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Crossover to PDT after the unsuccessful micropulse laser treatment of central serous chorioretinopathy 微脉冲激光治疗中心性浆液性脉络膜视网膜病变失败后转用光导疗法
Pub Date : 2024-02-01 DOI: 10.1016/j.aopr.2024.01.004
Maciej Gawęcki , Krzysztof Kiciński , Andrzej Grzybowski

Purpose

Subthreshold micropulse laser (SML) and photodynamic therapy (PDT) are among the most effective therapeutic modalities applied to central serous chorioretinopathy (CSCR). This study aimed to evaluate the efficacy and durability of PDT in CSCR cases unresponsive to at least two SML treatments.

Methods

The study included 26 consecutive eyes of 24 patients (21 males and three females) with chronic CSCR. In all cases, a lack of reduction in subretinal fluid (SRF) levels was noted after at least two consecutive SML sessions. The parameters of best corrected visual acuity (BCVA) and spectral domain optical coherence tomography (SD-OCT) were evaluated at baseline and 1, 3 and 12 months post-PDT.

Results

The mean duration of symptoms in the group was 53.81 ± 39.48 months, the mean age of the patients was 49.26 ± 12.91 years, and the mean subfoveal choroidal thickness (SFCT) was 572.11 ± 116.21 mm. Complete resorption of SRF was observed in 21 out of 26 eyes (80.77%) at 1 month and sustained in 18 cases (69.23%) at 12 months. At 12 months, in the sustained group, BCVA improved significantly from 0.39 ± 0.18 to 0.19 ± 0.2 logMAR (P = 0.01), central subfoveal thickness (CST) reduced from 316.44 ± 75.83 mm to 197.67 ± 22.99 mm (P < 0.0001), and SFCT reduced from 579.28 mm to 446.78 mm (P < 0.0001).

Conclusions

PDT provides the opportunity for the successful treatment of CSCR unresponsive to SML treatment. Improvements are possible even in cases with a long duration of symptoms and significant alterations in retinal morphology. Thus, PDT should be considered for patients with prominently increased choroidal thickness.

目的阈下微脉冲激光(SML)和光动力疗法(PDT)是治疗中心性浆液性脉络膜视网膜病变(CSCR)最有效的治疗方法之一。本研究旨在评估光动力疗法对至少两次 SML 治疗无效的 CSCR 病例的疗效和持久性。在所有病例中,经过至少两次连续的 SML 治疗后,视网膜下积液(SRF)水平均未下降。结果该组患者的平均病程为(53.81±39.48)个月,平均年龄为(49.26±12.91)岁,平均视网膜下脉络膜厚度(SFCT)为(572.11±116.21)毫米。26只眼睛中有21只(80.77%)在1个月时观察到SRF完全吸收,18只(69.23%)在12个月时观察到SRF持续吸收。12 个月时,持续组的 BCVA 从 0.39 ± 0.18 显著改善到 0.19 ± 0.2 logMAR(P = 0.01),中央眼底厚度(CST)从 316.44 ± 75.83 mm 减少到 197.结论PDT为成功治疗对SML治疗无反应的CSCR提供了机会。即使是症状持续时间较长、视网膜形态发生显著改变的病例,也有可能获得改善。因此,脉络膜厚度明显增加的患者应考虑使用 PDT。
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引用次数: 0
An assessment of the capability of ChatGPT in solving clinical cases of ophthalmology using multiple choice and short answer questions 评估 ChatGPT 使用选择题和简答题解决眼科临床病例的能力
Pub Date : 2024-01-19 DOI: 10.1016/j.aopr.2024.01.005
Anjana Christy Alexander , Suprithy Somineni Raghupathy , Krishna Mohan Surapaneni
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引用次数: 0
Is relying on RNFL specific enough to identify any changes in the CNS? 依靠 RNFL 的特异性是否足以识别中枢神经系统的任何变化?
Pub Date : 2024-01-17 DOI: 10.1016/j.aopr.2024.01.002
Dzakky Avecienna Nur Faridwazdi, Yuliono Trika Nur Hasan, Alvi Milliana, Zulvikar Syambani Ulhaq
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引用次数: 0
Evaluation of choroidal thickness and retinal nerve fiber layer thickness in Chinese pregnant women and healthy non-pregnant women 评估中国孕妇和健康非孕妇的脉络膜厚度和视网膜神经纤维层厚度
Pub Date : 2023-12-06 DOI: 10.1016/j.aopr.2023.12.001
Hanfei Wu , Haishuang Lin , Mengting Ruan , Huanjie Fang , Nannan Dong , Tiewei Wang , Feifei Yu , Jiawei Zhao

