Volatile profile and multivariant analysis of Sanhuang chicken breast in combination with Chinese 5-spice blend and garam masala

Sanhuang chicken is a popular native breed in China and well-known for delicious flavour.Spices could enhance the chicken meat flavour and work well in preservation.Chinese 5-spice blend(CS)and garam masala(GM)are routinely using spices in China and Pakistan,respectively.The flavour profiles of Sanhuang chicken breast(CB)and its blends with CS and GM were obtained by electronic nose(E-nose),solid-phase microextraction gas chromatography-mass spectrometry(SPME GC-MS)and GC-ion mobility spectrometry(GC-IMS).Principal component analysis(PCA)efficiently discriminated the aroma profiles of three chicken formulations.The GC-chromatographs revealed the significant aroma alterations of chicken breast meat after marination with spices.Aldehydes were the major contributors of chicken aroma,while most of the aromatic hydrocarbons were generated by spices.Almost all chicken key-compounds produced by oxidation reaction were either reduced or eliminated by marination,showing the antioxidation capacity of spices leading to meat preservation.GC-IMS is not only a rapid and comprehensive detection method,but also proved to be more sensitive than GC-MS.The substantial role of both traditional spices in enhancing flavour quality of chicken meat,and their exposure as functional ingredients in Chinese and Pakistan cuisines could lead to the cross-cultural meat trade opportunities.

Clinical outcome and prognostic factors of T4N0M0 colon cancer after R0 resection:A retrospective study

BACKGROUND Paradoxically,patients with T4N0M0(stage II,no lymph node metastasis)colon cancer have a worse prognosis than those with T2N1-2M0(stage III).However,no previous report has addressed this issue.AIM To screen prognostic risk factors for T4N0M0 colon cancer and construct a prognostic nomogram model for these patients.METHODS Two hundred patients with T4N0M0 colon cancer were treated at Tianjin Medical University General Hospital between January 2017 and December 2021,of which 112 patients were assigned to the training cohort,and the remaining 88 patients were assigned to the validation cohort.Differences between the training and validation groups were analyzed.The training cohort was subjected to multi-variate analysis to select prognostic risk factors for T4N0M0 colon cancer,followed by the construction of a nomogram model.RESULTS The 3-year overall survival(OS)rates were 86.2%and 74.4%for the training and validation cohorts,respectively.Enterostomy(P=0.000),T stage(P=0.001),right hemicolon(P=0.025),irregular review(P=0.040),and carbohydrate antigen 199(CA199)(P=0.011)were independent risk factors of OS in patients with T4N0M0 colon cancer.A nomogram model with good concordance and accuracy was constructed.CONCLUSION Enterostomy,T stage,right hemicolon,irregular review,and CA199 were independent risk factors for OS in patients with T4N0M0 colon cancer.The nomogram model exhibited good agreement and accuracy.

Characteristics and genesis of groundwater salinization in coastal areas of the Lower Reaches of Oujiang Basin

The coastal areas of the lower reaches of Oujiang River Basin are rich in groundwater resources.However,the unsustainable exploitation and utilization of groundwater have led to significant changes in the groundwater environment.Understanding the characteristics and genesis of groundwater salinization is crucial for preventing its deterioration and ensuring sustainable utilization.In this study,a comprehensive approach combining the ion ratio method,mineral saturation index method and multivariate statistical analysis was employed to investigate the hydrochemical characteristics and main controlling factors in the study area.The findings reveal that:(1)Groundwater samples in study area exhibit a neutral to slightly alkaline pH.The predominant chemical types of unconfined water are HCO_(3)-Ca·Na,HCO_(3)·Cl-Na·Ca and HCO_(3)·SO_(4)-Ca·Na,while confined water mainly exhibits Cl·HCO_(3)-Na and Cl-Na types.(2)Salinity coefficients indicate an increase in salinity from unconfined to confined water.TDS,Na^(+)and Cl^(–)concentrations show an increasing trend from mountainous to coastal areas in unconfined water,while confined water displays variability in TDS,Na^(+)and Cl^(–)concentrations.(3)Groundwater salinity is mainly influenced by water-rock interactions,including the dissolution of halite and gypsum,cation exchange,and seawater intrusion etc.Additionally,human activities and carbonate dissolution contribute to salinity in unconfined water.Seawater intrusion is identified as the primary factor leading to higher salinity in confined water compared to unconfined water,with increasing cation exchange and seawater interaction observed from unconfined to confined water.

Groundwater quality assessment using multivariate analysis,geostatistical modeling, and water quality index(WQI): a case of study in the Boumerzoug-El Khroub valley of Northeast Algeria

In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.

