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BackgroundOptical coherence tomography angiography (OCTA) enables fast and non-invasive high-resolution imaging of retinal microvasculature and is suggested as a potential tool in the early detection of retinal microvascular changes in Alzheimer’s Disease (AD). We developed a standardised OCTA analysis framework and compared their extracted parameters among controls and AD/mild cognitive impairment (MCI) in a cross-section study.MethodsWe defined and extracted geometrical parameters of retinal microvasculature at different retinal layers and in the foveal avascular zone (FAZ) from segmented OCTA images obtained using well-validated state-of-the-art deep learning models. We studied these parameters in 158 subjects (62 healthy control, 55 AD and 41 MCI) using logistic regression to determine their potential in predicting the status of our subjects.ResultsIn the AD group, there was a significant decrease in vessel area and length densities in the inner vascular complexes (IVC) compared with controls. The number of vascular bifurcations in AD is also significantly lower than that of healthy people. The MCI group demonstrated a decrease in vascular area, length densities, vascular fractal dimension and the number of bifurcations in both the superficial vascular complexes (SVC) and the IVC compared with controls. A larger vascular tortuosity in the IVC, and a larger roundness of FAZ in the SVC, can also be observed in MCI compared with controls.ConclusionOur study demonstrates the applicability of OCTA for the diagnosis of AD and MCI, and provides a standard tool for future clinical service and research. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of AD and MCI.

Neovascular age‐related macular degeneration (AMD), which is characterized by choroidal neovascularization (CNV), leads to vision loss. M2 macrophages produce vascular endothelial growth factor (VEGF), which aggravates CNV formation. The histone acetyltransferase p300 enhances the stability of spliced X‐box binding protein 1 (XBP1s) and promotes the transcriptional activity of the XBP1s target gene homocysteine inducible endoplasmic reticulum protein with ubiquitin‐like domain 1 (Herpud1). Herpud1 promotes the M2 polarization of macrophages. This study aimed to explore the roles of the p300/XBP1s/Herpud1 axis in the polarization of macrophages and the pathogenesis of CNV. Hypoxia‐induced p300 interacted with XBP1s to acetylate XBP1s in RAW264.7 cells. Additionally, hypoxia‐induced p300 enhanced the XBP‐1s‐mediated unfolded protein response (UPR), alleviated the proteasome‐dependent degradation of XBP1s and enhanced the transcriptional activity of XBP1s for Herpud1. The hypoxia‐induced p300/XBP1s/Herpud1 axis facilitated RAW264.7 cell M2 polarization. Knockdown of the p300/XBP1s/Herpud1 axis in RAW264.7 cells inhibited the proliferation, migration and tube formation of mouse choroidal endothelial cells (MCECs). The p300/XBP1s/Herpud1 axis increased in infiltrating M2‐type macrophages in mouse laser‐induced CNV lesions. Blockade of the p300/XBP1s/Herpud1 axis inhibited macrophage M2 polarization and alleviated CNV lesions. Our study demonstrated that the p300/XBP1s/Herpud1 axis in infiltrating macrophages increased the M2 polarization of macrophages and the development of CNV.

Improving citizen epidemic prevention information literacy is one of the most cost-efficient and important measures to improve people’s epidemic prevention abilities to effectively deal with future public health crises. Epidemic prevention information literacy is beneficial to improve individuals’ ability to deal with public health crises in the future. By summarizing related domestic and international research, and utilizing an empirical methodology, we constructed an epidemic prevention information literacy assessment model with good reliability, validity, and model fit. The model is composed of four indicators: (1) “epidemic prevention information awareness”; (2) “epidemic prevention information knowledge”; (3) “epidemic prevention information ability”; (4) “epidemic prevention information morality”. We used the model to assess the epidemic prevention information literacy of Chinese citizens. The results showed the following: (1) the overall level of the epidemic prevention information literacy of Chinese citizens was comparatively high, however, its development was unbalanced, and the capability and moral levels of the epidemic prevention information were comparatively low; (2) the four dimensions of the epidemic prevention information literacy were different in terms of the citizens’ education levels and locations. We analyzed the probable causes of these problems, and we propose specific corresponding countermeasures. The research provides a set of methods and norms for the evaluation of citizen epidemic prevention information literacy in the post-epidemic era.

