Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biotech/medical – Page 1,362

Recently Discovered Molecule Kills Hard-To-Treat Cancers

A new molecule created by a researcher at the University of Texas at Dallas kills a variety of difficult-to-treat cancers, including triple-negative breast cancer, by taking advantage of a weakness in cells that was not previously targeted by existing drugs.

The research, which was conducted using isolated cells, human cancer tissue, and mouse-grown human cancers, was recently published in Nature Cancer.

A co-corresponding author of the study and an associate professor of chemistry and biochemistry in the School of Natural Sciences and Mathematics at the University of Texas at Dallas, Dr. Jung-Mo Ahn has dedicated more than ten years of his career to developing small molecules that target protein-protein interactions in cells. He previously created potential therapeutic candidate compounds for treatment-resistant prostate cancer and breast cancer using a method called structure-based rational drug design.

Highly Sensitive, Mass Producible Organic Photodetectors for Medical Sensors, Fingerprint Recognition

New green-light absorbing photodetectors could be useful for medical sensors, fingerprint recognition, and more.

New green-light absorbing transparent organic photodetectors that are highly sensitive and compatible with CMOS fabrication methods have been developed and demonstrated by researchers. Incorporating these new photodetectors into organic-silicon hybrid image sensors could be useful for many applications. These include light-based heart-rate monitoring, fingerprint recognition, and devices that detect the presence of nearby objects.

Whether used in scientific cameras or smartphones, most of today’s imaging sensors are based on CMOS technology and inorganic photodetectors that convert light signals into electric signals. Although photodetectors made from organic materials are attracting attention because they can help boost sensitivity, for example, it has thus far proven difficult to fabricate high-performance organic photodetectors.

Shrouded in Mystery: Scientists Finally Discover the Origin of Chromatin

Analysis of the genome and proteome shows that eukaryotic evolution gave rise to the regulatory function of chromatin.

Two meters 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).

Artificial Intelligence Model Can Detect Parkinson’s From Breathing Patterns

Summary: A newly developed artificial intelligence model can detect Parkinson’s disease by reading a person’s breathing patterns. The algorithm can also discern the severity of Parkinson’s disease and track progression over time.

Source: MIT

Parkinson’s disease is notoriously difficult to diagnose as it relies primarily on the appearance of motor symptoms such as tremors, stiffness, and slowness, but these symptoms often appear several years after the disease onset.

Protein-Designing AI Opens Door to Medicines Humans Couldn’t Dream Up

A new study in Science overthrew the whole gamebook. Led by Dr. David Baker at the University of Washington, a team tapped into an AI’s “imagination” to dream up a myriad of functional sites from scratch. It’s a machine mind’s “creativity” at its best—a deep learning algorithm that predicts the general area of a protein’s functional site, but then further sculpts the structure.

As a reality check, the team used the new software to generate drugs that battle cancer and design vaccines against common, if sometimes deadly, viruses. In one case, the digital mind came up with a solution that, when tested in isolated cells, was a perfect match for an existing antibody against a common virus. In other words, the algorithm “imagined” a hotspot from a viral protein, making it vulnerable as a target to design new treatments.

The algorithm is deep learning’s first foray into building proteins around their functions, opening a door to treatments that were previously unimaginable. But the software isn’t limited to natural protein hotspots. “The proteins we find in nature are amazing molecules, but designed proteins can do so much more,” said Baker in a press release. The algorithm is “doing things that none of us thought it would be capable of.”

Neurological and psychiatric risk trajectories after SARS-CoV-2 infection: an analysis of 2-year retrospective cohort studies including 1 284 437 patients

This analysis of 2-year retrospective cohort studies of individuals diagnosed with COVID-19 showed that the increased incidence of mood and anxiety disorders was transient, with no overall excess of these diagnoses compared with other respiratory infections. In contrast, the increased risk of psychotic disorder, cognitive deficit, dementia, and epilepsy or seizures persisted throughout. The differing trajectories suggest a different pathogenesis for these outcomes. Children have a more benign overall profile of psychiatric risk than do adults and older adults, but their sustained higher risk of some diagnoses is of concern. The fact that neurological and psychiatric outcomes were similar during the delta and omicron waves indicates that the burden on the health-care system might continue even with variants that are less severe in other respects. Our findings are relevant to understanding individual-level and population-level risks of neurological and psychiatric disorders after SARS-CoV-2 infection and can help inform our responses to them.

National institute for health and care research oxford health biomedical research centre, the wolfson foundation, and MQ mental health research.

Exposure to phenytoin associates with a lower risk of post-COVID cognitive deficits: a cohort study

A proportion of patients experience long-lasting symptoms in the weeks and months after a diagnosis of COVID-19. 1–3 Of those symptoms, cognitive impairment (also referred to as ‘brain fog’) is particularly worrisome: it is one of the most common, 4, 5 can affect those with even relatively mild acute COVID-19 illness 1, 5 and results in the inability to work for many affected patients. 3 While emerging research is starting to characterize the clinical presentation of post-COVID cognitive deficits, 6 its pathogenesis remains elusive. Identifying therapeutic targets is critical to reducing the burden of this COVID-19 complication.

