Prophylactic co-trimoxazole in biliary surgery.

A double-blind study was conducted to test the prophylactic effect of a single dose of co-trimoxazole on the incidence of septic complications after elective cholecystectomy. Forty-eight patients received co-trimoxazole and 47 placebo. Wound sepsis occurred in 10 (21%) of the controls but in only 2 (4%) of the treated group, and the incidences of pulmonary complications were 49% (23 cases) and 19% (9) respectively. These differences were significnat. Wound sepsis after cholecystectomy occurs mostly in patients with infected bile. Co-trimoxazole given by intravenous infusion rapidly achieves a high concentration in the palsma and is effective against most biliary pathogens.     

Bacillus subtilis as potential producer for polyhydroxyalkanoates

Polyhydroxyalkanoates (PHAs) are biodegradable polymers produced by microbes to overcome environmental stress. Commercial production of PHAs is limited by the high cost of production compared to conventional plastics. Another hindrance is the brittle nature and low strength of polyhydroxybutyrate (PHB), the most widely studied PHA. The needs are to produce PHAs, which have better elastomeric properties suitable for biomedical applications, preferably from inexpensive renewable sources to reduce cost. Certain unique properties of Bacillus subtilis such as lack of the toxic lipo-polysaccharides, expression of self-lysing genes on completion of PHA biosynthetic process – for easy and timely recovery, usage of biowastes as feed enable it to compete as potential candidate for commercial production of PHA.     

Cloning and expression analysis of two distinct HIF-alpha isoforms – gcHIF-1alpha and gcHIF-4alpha – from the hypoxia-tolerant grass carp,Ctenopharyngodon idellus

Background  

Hypoxia-inducible factors (HIFs) are involved in adaptive and survival responses to hypoxic stress in mammals. In fish, very little is known about the functions of HIFs.     

AmylPepPred: Amyloidogenic Peptide Prediction tool

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibril forming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties of primary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a user friendly web interface for the researchers to easily observe the fibril forming and non-fibril forming hexmers in a given protein sequence. We expect that this stratagem will be highly encouraging in discovering fibril forming regions in proteins thereby benefit in finding therapeutic agents that specifically aim these sequences for the inhibition and cure of amyloid illnesses.

Availability

AmylPepPred is available freely for academic use at www.zoommicro.in/amylpeppred