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Generative Artificial Intelligence (GAI), such as OpenAI’s ChatGPT, has rapidly emerged as a transformative tool in higher education, offering opportunities to enhance teaching and learning. This paper describes the design and implementation of ChatGPT-integrated curriculum activities, featuring coding learning in psychology and conceptual discussions in physics, and presents the findings of a year-long experimental study in both types of classrooms. Our findings suggest that students generally found ChatGPT easy to use and beneficial to their learning, reporting improved confidence, motivation, and engagement. However, its ability to address individual needs or replace instructors was viewed less favorably. Comparative analyses showed that coding activities in psychology led to higher levels of activity satisfaction and perceived usefulness of ChatGPT compared to the more abstract discussion activities in physics. While graduate students were more enthusiastic about using ChatGPT for skill acquisition than undergraduates, demographic factors such as gender, race, and first-generation college status showed no significant influence on such perceptions. Meanwhile, instructors’ reflections emphasize the importance of thoughtful integration, technical support, and pedagogical balance to maximize GAI’s potential while mitigating its limitations. Recommendations for integrating GAI into teaching practices and future research directions are discussed, contributing to the evolving discourse on GAI’s role in transforming modern classrooms. 

Increasing evidence strongly links neuroinflammation to Alzheimer’s disease (AD) pathogenesis. Peripheral monocytes are crucial components of the human immune system, but their contribution to AD pathogenesis is still largely understudied partially due to limited human models. Here, we introduce human cortical organoid microphysiological systems (hCO-MPSs) to study AD monocyte-mediated neuroinflammation. By culturing doughnut-shape organoids on 3D-printed devices within standard 96-well plates, we generate hCO-MPSs with reduced necrosis, minimized hypoxia, and improved viability. Using these models, we found that monocytes from AD patients exhibit increased infiltration ability, decreased amyloid-β clearance capacity, and stronger inflammatory response than monocytes from age-matched control donors. Moreover, we observed that AD monocytes induce pro-inflammatory effects such as elevated astrocyte activation and neuronal apoptosis. Furthermore, the marked increase in IL1B and CCL3 expression underscores their pivotal role in AD monocyte-mediated neuroinflammation. Our findings provide insight into understanding monocytes’ role in AD pathogenesis, and our lab-compatible MPS models may offer a promising way for studying various neuroinflammatory diseases. 

Alzheimer's disease (AD) is a progressive and neurodegenerative disease, predominantly causing dementia. Despite increasing clinical evidence suggesting the involvement of peripheral immune cells such as monocytes in AD pathology, the dynamic penetration and infiltration of monocytes crossing blood–brain barrier (BBB) and inducing neuroinflammation is largely understudied in an AD brain. Herein, we engineer BBB-like microphysiological system (BBB-MPS) models for recapitulating the dynamic penetration and infiltration of monocytes in an AD patient's brain. Each BBB-MPS model can be engineered by integrating a functional BBB-like structure on a human cortical organoid using a 3D-printed device within a well of a plate. By coculturing these BBB-MPS models with monocytes from AD patients and age-matched healthy donors, we found that AD monocytes exhibit significantly greater BBB penetration and brain infiltration compared to age-matched control monocytes. Moreover, we also tested the interventions including Minocycline and Bindarit, and found they can effectively inhibit AD monocyte infiltration, subsequently reducing neuroinflammation and neuronal apoptosis. We believe these scalable and user-friendly BBB-MPS models may hold promising potential in modeling and advancing therapeutics for neurodegenerative and neuroinflammatory diseases. 

We integrate quasi-liquid surfaces, nanovibration technology, and capacitive sensing to create an energy-efficient system for detecting and removing frost and ice without complete melting. 

• Drought-induced xylem embolism is a primary cause of plant mortality. Although ~70% of cycads are threatened by extinction and extant cycads diversified during a period of increasing aridification, the vulnerability of cycads to embolism spread has been overlooked. • We quantified the vulnerability to drought-induced embolism, pressure-volume curves, in situ water potentials, and a suite of xylem anatomical traits of leaf pinnae and rachises for 20 cycad species. We tested whether anatomical traits were linked to hydraulic safety in cycads. • Compared to other major vascular plant clades, cycads exhibited similar embolism resistance to angiosperms and pteridophytes but were more vulnerable to embolism than non-cycad gymnosperms. All 20 cycads had both tracheids and vessels, the proportions of which were unrelated to embolism resistance. Only vessel pit membrane fraction was positively correlated to embolism resistance, contrary to angiosperms. Water potential at turgor loss was significantly correlated to embolism resistance among cycads. • Our results show that cycads exhibit low resistance to xylem embolism and that xylem anatomical traits–particularly vessels–may influence embolism resistance together with tracheids. This study highlights the importance of understanding the mechanisms of drought resistance in evolutionarily unique and threatened lineages like the cycads. 

Abstract The synthesis and characterization of two new porphyrin-based porous organic polymers (POPs) via Sonogashira cross-coupling reaction and leverage the two obtained POPs is reported for the fabrication of electrochemical aptasensors to detect kanamycin at an ultratrace level. The resultant electrochemical aptasensor demonstrates a high linear relationship with the logarithmic value of kanamycin concentration in the range 5 × 10⁻⁵–5 μg/L with the limit of detection of 17.6 pg/L or 36.3 fM. During the analysis of real samples from milk and river, a relative standard deviation of less than 4.39%, and good recovery values in the range 97.0–105% were obtained. Graphical Abstract