Carlos Polanco González

CUBA HAS PASSED A LAW FOR THE DETERMINATION AND CERTIFICATION OF DEATH

During the last several decades physicians and the community have needed urgent changes in the legal codes for accepting brain death (BD) as death, to obtain organs from heart-beating donors. The “dead donor rule” requires that donors must be first declared dead.1 For this reason, most codes legalizing BD are usually sections of transplant laws.2 Thus, a conceptual and practical controversy emerged: if brain-dead cases were not useful as organ donors, they were usually kept on life support until cardiac arrest occurred.2–4

An FPGA Implementation to Detect Selective Cationic Antibacterial Peptides

Exhaustive prediction of physicochemical properties of peptide sequences is used in different areas of biological research. One example is the identification of selective cationic antibacterial peptides (SCAPs), which may be used in the treatment of different diseases. Due to the discrete nature of peptide sequences, the physicochemical properties calculation is considered a high-performance computing problem. A competitive solution for this class of problems is to embed algorithms into dedicated hardware. In the present work we present the adaptation, design and implementation of an algorithm for SCAPs prediction into a Field Programmable Gate Array (FPGA) platform. Four physicochemical properties codes useful in the identification of peptide sequences with potential selective antibacterial activity were implemented into an FPGA board. The speed-up gained in a single-copy implementation was up to 108 times compared with a single Intel processor cycle for cycle. The inherent scalability of our design allows for replication of this code into multiple FPGA cards and consequently improvements in speed are possible. Our results show the first embedded SCAPs prediction solution described and constitutes the grounds to efficiently perform the exhaustive analysis of the sequence-physicochemical properties relationship of peptides.

Moonlighting Peptides with Emerging Function

Hunter-killer peptides combine two activities in a single polypeptide that work in an independent fashion like many other multi-functional, multi-domain proteins. We hypothesize that emergent functions may result from the combination of two or more activities in a single protein domain and that could be a mechanism selected in nature to form moonlighting proteins. We designed moonlighting peptides using the two mechanisms proposed to be involved in the evolution of such molecules (i.e., to mutate non-functional residues and the use of natively unfolded peptides). We observed that our moonlighting peptides exhibited two activities that together rendered a new function that induces cell death in yeast. Thus, we propose that moonlighting in proteins promotes emergent properties providing a further level of complexity in living organisms so far unappreciated.

Electronic Devices That Identify Individuals with Fever in Crowded Places: A Prototype

Most epidemiological surveillance systems for severe infections with epidemic potential are based on accumulated symptomatic cases in defined geographical areas. Eventually, all cases have to be clinically verified to confirm an outbreak. These patients will present high fever at the early stages of the disease. Here, we introduce a non-invasive low-cost electronic device (bracelet) that measures and reports 24/7, year-round information on the temperature, geographical location, and identification of the subject using the device. The data receiver can be installed in a tower (ground) or a drone (air) in densely populated or remote areas. The prototype was made with low-cost electronic components, and it was tested indoors and outdoors. The prototype shows efficient ground and air connectivity. This electronic device will allow health professionals to monitor the prevalence of fever in a geographical area and to reduce the time span between the presentation of the first cases of a potential outbreak and their medical evaluation by giving an early warning. Field tests of the device, programs, and technical diagrams of the prototype are available as Supplementary Materials.

The Use of Dedicated Processors to Accelerate the Identification of Novel Antibacterial Peptides

Abstract: In the past decades, the procedure to identify novel antibiotic compounds has been motivated by the heuristic discovery of the antibiotic penicillin by Fleming in 1929. Since then, researches have been isolating compounds from very wide range of living forms with the hope of repeating Fleming’s story. Yet, the rate of discovery of new pharmaceutical compounds has reached a plateau in the last decade and this has promoted the use of alternative approaches to identify antibiotic compounds. One of these approaches uses the accumulated information on pharmaceutical compounds to predict new ones using high-performance computers. Such approach brings up the possibility to screen for millions of compounds in computer simulations. The better predictors though use sophisticated algorithms that take up significant amount of computer time, reducing the number of compounds to analyze and the likelihood to identify potential antibiotic compounds. At the same time, the appearance of computer processors that may be tailored to perform specific tasks by the end of the past century provided a tool to accelerate high-performance computations. The current review focuses on the use of these dedicated processor devices, particularly Field Programmable Gate Arrays and Graphic Processing Units, to identify new antibacterial peptides. For that end, we review some of the common computational methods used to identify antibacterial peptides and highlight the difficulties and advantages these algorithms present to be coded into FPGA/GPU computational devices. We discuss the potential of reaching supercomputing performance on FPGA/GPU, and the approaches for parallelism on these platforms.