A flavone from the ethyl acetate extract of Leea rubra leaves with DNA damage protection and antineoplastic activity.

Among the major constituents of Leea rubra (Family Vitaceae) leaves, phenolic and flavonoind compounds are most important for therapeutic purposes and the plant parts have been used in traditional medicine to treat several diseases for long. Thus, in order to scientifically confirm the traditional uses of the L. rubra leaves, the present study was designed to investigate the efficacy of the isolated flavones against AAPH induced oxidative damage to pUC19 DNA by gel electrophoresis and antineoplastic activity was evaluated on Ehrlich ascites carcinoma (EAC) bearing Swiss albino mice by evaluating percentage inhibition of cell growth, morphological changes of EAC cells and hematological parameters of the mice. The isolation was carried out by column chromatography and structure was revealed by 1H-NMR and 13C NMR. The result shows that, the isolated compound was identified as myricetin 4'-methoxy-3-O-α-l-rhamnopyranoside based on previously reported data. The isolated flavone effectively inhibited AAPH-induced oxidative damage to DNA; because it could inhibit the formation of circular and linear forms of the DNA. In anti-proliferative assay, 76% growth inhibition of EAC cells was observed as compare to the control mice (p<0.05) at a dose 100 mg/kg body weight. Thus the isolated flavone showed great importance as a possible therapeutic agent in preventing oxidative damage to DNA and the chronic diseases caused by such DNA damage, and can also become important in cancer chemotherapy.

A Secure Occupational Therapy Framework for Monitoring Cancer Patients' Quality of Life.

Once diagnosed with cancer, a patient goes through a series of diagnosis and tests, which are referred to as "after cancer treatment". Due to the nature of the treatment and side effects, maintaining quality of life (QoL) in the home environment is a challenging task. Sometimes, a cancer patient's situation changes abruptly as the functionality of certain organs deteriorates, which affects their QoL. One way of knowing the physiological functional status of a cancer patient is to design an occupational therapy. In this paper, we propose a blockchain and off-chain-based framework, which will allow multiple medical and ambient intelligent Internet of Things sensors to capture the QoL information from one's home environment and securely share it with their community of interest. Using our proposed framework, both transactional records and multimedia big data can be shared with an oncologist or palliative care unit for real-time decision support. We have also developed blockchain-based data analytics, which will allow a clinician to visualize the immutable history of the patient's data available from an in-home secure monitoring system for a better understanding of a patient's current or historical states. Finally, we will present our current implementation status, which provides significant encouragement for further development.

Hybrid sensor for metal grade measurement of a falling stream of solid waste particles.

A hybrid sensor system for accurate detection of the metal grade of a stream of falling solid waste particles is investigated and experimentally verified. The system holds an infrared and an electromagnetic unit around a central tube and counts all the particles and only the metal particles, respectively. The count ratio together with the measured average particle mass ratio (k) of non-metal and metal particles is sufficient for calculation of grade. The performance of the system is accurately verified using synthetic mixtures of sand and metal particles. Towards an application a case study is performed using municipal solid waste incineration bottom ash in size fractions 1-6mm, which presents a major challenge for nonferrous metal recovery. The particle count ratio was inherently accurate for particle feed rates up to 13 per second. The average value and spread of k for bottom ash was determined as 0.49 ± 0.07 and used to calculate grade within 2.4% from the manually analysed grade. At higher feed rates the sensors start missing particles which fall simultaneously through the central tube, but the hybrid system still counted highly repeatable. This allowed for implementation of a count correction ratio to eliminate the stationary error. In combination with averaging in measurement intervals for suppression of stochastic variations the hybrid system regained its accuracy for particle feed rates up to 143 per second. This performance and its special design, intended to render it insensitive to external interference and noise when applied in an eddy current separator, make the hybrid sensor suitable for applications such as quality control and sensor controlled separation.