Can Ayurveda be leveraged for COVID-19?

The world is experiencing an unprecedented health crisis as a result of the highly infectious novel coronavirus. Even economically powerful countries with the best healthcare and technology infrastructure are struggling to contain COVID-19. Conventional medicine is racing against time to produce vaccine and repurpose drugs used in other viral diseases. India has been using its resources maximally to fight COVID-19. However, it is yet to make full use of one of its major resource, namely AYUSH (Ayurveda, Yoga, Unaani, Siddha and Homeopathy) systems. Ayurveda, which occupies a prime position in the AYUSH systems, has a huge knowledge base and infrastructure accessible in terms of registered practitioners, dispensaries, colleges, hospitals, pharmacies, research centres, etc. It is hence only logical that in a crisis like COVID -19, ayurveda is utilised for the public. Considering the vast clinical knowledge and experience available with ayurveda, this sector should definitely be an advantage for India. This article will discuss why and how the knowledge base and support system of ayurveda sector should be leveraged in trying times as the present one

Spectroscopic and E-tongue evaluation of medicinal plants: A taste of how rasa can be studied

AbstractBackgroundThe use of medicinal plants in Ayurveda is based on rasa, generally taken to represent taste as a sensory perception. This chemosensory parameter plays an important role in Ayurvedic pharmacology.ObjectiveThe aim is to explore the use of structuro-functional information deduced from analytical techniques for the rasa-based classification of medicinal plants in Ayurveda.Materials and methodsMethods of differential sensing and spectroscopic metabolomics have been used in select medicinal plants from three different taste categories (sweet, pungent and multiple taste): Tribulus terrestris, Vitis vinifera and Glycyrrhiza glabra from sweet category; Piper longum, Cuminum cyminum and Capsicum annum from pungent group; Emblica officinalis with five tastes. While Electronic tongue was used for evaluation of the sensorial property of taste, the chemical properties were studied with Nuclear Magnetic Resonance (NMR), Fourier Transform InfraRed (FTIR) and Laser Induced Breakdown Spectroscopy (LIBS).ResultsIn terms of taste and phytochemical profiles, all samples were unique but with similarities within each group. While the sensor response in E-tongue showed similarities within the sweet and pungent categories, NMR spectra in the aromatic region showed close similarities between the plants in the sweet category. The sensory, phytochemical and phytoelemental profiles of E. officinalis (with five rasa) in particular, were unique.ConclusionA combination of sensorial and chemical descriptors is a promising approach for a comprehensive evaluation and fingerprinting of the Ayurvedic pharmacological parameter rasa

Sequential diffusion-weighted magnetic resonance imaging study of lysophosphatidyl choline-induced experimental demyelinating lesion: an animal model of multiple sclerosis

Purpose: To differentiate the surrounding edema from the focal demyelinating lesion during the early phase of the lesion using an apparent diffusion coefficient (ADC), and to monitor the changes in ADCs during the complete progression of a lysophosphatidyl choline (LPC)-induced experimental demyelinating lesion, an animal model of multiple sclerosis (MS). Material and Methods: Eighteen rats divided into two groups-demyelinating lesion (group I, N = 12) and vehicle group (saline injected; group II, N = 6)-were studied. A 0.2-μl quantity of 1% LPC solution in isotonic saline was injected in the rat brain internal capsule (IC) area to create the demyelinating lesion. Six rats were used exclusively for histology. Diffusion-weighted (DW) images were acquired at different diffusion weightings on the 3rd, 5th, 10th, 15th, and 20th days after LPC injection. ADC was measured from three regions of interest (ROIs) within the IC: focal demyelinating lesion (area A), surrounding area of the lesion (area B), and contralateral IC area (area C). Results: Histology revealed demyelination of the IC area during the early phase of lesion progression up to day 10 and remyelination thereafter. Elevated ADCs were observed for the surrounding edematous area (area B), compared to the focal demyelinating lesion (area A) during the early phase of the demyelination process, while substantial reduction of ADCs was noticed during remyelination for both regions. Conclusion: Measurement of ADC showed clear differentiation of the surrounding edema from the LPC-induced focal demyelinating lesion in rats, especially during the early phase of the lesion progression

