Lifeboat Foundation

Algae provide a wide range of nutrients that are beneficial for health, including protein, sterols, and vitamins. Numerous health-promoting characteristics, including antioxidant and anti-proliferative actions in relation to algal phenolic and flavonoid concentrations, have been shown by scientific research ^6–9. Produced for both humans and animals, algae and microalgae are often rich sources of fats (especially omega-3 fatty acids and carotenoids), carbohydrates, minerals, enzymes, hormones, and colors ¹⁰.

Health benefits supported by science

Algae have been shown to have multiple health benefits, including the ability to combat microbiological infections, hypertension, obesity, and diabetes, owing to their complex nutritional composition. As a result, the market for nutraceuticals generated from algae is growing quickly in the food supplement industry. A major factor in this has also been the idea of algae prebiotics and how they affect the gut microbiota ¹¹.

Some cancer vaccines, such as mRNA-based vaccines, can be personalized and custom-made for each patient. Personalized vaccines—while promising—also have challenges such as cost and long production times. However, a cancer vaccine that could be used as a potential off-the-shelf treatment for certain patients that share specific mutations is an intriguing possibility. The off-the-shelf vaccine could be manufactured in batches and given to patients with minimal delay. It also would be cheaper to produce.

Colorectal and pancreatic cancers—the second and third leading causes of cancer death, respectively—often have mutations in the KRAS protein. Now, a new vaccine shows encouraging early results as a potential off-the-shelf treatment for patients with pancreatic or colorectal cancer, according to a study co-led by researchers at Memorial Sloan Kettering Cancer Center (MSK).

The vaccine being tested here, ELI-002 2P, is described to enhance “lymph node delivery and immune response using amphiphile modification of G12D and G12R mutant KRAS (mKRAS) peptides (Amph-Peptides-2P) together with CpG oligonucleotide adjuvant (Amph-CpG-7909).”

How can melting permafrost influence climate change? This is what a recent study published in the Proceedings of the National Academy of Sciences hopes to address as a team of researchers from Dartmouth College investigated how permafrost landscapes, which are known for being repositories of organic carbon, could potentially contribute as much carbon to the environment as 35 million cars per year. This study holds the potential to help scientists and policymakers better understand the long-term consequences of climate change across the planet.

“The whole surface of the Earth is in a tug of a war between processes such as hillslopes that smooth the landscape and forces like rivers that carve them up,” said Dr. Joanmarie Del Vecchio, who is a Neukom Postdoctoral Fellow at Dartmouth and lead author of the study.

For the study, the researchers analyzed satellite data on more than 69,000 watersheds between just north of the Tropic of Cancer to the North Pole. For context, the Tropic of Cancer runs through central Mexico and northern Africa. The goal of the study was to ascertain the differences in landscapes between regions with and without permafrost. In the end, the researchers found that permafrost landscapes exhibit fewer rivers than landscapes in warmer climates around the world. They then estimated the amount of carbon that was stored within the permafrost that would be released if the permafrost should melt, which they determined would be between 22 billion and 432 billion tons of carbon between now and the end of the century.

Multiple sclerosis (MS) is a neurological disease that usually leads to permanent disabilities. It affects about 2.9 million people worldwide, and about 15,000 in Switzerland alone. One key feature of the disease is that it causes the patient’s own immune system to attack and destroy the myelin sheaths in the central nervous system.

These protective sheaths insulate the nerve fibers, much like the plastic coating around a copper wire. Myelin sheaths ensure that electrical impulses travel quickly and efficiently from nerve cell to nerve cell. If they are damaged or become thinner, this can lead to irreversible visual, speech and coordination disorders.

So far, however, it hasn’t been possible to visualize the myelin sheaths well enough to reliably diagnose and treat MS. Now researchers at ETH Zurich, led by Markus Weiger and Emily Baadsvik from the Institute for Biomedical Engineering, have developed a new magnetic resonance imaging (MRI) procedure that maps the condition of the myelin sheaths more accurately than was previously possible. The researchers successfully tested the procedure on healthy people for the first time.

We’re crawling with microbes, and scientists want to use them to treat disease.

A Learn more on https://scim.ag/5KM

Shots enter early clinical trials for healthy people at high risk for disease.

Multifocal Choroiditis (MFC) patients with inflammatory choroidal neovascularization (iCNV) face challenges in visual and treatment outcomes. A recently published study delves into the effectiveness of Immunomodulatory Therapy (IMT) compared to an approach using steroids as needed, shedding light on visual and treatment outcomes. This study was published in the American Journal of Ophthalmology by Matteo Airaldi and colleagues.

Elon Musk said Neuralink’s first patient was recovering well after being implanted with a product called Telepathy.

Research conducted by a team of scientists from Kaunas universities, Lithuania, revealed that low-frequency ultrasound influences blood parameters. The findings suggest that ultrasound’s effect on haemoglobin can improve oxygen’s transfer from the lungs to bodily tissues.

The research was undertaken on 300 blood samples collected from 42 pulmonary patients. The samples were exposed to six different low-frequency ultrasound modes at the Institute of Mechatronics of Kaunas University of Technology (KTU).

The changes in 20 blood parameters were registered using the blood analysing equipment at the Lithuanian University of Health Sciences (LSMU) laboratories. For the prediction of ultrasound exposure, artificial intelligence, i.e. analysis of variance (ANOVA), non-parametric Kruskal-Wallis method and machine learning algorithms were applied. The calculations were made at the KTU Artificial Intelligence Centre.