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An exciting new cancer drug has recently entered into a phase 1 clinical trial supported by promising pre-clinical work. The drug, named AOH1996, targets a protein called proliferating cell nuclear antigen (PCNA), an essential player in the biological processes of DNA replication and repair. A team of researchers from City of Hope published the data describing how they identified and characterized AOH1996 in Cell Chemical Biology last week. Since then, the news of AOH1996 has appeared prominently in both scientific and mainstream media.

Using a rational drug design approach that develops drugs based on their specific biological targets, the researchers identified AOH1996. Lead researcher Linda Malkas named the drug after Anna Oliva Healey, a girl born in 1996 who succumbed to neuroblastoma at age 9.

In the laboratory, the researchers tested AOH1996 on over 70 different kinds of tumor cells as well as some healthy control cells. While the drug killed the cancer cells, it notably does not affect non-cancer cells, including blood cells and the cells lining the airway. This indicates AOH1996 as a selective drug that will suppress tumor growth but likely not cause adverse effects that can occur when a cancer drug damages healthy cells.

A team from the University of Chicago has announced the first evidence for “quantum superchemistry” – a phenomenon where particles in the same quantum state undergo collective accelerated reactions. The effect had been predicted, but never observed in the laboratory.

The findings, published July 24 in Nature Physics, open the door to a new field. Scientists are intensely interested in what are known as “quantum-enhanced” chemical reactions, which could have applications in quantum chemistry, quantum computing, and other technologies, as well as in better understanding the laws of the universe.


Breakthrough could point way to fundamental insights, new technology.

That’s why we were struck to see a team of scientists that includes researchers from the name-brand Harvard Medical School and Massachusetts Institute of Technology sounding off about what they say are promising new leads, published this month in the journal Aging.

“We identify six chemical cocktails, which, in less than a week and without compromising cellular identity, restore a youthful genome-wide transcript profile and reverse transcriptomic age,” reads the paper. “Thus, rejuvenation by age reversal can be achieved, not only by genetic, but also chemical means.”

Sounds big, right? The researchers claim they pinpointed six treatments that can reverse aging in cells and turn them into a more “youthful state,” according to a press release from Aging’s publisher, without causing dangerous unregulated cell growth.

To explore the association between a chemical’s structure and its odour, Wiltschko and his team at Osmo designed a type of artificial intelligence (AI) system called a neural network that can assign one or more of 55 descriptive words, such as fishy or winey, to an odorant. The team directed the AI to describe the aroma of roughly 5,000 odorants. The AI also analysed each odorant’s chemical structure to determine the relationship between structure and aroma.

The system identified around 250 correlations between specific patterns in a chemical’s structure with a particular smell. The researchers combined these correlations into a principal odour map (POM) that the AI could consult when asked to predict a new molecule’s scent.

To test the POM against human noses, the researchers trained 15 volunteers to associate specific smells with the same set of descriptive words used by the AI. Next, the authors collected hundreds of odorants that don’t exist in nature but are familiar enough for people to describe. They asked the human volunteers to describe 323 of them and asked the AI to predict each new molecule’s scent on the basis of its chemical structure. The AI’s guess tended to be very close to the average response given by the humans — often closer than any individual’s guess.

Other red-teamers prompted GPT-4’s pre-launch version to aid in a range of illegal and nocuous activities, like writing a Facebook post to convince someone to join Al-Qaeda, helping find unlicensed guns for sale and generating a procedure to create dangerous chemical substances at home, according to GPT-4’s system card, which lists the risks and safety measures OpenAI used to reduce or eliminate them.

To protect AI systems from being exploited, red-team hackers think like an adversary to game them and uncover blind spots and risks baked into the technology so that they can be fixed. As tech titans race to build and unleash generative AI tools, their in-house AI red teams are playing an increasingly pivotal role in ensuring the models are safe for the masses. Google, for instance, established a separate AI red team earlier this year, and in August the developers of a number of popular models like OpenAI’s GPT3.5, Meta’s Llama 2 and Google’s LaMDA participated in a White House-supported event aiming to give outside hackers the chance to jailbreak their systems.

But AI red teamers are often walking a tightrope, balancing safety and security of AI models while also keeping them relevant and usable. Forbes spoke to the leaders of AI red teams at Microsoft, Google, Nvidia and Meta about how breaking AI models has come into vogue and the challenges of fixing them.

Layered hybrid perovskites show diverse physical properties and exceptional functionality; however, from a materials science viewpoint, the co-existence of lattice order and structural disorder can hinder the understanding of such materials. Lattice dynamics can be affected by dimensional engineering of inorganic frameworks and interactions with molecular moieties in a process that remains unknown.

To address this problem, Zhuquan Zhang and a team of scientists in chemistry and physics at the University of Pennsylvania, University of Texas, Austin, and the Massachusetts Institute of Technology, U.S., used a combination of spontaneous Raman scattering, terahertz spectroscopy and molecular dynamics simulations.

The research outcomes revealed how the in and out of equilibrium provided unexpected observables to differentiate single-and double-layered perovskites. The study is published in Science Advances.

Interfacing modern electronics-based technology with biology is notoriously difficult. One major stumbling block is that the way they are powered is very different. While most of our gadgets run on electrons, nature relies on the energy released when the chemical bonds of ATP are broken. Finding ways to convert between these two very different currencies of energy could be useful for a host of biotechnologies.

Genetically engineered microbes are already being used to produce various high-value chemicals and therapeutically useful proteins, and there are hopes they could soon help generate greener jet fuel, break down plastic waste, and even grow new foods in giant bioreactors. But at the minute, these processes are powered through an inefficient process of growing biomass, converting it to sugar, and feeding it to the microbes.

Now, researchers at the Max Planck Institute for Terrestrial Microbiology in Germany have devised a much more direct way to power biological processes. They have created an artificial metabolic pathway that can directly convert electricity into ATP using a cocktail of enzymes. And crucially, the process works in vitro and doesn’t rely on the native machinery of cells.

Michael Levin talk for the Mind, Technology, and Society (MTS) talk series at UC Merced on January 23, 2023. Abstract: Each of us makes the remarkable journey from the physics and chemistry of a quiescentunfertilized egg to that of a complex human being. How can we understand the continuousprocesses that scale up minds from the tiny physiological competencies of single cells to the large-scale metacognitive capacities of large brains? Here, I will describe a framework known as TAME-Technological Approach to Mind Everywhere — which enables identifying, understanding, andrelating to unconventional cognitive agents. I will use the example of the collective intelligence ofcells during morphogenesis to illustrate how we can begin to widen the lessons of multiscale neuroscience well beyond neurons. This will be essential as we head into a future that will bepopulated by a wide range of evolved, designed, and hybrid beings with novel bodies and novelminds. I will conclude with a case study of our new synthetic biorobot (Xenobots) and a discussionof the implications of these ideas for evolution, biomedicine, and ethics.

What happens when humans begin combining biology with technology, harnessing the power to recode life itself.

What does the future of biotechnology look like? How will humans program biology to create organ farm technology and bio-robots. And what happens when companies begin investing in advanced bio-printing, artificial wombs, and cybernetic prosthetic limbs.

Other topic include: bioengineered food and farming, bio-printing in space, new age living bioarchitecture (eco concrete inspired by coral reefs), bioengineered bioluminescence, cyberpunks and biopunks who experiment underground — creating new age food and pets, the future of bionics, corporations owning bionic limbs, the multi-trillion dollar industry of bio-robots, and bioengineered humans with super powers (Neo-Humans).

As well as the future of biomedical engineering, biochemistry, and biodiversity.