Mobilizing Stockpile of Nature: Phytochemicals, Herbal Extracts, and Dietary Supplements for Managing Metabolic Diseases with Concentric Focus on Obesity

Obesity and associated health impairments are proven to exhibit multifocal health disorders along with increasing co-morbidity. Underlying obesity pathology is linked up with almost every major disease, which may increase the risk of heart disease, hypertension, diabetes, cancer, osteoarthritis, etc. The prevalence of overweight and obesity is on the rise around the world, which enormously affects the life span of individuals. Due to the foggier nature of the underlying pathology, the efficacy is questionable for conventional treatments. The traditional therapy of obesity may involve synthetic moieties and surgical procedures, which have many harmful side effects and chances of recurrent severity. Scientists are continuously focusing on prophylactic remedies alongside maintaining a proper lifestyle. In that context, nature always helped with traditional medications. As per folklore medicine reports, many plants have been used to treat obesity and its associated complications. This review compiles a vast array of datasets, including the impact of obesity and the need for the introduction of phytochemicals in place of conventional pharmacotherapies, the impact of phytochemicals along with the reported mechanisms of action, recent clinical trial reports, and recently explored dietary supplements. The primary objective of this presentation is to chart the future trajectory of phytochemical research for metabolic disorders, establishing a foundational framework for future investigations to build upon.

Potential Therapeutic Targets for the management of Diabetes Mellitus Type 2.

Diabetes is one of the lifelong chronic metabolic diseases which is prevalent globally. There is a continuous rise in the number of people suffering from this disease with time. It is characterized by hyperglycemia, which leads to severe damage to the body's system, such as blood vessels and nerves. Diabetes occurs due to the dysfunction of pancreatic ß-cell which leads to the reduction in the production of insulin or body cells unable to use insulin produce efficiently. As per the data shared International diabetes federation (IDF), there are around 415 million affected by this disease worldwide. There are a number of hit targets available that can be focused on treating diabetes. There are many drugs available and still under development for the treatment of type 2 diabetes. Inhibition of gluconeogenesis, lipolysis, fatty acid oxidation, and glucokinase activator is emerging targets for type 2 diabetes treatment. Diabetes management can be supplemented with drug intervention for obesity. The antidiabetic drug sale is the second-largest in the world, trailing only that of cancer. The future of managing diabetes will be guided by research on various novel targets and the development of various therapeutic leads, such as GLP-1 agonists, DPP-IV inhibitors, and SGLT2 inhibitors that have recently completed their different phases of clinical trials. Among these therapeutic targets associated with type 2 diabetes, this review focused on some common therapeutic targets for developing novel drug candidates of the newer generation with better safety and efficacy.

Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India.

BACKGROUND: Price forecasting of perishable crop like vegetables has importance implications to the farmers, traders as well as consumers. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. The farmers can use the information to make choices around the timing of marketing. For forecasting price of agricultural commodities, several statistical models have been applied in past but those models have their own limitations in terms of assumptions. METHODS: In recent times, Machine Learning (ML) techniques have been much successful in modeling time series data. Though, numerous empirical studies have shown that ML approaches outperform time series models in forecasting time series, but their application in forecasting vegetables prices in India is scared. In the present investigation, an attempt has been made to explore efficient ML algorithms e.g. Generalized Neural Network (GRNN), Support Vector Regression (SVR), Random Forest (RF) and Gradient Boosting Machine (GBM) for forecasting wholesale price of Brinjal in seventeen major markets of Odisha, India. RESULTS: An empirical comparison of the predictive accuracies of different models with that of the usual stochastic model i.e. Autoregressive integrated moving average (ARIMA) model is carried out and it is observed that ML techniques particularly GRNN performs better in most of the cases. The superiority of the models is established by means of Model Confidence Set (MCS), and other accuracy measures such as Mean Error (ME), Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Prediction Error (MAPE). To this end, Diebold-Mariano test is performed to test for the significant differences in predictive accuracy of different models. CONCLUSIONS: Among the machine learning techniques, GRNN performs better in all the seventeen markets as compared to other techniques. RF performs at par with GRNN in four markets. The accuracies of other techniques such as SVR, GBM and ARIMA are not up to the mark.

