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Purpose: To evaluate the safety and efficacy of intravitreal injections of 0.5 mg conbercept in patients with choroidal neovascularization secondary to pathological myopia (pmCNV). Methods: The 177 pmCNV patients were randomly assigned in a 3:1 ratio to receive conbercept or sham injection, respectively. The conbercept group receive conbercept intravitreal injections administered on a pro re nata (PRN) basis after 3 monthly loading doses. The sham group received three consecutive monthly sham injections and then one conbercept injection followed by PRN conbercept intravitreal injections. Results: At month 3, the mean BCVA for the two groups were improved by 12.0 letters (conbercept group, from 54.05 letters to 66.05 letters) and 0.6 letters (sham group, from 49.77 letters to 50.33 letters), respectively (p < 0.001). The mean central retinal thickness (CRT) at month 3 in the two groups decreased 62.0 μm (conbercept group, from 348.90 μm to 286.18 μm) and 4.4 μm (sham group, from 347.86 μm to 343.47 μm) (p < 0.001). At month 9, the mean BCVA improved by 13.3 letters in the conbercept group and 11.3 letters in the sham group. The mean CRT decreased 73.6 μm in the conbercept group and 55.9 μm in the sham group (p < 0.001). The most common ocular adverse events were associated with intravitreal injections, such as conjunctival haemorrhage and increased intraocular pressure. Conclusion: Intravitreal injections of 0.5 mg conbercept provided improvement in visual and anatomical outcomes in pmCNV patients with low rates of ocular and nonocular safety events. [ABSTRACT FROM AUTHOR]

Background The choice of polypectomy device and surveillance intervals for colorectal polyps are primarily decided by polyp size. We developed a deep learning-based system (ENDOANGEL-CPS) to estimate colorectal polyp size in real time. Methods ENDOANGEL-CPS calculates polyp size by estimating the distance from the endoscope lens to the polyp using the parameters of the lens. The depth estimator network was developed on 7297 images from five virtually produced colon videos and tested on 730 images from seven virtual colon videos. The performance of the system was first evaluated in nine videos of a simulated colon with polyps attached, then tested in 157 real-world prospective videos from three hospitals, with the outcomes compared with that of nine endoscopists over 69 videos. Inappropriate surveillance recommendations caused by incorrect estimation of polyp size were also analyzed. Results The relative error of depth estimation was 11.3% (SD 6.0%) in successive virtual colon images. The concordance correlation coefficients (CCCs) between system estimation and ground truth were 0.89 and 0.93 in images of a simulated colon and multicenter videos of 157 polyps. The mean CCC of ENDOANGEL-CPS surpassed all endoscopists (0.89 vs. 0.41 [SD 0.29]; P <0.001). The relative accuracy of ENDOANGEL-CPS was significantly higher than that of endoscopists (89.9% vs. 54.7%; P <0.001). Regarding inappropriate surveillance recommendations, the system's error rate is also lower than that of endoscopists (1.5% vs. 16.6%; P <0.001). Conclusions ENDOANGEL-CPS could potentially improve the accuracy of colorectal polyp size measurements and size-based surveillance intervals. [ABSTRACT FROM AUTHOR]

Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that users are interested in are recommended to users. Matrix factorization is widely used in collaborative filtering algorithms because of its simplicity and efficiency. However, the simple dot-product method cannot establish a nonlinear relationship between user latent features and item latent features or make full use of their personalized information. The model of a neural network combined with an attention mechanism can effectively establish a nonlinear relationship between the potential features of users and items and improve the recommendation accuracy of the model. However, it is difficult for the general attention mechanism algorithm to solve the problem of attention interaction when the number of features between the users and items is not the same. To solve the above problems, this paper proposes an attention interaction matrix factorization (AIMF) model. The AIMF model adopts a symmetric structure using MLP calculation. This structure can simultaneously extract the nonlinear features of user latent features and item latent features, thus reducing the computation time of the model. In addition, an improved attention algorithm named slide-attention is included in the model. The algorithm uses the sliding query method to obtain the user's attention to the latent features of the item and solves the interaction problem among different dimensions of the user, and the latent features of the item. [ABSTRACT FROM AUTHOR]

Regional soil organic carbon (SOC) investigations play an important role in building knowledge of the global soil C cycle system. The purpose of the present study was to estimate soil organic carbon (SOC) storage for different soil types and land uses in Guangdong Province, China. The results showed that the total SOC storage in the study area was 1.25 Pg, of which 0.41 Pg SOC was in A horizon soils (mean depth 17.0 cm), 0.51 Pg SOC was in the B horizon (mean depth 29.5 cm) and 0.33 Pg SOC was in the C horizon (mean depth 48.9 cm). SOC storage in Fcrrallisols was approximately 0.976 Pg for the total soil profile, accounting for 78.1 % of total SOC storage. Forest soils were the main SOC pool by land use, accounting for approximately 80.3% of total SOC storage. Regardless of soil type and land use, subsoil was the primary SOC storage location in the study area. The SOC contents of the upper soil horizon were closely related to the SOC contents of the lower soil horizon, possibly suggesting that there is movement of SOC from the surface soil to lower horizons. Because of soil degradation and erosion, approximately 13.3 Tg SOC entered the surrounding water, accounting for 3.2% of the SOC storage of A horizon soils, and approximately 20.9 Tg SOC was redistributed in surface soils of the study area each year. Additional keywords: carbon sequestration, soil erosion, soil organic carbon, subsoil. Received 28 June 2016, accepted 11 December 2016, published online 11 January 2017, Introduction Global soil organic carbon (SOC) storage is within the range 1200-2500 Pg, which is twice the C in the atmosphere, and two- to threefold greater than that stored in [...]