ObjectiveBased on the clinical characteristics of chronic gouty arthritis （CGA） in both traditional Chinese and western medicine， this study aims to systematically evaluate the clinical concordance of existing CGA animal models， providing recommendations for establishing animal models that align with the pathological characteristics of CGA and the manifestations of traditional Chinese medicine syndromes. MethodsBy comprehensively retrieving Chinese and international databases such as China National Knowledge Infrastructure， Wanfang， VIP Chinese Science and Technology Periodical Database （VIP）， and PubMed， all relevant literature on CGA animal models was collected. Based on the guidelines， the diagnostic criteria of both traditional Chinese and western medicine were summarized and organized. The evaluation indicators for the CGA model were constructed with reference to existing evaluation modes， and the CGA animal models were analyzed to systematically evaluate the clinical concordance of existing models. ResultsThe current methods used to construct CGA animal models mainly include monosodium urate crystal induction， high-protein diet induction （poultry lack urate oxidase）， and high-fat diet combined with urate oxidase inhibitors and joint injection. Based on 11 pieces of included literature， the traditional Chinese and western medicine scoring data of each model were extracted， and the average scoring values of all models were ultimately calculated. The results show that the average clinical concordances of existing CGA animal models in both traditional Chinese and western medicine are 43.33% and 64.44%， respectively. Among them， the model with the highest clinical concordance rate is the one with a high-fat diet combined with potassium oxonate to induce hyperuricemia plus joint injection， achieving 83.33% clinical concordance in western medicine and 60% in traditional Chinese medicine. This model aligns well with the pathogenic characteristics and pathological changes of clinical CGA. ConclusionAlthough current CGA animal models can simulate some pathological characteristics of CGA， they struggle to comprehensively reflect the complex pathological processes of CGA and the characteristics of traditional Chinese medicine syndromes. Therefore， in the future， it is necessary to establish the CGA animal models that incorporate the clinical disease and syndrome characteristics of traditional Chinese and western medicine and formulate the uniform model evaluation criteria， providing more precise tools for CGA mechanism research and the development of traditional Chinese medicine.

Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Jiuwei Xifeng Granules have become a Chinese patent medicine in the market. Because the formula contains Os Draconis, a top-level protected fossil of ancient organisms, the formula was to be improved by replacing Os Draconis with Ostreae Concha. To evaluate whether the improved formula has the same effectiveness and safety as the original formula, a randomized, double-blind, parallel-controlled, equivalence clinical trial was conducted. This study enrolled 288 tic disorder(TD) of children and assigned them into two groups in 1∶1. The treatment group and control group took the modified formula and original formula, respectively. The treatment lasted for 6 weeks, and follow-up visits were conducted at weeks 2, 4, and 6. The primary efficacy endpoint was the difference in Yale global tic severity scale(YGTSS)-total tic severity(TTS) score from baseline after 6 weeks of treatment. The results showed that after 6 weeks of treatment, the declines in YGTSS-TSS score showed no statistically significant difference between the two groups. The difference in YGTSS-TSS score(treatment group-control group) and the 95%CI of the full analysis set(FAS) were-0.17[-1.42, 1.08] and those of per-protocol set(PPS) were 0.29[-0.97, 1.56], which were within the equivalence boundary [-3, 3]. The equivalence test was therefore concluded. The two groups showed no significant differences in the secondary efficacy endpoints of effective rate for TD, total score and factor scores of YGTSS, clinical global impressions-severity(CGI-S) score, traditional Chinese medicine(TCM) response rate, or symptom disappearance rate, and thus a complete evidence chain with the primary outcome was formed. A total of 6 adverse reactions were reported, including 4(2.82%) cases in the treatment group and 2(1.41%) cases in the control group, which showed no statistically significant difference between the two groups. No serious suspected unexpected adverse reactions were reported, and no laboratory test results indicated serious clinically significant abnormalities. The results support the replacement of Os Draconis by Ostreae Concha in the original formula, and the efficacy and safety of the modified formula are consistent with those of the original formula.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Male ; Double-Blind Method ; Drugs, Chinese Herbal/therapeutic use* ; Tic Disorders/drug therapy* ; Treatment Outcome

