Publications by authors named "Nosheen Rashid"

19 Publications

  • Page 1 of 1

Surface-enhanced Raman spectral analysis for comparison of PCR products of hepatitis B and hepatitis C.

Photodiagnosis Photodyn Ther 2021 Jul 16;35:102440. Epub 2021 Jul 16.

Department of Chemistry, University of Central Punjab, Faisalabad Campus, Faisalabad, Pakistan.

Background: Surface-enhanced Raman spectroscopy is a reliable tool for identification and differentiation of two diseases showing similar symptoms, hepatitis B (HBV) and hepatitis C (HCV).

Objectives: To develop a polymerase chain reaction technique (PCR) based SERS technique for differentiation of two human pathological conditions sharing the same symptoms using multivariate data analysis techniques e.g. principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA).

Methods: PCR products of HBV and HCV were differentiated by SERS using silver nanoparticles (AgNPs) as a SERS substrate. For this analysis, PCR products of both the diseases with predetermined viral loads were collected and analyzed under SERS instrument and unique SERS spectra of HBV and HCV was compared showing many differences at various points. Diseased classes of HBV and HCV and their negative control classes (viral load less than 1) were compared. PCR products of true healthy DNA and RNA were also compared, which were significantly separated. Moreover, SERS data was analyzed using multivariate data analysis techniques including principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA) and differences were so prominent to observe.

Results: SERS spectral data of HBV and HCV showed clear differences and were significantly separated using PCA. Negative control samples of both disorders and their true healthy samples of DNA and RNA were separated according to 1 principle component. By analyzing data using partial least square discriminate analysis, differentiation of two disease classes was considered more valid with sensitivity, specificity and accuracy value of 96%, 94% and 98% respectively. Value of area under curve (AUROC) was 0.7527.

Conclusion: SERS can be employed for identification and comparison of two human pathological conditions sharing the same symptomology.
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http://dx.doi.org/10.1016/j.pdpdt.2021.102440DOI Listing
July 2021

Surface-enhanced Raman spectroscopy for comparison of serum samples of typhoid and tuberculosis patients of different stages.

Photodiagnosis Photodyn Ther 2021 Jul 1;35:102426. Epub 2021 Jul 1.

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.

Background: Surface-enhanced Raman spectroscopy (SERS) is a reliable tool for the identification and differentiation of two different human pathological conditions sharing the same symptomology, typhoid and tuberculosis (TB).

Objectives: To explore the potential of surface-enhanced Raman spectroscopy for differentiation of two different diseases showing the same symptoms and analysis by principal component analysis (PCA) and partial least square discriminate analysis (PLS-DA).

Methods: Serum samples of clinically diagnosed typhoid and tuberculosis infected individuals were analyzed and differentiated by SERS using silver nanoparticles (Ag NPs) as a SERS substrate. For this purpose, the collected serum samples were analyzed under the SERS instrument and unique SERS spectra of typhoid and tuberculosis were compared showing notable spectral differences in protein, lipid and carbohydrates features. Different stages of the diseased class of typhoid (Early acute and late acute stage) and tuberculosis (Pulmonary and extra-pulmonary stage) were compared with each other and with healthy human serum samples, which were significantly separated. Moreover, SERS data was analyzed using multivariate data analysis techniques including principal component analysis (PCA) and partial least square discriminate analysis (PLS-DA) and differences were so prominent to observe.

Results: SERS Spectral data of typhoid and tuberculosis showed clear differences and were significantly separated using PCA. SERS spectral data of both stages of typhoid and tuberculosis were separated according to 1st principle component. Moreover, by analyzing data using partial least square discriminate analysis, differentiation of two disease classes were considered more valid with a 100% value of sensitivity, specificity and accuracy.

Conclusion: SERS can be employed for identification and comparison of two different human pathological conditions sharing same symptomology.
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http://dx.doi.org/10.1016/j.pdpdt.2021.102426DOI Listing
July 2021

Characterization and prediction of viral loads of Hepatitis B serum samples by using surface-enhance Raman spectroscopy (SERS).

Photodiagnosis Photodyn Ther 2021 Jun 9;35:102386. Epub 2021 Jun 9.

