Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Equidistant combination wavelength screening and step-by-step phase-out method for the near-infrared spectroscopic analysis of serum urea nitrogen

We applied near-infrared(NIR)spectroscopy with chemometrics for the rapid and reagent-fee analysis of serum urea nitrogen(SUN).The modeling is based on the average effect of multiple sample partitions to achieve parameter selection with stability.A multiparameter optimization platform with Norris derivative filter-partial least squares(Norris-PLS)was developed to select the most suitable mode(d=2,s=33,g=15).Using equidistant combination PLS(EC-PLS)with four parameters(initial wavelength I,number of wavelengths N,number of wavelength gaps G and latent variables LV),we performed wavelength screening after eliminating high-absorption wavebands.The optimal EC-PLS parameters were I=1228 nm,N=26,G=16 and LV=12.The root-mean square error(SEP),correlation coefficient(R_(p))for prediction and ratio of performance-to-deviation(RPD)for validation were 1.03 mmol L^(-1),0.992 and 7.6,respectively.We proposed the wavelength step-by-step phase-out PLS(WSP-PLS)to remove redun-dant wavelengths in the top 100 EC-PLS models with improved prediction performance.The combination of 19 wavelengths was identifed as the optimal model for SUN.The SEP,Rp and RPD in validation were 1.01 mmol L^(-1),0.992 and 7.7,respectively.The prediction effect and wavelength complexity were better than those of EC-PIS.Our results showed that NIR spectroscopy combined with the EC-PLS and WSP-PLS methods enabled the high-precision analysis ofSUN.WSP-PLS is a secondary optimization method that can further optimize any wavelength moc odel obtained through other continuous or discrete strategies to establish a simple and better model.

Near-Infrared Spectroscopy Combined with Partial Least Squares Discriminant Analysis Applied to Identification of Liquor Brands

The identification of liquor brands is very important for food safety. Most of the fake liquors are usually made into the products with the same flavor and alcohol content as regular brand, so the identification for the liquor brands with the same flavor and the same alcohol content is essential. However, it is also difficult because the components of such liquor samples are very similar. Near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was applied to identification of liquor brands with the same flavor and alcohol content. A total of 160 samples of Luzhou Laojiao liquor and 200 samples of non-Luzhou Laojiao liquor with the same flavor and alcohol content were used for identification. Samples of each type were randomly divided into the modeling and validation sets. The modeling samples were further divided into calibration and prediction sets using the Kennard-Stone algorithm to achieve uniformity and representativeness. In the modeling and validation processes based on PLS-DA method, the recognition rates of samples achieved 99.1% and 98.7%, respectively. The results show high prediction performance for the identification of liquor brands, and were obviously better than those obtained from the principal component linear discriminant analysis method. NIR spectroscopy combined with the PLS-DA method provides a quick and effective means of the discriminant analysis of liquor brands, and is also a promising tool for large-scale inspection of liquor food safety.

Discriminant Analysis of Liquor Brands Based on Moving-Window Waveband Screening Using Near-Infrared Spectroscopy

Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.

Visible and Near-Infrared Spectroscopy with Multi-Parameters Optimization of Savitzky-Golay Smoothing Applied to Rapid Analysis of Soil Cr Content of Pearl River Delta

Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters d, p, m and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEPV), relative root mean square error (R-SEPV) and correlation coefficients (RP, V) of prediction were 11.66 mg·kg-1, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.

Classification of hyperspectral images for detection of hepatic carcinoma cells based on spectral-spatial features of nucleus

A distinguishing characteristic of normal and cancer cells is the difference in their nuclear chromatin content and distribution.This difference can be revealed by the transmission spectra of nuclei stained with a pH-sensitive stain.Here,we used hematoxylin-eosin(HE)to stain hepatic carcinoma tissues and obtained spectral-spatial data from their nuclei using hyper-spectral microscopy.The transmission spectra of the nuclei were then used to train a support vector machine(SVM)model for cell classification.Especially,we found that the chromatin distribution in cancer cells is more uniform,because of which the correlation coefficients for the spectra at different points in their nuclei are higher.Consequently,we exploited this feature to improve the SVM model.The sensitivity and specificity for the identification of cancer cells could be increased to 99%and 98%,respectively.We also designed an image-processing method for the extraction of information from cell nuclei to automate the identification process.

