Lifeboat Foundation: Safeguarding Humanity
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Circa 2019 😀

Because they can process massive amounts of data, computers can perform analytical tasks that are beyond human capability. Google, for instance, is using its computing power to develop AI algorithms that construct two-dimensional CT images of lungs into a three-dimensional lung and look at the entire structure to determine whether cancer is present. Radiologists, in contrast, have to look at these images individually and attempt to reconstruct them in their heads. Another Google algorithm can do something radiologists cannot do at all: determine patients’ risk of cardiovascular disease by looking at a scan of their retinas, picking up on subtle changes related to blood pressure, cholesterol, smoking history and aging. “There’s potential signal there beyond what was known before,” says Google product manager Daniel Tse.

The Black Box Problem

AI programs could end up revealing entirely new links between biological features and patient outcomes. A 2019 paper in JAMA Network Open described a deep-learning algorithm trained on more than 85,000 chest x-rays from people enrolled in two large clinical trials that had tracked them for more than 12 years. The algorithm scored each patient’s risk of dying during this period. The researchers found that 53 percent of the people the AI put into a high-risk category died within 12 years, as opposed to 4 percent in the low-risk category. The algorithm did not have information on who died or on the cause of death. The lead investigator, radiologist Michael Lu of Massachusetts General Hospital, says that the algorithm could be a helpful tool for assessing patient health if combined with a physician’s assessment and other data such as genetics.

Continue reading “Rise of Robot Radiologists” | >

The Mayo Foundation Institutional Review Board (IRB) approved the study. All patients gave written informed consent to have their medical records reviewed and samples analyzed according to IRB requirements and federal regulations. Patients were eligible for this retrospective study if they: were diagnosed with AL amyloidosis between January 2000 and May 2015; were classified as amyloidosis complete hematologic response by immunofixation electrophoresis (IFE), serum free light chain (FLC) by consensus criteria;6,7 had a negative bone marrow by six-color flow cytometry; and had both a stored research sample prior to starting a line of therapy and a repeat sample while in complete hematologic response. The diagnosis of amyloidosis was made by Congo red with green birefringence under polarized light; the typing of the amyloid was with immunohistochemical stains or proteomics8,9. Supplementary Figure 1 is a consort diagram illustrating patient selection. Median time from institution of therapy to complete response (CR) sample was 18 months (interquartile range 9.1, 20 months).

The serum IFE (SIFE), urine IFE (UIFE), FLC, and bone marrow measurements were done as part of routine clinical practice as previously described4,5. Urine samples were concentrated to a maximum of 200× to achieve final concentrations of urine protein between 20 and 80 g/L4,5. The FLC assay (Freeliteℱ, The Binding Site Ltd.) was performed on a Siemens BNII nephelometer10, and an abnormal FLC result was defined as an abnormal FLC Îș/λ ratio. Bone marrow clonality was determined by six-color flow cytometry11. This method has sensitivity of ~10−4 to 10−5.

For MASS-FIX, immunoglobulins were enriched from serum using camelid-derived nanobodies directed against the heavy-chain constant domains of IgG, IgA, and IgM or the light-chain constant domains of Îș and λ (Thermo Fisher Scientific)4,5. The +1 and +2 charge states of the light chains and heavy chains were measured by configuring the mass spectrometer to analyze ions between an m/z of 9000–32,000 Da.

Continue reading “Blood mass spectrometry detects residual disease better than standard techniques in light-chain amyloidosis” | >

ABINGDON, England — Harnessing fusion energy into something commercially viable — and maybe, ultimately, a clean source of power that replaces fossil fuels for centuries to come — has long been considered by some as the ultimate moonshot.

But investor interest in fusion energy continues to slowly rise, and the number of startups in the field is multiplying, with an estimated 1,100 people in several countries making their living at these firms. An industry is taking shape, with a growing network of companies that supply highly specialized equipment, like the components of the powerful magnets that fusion devices require.

The British government even recently saw the need to issue regulations for fusion energy — a kind of milestone for a burgeoning industry.

Continue reading “Nuclear fusion edges toward the mainstream” | >

Glucose monitoring with mass spectrometry circa 2013.

Diabetes is a common endocrine disorder characterized by hyperglycemia leading to nonenzymatic glycation of proteins, responsible for chronic complications. The development of mass spectrometric techniques able to give highly specific and reliable results in proteome field is of wide interest for physicians, giving them new tools to monitor the disease progression and the possible complications related to diabetes, as well as the effectiveness of therapeutic treatments. This paper reports and discusses some of the data pertaining protein glycation in diabetic subjects obtained by matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). The preliminary studies carried out by in vitro protein glycation experiments show clear differences in molecular weight of glycated and unglycated proteins. Then, the attention was focused on plasma proteins human serum albumin (HSA) and immunoglobulin G (IgG). Enzymatic degradation products of in vitro glycated HSA were studied in order to simulate the in vivo enzymatic digestion of glycated species by the immunological system leading to the highly reactive advanced glycation end-products (AGEs) peptides. Further studies led to the evaluation of glycated Apo A-I and glycated haemoglobin levels. A different MALDI approach was employed for the identification of markers of disease in urine samples of healthy, diabetic, nephropathic, and diabetic-nephropathic subjects.