Comprehensive multivariate grey incidence degree based on principal component analysis

To overcome the too fine-grained granularity problem of multivariate grey incidence analysis and to explore the comprehensive incidence analysis model, three multivariate grey incidences degree models based on principal component analysis （PCA） are proposed. Firstly, the PCA method is introduced to extract the feature sequences of a behavioral matrix. Then, the grey incidence analysis between two behavioral matrices is transformed into the similarity and nearness measure between their feature sequences. Based on the classic grey incidence analysis theory, absolute and relative incidence degree models for feature sequences are constructed, and a comprehensive grey incidence model is proposed. Furthermore, the properties of models are researched. It proves that the proposed models satisfy the properties of translation invariance, multiple transformation invariance, and axioms of the grey incidence analysis, respectively. Finally, a case is studied. The results illustrate that the model is effective than other multivariate grey incidence analysis models.

ASSESSMENT OF LOCAL INFLUENCE IN MULTIVARIATE ANALYSIS

A recent method for assessing the local influence is introduced by Cook(1986), in which the normal curvature of the influence graph based on the likelihood displacement is used to monitor the influence of small perturbation. Since then this method has been applied to various kind of models. However, the local influence in multivariate analysis is still an unexplored area because the influence for many statistics in multivariate analysis is not convenient to handle based on the Cook's likelihood displacement. In this paper, we suggest a method with a slight modification in Cook's approach to assess the local influence of small perturbation on a certain statistic. The local influence of the perturbation on eigenvalue and eigenvector of variance-covariance matrix in theoretical and sample version is assessed, some results for the other statistics in multivariate analysis such as generalized variance, canonical correlations are studied. Finally, two examples are analysed for illustration.

Surgical mortality in patients with malignant obstructive jaundice: a multivariate discriminant analysis

OBJECTIVE: To estimate the operative mortality in patients with malignant obstructive jaundice. METHODS: Twelve risk factors were analyzed using multivariate discriminant analysis in 90 patients who had been operated on. RESULTS: Operative mortality was significantly related to the following factors: age, duration of jaundice, packed RBC volume, white blood cell count and concentration of blood urine nitrogen; it was not significantly related to diseases and types of operation. The following formula was obtained: packed RBC volume×0.09954-age×0. 04018-blood urine nitrogen×0. 23693-duration of jaundice× 2. 07388-WBC count×0. 21118+5. 26593. With this formula, an operative mortality of 77. 8% was predicted. CONCLUSION: With a positive value from the formula, the patient should be operated on; otherwise non-operative treatment is advocated.

Metabolomics-based comparative analysis of the effects of host and environment on Viscum coloratum metabolites and antioxidative activities

Viscum coloratum(Kom.)Nakai is a well-known medicinal hemiparasite widely distributed in Asia.The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants,while the latter of which is usually overlooked.The purpose of this study was to comprehensively evaluate the effects of host and habitat on the metabolites in V.coloratum through multiple chemical and biological approaches.The metabolite profile of V.coloratum harvested from three different host plants in two habitats were determined by multiple chemical methods including high-performance liquid chromatography-ultraviolet(HPLC-UV),gas chromatography-flame ionization detector(GC-FID)and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry(UPLC-QTOF/MS).The differences in antioxidant efficacy of V.coloratum were determined based on multiple in vitro models.The multivariate statistical analysis and data fusion strategy were applied to analyze the differences in metabolite profile and antioxidant activity of V.coloratum.Results indicated that the metabolite profile obtained by various chemical approaches was simultaneously affected by host and environment factors,and the environment plays a key role.Meanwhile,three main differential metabolites between two environment groups were identified.The results of antioxidant assay indicated that the environment has greater effects on the biological activity of V.coloratum than the host.Therefore,we conclude that the integration of various chemical and biological approaches combined with multivariate statistical and data fusion analysis,which can determine the influences of host plant and habitat on the metabolites,is a powerful strategy to control the quality of semi-parasitic herbal medicine.

Discrimination of aqueous and vinegary extracts of Shixiao San using metabolomics coupled with multivariate data analysis and evaluation of antihyperlipidemic effect

A novel study using LCeMS(Liquid chromatography tandem mass spectrometry)coupled with multivariate data analysis and bioactivity evaluation was established for discrimination of aqueous extract and vinegar extract of Shixiao San.Batches of these two kinds of samples were subjected to analysis,and the datasets of sample codes,tR-m/z pairs and ion intensities were processed with principal component analysis(PCA).The result of score plot showed a clear classification of the aqueous and vinegar groups.And the chemical markers having great contributions to the differentiation were screened out on the loading plot.The identities of the chemical markers were performed by comparing the mass fragments and retention times with those of reference compounds and/or the known compounds published in the literatures.Based on the proposed strategy,quercetin-3-Oneohesperidoside,isorhamnetin-3-O-neohespeeridoside,kaempferol-3-O-neohesperidoside,isorhamnetin-3-O-rutinoside and isorhamnetin-3-O-(2G-a-l-rhamnosyl)-rutinoside were explored as representative markers in distinguishing the vinegar extract from the aqueous extract.The anti-hyperlipidemic activities of two processed extracts of Shixiao San were examined on serum levels of lipids,lipoprotein and blood antioxidant enzymes in a rat hyperlipidemia model,and the vinegary extract,exerting strong lipid-lowering and antioxidative effects,was superior to the aqueous extract.Therefore,boiling with vinegary was predicted as the greatest processing procedure for anti-hyperlipidemic effect of Shixiao San.Furthermore,combining the changes in the metabolic profiling and bioactivity evaluation,the five representative markers may be related to the observed antihyperlipidemic effect.