Toxicity effects of size fractions of incinerated sewage sludge bottom ash on human cell lines.

Sewage sludge bottom ash (SSBA) from the incineration plant used for the production of construction materials possibly possess heavy metals which might cause a negative impact on human health. Considering biosafety, we investigated the toxicity effects of 0.5-2 mm (aggregate substitute) and < 0.075 mm (cement substitute) in its solid and leachate form on human lung fibroblast cells (MRC-5) and human skin epidermal cells (HaCaT) on exposure through contact. MTS assay revealed the cellular responses of lung and skin cell lines to the leachates showing that the skin cells, which often interact with the external environment displayed better tolerance than the lung cells, whereas solid ash showed a concentration and size-dependent toxicity. Solid ash was found to downregulate the intracellular glutathione/superoxide dismutase activities and upregulate lactate dehydrogenase/lipid peroxidation activities thus inducing oxidative stress to the cell and subsequently resulting in the cell membrane leakage, destructive mitochondrial membrane potential (Δψm), apoptosis, and DNA damage, which is nearly 7-fold higher than the negative control. At a high concentration, DNA damage index of 1.09 and 1.29 was observed for the 0.5-2 mm sized ash leachate on skin cells and lung cells respectively, whereas for ash (<0.075 mm size) leachate, this fraction was 1.29 and 2.96, respectively. Overall, the ash leachate is found to be safer/biocompatible if they come in contact with humans as compared to SSBA in its solid form.

Role of vitamin e in prevention of oral cancer:-a review.

Oral cancer is one of the major global threads to public health. The development of oral cancer is tobacco related mainly. Vitamin-E can inhibit reaction of the tobacco specific nitrosamine which undergoes specific activation, detoxification process. Dietary substitute such as vitamin-E can prevent oral cancer at a very early stage that is in premalignant lesions, in premalignant conditions. Main action of vitamin E includes increase immunity, controls free radicals mediated cell disturbances, maintains membrane integrity, inhibit cancer cell growth, cytotoxicity. Many past studies suggest the role of antioxidant (vitamin-E) in treatment of oral mucosal lesions particularly includes oral leukoplakia, oral lichen planus, oral submucous fibrosis and oral cancer. Vitamin-E as an antioxidant helps in prevention and slow the growth of Head and Neck cancer, improve the effects of cancer chemotherapy and reduce the side effects from both chemotherapy and radiation therapy for cancer patients. As prevention modality use of Vitamin-E may be beneficial for human beings.

Gross anatomical studies on the adrenal gland in prenatal goat (Capra Hircus) / Estudio anatómico macroscópico de la glándula suprarrenal en fetos de cabra (Capra Hircus)

The present study was conducted on the 24 healthy and normal embryos/foeti of non- descript goat (Capra hircus) varying from day old to 150 days of gestation. The embryo/foeti were assigned into three groups according to their gestational ages; Groups I (0-50 days), II (51-100 days) and III (101-till term). At 38 days of gestation the primordia of right and left adrenal gland were observed as a pea shaped spherical swelling located just cranial to the respective metanephros. Biometrical studies revealed the increase in the all parameters of the adrenal gland with the advancement of age. Adrenal glands were harvested first grossly at 50 days of gestation.

El presente estudio se realizó en 24 embriones / fetos de cabra (Capra hircus) sanos de un día hasta los 150 días de gestación. Los embriónes fueron separados en tres grupos de acuerdo a la edad gestacional: grupos I (0-50 días), II (51 a 100 días) y III (101-till plazo). A los 38 días de gestación se observó el primordio de las glándulas suprarrenales derecha e izquierda como una protuberancia de forma esférica, situada justo en la zona craneal en relación al metanefros. C on el avance de la edad, estudios biométricos revelan aumento de todos los parámetros de la glándula suprarrenal. Las glándulas suprarrenales fueron extraídas inicialmente a los 50 días de gestación.