Lifeboat Foundation

An important objective of medical research is to identify the underlying molecular mechanisms of human brain health and diseases.

This objective has been predominantly achieved through observational studies of gene expression in human brain tissues obtained from post-mortem brain donors for their analysis. Importantly, many of these studies are based on the assumption that gene expression in the post-mortem human brain is an exact representation of gene expression in the living human brain.

A recent study published on the medRxiv preprint server challenges this assumption by comparing human prefrontal cortex gene expression between living and post-mortem samples.

A recent study posted to the medRxiv preprint server investigates the association between the circulating proteome and brain health.

Study: The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses. Image Credit: Abduramanova Elena / Shutterstock.com.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

“As our health has started deteriorating, more people are moving towards old habits now. We have been following a simple life since our birth and are healthy. I am happy that people are learning about the benefits of clay pots and cooking in them. To help people live sustainably, I have built this fridge,” he adds.

However, he notes, due to a shortage of potters, he is unable to make more fridges and other products.

“I used to have four people helping me, now only two of them continue, and even they are old. No youngster comes to this field nowadays. They think that those who do pottery are dirty, as our hands get dirty. That’s why we have to limit our production,” he laments.

Mayo Clinic scientists are building an expansive library of DNA blueprints of disease-causing bacterial species. The unique collection of genomic sequences is serving as a reference database to help doctors provide rapid and precise diagnoses and pinpoint targeted treatments to potentially improve patient outcomes.

The vast data set is also being studied by researchers in an effort to develop new individualized treatments to combat bacteria-related diseases.

Bacterial infections were linked to more than 7 million global deaths in 2019. Of those, nearly 1.3 million were the direct result of drug-resistant bacteria, according to the National Institutes of Health.

Assessments of the health impacts of the non-sugar sweetener aspartame are released today by the International Agency for Research on Cancer (IARC) and the World Health Organization (WHO) and the Food and Agriculture Organization (FAO) Joint Expert Committee on Food Additives (JECFA). Citing “limited evidence” for carcinogenicity in humans, IARC classified aspartame as possibly carcinogenic to humans (IARC Group 2B) and JECFA reaffirmed the acceptable daily intake of 40 mg/kg body weight. Aspartame is an artificial (chemical) sweetener widely used in various food and beverage products since the 1980s, including diet drinks, chewing gum, gelatin, ice cream, dairy products such as yogurt, breakfast cereal, toothpaste and medications such as cough drops and chewable vitamins.

https://www.who.int/news/item/14-07-2023-aspartame-h…s-released

An expert panel found a potential association with liver cancer, but too little research exists to assume a causal connection. For now, the WHO left current consumption guidelines unchanged.

Continue reading “WHO expert cancer group states that the sweetener aspartame is a possible carcinogen, but evidence is limited — 6 questions answered” »

(WTAJ) — The U.S. Department of Agriculture’s Food Safety and Inspection Service (FSIS) is issuing a public health alert due to concerns about a raw beef product that may be contaminated.

According to the release, the raw beef item may contain soft, clear plastic. FSIS is issuing this public health alert to ensure that consumers are aware that this product should not be consumed. However, the product is no longer available for purchase.

A new artificial intelligence model finds that X-ray images collected during routine medical care can provide warning signs for diabetes, even in patients who don’t meet the guidelines for elevated risk. The model could help physicians detect the disease earlier and prevent complications, says a multi-institutional team which published the findings in Nature Communications.

Applying the computational method known as deep learning to images and electronic health record data, the researchers developed a model that successfully flagged elevated diabetes risk in a retrospective analysis, often years before patients were diagnosed with the disease. That’s significant, the researchers say, given the prevalence of diabetes in the U.S. has more than doubled over the past 35 years.

Current guidelines suggest screening patients for type 2 diabetes if they are between 35 and 70 years old and have a body mass index (BMI) in the overweight to obese range.

Each cell in the body stores its genetic information in DNA in a stable and protected form that is readily accessible for the cell to carry on its activities. Nevertheless, mutations—changes in genetic information—occur throughout the human genome and can have a powerful influence on human health and evolution.

“Our team is interested in a classical question about mutation—why do mutation rates in the genome vary so tremendously from one DNA location to another? We just do not have a clear understanding of why this occurs,” said Dr. Md. Abul Hassan Samee, assistant professor of integrative physiology at Baylor College of Medicine and corresponding author of the work.

Previous studies have shown that the DNA sequences flanking a mutated position—the sequence context—play a strong role in the mutation rate. “But this explanation still leaves unanswered questions,” Samee said. “For example, one type of mutation occurs frequently in a specific sequence context while a different type of mutation occurs infrequently in that same sequence context. So, we think that a different mechanism could explain how mutation rates vary in the genome. We know that each building block or base that makes up a DNA sequence has its own 3D chemical shape. We proposed, therefore, that there is a connection between DNA shape and mutations rates, and this paper shows that our idea was correct.”

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