Purpose

To evaluate choroidal thickness and retinal nerve fiber layer (RNFL) thickness in different trimesters using enhanced depth imaging optical coherence tomography (EDI-OCT).

Methods

A prospective comparative study included 45 healthy pregnant women in the first trimester, 45 women in the second, 45 women in the third and 45 healthy non-pregnant women as the control group. Macular choroidal thickness was measured at three locations: The subfoveal, 1 ​mm temporal, and 1 ​mm nasal from the fovea with EDI-OCT. Peripapillary choroidal thickness (PPCT) and RNFL thickness parameters were automatically calculated by the Spectralis OCT.

Results

The subfoveal, temporal and nasal macular choroidal thickness were all significantly thicker in the second trimester, compared with those parameters in the first, the third trimesters and the control group (all P ​< ​0.05). The PPCT was significantly increased in the second trimeter compared with the control group at global, temporal, temporal inferior, nasal and nasal inferior positions (all P ​< ​0.05). The RNFL thickness was also significantly increased in pregnant women at nasal superior and nasal inferior quadrants (all P ​< ​0.05).

Conclusions

The choroidal thickness in pregnant women was found to be thicker than the control group, regardless of macular or optic disc location. Findings of RNFL thickening might indicate subclinical involvement of the central nervous system.

目的 使用增强型深度成像光学相干断层扫描(EDI-OCT)评估不同孕期的脉络膜厚度和视网膜神经纤维层(RNFL)厚度。方法 一项前瞻性比较研究纳入了 45 名健康孕妇,包括孕期前三个月的孕妇、孕期后三个月的孕妇、孕期前三个月的孕妇以及作为对照组的 45 名健康非孕妇。在三个位置测量黄斑脉络膜厚度:使用 EDI-OCT 在三个位置测量黄斑脉络膜厚度:眼窝下、距离眼窝 1 毫米的颞侧和 1 毫米的鼻侧。结果与妊娠头三个月、妊娠三个月和对照组相比,妊娠后三个月的眼底、颞侧和鼻侧黄斑脉络膜厚度均明显增厚(均为 P <0.05)。与对照组相比,妊娠中期的 PPCT 在全球、颞、颞下、鼻和鼻下位置均明显增加(均为 P < 0.05)。结论无论黄斑或视盘位置如何,孕妇的脉络膜厚度都比对照组厚。RNFL增厚的发现可能表明中枢神经系统受到亚临床影响。
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引用次数: 0
Global research on artificial intelligence in thyroid-associated ophthalmopathy: A bibliometric analysis 全球甲状腺相关眼病人工智能研究:文献计量分析
Pub Date : 2023-11-30 DOI: 10.1016/j.aopr.2023.11.002
Xiaobin Zhang

Purpose

To provide an overview of global publications on artificial intelligence (AI) in thyroid-associated ophthalmopathy (TAO) through bibliometric analysis.

Methods

Publications related to AI in TAO from inception until April 2023 were retrieved from the Web of Science database. The trends of publications and citations, publishing performance, collaboration among countries and institutions, and the funding agencies, relevant research domains, leading journals, hotspots and their evolution were identified.

Results

A total of 55 publications were included for analysis. The number of publications and citations continued to grow since 1998, with a significant acceleration of growth after 2020. China is the most productive country with the highest number of productive institutions, followed by the United States. European countries have the most extensive collaboration. The most relevant research domain was radiology, nuclear medicine & medical imaging. The European Journal of Radiology was one of the most productive journals, with the most influential articles published. "Thyroid-associated ophthalmopathy" and "neural network" maintain hotspots during the entire period. Studies were more focused on clinical features during 1998 and 2016, clinical features and medical data during 2017 and 2020, and medical data and AI techniques during 2021 and 2023.

