RESUMEN
Glaucoma is characterized by the progressive loss of retinal ganglion cells (RGCs), although the pathogenic mechanism remains largely unknown. To study the mechanism and assess RGC degradation, mouse models are often used to simulate human glaucoma and specific markers are used to label and quantify RGCs. However, manually counting RGCs is time-consuming and prone to distortion due to subjective bias. Furthermore, semi-automated counting methods can produce significant differences due to different parameters, thereby failing objective evaluation. Here, to improve counting accuracy and efficiency, we developed an automated algorithm based on the improved YOLOv5 model, which uses five channels instead of one, with a squeeze-and-excitation block added. The complete number of RGCs in an intact mouse retina was obtained by dividing the retina into small overlapping areas and counting, and then merging the divided areas using a non-maximum suppression algorithm. The automated quantification results showed very strong correlation (mean Pearson correlation coefficient of 0.993) with manual counting. Importantly, the model achieved an average precision of 0.981. Furthermore, the graphics processing unit (GPU) calculation time for each retina was less than 1 min. The developed software has been uploaded online as a free and convenient tool for studies using mouse models of glaucoma, which should help elucidate disease pathogenesis and potential therapeutics.
Asunto(s)
Glaucoma , Enfermedades de los Roedores , Animales , Recuento de Células/veterinaria , Modelos Animales de Enfermedad , Glaucoma/patología , Glaucoma/veterinaria , Humanos , Ratones , Retina/patología , Células Ganglionares de la Retina/patología , Enfermedades de los Roedores/patologíaRESUMEN
We investigated the effects of forest age and season on soil microbial community structure and enzyme activities in Hippophae rhamnoides plantation. The results showed that the amounts of total PLFAs, bacterial PLFAs, and fungal PLFAs increased with the increases of forest age. The highest values presented in mature plantation (CL). Soil enzyme activities showed the same trend as soil microbial communities. The total PLFAs, bacteria PLFAs, and fungal PLFAs exhibited significantly positive correlations with soil pH, total nitrogen, and available phosphorus. In conclusion, forest age and season has significant impacts on soil microbial community structure and enzyme activities. H. rhamnoides plantation is a suitable afforestation model, which would help improve soil fertility.
