Effect of Chitosan-assisted Combination of Laparoscope and Hysteroscope on the Levels of IFN-γ and ICAM-1 in Treatment of Infertility Caused by Obstruction of Fallopian Tubes.

This experiment was carried out to investigate the effect of combined treatment of tubal obstruction infertility with deacetylated chitosan and two microscopes on the levels of IFN-γ and ICAM-1. In this study, 100 infertile patients with fallopian tube obstruction who were treated in Jiangbei District Hospital of traditional Chinese medicine from January to August 2019 were divided into two groups according to the alternating grouping method, group A (50 cases) received combined surgery, and Group B (50 cases) received combined surgery and chitosan. The curative effect and postoperative pelvic adhesion of the two groups were analyzed, and the levels of IFN-γ, ICAM-1 and IL6(IL-6), laminin (LN), Transforming growth factor beta 1(TGF-ß1) and fibronectin (FN) were observed before and after treatment. Results showed that the total effective rate of Group B was higher than that of Group A (92. 00% vs 76. 00%). The incidence of pelvic adhesion was lower in Group A (4. 00% vs 16. 00%) (P < 0.05). The levels of IFN-γ, ICAM-1, IL-6, LN, FN and TGF-ß1 in Group B were significantly lower than those in group A (P < 0.05). In conclusion, the treatment of tubal obstruction infertility with combined deacetylated chitosan and biendoscopy is effective, which can reduce the levels of IFN-γ and ICAM-1, improve the expression of adhesion-related factors and reduce the occurrence of pelvic adhesion.

Dual-Comb Gas Sensor Integrated with a Neural Network-Based Spectral Decoupling Algorithm of Overlapped Spectra for Gas Mixture Sensing.

Cross-interference among absorptions severely affects the ability to achieve accurate gas concentration retrieval through gas molecular specificity. In this study, a novel dual gas sensor was proposed to separate methane and water absorbance from the blended spectra of their mixture in the mid-infrared (MIR) band by employing a neural network algorithm. To address the scarcity of experimental data, the neural network was trained over a simulated data set constructed with the same distribution as the experimental ones. The system takes advantages of the broadband spectra to provide high-quality comb data and allows the neural network to establish an accurate spectral decoupling function. In addition, a feature absorption peak screening mechanism was proposed to achieve more accurate concentration retrieval, which avoids the prediction error introduced by interrogating the only peak of the separated spectra. The promising results of the systematic evaluation have demonstrated the feasibility of our methods in practical detections.

A Multi-Task Convolutional Neural Network for Lesion Region Segmentation and Classification of Non-Small Cell Lung Carcinoma.

Targeted therapy is an effective treatment for non-small cell lung cancer. Before treatment, pathologists need to confirm tumor morphology and type, which is time-consuming and highly repetitive. In this study, we propose a multi-task deep learning model based on a convolutional neural network for joint cancer lesion region segmentation and histological subtype classification, using magnified pathological tissue images. Firstly, we constructed a shared feature extraction channel to extract abstract information of visual space for joint segmentation and classification learning. Then, the weighted losses of segmentation and classification tasks were tuned to balance the computing bias of the multi-task model. We evaluated our model on a private in-house dataset of pathological tissue images collected from Qilu Hospital of Shandong University. The proposed approach achieved Dice similarity coefficients of 93.5% and 89.0% for segmenting squamous cell carcinoma (SCC) and adenocarcinoma (AD) specimens, respectively. In addition, the proposed method achieved an accuracy of 97.8% in classifying SCC vs. normal tissue and an accuracy of 100% in classifying AD vs. normal tissue. The experimental results demonstrated that our method outperforms other state-of-the-art methods and shows promising performance for both lesion region segmentation and subtype classification.

Rapamycin enhances HBV production by inducing cellular autophagy.

BACKGROUND: Some reports revealed that rapamycin could reactivate HBV infection. However, the mechanism has not been clearly explained. OBJECTIVES: In this report, we studied the mechanism by which rapamycin enhances HBV replication and expression by inducing cellular autophagy. MATERIALS AND METHODS: HepG2.2.15 cells were treated with rapamycin to induce autophagy. Autophagosomes were observed by fluorescence microscopy and transmission electron microscopy. Autophagy marker protein LC3-Ⅱ/LC3-Ⅰwas detected by Western blotting. HBV DNA and mRNA were determined by real time PCR and Southern blotting. HBsAg was evaluated by ELISA. RESULTS: In HepG2.2.15 cells, HBV DNA and HBsAg increased when host cells were treated with rapamycin and the effect was reversed by autophagy inhibitor, 3-methyladenine (3-MA). CONCLUSIONS: These results indicated a potential explanation for reactivation of HBV infection when patients with hepatitis receive rapamycin.

Meta-analysis assessment of GP210 and SP100 for the diagnosis of primary biliary cirrhosis.

