Leukocyte recognition algorithm in leucorrhea microscopic images based on ResNet-34 neural network

Automatic leucocyte recognition for leukorrhea microscopic images is a digital image processing technology in the field of machine learning. The existence and quantity of leukocytes in leucorrhea microscopic image is an important sign and basis to judge the inflammation of vagina or cervix. Therefore, the recognition and count of leucocyte is an effective means to evaluate the condition of the disease. To solve the problem of low efficiency of leucocyte recognition in traditional artificial microscopy, this paper proposes an automatic recognition algorithm based on ResNet-34 neural network. Firstly, Canny edge detection algorithm based on genetic algorithm is used to extract the foreground target in the leucorrhea microscopic image. Secondly, the leucocyte target is selected according to the connected region and boundary rectangle parameters of the foreground target. Finally, ResNet-34 neural network is applied for the classification of leukocytes. Experiments show that the recognition accuracy of leukocytes in leucorrhea microscopic image is 92.8%, and the recall is 97.1%, which is higher and better than other methods

Automatic segmentation and recognition of red and white cells in stool microscopic images of human

Aiming to solve the problem of low efficiency in manually recognizing the red and white cells in stool microscopic images, we propose an automatic segmentation method based on iterative corrosion with marker-controlled watershed segmentation and an automatic recognition method based on support vector machine (SVM) classification. The method first obtains saliency map of the images in HSI and Lab color spaces through saliency detection algorithm, then fuses the salient images to complete the initial segmentation. Next, we segment the red and white cells completely based on the initial segmentation images using marker-controlled watershed algorithm and other complementary methods. According to the differences in geometrical and texture features of red and white cells such as area, perimeter, circularity, energy, entropy, correlation and contrast, we extract them as feature vectors to train SVM and finally complete the classification and recognition of red and white cells. The experimental results indicate that our proposed marker-controlled watershed method can help increase the segmentation and recognition accuracy. Moreover, since it is also less susceptible to the heteromorphic red and white cells, our method is effective and robust

#DontTweetThis: Scoring Private Information in Social Networks

With the growing popularity of online social networks, a large amount of private or sensitive information has been posted online. In particular, studies show that users sometimes reveal too much information or unintentionally release regretful messages, especially when they are careless, emotional, or unaware of privacy risks. As such, there exist great needs to be able to identify potentially-sensitive online contents, so that users could be alerted with such findings. In this paper, we propose a context-aware, text-based quantitative model for private information assessment, namely PrivScore, which is expected to serve as the foundation of a privacy leakage alerting mechanism. We first solicit diverse opinions on the sensitiveness of private information from crowdsourcing workers, and examine the responses to discover a perceptual model behind the consensuses and disagreements. We then develop a computational scheme using deep neural networks to compute a context-free PrivScore (i.e., the “consensus” privacy score among average users). Finally, we integrate tweet histories, topic preferences and social contexts to generate a personalized context-aware PrivScore. This privacy scoring mechanism could be employed to identify potentially-private messages and alert users to think again before posting them to OSNs

Spred2 modulates the erythroid differentiation induced by imatinib in chronic myeloid leukemia cells.

Differentiation induction is currently considered as an alternative strategy for treating chronic myelogenous leukemia (CML). Our previous work has demonstrated that Sprouty-related EVH1 domainprotein2 (Spred2) was involved in imatinib mediated cytotoxicity in CML cells. However, its roles in growth and lineage differentiation of CML cells remain unknown. In this study, we found that CML CD34+ cells expressed lower level of Spred2 compared with normal hematopoietic progenitor cells, and adenovirus mediated restoration of Spred2 promoted the erythroid differentiation of CML cells. Imatinib could induce Spred2 expression and enhance erythroid differentiation in K562 cells. However, the imatinib induced erythroid differentiation could be blocked by Spred2 silence using lentiviral vector PLKO.1-shSpred2. Spred2 interference activated phosphorylated-ERK (p-ERK) and inhibited erythroid differentiation, while ERK inhibitor, PD98059, could restore the erythroid differentiation, suggesting Spred2 regulated the erythroid differentiation partly through ERK signaling. Furthermore, Spred2 interference partly restored p-ERK level leading to inhibition of erythroid differentiation in imatinib treated K562 cells. In conclusion, Spred2 was involved in erythroid differentiation of CML cells and participated in imatinib induced erythroid differentiation partly through ERK signaling

