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Resistive switching (RS) devices have evolved as one of the most promising candidates in the memory filed due to their excellent endurance and retention, fast switching speed, and extra‐high storage density capability. However, the coexistence of toxic lead cations and low RS performance have largely limited the application of halide perovskite in nonvolatile memory filed. Herein, the lead‐free all‐inorganic perovskite CsSnBr3 films are synthesized on flexible polyimide (PI) substrates through a one‐step chemical vapor deposition (CVD) method to construct environmentally friendly RS devices. The RS devices with Pt/CsSnBr3/Pt/PI structure exhibit reliable and reproducible bipolar RS characteristics with an ultralow set/reset voltage (≈0.2/−0.15 V) and a high on/off ratio (≈105). Additionally, the RS devices are further tested by robust current–voltage curves under consecutive flexing cycles, exhibiting high mechanical bendability and electrical reliability. This work demonstrates that lead‐free all‐inorganic perovskite CsSnBr3 film is a good candidate as switching media for applications in the next‐generation environmentally friendly RS devices and opens an avenue for future flexible electronics. [ABSTRACT FROM AUTHOR]

The number of flowers is essential for evaluating the growth status of litchi trees and enables researchers to estimate flowering rates and conduct various phenotypic studies, particularly focusing on the information of individual panicles. However, manual counting remains the primary method for quantifying flowers, and there has been insufficient emphasis on the advancement of reliable deep learning methods for estimation and their integration into research. Furthermore, the current density map-based methods are susceptible to background interference. To tackle the challenges of accurately quantifying small and dense male litchi flowers, a framework counting the flowers in panicles is proposed. Firstly, an existing effective algorithm YOLACT++ is utilized to segment individual panicles from images. Secondly, a novel algorithm FlowerNet based on density map regression is proposed to accurately count flowers in each panicle. By employing a multitask learning approach, FlowerNet effectively captures both foreground and background information, thereby overcoming interference from non-target areas during pixel-level regression tasks. It achieves a mean absolute error of 47.71 and a root mean squared error of 61.78 on the flower dataset constructed. Additionally, a regression equation is established using a dataset of inflorescences to examine the application of the algorithm for flower counting. It captures the relationship between the predicted number of flowers by FlowerNet and the manually counted number, resulting in a determination coefficient ( R 2 ) of 0.81. The proposed algorithm shows promise for automated estimation of litchi flowering quantity and can serve as a valuable reference for litchi orchard management during flowering period., Competing Interests: Competing interests: The authors declare that they have no competing interests.

Spinal cord injury (SCI) is one of the most destructive traumatic diseases in human beings. The balance of inflammation in the microenvironment is crucial to the repair process of spinal cord injury. Inflammatory cytokines are direct mediators of local lesion inflammation and affect the prognosis of spinal cord injury to varying degrees. In spinal cord injury models, some inflammatory cytokines are beneficial for spinal cord repair, while others are harmful. A large number of animal studies have shown that local targeted administration can effectively regulate the secretion and delivery of inflammatory cytokines and promote the repair of spinal cord injury. In addition, many clinical studies have shown that drugs can promote the repair of spinal cord injury by regulating the content of inflammatory cytokines. However, topical administration affects only a small portion of inflammatory cytokines. In addition, different individuals have different inflammatory cytokine profiles during spinal cord injury. Therefore, future research should aim to develop a personalized local delivery therapeutic cocktail strategy to effectively and accurately regulate inflammation and obtain substantial functional recovery from spinal cord injury.

Objectives: Resveratrol has been recognized as a potential therapeutic drug in spinal cord injury (SCI). Sirtuin 1 (SIRT1) is vital in the regulation of apoptosis and cell stress response. In this research, our purpose was to explore the mechanisms of resveratrol on neuroprotection and to explore the role of SIRT1., Materials and Methods: We used lipopolysaccharide (LPS) in the VSC4.1 spinal cord neuron cell line to mimic the micro-environment of the injured spinal cord. The apoptosis of VSC4.1 motoneurons was assessed by TUNEL staining, Western blot, and RT-PCR. Immunofluorescence staining was used to observe the expression site of SIRT1, LC3-B, and Beclin-1, and their protein levels were measured by Western blot and RT-PCR., Results: Our results showed that resveratrol inhibits LPS-induced apoptosis in VSC4.1 motoneurons. Levels of LC3-B, beclin-1, and SIRT1 indicated a significant increase after resveratrol treatment. But, if autophagy was inhibited, apoptosis in VSC4.1 motoneurons significantly increased. When the cells were treated with EX527, a SIRT1 inhibitor, the protein contents of LC3-B and Beclin-1 were suppressed., Conclusion: Resveratrol inhibits apoptosis through promoting autophagy in VSC4.1 motoneurons. SIRT1 was involved in autophagy activated by resveratrol in VSC4.1 motoneurons.