Chemometric Based Identification and Validation of Specific Chemical Markers for Geographical, Seasonal and Gender Variations in Tinospora cordifolia Stem using HPLC-ESI-QTOF-MS Analysis

Determination of Alzheimer's Drugs in a Human Urine Sample by Different Chemometric Methods: Chemometric Determination of Alzheimer's Drugs

In this study, spectrophotometric determination of donepezil and rivastigmine in healthy human urine samples was carried out by the statistical method. Partial least squares (PLS) and principal component regression (PCR) from multivariate calibration methods were used to evaluate the data obtained from the UV-Vis spectroscopy analysis of the urine sample. Mixtures of each early substance were prepared prior to urine sample analysis, and simultaneous determination of donepezil and rivastigmine was performed on the established chemometric model without any prior separation. The calibration curves of each drug were analyzed, and linearity values were also analyzed. For donepezil and rivastigmine, they were 0.9989 and 0.9997, respectively, and were linear over the concentration range of the synthetic mixture. When both chemometric methods (PLS and PCR) were evaluated in terms of accuracy and reproducibility, very high recoveries and small standard deviations were determined. In the PLS method, the standard error of prediction (SEC), the sum of the prediction residual errors (PRESS), the limit of quantitation (LOQ), and the limit of detection (LOD) values were 0.015, 0.0030, 0.067, 0.24, 0.018, 0.0042, 0.089, and 0.301 for donepezil and rivastigmine, respectively. In the PCR method, SEC, PRESS, LOD, and LOQ values are 0.016, 0.0054, 0.066, and 0.23 for donepezil and 0.022, 0.0062, 0.091, and 0.300 for rivastigmine. Chemometrics is used for speed, simplicity, and reliability. The proposed methods have been successfully applied to a sample of urine.

Exploring gender-based diversity for phenolic and organic acid profiles in the genetic resource of betel vine (Piper betle L.) from India as revealed through high-performance liquid chromatography (HPLC-DAD)

Betel vine (Piper betle L.) is a dioecious plant and has paved way for researchers to explore the available genetic resources for the biochemical compounds. In the study, twenty sexually dimorphic genotypes of betel vine were characterized for bio-compounds using high-performance liquid chromatography (HPLC-DAD), and as a result identified phenolic compounds and organic acids, including caffeic acid, salicylic acid, t-ferulic acid, sinapic acid, p-coumaric acid, t-cinnamic acid, gallic acid, p-hydroxybenzoic acid, gluconic acid, oxalic acid, lactic acid, tartaric acid, malonic acid, citric acid, and succinic acid. The phenolics and organic acids in the male genotypes were more than the female genotypes; this insight of phytochemicals variability could aid in the gender differences. However, the highest phenolic contents was found in the Kapoori Chintalapudi (68.77 mg/100 g), followed by Kapoori Bihar (67.03 mg/100 g) and Ghanegatte (63.31 mg/100 g) genotypes. The abundance of biomolecules was found in the order, namely gallic acid, sinapic acid, caffeic acid, tartaric acid, citric acid, and malonic acid in regardless of gender. The chemical profile of sexual dimorphs in betel vine and serve as a possible index for gender differentiation. The principal component analysis showed the hierarchical grouping of the genotypes based on the phenolic compounds and organic acids; thereby the divergent genotypes Kapoori Chintalapudi, Ghanaghette, Kapoori Bihar, and Sirugamani-1 were identified for phenolic acid richness. Similarly, CARI-6, Halisahar Sanchi, Kapoori Bihar, and Gangarampur Sanchi were identified for organic acids richness which can be promoted for commercial cultivation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03907-2.

Quantification of adulteration in traded ayurvedic raw drugs employing machine learning approaches with DNA barcode database

