Lifeboat Foundation

Twitter CEO Linda Yaccarino regrets that she was not able to use her boss Elon Musk’s wildly vulgar AI chatbot to teach her kids about sex. You know, regular stuff for an exec to say publicly!

To back up for a second: Grok, as the AI is called, was released this weekend to a small group of test users. Whereas other chatbots like OpenAI’s ChatGPT and Google’s Bard have been criticized by many on the right for being too liberal, Grok is specifically designed to be anti-“woke,” like a seasoned Twitter troll; it has the humor of a 13-year-old boy, and yet somehow a 53-year-old man. Unsurprisingly, the limited users with access quickly took to X-formerly-Twitter to share the AI’s sometimes tame-ish, sometimes deranged outputs with their followers.

One of those posts, shared to X on Tuesday by Babylon Bee staffer Ashley St. Clair and reshared by Musk, featured Grok’s response to the question of how babies are made.

In this study we aimed to detect epigenetic and genetic loci associated with PTSD in a homogeneous cohort of traumatized police officers. Both a genome-wide and hypothesis-driven replication approach did not result in DMPs between PTSD patients and trauma-exposed controls. GSE analysis on the top 100 DMPs showed, however, a plausible association of the dopaminergic neurogenesis pathway with PTSD. Furthermore, we observed one DMR located at the PAX8 gene suggesting consistent hypermethylation in PTSD patients. Genetic analyses yielded three CpG-SNPs significantly associated with PTSD. Of these, one CpG-SNP, located at the CACNA1C locus, was also significantly associated with PTSD in an independent replication sample of trauma-exposed children. Notably, this result shows that the Illumina 450K array is not restricted to epigenetic surveys but can provide informative genetic data as well.

Although our sample was small, it was highly homogenous as all participants were former or current police officers, and cases and controls were matched for sex, age, education, and years of police service. All participants reported multiple prior traumatic events, without significant group differences in reported types of traumatic experiences. PTSD patients fulfilled current diagnostic criteria for PTSD, while our trauma-exposed controls had minimal PTSD symptoms and did not report lifetime PTSD or other trauma-related psychiatric disorders. Thus our controls were apparently resilient to adverse mental health outcome of trauma. This study design, including extreme phenotypes following similar trauma load, was considered to favor detection of PTSD-associated loci, as also suggested by others [22]. Nevertheless, our genome-wide survey clearly remains limited in statistical power.

The thymus, a small and relatively unknown organ, may play a bigger role in the immune system of adults than was previously believed. With age, the glandular tissue in the thymus is replaced by fat, but, according to a new study from Linköping University, the rate at which this happens is linked to sex, age and lifestyle factors. These findings also indicate that the appearance of the thymus reflects the aging of the immune system.

“We doctors can assess the appearance of the thymus from largely all chest CT scans, but we tend to not see this as very important. But now it turns out that the appearance of the thymus can actually provide a lot of valuable information that we could benefit from and learn more about,” says Mårten Sandstedt, MD, Ph.D., at the Department of Radiology in Linköping and Department of Health, Medicine and Caring Sciences, Faculty of Medicine and Health Sciences, Linköping University.

The thymus is a gland located in the upper part of the chest. It has been long known that this small organ is important for immune defense development in children. After puberty, the thymus decreases in size and is eventually replaced by fat, in a process known as fatty degeneration. This has been taken to mean that it loses its function, which is why the thymus has for a long time been considered as being not important in adult life.

In America, roughly 40 million Americans have diabetes and about 95% of them have type 2 diabetes. Type 2 diabetes occurs when the body cannot correctly process sugar and fuel cells. More specifically, the body does not produce enough insulin to break down sugar into glucose for the cells to use. In this case, treatment includes insulin shots or a pump in addition to a strict diet excluding sweets or high fat meals. Treatment limitations disrupt patient quality of life. Some researchers have been working on better detection for diabetic retinopathy with artificial intelligence (AI), but research is limited on how to better detect diabetes itself. Thus, many researchers are working to detect diabetes early on and discover better treatments.

Klick labs, located in multiple cities across the world, is trying to detect type 2 diabetes by having a patient speak into a microphone for 10 seconds. Klick labs believes this technology can better detect diabetes and help patients get treatment earlier. The study was published in Mayo Clinic Proceedings: Digital Health, which details how patients spoke for 10 seconds and combined with health data, including age, sex, height, and weight, created an AI model that discerns whether a person has type 2 diabetes or not. After further tests, scientists determined it has 89% and 86% accuracy for women and men, respectively.

In the study, Klick Labs collected voice recordings of 267 people, either non-diabetic or diabetic. The participants were asked to record a phrase into their smartphones six times a day for a total of 2-weeks. Over 18,000 recordings were taken and analyzed to distinguish 14 acoustic features that helped distinguish non-diabetic to type 2 diabetic individuals. The research highlights specific vocal variations in pitch and intensity that could lead to how the medical community screens for early-onset diabetes. A major barrier to early detection includes time, travel, and cost, which many people do not have. Voice diagnosis can help eliminate those barriers and improve detection and treatment in diabetic patients.

O.o!!!!

Cybrothel.

“We are the future of sex,” says Philipp Fussenegger–owner of Cybrothel is the first immersive sex doll brothel in Germany’s capital city Berlin.

Central learning and memory hubs change in response to sex hormones. A new study in Nature Mental Health by Rachel Zsido and Julia Sacher of the Max Planck Institute for Human Cognitive and Brain Sciences and the University Clinic in Leipzig, Germany, links rhythmic oscillations in ovarian hormone levels in women during the menstrual cycle to changes in brain structure.

Ovarian hormones have significant effects on the brain, and early menopause may be associated with an increased risk of accelerated brain aging and dementia later in life. However, the effects of ovarian hormone fluctuations on brain structure earlier in life are less defined. In their current study, Zsido and Sacher show that fluctuations in ovarian hormones affect structural plasticity in key brain regions during the reproductive years.

To do this, the scientists collected blood samples from 27 female study participants, used ultrasound to track follicle growth in the ovaries to pinpoint ovulation timing, and utilized ultra-high field 7 Tesla MRI to zoom into subregions of the medial temporal lobe and hippocampus. That’s because these regions are dense with sex hormone receptors and are critical for cognitive function, such as episodic memory.

Hospital nurseries routinely place soft bands around the tiny wrists of newborns that hold important identifying information such as name, sex, mother, and birth date. Researchers at Rockefeller University are taking the same approach with newborn brain cells—but these neonates will keep their ID tags for life, so that scientists can track how they grow and mature, as a means for better understanding the brain’s aging process.

As described in a new paper in Cell, the new method developed by Rockefeller geneticist Junyue Cao and his colleagues is called TrackerSci (pronounced “sky”). This low-cost, high-throughput approach has already revealed that while newborn cells continue to be produced through life, the kinds of cells being produced greatly vary in different ages. This groundbreaking work, led by co-first authors Ziyu Lu and Melissa Zhang from Cao’s lab, promises to influence not only the study of the brain but also broader aspects of aging and disease across the human body.

“The cell is the basic functional unit of our body, so changes to the cell essentially underlie virtually every disease and the aging process,” says Cao, head of the Laboratory of Single-Cell Genomics and Population Dynamics. “If we can systematically characterize the different cells and their dynamics using this novel technique, we may get a panoramic view of the mechanisms of many diseases and the enigma of aging.”

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.