Fear is often thought of as a negative emotion but is actually a natural protective response to perceived threats or danger. It helps us survive. When we experience a situation that causes fear, it becomes stored in our brain as a fear memory. These fear memories prevent us from touching a hot stove after being burned or from stepping onto a busy street.
What about fear memories that take over? Post-traumatic stress disorder, or PTSD, is caused by severe acute or chronic stress that disrupts the learning process designed to suppress fear memories. These memories then begin to negatively affect a person’s quality of life.
Typically, our fear memories can be suppressed through extinction learning. The original memory or fear isn’t forgotten, but a new memory is formed and suppresses the original fear memory. However, extinction learning can become tricky in situations that involve traumatic memories.
Diabetes opens people to other noncommunicable diseases like obesity, retinopathy and cardiovascular diseases like heart attacks and hypertension. A recent study by researchers at the University of Virginia School of Medicine sought to understand how common high blood pressure (BP) was among people with diabetes. They measured the BP of 172 adults with type 1 or type 2 diabetes and asked for their opinions on being screened during their eye exams.
Uncontrolled blood pressure was a common finding among the patients. Of the entire cohort, only about one in 12 had a normal blood pressure reading. Roughly half of the patients had stage 2 hypertension. They also found that about 10.5% had BP levels in the hypertensive crisis range—a level at which BP becomes a medical emergency because, if left untreated, it can lead to serious events such as a heart attack or stroke.
Having their blood pressure checked at the eye doctor was considered reasonable and acceptable by 93% of patients, as many were unaware they had a medical condition that needed attention, and some were under the impression that their BP was under control.
Human trisomy 21, responsible for Down syndrome, is the most prevalent genetic cause of cognitive impairment and remains a key focus for prenatal and preimplantation diagnosis. However, research directed toward eliminating supernumerary chromosomes from trisomic cells is limited. The present study demonstrates that allele-specific multiple chromosome cleavage by clustered regularly interspaced palindromic repeats Cas9 can achieve trisomy rescue by eliminating the target chromosome from human trisomy 21 induced pluripotent stem cells and fibroblasts. Unlike previously reported allele-nonspecific strategies, we have developed a comprehensive allele-specific (AS) Cas9 target sequence extraction method that efficiently removes the target chromosome. The temporary knockdown of DNA damage response genes increases the chromosome loss rate, while chromosomal rescue reversibly restores gene signatures and ameliorates cellular phenotypes. Additionally, this strategy proves effective in differentiated, nondividing cells. We anticipate that an AS approach will lay the groundwork for more sophisticated medical interventions targeting trisomy 21.
Keywords: CRISPR/Cas; Down syndrome; allele specificity; chromosome cut; chromosome loss; human trisomy 21.
© The Author(s) 2025. Published by Oxford University Press on behalf of National Academy of Sciences.
Scientists have engineered a nanoscale switch using DNA “origami.” Inspired by macroscale mechanical switches, the device achieves long-term functionality without the continuous forcing mechanism that past versions required while remaining capable of fast switching. The paper is published in the journal Science Robotics.
This is not the first time scientists have used DNA as a building material. DNA origami—a technique that folds a single-stranded DNA scaffold into precise 2D or 3D shapes using short DNA strands—offers a way to build custom nanomachines. It has been used in everything from drug delivery to electrically actuated devices. However, in electrically actuated devices, many prior designs faced a trade-off between speed, stability and durability.
In particular, researchers have been interested in creating nanoscale switches that act like their macroscopic counterparts. So far, attempts at DNA-based nanoswitches have lacked either long-term stability without continuous forcing, millisecond switching or high cycle endurance. Many earlier devices relied on DNA “latches,” but these were slow or prone to spontaneous dissociation from natural nanoscale thermal movements.
A Berlin-based team from HZB and Center for the Science of Materials Berlin (CSMB) at Humboldt-Universität zu Berlin has set a new record for a tandem solar cell. Using a combination of a CIGS semiconductor layer and perovskite, along with several optimized intermediate layers, the team converted 25.5% of sunlight into electrical energy. The previous record for this combination of materials and this size cell had stood at 24.6%.
The new record has been certified and is visible in the Solar Cell Efficiency Tables (the “Green Tables”) published in the journal Joule, which serve as the definitive ledger for the global photovoltaic community. To be included in this special “record table,” not only is high efficiency required, but also an area of more than 1 cm2. The well-known NLR table (formerly NREL), by contrast, lists only the maximum efficiency per technology, even if the cell has an area of 0.001 cm2.
As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess depth perception, and visually examine and enjoy all manner of objects and happenings.
But trying to envision subvisible structures and high-dimensional processes that our human-engineered scopes can’t capture is a challenge for data scientists and visualization experts, who turn to machine learning and AI tools to amplify visual exploration.
“Biological processes are an example of complex, high-dimensional data,” says Kevin Moon, director of USU’s Data Science and Artificial Intelligence (DSAI) Center and associate professor in the Department of Mathematics and Statistics.