Adulteration of expensive raw drugs with inferior taxa has become a routine practice, conceding the quality and safety of derived herbal products. In this regard, the study addresses the development of an integrated approach encompassing DNA barcode and HPTLC fingerprinting to authenticate chiefly traded ayurvedic raw drugs in south India [viz. Saraca asoca (Roxb.) Willd., Terminalia arjuna (Roxb. ex DC.) Wight and Arn., Sida alnifolia L. and Desmodium gangeticum (L.) DC.] from its adulterants. Consortium of Barcode of Life (CBOL) recommended DNA barcode gene regions viz. nuclear ribosomal-Internal Transcribed Spacer (nrDNA-ITS), maturase K (matK), ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (rbcL) and psbA-trnH spacer regions along with HPTLC profiling were experimented and a reference database was created. Further, an integrated analytical approach employing genetic distance-based Maximum Likelihood phylogenetic tree and Artificial Intelligence (AI)based Machine Learning Algorithms (MLA)-Waikato Environment for Knowledge Analysis (WEKA) and Barcoding with Logic (BLOG) were employed to prove efficacy of DNA barcode tool. Even though, among the four barcodes, psbA-trnH (S. alnifolia and its adulterants, T. arjuna and its adulterants) or ITS region (S. asoca and its adulterants, D. gangeticum and its adulterants) showed highest inter specific divergences in the selected Biological Reference Materials (BRMs), rbcL or matK barcode regions alone were successful for authentication of traded samples. The automated species identification techniques, WEKA and BLOG, experimented for the first time in India for raw drug validation, could achieve rapid and precise identification. A national certification agency for raw drug authentication employing an integrated approach involving a DNA barcoding tool along with standard organoleptic and analytical methods can strengthen and ensure safety and quality of herbal medicines in India.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03001-5.

Phytotherapeutics Against Alzheimer's Disease: Mechanism, Molecular Targets and Challenges for Drug Development

Alzheimer's disease is inflating worldwide and is combatted by only a few approved drugs. At best, these drugs treat symptomatic conditions by targeting cholinesterase and N-methyl-D-aspartate receptors. Most of the clinical trials in progress are focused to develop disease-modifying agents that aim single targets. The 'one drug-one target' approach is failing in the case of Alzheimer's disease due to its labyrinth etiopathogenesis. Traditional medicinal systems like ayurveda uses a holistic approach encompassing legion of medicinal plants exhibiting multimodal activity. Recent advances in high-throughput technologies have catapulted the research in the arena of ayurveda, specifically in identifying plants with potent anti-Alzheimer's disease properties and their phytochemical characterization. Nonetheless, clinical trials of very few herbal medicines are in progress. This review is a compendium of Indian plants and ayurvedic medicines against Alzheimer's disease and their paraphernalia. A record of 230 plants that are found in India with anti-Alzheimer's disease potential and about 500 phytochemicals from medicinal plants has been solicited with the hope of exploring the unexplored. Further, the molecular targets of phytochemicals isolated from commonly used medicinal plants such as Acorus calamus, Bacopa monnieri, Convolvulus pluricaulis, Tinospora cordifolia and Withania somnifera have been reviewed with respect to their multidimensional property such as antioxidant, anti-inflammation, anti-aggregation, synaptic plasticity modulation, cognition and memory enhancing activity. In addition, the strengths, and challenges in ayurvedic medicine that limit its use as mainstream therapy is discussed and a framework for the development of herbal medicine has been proposed.

Trends and Application of Chemometric Pattern Recognition Techniques in Medicinal Plants Analysis

Medicinal plants have been used and studied for ages, from very old registers to modern ethnopharmacology, which encompasses analytical chemistry, foods, and pharmacy. Based on international norms and governmental organizations of health, phytomedicine-for example, herbal drugs-needs to guarantee the quality control of products and identify contaminants, biomarkers, and chemical profiles, among other issues. In this sense, is necessary to develop advanced analytical methods that show interesting possibilities and obtain a great amount of data. In order to treat the data, a set of mathematical and statistical procedures named chemometrics is necessary. In terms of herbal drugs, chemometric tools may be used to identify the following in plants: parts, development stages, processing, geographic origin, authentication, and chemical markers. This review describes applications of chemometric pattern recognition tools to analyze herbal drugs in different conditions associated with analytical methods in the last six years (2015-2020).

Interactions of a medicinal climber Tinospora cordifolia with supportive interspecific plants trigger the modulation in its secondary metabolic profiles

