Diagnosis of basal cell carcinoma by infrared spectroscopy of whole blood samples applying soft independent modeling class analogy

Khanmohammadi, Mohammadreza; Nasiri, Razieh; Ghasemi, Keyvan; Samani, Simin; Garmarudi, Amir Bagheri

doi:10.1007/s00432-007-0300-3

Cited by 3 publications

(5 citation statements)

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“…44,45 Additionally, multivariate regression analysis of spectral data is increasingly being used in biomedical, medical, and clinical studies for effective diagnosis of various cancer cells in complex biological matrices and for the determination of venous blood and muscle pH. 46,50 The use of multivariate regression analysis of spectral data for analysis of muscle oxygen saturation with no sample pretreatment without influence from skin and fat has also been reported. 47 Another advantage of multivariate regression modeling is its robustness.…”

Section: Resultsmentioning

confidence: 99%

“…41,–45 The practical applications of multivariate regression analysis of spectral data for the determination of diverse analytes, metabolites, and for fast screening of cancer cells with little or no sample preparation have also been well demonstrated in biomedical studies and clinical diagnoses. 46,–51 Besides, the multivariate regression approach to chemical analysis is not only rapid, sensitive, accurate, and inexpensive, but it is also robust. Once the calibration model is developed and carefully optimized, it can be used for accurate determination of analytes in samples for six months without recalibration, 52 considerably reducing the time and the cost of chemical analysis.…”

Section: Introductionmentioning

confidence: 99%

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Determination of Mercury (II) Ion Concentrations in Human Serum Albumin Using Fluorescence Spectroscopy and Multivariate Regression Analysis

Fakayode

Taylor

et al. 2012

Appl Spectrosc

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Human serum albumin (HSA) is a protein responsible for the transportation and delivery of drug molecules, fatty acids, and metabolites to various targets and the removal of waste products from the body. However, the binding of heavy metal ions, including mercury (II) (Hg(II)), can adversely affect HSA physiological properties with deleterious health consequences. The volatility of Hg at room temperature precludes the use of conventional flame, graphite furnace, or inductively couple atomic absorption spectroscopy for routine analysis of Hg in most research and medical laboratories. This study reports the first potential utility of fluorescence spectroscopy and multivariate regression analysis for the determination of Hg(II) concentration in HSA samples. The results of Fourier transform infrared (FT-IR) spectroscopy indicated the binding of Hg(II) at HSA amide I and amide II sites. Also, the binding of Hg(II) with HSA resulted in a decreased HSA ultraviolet (UV)-visible absorption and dramatic quenching of HSA fluorescence emission. The developed multivariate partial least squares regression (PLSR) model from Hg(II)–HSA fluorescence emission data was able to predict the Hg(II) concentration in HSA samples, with a root mean square percent relative error of prediction of 6.59%. The simplicity, low cost, and robustness of this method makes it a promising alternative method for rapid determination of Hg(II) concentration in biological specimens.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determination of Mercury (II) Ion Concentrations in Human Serum Albumin Using Fluorescence Spectroscopy and Multivariate Regression Analysis

Fakayode

Taylor

et al. 2012

Appl Spectrosc

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“…The obtained results suggest that the presence of ACPA may affect the protein profile in sera samples, which can be explained by conformation changes and glycosylation of the autoantibodies. ANA has been reported to mainly correlate with bands at 1620-1625 cm −1 , a marker of the amide I β-sheet (IgG3, IgG2) 51 , 1200-1215 cm −1 , markers of protein phosphorylation 52 , and 929 cm −1 , the absorption band for carbohydrates 53 . The fact that ANA presence correlates with bands corresponding to proteins and antibodies may be explained by the unique chemical structure of the autoantibodies.…”

Section: Discussionmentioning

confidence: 99%

Correlations between autoantibodies and the ATR-FTIR spectra of sera from rheumatoid arthritis patients

Durlik-Popińska

Żarnowiec

Konieczna-Kwinkowska³

et al. 2021

Sci Rep

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Rheumatoid arthritis (RA) is one of the most common autoimmune diseases worldwide. Due to high heterogeneity in disease manifestation, accurate and fast diagnosis of RA is difficult. This study analyzed the potential relationship between the infrared (IR) spectra obtained by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and the presence of autoantibodies and antibodies against urease in sera. Additionally, the wave number of the IR spectrum that enabled the best differentiation between patients and healthy blood donors was investigated. Using a mathematical model involving principal component analysis and discriminant analysis, it was shown that the presence of anti-citrullinated protein antibody, rheumatoid factor, anti-neutrophil cytoplasmic antibodies, and anti-nuclear antibodies correlated significantly with the wave numbers in the IR spectra of the tested sera. The most interesting findings derived from determination of the best predictors for distinguishing RA. Characteristic features included an increased reaction with urease mimicking peptides and a correspondence with particular nucleic acid bands. Taken together, the results demonstrated the potential application of ATR-FTIR in the study of RA and identified potential novel markers of the disease.

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“…It would be interesting as an idea to investigate the blood according to its ability to play the role of traveling media for malignant cells. The spectroscopic investigation of whole blood samples was previously introduced as a novel, accurate, precise and easy to perform method for diagnosis of cancer [9,10]. It is of high importance that blood is a homogeneous sample and its preparation procedure is very simple.…”

Section: Introductionmentioning

confidence: 99%

“…We had applied LDA and soft independent modeling class analogy (SIMCA) in the field of cancer diagnosis via spectroscopy of blood sample. LDA was used in a general purpose research while we had focused on BCC applying SIMCA [9,10].…”

Section: Introductionmentioning

confidence: 99%

Back‐propagation artificial neural network and attenuated total reflectance‐Fourier transform infrared spectroscopy for diagnosis of basal cell carcinoma by blood sample analysis

Khanmohammadi

Garmarudi

Ghasemi

2009

Journal of Chemometrics

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A diagnostic method for the cancer, based on investigation of infrared spectra of blood samples, has been developed. The two-layer modified principal component feed forward back-propagation artificial neural network (BP-ANN) was used to classify the attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectra of blood samples obtained from healthy people and those with basal cell carcinoma (BCC). Results showed 98.33% of accuracy, in comparison with the current clinical methods. In the first step, 20 blood samples (10 normal and 10 cancer cases) were applied to construct the calibration model. Spectroscopic studies were performed in 900-1800 cm S1 spectral region with 3.85 cm S1 data space. In order to modify the capability of ANN in prediction of test samples, two different algorithms were applied. The obtained results confirmed the compatibility of the proposed network with the architecture of 20-8-2 (input-hidden-output) with the pattern model. It was concluded that analysis of blood samples by ATR-FTIR spectroscopy and ANN chemometric technique would be a reliable approach for detection of BCC.

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Diagnosis of basal cell carcinoma by infrared spectroscopy of whole blood samples applying soft independent modeling class analogy

Cited by 3 publications

References 0 publications

Determination of Mercury (II) Ion Concentrations in Human Serum Albumin Using Fluorescence Spectroscopy and Multivariate Regression Analysis

Determination of Mercury (II) Ion Concentrations in Human Serum Albumin Using Fluorescence Spectroscopy and Multivariate Regression Analysis

Correlations between autoantibodies and the ATR-FTIR spectra of sera from rheumatoid arthritis patients

Back‐propagation artificial neural network and attenuated total reflectance‐Fourier transform infrared spectroscopy for diagnosis of basal cell carcinoma by blood sample analysis

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