目的：评估超脉冲二氧化碳(CO₂)激光治疗不同类型眼睑肿物的疗效和安全性。方法：纳入50例眼睑肿物患者，其中男12例、女38例。患者年龄4~84岁。肿物类型包括眼睑色素痣、睑黄瘤、分裂痣、眼睑疣等，其中25例累及眼睑灰线，10例肿物直径>10 mm。所有患者接受超脉冲CO₂激光治疗，并进行术后随访。治疗效果通过术后数码照片评估，同时记录术后1个月并发症发生情况。结果：50例眼睑肿物总体治愈率为92%，有效率达到100%。4例眼睑色素痣在治疗后1个月内复发。术后并发症主要包括轻微倒睫(5例)、睫毛稀疏部分缺失(4例)和瘢痕增生及色素沉着(4例)，未出现其他严重并发症。结论：对于眼睑肿物，特别是睑缘肿物及大肿物，超脉冲CO₂激光是一种更为精确、微创、安全有效的治疗方法，可作为眼睑肿物治疗的优选方案。

Objective: To evaluate the efficacy and safety of ultrapulse carbon dioxide (CO₂) laser in the treatment for various types of eyelid tumors. Methods: A total of 50 patients, including 12 males and 38 females,with eyelid tumors were included in the study The age range is  from 4 to 84 years, with an average age of 37.9±20.0 years. The tumors found in our study include eyelid pigmented nevus, xanthelasma, divided nevus, and molluscum. Among them, 25 cases involved the gray line of the eyelid,and 10 cases had a tumor diameter greater than 10 mm. All patients underwent ultrapulse CO₂ laser treatment and postoperative follow-up. The treatment outcomes were assessed through digital photos, and complications were recorded one month after surgery. Results: The total cure rate of the 50 cases of eyelid tumors in our study was 92%, with the effective rate reaching 100%. 4 cases of eyelid pigmented nevi recurred within one month after treatment, while all other patients were cured. Postoperative complications mainly included minor trichiasis (5 cases), partial sparse to absent eyelashes (4 cases), and hypertrophic scar with hyperpigmentation (4 cases). No other serious complications were reported in our study. Conclusions: For eyelid tumors, especially eyelid margin and larger tumors, the ultrapulse CO₂ laser is a more precise, minimally invasive, safe and effective treatment method. It can be used as a preferred treatment option for eyelid tumors, and should be promoted widely in clinical practice.

近年来随着人口老龄化的发展、人群用眼方式的改变，现有的眼科医疗资源正越来越难以满足日渐增长的医疗需求，亟需新型的诊疗模式予以补足。眼科人工智能作为眼科领域的新兴元素，在眼病的筛查诊断中发展迅速，主要表现为“眼部图像数据+人工智能”的模式。近年来，随着该模式在白内障、青光眼、糖尿病性视网膜病变(diabetic retinopathy，DR)等常见病中研究的深入，相关技术日渐成熟，表现出了较大的应用优势与应用前景，部分技术甚至成功转化并被逐渐应用于临床。眼科诊疗向智慧医学模式的过渡，有望缓解日益增长的医疗需求与紧缺的医疗资源之间的矛盾，从而提高整体的医疗服务水平。

The development of population aging and changes in the way people use their eyes over the recent years have increasingly challenged the existing ophthalmic medical resources to meet the growing medical needs, thus urgently calling for a novel diagnostic and treatment mode. Despite its status as an emerging sector in ophthalmology, ophthalmic artificial intelligence has developed rapidly in the screening and diagnosis of eye diseases, as can be seen in practices adopting the “eye imaging data + AI” mode. In recent years, with the intensified research on this mode with respect to common diseases such as cataract, glaucoma and diabetic retinopathy, relevant technologies have grown increasingly mature, presenting undeniable application superiority and prospects. Some of the relevant technical achievements have also been successfully transformed for practical usage, and are gradually being applied to clinical practices. Ophthalmic diagnosis and treatment are transitioning toward the era of intelligent medical services, which are expected to reduce the contradictions between the growing medical needs and the shortage of medical resources, as well as ultimately improve the overall experience of medical services.

