Publications by authors named "Zan Lin"

26 Publications

  • Page 1 of 1

Detection of glibenclamide adulterated in antidiabetic Chinese patent medicine by attenuated total reflectance -infrared spectroscopy and chemometrics.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Jul 19;255:119723. Epub 2021 Mar 19.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; Sichuan Provincial Orthopedic Hospital, Chengdu, Sichuan 610041, China.

There have been many reports of adulterated Chinese patent medicine with synthetic prescription that are claimed to be "pure natural". The present work investigates the feasibility of combining attenuated total reflectance-Mid-infrared (ATR-MIR) spectroscopy and several interval-based PLS algorithms for detecting the glibenclamide illegally adulterated in antidiabetic Chinese patent medicine (Jiangtangning). The full-spectrum PLS, four kinds of traditional interval PLS algorithms (iPLS, biPLS, siPLS and mwPLS) and a modified algorithm, i.e., a combination of mwPLS and window size optimization, named cmwPLS, were used for building calibration models. A total of 21 samples adulterated with 0-3.5% glibenclamide were prepared. The dataset was equally split into a training set and a test set for building and testing the prediction models, respectively. For those interval-based PLS, the whole wavenumber axis was divided into 20 sub-intervals. In terms of the prediction on the test set, the new cmwPLS produce the best model, followed by mwPLS. The modified algorithm can optimize automatically the window width (i.e., the number of adjacent variables used for modeling) and position. It can be concluded that cmwPLS coupled with ATR-MIR technique is a good alternative to other traditional chemical analysis for detecting the adulteration of Chinese patent medicine.
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http://dx.doi.org/10.1016/j.saa.2021.119723DOI Listing
July 2021

Classification of different liquid milk by near-infrared spectroscopy and ensemble modeling.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Apr 14;251:119460. Epub 2021 Jan 14.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

Dairy products are necessary components of a healthy diet for human and nowadays, liquid milk become very popular because of its convenience. The identification of a brand of liquid milk is of importance. In this study, near-infrared (NIR) spectroscopy is used for rapid and objective classification of different brands of liquid milk. Chemometric methods including extreme learning machine (ELM) and its ensemble version (EELM) are investigated and compared. A dataset containing 144 samples from 6 brands are collected for experiment. A model-independent filter algorithm, i.e., relief-based feature selection, was used for variable reduction. Principal component analysis (PCA) is used as a tool of exploratory analysis for visualizing the difference among liquid milk samples of different brands. All samples were divided into three subsets, i.e., the training set, validation set and test set, for constructing, optimizing and testing the model, respectively. The model developed by the EELM procedure achieved 100% of classification accuracy, indicating that NIR spectroscopy combined with variable reduction and the EELM algorithm is feasible for classifying the brands of liquid milk.
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http://dx.doi.org/10.1016/j.saa.2021.119460DOI Listing
April 2021

Ensemble of extreme learning machines for multivariate calibration of near-infrared spectroscopy.

Spectrochim Acta A Mol Biomol Spectrosc 2020 Mar 24;229:117982. Epub 2019 Dec 24.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; Sichuan Provincial Orthopedic Hospital, Chengdu, Sichuan 610041, China.

Inspired by the attractive features of extreme learning machine (ELM), a simple ensemble ELM algorithm, named EELM, is proposed for multivariate calibration of near-infrared spectroscopy. Such an algorithm takes full advantage of random initialization of the weights of the hidden layer in ELM for obtaining the diversity between member models. Also, by combining a large number of member models, the stability of the final prediction can be greatly improved and the ensemble model outperforms its best member model. Compared with partial least-squares (PLS), the superiority of EELM is attributed to its inherent characteristics of high learning speed, simple structure and excellent predictive performance. Three NIR spectral datasets concerning solid samples are used to verify the proposed algorithm in terms of both the accuracy and robustness. The results confirmed the superiority of EELM to classic PLS. Also, even if the experiment is done on NIR datasets, it provides a good reference for other spectral calibration.
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http://dx.doi.org/10.1016/j.saa.2019.117982DOI Listing
March 2020

Application of near-infrared spectroscopy and class-modeling to antibiotic authentication.