Corneal astigmatism frequently coexists with age-related cataract and may impair uncorrected distance visual acuity (UDVA) if not addressed during surgery. Limbal relaxing incisions (LRI) and toric intraocular lenses (toric IOL) are two common methods for astigmatism correction, but evidence comparing their effectiveness in patients with moderate regular astigmatism remains limited. A prospective study was conducted at Yuyao Maternity and Child Health Care Hospital between January and December 2024. Ninety-three patients aged 55–80 years with moderate regular corneal astigmatism undergoing cataract surgery were allocated to either the LRI group (n = 45) or the toric IOL group (n = 48) based on informed voluntary choice following standardized preoperative counseling. All procedures were performed by a single experienced surgeon. The primary outcome was residual refractive cylinder at 6 months postoperatively. Secondary outcomes included UDVA, best-corrected visual acuity (BCVA), corneal astigmatism (K2–K1), and subjective visual satisfaction. Both groups showed significant improvement in UDVA and reduction in refractive cylinder postoperatively. At 6 months, the toric IOL group had significantly lower residual cylinder (0.67 ± 0.28 D vs. 0.94 ± 0.30 D, P < 0.001) and superior UDVA (0.15 ± 0.03 vs. 0.20 ± 0.03 LogMAR, P < 0.001) compared to the LRI group. No differences in BCVA were observed. Subjective satisfaction was significantly higher in the toric IOL group (P = 0.009). Toric IOL provide more favorable refractive and subjective outcomes than LRI for correcting moderate astigmatism during cataract surgery. These findings support a personalized approach that considers visual expectations, cost, and access to technology.

Macular edema (ME) is a leading cause of visual impairment in various retinal disorders. Current treatment modalities, including anti-vascular endothelial growth factor (anti-VEGF) agents and corticosteroids, often require repeated applications, increasing both medical and economic burdens. ME is driven by chronic inflammation and VEGF overexpression, causing fluid accumulation in the macula. Recent studies have highlighted the role of various cytokines in ME pathogenesis, necessitating a comprehensive approach to treatment. While monotherapies have shown efficacy, they are associated with limitations such as the need for frequent injections and potential side effects. Combination therapies, including anti-VEGF drugs with macular laser photocoagulation, triamcinolone acetonide, or dexamethasone intravitreal implant (Ozurdex), have emerged as promising strategies. This review analyzes the outcomes of various combination approaches in different types of ME, including diabetic macular edema (DME), retinal vein occlusion-associated ME (RVO-ME), and uveitic macular edema (UME). The potential benefits of combining anti-VEGF and anti-inflammatory treatments are discussed, along with the need for personalized treatment regimens. Future research directions are outlined, emphasizing the importance of large-scale, long-term studies to evaluate the sustained efficacy and safety of combination therapies. The integration of advanced imaging techniques, biomarker analysis, and innovative therapeutic approaches is expected to shape the future landscape of ME management, moving towards more targeted and effective combination therapies.

Segmentation of corneal layer interfaces in optical coherence tomography (OCT) images is important for diagnostic and surgical purposes, while manual segmentation is a time-consuming and tedious process. This paper presents a novel technique for the automatic segmentation of corneal layer interfaces using customized initial layer estimation and a gradient-based segmentation method. The proposed method was also extended to three-dimensional OCT images. Validation was performed on two corneal datasets, one with 37 B-scan images of healthy human eyes and the other with a 3D volume scan of a porcine eye. The approach showed robustness in extracting different layer boundaries in the low-SNR region with lower computational cost but higher accuracy compared to existing techniques. It achieved segmentation errors below 2.1 pixels for both the anterior and posterior layer boundaries in terms of mean unsigned surface positioning error for the first dataset and 2.6 pixels (5.2 μ m ) for segmenting all three layers that can be resolved in the second dataset. On average, it takes 0.7 and 0.4 seconds to process a cross-sectional B-scan image for datasets one and two, respectively. Our comparative study also showed that it outperforms state-of-the-art methods for quantifying layer interfaces in terms of accuracy and time efficiency.

The accurate segmentation of medical images is of great importance in many clinical applications and is generally achieved by training deep learning networks on a large number of labeled images. However, it is very hard to obtain enough labeled images. In this paper, we develop a novel semi-supervised segmentation method (called PE-MT) based on the uncertainty-aware mean teacher (UA-MT) framework by introducing a perturbation-enhanced exponential moving average (pEMA) and a residual-guided uncertainty map (RUM) to enhance the performance the student and teacher models. The former is used to alleviate the coupling effect between student and teacher models in the UA-MT by adding different weight perturbations to them, and the latter can accurately locate image regions with high uncertainty via a unique quantitative formula and then highlight these regions effectively in image segmentation. We evaluated the developed method by extracting four different cardiac regions from the public LASC and ACDC datasets. The experimental results showed that our developed method achieved an average Dice similarity coefficient (DSC) of 0.6252 and 0.7836 for four object regions when trained on 5% and 10% labeled images, respectively. It outperformed the UA-MT and can compete with several existing semi-supervised learning methods (e.g., SASSNet and DTC).