PCR Laboratory, PINUM Hospital, Faisalabad, Pakistan.

Background: Raman spectroscopy is a promising technique to analyze the body fluids for the purpose of non-invasive disease diagnosis.

Objectives: To develop a surface-enhanced Raman spectroscopy (SERS) based method for qualitative and quantitative analysis of hepatitis B viral (HBV) infection from blood serum samples.

Methods: Clinically diagnosed hepatitis B virus (HBV) infected serum samples of patients of different levels of viral loads have been subjected for SERS analysis in comparison with the healthy ones by using silver nanoparticles (Ag NPs) based SERS substrates. The SERS measurements were performed on blood serum samples of 11 healthy and 32 clinically diagnosed HBV patients of different viral load levels of different exponentials including (10, 10 called as low level), (10, 10 called as medium level) and (10, 10 called as high level). Furthermore, multivariate data analysis techniques, Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were also performed on SERS spectral data.

Results: The SERS spectral features due to biochemical changes in HBV positive serum samples associated with the increasing viral loads were established which could be employed for HBV diagnostic purpose. PCA was found helpful for the differentiation between SERS spectral data of serum samples of different levels of HBV infection and healthy individuals. PLSR model developed with standard samples of known viral loads for predicting the viral loads of blind/unknown samples with 99% predicted accuracy.

Conclusion: SERS can be employed for qualitative and quantitative analysis of HBV infection from blood serum samples.
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http://dx.doi.org/10.1016/j.pdpdt.2021.102386DOI Listing
June 2021

Surface-enhanced Raman spectroscopy for identification of food processing bacteria.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Nov 23;261:119989. Epub 2021 May 23.

Industrial Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan.

Food processing bacteria play important role in providing flavors, ingredients and other beneficial characteristics to the food but at the same time some bacteria are responsible for food spoilage. Therefore, quick and reliable identification of these food processing bacteria is very necessary for the differentiation between different species which may help in the development of more useful food processing methodologies. In this study, analysis of different bacterial species (Lactobacillus fermentum, Fructobacillus fructosus, Pediococcus pentosaceus and Halalkalicoccus jeotgali) was performed with our in-house developed Ag NPs-based surface-enhanced Raman spectroscopy (SERS) method. The SERS spectral data was analyzed by multivariate data analysis techniques including principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). Bacterial species were differentiated on the basis of SERS spectral features and potential of SERS was compared with the Raman spectroscopy (RS). SERS along with PCA and PLS-DA was found to be an efficient technique for identification and differentiation of food processing bacterial species. Differentiation with accuracy of 99.5% and sensitivity of 99.7% was depicted by PLS-DA model using leave one out cross validation.
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http://dx.doi.org/10.1016/j.saa.2021.119989DOI Listing
November 2021

Surface-enhanced Raman spectroscopy for analysis of PCR products of viral RNA of hepatitis C patients.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Oct 5;259:119908. Epub 2021 May 5.

PCR Laboratory, PINUM Hospital, Faisalabad, Pakistan.

In the current study, for a qualitative and quantitative study of Polymerase Chain Reaction (PCR) products of viral RNA of Hepatitis C virus (HCV) infection, surface-enhanced Raman spectroscopy (SERS) methodology has been developed. SERS was used to identify the spectral features associated with the PCR products of viral RNA of Hepatitis C in various samples of HCV-infected patients with predetermined viral loads. The measurements for SERS were performed on 30 samples of PCR products, which included three PCR products of RNA of healthy individuals, six negative controls, and twenty-one HCV positive samples of varying viral loads (VLs) using Silver nanoparticles (Ag NPs) as a SERS substrates. Additionally, on SERS spectral data, the multivariate data analysis methods including Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) were also carried out which help to illustrate the diagnostic capabilities of this method. The PLSR model is designed to predict HCV viral loads based on biochemical changes observed as SERS spectral features which can be associated directly with HCV RNA. Several SERS characteristic features are observed in the RNA of HCV which are not detected in the spectra of healthy RNA/controls. PCA is found helpful to differentiate the SERS spectral data sets of HCV RNA samples from healthy and negative controls. The PLSR model is found to be 99% accurate in predicting VLs of HCV RNA samples of unknown samples based on SERS spectral changes associated with the Hepatitis C development.
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http://dx.doi.org/10.1016/j.saa.2021.119908DOI Listing
October 2021

Surface-enhanced Raman spectroscopy analysis of serum samples of typhoid patients of different stages.