This study aims to investigate the protective effects and mechanisms of polysaccharide extract PCP1 from Polygonatum cyrtonema in ameliorating cerebral ischemia-reperfusion(I/R) injury in rats through modulation of the Toll-like receptor 4(TLR4)/NOD-like receptor protein 3(NLRP3) signaling pathway. In vivo, SD rats were randomly divided into the sham group, model group, PCP1 group, nimodipine(NMDP) group, and TLR4 signaling inhibitor(TAK-242) group. A middle cerebral artery occlusion/reperfusion(MCAO/R) model was established, and neurological deficit scores and infarct size were evaluated 24 hours after reperfusion. Hematoxylin-eosin(HE) and Nissl staining were used to observe pathological changes in ischemic brain tissue. Transmission electron microscopy(TEM) assessed ultrastructural damage in cortical neurons. Enzyme-linked immunosorbent assay(ELISA) was used to measure the levels of interleukin-1β(IL-1β), interleukin-6(IL-6), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), interleukin-10(IL-10), and nitric oxide(NO) in serum. Immunofluorescence was used to analyze the expression of TLR4 and NLRP3 proteins. In vitro, a BV2 microglial cell oxygen-glucose deprivation/reperfusion(OGD/R) model was established, and cells were divided into the control, OGD/R, PCP1, TAK-242, and PCP1 + TLR4 activator lipopolysaccharide(LPS) groups. The CCK-8 assay evaluated BV2 cell viability, and ELISA determined NO release. Western blot was used to analyze the expression of TLR4, NLRP3, and downstream pathway-related proteins. The results indicated that, compared with the model group, PCP1 significantly reduced neurological deficit scores, infarct size, ischemic tissue pathology, cortical cell damage, and the levels of inflammatory factors IL-1β, IL-6, IL-18, TNF-α, and NO(P<0.01). It also elevated IL-10 levels(P<0.01) and decreased the expression of TLR4 and NLRP3 proteins(P<0.05, P<0.01). Moreover, in vitro results showed that, compared with the OGD/R group, PCP1 significantly improved BV2 cell viability(P<0.05, P<0.01), reduced cell NO levels induced by OGD/R(P<0.01), and inhibited the expression of TLR4-related inflammatory pathway proteins, including TLR4, myeloid differentiation factor 88(MyD88), tumor necrosis factor receptor-associated factor 6(TRAF6), phosphorylated nuclear factor-kappaB dimer RelA(p-p65)/nuclear factor-kappaB dimer RelA(p65), NLRP3, cleaved-caspase-1, apoptosis-associated speck-like protein(ASC), GSDMD-N, IL-1β, and IL-18(P<0.05, P<0.01). The protective effects of PCP1 were reversed by LPS stimulation. In conclusion, PCP1 ameliorates cerebral I/R injury by modulating the TLR4/NLRP3 signaling pathway, exerting anti-inflammatory and anti-pyroptotic effects.
Animals ; Toll-Like Receptor 4/genetics* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Rats, Sprague-Dawley ; Rats ; Reperfusion Injury/genetics* ; Male ; Signal Transduction/drug effects* ; Polysaccharides/isolation & purification* ; Polygonatum/chemistry* ; Brain Ischemia/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Humans

In the present study, a mouse model of coronary artery ligation was employed to evaluate the effects of Jiming Powder on mitophagy in the mouse model of myocardial infarction and elucidate its underlying mechanisms. A mouse model of myocardial infarction post heart failure was constructed by ligating the left anterior descending branch of the coronary artery. The therapeutic efficacy of Jiming Powder was assessed from multiple perspectives, including ultrasonographic imaging, hematoxylin-eosin(HE) staining, Masson staining, and serum cardiac enzyme profiling. Dihydroethidium(DHE) staining was employed to evaluate the oxidative stress levels in the hearts of mice from each group. Mitophagy levels were assessed by scanning electron microscopy and immunofluorescence co-localization. Western blot was employed to determine the levels of key proteins involved in mitophagy, including Bcl-2-interacting protein beclin 1(BECN1), sequestosome 1(SQSTM1), microtubule-associated protein 1 light chain 3 beta(LC3B), PTEN-induced putative kinase 1(PINK1), phospho-Parkinson disease protein(p-Parkin), and Parkinson disease protein(Parkin). The results demonstrated that compared with the model group, high and low doses of Jiming Powder significantly reduced the left ventricular internal diameter in systole(LVIDs) and left ventricular internal diameter in diastole(LVIDd) and markedly improved the left ventricular ejection fraction(LVEF) and left ventricular fractional shortening(LVFS), effectively improving the cardiac function in post-myocardial infarction mice. Jiming Powder effectively reduced the levels of myocardial injury markers such as creatine kinase(CK), creatine kinase isoenzyme(CK-MB), and lactate dehydrogenase(LDH), thereby protecting ischemic myocardium. HE staining revealed that Jiming Powder attenuated inflammatory cell infiltration after myocardial infarction. Masson staining indicated that Jiming Powder effectively inhibited ventricular remodeling. Western blot results showed that Jiming Powder activated the PINK1-Parkin pathway, up-regulated the protein level of BECN1, down-regulated the protein level of SQSTM1, and increased the LC3Ⅱ/LC3Ⅰ ratio to promote mitophagy. In conclusion, Jiming Powder exerts therapeutic effects on myocardial infarction by inhibiting ventricular remodeling. The findings pave the way for subsequent pharmacological studies on the active components of Jiming Powder.
