Muhammad Shakeel | University of Agriculture, Faisalabad, Pakistan (original) (raw)
Papers by Muhammad Shakeel
Raman spectroscopy is an important analytical technique because of its use for the quantification... more Raman spectroscopy is an important analytical technique because of its use for the quantification of different antibiotics used for the treatment of different diseases. Florfenicol is considered a broadspectrum antibiotic drug that is used for bacterial infection and livestock species, including porcine, bovine, and chicken.
son of surface-enhanced Raman spectral data sets of filtrate portions of serum samples of hepatit... more son of surface-enhanced Raman spectral data sets of filtrate portions of serum samples of hepatitis B and Hepatitis C infected patients obtained by centrifugal filtration, Photodiagnosis and Photodynamic Therapy (2023), doi:
Background: Surface-enhanced Raman spectroscopy (SERS) is explored to design a rapid screening me... more Background: Surface-enhanced Raman spectroscopy (SERS) is explored to design a rapid screening method for the characterization and diagnosis of typhoid fever by employing filtrate fractions of blood serum samples obtained by centrifugal filtration with 50 KDa filters. Objectives: The purpose of this study, to separate the filtrate portions of blood serum samples in this way contain proteins smaller than 50 kDa and removal of bigger size protein which allows to acquire the SERS spectral features of smaller proteins more effectively which are probably associated with typhoid disease. Disease caused by Salmonella typhi diagnose more effectively by using surface-enhanced Raman spectroscopy (SERS) and multivariate data analysis tools. Methods: SERS was used as a diagnostic tool for typhoid fever by comparison between healthy and diseased samples. For this purpose, all the samples were analyzed by comparing their SERS spectral features. Over the spectral range of 400-1800cm − 1 , multivariate data analysis techniques such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) are applied to diagnose and differentiate different filtrate fractions of blood serum samples of patients of typhoid fever and healthy ones. Results: By comparing SERS spectra of healthy filtrate with that of filtrate of typhoid sample, the SERS spectral features associated with disease development are identified including PCA is found to be efficient for the qualitative differentiation of all of the samples analyzed. Moreover, PLS-DA successfully identified and classified healthy and typhoid positive blood serum samples with 97 % accuracy, 99 % specificity, 91 % sensitivity and 0.78 area under the receiver operating characteristic (AUROC) curve. Conclusions: Surface enhanced Raman spectroscopy using silver nanoparticles SERS substrate, is found to be useful technique for the quick identification and evaluation of filtrate fractions of the blood serum samples of healthy and typhoid samples for disease diagnosis.
Elsevier, 2022
Background: Surface-enhanced Raman spectroscopy (SERS) is an effective tool for identifying biofi... more Background: Surface-enhanced Raman spectroscopy (SERS) is an effective tool for identifying biofilm forming bacterial strains. Biofilm forming bacteria are considered a major issue in the health sector because they have strong resistance against antibiotics. Staphylococcus epidermidis is commonly present on intravascular devices and prosthetic joints, catheters and wounds. Objectives: To identify and characterize biofilm forming and non-biofilm forming bacterial strains, surfaceenhanced Raman spectroscopy with principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were used. Methods: Surface-enhanced Raman spectroscopy (SERS) with silver nanoparticles were employed for the analysis and characterization of biofilm forming bacterial strains. SERS is used to differentiate between non biofilm forming (five samples), medium biofilm forming (five samples) and strong biofilm forming (five samples) bacterial strains by applying silver nanoparticles (AgNPs) as SERS substrate. Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) were used to discriminate between non, medium and strong biofilm ability of bacterial strains. Results: Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been used to identify the biochemical differences in the form of SERS features which can be used to differentiate between biofilm forming and non-biofilm forming bacterial strains. PLS-DA provides successful differentiation and classification of these different strains with 94.5% specificity, 96% sensitivity and 89% area under the curve (AUC). Conclusions: Surface-enhanced Raman spectroscopy can be utilized to differentiate between non, medium and strong biofilm forming bacterial strains.
Photodiagnosis and Photodynamic Therapy, 2022
Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is r... more Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is robust, reliable, and rapid. To develop a polymerase chain reaction technique (PCR) based on Surface Enhanced Raman Spectroscopy (SERS) technique with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to assess diagnostic capability of SERS for distinguishing between tuberculosis (TB) positive rifampin resistant and tuberculosis (TB) positive rifampin susceptible samples. Silver nanoparticles (Ag NPs) were used as SERS substrates and technique was used to distinguish TB positive rifampin (RIF) resistant and TB positive rifampin (RIF) susceptible patients on the basis of characteristic SERS spectral features of their respective PCR products. SERS spectra were acquired from 52 samples of PCR products including 22 samples of TB positive rifampin susceptible, 30 samples of TB positive rifampin resistant and negative control samples. All these samples were collected from individuals of same age. Furthermore, multivariate data analyses techniques such as PCA and PLS-DA were used to assess diagnostic capability of SERS for distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples. PCA is found helpful for successful differentiation among these two groups of spectral data sets. Moreover, PLS-DA provides this classification quantitatively by predicting the class of SERS spectral data set with 73% area under curve, 96% sensitivity, 95.6% specificity and 95% accuracy. SERS can be employed for the rapid distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples.
