Lifeboat Foundation

Dopamine seems to be having a moment in the zeitgeist. You may have read about it in the news, seen viral social media posts about “dopamine hacking,” or listened to podcasts about how to harness what this molecule is doing in your brain to improve your mood and productivity. However, recent neuroscience research suggests that popular strategies to control dopamine are based on an overly narrow view of how it functions.

Dopamine is one of the brain’s neurotransmitters — tiny molecules that act as messengers between neurons. It is known for its role in tracking your reaction to rewards such as food, sex, money, or answering a question correctly. There are many kinds of dopamine neurons located in the uppermost region of the brainstem that manufacture and release dopamine throughout the brain. Whether neuron type affects the function of the dopamine it produces has been an open question.

Recently published research reports a relationship between neuron type and dopamine function, and one type of dopamine neuron has an unexpected function that will likely reshape how scientists, clinicians, and the public understand this neurotransmitter.

A team of researchers in Japan claims to have figured out a way to translate the clucking of chickens with the use of artificial intelligence.

As detailed in a yet-to-be-peer-reviewed preprint, the team led by University of Tokyo professor Adrian David Cheok — who has previously studied sex robots — came up with a “system capable of interpreting various emotional states in chickens, including hunger, fear, anger, contentment, excitement, and distress” by using “cutting-edge AI technique we call Deep Emotional Analysis Learning.”

They say the technique is “rooted in complex mathematical algorithms” and can even be used to adapt to the ever-changing vocal patterns of chickens, meaning that it only gets better at deciphering “chicken vocalizations” over time.

Microglial cells are the maintenance workers of the central nervous system (CNS), protecting against pathogens and pruning damaged neurons to help the brain maintain homeostasis. Considered immune cells, microglia work to protect the brain from before it is fully formed through its lifetime, but they aren’t infallible. The cells can be primed early on to respond in certain ways, making the microglia’s clean-up efforts less efficient. As other cells age, they can complicate microglial function, making them less effective.

But the underlying mechanism of how microglial cells age and how their aging directly affects the brain is poorly understood—meaning that attempts to prevent or treat brain dysfunction may not be as effective as they could be, according to a multi-institutional collaboration led by Bo Peng and Yanxia Rao, both professors at Fudan University.

The team investigated how microglial cells change as they age in both male and female mice across their lifespans, finding what the researchers called “unexpected sex differences.” They also established a model to study aged microglial cells in a non-aged brain, revealing that aged-like microglia contribute to cognitive decline even in young mice. The researchers published their findings in Nature Aging.

Here’s my new article for Aporia magazine, the final futurist story in my 4-part series for them!

Written by Zoltan Istvan.

I met my wife on Match.com 15 years ago. She didn’t have a picture on her profile, but she had written a strong description of herself. It was enough to warrant a first date, and we got married a year later.

Continue reading “Dating in the world of ‘Deep Fakes’” »

The Y chromosome is a never-ending source of fascination (particularly to men) because it bears genes that determine maleness and make sperm. It’s also small and seriously weird; it carries few genes and is full of junk DNA that makes it horrendous to sequence.

However, new “long-read” sequencing techniques have finally provided a reliable sequence from one end of the Y to the other. The paper describing this Herculean effort has been published in Nature.

The findings provide a solid base to explore how genes for sex and sperm work, how the Y chromosome evolved, and whether—as predicted—it will disappear in a few million years.

Female kidneys are known to be more resilient to disease and injury, but males need not despair. A new USC Stem Cell-led study published in Developmental Cell describes not only how sex hormones drive differences in male and female mouse kidneys, but also how lowering testosterone can “feminize” this organ and improve its resilience.

“By exploring how differences emerge in male and female kidneys during development, we can better understand how to address sex-related health disparities for patients with kidney diseases,” said Professor Andy McMahon, the study’s corresponding author, and the director of the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at the Keck School of Medicine of USC.

First authors Lingyun “Ivy” Xiong and Jing Liu from the McMahon Lab and their collaborators identified more than 1,000 genes with different levels of activity in male and female mouse kidneys, in a study supported by the National Institutes of Health. The differences were most evident in the section of the kidney’s filtering unit known as the proximal tubule, responsible for reabsorbing most of the nutrients such as glucose and amino acids back into the blood stream.

A new study reveals the brain circuit that controls sex drive in male mice. Scientists believe this finding could apply to humans and may allow them to manipulate the male libido.

Scientists at Stanford Medicine have identified the exact part of the brain that controls sex drive in mice. It is possible that the same part of the human brain also regulates libido in men.

“We’ve singled out a circuit in male mammals’ brains that controls sexual recognition, libido, and mating behavior and pleasure,” said Nirao Shah, one of the senior researchers and a professor of behavioral sciences at Stanford.

One of the smallest chromosomes in humans, the male sex chromosome is the final one to be fully sequenced.

Brain age was estimated using an algorithm that combined multiple measures of brain structure obtained through MRI scans when the participants were 45 years old. This algorithm quantified the difference between estimated brain age and the participants’ chronological age, referred to as brain age gap estimate.

If the estimated brain age is higher than the chronological age, it suggests that the brain’s structural characteristics are more similar to those of an older individual. Conversely, if the estimated brain age is lower than the chronological age, the brain’s structural characteristics resemble those of a younger individual.

Lay-Yee and his colleagues also adjusted their analyses for various potential confounding factors. These included socio-demographic factors like sex and socio-economic status, as well as family factors (teen-aged mother, single parent, change in residence, maltreatment) and child-behavioral factors (self-control, worry/fearfulness).