The corneal wound healing response to Riboflavin-ultraviolet-crosslinking (RIB-UV-CXL) depends on the specific method used in treatment. The predominance of clinical evidence supports the classical "epithelium-off" RIB-UV-CXL method being more effective in halting ectasia progression than various "epithelium-on" methods, where the corneal epithelium is maintained intact. Corneal transparency results from the precise organization of collagen fibrils and extracellular matrix, along with transparent keratocytes. The mild and transient stromal opacity seen after standard RIB-UV-CXL is linked to changes in hydration, cellularity, and matrix composition. As hydration normalizes, opacity arises from the development of corneal fibroblasts and their secretion of disordered extracellular matrix materials including collagens. Over months, as the epithelial basement membrane regenerates, transitioning stromal cells either undergo apoptosis or revert to keratocan-positive keratocytes, restoring stromal transparency. In normal healing after standard RIB-UV-CXL, the stroma is eventually repopulated predominantly by keratocytes without significant persisting fibroblasts, immune cells, or myofibroblasts. Biomechanical studies have extensively explored how CXL strengthens corneal tissue, providing insight into its therapeutic mechanisms. The purpose of this review is to evaluate the wound healing response and biomechanical changes in the cornea following RIB-UV-CXL.

Objectives: to evaluate the feasibility and utility of intraoperative optical coherence tomography (iOCT) utilizing an immersive augmented reality surgical headset (Beyeonics iOCT, Beyeonics Vision Ltd., Haifa, Israel) digital visualization platform with swept-source integrated OCT in ophthalmic surgery. Methods: As part of the Institutional Review Board-approved prospective DISCOVER study, the Beyeonics iOCT was utilized in multiple ophthalmic surgical procedures to evaluate the feasibility and utility of iOCT with this platform. The Beyeonics iOCT is a three-dimensional surgical visualization system that utilizes a swept-source integrated OCT within the digital microscope system. Surgeon feedback on system performance and integration into the surgical workflow was gathered via a prespecified survey. Results: Thirteen eyes of thirteen patients were included in this study. The surgical procedures consisted of four cataract surgeries, two lamellar corneal transplants, one pterygium removal, and six vitreoretinal surgeries. Surgeons were able to successfully view and review the iOCT images within the surgical Head-Mounted Display, eliminating the need for an external display. Utility feedback from surgeons included iOCT assisting with confirming wound architecture, corneal graft orientation, and retinal structure. All surgeries were completed without reverting to a conventional microscope, and no intraoperative adverse events occurred. Conclusions: The new visualization platform with integrated swept-source iOCT demonstrated feasibility and potential utility in multiple ophthalmic surgical platforms. Additional research related to outcomes, ergonomics, and enhanced software analysis is needed in the future.

Purpose: To determine the misclassification rate of the keratoconus percentage (KISA%) index efficacy in eyes with progressive keratoconus. Methods: This was a retrospective case-control study of consecutive patients with confirmed progressive keratoconus and a contemporaneous normal control group with 1.00 diopters or greater regular astigmatism. Scheimpflug imaging (Pentacam HR) was obtained for all patients. KISA% index and inferior-superior (IS) values were obtained from the Pentacam topometric/keratoconus staging map. Receiver operating characteristic curves were generated to determine the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity values. Results: There were 160 eyes from 160 patients evaluated, including 80 eyes from 80 patients with progressive keratoconus and 80 eyes from 80 control patients. There were 20 eyes (25%) with progressive keratoconus misclassified by the KISA% index, with 16 eyes (20%) of the progressive keratoconus cohort classified as normal (ie, KISA% < 60). There were 4 eyes (5%) with progressive keratoconus that would classify as having “normal topography” using the published criteria for very asymmetric ectasia with normal topography of KISA% less than 60 and IS value less than 1.45. All controls had a KISA% index value of less than 15. The optimal cut-off value to distinguish cohorts was 15.31 (AUROC = 0.972, 93.75% sensitivity). KISA% index values of 60 and 100 achieved low sensitivity (80% and 73.75%, respectively). Conclusions: The KISA% index misclassified a significant proportion of eyes with progressive keratoconus as normal. Although highly specific for clinical keratoconus, the KISA% index lacks sensitivity, does not effectively discriminate between normal and abnormal topography, and thus should not be used in large data analysis or artificial intelligence–based modeling. [ J Refract Surg . 2024;40(9):e614–e624.]