Photodiagnosis Photodyn Ther 2021 Jun 6;34:102329. Epub 2021 May 6.

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, 38040, Pakistan.

Background: Surface-enhanced Raman spectroscopy (SERS) of body fluids is considered a quick, simple and easy to use method for the diagnosis of disease.

Objectives: To evaluate rapid, reliable, and non-destructive SERS-based diagnostic tool with multivariate data analysis including principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) for classification of different stages of typhoid on the basis of characteristic SERS spectral features.

Methods: SERS has been used for analysis of serum samples of different stages of typhoid including early acute stage and late acute stage in comparison with healthy samples, in order to investigate capability of this technique for diagnosis of typhoid. SERS spectral features associated with the biochemical changes taking place during the development of the typhoid fever were analyzed and identified.

Results: The value of area under the receiver operating characteristics (AUROC) for early acute stage versus healthy is 0.87 and that for healthy versus late acute stage is 0.52. PLS-DA classifier model gives values of 100 % for accuracy, sensitivity and specificity, respectively for the SERS spectral data sets of healthy versus early acute stage. Moreover, this classifier model gives values of 91 %, 89 % and 97 % for accuracy, sensitivity and specificity, respectively for the SERS spectral data sets of healthy versus late acute stage.

Conclusions: Based on preliminary work it is concluded that SERS has potential to diagnose various stages of typhoid fever including early acute and late acute stage in comparison with healthy samples.
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http://dx.doi.org/10.1016/j.pdpdt.2021.102329DOI Listing
June 2021

Surface-enhanced Raman spectroscopy for the identification of tigecycline-resistant E. coli strains.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Sep 24;258:119831. Epub 2021 Apr 24.

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.

Tigecycline (TGC) is recognised as last resort of drugs against several antibiotic-resistant bacteria. Bacterial resistance to tigecycline due to presence of plasmid-mediated mobile TGC resistance genes (tet X3/X4) has broken another defense line. Therefore, rapid and reproducible detection of tigecycline-resistant E. coli (TREC) is required. The current study is designed for the identification and differentiation of TREC from tigecycline-sensitive E. coli (TSEC) by employing SERS by using Ag NPs as a SERS substrate. The SERS spectral fingerprints of E. coli strains associated directly or indirectly with the development of resistance against tigecycline have been distinguished by comparing SERS spectral data of TSEC strains with each TREC strain. Moreover, the statistical analysis including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were employed to check the diagnostic potential of SERS for the differentiation among TREC and TSEC strains. The qualitative identification and differentiation between resistant and sensitive strains and among individual strains have been efficiently done by performing both PCA and HCA. The successful discrimination among TREC and TSEC at the strain level is performed by PLS-DA with 98% area under ROC curve, 100% sensitivity, 98.7% specificity and 100% accuracy.
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http://dx.doi.org/10.1016/j.saa.2021.119831DOI Listing
September 2021

Rapid and sensitive discrimination among carbapenem resistant and susceptible E. coli strains using Surface Enhanced Raman Spectroscopy combined with chemometric tools.

Photodiagnosis Photodyn Ther 2021 Jun 3;34:102280. Epub 2021 Apr 3.

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad, 38040, Pakistan.

Background: Raman spectroscopy is a powerful technique for the robust, reliable and rapid detection and discrimination of bacteria.

Objectives: To develop a rapid and sensitive technique based on surface-enhanced Raman spectroscopy (SERS) with multivariate data analysis tools for discrimination among carbapenem resistant and susceptible E. coli strains.

Methods: SERS was employed to differentiate different strains of carbapenem resistant and susceptible E. coli by using silver nanoparticles (Ag NPs) as a SERS substrate. For this purpose, four strains of carbapenem resistant and three strains of carbapenem susceptible E. coli were analyzed by comparing their SERS spectral signatures. Furthermore, multivariate data analysis techniques including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were performed over the spectral range of 400-1800 cm (fingerprint region) for the identification and differentiation of different E. coli strains.

