Detection of 232bp Virulent Gene of Pathogenic <i>Aeromonas hydrophila</i>through PCR Based Technique: (<i>A Rapid Molecular Diagnostic Approach</i>)

The pathogenicity of aeromonads produces due to exotoxins such as cytolytic enterotoxin, hemolysin or aerolysin, lipases and proteases. Rapid detection of A. hydrophila cytolytic enterotoxin (AHCYTONE) gene and their characterization has proven importance so that proper and rapid preventive and control measures could be taken up to reduce mortality and loss in fish culture. The main objective of the present study is to genetic identification of AHCYTONE positive Aeromonas hydrophila. Strains were isolated from fishes from different fish market in West Bengal and water samples from different river and ponds. Initially strains were identified by their phenotypic and biochemical characterization. Due to contradiction of those results, molecular characterization was done by polymerase chain reaction, which is proved a suitable and rapid diagnostic tool for identification and characterization of A. hydrophila. We have also evaluated the potential risk to human health that this finding can represent by determining the presence of the cytolytic enterotoxin gene in such isolates.

Characterization of Aeromonas hydrophila through RAPD-PCR and SDS-PAGE Analysis

Aeromonas hydrophila isolated from fish (Labeo rohita), pond water, river water, raw meat of chicken and mutton and raw cow milk were characterized through Random Amplified Polymorphic DNA (RAPD) analysis and Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS PAGE) of cellular proteins. RAPD-PCR amplification of bacterial DNA was done by using ten random primers (OPA-01 to 10) and found some distinct banding pattern on agarose gel. RAPD profile was studied with each isolate and absolute polymorphism indicating its application as an ideal tool for molecular characterization. Other methods like morphological, serological and biochemical characterization gives contradictory results and total cellular protein profiling does not show any significant polymorphism for identification and discrimination.

Cellular automata basedmulti-bit stuck-at fault diagnosis for resistive memory

This paper presents a group-based dynamic stuck-at fault diagnosis scheme intended for resistive randomaccess memory(ReRAM).Traditional static random-access memory,dynamic random-access memory,NAND,and NOR flash memory are limited by their scalability,power,package density,and so forth.Next-generation memory types like ReRAMs are considered to have various advantages such as high package density,non-volatility,scalability,and low power consumption,but cell reliability has been a problem.Unreliable memory operation is caused by permanent stuck-at faults due to extensive use of write-or memory-intensive workloads.An increased number of stuck-at faults also prematurely limit chip lifetime.Therefore,a cellular automaton(CA)based dynamic stuck-at fault-tolerant design is proposed here to combat unreliable cell functioning and variable cell lifetime issues.A scalable,block-level fault diagnosis and recovery scheme is introduced to ensure readable data despite multi-bit stuck-at faults.The scheme is a novel approach because its goal is to remove all the restrictions on the number and nature of stuck-at faults in general fault conditions.The proposed scheme is based on Wolfram’s null boundary and periodic boundary CA theory.Various special classes of CAs are introduced for 100%fault tolerance:single-lengthcycle single-attractor cellular automata(SACAs),single-length-cycle two-attractor cellular automata(TACAs),and single-length-cycle multiple-attractor cellular automata(MACAs).The target micro-architectural unit is designed with optimal space overhead.