Evaluation of Na and K in anti-diabetic ayurvedic medicine using LIBS

Kumari, Reshu; Kumar, Rohit; Rai, Apeksha; Kumar, Awadhesh

doi:10.1007/s10103-021-03289-y

Cited by 11 publications

(5 citation statements)

References 33 publications

(38 reference statements)

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“…Therefore, it is essential to evaluate the actual concentration and ratios of elements present in any medicine in order to correlate their specific bioactivity with specific elemental ratios. Kumari et al evaluated the ratio of minerals helpful in diabetic management and concluded that in most ayurvedic antidiabetic medicine the ratio of Mg/Na and Mg/K are approximately the same [24]. The present work also confirms, as shown in Figure 3, that the ratios of spectral intensity of Mg/Na and Mg/K are the same in t. dioica sample.…”

Section: Determination Of the Elemental Compositionsupporting

confidence: 84%

“…The importance of various bio-elements in the medicinal activity of plants cannot be ignored and thus it becomes imperative to detect their presence, concentrations, and ratios in which they are present in T. dioica leaves sample. Hence, the anti-diabetic activity of T. dioica leaves could be correlated not only with the presence of Na, K, and Mg but also with the assessment of specific ratios of Mg/Na and Mg/K, which are just the same as in the earlier results of other anti-diabetic ayurvedic medicines [24]. For CF-LIBS one utilizes recorded intensities of different spectral lines of the elements, however, the laserinduced plasma needs to fulfill three cconditions that must be verified: (i) plasma must be stoichiometric, (ii) plasma must be optically thin, and (iii) plasma must show local thermal equilibrium [26][27][28].…”

Section: Quantitative Analysissupporting

confidence: 55%

“…Thus, low potassium levels could be risky as well for developing diabetes due to persistent high blood glucose levels. Hence, the presence of elements like Mg , K , and Na in the sample could be correlated well with the observed significant efficacy of t. dioica leaves in insulin-dependent diabetes mellitus (IDDM) [24,25].…”

Section: Determination Of the Elemental Compositionsupporting

confidence: 55%

See 2 more Smart Citations

Elemental Laser-Plasma Analysis of Pointed Gourd Leaves for Diabetes Management

Kumar¹,

Prashant²,

Abhishek³

et al. 2022

Preprint

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This interdisciplinary work communicates identification and quantification of elements responsible for the bioactive potency of leaves from pointed gourd, trichosanthes dioica,using laser induced breakdown spectroscopy (LIBS). Calibration-free LIBS determines the presence of various trace and major elements, their concentrations, and ratios in which they are present in the leaves. The presence of specific elemental ratios of magnesium/sodium and magnesium/potassium could be promising for managing diabetes mellitus. Variable doses of 500, 750, 1000, and 1250 mg per kg body weight of aqueous extract from trichosanthes dioica leaves are administered. A dose of 1000 mg per kg body weight is found to be the most effective. Based on encouraging results, the extract could be harvested to serve as anti-diabetic medication for diabetes and associated symptoms.

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Section: Determination Of the Elemental Compositionsupporting

confidence: 84%

Section: Quantitative Analysissupporting

confidence: 55%

Section: Determination Of the Elemental Compositionsupporting

confidence: 55%

See 1 more Smart Citation

Elemental Laser-Plasma Analysis of Pointed Gourd Leaves for Diabetes Management

Kumar¹,

Prashant²,

Abhishek³

et al. 2022

Preprint

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“…This method features rapid detection, simple sample preparation, real-time online detection of multiple elements, and a small sample size requirement [15,16]. It has been employed extensively in food analysis [17], coal metallurgy [18], environmental monitoring [19], and medical diagnosis [20].…”

Section: Introductionmentioning

confidence: 99%

Substrate-Assisted Laser-Induced Breakdown Spectroscopy Combined with Variable Selection and Extreme Learning Machine for Quantitative Determination of Fenthion in Soybean Oil

Ding,

Wang,

Chen

et al. 2024

Photonics

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The quality and safety of edible vegetable oils are closely related to human life and health, meaning it is of great significance to explore the rapid detection methods of pesticide residues in edible vegetable oils. This study explored the applicability potential of substrate-assisted laser-induced breakdown spectroscopy (LIBS) for quantitatively determining fenthion in soybean oils. First, we explored the impact of laser energy, delay time, and average oil film thickness on the spectral signals to identify the best experimental parameters. Afterward, we quantitatively analyzed soybean oil samples using these optimized conditions and developed a full-spectrum extreme learning machine (ELM) model. The model achieved a prediction correlation coefficient (RP2) of 0.8417, a root mean square error of prediction (RMSEP) of 167.2986, and a mean absolute percentage error of prediction (MAPEP) of 26.46%. In order to enhance the prediction performance of the model, a modeling method using the Boruta algorithm combined with the ELM was proposed. The Boruta algorithm was employed to identify the feature variables that exhibit a strong correlation with the fenthion content. These selected variables were utilized as inputs for the ELM model, with the RP2, RMSEP, and MAPEP of Boruta-ELM being 0.9631, 71.4423, and 10.06%, respectively. Then, the genetic algorithm (GA) was used to optimize the parameters of the Boruta-ELM model, with the RP2, RMSEP, and MAPEP of GA-Boruta-ELM being 0.9962, 11.005, and 1.66%, respectively. The findings demonstrate that the GA-Boruta-ELM model exhibits excellent prediction capability and effectively predicts the fenthion contents in soybean oil samples. It will be valuable for the LIBS quantitative detection and analysis of pesticide residues in edible vegetable oils.

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“…Hypoglycemia is a condition in which blood glucose levels are below normal limits, less than 70 mg/dl [11,12]. In the event of hypoglycemia, the body defence mechanism that functions to activate when several neuroendocrine systems are disrupted, causing the body's failure to maintain normal blood glucose levels, either by external or internal causes [13].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2021

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This study aimed to determine the effect of video education about hypoglycemia on knowledge of diabetes mellitus patients and their families. This type of research is a quantitative study with a pre-experiment method. This study focused on two groups, namely, type 2 diabetes mellitus patients by 162 people, and the families of diabetes mellitus patients by 162 people. In the group of diabetes mellitus patients, the sample used 30 respondents who were divided into two groups, namely 15 respondents in the experimental group and 15 respondents in the control group. In the population of family diabetes mellitus patients, the sample applied 30 respondents, who were divided into 15 respondents for the experimental group and 15 respondents for the control group. Non-probability sampling with a purposive sampling technique was utilized. Data analysis using the paired t-test showed a p-value of 0.001 <0.05. So, it can be concluded that health education on knowledge of hypoglycemia in type 2 diabetes mellitus patients was effective in the working area of Puskesmas Nguter Sukoharjo. For the results of the paired t-test, we found p = <0.001 in the experimental group, which showed that there was an effect of hypoglycemia health education with videos on knowledge of type 2 diabetes families. Diabetes mellitus patients need to always adopt a healthy lifestyle so as to create a good health status and avoid complications of diabetes mellitus patients.

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Evaluation of Na and K in anti-diabetic ayurvedic medicine using LIBS

Cited by 11 publications

References 33 publications

Elemental Laser-Plasma Analysis of Pointed Gourd Leaves for Diabetes Management

Elemental Laser-Plasma Analysis of Pointed Gourd Leaves for Diabetes Management

Substrate-Assisted Laser-Induced Breakdown Spectroscopy Combined with Variable Selection and Extreme Learning Machine for Quantitative Determination of Fenthion in Soybean Oil

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