阿尔茨海默病(Alzheimer’s disease，AD)是发生于老年期或老年前期的中枢神经系统退行性病变，以进行性认知功能障碍为特征。随着社会老龄化加剧，AD已成为全球公共卫生问题，亟需研发更敏感、便捷和经济的筛查技术进行早期防控。眼球运动与认知功能密切相关，且眼球运动检查有非侵入性、成本低、检查时间短等优点。研究眼球运动异常和认知功能障碍之间的相关性，有助于研发更简便易操作的认知功能障碍筛查工具。随着人工智能技术的发展，机器学习算法强大的特征提取和计算能力对处理眼球运动检查结果有显著优势。本文对既往AD患者与眼球运动异常之间的相关性研究进行综述，并对机器学习算法模型辅助下，基于眼球运动异常模式进行认知功能障碍早期筛查技术开发的研究前景予以展望。

Alzheimer’s disease (AD) is a degenerative disease of the central nervous system that occurs in old age or early old age. It is characterized by progressive cognitive dysfunction. With the world population aging, AD has become a global public health problem. The development of a more sensitive, convenient, and economic screening technology for AD is urgently needed. The eye movement function is closely related to cognitive function. Moreover, eye movement examination has advantages including non-invasiveness, low cost, and short examination time. Researches on the correlation between abnormal eye movement and cognitive dysfunction can help to develop a simple and easy-to-use screening tool for cognitive dysfunction. With the development of artificial intelligence technology, the dominant feature extraction and computing capabilities of machine learning algorithms have a significant advantage in processing eye movement inspection results. This article reviews the correlation between AD and eye movement abnormalities aiming to provide the research prospects of early screening technology development for cognitive dysfunction based on abnormal eye movement with the application of machine learning models.

近年来随着医疗领域数字化、信息化建设的加速推进，人工智能的应用越来越广泛，在眼科医学方面尤为突出。婴幼儿处于视觉系统发育的关键时期，此时发生的眼病往往会造成不可逆的视功能损伤，带来沉重的家庭和社会负担。然而，由于婴幼儿群体的特殊性以及小儿眼科医生的短缺，开展大规模小儿眼病筛查工作十分困难。最新研究表明：人工智能在先天性白内障、先天性青光眼、斜视、早产儿视网膜病变以及视功能评估等领域已经得到相关应用，在多种婴幼儿眼病的早期筛查、诊断分期、治疗建议等方面都有令人瞩目的表现，有效解决了许多临床难点与痛点。但目前婴幼儿眼科人工智能仍然不如成年人眼科发展充分，亟须进一步的探索和研发。

In recent years, with the acceleration of digitalization and informatization in medical field, artificial intelligence (AI) is more and more widely applied, especially in ophthalmology. Infants are in the critical period of visual development, during which eye diseases can lead to irreversible visual impairment and bring heavy burden to family and society. Due to the particularity of infants and the shortage of pediatric ophthalmologists, it is challenging to carry out large-scale screening for eye diseases of infants. According to the latest studies, AI has been studied and applied in the fields of congenital cataract, congenital glaucoma, strabismus, amblyopia, retinopathy of prematurity, and evaluation of visual function, and it has achieved remarkable performance in the early screening, diagnosis stage and treatment suggestions, solving many clinical difficulties and pain points effectively. However, AI for infantile ophthalmology is not as developed as for adult ophthalmology, so it needs further exploration and development.

