QEMCGAN: Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN for Medical Image Translation.

Generative adversarial networks (GANs) have become popular in medical imaging because of their remarkable performance and ability to translate images across different domains. However, GANs face several issues in image-to-image translation, including training instability, lack of diversity, and mode collapse. These issues become even more complex when using cyclic GANs. Additionally, collecting paired images required for GANs may be costly, especially in the medical domain. Cyclic GANs are a favorable choice for addressing this issue, as they can convert cross-domain images. However, no pre-existing technique or algorithm is comprehensive enough to handle diverse datasets and applications. To address these issues, we propose a novel Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) that employs evolutionary computation, multiobjective optimization, and an intelligent selection scheme. We use simulated annealing and Pareto ranking selection using three fitness criteria to address local optima stagnation. Additionally, we use model quantization because of its suitability for low-cost IoT-based applications. Extensive trials reveal that EMCGAN and QEMCGAN produces more visually realistic images than other approaches while preserving both background information and salient features. In addition, QEMCGAN performs on par with the baseline approach even when the model size is halved, making it more efficient.

Concept drift detection in toxicology datasets using discriminative subgraph-based drift detector.

Due to the increasing importance of graphs and graph streams in data representation in today's era, concept drift detection in graph streaming scenarios is more important than ever. Contributions to concept drift detection in graph streams are minimal and practically non-existent in the field of toxicology. This paper applied the discriminative subgraph-based drift detector (DSDD) to graph streams generated from real-world toxicology datasets. We used four toxicology datasets, each of which yielded two graph streams - one with abrupt drift points and one with gradual drift points. We used DSDD both with the standard minimum description length (MDL) heuristic and after replacing MDL with a much simpler heuristic SIZE (number of vertices + number of edges), and applied it to all generated graph streams containing abrupt drift points and gradual drift points for varying window sizes. Following that, we compared and analyzed the results. Finally, we applied a long short-term memory based graph stream classification model to all the generated streams and compared the difference in the performances obtained with and without detecting drift using DSDD. We believe that the results and analysis presented in this paper will provide insight into the task of concept drift detection in the toxicology domain and aid in the application of DSDD in a variety of scenarios.

Anti-hyperglycemic potential of Lactobacillus spp. in alloxan-induced Wistar rats.

This research was aimed to investigate anti-hyperglycemic effects of two Lactobacillus spp. on alloxan induced diabetic rats. Alloxan was administered intraperitoneally to induce the diabetic conditions in experimental rats. Animals were treated with oral administration of Lactobacillus spp., such as L. plantarum and L. acidophilus at the dose of 108 CFU/ml. As a result, administration of Lactobacillus spp. significantly (P<0.05) lowered blood glucose levels in diabetic rats by (201-220mg/dl) as compared to diabetic control (265mg/dl). Also, both the Lactobacillus spp. were able to reduce body weight of experimental animals as compared to control group, suggesting potent anti-hyperglycemic effect of Lactobacillus spp. in terms of their anti-diabetic potential.

Pharmacognostical Standardization of Upodika- Basella alba L.: An Important Ayurvedic Antidiabetic Plant.

OBJECTIVE: To establish the pharmacognostic standards for the correct identification and standardization of an important Antidiabetic plant described in Ayurveda. MATERIALS AND METHODS: Standardization was carried out on the leaf and stem of Basella alba L. with the help of the macro-morphological, microscopic, physicochemical and qualitative phytochemical studies. RESULTS: Several specific characters were identified viz. clustered calcium oxalate crystals in the cortex region, absence of trichomes, succulent, thick, mucilaginous, fibrous stem. Rubiaceous type of stomata on both sides of the leaf. Quantitative microscopy along with physicochemical and qualitative phytochemical analysis were also established. CONCLUSION: The pharmacognostic standards could serve as the reference for the proper identification of the Basella alba L. which is an important anti-diabetic plant described in Ayurveda.

Abscisic acid and abiotic stress tolerance - different tiers of regulation.

Abiotic stresses affect plant growth, metabolism and sustainability in a significant way and hinder plant productivity. Plants combat these stresses in myriad ways. The analysis of the mechanisms underlying abiotic stress tolerance has led to the identification of a highly complex, yet tightly regulated signal transduction pathway consisting of phosphatases, kinases, transcription factors and other regulatory elements. It is becoming increasingly clear that also epigenetic processes cooperate in a concerted manner with ABA-mediated gene expression in combating stress conditions. Dynamic stress-induced mechanisms, involving changes in the apoplastic pool of ABA, are transmitted by a chain of phosphatases and kinases, resulting in the expression of stress inducible genes. Processes involving DNA methylation and chromatin modification as well as post transcriptional, post translational and epigenetic control mechanisms, forming multiple tiers of regulation, regulate this gene expression. With recent advances in transgenic technology, it has now become possible to engineer plants expressing stress-inducible genes under the control of an inducible promoter, enhancing their ability to withstand adverse conditions. This review briefly discusses the synthesis of ABA, components of the ABA signal transduction pathway and the plants' responses at the genetic and epigenetic levels. It further focuses on the role of RNAs in regulating stress responses and various approaches to develop stress-tolerant transgenic plants.