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Exploring the potential of LLM to enhance teaching plans through teaching simulation
The introduction of large language models (LLMs) may change future pedagogical practices. Current research mainly focuses on the use of LLMs to tutor students, while the exploration of LLMs’ potential to assist teachers is limited. Taking high school mathematics as an example, we propose a method that utilizes LLMs to enhance the quality of teaching plans through guiding the LLM to simulate teacher-student interactions, generate teaching reflections, and subsequently direct the LLM to refine the teaching plan by integrating these teaching process and reflections. Human evaluation results show that this method significantly elevates the quality of the original teaching plans generated directly by LLM. The improved teaching plans are comparable to high-quality ones crafted by human teachers across various assessment dimensions and knowledge modules. This approach provides a pre-class rehearsal simulation and ideas for teaching plan refinement, offering practical evidence for the widespread application of LLMs in teaching preparation.
Urban growth strategy in Greater Sydney leads to unintended social and environmental challenges
Cities have advanced in terms of economic and social status over the past five decades, improving the living conditions of hundreds of millions of people. However, population growth and urban expansion have put pressure on social and environmental conditions. This study examines urban policymakers’ perceptions about causal relationships in the urban system as revealed in urban planning reports. Here we analyzed 500 pages from published urban plans of Greater Sydney between 1968 and 2018 and coded the text into causal maps. The findings show that policymakers adopted a dominant urban development strategy over the past 50 years to pursue economic and public infrastructure growth. Over time, this growth strategy resulted in a number of social and environmental challenges that negatively impacted societal well-being. Although policymakers eventually recognized the seriousness of social and environmental challenges, they never attempted to fundamentally change the dominant growth strategy. Instead, policymakers sought to address the challenges (that is, symptoms) by responding to each issue piecemeal.
The spinal cord injury (SCI) peer support evaluation tool: the development of a tool to assess outcomes of peer support programs within SCI community-based organizations
Guided by the 4-step process outlined in the Consensus-based Standards for the selection of health Measurement INstruments (COSMIN) guideline, multiple methodologies were used: Delphi, literature reviews, ratings with consensus, think-aloud, and test-retest.
Modeling critical dosing strategies for stromal-induced resistance to cancer therapy
Complex interactions between stromal cells, tumor cells and therapies can influence environmental factors that in turn impact anticancer treatment efficacy. Disentangling these phenomena is critical for understanding treatment response and designing effective dosing strategies. We propose a mathematical model for a common tumor-stromal interaction motif where stromal cells secrete factors that promote drug resistance. We demonstrate that the presence of this interaction modulates the therapeutic dose window of efficacy and can lead to nonmonotonic treatment response. We consider combination strategies that target stromal cells and their secretome, and identify strategies that constrain drug concentrations within the efficacious window for long-term response. We explore an experimental dataset from colorectal cancer cells treated with anti-EGFR targeting therapy, cetuximab, where cancer-associated fibroblasts increase epidermal growth factor secretion under treatment. We apply our general approach to identify a critical drug concentration threshold and study effective dosing regimens for single-drug and combination therapies.
Energy metabolism in health and diseases
Energy metabolism is indispensable for sustaining physiological functions in living organisms and assumes a pivotal role across physiological and pathological conditions. This review provides an extensive overview of advancements in energy metabolism research, elucidating critical pathways such as glycolysis, oxidative phosphorylation, fatty acid metabolism, and amino acid metabolism, along with their intricate regulatory mechanisms. The homeostatic balance of these processes is crucial; however, in pathological states such as neurodegenerative diseases, autoimmune disorders, and cancer, extensive metabolic reprogramming occurs, resulting in impaired glucose metabolism and mitochondrial dysfunction, which accelerate disease progression. Recent investigations into key regulatory pathways, including mechanistic target of rapamycin, sirtuins, and adenosine monophosphate-activated protein kinase, have considerably deepened our understanding of metabolic dysregulation and opened new avenues for therapeutic innovation. Emerging technologies, such as fluorescent probes, nano-biomaterials, and metabolomic analyses, promise substantial improvements in diagnostic precision. This review critically examines recent advancements and ongoing challenges in metabolism research, emphasizing its potential for precision diagnostics and personalized therapeutic interventions. Future studies should prioritize unraveling the regulatory mechanisms of energy metabolism and the dynamics of intercellular energy interactions. Integrating cutting-edge gene-editing technologies and multi-omics approaches, the development of multi-target pharmaceuticals in synergy with existing therapies such as immunotherapy and dietary interventions could enhance therapeutic efficacy. Personalized metabolic analysis is indispensable for crafting tailored treatment protocols, ultimately providing more accurate medical solutions for patients. This review aims to deepen the understanding and improve the application of energy metabolism to drive innovative diagnostic and therapeutic strategies.
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