ObjectiveTo study the role of catecholamine in genesis of myocardium injury after organophosphorus poisoning (OP) in order to elucidate the underlying mechanisms of OP-induced cardiotoxicity.Methods Of 92 patients with severe acute dichlorvos poisoning,41 were consecutively enrolled for study and followed up for three months. The levels of serum creatine kinase isoenzyme myocardium (CK-MB),cardiac troponin Ⅰ (cTnI),acetylcholinesterase (AChE),acetylcholine (Ach),epinephrine and norepinephrine were assayed on the 1st,3rd and 5th days after admission and on the day of discharge.Electrocardiography was recorded every day after admission.ResultsOf them,37 (90.2％ )patients survived and four ( 9.8％ ) patients died during treatment.Sinus tachycardia was found in 37 (90.2％ ) patients and ST-T changes in 33 (80.4％ ) patients.CK-MB and cTnI levels peaked 3 days after admission,and then decreased to normal levels.Serum Ach,epinephrine and norepinephrine peaked on the 1st day after admission and then decreased.ConclusionsSevere acute dichlorvos poisoning is associated with myocardial dysfunction likely caused by increase in catecholamine levels.

Objective To generate various types of diabetic retinopathy ( DR) fundus images automatically by computer vision algorithm. Methods A method based on deep learning to generate fundus images was proposed,which used the vascular vein of the fundus image and the text description of lesions as the constraint conditions to generate fundus image. The text description was encoded by using a long short-term memory ( LSTM) , and the vascular vein image was encoded by a convolutional neural network (CNN). Then the encoded information was combined and used to generate a fundus image by generative adversarial networks ( GAN ) . Results The results showed that the algorithm can generate realistic fundus images. However, the image detail features were not obvious because the text-encoded recurrent neural network ( RNN ) loss function did not converge well. Conclusions Using the GAN can generate realistic DR fundus images, which has certain application value in expanding medical data. However,the generation of detail features in small areas still needs improvement.