Anal Biochem 2020 02 28;590:113514. Epub 2019 Nov 28.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan, 644000, China. Electronic address:

Nowadays, counterfeit medicines have become very popular due to the extension of the Internet. Broad-spectrum antibiotics with similar effect, but different prices, provide a gold opportunity for illegal traders to counterfeit. It is found that some genuine packaging of expensive brand drugs are recycled and then used to refill other kinds of cheap antibiotic tablets. It is of great importance to establish an effective antibiotic authentication method to check whether a product with a specific claim on its label is compatible with that declaration. In the present work, the feasibility of near-infrared (NIR) spectroscopy coupled with class-modeling for antibiotics authentication, i.e., counterfeiting between different antibiotics, is investigated. A total of 591 antibiotics samples of nine classes of different dosage forms were collected. Principal component analysis (PCA) was used for exploratory analysis. An effective model-independent filter method, i.e., relief, was used for feature selection and a novel class-modeling algorithm was used to construct authentication models. Three kinds of antibiotics were used as the target classes for experiments. The results confirmed that such a scheme is feasible and can be used in the screening of fake drug.
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http://dx.doi.org/10.1016/j.ab.2019.113514DOI Listing
February 2020

Soil and biomass carbon re-accumulation after landslide disturbances.

Geomorphology (Amst) 2019 Jul 1;288:164-174. Epub 2017 Apr 1.

Department of Forest and Soil Science, Institute of Soil Research, University of Natural Resources and Life Sciences, Vienna, Austria.

In high-standing islands of the Western Pacific, typhoon-triggered landslides occasionally strip parts of the landscape of its vegetative cover and soil layer and export large amounts of biomass and soil organic carbon (OC) from land to the ocean. After such disturbances, new vegetation colonizes the landslide scars and OC starts to reaccumulate. In the subtropical mountains of Taiwan and in other parts of the world, bamboo () species may invade at a certain point in the succession of recovering landslide scars. Bamboo has a high potential for carbon sequestration because of its fast growth and dense rooting system. However, it is still largely unknown how these properties translate into soil OC re-accumulation rates after landslide disturbance. In this study, a chronosequence was established on four former landslide scars in the Central Mountain Range of Taiwan, ranging in age from 6 to 41 years post disturbance as determined by landslide mapping from remote sensing. The younger landslide scars were colonized by , while after approx. 15 to 20 years of succession, bamboo species () were dominating. Biomass and soil OC stocks were measured on the recovering landslide scars and compared to an undisturbed forest stand in the area. After initially slow re-vegetation, biomass carbon accumulated in stands with mean annual accretion rates of 2 ± 0.5 Mg C ha yr. Biomass carbon continued to increase after bamboo invasion and reached ~40% of that in the reference forest site after 41 years of landslide recovery. Soil OC accumulation rates were ~2.0 Mg C ha yr, 6 to 41 years post disturbance reaching ~64% of the level in the reference forest. Our results from this in-situ study suggest that recovering landslide scars are strong carbon sinks once an initial lag period of vegetation re-establishment is overcome.
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http://dx.doi.org/10.1016/j.geomorph.2017.03.032DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6616031PMC
July 2019

Express detection of expired drugs based on near-infrared spectroscopy and chemometrics: A feasibility study.

Spectrochim Acta A Mol Biomol Spectrosc 2019 Sep 22;220:117153. Epub 2019 May 22.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; The First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China.

Levofloxacin is a third-generation fluoroquinolone antimicrobials drug that inhibits bacterial DNA replication. Driven by huge profit, one kind of particular counterfeit, e.g., repackaged expired tablets, becomes very common especially in developing countries. The feasibility of identifying expired levofloxacin tablets by combining NIR spectroscopy with chemometrics was investigated. Five kinds of levofloxacin samples from different manufacturers were collected for experiment. Two types of expired mode were considered and a simple model-independent algorithm was used for feature selection. Principal component analysis (PCA) was used for exploratory analysis and simple discriminant analysis. Taking seventy samples as the target class, a final one-class model based on Data Driven Soft Independent Modeling by Class Analogy with abbreviation DD-SIMCA was constructed, which achieved 97% sensitivity and 100% specificity on the independent set composed of 34 unexpired and 128 expired tablets. These results confirm that the combination of NIR spectroscopy, feature selection and class-modeling is feasible for identifying the expired levofloxacin tablets. Such a method can be extended to the analysis of similar drugs.
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http://dx.doi.org/10.1016/j.saa.2019.117153DOI Listing
September 2019

Quantifying several adulterants of notoginseng powder by near-infrared spectroscopy and multivariate calibration.

