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Background: Plastic Solid Waste (PSW) sorting is a procedure of paramount importance in the mechanical recycling process of plastics waste. The major limitation of the techniques relying on physical properties of plastics is the time taken for analysis and poor accuracy. Spectroscopy has been shown to be a suitable method in plastic sorting due to its atomic and molecular characterization capabilities, and ability to give results in very short time scales. However, for practical applications it is essential to translate this technique into an automatic technology, by combining it with advanced chemometric tools which can give observer independent judgement., Results: The indigenously developed bi-model Laser Induced Breakdown Spectroscopy (LIBS)-Raman system with single source and single detector can record the LIBS-Raman spectral signals in single-shot mode in a total time frame of 20 ms. Out of the combinations of Principal Component Analysis (PCA) and Partial Least Squares (PLS) with Logistic Regression (LR), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Partial Least Squares-Discriminant Analysis (PLS-DA) based classifiers, the PLS-DA based model showed the maximum classification accuracy with 95 % based on LIBS data and 100 % based on Raman data. The reliability of the model was assessed using 4-fold cross-validation which showed a sensitivity of 90.28 % and specificity of 98.29 % for predictions based on LIBS data, and 99 % sensitivity and 99.82 % specificity for predictions relying on Raman data., Significance: The results show how the combination of multimodal spectroscopy with chemometric analysis enhances the applicability of spectroscopic techniques for plastic sorting. The classification model successfully classified seven types of post-consumer plastic samples based on combined LIBS and Raman data. With the home-built software for automated prediction, the system takes less than a second to predict the plastic type illustrating the potential of the method for translation to regular routine industrial applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: The study showcased the application of the lab-assembled HPLC-LED-IF system to analyze proteins in tear fluid samples collected from individuals diagnosed with primary open-angle glaucoma (POAG)., Methods: Clinical application of the said technique was evaluated by recording chromatograms of tear fluid samples from control and POAG subjects and by analyzing the protein profile using multivariate analysis. The data analysis methods involved are principal component analysis (PCA), Match/No-Match, and artificial neural network (ANN) based binary classification for disease diagnosis., Results: Mahalanobis distance and spectral residual values calculated using a standard calibration set of clinically confirmed POAG samples for the Match/No-Match test gave 86.9% sensitivity and 81.8% specificity. ANN with leaving one out procedure has given 87.1% sensitivity and 81.8% specificity., Conclusion: The results of the study revealed that the utilization of a 278 nm LED excitation in the HPLC system offers good sensitivity for detecting proteins at low concentrations allowing to obtain reliable protein profiles for the diagnosis of POAG.

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Breath analysis is emerging as a universal diagnostic method for clinical applications. The possibility of breath analysis is being explored vigorously using different analytical techniques. We have designed and assembled a multiwavelength UV photoacoustic spectroscopy (PAS) sensor for the said application. To optimize laser wavelength for sample excitation, photoacoustic signals from disease and normal conditions are recorded with different laser excitations (213, 266, 355, and 532 nm) on exhaled breath samples. Principal component analysis (PCA) of the PA signals has shown that 213, 266, and 355 nm laser excitations are suitable for breath analysis, with reliable descriptive statistics obtained for 266 nm laser. The study has, therefore, been extended for breath samples collected from asthma, chronic obstructive pulmonary disease (COPD), and normal subjects, using 266 nm laser excitation. PCA of the PA data shows good classification among asthma, COPD, and normal subjects. Match/No-match study performed with asthma, COPD, and normal calibration set has demonstrated the potential of using this method for diagnostic application. Sensitivity and specificity are observed as 88 and 89%, respectively. The area under the curve of the ROC curve is found to be 0.948, which justifies the diagnostic capability of the device for lung diseases. The same samples were studied using a commercial E-Nose, and the measurement outcome strongly supports the PAS results.

The 325 nm-excited autofluorescence spectra from cancerous and normal renal tissues were collected ex vivo biopsy tissue samples, through an optical fiber probe-based system. Noticeable changes in intensity/wavelength were observed in the fluorescence emissions from endogenous fluorophores such as collagen, Nicotinamide adenine dinucleotide (NADH), Vitamin A (retinol), and flavin adenine dinucleotide, in pathological conditions with respect to the normal state. The energy metabolism involved in clear cell renal cell carcinoma (ccRCC) and chromophobe renal cell carcinoma (chRCC) are reflected in the fluorescence emission band at 445 nm due to bound NADH attributed to enhanced oxidative phosphorylation in chRCC and emission at 465 nm contributed by free NADH showing higher glycolytic action in ccRCC. The principal component analysis and one-way ANOVA effectively discriminate ccRCC from chRCC. It is shown that laser induced fluorescence technique with 325 nm excitation can be a suitable technique for optical pathology and in vivo surgical boundary demarcation in renal cell carcinoma., (© 2023 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)

