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Researchers at Baylor College of Medicine have developed a new compound called d16 that can reduce tumor growth and overcome therapeutic resistance in mutant p53-bearing cancers in the lab. The findings, published in the journal Cancer Research Communications, a journal of the American Association for Cancer Research, open opportunities for new combination therapies for these difficult-to-treat cancers.

“One of the most common alterations in many human cancers is mutations in p53, a gene that normally provides one of the most powerful shields against tumor growth,” said first author, Dr. Helena Folly-Kossi, a postdoctoral associate in Dr. Weei-Chin Lin’s lab at Baylor. “Mutations that alter the normal function of p53 can promote tumor growth, cancer progression and resistance to therapy, which are associated with poor prognosis. It is important to understand how p53 mutations help cancer grow to develop therapies to counteract their effects.”

Studying how to target p53 mutations that promote cancer growth has been difficult. “One of the challenges has been to develop drugs that act on mutant p53 directly. Some of these drugs are under development, but they appear to be toxic,” said Lin, professor of medicine-hematology and oncology and of molecular and cellular biology. He also is a member of Baylor’s Dan L Duncan Comprehensive Cancer Center and the corresponding author of the work.

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Set in Salem, Oregon, “RoboFab”, Agility Robotics’ 70,000-square-foot robot factory is slated to open later this year and manufacture the company’s bipedal robot Digit.

MENLO PARK, California, Sept 28 (Reuters) — Meta Platforms (META.O) used public Facebook and Instagram posts to train parts of its new Meta AI virtual assistant, but excluded private posts shared only with family and friends in an effort to respect consumers’ privacy, the company’s top policy executive told Reuters in an interview.

Meta also did not use private chats on its messaging services as training data for the model and took steps to filter private details from public datasets used for training, said Meta President of Global Affairs Nick Clegg, speaking on the sidelines of the company’s annual Connect conference this week.

“We’ve tried to exclude datasets that have a heavy preponderance of personal information,” Clegg said, adding that the “vast majority” of the data used by Meta for training was publicly available.

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CHAPTERS
00:00 Required Technologies.
01:42 The Processes of Uploading a Mind.
03:32 Positive Impacts On Society.
05:34 When Will It Become Possible?
05:53 Is Digital Immortality Potentially Dangerous?

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Meet AV1, the mini robot that goes to the zoo or school for sick children who can’t.

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The animal looked and barked like a dog—albeit one with long, pointed, foxlike ears—but it also climbed bushes, a behavior more typical of the local Pampas fox, and it refused common dog food, preferring to eat rats.

Caretakers began to wonder if it might be a hybrid—a mixture of domestic dog and some local wild canid. They contacted geneticists Thales Renato Ochotorena de Freitas from the Universidade Federal do Rio Grande do Sul and Rafael Kretschmer from the Universidade Federal de Pelotas who, last month, published a study confirming the animal was the world’s first documented fox-dog. The finding excited and intrigued experts in animal genetics.

“What a strange hybrid beast!” wrote Roland Kays, a biologist with North Carolina State University and the North Carolina Museum of Natural Sciences, on X (formerly Twitter), alongside a photo of the creature and link to the study.

In cybersecurity, “threat data feeds” and “threat intelligence” are often used interchangeably. They are, however, quite different. To make matters worse, the term “threat intelligence” has been co-opted and watered down by vendors, making it even more difficult to define the difference between threat data feeds and threat intelligence.

An easy, and accessible, way to tell the difference is to think about weather forecasts. National TV news shows present a forecast for the entire country. You might get some useful information from this, but usually you just get an idea of what the weather is like nationwide. Local weather, however, drills down into the expected conditions for your specific area — not only temperature and weather, but also wind speed, barometric pressure, times for weather changes, and so on. You can use this information to plan out your actions for the next few days.

Using the weather forecast analogy, threat data feeds provide a high-level view of the security landscape. For example, it is useful to know that there is a vulnerability in a specific type of software, but it can be relatively trivial if that software is not in use at your organization. Likewise, knowing which threat groups are active is useful information, but how do you know if they are targeting your sector or organization and what processes and tools they are using?

In the age of AI, computer science is no longer the safe major.

WASHINGTON, Sept 27 (Reuters) — The founder of Branch Metrics, which developed a method of searching within smartphone apps, told a U.S. antitrust trial on Wednesday how his company struggled to integrate with devices because of steps Google took to block them.

The testimony came during the third week of a more than two-month trial in which the U.S. Justice Department is seeking to show that Alphabet’s Google (GOOGL.O) abused its monopoly of search and some search advertising. Google has said that its business practices were legal.

Google is accused of paying $10 billion a year based on “revenue share agreements” to smartphone makers, wireless carriers and others who agree to make its software the default and maintain its monopoly in search.