Development of a novel bioartificial cornea using 3D bioprinting based on electrospun micro-nanofibrous decellularized extracellular matrix

Corneal damage contributes to blindness in millions of people. Simulating natural corneas with artificial corneas is challenging due to material and manufacturing limitations, including poor mechanical properties, complex manufacturing processes, and ocular histocompatibility. In this study, electrospun micro-nanofibrous decellularized extracellular matrix (dECM) is combined with digital light processing 3D bioprinting and validated as a bioartificial cornea for the first time. Electrospinning gives the material a controllable shape, and the electrospun micro-nanofibrous dECM, with preserved inherent biochemical components, can better mimic the natural ECM native microenvironment. An efficient platform can be developed for creating novel structural materials, when combined with intelligent manufacturing. Artificial biological corneas developed using this method showed five-fold improvements in mechanical properties (248.5 ± 35.67 kPa Vs. 56.91 ± 3.68 kPa, p<0.001), superior guidance for cell organization and adhesion, and better maintenance of the cellular phenotype of keratocytes. In animal studies, in vivo transplantation of this artificial cornea showed better regeneration, which accelerated corneal epithelialization and maintained corneal transparency. This method has potential for biomedical applications, and bioartificial corneas manufactured by this method have ideal properties as an alternative to lamellar keratoplasty, with promise for clinical transformation. .

Unsupervised corneal contour extraction algorithm with shared model for dynamic deformation videos: improving accuracy and noise resistance

BACKGROUND

In this study, an automatic corneal contour extraction algorithm with a shared model is developed to extract contours from dynamic corneal videos containing noise, which improves the accuracy of corneal biomechanical evaluation and clinical diagnoses. The algorithm does not require manual labeling and completes the unsupervised semantic segmentation of each frame in corneal dynamic deformation videos based on a fully convolutional deep-learning network using corneal geometry and texture information.

RESULTS

We included 1027 corneal videos at Tianjin Eye Hospital (Nankai University Affiliated Eye Hospital) from May 2020 to November 2021. The videos were obtained by the ultra-high-speed Scheimpflug camera, and then we used the shared model mechanism to accelerate the segmentation of corneal regions in videos, effectively resist noise, determine corneal regions based on shape factors, and finally achieve automatic and accurate extraction of corneal region contours. The Intersection over Union (IoU) of the extracted and real corneal contours using this algorithm reached 95%, and the average overlap error was 0.05, implying that the extracted corneal contour overlapped almost completely with the real contour.

CONCLUSIONS

Compared to other algorithms, the method introduced in this study does not require manual annotation of corneal contour data in advance and can still extract accurate corneal contours from noisy corneal videos with good repeatability.

Localized Corneal Biomechanical Alteration Detected In Early Keratoconus Based on Corneal Deformation Using Artificial Intelligence

PURPOSE

This study aimed to develop a novel method to diagnose early keratoconus by detecting localized corneal biomechanical changes based on dynamic deformation videos using machine learning.

DESIGN

Diagnostic research study.

METHODS

We included 917 corneal videos from the Tianjin Eye Hospital (Tianjin, China) and Shanxi Eye Hospital (Xi'an, China) from February 6, 2015, to August 25, 2022. Scheimpflug technology was used to obtain dynamic deformation videos under forced puffs of air. Fourteen new pixel-level biomechanical parameters were calculated based on a spline curve equation fitting by 115,200-pixel points from the corneal contour extracted from videos to characterize localized biomechanics. An ensemble learning model was developed, external validation was performed, and the diagnostic performance was compared with that of existing clinical diagnostic indices. The performance of the developed machine learning model was evaluated using precision, recall, F1 score, and the area under the receiver operating characteristic curve.

RESULTS

The ensemble learning model successfully diagnosed early keratoconus (area under the curve = 0.9997) with 95.73% precision, 95.61% recall, and 95.50% F1 score in the sample set (n=802). External validation on an independent dataset (n=115) achieved 91.38% precision, 92.11% recall, and 91.18% F1 score. Diagnostic accuracy was significantly better than that of existing clinical diagnostic indices (from 86.28% to 93.36%, all P <0.01).

