Clustering with neural networks

Partitioning a set ofN patterns in ad-dimensional metric space intoK clusters — in a way that those in a given cluster are more similar to each other than the rest — is a problem of interest in many fields, such as, image analysis, taxonomy, astrophysics, etc. As there are approximatelyK ^N/K! possible ways of partitioning the patterns amongK clusters, finding the best solution is beyond exhaustive search whenN is large. We show that this problem, in spite of its exponential complexity, can be formulated as an optimization problem for which very good, but not necessarily optimal, solutions can be found by using a Hopfield model of neural networks. To obtain a very good solution, the network must start from many randomly selected initial states. The network is simulated on the MPP, a 128 × 128 SIMD array machine, where we use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also in starting the network from many initial states at once thus obtaining many solutions in one run. We achieve speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of further speedups of three to six orders of magnitude.Supported by a National Research Council-NASA Research Associatship     

Study of quercetin and fisetin synergistic effect on breast cancer and potentially involved signaling pathways

Naturally-derived drugs have drawn much attention in recent decades. Efficiency, lower toxicity, and economic reasons are some of their advantages that justify this broad range of administration for different diseases, including cancer. If we can find a specific combination that boosts the effects of their single therapy, leading to synergism effect, increased efficiency, and decreased toxicity, they can act even better. Quercetin and fisetin, two well-known flavonoids, have been used to fight against various cancers. In this study, we investigated their possible synergism quercetin and fisetin on MCF7, MDA-MB-231, BT549, T47D, and 4T1 breast cancer cell lines. Then the optimum combined dose was used to study their impacts on wound healing abilities and clonogenic properties. The real-time qPCR was used to study the expression of their validated downstream effectors in predicted pathways. A significant synergism effect (p < .01, combination index: <1) was observed for all cell lines. Combination therapy was significantly more effective in colony formation (p < .0001) and wound healing assays (p < .001) compared to single therapies. The expression level of potential effectors was also showed a greater change. In vivo study confirmed the in vitro results and showed how significantly (p < .001) their synergism promotes their singular function in inhibiting cancer progression. The breast cancer mouse models receiving combined therapy lived longer with higher average body weight and smaller tumor sizes. These results exhibit that quercetin and fisetin inhibit cancer cell proliferation, migration and colony formation synergistically, and matrix metalloproteinase signaling and apoptotic pathways are relatively responsible for inhibitory activities.     

Using Immunoinformatics and Structural Approaches to Design a Novel HHV8 Vaccine

International Journal of Peptide Research and Therapeutics - Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) or human herpesvirus 8 (HHV8) has caused infection in different parts of the...     

Expression of recombinant human IFN-γ protein in soybean (Glycine max L.)

Plant Cell, Tissue and Organ Culture (PCTOC) - Globular androgenic haploid embryos of TV21 and TV19 cultivars of Camellia ssp., obtained on embryo induction medium (EIM), Murashige and Skoog medium...     

MicroRNA-424-5p enhances chemosensitivity of breast cancer cells to Taxol and regulates cell cycle,apoptosis, and proliferation

Molecular Biology Reports - Combination therapy has been considered as a potential method to overcome the BC chemoresistance. MicroRNAs (miRs) have been suggested as a therapeutic factor in the...     

Molecular phylogeny and historical biogeography of the Anatolian lizard Apathya (Squamata,Lacertidae)

Apathya is a lacertid genus occurring mainly in south-east Turkey and its adjacent regions (part of Iran and Iraq). So far two morphological species have been attributed to the genus; A. cappadocica (with five subspecies, A. c. cappadocica, A. c. muhtari, A. c. schmidtlerorum, A. c. urmiana and A. c. wolteri) and A. yassujica. The first species occupies most of the genus’ distribution range, while A. yassujica is endemic of the Zagros Mountains. Here, we explored Apathya’s taxonomy and investigated the evolutionary history of the species by employing phylogenetic and phylogeographic approaches and using both mitochondrial (mtDNA) and nuclear markers. The phylogenetic relationships and the genetic distances retrieved, revealed that Apathya is a highly variable genus, which parallels its high morphological variation. Such levels of morphological and genetic differentiation often exceed those between species of other Lacertini genera that are already treated as full species, suggesting the necessity for a taxonomic revision of Apathya. The phylogeographical scenario emerging from the genetic data suggests that the present distribution of the genus was determined by a combination of dispersal and vicariance events between Anatolia and Southwest Asia dating back to the Miocene and continuing up to the Pleistocene. Key geological events for the understanding of the phylogeography of the genus are the movement of the Arabian plate that led to the configuration of Middle East (orogenesis of the mountain ranges of Turkey and Iran) and the formation of Anatolian Diagonal.     

Structure-activity study of phosphoramido acid esters as acetylcholinesterasf inhibitors

Phosphoramido acid esters (CH₃)₂NP(O)X(p-OC₆H₄-CH₃) (containing P-Cl (1), P-O (2), P-F (3), P-CN (5), and P-N (4,6) bonds, X for 2, 4 and 6 is OCH₃, (C₂H₅)₂N and morpholin) have been synthesized to investigate the structure-activity study of AChE enzyme inhibition, through the parameters logP, δ³¹P and IC₅₀. After their characterization by ³¹P, ³¹P{¹H}, ¹³C, ¹H NMR, IR and mass spectroscopy, the parameters logP and δ³¹P (³¹P chemical shift in NMR) were used to evaluated the lipophilicity and electronical properties. The ability of compounds to inhibit human AChE was predicted by PASS software (version 1.193), and experimentally evaluated by a modified Ellman's assay.