慢性移植物抗宿主病(chronic graft-versus-host disease，cGVHD)是骨髓移植后最具有破坏性并发症之一。移植物抗宿主病(graft-versus-host disease，GVHD)发生在10%~80%的造血干细胞移植(hematopoietic stem cell transplantation)受者中，而眼睛是人身体最脆弱的器官之一，有40%~60%接受HSCT的患者发生眼部GVHD，它主要影响泪腺、睑板腺、角膜和结膜等。cGVHD相关性干眼(dry eye associated with chronic graft-versus-host disease，cGVHD-DE)是眼部GVHD最多见的表现形式。cGVHD-DE的长期治疗因涉及多学科、多重结合治疗，至今仍然具有挑战性，其除了全身免疫抑制和眼部润滑剂外，通常还使用局部类固醇、环孢霉素和他克莫司滴眼液。针对中度和重度cGVHD-DE的治疗干预包括使用自体血清滴眼液和佩戴巩膜镜等，新兴起的治疗方案包括重链透明质酸 (heavy chain-hvaluronan/穿透素(pentraxin 3)结膜下注射、间充质基质细胞静脉注射、抑制纤维化药物等。

Chronic graft-versus-host disease (cGVHD) is one of the most devastating complications following bone marrow transplantation. GVHD develops in 10–80% of patients after hematopoietic stem cell transplantation (HSCT). The eye is one of the most vulnerable organs of the human body. Ocular GVHD occurs in 40–60% of patients with GVHD undergoing HSCT, and it mostly affects the lacrimal glands, meibomian glands, cornea, and conjunctiva. The most common form of ocular GVHD is dry eye disease (DED). The long-term treatment of cGVHD-related dry eye syndrome remains challenging and involves a multidisciplinary approach. Besides systemic immunosuppression and ocular lubricants, topical steroids, topical cyclosporine, and topical tacrolimus are commonly prescribed. Newer therapeutic interventions for moderate and severe cGVHD-related DED include using serum eye drops and scleral contact lenses. Emerging treatment options include subconjunctival injection of heavy chain-hyaluronan (HC-HA)/ pentraxin 3 (PTX3), intravenous injection of mesenchymal stromal cells, antifibrotic drugs, etc. This article reviews the mechanisms, clinical findings, and treatment of cGVHD-related dry eye syndrome.

全身疾病通过一定途径累及眼球，产生眼部病变，这些眼部病变的严重程度与全身疾病的进展密切相关。人工智能(artificial intelligence，AI)通过识别眼部病变，可以实现对全身疾病的评估，从而实现全身疾病早期诊断。检测巩膜黄染程度可评估黄疸；检测眼球后动脉血流动力学可评估肝硬化；检测视盘水肿，黄斑变性可评估慢性肾病(chronic kidney disease，CKD)进展；检测眼底血管损伤可评估糖尿病、高血压、动脉粥样硬化。临床医生可以通过眼部影像评估全身疾病的风险，其准确度依赖于临床医生的经验水平，而AI识别眼部病变评估全身疾病的准确度可与临床医生相媲美，在联合多种检测指标后，AI模型的特异性与敏感度均可得到显著提升，因此，充分利用AI可实现全身疾病的早诊早治。

Systemic diseases affect eyeballs through certain ways, resulting in eye diseases; The severity of eye diseases is closely related to the progress of systemic diseases. By identifying eye diseases, artificial intelligence (AI) can assess systemic diseases, so as to make early diagnosis of systemic diseases. For example, detection of the degree of icteric sclera can be used to assess jaundice. Detection of the hemodynamics of posterior eyeball can be used to evaluate cirrhosis. Detection of optic disc edema and macular degeneration can be used to evaluate the progress of chronic kidney disease (CKD). Detection of ocular fundus vascular injury can be used to assess diabetes, hypertension and atherosclerosis. Clinicians can estimate the risk of systemic diseases through eye images, and its accuracy depends on the experience level of clinicians, while the accuracy of AI in identifying eye diseases and evaluating systemic diseases can be comparable to clinicians. After combining various detection indexes, the specificity and sensitivity of AI model can be significantly improved, so early diagnosis and early treatment of systemic diseases can be realized by making full use of AI.