CONCLUSIONS

Localized corneal biomechanical changes detected using dynamic deformation videos combined with machine learning algorithms were useful for diagnosing early keratoconus. Focusing on localized biomechanical changes may guide ophthalmologists, aiding the timely diagnosis of early keratoconus and benefiting the patient's vision.

Bibliometric and visualized analysis of myopic corneal refractive surgery research: from 1979 to 2022

Background

Myopic corneal refractive surgery is one of the most prevalent ophthalmic procedures for correcting ametropia. This study aimed to perform a bibliometric analysis of research in the field of corneal refractive surgery over the past 40 years in order to describe the current international status and to identify most influential factors, while highlighting research hotspots.

Methods

A bibliometric analysis based on the Web of Science Core Collection (WoSCC) was used to analyze the publication trends in research related to myopic corneal refractive surgery. VOSviewer v.1.6.10 was used to construct the knowledge map in order to visualize the publications, distribution of countries, international collaborations, author productivity, source journals, cited references, keywords, and research hotspots in this field.

Results

A total of 4,680 publications on myopic corneal refractive surgery published between 1979 and 2022 were retrieved. The United States has published the most papers, with Emory University contributing to the most citations. The Journal of Cataract and Refractive Surgery published the greatest number of articles, and the top 10 cited references mainly focused on outcomes and wound healing in refractive surgery. Previous research emphasized "radial keratotomy (RK)" and excimer laser-associated operation methods. The keywords containing femtosecond (FS) laser associated with "small incision lenticule extraction (SMILE)" and its "safety" had higher burst strength, indicating a shift of operation methods and coinciding with the global trends in refractive surgery. The document citation network was clustered into five groups: (1) outcomes of refractive surgery: (2) preoperative examinations for refractive surgery were as follows: (3) complications of myopic corneal refractive surgery; (4) corneal wound healing and cytobiology research related to photorefractive laser keratotomy; and (5) biomechanics of myopic corneal refractive surgery.

Conclusion

The bibliometric analysis in this study may provide scholars with valuable to information and help them better understand the global trends in myopic corneal refractive surgery research frontiers. Two stages of rapid development occurred around 1991 and 2013, shortly after the innovation of PRK and SMILE surgical techniques. The most cited articles mainly focused on corneal wound healing, clinical outcomes, ocular aberration, corneal ectasia, and corneal topography, representing the safety of the new techniques.

Novel Corneal Protein Biomarker Candidates Reveal Iron Metabolic Disturbance in High Myopia Eyes

Myopia is a major public health concern with increasing global prevalence and is the leading cause of vision loss and complications. The potential role of the cornea, a substantial component of refractive power and the protective fortress of the eye, has been underestimated in the development of myopia. Our study acquired corneal stroma tissues from myopic patients undergoing femtosecond laser-assisted small incision lenticule extraction (SMILE) surgery and investigated the differential expression of circulating proteins between subjects with low and high myopia by means of high-throughput proteomic approaches—the quantitative tandem mass tag (TMT) labeling method and parallel reaction monitoring (PRM) validation. Across all corneal stroma tissue samples, a total of 2,455 proteins were identified qualitatively and quantitatively, 103 of which were differentially expressed between those with low and high myopia. The differentially abundant proteins (DAPs) between the groups of stroma samples mostly demonstrated catalytic activity and molecular function regulator and transporter activity and participated in metabolic processes, biological regulation, response to stimulus, and so forth. Pathway enrichment showed that mineral absorption, ferroptosis, and HIF-1 signaling pathways were activated in the human myopic cornea. Furthermore, TMT analysis and PRM validation revealed that the expression of ferritin light chain (FTL, P02792) and ferritin heavy chain (FTH1, P02794) was negatively associated with myopia development, while the expression of serotransferrin (TF, P02787) was positively related to myopia status. Overall, our results indicated that subjects with low and high myopia could have different proteomic profiles or signatures in the cornea. These findings revealed disturbances in iron metabolism and corneal oxidative stress in the more myopic eyes. Iron metabolic proteins could serve as an essential modulator in the pathogenesis of myopia.

