Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method.

ABSTRACT: Raw Moutan cortex (RMC) is an important Chinese herbal medicine. Comprehensive and objective quality evaluation of Chinese herbal medicine has been one of the most important issues in the modern herbs development.To evaluate and compare the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method.The percentage composition of gallic acid, catechin, oxypaeoniflorin, paeoniflorin, quercetin, benzoylpaeoniflorin, paeonol in different batches of RMC was determined, and then adopting MATLAB programming to construct the gray correlation-TOPSIS assessment model for quality evaluation of RMC.The quality evaluation results of model evaluation and objective evaluation were consistent, reliable, and stable.The model of gray correlation-TOPSIS can be well applied to the quality evaluation of traditional Chinese medicine with multiple components and has broad prospect in application.The experiment tries to construct a model to evaluate the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Results show the model is reliable and provide a feasible way in evaluating quality of traditional Chinese medicine with multiple components.

SUBMITTER: Zhou S

PROVIDER: S-EPMC5551377 | biostudies-other | 2017 Jul-Sep

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Evaluation of raw and processed Phellodendri Chinensis Cortex using the quality marker analysis strategy by UHPLC-Q-Orbitrap MS and multivariate statistical analysis.

Project description:Introduction: Phellodendri Chinensis Cortex is a necessary part of healthcare for its significant clinical efficacy. Raw and processed Phellodendri Chinensis Cortex is both documented in the Chinese Pharmacopoeia (2015). After processing, the therapeutic effects are believed to differ according to traditional Chinese medicine theories. However, the chemical mechanism responsible for this processing, according to traditional Chinese medicine theories, is still not clear. Methods: In this study, the therapeutic effects of various ions were examined based on traditional Chinese medicine theories by ultra-high performance liquid chromatography-hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q-Orbitrap MS) coupled with multivariate statistical analysis, such as principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), to comprehensively compare the differences between raw and processed Phellodendri Chinensis Cortex for the first time. Results: A total of 48 compounds were screened, out and 10 of them simultaneously transformed with significant variation in processed products compared with raw materials. It was illustrated that the contents of berberine, palmatine, jatrorrhizine, magnoflorine, menisperine, phellodendrine, tetrahydrojatrorrhizine, and tetrahydropalmatine decreased, while the compounds of berberrubine and fernloylquinic acid methyl ester newly appeared in processed herbs. This is likely to be related to the conversion of ingredients during processing. Discussion: Altogether, the fact that quality markers have been successfully identified to differentiate processed Phellodendri Chinensis Cortex from raw materials suggests that this approach could be used for the investigation of chemical transformation mechanisms involved in the processing of herbal medicine.

| S-EPMC10423935 | biostudies-literature

A new method for evaluating air quality using an ideal grey close function cluster correlation analysis method.

Project description:To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to China's air quality standard, SO2, NO2, PM10, PM2.5 and O3 are selected as evaluation indexes to perform the evaluation. The results show that the air quality in this region in 2018 can be divided into three classifications, among which the relatively poor air quality in March, April and May is the first classification, the better air quality in August and September is the third classification, and the air quality in other months falls under the second classification. Correlation analysis is used to qualitatively determine that these three classifications correspond to first-level air quality in China's air quality standard, and the correlation degree, which is the distance between the three classifications and the first-level air quality, is quantitatively determined. Specifically, the correlation degrees of the first-classification, second-classification and third-classification of air quality are 0.674, 0.697 and 0.71, respectively. The research results indicate potential directions and objectives for air quality management to achieve scientific management.

| S-EPMC8639721 | biostudies-literature

Quality Markers' Discovery and Quality Evaluation of Jigucao Capsule Using UPLC-MS/MS Method.

Project description:Jigucao capsules (JGCC) have the effects of soothing the liver and gallbladder and clearing heat and detoxification. It is a good medicine for treating acute and chronic hepatitis cholecystitis with damp heat of the liver and gallbladder. However, the existing quality standard of JGCC does not have content determination items, which is not conducive to quality control. In this study, serum pharmacochemistry technology and UNIFI data processing software were used to identify the blood prototype components and metabolites under the condition of the obvious drug effects of JGCC, and the referenced literature reports and the results from in vitro analysis of JGCC in the early stage revealed a total of 43 prototype blood components and 33 metabolites in JGCC. Quality markers (Q-markers) were discovered, such as abrine, trigonelline, hypaphorine and isoschaftoside. In addition, ultra-high-performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-QQQ-MS) was used to determine the active ingredients in JGCC. The components of quantitative analysis have good correlation in the linear range with R2 ≥ 0.9993. The recovery rate is 93.15%~108.92% and the relative standard deviation (RSD) is less than 9.48%. The established UPLC-MS/MS quantitative analysis method has high sensitivity and accuracy, and can be used for the quality evaluation of JGCC.

