Lifeboat Foundation

Dr. Lecia Sequist is the Program Director of the Cancer Early Detection & Diagnostics Clinic at Mass General Cancer Center. For nearly 20 years, she’s specialized in lung cancer.

Observing first-hand the obstacles involved in current screenings of lung cancer, Dr. Sequist made a career switch to the research of early lung cancer detection. This led her to meet MIT professor, Regina Barzilay. Together, they created Sybil – an open-source AI tool that uses pattern recognition to predict one’s risk of lung cancer.

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Fyodor Urnov, PhD, is a pioneer in the field of genome editing and one of the scientists most invested in expanding the availability and utility of CRISPR-based therapies to the broadest possible population. He envisions a world in which genome editing can treat the nearly 400 million people who are suffering from one of the 7,000 diseases brought on by gene mutations.

USA: Medical researchers at the University of Minnesota have developed an experimental method for treating hard-to-treat blood cancers using natural killer cells pre-treated with nicotinamide, a compound commonly known as vitamin B3. These natural killer cells are part of the body’s immune system and have the unique ability to target and destroy malignant cells.

A recent study, published in Science Translational Medicine by Frank Cichocki and colleagues, highlights the potential of this approach in treating relapsed or refractory leukemias and lymphomas, where traditional treatments have often failed. The study involved boosting the effectiveness of natural killer cells through pre-treatment with nicotinamide and interleukin-15 (IL-15).

Last month, OM1, a leading real-world data and tech company focused on chronic conditions, announced the launch of its Parkinson’s disease (PD) premium dataset and the enhancement of its Mental Health & Neuroscience Real-World Data Network.

The dataset includes more than 7,000 patients prospectively followed by neurologists in hundreds of clinics across all 50 states. OM1 enriches the data by extracting relevant information from treating clinician notes using its AI and language modeling, and data points include key symptoms, disease severity, treatments, longitudinal outcomes and clinical response. In addition to the dataset, data from an additional 700,000 PD patients are available in the OM1 Real-World Data Cloud for modeling health economics outcomes, patient recruitment for clinical trials, prescriber trends and other research needs.

The dataset combines real-world data sources, such as electronic medical records (EMR), medical and pharmacy claims, mortality data and social determinants of health (SDoH), to provide deeper insights into Parkinson’s disease patient journeys. The data can be leveraged to accelerate medical research and to support approvals and reimbursement, reducing the time to market and improving existing therapies.

We know that migraines, which are recurrent and sometimes debilitating headaches, have some genetic basis, but the link with our DNA isn’t entirely clear. Newly identified genetic variants could help in developing treatments.

By Chen Ly

The company provided hundreds of virtual reality headsets to 30 healthcare centers across Israel to help patients struggling with PTSD, anxiety and stress.

A type of cell once only thought to exist in the gills of freshwater fish and the skin of frogs, but recently found in humans lungs, has given scientists new insight into the underlying cause of cystic fibrosis (CF).

CF is a progressive, genetic disease that impacts the lungs and other organs, sometimes causing severe symptoms that can be life-threatening.

The disease is marked by the absence or mutation of a protein in the lungs called the cystic fibrosis transmembrane conductance regulator (CFTR).

Quantum computers of the future hold promise in solving all sorts of problems. For example, they could lead to more sustainable materials and new medicines, and even crack the hardest problems in fundamental physics. But compared to the classical computers in use today, rudimentary quantum computers are more prone to errors. Wouldn’t it be nice if researchers could just take out a special quantum eraser and get rid of the mistakes?

Reporting in the journal Nature, a group of researchers led by Caltech is among the first to demonstrate a type of quantum eraser. The physicists show that they can pinpoint and correct for mistakes in quantum computing systems known as “erasure” errors.

“It’s normally very hard to detect errors in quantum computers, because just the act of looking for errors causes more to occur,” says Adam Shaw, co-lead author of the new study and a graduate student in the laboratory of Manuel Endres, a professor of physics at Caltech. “But we show that with some careful control, we can precisely locate and erase certain errors without consequence, which is where the name erasure comes from.”