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The worldwide prevalence of antimicrobial resistance coupled with the unavailability of newer antibiotics, has brought the sharp focus back among the scientific community, towards the discovery of novel alternative therapeutics to tackle the menace. Consequently, in the current post-antibiotic era, ‘Bacteriophage Therapy’ has emerged as one of the most promising option to address this problem. Bacteriophages, actually discovered long back, has shown greater potential to kill various bacterial pathogens, including the resistant clinical ones. Some of the other advantages for the use of bacteriophage therapy to treat infectious diseases include, wider availability of these microorganisms in nature, host-specific action, absence of any significant side-effects in humans and most often also exhibiting a broader anti-bacterial potential. In the recent times, the potential of phage therapy has been demonstrated in various treatments, clinical trials and infection models across the globe, where even antibiotics have completely failed. To address the global threat of AMR, WHO and UN have jointly illustrated “One Health” approach, recently extending the context to bacteriophage therapy. Many pharmaceutical companies have also recently started employing bacteriophages for developing different kinds of formulations for catering to medical and other industries. It has even shown great effect as combinatorial therapy along with antibiotics, to treat or manage various critical antibiotic resistant clinical infections. This continuously expanding potential of the bacteriophages holds great promise in the future, in the fight against the rising threat of AMR globally.

Prior research has established that dynamically trading-off the performance of the radio-frequency (RF) front-end for reduced power consumption across changing channel conditions, using a feedback control system that modulates circuit and algorithmic level “tuning knobs” in real-time based on received signal quality, leads to significant power savings. It is also known that the optimal power control strategy depends on the process conditions corresponding to the RF devices concerned. This leads to an explosion in the search space needed to find the best feedback control strategy, across all combinations of channel conditions and receiver process corners, making simulation driven optimal control law design impractical and computationally infeasible. Since this problem is largely intractable due to the above complexity of simulation, we propose a self-learning strategy for adaptive RF systems. In this approach, RF devices learn their own performance vs. power consumption vs. tuning knob relationships “on-the-fly” and formulate the most power-optimal control strategy for real-time adaptation of the RF system using neural-network based learning techniques during real-time operation. The methodology is demonstrated using SISO and MIMO RF receiver front-ends as test vehicles and is supported by hardware validation leading to 2.5X-3X power savings with minimal overhead. [ABSTRACT FROM PUBLISHER]

•An isoform of crustin antimicrobial peptide was cloned and expressed from black tiger shrimp.•Recombinant crustin exhibited broad spectrum antibacterial activity against both Gram positive and Gram negative bacteria.•Low minimum inhibitory concentration against vibrio pathogens of shrimp showed its potential for use in aquaculture.

A fish nodavirus was detected in the juveniles of Asian seabass (Lates calcarifer) during a massive outbreak in the seabass cage culture farm located in the south west coast of India. The clinical signs of the disease included anorexia, inflated abdomen, exophthalmia, darkening of the whole body, erratic swimming and cork-screw type movement followed by death. The dead and the moribund fish were analyzed for nodavirus by reverse transcriptase-polymerase chain reaction (RT-PCR) using specific primers targeting the T4 region of RNA2 coat protein gene. This is the first report of nodavirus infection in the fresh water cage-reared seabass fish in the west coast of India. The piscine nodavirus was detected in the brain, retina and kidney of all the fishes examined. The PCR products were cloned and sequenced. The sequence analysis showed more than 90 % homology with the other coat protein gene sequence of piscine nodaviruses from other countries. The phylogenetic analysis based on the partial nucleotide sequence of RNA2 coat protein gene revealed that the virus belonged to the red-spotted grouper nervous necrosis virus, which is one of the widely distributed genotype among the other four known genotypes of piscine nodavirus.

The extent of local excess or deficiency of a component solvent near the solute $$\delta _{s{_1}} $$ in a mixed binary solvent has been calculated using the Hall formalism for the Kirkwood-Buff equation. The possibility of calculation of the two solute-solvent Kirkwood-Buff parameters $$G_{s{_1}} $$ using the $$\delta _{s{_1}} $$ values is discussed. A model calculation using literature data for preferential solvation in mixed binary solvents is presented. The solute-solvent and solvent-solvent interactions and the relative size of the solvents are also shown to be relevant factors in determining the $$G_{s{_1}} $$ values.

The article elaborates on how best to manage an Agile software development team in India. Topics include subtle differences when Agile is applied for building enterprise software or Internet software as well as geography of teams and Agile software in the views of the executive, an engineering manager, a developer and a quality engineer. Also mentioned are some project recommendations, including looking for problems that should be resolved and building mutual respect among team members.