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Despite the great progress has been made on device parameters and working mechanism of perovskite‐based memristors, thermal instability under extreme conditions limits their performance, and thermal effect on their resistive switching (RS) characteristics remains unclear. Herein, from the viewpoint of organic/inorganic interfacial interaction in a novel 2D <100>‐oriented perovskite [(TZ‐H)2(PbBr4)]n (TZ = 1H‐1,2,4‐triazole), thermal effect on the RS performance of perovskite‐based memristor is investigated. This FTO/[(TZ‐H)2(PbBr4)]n/Ag memristor can exhibit high thermal tolerance with a working temperature of 170 °C, and the best RS characteristics can be achieved at 140 °C. Mechanistic studies are executed based on X‐ray single structural analysis, powder X‐ray diffraction, UV–Vis, and fluorescence. Before the occurrence of phase change below 140 °C (α‐phase), anisotropic lattice expansion illustrated by the weaker inter‐layer NH···Br hydrogen bond, longer layer–layer distances, more distorted PbBr6 octrahedra, larger optical gap, and quenched fluorescence can be beneficial for the trap‐filled limited process. After phase transformation into β‐phase, the breakage of layer–layer interaction and looser layer–layer packing will inhibit the halogen migration, resulting in more space charge limited conduction characters. The unique thermal enhanced RS performance with status monitored by fluorescent chromism can provide a new paradigm for the development of new memristors with highly environmental tolerance. [ABSTRACT FROM AUTHOR]

Intratympanic injection of gentamicin has proven to be an effective therapy for intractable vestibular dysfunction. However, most studies to date have focused on the cochlea, so little is known about the distribution and uptake of gentamicin by the counterpart of the auditory system, specifically vestibular hair cells (HCs). Here, with a combination of in vivo and in vitro approaches, we used a gentamicin‐Texas Red (GTTR) conjugate to investigate the mechanisms of gentamicin vestibulotoxicity in the developing mammalian utricular HCs. In vivo, GTTR fluorescence was concentrated in the apical cytoplasm and the cellular membrane of neonatal utricular HCs, but scarce in the nucleus of HCs and supporting cells. Quantitative analysis showed the GTTR uptake by striolar HCs was significantly higher than that in the extrastriola. In addition, the GTTR fluorescence intensity in the striola was increased gradually from 1 to 8 days, peaking at 8–9 days postnatally. In vitro, utricle explants were incubated with GTTR and candidate uptake conduits, including mechanotransduction (MET) channels and endocytosis in the HC, were inhibited separately. GTTR uptake by HCs could be inhibited by quinine, a blocker of MET channels, under both normal and stressed conditions. Meanwhile, endocytic inhibition only reduced GTTR uptake in the CoCl2 hypoxia model. In sum, the maturation of MET channels mediated uptake of GTTR into vestibular HCs. Under stressed conditions, MET channels play a pronounced role, manifested by channel‐dependent stress enhanced GTTR permeation, while endocytosis participates in GTTR entry in a more selective manner. [ABSTRACT FROM AUTHOR]