The increased use of plastic products and global industrial conditions have contaminated natural resources, especially water, with pollutants such as microplastics and trace elements, including heavy metals. Hence, continuous monitoring of water samples is an urgent requirement. However, the existing microplastic-heavy metal monitoring methodologies require discrete and sophisticated sampling approaches. The article proposes a multi-modal LIBS-Raman spectroscopy system for detecting microplastics and heavy metals from water resources with unified sampling and pre-processing approaches. The accomplishment of the detection process is using a single instrument by exploiting the trace element affinity of microplastics, which operates in an integrated methodology to monitor water samples for microplastic-heavy metal contamination. The polypropylene (PP), polyethylene (PE), and polyethylene terephthalate (PET) plastic types dominate the identified microplastics from different sampling spots: in an estuary formed by the Swarna River near Kalmadi (Malpe) in Udupi district, and from River Netravathi in Mangalore, Dakshina Kannada District, Karnataka, India. The detected trace elements from microplastic surfaces include heavy metals such as Al, Zn, Cu, Ni, Mn, and Cr and other elements counting Na, Mg, Ca, and Li. The system could record concentrations of trace elements down to 10 ppm, and comparing results with the conventional technique of Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) confirms the ability of the system to detect trace elements from microplastic surfaces. In addition, comparing results with direct LIBS analysis of water from the sampling site shows better results in microplastic-based trace element detection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Tear fluid contains organic and inorganic constituents, variations in their relative concentrations could provide valuable information and can be useful for the detection of several ophthalmological diseases. This report describes the application of the lab-assembled light-emitting diode (LED)-based high-performance liquid chromatography system for protein profiling of tear fluids to diagnose dry eye disease. Principal Component Analysis (PCA), match/no-match, and Artificial Neural Network (ANN) based binary classification of protein profile data were performed for disease diagnosis. Results from the match/no-match test of the protein profile data showed 94.4% sensitivity and 87.8% specificity. ANN with the leaving one out procedure has given 91.6% sensitivity and 93.9% specificity., Competing Interests: The authors are not involved with any organization or entity with a financial interest or financial conflict of interest., (This journal is © The Royal Society of Chemistry.)

Cardiovascular diseases (CVDs) are the major health conditions for high mortality and morbidity in humans. Delay in the diagnosis of CVDs effect patients long and short-term health condition. In -house assembled UV-light emitting diode (LED) based fluorescence detector for high -performance liquid chromatography (HPLC) (HPLC-LED-IF) system is used to record serum chromatograms of three categories of samples namely, before medicated- myocardial infarction (B-MI), after medicated- MI (A-MI), and normal. The sensitivity and performance of HPLC-LED-IF system is estimated using commercial serum proteins. Statistical analysis tools like, descriptive statistics, principal component analysis (PCA), and Match/ No Match test were applied to visualize the variation in three groups of samples. Statistical analysis of the protein profile data showed fairly good discrimination among the three categories. The receiver operating characteristic (ROC) curve also supported the reliability of the method to diagnose MI., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: Fiber optic probe-based in vivo spectroscopy techniques are fast and highly objective methods for intraoperative diagnoses and minimally invasive surgical interventions for all procedures where endoscopic observations are carried out for cancers of different types. The Raman spectral features provide molecular fingerprint-type information and can reveal the subjects' pathological state in label-free manner, making endoscopy multiplexed fiber optic probe-based devices with the potential for translation from bench to bedside for routine applications., Areas Covered: This review provides a general overview of different fiber-optic probes for in vivo measurements with emphasis on Raman spectroscopy for biomedical application. Various aspects such as fiber-optic probe, radiation source, detector, and spectrometer for extracting optimum spectral features have also been discussed., Expert Opinion: Optical spectroscopy-based fiber probe systems with 'Chip-on-Tip' technology, combined with machine learning, can in the near future, become a complementary diagnostic tool to magnetic resonance imaging (MRI), computed tomography (CT) scan, ultrasound, etc. Hyperspectral imaging and fluorescence-based devices are in the advanced stage of technology readiness level (TRL), and with advances in lasers and miniature spectroscopy systems, probe-based Raman devices are also coming up.

Cardiovascular diseases (CVD) are the major causative factors for high mortality and morbidity in developing and developed nations. The biomarker detection plays a crucial role in the early diagnosis of several non-infectious and life-threatening diseases like CVD and many cancers, which in turn will help in more successful therapy, reducing the mortality rate. Biomarkers have diagnostic, prognostic and therapeutic significances. The search for novel biomarkers using proteomics, bio-sensing, micro-fluidics, and spectroscopic techniques with good sensitivity and specificity for CVD is progressing rapidly at present, in addition to the use of gold standard biomarkers like troponin. This review is dealing with the current progress and prospects in biomarker research for the diagnosis of cardiovascular diseases. Expert opinion. Fast diagnosis of cardiovascular diseases (CVDs) can help to provide rapid medical intervention, which can affect the patient's short and long-term health. Identification and detection of proper biomarkers for early diagnosis are crucial for successful therapy and prognosis of CVDs. The present review discusses the analysis of clinical samples such as whole blood, blood serum, and other body fluids using techniques like high-performance liquid chromatography-LASER/LED-induced fluorescence, Raman spectroscopy, mainly, optical methods, combined with nanotechnology and micro-fluidic technologies, to probe patterns of multiple markers (marker signatures) as compared to conventional techniques., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s) 2022.)

