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| http://dx.doi.org/10.7812/TPP/05-098 | DOI Listing |
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Cancers exhibit a remarkable ability to develop resistance to a range of treatments, often resulting in relapse following first-line therapies and significantly worse outcomes for subsequent treatments. While our understanding of the mechanisms and dynamics of the emergence of resistance during cancer therapy continues to advance, many questions remain about which treatment strategies can minimize the probability that resistance will evolve, thereby improving long-term patient outcomes. In this study, we present an evolutionary simulation model of a clonal population of cells that can acquire resistance mutations to one or more treatments.
View Article and Find Full Text PDFEvolutionary biology as a frontier for research on misinformation.
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School of Social and Behavioral Sciences, Arizona State University, Phoenix, AZ, USA.
The field of misinformation studies has experienced a boom of scholarship in recent years. Buoyed by the emergence of information operations surrounding the 2016 election and the rise of so-called "fake news," researchers hailing from fields ranging from philosophy to computer science have taken up the challenge of detecting, analyzing, and theorizing false and misleading information online. In an attempt to understand the spread of misinformation online, researchers have adapted concepts from different disciplines.
View Article and Find Full Text PDFAn Extension to the stress-buffering model: Timing of support across the lifecourse.
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Department of Psychology, Carnegie Mellon University, 4825 Frew St, Suite 354E, Pittsburgh, PA, 15213, USA.
Children and adolescents exposed to severe stressors exhibit poorer health across the lifespan. However, decades of research evaluating the Stress-Buffering model suggests that social support can attenuate stressors' negative impacts. Psychoneuroimmunology research in this area has shifted from asking whether support buffers stress to when and why support would succeed (or fail) to confer protection.
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Proc Natl Acad Sci U S A
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Department of Computer Science, Princeton University, Princeton, NJ 08542.
The widespread adoption of large language models (LLMs) makes it important to recognize their strengths and limitations. We argue that to develop a holistic understanding of these systems, we must consider the problem that they were trained to solve: next-word prediction over Internet text. By recognizing the pressures that this task exerts, we can make predictions about the strategies that LLMs will adopt, allowing us to reason about when they will succeed or fail.
View Article and Find Full Text PDFMetamotivation: The regulation of motivation in self-control.
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Article Synopsis
- Psychological research has primarily focused on how individuals manage their thoughts and behaviors to prioritize long-term goals over immediate rewards.
- There has been less emphasis on understanding how people regulate their motivational states, which is surprising since this plays a key role in self-control dilemmas.
- The concept of "metamotivation" is introduced as a crucial aspect to explore, as it could provide valuable insights into the factors influencing self-control success or failure.
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