236 research outputs found

    Dynamic comparison between Daan real-time PCR and Cobas TaqMan for quantification of HBV DNA levels in patients with CHB

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    BACKGROUND: Hepatitis B virus (HBV) DNA levels are crucial for managing chronic hepatitis B (CHB). It was unclear whether Daan real-time polymerase chain reaction test (Daan test) or COBAS TaqMan HBV DNA Test (Cobas TaqMan) was superior in measuring different HBV DNA levels in clinical specimens. METHODS: We enrolled 67 treatment-naïve, HBV surface antigen-positive CHB patients (high baseline viral levels) who received either lamivudine/adefovir or entecavir. Serum samples were tested at baseline and treatment week 24 using the Daan test and Cobas TaqMan. RESULTS: In the 67-baseline samples, the HBV DNA levels with the Cobas TaqMan (7.90 ± 0.73 log(10) IU/mL) were significantly greater than those of the Daan test (7.11 ± 0.44 log(10) IU/mL; P < 0.001). Of the 67 24-week samples (low viral levels), the Cobas TaqMan detected 59 (88.1%; 8 undetected); the Daan test detected 33 (49.3%; 34 undetected; P < 0.001). The Cobas TaqMan detected HBV DNA in 26 of 34 samples undetectable by the Daan test (range, 1.4–3.7 log(10) IU/mL) or 38% of samples (26/67). The reductions in viral load after 24 weeks of oral antiviral treatment in the 33 samples that were positive for both the Daan test and the Cobas TaqMan test were significantly different (3.59 ± 1.11 log(10) IU/mL versus 4.87 ± 1.58 log(10) IU/mL, respectively; P = 0.001). Spearman correlation analysis showed positive correlation between results from two tests (r(p) = 0.602,P<0.001). The HBV genotypes and the anti-viral treatment did not affect the measurements of the HBV DNA by the Daan assay and the Cobas Taqman assay. CONCLUSION: The Cobas Taqman was more sensitive at low viral loads than the Daan test and the change from complete to partial virological response could affect clinical decisions. The Cobas Taqman may be more appropriate for detection of HBV DNA levels

    Photooxidation Contribution Study on the Decomposition of Azo Dyes in Aqueous Solutions by VUV-Based AOPs

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    The effects of pH value, VUV intensity, initial dye concentration, initial H2O2 concentration, and TiO2 loading dose on the degradation of three azo dyes: acid Orange 8, acid Blue 29, and acid Blue 113 were studied to explore and compare the treatment efficiencies among the adopted AOPs. It was found that pH played an important role in the degradation of dyes using VUV irradiation. For VUV/H2O2, VUV/TiO2, and VUV/TiO2/H2O2 processes, the decoloration rates of the three azo dyes were more efficient under acidic conditions relative to alkaline conditions. The degradation rates of dyes increased with increasing concentrations of H2O2, but reaction rates were retarded at high concentrations of H2O2 because the H2O2 compound acted as a scavenger of the hydroxyl radical. In this paper, three azo dyes were decomposed efficiently by VUV irradiation only demonstrating the effectiveness of VUV direct photolysis

    Observation of photonic antichiral edge states

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    Chiral edge states are a hallmark feature of two-dimensional topological materials. Such states must propagate along the edges of the bulk either clockwise or counterclockwise, and thus produce oppositely propagating edge states along the two parallel edges of a strip sample. However, recent theories have predicted a counterintuitive picture, where the two edge states at the two parallel strip edges can propagate in the same direction; these anomalous topological edge states are named as antichiral edge states. Here we report the experimental observation of antichiral edge states in a gyromagnetic photonic crystal. The crystal consists of gyromagnetic cylinders in a honeycomb lattice, with the two triangular sublattices magnetically biased in opposite directions. With microwave measurement, unique properties of antichiral edge states have been observed directly, which include the titled dispersion, the chiral-like robust propagation in samples with certain shapes, and the scattering into backward bulk states at certain terminations. These results extend and supplement the current understanding of chiral edge states