Global Optimization of Norris Derivative Filtering with Application for Near-Infrared Analysis of Serum Urea Nitrogen

Near-infrared (NIR) spectroscopy combined with chemometrics methods was applied to the rapid and reagent-free analysis of serum urea nitrogen (SUN). The mul-partitions modeling was performed to achieve parameter stability. A large-scale parameter cyclic and global optimization platform for Norris derivative filter (NDF) of three parameters (the derivative order: d, the number of smoothing points: s and the number of differential gaps: g) was developed with PLS regression. Meantime, the parameters’ adaptive analysis of NDF algorithm was also given, and achieved a significantly better modeling effect than one without spectral pre-processing. After eliminating the interference wavebands of saturated absorption, the modeling performance was further improved. In validation, the root mean square error (SEP), correlation coefficient (RP) for prediction and the ratio of performance to deviation (RPD) were 1.66 mmol?L-1, 0.966 and 4.7, respectively. The results showed that the high-precision analysis of SUN was feasibility based on NIR spectroscopy and Norris-PLS. The global optimization method of NDF is also expected to be applied to other analysis objects.

Rapid Analysis of Soil Copper Content for the Pearl River Delta Based on Near-Infrared Spectroscopy Combined with SG-PLS

Using near-infrared (NIR) spectroscopy combined with an optimal method for Savitzky-Golay (SG) smoothing and partial least squares (PLS) regression, a rapid analysis method was established for copper content in the beach reclamation soil samples from Pearl River Delta in China. A framework with calibration, prediction and validation was established by considering randomness and stability. The parameters were optimized according to the comprehensive index (SEP+) to produce modeling stability. The validation results show that, based on the SG-PLS model in long-NIR region (1100 - 2498 nm) with first-order derivative, fifth degree polynomial, seven smoothing points and six PLS factors, the corresponding root mean square error (SEP), correlation coefficient of prediction (RP) and average relative error (ARE) were 0.31 mg·kg-1, 0.924 and 4.5%, respectively. The result indicates high prediction accuracy. The relevant parameter selection can also provide a reference for designing small and dedicated spectrometer.

Near-Infrared Spectroscopy Combined with Absorbance Upper Optimization Partial Least Squares Applied to Rapid Analysis of Polysaccharide for Proprietary Chinese Medicine Oral Solution

Near-infrared (NIR) spectroscopy was applied to reagent-free quantitative analysis of polysaccharide of a brand product of proprietary Chinese medicine (PCM) oral solution samples. A novel method, called absorbance upper optimization partial least squares (AUO-PLS), was proposed and successfully applied to the wavelength selection. Based on varied partitioning of the calibration and prediction sample sets, the parameter optimization was performed to achieve stability. On the basis of the AUO-PLS method, the selected upper bound of appropriate absorbance was 1.53 and the corresponding wavebands combination was 400 - 1880 & 2088 - 2346 nm. With the use of random validation samples excluded from the modeling process, the root-mean-square error and correlation coefficient of prediction for polysaccharide were 27.09 mg·L-1 and 0.888, respectively. The results indicate that the NIR prediction values are close to those of the measured values. NIR spectroscopy combined with AUO-PLS method provided a promising tool for quantification of the polysaccharide for PCM oral solution and this technique is rapid and simple when compared with conventional methods.

Wavelength Selection for Near-Infrared Spectroscopic Analysis of Teicoplanin

Teicoplanin (TCP) is a multiple drug-resistant lipoglycopeptide antibiotic produced by fermenting Actinoplanes teichomyceticus. In this study, a mixture of TCP with the Tris-HCl buffer (TCP-Tris- HCl) was used to simulate TCP fermentation broth. The reagent-free, rapid and simultaneous quantitative analysis models for TCP and Tris in the TCP-Tris-HCl mixtures were established by near-infrared (NIR) spectroscopy. The equidistant combination partial least squares (EC-PLS) method and the equivalent model sets were proposed, the simplest equivalent model with the smallest number of wavelengths were further selected. The initial wavelength, number of wavelengths, number of wavelength gaps, number of PLS factors were 1520 nm, 28, 5, 5 for TCP and 1084 nm, 13, 6, 4 for Tris, respectively. Compared with the optimal EC-PLS models, the simplest equivalent models adopted fewer wavelengths. Thus, the redundant wavelengths were removed, the models were further simplified. The root-mean-square errors (SEP) and correlation coefficients (RP) for prediction were 0.043 mg·mL-1 and 0.9998 for TCP, and 0.222 mg·mL-1 and 0.9989 for Tris, respectively. The results indicate that NIR method can be applied to highly accurate quantitative analysis for TCP and provide valuable references for further application to TCP fermentation broth.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.