外泌体(exosome)是直径30 nm~150 nm的纳米级囊泡，由脂质双分子层、蛋白质和遗传物质组成。人体内几乎所有类型的细胞都能分泌外泌体。它们在细胞通信、免疫调节、炎症反应和新生血管形成中起着关键作用。目前，外泌体已在肿瘤、心血管及泌尿系统中得到广泛研究。近年来，外泌体在眼科疾病中的作用受到越来越多的关注。外泌体在角膜病变、年龄相关性黄斑病变、糖尿病视网膜病变、青光眼等常见眼科疾病的发生、发展中发挥重要作用。不同间充质干细胞来源的外泌体在眼科疾病中的治疗潜力是当下的热点。间充质干细胞来源的外泌体具有与间充质干细胞相似的抗炎、抗凋亡、神经保护和组织修复的作用，因此外泌体可能是多种眼科疾病无细胞疗法治疗研究的新方向。进一步了解外泌体的生物学特性以及外泌体在眼科疾病的最新研究进展，将为相关眼病的发生机制和防治策略提供参考依据。

Exosomes are nanoscale vesicles with a diameter of 30 nm to 150 nm, which are composed of lipid bilayers, proteins, and genetic material. Almost all types of cells in the human body can secrete exosomes. Tey play key roles in cellular communication, immune regulation, infammatory responses and neovascularization. At present, exosomes have been widely studied in tumors, cardiovascular and urinary systems. In recent years, the role of exosomes in eye diseases has attracted more and more attention. The exosomes play an important role in the occurrence and development of common eye diseases such as keratopathy, age-related macular disease, diabetic retinopathy, glaucoma, etc. Currently it is a hot topic that the therapeutic potential of extracellular vesicles derived from diferent mesenchymal stem cells in eye  diseases. Te exosomes derived from mesenchymal stem cells have anti-infammatory, anti apoptotic, neuroprotective and tissue repairing effects, which are similar to those of mesenchymal stem cells. Thus, exosomes may be a novel direction of research in the treatment of many eye diseases without cell therapy. Further understanding of the biological characteristics of exosomes and the latest research progress of exosomes in common eye diseases will provide reference for the pathogenesis and prevention strategies of related eye diseases.

随着智能手机覆盖率的增加与可用性的提升，实现智能健康管理的应用程序成为新兴研究热点。新一代智能手机可通过追踪步数，监测心率、睡眠，拍摄照片等方式进行健康分析，成为新的医学辅助工具。随着深度学习技术在图像处理领域的不断进展，基于医学影像的智能诊断已在多个学科全面开花,有望彻底改变医院传统的眼科疾病诊疗模式。眼科疾病的常规诊断往往依赖于各种形式的图像，如裂隙灯生物显微镜、眼底成像、光学相干断层扫描等。因此，眼科成为医学人工智能发展最快的领域之一。将眼科人工智能诊疗系统部署在智能手机上，有望提高疾病诊断效率和筛查覆盖率，改善医疗资源紧张的现状，具有极大的发展前景。综述的重点是基于深度学习和智能手机的眼病预防与远程诊疗的进展，以糖尿病性视网膜病变、青光眼、白内障3种疾病为例，讲述深度学习和智能手机在眼病管理方面的具体研究、应用和展望。

With the increasing coverage and availability of smart phones, the application of realizing intelligent health management has become an emerging research hotspot. The new generation of smart phones can perform health analysis by tracking the step numbers, monitoring heart rate and sleep quality, taking photos and other approaches, thereby becoming a new medical aid tool. With the continuous development of deep learning technology in the field of image processing, intelligent diagnosis based on medical imaging has blossomed in many disciplines, which is expected to completely change the traditional eye diseases diagnosis and treatment mode of hospitals. The conventional diagnosis of ophthalmic diseases often relies on various forms of images, such as slit lamp biological microscope, fundus imaging, optical coherence tomography, etc. As a result, ophthalmology has become one of the fastest growing areas of medical artificial intelligence (AI). The deployment of ophthalmological AI diagnosis and treatment system on smart phones is expected to improve the diagnostic efficiency and screening coverage to relieve the strain of medical resources, which has a great development prospect. This review focuses on the prevention and telemedicine progress of eye diseases based on deep learning and smart phones, taking diabetic retinopathy, glaucoma and cataract as examples to describe the specific research, application and prospect of deep learning and smart phones in the management of eye diseases.

