Author: Chen, Hui ; Mi, Lan ; Ji, Yuying ; Pang, Yuhui ; Zhang, Qingruo ; Gan, Yuhong ; Zhang, Xiongze ; Su, Yongyue ; Liao, Nanying ; Luo, Chaokun ; Wen, Feng

PurposeIdentify optimal metabolic features and pathways across diabetic retinopathy (DR) stages, develop risk models to differentiate diabetic macular edema (DME), and predict anti-vascular endothelial growth factor (anti-VEGF) therapy response.MethodsWe analyzed 108 aqueous humor samples from 78 type 2 diabetes mellitus patients and 30 healthy controls. Ultra-high-performance liquid chromatography-high-resolution-mass-spectrometry detected lipidomics and metabolomics profiles. DME patients received ≥3 anti-VEGF treatments, categorized into strong and weak response groups. Machine learning (ML) screened prospective metabolic features, developing prediction models.ResultsKey metabolic features identified in the metabolomics and lipidomics datasets included n-acetyl isoleucine (odds ratio [OR] = 1.635), cis-aconitic acid (OR = 3.296), and ophthalmic acid (OR = 0.836) for DR. For early-DR, n-acetyl isoleucine (OR = 1.791) and decaethylene glycol (PEG-10) (OR = 0.170) were identified as key markers. L-kynurenine (OR = 0.875), niacinamide (OR = 0.843), and linoleoyl ethanolamine (OR = 0.941) were identified as significant indicators for DME. Trigonelline (OR = 1.441) and 4-methylcatechol-2-sulfate (OR = 1.121) emerged as predictors for strong response to anti-VEGF. Predictive models achieved R² values of 99.9%, 97.7%, 93.9%, and 98.4% for DR, early-DR, DME, and strong response groups in the calibration set, respectively, and validated well with R² values of 96.3%, 96.8%, 79.9%, and 96.3%.ConclusionsThis research used ML to identify differential metabolic features from metabolomics and lipidomics datasets in DR patients. It implies that metabolic indicators can effectively predict early disease progression and potential weak responders to anti-VEGF therapy in DME eyes.Translational RelevanceThe identified metabolic indicators may aid in predicting the early progression of DR and optimizing therapeutic strategies for DME.

01 May 2004·Ceska a Slovenska farmacie : casopis Ceske farmaceuticke spolecnosti a Slovenske farmaceuticke spolecnosti

[Antimicrobial agents in eyedrops].

Article

Author: Sklubalová, Z

Microbial contamination of ophthalmic drops means a risk of serious injury to the eye. Ophthalmic drops must therefore comply with sterility requirements. Protection of multiple-dose drops against secondary contamination is ensured by an addition of an antimicrobial agent. Selection of a suitable antimicrobial agent is conditioned by many factors, such as the spectrum of effect, properties of the preparation, compatibility with the components of the preparation and the container, and the technology of manufacture. Although the added antimicrobial substance ensures the safety of the preparation, on the other hand it can produce a number of negative effects in the eye tissue. The present paper summarizes pharmacopoeial requirements for microbial quality of ophthalmic drops, outlining the properties and efficacy of antimicrobial substances commonly used in ophthalmic drops (benzalkonium chloride BAC, cetrimide CTM, phenyl mercuric salts PHg, thiomersal TM, chlorobutanol ChB, benzyl alcohol BA, phenyl ethyl alcohol PEA, chlorohexidin ChX, parabens PB), their typical concentrations and combinations, including the parameters of formulation and the interactions which affect their activity. It deals with the toxicity of these antimicrobial substances, side effects on the eye tissue, and alternatives to the use of antimicrobial agents.

Ophthalmic acid is a bloodborne metabolite that contributes to age-induced cardiomyocyte hypertrophy

Article

Author: Wei, Wei ; Mehdipour, Melod ; Long, Jonathan Z. ; Park, Sangsoon ; Huang, Guo N.

AbstractCardiac aging involves the development of left ventricular hypertrophy alongside a decline in functional capacity. Here, we use neutral blood exchange to demonstrate that the acute removal of age-accumulated blood factors significantly regresses cardiac hypertrophy in aged mice. The reversal of hypertrophy was not attributed to age-associated hemodynamic effects, implicating a role of blood-derived factors. In addition, the overarching paradigm of systemic aging maintains that the age-related overabundance of plasma proteins are largely responsible for causing pathological phenotypes in tissues. Our results suggest that blood metabolites, not proteins, drive cardiac hypertrophy instead. Upon analyzing serum metabolomics data sets, we identified ophthalmic acid as a circulating metabolite whose levels increase with advanced age. Treatment of adult mouse and neonatal rat cardiomyocytes in culture with ophthalmic acid increased their relative surface areas. This study uncovers a non-protein metabolite that may contribute to cardiomyocyte hypertrophy during aging. Identifying a method to counteract ophthalmic acid’s hypertrophic effects may reveal novel therapeutic opportunities for cardiac rejuvenation.

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Indication	Highest Phase	Country/Location	Organization	Date
Eye Diseases	Preclinical	US	Spotlight Therapeutics, Inc.Startup	08 May 2024

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