The susceptibility of SERPINE1 rs1799889 SNP in diabetic vascular complications: a meta-analysis of fifty-one case-control studies

BACKGROUND

The serine protease inhibitor-1 (SERPINE1) rs1799889 single nucleotide polymorphism (SNP) has been constantly associated with diabetes mellitus (DM) and its vascular complications. The aim of this meta-analysis was to evaluate this association with combined evidences.

METHODS

The systematic search was performed for studies published up to March 2021 which assess the associations between SERPINE1 rs1799889 SNP and the risks of DM, diabetic retinopathy (DR), diabetic cardiovascular disease (CVD) and diabetic nephropathy (DN). Only case-control studies were identified, and the linkage between SERPINE1 rs1799889 polymorphism and diabetic vascular risks were evaluated using genetic models.

RESULTS

51 comparisons were enrolled. The results revealed a significant association with diabetes risk in overall population (allelic: OR = 1.34, 95 % CI = 1.14-1.57, homozygous: OR = 1.66, 95 % CI = 1.23-2.14, heterozygous: OR = 1.35, 95 % CI = 1.08-1.69, dominant: OR = 1.49, 95 % CI = 1.18-1.88, recessive: OR = 1.30, 95 % CI = 1.06-1.59) as well as in Asian descents (allelic: OR = 1.45, 95 % CI = 1.16-1.82, homozygous: OR = 1.88, 95 % CI = 1.29-2.75, heterozygous: OR = 1.47, 95 % CI = 1.08-2.00, dominant: OR = 1.64, 95 % CI = 1.21-2.24, recessive: OR = 1.46, 95 % CI = 1.09-1.96). A significant association was observed with DR risk (homozygous: OR = 1.25, 95 % CI = 1.01-1.56, recessive: OR = 1.20, 95 % CI = 1.01-1.43) for overall population, as for the European subgroup (homozygous: OR = 1.32, 95 % CI = 1.02-1.72, recessive: OR = 1.38, 95 % CI = 1.11-1.71). A significant association were shown with DN risk for overall population (allelic: OR = 1.48, 95 % CI = 1.15-1.90, homozygous: OR = 1.92, 95 % CI = 1.26-2.95, dominant: OR = 1.41, 95 % CI = 1.01-1.97, recessive: OR = 1.78, 95 % CI = 1.27-2.51) and for Asian subgroup (allelic: OR = 1.70, 95 % CI = 1.17-2.47, homozygous: OR = 2.46, 95 % CI = 1.30-4.66, recessive: OR = 2.24, 95 % CI = 1.40-3.59) after ethnicity stratification. No obvious association was implied with overall diabetic CVD risk in any genetic models, or after ethnicity stratification.

CONCLUSIONS

SERPINE1 rs1799889 4G polymorphism may outstand for serving as a genetic synergistic factor in overall DM and DN populations, positively for individuals with Asian descent. The association of SERPINE1 rs1799889 SNP and DR or diabetic CVD risks was not revealed.

Value of Blood-Based microRNAs in the Diagnosis of Acute Myocardial Infarction: A Systematic Review and Meta-Analysis

