Lifeboat Foundation

Google DeepMind researchers have finally found a way to make life coaching even worse: infuse it with generative AI.

According to internal documents obtained by The New York Times reports, Google and the Google-owned DeepMind AI lab are working with “generative AI to perform at least 21 different types of personal and professional tasks.” And among those tasks, apparently, is an effort to use generative AI to build a “life advice” tool. You know, because an inhuman AI model knows everything there is to know about navigating the complexities of mortal human existence.

As the NYT points out, the news of the effort notably comes months after AI safety experts at Google said, back in just December, that users of AI systems could suffer “diminished health and well-being” and a “loss of agency” as the result of taking AI-spun life advice. The Google chatbot Bard, meanwhile, is barred from providing legal, financial, or medical advice to its users.

Recent advancements in deep learning have significantly impacted computational imaging, microscopy, and holography-related fields. These technologies have applications in diverse areas, such as biomedical imaging, sensing, diagnostics, and 3D displays. Deep learning models have demonstrated remarkable flexibility and effectiveness in tasks like image translation, enhancement, super-resolution, denoising, and virtual staining. They have been successfully applied across various imaging modalities, including bright-field and fluorescence microscopy; deep learning’s integration is reshaping our understanding and capabilities in visualizing the intricate world at microscopic scales.

In computational imaging, prevailing techniques predominantly employ supervised learning models, necessitating substantial datasets with annotations or ground-truth experimental images. These models often rely on labeled training data acquired through various methods, such as classical algorithms or registered image pairs from different imaging modalities. However, these approaches have limitations, including the laborious acquisition, alignment, and preprocessing of training images and the potential introduction of inference bias. Despite efforts to address these challenges through unsupervised and self-supervised learning, the dependence on experimental measurements or sample labels persists. While some attempts have used labeled simulated data for training, accurately representing experimental sample distributions remains complex and requires prior knowledge of sample features and imaging setups.

To address these inherent issues, researchers from the UCLA Samueli School of Engineering introduced an innovative approach named GedankenNet, which, on the other hand, presents a revolutionary self-supervised learning framework. This approach eliminates the need for labeled or experimental training data and any resemblance to real-world samples. By training based on physics consistency and artificial random images, GedankenNet overcomes the challenges posed by existing methods. It establishes a new paradigm in hologram reconstruction, offering a promising solution to the limitations of supervised learning approaches commonly utilized in various microscopy, holography, and computational imaging tasks.

Two molecular languages at the origin of life have been successfully recreated and mathematically validated, thanks to pioneering work by Canadian scientists at Université de Montréal.

The study, “Programming chemical communication: allostery vs. multivalent mechanism,” published August 15, 2023 in the Journal of the American Chemical Society, opens new doors for the development of nanotechnologies with applications ranging from biosensing, drug delivery and molecular imaging.

Living organisms are made up of billions of nanomachines and nanostructures that communicate to create higher-order entities able to do many essential things, such as moving, thinking, surviving and reproducing.

In a recent pre-print study posted to the medRxiv* server, researchers conducted a comprehensive genome-wide association study (GWAS) to elucidate the genetic architecture of circulating retinol, identify its potential causal relationships with various clinical phenotypes, and evaluate its therapeutic or nutritional implications.

Study: Genetic influences on circulating retinol and its relationship to human health. Image Credit: SciePro/Shutterstock.com.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

What if we could identify the earliest warning signs of cardiovascular disease from a simple saliva sample? Scientists think they have found a way to do so. Gum inflammation leads to periodontitis, which is linked with cardiovascular disease.

The team used a simple oral rinse to see if levels of white blood cells —an indicator of gum inflammation —in the saliva of healthy adults could be linked to warning signs for cardiovascular disease. they found that high levels correlated with compromised flow-mediated dilation, an early indicator of poor arterial health.

“Even in young healthy adults, low levels of oral inflammatory load may have an impact on cardiovascular health—one of the leading causes of death in North America,” said Dr. Trevor King of Mount Royal University, corresponding author of the study published in Frontiers in Oral Health.

Glioblastoma is a fast-growing and aggressive brain tumor. As one of the most common malignant brain tumors, life expectancy after diagnosis is between 14 and 16 months. Roughly 1% of patients survive more than ten years with the longest patients living over 20 years. Symptoms include headaches, double vision, vomiting, loss of appetite, changes in mood and personality, inability to accurately think and learn, seizures, and difficulty speaking. Unfortunately, there is no cure, and treatment options include radiation and chemotherapy with limited efficacy. Glioblastoma is difficult to treat due to its location in the brain, its resistance to common treatment, the brains limited ability to heal itself, disrupted blood supply, blood vessel leakage, seizures, and neurotoxicity from treatments. Due to limited treatment and the life expectancy of this devastating disease, researchers at the SALK Institute in La Jolla, California have set out to find better ways to treat glioblastoma and prolong survival in patients.

Immune checkpoint inhibitors (ICIs) are a form of immunotherapy that block receptors on immune cells which activate them to kill tumor cells. The ICI using by the SALK group is known as anti-CTLA-4, which binds to the CTLA-4 protein on the T immune cells responsible for killing infected cells. This therapy was generated by Dr. James Allison at the MD Anderson Comprehensive Cancer Center in Houston, Texas. For his work, he was awarded the Nobel Prize in Physiology or Medicine in 2018. While this therapy proved effective in other cancers such as melanoma, it was unclear its effect in glioblastoma. The researchers at SALK recently published their findings on the effect of anti-CTLA-4 on glioblastoma.

The study published in Immunity by Dr. Susan Kaech and colleagues at SALK demonstrated prolonged survival of mice with glioblastoma after treatment with anti-CTLA-4. They also discovered that the treatment was largely dependent on CD4+ T cells, which aid in activating other cells, and not CD8+ T cells, which directly kill the tumor. More specifically, CD4+ T cells were found to infiltrate the brain and trigger other immune cells, like microglia to destroy cancerous cells. In Kaech’s work, the lab significantly shrunk the glioblastoma in mice and in some cases completely eradicated it.

Benjamin Oakes’ Scribe Therapeutics is developing specialized Crispr proteins to tackle a wide range of diseases–and it’s garnered deals with Big Pharma potentially worth over $4 billion.

Pigs might help solve the organ transplant crisis if researchers can make the process safe enough. Preventing rejection in brain-dead subjects is a step toward that goal.

GTB-3550 is the company’s first TriKE® product candidate that was evaluated in Phase 1 clinical trials for the treatment of acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and other CD33+ hematopoietic malignancies. Phase 1 clinical trials were shown to be both safe and well-tolerated, as well as proving the molecule’s clinical concept and providing a framework for future product candidates.

GTB-3650 is a second-generation protein developed to treat AML and MDS. It has replaced GTB-3550 and utilizes camelid nanobody technology. GTB3650 has successfully completed pre-clinical trials and is in the good manufacturing process (GMP) stage, which is usually the last developmental milestone before progressing into phase 1 clinical trials.