Optical Coherence Tomography Angiography (OCTA) is a cutting-edge imaging technique that captures retinal capillaries at micrometer resolution using optical instrument. Accurate segmentation of retinal vasculature is essential for eye related diseases measurement and diagnosis. However, noise and artifacts from different imaging instruments can interfere with segmentation, and most existing deep learning models struggle with segmenting small vessels and capturing low-dimensional structural information. These challenges typically results in less precise segmentation performance. Therefore, we propose a novel and robust Dual-stream Disentangled Network (D2Net) for retinal OCTA microvascular segmentation. Specifically, the D2Net includes a dual-stream encoder that separately learns image artifacts and latent vascular features. By introducing vascular structure as a prior constraint and constructing auxiliary information, the network achieves disentangled representation learning, effectively minimizing the interference of noise and artifacts. The introduced vascular structure prior includes low-dimensional neighborhood energy from the Distance Correlation Energy (DCE) module, which helps to better perceive the structural information of continuous vessels. To precisely evaluate our method on small vessels, we delicately establish OCTA microvascular labels by performing comprehensive and detailed annotations on the FOCA dataset, which includes data collected from different instruments, and evaluated the proposed D2Net effectively mitigates the challenges of microvasculature region recognition caused by noise and artifacts. The method achieves more refined segmentation performance. In addition, we validated the performance of D2Net on four OCTA datasets (OCTA-500, ROSE-O, ROSE-Z, and ROSE-H) acquired using different instruments, demonstrating its robustness and generalization capabilities in retinal vessel segmentation compared to other state-of-the-art methods.

Background Infectious keratitis, a medical emergency with acute and rapid disease progression may lead to severe visual impairment and even blindness. Herein, an antimicrobial polypeptide from Crassostrea hongkongensis , named URP20, was evaluated for its therapeutic efficacy against keratitis caused by Staphylococcus aureus (S. aureus) and Escherichia coli ( E. coli) infection in rats, respectively. Methods A needle was used to scratch the surface of the eyeballs of rats and infect them with S. aureus and E.coli to construct a keratitis model. The two models were treated by giving 100 μL 100 μM URP20 drops. Positive drugs for S. aureus and E. coli infection were cefazolin eye drops and tobramycin eye drops, respectively. For the curative effect, the formation of blood vessels in the fundus was observed by a slit lamp (the third day). At the end of the experiment, the condition of the injured eye was photographed by cobalt blue light using 5 μL of 1% sodium fluorescein. The pathological damage to corneal tissues was assessed using hematoxylin–eosin staining, and the expression level of vascular endothelial growth factor (VEGF) was detected by immunohistochemistry. Results URP20 alleviated the symptoms of corneal neovascularization as observed by slit lamp and cobalt blue lamp. The activity of S. aureus and E.coli is inhibited by URP20 to protect corneal epithelial cells and reduce corneal stromal bacterial invasion. It also prevented corneal thickening and inhibited neovascularization by reducing VEGF expression at the cornea. Conclusion URP20 can effectively inhibit keratitis caused by E.coli as well as S. aureus in rats, as reflected by the inhibition of corneal neovascularization and the reduction in bacterial damage to the cornea.

Background Current human retina studies predominantly utilize post-mortem tissue, and the sample accessibility constraints make the characterization of the living human retina at single-cell resolution a challenge. Although single-nucleus RNA-seq expands the utility of frozen samples, it provides a nuclear-centric view, potentially missing key cytoplasmic information and transient biological processes. Thus, it is important to generate resources directly from living human retinal tissue to complement existing datasets. Methods We profiled 106,829 single cells from nine unfrozen human retina samples. Living samples were collected within 10 min of therapeutic enucleation and four postmortem samples were collected within 6 h. After standardized dissociation, single-cell transcriptomes were generated using 10x Genomics 3’ RNA-seq and applied scVI to generate batch-corrected integrated atlas. Major cell types and subtypes were annotated through iterative Leiden clustering, canonical markers. Subsequent analyses included differential expression comparisons between cell states and regulon activity profiling to further characterize cellular identities and regulatory networks. Transcriptional dynamics were assessed using RNA velocity, and cell-cell signaling pathways were inferred with CellChat. Key findings were validated in independent samples from two additional donors (four samples) using the identical workflow. Results We contribute to establishing a reference for retinal cell type proportions and cellular states. Our analysis revealed ELF1-mlCone, a distinct cluster of mlCone photoreceptors identified by distinct transcriptional features. The presence and transcriptional features of this cluster were validated in independent samples. Additionally, by comparing living and post-mortem samples, our study highlights differences in transcriptional dynamics: living tissue preserved coherent RNA velocity streams, enabling clear dynamic state transitions, while post-mortem tissue exhibited disorganized patterns. These findings suggest that using living tissue can improve the capture of active cellular states and transitions. Conclusions Our atlas provides a single-cell reference contrasting living versus early postmortem human retina, integrating cell type composition, transcriptional diversity, and functional insights. It may serve as a useful resource for retinal research and for understanding aspects of human retinal biology, particularly given its inclusion of living tissue and diverse pathological states.