Background: Recent studies have shown that blood-based miRNAs are dysregulated in patients with acute myocardial infarction (AMI) and are therefore a potential tool for the diagnosis of AMI. Therefore, this study summarized and evaluated studies focused on microRNAs as novel biomarkers for the diagnosis of AMI from the last ten years. Methods: MEDLINE, the Cochrane Central database, and EMBASE were searched between January 2010 and December 2019. Studies that assessed the diagnostic accuracy of circulating microRNAs in AMI were chosen. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) were used to assess the test performance of miRNAs. Results: A total of 58 studies that included 8,206 participants assessed the diagnostic accuracy of circulating miRNAs in AMI. The main results of the meta-analyses are as follows: (1) Total miRNAs: the overall pooled sensitivity and specificity were 0.82 (95% CI: 0.79-0.85) and 0.87 (95% CI: 0.84-0.90), respectively. The AUC value was 0.91 (95% CI: 0.88-0.93) in the overall summary receiver operator characteristic (SROC) curve. (2) The panel of two miRNAs: sensitivity: 0.88 (95% CI: 0.77-0.94), specificity: 0.84 (95% CI: 0.72-0.91), AUC: 0.92 (95% CI: 0.90-0.94). (3) The panel of three miRNAs: sensitivity: 0.91 (95% CI: 0.85-0.94), specificity: 0.87 (95% CI: 0.77-0.92), AUC: 0.92 (95% CI: 0.89-0.94). (4) Results by types of miRNAs: miRNA-1: sensitivity: 0.78 (95% CI: 0.71-0.84), specificity: 0.86 (95% CI: 0.77-0.91), AUC: 0.88 (95% CI: 0.85-0.90); miRNA-133a: sensitivity: 0.85 (95% CI: 0.69-0.94), specificity: 0.92 (95% CI: 0.61-0.99), AUC: 0.93 (95% CI: 0.91-0.95); miRNA-208b: sensitivity: 0.80 (95% CI: 0.69-0.88), specificity: 0.96 (95% CI: 0.77-0.99), AUC: 0.91 (95% CI: 0.88-0.93); miRNA-499: sensitivity: 0.85 (95% CI: 0.77-0.91), specificity: 0.95 (95% CI: 0.89-0.98), AUC: 0.96 (95% CI: 0.94-0.97). Conclusion: miRNAs may be used as potential biomarkers for the detection of AMI. For single, stand-alone miRNAs, miRNA-499 may have better diagnostic accuracy compared to other miRNAs. We propose that a panel of multiple miRNAs with high sensitivity and specificity should be tested.

Optical coherence tomography angiography findings of neurovascular changes in type 2 diabetes mellitus patients without clinical diabetic retinopathy

AIMS

To evaluate the effect of early screening with OCTA in type 2 diabetes mellitus (T2DM) patients without clinical DR (NDR).

METHODS

This was a cross-sectional case-control clinical study. Eighty-four eyes of 84 patients (44 T2DM and 40 control subjects) were included. Images were obtained using AngioVue software 2.0 of the OCTA device. Foveal avascular zone (FAZ) area, FAZ perimeter (PERIM), choriocapillary flow area (CCF), acircularity index (AI), foveal vessel density in a 300-µm-wide region around FAZ (FD), macular-associated vessel density (VD) and optic disc-associated capillary density (CD) were compared between the T2DM and control groups. In the T2DM group, the correlations between the above parameters and best-corrected visual acuity (BCVA) were assessed.

RESULTS

Enlarged FAZ, increased PERIM, reduced CCF, reduced parafoveal VD and decreased CD inside the disc were significantly more obvious in the NDR subjects than in the control subjects (FAZ 0.43 ± 0.13 versus 0.37 ± 0.08 mm², p = 0.02; PERIM 2.60 ± 0.45 versus 2.41 ± 0.28 mm, p = 0.04; CCF 1.94 ± 0.28 versus 2.05 ± 0.11 mm², p = 0.02; superficial parafoveal VD 48.01 ± 3.41 versus 50.74 ± 3.67%, p = 0.003; deep parafoveal VD 51.60 ± 3.52 versus 54.45 ± 4.19%, p = 0.004; CD inside disc 49.75 ± 4.84 versus 53.19 ± 4.04%, p = 0.003). In the NDR subjects, logMAR BCVA (β = - 0.55, p < 0.01) and FAZ (r = - 0.62, p < 0.01) showed a significant negative correlation with superficial total VD, respectively.

CONCLUSIONS

Preclinical DR can be detected by OCTA. Parameters such as FAZ, PERIM, CCF, VD and CD may be useful for early detection of microvascular impairments in DM patients with NDR. Superficial VD and FAZ are possible sensitive visual acuity predictors in NDR subjects. OCTA may be a promising non-invasive tool in daily DR screening.