Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases worldwide. Therefore, accurate PD screening is crucial for early clinical intervention and treatment. Recent clinical research indicates that changes in pathology, such as the texture and thickness of the retinal layers, can serve as biomarkers for clinical PD diagnosis based on optical coherence tomography (OCT) images. However, the pathological manifestations of PD in the retinal layers are subtle compared to the more salient lesions associated with retinal diseases. METHODS: Inspired by textural edge feature extraction in frequency domain learning, we aim to explore a potential approach to enhance the distinction between the feature distributions in retinal layers of PD cases and healthy controls. In this paper, we introduce a simple yet novel wavelet-based selection and recalibration module to effectively enhance the feature representations of the deep neural network by aggregating the unique clinical properties, such as the retinal layers in each frequency band. We combine this module with the residual block to form a deep network named Wavelet-based Selection and Recalibration Network (WaveSRNet) for automatic PD screening. RESULTS: The extensive experiments on a clinical PD-OCT dataset and two publicly available datasets demonstrate that our approach outperforms state-of-the-art methods. Visualization analysis and ablation studies are conducted to enhance the explainability of WaveSRNet in the decision-making process. CONCLUSIONS: Our results suggest the potential role of the retina as an assessment tool for PD. Visual analysis shows that PD-related elements include not only certain retinal layers but also the location of the fovea in OCT images.

Copper overload exacerbates testicular aging mediated by lncRNA:CR43306 deficiency through ferroptosis in Drosophila.

Testicular aging manifests as impaired spermatogenesis and morphological alterations in Drosophila. Nonetheless, the comprehensive molecular regulatory framework remains largely undisclosed. This investigation illustrates the impact of copper overload on testicular aging and underscores the interplay between copper overload and lncRNA. Copper overload triggers Cuproptosis through the mitochondrial TCA cycle, facilitating intracellular interactions with Ferroptosis, thereby governing testicular aging. Dysfunction of lncRNA:CR43306 also contributes to testicular aging in Drosophila, emphasizing the significance of lncRNA:CR43306 as a novel aging-associated lncRNA. Moreover, copper overload exacerbates spermatid differentiation defects mediated by lncRNA:CR43306 deficiency through oxidative stress, copper, and iron transport. Therapeutically, Ferrostatin-1 and Resveratrol emerge as potential remedies for addressing testicular aging. This study offers perspectives on the regulatory mechanisms involving copper overload and lncRNA:CR43306 deficiency in the context of testicular aging.

Layer-by-layer growth of Cu3(HHTP)2 films on Cu(OH)2 nanowire arrays for high performance ascorbic acid sensing.

Growing three-dimensional (3D) metal organic frameworks (MOFs) via heterogeneous epitaxial growth on metal hydroxide arrays are effective for constructing electrochemical sensor. However, the growth of MOFs is difficult to control, resulting in thick and irregular morphologies and even damage the metal hydroxide template. In this work, Cu3(HHTP)2 (HHTP = 2, 3, 6, 7, 10, 11-hexahydroxytriphenylene) films with controllable thickness and morphology were successfully prepared on Cu(OH)2 nanowire arrays (NWAs) through layer-by-layer (LBL) growth method. We have discovered that the LBL cycle and the reaction solvent composition are crucial for growing homogenous MOF thin films. The Cu3(HHTP)2 based ascorbic acid (AA) sensor, fabricated in ethanol within 10 LBL cycles, generated an ultrahigh sensitivity of 821.64 µA mM-1 cm-2 in the range of 6-981.41 µM, a low detection limit of 60 nM as well as the great selectivity, stability and reproducibility. Moreover, the relative deviation for AA detection in two fruit juices were 3.22 % and 3.71 %, and the test result for human sweat fall within the normal AA concentration range, verifying the feasibility of as-prepared sensor for practical application.