ABSTRACT
BACKGROUND: Abnormal blinking pattern is associated with ocular surface diseases. However, blink is difficult to analyze due to the rapid movement of eyelids. Deep learning machine (DLM) has been proposed as an optional tool for blinking analysis, but its clinical practicability still needs to be proven. Therefore, the study aims to compare the DLM-assisted Keratograph 5M (K5M) as a novel method with the currently available Lipiview in the clinic and assess whether blinking parameters can be applied in the diagnosis of dry eye disease (DED). METHODS: Thirty-five DED participants and 35 normal subjects were recruited in this cross-sectional study. DED questionnaire and ocular surface signs were evaluated. Blinking parameters including number of blinks, number of incomplete blinking (IB), and IB rate were collected from the blinking videos recorded by the K5M and Lipiview. Blinking parameters were individually collected from the DLM analyzed K5M videos and Lipiview generated results. The agreement and consistency of blinking parameters were compared between the two devices. The association of blinking parameters to DED symptoms and signs were evaluated via heatmap. RESULTS: In total, 140 eyes of 70 participants were included in this study. Lipiview presented a higher number of IB and IB rate than those from DLM-assisted K5M (P ≤ 0.006). DLM-assisted K5M captured significant differences in number of blinks, number of IB and IB rate between DED and normal subjects (P ≤ 0.035). In all three parameters, DLM-assisted K5M also showed a better consistency in repeated measurements than Lipiview with higher intraclass correlation coefficients (number of blinks: 0.841 versus 0.665; number of IB: 0.750 versus 0.564; IB rate: 0.633 versus 0.589). More correlations between blinking parameters and DED symptoms and signs were found by DLM-assisted K5M. Moreover, the receiver operating characteristic analysis showed the number of IB from K5M exhibiting the highest area under curve of 0.773. CONCLUSIONS: DLM-assisted K5M is a useful tool to analyze blinking videos and detect abnormal blinking patterns, especially in distinguishing DED patients from normal subjects. Large sample investigations are therefore warranted to assess its clinical utility before implementation.
ABSTRACT
Microsporidia are a group of obligate intracellular parasites causing significant disease in human beings and economically important animals. Though a few spore wall proteins (SWPs) have now been identified in these intriguing species, the information on SWPs remains too little to elucidate the spore wall formation mechanisms of microsporidia. It has been well described that numerous proteins with tandem repeats tend to be localized on the cell wall of fungi and parasites. Previously, by scanning the proteins with tandem repeats in microsporidian Nosema bombycis, we obtained 83 candidate SWPs based on whether those proteins possess a signal peptide and/or transmembrane domain. Here, we further characterized a candidate protein (EOB13250) with three tandem repeats in the N-terminal region and a transmembrane domain in C-terminus of N. bombycis. Sequence analysis showed that the tandem repeat domain of EOB13250 was species-specific for this parasite. RT-PCR indicated that the expression of the gene encoding this protein started on the fourth day postinfection. After cloned and expressed in Escherichia coli, a polyclone antibody against the recombinant EOB13250 protein was prepared. Western blotting demonstrated this protein exist in N. bombycis. Immunofluorescence analysis (IFA) and immunoelectron microscopy analysis (IEM) further provided evidence that EOB13250 was an endospore wall protein. These results together suggested that EOB13250 was a novel spore wall protein of N. bombycis. This study provides a further enrichment of the number of identified spore wall proteins in microsporidia and advances our understanding of the spore wall formation mechanism in these obligate unicellular parasites.