Conclusions

This study summarized the global research status regarding AI in TAO in terms of trends, countries, institutions, research domains, journals, and key topics. AI has shown great potential in TAO. Sponsored by funding agencies such as NSFC, China has become the most productive country in the field of AI in TAO. Our findings help researchers better understand the development of this field and provide valuable clues for future research directions.

目的 通过文献计量学分析,概述人工智能(AI)在甲状腺相关性眼病(TAO)中的全球发表情况。方法 从Web of Science数据库中检索了从开始到2023年4月与人工智能在TAO中的应用相关的出版物。结果共纳入 55 篇论文进行分析。自 1998 年以来,论文数量和引用次数持续增长,2020 年后增长速度明显加快。中国是成果最多的国家,拥有最多的成果机构,其次是美国。欧洲国家的合作最为广泛。最相关的研究领域是放射学、核医学和医学成像。欧洲放射学杂志》是成果最多的杂志之一,发表的文章最具影响力。"甲状腺相关性眼病 "和 "神经网络 "是整个研究期间的热点。1998年和2016年的研究更关注临床特征,2017年和2020年的研究更关注临床特征和医学数据,2021年和2023年的研究更关注医学数据和人工智能技术。结论本研究从趋势、国家、机构、研究领域、期刊和关键主题等方面总结了全球人工智能在TAO领域的研究现状。人工智能在医疗卫生领域显示出巨大潜力。在国家自然科学基金委等资助机构的赞助下,中国已成为人工智能在航空航天领域最有成效的国家。我们的研究结果有助于研究人员更好地了解这一领域的发展,并为未来的研究方向提供有价值的线索。
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引用次数: 0
Search of inhibitors of aldose reductase for treatment of diabetic cataracts using machine learning 利用机器学习寻找醛糖还原酶抑制剂治疗糖尿病性白内障。
Pub Date : 2023-11-01 DOI: 10.1016/j.aopr.2023.09.002
Trevor Chen , Richard Chen , Alvin You , Valentina L. Kouznetsova , Igor F. Tsigelny

Purpose

Patients with diabetes mellitus have an elevated chance of developing cataracts, a degenerative vision-impairing condition often needing surgery. The process of the reduction of glucose to sorbitol in the lens of the human eye that causes cataracts is managed by the Aldose Reductase Enzyme (AR), and it is been found that AR inhibitors may mitigate the onset of diabetic cataracts. There exists a large pool of natural and synthetic AR inhibitors that can prevent diabetic complications, and the development of a machine-learning (ML) prediction model may bring new AR inhibitors with better characteristics into clinical use.

Methods

Using known AR inhibitors and their chemical-physical descriptors we created the ML model for prediction of new AR inhibitors. The predicted inhibitors were tested by computational docking to the binding site of AR.

Results

Using cross-validation in order to find the most accurate ML model, we ended with final cross-validation accuracy of 90%. Computational docking testing of the predicted inhibitors gave a high level of correlation between the ML prediction score and binding free energy.

Conclusions

Currently known AR inhibitors are not used yet for patients for several reasons. We think that new predicted AR inhibitors have the potential to possess more favorable characteristics to be successfully implemented after clinical testing. Exploring new inhibitors can improve patient well-being and lower surgical complications all while decreasing long-term medical expenses.

