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

Targeted FT-NIR and SERS Detection of Breast Cancer HER-II Biomarkers in Blood Serum Using PCB-Based Plasmonic Active Nanostructured Thin Film Label-Free Immunosensor Immobilized with Directional GNU-Conjugated Antibody

This work describes our recent PCB-based plasmonic nanostructured platform patent (US 11,828,747B2) for the detection of biomarkers in breast cancer serum (BCS). A 50 nm thin gold film (TGF) was immersion-coated on PCB (i.e., PCB-TGF) and immobilized covalently with gold nanourchin (GNU) via a 1,6-Hexanedithiol (HDT) linkage to produce a plasmonic activated nanostructured thin film (PANTF) platform. A label-free SERS immunosensor was fabricated by conjugating the platform with monoclonal HER-II antibodies (mAb) in a directional orientation via adipic acid dihydrazide (ADH) to provide higher accessibility to overexpressed HER-II biomarkers (i.e., 2+ (early), 3+ (locally advanced), and positive (meta) in BCS. An enhancement factor (EF) of 0.3 × 105 was achieved for PANTF using Rhodamine (R6G), and the morphology was studied by scanning electron microscopy (SEM) and atomic force microscope (AFM). UV-vis spectroscopy showed the peaks at 222, 231, and 213 nm corresponding to ADH, mAb, and HER-II biomarkers, respectively. The functionalization and conjugation were investigated by Fourier Transform Near Infrared (FT-NIR) where the most dominant overlapped spectra of 2+, 3+, and Pos correspond to OH-combination of carbohydrate, RNH2 1st overtone, and aromatic CH 1st overtone of mAb, respectively. SERS data were filtered using the filtfilt filter from scipy.signals, baseline corrected using the Improved Asymmetric Least Squares (isals) function from the pybaselines.Whittaker library. The results showed the common peaks at 867, 1312, 2894, 3026, and 3258 cm-1 corresponding to glycine, alanine ν (C-N-C) assigned to the symmetric C-N-C stretch mode; tryptophan and α helix; C-H antisymmetric and symmetric stretching; NH3+ in amino acids; and N-H stretch primary amide, respectively, with the intensity of Pos > 3+ > 2+. This trend is justifiable considering the stage of each sample. Principal Component Analysis (PCA) and Linear Discrimination Analysis (LDA) were employed for the statistical analysis of data.

Non-invasive optical characterization and detection of CA 15-3 breast cancer biomarker in blood serum using monoclonal antibody-conjugated gold nanourchin and surface-enhanced Raman scattering

A proof-of-concept of colloidal surface-enhanced Raman scattering (SERS) substrate for rapid selective detection of overexpressed CA 15-3 biomarker in breast cancer serum (BCS) is suggested using PEGylated gold nanourchins (GNUs) conjugated with anti-CA 15-3 monoclonal antibody (mAb). UV-vis spectroscopy provided conformational information about mAb where the initial aromatic amino acid peak was red-shifted from 271 to 291 nm. The fluorescence peak of tyrosine in mAb was reduced by ≈ 77%, and red-shifted by ≈ 3 nm after incubation in BCS. Fourier transform near-infrared spectroscopy and SERS were used to study the composition and the molecular structure of the mAb and BCS. Some of the most dominant Raman shifts after GNU-PEG-mAb interaction with BCS are 498, 736, 818, 1397, 1484, 2028, 2271, and 3227 cm-1 mainly corresponding to C-N-C in amines, vibrational modes of amino acids, C-H out-of-plane bend, C-O stretching carboxylic acid, the vibrational mode in phospholipids, NH3+ amine salt, C≡N stretching in nitriles, and O-H stretching. The intensity of SERS signals varied per trial due to the statistical behavior of GNU in BCS, agglomeration, laser power, and the heating effect. Despite very small amount of plasmonic heating, the result of the ANOVA test demonstrated that under our experimental conditions, the heating effect on signal variation is negligible and that the differences in the laser power are insignificant for all SERS observations (p > 0.6); thus, other parameters are responsible. The absorbance of mAb-conjugated GNU was decreased after five minutes of irradiation at 8 mW in the BCS.