Raman spectroscopy is an important analytical technique because of its use for the quantification... more Raman spectroscopy is an important analytical technique because of its use for the quantification of different antibiotics used for the treatment of different diseases. Florfenicol is considered a broadspectrum antibiotic drug that is used for bacterial infection and livestock species, including porcine, bovine, and chicken.
son of surface-enhanced Raman spectral data sets of filtrate portions of serum samples of hepatit... more son of surface-enhanced Raman spectral data sets of filtrate portions of serum samples of hepatitis B and Hepatitis C infected patients obtained by centrifugal filtration, Photodiagnosis and Photodynamic Therapy (2023), doi:
Background: Surface-enhanced Raman spectroscopy (SERS) is explored to design a rapid screening me... more Background: Surface-enhanced Raman spectroscopy (SERS) is explored to design a rapid screening method for the characterization and diagnosis of typhoid fever by employing filtrate fractions of blood serum samples obtained by centrifugal filtration with 50 KDa filters. Objectives: The purpose of this study, to separate the filtrate portions of blood serum samples in this way contain proteins smaller than 50 kDa and removal of bigger size protein which allows to acquire the SERS spectral features of smaller proteins more effectively which are probably associated with typhoid disease. Disease caused by Salmonella typhi diagnose more effectively by using surface-enhanced Raman spectroscopy (SERS) and multivariate data analysis tools. Methods: SERS was used as a diagnostic tool for typhoid fever by comparison between healthy and diseased samples. For this purpose, all the samples were analyzed by comparing their SERS spectral features. Over the spectral range of 400-1800cm − 1 , multivariate data analysis techniques such as Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) are applied to diagnose and differentiate different filtrate fractions of blood serum samples of patients of typhoid fever and healthy ones. Results: By comparing SERS spectra of healthy filtrate with that of filtrate of typhoid sample, the SERS spectral features associated with disease development are identified including PCA is found to be efficient for the qualitative differentiation of all of the samples analyzed. Moreover, PLS-DA successfully identified and classified healthy and typhoid positive blood serum samples with 97 % accuracy, 99 % specificity, 91 % sensitivity and 0.78 area under the receiver operating characteristic (AUROC) curve. Conclusions: Surface enhanced Raman spectroscopy using silver nanoparticles SERS substrate, is found to be useful technique for the quick identification and evaluation of filtrate fractions of the blood serum samples of healthy and typhoid samples for disease diagnosis.
Elsevier, 2022
Background: Surface-enhanced Raman spectroscopy (SERS) is an effective tool for identifying biofi... more Background: Surface-enhanced Raman spectroscopy (SERS) is an effective tool for identifying biofilm forming bacterial strains. Biofilm forming bacteria are considered a major issue in the health sector because they have strong resistance against antibiotics. Staphylococcus epidermidis is commonly present on intravascular devices and prosthetic joints, catheters and wounds. Objectives: To identify and characterize biofilm forming and non-biofilm forming bacterial strains, surfaceenhanced Raman spectroscopy with principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were used. Methods: Surface-enhanced Raman spectroscopy (SERS) with silver nanoparticles were employed for the analysis and characterization of biofilm forming bacterial strains. SERS is used to differentiate between non biofilm forming (five samples), medium biofilm forming (five samples) and strong biofilm forming (five samples) bacterial strains by applying silver nanoparticles (AgNPs) as SERS substrate. Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) were used to discriminate between non, medium and strong biofilm ability of bacterial strains. Results: Principal component analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been used to identify the biochemical differences in the form of SERS features which can be used to differentiate between biofilm forming and non-biofilm forming bacterial strains. PLS-DA provides successful differentiation and classification of these different strains with 94.5% specificity, 96% sensitivity and 89% area under the curve (AUC). Conclusions: Surface-enhanced Raman spectroscopy can be utilized to differentiate between non, medium and strong biofilm forming bacterial strains.
Photodiagnosis and Photodynamic Therapy, 2022
Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is r... more Raman spectroscopy is an effective tool for detecting and discriminating microorganisms that is robust, reliable, and rapid. To develop a polymerase chain reaction technique (PCR) based on Surface Enhanced Raman Spectroscopy (SERS) technique with principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to assess diagnostic capability of SERS for distinguishing between tuberculosis (TB) positive rifampin resistant and tuberculosis (TB) positive rifampin susceptible samples. Silver nanoparticles (Ag NPs) were used as SERS substrates and technique was used to distinguish TB positive rifampin (RIF) resistant and TB positive rifampin (RIF) susceptible patients on the basis of characteristic SERS spectral features of their respective PCR products. SERS spectra were acquired from 52 samples of PCR products including 22 samples of TB positive rifampin susceptible, 30 samples of TB positive rifampin resistant and negative control samples. All these samples were collected from individuals of same age. Furthermore, multivariate data analyses techniques such as PCA and PLS-DA were used to assess diagnostic capability of SERS for distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples. PCA is found helpful for successful differentiation among these two groups of spectral data sets. Moreover, PLS-DA provides this classification quantitatively by predicting the class of SERS spectral data set with 73% area under curve, 96% sensitivity, 95.6% specificity and 95% accuracy. SERS can be employed for the rapid distinguishing between TB positive rifampin resistant and TB positive rifampin susceptible samples.