Lifeboat Foundation

The Wistar Institute’s David B. Weiner and collaborators have engineered novel monoclonal antibodies that engage natural killer (NK) cells through a unique surface receptor that activates the immune system to fight against cancer.

In their publication titled, “Siglec-7 glyco-immune binding MAbs or NK cell engager biologics induce potent anti-tumor immunity against ovarian cancers,” published in Science Advances, the team demonstrates the preclinical feasibility of utilizing these new cancer immunotherapeutic approaches against diverse ovarian cancer types, including treatment-resistant and refractory ovarian cancers—alone or in combination with checkpoint inhibitor treatment.

The research started as a collaboration between Wistar’s Drs. Weiner and Mohamed Abdel-Mohsen, who were exploring the development of new glyco-signaling biologic tools that may be important in the fight against cancer.

Atlassian has discovered yet another critical vulnerability in its Confluence Data Center and Server collaboration and project management platform, and it’s urging customers to patch the problem immediately. The latest advisory by Atlassian describes CVE-2023–22518 as an improper authorization vulnerability that affects all versions of the on-premises versions of Confluence.

It is the second critical vulnerability reported by Atlassian in a month, tied to its widely used Confluence Data Center and Server platform and among numerous security issues from the company during the past year. The previous bulletin (CVE-2023–22515) revealed a vulnerability that could allow an attacker to create unauthorized Confluence administrator accounts, thereby gaining access to instances. That vulnerability had a severity level of 10 and was discovered initially by some customers who reported they may have been breached by it.

To date, Atlassian is not aware of any active exploits of the newest vulnerability, which has a severity level of 9.1., though the company issued a statement encouraging customers to apply the patch. “We have discovered that Confluence Data Center and Server customers are vulnerable to significant data loss if exploited by an unauthenticated attacker,” Atlassian CISO Bala Sathiamurthy warned in a statement. “Customers must take immediate action to protect their instances.”

Lung cancer is the third most common cancer in the U.S. and there have been more than 235,000 new cases of lung cancer in 2021. While this figure is significant, the rate of new lung and bronchus cancer cases is decreasing, in part because more people have stopped smoking. This trend, along with innovations in early detection and treatment, is also reducing the number of lung cancer deaths.

Dr. Robert Taylor Ripley, associate professor of surgery in the Division of General Thoracic Surgery, is an expert in mesothelioma and thoracic surgical oncology. In the following Q&A, he discusses common causes of lung cancer, risks and the latest treatments.

Q: What are the most common causes of lung cancer? A: Smoking cigarettes is the most common cause, but others include secondhand smoke and environmental inhalants. We see a fair number of patients with lung cancer who have never smoked. Exposure to diesel exhaust or other chemicals may also cause lung cancer in some non-smokers.

How much would it cost to hack your phone? The best guess for an iPhone is between $0 and $65,000 — and that price mainly depends on you. If you skipped a really important security update, the cost is closer to $0.

Say you were up to date. That $65,000 figure is an upper cost of exploiting the median individual — switch to an Android, a Mac, or a PC and it could get a lot lower. Apple has invested enormous resources in hardening the iPhone. The asking price for an individual exploit, rather than as a service, can go as high as $8 million. Compare that to the cost of an exploit of a PDF reader like Adobe Acrobat — notoriously riddled with security vulnerabilities — which according to this TrendMicro research report (PDF) is $250 and up.

Switch from targeting a specific person to targeting any of the thousands of people at a large company and there are myriad ways in. An attacker only needs to find the cheapest one.

How did we get here? Not just we humans, scrabbling about on a pale blue dot, hurtling around a star, hurtling around a supermassive black hole, hurtling through the local cluster. But how did the dot get here, and the star, and the black hole, and the cluster?

How did the incomprehensibly immense everything of it all get to where it is now, from an unimaginable nothing, billions of years ago?

That’s it, really, the question of questions. And, with the largest project of its kind to date, astronomers are attempting to find answers – by conducting computer simulations of the entire Universe.

The large blue warning signs read “Video recording for fall detection and prevention” on the third-floor dementia care unit of the Trousdale, a private-pay senior living community in Silicon Valley where a studio starts from about $7,000 per month.

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Researchers from Tsinghua University, China, have developed an all-analog photoelectronic chip that combines optical and electronic computing to achieve ultrafast and highly energy-efficient computer vision processing, surpassing digital processors.

Computer vision is an ever-evolving field of artificial intelligence focused on enabling machines to interpret and understand visual information from the world, similar to how humans perceive and process images and videos.

It involves tasks such as image recognition, object detection, and scene understanding. This is done by converting analog signals from the environment into digital signals for processing by neural networks, enabling machines to make sense of visual information. However, this analog-to-digital conversion consumes significant time and energy, limiting the speed and efficiency of practical neural network implementations.

For the first time, a physical neural network has successfully been shown to learn and remember “on the fly,” in a way inspired by and similar to how the brain’s neurons work.

The result opens a pathway for developing efficient and low-energy machine intelligence for more complex, real-world learning and memory tasks.

Published today in Nature Communications, the research is a collaboration between scientists at the University of Sydney and University of California at Los Angeles.