Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biotech/medical – Page 16

Visualizing Transporter Structure Creates Platform for Antidepressant Drug Design

Researchers at Oregon Health and Sciences University’s Vollum Institute have revealed the molecular structure of the serotonin transporter (SERT), providing new insight into the mechanism of antidepressant action of two widely prescribed selective serotonin reuptake inhibitors (SSRIs) commonly used to treat depression. In their Nature paper, authors Jonathan Coleman, Evan Green, and Eric Gouaux describe their use of X-ray crystallography to capture images of human SERT structures. They collected data at the Beamline 5.0.2 in the Berkeley Center for Structural Biology and used the Phenix software suite to build models and refine the structures. The resulting structures show antidepressants citalopram and paroxetine lock SERT in an outward-open conformation, directly blocking serotonin binding.

New Ultrasound Helmet Reaches Deep Inside The Brain Without Surgery

Deep-brain structures like the basal ganglia or the thalamus wield major influence on our behavior. If something goes awry, dysregulation in the deep brain may trigger neurological conditions like Parkinson’s disease or depression.

Despite the clear importance of these structures, our knowledge about them remains limited by their location, making them difficult to study and treat.

In a new study, researchers unveil a device that might offer an alternative to invasive procedures. Featuring a novel ultrasound helmet, it not only modulates deep-brain circuits without surgery, but reportedly can do so with unrivaled precision.

Sam Altman’s longevity startup is testing a pill for a younger brain

I’ve just hopped on a video call with the CEO of Retro Biosciences, the Sam Altman-backed longevity company, when I mention it’s quite hot.

Joe Betts-LaCroix takes my passing comment as a cue to muse on the wonders of air conditioning, and how energy and heat were once synonymous — until they weren’t.

As a multi-hyphenate scientist, entrepreneur, and once-inventor of the world’s smallest computer, Betts-LaCroix is excited by paradigm change.

At the helm of what is essentially Altman’s playground for experimenting with pushing the limits of the human lifespan, Betts-LaCroix is hoping to engineer the same shift that air conditioning brought to hot summer days for your brain and body. Ideally, one day, decouple aging from decline and disease.

The experimental memory pill works by clearing out “gunk in the cells” linked to Alzheimer’s and Parkinson’s, Betts-LaCroix said. If the pill works, it will restart stalled autophagy processes in the body, cleaning up damage, “especially in the brain cells,” he said.

In contrast, other new Alzheimer’s drugs, like Eisai’s Leqembi and Eli Lilly’s Kisunla, slow down cognitive decline by flushing out sticky amyloid plaques that are a hallmark of the disease.

Continue reading “Sam Altman’s longevity startup is testing a pill for a younger brain” | >

Increasing the level of the protein PI31 demonstrates neuroprotective effects in mice

One fundamental feature of neurodegenerative diseases is a breakdown in communication. Even before brain cells die, the delicate machinery that keeps neurons in touch—by clearing away protein waste at the synapses—starts to fail.

When the cleanup falters, the connections between are impaired and the flow of signals responsible for reasoning, language, memory, and even basic bodily functions are progressively disrupted.

Now, a new study identifies a novel strategy for preventing unwanted proteins from clogging synapses and ultimately congealing into protein plaques.

Engineers develop technology that stimulates heart cells with light

In a new study, University of California, Irvine chemical and biomolecular engineering researchers report the creation of biomolecules that can help grow light-sensitive heart muscle cells in the laboratory. The development enables a biotechnology that could deliver light-triggered signals to the heart, improving its function, without requiring genetic modifications or invasive procedures.

“We show for the first time that light can be converted into cardiac stimulatory cues, with made of biomolecules,” said Herdeline Ann Ardoña, assistant professor of chemical and biomolecular engineering. “This can be beneficial for downstream medical applications, such as in cardiac pacemaking technologies, or helping direct therapeutic patient-derived stem to better mimic adult heart cell features.”

The findings are reported in the Proceedings of the National Academy of Sciences. The paper’s co-first authors are recent Ph.D. graduate Sujeung Lim, and Ze-Fan Yao, previous postdoctoral scholar in the Ardoña Research Group.

