EFFECT OF ANESTHESIA DURATION ON INTRAVITREAL INJECTION PAIN: A double-blinded, randomized, comparative study.

PURPOSE: To determine the effect of different durations of topical anesthesia on intravitreal injection (IVI) pain. METHODS: This was a double-blinded, randomized, comparative study . Three hundred and twelve sequential eyes undergoing IVI were randomized to one of six groups according to the duration of topical anesthesia (from 1 to 30 minutes, one group for every 5-minute range, Groups 1-6). Topical anesthesia before IVI was standardized. Patients graded their pain using the visual analog scale and the Wong-Baker FACES scale at 15 minutes after the procedure. RESULTS: The pain scores among the six groups were significantly different for the visual analog scale ( P = 0.013) and Wong-Baker FACES scale ( P = 0.024). The mean pain scores for Group 4 were 1.97 ± 1.04 (visual analog scale) and 2.02 ± 1.08 (Wong-Baker FACES scale) and were significantly lower than those of Group 1, 2, 5, or 6. CONCLUSION: The duration of topical anesthesia significantly correlated with IVI pain. Preoperative 0.5% proparacaine hydrochloride drops were most effective in relieving IVI pain 11 to 20 minutes after topical administration.

A Comparison of Adjustable Positioning and Free Positioning After Pars Plana Vitrectomy for Rhegmatogenous Retinal Detachment: A Prospective Randomized Controlled Study.

Purpose: To compare the effectiveness and safety of adjustable and free postoperative positioning after pars plana vitrectomy (PPV) for rhegmatogenous retinal detachment (RRD). Design: Prospective, randomized controlled study. Methods: A total of 94 eyes with RRD were enrolled from April 2020 to April 2023 and monitored postoperatively for at least 3 months. All patients underwent PPV combined with silicone oil injection or gas tamponade and were randomly divided postoperatively into two groups: an adjustable positioning group and a free positioning group. The success of the outcome was based on the retinal reattachment rate, best corrected visual acuity (BCVA), postoperative complications, and ocular biometric parameters such as anterior chamber depth (ACD) and lens thickness (LT). Results: The initial retinal reattachment rate was 97.9% in the adjustable positioning group and 95.7% in the free positioning group, manifesting no statistical difference between the two groups. Similarly, no statistical difference was observed between the two groups in the final BCVA, which was significantly improved compared to the preoperative BCVA. The comparison of the 1-month postoperative ACD and LT with the preoperative values showed no statistically significant differences in the two groups. The rates of complications were not statistically different in the two groups. Conclusion: After treating RRD using PPV, neither the adjustable nor the free postoperative positioning affected the retinal reattachment rate or the incidence of complications. Therefore, our study showed that it is safe and effective to adopt free positioning postoperatively, which may provide more options for patients with RRD undergoing PPV.

Applying differential network analysis to longitudinal gene expression in response to perturbations.

Differential Network (DN) analysis is a method that has long been used to interpret changes in gene expression data and provide biological insights. The method identifies the rewiring of gene networks in response to external perturbations. Our study applies the DN method to the analysis of RNA-sequencing (RNA-seq) time series datasets. We focus on expression changes: (i) in saliva of a human subject after pneumococcal vaccination (PPSV23) and (ii) in primary B cells treated ex vivo with a monoclonal antibody drug (Rituximab). The DN method enabled us to identify the activation of biological pathways consistent with the mechanisms of action of the PPSV23 vaccine and target pathways of Rituximab. The community detection algorithm on the DN revealed clusters of genes characterized by collective temporal behavior. All saliva and some B cell DN communities showed characteristic time signatures, outlining a chronological order in pathway activation in response to the perturbation. Moreover, we identified early and delayed responses within network modules in the saliva dataset and three temporal patterns in the B cell data.

Automated detection of myopic maculopathy from color fundus photographs using deep convolutional neural networks.

BACKGROUND: Myopic maculopathy (MM) has become a major cause of visual impairment and blindness worldwide, especially in East Asian countries. Deep learning approaches such as deep convolutional neural networks (DCNN) have been successfully applied to identify some common retinal diseases and show great potential for the intelligent analysis of MM. This study aimed to build a reliable approach for automated detection of MM from retinal fundus images using DCNN models. METHODS: A dual-stream DCNN (DCNN-DS) model that perceives features from both original images and corresponding processed images by color histogram distribution optimization method was designed for classification of no MM, tessellated fundus (TF), and pathologic myopia (PM). A total of 36,515 gradable images from four hospitals were used for DCNN model development, and 14,986 gradable images from the other two hospitals for external testing. We also compared the performance of the DCNN-DS model and four ophthalmologists on 3000 randomly sampled fundus images. RESULTS: The DCNN-DS model achieved sensitivities of 93.3% and 91.0%, specificities of 99.6% and 98.7%, areas under the receiver operating characteristic curves (AUC) of 0.998 and 0.994 for detecting PM, whereas sensitivities of 98.8% and 92.8%, specificities of 95.6% and 94.1%, AUCs of 0.986 and 0.970 for detecting TF in two external testing datasets. In the sampled testing dataset, the sensitivities of four ophthalmologists ranged from 88.3% to 95.8% and 81.1% to 89.1%, and the specificities ranged from 95.9% to 99.2% and 77.8% to 97.3% for detecting PM and TF, respectively. Meanwhile, the DCNN-DS model achieved sensitivities of 90.8% and 97.9% and specificities of 99.1% and 94.0% for detecting PM and TF, respectively. CONCLUSIONS: The proposed DCNN-DS approach demonstrated reliable performance with high sensitivity, specificity, and AUC to classify different MM levels on fundus photographs sourced from clinics. It can help identify MM automatically among the large myopic groups and show great potential for real-life applications.

Longitudinal saliva omics responses to immune perturbation: a case study.

Saliva omics has immense potential for non-invasive diagnostics, including monitoring very young or elderly populations, or individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over three periods (100 timepoints) involving: (1) hourly sampling over 24 h without intervention, (2) hourly sampling over 24 h including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (3) daily sampling for 33 days profiling the post-vaccination response. At each timepoint total saliva transcriptome and proteome, and small RNA from salivary extracellular vesicles were profiled, including mRNA, miRNA, piRNA and bacterial RNA. The two 24-h periods were used in a paired analysis to remove daily variation and reveal vaccination responses. Over 18,000 omics longitudinal series had statistically significant temporal trends compared to a healthy baseline. Various immune response and regulation pathways were activated following vaccination, including interferon and cytokine signaling, and MHC antigen presentation. Immune response timeframes were concordant with innate and adaptive immunity development, and coincided with vaccination and reported fever. Overall, mRNA results appeared more specific and sensitive (timewise) to vaccination compared to other omics. The results suggest saliva omics can be consistently assessed for non-invasive personalized monitoring and immune response diagnostics.