Simultaneous detection of multiple tumor biomarkers in body fluids could facilitate early diagnosis of lung cancer, so as to provide scientific reference for clinical treatment. This paper depicted a ...multi-parameter paper-based electrochemical aptasensor for simultaneous detection of carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) in a clinical sample with high sensitivity and specificity. The paper-based device was fabricated through wax printing and screen-printing, which enabled functions of sample filtration and sample auto injection. Amino functional graphene (NG)-Thionin (THI)- gold nanoparticles (AuNPs) and Prussian blue (PB)- poly (3,4- ethylenedioxythiophene) (PEDOT)- AuNPs nanocomposites were synthesized respectively. They were used to modify the working electrodes not only for promoting the electron transfer rate, but also for immobilization of the CEA and NSE aptamers. A label-free electrochemical method was adopted, enabling a rapid simple point-of-care testing. Experimental results showed that the proposed multi-parameter aptasensor exhibited good linearity in ranges of 0.01–500 ng mL−1 for CEA (R2 = 0.989) and 0.05–500 ng mL−1 for NSE (R2 = 0.944), respectively. The limit of detection (LOD) was 2 pg mL−1 for CEA and 10 pg mL−1 for NSE. In addition, the device was evaluated using clinical serum samples and received a good correlation with large electrochemical luminescence (ECL) equipment, which would offer a new platform for early cancer diagnostics, especially in those resource-limit areas.
•The aptasensor could enable simultaneous detection of two tumor markers in a single sample with high sensitivity.•The aptasensor had a fast response time as a label-free electrochemical detection method was adopted.•The aptasensor was fabricated by wax printing and screen-printing, which could be mass-produced easily with low cost.
An accurate prediction of cage-cultured water quality is a hot topic in smart mariculture. Since the mariculturing environment is always open to its surroundings, the changes in water quality ...parameters are normally nonlinear, dynamic, changeable, and complex. However, traditional forecasting methods have lots of problems, such as low accuracy, poor generalization, and high time complexity. In order to solve these shortcomings, a novel water quality prediction method based on the deep LSTM (long short-term memory) learning network is proposed to predict pH and water temperature. Firstly, linear interpolation, smoothing, and moving average filtering techniques are used to repair, correct, and de-noise water quality data, respectively. Secondly, Pearson's correlation coefficient is used to obtain the correlation priors between pH, water temperature, and other water quality parameters. Finally, a water quality prediction model based on LSTM is constructed using the preprocessed data and its correlation information. Experimental results show that, in the short-term prediction, the prediction accuracy of pH and water temperature can reach 98.56% and 98.97%, and the time cost of the predictions is 0.273 s and 0.257 s, respectively. In the long-term prediction, the prediction accuracy of pH and water temperature can reach 95.76% and 96.88%, respectively.
The inadequate trophoblast invasion is associated with the development of preeclampsia (PE). Considering that annexin A4 (ANXA4) enhances tumor invasion, we aimed to explore the functional role of ...ANXA4 in trophoblast cells and to examine the underlying mechanism. ANXA4 expression in PE placentas was analyzed using immunohistochemistry and Western blotting. Cell proliferation, invasion, and apoptosis were determined using a MTT assay, Transwell assay, and flow cytometry, respectively. The expression levels of matrix metalloproteinase (MMP)-2, MMP-9, phosphoinositide 3-kinase (PI3K), Akt, phosphorylated (p)-Akt, and phosphorylated endothelial nitric oxide synthase (p-eNOS) were detected by Western blotting. Placentas were prepared for pathological examination using hematoxylin and eosin staining and apoptosis determination using the TUNEL method. Expression of ANXA4, PI3K, p-Akt and p-eNOS was downregulated in human PE placentas and PE placenta-derived extravillous cytotrophoblasts (EVCTs). Furthermore, ANXA4 overexpression promoted cell proliferation and invasion, inhibited cell apoptosis, and upregulated protein expression of PI3K, p-Akt, and p-eNOS in human trophoblast cells HTR-8/SVneo and JEG-3. By contrast, ANXA4 knockdown exerted the opposite effects. Furthermore, inhibition of the PI3K/Akt pathway by LY294002 abrogated the ANXA4 overexpression-mediated effects on trophoblast behavior. Furthermore, eNOS knockdown abrogated the ANXA4 overexpression-induced promotion of cell invasion and MMP2/9 expression. Additionally, in N-nitro-l-arginine methyl ester (l-NAME)-induced PE rats, ANXA4 overexpression alleviated PE progression, accompanied by an increase in expression of PI3K, p-Akt, and p-eNOS in rat placentas. Our findings demonstrate that ANXA4 expression is downregulated in PE. ANXA4 may promote trophoblast invasion via the PI3K/Akt/eNOS pathway.