Spectrochim Acta A Mol Biomol Spectrosc 2019 Mar 4;211:280-286. Epub 2018 Dec 4.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

The authentication of traditional Chinese medicine (TCM) is critically important for public-health and economic terms. Notoginseng, a classical TCM of high economic and medical value, could be easily adulterated with Sophora flavescens powder (SFP), corn flour (CF) or other analogues of low-grade (ALG) because of their similar tastes, appearances and much lower cost. The main objective of this study was to evaluate the feasibility of applying of near-infrared (NIR) spectroscopy and multivariate calibration for identifying and quantifying several common adulterants in notoginseng powder. Two datasets were prepared for experiment. The competitive adaptive reweighted sampling (CARS) was used to select informative variables. Two different schemes were used for sample set partition. Model population analysis (MPA) was made. The results showed that, the constructed partial least squares (PLS) model using a reduced set of variables from CARS can provide superior performance to the full-spectrum PLS model. Also, the sample set partition is very of great importance. It seems that the combination of NIR spectroscopy, CARS and PLS is feasible to quantify common adulterants in notoginseng powder.
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http://dx.doi.org/10.1016/j.saa.2018.12.003DOI Listing
March 2019

Random subspace-based ensemble modeling for near-infrared spectral diagnosis of colorectal cancer.

Anal Biochem 2019 02 11;567:38-44. Epub 2018 Dec 11.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan, 644000, China. Electronic address:

The feasibility of using near-infrared (NIR) spectroscopy coupled with classifier ensemble for improving the diagnosis of colorectal cancer was explored. A total of 157 NIR spectra from the patients were recorded and partitioned into the training set and the test set. Four algorithms, i.e., Adaboost.M1, Totalboost and LPboost using decision tree as weak learners, together with random subspace method (RSM) using linear discriminant classifier (LDA) as weak learners, were used to construct diagnostic models. Some key parameters such as the size of ensemble, i.e., the number of weak learners in ensemble, and the size of each subspace in RSM, were optimized. The results indicated that, in terms of generalization ability, the RSM-based classifier outperforms all other classifiers by only 40 members with 30 features each. On the basis of 200 different training sets, model population analysis (MPA) was made. The average sensitivity and specificity of the RSM classifier were 97.4% and 95.6%, respectively. It indicates that the NIR technique combined with the RSM algorithm can serve as a potential means for automatic identification of colorectal tissues.
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http://dx.doi.org/10.1016/j.ab.2018.12.009DOI Listing
February 2019

Fast discrimination of the geographical origins of notoginseng by near-infrared spectroscopy and chemometrics.

J Pharm Biomed Anal 2018 Nov 27;161:239-245. Epub 2018 Aug 27.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China. Electronic address:

Notoginseng is a type of highly valued Traditional Chinese medicine (TCM) due to its hemostatic and cardiovascular functions. Notoginseng of Yunnan in China usually commands a premium price and is often the subject of fraudulent practices. The feasibility of combining near-infrared (NIR) spectroscopy with chemometrics was investigated to discriminate notoginseng of different geographical origins. A total of 250 samples of four different provinces in China were collected and divided equally into the training and test sets. Principal component analysis (PCA) was used for observing possible trend of grouping. Two chemometric algorithms including partial least squares-discriminant analysis (PLSDA) and soft independent modeling of class analogy (SIMCA) were used to construct the discriminant models. Standard normal variate (SNV) and first derivative were used for pre-processing spectra. On the independent test set, the PLSDA model outperforms the SIMCA model. When combining both pre-processing methods, the constructed PLSDA model achieved 100% sensitivity and 100% specificity on both the training set and the test set. It indicates that SNV+first derivative pre-processing and PLSDA algorithm can serve as the potential tool of fast discriminating the geographical origins of notoginseng.
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http://dx.doi.org/10.1016/j.jpba.2018.08.052DOI Listing
November 2018

Non-destructive identification of native egg by near-infrared spectroscopy and data driven-based class-modeling.

Spectrochim Acta A Mol Biomol Spectrosc 2019 Jan 25;206:484-490. Epub 2018 Aug 25.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000,China; Department of Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.

Eggs are very important parts of human diets worldwide. It is very common to pass feed eggs off as native ones of high commercial values in Chinese markets. One urgent and challenging work is to develop a non-destructive method for verifying the authenticity of native eggs. The present work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy with data driven-based class-modeling (DDCM) and model-independent variable selection, i.e., joint mutual information (JMI). A total of 122 eggs of three types were collected. Principal component analysis (PCA) was utilized for exploratory analysis. The JMI algorithm selected only 20 informative variables out of 1557 original variables for class-modeling. DDCM constructed a class-model for each kind of eggs by optimizing parameters such as degrees of freedom (DoF) and the number of principal components (NPC). All class-models and the decision rules were validated on the corresponding test sets. In short, these models achieved an acceptable performance and are also more consistent with actual needs than classification models. The results show that NIR spectroscopy combined with class-modeling is a potential tool for detecting the authenticity of a specific kind of native eggs.
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http://dx.doi.org/10.1016/j.saa.2018.08.041DOI Listing
January 2019

Authenticity Detection of Black Rice by Near-Infrared Spectroscopy and Support Vector Data Description.

