Lifeboat Foundation

Abstract of full article w/ downloadable pdf:

Fluorescence-guided intervention can bolster standard therapies by detecting and treating microscopic tumors before lethal recurrence. Tremendous progress in photoimmunotherapy and nanotechnology has been made to treat metastasis. However, many are lost in translation due to heterogeneous treatment effects. Here, we integrate three technological advances in targeted photo-activable multi-agent liposome (TPMAL), fluorescence-guided intervention, and laser endoscopy (ML7710) to improve photoimmunotherapy. TPMAL consists of a nanoliposome chemotherapy labeled with fluorophores for tracking and photosensitizer immunoconjugates for photoimmunotherapy… More.

Fluorescence-guided photoimmunotherapy using nanotechnology and ML7710 reduces heterogeneous therapy effects and tumor metastasis.

Chemotherapy as a treatment for cancer is one of the major medical success stories of the 20th century, but it’s far from perfect. Anyone who has been through chemotherapy or who has had a friend or loved one go through it will be familiar with its many side effects: hair loss, nausea, weakened immune system, and even infertility and nerve damage.

This is because chemotherapy drugs are toxic. They’re meant to kill cancer cells by poisoning them, but since cancer cells derive from healthy cells and are substantially similar to them, it is difficult to create a drug that kills them without also harming healthy tissue.

But now a pair of Caltech research teams have created an entirely new kind of drug delivery system, one that they say may finally give doctors the ability to treat cancer in a more targeted way. The system employs drugs that are activated by ultrasound —and only right where they are needed in the body.

NIH-funded study suggests need to reevaluate opioid addiction treatment recommendations in the era of fentanyl.

Individuals with opioid use disorder who were prescribed a lower buprenorphine dose were 20% more likely to discontinue treatment than those on a higher dose, according to a study of patients prescribed buprenorphine in Rhode Island from 2016 to 2020, as fentanyl became widely available. The study, published today in JAMA Network Open, was supported by the National Institute on Drug Abuse (NIDA), part of the National Institutes of Health, and conducted by researchers at Brown University, Providence, Rhode Island; NIDA and the Rhode Island Department of Health.

Among patients newly initiating buprenorphine treatment for opioid use disorder, 59% of those prescribed the target daily dose of 16 milligrams recommended by the U.S. Food and Drug Administration and 53% of those prescribed the higher 24 mg daily dose discontinued treatment within 180 days. A statistical analysis that allowed for multivariable comparison of these two dose groups showed patients prescribed the recommended dose (16 mg) were significantly more likely to discontinue treatment over 180 days compared to those prescribed 24 mg.

Smaller cells occur in larger numbers in the human body, and cells of different size classes contribute equally to our overall mass.

At Science4Seniors we strive to take rigorous research published in Scientific Journals and make the core information accessible to all. If you want to support us please like and follow us on Facebook. In recent years, the intersection of medical science and technology has unfurled fascinating possibilities, especially in diagnostics. Among the many marvels we’ve been introduced to, medical artificial intelligence (AI) is reshaping how we detect and diagnose a plethora of health conditions. One area that stands out significantly in this transformation is the potential of AI in the analysis of retinal images.

In response to the increasing demand for medical services amid labor shortages and a rapidly aging population, Shanghai-based Fourier Intelligence is developing an innovative humanoid robot. The GR-1, as it is called, promises to transform healthcare facilities and offer vital assistance to the elderly.

Like many countries, China is confronting the challenge of an aging population. The number of individuals aged 60 and over is projected to rise from 280 million to over 400 million by 2035, according to estimates from the country’s National Health Commission. That’s more than the entire population of the United States projected for that year.

Continue reading “World’s first mass-produced humanoid robot wants to solve China’s aging population problem” »

Elon Musk’s neurotech startup announced that it is now seeking patients with paralysis to test a brain-computer interface.

New research indicates that butterflies and moths share “blocks” of DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

Numerous natural language processing (NLP) applications have benefited greatly from using large language models (LLMs). While LLMs have improved in performance and gained additional capabilities due to being scaled, they still have a problem with “hallucinating” or producing information inconsistent with the real-world facts detected during pre-training. This represents a significant barrier to adoption for high-stakes applications (such as those found in clinical and legal settings), where the generation of trustworthy text is essential.

The maximum likelihood language modeling target, which seeks to minimize the forward KL divergence between the data and model distributions, may be to blame for LMs’ hallucinations. However, this is far from certain. The LM may assign a non-zero probability to phrases that are not fully consistent with the knowledge encoded in the training data if this goal is pursued.

From the perspective of the interpretability of the model, studies have shown that the earlier layers of transformer LMs encode “lower level” information (such as part-of-speech tags). In contrast, the later levels encode more “semantic” information.