MRS characterization of central neurocytomas using glycine

This study reports in vivo MRS findings in 11 patients with histologically diagnosed central neurocytomas, which are rare intraventricular tumors of neuronal origin. Single-voxel 1H MRS was carried out prior to surgery using a point-resolved spectroscopy sequence with TR=6s, TE=135 ms and 128 scans. In vitro high-resolution 1H spectroscopy was also carried out on two surgically excised samples. The striking features of the spectra from the central neurocytomas were the presence of high glycine, decreased N-acetylaspartate, increased choline and alanine. Retrospective, blind analysis of the spectra by two independent observers correctly identified all but one central neurocytoma based on the presence of glycine. The presence of glycine and prominent choline in the1H MR spectrum is a characteristic feature of the central neurocytomas, and could be used to characterize and differentiate them from other brain tumors

In vivo and in vitro MR spectroscopic profile of central neurocytomas

The metabolic differences between the muscle biopsies of patients with limb girdle muscular dystrophy (LGMD) and normal controls were characterized using high-resolution 1H and 13C NMR spectroscopy. In all, 44 metabolites were unambiguously assigned in the perchloric acid extracts of skeletal muscle tissue, using 2D double quantum filtered (DQF COSY), total correlation (TOCSY), and 1H/13C heteronuclear multiple quantum coherence (HMQC) spectroscopy. The concentrations of glycolytic substrate, glucose (p=0.03), gluconeogenic amino acids, glutamine (p=0.02) and alanine (p=0.009) together with glycolytic product, lactate (p=0.04), were found to be significantly lowered in LGMD patients as compared with controls. The reduction in the concentration of glucose may be attributed to the decrease in the concentration of gluconeogenic amino acids in the degenerated muscle. Reduction in the rate of anaerobic glycolysis and lowered substrate concentration appear to be the possible reasons for the decrease in the concentration of lactate. A significant reduction in the concentration of choline in LGMD patients was also observed compared with controls. Lower concentration of choline may be the result of decreased rate of membrane turnover in LGMD patients. The data presented here provide an insight into the potentials of in-vitro NMR spectroscopy in the study of muscle metabolism

Evaluation of folate conjugated pegylated thermosensitive magnetic nanocomposites for tumor imaging and therapy

Superparamagnetic iron oxide nanoparticles (SPIONs) have been receiving great attention lately in biomedical applications, such as in magnetic resonance imaging and drug delivery. However, their systemic administration still remains a challenge due to their hydrophobic nature with instances of aggregation leading to fast reticuloendothelial system (RES) uptake. In this study, magnetic nanocomposites with thermosensitive polymer have been investigated. Random polymers of N-isopropylacrylamide (NIPAAM), acrylic acid (AA) and PEGMA have been coated on SPIONs followed by conjugation with folic acid. Particles of ∼200 nm and low polydispersity 0.1–0.2 having a critical temperature (Tc) of 44 °C were formed. Thermogravimetric and powder X-ray diffraction studies showed that the nanocomposites were composed of 90% cubic face-centered magnetite. Nearly 76.5% doxorubicin was loaded onto the nanoparticles by diffusion method. Drug release was higher at the hyperthermia temperature (72.42 ± 5.25% in 48 h) proving the thermoresponsive nature of the polymer. Folate conjugated samples showed a magnetization value of 32 emu/g as well as high r1 and r2 relaxivities in magnetic resonance imaging. R2 weighted images of nanocomposites were darker than the control with 20 μg/mL as the darkest. At this concentration the magnetic composites showed nearly 95% viability in L929 fibroblast cells. These thermoresponsive nanosystems with pegylated surfaces and size of ∼200 nm are therefore highly suitable for in vivo imaging and hyperthermia based drug delivery

Image8_No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.TIF

Background: Ayurveda, the indigenous medical system of India, has chemosensory property (rasa) as one of its major pharmacological metric. Medicinal plants have been classified in Ayurveda under six rasas/tastes—sweet, sour, saline, pungent, bitter and astringent. This study has explored for the first time, the use of Electronic tongue for studies of rasa-based classification of medicinal plants.Methods: Seventy-eight medicinal plants, belonging to five taste categories (sweet, sour, pungent, bitter, astringent) were studied along with the reference taste standards (citric acid, hydrochloric acid, caffeine, quinine, L-alanine, glycine, β-glucose, sucrose, D-galactose, cellobiose, arabinose, maltose, mannose, lactose, xylose). The studies were carried out with the potentiometry-based Electronic tongue and the data was analysed using Principle Component Analysis, Discriminant Function Analysis, Taste Discrimination Analysis and Soft Independent Modeling of Class Analogy.Results: Chemosensory similarities were observed between taste standards and the plant samples–citric acid with sour group plants, sweet category plants with sucrose, glycine, β-glucose and D-galactose. The multivariate analyses could discriminate the sweet and sour, sweet and bitter, sweet and pungent, sour and pungent plant groups. Chemosensory category of plant (classified as unknown) could also be identified.Conclusion: This preliminary study has indicated the possibility of fingerprinting the chemosensory-based ayurvedic classification of medicinal plants using E-tongue coupled with multivariate statistical analysis.</p