Int J Anal Chem 2018 9;2018:8032831. Epub 2018 Jul 9.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

Black rice is an important rice species in Southeast Asia. It is a common phenomenon to pass low-priced black rice off as high-priced ones for economic benefit, especially in some remote towns. There is increasing need for the development of fast, easy-to-use, and low-cost analytical methods for authenticity detection. The feasibility to utilize near-infrared (NIR) spectroscopy and support vector data description (SVDD) for such a goal is explored. Principal component analysis (PCA) is used for exploratory analysis and feature extraction. Another two data description methods, i.e., k-nearest neighbor data description (KNNDD) and GAUSS method, are used as the reference. A total of 142 samples from three brands were collected for spectral analysis. Each time, the samples of a brand serve as the target class whereas other samples serve as the outlier class. Based on both the first two principal components (PCs) and original variables, three types of data descriptions were constructed. On average, the optimized SVDD model achieves acceptable performance, i.e., a specificity of 100% and a sensitivity of 94.2% on the independent test set with tight boundary. It indicates that SVDD combined with NIR is feasible and effective for authenticity detection of black rice.
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http://dx.doi.org/10.1155/2018/8032831DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6076898PMC
July 2018

Current situation and future prospects for beef production in China - A review.

Asian-Australas J Anim Sci 2018 Jul 31;31(7):984-991. Epub 2018 May 31.

Department of Animal Science, Northwest A&F University, Yangling, Shaanxi 712100, China.

The beef industry is an important part of livestock and meat production in China. China ranks third in the world for beef production. With the rapid development of the Chinese economy, beef consumption has grown rapidly, and beef consumption has been increasing with rising per capita gross domestic production. However, the domestic beef industry in China has not been able to keep pace with growth in consumption, making China a net importer of beef from other countries. Moreover, the volume of production has increased little despite rising demand. The slowing of growth in beef production in recent years has led to a sharp rise in beef prices. Domestic beef production and consumption is restricted by a shortage of beef cattle inventory. The Chinese beef industry is facing many technical problems including transformation of traditional practices, feeding and management systems, and genetic improvement of cattle breeds. The long-term, sustainable development of the Chinese beef industry is an important issue for China.
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http://dx.doi.org/10.5713/ajas.18.0212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039324PMC
July 2018

Quantitative determination of wool in textile by near-infrared spectroscopy and multivariate models.

Spectrochim Acta A Mol Biomol Spectrosc 2018 Aug 4;201:229-235. Epub 2018 May 4.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China; Department f Orthopedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.

The wool content in textiles is a key quality index and the corresponding quantitative analysis takes an important position due to common adulterations in both raw and finished textiles. Conventional methods are maybe complicated, destructive, time-consuming, environment-unfriendly. Developing a quick, easy-to-use and green alternative method is interesting. The work focuses on exploring the feasibility of combining near-infrared (NIR) spectroscopy and several partial least squares (PLS)-based algorithms and elastic component regression (ECR) algorithms for measuring wool content in textile. A total of 108 cloth samples with wool content ranging from 0% to 100% (w/w) were collected and all the compositions are really existent in the market. The dataset was divided equally into the training and test sets for developing and validating calibration models. When using local PLS, the original spectrum axis was split into 20 sub-intervals. No obvious difference of performance can be seen for the local PLS models. The ECR model is comparable or superior to the other models due its flexibility, i.e., being transition state from PCR to PLS. It seems that ECR combined with NIR technique may be a potential method for determining wool content in textile products. In addition, it might have regulatory advantages to avoid time-consuming and environmental-unfriendly chemical analysis.
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http://dx.doi.org/10.1016/j.saa.2018.05.010DOI Listing
August 2018

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares.

Spectrochim Acta A Mol Biomol Spectrosc 2018 Jan 10;189:183-189. Epub 2017 Aug 10.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.
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http://dx.doi.org/10.1016/j.saa.2017.08.034DOI Listing
January 2018

Influence of cigarette smoking on osteonecrosis of the femoral head (ONFH): a systematic review and meta-analysis.

Hip Int 2017 Sep 29;27(5):425-435. Epub 2017 May 29.