Results: The SERS spectral features associated with resistant development against carbapenem antibiotics were separated by comparing each spectrum of susceptible strains with each resistant strain. PCA and HCA were found effective for the qualitative differentiation of all the strains analysed. PLS-DA successfully discriminated the carbapenem resistant and susceptible E. coli pellets on the strain level with 99.8 % sensitivity, 100 % specificity, 100 % accuracy and 86 % area under receiver operating characteristic (AUROC) curve.

Conclusion: SERS can be employed for the rapid discrimination among carbapenem resistant and susceptible strains of E. coil.
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http://dx.doi.org/10.1016/j.pdpdt.2021.102280DOI Listing
June 2021

SERS-based viral load quantification of hepatitis B virus from PCR products.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Jul 19;255:119722. Epub 2021 Mar 19.

PCR Laboratory, PINUM Hospital, Faisalabad, Pakistan.

Hepatitis B is a contagious liver disorder caused by hepatitis B virus and if not treated at an early stage, it becomes chronic and results in liver cirrhosis and hepatocellular carcinoma which can even lead to death. In present study, surface-enhanced Raman spectroscopy (SERS) is employed for the analysis of polymerase chain reaction (PCR) products of DNA extracted from hepatitis B virus (HBV) infected patients in comparison with healthy individuals. SERS spectral features are identified which are solely present in the HBV positive samples and consistently increase in intensities with increase in viral load which can be considered as a SERS spectral marker for HBV infection. For sake of understanding, these various levels of viral loads in this study are classified as low (1-1000 IU), medium (1000-10,000 IU), high (above 10,000 IU) and negative control (>1). In order to explore the efficiency of SERS for discrimination of SERS spectral datasets of different samples of varying viral loads and healthy individuals, principal component analysis (PCA) is applied. PCA is used for comparison of these classes including low, medium and high levels of viral loads with each other and with healthy class. Moreover, partial least square discriminant analysis and partial least square regression analysis are employed for the classification of different levels of viral loads in the HBV positive samples and prediction of viral loads in the unknown samples, respectively. PLS-DA is applied for validity of classification and its sensitivity and specificity was found to be 89% and 98% respectively. PLSR model was constructed for prediction of viral loads on the bases of SERS spectral markers of HBV infection with goodness value of 0.9031 and value of root means square error (RMSE) 0.2923. PLSR model also proved to be valid for prediction of blind sample.
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http://dx.doi.org/10.1016/j.saa.2021.119722DOI Listing
July 2021

Surface enhanced Raman spectroscopy of RNA samples extracted from blood of hepatitis C patients for quantification of viral loads.

Photodiagnosis Photodyn Ther 2021 Mar 30;33:102152. Epub 2020 Dec 30.

PCR Laboratory, PINUM Hospital, Faisalabad, Pakistan.

Background: Raman spectroscopy is a promising technique to analyze the body fluids for the purpose of non-invasive disease diagnosis.

Objectives: To develop a surface-enhanced Raman spectroscopy (SERS) based method for qualitative and quantitative analysis of HCV from blood samples.

Methods: SERS was employed to characterize the Hepatitis C viral RNA extracted from different blood samples of hepatitis C virus (HCV) infected patients with predetermined viral loads in comparison with total RNA of healthy individuals. The SERS measurements were performed on 27 extracted RNA samples including low viral loads, medium viral loads, high viral loads and healthy/negative viral load samples. For this purpose, silver nanoparticles (Ag NPs) were used as SERS substrates. Furthermore, multivariate data analysis technique, Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were also performed on SERS spectral data.

Results: The SERS spectral features due to biochemical changes in the extracted RNA samples associated with the increasing viral loads were established which could be employed for HCV diagnostic purpose. PCA was found helpful for the differentiation between Raman spectral data of RNA extracted from hepatitis infected and healthy blood samples. PLSR model is established for the determination of viral loads in HCV positive RNA samples with 99 % accuracy.

