Objective To evaluate the clinical effectiveness of Periocline (2% minocycline hydrochloride ointment) versus Yakang (metronidazole stilus) for treating chronic periodontitis in adults by means of meta-analysis. Methods The following electronic databases as PubMed, The Cochrane Library, EMbase, CNKI, CBM and WanFang Data were searched on computer from inception to July, 2012, and the references of all selected studies were also retrieved to collect the relevant randomized controlled trials (RCTs) on periocline vs. Yakang for chronic periodontitis. According to the inclusion and exclusion criteria, two reviewers independently screened studies, extracted data, and evaluated the methodological quality of the included RCTs. Then meta-analysis was performed using RevMan 5.0 software. Results A total of 7 RCTs involving 737 patients were included. The results of meta-analysis showed that there were no significant differences in probing depth (MD=0.26, 95%CI −0.35 to 0.87, P=0.40), clinical attachment level (MD=−0.10, 95%CI −0.75 to 0.54, P=0.75), sulcus bleeding index (MD=0.12, 95%CI −0.30 to 0.53, P=0.59), and plaque index (MD=0.07, 95%CI −0.09 to 0.22, P=0.41) between the Periocline group and the Yakang group. Conclusion The current evidence shows that based on periodental non-surgical treatment, Periocline is similar to Yakang in improving the symptoms of chronic periodontitis in adults. However, given the low methodological quality and the limited sample size of most included studies, this conclusion still needs to be further proved by conducting more strictly-designed, high-quality and large-scale RCTs. The long-term effectiveness of those 2 treatment modalities also needs to be observed in a longer follow-up duration.
Diffusion tensor imaging technology can provide information on the white matter of the brain, which can be used to explore changes in brain tissue structure, but it lacks the specific description of the microstructure information of brain tissue. The neurite orientation dispersion and density imaging make up for its shortcomings. But in order to accurately estimate the brain microstructure, a large number of diffusion gradients are needed, and the calculation is complex and time-consuming through maximum likelihood fitting. Therefore, this paper proposes a kind of microstructure parameters estimation method based on the proximal gradient network, which further avoids the classic fitting paradigm. The method can accurately estimate the parameters while reducing the number of diffusion gradients, and achieve the purpose of imaging quality better than the neurite orientation dispersion and density imaging model and accelerated microstructure imaging via convex optimization model.
Objective To study the relationship between central retinal thickness and retinal vascular filling state of patients with non-proliferative diabetic retinopathy (NPDR). Methods A total of 248 diabetic patients without retinopathy or with NPDR in the hospital were enrolled in the study. Only the right eye of these patients were examined by optical coherence tomography (OCT), fundus fluorescein angiography (FFA), color Doppler flow imaging (CDFI). Patients with central retinal edema, hemorrhage and exudation were excluded from this study. Central retinal thickness was measured by OCT at the points of 1 mm, 1 to 3 mm, and 3 to 6 mm from the fovea. The patients were divided into retinal thickness normal, thinning and thickening groups according to their central retinal thickness. The normal range of central retinal thickness was defined as 216.4-304.9 μm in this study. The arm retinal circulation time and retinal arterial phase and venous phase (A-V) fluorescence filling time were recorded by FFA examination. The peak systolic velocity (PSV), pulsatility index (PI) and resistance index (RI) of ophthalmic artery (OA), central retinal artery (CRA) and posterior ciliary artery (PCA) were measured by CDFI examination. The retinal fundus vascular filling state and ocular hemodynamic indexes were compared between different groups. Results The arm retinal circulation time of retinal thickness normal, thinning, thickening groups was (10.42±0.51), (10.36±0.64), (12.94±0.46) seconds respectively; the retinal A-V fluorescence filling time was (9.15±1.36), (6.36±1.15), (13.56±2.04) seconds. The difference of the arm retinal circulation time was statistically significant between the thickening and normal groups (t=1.93,P=0.04), and between the thickening and thinning groups (t=4.49,P=0.00). The retinal A-V fluorescence filling time was statistically significant between the thinning and normal groups (t=2.13,P=0.03), and between the thickening and normal groups (t=2.49,P=0.02), and between the thickening and thinning groups (t=5.38,P=0.00).The difference of PSV (t=3.290, -5.520, -4.900), PI (t=-4.310,-5.230, -4.390) and RI (t=4.970, 6.160, 5.990) of OA, CRA and PCA was statistically significant between the thickening and thinning groups (P＜0.05). Conclusion Central retinal thickness can affect the retinal vascular filling state of diabetic patients without retinopathy or with NPDR.