scholarly journals Biochemical Changes in Irradiated Oral Mucosa: A FTIR Spectroscopic Study

Biosensors ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Helena Ukkonen ◽  
Simo Vuokila ◽  
Jopi Mikkonen ◽  
Hannah Dekker ◽  
Engelbert Schulten ◽  
...  
Keyword(s):  
Oral Mucosa ◽  
Infrared Imaging ◽  
Objective Assessment ◽  
Principal Component ◽  
Superficial Layer ◽  
Label Free ◽  
Differential Distribution ◽  
Biochemical Alterations ◽  
Patient Groups ◽  
Therapeutic Irradiation

Radiation exposure during the course of treatment in head and neck cancer (HNC) patients can induce both structural and biochemical anomalies. The present study is focused on utilizing infrared imaging for the identification of the minor biochemical alterations in the oral mucosa. Chemical maps generated using glycoprotein band indicates its differential distribution along the superficial layer. Spectra extracted from this layer suggests changes in overall nucleic acid and protein content in response to the therapeutic irradiation. Discrimination among control and irradiated groups have been achieved using principal component analysis. Findings of this preliminary study further support prospective utilization of Fourier Transform InfraRed (FTIR) imaging as a non-destructive, label-free tool for objective assessment of the oral mucosa in patient groups with or without radiation therapy.

scholarly journals Diagnosing COVID-19 in human serum using Raman spectroscopy: a preliminary study

2021 ◽  
Author(s):  
Ana Cristina Castro Goulart ◽  
Landulfo Silveira ◽  
Henrique Cunha Carvalho ◽  
Cristiane Bissoli Dorta ◽  
Marcos Tadeu Tavares Pacheco ◽  
...  
Keyword(s):  
Amino Acids ◽  
Raman Spectroscopy ◽  
Discriminant Analysis ◽  
Blood Serum ◽  
Principal Component ◽  
Label Free ◽  
Rt Pcr ◽  
Difference Spectra ◽  
Biochemical Alterations ◽  
Preliminary Study

This preliminary study proposed the diagnosis of COVID-19 by means of Raman spectroscopy. Samples of blood serum from 10 patients positive and 10 patients negative for COVID-19 by RT-PCR RNA and ELISA tests were analyzed. Raman spectra were obtained with a dispersive Raman spectrometer (830 nm, 350 mW) in triplicate, being submitted to exploratory analysis with principal component analysis (PCA) to identify the spectral differences and discriminant analysis with PCA (PCA-DA) and partial least squares (PLS-DA) for classification of the blood serum spectra into Control and COVID-19. The spectra of both groups positive and negative for COVID-19 showed peaks referred to the basal constitution of the serum (mainly albumin). The difference spectra showed decrease in the peaks referred to proteins and amino acids for the group positive. PCA variables showed more detailed spectral differences related to the biochemical alterations due to the COVID-19 such as increase in lipids, nitrogen compounds (urea and amines/amides) and nucleic acids, and decrease of proteins and amino acids (tryptophan) in the COVID-19 group. The discriminant analysis applied to the principal component loadings (PC 2, PC 4, PC 5 and PC 6) could classify spectra with 87% sensitivity and 100% specificity compared to 95% sensitivity and 100% specificity indicated in the RT-PCR kit leaflet, demonstrating the possibilities of a rapid, label-free and costless technique for diagnosing COVID-19 infection.

scholarly journals Serum N-Glycomics Stratifies Bacteremic Patients Infected with Different Pathogens

2021 ◽  
Vol 10 (3) ◽  
pp. 516
Author(s):  
Sayantani Chatterjee ◽  
Rebeca Kawahara ◽  
Harry C. Tjondro ◽  
David R. Shaw ◽  
Marni A. Nenke ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Principal Component ◽  
Bloodstream Infections ◽  
Blood Stream ◽  
Label Free ◽  
Healthy Donors ◽  
Liquid Chromatography Tandem Mass ◽  
Life Threatening ◽  
Patient Groups ◽  
Bacteremic Patient