Conclusion: SERS can be employed for qualitative and quantitative analysis of HCV from blood samples.
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http://dx.doi.org/10.1016/j.pdpdt.2020.102152DOI Listing
March 2021

Raman spectroscopy for the qualitative and quantitative analysis of solid dosage forms of Sitagliptin.

Spectrochim Acta A Mol Biomol Spectrosc 2021 Jan 2;245:118900. Epub 2020 Sep 2.

EA 6295 Nano-médicaments and Nano-sondes, Université de Tours, Tours, France.

To demonstrate the potential of Raman spectroscopy for the qualitative and quantitative analysis of solid dosage pharmacological formulations, different concentrations of Sitagliptin, an Active Pharmaceutical Ingredient (API) currently prescribed as an anti-diabetic drug, are characterised. Increase of the API concentrations induces changes in the Raman spectral features specifically associated with the drug and excipients. Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR), were used for the qualitative and quantitative analysis of the spectral responses. A PLSR model is constructed which enables the prediction of different concentrations of drug in the complex excipient matrices. During the development of the prediction model, the Root Mean Square Error of Cross Validation (RMSECV) was found to be 0.36 mg and the variability explained by the model, according to the (R) value, was found to be 0.99. Moreover, the concentration of the API in the unknown sample was determined. This concentration was predicted to be 64.28/180 mg (w/w), compared to the 65/180 mg (w/w). These findings demonstrate Raman spectroscopy coupled to PLSR analysis to be a reliable tool to verify Sitagliptin contents in the pharmaceutical samples based on calibration models prepared under laboratory conditions.
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http://dx.doi.org/10.1016/j.saa.2020.118900DOI Listing
January 2021

Quantitative analysis of solid dosage forms of cefixime using Raman spectroscopy.

Spectrochim Acta A Mol Biomol Spectrosc 2020 Sep 6;238:118446. Epub 2020 May 6.

Department of Chemistry, University of Agriculture, Faisalabad, Pakistan.

Quantification of antibiotics is of significant importance because of their use in the prevention and treatment of different diseases. Cefixime (CEF) is a cephalosporin antibiotic that is used against bacterial infections. In the present study, Raman spectroscopy has been applied for the identification and quantification of Raman spectral features of cefixime with different concentrations of Active Pharmaceutical Ingredient (API) and excipients in solid dosage forms. The changes in Raman spectral features of API and excipients in the solid dosage forms of cefixime were studied and Raman peaks were assigned based on the literature. Multivariate data analysis techniques including the Principal Component Analysis (PCA) and Partial Least Squares Regression analysis (PLSR) have been performed for the qualitative and quantitative analysis of solid dosage forms of cefixime. PCA was found helpful in differentiating all the Raman spectral data associated with the different solid dosage forms of cefixime. The coefficient of determination (R), mean absolute error (MAE), and mean relative error (MRE) for the calibration data-set were 0.99, 0.72, and 0.01 respectively and for the validation data-set were 0.99, 3.15, and 0.02 respectively, that shows the performance of the model. The root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.56 mg and 3.13 mg respectively.
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http://dx.doi.org/10.1016/j.saa.2020.118446DOI Listing
September 2020

Raman spectroscopy for the analysis of different exo-polysaccharides produced by bacteria.

Spectrochim Acta A Mol Biomol Spectrosc 2020 Aug 26;237:118408. Epub 2020 Apr 26.

Industrial Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Constituent College of Pakistan Institute of Engineering and Applied Sciences, PO Box 577, Jhang Road, Faisalabad, Pakistan.

In this study, Raman spectroscopy is employed for the characterization and comparison of two different classes of exo-polysaccharides including glucans and fructans which are produced by different bacteria. For this purpose, nine samples are used including five samples of glucans and four of fructans. Raman spectral results of all these polysaccharides show clear differences among various glucans as well as fructans showing the potential of this technique to identify the differences within the same class of the compounds. Moreover, these two classes are also compared on the basis of their Raman spectral data and can be differentiated on the basis of their unique Raman features. Multivariate data analysis techniques, Principle Component Analysis (PCA) is found very helpful for the comparison of the Raman spectral data of these classes of the carbohydrates.
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http://dx.doi.org/10.1016/j.saa.2020.118408DOI Listing
August 2020

Raman spectral characterization of silver metal-based complexes of different benzimidazolium ligands.

