Bridging the gap between measurement-based and simulation-based metamodels for deriving bulk optical properties from spatially-resolved reflectance profiles: effect of illumination and detection geometry.

Non-invasive determination of the optical properties is essential for understanding the light propagation in biological tissues and developing optical techniques for quality detection. Simulation-based models provide flexibility in designing the search space, while measurement-based models can incorporate the unknown system responses. However, the interoperability between these two types of models is typically poor. In this research, the mismatches between measurements and simulations were explored by studying the influences from light source and the incident and detection angle on the diffuse reflectance profiles. After reducing the mismatches caused by the factors mentioned above, the simulated diffuse reflectance profiles matched well with the measurements, with R2 values above 0.99. Successively, metamodels linking the optical properties with the diffuse reflectance profiles were respectively built based on the measured and simulated profiles. The prediction performance of these metamodels was comparable, both obtaining R2 values above 0.96. Proper correction for these sources of mismatches between measurements and simulations thus allows to build a simulation-based metamodel with a wide range of desired optical properties that is applicable to different measurement configurations.

[Detection of Lead Chrome Green Illegally Added in Tea Based on Confocal Raman Spectroscopy].

In this paper, confocal Raman spectroscopy was applied to detect the contents of lead chrome green as a heavy-metal stain illegally added in tea. Firstly, Raman spectra of five different concentrations of lead chrome green in tea infusion were acquired based on specific concentration method. The qualitative analysis of sample added with lead chrome green was achieved with comparing the Raman spectra of sample and standard substance. Four main Raman characteristic wavenumbers, 1 341, 1 451, 1 527 and 1 593 cm(-1), were extracted for the qualitative identification of lead chrome green in tea. After spectral preprocessing of the raw Raman spectra, backward interval PLS (biPLS), competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were combined to deeply mine the characteristic wavenumbers of lead chrome green in Raman spectra, and finally 14 characteristic wavenumbers were optimized. Partial least squares (PLS) and least square support vector machine (LS-SVM) were separately used to build the model based on the extracted 14 wavenumbers. As a result, these two models both had good robustness and high ability to predict and all the determination coefficient (R(2)) of calibration, validation and prediction were higher than 0.9, which proved the effectiveness of the extracted characteristic wavenumbers. Compared with the PLS model, the nonlinear model built by LS-SVM got a better result, R(2) of prediction was 0.964 and the root mean square error of prediction (RMSEP) was 0.535. This study indicated that it is feasible to detect the contents of lead chrome green illegally added in tea based on confocal Raman spectroscopy combined with specific sample treatment and chemometrics methods. This study helped the valid supervision of food safety problem on lead chrome green illegally added in tea.

[In Vivo Study of Chitin in Fungal Hyphae Based on Confocal Raman Microscopy].

Chitin is an important structural polysaccharide of fungal cell wall. In this paper, aerial hyphae of Colletotrichum camelliae Massee was first studied by confocal Raman microscopy in vivo. Firstly, the optimal experimental parameters of hyphae for collecting the Raman spectra were determined, and the typical Raman spectra of hyphae, chitin standard and background were acquired. By comparing analysis, characteristic peaks of chitin were found in hyphae. Then, a region of interesting on hyphae was selected for Raman scanning. Through principal component analysis, the Raman signal of hyphae and background in the scanning area can be separated clearly. Combined with loading weight plot, two main characteristic peaks of hyphae were obtained, 1 622 cm(-1) was belong to chitin and 1 368 cm(-1) was assigned to pectic polysaccharide. Finally, two and three dimension chemical images of fungal hyphae were realized based on Raman fingerprint spectra of chitin in a nondestructive way.

Dynamic Nondestructive Detection Models of Apple Quality in Critical Harvest Period Based on Near-Infrared Spectroscopy and Intelligent Algorithms.

Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.

Early bruising detection of 'Korla' pears by low-cost visible-LED structured-illumination reflectance imaging and feature-based classification models.