Ever-accumulating amounts of plastic waste raises alarming concern over environmental and public health. A practical solution for addressing this threat is recycling, and the success of an industry-oriented plastic recycling system relies greatly on the accuracy of the waste sorting technique adapted. We propose a multi-modal spectroscopic sensor which combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy in a single optical platform for characterizing plastics based on elemental and molecular information to assist the plastic identification-sorting process in recycling industries. The unique geometry of the system makes it compact and cost-effective for dual spectroscopy. The performance of the system in classifying industrially important plastic classes counting PP, PC, PLA, Nylon-1 1, and PMMA is evaluated, followed by the application of the same in real-world plastics comprising PET, HDPE, and PP in different chemical-physical conditions where the system consumes less than 30 ms for acquiring LIBS-Raman signals. The evaluation of the system in characterizing commuting samples shows promising results to be applied in industrial conditions in future. The study on effect of physical-chemical conditions of plastic wastes in characterizing them using the system shows the necessity for combining multiple techniques together. The proposal is not to determine the paramount methodology to characterize and sort plastics, but to demonstrate the advantages of dual-spectroscopy sensors in such applications. The outcomes of the study suggest that the system developed herein has the potential of emerging as an industrial-level plastic waste sorting sensor., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

There is an urgent need to have reliable technologies to diagnose post-coronavirus disease syndrome (PCS), as the number of people affected by COVID-19 and related complications is increasing worldwide. Considering the amount of risks associated with the two chronic lung diseases, asthma and chronic obstructive pulmonary disease (COPD), there is an immediate requirement for a screening method for PCS, which also produce symptoms similar to these conditions, especially since very often, many COVID-19 cases remain undetected because a good share of such patients is asymptomatic. Breath analysis techniques are getting attention since they are highly non-invasive methods for disease diagnosis, can be implemented easily for point-of-care applications even in primary health care centres. Electronic (E-) nose technology is coming up with better reliability, ease of operation, and affordability to all, and it can generate signatures of volatile organic compounds (VOCs) in exhaled breath as markers of diseases. The present report is an outcome of a pilot study using an E-nose device on breath samples of cohorts of PCS, asthma, and normal (control) subjects. Match/no-match and k-NN analysis tests have been carried out to confirm the diagnosis of PCS. The prediction model has given 100% sensitivity and specificity. Receiver operating characteristics (ROC) has been plotted for the prediction model, and the area under the curve (AUC) is obtained as 1. The E-nose technique is found to be working well for PCS diagnosis. Our study suggests that the breath analysis using E-nose can be used as a point-of-care diagnosis of PCS.Trial registrationBreath samples were collected from the Kasturba Hospital, Manipal. Ethical clearance was obtained from the Institutional Ethics Committee, Kasturba Medical College, Manipal (IEC 60/2021, 13/01/2021) and Indian Council of Medical Research (ICMR) (CTRI/2021/02/031357, 06/02/2021) Government of India; trials were prospectively registered., (© 2022. The Author(s).)

Research activities are in full swing globally to translate the use of saliva as a non-invasive and highly potential specimen for clinical diagnostics, particularly for COVID-19 detection. Being comprised of a pool of biomarkers also enriched with ACE-2 receptors, saliva can provide vital information regarding the state of the human body. Advancements in biophotonics tools for saliva investigation may offer promise for developing rapid, highly objective, optical modalities for COVID- 19 detection. This article presents concept/design study, which propose the use of Raman/laser induced fluorescence spectroscopic device that have the potential for viral detection via saliva from a safer distance. Noticeable changes of biomarkers present in saliva in response to viral infection can reflect the pathological state, thus can altogether affect the Raman spectral pattern. Monitoring these spectral patterns of saliva, which are further enhanced by using cost effective and reproducible Surface Enhanced Raman Spectroscopy substrates can be a viable option for sensitive and non-invasive viral detection. The spectral information acquired from the optical device can be processed using various multivariate statistical analytical tools, which ultimately facilitate effective viral detection in few minutes. This method doesn't demand the necessity of qualified professionals and sample processing with reagents unlike in RT-PCR test. The proposed optical device can be further modified into a portable form, which can be easily transported for field applications. The stand-off observation, contactless and highly non-invasive technique can be of paramount importance in the current context, where the safer screening of a large population for viral infection by maintaining social distances is a necessity. The proposed stand-off spectroscopic technique can also address the major concern of nosocomial viral transmission amongst healthcare workers during sample collection in a pandemic scenario., (© 2021 Published by Elsevier B.V.)

Introduction : Human blood and saliva are increasingly under investigation for the detection of biomarkers for early diagnosis of non-communicable (e.g.cancers) and communicable diseases like COVID-19. Exploring the potential application of human tears, an easily accessible body fluid, for the diagnosis of various diseases is the need of the hour. Areas covered : This review deals with a comprehensive account of applications of tear analysis using different techniques, their comparison and overall progress achieved till now. The techniques used for tear fluid analysis are HPLC/UPLC/SDS-PAGE, CE, etc., together with ELISA, Mass Spectrometry, etc. But, with advances in instrumentation and data processing methods, it has become easy to couple the various separation methods with highly sensitive optical techniques for the analysis of body fluids. Expert opinion : Tear analysis can provide valuable information about the health condition of the eyes since it contains several molecular constituents, and their relative concentrations may alter under abnormal conditions. Tear analysis has the advantage that it is totally non-invasive. This study recommends tear fluid as a reliable clinical sample to be probed by highly sensitive optical techniques to diagnose different health conditions, with special emphasis on eye diseases.

Human saliva can be treated as a pool of biological markers able to reflect on the state of personal health. Recent years have witnessed an increase in the use of optical devices for the analysis of body fluids. Several groups have carried out studies investigating the potential of saliva as a non-invasive and reliable clinical specimen for use in medical diagnostics. This brief review aims to highlight the optical technologies, mainly surface plasmon resonance (SPR), Raman, and Fourier transform infrared (FTIR) spectroscopy, which are being used for the probing of saliva for diverse biomedical applications. Advances in bio photonics offer the promise of unambiguous, objective and fast detection of abnormal health conditions and viral infections (such as COVID-19) from the analysis of saliva., (© The Author(s) 2021.)