近视防控已经上升到我国国家战略层面，高度近视引起的视神经病变会损害视功能，但在临床上常常被忽视。OCT可以非侵入、高分辨率、快速以及可重复地定量视网膜各层厚度，是评估高度近视相关视神经病变的有力工具。由于高度近视常合并视盘和盘周的改变，视神经纤维层厚度的定量常出现误差。近年来，学者开始聚焦于黄斑区神经节细胞复合体(ganglion cell complex,GCC)厚度的研究，但其在高度近视眼中的变化规律尚不统一。该文针对近年来高度近视眼黄斑区GCC的测量规范、诊断价值、变化规律等进行综述，以期提高眼科医师对高度近视视神经病变的重视和研究水平。

Myopia prevention and control has risen to the national strategic level in China. Optic neuropathy caused by high myopia can damage visual function, but it is often ignored in clinical practice Optical coherence tomography (OCT) characterized by non-invasiveness, high resolution, rapid, and repeatable quantifying the thickness of each layer in the retina has emerged as a powerful tool for evaluating high myopia related optic neuropathy. Due to the changes in and near the optic disc in high myopia, errors often occur in the quantification of the thickness of the optic nerve fiber layer. In recent years, researchers have gradually focused on the study of the thickness of ganglion cell complex (GCC), but the regularity of its changes in high myopia is not yet unified. This article reviews the measurement specifications, diagnostic values, and change rules of GCC in the macular region of high myopia in recent years, in order to improve the attention and research level of ophthalmologists on high myopia optic neuropathy.

人工智能(artificial intelligence, AI)在医学领域的广泛应用为探索眼部与全身健康的关系提供了新的机遇。文章回顾了眼科AI在心血管健康、神经系统健康、肾脏健康和衰老过程中的应用。在心血管健康方面，AI能够通过分析眼底图像预测心血管疾病风险因素和未来心血管事件，并提供了简便、有效的风险分层方法。在神经系统健康方面，眼科AI在阿尔茨海默病早期诊断和帕金森病识别方面显示出潜力，尽管对未来事件预测仍具挑战性。针对多发性硬化，眼科AI在诊断和预测残疾进程上展现了良好效果。在肾脏健康中，眼科AI技术通过分析视网膜图像可预测肾功能相关指标、直接检测肾病事件，展示了其在改善肾病筛查方式和减轻医疗负担方面的潜力。在衰老过程中，AI能够利用眼部图像预测生物年龄、视网膜年龄差和晶状体年龄等参数提供了生物衰老指标，为理解衰老与眼部健康的关联提供了新视角。

The widespread application of artificial intelligence (AI) in the medical field has provided new opportunities to explore the relationship between eye and whole body health. This article reviews the application of ophthalmic AI in cardiovascular health, neurological health and aging. In terms of cardiovascular health, AI can predict cardiovascular disease risk factors and future cardiovascular events by analyzing fundus images, and provides a simple and effective risk stratification method. In terms of neurological health, ophthalmic AI shows potential in early diagnosis of Alzheimer's disease and identification of Parkinson's disease, although the prediction of future events remains challenging. For multiple sclerosis, ophthalmic AI has shown good results in diagnosing and predicting the progression of disability. In kidney health, ophthalmic AI technology can predict kidney function-related parameters and detect kidney disease events by analyzing retinal images, demonstrating its potential in improving kidney disease screening methods and reducing medical burdens. In the aging process, AI can use eye images to predict biological age. Parameters such as retinal age gap and LensAge provide biological aging indicators, providing a new perspective for understanding the relationship between aging and eye health.