Cutting-edge genetics research reveals a startling legacy embedded in our DNA.
This will help clinicians understand where a person sits on the disease pathway and who may need closer monitoring or earlier, targeted treatment.
There may be two distinct subtypes of multiple sclerosis, according to a new study led by scientists at University College London (UCL). The finding, if validated, could help doctors provide more specialized care for patients.
The study used machine learning to analyze data drawn from blood tests and brain scans of 634 patients participating in two different clinical trials. Machine learning models are trained to pick up subtle patterns that humans might miss.
The blood tests were for detecting a protein called serum neurofilament light chain (sNfL), a known biomarker of diseases of the nervous system, including multiple sclerosis (MS).
How do we slow down atherosclerosis? Researcher Amanda Foks believes this is possible by eliminating aging immune cells. This would represent a completely new treatment for heart attacks and strokes. For this research, she has received the Established Investigator Dekker Grant from the Dutch Heart Foundation.
Hoe remmen we slagaderverkalking af? Onderzoeker Amanda Foks denkt dat dit mogelijk is door verouderde afweercellen uit te schakelen. Dat zou een geheel nieuwe behandeling tegen hart-en herseninfarcten zijn. Voor dit onderzoek ontvangt ze de Established Investigator Dekkerbeurs van de Hartstichting.
Slagaderverkalking ontstaat doordat vetten en cellen zich jarenlang ophopen in de vaatwand. Vaak merk je daar niets van, totdat zo’n verdikking plotseling scheurt. Dan kan er acuut een hart-of herseninfarct ontstaan.
Met de leeftijd neemt het risico toe: bloedvaten worden minder soepel en het afweersysteem werkt minder goed, waardoor ontstekingen ontstaan. Die ontstekingen versnellen juist weer de slagaderverkalking.
The new 3D model system looks to replicate the complex physiological properties and cellular composition of the endometrium. The model is built in a step-by-step process by bringing together the different components of endometrial tissue. The team isolated two essential cell types that form endometrial tissue – epithelial cells and stromal cells – from tissue donated by healthy people who had endometrial biopsies.
As well as the cell types, the researchers sought to recreate the structure of the womb lining. Information from donated endometrial tissue was used to identify the tissue components that give the womb lining its structure. The researchers were able to incorporate these components together with the stromal cells into a special type of gel to support the growth of the cells in a thick layer. On top of this, they added the epithelial cells, which spread out over the surface of the stromal cells.
Once assembled, this formed an advanced replica of the womb lining, matching a biopsy of endometrial tissue in terms of cellular architecture, and showing responses to hormone stimulation that indicate the engineered womb lining’s receptivity for embryo implantation.
The team tested their model using donated early-stage human embryos from IVF procedures, and found that the embryo – at this point a compact ball of cells – underwent the expected stages expected of adhesion and invasion into the endometrial scaffold. Following implantation, the embryos increased secretion of human chorionic gonadotropin (hCG), a biochemical marker used in pregnancy tests to confirm pregnancy, and other pregnancy-associated proteins.
Furthermore, the system supported post-implantation development of the embryo, enabling the analysis of embryo stages (12−14 days post fertilisation) that have been largely unexplored. The researchers observed that implanted embryos reached several developmental milestones, such as the appearance of specialist cell types in the embryo and also the establishment of precursor cell types important for the development of the placenta.
Using single cell analysis of implantation sites, the researchers were able to profile cells at the interface between the embryo and endometrium model, effectively listening in to the molecular communication between the tissues. Their results provide new insight into the complex interactions between the embryo and endometrial environment that underpin embryo development immediately after implantation.
Over 70 million Americans wear digital activity trackers (DATs) to record their sleep, steps and heart rate. A new study from Scripps Research found that these devices could also provide insight into even more, including individual health risks like obstructive sleep apnea (OSA) and high blood pressure.
The findings, published in the Journal of Medical Internet Research on December 3, 2025, used DATs to identify an association between sleep variability—the night-to-night fluctuation of when an individual falls asleep and wakes—and their risk of developing sleep apnea and hypertension. This research joins a growing body of evidence that DATs could become more useful clinical tools to assess health risks in the near future.
“Data from digital activity trackers provides a unique way to detect meaningful health patterns from the devices that people already own,” says Stuti Jaiswal, senior author and assistant professor at Scripps Research, who is also a faculty hospitalist at Scripps Clinic. “Digital health studies have been gaining acceptance over the past decade, and we’re now demonstrating what these technologies can reveal about how sleep influences cardiovascular health.”
A systematic review and meta-analysis found that people with kidney stones have about twice the risk of developing kidney cancer compared with those without stones, across patient subgroups. The findings support closer cancer surveillance in patients with a history of kidney stones and further research into shared disease mechanisms, given the prevalence of kidney stones and the aggressive nature of kidney cancer.
A new meta-analysis further supports the previously reported link between kidney stones and an increased risk for kidney cancer, with a stronger relationship observed in newer studies.
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Long-term exposure to fine particulate matter like PM2.5 components in polluted air can not only cause respiratory diseases, but also increase the risk of depression in older people, especially in those living with preexisting heart, metabolic and neurological conditions.
Depression has caused more loss of healthy life worldwide than any other mental health condition. This disorder has snatched away people’s will to perform the basics of daily activities. An analysis of global health data in 2021 showed that all the years people lived with disability or reduced quality of life because of depression added up to about 56.3 million years.
A recent population-based cohort study collected data from nearly 23.7 million U.S. Medicare beneficiaries aged 65 years and older between 2000 and 2018 to examine specific components of PM2.5 exposure, both individually and in combination, and its associations with the risk of developing depression. Among those tracked, more than 5.5 million developed depression during the follow-up period. These findings are published in JAMA Network Open.