Extraction of a Triterpene Solution and Evaluation of the Hypolipidemic Efficacy of the Pleurotus tuber-regium (Fr.) Sing Sclerotium

The total triterpenes in edible mushrooms have high medicinal value, and the sclerotium has various biological activities, such as the regulation of blood pressure and blood glucose. In this study, the total triterpenes of the Pleurotus tuber-regium (Fr.) Sing Sclerotium (PTRSS) were extracted, and their hypolipidemic effects were also investigated. The infrared spectra showed that the total triterpenes were consistent with the characteristic structures of the total triterpenes before and after purification. The binding abilities of total triterpenes to sodium glycocholate, sodium taurocholate, and sodium cholate were investigated, and all of them had a good binding ability to cholate. In vivo experiments showed that zebrafish tolerated the total triterpenes from the mushroom nuclei at a maximum concentration of 500 µg/mL. A correlation analysis showed that the total triterpenes from the mushroom nuclei reduced the lipid accumulation in zebrafish induced by a high-fat diet, and the lipid-lowering effect showed a correlation with dose.

Emerging Nanotheranostics for 5-Fluorouracil in Cancer Therapy: A Systematic Review on Efficacy, Safety, and Diagnostic Capability

The conventional concept of using nanocarriers to deliver chemotherapeutic drugs has advanced to accommodate additional diagnostic capability. Nanotheranostic agents (NTA), combining both treatment and diagnostic tools, are an ideal example of engineering-health integration for cancer management. Owing to the diverse materials used to construct NTAs, their safety, effectiveness, and diagnostic accuracy could vary substantially. This systematic review consolidated current NTAs incorporating 5-fluorouracil and elucidated their toxicity, anticancer efficacy, and imaging capability. Medline and Embase databases were searched up to March 18, 2022. The search, selection, and extraction were performed by the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines to ensure completeness and reproducibility. Original research papers involving 5-fluorouracil in the preparation of nanoparticles which reported their efficacy, toxicity, and diagnostic capability in animal cancer models were recruited. The quality of included studies was assessed using the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies (CAMARADES) checklist. Nine studies were eligible for the systematic review. There was no significant toxicity reported based on animal weight and organ histology. Complete tumor remission was observed in several animal models using chemo-thermal ablation with NTAs, proving the enhancement of 5-fluorouracil efficacy. In terms of imaging performance, the time to achieve maximum tumor image intensity correlates with the presence of targeting ligand on NTAs. The NTAs, which are composed of tumor-targeting ligands, hold promises for further development. Based on the input of current NTA research on cancer, this review proposed a checklist of parameters to recommend researchers for their future NTA testing, especially in animal cancer studies. Systematic Review Registration: website, identifier registration number.

Effectiveness of near-infrared spectroscopy as a non-invasive tool to discriminate spectral profiles of in vitro cultured oocytes from goats

Here, we aimed to discriminate between the spectral profiles of spent culture media after oocyte in vitro maturation (IVM) and culture (IVC) from goats of different ages subjected to repeated hormonal treatments. The profiles were discriminated using near infrared (NIR) spectroscopy combined with multivariate methods. A total of 19 goats (young = 10; old = 9) were subjected to serial hormonal stimulation (HS) with gonadotropins. Cumulus oophorus complexes (COCs) were collected using laparoscopic ovum pick-up (LOPU) and subjected to IVM and parthenogenetic activation. The initial embryos were subjected to IVC. Spent culture media were collected after oocyte IVM and on day 2 of IVC and analyzed using NIR spectroscopy. NIR spectral data were interpreted through chemometric methods, such as principle component analysis (PCA) and partial least square discriminant analysis (PLS-DA). The results of PCA analysis clearly showed a separation in the spectral profiles between the experimental groups (HS sessions; young and old animals) both after IVM and IVC. Overall, the main absorption bands were attributed to the C-H group second overtone, first overtone of O-H and N-H, and C-H combinations and may serve as molecular markers. On the other hand, the spectral data obtained using PLS-DA models provided a better classification of the groups. The results showed the possibility of discriminating young and old groups as well as the three HS sessions with high specificity, sensitivity, and accuracy using NIR spectra. Thus, the culture medium analysis using NIR spectroscopy combined with multivariate methods indicated the dissimilarities between the groups and provided an insight into the in vitro development of goat oocytes. This technique serves as an efficient, objective, rapid, and non-invasive method to discriminate spectral profiles.