The Bio-Geographical Regions Division of Global Terrestrial Animal by Multivariate Similarity Clustering Analysis Method

A novel multivariate similarity clustering analysis (MSCA) approach was used to estimate a biogeographical division scheme for the global terrestrial fauna and was compared against other widely used clustering algorithms. The faunal dataset included almost all terrestrial and freshwater fauna, a total of 4631 families, 141,814 genera, and 1,334,834 species. Our findings demonstrated that suitable results were only obtained with the MSCA method, which was associated with distinct hierarchies, reasonable structuring, and furthermore, conformed to biogeographical criteria. A total of seven kingdoms and 20 sub-kingdoms were identified. We discovered that the clustering results for the higher and lower animals did not differ significantly, leading us to consider that the analysis result is convincing as the first zoogeographical division scheme for global all terrestrial animals.

A New Fracability Evaluation Approach for Shale Reservoirs Based on Multivariate Analysis: A Case Study in Zhaotong Shale Gas Demonstration Zone in Sichuan, China

Fracability characterizes the effectiveness of hydraulic fracturing.The existing assessment methods cannot reflect the actual value of the effectiveness due to a lack of comprehensive consideration and neglect of the influences of engineering factors.This study aims to solve this problem by implementing geological static data and production dynamic data in multivariate analysis in Zhaotong shale gas demonstration zone.First,the reservoir quality index(RQI)was introduced to evaluate the exploration potential by integrating the geological parameters with gray relational analysis.Moreover,the differences in fracturing fluid types and proppant sizes were considered,and the operating parameters were normalized on the basis of the equivalence principle.Finally,the general reservoir fracability index(GRFI)was proposed based on a dimensioned processing of the various parameters.A case study was conducted to verify the accuracy and feasibility of this new approach.The results demonstrate that(1)the organic carbon and gas content are adjusted to contribute the most to the calculation of the RQI,while the effective porosity contributes the least;(2)the fracturing scale is the main operating parameter determining the fracability,which has the strongest correlation with the effectiveness of fracking;and(3)the GRFI has a positive correlation with shale gas production,and the lower limit of the GRFI of 2,000 corresponds to a daily production of 50,000 m3/d;this value is defined as the threshold value of a stripper well.The GRFI is consistent with the productivity trend of shale gas wells in the research block,which suggests that the new model is accurate and practical for well candidate selection.

Hydrogeochemical processes and multivariate analysis for groundwater quality in the arid Maadher region of Hodna,northern Algeria

This study focused on water quality and hydrogeochemical processes(evolution,origin)in the Maadher region,central Hodna in Algeria.In recent decades,the excessive exploitation of this resource due to urbanization,irrigation,and the effect of climate change reaching the countries of northern Africa have caused a decline in water levels and hydrochemical changes in the aquifer.The sampling campaign in 2019 based on 13 physicochemical parameters was carried out on the water from 32 boreholes in the study area,compared to data archives of both sampling campaigns in 1967 and 1996.The result revealed that the groundwater as a whole has moderate freshwater quality,due to its total dissolved solids(TDS)content and other dissolved ions of concern(nitrate NO),which exceed WHO standards.In addition,Piper diagram indicates that the hydrochemical facies of sulfate–chloride–nitrate–calcium(SO–Cl–NO–Catype),which globally characterizes the study area and these elements are the dominant dissolved ions.Principal component analysis and hierarchical cluster analysis(HCA)methodologies are applied in order to define the major control factors that affect the hydrochemistry of Maadher plain.Three distinct water groups were found,illustrating a different evolution of salinity(EC and TDS).The HCA indicated an interesting cluster with a distinct contamination signature and most likely with significantly higher sulfate,chloride,and nitrate concentrations.Anthropogenic processes also play an important role in the study area.The water resource comes from Bousaada Wadi,the exchange at the aquifer depth and the agricultural practices contribute to the deterioration of the quality.

