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A team of scientists at UC San Francisco reported a way to leverage cancers’ unique metabolic profile to ensure that drugs only target cancer cells: Freethink.

To make matters worse, cancer cells sometimes only die when patients take relatively high doses of a drug. This is because cancer’s metabolism is often greater in cancer cells than in normal cells. For instance, some cancer cells have more MEK enzyme — meaning more cobimetinib is required to stop these cells from replicating. Unfortunately, the doses cancer patients receive often closely approach or even exceed the levels at which the drug causes toxicities in healthy tissues.

Cancer cells hoard iron at a far greater rate than healthy cells, according to previous studies. Although the reason for this remains unclear, the UCSF team realized this could be leveraged to increase the specificity of cancer drugs. If a cancer drug, such as cobimetinib, were only activated in the iron-rich environment of a cancer cell, the drug would be inert when it interacts with healthy cells. It’s something like a two-factor authentication system for cancer drugs.

Continue reading “Is iron the Achilles’ heel for cancer?” »

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Researchers examine how the brain processes language by using intracranial recordings in epilepsy patients during reading tasks, revealing the neural networks responsible for semantic integration and distinguishing between semantic coherence and task-based referentiality. The study pinpoints specific brain regions activated during sentence processing and offers new insights into the spatiotemporal dynamics of language understanding.

Regenerative medicine and tissue engineering strategies have made remarkable progress in remodeling, replacing, and regenerating damaged cardiovascular tissues. The design of three-dimensional (3D) scaffolds with appropriate biochemical and mechanical characteristics is critical for engineering tissue-engineered replacements. The extracellular matrix (ECM) is a dynamic scaffolding structure characterized by tissue-specific biochemical, biophysical, and mechanical properties that modulates cellular behavior and activates highly regulated signaling pathways. In light of technological advancements, biomaterial-based scaffolds have been developed that better mimic physiological ECM properties, provide signaling cues that modulate cellular behavior, and form functional tissues and organs.

Despite many studies showing pigeons are surprisingly smart, from being as good at counting as primates, to being able to identify breast cancer in X-rays, scientists are fighting a losing battle to dispute their widely held reputation as being a bit “dim-witted.”

A new study has pitted the pigeon up against an artificial-intelligence model and found that both bird and computer follow a similar process in order to work out the problem they’re presented with.

“We found really strong evidence that the mechanisms guiding pigeon learning are remarkably similar to the same principles that guide modern machine learning and AI techniques,” said Brandon Turner, lead author of the study and professor of psychology at Ohio State University. “Our findings suggest that in the pigeon, nature may have found a way to make an incredibly efficient learner that has no ability to generalize or extrapolate like humans would.”

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.

Continue reading “Detecting Lung Cancer EARLY With AI: Dr. Lecia Sequist” »

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Continue reading “Telomere Length Test #5 in 2023: Which Dietary Factors Are Significantly Correlated?” »

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.