Diabetes is usually considered as a disease related to glucose dysmetabolism. In particular, type 1 diabetes is a chronic disease related to metabolism of carbohydrates, fats, and proteins, caused by the lack of insulin. It results from the marked and progressive inability of the pancreas to secrete insulin, due to autoimmune destruction of the beta cells. On the other hand, type 2 diabetes is caused by islet beta cells being unable to secrete adequate insulin in response to varying degrees of overnutrition, inactivity, obesity, and insulin resistance. Nowadays, the burden of diabetes is enormous, due to its increasing global prevalence and the occurrence of chronic complications affecting many tissues (retinopathy, nephropathy, neuropathy, and cardiovascular disease) reflecting in high direct and indirect costs [1].

This view may be seen somehow reductive, considering that the side effects of the previous mechanisms are at systemic level, and, taking into account the high complexity of the biological environment, it necessarily reflects on a high number of different pathological pathways, catalyzed by the glucose dysmetabolism. In this context, considering the Maillard reaction pattern [2], proteins seem to be at first sight the target of the glucose molecules circulating at high level in diabetes, and only some papers gave contradictory results about the reactivity of sugar with respect to DNA [3, 4].

Continue reading “Protein Glycation in Diabetes as Determined” | >

On October 1 2021, the joint European Space Agency (ESA) and Japan Aerospace Exploration Agency (JAXA) BepiColombo spacecraft successfully performed its first flyby of the solar system’s innermost planet, Mercury. The flyby is the first in a set of six such events BepiColombo will complete before entering orbit around Mercury in late 2025.

Following the flyby, initial science returns from different instruments onboard BepiColombo revealed interesting details about the environment surrounding Mercury, as well as details on the planet itself.

Continue reading “BepiColombo completes first Mercury flyby, science provides insight into planet’s unique environment” | >

While analyzing some of the world’s oldest colored gemstones, researchers from the University of Waterloo discovered carbon residue that was once ancient life, encased in a 2.5 billion-year-old ruby.

The research team, led by Chris Yakymchuk, professor of Earth and Environmental Sciences at Waterloo, set out to study the geology of rubies to better understand the conditions necessary for ruby formation. During this research in Greenland, which contains the oldest known deposits of rubies in the world, the team found a ruby sample that contained graphite, a mineral made of pure carbon. Analysis of this carbon indicates that it is a remnant of early life.

“The graphite inside this ruby is really unique. It’s the first time we’ve seen evidence of ancient life in ruby-bearing rocks,” says Yakymchuk. “The presence of graphite also gives us more clues to determine how rubies formed at this location, something that is impossible to do directly based on a ruby’s color and chemical composition.”

Continue reading “Ancient Traces of Life Discovered Encased in a 2.5 Billion-Year-Old Ruby” | >

Estimate measures information encoded in particles, opens door to practical experiments.

Researchers have long suspected a connection between information and the physical universe, with various paradoxes and thought experiments used to explore how or why information could be encoded in physical matter. The digital age propelled this field of study, suggesting that solving these research questions could have tangible applications across multiple branches of physics and computing.

In AIP Advances, from AIP Publishing, a University of Portsmouth researcher attempts to shed light on exactly how much of this information is out there and presents a numerical estimate for the amount of encoded information in all the visible matter in the universe — approximately 6 times 10 to the power of 80 bits of information. While not the first estimate of its kind, this study’s approach relies on information theory.

Continue reading “Physicist Quantifies Amount of Information in Entire Visible Universe” | >

I’m convinced a lot of diseases, MS, parkinsons, alzheimers, most cancers, are the result of bacterial or viral infections.

Building on a growing body of evidence linking viral infections with neurodegenerative disease, a new study published in Nature Communications has demonstrated how certain molecules on the surfaces of viruses can promote the aggregation of toxic proteins associated with diseases such as Alzheimer’s and Parkinson’s.

The idea that microbial infections can trigger neurodegenerative disease is not new. As far back as the 1950s scientists have been postulating ways an acute viral infection can lead to progressive neurological problems years, or even decades, later.

While evidence for this association is certainly growing, the mechanisms by which viral threats can influence the progression of brain diseases are still resolutely hypothetical. A common hypothesis speculates some viral infections may trigger abnormal immune responses that subsequently linger for years, ultimately generating neurological damage associated with some brain diseases.

Continue reading “New evidence shows how viral infections could promote Alzheimer’s” | >