This is a clear case of using biology as a solution to — and a healthier and safe alternative to — the environmentally toxic process of synthetic chemical dyeing of leather.
Researchers from Imperial College London have genetically engineered bacteria to actually grow leather that can dye itself using the bacteria’s own pigment. What’s more, the leather grown thus neither contains animal flesh (or any animal parts) nor any plastic.
While scientists have been resorting to microbes to produce sustainable textiles and make dyes for industrial purposes, this is the first time that bacteria are being engineered to produce material, simultaneously producing pigment to dye it. The researchers call it a self-dyeing vegan, plastic-free leather, and they have already come out with prototypes of shoes and wallets to present their findings, which have been published in the journal Nature Biotechnology. It convincingly represents steps in the direction of sustainable fashion.
As things stand, the Imperial College London’s research team’s findings have the adaptive potential to make bacteria grow various materials with a range of vibrant colours and patterns using their own pigments. The researchers used bacterial cellulose, which is vegan, and requires minuscule amounts of carbon emissions compared to conventional methods, minimal water or land use and saves considerable time that involves farming cows for conventional leather. Besides, bacterial cellulose can be made without petrochemicals and it is safely biodegradable, and therefore safe for the environment.
Neural plasticity
Universal brain-computer interfa ce lets people play games with just thoughts
Imagine playing a racing game like Mario Kart, using only your brain to execute the complex series of turns in a lap. This is not a video game fantasy, but a real programme that engineers at The University of Texas at Austin have created as part of research into brain-computer interfaces to help improve the lives of people with motor disabilities.
More importantly, the researchers incorporated machine learning capabilities with their braincomputer interface, making it a one-size-fits-all solution. These devices require extensive calibration for each user – every brain is different, both for healthy and disabled users – and that has been a major hurdle to mainstream adoption. This new solution can quickly understand the needs of an individual subject and self-calibrate through repetition. That means multiple patients could use the device without needing to tune it to the individual.
“When we think about this in a clinical setting, this technology will make it so we won’t need a specialised team to do this calibration process, which is long and tedious,” says Satyam Kumar, a graduate student in the lab of Jose del R Millan, a professor in the Cockrell School of Engineering’s Chandra Family Department of Electrical and Computer Engineering and Dell Medical School’s Department of Neurology.
“It will be much faster to move from patient to patient.” The subjects wear a cap packed with electrodes that is hooked up to a computer. The electrodes gather data by measuring electrical signals from the brain, and the decoder interprets that information and translates it into game action. Millan’s work helps users guide and strengthen their neural plasticity, the ability of the brain to change, grow and reorganise over time.
These experiments are designed to improve brain function for patients and use the devices controlled by brain-computer interfaces to make their lives easier. In this case, the actions were two-fold: the car racing game, and a simpler task of balancing the left and right sides of a digital bar.
Source: University of Texas at Austin