Introduction: Nondestructive detection of thin-skinned fruit bruising is one of the main challenges in the automated grading of post-harvest fruit. The structured-illumination reflectance imaging (SIRI) is an emerging optical technique with the potential for detection of bruises. Methods: This study presented the pioneering application of low-cost visible-LED SIRI for detecting early subcutaneous bruises in 'Korla' pears. Three types of bruising degrees (mild, moderate and severe) and ten sets of spatial frequencies (50, 100, 150, 200, 250, 300, 350, 400, 450 and 500 cycles m-1) were analyzed. By evaluation of contrast index (CI) values, 150 cycles m-1 was determined as the optimal spatial frequency. The sinusoidal pattern images were demodulated to get the DC, AC, and RT images without any stripe information. Based on AC and RT images, texture features were extracted and the LS-SVM, PLS-DA and KNN classification models combined the optimized features were developed for the detection of 'Korla' pears with varying degrees of bruising. Results and discussion: It was found that RT images consistently outperformed AC images regardless of type of model, and LS-SVM model exhibited the highest detection accuracy and stability. Across mild, moderate, severe and mixed bruises, the LS-SVM model with RT images achieved classification accuracies of 98.6%, 98.9%, 98.5%, and 98.8%, respectively. This study showed that visible-LED SIRI technique could effectively detect early bruising of 'Korla' pears, providing a valuable reference for using low-cost visible LED SIRI to detect fruit damage.

Transgelin promotes lung cancer progression via activation of cancer-associated fibroblasts with enhanced IL-6 release.

Cancer-associated fibroblasts (CAFs), the principal constituent of the heterogenous tumor microenvironment, have been shown to promote tumor progression; however, the underlying mechanism is still less clear. Here, we find that transgelin (TAGLN) protein levels increased in primary CAFs isolated from human lung cancer, compared with those in paired normal fibroblasts. Tumor microarrays (TMAs) revealed that increased stromal TAGLN levels correlates with more lymphatic metastasis of tumor cells. In a subcutaneous tumor transplantation model, overexpression of Tagln in fibroblasts also increased tumor cell spread in mice. Further experiments show that Tagln overexpression promoted fibroblast activation and mobility in vitro. And TAGLN facilitates p-p65 entry into the nucleus, thereby activating the NF-κB signaling pathway in fibroblasts. Activated fibroblasts promote lung cancer progression via enhancing the release of pro-inflammatory cytokines, especially interleukine-6 (IL-6). Our study revealed that the high levels of stromal TAGLN is a predictive risk factor for patients with lung cancer. Targeting stromal TAGLN may present an alternative therapeutic strategy against lung cancer progression.

A feasibility study on nondestructive classification of frozen Atlantic salmon (Salmo salar) fillets based on temperature history at the logistics using NIR spectroscopy.

Temperature fluctuation commonly occurs in the cold chain leading to complete or partial thawing and refreezing of frozen products resulting in a multifrozen product. Such oscillation of temperature could cause significant quality reduction compared to single frozen products. This study was designed to differentiate frozen Atlantic salmon fillets based on the level of temperature fluctuation. Near-infrared spectroscopy (NIRS) coupled with chemometrics was used to classify the frozen fillets stored at no fluctuation (NF), low fluctuation (LF), high fluctuation (HF), and very high fluctuation (VF) temperature. Using spectral profiles obtained at both frozen and thawed states, fillets were classified based on the level of temperature fluctuation by partial least squares discriminant analysis (PLS-DA). The thawed samples showed better classification accuracy (71%) than frozen samples (66%) in a four-class model. Considering the small variation within the first two (NF, LF) and the last two (HF, VF) groups, a two-class classification model was developed using thawed samples, and the obtained model correctly classified the two groups ([NF, LF] and [HF, VF]) with 100 % classification accuracy. Protein- and water-related changes were found important to distinguish the fillets. Based on these findings, the four-class prediction model is found insufficient to be used for nondestructive determination of temperature history of frozen fillets. However, the two-class prediction model with further external validation can be applied to determine the level of temperature fluctuation particularly using fillets scanned at thawed state. PRACTICAL APPLICATION: NIR spectroscopy can be used to evaluate the degree of temperature fluctuation and thus related quality loss throughout the logistics of frozen Atlantic salmon fillets. Researchers, food control authorities, and the retail industry could be the primary beneficiaries of this research output.