Machine learning applied to near-infrared spectra for clinical pleural effusion classification

Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method based on FTIR near-infrared spectroscopy (NIRS) combined with machine learning strategy for clinical pleural effusion classification. NIRS spectra were recorded for 47 MPE samples and 35 BPE samples. The sample data were randomly divided into train set (n = 62) and test set (n = 20). Partial least squares, random forest, support vector machine (SVM), and gradient boosting machine models were trained, and subsequent predictive performance were predicted on the test set. Besides the whole spectra used in modeling, selected features using SVM recursive feature elimination algorithm were also investigated in modeling. Among those models, NIRS combined with SVM showed the best predictive performance (accuracy: 1.0, kappa: 1.0, and AUC_ROC: 1.0). SVM with the top 50 feature wavenumbers also displayed a high predictive performance (accuracy: 0.95, kappa: 0.89, AUC_ROC: 0.99). Our study revealed that the combination of NIRS and machine learning is an innovative, rapid, and convenient method for clinical pleural effusion classification, and worth further evaluation.

Preliminary Study on the Identification of BRAFV600E Mutation in Colorectal Cancer by Near-Infrared Spectroscopy

Introduction

In metastatic colorectal cancer (mCRC), the B-type Raf kinase (BRAF)^V600E mutation is a molecular biomarker of poor prognosis and is of great importance to drug target. Currently, the commonly used methods for detecting BRAF^V600E mutation include immunohistochemistry (IHC) and gene sequencing, but both present certain limitations. Near-infrared (NIR) spectroscopy is a spectroscopy technology that takes advantage of the electromagnetic wavelength between visible light and mid-infrared light.

Methods

IHC was used to detect the expression of BRAF^V600E protein with the BRAF^V600E (VE1) antibody in 42 cases of paraffin-embedded (FFPE) mCRC tissue sections. The NIR-discriminant analysis model (NIRS-DA) was established using 6 cases of wild-type and 6 cases of mutant-type BRAF specimens.

Results

IHC detection results revealed 13 cases of weakly positive (+), 1 case of moderately positive (++), and 28 cases of negative (-) CRC. Compared with the next-generation sequencing (NGS) results, the positive rate was 66.7%. The classification accuracy of calibration (CAC) was 100% compared with the results of NGS, demonstrating that the BRAF^V600E mutant NIRS-DA model, verified by 2 cases of wild-type and 2 cases of mutant-type CRC samples was established. The NIRS-DA model was used to predict gene mutation in the CRC samples, 7 cases were positive (+), and 35 cases were negative (-), and the classification accuracy of prediction (CAP) was 83.3% (35/42).

Discussion

The NIRS-DA model-predicted results were in high agreement with the detection results of NGS, and the difference in IHC is not statistically significant (P>0.05). However, this study is a preliminary discussion on a methodology due to its small sample size.

Near-Infrared Spectroscopy in Bio-Applications

Near-infrared (NIR) spectroscopy occupies a specific spot across the field of bioscience and related disciplines. Its characteristics and application potential differs from infrared (IR) or Raman spectroscopy. This vibrational spectroscopy technique elucidates molecular information from the examined sample by measuring absorption bands resulting from overtones and combination excitations. Recent decades brought significant progress in the instrumentation (e.g., miniaturized spectrometers) and spectral analysis methods (e.g., spectral image processing and analysis, quantum chemical calculation of NIR spectra), which made notable impact on its applicability. This review aims to present NIR spectroscopy as a matured technique, yet with great potential for further advances in several directions throughout broadly understood bio-applications. Its practical value is critically assessed and compared with competing techniques. Attention is given to link the bio-application potential of NIR spectroscopy with its fundamental characteristics and principal features of NIR spectra.

Optimizing algorithm development for tissue classification in colorectal cancer based on diffuse reflectance spectra

Diffuse reflectance spectroscopy can be used in colorectal cancer surgery for tissue classification. The main challenge in the classification task is to separate healthy colorectal wall from tumor tissue. In this study, four normalization techniques, four feature extraction methods and five classifiers are applied to nine datasets, to obtain the optimal method to separate spectra measured on healthy colorectal wall from spectra measured on tumor tissue. All results are compared to the use of the entire non-normalized spectra. It is found that the most optimal classification approach is to apply a feature extraction method on non-normalized spectra combined with support vector machine or neural network classifier.