| S-EPMC10058756 | biostudies-literature

Identification and Quality Evaluation of Raw and Processed Asarum Species Using Microscopy, DNA Barcoding, and Gas Chromatography-Mass Spectrometry.

Project description:Asarum (Aristolochiaceae) is one of the common herbs used to relieve exterior syndromes. Some volatile components of Asarum which have toxic effect may cause adverse reactions such as headache, general tension, unconsciousness, and respiratory paralysis. Therefore, Asarum is normally processed to reduce such toxicity and adverse effects. The bioactive ingredients contained in different Asarum herbs vary significantly; this variation may be attributed to their differences in species, origins, or processing methods. In this study, 16 batches of Asarum herbs were collected, and their species were identified using DNA barcoding, which is a method for distinguishing plant species, coupled with microscopy. A gas chromatography-mass spectrometry (GC-MS) method for simultaneous determination of 10 compounds was established to evaluate the contents of raw and processed Asarum herbs. Multivariate analysis was then applied to compare different batches of herbs based on the GC-MS data. DNA barcoding identified the herbs as being derived from four sources, and herbs from different origins showed different microscopic features. The results demonstrated that most of the samples were clearly clustered into distinct groups that corresponded to species types. All raw and processed samples were classified by partial least squares discriminant analysis (PLS-DA) based on the 10 analyzed compounds. The findings suggested that safrole and methyleugenol with a variable importance in the project (VIP)?>?1 are unique compounds that can be used to differentiate between Asarum species. Safrole, methyleugenol, and 2,6,6-trimethylcyclohepta-2,4-dien-1-one were identified as significant constituents, the presence of which can be used to differentiate between raw and processed Asarum samples. These results indicate that species and processing methods show important effects on the composition of Asarum herbs.

| S-EPMC7174948 | biostudies-literature

Quality evaluation of Enzymatic Methyl-seq library constructed using crude cell lysate

Project description:Enzymatic Methyl-seq (EM-seq) is an enzyme-based method giving us reliable methylome data from small amounts of purified DNA. However, it is unclear whether EM-seq library can be constructed from crude cell lysate containing genomic DNA. We evaluated the quality of EM-seq libraries directly prepared from crude cell lysate.

2024-02-26 | GSE249962 | GEO

Research on Quality Markers of Guizhi Fuling Prescription for Endometriosis Treatment Based on Gray Correlation Analysis Strategy.

Project description:Guizhi Fuling prescription (GFP), a prestigious prescription of traditional Chinese medicine (TCM) recorded in "Jingui Yaolue," was composed of five Chinese medicines, including Moutan Cortex, Paeoniae Radix Alba, Persicae Semen, Poria Cocos, and Cinnamomi Ramulus. It was used for the treatment of endometriosis, primary dysmenorrhea, and blood stasis for centuries. However, its Quality Markers of treating endometriosis have not been clearly elucidated. In this study, a rapid ultraperformance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF-MS/MS) method was established for Quality Markers investigation on GFP, and a total of 50 potentially bioactive constituents including triterpenoids, paeoniflorin and its derivatives, phenolic acids, and other species were identified based on their retention time, fragmentation pattern, and accurately measured mass value. Furthermore, regularity of recipe composition and gray correlation analysis revealed that all of the characteristic peaks contributed to the treatment of endometriosis. The relative correlation degrees were greater than 0.6. Among them, peaks 1 and 10, which were most closely correlated to the endometriosis, were identified as amygdalin and cinnamic acid. Finally, all of the active ingredients were molecularly docked with proteins associated with endometriosis by Schrodinger method. Among them, amygdalin, cinnamic acid, paeonol, gallic acid, and paeoniflorin had the lower binding energies. It was proposed that these constituents could be directed at Quality Markers for GFP. Thus, the integrated approach describing for revealing Quality Markers of GFP could be expected to provide a method for quality evaluation.

| S-EPMC7835882 | biostudies-literature

High-sensitivity CEST mapping using a spatiotemporal correlation-enhanced method.

