HIF-1 inactivation empowers HIF-2 to drive hypoxia adaptation in aggressive forms of medulloblastoma.

Medulloblastoma (MB) is the most prevalent brain cancer in children. Four subgroups of MB have been identified; of these, Group 3 is the most metastatic. Its genetics and biology remain less clear than the other groups, and it has a poor prognosis and few effective treatments available.

The marine-derived HIF-1α inhibitor, Yardenone 2, reduces prostate cancer cell proliferation by targeting HIF-1 target genes.

Background: Prostate cancer (PCa) ranks as the second most prevalent cancer in men, with advanced stages posing significant treatment challenges. Given its solid tumor nature, PCa is highly susceptible to hypoxia, a condition associated with resistance to radiation and chemotherapy, metastasis, and unfavorable patient outcomes. Hypoxia-inducible factors (HIFs) play a pivotal role in cancer cell adaptation to hypoxic environments, contributing to treatment resistance.

The mitochondrial NADH shuttle system is a targetable vulnerability for Group 3 medulloblastoma in a hypoxic microenvironment.

Medulloblastoma is a cancerous brain tumor that affects mostly children. Among the four groups defined by molecular characteristics, Group 3, the least well characterized, is also the least favorable, with a survival rate of 50%. Current treatments, based on surgery, radiotherapy, and chemotherapy, are not adequate and the lack of understanding of the different molecular features of Group 3 tumor cells makes the development of effective therapies challenging.

HIF-1 inactivation empowers HIF-2 to drive hypoxia adaptation in aggressive forms of medulloblastoma.

Medulloblastoma (MB) is the most prevalent brain cancer in children. Four subgroups of MB have been identified; of these, Group 3 is the most metastatic. Its genetics and biology remain less clear than the other groups, and it has a poor prognosis and few effective treatments available.

A Cognitive Control-Inspired Approach to Object Tracking.

Under a tracking framework, the definition of the target state is the basic step for automatic understanding of dynamic scenes. More specifically, far object tracking raises challenges related to the potentially abrupt size changes of the targets as they approach the sensor. If not handled, size changes can introduce heavy issues in data association and position estimation.