The Management of Diabetes Mellitus Using Medicinal Plants and Vitamins.

Diabetes mellitus (DM) is a serious chronic metabolic disease that is associated with hyperglycemia and several complications including cardiovascular disease and chronic kidney disease. DM is caused by high levels of blood sugar in the body associated with the disruption of insulin metabolism and homeostasis. Over time, DM can induce life-threatening health problems such as blindness, heart disease, kidney damage, and stroke. Although the cure of DM has improved over the past decades, its morbidity and mortality rates remain high. Hence, new therapeutic strategies are needed to overcome the burden of this disease. One such prevention and treatment strategy that is easily accessible to diabetic patients at low cost is the use of medicinal plants, vitamins, and essential elements. The research objective of this review article is to study DM and explore its treatment modalities based on medicinal plants and vitamins. To achieve our objective, we searched scientific databases of ongoing trials in PubMed Central, Medline databases, and Google Scholar websites. We also searched databases on World Health Organization International Clinical Trials Registry Platform to collect relevant papers. Results of numerous scientific investigations revealed that phytochemicals present in medicinal plants (Allium sativum, Momordica charantia, Hibiscus sabdariffa L., and Zingiber officinale) possess anti-hypoglycemic activities and show promise for the prevention and/or control of DM. Results also revealed that intake of vitamins C, D, E, or their combination improves the health of diabetes patients by reducing blood glucose, inflammation, lipid peroxidation, and blood pressure levels. However, very limited studies have addressed the health benefits of medicinal plants and vitamins as chemo-therapeutic/preventive agents for the management of DM. This review paper aims at addressing this knowledge gap by studying DM and highlighting the biomedical significance of the most potent medicinal plants and vitamins with hypoglycemic properties that show a great potential to prevent and/or treat DM.

Improving Invasive Breast Cancer Care Using Machine Learning Technology.

Breast cancer (BC) is the most common malignancy in women worldwide. In the United States, the lifetime risk of developing an invasive form of breast cancer is 12.5% among women. BC arises in the lining cells (epithelium) of the ducts or lobules in the glandular tissue of the breast. The goal of the present study was to use machine learning (ML) as a novel technology to assess and compare the invasive forms of BC including, infiltrating ductal carcinoma, infiltrating lobular carcinoma, and mucinous carcinoma. To achieve this goal, we used ML algorithms and collected a dataset of 334 BC patients available at https://www.kaggle.com/amandam1/breastcancerdataset and interpreted this dataset based on the form of BC, age, sex, tumor stages, surgery type, and survival rate. Among the 334 patients, 70% were diagnosed with infiltrating ductal carcinoma, 27% with infiltrating lobular carcinoma, and 3% with mucinous carcinoma. Overall, out of 334 BC patients: 64 (19.16%) were in stage I, 189 (56.59%) in stage II, and 81 (24.25%) in stage III. Sixty-six, 67, 96, and 105 patients underwent lumpectomy, simple mastectomy, modified radical mastectomy, and other types of surgery, respectively. The survival rates were 83.4% for stage I, 79.1% for stage II, and 77% for stage III. Findings from the present study demonstrated that ML provides an important tool to curate large amount of BC data, as well as a scientific means to improve BC outcomes.