This invention relates to methods and compositions for detecting, identifying and treating glaucoma diseases. More particularly, this invention discloses compositions and methods for affecting intraocular pressure and increasing ocular outflows in glaucoma. Compositions and methods provided include purified and synthesized extracellular vesicle complexes from glaucoma ocular humor for use in methods and devices for detecting, characterizing and treating glaucoma diseases along with active agents. The presence of extracellular vesicle complexes in glaucoma can also be used as a biomarker.

[Problem] To provide a fluorescent probe that detects calpain activity in cells at high sensitivity. [Solution] A compound represented by the following general formula (I) or a salt thereof. ##STR00001##

Antibodies comprising an antigen recognition region which binds a semaphorin 3A (Sema3A) are disclosed. Uses thereof are also disclosed.

The present disclosure provided methods for determining the severity of glaucoma using the expression levels of GDF15. Determining the severity of glaucoma aids in treatment decisions.

The disclosure teaches methods of utilizing precisely engineered biodegradable drug delivery systems to treat ocular conditions. In aspects, the disclosure provides methods of treating elevated intraocular pressure with intracameral implants administered to the anterior region of an eye. Furthermore, the disclosure provides for methods of lowering intraocular pressure in a subject, by administering intracameral implants that maintain a multi-month sustained level of travoprost acid in the aqueous humor of said subject' eye, which is at least 8× lower than the EC50 values of travoprost acid on its molecular target, but yet still achieves clinically significant lowering of IOP.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

A method for assessing glaucoma in a patient may involve measuring an intraocular pressure of the patient and measuring an intracranial pressure in the patient, using a noninvasive eye tracking system. The method may then involve comparing the intraocular pressure to the intracranial pressure and assessing glaucoma in the patient, based on the comparing of the intraocular pressure to the intracranial pressure.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.

A method for assessing glaucoma in a patient may involve measuring an intraocular pressure of the patient and measuring an intracranial pressure in the patient, using a noninvasive eye tracking system. The method may then involve comparing the intraocular pressure to the intracranial pressure and assessing glaucoma in the patient, based on the comparing of the intraocular pressure to the intracranial pressure.

The present invention relates to a method for the early diagnosis of glaucoma based on the quantification of nestin in the aqueous humor of a patient.