Bacteremia—i.e., the presence of pathogens in the blood stream—is associated with long-term morbidity and is a potential precursor condition to life-threatening sepsis. Timely detection of bacteremia is therefore critical to reduce patient mortality, but existing methods lack precision, speed, and sensitivity to effectively stratify bacteremic patients. Herein, we tested the potential of quantitative serum N-glycomics performed using porous graphitized carbon liquid chromatography tandem mass spectrometry to stratify bacteremic patients infected with Escherichia coli (n = 11), Staphylococcus aureus (n = 11), Pseudomonas aeruginosa (n = 5), and Streptococcus viridans (n = 5) from healthy donors (n = 39). In total, 62 N-glycan isomers spanning 41 glycan compositions primarily comprising complex-type core fucosylated, bisecting N-acetylglucosamine (GlcNAc), and α2,3-/α2,6-sialylated structures were profiled across all samples using label-free quantitation. Excitingly, unsupervised hierarchical clustering and principal component analysis of the serum N-glycome data accurately separated the patient groups. P. aeruginosa-infected patients displayed prominent N-glycome aberrations involving elevated levels of fucosylation and bisecting GlcNAcylation and reduced sialylation relative to other bacteremic patients. Notably, receiver operating characteristic analyses demonstrated that a single N-glycan isomer could effectively stratify each of the four bacteremic patient groups from the healthy donors (area under the curve 0.93–1.00). Thus, the serum N-glycome represents a new hitherto unexplored class of potential diagnostic markers for bloodstream infections.

scholarly journals Raman Microscopy: Progress in Research on Cancer Cell Sensing

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5525
Author(s):  
Satheeshkumar Elumalai ◽  
Stefano Managó ◽  
Anna Chiara De Luca
Keyword(s):  
Cancer Cells ◽  
Cancer Cell ◽  
Cancer Progression ◽  
High Throughput Screening ◽  
Objective Assessment ◽  
Single Point ◽  
Principal Component ◽  
Raman Microscopy ◽  
Label Free ◽  
Number Of Cells

In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.

scholarly journals Small Extracellular Vesicles Isolated from Serum May Serve as Signal-Enhancers for the Monitoring of CNS Tumors

2020 ◽  
Vol 21 (15) ◽  
pp. 5359 ◽  
Author(s):  
Gabriella Dobra ◽  
Matyas Bukva ◽  
Zoltan Szabo ◽  
Bella Bruszel ◽  
Maria Harmati ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Serum Proteins ◽  
Lumbar Disc ◽  
Principal Component ◽  
Cns Tumors ◽  
Serum Samples ◽  
Force Microscopy ◽  
Isolation And Characterization ◽  
Atomic Force ◽  
Patient Groups

Liquid biopsy-based methods to test biomarkers (e.g., serum proteins and extracellular vesicles) may help to monitor brain tumors. In this proteomics-based study, we aimed to identify a characteristic protein fingerprint associated with central nervous system (CNS) tumors. Overall, 96 human serum samples were obtained from four patient groups, namely glioblastoma multiforme (GBM), non-small-cell lung cancer brain metastasis (BM), meningioma (M) and lumbar disc hernia patients (CTRL). After the isolation and characterization of small extracellular vesicles (sEVs) by nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM), liquid chromatography -mass spectrometry (LC-MS) was performed on two different sample types (whole serum and serum sEVs). Statistical analyses (ratio, Cohen’s d, receiver operating characteristic; ROC) were carried out to compare patient groups. To recognize differences between the two sample types, pairwise comparisons (Welch’s test) and ingenuity pathway analysis (IPA) were performed. According to our knowledge, this is the first study that compares the proteome of whole serum and serum-derived sEVs. From the 311 proteins identified, 10 whole serum proteins and 17 sEV proteins showed the highest intergroup differences. Sixty-five proteins were significantly enriched in sEV samples, while 129 proteins were significantly depleted compared to whole serum. Based on principal component analysis (PCA) analyses, sEVs are more suitable to discriminate between the patient groups. Our results support that sEVs have greater potential to monitor CNS tumors, than whole serum.