There are a number of analytical techniques used to study material related problems. Most of them imply experimental determination of parameters and functions by means of which elemental, optical and other properties of materials can be described. Laser Induced Breakdown Spectroscopy (LIBS) and Raman spectroscopy are highly complementary spectroscopic techniques used for lab, in-situ, and remote analyses of materials. The LIBS-Raman system provides further information compared to other conventional techniques since it can detect the presence of low atomic number-elements, isotopic composition, hydration and structure of trace materials which may be present as surface layers etc., which are very difficult, if not impossible, by portable X-ray based systems. A setup for LIBS and Raman spectroscopy measurements in a single unit has been developed and reported recently by us using an echelle spectrograph system. The system utilizes a single nanosecond pulsed Nd:YAG laser (532 nm) and an ICCD coupled echelle spectrograph for both measurements. The unit has been successfully used for multipurpose applications such as identification of minerals, pigments etc and also for checking quality assurance. The combined atomic and molecular information from the same location on a sample, at several locations, can provide more comprehensive information regarding its properties than using either of these quantities taken singly. In many cases, it has been observed that the high resolution of the echelle spectrograph provides better quality Raman signals by virtue of the small degeneracy/crystal field splitting of many fundamental Raman bands. This can provide valuable information on inclusions in bulk samples, changes due to symmetry alteration or complex formation with surroundings, hydrogen bonding etc. The advantage of echelle system to identify natural and artificial pigments by identifying the minor and trace components by the spectra of the elements therein, is also helpful in many situations. In the present paper, the orthogonal use of LIBS and Raman spectroscopy is assessed and highlighted. The results clearly demonstrate the potential of echelle-based LIBS-Raman system in applications where more detailed information on complex samples like minerals, archaeological artifacts etc, is required with minimum sample damage or consumption., (Copyright © 2019 Elsevier B.V. All rights reserved.)

We have developed and standardized a novel hybrid laser-induced breakdown spectroscopy (LIBS)-Raman system using a single pulsed laser and a high-resolution intensified charge coupled device coupled echelle spectrograph. LIBS and Raman spectroscopy are highly complementary techniques which yield elemental and molecular information. Both techniques share an apparently similar instrumental configuration but need entirely different requirements like spectral range covered, resolution, and light-gathering efficiencies. There are thus many challenges to be faced in developing a combined system. In the present work, we show that an echelle spectrograph combined with a compact Q-switched Nd:YAG laser operating at 532 nm as an excitation source in a portable configuration can be efficiently used for such multi-purpose spectroscopy. Atomic and molecular emissions from the sample surface have been recorded in a gated mode using this setup. Compared to conventional spectrographs, echelle provides simultaneous broad bandpass (250-900 nm) and better spectral resolution at an extremely small fixed slit width of 10 × 50 μm without moving the dispersive elements. The echelle-based hyphenated system provides fast and reliable analysis of materials with combined atomic and molecular spectra of the same spot with better reliability. In this paper, we discuss the optimization of various instrumental parameters and optical components of this hyphenated system using a medium Raman cross section sample, CaCO 3 . The feasibility of single shot LIBS-Raman measurement capabilities of echelle has also been demonstrated using the developed system.

Presence of renal-calculi (kidney stones) in human urethra is being increasingly diagnosed over the last decade and is considered as one of the most painful urological disorders. Accurate analysis of such stones plays a vital role in the evaluation of urolithiasis patients and in turn helps the clinicians toward exact etiologies. Two highly complementary laser-based analytical techniques; laser-induced breakdown spectroscopy (LIBS) and micro-Raman spectroscopy have been used to identify the chemical composition of different types of renal-calculi. LIBS explores elemental characteristics while Raman spectroscopy provides molecular details of the sample. This complete information on the sample composition might help clinicians to identify the key aspects of the formation of kidney stones, hence assist in therapeutic management and to prevent recurrence. The complementarity of both techniques has been emphasized and discussed. LIBS spectra of different types of stones suggest the probable composition of it by virtue of the major, minor and trace elements detected from the sample. However, it failed to differentiate the crystalline form of different hydrates of calcium oxalate stone. This lacuna was overcome by the use of Raman spectroscopy and these results are compared with conventional chemical analysis., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Classification of plastics is of great importance in the recycling industry as the littering of plastic wastes increases day by day as a result of its extensive use. In this paper, we demonstrate the efficacy of a combined laser-induced breakdown spectroscopy (LIBS)-Raman system for the rapid identification and classification of post-consumer plastics. The atomic information and molecular information of polyethylene terephthalate, polyethylene, polypropylene, and polystyrene were studied using plasma emission spectra and scattered signal obtained in the LIBS and Raman technique, respectively. The collected spectral features of the samples were analyzed using statistical tools (principal component analysis, Mahalanobis distance) to categorize the plastics. The analyses of the data clearly show that elemental information and molecular information obtained from these techniques are efficient for classification of plastics. In addition, the molecular information collected via Raman spectroscopy exhibits clearly distinct features for the transparent plastics (100% discrimination), whereas the LIBS technique shows better spectral feature differences for the colored samples. The study shows that the information obtained from these complementary techniques allows the complete classification of the plastic samples, irrespective of the color or additives. This work further throws some light on the fact that the potential limitations of any of these techniques for sample identification can be overcome by the complementarity of these two techniques. Graphical Abstract ᅟ.

