From the article: It’s one of the most exciting areas of cancer research, but identifying the tumors through blood tests remains difficult, particularly for early-stage detection.

Despite breakthrough blood-test research for many types of cancers and specific sources such as lung and breast cancers, and the flourishing field of development of multi-cancer early detection (MCED) tests, screening generally still involves invasive biopsies of cells.

Researchers at the University of Technology (UTS) in Sydney, Australia, are hoping to change that, with the development of their new biotech, the Static Droplet Microfluidic (SDM) device. It can quickly detect circulating tumor cells (CTC) that have split from the cancer source to enter the bloodstream. It paves the way for very early detection, monitoring and treatment.

“A single tumor cell can exist among billions of blood cells in just one milliliter of blood, making it very difficult to find," said Majid Warkiana, professor from the UTS School of Biomedical Engineering. "The new detection technology has 38,400 chambers capable of isolating and classifying the number of metabolically active tumor cells."

The SDM can pick out tumor cells through a unique metabolic signature involving waste product lactate.

From the article: Importantly, the study found no evidence that the results varied based on the presence of a genetic variant associated with alcohol use disorder.

Topiramate is a medication that is commonly used to treat epilepsy and prevent migraine headaches. It works by regulating the activity of certain chemicals in the brain that can contribute to seizures or migraines. In recent years, topiramate has also been studied as a potential treatment for alcohol dependence, as it may help reduce cravings and symptoms of withdrawal. But scientists are not sure if a specific variation in the GRIK1 gene (rs2832407) affects how well topiramate works to reduce drinking.

“My research interests include personalizing substance use disorder treatments for people based on different characteristics, including why they use substances, co-occurring psychological disorders, and biological characteristics (e.g., genetics), among other considerations,” said study author Victoria Votaw, a PhD candidate and National Institute on Alcohol Abuse and Alcoholism predoctoral fellow at the University of New Mexico.

“Therefore, I was very interested in research showing that the effect of topiramate, a medication that has shown efficacy for treating alcohol use disorder, on alcohol use outcomes might vary by a type of genetic mutation called a single-nucleotide polymorphism. Upon doing a deeper dive into this literature, I realized the findings were mixed, and my co-authors and I decided to look at daily data reported via telephone from a trial of topiramate to further explore this research question.”

“Using daily data might help clarify how topiramate works for different people and provide more information regarding whether topiramate’s effectiveness depends on the genetic variant we examined.”

The study involved 164 people who wanted to stop or reduce their drinking. They were randomly divided into two groups: one group received topiramate, while the other group received a placebo (a “dummy” medication with no active ingredients). Participants were seen once a week for six weeks and the medication dosage was gradually increased from 25 mg/day to a maximum of 200 mg/day.

From the article: Scientists across multiple disciplines are working to create revolutionary biocomputers where three-dimensional cultures of brain cells, called brain organoids, serve as biological hardware. They describe their roadmap for realizing this vision in the journal Frontiers in Science.

“We call this new interdisciplinary field ‘organoid intelligence’ (OI),” said Prof Thomas Hartung of Johns Hopkins University. “A community of top scientists has gathered to develop this technology, which we believe will launch a new era of fast, powerful, and efficient biocomputing.”

Brain organoids are a type of lab-grown cell-culture. Even though brain organoids aren’t ‘mini brains’, they share key aspects of brain function and structure such as neurons and other brain cells that are essential for cognitive functions like learning and memory. Also, whereas most cell cultures are flat, organoids have a three-dimensional structure. This increases the culture's cell density 1,000-fold, meaning that neurons can form many more connections.

But even if brain organoids are a good imitation of brains, why would they make good computers? After all, aren't computers smarter and faster than brains?

"While silicon-based computers are certainly better with numbers, brains are better at learning,” Hartung explained. “For example, AlphaGo [the AI that beat the world’s number one Go player in 2017] was trained on data from 160,000 games. A person would have to play five hours a day for more than 175 years to experience these many games.” 

Brains are not only superior learners, they are also more energy efficient. For instance, the amount of energy spent training AlphaGo is more than is needed to sustain an active adult for a decade.

“Brains also have an amazing capacity to store information, estimated at 2,500TB,” Hartung added. “We’re reaching the physical limits of silicon computers because we cannot pack more transistors into a tiny chip. But the brain is wired completely differently. It has about 100bn neurons linked through over 1015 connection points. It’s an enormous power difference compared to our current technology.”

From the article: New research provides evidence that people who grew up in an unstable environment are more susceptible to food addiction. The findings, published in the journal Appetite, indicate that unpredictability in one’s earlier stages of life is associated with maladaptive patterns of food intake.

Food addiction is a term used to describe a problematic pattern of food intake characterized by a lack of control, unsuccessful attempts to eat less, and continuing to overeat despite negative consequences.

“Considering the deleterious consequences of food addiction (e.g., obesity and depression), the risk factors leading to adults’ food addiction warrant examination,” said study author Hope Zhou, a PhD student at the University of Macau.

“Understanding the psychological mechanism of food addiction from the perspective of life history may help evaluate and decrease one’s risks for food addiction. These results may yield a theoretical framework for the development of food addiction and practical insights for future food addiction intervention programs.”

The new study was based on life history theory, which seeks to explain how organisms allocate resources over their lifetime in order to maximize their reproductive success. The theory holds that one’s early life environment shapes internal strategies of how to allocate energy and resources.