Background: The aim of this study was to develop an intelligent system based on a deep learning algorithm for automatically diagnosing fungal keratitis (FK) in in vivo confocal microscopy (IVCM) images. Methods: A total of 2,088 IVCM images were included in the training dataset. The positive group consisted of 688 images with fungal hyphae, and the negative group included 1,400 images without fungal hyphae. A total of 535 images in the testing dataset were not included in the training dataset. Deep Residual Learning for Image Recognition (ResNet) was used to build the intelligent system for diagnosing FK automatically. The system was verified by external validation in the testing dataset using the area under the receiver operating characteristic curve (AUC), accuracy, specificity and sensitivity. Results: In the testing dataset, 515 images were diagnosed correctly and 20 were misdiagnosed (including 6 with fungal hyphae and 14 without). The system achieved an AUC of 0.9875 with an accuracy of 0.9626 in detecting fungal hyphae. The sensitivity of the system was 0.9186, with a specificity of 0.9834. When 349 diabetic patients were included in the training dataset, 501 images were diagnosed correctly and thirty-four were misdiagnosed (including 4 with fungal hyphae and 30 without). The AUC of the system was 0.9769. The accuracy, specificity and sensitivity were 0.9364, 0.9889 and 0.8256, respectively. Conclusions: The intelligent system based on a deep learning algorithm exhibited satisfactory diagnostic performance and effectively classified FK in various IVCM images. The context of this deep learning automated diagnostic system can be extended to other types of keratitis.

The objective of this study is to expound the CT features of COVID-19 patients whose throat swab samples were negative for two consecutive nucleic acid tests after treatment. We retrospectively reviewed 46 COVID-19 patients with two consecutive negative RT-PCR tests after treatment. The cases were divided into moderate group and severe/critical group according to disease severity. Clinical and CT scanning data were collected. CT signs of pulmonary lesions and the score of lung involvement were expounded. Thirty-nine moderate cases and seven severe/critical cases were included. Residual pulmonary lesions were visible in CT images. Moderate patients showed peripheral lesions while severe/critical cases exhibited both central and peripheral lesions with all lobes involvement. Mixed ground glass opacity (GGO) and pulmonary consolidation were noted. A larger proportion of severe patients showed reticular pulmonary interstitium thickening. Air bronchogram, pleural effusion, vascular enlargement, bronchial wall thickening, bronchiectasis, pleural thickening and pleural adhesion were more frequently observed in severe/critical group. The severe/critical group showed higher CT score. Pulmonary lesions persisted even after twice consecutive negative nucleic acid tests. We strongly recommended regular follow-up of CT scans after nucleic acid tests conversion. Evaluation of complete remission should base on chest CT.

Purpose: Strategies for neuroprotection are the main targets of glaucoma research. The neuroprotective properties of SRT2104 administration have been proven in central nervous system degeneration diseases through the activation of nicotinamide adenine dinucleotide-dependent deacetylase-silence information regulator 1 (Sirt1). Here, we investigated whether SRT2104 could protect the retina from ischemia/reperfusion (I/R) injury and the underlying mechanisms. Methods: SRT2104 was intravitreally injected immediately after I/R induction. RNA and protein expression were detected by quantitative real-time PCR and Western blot. Protein expression and distribution were examined by immunofluorescence staining. Retinal structure and function were analyzed by hematoxylin and eosin staining, optical coherence tomography, and electroretinogram. Optic nerve axons were quantified using toluidine blue staining. Cellular apoptosis and senescence were evaluated by TUNEL assay and SA-β-gal staining. Results: The protein expression of Sirt1 decreased dramatically after I/R injury and SRT2104 administration effectively enhanced the stability of Sirt1 protein without significantly influencing Sirt1 mRNA synthesis. SRT2104 administration alone exerted no influence on the structure and function of normal retinas. However, SRT2104 intervention significantly protected the inner retinal structure and neurons; partially restored retinal function after I/R injury. I/R-induced cellular apoptosis and senescence were effectively alleviated by SRT2104 administration. Additionally, SRT2104 intervention markedly reduced neuroinflammation, including reactive gliosis, retinal vascular inflammation, and the overexpression of pro-inflammatory cytokines after I/R injury. Mechanistically, I/R-induced acetylation of p53, NF-κB p65, and STAT3 was significantly reversed by SRT2104 intervention. Conclusions: We demonstrated that SRT2104 exerted potent protective effects against I/R injury by enhancing Sirt1-mediated deacetylation and suppressing apoptosis, senescence, and neuroinflammation-related pathways.