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper., Biological Significance: In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Cervical cancer, the second most common cancer in women, progresses silently over long periods before producing any clinical manifestation. Research in early detection of this condition using proteomic techniques is of very recent origin. We used high-performance liquid chromatography combined with laser-induced fluorescence method in our lab to record the protein profiles of tissue homogenate, cell lysate and serum samples of normal and different stages of malignant conditions of the cervix. Information on protein markers in the protein profiles was derived using various data processing methods including curve resolution. The variations in relative intensities of different peaks with respect to peak height, width and area under the curve from different sample types were compared to get information regarding the concentration of the various proteins and their significance in the induction and metastasis of cervical cancer. The method can be used in diagnosis, follow-up with respect to the progression, remission and effective therapy, in cervical malignancy., (© The Author [2014]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

An ultra-sensitive hyphenated technique, high-performance liquid chromatography-laser-induced fluorescence detection protein profiling of saliva, is evaluated for early detection and diagnosis of oral premalignancy and malignancy. Calibration sets of protein profiles of unstimulated whole saliva are collected from clinically/pathologically normal, premalignant, and malignant subjects and used as standards. Three parameters-scores of factors, sum of squared residuals, and Mahalanobis distance-derived from principal component analysis of protein profiles of the standard calibration sets, and blind samples are used for "match/no-match" diagnosis of the blind samples. Analyses of the results show that the method is capable of differentiating normal, premalignant, and malignant conditions with the sensitivity and specificity of 79% and 78%, respectively. The technique provides a fast, highly objective (free from personal judgment and statistically defined), and noninvasive diagnostic method for screening and early detection of oral cancer.

A highly objective method, High Performance Liquid Chromatography with Laser Induced Fluorescence (HPLC-LIF) technique was used to study the protein profiles of normal and cervical cancer tissue homogenates. A total of 44 samples including normal cervical biopsy samples from the hysterectomy patients and the patients suffering from different stages of the cervical cancer were recorded by HPLC-LIF and analysed by Principle Component Analysis (PCA) to get statistical information on different tissue components. Discrimination of different stages of the samples was carried out by considering three parameters--scores of factor, spectral residual, and Mahalanobis Distance. Diagnostic accuracy of the method was evaluated using Receiver Operating Characteristic (ROC) analysis, and Youden's index (J) plots. The PCA results showed high sensitivity and specificity (~100) for cervical cancer diagnosis. ROC and Youden's index curves for both normal and malignant standard sets show good diagnostic accuracy with high AUC values. The statistical analysis has shown that the differences in protein profiles can be used to diagnose biochemical changes in the tissue, and thus can be readily applied for the detection of cervical cancer, even in situations where a histopathology examination is not easy because of nonavailability of experienced pathologists.

Protein profiles of cytologic samples from the cervix were studied using High Performance Liquid Chromatographic (HPLC) separation combined with ultra-sensitive laser induced fluorescence (LIF) detection. HPLC-LIF protein profiles of samples from clinically normal subjects, individuals suffering from cervical cancer (different stages), and subjects who had other gynecological problems related to cervix, like erosion of cervix and Nabothian cyst, but no malignancy, were subjected to Principal Component Analysis (PCA). The application of HPLC-LIF protein profiling combined with PCA was found to be a highly efficient method for discrimination of different classes of samples with high sensitivity and specificity. Diagnostic accuracy and optimal threshold - decision criterion - for objective discrimination were estimated using sensitivity-specificity pairs and Youden's index (J) plots., (Copyright © 2010 Elsevier B.V. All rights reserved.)

The present work deals with the evaluation of a high-performance liquid chromatography laser-induced fluorescence (HPLC-LIF) technique developed in our laboratory for early detection of oral cancer from protein profiles of body fluids. The results show that protein profiles of serum samples from a given class of samples, say, normal, premalignant, or malignant, are statistically very close to each other, while profiles of members of any class are significantly different from other classes. The performance of the technique is evaluated by the use of sensitivity and specificity pairs, receiver operating characteristic (ROC) analysis, and Youden's Index. The technique uses protein profile differences in serum samples, registered by the HPLC-LIF technique. The study is carried out using serum samples from volunteers diagnosed as normal or premalignant clinically, and as malignant by histopathology. The specificities and sensitivities of the HPLC-LIF method at an ideal threshold (M-distance = 2) for normal, malignant, and premalignant classes are 100, 69.5, and 61.5%, and 86.5, 87.5, and 87.5% respectively.

High performance liquid chromatography with high sensitivity laser-induced fluorescence detection is used to study the protein profiles of serum samples from healthy volunteers and cervical cancer subjects. The protein profiles are subjected to principal component analysis (PCA). PCA shows that the large number of chromatograms of a given class of serum samples--say normal/malignant--can be expressed in terms of a small number of factors (principal components). Three parameters--scores of the factors, squared residuals, and Mahalanobis distance--are derived from PCA. The parameters are observed to have a narrow range for protein profiles of standard calibration sets formed from groups of clinically confirmed normal/malignant classes. Limit tests using match/no match of the parameters of any test sample with parameters derived for the standard calibration sets give very good discrimination between malignant and normal samples with high sensitivity (approximately 100%) aand specificity (approximately 94%).