Department of Orthopaedics, The First Affiliated Hospital of Chongqing Medical University, Chongqing - China.

Background: Current studies demonstrate controversy regarding the relationship between cigarette smoking and osteonecrosis of the femoral head (ONFH).

Methods: We conducted a meta-analysis to evaluate the association between smoking and ONFH. Relevant articles published before September 2016 were identified by a systematic search of EMBASE and MEDLINE via Ovid. Summary odds ratios (OR) were calculated using random effects models, and study quality was assessed using a modified Newcastle-Ottawa scale.

Results: 102 citations were screened and 7 case-control studies were identified and included in the review. When compared with nonsmokers, current smokers had a higher risk of developing ONFH (OR 2.53; 95% confidence interval [CI] 1.68-3.79), as did former smokers (OR 1.82; 95% CI, 1.10-3.00). Within the group of current smokers, those classified as heavy smokers (with a daily number >20 cigarettes/day) demonstrated higher risks of ONFH (OR 2.03; 95% CI, 1.29-3.19), and light smokers classified as smoking <20 cigarettes/day, also demonstrated a higher risk of ONFH when compared with nonsmokers (OR 1.73; 95% CI, 1.06-2.83). When smoking was classified by pack-years, heavy smokers (>20 pack-years) were at a higher risk of ONFH (OR 2.26; 95% CI, 1.24-4.13), but no significant difference in risk was identified in light smokers (<20 pack-years) (OR 1.81; 95% CI, 0.88-3.71) when compared with nonsmokers.

Conclusions: Our meta-analysis showed that current smokers were at a higher risk of ONFH, this high risk can also be found in former smokers. And heavy cigarette smoking showed a higher risk of ONFH than light smoking.
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http://dx.doi.org/10.5301/hipint.5000516DOI Listing
September 2017

Detection of melamine adulteration in milk by near-infrared spectroscopy and one-class partial least squares.

Spectrochim Acta A Mol Biomol Spectrosc 2017 Feb 28;173:832-836. Epub 2016 Oct 28.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

Melamine is a noxious nitrogen-rich substance and has been illegally adulterated in milk to boost the protein content. The present work investigated the feasibility of using near-infrared (NIR) spectrum and one-class partial least squares (OCPLS) for detecting the adulteration of melamine. A total of 102 liquor milks were prepared for experiment. A special variable importance (VI) index was defined to select 40 most significant variables. Thirty-two pure milk samples constitute the training set for constructing a one-class model and the other samples were used for the test set. The results showed that on the independent test set, it can achieve an acceptable performance, i.e., the total accuracy of 89%, the sensitivity of 90%, and the specificity of 88%. It seems that the combination of NIR spectroscopy and OCPLS classifier can serve as a potential tool for rapid and on-site screening melamine in milk samples.
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http://dx.doi.org/10.1016/j.saa.2016.10.051DOI Listing
February 2017

Expression patterns of miR-146a and miR-146b in mastitis infected dairy cattle.

Mol Cell Probes 2016 10 13;30(5):342-344. Epub 2016 Aug 13.

Key Laboratory of Zoology in Hunan Higher Education, College of Life Science, Hunan University of Arts and Science, Changde, Hunan, China.

This study reports a significant up-regulation of bta-miR-146a and bta-miR-146b expression levels in bovine mammary tissues infected with subclinical, clinical and experimental mastitis. Potential target genes are involved in multiple immunological pathways. These results suggest a regulatory function of both miRNAs for the bovine inflammatory response in mammary tissue.
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http://dx.doi.org/10.1016/j.mcp.2016.08.004DOI Listing
October 2016

Continuous wavelet transform-based feature selection applied to near-infrared spectral diagnosis of cancer.

Spectrochim Acta A Mol Biomol Spectrosc 2015 29;151:286-91. Epub 2015 Jun 29.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China. Electronic address:

Spectrum is inherently local in nature since it can be thought of as a signal being composed of various frequency components. Wavelet transform (WT) is a powerful tool that partitions a signal into components with different frequency. The property of multi-resolution enables WT a very effective and natural tool for analyzing spectrum-like signal. In this study, a continuous wavelet transform (CWT)-based variable selection procedure was proposed to search for a set of informative wavelet coefficients for constructing a near-infrared (NIR) spectral diagnosis model of cancer. The CWT provided a fine multi-resolution feature space for selecting best predictors. A measure of discriminating power (DP) was defined to evaluate the coefficients. Partial least squares-discriminant analysis (PLS-DA) was used as the classification algorithm. A NIR spectral dataset associated to cancer diagnosis was used for experiment. The optimal results obtained correspond to the wavelet of db2. It revealed that on condition of having better performance on the training set, the optimal PLS-DA model using only 40 wavelet coefficients in 10 scales achieved the same performance as the one using all the variables in the original space on the test set: an overall accuracy of 93.8%, sensitivity of 92.5% and specificity of 96.3%. It confirms that the CWT-based feature selection coupled with PLS-DA is feasible and effective for constructing models of diagnostic cancer by NIR spectroscopy.
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http://dx.doi.org/10.1016/j.saa.2015.06.109DOI Listing
September 2016