Spectrochim Acta A Mol Biomol Spectrosc 2020 May 19;232:118162. Epub 2020 Feb 19.

Department of Chemistry, University of Agriculture Faisalabad-38040, Pakistan.

In this study, Raman spectroscopy has been employed for the characterization of two structurally different monodentate N-heterocyclic carbene ligands (ligand-1 and ligand-2) and their respective complexes (complex-1 and complex-2). The Raman spectral features are found helpful for the confirmation of formation of complexes. The significant Raman spectral features are identified for benzimidazole ring with higher intensities in carbene complexes having more polarizability as compared to their ligands, providing the evidence for the formation of coordinate covalent bond. The successful complexation is further supported by using multivariate data analysis technique, Principal Component Analysis (PCA), which is found very helpful to highlight the variability of Raman spectral data of both ligands and their respective metal complexes from each other. Moreover, the coordination of carbene with Ag(I) is confirmed from the dominant spectral markers of higher intensities at 359 cm in complex-1 and 338 cm in complex-2. The effective and reliable characterization and confirmation of metal complexes indicates the potential of Raman spectroscopy for its use for the characterization of the organometallic complexes and other chemical products.
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http://dx.doi.org/10.1016/j.saa.2020.118162DOI Listing
May 2020

Raman spectroscopy along with Principal Component Analysis for the confirmation of Silver(I)-N-heterocyclic carbene complex formation.

Spectrochim Acta A Mol Biomol Spectrosc 2020 Mar 23;228:117851. Epub 2019 Nov 23.

Department of Chemistry, University of Agriculture Faisalabad, 38040, Pakistan. Electronic address:

In this study Raman spectroscopy is employed for the characterization of two different ligands called as S1 and S2 and their respective co-ordinate complexes called C1 and C2. Specific Raman spectral signatures are observed for each of these Silver(I)-N-heterocyclic carbene complexes Ag(I)-(NHCs), which can be associated with the imidazolium ring, part of both of the ligands, indicating the formation of new coordinate covalent bond. For the detailed analysis, Raman spectral data of these ligands and complexes is analyzed by multivariate data analysis technique, Principal Component Analysis (PCA) which is found very helpful to differentiate two ligands and complexes from each other. The significant Raman peaks with higher intensities in the complexes as compared to the respective ligands are associated with imidazole ring which can be attributed to the enhanced polarizability of this ring on complex formation. Moreover, the spectral features associated with (AgC) bond are observed with higher intensity at 360 in (C1) and 383 in (C2). This study indicates the potential of Raman spectroscopy for the characterization and confirmation of formation of organometallic complexes and other chemical products.
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http://dx.doi.org/10.1016/j.saa.2019.117851DOI Listing
March 2020

Raman spectroscopy for the evaluation of the effects of different concentrations of Copper on the chemical composition and biological activity of basil essential oil.

Spectrochim Acta A Mol Biomol Spectrosc 2017 Oct 24;185:130-138. Epub 2017 May 24.

National Institute of Lasers and Optronics (NILOP), Islamabad, Pakistan.

The present study is performed to evaluate the effect of different concentrations of Cu as fertilizer on the chemical composition of basil essential oil and its biological activity including antioxidant and antifungal activities by employing Raman spectroscopy. Moreover, the effect of Cu is also determined on the vegetative growth and essential oil yield. Both, antifungal and antioxidant activities were found to be maximum with essential oils obtained at 0.04mg/l concentration of Cu fertilizer. The results of the GC-MS and Raman spectroscopy have revealed that the linalool and estragole are found to be as a major chemical compound in basil essential oil. The Raman spectral changes associated with these biological components lead to the conclusion that estragole seems to have dominating effect in the biological activities of the basil essential oil as compared to linalool although the latter is observed in greater concentration.
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http://dx.doi.org/10.1016/j.saa.2017.05.049DOI Listing
October 2017

Raman spectroscopy for the characterization of different fractions of hemp essential oil extracted at 130°C using steam distillation method.