Pork Quality Classification Using a Hyperspectral Imaging System and Neural Network

2007 ◽  
Vol 3 (1) ◽  
Author(s):  
Qiao Jun ◽  
Michael Ngadi ◽  
Ning Wang ◽  
Aynur Gunenc ◽  
Mariana Monroy ◽  
...  
Keyword(s):  
Neural Network ◽  
Hyperspectral Imaging ◽  
Imaging System ◽  
Objective Assessment ◽  
Principal Component ◽  
Pork Quality ◽  
Pca Analysis ◽  
Error Frequency ◽  
Quality Classification ◽  
Average Reflectance

Pork quality is usually determined subjectively as PSE, PFN, RFN, RSE and DFD based on color, texture and exudation of the meat. In this study, a hyperspectral-imaging-based technique was developed to achieve rapid, accurate and objective assessment of pork quality. The principal component analysis (PCA) and stepwise operation methods were used to select feature waveband from the entire spectral wavelengths (430 to 980 nm). Then the feature waveband images were extracted at the selected feature wavebands from raw hyperspectral images, and the average reflectance (R) was calculated within the whole loin-eye area. Artificial neural network was used to classify these groups. Results showed that PCA analysis had a better performance than that of stepwise operation for feature waveband images selection. The 1st derivative data gave a better result than that of mean reflectance spectra data. The best classified result was 87.5% correction. The error frequency showed that RSE samples were easier to classify. The PFN and PSE samples were difficult to separate from each other.

scholarly journals The research of the state of prosthetic bed tissues in patients with pemphigus vulgaris.

2017 ◽  
Vol 23 (1) ◽  
Author(s):  
Bohdan Lyubomyrovych Henyk ◽  
Mykola Mykhaylovych Rozko
Keyword(s):  
Survey Data ◽  
Oral Mucosa ◽  
Clinical Examination ◽  
Comparative Evaluation ◽  
Objective Assessment ◽  
Pemphigus Vulgaris ◽  
The State ◽  
Control Group

The clinical examination of condition of tissues prosthetic bed was conducted in 20 patients with  pemphigus vulgaris. The results are compared with survey data of 20 persons of control group without somatic pathology. It was conducted the analyzes of subjective and objective assessment of tissues prosthetic bed, the results of clinical examination and frequency of various pathologies of the oral mucosa membrane in the studied groups, conducted the comparative evaluation of dental indicators.

scholarly journals Harnessing intrinsic fluorescence for typing of secondary structures of DNA

2020 ◽  
Author(s):  
Michela Zuffo ◽  
Aurélie Gandolfini ◽  
Brahim Heddi ◽  
Anton Granzhan
Keyword(s):  
High Throughput ◽  
Conformational Changes ◽  
Emission Spectra ◽  
Principal Component ◽  
Secondary Structures ◽  
Intrinsic Fluorescence ◽  
Label Free ◽  
Linear Discriminant ◽  
Effective Manner

ABSTRACTDNA is polymorphic since, despite its ubiquitous presence as a double-stranded helix, it is able to fold into a plethora of other secondary structures both in vitro and in cells. Despite the considerable advances that have been made in understanding this structural diversity, its high-throughput investigation still faces severe limitations. This mainly stems from the lack of suitable label-free methods, combining a fast and cheap experimental workflow with high information content. Here, we explore the use of intrinsic fluorescence emitted by nucleic acids for this scope. After a preliminary assessment of the suitability of this phenomenon for tracking the conformational changes of DNA, we examined the intrinsic steady-state emission spectra of an 89-membered set of synthetic oligonucleotides with reported conformation (G-quadruplexes, i-motifs, single- and double stranded DNA) by means of multivariate analysis. Specifically, principal component analysis of emission spectra resulted in successful clustering of oligonucleotides into three corresponding conformational groups, albeit without discrimination between single- and double-stranded structures. Linear discriminant analysis of the same training set was exploited for the assessment of new sequences, allowing the evaluation of their G4-forming propensity. Our method does not require any labelling agent or dye, avoiding the related intrinsic bias, and can be utilized to screen novel sequences of interest in a high-throughput and cost-effective manner. In addition, we observed that left-handed (Z-) G4 structures were systematically more fluorescent than most other G4 structures, almost reaching the quantum yield of 5′-d[(G3T)3G3]-3′ (G3T), the most fluorescent G4 structure reported to date. This property is likely to arise from the similar base-stacking geometry in both types of structures.

scholarly journals Label-free digital pathology by infrared imaging

2020 ◽  
Vol 9 (1-2) ◽  
pp. 5-12 ◽  
Author(s):  
Frederik Großerueschkamp ◽  
Klaus Gerwert
Keyword(s):  
Infrared Imaging ◽  
Digital Pathology ◽  
Label Free

scholarly journals Rapid label-free SERS detection of foodborne pathogenic bacteria based on hafnium ditelluride-Au nanocomposites