Background: Temporal bone computed tomography (CT) helps diagnose chronic otitis media (COM). However, its interpretation requires training and expertise. Artificial intelligence (AI) can help clinicians evaluate COM through CT scans, but existing models lack transparency and may not fully leverage multidimensional diagnostic information., Objective: We aimed to develop an explainable AI system based on 3D convolutional neural networks (CNNs) for automatic CT-based evaluation of COM., Methods: Temporal bone CT scans were retrospectively obtained from patients operated for COM between December 2015 and July 2021 at 2 independent institutes. A region of interest encompassing the middle ear was automatically segmented, and 3D CNNs were subsequently trained to identify pathological ears and cholesteatoma. An ablation study was performed to refine model architecture. Benchmark tests were conducted against a baseline 2D model and 7 clinical experts. Model performance was measured through cross-validation and external validation. Heat maps, generated using Gradient-Weighted Class Activation Mapping, were used to highlight critical decision-making regions. Finally, the AI system was assessed with a prospective cohort to aid clinicians in preoperative COM assessment., Results: Internal and external data sets contained 1661 and 108 patients (3153 and 211 eligible ears), respectively. The 3D model exhibited decent performance with mean areas under the receiver operating characteristic curves of 0.96 (SD 0.01) and 0.93 (SD 0.01), and mean accuracies of 0.878 (SD 0.017) and 0.843 (SD 0.015), respectively, for detecting pathological ears on the 2 data sets. Similar outcomes were observed for cholesteatoma identification (mean area under the receiver operating characteristic curve 0.85, SD 0.03 and 0.83, SD 0.05; mean accuracies 0.783, SD 0.04 and 0.813, SD 0.033, respectively). The proposed 3D model achieved a commendable balance between performance and network size relative to alternative models. It significantly outperformed the 2D approach in detecting COM (P≤.05) and exhibited a substantial gain in identifying cholesteatoma (P<.001). The model also demonstrated superior diagnostic capabilities over resident fellows and the attending otologist (P<.05), rivaling all senior clinicians in both tasks. The generated heat maps properly highlighted the middle ear and mastoid regions, aligning with human knowledge in interpreting temporal bone CT. The resulting AI system achieved an accuracy of 81.8% in generating preoperative diagnoses for 121 patients and contributed to clinical decision-making in 90.1% cases., Conclusions: We present a 3D CNN model trained to detect pathological changes and identify cholesteatoma via temporal bone CT scans. In both tasks, this model significantly outperforms the baseline 2D approach, achieving levels comparable with or surpassing those of human experts. The model also exhibits decent generalizability and enhanced comprehensibility. This AI system facilitates automatic COM assessment and shows promising viability in real-world clinical settings. These findings underscore AI's potential as a valuable aid for clinicians in COM evaluation., Trial Registration: Chinese Clinical Trial Registry ChiCTR2000036300; https://www.chictr.org.cn/showprojEN.html?proj=58685., (©Binjun Chen, Yike Li, Yu Sun, Haojie Sun, Yanmei Wang, Jihan Lyu, Jiajie Guo, Shunxing Bao, Yushu Cheng, Xun Niu, Lian Yang, Jianghong Xu, Juanmei Yang, Yibo Huang, Fanglu Chi, Bo Liang, Dongdong Ren. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.08.2024.)

Objective: To investigate the technique and efficacy of fully endoscope resection of intralabyrinthine schwannomas (ILS) by transcanal transpromontorial endoscopic approach (TTEA). Study Design: Retrospective case review. Setting: Hospital. Patients: All patients who were affected by ILS, without extension to the internal auditory canal and underwent surgery with TTEA in our hospital in 2020. Intervention(s): Therapeutic. Main Outcome Measure(s): Recovery status, postoperative complications and remaining symptoms after surgery. Results: Three patients were included, all of which underwent gross total resections. The follow-up period was from 10 months to 2 years. No intraoperative and postoperative major complications were observed. There was no facial paralysis or cerebrospinal fluid leakage postoperatively. The hospitalization time of TTEA was 5 days. Three patients' vertigo was relieved after 1 week without receiving vestibular therapy. Only 1 patient complained of transient episodes of vertigo when climbing or holding heavy objects. Conclusions: TTEA has the advantages of clear vision to identify the anatomical structure, enabling complete tumor resection, reduced operation time, and faster postoperative recovery. Level of Evidence: IV., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Hair cells in cochlea and vestibular organs depend on the coordinated cell polarity to perform the normal auditory or balance function. The mouse inner ear is one of the ideal model to study planar cell polarity. In this chapter, we introduce a series of general experimental methods for studying planar cell polarity in the inner ear. The approaches presented here are also applicable to other organs with particular polarity phenotypes., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)