Anticancer activity of aqueous myrrh extract alone and in combination with cisplatin in HeLa cells

Purpose: To study the impact of an aqueous myrrh extract on the proliferation of cervical cancer cells in vitro.Methods: First, 100 g of ground myrrh resin was boiled in 1000 mL of distilled water for 30 min. Different components of the decoction were identified using gas chromatography–mass spectrometry and high-performance liquid chromatography. The effects of high (20 μg/mL) and low (10 μg/mL) concentrations of cisplatin, serial concentrations of myrrh (20, 40, 60, and 80 μg/mL), and a combination of both were evaluated using cell proliferation assay, DNA fragmentation, and electron microscopy.Results: All four myrrh concentrations decreased the viability of HeLa cells (16.25 % p < 0.01). A significant further decrease occurred when myrrh was combined with 10 μg/mL cisplatin (11.42 % p < 0.01). This was confirmed by quantifying DNA fragmentation. Ultrastructurally, HeLa cells showed typical apoptosis after treatment with 10 μg/mL cisplatin or a high dose of myrrh. The use of 20 μg/mL cisplatin or the combined therapy resulted in cell necrosis with ruptured cell membranes and autophagosomes. The effect of combined therapy was more lethal than the effect of either of them alone.Conclusion: Myrrh induces apoptosis and autophagy and enhances the activity of cisplatin in vitro. It is potentially a basis for further studies of other types of cancer cell. The clinical use of myrrh in the palliative therapy of human cervical carcinoma might be justified.Keywords: Cervical cancer, Cell viability, Chemotherapy, DNA fragmentation, Myrrh, Cisplatin, Cell ultrastructure, HeLa cell

Teaching medical students how to interpret chest X-rays: the design and development of an e-learning resource

Introduction: The teaching of radiology to medical students has often been criticised for being inadequate and unstructured, with students reporting lack of confidence in assessing x-rays. In this paper, we describe how an e-learning resource, on how to interpret a chest x-ray for medical students, was designed and developed. The aim of the resource was to provide medical students with knowledge of how to interpret a chest x-ray in a systematic approach. Methods: The technology used to design the e-learning resource was Xerte Online Toolkits. The design and development of the e-learning resource was based upon andragogical principles and followed Overbaugh’s guidelines and Mayer’s 12 multimedia principles. An instructional design model called ADDIE was used to help develop the resource and its content. These included cases of common conditions, a quiz and summary table at the end. The paper focuses mainly on the way in which instructional design, education and multimedia principles were used to inform the development of the resource. Findings: A preliminary evaluation was completed by 18 medical students from year 3– 5 who completed the e-learning resource. The feedback was positive with an average rating of 9/10 and 100% of students saying they would recommend the resource to a colleague. Students commented that they liked the resource as it was easy to navigate, had good visual learning and contained good explanations with relevant content. Conclusion and Future Implications: This paper demonstrates how, with the use of instructional models, educational theories and principles, an e-learning resource can be created. Preliminary evaluation showed that students were satisfied with the resource and felt it helped them acquire knowledge on how to interpret chest x-rays. This resource can be further utilized either as a standalone resource or before starting clinical placements and may prove particularly useful in the current and challenging learning environment where there is an increased need for digital resources

GSA: Scheduling and Allocation using Genetic Algorithm

This paper describes a unique approach to schedul- ing and allocation problem in high-level synthesis us- ing genetic algorithm (GA). This approach is di�er- ent from a previous attempt using GA [1] in many respects. Our contributions include: a new chromo- somal representation for scheduling and two subprob- lems of allocation; and two novel crossover operators to generate legal schedules. The approach has been tested on various benchmarks and results are com- pared with those obtained by other approaches such as simulated evolution, tabu search, HAL, SALSA II, STAR, etc

GAP - A GENETIC ALGORITHM APPROACH TO OPTIMIZE 2-BIT DECODER PLAS

PLAs with two bit decoders at the inputs require a smaller area compared with standard two level PLAs. The number of product rows required for such PLas is a function of the assignment of pairs of variables to the decoders. This paper describes a minimization procedure that uses a genetic algorithm approach to reduce the size to the two bit decoder PLAs. Results are compared with those obtained by other approaches such as the Tomczuk and MIller heuristic and the simulated annealing technique (Abd-el-Barr and Choy 1993). For large randomly generated test cases and benchmarks, our results are optimal or very near optimal

GENETIC SCHEDULING OF TASK GRAPHS

A genetic algorithm for scheduling computational task graphs is presented. The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. The objective function to be minimized is the 'time on completion\ of all tasks. Results are compared with those published in the literature and with randomly generated task graphs whose optimal schedules are known a priori

Scheduling and allocation in high-level synthesis using stochastic techniques

High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. Operation scheduling and hardware allocation are the two most important phases in the synthesis of circuits from behavioral specification. Scheduling and allocation can be formulated as an optimization problem. In this work, a unique approach to scheduling and allocation problem using the genetic algorithm (GA) is described. This approach is different from a previous attempt using GA (Wehn et al., IFIP Working Conference on Logic and Architecture Synthesis, Paris, 1990, pp. 47–56) in many respects. The main contributions include: (1) a new chromosomal representation for scheduling and for two subproblems of allocation; and (2) two novel crossover operators to generate legal schedules. In addition the application of tabu search (TS) to scheduling and allocation is also implemented and studied. Two implementations of TS are reported and compared. Both genetic scheduling and allocation (GSA) and tabu scheduling and allocation (TSA) have been tested on various benchmarks and results obtained for data-oriented control-data flow graphs are compared with other implementations in the literature. (A discussion on GSA was presented at the European Design Automation Conference Euro-DAC'94 in Grenoble, France, and TSA at the International Conference on Electronics, Circuits and Systems — ICECS'94 in Cairo, Egypt.) A novel interconnect optimization technique using the GA is also realized

Timing Influenced Force Directed Floorplanning

We represent a timing driven floorplanning program for general cell layouts. The approach used combines quality of force directed approach wit that of constraint graph approach. A floorplan solution is produced in two steps. First a timing and connectivity driven topological arrangement is obtained using a force directed approach. In the second step, the topoligical arrangement is trasnformed into a legal floorplan. The objective of the second step is to minimize the overall area of the floorplan. The floorplanner is validated with circuits of sizes varying from 7-125 block