Animals ; Myocardial Infarction/physiopathology* ; Mitophagy/drug effects* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Protein Kinases/genetics* ; Male ; Ubiquitin-Protein Ligases/genetics* ; Humans ; Disease Models, Animal ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

This study employed a mouse model of coronary artery ligation to assess the effect and mechanism of Jiming Powder on mitochondrial autophagy in mice with myocardial infarction. The mouse model of heart failure post-myocardial infarction was established by ligating the left anterior descending coronary artery. The pharmacological efficacy of Jiming Powder was evaluated through echocardiographic imaging, hematoxylin-eosin(HE) staining, and Masson staining. The levels of malondialdehyde(MDA), Fe~(2+), reduced glutathione(GSH), and superoxide dismutase(SOD) in heart tissues, as well as MDA immunofluorescence of heart tissues, were measured to assess lipid peroxidation and Fe~(2+) levels in the hearts of mice in different groups. Ferroptosis levels in the groups were evaluated using scanning electron microscopy and Prussian blue staining. Western blot analysis was conducted to detect the levels of key ferroptosis-related proteins, including nuclear factor erythroid 2-related factor 2(NRF2), ferritin heavy chain(FTH), glutathione peroxidase 4(GPX4), solute carrier family 7 member 11(SLC7A11), heme oxygenase 1(HO-1), and Kelch-like ECH-associated protein 1(KEAP1). The results showed that compared with the model group, both the high-and low-dose Jiming Powder groups exhibited significantly reduced left ventricular internal diameter in systole(LVIDs) and left ventricular internal diameter in diastole(LVIDd), while the left ventricular ejection fraction(EF) and left ventricular fractional shortening(FS) were significantly improved, effectively enhancing cardiac function in mice post-myocardial infarction. HE staining revealed that Jiming Powder attenuated myocardial inflammatory cell infiltration post-infarction, and Masson staining indicated that Jiming Powder effectively reduced fibrosis in the infarct margin area. Treatment with Jiming Powder reduced the levels of MDA and Fe~(2+), indicators of lipid peroxidation post-myocardial infarction, while increasing GSH and SOD levels, thus protecting ischemic myocardium. Western blot results demonstrated that Jiming Powder reduced KEAP1 protein accumulation, activated the NRF2/HO-1/GPX4 pathway, and up-regulated the protein expression of FTH and SLC7A11, exerting an inhibitory effect on ferroptosis. This study reveals that Jiming Powder exerts a therapeutic effect on myocardial infarction by inhibiting ferroptosis through the NRF2/HO-1/GPX4 pathway, providing a foundation for subsequent research on the pharmacological effects of Jiming Powder.
Animals ; Ferroptosis/drug effects* ; Myocardial Infarction/physiopathology* ; NF-E2-Related Factor 2/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Heme Oxygenase-1/genetics* ; Phospholipid Hydroperoxide Glutathione Peroxidase/genetics* ; Humans ; Mice, Inbred C57BL ; Signal Transduction/drug effects* ; Disease Models, Animal

The antidepressant activity and molecular mechanisms of Yueju Wan volatile oil were investigated. The Yueju Wan volatile oil was extracted by using supercritical CO_2. Gas chromatography-mass spectrometry(GC-MS) combined with network pharmacology identified 28 chemical constituents in Yueju Wan volatile oil, primarily terpenes and lactones. A total of 123 overlapping targets were associated with depression, including core targets of interleukin-1β(IL-1β), signal transducer and activator of transcription 3(STAT3), and caspase-3(CASP3). These targets were mainly involved in the prolactin, advanced glycation end products/receptor(AGE/RAGE), and phosphoinositide 3-kinase/protein kinase B(PI3K/Akt) signaling pathways. A reserpine-induced depression mouse model was established to evaluate the therapeutic effects and mechanisms of Yueju Wan volatile oil. The effects of Yueju Wan volatile oil on depression-like behavior in mice were evaluated by analyzing body mass, body temperature index, tail suspension immobility time, forced swimming immobility time, and sucrose preference. Hematoxylin-eosin(HE) staining revealed neuronal protection of Yueju Wan volatile oil in the brain of mice. Enzyme-linked immunosorbent assay(ELISA) and Western blot were employed to detect the protein expression of AGEs, IL-1β, phosphorylated PI3K(p-PI3K), Akt, phosphorylated Akt(p-Akt), nuclear factor κB(NF-κB), and brain-derived neurotrophic factor(BDNF). Behavioral evaluation showed that Yueju Wan volatile oil