The prevalence of autism spectrum disorders in China: A comprehensive meta-analysis

There are conflicting prevalence estimates of autism spectrum disorders (ASDs) in mainland China (China thereafter). This study is a comprehensive meta-analysis of the pooled prevalence of ASDs in the general population in China. Study investigators independently conducted a systematic literature search of the following databases: PubMed, EMBASE, PsycINFO, China National Knowledge Infrastructure, Chinese biomedical literature service system, and Wan Fang. Studies reporting prevalence of ASDs and autism in Chinese population were identified and analysed using the Comprehensive Meta-Analysis program with the random effects model. Forty-four studies were included in the meta-analysis comprising 2,337,321 subjects of whom 46.66 % were females. The mean age of subjects ranged from 1.6 to 8 years. Based on diagnostic criteria the pooled prevalence of ASDs was 39.23 per 10,000 (95% CI: 28.44-50.03 per 10,000, I2=89.2%); specifically, the prevalence of autism was 10.18 per 10,000 (95% CI: 8.46-11.89 per 10,000, I2=92.5%). Subgroup analyses revealed significant difference in the prevalence of ASDs between genders (72.77 per 10,000 in males vs. 16.45 per 10,000 in females). In conclusion, the prevalence of ASDs and autism in China was found generally lower than those reported in other countries. Further studies are needed to clarify the variation in prevalence

Inhibitory effect of microRNA34a on retinal pigment epithelial cell proliferation and migration,”

Citation: Hou Q, Tang J, Wang Z, et al. Inhibitory effect of microRNA-34a on retinal pigment epithelial cell proliferation and migration. Invest Ophthalmol Vis Sci. 2013;54:6481-6488. DOI:10.1167/iovs.13-11873 PURPOSE. Retinal pigment epithelial (RPE) cells play important roles in ophthalmologic diseases such as proliferative vitreoretinopathy, AMD, and diabetic retinopathy. MicroRNA34a (miR-34a) has been reported to be important in the regulation of cell proliferation, migration, differentiation, and apoptosis. In this study, we explored the effects of miR-34a on RPE cells. METHODS. The expression level of miR-34a in subconfluent and postconfluent ARPE-19 cells was investigated with quantitative real-time PCR. MicroRNA mimic and small interfering RNA (siRNA) were transiently transfected into RPE cells. Transfected RPE cells were analyzed with WST-1 proliferation assay, and their migration was analyzed with transwell assay and in vitro scratch study. The expression or activation of target proteins was detected by Western blotting. RESULTS. MicroRNA-34a was significantly downregulated in subconfluent ARPE-19 cells compared with postconfluent cells. Introduction of miR-34a inhibited the proliferation and migratory ability of RPE cells without obvious cell apoptosis. In miR-34a transfected cells, many important proliferation and/or migration related molecules such as c-Met, CDK2, CDK4, CDK6, E2F1, and phosphorylated-Cdc2 (p-Cdc2) were downregulated. Small interfering RNA designed to target c-Met also inhibited the proliferation and migration of RPE cells and downregulated CDK2, CDK6, E2F1, and p-Cdc2. CONCLUSIONS. MicroRNA-34a is downregulated in subconfluent RPE cells. MicroRNA-34a can inhibit the proliferation and migration of RPE cells through downregulation of its targets c-Met and other cell cycle-related molecules. Our results indicated that miR-34a is involved in the regulation of RPE cells

Understanding the Mechanism of Deep Learning Frameworks in Lesion Detection for Pathological Images with Breast Cancer

With the advances of scanning sensors and deep learning algorithms, computational pathology has drawn much attention in recent years and started to play an important role in the clinical workflow. Computer-aided detection (CADe) systems have been developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing misdetections. In this study, we conducted four experiments to demonstrate that the features learned by deep learning models are interpretable from a pathological perspective. In addition, classifiers such as the support vector machine (SVM) and random forests (RF) were used in experiments to replace the fully connected layers and decompose the end-to-end framework, verifying the validity of feature extraction in the convolutional layers. The experimental results reveal that the features learned from the convolutional layers work as morphological descriptors for specific cells or tissues, in agreement with the diagnostic rules in practice. Most of the properties learned by the deep learning models summarized detection rules that agree with those of experienced pathologists. The interpretability of deep features from a clinical viewpoint not only enhances the reliability of AI systems, enabling them to gain acceptance from medical experts, but also facilitates the development of deep learning frameworks for different tasks in pathological analytics

cDNA Cloning, Overexpression, Purification and Pharmacologic Evaluation for Anticancer Activity of Ribosomal Protein L23A Gene (RPL23A) from the Giant Panda