Project description:PurposeTo obtain high-sensitivity CEST maps by exploiting the spatiotemporal correlation between CEST images.MethodsA postprocessing method accomplished by multilinear singular value decomposition (MLSVD) was used to enhance the CEST SNR by exploiting the correlation between the Z-spectrum for each voxel and the low-rank property of the overall CEST data. The performance of this method was evaluated using CrCEST in ischemic mouse brain at 11.7 tesla. Then, MLSVD CEST was applied to obtain Cr, amide, and amine CEST maps of the ischemic mouse brain to demonstrate its general applications.ResultsComplex-valued Gaussian noise was added to CEST k-space data to mimic a low SNR situation. MLSVD CEST analysis was able to suppress the noise, recover the degraded CEST peak, and provide better CrCEST quality compared to the smoothing and singular value decomposition (SVD)-based denoising methods. High-resolution Cr, amide, and amine CEST maps of an ischemic stroke using MLSVD CEST suggest that CrCEST is also a sensitive pH mapping method, and a wide range of pH changes can be detected by combing CrCEST with amine CEST at high magnetic fields.ConclusionMLSVD CEST provides a simple and efficient way to improve the SNR of CEST images.

| S-EPMC7722217 | biostudies-literature

Evaluation of Invasive Breast Cancer Using a 12-Chemokine Gene Expression Score: Correlation With Clinical Outcomes

Project description:Clinically annotated GEPs of 366 primary resected breast tumors ranked by a 12 gene chemokine score

2017-12-31 | GSE86166 | GEO

RCRdiff: A fully integrated Bayesian method for differential expression analysis using raw NanoString nCounter data.

Project description:The medium-throughput mRNA abundance platform NanoString nCounter has gained great popularity in the past decade, due to its high sensitivity and technical reproducibility as well as remarkable applicability to ubiquitous formalin fixed paraffin embedded (FFPE) tissue samples. Based on RCRnorm developed for normalizing NanoString nCounter data and Bayesian LASSO for variable selection, we propose a fully integrated Bayesian method, called RCRdiff, to detect differentially expressed (DE) genes between different groups of tissue samples (eg, normal and cancer). Unlike existing methods that often require normalization performed beforehand, RCRdiff directly handles raw read counts and jointly models the behaviors of different types of internal controls along with DE and non-DE gene patterns. Doing so would avoid efficiency loss caused by ignoring estimation uncertainty from the normalization step in a sequential approach and thus can offer more reliable statistical inference. We also propose clustering-based strategies for DE gene selection, which do not require any external dataset and are free of any arbitrary cutoff. Empirical evidence of the attractiveness of RCRdiff is demonstrated via extensive simulation and data examples.

| S-EPMC8795478 | biostudies-literature

Evaluation of Ocular Versions in Graves' Orbitopathy: Correlation between the Qualitative Clinical Method and the Quantitative Photographic Method.

Project description:Purpose:To assess the agreement between the qualitative clinical method and the quantitative photographic method of evaluating normal and abnormal ocular versions in patients with inactive Graves' orbitopathy (GO). Methods:Forty-two patients with inactive GO had their ocular versions evaluated clinically according to three categories: normal, moderate alterations (-1 or -2 hypofunction), and severe alterations (-3 or -4 hypofunction). The subjects were photographed in the 9 positions of gaze, and the extent (mm) of eye movement in each position was estimated using Photoshop® and ImageJ and converted into degrees with a well-established method. The agreement between the two methods (qualitative vs. quantitative) for classifying ocular versions as normal or abnormal was assessed. Results:The mean quantitative measurements of versions were significantly different for each clinical category (normal, moderate alterations, and severe alterations) in the following five positions: abduction, adduction, elevation in abduction, elevation, and elevation in adduction (p < 0.001). No such pattern was observed for the three infraversion positions (depression in abduction, p=0.573; depression, p=0.468; depression in adduction, p=0.268). Conclusion:The agreement was strong between the quantitative photographic method and the qualitative clinical method of classifying ocular versions, especially in lateral and supraversions, which are typically affected in GO. Digital photography is recommended for the assessment of ocular versions due to its practicality, suitability for telemedicine applications, and ease of monitoring during follow-up. This trial is registered with NCT03278964.

| S-EPMC7422460 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data