A pyruvate decarboxylase-mediated therapeutic strategy for mimicking yeast metabolism in cancer cells.

Cancer cells have high rates of glycolysis and lactic acid fermentation in order to fuel accelerated rates of cell division (Warburg effect). Here, we present a strategy for merging cancer and yeast metabolism to remove pyruvate, a key intermediate of cancer cell metabolism, and produce the toxic compound acetaldehyde. This approach was achieved by administering the yeast enzyme pyruvate decarboxylase to triple negative breast cancer cells. To overcome the challenges of protein delivery, a nanoparticle-based system consisting of cationic lipids and porous silicon were employed to obtain efficient intracellular uptake. The results demonstrate that the enzyme therapy decreases cancer cell viability through production of acetaldehyde and reduction of lactic acid fermentation.

Evaluation of anticancer activity of celastrol liposomes in prostate cancer cells.

CONTEXT: Celastrol, a natural compound derived from the herb Tripterygium wilfordii, is known to have anticancer activity, but is not soluble in water. OBJECTIVE: Formation of celastrol liposomes, to avoid the use of toxic solubilising agents. MATERIALS AND METHODS: Two different formulations of PEGylated celastrol liposomes were fabricated. Liposomal characteristics and serum stability were determined using dynamic light scattering. Drug entrapment efficacy and drug release were measured spectrophotometrically. Cellular internalisation and anticancer activity was measured in prostate cancer cells. RESULTS: Liposomal celastrol displayed efficient serum stability, cellular internalisation and anticancer activity, comparable to that of the free drug reconstituted in dimethyl sulfoxide. DISCUSSION AND CONCLUSION: Liposomal celastrol can decrease the viability of prostate cancer cells, while eliminating the need for toxic solubilising agents.

Development of a novel cardiopulmonary resuscitation measurement tool using real-time feedback from wearable wireless instrumentation.

AIM: The design and implementation of a wearable training device to improve cardiopulmonary resuscitation (CPR) is presented. METHODS: The MYO contains both Electromyography (EMG) and Inertial Measurement Unit (IMU) sensors which are used to detect effective CPR, and the four common incorrect hand and arm positions viz. relaxed fingers; hands too low on the sternum; patient too close; or patient too far. The device determines the rate and depth of compressions calculated using a Fourier transform and dual-quaternions respectively. In addition, common positional mistakes are determined using classification algorithms (six machine learning algorithms are considered and tested). Feedback via Graphical User Interface (GUI) and audio is integrated. RESULTS: The system is tested by performing CPR on a mannequin and comparing real-time results to theoretical values. Tests show that although the classification algorithm performed well in testing (98%), in real time, it had low accuracy for certain categories (60%), which are attributable to the MYO calibration, sampling rate and misclassification of similar hand positions. Combining these similar incorrect positions into more general categories significantly improves accuracy, and produces the same improved outcome of improved CPR. The rate and depth measures have a general accuracy of 97%. CONCLUSION: The system allows for portable, real-time feedback for use in training and in the field, and shows promise toward classifying and improving the administration of CPR.

Data from wearable wireless instrumentation device taken during simulated CPR with and without intentional error toward a quality feedback device.

Data of Cardiopulmonary Resuscitation performed on a mannequin was collected via wearable instrumentation (using the MYO device). The data were collected for both "good" CPR and for performance of CPR with common errors introduced intentionally for this study. The data are labelled according to the error, and contain a variety of derived measurements. Data collected were used toward "Development of a novel cardiopulmonary resuscitation measurement tool using real-time feedback from wearable wireless instrumentation' (Ward et al., 2019) in which full context is available'. The data are available at Mendeley Data, doi:10.17632/pvjghfjmy4.1 (Ward et al., 2019).

Hesperetin Liposomes for Cancer Therapy.

Hesperetin is a compound from citrus fruit that has previously been found to exert anticancer activity through a variety of mechanisms. However, the application of hesperetin to cancer therapy has been hampered by its hydrophobicity, necessitating the use of toxic solubilizing agents. Here, we have developed the first liposome-based delivery system for hesperetin. Liposomes were fabricated using the thin-layer evaporation technique and physical and pharmacological parameters were measured. The liposomes remained stable for prolonged periods of time in serum and under storage conditions, and displayed anticancer efficacy in both H441 lung cancer cells and MDA-MB-231 breast cancer cells. Furthermore, the anticancer activity was not impaired in cells expressing the multidrug resistance protein 1 (MDR-1). In conclusion, the encapsulation of hesperetin in liposomes does not interfere with therapeutic efficacy and provides a biocompatible alternative to toxic solubilizing agents, thereby enabling future clinical use of this compound for cancer therapy.