Diagnosis of HIV-1 infection by near-infrared spectroscopy: Analysis using molecular clones of various HIV-1 subtypes

Sakudo, Akikazu; Suganuma, Yoshikazu; Sakima, Rina; Ikuta, Kazuyoshi

doi:10.1016/j.cca.2011.10.035

Cited by 23 publications

(22 citation statements)

References 11 publications

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“…Taken from Martin et al [47]. [8] analyzed near-infrared spectra using molecular clones of various HIV-1 subtypes. The spectra obtained were subjected to PCA to extract information and exploratory analysis, where it was observed that the presence of HIV-1 in the medium altered wavelength absorption at around 950 and 1030 nm, suggesting that HIV-1 changes the vibrations of OH in water [8].…”

Section: Molecular Fluorescencementioning

confidence: 99%

“…This field of science is known as biospectroscopy, and means the use of spectroscopy to analyze biological samples [4]. Several studies have been conducted involving identification of bacteria [5,6], viruses [7,8], cancer diagnosis [9], and even in the field of forensic entomotoxicology [10], demonstrating that spectroscopic techniques are capable of detecting biochemical changes in biological matrices.…”

Section: Introductionmentioning

confidence: 99%

“…The potential of spectroscopic techniques in the detection and identification of virus-infected cells has been studied using statistical methods as a sensitive, rapid and reliable methodology. The ability to discriminate between contaminated and noncontaminated samples in a short time with good sensitivity and specificity is pragmatic, suggesting that biospectroscopy is a field that should be more studied in virology [7,8,14].…”

Section: Introductionmentioning

confidence: 99%

“…The main spectroscopic techniques that have been used in virological studies are nuclear magnetic resonance (NMR) spectroscopy [16], Raman spectroscopy [7], infrared spectroscopy (IR) [8] and molecular fluorescence spectroscopy [17]. These techniques are known to provide rapid responses and reliable data, as well as having powerful structural elucidation capability.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Spectroscopy with computational analysis in virological studies: A decade (2006–2016)

Santos

Morais

Nascimento

et al. 2017

TrAC Trends in Analytical Chemistry

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a b s t r a c tThis review presents a retrospective of the studies carried out in the last 10 years (2006e2016) using spectroscopic methods as a research tool in the field of virology. Spectroscopic analyses are sensitive to variations in the biochemical composition of the sample, are non-destructive, fast and require the least sample preparation, making spectroscopic techniques tools of great interest in biological studies. Herein important chemometric algorithms that have been used in virological studies are also evidenced as a good alternative for analyzing the spectra, discrimination and classification of samples. Techniques that have not yet been used in the field of virology are also suggested. This methodology emerges as a new and promising field of research, and may be used in the near future as diagnosis tools for detecting diseases caused by viruses.

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Section: Molecular Fluorescencementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spectroscopy with computational analysis in virological studies: A decade (2006–2016)

Santos

Morais

Nascimento

et al. 2017

TrAC Trends in Analytical Chemistry

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“…Likewise, FT‐IR spectroscopy has been successfully used to investigate spectral variations linked to different molecular constituents and to detect diseased states in different tissues and cells . Segregation of HIV‐infected patients vs. control by applying FT‐IR technology has also been analyzed in a few studies .…”

Section: Introductionmentioning

confidence: 99%

Discrimination of patients with different serological evolution of HIV and co‐infection with HCV using metabolic fingerprinting based on Fourier transform infrared

Pizarro

Esteban‐Díez

Arenzana-Rámila

et al. 2017

Journal of Biophotonics

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Human immunodeficiency virus (HIV) is a retrovirus that weakens the immune system and permits opportunistic diseases such as hepatitis C (HCV) to enter the body. These diseases induce metabolic disorders in the patients and it is therefore logical to approach them from a holistic, functional perspective, studying the metabolome comprehensively to identify metabolic signatures associated with certain disease states. The metabolomics strategy here proposed involves metabolic fingerprinting using Fourier transform infrared spectroscopy and chemometric tools on 72 plasma samples (subdivided into 63 training and 9 test samples) to differentiate between healthy subjects and patients with different disease stages. Several options, relating to the variable selection method used in linear discriminant analysis and the number of categories being considered, were explored to optimize discrimination ability. A total of 18 bands enabled differentiation between control subjects, HIV patients and the group that encompassed patients with acquired immune deficiency syndrome (AIDS), AIDS/HCV and HIV/HCV, providing overall classification and internal prediction rates of 97.67% and 93.65%, respectively. Only 9 bands were required to further discriminate between AIDS, AIDS/HCV and HIV/HCV, with 99.20% (training) and 89.66% (cross-validation) correct classifications. The simplicity and effectiveness of the classification methodology proposed was reinforced by the satisfactory results obtained in external prediction.

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Label‐free laser spectroscopy for respiratory virus detection: A review

Kistenev

Das

Mazumder

et al. 2022

Journal of Biophotonics

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Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real‐time, low cost and label‐free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.

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Diagnosis of HIV-1 infection by near-infrared spectroscopy: Analysis using molecular clones of various HIV-1 subtypes

Cited by 23 publications

References 11 publications

Spectroscopy with computational analysis in virological studies: A decade (2006–2016)

Spectroscopy with computational analysis in virological studies: A decade (2006–2016)

Discrimination of patients with different serological evolution of HIV and co‐infection with HCV using metabolic fingerprinting based on Fourier transform infrared

Label‐free laser spectroscopy for respiratory virus detection: A review

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