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Researchers at the University of California, Davis, have been able to produce antibodies to the SARS-CoV-2 spike protein in hen eggs. Antibodies harvested from eggs might be used to treat COVID-19 or as a preventative measure for people exposed to the disease. The work was published July 9 in the journal Viruses.

“The beauty of the system is that you can produce a lot of antibodies in birds,” said Rodrigo Gallardo, professor in poultry medicine, Department of Population Health and Reproduction at the UC Davis School of Veterinary Medicine. “In addition to a low cost to produce these antibodies in hens, they can be updated very fast by using updated antigens to hyperimmunize hens, allowing protection against current variant strains.”

Birds produce a type of antibody called IgY, comparable to IgG in humans and other mammals. IgY does not cause allergy or set off immune reactions when injected into humans. IgY appears both in birds’ serum and in their eggs. As a hen lays about 300 eggs a year, you can get a lot of IgY, Gallardo said.

Nearly two-and-a-half years since the coronavirus pandemic began, the most infectious and transmissible variant yet has arrived.

Repeated Covid-19 waves have left millions of people dead, with only vaccines helping to blunt the toll. Now the virus is spreading again — evolving, escaping immunity and driving an uptick in cases and hospitalizations. The latest version of its shape-shifting, BA.5, is a clear sign that the pandemic is far from over.

The newest offshoot of Omicron, along with a closely related variant, BA.4, are fueling a global surge in cases — 30% over the past fortnight, according to the World Health Organization (WHO).

Engineers have developed a new class of smart textiles that can shape-shift and turn a two-dimensional material into 3D structures.

The team from UNSW Sydney’s Graduate School of Biomedical Engineering, and Tyree Foundation Institute of Health Engineering (Tyree iHealthE), led by Dr. Thanh Nho Do, have produced a material which is constructed from tiny soft artificial “muscles”—which are long silicon tubes filled with fluid which are manipulated to move via hydraulics.

These , which are surrounded by a helical coil of traditional fibers, can be programmed to contract or expand into a variety of shapes depending on its initial structure.

The entirety of the known universe is teeming with an infinite number of molecules. But what fraction of these molecules have potential drug-like traits that can be used to develop life-saving drug treatments? Millions? Billions? Trillions? The answer: novemdecillion, or 1060. This gargantuan number prolongs the drug development process for fast-spreading diseases like COVID-19 because it is far beyond what existing drug design models can compute. To put it into perspective, the Milky Way has about 100 thousand million, or 108, stars.

In a paper that will be presented at the International Conference on Machine Learning (ICML), MIT researchers developed a geometric deep-learning model called EquiBind that is 1,200 times faster than one of the fastest existing computational molecular docking models, QuickVina2-W, in successfully binding drug-like molecules to proteins. EquiBind is based on its predecessor, EquiDock, which specializes in binding two proteins using a technique developed by the late Octavian-Eugen Ganea, a recent MIT Computer Science and Artificial Intelligence Laboratory and Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) postdoc, who also co-authored the EquiBind paper.

Before can even take place, drug researchers must find promising drug-like molecules that can bind or “dock” properly onto certain protein targets in a process known as . After successfully docking to the protein, the binding drug, also known as the ligand, can stop a protein from functioning. If this happens to an essential protein of a bacterium, it can kill the bacterium, conferring protection to the human body.

While many artificial materials have advanced properties, they have a long way to go to combine the versatility and functionality of living materials that can adapt to their situation. For example, in the human body bone and muscle continuously reorganise their structure and composition to better sustain changing weight and level of activity.

Now, researchers from Imperial College London and University College London have demonstrated the first spontaneously self-organising laser device, which can reconfigure when conditions change.

The innovation, reported in Nature Physics (“Self-organized Lasers of Reconfigurable Colloidal Assemblies”), will help enable the development of smart photonic materials capable of better mimicking properties of biological matter, such as responsiveness, adaptation, self-healing, and collective behaviour.

The team of researchers who transplanted a genetically modified pig’s heart into a living human earlier this year have completed two more pig heart transplant surgeries, setting the protocol for such operations.

In January this year, 57-year-old David Bennett became the first man on the planet to receive a heart from a genetically modified pig. Before this, researchers transplanted kidneys from similarly modified pigs into patients that were brain dead.

The organs are sourced from a company called Revivicor which uses genetic engineering to remove specific genes in the pigs to help in reducing transplant rejection while adding some that make the organs more compatible with the human immune system.