Endotheliopathy has been hypothesized as one potential mechanism underlying post-COVID cognitive deficits. 7 According to recent research, microvascular brain pathology following COVID-19 can be caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease Mpro cleaving nuclear factor-κB essential modulator thus inducing the death of brain endothelial cells. 8 The same study showed that pharmacologically inhibiting receptor-interacting protein kinase (RIPK) signaling prevents the Mpro-induced microvascular pathology. 8

This research leads to the following hypothesis: exposure to a pharmacological inhibitor of RIPK signaling at the time of COVID-19 infection reduces the risk of post-COVID cognitive deficits. In this study, we tested this hypothesis using a retrospective cohort study based on electronic health records (EHRs) data. While many pharmacological agents inhibit RIPK signaling, 9 most are only used in very rare clinical scenarios (e.g. sunitinib for the treatment of advanced renal cell carcinoma or pancreatic neuroendocrine tumors). The exception is phenytoin which is used as an anti-epileptic drug and which, among its other effects, is a RIPK1 inhibitor protecting against necroptosis. 10, 11 In this study, we compared the incidence of post-COVID cognitive deficits between patients exposed to phenytoin and matched cohorts of patients exposed to other anti-epileptic drugs at the time of their COVID-19 diagnosis.

Master equation to boost quantum technologies

As the size of modern technology shrinks down to the nanoscale, weird quantum effects—such as quantum tunneling, superposition, and entanglement—become prominent. This opens the door to a new era of quantum technologies, where quantum effects can be exploited. Many everyday technologies make use of feedback control routinely; an important example is the pacemaker, which must monitor the user’s heartbeat and apply electrical signals to control it, only when needed. But physicists do not yet have an equivalent understanding of feedback control at the quantum level. Now, physicists have developed a “master equation” that will help engineers understand feedback at the quantum scale. Their results are published in the journal Physical Review Letters.

“It is vital to investigate how can be used in quantum technologies in order to develop efficient and fast methods for controlling , so that they can be steered in real time and with high precision,” says co-author Björn Annby-Andersson, a quantum physicist at Lund University, in Sweden.

An example of a crucial feedback-control process in is . A quantum computer encodes information on physical qubits, which could be photons of light, or atoms, for instance. But the quantum properties of the qubits are fragile, so it is likely that the encoded information will be lost if the qubits are disturbed by vibrations or fluctuating electromagnetic fields. That means that physicists need to be able to detect and correct such errors, for instance by using feedback control. This error correction can be implemented by measuring the state of the qubits and, if a deviation from what is expected is detected, applying feedback to correct it.

Researchers engineer first sustainable chromosome changes in mice

This finding “proved” the significance of chromosomal rearrangement, a crucial evolutionary indicator of the emergence of a new species.

Researchers from the Chinese Academy of Sciences (CAS) claim to have found a novel technique for programmable chromosome fusion successfully producing mice with genetic changes “that occur on a million-year evolutionary scale” in the laboratory.

The findings could shed light on how chromosome rearrangements—the tidy packages of organized genes provided in equal numbers by each parent, which align and trade or blend traits to produce offspring—influence evolution, reported Phys.org on Thursday.

Evolutionary chromosomal changes may take a million years in nature, but researchers are now reporting a novel technique enabling programmable chromosome fusion that has successfully produced mice with genetic changes that occur on a million-year evolutionary scale in the laboratory. The result may provide critical insights into how rearrangements of chromosomes—the tidy packages of organized genes, provided in equal number from each parent, which align and trade or blend traits to produce offspring—influence evolution.

In results published today in Science, the researchers reveal that chromosome-level engineering can be achieved in mammals, and they successfully derived a laboratory house mouse with novel and sustainable karyotype, providing critical insight into how may influence evolution.

“The laboratory house mouse has maintained a standard 40-chromosome karyotype—or the full picture of an organism’s chromosomes—after more than 100 years of artificial breeding,” said co-first author Li Zhikun, researcher in the Chinese Academy of Sciences (CAS) Institute of Zoology and the State Key Laboratory of Stem Cell and Reproductive Biology. “Over longer time scales, however, karyotype changes caused by chromosome rearrangements are common. Rodents have 3.2 to 3.5 rearrangements per million years, whereas primates have 1.6.”

Continue reading “Researchers engineer first sustainable chromosome changes in mice” | >

Neuralink will probably not be wanted

Meta CEO Mark Zuckerberg was a recent guest on The Joe Rogan Experience podcast, and during the episode, he discussed, among other things, neural technology. During his conversation, Zuckerberg remarked that Elon Musk’s Neuralink would probably not be popular in the next 10–15 years because “normal people” would not want to have devices implanted in their brains that are made of non-mature technology.

Zuckerberg admitted that Meta is researching neural interface tech as part of the company’s push into the metaverse, though he also noted that the tech company is focusing on innovations that can receive signals from the brain but does not send any information back to it.

In later comments, the Meta CEO noted that companies like Elon Musk’s Neuralink, which is developing a device that can be implanted into people’s skulls, is taking neural technology “super far-off.” Neuralink’s implant is designed to record and stimulate brain activity, which Musk has stated could help people address conditions such as obesity.