Multivariate analysis of serum surface-enhanced Raman spectroscopy of liver cancer patients

Early diagnosis of liver cancer plays a significant role in reducing its high mortality.In this preliminary study,the feasibility of using serum surface-enhanced Raman spectroscopy(SERS)to identify liver cancer was studied.Serum samples were obtained from liver cancer patients and healthy controls.The differences between the SERS spectra of pre-operation and postoperation of liver cancer patients were also analyzed.The general shape and trend of SERS spectra of health control and liver cancer patients were similar.Multivariate analysis,e.g.,PLSSVM,might be useful for the discrimination of serum SERS spectra of pre-operation and post-operation.

A comparative study of Salvia miltiorrhiza Radix & Rhizoma raw material and granule products using chromatographic analysis and antioxidant activity

Objective: Granules of herbal extracts are a popular medicinal preparation consumed in traditional Chinese medicine clinical practice. However, their quality and efficacy evaluation are lacking. This study aimed to compare the quality and anti-oxidant activity of Dan Shen(Salvia miltiorrhiza Radix & Rhizoma)granule extracts with their herbal extracts.Methods: Chromatographic method was used to determine the content of 7 marker compounds in the water extracts of the herb compared to that of 12 granule extracts. Agglomerative hierarchical clustering(AHC) and principal component analysis(PCA) distinguished the herbal and granule extracts based on the content of the marker compounds. The antioxidant activities of herbal and granule extracts were evaluated by 2, 2'-azino-bis(3-ethylbenz-thiazoline-6-sulfonic acid)(ABTS), organic chemical compound 2,2-diphenyl-1-picrylhydrazyl(DPPH) and ferric ion reducing antioxidant power(FRAP) assays.Results: The herbal extracts group showed significantly higher contents of salvianolic acid B, sodium danshensu and cryptotanshinone compared with that of the granule group. This corresponded to significantly higher ABTS, DPPH and FRAP(P <.05) activities of the herbal extracts. The AHC and PCA analysis distinguished granule extracts from most herbal extracts predominantly by the content of salvianolic acid B.Conclusion: The results confirm the need for the assessment of granule products so that healthcare practitioners and consumers are better informed of their quality and efficacy.

COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA

Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma.

Multivariate analysis for ordination and comparison of size of Artemia cysts

It is known that the biometrics of brine shrimp cysts is of strain inherent. The analysis and comparison of the cyst charcters for the identification of unknown cysts from different geqraphical origin become mpible. In this paper, multivallate methods, mainly Principle Component Analysis (PCA) and Nonmetric Multi-dimensional Scaling (MDS), are used for the purpose. od results are gained with the analysis of the published data and some row data from cyst sizes. It shows that multivariate methods can cluster the similar characteristics of batch cysts and make out impure or mingled cysts of different origin. Amng others, MDS, with row data from the cyst measurement, can be easily used for the analysis of cyst ordination and comparison. The result demonstrates that the cysts of Chinese parthenopnetic brine shrimp are well discriminated by their geographic locations along the coastal China with larger size disttibuting in the south.

Optimization of wavelength range and data interval in chemometric analysis of complex pharmaceutical mixtures

The performance of different chemometric approaches was evaluated in the spectrophotometric determination of pharmaceutical mixtures characterized by having the amount of components with a very high ratio. Principal component regression （PCR）, partial least squares with one dependent variable （PLS1） or multi-dependent variables （PLS2）, and multivariate curve resolution （MCR） were applied to the spectral data of a ternary mixture containing paracetamol, sodium ascorbate and chlorpheniramine （150：140：1, m/m/m）, and a quaternary mixture containing paracetamol, caffeine, phenylephrine and chlorpheniramine （125：6. 25：1.25：1, m/m/m/m）. The UV spectra of the calibration samples in the range of 200-320 nm were pre-treated by removing noise and useless data, and the wavelength regions having the most useful analytical information were selected using the regression coefficients calculated in the multivariate modeling. All the defined chemometric models were validated on external sample sets and then applied to commercial pharmaceutical formulations. Different data intervals, fixed at 0.5, 1.0, and 2.0 point/nm, were tested to optimize the prediction ability of the models. The best results were obtained using the PLSlcalibration models and the quantification of the species of a lower amount was sig- nificantly improved by adopting 0.5 data interval, which showed accuracy between 94.24% and 107.76%.

Some Experiments with Multivariate Objective Analysis Scheme of Heights and Winds Using Optimum Interpolation

A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976-1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.

Quality assessment of Jinhongtang Granule using UFLC-MS/MS and multivariate statistical analysis

Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for Jinhongtang is not available.In present study,we developed a UFLC-MS/MS method to determine 16 analytes in 20 batches of home-made and commercial Jinhongtang.Multivariate statistical analysis revealed the significant differences in the quality of home-made and commercial Jinhongtang and the difference in the quality of home-made samples was more significant.The integrated strategy based on UFLC-MS/MS and multivariate statistical analysis provided a new basis for the overall quality assessment of Jinhongtang.