2020 ◽  
Vol 13 (05) ◽  
pp. 2041004 ◽  
Author(s):  
Yang Li ◽  
Yanxian Guo ◽  
Binggang Ye ◽  
Zhengfei Zhuang ◽  
Peilin Lan ◽  
...  
Keyword(s):  
Pathogenic Bacteria ◽  
Limit Of Detection ◽  
Principal Component ◽  
High Sensitivity ◽  
Chemical Mechanism ◽  
Sers Substrate ◽  
Label Free ◽  
Label Free Detection ◽  
Surface Enhanced Raman ◽  
Foodborne Pathogenic Bacteria

Two-dimensional (2D) nanomaterials have captured an increasing attention in biophotonics owing to their excellent optical features. Herein, 2D hafnium ditelluride (HfTe[Formula: see text], a new member of transition metal tellurides, is exploited to support gold nanoparticles fabricating HfTe2-Au nanocomposites. The nanohybrids can serve as novel 2D surface-enhanced Raman scattering (SERS) substrate for the label-free detection of analyte with high sensitivity and reproducibility. Chemical mechanism originated from HfTe2 nanosheets and the electromagnetic enhancement induced by the hot spots on the nanohybrids may largely contribute to the superior SERS effect of HfTe2-Au nanocomposites. Finally, HfTe2-Au nanocomposites are utilized for the label-free SERS analysis of foodborne pathogenic bacteria, which realize the rapid and ultrasensitive Raman test of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus and Salmonella with the limit of detection of 10 CFU/mL and the maximum Raman enhancement factor up to [Formula: see text]. Combined with principal component analysis, HfTe2-Au-based SERS analysis also completes the bacterial classification without extra treatment.

scholarly journals A lectin-coupled porous silicon-based biosensor: label-free optical detection of bacteria in a real-time mode

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mona Yaghoubi ◽  
Fereshteh Rahimi ◽  
Babak Negahdari ◽  
Ali Hossein Rezayan ◽  
Azizollah Shafiekhani
Keyword(s):  
Fourier Transform ◽  
Porous Silicon ◽  
Real Time ◽  
Limit Of Detection ◽  
Principal Component ◽  
The Other ◽  
Detection Methods ◽  
Carbohydrate Binding ◽  
Label Free ◽  
E Coli

Abstract Accuracy and speed of detection, along with technical and instrumental simplicity, are indispensable for the bacterial detection methods. Porous silicon (PSi) has unique optical and chemical properties which makes it a good candidate for biosensing applications. On the other hand, lectins have specific carbohydrate-binding properties and are inexpensive compared to popular antibodies. We propose a lectin-conjugated PSi-based biosensor for label-free and real-time detection of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by reflectometric interference Fourier transform spectroscopy (RIFTS). We modified meso-PSiO2 (10–40 nm pore diameter) with three lectins of ConA (Concanavalin A), WGA (Wheat Germ Agglutinin), and UEA (Ulex europaeus agglutinin) with various carbohydrate specificities, as bioreceptor. The results showed that ConA and WGA have the highest binding affinity for E. coli and S. aureus respectively and hence can effectively detect them. This was confirmed by 6.8% and 7.8% decrease in peak amplitude of fast Fourier transform (FFT) spectra (at 105 cells mL−1 concentration). A limit of detection (LOD) of about 103 cells mL−1 and a linear response range of 103 to 105 cells mL−1 were observed for both ConA-E. coli and WGA-S. aureus interaction platforms that are comparable to the other reports in the literature. Dissimilar response patterns among lectins can be attributed to the different bacterial cell wall structures. Further assessments were carried out by applying the biosensor for the detection of Klebsiella aerogenes and Bacillus subtilis bacteria. The overall obtained results reinforced the conjecture that the WGA and ConA have a stronger interaction with Gram-positive and Gram-negative bacteria, respectively. Therefore, it seems that specific lectins can be suggested for bacterial Gram-typing or even serotyping. These observations were confirmed by the principal component analysis (PCA) model.

Sign in / Sign up

Export Citation Format

Share Document