Antimicrobial peptides as novel anti-tuberculosis therapeutics

"Available online 24 May 2016"Tuberculosis (TB), a disease caused by the human pathogen Mycobacterium tuberculosis, has recently joined HIV/AIDS as the world's deadliest infectious disease, affecting around 9.6 million people worldwide in 2014. Of those, about 1.2 million died from the disease. Resistance acquisition to existing antibiotics, with the subsequent emergence of Multi-Drug Resistant mycobacteria strains, together with an increasing economic burden, has urged the development of new anti-TB drugs. In this scope, antimicrobial peptides (AMPs), which are small, cationic and amphipathic peptides that make part of the innate immune system, now arise as promising candidates for TB treatment. In this review, we analyze the potential of AMPs for this application. We address the mechanisms of action, advantages and disadvantages over conventional antibiotics and how problems associated with its use may be overcome to boost their therapeutic potential. Additionally, we address the challenges of translational development from benchside to bedside, evaluate the current development pipeline and analyze the expected global impact from a socio-economic standpoint. The quest for more efficient and more compliant anti-TB drugs, associated with the great therapeutic potential of emerging AMPs and the rising peptide market, provide an optimal environment for the emergence of AMPs as promising therapies. Still, their pharmacological properties need to be enhanced and manufacturing-associated issues need to be addressed.Portuguese Foundation for Science and Technology (FCT) - UID/ BIO/04469/2013 unit ; COMPETE 2020 (POCI-01-0145-FEDER- 006684) ; SFRH/BPD/64958/2010Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462

Scalable computational framework using intelligent optimization: Microgrids dispatch and electricity market joint simulation

International audienceWorldwide microgrid capacity is expected to reach 7 GW and a market value of $35 billion dollars in the next few years. The decentralization of the generation dispatch role and different ownership models concerning microgrids, will contribute to increase the complexity of the future power systems. Analyzing new policies and strategies as well as evaluating those impacts is only possible with the use of sophisticated simulation tools. This paper presents a scalable computational simulation to address microgrid dispatch and the impact in the electricity market. Computational intelligence techniques are integrated to improve the effectiveness of the simulation tool. These techniques include CPLEX; differential search algorithm and quantum particle swarm optimization. Each microgrid player is able to solve a day-ahead scheduling problem and submit bids to the electricity market agent (spot market), which calculates the market clearing price. The developed case study with a large number of players totaling about 150,000 consumers suggest the relevance of the developed computational framework