Browsing by Author "Dhakne, Rahul"
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- Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overviewPublication . Pereira, Jorge; Porto-Figueira, Priscilla; Cavaco, Carina; Taunk, Khushman; Rapole, Srikanth; Dhakne, Rahul; Nagarajaram, Hampapathalu; Câmara, JoséCurrently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.
- Investigation of urinary volatomic alterations in head and neck cancer: a non-invasive approach towards diagnosis and prognosisPublication . Taware, Ravindra; Taunk, Khushman; Pereira, Jorge A. M.; Dhakne, Rahul; Kannan, Narayanan; Soneji, Dharmesh; Câmara, José S.; Nagarajaram, H. A.; Rapole, SrikanthIntroduction Head and neck cancer (HNC), like many other forms of cancer, is usually detected in advanced stages, causing poor survival outcomes. Lack of specific and sensi tive screening markers for early detection of HNC has wors ened the scenario for the patients as well as the clinicians. Therefore, identification of efficient, noninvasive and afford able screening marker/methodology with high specificity and sensitivity is imminent need of situation. Objectives This study aims to identify and characterize urinary volatomic alterations specific to HNC. Methods Volatomic analysis of urine samples collected from HNC patients (n=29) and healthy controls (n=31) was performed using headspace solid phase microextraction coupled to gas chromatography mass spectrometry (GC– MS). Both univariate and multivariate statistical approaches were used to investigate HNC specific volatomic alterations. Results Statistical analysis revealed a total of 28 metabo lites with highest contribution towards discrimination of HNC patients from healthy controls (VIP >1, p < 0.05, Log2 FC ≥0.58/≤−0.57). The discrimination efficiency and accuracy of urinary VOCs was ascertained by ROC curve analysis that allowed the identification of four metabolites viz. 2,6-dimethyl-7-octen-2-ol, 1-butanol, p-xylene and 4-methyl-2-heptanone with highest sensitivity and speci ficity to discriminate HNC patients from healthy controls. Further, the metabolic pathway analysis identified several dysregulated pathways in HNC patients and their detailed investigations could unravel novel mechanistic insights into the disease pathophysiology. Conclusion Overall, this study provides valuable finger print of the volatile profile of HNC patients, which in turn, might help in improving the current understanding of this form of cancer and lead to the development of non-invasive approaches for HNC diagnosis.