Extracellular ATP and its ultimate degradation product adenosine are potent extracellular signaling molecules that elicit a variety of pathophysiological pathways in retina through the activation of P2 and P1 purinoceptors, respectively. Excessive build-up of extracellular ATP accelerates pathologic responses in retinal diseases, whereas accumulation of adenosine protects retinal cells against degeneration or inflammation. This mini-review focuses on the roles of ATP and adenosine in three types of blinding diseases including age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy (DR). Several agonists and antagonists of ATP receptors and adenosine receptors (ARs) have been developed for the potential treatment of glaucoma, DR and AMD: antagonists of P2X7 receptor (P2X7R) (BBG, MRS2540) prevent ATP-induced neuronal apoptosis in glaucoma, DR, and AMD; A1 receptor (A1R) agonists (INO-8875) lower intraocular pressure in glaucoma; A2A receptor (A2AR) agonists (CGS21680) or antagonists (SCH58261, ZM241385) reduce neuroinflammation in glaucoma, DR, and AMD; A3 receptor (A3R) agonists (2-Cl-lB-MECA, MRS3558) protect retinal ganglion cells (RGCs) from apoptosis in glaucoma.

Background While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. Results CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO2) and ozone (O38h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO2 + 0.0008 *O38h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. Conclusion Low temperatures, wind speed, and SO2 and high daily temperature changes, O38h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning.