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Background: Tanshinone IIA (TSIIA) is an element of the effective ingredients of Salvia miltiorrhiza Bunge (Labiatae), exhibits a significant therapeutic effect in brain neuroprotection. The focus of this study was the examination of synaptic plasticity of in Mg2+-free-induced epileptic hippocampus neurons and how TSIIA protects against it., Methods: The purity of the primary hippocampal neurons extracted from Sprague Dawley rats was assessed within 24 hours by microtubule-associated protein (MAP2) immunofluorescence staining. A hippocampal neuron model for Mg2+-free-induced spontaneous recurrent epileptiform discharge was developed, five experimental groups were then randomized: blank (Blank), model (Model), TSIIA (TSIIA, 20 µM), LY294002 (LY294002, 25 µM), and TSIIA+LY294002 (TSIIA+LY294002, 20 µM+25 µM). FIJI software was used to examine variations of neurite complexity, total length of hippocampal neurons, number of primary dendrites and density of dendritic spines. Developmental regulation brain protein (Drebrin) and brain-derived neurotrophic factor (BDNF) expression was evaluated using immunofluorescence staining and the relative expression of phospho-protein kinase B (p-Akt)/Akt, BDNF, synaptophysin (SYN) and postsynaptic density 95 (PSD-95) determined by Western blot., Results: In contrast to the model group, TSIIA drastically reduced damage to synaptic plasticity of hippocampal neurons caused by epilepsy ( p < 0.05). The TSIIA group showed a significant increase in the relative expression of PSD-95, SYN, BDNF, and p-Akt/Akt ( p < 0.01)., Conclusions: TSIIA was effective in reducing harm to the synaptic plasticity of hippocampal neurons induced by persistent status epilepticus, with the possible mechanism being regulation of the phosphatidylinositol 3-kinase 56 (PI3K)/Akt signaling pathway., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s). Published by IMR Press.)

Renewable energy generation has become the general trend with increasing environmental problems. However, the instability of renewable energy generation and the diversification of user demand are highlighted and the optimization of energy scheduling has become the key to solve the problem. This study introduces an energy scheduling optimization model tailored for building integrated energy systems, encompassing elements like gas turbines, wind and solar modules, ground source heat pumps, electric vehicles, central air-conditioning, and energy storage. The model prioritizes economic efficiency and minimal carbon emissions by first collecting and pre-processing the data for the regional building conformance, and then utilizing an enhanced multi-objective genetic whale algorithm. Evaluations on a regional complex building highlighted the algorithm's robust convergence and stability. The resulting optimized scheduling effectively balances economic and environmental concerns, reducing costs by about 92.896 yuan per day on average and reducing carbon emissions by about 0.091 tons, promoting efficient system operation, reducing costs and mitigating environmental impacts., (© 2024. The Author(s).)