ZIP1+ fibroblasts protect lung cancer against chemotherapy via connexin-43 mediated intercellular Zn2+ transfer.

Tumour-stroma cell interactions impact cancer progression and therapy responses. Intercellular communication between fibroblasts and cancer cells using various soluble mediators has often been reported. In this study, we find that a zinc-transporter (ZIP1) positive tumour-associated fibroblast subset is enriched after chemotherapy and directly interconnects lung cancer cells with gap junctions. Using single-cell RNA sequencing, we identify several fibroblast subpopulations, among which Zip1+ fibroblasts are highly enriched in mouse lung tumours after doxorubicin treatment. ZIP1 expression on fibroblasts enhances gap junction formation in cancer cells by upregulating connexin-43. Acting as a Zn2+ reservoir, ZIP1+ fibroblasts absorb and transfer Zn2+ to cancer cells, leading to ABCB1-mediated chemoresistance. Clinically, ZIP1high stromal fibroblasts are also associated with chemoresistance in human lung cancers. Taken together, our results reveal a mechanism by which fibroblasts interact directly with tumour cells via gap junctions and contribute to chemoresistance in lung cancer.

Metabolic reprogramming of cancer-associated fibroblasts and its effect on cancer cell reprogramming.

Cancer cells are well-known for adapting their metabolism to maintain high proliferation rates and survive in unfavorable environments with low oxygen and nutritional deficiency. Metabolic reprogramming most commonly arises from the tumor microenvironment (TME). The events of metabolic pathways include the Warburg effect, shift in Krebs cycle metabolites, and increase rate of oxidative phosphorylation that provides the energy for the development and invasion of cancer cells. The TME and shift in tumor metabolism shows a close relationship through bidirectional signaling pathways between the stromal and tumor cells. Cancer-associated fibroblasts (CAFs) are the main type of stromal cells in the TME and consist of a heterogeneous and plastic population that play key roles in tumor growth and metastatic capacity. Emerging evidence suggests that CAFs act as major regulators in shaping tumor metabolism especially through the dysregulation of several metabolic pathways, including glucose, amino acid, and lipid metabolism. The arrangement of these metabolic switches is believed to shape distinct CAF behavior and change tumor cell behavior by the CAFs. The crosstalk between cancer cells and CAFs is associated with cell metabolic reprogramming that contributes to cancer cell growth, progression, and evasion from cancer therapies. But the mechanism and process of this interaction remain unclear. This review aimed to highlight the metabolic couplings between tumor cells and CAFs. We reviewed the recent literature supporting an important role of CAFs in the regulation of cancer cell metabolism, and the relevant pathways, which may serve as targets for therapeutic interventions.

Simultaneous determination of six main types of lipid-soluble pigments in green tea by visible and near-infrared spectroscopy.

Lipid-soluble pigments make great contributions to the color of green tea. This study aimed to rapidly and simultaneously measure six main types of lipid-soluble pigments in green tea by using the visible and near-infrared (Vis-NIR) spectroscopy. A total of 135 tea samples with five kinds and three grades were collected for spectral scanning and color measurement, and their lipid-soluble pigments contents were measured by high performance liquid chromatography. It can be found that tea color was closely related to the six pigments. And there were significant differences in lipid-soluble pigments contents among these kinds and grades. Finally, quantitative determination models of the six pigments obtained excellent results with Rp2 of 0.975, 0.973, 0.993, 0.919, 0.962 and 0.965 respectively based on multiple linear regression with the characteristic wavelengths. These results demonstrated that the Vis-NIR spectroscopy combined with chemometrics is a powerful tool for rapid determination of lipid-soluble pigments in green tea.

Aspirin, a Potential GLUT1 Inhibitor in a Vascular Endothelial Cell Line.

