracy rate was 0.92,the recall rate was 0.72,and the recall rate of the model-assisted manual reading group was higher than that of the manual reading group,but lower than that of the model reading group,indicating the superiority of the model diagnosis.Conclusion The diagnostic model established based on artificial intelligence and radiomics in this study has reached an ideal level of efficacy,with better diagnostic efficacy compared with manual reading,and can be used to assist X-ray in the early diagnosis of OVCF.

Objective To develop a clinical prediction model for predicting risk factors for prolonged hospital stay after anterior cervical discectomy and fusion(ACDF).Methods The clinical data of 914 patients underwent ACDF treatment for cervical spondylotic myelopathy(CSM)were retrospectively analyzed.According to the screening criteria,800 eligible patients were eventually included,and the patients were divided into the development cohort(n=560)and the validation cohort(n=240).LASSO regression was used to screen variables,and multivariate Logistic regression analysis was used to establish a prediction model.The prediction model was evaluated from three aspects:differentiation,calibration and clinical effectiveness.The performance of the model was evaluated by area under the curve(AUC)and Hosmer-Lemeshow test.Decision curve analysis(DCA)was used to evaluate the clinical effectiveness of the model.Results In this study,the five factors that were significantly associated with prolonged hospital stay were male,abnormal BMI,mild-to-moderate anemia,stage of surgery(morning,afternoon,evening),and alcohol consumption history.The AUC of the development cohort was 0.778(95%CI:0.740 to 0.816),with a cutoff value of 0.337,and that of the validation cohort was 0.748(95%CI:0.687 to 0.809),with a cutoff value of 0.169,indicating that the prediction model had good differentiation.At the same time,the Hosmer-Lemeshow test showed that the model had a good calibration degree,and the DCA proved that it was effective in clinical application.Conclusion The prediction model established in this study has excellent comprehensive performance,which can better predict the risk of prolonged hospital stay,and can guide clinical intervention as soon as possible,so as to minimize the postoperative hospital stay and reduce the cost of hospitalization.

Objective To explore the risk factors for surgical site infection(SSI)after transforaminal lumbar interbody fusion(TLIF)for the treatment of lumbar degenerative diseases.Methods A total of 1 000 patients who underwent TLIF for lumbar degenerative diseases in our hospital were included and divided into the infection group(n=23)and the non-infection group(n=977)according to whether the surgical incision was infected.General data,surgical and laboratory indicators of patients were collected,and potential risk factors of SSI were screened by univariate analysis and multivariate regression analysis,a nomogram model was established,and its predictive efficiency was validated by the receive operating characteristic(ROC)curve.Results The incidence of SSI in patients after TLIF was 2.3％.The results of univariate analysis showed that age,operative time,intraoperative blood loss,preoperative C-reactive protein(CRP),smoking,and diabetes mellitus were the significant risk factors for the occurrence of SSI.Multivariate regression analysis showed that older age,longer operation time,more intraoperative blood loss,smoking and diabetes mellitus were the independent risk factors for postoperative SSI.ROC curve showed that the nomogram model established in this study has good predictive efficiency.Conclusion Older age,longer operation time,more intraoperative blood loss,smoking,and diabetes mellitus were independent risk factors for postoperative SSI.For patients with these high risk factors,corresponding intervention measures should be taken before operation to reduce the incidence of SSI.

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS) was used to rapidly identify the chemical components in Dracocephalum moldavica, and UPLC was employed to determine the content of its main components. MS analysis was performed using an electrospray ionization(ESI) source and data were collected in the negative ion mode. By comparing the retention time and mass spectra of reference compounds, and using a self-built compound database and the PubChem database, 68 compounds were identified from D. moldavica, including 36 flavonoids, 22 phenylpropanoids, 4 phenols, and 6 other compounds. On this basis, a UPLC quantitative method was established to simultaneously determine 8 main components, i.e., luteolin-7-O-glucuronide, apigenin-7-O-glucuronide, rosmarinic acid, diosmetin-7-O-glucuronide, tilianin, acacetin-7-O-glucuronide, acacetin-7-O-(6″-O-malonyl)-glucoside, and acacetin. A Waters ACQUITY BEH C_(18) column(2.1 mm × 100 mm, 1.7 μm) was used, with acetonitrile and a water solution containing 0.1% formic acid and 0.1% phosphoric acid as the mobile phase for gradient elution. The detection wavelength was set at 330 nm, with a flow rate of 0.4 mL·min~(-1), and the column temperature was maintained at 35 ℃. The 8 components demonstrated good linearity(r≥0.999 9) over a wide mass concentration range(50 or 100 times). The average recovery rate ranged from 97.5% to 105.1%, and the relative standard deviations(RSDs) were 0.90% to 3.4%(n= 6), indicating that the method was simple, accurate, and reliable. In 17 batches of D. moldavica samples, the content of these 8 components ranged from 0.405 to 2.10, 0.063 to 0.342, 0.446 to 2.43, 0.415 to 1.47, 1.57 to 4.34, 0.173 to 0.386, 1.00 to 5.40, and 0.069 to 0.207 mg·g~(-1), respectively. These results indicate significant differences in the internal quality of the samples, highlighting the need for strict quality control to ensure their pharmacodynamic efficacy. This study provides a scientific basis for the rapid discovery of pharmacodynamic substances, comprehensive quality control, and the formulation or revision of quality standards for D. moldavica.
Tandem Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Lamiaceae/chemistry* ; Flavonoids/chemistry*

The AP2/ERF gene family is one of the largest transcription factor families in the plant kingdom, and plays an important role in response to biological and abiotic stresses, plant hormone responses, and plant growth and development. In this study, the AP2/ERF family of Panax notoginseng was identified by bioinformatics methods, and the physicochemical properties, structure, phylogenetic relationship, expression pattern and function of PnDREB4 gene of the family were analyzed. The results showed that 140 AP2/ERF family members were identified in P. notoginseng, which were divided into DREB, ERF, AP2, RAV and Sololit subgroups. The physicochemical properties and motifs of proteins were similar among the subgroups. There were 34 differentially expressed genes in the AP2/ERF family of Fusarium oxysporum infected P. notoginseng plants, and 19 genes were up-regulated. The expression level of PnDREB84 was up-regulated with the extension of Fusarium oxysporum infection time in the range of 0-96 h. The content of ABA and SA in P. notoginseng plants overexpressing PnDREB84 gene increased after 4 ℃ stress. The results showed that PnDREB84 gene plays a dual regulatory role in the process of biological stress and abiotic stress. PnDREB84 gene can be used as a potential molecular marker for the breeding of new varieties of P. notoginseng. The identification of AP2/ERF transcription factor and function analysis of PnDREB84 gene of P. notoginseng provided data support for the analysis of stress resistance mechanism of P. notoginseng and the breeding of new varieties.