Semi-quantitative analysis on the content of berberine hydrochloride in compound berberine tablets with the fluorescence spectral imaging method

The content of berberine hydrochloride(BH)in compound berberine tablets(CBTs)is subject to strict requirements.Its content is usually measured based on chemical analysis.In this paper,the fluorescence spectral imaging method was used to study the relative content of BH from a physics perspective.By comparing the relative fluorescence intensity of self-made CBTs with di®erent mass percentages of BH,a linear positive relationship was observed between the BH content and the relative fluorescence intensity,and accordingly the quality of CBTs of different brands was evaluated.The results indicate that the fluorescence spectral imaging method can be a simple,fast and nondestructive semi-quantitative analysis method to determine the content of BH in CBTs,and this method has great potential in the quality control of CBTs.

Dephasing of quantum tunnelling in molecular nanomagnets

Dephasing mechanism of quantum tunnelling in molecular magnets has been studied by means of the spin-coherentstate path integral in a mean field approximation. It is found that the fluctuating uncompensated transverse field from the dipolar-dipolar interaction between molecular magnets contributes a random phase to the quantum interference phase. The resulting transition rate is determined by the average tunnel splitting over the random phase. Such a dephasing process leads to the suppression of quenching due to the quantum phase interference, and to the steps due to odd resonances in hysteresis loop survived, which is in good agreement with experimental observations in molecular nanomagnets Fes and Mn12.

Spectral Correction Method of Multi-Channels Near-Infrared Spectrometer and Applications

Near-infrared (NIR) spectrometer based on semiconductor lasers can combine light source and splitter into one, which is an important direction for development of miniature instruments. In order to avoid random interference caused by inconsistency between light sources, the novel evaluation indicators for global stability of multi-channels spectral system were proposed based on the correlation between dynamic deviation spectra of any two channels. The NIR analysis of moisture for corn powder samples based on the partial least squares combined with Savitzky-Golay (SG) smoothing was taken as an example, and a spectral correction method for enhancing prediction performance of multi-channels spectral system was further provided using above evaluation indicators. The experiment results showed that the global stability evaluation indicators significantly increased after SG smoothing correction. Meanwhile, the root-mean-square errors of prediction for corn moisture reduced from 0.373 to 0.283 (%), and the correlation coefficient between predicted and actual values was improved from 0.702 to 0.855. The above results indicated that by improving global stability indicators, the prediction ability of multi-channels spectral system can be improved. The proposed method provided a valuable reference for designing multi-channels diminutive spectrometer with high prediction performance, which had significance for large-scale application of NIR technology.

AO-MW-PLS method applied to rapid quantification of teicoplanin with near-infrared spectroscopy

Teicoplanin(TCP)is an important lipoglycopeptide antibiotic produced by fermenting Acti-noplanes teichomyceticus.The change in TCP concentration is important to measure in the fermentation process.In this study,a reagent-free and rapid quantification method for TCP in the TCP-Tris-HCl mixture samples was developed using near infrared(NIR)spectroscopy by focusing our attention on the fermentation process for TCP.The absorbance optimization(AO)partial least squares(PLS)was proposed and integrated with the moving window(MW)PLS,which is called AO-MW-PLS method,to select appropriate wavebands.Amodel set that includes various wavebands that were equivalent to the optimal AO-MW-PLS waveband was,proposed based on statistical considerations.The public region of all equivalent wavebands was just one of the equivalent wavebands.The obtained public regions were 1540-1868 nm for TCP and 1114-1310 nm for Tris.The root-mean-square error and correlation coeficient for leave-one-out cross validation were 0.046 mg mL^(-1)and 0.9998 mg mL^(-1)for TCP,and 0.235 mg mL^(-1)and 0.9986 mg mL^(-1)for Tris,respectively.All the models achieved highly accurate prediction effects,and the selected wavebands provided valuable references for designing specialized spectrometers.This study provided a valuable reference for further application of the proposed methods to TCP fermentation broth and to other spectroscopic analysis fields.