Near-infrared spectroscopy as a diagnostic tool for distinguishing between normal and malignant colorectal tissues.

Biomed Res Int 2015 13;2015:472197. Epub 2015 Jan 13.

Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644000, China.

Cancer diagnosis is one of the most important tasks of biomedical research and has become the main objective of medical investigations. The present paper proposed an analytical strategy for distinguishing between normal and malignant colorectal tissues by combining the use of near-infrared (NIR) spectroscopy with chemometrics. The successive projection algorithm-linear discriminant analysis (SPA-LDA) was used to seek a reduced subset of variables/wavenumbers and build a diagnostic model of LDA. For comparison, the partial least squares-discriminant analysis (PLS-DA) based on full-spectrum classification was also used as the reference. Principal component analysis (PCA) was used for a preliminary analysis. A total of 186 spectra from 20 patients with partial colorectal resection were collected and divided into three subsets for training, optimizing, and testing the model. The results showed that, compared to PLS-DA, SPA-LDA provided more parsimonious model using only three wavenumbers/variables (4065, 4173, and 5758 cm(-1)) to achieve the sensitivity of 84.6%, 92.3%, and 92.3% for the training, validation, and test sets, respectively, and the specificity of 100% for each subset. It indicated that the combination of NIR spectroscopy and SPA-LDA algorithm can serve as a potential tool for distinguishing between normal and malignant colorectal tissues.
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http://dx.doi.org/10.1155/2015/472197DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4309295PMC
October 2015

Diagnosis of colorectal cancer by near-infrared optical fiber spectroscopy and random forest.

Spectrochim Acta A Mol Biomol Spectrosc 2015 Jan 10;135:185-91. Epub 2014 Jul 10.

Department of Chemistry and Chemical Engineering and Key Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Yibin, Sichuan 644007, China; Computational Physics Key Laboratory of Sichuan Province, Yibin University, Yibin, Sichuan 644007, China. Electronic address:

Near-infrared (NIR) spectroscopy has such advantages as being noninvasive, fast, relatively inexpensive, and no risk of ionizing radiation. Differences in the NIR signals can reflect many physiological changes, which are in turn associated with such factors as vascularization, cellularity, oxygen consumption, or remodeling. NIR spectral differences between colorectal cancer and healthy tissues were investigated. A Fourier transform NIR spectroscopy instrument equipped with a fiber-optic probe was used to mimic in situ clinical measurements. A total of 186 spectra were collected and then underwent the preprocessing of standard normalize variate (SNV) for removing unwanted background variances. All the specimen and spots used for spectral collection were confirmed staining and examination by an experienced pathologist so as to ensure the representative of the pathology. Principal component analysis (PCA) was used to uncover the possible clustering. Several methods including random forest (RF), partial least squares-discriminant analysis (PLSDA), K-nearest neighbor and classification and regression tree (CART) were used to extract spectral features and to construct the diagnostic models. By comparison, it reveals that, even if no obvious difference of misclassified ratio (MCR) was observed between these models, RF is preferable since it is quicker, more convenient and insensitive to over-fitting. The results indicate that NIR spectroscopy coupled with RF model can serve as a potential tool for discriminating the colorectal cancer tissues from normal ones.
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http://dx.doi.org/10.1016/j.saa.2014.07.005DOI Listing
January 2015

The diagnostics of diabetes mellitus based on ensemble modeling and hair/urine element level analysis.

Comput Biol Med 2014 Jul 28;50:70-5. Epub 2014 Apr 28.

Department of Chemistry and Chemical Engineering and Key Lab of Process Analysis and Control, Yibin University, Yibin, Sichuan, China.

