Mechanisms

By Jianrong Qiu, Yang Li, Yongchao Jia. 2019

Ovatodiolide, a macrocyclic diterpenoid isolated from the traditional Chinese medicinal herb Anisomeles indica , exhibits diverse pharmacological activities in recent research. Its antitumor effects involve modulation of key signaling pathways (e. g., NF-κ B/MMP ‑ 9, JAK2/STAT3, PI3K/AKT/mTOR, and Wnt/ β - catenin) and effective targeting of cancer stem cells. For anti-fibrotic activity, it suppresses the TGF-β pathway and directly inhibits glucose-6-phosphate dehydrogenase. Additionally, it demonstrates antiviral, antibacterial, and anti-inflammatory activities. This review comprehensively summarizes current knowledge on ovatodiolide, including its discovery, synthesis, pharmacological actions, and underlying molecular mechanisms against target diseases. A deeper understanding of ovatodiolide ʼ s multifaceted pharmacological activities and mechanisms of action will accelerate its clinical translation as a therapeutic agent.

Citations in the corpus

• Recurrent World Models Facilitate Policy Evolution (2018, neutral): “An exciting research direction is to look at ways to incorporate artificial curiosity and intrinsic motivation [61, 64, 77, 80, 81] and information seeking [23, 86] abilities in an agent to encourage novel exploration [47].”
• World Models (2018, neutral): “…at ways to incorporate artificial curiosity and intrinsic motivation (Schmidhu-ber, 2010; 2006; 1991b; Pathak et al., 2017; Oudeyer et al., 2007) and information seeking (Schmidhuber et al., 1994; Gottlieb et al., 2013) abilities in an agent to encourage novel exploration (Lehman & Stanley, 2011).”
• Learning to Play with Intrinsically-Motivated Self-Aware Agents (2018, neutral): “Oudeyer and colleagues [14, 33, 34] have explored formalizations of curiosity as maximizing prediction-ability change, showing the emergence of interesting realistic cognitive behaviors from simple intrinsic motivations.”
• Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies. (2016, unknown): “However, these theories do not provide an account of certain spontaneous exploration behaviors which increase uncertainty (Gottlieb et al., 2013).”
• What do we learn about development from baby robots? (2015, unknown): “Neuroscientists are only beginning to identify brain circuits involved in spontaneous exploratory behaviors (Gottlieb et al., 2013).”
• Process Account of Curiosity and Interest: A Reward-Learning Perspective (2018, unknown): “Indeed, in the field of cognitive science, researchers prefer to using the term “information seeking” rather than curiosity when describing curiosity-related phenomena (e.g., Gottlieb et al. 2013).”
• The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration (2014, unknown): “ORIGINAL RESEARCH ARTICLE published: 14 October 2014 doi: 10.3389/fnins.2014.00317 The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration”
• World Discovery Models (2019, unknown): “…& Csikszentmihalyi, 1992), neuroscience (Dayan & Balleine, 2002; Kakade & Dayan, 2002; Horvitz, 2000) and machine learning (Oudeyer & Kaplan, 2008; Gottlieb et al., 2013; Schmidhuber, 1991a) that an agent maximising a simple intrinsic reward based on patterns that are both novel and learnable…”
• Interest development, self-related information processing, and practice (2021, unknown): “…of its beneficial outcomes: the way in which the brain processes self-related information (the links between individuals’ personal experience and content to be learned, e.g., Hidi et al., 2017, 2019), how it activates reward circuitry (e.g., Gottlieb et al., 2013), and makes interest rewarding.”
• Curiosity-Driven Development of Tool Use Precursors: a Computational Model (2016, unknown): “…has considered a curiosity-driven learning mechanism where the learner actively engages in sensorimotor activities that provide high learning progress, avoiding situations that are too easy or too difficult and progressively focusing on activities of increasing complexity (Gottlieb et al., 2013).”
• Self-organization of early vocal development in infants and machines: the role of intrinsic motivation (2014, unknown): “Speech acquisition is such a complex task that intrinsic motivation could be a crucial component to make it possible in the infant’s first year of life.”
• Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning (2017, unknown): “…of computational and robotic models of intrinsically motivated exploration and learning in infants have been developed (Oudeyer and Kaplan, 2007; Baldassarre and Mirolli, 2013; Bazhydai et al., 2020), opening new theoretical perspectives in neuroscience and psychology (Gottlieb et al., 2013).”
• Electronic skins and machine learning for intelligent soft robots (2020, unknown): “It is currently conjectured that human exploration is driven by a combination of extrinsic and intrinsic reward variables ( 97 ).”