Comprehensive mapping of pathogen populations points way to precision treatments to improve outcomes.
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Targeted Therapy Reduces Immunotherapeutic Neurotoxicity
Immunotherapy is a form of cancer treatment that harnesses the immune system to recognize and target the tumor. In most cancers, the immune system fails to detect the rapid proliferation of tumor cells. Lack of immune cell detection is due to the tumor polarizing or reprogramming immune cells to promote cancer progression and suppress the immune system. This is done through variety of ways including the release of proteins or cytokines that direct immune cell development and function. Current immunotherapies target these polarized immune cells to switch them back toward an anti-tumor function. Although there are many ways to redirect immune cells to attack cancer, immunotherapies maintain limited efficacy due to the immunosuppressive mechanisms within the tumor microenvironment (TME). In addition, heightened toxicity associated with immunotherapy also pose challenges when prescribing treatments to patients.
One immunotherapy that has demonstrated significant promise in cancer patients is chimeric antigen receptor (CAR) T cells are immune cells within the body that are responsible for killing or lysing invading pathogens, including cancer. The immune system orchestrates a response by employing T cells to recognize an infection, in healthy individuals. In the context of cancer, T cells cannot recognize that the tumor is deleterious to the body. Therefore, CAR T cells are generated to reprogram the cell’s ability to recognize and lyse the tumor. CAR T cell therapy takes the patient’s T cells and engineers them to target specific surface markers on the tumor. They are then grown in a dish and expanded before being intravenously reinfused in the patient. CAR T cell therapy is commonly associated with lymphoma, but unfortunately neurotoxicity can be an adverse side effect which limits efficacy.
Secrets from the Algorithm: Google Search’s Internal Engineering Documentation Has Leaked
Learn what you always wish you knew about Google’s algorithms.
CISA Alerts Federal Agencies to Patch Actively Exploited Linux Kernel Flaw
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Thursday added a security flaw impacting the Linux kernel to the Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation.
Tracked as CVE-2024–1086 (CVSS score: 7.8), the high-severity issue relates to a use-after-free bug in the netfilter component that permits a local attacker to elevate privileges from a regular user to root and possibly execute arbitrary code.
“Linux kernel contains a use-after-free vulnerability in the netfilter: nf_tables component that allows an attacker to achieve local privilege escalation,” CISA said.
Cyber Espionage Alert: LilacSquid Targets IT, Energy, and Pharma Sectors
A previously undocumented cyber espionage-focused threat actor named LilacSquid has been linked to targeted attacks spanning various sectors in the United States (U.S.), Europe, and Asia as part of a data theft campaign since at least 2021.
“The campaign is geared toward establishing long-term access to compromised victim organizations to enable LilacSquid to siphon data of interest to attacker-controlled servers,” Cisco Talos researcher Asheer Malhotra said in a new technical report published today.
Targets include information technology organizations building software for the research and industrial sectors in the U.S, energy companies in Europe, and the pharmaceutical sector in Asia, indicating a broad victimology footprint.
Data-driven model generates natural human motions for virtual avatars
Humans can innately perform a wide range of movements, as this allows them to best tackle various tasks in their day-to-day life. Automatically reproducing these motions in virtual avatars and 3D animated human-like characters could be highly advantageous for many applications, ranging from metaverse spaces to digital entertainment, AI interfaces and robotics.
Researchers at Max Planck Institute for Intelligent Systems and ETH Zurich recently developed WANDR, a new model that can generate natural human motions for avatars. This model, to be introduced in a paper presented at the Conference on Computer Vision and Pattern Recognition (CVPR 2024) in June, unifies different data sources under a single model to attain more realistic motions in 3D humanoid characters. The paper is also posted to the arXiv preprint server.
“At a high-level, our research aims at figuring out what it takes to create virtual humans able to behave like us,” Markos Diomataris, first author of the paper, told Tech Xplore. “This essentially means learning to reason about the world, how to move in it, setting goals and trying to achieve them.