Recent epidemiological and preclinical studies have revealed that aspirin possesses antitumor properties; one of the mechanisms results from inhibition of angiogenesis. However, the underlying mechanisms of such action remain to be elucidated, in particular, the effect of aspirin on glucose metabolism of vascular endothelial cells (ECs) has not yet been reported. Herein, we demonstrate that glucose transporter 1 (GLUT1), a main glucose transporter in ECs, can be down-regulated by aspirin. Exposure to 4-mM aspirin significantly decreased GLUT1 at the mRNA and protein level, resulting in impaired glucose uptake capacity in vascular ECs. In addition, we also showed that exposure to 4-mM aspirin led to an inhibition of intracellular ATP and lactate synthesis in vascular ECs, and a down-regulation of the phosphorylation level of NF-κB p65 was observed. Taken together, these findings indicate 4-mM aspirin inhibits glucose uptake and glucose metabolism of vascular ECs through down-regulating GLUT1 expression and suggest that GLUT1 has potential to be a target for aspirin in vascular ECs.

Optical Determination of Lead Chrome Green in Green Tea by Fourier Transform Infrared (FT-IR) Transmission Spectroscopy.

The potential of Fourier transform infrared (FT-IR) transmission spectroscopy for determination of lead chrome green in green tea was investigated based on chemometric methods. Firstly, the qualitative analysis of lead chrome green in tea was performed based on partial least squares discriminant analysis (PLS-DA), and the correct rate of classification was 100%. And then, a hybrid method of interval partial least squares (iPLS) regression and successive projections algorithm (SPA) was proposed to select characteristic wavenumbers for the quantitative analysis of lead chrome green in green tea, and 19 wavenumbers were obtained finally. Among these wavenumbers, 1384 (C = C), 1456, 1438, 1419(C = N), and 1506 (CNH) cm-1 were the characteristic wavenumbers of lead chrome green. Then, these 19 wavenumbers were used to build determination models. The best model was achieved by least squares support vector machine (LS-SVM)algorithm with high coefficient of determination and low root-mean square error of prediction set (R2p = 0.864 and RMSEP = 0.291). All these results indicated the feasibility of IR spectra for detecting lead chrome green in green tea.

Determination of Hemicellulose, Cellulose and Lignin in Moso Bamboo by Near Infrared Spectroscopy.

The contents of hemicellulose, cellulose and lignin are important for moso bamboo processing in biomass energy industry. The feasibility of using near infrared (NIR) spectroscopy for rapid determination of hemicellulose, cellulose and lignin was investigated in this study. Initially, the linear relationship between bamboo components and their NIR spectroscopy was established. Subsequently, successive projections algorithm (SPA) was used to detect characteristic wavelengths for establishing the convenient models. For hemicellulose, cellulose and lignin, 22, 22 and 20 characteristic wavelengths were obtained, respectively. Nonlinear determination models were subsequently built by an artificial neural network (ANN) and a least-squares support vector machine (LS-SVM) based on characteristic wavelengths. The LS-SVM models for predicting hemicellulose, cellulose and lignin all obtained excellent results with high determination coefficients of 0.921, 0.909 and 0.892 respectively. These results demonstrated that NIR spectroscopy combined with SPA-LS-SVM is a useful, nondestructive tool for the determinations of hemicellulose, cellulose and lignin in moso bamboo.

Nondestructive detection of lead chrome green in tea by Raman spectroscopy.

Raman spectroscopy was first adopted for rapid detecting a hazardous substance of lead chrome green in tea, which was illegally added to tea to disguise as high-quality. 160 samples of tea infusion with different concentrations of lead chrome green were prepared for Raman spectra acquirement in the range of 2804 cm(-1)-230 cm(-1) and the spectral intensities were calibrated with relative intensity standards. Then wavelet transformation (WT) was adopted to extract information in different time and frequency domains from Raman spectra, and the low-frequency approximation signal (ca4) was proved as the most important information for establishment of lead chrome green measurement model, and the corresponding partial least squares (PLS) regression model obtained good performance in prediction with Rp and RMSEP of 0.936 and 0.803, respectively. To further explore the important wavenumbers closely related to lead chrome green, successive projections algorithm (SPA) was proposed. Finally, 8 characteristic wavenumbers closely related to lead chrome green were obtained and a more convenient and fast model was also developed. These results proved the feasibility of Raman spectroscopy for nondestructive detection of lead chrome green in tea quality control.