could effectively control the decline of body mass and body temperature of depressed mice, reduce tail suspension and swimming immobility time, and enhance their preference for sucrose. Histopathological examination showed that Yueju Wan volatile oil could alleviate the neuronal damage in CA1 and dentate gyrus(DG) of the hippocampus of mice. ELISA and Western blot results showed that Yueju Wan volatile oil could significantly increase the protein expression levels of PI3K, Akt, and BDNF and significantly decrease the protein expression levels of AGEs, IL-1β, p-PI3K, p-Akt, and NF-κB in the hippocampus of mice. Furthermore, the p-PI3K/PI3K and p-Akt/Akt ratios were significantly decreased at medium and high doses. These findings suggest that the aromatherapy of Yueju Wan volatile oil can significantly improve reserpine-induced depression-like behavior in mice, which may be related to reducing the expression of neuronal membrane protein AGEs, reducing the phosphorylation levels of PI3K and Akt, inhibiting NF-κB entry into the nucleus, and alleviating the release of pro-inflammatory factors and nerve injury.
Animals ; Antidepressive Agents/chemistry* ; Mice ; Proto-Oncogene Proteins c-akt/immunology* ; Phosphatidylinositol 3-Kinases/immunology* ; Oils, Volatile/chemistry* ; Male ; Drugs, Chinese Herbal/chemistry* ; Signal Transduction/drug effects* ; Depression/metabolism* ; Glycation End Products, Advanced/immunology* ; Humans

This study aims to explore the scientific connotation of sinking Rehmanniae Radix has the best quality and compare the quality between floating and sinking fresh Rehmanniae Radix samples. Ultra-performance liquid chromatography tandem quadrupole electrostatic field Orbitrap high-resolution mass spectrometry(UHPLC-Q-Orbitrap HRMS) was employed to detect the chemical components in floating and sinking fresh Rehmanniae Radix samples. The fingerprint of fresh Rehmanniae Radix was established by high performance liquid chromatography(HPLC), and four index components were determined simultaneously. The cluster analysis, principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) were conducted to compare the quality of floating and sinking fresh Rehmanniae Radix samples. An evaporative light-scattering detector was used to compare the content of five sugars. The extract yield and drying rate were determined, and the quality connotation of sinking Rehmanniae Radix has the best quality was explained by multiple indicators. A total of 41 components were preliminarily identified from fresh Rehmanniae Radix by UHPLC-Q-Orbitrap HRMS, including 7 iridoid glycosides, 9 phenylethanol glycosides, 6 amino acids, 4 sugars, 3 phenolic acids, 5 nucleosides, 3 organic acids, 1 ionone, 1 furan, 1 coumarin, and 1 phenylpropanoid. The results showed that the main chemical components were consistent between floating and sinking fresh Rehmanniae Radix. Nine common peaks were identified in the fingerprints of 15 batches of floating and sinking fresh Rehmanniae Radix samples, and the similarity of fingerprints was greater than 0.9. The cluster analysis, PCA, and OPLS-DA classified floating and sinking fresh Rehmanniae Radix sasmples into two categories, indicating differences in the quality between them. The total content of catalpol, rehmannioside D, ajugol, and verbascoside in sinking fresh Rehmanniae Radix samples was higher than that in floating samples of the same batch and specification, and the main differential component was catalpol. The total content of fructose, glucose, sucrose, raffinose, and stachyose in sinking fresh Rehmanniae Radix samples was higher than that in floating samples of the same batch and specification, and the main differential component was stachyose. The extract yield and drying rate of the sinking samples were higher than those of floating samples. This study preliminarily showed that floating and sinking fresh Rehmanniae Radix samples had the same components but great differences in the content of medicinal substance basis. The total content of four glycosides and five sugars, extract yield, and drying rate of sinking fresh Rehmanniae Radix samples is higher than that of floating samples of the same batch and specification. These findings, to a certain extent, explains the scientificity of sinking Rehmanniae Radix has the best quality recorded in ancient books and provide a reference for the quality control and clinical application of fresh Rehmanniae Radix.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Rehmannia/chemistry* ; Chemometrics ; Mass Spectrometry/methods* ; Quality Control ; Principal Component Analysis ; Plant Extracts