An Automated Preprocessing Method for Diffuse Optical Tomography to Improve Breast Cancer Diagnosis

The ultrasound-guided diffuse optical tomography is a noninvasive imaging technique for breast cancer diagnosis and treatment monitoring. The technique uses a handheld probe capable of providing measurements of multiple wavelengths in a few seconds. These measurements are used to estimate optical absorptions of lesions and calculate the total hemoglobin concentration. Any measurement errors caused by low signal to noise ratio data and/or movements during data acquisition would reduce the accuracy of reconstructed total hemoglobin concentration. In this article, we introduce an automated preprocessing method that combines data collected from multiple sets of lesion measurements of 4 optical wavelengths to detect and correct outliers in the perturbation. Two new measures of correlation between each pair of wavelength measurements and a wavelength consistency index of all reconstructed absorption maps are introduced. For phantom and patients' data without evidence of measurement errors, the correlation coefficient between each pair of wavelength measurements was above 0.6. However, for patients with measurement errors, the correlation coefficient was much lower. After applying the correction method to 18 patients' data with measurement errors, the correlation has improved and the wavelength consistency index is in the same range as the cases without wavelength-dependent measurement errors. The results show an improvement in classification of malignant and benign lesions.

Effects of isoflurane anesthesia on physiological parameters in murine subcutaneous tumor allografts measured via diffuse reflectance spectroscopy

Diffuse reflectance spectroscopy (DRS) has been used in murine studies to quantify tumor perfusion and therapeutic response. These studies frequently use inhaled isoflurane anesthesia, which depresses the respiration rate and results in the desaturation of arterial oxygen saturation, potentially affecting tissue physiological parameters. However, there have been no controlled studies quantifying the effect of isoflurane anesthesia on DRS-derived physiological parameters of murine tissue. The goal of this study was to perform DRS on Balb/c mouse (n = 10) tissue under various anesthesia conditions to quantify effects on tissue physiological parameters, including total hemoglobin concentration, tissue oxygen saturation, oxyhemoglobin and reduced scattering coefficient. Two independent variables were manipulated including metabolic gas type (pure oxygen vs. medical air) and isoflurane concentration (1.5 to 4.0%). The 1.5% isoflurane and 1 L/min oxygen condition most closely mimicked a no-anesthesia condition with oxyhemoglobin concentration within 89% ± 19% of control. The time-dependent effects of isoflurane anesthesia were tested, revealing that anesthetic induction with 4.0% isoflurane can affect DRS-derived physiological parameters up to 20 minutes post-induction. Finally, spectroscopy with and without isoflurane anesthesia was compared for colon tumor Balb/c-CT26 allografts (n = 5) as a representative model of subcutaneous murine tumor allografts. Overall, isoflurane anesthesia yielded experimentally-induced depressed oxyhemoglobin, and this depression was both concentration and time dependent. Investigators should understand the dynamic effects of isoflurane on tissue physiological parameters measured by DRS. These results may guide investigators in eliminating, limiting, or managing anesthesia-induced physiological changes in DRS studies in mouse models.

Molecular and structural changes induced by essential oil treatments in Vicia faba roots detected by FTIR and FTNIR spectroscopy

Essential oils have recognized antimicrobial and antifungal properties which allow their utilization in agriculture like an alternative to pesticides, but their utilization requires the knowledge of all the potential structural changes and damages produced by the interaction with the vegetal organisms. In this paper, we investigated the effects of two essential oils, the tea tree oil (TTO) and the mixture of clove and rosemary oils (C + R), on the molecular structure of Vicia faba roots by Fourier transform infrared (FTIR) and Fourier near infrared transform (FTNIR) spectroscopy. FTIR spectroscopy showed structural modifications of the absorption bands related to DNA (1100 and 1050 cm^-1, carbohydrate backbones, and nucleotide bands within 900 and 850 cm^-1), proteins (1700 and 1600 cm^-1 amide I band, 1580 and 1520 cm^-1 amide II band), and lipids (methylene group of aliphatic chains between 2950 and 2800 cm^-1). The changes in the secondary structures of proteins consisted of a denaturation depending on increased presence of random coil structures. In addition, in the samples treated with TTO oils, we observed the presence of protein oxidation, an effect negligible instead for the C + R-treated samples. The modified shapes of the infrared methyl bands of aliphatic chains suggested an increased lipid disorder which could also determine lipid peroxidation. The changes observed for the DNA structures at the highest concentration of the above essential oils can be related to the genotoxic effect of eugenol, an important constituent of both TTO and C + R mixture oils. FTNIR spectroscopy showed the modified shape of the second overtone bands belonging to methyl and methylene groups, between 8500 and 8000 cm^-1. This confirmed the increased lipid disorders already observed by FTIR spectroscopy. The results obtained on the probe organism V. faba show that FTIR and FTNIR spectroscopy can become a useful support to the conventional cytogenetic tests used in the evaluation of the allelopathic uses of essential oils in agriculture.