Abnormal corneal nerve function and associated disease is a significant public health concern. It is associated with prevalent ocular surface diseases, including dry eye disease. Corneal nerve dysfunction is also a common side effect of refractive surgeries, as well as a symptom of diseases that cause peripheral neuropathies. Here, we demonstrate in vivo calcium imaging of mouse corneal nerves expressing GCaMP6f, a genetically encoded calcium indicator. A custom fluorescence imaging and stereotactic system was designed, allowing for non-contact imaging of the mouse cornea with an air objective. Dynamic imaging of neuronal activity is demonstrated in the various layers of the cornea and in response to local anesthetic administration. This approach demonstrates a less invasive means of assessing corneal nerve function than has been previously used, and has significant potential for studying the effects of ocular diseases, refractive surgeries, and peripheral neuropathies on corneal nerve function, as well as the effectiveness of various therapies to treat corneal nerve dysfunction.

PURPOSE: To review the atypical development of Salzmann's nodular degeneration (SND) after two cases of laser in situ keratomileusis (LASIK) and one case of photorefractive keratomileusis (PRK), and to highlight the pathophysiology of SND and its treatment. METHODS: Three cases of SND (two following LASIK performed with microkeratomes and one following PRK) were reviewed and Pubmed.gov and internet searches were performed. RESULTS: SND is myofibroblast-generated fibrosis in the subepithelial space between the epithelium and Bowman's layer that develops years or decades after traumatic, surgical, infectious, or inflammatory injuries to the cornea in which the epithelial basement membrane is damaged in one or more locations and does not fully regenerate. It is hypothesized based on these cases, and the previous immunohistochemistry of other investigators, that myofibroblast precursors, such as fibrocytes or corneal fibroblasts, that enter the subepithelial space are driven to develop into myofibroblasts, which slowly proliferate and extend the fibrosis, by transforming growth factor-beta from epithelium and tears that passes through the defective epithelial basement membrane. These myofibroblasts and the disordered collagens, and other extracellular matrix components they produce, make up the subepithelial opacity characteristic of SND. Nodules are larger accumulations of myofibroblasts and disordered extracellular matrix. If the injury is associated with damage to the underlying Bowman's layer and stroma, as in LASIK flap generation, then the myofibroblasts and fibrosis can extend into Bowman's layer and the under - lying anterior stroma. CONCLUSIONS: SND fibrosis often extends into Bowman's layer and the anterior stroma if there are associated Bow - man's defects, such as incisions or lacerations. In the latter cases, SND frequently cannot be removed by simple scrape and peel, as typically performed for most common SND cases, but can be trimmed to remove the offending tissue. This condition is more accurately termed Salzmann's subepithelial fibrosis.

Both disease and treatment of the cornea alter its microstructural and biomechanical properties. Previous work showed that dynamic light scattering (DLS) reflects changes in the cornea with respect to crosslinking treatment and post-surgical healing in vivo. However, due to the complex structure of the corneal stroma, the exact mechanisms which give rise to the DLS signal are unclear. This work attempts to determine the cause of DLS in the cornea by comparing the scattering signal under different conditions. The conclusions drawn from these studies inform the use of OCT-based dynamic light scattering measurements for corneal assessment.

