When Biology Takes a Back Seat

Powerful antibiotic discovered using machine learning for first time
Feb 2020, The Guardian

The drug works in a different way to existing antibacterials and is the first of its kind to be found by setting AI loose on vast digital libraries of pharmaceutical compounds.
“In terms of antibiotic discovery, this is absolutely a first,” said Regina Barzilay, a senior researcher on the project and specialist in machine learning at Massachusetts Institute of Technology (MIT). 

“I think this is one of the more powerful antibiotics that has been discovered to date,” added James Collins, a bioengineer on the team at MIT. “It has remarkable activity against a broad range of antibiotic-resistant pathogens.” 

To find new antibiotics, the researchers first trained a “deep learning” algorithm to identify the sorts of molecules that kill bacteria. To do this, they fed the program information on the atomic and molecular features of nearly 2,500 drugs and natural compounds, and how well or not the substance blocked the growth of the bug E coli.
Once the algorithm had learned what molecular features made for good antibiotics, the scientists set it working on a library of more than 6,000 compounds under investigation for treating various human diseases. Rather than looking for any potential antimicrobials, the algorithm focused on compounds that looked effective but unlike existing antibiotics. This boosted the chances that the drugs would work in radical new ways that bugs had yet to develop resistance to. 

Jonathan Stokes, the first author of the study, said it took a matter of hours for the algorithm to assess the compounds and come up with some promising antibiotics. One, which the researchers named “halicin” after Hal, the astronaut-bothering AI in the film 2001: A Space Odyssey, looked particularly potent.

Reprogramming of immune system cures child with often-fatal fungal infection
June 2020, phys.org

"Immune modulation isn't currently part of the strategy with any of these severe infections," said Dr. Manish Butte, the report's senior author, who holds the E. Richard Stiehm Endowed Chair in Pediatric Allergy, Immunology and Rheumatology at the David Geffen School of Medicine at UCLA. "Our case suggests that rather than hoping to get the upper hand with more and more antibiotics or antifungals, we can have some success by combining these established approaches with the new idea of programming the patient's immune response to better fight the infection."

Synthetic red blood cells mimic natural ones, and have new abilities
June 2020, phys.org

Bioengineers have made synthetic red blood cells that have all the same abilities of natural blood cells, and even a few more.

On a sidenote, I'm also thinking about the Impossible burger that uses synthetically produced hemoglobin. And on a supersidenote, that had me wondering what's worse, humans eating animals, or humans trying to avoid eating animals so they re-engineer a bacteria's genetic code so that it can make blood, and then take that blood and add it to a plant, so that we can eat plants that taste like meat. Like, bacteria didn't even bleed before we got involved, and now that they do, doesn't that mean we should stop eating them too?

Post Script on Biomimicry

A self-cleaning surface that repels even the deadliest superbugs
Dec 2019, phys.org

Researchers develop new method to remove dust on solar panels
Dec 2019, phys.org

Taking a cue from the self-cleaning properties of the lotus leaf, researchers at Ben-Gurion University of the Negev have shed new light on microscopic forces and mechanisms that can be optimized to remove dust from solar panels to maintain efficiency and light absorption. The new technique removed 98 percent of dust particles.
In a new study published in Langmuir, the researchers confirmed that modifying the surface properties of solar panels may greatly reduce the amount of dust remaining on the surface, and significantly increase the potential of solar energy harvesting applications in the desert.
Particle removal increased from 41 percent on hydrophilic smooth Si wafers to 98 percent on superhydrophobic Si-based nanotextured surfaces.
"We determined that the reason for the increased particle removal is not low friction between the droplets and the superhydrophobic surfaces," Heckenthaler says. "Rather, it is the increase in the forces that can detach particles from the surfaces. The experimental methods we used and the criterion for particle removal we derived can be implemented to engineer self-cleaning surfaces exhibiting different chemistries and/or textures."

-image source: I really hate it when websites don't credit their artwork (almost as much as I hate the threeway image clusterfu**ing olympics performed by Google-Getty-Pinterest triangle). This image came from the site at this link, but they list no artist credits.