Lifeboat Foundation

Is the Ira Rubinoff Director of the Smithsonian Tropical Research Institute (STRI https://www.si.edu/about/bios/joshua-tewksbury), part of the Smithsonian Institution, the world’s largest museum, education, and research complex. He oversees more than 400 employees, with an annual budget of $35 million. Headquartered in Panama City, Panama, with field sites around the world, STRI furthers the understanding and public awareness of tropical biodiversity and its importance to human welfare. In addition to its resident scientists and support staff, STRI’s facilities are used annually by some 1,400 visiting scientists, pre-and postdoctoral fellows and interns from around the world.

Dr. Tewksbury is an ecologist with more than two decades of research in conservation and biodiversity, as well as nearly a decade of executive leadership experience at international research institutes.

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Catalytic molecules can form metabolically active clusters by creating and following concentration gradients—this is the result of a new study by scientists from the Max Planck Institute for Dynamics and Self-Organization (MPI-DS). Their model predicts the self-organization of molecules involved in metabolic pathways, adding a possible new mechanism to the theory of the origin of life.

The results can help to better understand how molecules participating in complex biological networks can form dynamic functional structures, and provide a platform for experiments on the origins of life.

One possible scenario for the origin of life is the spontaneous organization of interacting molecules into cell-like droplets. These molecular species would form the first self-replicating metabolic cycles, which are ubiquitous in biology and common throughout all organisms. According to this paradigm, the first biomolecules would need to cluster together through slow and overall inefficient processes.

Optical phase retrieval and imaging appear in a wide variety of science fields, such as imaging of quasi-transparent biological samples or nanostructures metrological characterization, for example, in the semiconductor industry. At a fundamental level, the limit to imaging accuracy in classical systems comes from the intrinsic fluctuation of the illuminating light, since the photons that form it are emitted randomly by conventional sources and behave independently of one another.

Quantum correlation in light beams, in which photons show certain cooperation, can surpass those limits. Although quantum advantage obtained in phase estimation through first-order interference is well understood, interferometric schemes are not suitable for multi-parameter wide-field imaging, requiring raster scanning for extended samples.

In a new paper published in Light Science & Application, a team of scientists from the Quantum Optics Group of the Italian National Metrology Institute (INRiM), Italy, and from the Imaging Physics Dept. Optics Research Group, Faculty of Applied Sciences of Delft University of Technology, The Netherlands, has developed a technology exploiting quantum correlations to enhance imaging of phase profiles in a non-interferometric way.

The Mexican salamander is only found in two lakes and is considered critically endangered, with pollution and invasive predators driving the species’ decline.

New chemistry, new enzymology. With a new method that merges the best of two worlds—the unique and complementary activities of enzymes and small-molecule photochemistry—researchers at UC Santa Barbara have opened the door to new catalytic reactions. Their synergistic method allows for new products and can streamline existing processes, in particular, the synthesis of non-canonical amino acids, which are important for therapeutic purposes.

“This method solves what in my opinion is one of the most important problems in our field: how to develop new catalytic reactions in a general sense that are new to both biology and chemistry,” said chemistry Professor Yang Yang, an author of a paper that appears in the journal Science. “On top of that, the process is stereoselective, meaning it can select for a preferred “shape” of the resulting amino acid.”

The synergistic photobiocatalytic method consists of two co-occurring catalytic reactions. The photochemical reaction generates a short-lived intermediate molecule that works with the reactive intermediate of the enzymatic process, resulting in the amino acid.

In September 2020 we sat down with Robert Sapolsky, Stanford professor and the author of Human Behavioral Biology lectures (https://youtu.be/NNnIGh9g6fA) to discuss if it’s possible for our society to reconcile our understanding of justice with scientific understanding of human behaviour.

Why do humans, most likely, have no free will? How does that link to depression and other psychiatric disorders? Can people accept the idea that there is no free will and start using, what science tells us about the reasons behind our behaviour, as a basis for making sense of justice and morality? If yes, can we even imagine what such society would look like?

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Fragile X syndrome is a genetic disorder caused by a mutation in a gene that lies at the tip of the X chromosome. It is linked to autism spectrum disorders.

People with fragile X experience a range of symptoms that include cognitive impairment, developmental and speech delays and hyperactivity. They may also have some physical features such as large ears and foreheads, flabby muscles and poor coordination.

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A team of researchers has recently claimed to have discovered six chemical cocktails that could help reverse biological aging. Yet these preliminary laboratory results are a long way away from being applied to humans.

The show provides a glimpse into humanity’s astonishing diversity. Social scientists have a similar goal—understanding the behavior of different people, groups, and cultures—but use a variety of methods in controlled situations. For both, the stars of these pursuits are the subjects: humans.

But what if you replaced humans with AI chatbots?

The idea sounds preposterous. Yet thanks to the advent of ChatGPT and other large language models (LLMs), social scientists are flirting with the idea of using these tools to rapidly construct diverse groups of “simulated humans” and run experiments to probe their behavior and values as a proxy to their biological counterparts.