Never trust anything that can think for itself if you can't see where it keeps its brain. —J.K. Rowling, Harry Potter and the Chamber of Secrets, 1998 Artificial intelligence (AI) has revolutionized many aspects of our lives, from healthcare to entertainment. But what about academic publishing? AI tools such as ChatGPT (OpenAI, San Francisco, California) and Google Bard (Alphabet, Inc., Mountain View, California) can help researchers conduct literature reviews, write manuscripts, and generate references with ease. However, these tools also pose serious ethical challenges for the academic community. One of the main challenges is plagiarism. How can we ensure that the content generated by AI is original and not copied from existing sources? How can we detect and prevent AI-generated plagiarism, especially when it is imperceptible to human readers and antiplagiarism software? How can we protect the intellectual property rights of the authors and publishers when AI can reproduce their work without permission? Another challenge is authorship. Who should be credited as the author of an AI-generated manuscript? Does AI meet the criteria for authorship, such as making substantial contributions, approving the final version, and being accountable for its accuracy and integrity? How can we acknowledge the role of AI in the writing process without compromising the credibility and reputation of human authors? A third challenge is quality. How can we ensure that the content generated by AI is reliable, valid, and relevant? How can we evaluate and peer review AI-generated manuscripts, especially when they may contain errors, biases, or misinformation? How can we maintain the standards and expectations of academic publishing when AI can produce large volumes of content with minimal human input? These challenges require urgent attention and action from researchers, publishers, editors, reviewers, and policymakers. We need to develop clear and consistent guidelines for using AI in academic publishing, such as declaring and explaining its use, acknowledging its limitations, and verifying its sources. We also need to create robust and transparent mechanisms for detecting and addressing AI-related misconduct, such as plagiarism, fabrication, or falsification. Moreover, we need to foster a culture of ethical awareness and responsibility among researchers who use AI tools, such as educating them about the potential risks and benefits, encouraging them to critically assess their outputs, and reminding them to respect the values and norms of academic publishing. AI has enormous potential to enhance and accelerate scientific communication, but it also poses significant perils that cannot be ignored or underestimated. We must be vigilant and proactive in ensuring that AI is used in a responsible and ethical manner that respects the integrity and quality of academic publishing. Now for a disclosure. The entirety of the text above was generated using a free and nearly ubiquitous browser, Microsoft Edge (Microsoft Corp., Redmond, Washington). Microsoft began offering a version of the generative AI engine ChatGPT in combination with its Bing search engine in February 2023. The text appeared seconds after I typed “perils of generative AI in academic publishing” as a prompt in the “Compose” section of the Microsoft Edge sidebar and selected “Blog” for the writing style. Not a word was changed, and the only addition I made was to add the company locations after each of the cited AI technologies. I would argue that the text could have stood alone as an editorial on the key issues that dominate this topic. I would argue even more strongly that it would be difficult for anyone to differentiate this text from the spontaneous musings of a journal editor. Although generative AI is not new, the remarkable increase in accessibility of generative tools in the past 6 months and the accompanying frenzy of AI-related media stories has catapulted the subject to the forefront of public discourse, perhaps most acutely in the spheres of education and academic publishing. Education at all levels places a premium on the learning process as integral to personal development. This is a domain where “show your work” and “explain your answer” are valued above simply providing an answer. Education is about growth: growth in intellectual prowess, yes, but also growth in character, which often occurs through the stress and strain of a nonlinear path that treats successes and failures as learning opportunities. In academia, the themes of originality, innovation, attribution, and intellectual property are core tenants of the reward system and the honor code. Formalized processes exist for ascribing credit to people for their ideas and work. Where, then, does generative AI fit in? How can it be used—because it WILL be used—in ways that avoid compromising core ideals? And, how can it be harnessed to accelerate learning and enhance discovery of ideas and attributions that would otherwise be overlooked? Discourse between stakeholders that prioritizes listening and cultivating consensus on the purpose and core values of the enterprise will be crucial for managing the risks and rewards of AI, whether the area of practice is education, publishing, code writing, or art. A realistic appraisal of what AI is and what it can do is essential. Any intelligence that an AI engine possesses is a characteristic of the designer and is dependent on the finite information that is used to build it. At a time in history when technology can increasingly be confused with personhood, the value of the people and the human processes that birthed these technologies should always be the measure against which policy is measured.

