TY - JOUR
AB - Glioblastoma is the most malignant cancer in the brain and currently incurable. It is urgent to identify effective targets for this lethal disease. Inhibition of such targets should suppress the growth of cancer cells and, ideally also precancerous cells for early prevention, but minimally affect their normal counterparts. Using genetic mouse models with neural stem cells (NSCs) or oligodendrocyte precursor cells (OPCs) as the cells‐of‐origin/mutation, it is shown that the susceptibility of cells within the development hierarchy of glioma to the knockout of insulin‐like growth factor I receptor (IGF1R) is determined not only by their oncogenic states, but also by their cell identities/states. Knockout of IGF1R selectively disrupts the growth of mutant and transformed, but not normal OPCs, or NSCs. The desirable outcome of IGF1R knockout on cell growth requires the mutant cells to commit to the OPC identity regardless of its development hierarchical status. At the molecular level, oncogenic mutations reprogram the cellular network of OPCs and force them to depend more on IGF1R for their growth. A new‐generation brain‐penetrable, orally available IGF1R inhibitor harnessing tumor OPCs in the brain is also developed. The findings reveal the cellular window of IGF1R targeting and establish IGF1R as an effective target for the prevention and treatment of glioblastoma.
AU - Tian, Anhao
AU - Kang, Bo
AU - Li, Baizhou
AU - Qiu, Biying
AU - Jiang, Wenhong
AU - Shao, Fangjie
AU - Gao, Qingqing
AU - Liu, Rui
AU - Cai, Chengwei
AU - Jing, Rui
AU - Wang, Wei
AU - Chen, Pengxiang
AU - Liang, Qinghui
AU - Bao, Lili
AU - Man, Jianghong
AU - Wang, Yan
AU - Shi, Yu
AU - Li, Jin
AU - Yang, Minmin
AU - Wang, Lisha
AU - Zhang, Jianmin
AU - Hippenmeyer, Simon
AU - Zhu, Junming
AU - Bian, Xiuwu
AU - Wang, Ying‐Jie
AU - Liu, Chong
ID - 8592
IS - 21
JF - Advanced Science
KW - General Engineering
KW - General Physics and Astronomy
KW - General Materials Science
KW - Medicine (miscellaneous)
KW - General Chemical Engineering
KW - Biochemistry
KW - Genetics and Molecular Biology (miscellaneous)
SN - 2198-3844
TI - Oncogenic state and cell identity combinatorially dictate the susceptibility of cells within glioma development hierarchy to IGF1R targeting
VL - 7
ER -
TY - JOUR
AB - Error analysis and data visualization of positive COVID-19 cases in 27 countries have been performed up to August 8, 2020. This survey generally observes a progression from early exponential growth transitioning to an intermediate power-law growth phase, as recently suggested by Ziff and Ziff. The occurrence of logistic growth after the power-law phase with lockdowns or social distancing may be described as an effect of avoidance. A visualization of the power-law growth exponent over short time windows is qualitatively similar to the Bhatia visualization for pandemic progression. Visualizations like these can indicate the onset of second waves and may influence social policy.
AU - Merrin, Jack
ID - 8597
IS - 6
JF - Physical Biology
TI - Differences in power law growth over time and indicators of COVID-19 pandemic progression worldwide
VL - 17
ER -
TY - CONF
AB - A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an "auction" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and study their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We show how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games.
AU - Avni, Guy
AU - Henzinger, Thomas A
ID - 8599
SN - 18688969
T2 - 31st International Conference on Concurrency Theory
TI - A survey of bidding games on graphs
VL - 171
ER -
TY - CONF
AB - A vector addition system with states (VASS) consists of a finite set of states and counters. A transition changes the current state to the next state, and every counter is either incremented, or decremented, or left unchanged. A state and value for each counter is a configuration; and a computation is an infinite sequence of configurations with transitions between successive configurations. A probabilistic VASS consists of a VASS along with a probability distribution over the transitions for each state. Qualitative properties such as state and configuration reachability have been widely studied for VASS. In this work we consider multi-dimensional long-run average objectives for VASS and probabilistic VASS. For a counter, the cost of a configuration is the value of the counter; and the long-run average value of a computation for the counter is the long-run average of the costs of the configurations in the computation. The multi-dimensional long-run average problem given a VASS and a threshold value for each counter, asks whether there is a computation such that for each counter the long-run average value for the counter does not exceed the respective threshold. For probabilistic VASS, instead of the existence of a computation, we consider whether the expected long-run average value for each counter does not exceed the respective threshold. Our main results are as follows: we show that the multi-dimensional long-run average problem (a) is NP-complete for integer-valued VASS; (b) is undecidable for natural-valued VASS (i.e., nonnegative counters); and (c) can be solved in polynomial time for probabilistic integer-valued VASS, and probabilistic natural-valued VASS when all computations are non-terminating.
AU - Chatterjee, Krishnendu
AU - Henzinger, Thomas A
AU - Otop, Jan
ID - 8600
SN - 18688969
T2 - 31st International Conference on Concurrency Theory
TI - Multi-dimensional long-run average problems for vector addition systems with states
VL - 171
ER -
TY - JOUR
AB - We consider large non-Hermitian real or complex random matrices X with independent, identically distributed centred entries. We prove that their local eigenvalue statistics near the spectral edge, the unit circle, coincide with those of the Ginibre ensemble, i.e. when the matrix elements of X are Gaussian. This result is the non-Hermitian counterpart of the universality of the Tracy–Widom distribution at the spectral edges of the Wigner ensemble.
AU - Cipolloni, Giorgio
AU - Erdös, László
AU - Schröder, Dominik J
ID - 8601
JF - Probability Theory and Related Fields
SN - 01788051
TI - Edge universality for non-Hermitian random matrices
ER -