The Role of Bioelectrical Patterns in Regulative Morphogenesis: An Evolutionary Simulation and Validation in Planarian Regeneration

Endogenous bioelectrical patterns are an important regulator of anatomical pattern during embryogenesis, regeneration, and cancer. While there are three known classes of instructive bioelectric patterns: directly encoding, indirectly encoding, and binary trigger, it is not known how these design principles could be exploited by evolution and what their relative advantages might be. To better understand the evolutionary role of bioelectricity in anatomical homeostasis, we developed a neural cellular automaton (NCA). We used evolutionary algorithms to optimize these models to achieve reliable morphogenetic patterns driven by the different ways in which tissues can interpret their bioelectrical pattern for downstream anatomical outcomes. We found that: All three types of bioelectrical codes allow the reaching of target morphologies; Resetting of the bioelectrical pattern and the change in duration of the binary trigger alter morphogenesis; Direct pattern organisms show an emergent robustness to changes in initial anatomical configurations; Indirect pattern organisms show an emergent robustness to bioelectrical perturbation; Direct and indirect pattern organisms show a emergent generalizability competency to new (rotated) bioelectrical patterns; Direct pattern organisms show an emergent repatterning competency in post-developmental-phase. Because our simulation was fundamentally a homeostatic system seeking to achieve specific goals in anatomical state space (the space of possible morphologies), we sought to determine how the system would react when we abrogated the incentive loop driving anatomical homeostasis. To abrogate the stress/reward system that drives error minimization, we used anxiolytic neuromodulators. Simulating the effects of selective serotonin reuptake inhibitors diminished the ability of artificial embryos to reduce error between anatomical state and bioelectric prepattern, leading to higher variance of developmental outcomes, global morphological degradation, and induced in some organisms a bistability with respect to possible anatomical outcomes. These computational findings were validated by data collected from in vivo experiments in SSRI exposure in planarian flatworm regeneration.

Caltech Researchers Upend Decades-Old Model of Mitochondrial Protein Import

Researchers showed that many mitochondrial proteins enter the organelle during synthesis, guided by folding patterns and structural signals. This discovery revises decades of biochemical models. Mitochondria are organelles most commonly known as the “powerhouses of the cell” because they generate

AI to integrate bulk multi-omics data for precision oncology

“Cancer and other complex diseases arise from the interplay of various biological factors, for example, at the DNA, RNA, and protein levels,” explains the author. Characteristic changes at these levels — such as the amount of HER2 protein produced in breast or stomach cancer — are often recorded, but typically not yet analyzed in conjunction with all other therapy-relevant factors.

This is where Flexynesis comes in. “Comparable tools so far have often been either difficult to use, or only useful for answering certain questions,” says the author. “Flexynesis, by contrast, can answer various medical questions at the same time: for example, what type of cancer is involved, what drugs are particularly effective in this case, and how these will affect the patient’s chances of survival.” The tool also helps identify suitable biomarkers for diagnosis and prognosis, or — if metastases of unknown origin are discovered — to identify the primary tumor. “This makes it easier to develop comprehensive and personalized treatment strategies for all kinds of cancer patients,” says the author.

Nearly 50 new cancer therapies are approved every year. This is good news. “But for patients and their treating physicians, it is becoming increasingly difficult to keep track and to select the treatment methods from which the people affected — each with their very individual tumor characteristics — will benefit the most,” says the senior author. The researcher has been working for some time on developing tools that use artificial intelligence to make more precise diagnoses and that also determine the best form of therapy tailored to individual patients.

The team has now developed a toolkit called Flexynesis, which does not rely solely on classical machine learning but also uses deep learning to evaluate very different types of data simultaneously — for example, multi-omics data as well as specially processed texts and images, such as CT or MRI scans. “In this way, it enables doctors to make better diagnoses, prognoses, and develop more precise treatment strategies for their patients,” says the author. Flexynesis is described in detail in a paper published in “Nature Communications.”

“We are running multiple translational projects with medical doctors who want to identify biomarkers from multi-omics data that align with disease outcomes,” says the first and co-corresponding author of the publication. “Although many deep-learning based methods have been published for this purpose, most have turned out to be inflexible, tied to specific modeling tasks, or difficult to install and reuse. That gap motivated us to build Flexynesis as a proper toolkit, which is flexible for different modeling tasks and packaged on PyPI, Guix, Docker, Bioconda, and Galaxy, so others can readily apply it in their own pipelines.”

/* */