March 2026 - CarboHyde

Cyclodextrin – retinol complex

Mar 17, 2026adminnews, educationcarbohyde, cyclodextrin, retinol

Retinol is one of the most powerful actives in skincare—but also one of the most challenging to formulate.

In this short deck, we explore how cyclodextrin complexation can unlock better retinol performance by addressing its biggest formulation hurdles:
• Improved chemical stability against oxidation, UV, and heat
• Reduced irritation risk through controlled, gradual release
• Maintained bioavailability via reversible complexation
• Simpler formulation systems compared with traditional encapsulation approaches

The result: better tolerability, sustained activity, and improved commercial viability for retinol-based products.

Curious how it works in practice?
Take a look at the full deck 👇

CDs retinol complex Download

2nd Bicyclos HEurope workshop

Mar 16, 2026adminnewsbicyclos, carbohyde, conference

Just last week, some members of the closer (Milo Malanga PhD and Mihaly Balint) and larger (Szabolcs Béni) CarboHyde team attended the 2nd Bicyclos HEurope workshop and annual gathering.

Our grant is progressing well, sharing knowledge and experience among the fantastic members under the scope of this MSCA Staff Exhange grant has been really rewarding.

See you all in 2027 in Budapest, if not sooner 😉

AI will write your grant proposal

Mar 13, 2026adminnews, educationcarbohyde, cyclodextrin

Sounds exciting and dangerously misleading.

What generative AI can realistically do in scientific research is find relevant papers when connected to real databases, accelerate structured summaries and cross-paper comparisons, and polish rough drafts into precise, evidence-based language. What it cannot do is guarantee that a single citation it generates actually exists.

At the 2nd Bicyclos HEurope International School and Workshop in Sevilla, our very own Milo Malanga PhD delivered a hands-on session on the responsible use of generative AI in literature search, analysis and proposal writing, putting five major AI platforms to the test with a deliberately fabricated citation request. Some tools generated complete references to authors, journals, and DOIs to a paper that was never written, while others searched real databases and returned only verified sources.

The difference between a hallucinated DOI in your MSCA proposal and a verified one is not a minor detail; it is a credibility risk that can undermine months of work.

AI is a powerful accelerator for research workflows, but verification is not optional, IP protection is not an afterthought, and critical thinking is not something we can afford to outsource.

Speed matters, but accuracy matters more.

Have you ever caught an AI-generated citation that turned out to be completely fabricated? We’d love to hear how you’re navigating AI in your research workflow.