Editorial freeScientific Nomenclature for Keratorefractive Lenticule Extraction (KLEx) Procedures: A Joint Editorial Statement William J. Dupps Jr., MD, PhD, ; , MD, PhD J. Bradley Randleman, MD, ; , MD Thomas Kohnen, MD, PhD, FEBO, ; , MD, PhD, FEBO Sathish Srinivasan, FRCSEd, FRCOphth, FACS, ; , FRCSEd, FRCOphth, FACS Liliana Werner, MD, PhD, , MD, PhD William J. Dupps Jr., MD, PhD , J. Bradley Randleman, MD Correspondence: J. Bradley Randleman, MD, Cole Eye Institute, Cleveland Clinic, 9500 Euclid Avenue, i-32, Cleveland, OH 44195. Email: E-mail Address: [email protected] , Thomas Kohnen, MD, PhD, FEBO , Sathish Srinivasan, FRCSEd, FRCOphth, FACS , and Liliana Werner, MD, PhD Journal of Refractive Surgery, 2023;39(11):726–727Published Online:November 01, 2023https://doi.org/10.3928/1081597X-20231010-0PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreIntroductionCorneal refractive surgery has a rich history of novel procedures and nomenclature. For longstanding stalwarts such as photorefractive keratectomy (PRK) and laser in situ keratomileusis (LASIK), the naming conventions were firmly established from the first publications on these approaches, in 1998 and 1990.1,2 For refractive lenticule extraction procedures, however, the development of nomenclature has been more evolutionary than revolutionary. Early scientific reports referred to the approach as femtosecond lenticule extraction (FLE or FLEx), which the manufacturer (Carl Zeiss Meditec AG) modified to refractive lenticule extraction (ReLEx) then branded with the proprietary term small incision lenticule extraction (SMILE) when the procedure incorporated a small incision as an alternative to a flap-dependent lenticule removal process.3,4As refractive lenticule extraction procedures have gained in popularity, other commercial entities are advancing similar approaches and thus introducing additional terminology to describe their proprietary efforts. These include corneal lenticule extraction for advanced refractive correction (CLEAR; Ziemer), smooth incision lenticule keratomileusis (SILK; Johnson & Johnson), and small incision–guided human-cornea treatment (SmartSight; SCHWIND eye-tech-solutions), and more are sure to come.This flourishing of a new class of procedure is an exciting development for refractive surgeons and the patients they serve. But, as others have pointed out, a proliferation of new proprietary terms aimed at market differentiation can also create confusion and obscure the common mechanistic underpinnings of these procedures.5,6 As the editors of scientific journals dedicated to the field of refractive surgery, we recognize a responsibility to agree upon a common term for these procedures that can be used as a nonproprietary descriptor alongside any other necessary methodological details that make it clear which tools and settings were used to perform the procedure under study. This is crucial for enhancing the discoverability of closely related research publications as the number of entries into the category increases.In deliberating on a term, we sought (1) descriptive accuracy, (2) sufficient specificity to differentiate it from other procedures, (3) sufficient breadth to be inclusive of variations that arise but are substantially the same procedure class, and (4) avoidance of any existing proprietary names. The result: keratorefractive lenticule extraction (KLEx). This term tells the reader the tissue altered (the cornea), the purpose of the alteration (refractive), and the mechanism of alteration (lenticule extraction). KLEx avoids proprietary terms, both past and present, and it represents a consistent common denominator that is also easily expressed phonetically as an acronym ("kay-lex"). We