biomedical research
Coverage of biomedical research in the Nexus archive.
- Trump slashed medical research. A Maryland lawmaker fears the next move.
President Donald Trump's administration has reduced funding for health and science research through administrative actions. A proposed rule would grant GOP political appointees significant control over federal research funding, prompting concerns from Maryland's biomedical community and Rep. Jamie Raskin, who called the move 'disastrous and likely unlawful.'
- Diabetes Association in uproar after members expelled from annual meeting over protest of NIH cuts
Five diabetes experts were expelled from the American Diabetes Association annual meeting in New Orleans for distributing an editorial criticizing federal cuts to biomedical research. The incident has sparked backlash in the diabetes research and practice community, with the ADA's communications further worsening the situation.
- Northwestern researcher among group kicked out of conference for distributing paper critical of Trump
A Northwestern researcher and four others were removed from an American Diabetes Association conference for distributing an editorial critical of President Trump's attacks on scientific research. The group faced police intervention and had their materials confiscated, with the association citing code of conduct violations.
- Senior NIH official pushes MAHA strategy to skeptical ADA audience
A senior NIH official endorsed the Make America Healthy Again (MAHA) movement at a diabetes research conference and defended criticism of biomedical research funding cuts. Richard Woychik, an adviser to NIH Director Jay Bhattacharya, stated he could have written the MAHA agenda, referencing Health Secretary Robert F. Kennedy Jr.'s policy.
- ‘Virtual cells’ aim to turn raw data into predictive models of biology
Researchers are developing 'virtual cells' to create predictive models of biology using simulations, aiming to advance biomedical research. However, challenges remain in accurately replicating biological complexity without being overwhelmed by data.