RPL23A gene encodes a ribosomal protein that is a component of the 60S subunit. The protein belongs to the L23P family of ribosomal proteins, which is located in the cytoplasm. The purpose of this paper was to explore the structure and anti-cancer function of ribosomal protein L23A (RPL23A) gene of the Giant Panda (Ailuropoda melanoleuca). The cDNA of RPL23A was cloned successfully from the Giant Panda using RT-PCR technology. We constructed a recombinant expression vector containing RPL23A cDNA and over-expressed it in Escherichia coli using pET28a plasmids. The expression product obtained was purified by using Ni chelating affinity chromatography. Recombinant protein of RPL23A obtained from the experiment acted on Hep-2 cells and human HepG-2 cells, then the growth inhibitory effect of these cells was observed by MTT (3-[4,5-dimethyl-2-thiazolyl]-2,5-diphenyl-2H-tetrazolium bromide) assay. The result indicated that the length of the fragment cloned is 506 bp, and it contains an open-reading frame (ORF) of 471 bp encoding 156 amino acids. Primary structure analysis revealed that the molecular weight of the putative RPL23A protein is 17.719 kDa with a theoretical pI 11.16. The molecular weight of the recombinant protein RPL23A is 21.265 kDa with a theoretical pI 10.57. The RPL23A gene can be really expressed in E. coli and the RPL23A protein, fusioned with the N-terminally His-tagged protein, gave rise to the accumulation of an expected 22 KDa polypeptide. The data showed that the recombinant protein RPL23A had a time- and dose-dependency on the cell growth inhibition rate. The data also indicated that the effect at low concentrations was better than at high concentrations on Hep-2 cells, and that the concentration of 0.185 μg/mL had the best rate of growth inhibition of 36.31%. All results of the experiment revealed that the recombinant protein RPL23A exhibited anti-cancer function on the Hep-2 cells. The study provides a scientific basis and aids orientation for the research and development of cancer protein drugs as well as possible anti-cancer mechanisms. Further research is on going to determine the bioactive principle(s) of recombinant protein RPL23A responsible for its anticancer activity

Modelling the dynamical friction timescale of sinking satellite

When a satellite galaxy falls into a massive dark matter halo, it suffers the dynamical friction force which drag it into the halo center and finally it merger with the central galaxy. The time interval between entry and merger is called as the dynamical friction timescale (T_df). Many studies have been dedicated to derive T_df using analytical models or N-body simulations. These studies have obtained qualitative agreements on how T_df depends on the orbit parameters, and mass ratio between satellite and host halo. However, there are still disagreements on the accurate form of T_df . In this paper, we present a semi-analytical model to predict T_df and we focus on interpreting the discrepancies among different studies. We find that the treatment of mass loss from satellite by tidal stripping dominates the behavior of T_df . We also identify other model parameters which affect the predicted T_df.Comment: 13 pages, 7 figures, accepted for publication in Research in Astronomy and Astrophysics (RAA

Clinical Study on Prospective Efficacy of All-Trans Acid, Realgar-Indigo Naturalis Formula Combined with Chemotherapy as Maintenance Treatment of Acute Promyelocytic Leukemia

Objectives. To test the efficiency and safety of sequential application of retinoic acid (ATRA), Realgar-Indigo naturalis formula (RIF) and chemotherapy (CT) were used as the maintenance treatment in patients with acute promyelocytic leukemia (APL). Methods. This was a retrospective study of 98 patients with newly diagnosed APL who accepted two different maintenance treatments. After remission induction and consolidation chemotherapy according to their Sanz scores, patients received two different kinds of maintenance scheme. The first regimen was using ATRA, RIF, and standard dose of CT sequentially (ATRA/RIF/CT regimen), while the second one was using ATRA and low dose of chemotherapy with methotrexate (MTX) plus 6-mercaptopurine (6-MP) alternately (ATRA/CTlow regimen). The OS, DFS, relapse rate, minimal residual disease, and adverse reactions in two groups were monitored and evaluated. Results. ATRA/RIF/CT regimen could effectively reduce the chance of relapse in different risk stratification of patients, but there was no significant difference in 5-year DFS rate and OS rate between the two groups. Besides, the patients in the experimental group suffered less severe adverse reactions than those in the control group. Conclusions. The repeated sequential therapeutic regimen to APL with ATRA, RIF, and chemotherapy is worth popularizing for its high effectiveness and low toxicity

The relationship between perceived stress and problematic social networking site use among Chinese college students

Background and aims: Perceived stress has been regarded as a risk factor for problematic social networking site (SNS) use, yet little is known about the underlying processes whereby confounding variables may mediate or moderate this relationship. To answer this question, this study examined whether depression and anxiety mediated the relationship between perceived stress and problematic SNS use, and whether these mediating processes were moderated by psychological resilience and social support. Methods: Participants were 641 Chinese college students who completed anonymous questionnaires measuring perceived stress, depression/anxiety, psychological resilience, social support, and problematic SNS use. Results: The results showed that (a) depression/anxiety mediated the relationship between perceived stress and problematic SNS use; (b) the mediating effects of depression/anxiety on the association between perceived stress and problematic SNS use were moderated by psychological resilience. Specifically, the mediating effects of depression/anxiety were stronger for individuals with lower levels of psychological resilience, compared with those with higher levels of psychological resilience; and (c) the mediating effects of depression/anxiety were not moderated by social support, although social support was negatively related to depression/anxiety. Discussion and conclusion: This study can contribute to a better understanding of how and when perceived stress increases the risk of problematic SNS use, and implies the importance of enhancing psychological resilience in preventing problematic SNS use