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Plants have the unique ability to regenerate entirely from a somatic cell, i.e., an ordinary cell that does not typically participate in reproduction. This process involves the de novo (or new) formation of a shoot apical meristem (SAM) that gives rise to lateral organs, which are key for the plant’s reconstruction.

At the , SAM formation is tightly regulated by either positive or negative regulators (genes/) that may induce or restrict shoot regeneration, respectively. But which molecules are involved? Are there other regulatory layers that are yet to be uncovered?

To seek answers to the above questions, a research group led by Nara Institute of Science and Technology (NAIST), Japan studied the process in Arabidopsis, a plant commonly used in . Their research—which was published in Science Advances —identified and characterized a key negative regulator of shoot regeneration.

This benefits customers by accelerating access to future vehicles that feature the latest technology while also enabling their current vehicles to be eligible to receive updates and improvements over time—unlocking additional value beyond the initial point of purchase. And for large enterprises, shorter development cycles with less ground-up engineering can equate to significant cost savings and allow more investment in innovation.

Beyond vehicles themselves, the tools, techniques and processes that are required to engineer and manufacture at scale are also benefitting from developments in the latest hardware technology. Advancements in raw material chemistry and processing, fabrication and physical sciences are leading to lighter, stronger and better-performing vehicle applications in parallel with greater connectivity.

As advancements in transportation technology continue to evolve, it’s important for companies to balance their focus on the continual development of both hardware and software technologies. Forgoing advancements in one without investing in the development of the other can lead to significant risks and missed opportunities for long-term success.

Join top executives in San Francisco on July 11–12 and learn how business leaders are getting ahead of the generative AI revolution. Learn More

As the cookieless future continues to gain momentum, the global digital advertising sector is experiencing a tectonic shift. Companies are being forced to reimagine the way they reach out to customers.

Online marketing has been dominated by third-party cookies — tracking codes posted on websites to extract users’ information — and data brokers who sell the information in bulk.

The mesh has already proved successful on fruit fly larvae in Minnesota, and with two species of mushroom coral in Hawaii and Australia. In Florida, Hagedorn and colleagues were trying it on Diploria labyrinthiformis, a kind of brain coral whose larvae are more than 100 times bigger than those of mushroom coral. In the first few attempts, rewarmed larvae were falling apart. Each larval size, Hagedorn was learning, needs its own version of the treatment. “We’re struggling a little bit to get this to work,” she says.

WHILE SCIENTISTS such as Bischof and Hagedorn wrestle with vitrification, others are seeking an easier route by avoiding ultralow temperatures that require large infusions of cryoprotectant and make rewarming so challenging.

At Harvard University and MGH, scientists are taking cues from nature to push tissues below freezing while holding back the ice. The wood frog (Rana sylvatica) is a champion of this realm. Found in much of North America, including the frigid Canadian Arctic, it can spring to life after spending months with as much as two-thirds of its body frozen at temperatures as low as −16°C.

If you are looking for a side hustle and have a knack for tech and language, picking up a gig to help employers create content like LinkedIn posts, blog posts, podcast show notes and even social media posts for Twitter and Instagram using ChatGPT could prove effective. Here’s how to do it.


ChatGPT is all the rage, and it turns out businesses are hiring experts in the tool to help them create content. Here’s how to start the side hustle.

Each time our cells divide, the protective caps that keep our chromosomes from fraying, called telomeres, lose a bit of their DNA. Telomeres shorten steadily as we age, but in certain medical conditions like dyskeratosis congenita, the process is accelerated.

“Your telomeres determine your lifeline; how long they are determines how old your body is,” says Becca Hudson, who was diagnosed with at age 14. “My was below the first percentile for my age.”

Trying out for cheerleading, 14-year-old Becca was pulled when testing found something amiss with her blood work. She had very low counts of platelets, red cells, and white cells. Her doctor called later that day and said she should be admitted that night to Boston Children’s Hospital.

A bit long 😪

Anyone can have a Mastodon server. People turned their backs on Tom, whose Myspace was the best space. Zuckerberg copied both Tom and the Twins. I rejoined Myspace after Facebook started harrassing my account because of the Virality Project because I questioned the popular vaccines, and told people how long it took to create an effective vaccine, and the effectiveness of the BCG vaccine I took as an infant. They silenced me.

In this group even before Musk paid for Twitter I posted about Mastodon, an open source Twitter option, and I still will pay for a blue tick. I won’t pay for anything Zuckerberg does what Mastodon already did, and people line up like sheep, yet… More.


Mastodon: @[email protected]

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Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to predict molecular properties and narrow down the molecules they need to synthesize and test in the lab.

Researchers from MIT and the MIT-Watson AI Lab have developed a new, unified framework that can simultaneously predict molecular properties and generate new much more efficiently than these popular deep-learning approaches.

To teach a to predict a molecule’s biological or , researchers must show it millions of labeled molecular structures—a process known as training. Due to the expense of discovering and the challenges of hand-labeling millions of structures, large training datasets are often hard to come by, which limits the effectiveness of machine-learning approaches.