Modern scientific societies are increasingly vulnerable due to their dependence on membership fees and journal subscriptions, which are being challenged by the rise of virtual networking and open-access publishing.
"We hope that by taking strong action against violations of agreed-upon policy we will remind the community that as our field changes rapidly the thing we must protect most actively is our trust in each other."
Do you blame others for the choices you are making? Have you blamed others for the previous choices you have made? To shed more light on these questions, you might also ask yourself: "What am I responsible for, and what power do I have?" From there, you might agree with this self-reflective response: "I am responsible for, and I've got the power over what I think, do, say, learn, and choose" (Purje, 2014).
Within a couple of years of ChatGPT coming out, I had come to rely on the artificial-intelligence tool, for my work as a professor of plant sciences at the University of Cologne in Germany. Having signed up for OpenAI's subscription plan, ChatGPT Plus, I used it as an assistant every day - to write e-mails, draft course descriptions, structure grant applications, revise publications, prepare lectures, create exams and analyse student responses, and even as an interactive tool as part of my teaching.
As it turns out, neuroscience might be able to explain why. In a new study whose findings will surprise absolutely no one who's endured a fiery holiday dinner debate, researchers discovered that conservative and liberal brains don't just arrive at fundamentally different conclusions, but take strikingly different paths to get there. It's a fascinating piece of research which just might explain something about the yawning political divides currently tearing society apart.
Publisher Correction: Multiple oestradiol functions inhibit ferroptosis and acute kidney injury Publisher Correction Open access Published: 21 January 2026 Wulf Tonnus orcid.org/0000-0002-9728-14131 na1, Francesca Maremonti2 na1, Shubhangi Gavali orcid.org/0000-0003-2876-14532 na1, Marlena Nastassja Schlecht orcid.org/0000-0001-8893-53261, Florian Gembardt2, Alexia Belavgeni orcid.org/0000-0001-6311-58583, Nadja Leinung2, Karolin Flade orcid.org/0009-0009-5449-28251, Natalie Bethe1,
I'm less interested in topics than in questions, and I'm less interested in publishing than I am in curation. When I've testified before Congress or dealt with an appropriations bill or a budget negotiation, this question, of what is the return on investments when you're doing R&D, comes up quite often. It's been asked by economists in very formal ways since at least the 1950s, but the data and the methods that were available were really not very strong.
Some clinicians have an uncanny quality. A colleague describes herself and others with this instinct as "witchy"-a capacity to know things about patients they haven't said yet, to follow a stray association to a song lyric or a half-remembered cultural reference and arrive, reliably, at something the patient urgently needed to say but couldn't reach on their own. We see with artificial intelligence these intriguing possibilities for discovery, especially as connections that human beings never would see pop out of apparently unrelated data.
In 2023, Australia abandoned its expensive and bureaucratic scholar-led research-assessment programme. New Zealand followed suit soon after. The hope, according to a transition plan unveiled by the Australian federal government's Department of Education and the research sector, was to find a "more modern, data-driven approach". In the United Kingdom, where financial pressures on universities are especially acute, there are similar calls to reform the Research Excellence Framework (REF), the country's performance-based research-funding system.
Fifty-four seconds. That's how long it took Raphael Wimmer to write up an experiment that he did not actually perform, using a new artificial-intelligence tool called Prism, released by OpenAI last month. "Writing a paper has never been easier. Clogging the scientific publishing pipeline has never been easier," wrote Wimmer, a researcher in human-computer action at the University of Regensburg in Germany, on Bluesky. Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process.
Ever since our ancestors first stood upright and squinted at the horizon, we've been wired to notice patterns. A rustle in the grass might have meant a stalking predator. Dark clouds often meant rain. Those who made these connections and guessed that one thing caused another tended to survive. Over time, this ability to link events became one of our most significant evolutionary advantages. It's how we built tools, tamed fire, and eventually invented Wi-Fi.