An experimental system for measuring simultaneously photoacoustic (PA) and fluorescence signals is described. The simultaneous measurement of laser induced fluorescence and photoacoustic signals provide a suitable method for the study of different quenching phenomena occurring in fluorescent systems. In this paper we report tryptophan solvation dynamics in water using fluorescence and photoacoustic spectra recorded simultaneously by photoacoustic and fluorescence signals as functions of concentration, indicate that quantum yield is maximum at low concentrations. Also, the energy lost in the fluorescence path of tryptophan, due to different quenching phenomena like self quenching, Resonance energy transfer (RET), solvation relaxation, etc. is clearly seen from the photoacoustic signal intensity which increases as the fluorescence intensity decreases.

Radiotherapy is the choice of treatment for locally advanced stages of the cervical cancers, one of the leading female cancers. Because of intrinsic factors, tumors of same clinical stage and histological type often exhibit differential radioresponse. Radiotherapy regimen, from first fraction of treatment to clinical evaluation of response, spans more than 4 months. Clinical assessment by degree of tumor shrinkage is the only routinely practiced method to evaluate the tumor response. Hence, a need is created for development new methodologies that can predict the tumor response to radiotherapy at an early stage of the treatment which can lead to tailor-made protocols. To explore the feasibility of prediction of tumor radioresponse, Raman spectra of cervix cancer tissues that were collected before (malignant) and 24 h after patient was treated with 2nd fraction of radiotherapy (RT) were recorded. Data were analyzed by Principal Components Analysis (PCA) and results were correlated with clinical evaluation of radioresponse. Mean Raman spectra of RT tissues corresponding to different levels of tumor response, complete, partial, and no response, showed minute but significant variations. The unsupervised PCA of malignant tissues failed to provide any classification whereas RT spectra gave clear classification between responding (complete and partial response) and nonresponding conditions as well as a tendency of separation among responding conditions. These results were corroborated by supervised classification, by means of discrimination parameters: Mahalanobis distance and spectral residuals. Thus, findings of the study suggest the feasibility of Raman spectroscopic prediction of tumor radioresponse in cervical cancers.

Optical histopathology is fast emerging as a potential tool in cancer diagnosis. Fresh tissues in saline are ideal samples for optical histopathology. However, evaluation of suitability of ex vivo handled tissues is necessitated because of severe constraints in sample procurement, handling, and other associated problems with fresh tissues. Among these methods, formalin-fixed samples are shown to be suitable for optical histopathology. However, it is necessary to further evaluate this method from the point of view discriminating tissues with minute biochemical variations. A pilot Raman and Fourier transform infrared (FTIR) microspectroscopic studies of formalin-fixed tissues normal, malignant, and after-2-fractions of radiotherapy from the same malignant cervix subjects were carried out, with an aim to explore the feasibility of discriminating these tissues, especially the tissues after-2-fractions of radiotherapy from other two groups. Raman and FTIR spectra exhibit large differences for normal and malignant tissues and subtle differences are seen between malignant and after-2-fractions of radiotherapy tissues. Spectral data were analyzed by principal component analysis (PCA) and it provided good discrimination of normal and malignant tissues. PCA of data of three tissues, normal, malignant, and 2-fractions after radiotherapy, gave two clusters corresponding to normal and malignant + after-2-fractions of radiotherapy tissues. A second step of PCA was required to achieve discrimination between malignant and after-2-fractions of radiotherapy tissues. Hence, this study not only further supports the use of formalin-fixed tissues in optical histopathology, especially from Raman spectroscopy point of view, it also indicates feasibility of discriminating tissues with minute biochemical differences such as malignant and after-2-fractions of radiotherapy., (2006 Wiley Periodicals, Inc.)

Cancer cells escape cytotoxic effects of anticancer drugs by a process known as multidrug resistance (MDR). Identification of cell status by less time-consuming methods can be extremely useful in patient management and treatment. This study aims at evaluating the potentials of vibrational spectroscopic methods to perform cell typing and to differentiate between sensitive and resistant human cancer cell lines, in particular those that exhibit the MDR phenotype. Micro-Raman and Fourier transform infrared (FTIR) spectra have been acquired from the sensitive promyelocytic HL60 leukemia cell line and two of its subclones resistant to doxorubicin (HL60/DOX) and daunorubicin (HL60/DNR), and from the sensitive MCF7 breast cancer cell line and its MDR counterpart resistant to verapamil (MCF7/VP). Principal components analysis (PCA) was employed for spectral comparison and classification. Our data show that cell typing was feasible with both methods, giving two distinct clusters for HL60- and MCF7-sensitive cells. In addition, phenotyping of HL60 cells, i.e., discriminating between the sensitive and MDR phenotypes, was attempted by both methods. FTIR could not only delineate between the sensitive and resistant HL60 cells, but also gave two distinct clusters for the resistant cells, which required a two-step procedure with Raman spectra. In the case of MCF7 cell lines, both the sensitive and resistant phenotypes could be differentiated very efficiently by PCA analysis of their FTIR and Raman point spectra. These results indicate the prospective applicability of FTIR and micro-Raman approaches in the differentiation of cell types as well as characterization of the cell status, such as the MDR phenotype exhibited in resistant leukemia cell lines like HL60 and MCF7., ((c) 2006 Wiley Periodicals, Inc.)

