Lifeboat Foundation

Year 2021 😀 😍

The COVID-19 pandemic has reached direct and indirect medical and social consequences with a subset of patients who rapidly worsen and die from severe-critical manifestations. As a result, there is still an urgent need to identify prognostic biomarkers and effective therapeutic approaches. Severe-critical manifestations of COVID-19 are caused by a dysregulated immune response. Immune checkpoint molecules such as Programmed death-1 (PD-1) and its ligand programmed death-ligand 1 (PD-L1) play an important role in regulating the host immune response and several lines of evidence underly the role of PD-1 modulation in COVID-19. Here, by analyzing blood sample collection from both hospitalized COVID-19 patients and healthy donors, as well as levels of PD-L1 RNA expression in a variety of model systems of SARS-CoV-2, including in vitro tissue cultures, ex-vivo infections of primary epithelial cells and biological samples obtained from tissue biopsies and blood sample collection of COVID-19 and healthy individuals, we demonstrate that serum levels of PD-L1 have a prognostic role in COVID-19 patients and that PD-L1 dysregulation is associated to COVID-19 pathogenesis. Specifically, PD-L1 upregulation is induced by SARS-CoV-2 in infected epithelial cells and is dysregulated in several types of immune cells of COVID-19 patients including monocytes, neutrophils, gamma delta T cells and CD4+ T cells. These results have clinical significance since highlighted the potential role of PD-1/PD-L1 axis in COVID-19, suggest a prognostic role of PD-L1 and provide a further rationale to implement novel clinical studies in COVID-19 patients with PD-1/PD-L1 inhibitors.

COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) holds the world in thrall since early March 2020. COVID-19 manifests a spectrum of signs and symptoms from mild illness to acute pneumonia. Unfortunately, a considerable percentage of patients rapidly worse to acute respiratory distress syndrome (ARDS) requiring intensive care (1, 2).

Continue reading “PD-L1 Dysregulation in COVID-19 Patients” »

Autonomous Microscopy powered by Aivia enables scientists to discover more by extracting the most relevant data from their experiments.

06 June 2023, Wetzlar, Germany - Leica Microsystems, a leader in microscopy and scientific instrumentation, has launched Autonomous Microscopy powered by Aivia. This new AI-based detection workflow for confocal microscopy automates the detection of rare events. It follows what the user has defined as the objects of interest that will trigger the rare event scan. Users benefit from the potential to discover more by automatically detecting up to 90% of rare events during an experiment. By focusing on the data that matter during the acquisition process itself, time to result can be reduced by up to 70%. The Aivia-powered workflow reduces time spent at the microscope by up to 75%, leading to increased productivity to do more.

“Autonomous Microscopy powered by Aivia brings the power of Artificial Intelligence to everyday experimental environments in an easy-to-use way,” says James O’Brien, Vice President of Life Sciences and Applied Microscopy at Leica Microsystems. “Researchers can now establish confocal microscopy workflows that address advanced experiments and biological questions that would be impossible or very laborious without automated procedures. This solution gives them outstanding new options to obtain results that answer their research questions.”

Biologists are finally beginning to corral molecules, cells and whole organisms to carry out complex computations. These living processors could find use in everything from smart materials to new kinds of artificial intelligence.

By Edd Gent

A two-year expedition to coral reefs in the Pacific Ocean detected half a million types of microbes, the latest estimate in the quest to quantify the planet’s microbiome.

The big picture: There is intense debate among scientists about how many different types of bacteria and other microorganisms live on Earth — information that could aid conservation of species and fragile ecosystems brimming with biodiversity.

The mammalian retina is a complex system consisting out of cones (for color) and rods (for peripheral monochrome) that provide the raw image data which is then processed into successive layers of neurons before this preprocessed data is sent via the optical nerve to the brain’s visual cortex. In order to emulate this system as closely as possible, researchers at Penn State University have created a system that uses perovskite (methylammonium lead bromide, MAPbX₃) RGB photodetectors and a neuromorphic processing algorithm that performs similar processing as the biological retina.

Panchromatic imaging is defined as being ‘sensitive to light of all colors in the visible spectrum’, which in imaging means enhancing the monochromatic (e.g. RGB) channels using panchromatic (intensity, not frequency) data. For the retina this means that the incoming light is not merely used to determine the separate colors, but also the intensity, which is what underlies the wide dynamic range of the Mark I eyeball. In this experiment, layers of these MAPbX₃ (X being Cl, Br, I or combination thereof) perovskites formed stacked RGB sensors.

The output of these sensor layers was then processed in a pretrained convolutional neural network, to generate the final, panchromatic image which could then be used for a wide range of purposes. Some applications noted by the researchers include new types of digital cameras, as well as artificial retinas, limited mostly by how well the perovskite layers scale in resolution, and their longevity, which is a long-standing issue with perovskites. Another possibility raised is that of powering at least part of the system using the energy collected by the perovskite layers, akin to proposed perovskite-based solar panels.

Quantum effects are phenomena that occur between atoms and molecules that can’t be explained by classical physics. It has been known for more than a century that the rules of classical mechanics, like Newton’s laws of motion, break down at atomic scales. Instead, tiny objects behave according to a different set of laws known as quantum mechanics.

For humans, who can only perceive the macroscopic world, or what’s visible to the naked eye, quantum mechanics can seem counterintuitive and somewhat magical. Things you might not expect happen in the quantum world, like electrons “tunneling” through tiny energy barriers and appearing on the other side unscathed or being in two different places at the same time in a phenomenon called superposition.

I am trained as a quantum engineer. Research in quantum mechanics is usually geared toward technology. However, and somewhat surprisingly, there is increasing evidence that nature – an engineer with billions of years of practice — has learned how to use quantum mechanics to function optimally. If this is indeed true, it means that our understanding of biology is radically incomplete. It also means that we could possibly control physiological processes by using the quantum properties of biological matter.

Given this new information humans could modify their genetic code to rapidly accelerate their evolution aswell leading to a biological singularity of evolution.

Codfish have been telling a story of rapid fish evolution, reshaped by human activity more swiftly than previously assumed, reveals a cutting-edge study led by Rutgers University.

This evolutionary tale, illuminated during the latter half of the twentieth century, signifies the impact of human-driven overfishing. The findings suggest that evolutionary changes, once thought to span millions of years, can be catalyzed within mere decades.

Continue reading “Fish evolution takes place in decades — not millions of years” »

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Continue reading “Can We Move PLANET EARTH Across the Universe?” »

Radhika is a professor at Harvard and a core faculty member of the Wyss Institute for Biologically Inspired Engineering. She studies collective behavior in biological systems and how such behaviors can be applied to computing and robotics.

Radhika Nagpal is the Kavli Professor of Computer Science at Harvard University and a core faculty member of the Wyss Institute.
for Biologically Inspired Engineering. At Harvard, she leads the Self-organizing Systems Research Group (SSR) and her research combines.
computer science, robotics, and biology. Her main area of interest is how cooperation can emerge or be programmed from large groups of.
simple agents. Radhika Nagpal is a Core Faculty Member at the Wyss Institute for Biologically Inspired Engineering at Harvard, where she heads the Self-Organizing Systems Research Group in the study of collective behavior in biological systems and how such behaviors can be applied to computing and robotics. A professor at the Harvard School of Engineering and Applied Sciences (SEAS), her research draws on inspiration from social insects and multicellular biology, with the goal of creating globally robust systems made up of many cooperative parts.

Continue reading “Taming the swarm” »