Search

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.)

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.)

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.)

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.)

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.)

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.)

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.)

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.)

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.

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.