Tinospora cordifolia (TC) is scientifically proven immunomodulatory drug being used for centuries. Ancient literature reported that inter-specific interactions change medicinal properties of TC. Thus, the current study is aimed to understand the influence of interspecific biotic interactions on chemo-profiles of TC. To explore it, TC samples collected from six co-occurring plants, i.e. Azarditchita indica, Acacia nilotica, Albezia lebbeck, Ficus benghalensis, Tamarandus indica and Acacia leucophloea were analyzed by HPLC-ESI-QTOF-MS. Mass data were subjected to multivariate analysis. Support vector machines (SVMs) was found to be best classifier (r² < 0.93). Data analysis showed the specific compounds in all TC due to inter-specific interactions. Data were further analyzed with SNK post-hoc test followed by permutative (n = 50) Bonferroni FDR multiple testing correction. The compound without any missing values reduced the number of variables to 133 (p < 0.01). Statistical analysis revealed that TC having interactions with A.lebbeck and A. nilotica formed the most distant groups. However, TC co-occurred with A. indica showed the highest number of up-regulated metabolites, including jatrorrhizine, chrysin, peonidin, 6-methylcoumarin and some terpenoids. Some metabolites, including jatrorrhizine and magnoflorine were quantified to confirm the accuracy of qualitative analysis. Results demonstrated the influence of inter-specific biotic interactions on TC chemo-profiles, hence its medicinal properties.

The Determination of Parkinson's Drugs in Human Urine by Applying Chemometric Methods

The spectrophotometric-chemometric analysis of levodopa and carbidopa that are used for Parkinson's disease was analyzed without any prior reservation. Parkinson's drugs in the urine sample of a healthy person (never used drugs in his life) were analyzed at the same time spectrophotometrically. The chemometric methods used were partial least squares regression (PLS) and principal component regression (PCR). PLS and PCR were successfully applied as chemometric determination of levodopa and carbidopa in human urine samples. A concentration set including binary mixtures of levodopa and carbidopa in 15 different combinations was randomly prepared in acetate buffer (pH 3.5).). UV spectrophotometry is a relatively inexpensive, reliable, and less time-consuming method. Minitab program was used for absorbance and concentration values. The normalization values for each active substance were good (r2>0.9997). Additionally, experimental data were validated statistically. The results of the analyses of the results revealed high recoveries and low standard deviations. Hence, the results encouraged us to apply the method to drug analysis. The proposed methods are highly sensitive and precise, and therefore they were implemented for the determination of the active substances in the urine sample of a healthy person in triumph.

Authentication of Garcinia fruits and food supplements using DNA barcoding and NMR spectroscopy

Garcinia L. (Clusiaceae) fruits are a rich source of (-)-hydroxycitric acid, and this has gained considerable attention as an anti-obesity agent and a popular weight loss food supplement. In this study, we assessed adulteration of morphologically similar samples of Garcinia using DNA barcoding, and used NMR to quantify the content of (-)-hydroxycitric acid and (-)-hydroxycitric acid lactone in raw herbal drugs and Garcinia food supplements. DNA barcoding revealed that mostly G. gummi-gutta (previously known as G. cambogia) and G. indica were traded in Indian herbal markets, and there was no adulteration. The content of (-)-hydroxycitric acid and (-)-hydroxycitric acid lactone in the two species varied from 1.7% to 16.3%, and 3.5% to 20.7% respectively. Analysis of ten Garcinia food supplements revealed a large variation in the content of (-)-hydroxycitric acid, from 29 mg (4.6%) to 289 mg (50.6%) content per capsule or tablet. Only one product contained quantifiable amounts of (-)-hydroxycitric acid lactone. Furthermore the study demonstrates that DNA barcoding and NMR could be effectively used as a regulatory tool to authenticate Garcinia fruit rinds and food supplements.

Authentication of Garcinia fruits and food supplements using DNA barcoding and NMR spectroscopy

Garcinia L. (Clusiaceae) fruits are a rich source of (−)-hydroxycitric acid, and this has gained considerable attention as an anti-obesity agent and a popular weight loss food supplement. In this study, we assessed adulteration of morphologically similar samples of Garcinia using DNA barcoding, and used NMR to quantify the content of (−)-hydroxycitric acid and (−)-hydroxycitric acid lactone in raw herbal drugs and Garcinia food supplements. DNA barcoding revealed that mostly G. gummi-gutta (previously known as G. cambogia) and G. indica were traded in Indian herbal markets, and there was no adulteration. The content of (−)-hydroxycitric acid and (−)-hydroxycitric acid lactone in the two species varied from 1.7% to 16.3%, and 3.5% to 20.7% respectively. Analysis of ten Garcinia food supplements revealed a large variation in the content of (−)-hydroxycitric acid, from 29 mg (4.6%) to 289 mg (50.6%) content per capsule or tablet. Only one product contained quantifiable amounts of (−)-hydroxycitric acid lactone. Furthermore the study demonstrates that DNA barcoding and NMR could be effectively used as a regulatory tool to authenticate Garcinia fruit rinds and food supplements.