Strain Engineering and Halogen Compensation of Buried Interface in Polycrystalline Halide Perovskites

Inverted perovskite solar cells based on weakly polarized hole-transporting layers suffer from the problem of polarity mismatch with the perovskite precursor solution, resulting in a nonideal wetting surface. In addition to the bottom-up growth of the polycrystalline halide perovskite, this will inevitably worse the effects of residual strain and heterogeneity at the buried interface on the interfacial carrier transport and localized compositional deficiency. Here, we propose a multifunctional hybrid pre-embedding strategy to improve substrate wettability and address unfavorable strain and heterogeneities. By exposing the buried interface, it was found that the residual strain of the perovskite films was markedly reduced because of the presence of organic polyelectrolyte and imidazolium salt, which not only realized the halogen compensation and the coordination of Pb2+ but also the buried interface morphology and defect recombination that were well regulated. Benefitting from the above advantages, the power conversion efficiency of the targeted inverted devices with a bandgap of 1.62 eV was 21.93% and outstanding intrinsic stability. In addition, this coembedding strategy can be extended to devices with a bandgap of 1.55 eV, and the champion device achieved a power conversion efficiency of 23.74%. In addition, the optimized perovskite solar cells retained 91% of their initial efficiency (960 h) when exposed to an ambient relative humidity of 20%, with a T80 of 680 h under heating aging at 65 °C, exhibiting elevated durability

Primers for real-time PCR detection.

<p>Primers for real-time PCR detection.</p

Spred2 over-expression enhanced imatinib-induced erythroid differentiation of K562 cells.

<p>K562 cells were infected by adenoviral vector (Ad5/F11p-Spred2 or Ad5/F11p-GFP) at a MOI of 150 and cultured with or without 1μM imatinib for 48 hours. The mRNA expression of Spred2 (A), CD235a (D) and GATA1 (E) were detected by real-time RT-PCR. The percentage of CD235a positive cells (B) and relative fluorescence intensity (C) were detected by flow cytometer. Data are shown as mean±s.d. of three independent experiments. *, p<0.05, **, p<0.01 vs the first column; #, p<0.05; ##, p<0.01 vs the second column; $, p<0.05,$$, p<0.01 vs the third column.</p

Spred2 interference suppressed the eryhtroid differentiation of human normal bone marrow (NBM) CD34⁺ cells.

<p>The scheme of lentivirus vector with shRNA specifically targeting Spred2, PLKO.1-shSpred2, was shown in A. 48h after transduced with 5 multiplicity of infection (MOI) PLKO.1-shSpred2 or PLKO.1-shScramble, the expression of Spred2 was detected to confirm the interference efficiency by Western-blotting (B) in human NBM CD34⁺ cells. Human NBM CD34⁺ cells were infected by PLKO.1-sh-Scramble or PLKO.1-sh-Spred2 at a MOI of 10 and cultured in GEMM medium. At day 0, 3 and 7 post-infection, the expression Spred2 was confirmed by real-time PCR (C), and the expression of CD34, CD235a and CD11b were analyzed by flow cytometer (E-F). Furthermore, the mRNA expression of CD235a (G), GATA1 (H) and PU.1 were detected by real-time RT-PCR. The expression of GATA1 expression was normalized by the expression level at day 0. And, the PU.1 expression at day 3 post-infection was normalized by the expression in PLKO.1-sh-Scramble group (I). PLKO.1-sh-Scramble or PLKO.1-sh-Spred2 transduced CD34⁺ cells were plated in 24-well plateand cultured in GEMM medium plus 1% methylcellulose for 14 days the presence of colonies (>40 cells) was counted and scored (D). Data are mean±s.d. of three independent experiments. *, p<0.05; **, p<0.01 vs the PLKO.1-sh-Scramble group at the same time point.</p