PURPOSE: To conduct a systematic review of included studies assessing the association of GP210 and SP100 with the risk of primary biliary cirrhosis (PBC) using meta-analysis. METHODS: Five databases, the Cochrane Library, MEDLINE, VIP, CNKI, WANFANG were used to detect the role of GP210 and SP100 in diagnosis of PBC. Approximately 13,000 participants from several countries were included in this analysis. Meta-DiSc statistical software was used for analysis. RESULTS: 25 studies on GP210 and 21 studies on SP100 were included in the meta-analysis. The DOR, sensitivity, specificity of GP210 in diagnosis of PBC were 24.854 (11.957-51.660), 0.272 (0.257-0.288), 0.985 (0.982-0.988), respectively, and they were 9.133 (4.739-17.600), 0.231 (0.213-0.249), 0.977 (0.973-0.981) for SP100. CONCLUSION: Our meta-analysis indicated both GP210 and SP100 had high specificity but low sensitivity in diagnosis of PBC.

Meta-analysis: diagnostic accuracy of antinuclear antibodies, smooth muscle antibodies and antibodies to a soluble liver antigen/liver pancreas in autoimmune hepatitis.

BACKGROUND: Antinuclear antibodies (ANA), smooth muscle antibodies (SMA) and antibodies to a soluble liver antigen/liver pancreas (anti-SLA/LP) are useful markers that can help clinicians to diagnose and classify autoimmune hepatitis (AIH). OBJECTIVES: To determine whether ANA, SMA and anti-SLA/LP help to accurately diagnose patients with AIH. SEARCH STRATEGY: The PubMed, CNKI, WANFANG, and SinoMed databases were accessed to retrieve studies published in English and Chinese. Studies published up to October 2013 were reviewed. SELECTION CRITERIA: Studies on the diagnostic value of ANA, SMA or anti-SLA/LP in the diagnosis of known or suspected AIH were included. DATA COLLECTION AND ANALYSIS: Two authors evaluated studies independently and rated their methodological quality using quality assessment of diagnostic accuracy studies (QUADAS) tools; relevant data were abstracted. The random-effects method was used to summarize sensitivities, specificities, positive and negative likelihood ratios, and diagnostic odds ratios (DORs) from all 29 studies. RESULTS: The pooled sensitivity, specificity, positive and negative likelihood ratios, and DOR for ANA were 0.650 (95% confidence interval [CI], 0.619 to 0.680), 0.751 (95%CI, 0.737 to 0.764), 3.030 (95%CI, 2.349 to 3.910), 0.464 (95%CI, 0.356 to 0.604), and 7.380 (95%CI, 4.344 to 12.539), respectively. For SMA, the values were 0.593 (95%CI, 0.564 to 0.621), 0.926 (95%CI, 0.917 to 0.934), 11.740 (95%CI, 7.379 to 18.678), 0.449 (95%CI, 0.367 to 0.549), and 31.553 (95%CI, 17.147 to 58.060), respectively. Finally, for anti-SLA/LP, the values were 0.194 (95%CI, 0.168 to 0.222), 0.989 (95%CI, 0.985 to 0.993), 11.089 (95%CI, 7.601 to 16.177), 0.839 (95%CI, 0.777 to 0.905), and 16.867 (95%CI, 10.956 to 25.967), respectively. AUTHORS' CONCLUSIONS: ANA provided moderate sensitivity and specificity, while SMA gave moderate sensitivity and high specificity, and anti-SLA/LP exhibited low sensitivity and high specificity. All three antibodies were limited by their unsatisfactory sensitivities and lack of consistency.

The accuracy of the anti-mitochondrial antibody and the M2 subtype test for diagnosis of primary biliary cirrhosis: a meta-analysis.

The aim of this study was to evaluate the diagnostic value of anti-mitochondrial antibodies (AMAs) and/or the M2 subtype (AMA-M2) in patients with primary biliary cirrhosis (PBC). AMA/AMA-M2 data were obtained by searching electronic databases. Studies showing AMA/AMA-M2 results in patients with PBC and control groups with other liver diseases or healthy livers were included. The quality of the involved studies was assessed using the QUADAS tool. The pooled sensitivity and specificity were calculated, and stratified analysis was performed according to possible heterogeneity sources. The pooled AMA (all methods) sensitivity and specificity were 84.5% (95% confidence interval (CI) 83.3%-85.6%) and 97.8% (95% CI 97.6%-98.0%), respectively. The positive and negative likelihood ratios were 25.201 (95% CI 17.583-36.118) and 0.162 (95% CI 0.131-0.199), respectively. The current evidence suggests that AMA and AMA-M2 show favorable accuracy for the diagnosis of PBC with high specificity and sensitivity. AMA is a better and more comprehensive marker than AMA-M2. The accuracy established in this meta-analysis is based on clinical studies using patient cohorts from different ethnicities.