In the present work, we examine normal and malignant stage IIIB cervical tissue by laser induced fluorescence, with 2 different objectives. (i) Development of the fluorescence spectroscopy technique as a standard optical method for discrimination of normal and malignant tissue samples and, (ii) Optimization of the technique by the method of matching of a sample spectrum with calibration sets of spectra of pathologically certified samples. Laser-induced fluorescence spectra were measured using samples from 62 subjects at different excitation wavelengths. Principal component analysis (PCA) of spectra and intensity ratios of curve-resolved fluorescence peaks were tested for discrimination. It was found that PCA of total fluorescence at 325 nm excitation gives specificity and sensitivity over 95%. Use of calibration sets of spectra of histo-pathologically certified samples combined with PCA for matching and pass/fail classification of test samples is shown to have high sensitivity/specificity for routine diagnostic purposes as well as for possible staging of the disease. Further, the multi-component origin of the fluorescence spectra is illustrated by curve resolution and fluorescence spectra of separated proteins of tissue homogenates.

Pulsed laser-induced autofluorescence spectroscopic studies of pathologically certified normal, premalignant, and malignant oral tissues were carried out at 325 nm excitation. The spectral analysis and classification for discrimination among normal, premalignant, and malignant conditions were performed using principal component analysis (PCA) and artificial neural network (ANN) separately on the same set of spectral data. In case of PCA, spectral residuals, Mahalanobis distance, and scores of factors were used for discrimination among normal, premalignant, and malignant cases. In ANN, parameters like mean, spectral residual, standard deviation, and total energy were used to train the network. The ANN used in this study is a classical multiplayer feed-forward type with a back-propagation algorithm for the training of the network. The specificity and sensitivity were determined in both classification schemes. In the case of PCA, they are 100 and 92.9%, respectively, whereas for ANN they are 100 and 96.5% for the data set considered., (Copyright 2005 Wiley Periodicals, Inc.)

Quasielastic neutron scattering (QENS) and Fourier transform infrared spectroscopic studies were carried out on methanol molecules adsorbed in HMCM-41 and HZSM-5 molecular sieves to monitor the effect of pore structure on their occluded state under the conditions of ambient temperature and 5-250 mbar pressures. The QENS results have shown that the pore geometry of the host matrix and the dipolar character of the adsorbate are together responsible for the binding state of guest molecules in the confining medium. Thus, neither translational nor free rotational motion was noticed for methanol molecules adsorbed in HZSM-5, in contrast to benzene and cyclohexane molecules of almost similar size that are reported to undergo a rotational motion under the identical conditions of loading (Phys. Chem. Chem. Phys. 2001, 3, 4449; 2003, 5, 3066). In the case of HMCM-41, a translational motion of occluded methanol molecules was clearly observed with a diffusion constant D approximately 1.5 x 10(-5) cm2 s(-1), as compared to a value of D approximately 2.6 x 10(-5) cm2 s(-1) for its liquid state. These results indicate that the adsorbed methanol experiences a considerable extent of supercooling due to capillary condensation in zeolitic pores, giving rise to formation of a metastable state even at room temperature. In HZSM-5, entrapped methanol exists in an almost solidlike state, whereas in HMCM-41, its density lies between that of the solid and the liquid phases. Infrared spectroscopic study conducted using deuterium-labeled adsorbate and host matrixes have given evidence for different kinds of interactions between the methanol molecules and the host matrix, depending upon the loading. For small loadings the internal hydroxy groups within the pore system get perturbed first, giving rise to formation of the methoxy groups. Multilayer adsorption and capillary condensation of methanol occur for a loading of 0.05 mmol per gram and above, within the pore system and also at the external surface, giving rise to a highly compressed state due to strong intermolecular bonding. At the same time, a considerable amount of exchange occurred between the hydroxy groups of the adsorbed methanol and those of the host matrix. Such exchange of hydroxy groups may play an important role in the catalytic properties of the porous aluminosilicates.

Optical spectroscopy methods are fast emerging as potential alternatives for early diagnosis of cancer. A Raman spectroscopy method for discrimination of normal and malignant oral tissues has been developed by us earlier. It is necessary to evaluate and establish the validity of the approach before it can be routinely used. In the present study, our Raman spectroscopy investigations are extended further to evaluate the efficacy of the technique to discriminate between normal, inflammatory, premalignant, and malignant conditions in oral tissue. Spectral profiles of normal, malignant, premalignant, and inflammatory conditions show pronounced differences between one another. Spectra of normal tissues can be attributed mainly to lipids whereas pathological tissue spectra are dominated by proteins. Principal components analysis (PCA) of the spectral data sets belonging to the four different categories showed that scores of factors differentiated between normal and all pathological conditions but gave only poor discrimination among the three pathological states. PCA combined with multiparameter limit tests allow match/mismatch criteria to be applied to test samples when pathologically certified calibration sets are available in each class. It is shown that by this method all the four tissue types could be discriminated and diagnosed correctly. The biochemical differences between normal and pathological conditions of oral tissue are also discussed from spectral differences of the different classes of spectra., (Copyright (c) 2005 Wiley Periodicals, Inc.)

Multidrug resistance (MDR) enables cancer cells to escape cytotoxic insults of anticancer drugs. Rapid identification of cells exhibiting the MDR phenotype is very important since it can lead to an effective and individual patient based treatment plan. We have investigated a combined vibrational spectroscopic approach, using both micro-Raman and FTIR techniques, in order to characterise a sensitive human uterine sarcoma cell line MES-SA and its multidrug-resistant derivative Garf. In this study, these two complementary methods have been evaluated via the use of principal components analysis (PCA), for discrimination of cells exhibiting the MDR phenotype. Our results indicate that, though they inherently have different sensitivities, both Raman and IR methods can provide a good differentiation of cell phenotypes.