目的:糖尿病患者患白内障的几率较高,白内障是一种退行性视力受损的疾病,通常需要手术治疗。导致白内障的人眼晶状体中葡萄糖还原为山梨醇的过程由醛糖还原酶(AR)控制,已经发现AR抑制剂可以减轻糖尿病性白内障的发作。存在大量可以预防糖尿病并发症的天然和合成AR抑制剂,机器学习(ML)预测模型的开发可能会使具有更好特性的新型AR抑制剂投入临床使用。方法:使用已知的AR抑制剂及其化学-物理描述符,我们创建了预测新AR抑制剂的ML模型。预测的抑制剂通过与AR结合位点的计算对接进行了测试。结果:使用交叉验证,为了找到最准确的ML模型,我们最终的交叉验证准确率为90%。预测抑制剂的计算对接测试给出了ML预测分数和结合自由能之间的高度相关性。结论:由于多种原因,目前已知的AR抑制剂尚未用于患者。我们认为,新的预测AR抑制剂有可能具有更有利的特性,在临床测试后成功实施。探索新的抑制剂可以改善患者的健康状况,降低手术并发症,同时减少长期医疗费用。
{"title":"Search of inhibitors of aldose reductase for treatment of diabetic cataracts using machine learning","authors":"Trevor Chen ,&nbsp;Richard Chen ,&nbsp;Alvin You ,&nbsp;Valentina L. Kouznetsova ,&nbsp;Igor F. Tsigelny","doi":"10.1016/j.aopr.2023.09.002","DOIUrl":"10.1016/j.aopr.2023.09.002","url":null,"abstract":"<div><h3>Purpose</h3><p>Patients with diabetes mellitus have an elevated chance of developing cataracts, a degenerative vision-impairing condition often needing surgery. The process of the reduction of glucose to sorbitol in the lens of the human eye that causes cataracts is managed by the Aldose Reductase Enzyme (AR), and it is been found that AR inhibitors may mitigate the onset of diabetic cataracts. There exists a large pool of natural and synthetic AR inhibitors that can prevent diabetic complications, and the development of a machine-learning (ML) prediction model may bring new AR inhibitors with better characteristics into clinical use.</p></div><div><h3>Methods</h3><p>Using known AR inhibitors and their chemical-physical descriptors we created the ML model for prediction of new AR inhibitors. The predicted inhibitors were tested by computational docking to the binding site of AR.</p></div><div><h3>Results</h3><p>Using cross-validation in order to find the most accurate ML model, we ended with final cross-validation accuracy of 90%. Computational docking testing of the predicted inhibitors gave a high level of correlation between the ML prediction score and binding free energy.</p></div><div><h3>Conclusions</h3><p>Currently known AR inhibitors are not used yet for patients for several reasons. We think that new predicted AR inhibitors have the potential to possess more favorable characteristics to be successfully implemented after clinical testing. Exploring new inhibitors can improve patient well-being and lower surgical complications all while decreasing long-term medical expenses.</p></div>","PeriodicalId":72103,"journal":{"name":"Advances in ophthalmology practice and research","volume":"3 4","pages":"Pages 187-191"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71489518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
TOC 技术选择委员会
Pub Date : 2023-11-01 DOI: 10.1016/S2667-3762(23)00057-4
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引用次数: 0
A deep learning model for generating fundus autofluorescence images from color fundus photography 彩色眼底摄影生成眼底自体荧光图像的深度学习模型
Pub Date : 2023-11-01 DOI: 10.1016/j.aopr.2023.11.001
Fan Song , Weiyi Zhang , Yingfeng Zheng , Danli Shi , Mingguang He

Background

Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD).

Methods

A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset.

Results

A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968.

Conclusions

This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.