ask that authors use this term as a generic expression for such procedures in their submissions but also include the necessary details in the Methods section to ensure that the research is repeatable.7"All language—especially English—is flooded with neologisms continuously. In refractive surgery, let us use accurate scientific and clinical terminology for those purposes, while enjoying the manipulative marketing jargon that will inevitably arise." —George O. Waring, III81.Munnerlyn CR, Koons SJ, Marshall J. Photorefractive keratectomy: a technique for laser refractive surgery. J Cataract Refract Surg. 1988; 14(1):46–52. 10.1016/S0886-3350(88)80063-4 PMID:3339547 > Crossref MedlineGoogle Scholar2.Pallikaris IG, Papatzanaki ME, Stathi EZ, Frenschock O, Georgiadis A. Laser in situ keratomileusis. Lasers Surg Med. 1990; 10(5):463–468. 10.1002/lsm.1900100511 PMID:2233101 > Crossref MedlineGoogle Scholar3.Sekundo W, Kunert K, Russmann Cet al.. First efficacy and safety study of femtosecond lenticule extraction for the correction of myopia: six-month results. J Cataract Refract Surg. 2008; 34(9):1513–1520. 10.1016/j.jcrs.2008.05.033 PMID:18721712 > Crossref MedlineGoogle Scholar4.Blum M, Sekundo W. [Femtosecond lenticule extraction (FLEx)] [in German]. Ophthalmologe. 2010; 107(10):967–970. 10.1007/s00347-010-2222-8 PMID:20694728 > Crossref MedlineGoogle Scholar5.Moshirfar M, Tuttle JJ, Stoakes IM, Bundogji N, Hoopes PC. SMILE, CLEAR, SILK: it's time for a common term. J Refract Surg. 2023; 39(8):575. 10.3928/1081597X-20230711-01 PMID:37578175 > LinkGoogle Scholar6.Dick HB, Seiler T, Cummings AB. Lenticule extraction. J Refract Surg. 2022; 38(9):618. 10.3928/1081597X-20220817-01 PMID:36098389 > LinkGoogle Scholar7.Dupps WJ, Randleman JB, Kohnen T, Srinivasan S, Werner L. Scientific nomenclature for keratorefractive lenticule extraction (KLEx) procedures: a joint editorial statement. J Cataract Refract Surg. 2023; 49:1085. > Crossref MedlineGoogle Scholar8.Waring GO. Neo-neologisms. J Refract Surg. 2008; 24(1):7–8. 10.3928/1081597X-20080101-02 PMID:18269142 > LinkGoogle Scholar Next article FiguresReferencesRelatedDetails Request Permissions InformationCopyright 2023, SLACK IncorporatedPDF download • 128 KBCorrespondence: J. Bradley Randleman, MD, Cole Eye Institute, Cleveland Clinic, 9500 Euclid Avenue, i-32, Cleveland, OH 44195. Email: randlej@ccf.orgFrom Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio (WJD, JBR); Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio (WJD); the Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio (WJD); the Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany (TK); University Hospital Ayr, Ayr, Scotland, United Kingdom (SS); and John A. Moran Eye Center, University of Utah, Salt Lake City, Utah (LW).Disclosure: Dr. Dupps has received grants from Alcon Laboratories and the National Institutes of Health/National Eye Institute, RO1 and UO2 grants, and Seed Fund grants, has received consulting fees from Alcon Laboratories, Inc, has patents under Cleveland Clini Innovation, and is an advisory board member for the National Institutes of Health/National Eye Institute. Dr. Kohnen is a consultant and researcher for Alcon/Novartis, J&J, Lensgen, Oculentis, Oculus, Presbia, SCHWIND, and Zeiss, and a consultant for Allergan, Bausch & Lomb, Geuder, Med Update, Santen, STAAR, Thieme, and Ziemer. The remaining authors have no financial or proprietary interest in the materials presented herein.This editorial is a joint publication by the Journal of Cataract & Refractive Surgery and the Journal of Refractive Surgery.Drs. Dupps and Randleman contributed equally to this work and should be considered as equal first authors. Published online11/01/23