Rapid biodegradation of microplastics generated from bio-based thermoplastic polyurethane in compost

Accumulation of microplastics in the natural environment is ultimately due to the chemical nature of widely used petroleum-based plastic polymers, which typically are inaccessible to biological processing. One way to mitigate this crisis is adoption of plastics that biodegrade if released into natural environments. In this work, we generated microplastic particles from a bio-based, biodegradable thermoplastic polyurethane (TPU-FC1) and demonstrated their rapid biodegradation via direct visualization and respirometry. Furthermore, we isolated multiple bacterial strains capable of using TPU-FC1 as a sole carbon source and characterized their depolymerization products. To visualize biodegradation of TPU materials as real-world products, we generated TPU-coated cotton fabric and an injection molded phone case and documented biodegradation by direct visualization and scanning electron microscopy (SEM), both of which indicated clear structural degradation of these materials and significant biofilm formation.

Source: Rapid biodegradation of microplastics generated from bio-based thermoplastic polyurethane | Scientific Reports

Conclusion

In this work, particle count and respirometry experiments demonstrated that microplastic particles from a bio-based thermoplastic polyurethane can rapidly biodegrade and therefore are transiently present in the environment. In contrast, microplastic particles from a widely used commercial thermoplastic, ethyl vinyl acetate, persists in the environment and showed no significant signs of biodegradation over the course of this experiment. Bacteria capable of utilizing TPU-FC1 as a carbon source were isolated and depolymerization of the material was confirmed by the early accumulation of monomers derived from the original polymer, which are metabolized by microbes in short order. Finally, we demonstrated that prototype products made from these materials biodegrade under home compost conditions. The generation of microplastics is an unavoidable consequence of plastic usage and mitigating the persistence of these particles by adoption of biodegradable material alternatives is a viable option for a future green circular economy.

GitHub’s new AI-powered tool auto-fixes vulnerabilities in your code

GitHub introduced a new AI-powered feature capable of speeding up vulnerability fixes while coding. This feature is in public beta and automatically enabled on all private repositories for GitHub Advanced Security (GHAS) customers.

Known as Code Scanning Autofix and powered by GitHub Copilot and CodeQL, it helps deal with over 90% of alert types in JavaScript, Typescript, Java, and Python.

After being toggled on, it provides potential fixes that GitHub claims will likely address more than two-thirds of found vulnerabilities while coding with little or no editing.

“When a vulnerability is discovered in a supported language, fix suggestions will include a natural language explanation of the suggested fix, together with a preview of the code suggestion that the developer can accept, edit, or dismiss,” GitHub’s Pierre Tempel and Eric Tooley said.

The code suggestions and explanations it provides can include changes to the current file, multiple files, and the current project’s dependencies.

Implementing this approach can significantly reduce the frequency of vulnerabilities that security teams must handle daily.

This, in turn, enables them to concentrate on ensuring the organization’s security rather than being forced to allocate unnecessary resources to keep up with new security flaws introduced during the development process.

However, it’s also important to note that developers should always verify if the security issues are resolved, as GitHub’s AI-powered feature may suggest fixes that only partially address the security vulnerability or fail to preserve the intended code functionality.

“Code scanning autofix helps organizations slow the growth of this “application security debt” by making it easier for developers to fix vulnerabilities as they code,” added Tempel and Tooley.

“Just as GitHub Copilot relieves developers of tedious and repetitive tasks, code scanning autofix will help development teams reclaim time formerly spent on remediation.”

The company plans to add support for additional languages in the coming months, with C# and Go support coming next.

More details about the GitHub Copilot-powered code scanning autofix tool are available on GitHub’s documentation website.

Last month, the company also enabled push protection by default for all public repositories to stop the accidental exposure of secrets like access tokens and API keys when pushing new code.

This was a significant issue in 2023, as GitHub users accidentally exposed 12.8 million authentication and sensitive secrets via more than 3 million public repositories throughout the year.

As BleepingComputer reported, exposed secrets and credentials have been exploited for multiple high-impact breaches [123] in recent years.

Source: GitHub’s new AI-powered tool auto-fixes vulnerabilities in your code