眼底自体荧光(FAF)是一种有价值的成像技术,用于评估视网膜色素上皮(RPE)与各种年龄相关和疾病相关变化相关的代谢改变。FAF的实际应用正在不断增长。本研究旨在评估生成式深度学习(DL)模型在将彩色眼底(CF)图像转化为合成FAF图像方面的有效性,并探讨其在增强年龄相关性黄斑变性(AMD)筛查方面的潜力。在CF和FAF图像对上训练生成对抗网络(GAN)模型,生成合成FAF图像。采用常用的生成指标客观评价合成FAF图像的质量。此外,使用LabelMe数据集,通过测量曲线下面积(AUC)来评估生成的FAF图像在AMD分类中的临床有效性。共分析2586例患者的8410张FAF图像。合成的FAF图像表现出令人印象深刻的客观评价质量,实现了0.67的多尺度结构相似指数(MS-SSIM)。当在LabelMe数据集上进行评估时,生成的FAF图像和CF图像组合在AMD分类精度上有了显著的提高,AUC从0.931提高到0.968。本研究首次尝试使用生成式深度学习模型从CF图像中创建真实且高质量的FAF图像。将翻译后的FAF图像合并到CF图像上,提高了AMD分类的准确性。总的来说,这项研究提出了一种有希望的方法来加强大规模AMD筛查。
{"title":"A deep learning model for generating fundus autofluorescence images from color fundus photography","authors":"Fan Song ,&nbsp;Weiyi Zhang ,&nbsp;Yingfeng Zheng ,&nbsp;Danli Shi ,&nbsp;Mingguang He","doi":"10.1016/j.aopr.2023.11.001","DOIUrl":"10.1016/j.aopr.2023.11.001","url":null,"abstract":"<div><h3>Background</h3><p>Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD).</p></div><div><h3>Methods</h3><p>A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset.</p></div><div><h3>Results</h3><p>A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968.</p></div><div><h3>Conclusions</h3><p>This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.</p></div>","PeriodicalId":72103,"journal":{"name":"Advances in ophthalmology practice and research","volume":"3 4","pages":"Pages 192-198"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266737622300032X/pdfft?md5=ab962b7e180285dcce3d53b2bce956a7&pid=1-s2.0-S266737622300032X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135614131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Oxidative stress, epigenetic regulation and pathological processes of lens epithelial cells underlying diabetic cataract 糖尿病性白内障晶状体上皮细胞的氧化应激、表观遗传调控及病理过程
Pub Date : 2023-10-05 DOI: 10.1016/j.aopr.2023.10.001
Zaoxia Guo , Xiaopan Ma , Rui Xue Zhang , Hong Yan

Background

Cataract is a blinding disease worldwide. It is an age-related disease that mainly occurs in people over 65 years old. Cataract is also prevalent in patients with diabetes mellites (DM). The pathological mechanisms underlying diabetic cataract (DC) are more complex than that of age-related cataract. Studies have identified that polyol pathway, advanced glycation end products (AGEs) and oxidative stress are the primary pathogenesis of DC. In recent years, molecular-level regulations and pathological processes of lens epithelial cells (LECs) have been confirmed to play roles in the initiation and progression of DC. A comprehensive understanding and elucidation of how chronic hyperglycemia drives molecular-level regulations and cytopathological processes in the lens will shed lights on the prevention, delay and treatment of DC.

Main text

Excessive glucose in the lens enhances polyol pathway and AGEs formation. Polyol pathway causes imbalance in the ratio of NADPH/NADP+ and NADH/NAD+. Decrease in NADPH/NADP+ ratio compromises antioxidant enzymes, while increase in NADH/NAD+ ratio promotes reactive oxygen species (ROS) overproduction in mitochondria, resulting in oxidative stress. Oxidative stress in the lens causes oxidation of DNA, proteins and lipids, leading to abnormalities in their structure and functions. Glycation of proteins by AGEs decreases solubility of proteins. High glucose triggered epigenetic regulations directly or indirectly affect expressions of genes and proteins in LECs. Changes in autophagic activity, increases in fibrosis and apoptosis of LECs destroy the morphological structure and physiological functions of the lens epithelium, disrupting lens homeostasis.

Conclusions

In both diabetic animal models and diabetics, oxidative stress plays crucial roles in the formation of cataract. Epigenetic regulations, include lncRNA, circRNA, microRNA, methylation of RNA and DNA, histone acetylation and pathological processes, include autophagy, fibrosis and apoptosis of LECs also involved in DC.