Image1_No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.TIF

Background: Ayurveda, the indigenous medical system of India, has chemosensory property (rasa) as one of its major pharmacological metric. Medicinal plants have been classified in Ayurveda under six rasas/tastes—sweet, sour, saline, pungent, bitter and astringent. This study has explored for the first time, the use of Electronic tongue for studies of rasa-based classification of medicinal plants.Methods: Seventy-eight medicinal plants, belonging to five taste categories (sweet, sour, pungent, bitter, astringent) were studied along with the reference taste standards (citric acid, hydrochloric acid, caffeine, quinine, L-alanine, glycine, β-glucose, sucrose, D-galactose, cellobiose, arabinose, maltose, mannose, lactose, xylose). The studies were carried out with the potentiometry-based Electronic tongue and the data was analysed using Principle Component Analysis, Discriminant Function Analysis, Taste Discrimination Analysis and Soft Independent Modeling of Class Analogy.Results: Chemosensory similarities were observed between taste standards and the plant samples–citric acid with sour group plants, sweet category plants with sucrose, glycine, β-glucose and D-galactose. The multivariate analyses could discriminate the sweet and sour, sweet and bitter, sweet and pungent, sour and pungent plant groups. Chemosensory category of plant (classified as unknown) could also be identified.Conclusion: This preliminary study has indicated the possibility of fingerprinting the chemosensory-based ayurvedic classification of medicinal plants using E-tongue coupled with multivariate statistical analysis.</p

Image7_No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.TIF

Background: Ayurveda, the indigenous medical system of India, has chemosensory property (rasa) as one of its major pharmacological metric. Medicinal plants have been classified in Ayurveda under six rasas/tastes—sweet, sour, saline, pungent, bitter and astringent. This study has explored for the first time, the use of Electronic tongue for studies of rasa-based classification of medicinal plants.Methods: Seventy-eight medicinal plants, belonging to five taste categories (sweet, sour, pungent, bitter, astringent) were studied along with the reference taste standards (citric acid, hydrochloric acid, caffeine, quinine, L-alanine, glycine, β-glucose, sucrose, D-galactose, cellobiose, arabinose, maltose, mannose, lactose, xylose). The studies were carried out with the potentiometry-based Electronic tongue and the data was analysed using Principle Component Analysis, Discriminant Function Analysis, Taste Discrimination Analysis and Soft Independent Modeling of Class Analogy.Results: Chemosensory similarities were observed between taste standards and the plant samples–citric acid with sour group plants, sweet category plants with sucrose, glycine, β-glucose and D-galactose. The multivariate analyses could discriminate the sweet and sour, sweet and bitter, sweet and pungent, sour and pungent plant groups. Chemosensory category of plant (classified as unknown) could also be identified.Conclusion: This preliminary study has indicated the possibility of fingerprinting the chemosensory-based ayurvedic classification of medicinal plants using E-tongue coupled with multivariate statistical analysis.</p

Image4_No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.TIF

Background: Ayurveda, the indigenous medical system of India, has chemosensory property (rasa) as one of its major pharmacological metric. Medicinal plants have been classified in Ayurveda under six rasas/tastes—sweet, sour, saline, pungent, bitter and astringent. This study has explored for the first time, the use of Electronic tongue for studies of rasa-based classification of medicinal plants.Methods: Seventy-eight medicinal plants, belonging to five taste categories (sweet, sour, pungent, bitter, astringent) were studied along with the reference taste standards (citric acid, hydrochloric acid, caffeine, quinine, L-alanine, glycine, β-glucose, sucrose, D-galactose, cellobiose, arabinose, maltose, mannose, lactose, xylose). The studies were carried out with the potentiometry-based Electronic tongue and the data was analysed using Principle Component Analysis, Discriminant Function Analysis, Taste Discrimination Analysis and Soft Independent Modeling of Class Analogy.Results: Chemosensory similarities were observed between taste standards and the plant samples–citric acid with sour group plants, sweet category plants with sucrose, glycine, β-glucose and D-galactose. The multivariate analyses could discriminate the sweet and sour, sweet and bitter, sweet and pungent, sour and pungent plant groups. Chemosensory category of plant (classified as unknown) could also be identified.Conclusion: This preliminary study has indicated the possibility of fingerprinting the chemosensory-based ayurvedic classification of medicinal plants using E-tongue coupled with multivariate statistical analysis.</p