Spectrochim Acta A Mol Biomol Spectrosc 2017 Jul 1;182:168-174. Epub 2017 Apr 1.

National Institute of Lasers and Optronics (NILOP), Islamabad, Pakistan.

In this study, Raman spectroscopy along with Principal Component Analysis (PCA) is used for the characterization of pure essential oil (pure EO) isolated from the leaves of the Hemp (Cannabis sativa L.,) as well as its different fractions obtained by fractional distillation process. Raman spectra of pure Hemp essential oil and its different fractions show characteristic key bands of main volatile terpenes and terpenoids, which significantly differentiate them from each other. These bands provide information about the chemical composition of sample under investigation and hence can be used as Raman spectral markers for the qualitative monitoring of the pure EO and different fractions containing different active compounds. PCA differentiates the Raman spectral data into different clusters and loadings of the PCA further confirm the biological origin of the different fractions of the essential oil.
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http://dx.doi.org/10.1016/j.saa.2017.03.072DOI Listing
July 2017

Raman microspectroscopy for the early detection of pre-malignant changes in cervical tissue.

Exp Mol Pathol 2014 Dec 3;97(3):554-64. Epub 2014 Nov 3.

DIT Centre for Radiation and Environmental Science (RESC), Focas Research Institute, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland; School of Physics, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland. Electronic address:

Cervical cancer is the third most common cancer affecting women worldwide. The mortality associated with cervical cancer can, however, be significantly reduced if the disease is detected at the pre-malignant stage. The aim of this study was to evaluate the potential of Raman microspectroscopy for elucidation of the biochemical changes associated with the pre-malignant stages of cervical cancer. Formalin fixed paraffin preserved tissue sections from cervical biopsies classified as negative for intraepithelial lesion and malignancy (NILM), low grade squamous intraepithelial lesion (LSIL) or high grade squamous intraepithelial lesion (HSIL) were analysed by Raman spectral mapping. Raman mapping, with K-means cluster analysis (KMCA), was able to differentiate the NILM cervical tissue into three layers including stroma, basal/para-basal and superficial layers, characterised by spectral features of collagen, DNA bases and glycogen respectively. In the LSIL and HSIL samples, KMCA clustered regions of the superficial layer with the basal layer. Using principal components analysis (PCA), biochemical changes associated with disease were also observed in normal areas of the abnormal samples, where morphological changes were not apparent. This study has shown that Raman microspectroscopy could be useful for the early detection of pre-malignant changes in cervical tissue.
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http://dx.doi.org/10.1016/j.yexmp.2014.10.013DOI Listing
December 2014

Production of tylosin in solid-state fermentation by Streptomyces fradiae NRRL-2702 and its gamma-irradiated mutant (gamma-1).

Lett Appl Microbiol 2009 Nov 22;49(5):635-40. Epub 2009 Aug 22.

Industrial Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan.

Aims: To develop solid-state fermentation system (SSF) for hyper production of tylosin from a mutant gamma-1 of Streptomyces fradiae NRRL-2702 and its parent strain.

Methods And Results: Various agro-industrial wastes were screened to study their effect on tylosin production in SSF. Wheat bran as solid substrate gave the highest production of 2500 microg of tylosin g(-1) substrate by mutant gamma-1 against parent strain (300 microg tylosin g(-1) substrate). The tylosin yield was further improved to 4500 microg g(-1) substrate [70% moisture, 10% inoculum (v/w), pH 9.2, 30 degrees C, supplemental lactose and sodium glutamate on day 9]. Wild-type strain displayed less production of tylosin (655 microg of tylosin g(-1) substrate) in SSF even after optimization of process parameters.

Conclusion: The study has shown that solid-state fermentation system significantly enhanced the tylosin yield by mutant gamma-1.

Significance And Impact Of The Study: This study proved to be very useful and resulted in 6.87 +/- 0.30-fold increase in tylosin yield by this mutant when compared to that of wild-type strain.
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http://dx.doi.org/10.1111/j.1472-765X.2009.02720.xDOI Listing
November 2009
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