背景白内障是一种全球性的致盲性疾病。它是一种与年龄相关的疾病,主要发生在65岁以上的人群中。白内障在患有糖尿病的患者中也很普遍。糖尿病性白内障(DC)的病理机制比年龄相关性白内障更为复杂。研究表明,多元醇途径、晚期糖基化终产物(AGEs)和氧化应激是DC的主要发病机制。近年来,晶状体上皮细胞(LECs)的分子水平调控和病理过程已被证实在DC的发生和发展中发挥作用。全面了解和阐明慢性高血糖如何驱动晶状体中的分子水平调节和细胞病理过程,将有助于DC的预防、延迟和治疗。正文晶状体中过量的葡萄糖会增强多元醇途径和AGEs的形成。多元醇途径导致NADPH/NADP+和NADH/NAD+的比例失衡。NADPH/NADP+比率的降低会损害抗氧化酶,而NADH/NAD+比率的增加会促进线粒体中活性氧(ROS)的过量产生,从而导致氧化应激。晶状体中的氧化应激会导致DNA、蛋白质和脂质的氧化,导致其结构和功能异常。AGEs对蛋白质的糖化作用降低了蛋白质的溶解度。高糖触发的表观遗传调控直接或间接影响LECs中基因和蛋白质的表达。LECs自噬活性的变化、纤维化的增加和细胞凋亡破坏了晶状体上皮的形态结构和生理功能,破坏了晶状体的稳态。结论在糖尿病动物模型和糖尿病模型中,氧化应激在白内障的形成中起着至关重要的作用。表观遗传学调控,包括lncRNA、circRNA、microRNA、RNA和DNA的甲基化、组蛋白乙酰化和病理过程,包括自噬、纤维化和也参与DC的LECs的凋亡。
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引用次数: 0
Development and material characteristics of glaucoma surgical implants 青光眼手术植入物的研制及材料特性
Pub Date : 2023-09-23 DOI: 10.1016/j.aopr.2023.09.001
Qiyu Qin , Chengshou Zhang , Naiji Yu , Fan Jia , Xin Liu , Qi Zhang , Min Chen , Kaijun Wang

Background

Glaucoma is the leading cause of irreversible blindness worldwide. The reduction of intraocular pressure has proved to be the only factor which can be modified in the treatment, and surgical management is one of the important methods for the treatment of glaucoma patients.

Main text

In order to increase aqueous humor outflow and further reduce intraocular pressure, various drainage implants have been designed and applied in clinical practice. From initial Molteno, Baerveldt and Ahmed glaucoma implants to the Ahmed ClearPath device, Paul glaucoma implant, EX-PRESS and the eyeWatch implant, to iStent, Hydrus, XEN, PreserFlo, Cypass, SOLX Gold Shunt, etc., glaucoma surgical implants are currently undergoing a massive transformation on their structures and performances. Multitudinous materials have been used to produce these implants, from original silicone and porous polyethylene, to gelatin, stainless steel, SIBS, titanium, nitinol and even 24-carat gold. Moreover, the material geometry, size, rigidity, biocompatibility and mechanism (valved versus nonvalved) among these implants are markedly different. In this review, we discussed the development and material characteristics of both conventional glaucoma drainage devices and more recent implants, such as the eyeWatch and the new minimally invasive glaucoma surgery (MIGS) devices.

Conclusions

Although different in design and materials, these delicate glaucoma surgical implants have widely expanded the glaucoma surgical methods, and improved the success rate and safety of glaucoma surgery significantly. However, all of these glaucoma surgical implants have various limitations and should be used for different glaucoma patients at different conditions.

背景青光眼是世界范围内不可逆失明的主要原因。眼压降低已被证明是治疗中唯一可以改变的因素,手术治疗是治疗青光眼患者的重要方法之一。为了增加房水流出量,进一步降低眼压,人们设计了各种引流植入物并在临床实践中应用。从最初的Molteno、Baerveldt和Ahmed青光眼植入物到Ahmed ClearPath设备、Paul青光眼植入物、EX-PRESS和eyeWatch植入物,再到iStent、Hydrus、XEN、PreserFlo、Cypass、SOLX Gold Shunt等,青光眼手术植入物目前正在经历结构和性能的巨大转变。多种材料已被用于生产这些植入物,从原始的硅树脂和多孔聚乙烯,到明胶、不锈钢、SIBS、钛、镍钛诺,甚至24克拉黄金。此外,这些植入物的材料几何形状、尺寸、刚度、生物相容性和机制(有阀和无阀)明显不同。在这篇综述中,我们讨论了传统青光眼引流装置和最近的植入物的发展和材料特性,如eyeWatch和新型微创青光眼手术(MIGS)装置。结论尽管在设计和材料上有所不同,但这些精致的青光眼手术植入物广泛扩展了青光眼手术方法,显著提高了青光眼手术的成功率和安全性。然而,所有这些青光眼手术植入物都有各种局限性,应该用于不同条件下的不同青光眼患者。
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引用次数: 0
期刊
Advances in ophthalmology practice and research
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