    Upregulation of lncRNA NR_046683 Serves as a Prognostic Biomarker and Potential Drug Target for Multiple Myeloma

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    Aim: To investigate the prognostic value of lncRNA NR_046683 in multiple myeloma (MM).Methods: High-throughput lncRNA array was combined with bioinformatics techniques to screen differentially expressed lncRNA in MM. qRT-PCR was adopted to determine the expression of target lncRNAs in MM patients and controls.Results: It was found for the first time that lncRNA NR_046683 is closely related to the prognosis of MM. It was also detected in tumor cell lines KM3, U266, especially in drug-resistant cell lines KM3/BTZ and MM1R. The NR_046683 expression differed significantly in patients of different MM subtypes and staging. Moreover, the overexpression of NR-046683 is closely related to β2-microglobulin. We also found that the overexpression of NR-046683 correlates to chromosomal aberrations, such as del(13q14), gain 1q21, and t(4;14).Conclusion: lncRNA NR_046683 can serve as a novel biomarker for potential drug target and prognostic prediction in MM

    Rectal cancer patients with downstaging after neoadjuvant chemoradiotherapy and radical resection do not benefit from adjuvant chemotherapy

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    Background: Whether adjuvant chemotherapy is beneficial for rectal cancer patients who respond well to neoadjuvant chemoradiotherapy (NCRT) and undergo radical resection is controversial. This study aimed to assess the effect of adjuvant chemotherapy on the oncological outcomes of ypT0-2N0 rectal cancer patients after NCRT and radical resection, and identify the prognostic factors. Methods: The clinical and pathological data of rectal cancer patients with ypT0-2N0 who underwent NCRT and radical resection between January, 2010 and June, 2018 were collected and retrospectively analyzed. The oncological outcomes of the chemotherapy (chemo) group and the non-chemotherapy (non-chemo) group were compared. Multivariate analysis, using a Cox proportional hazard model, was performed to identify independent predictors of oncological outcome. Results: Of the 121 rectal cancer patients enrolled, 90 patients received postoperative adjuvant chemotherapy with no fewer than 3 cycles (the chemo group), and the other 31 patients with fewer than 3 cycles (the non-chemo group). There was no significant difference in the 5-year disease-free survival (DFS) or overall survival (OS) rates between the two groups (DFS: 79.1% vs. 82.9%, P=0.442; OS: 87.5% vs. 78.2%, P=0.667). cT4 is an independent risk factor for OS (HR =4.227, 95% CI: 1.128-15.838, P=0.02) and DFS (HR =4.878, 95% CI: 1.752-13.578). Preoperative consolidation chemotherapy with Capeox or FOLFOX after NCRT significantly improved the DFS rate (HR =0.212, 95% CI: 0.058-0.776, P=0.019). Conclusions: Rectal cancer patients with ypT0-2N0 who underwent NCRT and radical resection did not benefit significantly from postoperative adjuvant chemotherapy. For these patients, cT4 was an independent risk factor for OS and DFS. Preoperative consolidation chemotherapy with Capeox or FOLFOX after NCRT can significantly improve DFS

    Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features

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    Multi-task learning (MTL) has received considerable attention, and numerous deep learning applications benefit from MTL with multiple objectives. However, constructing multiple related tasks is difficult, and sometimes only a single task is available for training in a dataset. To tackle this problem, we explored the idea of using unsupervised clustering to construct a variety of auxiliary tasks from unlabeled data or existing labeled data. We found that some of these newly constructed tasks could exhibit semantic meanings corresponding to certain human-specific attributes, but some were non-ideal. In order to effectively reduce the impact of non-ideal auxiliary tasks on the main task, we further proposed a novel meta-learning-based multi-task learning approach, which trained the shared hidden layers on auxiliary tasks, while the meta-optimization objective was to minimize the loss on the main task, ensuring that the optimizing direction led to an improvement on the main task. Experimental results across five image datasets demonstrated that the proposed method significantly outperformed existing single task learning, semi-supervised learning, and some data augmentation methods, including an improvement of more than 9% on the Omniglot dataset
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