Lifeboat Foundation

An artificial intelligence (AI)-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy, according to a report by scientists from University of Utah Health and Fabric Genomics, collaborators on a study led by Rady Children’s Hospital in San Diego. The benchmark finding, published in Genomic Medicine, foreshadows the next phase of medicine, where technology helps clinicians quickly determine the root cause of disease so they can give patients the right treatment sooner.

“This study is an exciting milestone demonstrating how rapid insights from AI-powered decision support technologies have the potential to significantly improve patient care,” says Mark Yandell, Ph.D., co-corresponding author on the paper. Yandell is a professor of human genetics and Edna Benning Presidential Endowed Chair at U of U Health, and a founding scientific advisor to Fabric.

Worldwide, about seven million infants are born with serious genetic disorders each year. For these children, life usually begins in intensive care. A handful of NICUs in the U.S., including at U of U Health, are now searching for genetic causes of disease by reading, or sequencing, the three billion DNA letters that make up the human genome. While it takes hours to sequence the whole genome, it can take days or weeks of computational and manual analysis to diagnose the illness.

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More AI in the exam room means doctors can spend more time actually talking to patients.

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

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 proteomics^8,9. 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 described^4,5. Urine samples were concentrated to a maximum of 200× to achieve final concentrations of urine protein between 20 and 80 g/L^4,5. The FLC assay (Freelite™, The Binding Site Ltd.) was performed on a Siemens BNII nephelometer¹⁰, and an abnormal FLC result was defined as an abnormal FLC κ/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 κ 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.

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.

It may be more contagious than Delta, but there is no evidence yet that it causes worse illness, experts say.

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].

Continue reading “Protein Glycation in Diabetes as Determined” »

Mini mass spectrometry can lead to essentially a real life tricorder #startrek

Mass Spectrometry.

Mini mass specs are still looking for an audience.

Continue reading “Mini mass specs are still looking for an audience” »

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.