Bauhinia forficata in the treatment of diabetes mellitus: a patent review

Introduction: Diabetes Mellitus has been considered an epidemic by the World Health Organization, with a high risk of morbidity and mortality. The treatment of this pathology consists in glycemic control, which can be done by oral hypoglycemic agents, insulin therapy, dietary guidance, regular physical activity, and psychosocial support. In addition, other adjuvant treatments are employed, such as phytotherapic, and one of the most used plants is Bauhinia forficata.

Areas covered: In the current review, patents using Bauhinia forficata for the Diabetes Mellitus treatment have been analyzed. There were 03 patents in WIPO, 01 in Espacenet, 01 in USPTO, and 02 in INPI.

Expert opinion: Patents on the adjuvant treatment of Diabetes Mellitus by Bauhinia forficata are discussed. Although there are some phytotherapy products containing this medicinal plant which has hypoglycemic effect here is still a need for the development of more products based on natural resources, for the treatment of this pathology, without side effects and with other benefits, to assist in the glycemia control in diabetic patients, and to improve their quality of life.     

New,Immunomodulatory, Oral Nutrition Formula for Use Prior to Surgery in Patients With Head and Neck Cancer: An Exploratory Study

Background: The perioperative use of immunomodulatory nutrition formulas in patients with head and neck cancer reduces the number of postoperative infections and the length of hospital stay. Objective: An exploratory, randomized, controlled, blind, clinical trial was designed to examine the effect of the preoperative consumption of a new, immunomodulatory, oral nutrition formula in patients with head and neck cancer. Methods: Thirty‐eight patients were randomized to receive either 400 mL/d of either the new immunomodulatory formula (IF) or that commonly used in clinical practice (CF) over 10 days prior to surgery. Thirty‐three patients completed the study. Compliance, tolerance, the length of hospital stay, the incidence of infections and noninfectious complications before discharge, and the same up to 15 and 30 days after discharge were recorded. Results: The percentage of patients who developed infections before discharge was significantly lower in the IF than in the CF group (P = .013), as was the number of infections/100 patients/d (P = .035). The length of hospital stay was significantly shorter in the IF group (P = .001). Both formulas were safe and well tolerated. No other differences were detected. These results suggest preoperative consumption of the new formula to be beneficial for patients with neck and head cancer. Further trials are needed to confirm these results and to test the efficacy of the formula in patients with other conditions. Conclusion: The new formula can be safely prescribed as part of the preoperative treatment of patients with head and neck cancer and might reduce the problem of postoperative infection.     

Singular value based characterization and analysis of thermal patches for early breast abnormality detection

The purpose of this study is to develop a novel breast abnormality detection system by utilizing the potential of infrared breast thermography (IBT) in early breast abnormality detection. Since the temperature distributions are different in normal and abnormal thermograms and hot thermal patches are visible in abnormal thermograms, the abnormal thermograms possess more complex information than the normal thermograms. Here, the proposed method exploits the presence of hot thermal patches and vascular changes by using the power law transformation for pre-processing and singular value decomposition to characterize the thermal patches. The extracted singular values are found to be statistically significant (p?<?0.001) in breast abnormality detection. The discriminability of the singular values is evaluated by using seven different classifiers incorporating tenfold cross-validations, where the thermograms of the Department of Biotechnology-Tripura University-Jadavpur University (DBT-TU-JU) and Database of Mastology Research (DMR) databases are used. In DMR database, the highest classification accuracy of 98.00% with the area under the ROC curve (AUC) of 0.9862 is achieved with the support vector machine using polynomial kernel. The same for the DBT-TU-JU database is 92.50% with AUC of 0.9680 using the same classifier. The comparison of the proposed method with the other reported methods concludes that the proposed method outperforms the other existing methods as well as other traditional feature sets used in IBT based breast abnormality detection. Moreover, by using Rank1 and Rank2 singular values, a breast abnormality grading (BAG) index has also been developed for grading the thermograms based on their degree of abnormality.     

Estimating transmitted power density from mobile phone: an epidemiological pilot study with a software modified phone

The aims of this study were to evaluate the weekly and annual cumulative radiofrequency-electromagnetic field (RF-EMF) exposure attributed to mobile phone (MP) use, and assess whether a novel app (Quanta Monitor?) could be employed in a small human sample to characterise the RF-EMF exposures associated with the use of MPs. Ten participants provided their two months’ daily objective data on their MP exposures (i.e. transmitted and received power densities) attributed to different modes of MP usage such as cellular calls, cellular data and Wi-Fi. The results demonstrated that total transmitted power density (cellular phone calls, data and Wi-Fi surfing) could be many orders of magnitude higher than that from the total received power density. Of the total transmitted power density, cellular data use contributed the largest portion. Our study showed that Quanta Monitor? could be employed in prospective assessment of exposures to MPs in epidemiological studies.