Global Solution of a Nonlinear Conservation Law with Weak Discontinuous Flux in the Half Space

This paper is concerned with the initial-boundary value problem of a nonlinear conservation law in the half space R+= {x |x > 0} where a>0 , u(x,t) is an unknown function of x ∈ R+ and t>0 , u ± , um are three given constants satisfying um=u+≠u- or um=u-≠u+ , and the flux function f is a given continuous function with a weak discontinuous point ud. The main purpose of our present manuscript is devoted to studying the structure of the global weak entropy solution for the above initial-boundary value problem under the condition of f '-(ud) > f '+(ud). By the characteristic method and the truncation method, we construct the global weak entropy solution of this initial-boundary value problem, and investigate the interaction of elementary waves with the boundary and the boundary behavior of the weak entropy solution.

Construction of Global Weak Entropy Solution of Initial-Boundary Value Problem for Scalar Conservation Laws with Weak Discontinuous Flux

This paper is concerned with the initial-boundary value problem of scalar conservation laws with weak discontinuous flux, whose initial data are a function with two pieces of constant and whose boundary data are a constant function. Under the condition that the flux function has a finite number of weak discontinuous points, by using the structure of weak entropy solution of the corresponding initial value problem and the boundary entropy condition developed by Bardos-Leroux-Nedelec, we give a construction method to the global weak entropy solution for this initial-boundary value problem, and by investigating the interaction of elementary waves and the boundary, we clarify the geometric structure and the behavior of boundary for the weak entropy solution.

Application of Portable Near-Infrared Spectrometer for Analysis of Organic Carbon in Marine Sediments

The performance of a portable near-infrared (NIR) spectrometer to determine organic carbon (OC) in marine sediments was evaluated. The NIR reflection spectra of 180 samples in the range 950 - 1650 nm were acquired using an ultra-compact spectrometer. NIR spectroscopy combined with the partial least squares (PLS) regression and Savitzky-Golay (SG) smoothing was successfully applied to rapid and reagent-free determination of OC. Using the PLS-SG model with 1nd order derivative, 2th polynomial and eleven smoothing points, the root-mean-square errors (RMSEPM) and correlation coefficients (RP,M) of prediction for modeling were 0.073% and 0.894, respectively, the root-mean-square errors (RMSEPV) and correlation coefficients (RP,V) of prediction for validation were 0.075% and 0.883, respectively. Results showed that the small portable NIR instrument achieved well prediction effect for the analysis of OC in marine sediments, which had advantages of rapid, easy to carry and operate suitable for large-scale applications to analyze marine sediments.

Multispectral Imaging for Authenticity Identification and Quality Evaluation of <i>Flos carthami</i>

The identification and quality evaluation of Flos carthami were studied using tunable liquid spectral imaging instrument, to discuss the application range and advantages of spectral imaging technology in Chinese medicine identification and quality control field. The Flos carthami was indentified by extracting the normalized characteristic spectral curves of Flos carthami, Crocus sativus and Dendranthema morifolium, which were standard samples supplied by National Institute for Drug Control. The qualities of Flos carthamies collecting from different pharmacies were evaluated by extracting their normalized characteristic spectral curves. The imaging spectrum testing system was designed independently. The spectral resolution was 5 nm, and the spectral range was from 400 nm to 680 nm. The results showed that the normalized characteristic spectral curve of Flos carthami was significantly different from those of Crocus sativus’ and Dendranthema morifolium’s, and the fluorescence intensity of Flos carthami from different commercial sources were different. Spectral imaging technology could be used to identify and evaluate Flos carthami, and operation method was rapid, convenient and non-destructive.

Application of Multispectral Imaging Method in Rapid Identification and Analysis of Chinese Herbal Medicine Powders

Five kinds of traditional flower Chinese medicine powders (TFCMD) were identified using tuneable liquid spectral imaging instrument, to discuss the application range and advantages of spectral imaging technology in Chinese medicine identification and analysis field. The testing system is the liquid crystal multispectral imaging system designed by ourselves. All the tests are standard samples supplied by National Institute for Drug Control. The spectral cubes of Campsis grandiflora, Carthamus tinctorius, Albizzia julibrissin, Dendranthema morifolium, and Dendranthema indicum were captured, and then the normalized characteristic spectral curves of them were picked up. The spectral resolution is 5 nm, and the spectral range is 400 nm - 650 nm. The result shows that different TFCMD has different normalized characteristic fluorescence spectral curve. Spectral imaging technology can be used to identify TFCMD, and the testing course is convenient, quick, noninvasive and without pre-treatment.