Micro-Raman spectra of formalin-fixed oral squamous normal and carcinoma tissues, stored at room temperature for 2 months, have been recorded. Spectra were recorded both in the epithelial and subepithelial regions of the tissues. No noticeable spectral contamination due to formalin was observed. Very significant differences between spectra of normal epithelial and malignant epithelial samples were found. No such differences in spectra of subepithelial malignant and subepithelial normal samples could be observed. This study shows that spectra from the epithelial region changes drastically because of malignancy-induced biochemical changes in this region. Major differences between normal and malignant spectra seem to arise from the protein composition, conformational/structural changes, and possible increase in protein content in malignant epithelia. The differences between normal epithelial and subepithelial spectra, as expected, arise mainly from the collagen in subepithelial tissue. Principal component analysis of the combined sets of spectra-epithelial and subepithelial, normal and malignant- showed that very good discrimination can be achieved by Raman microspectroscopy. This study thus validates the suitability of formalin-fixed tissues for optical pathology in oral malignancy.

Pulsed laser-induced-fluorescence studies of pathologically certified oral tissues are carried out at different excitations and time delays. Among the several excitations used, 325 nm produced noticeably different spectral profile for normal and malignant tissues. Extensive curve analysis was carried out in order to understand changes in biochemical composition of tissue based on spectral profiles. Curve resolution and principal component analysis (PCA) show that the fluorescence intensity changes from normal to malignant tissue samples are not completely explained in terms of simple collagen and NAD(P)H intensity changes. The spectra require at least five components to be fully accounted for. Several discrimination methodologies based on PCA and intensity differences between different emission peaks (resultant peaks of curve analysis) were also evaluated. The results obtained indicate PCA using Mahalanobis distance and spectral residual as discrimination parameters provides best discrimination and can be used for matching unknown samples to standard calibration sets. Intensity ratio of bound NAD(P)H to collagen seems to be more suitable for discrimination between normal and malignant oral tissue, compared to ratio of collagen to total intensity of all the other components together.

The single crystals of glycinium oxalate are grown by slow evaporation technique and vibrational spectral analysis is carried out using NIR-FT Raman and FT-IR spectra. The ab initio quantum computations are also performed at HF/6-31 G(d) level to derive the optimized geometry, atomic charges and vibrational frequencies of the glycinium oxalate molecule. Vibrational analysis indicates the presence of peculiar intermolecular C-H...O hydrogen bonding interaction producing "blue shift" of C-H stretching frequency. The vibrational spectra confirm the existence of NH3(+) in glycinium oxalate. Hydroxyl vibrations with different inter and intra molecular H-bonding are analysed, supported by computed results.

Laser Raman spectroscopy has been used in this study to characterize mandibular bone samples from patients who had undergone radiation therapy for oral cancer. The paper discusses spectral changes resulting in osteoradionecrosis (ORN) of the mandibular bone, a serious complication that may occur after radiation therapy. Histopathological studies normally reveal the radiation damage on vascular canals and loss in bone cells, but will not reveal any structural or biochemical changes. All radiation-induced side effects are attributed to this hypovascularity and hypocellularity caused by early- and/or late-delayed effects. Our Raman studies on normal and ORN bone and on bone exposed to radiation, but not in the ORN state, show that irradiation produces immediate structural changes in the inorganic bone matrix with a slight loss in cells. ORN bone, in addition to the structural changes that had already occurred on radiation exposure, shows almost complete loss of cellular components. Since bone tissue is continuously being remodeled (dissolved and rebuilt) under normal conditions, our results suggest that the immediate structural changes in the calcium hydroxy apatite mineral part is not repaired in ORN, due to loss of the highly transient osteoblasts and osteoclasts resulting from destruction of stem cells. The spectral studies also show changes in the organic matrix, which is mostly type I collagen.

Radiotherapy is routinely employed in the treatment of head and neck cancers. Acute cell death, radiation-activated chemical cascades, and the induction of genes coding for protective factors like cytokines are considered to be the major processes involved in radiation damage and repair. It should be possible to follow these processes by monitoring the biochemical interactions initiated by radiation. We have carried out Raman spectroscopy studies on tissue from mice subjected to brain irradiation to identify the biochemical changes occurring in tissue and brain as a result of radiation injury. These studies show that brain irradiation produces drastic spectral changes even in tissue far removed from the irradiation site. The changes are very similar to those produced by the stress of inoculation and restraint and the administration of an anesthetic drug. While the changes produced by stress or anesthetics last for only a short time (a few hours to 1 or 2 days), radiation-induced changes persist even after 1 week. The spectral changes can be interpreted in terms of the observation of new spectra that are dominated by bands due to proteins. The results thus support the hypothesis that various protective factors are released throughout the body when the central nervous system (CNS) is exposed to radiation.

The temporal behavior of uranium neutrals in the postdischarge conditions in a pulsed hollow cathode discharge has been investigated by monitoring the time dependent absorption of the output radiation of a single-axial-mode dye laser by uranium atoms. Studies of the kinetics of the absorption suggest that electron ion recombination followed by deactivation, Penning ionization, and diffusion to the cathode wall are the dominant mechanisms in the postdischarge conditions.