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Roger Guillemin (1924–2024), neuroscientist who showed how the brain controls hormones

Roger Guillemin identified the molecules in the brain that control the production of hormones in endocrine glands such as the pituitary and thyroid. His work led to a torrent of advances in neuroendocrinology, with far-reaching effects on studies of metabolism, reproduction and growth. For his discoveries on peptide-hormone production in the brain, Guillemin shared the 1977 Nobel Prize in Physiology or Medicine with Andrew Schally and Rosalyn Yalow. He has died at the age of 100.

In the autumn of 1969, after analysing millions of sheep brains for more than a decade, Guillemin and his colleagues determined the structure of thyrotropin-releasing factor (TRF). This small peptide is produced in the hypothalamus, a small region at the base of the brain, and is transported to the anterior lobe of the nearby pituitary gland, where it triggers the release of the hormone thyrotropin. Thyrotropin, in turn, stimulates the thyroid gland to produce the hormone thyroxine, which regulates metabolic activity in nearly every tissue of the body. More than two dozen drugs use such hypothalamic hormones to treat endocrine disorders and cancers, and the worldwide market for these drugs is worth several billion dollars.

Guillemin was born in Dijon, France, and came of age at the end of the Second World War. He graduated from medical school in the University of Lyon, France, in 1949 and worked as a country doctor in the small commune of Saint-Seine-l’Abbaye in Burgundy. He found the work satisfying but intellectually limiting, noting that “in those days I could take care of all my patients with three prescriptions, including aspirin”. Fascinated by how the brain and pituitary gland control the body’s response to stress, he attended lectures in Paris by the Hungarian–Canadian endocrinologist Hans Selye, after which Selye accepted Guillemin’s request to spend a year doing research in his laboratory at the University of Montreal, Canada.

Blood in Space: Exploring Forensic Science Beyond Earth

With the continued advancement of human space exploration, how can forensic science—which contributes to the criminal justice system by analyzing evidence through a myriad of methods—be applied to outer space? This is what a soon-to-be-published study in Forensic Science International Reports hopes to address as a team of international researchers led by Staffordshire University investigated how bloodstain patterns behave under microgravity conditions. This study holds the potential to help scientists and astronauts better understand how Earth-based science can be applied to space, specifically long-term spaceflight.

“Studying bloodstain patterns can provide valuable reconstructive information about a crime or accident,” said Zack Kowalske, who is a PhD student at Staffordshire University and a Crime Scene Investigator for the Roswell Police Department in the State of Georgia, and lead author of the study. “However, little is known about how liquid blood behaves in an altered gravity environment. This is an area of study that, while novel, has implications for forensic investigations in space.”

For the study, the researchers conducted blood spatters experiments on parabolic flights onboard a modified Boeing 747 with an emphasis on observing various angles of impact of the blood droplets and comparing their splatter patterns to those obtained under normal gravity conditions. The reason parabolic flights were used was due to their ability to simulate microgravity conditions, as they are designed to rapidly drop in altitude, thus providing passengers with a few moments of weightlessness.

Daratumumab Plus Standard Therapy for Multiple Myeloma

People in the daratumumab group who stayed MRD negative for at least a year were able to stop taking daratumumab as maintenance therapy and remained cancer free. That’s important, Dr. Sonneveld said, because taking fewer drugs long-term for maintenance therapy often translates to a better well-being and quality of life.

Adding daratumumab to the standard treatment resulted in a nearly 60% drop in the risk of cancer progression or death (hazard ratio of 0.42), the researchers determined.

The magnitude of that change is “unprecedented in these kinds of phase 3 trials [for] multiple myeloma,” Dr. Sonneveld said.

Checkpoint Dimer May Toggle between Anticancer and Antiautoimmune Action

The authors cited results from a recent Phase II clinical trial reporting that Peresolimab, a PD-1 agonist monoclonal antibody, was effective in treating rheumatoid arthritis, but that the mechanism whereby peresolimab acts as an agonist was not reported. “Our characterization of PD-1 TMD dimerization may help inform evolving strategies for developing both agonists and antagonists,” they stated.

Co-senior investigator and cancer immunologist Jun Wang, PhD, an assistant professor in the Department of Pathology at NYU Grossman and Perlmutter, added, “Our findings offer new insights into the molecular workings of the PD-1 immune cell protein that have proven pivotal to the development of the current generation of anticancer immunotherapies, and which are proving essential in the design and developing of the next generation of immunotherapies for autoimmune diseases.”

Among the study’s findings was that a single change in the amino acid structure of the transmembrane segment can act to either enhance or diminish the inhibitory function of PD-1 in immune responses. The team plans further investigations of PD-1 inhibitors and agonists to see if they can tailor what they say are more effective, “rationally designed” therapies for both cancer and autoimmune disorders. Concluding on their findings in their paper, the team wrote, “In this study, we show that PD-1 and its ligands form dimers as a consequence of transmembrane domain (TMD) interactions and that propensity for dimerization correlates with PD-1 ability to inhibit immune responses, antitumor immunity, cytotoxic T cell function, and autoimmune tissue destruction. These observations contribute to our understanding of the PD-1 axis and how it can potentially be manipulated for improved treatment of cancer and autoimmune diseases.”

AI finds Key Signs that Predict Patient Survival Across Dementia Types

Researchers at the Icahn School of Medicine at Mount Sinai and others have harnessed the power of machine learning to identify key predictors of mortality in dementia patients.

The study, published in the February 28 online issue of Communications Medicine, addresses critical challenges in dementia care by pinpointing patients at high risk of near-term death and uncovers the factors that drive this risk.

Unlike previous studies that focused on diagnosing dementia, this research delves into predicting patient prognosis, shedding light on mortality risks and contributing factors in various kinds of dementia.