Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning

Khan, Saranjam; Ullah, Rahat; Khan, Asifullah; Ashraf, R.; Ali, Hina; Bilal, Muhammad; Saleem, Muhammad

doi:10.1016/j.pdpdt.2018.05.010

Cited by 91 publications

(66 citation statements)

References 27 publications

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“…Raman spectroscopy is used as a label‐free technique for the diagnosis of malignant and infectious agents in whole blood and blood sera. Many researchers have already utilized these techniques for the study of many biological diseases like diabetes, hepatitis B, hepatitis C, malaria, typhoid, and dengue virus . These molecular screening techniques are based on identification of specific antibody or antigen production and study of their conformational changes against these biological diseases.…”

Section: Introductionmentioning

confidence: 99%

Detection of enzyme‐triggered peptide self‐assembly via laser confocal Raman microscopy and circular dichroism spectroscopy in cellular environment

Anwar

Ovais

Hassan

et al. 2020

J Raman Spectroscopy

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Vibrational spectroscopy of peptides and peptide‐based self‐assembled macromolecules plays key role in early stage detection of cancerous and viral diseases. We provide here a rapid and accurate trace detection system for enzyme‐triggered peptide self‐assembly by taking a snapshot of peptide nanostructures to identify specific domains based on amino acid vibrational bands. The enzyme‐triggered peptides present in both aqueous solution and human umbilical vein endothelial cells along with controlled cell lines were excited by a laser line of 543 nm, and intensities of Raman bands were recorded from 500 to 1,800 cm−1. The spectra consisted of several well‐resolved peaks located at 655, 1,081, and 1670 cm−1 for peptide and at 834, 851, 896, and 915 cm−1 for enzyme, indicating vibrational bands of their functional groups. Raman signatures at 768, 1,144, 1,297, 1,305, and 1,571 cm−1 appeared in case of self‐assembled peptides at new positions, indicating the presence of highly stable secondary structure of beta sheets. We studied here the 0.78 μg/ml limit of detection of peptide self‐assembly with this technique in aqueous solution. These self‐assembled nanomachines in cellular environment can be used to monitor and regulate the cellular processes for the diagnosis of biological diseases incorporated with our label‐free laser confocal Raman microscopy methodology.

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Section: Introductionmentioning

confidence: 99%

Detection of enzyme‐triggered peptide self‐assembly via laser confocal Raman microscopy and circular dichroism spectroscopy in cellular environment

Anwar

Ovais

Hassan

et al. 2020

J Raman Spectroscopy

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“…Moreover, it offers rapid and nondestructive analysis with minimal or no sample preparation, which is highly beneficial for the screening test. The literature provides numbers of examples of the successful application of biofluid‐based RS for screening of various cancer types, some infections and neurological diseases . Blood serum and plasma samples are the most often used ones, because they provide an overview of the whole organism health status.…”

Section: Introductionmentioning

confidence: 99%

Towards Raman spectroscopy of urine as screening tool

Žukovskaja

Ryabchykov

Straßburger

et al. 2019

Journal of Biophotonics

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For the screening purposes urine is an especially attractive biofluid, since it offers easy and noninvasive sample collection and provides a snapshot of the whole metabolic status of the organism, which may change under different pathological conditions. Raman spectroscopy (RS) has the potential to monitor these changes and utilize them for disease diagnostics. The current study utilizes mouse models aiming to compare the feasibility of the urine based RS combined with chemometrics for diagnosing kidney diseases directly influencing urine composition and respiratory tract diseases having no direct connection to urine formation. The diagnostic models for included diseases were built using principal component analysis with linear discriminant analysis and validated with a leave‐one‐mouse‐out cross‐validation approach. Considering kidney disorders, the accuracy of 100% was obtained in discrimination between sick and healthy mice, as well as between two different kidney diseases. For asthma and invasive pulmonary aspergillosis achieved accuracies were noticeably lower, being, respectively, 77.27% and 78.57%. In conclusion, our results suggest that RS of urine samples not only provides a solution for a rapid, sensitive and noninvasive diagnosis of kidney disorders, but also holds some promises for the screening of nonurinary tract diseases.

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“…It also provides the conformation structure of molecules and specific fingerprint-type information, which have been widely used in the field of medical diagnostics and biomedical research [7]- [13]. Almost all types of diseases, e.g., cancers and infectious diseases, initially occur at the molecular level [14]. These changes in the Raman spectrum show that the position, intensity and line width of the characteristic peaks may change, which provides a basis for disease diagnosis.…”

Section: Introductionmentioning

confidence: 99%

“…In practical applications, because the Raman scattering signal is very weak and can be influenced by strong fluorescence, the signal-to-noise ratio (SNR) of the obtained spectral signal is not ideal, and it is difficult to directly observe differences among spectra. Therefore, robust and powerful spectral data mining algorithms are urgently needed to extract useful information and improve distinguishing accuracy [10], [14]. In recent years, support vector machines (SVMs) have been widely used in disease diagnosis based on Raman spectra and have yielded better discriminant results [14]- [17].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, robust and powerful spectral data mining algorithms are urgently needed to extract useful information and improve distinguishing accuracy [10], [14]. In recent years, support vector machines (SVMs) have been widely used in disease diagnosis based on Raman spectra and have yielded better discriminant results [14]- [17]. For example, Saranjam Khan et al explored the use of Raman spectra together with SVM for the analysis of nasopharyngeal cancer and hepatitis B virus infection in human blood sera [14].…”

Section: Introductionmentioning

confidence: 99%

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Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine

Zheng

et al. 2018

IEEE Photonics J.

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This study presents a rapid and low-cost method to detect thyroid dysfunction using serum Raman spectroscopy combined with support vector machine (SVM). The serum samples taken from 34 thyroid dysfunction patients and 40 healthy volunteers were measured in this study. Tentative assignments of the Raman bands in the measured serum spectra suggested specific biomolecular changes between the groups. Principal component analysis (PCA) was used for feature extraction and reduced the dimension of high-dimension spectral data; then, SVM was employed to establish an effective discriminant model. To improve the efficiency and accuracy of the SVM discriminant model, we proposed artificial fish coupled with uniform design (AFUD) algorithm to optimize the SVM parameters. The average accuracy of 30 discriminant results reached 82.74%, and the average optimization time was 0.45 s. The results demonstrate that the serum Raman spectroscopy technique combined with the AFUD-SVM discriminant model has great potential for the detection of thyroid dysfunction. This technique could be used to develop a portable, rapid, and low-cost device for detecting thyroid function to meet the needs of individuals and communities.

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Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning

Cited by 91 publications

References 27 publications

Detection of enzyme‐triggered peptide self‐assembly via laser confocal Raman microscopy and circular dichroism spectroscopy in cellular environment

Detection of enzyme‐triggered peptide self‐assembly via laser confocal Raman microscopy and circular dichroism spectroscopy in cellular environment

Towards Raman spectroscopy of urine as screening tool

Rapid and Low-Cost Detection of Thyroid Dysfunction Using Raman Spectroscopy and an Improved Support Vector Machine

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