The aim of the present work focuses on exploring the feasibility of analyzing the relationship between diabetes mellitus and several element levels in hair/urine specimens by chemometrics. A dataset involving 211 specimens and eight element concentrations was used. The control group was divided into three age subsets in order to analyze the influence of age. It was found that the most obvious difference was the effect of age on the level of zinc and iron. The decline of iron concentration with age in hair was exactly consistent with the opposite trend in urine. Principal component analysis (PCA) was used as a tool for a preliminary evaluation of the data. Both ensemble and single support vector machine (SVM) algorithms were used as the classification tools. On average, the accuracy, sensitivity and specificity of ensemble SVM models were 99%, 100%, 99% and 97%, 89%, 99% for hair and urine samples, respectively. The findings indicate that hair samples are superior to urine samples. Even so, it can provide more valuable information for prevention, diagnostics, treatment and research of diabetes by simultaneously analyzing the hair and urine samples.
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http://dx.doi.org/10.1016/j.compbiomed.2014.04.012DOI Listing
July 2014

A feasibility study of diagnosing cardiovascular diseases based on blood/urine element analysis and consensus models.

Comput Biol Med 2013 Aug 9;43(7):865-9. Epub 2013 Apr 9.

Hospital, Yibin University, Yibin, Sichuan 644007, China.

The classification of normal and cardiovascular disease groups with consensus models according to metal concentration in blood/urine samples is discussed in this study. The concentrations of nine elements (i.e., chromium, iron, manganese, aluminum, cadmium, copper, zinc, nickel and selenium) were analyzed using three types of chemometric methods including fisher linear discriminant analysis (FLDA), support vector machine (SVM) and decision tree (DTree). Data from 60 healthy individuals and 24 cardiovascular patients were collected and analyzed. Principal component analysis (PCA) was initially used in a preliminary analysis; however, it proved a difficult task to distinguish normal samples from cardiovascular ones using this method. Then, based on the consensus strategy, a series of classifiers were constructed and compared. In terms of three performance indices, i.e., accuracy, sensitivity and specificity, the DTree classifier exhibited the best overall performance, followed by SVM and FLDA is the poorest. In addition, analysis of blood samples was superior to urine samples. In conclusion, the combination of a consensus DTree classifier and elemental analysis of blood samples can serve as an aid for diagnosis of cardiovascular diseases, especially in routine physical examination.
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http://dx.doi.org/10.1016/j.compbiomed.2013.03.012DOI Listing
August 2013

Three novel SNPs in the coding region of PPARγ gene and their associations with meat quality traits in cattle.

Mol Biol Rep 2011 Jan 21;38(1):131-7. Epub 2010 Mar 21.

College of Animal Science and Technology, Northwest A & F University, No. 22 Xinong Road, Yangling, 712100, Shaanxi, People's Republic of China.

The peroxisome proliferator-activated receptor γ (PPARγ) is a nuclear hormone receptor that regulates adipogenesis and many other biological processes. In the present study, we carried out PCR-SSCP and DNA sequencing analyses to examine SNPs in coding region of the PPARγ gene. A total of 660 individuals from five Chinese cattle breeds were genotyped. We identified three SNPs and their associations with meat quality traits were analyzed in 108 Qinchuan cattle. Two missense mutations and one synonymous mutation were found: 200 A>G (genotypes AA, AB and BB) resulting in D7G change, the silent substitution 42895 C>T (genotypes JJ and JI) and 72472 G>T (genotypes CC, DC and DD) producing Q448H change, respectively. The frequencies of PPARγ-A allele were 0.86, 0.83, 0.80, 0.72 and 0.87 for Qinchuan, Nanyang, Jiaxian, Luxi and Xianan populations, respectively. The frequencies of PPARγ-J allele varied from 0.87 to 0.96 in the five populations. In the 72472 G>T locus, the frequencies of PPARγ-C allele were higher than PPARγ-D allele in the five populations, and ranged from 0.58 to 0.82. Least squares analysis revealed that in 42895 C>T locus, there was a significant effect on tenderness in 18-20 months Qinchuan cattle (P<0.01), and in the 72472 G>T locus, animals with the genotype DC had lower mean values than these with genotype CC (P<0.01) for back fat thickness in 18-20 months, and animals with the genotype DD had lower mean values than these with genotypes CC and DC (P<0.01) for water holding capacity in 21-24 months (P<0.01). The SNPs we have identified may contribute to establishing a more efficient selection program for improving of genetic characteristics in indigenous Chinese cattle.
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http://dx.doi.org/10.1007/s11033-010-0086-2DOI Listing
January 2011

A novel polymorphism of GDF5 gene and its association with body measurement traits in Bos taurus and Bos indicus breeds.

Mol Biol Rep 2010 Jan 10;37(1):429-34. Epub 2009 Jul 10.

