Lifeboat Foundation

Separating molecules is critical to producing many essential products. For example, in petroleum refining, the hydrocarbons—chemical compounds composed of hydrogens and carbons—in crude oil are separated into gasoline, diesel and lubricants by sorting them based on their molecular size, shape and weight. In the pharmaceutical industry, the active ingredients in medications are purified by separating drug molecules from the enzymes, solutions and other components used to make them.

These separation processes take a substantial amount of energy, accounting for roughly half of U.S. industrial energy use. Traditionally, molecular separations have relied on methods that require intensive heating and cooling that make them very energy inefficient.

We are chemical and biological engineers. In our newly published research in Science, we designed a new type of membrane with nanopores that can quickly and precisely separate a diverse range of molecules under harsh industrial conditions.

Spina bifida is the most common birth defect of the central nervous system and the second most common of all structural birth defects. To learn more about it, From the Labs sat with Dr. Richard H. Finnell, whose lab at Baylor College of Medicine focuses on discovering the role of folic acid in the prevention of birth defects and in identifying the genes that determine susceptibility to human neural tube defects such as spina bifida.

FTL: What is spina bifida?

RHF: Spina bifida is a condition that occurs during very early development affecting the neural tube, which will give rise to the spinal cord and brain. It can be diagnosed during pregnancy or after the baby is born. Typically, the neural tube closes by the 28th day after conception. In babies with spina bifida, a portion of the neural tube doesn’t close properly, resulting in a malformed spinal cord and problems in the bones of the spine. The neural tube exposed to amniotic fluid results in bladder and bowel dysfunction and in orthopedic problems that limit the child’s ability to walk.

In a breakthrough in cancer therapeutics, a team of researchers at the Magzoub Biophysics Lab at NYU Abu Dhabi (NYUAD) has made a significant advance in light-based therapies—biocompatible and biodegradable tumor-targeting nanospheres that combine tumor detection and monitoring with potent, light-triggered cancer therapy to dramatically increase the efficacy of existing light-based approaches.

Non-invasive, light-based therapies, photodynamic therapy (PDT) and photothermal therapy (PTT) have the potential to be safe and effective alternatives to conventional cancer treatments, which are beset by a number of issues, including a range of side-effects and post-treatment complications.

However, to date, the development of effective light-based technologies for cancer has been hindered by poor solubility, low stability, and lack of tumor specificity, among other challenges. Nanocarriers designed to deliver PDT and PTT more effectively have also proven to have significant limitations.

Sarilumab„ allowed for more-rapid tapering of prednisone in a randomized trial.

When patients with polymyalgia rheumatica (PMR) have recurrent symptoms repeatedly during tapering of steroids, rheumatologists sometimes add agents such as methotrexate to decrease cumulative steroid exposure. Sarilumab (Kevzara; an interleukin-6 receptor antagonist) recently was FDA-approved in the U.S. for this purpose, based on results of this clinical trial.

Researchers identified 118 patients with PMR who had received at least 8 weeks of prednisone (≥10 mg daily) during their treatment course and had at least one symptom flare while taking ≥7.5 mg daily. Patients were randomized to receive either sarilumab, injected twice monthly for 1 year, while tapering prednisone over 14 weeks, or placebo, while tapering prednisone over 1 year. The protocol allowed for steroid “rescue” therapy if symptoms flared.

Sustained remission between weeks 12 and 52 occurred significantly more often in the sarilumab group than in the placebo group (28% vs. 10%). At 52 weeks, patients in the sarilumab group were significantly more likely to be asymptomatic and to have received no rescue therapy (45% vs. 14%). Median cumulative prednisone exposure was much lower in the sarilumab group (777 mg vs. 2044 mg). Neutropenia, diarrhea, and arthralgia occurred more commonly with sarilumab than with placebo. No deaths occurred during the trial.

Continue reading “A Biologic Agent for Treating Patients with Polymyalgia Rheumatica” »

Scholars’ understanding of the Dead Sea Scrolls may be enhanced by an unusual source: the DNA of the animals they’re printed on.

Researchers catalogue more than 3,000 different types of cell in our most complex organ.

I dont really care where it comes from but we need Crispr tec to be where any alteration we do want causes Zero un intended alterations any where else 100% of the time, aim for by 2030–2035 window.

A diverse set of species, from snails to algae to amoebas, make programmable DNA-cutting enzymes called Fanzors—and a new study from scientists at MIT’s McGovern Institute for Brain Research has identified thousands of them. Fanzors are RNA-guided enzymes that can be programmed to cut DNA at specific sites, much like the bacterial enzymes that power the widely used gene-editing system known as CRISPR. The newly recognized diversity of natural Fanzor enzymes, reported Sept. 27 in the journal Science Advances, gives scientists an extensive set of programmable enzymes that might be adapted into new tools for research or medicine.

“RNA-guided biology is what lets you make programmable tools that are really easy to use. So the more we can find, the better,” says McGovern Fellow Omar Abudayyeh, who led the research with McGovern Fellow Jonathan Gootenberg.

Continue reading “Thousands of programmable DNA-cutters found in algae, snails, and other organisms” »

Researchers at the Department of Energy’s SLAC National Accelerator Laboratory have demonstrated a new approach to peer deeper into the complex behavior of materials. The team harnessed the power of machine learning to interpret coherent excitations, collective swinging of atomic spins within a system.

This groundbreaking research, published recently in Nature Communications, could make experiments more efficient, providing real-time guidance to researchers during data collection, and is part of a project led by Howard University including researchers at SLAC and Northeastern University to use machine learning to accelerate research in materials.

The team created this new data-driven tool using “neural implicit representations,” a machine learning development used in computer vision and across different scientific fields such as medical imaging, particle physics and cryo-electron microscopy. This tool can swiftly and accurately derive unknown parameters from experimental data, automating a procedure that, until now, required significant human intervention.

NIH-supported research finds key differences between children & adults with COVID-19.