College of Animal Science and Technology, Northwest A & F University, Shaanxi, People's Republic of China.

Body measurement traits, influenced by genes and environmental factors, play numerous important roles in the value assessment of productivity and economy. Growth differentiate factor 5 (GDF5), involved in the development and maintenance of bone and cartilage, is an important candidate gene for body measurement traits selection through marker-assisted selection (MAS). In this study, based on the PCR-RFLP technology, we discovered and evaluated the potential association of the single nucleotide polymorphism (SNP) (T586C in exon 1) of the bovine GDF5 gene with body measurement traits in 985 Bos taurus breed, 42 Bos indicus breed and 76 Bos indicus x Bos taurus individuals. As the SNP marker, there were the significant effects on the Body length (BL) in the Bos taurus (BT) and Bos indicus x Bos taurus (BMY) populations (P < 0.05). In BT population, animals with the genotype TT had lower mean values for BL and Hip width (HW) than these with the TC and CC genotype (P < 0.01). In BMY population, animals with the genotype TC had lower mean values for BL than these with the genotype CC (P < 0.05). These results suggest that the SNP of the GDF5 gene could be a very useful genetic marker for body measurement traits in the bovine reproduction and breeding.
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http://dx.doi.org/10.1007/s11033-009-9604-5DOI Listing
January 2010

Photocatalytic degradation of commercial phoxim over La-doped TiO2 nanoparticles in aqueous suspension.

Environ Sci Technol 2009 Mar;43(5):1540-5

College of Chemistry and Molecular Science, Wuhan University, Wuhan 430072, PR China.

Photocatalytic degradation of commercial phoxim emulsion in aqueous suspension was investigated by using La-doped mesoporous TiO2 nanoparticles (m-TiO2) as the photocatalyst under UV irradiation. Effects of La-doping level, calcination temperature, and additional amount of the photocatalyst on the photocatalytic degradation efficiency were investigated in detail. Experimental results indicate that 20 mg L(-1) phoxim in 0.5 g L(-1) La/m-TiO2 suspension (the initial pH 4.43) can be decomposed as prolonging the irradiation time. Almost 100% phoxim was decomposed after 4 h irradiation according to the spectrophotometric analyses, whereas the mineralization rate of phoxim just reached ca. 80% as checked by ion chromatography (IC) analyses. The elimination of the organic solvent in the phoxim emulsion as well as the formation and decomposition of some degradation intermediates were observed by high-performance liquid chromatography-mass spectroscopy (HPLC-MS). On the basis of the analysis results on the photocatalytic degradation intermediates, two possible photocatalytic degradation pathways are proposed under the present experimental conditions, which reveal that both the hydrolysis and adsorption of phoxim under UV light irradiation play important roles during the photocatalytic degradation of phoxim.
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http://dx.doi.org/10.1021/es802724qDOI Listing
March 2009

[Effects of granulosa cells treatments and follicular fluid on cleavage rate and blastocyst rate of bovine oocyte after in vitro fertilization and culture].

Fen Zi Xi Bao Sheng Wu Xue Bao 2008 Oct;41(5):393-402

College of Animal Science and Technology, Henan University of Sci-Tech, Luoyang, Henan 471003.

Experiments were conducted to study the effects of granulosa cell (GC), follicular fluid and their interaction on cleavage rate and blastocyst rate of Bovine oocytes following in vitro maturation (IVM), in vitro fertilization (IVF) and in vitro culture (IVC). A total of 2178 oocytes were used for studies on maturation, fertilization and embryo development. The cleavage rate was affected significantly (P < 0.05) by GC, follicular fluid and the interaction of GC and follicular fluid. The blastocyst rate was affected significantly (P < 0.05) by GC, the blastocyst rate wasn't affected significantly by GC, follicular fluid and the interaction of GC and follicular fluid (P > 0.05). Effects of granulosa cell and follicular fluid and their interaction on the cleavage rate and the blastocyst rate in embryo cultured sort order was GC > follicular fluid > interaction of follicular fluid and GC. It was concluded that follicular fluid and granulosa cell monolayer (GCM) adding in TCM199 better support maturation of oocytes and development of embryos in Bovine. There were no differences in the cleavage rate and blastocyst rate, between the groups granulosa cell monolayer and incubating granulosa cell (which were incubated 10 min in incubator before oocytes being transferred) on co-culture system. Granulosa cell monolayer could be replaced by incubating granulosa cell on coculture system on Bovine oocytes IVM, IVF and IVC.
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October 2008
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