We present a new de novo transcriptome assembler, Bridger, which takes advantage of techniques employed in Cufflinks to overcome limitations of the existing de novo assemblers. When tested on dog, ...human, and mouse RNA-seq data, Bridger assembled more full-length reference transcripts while reporting considerably fewer candidate transcripts, hence greatly reducing false positive transcripts in comparison with the state-of-the-art assemblers. It runs substantially faster and requires much less memory space than most assemblers. More interestingly, Bridger reaches a comparable level of sensitivity and accuracy with Cufflinks. Bridger is available at https://sourceforge.net/projects/rnaseqassembly/files/?source=navbar.
Schistosome infection persists for decades. Parasites are in close contact with host peripheral blood immune cells, yet little is known about the regulatory interactions between parasites and these ...immune cells. Here, we report that extracellular vesicles (EVs) released from Schistosoma japonicum are taken up primarily by macrophages and other host peripheral blood immune cells and their miRNA cargo transferred into recipient cells. Uptake of S. japonicum EV miR-125b and bantam miRNAs into host cells increased macrophage proliferation and TNF-α production by regulating the corresponding targets including Pros1, Fam212b, and Clmp. Mice infected with S. japonicum exhibit an increased population of monocytes and elevated levels of TNF-α. Reduction of host monocytes and TNF-α level in S. japonicum infected mice led to a significant reduction in worm and egg burden and pathology. Overall, we demonstrate that S. japonicum EV miRNAs can regulate host macrophages illustrating parasite modulation of the host immune response to facilitate parasite survival. Our findings provide valuable insights into the schistosome-host interaction which may help to develop novel intervention strategies against schistosomiasis.
Nowadays, recommender systems face the problem of time heterogeneous feedback recommendation, in which items are recommended according to several kinds of user feedback with time stamps. Previously ...proposed recurrent neural network based recommendation method (RNNRec) cannot analyze feedback sequences on multiple time scales, and gradient vanishing may occur when the model is trained through back propagation through time (BPTT) algorithm. To address these issues, we propose a gated recurrent units (GRU) based neural network to predict which items users will access in the future. The GRU layer in the model can analyze feedback sequences on multiple time scales and can avoid gradient vanishing during training. The proposed approach is verified on three large-scale real-life datasets, and the comparison indicates that the proposed approach outperforms several state-of-the-art methods.
Recommendation systems have received great attention for their commercial value in today's online business world. However, most recommendation systems encounter the data sparsity problem and the ...cold-start problem. To improve recommendation accuracy in this circumstance, additional sources of information about the users and items should be incorporated in recommendation systems. In this paper, we modify the model in Bayesian Probabilistic Matrix Factorization, and propose two recommendation approaches fusing social relations and item contents with user ratings in a novel way. The proposed approach is computationally efficient and can be applied to trust-aware or content-aware recommendation systems with very large dataset. Experimental results on three real world datasets show that our method gets more accurate recommendation results with faster converging speed than other matrix factorization based methods. We also verify our method in cold-start settings, and our method gets more accurate recommendation results than the compared approaches.
•We modify the model of Bayesian Probabilistic Matrix Factorization.•We fuse social relations and item contents with rating data in a novel way.•The proposed method gets more accurate results in faster converge speed.•The proposed method can alleviate data sparsity problem and cold-start problem.
Abstract
Background
Advances in single-cell RNA-seq technology have led to great opportunities for the quantitative characterization of cell types, and many clustering algorithms have been developed ...based on single-cell gene expression. However, we found that different data preprocessing methods show quite different effects on clustering algorithms. Moreover, there is no specific preprocessing method that is applicable to all clustering algorithms, and even for the same clustering algorithm, the best preprocessing method depends on the input data.
Results
We designed a graph-based algorithm, SC3-e, specifically for discriminating the best data preprocessing method for SC3, which is currently the most widely used clustering algorithm for single cell clustering. When tested on eight frequently used single-cell RNA-seq data sets, SC3-e always accurately selects the best data preprocessing method for SC3 and therefore greatly enhances the clustering performance of SC3.
Conclusion
The SC3-e algorithm is practically powerful for discriminating the best data preprocessing method, and therefore largely enhances the performance of cell-type clustering of SC3. It is expected to play a crucial role in the related studies of single-cell clustering, such as the studies of human complex diseases and discoveries of new cell types.
We present TransLiG, a new de novo transcriptome assembler, which is able to integrate the sequence depth and pair-end information into the assembling procedure by phasing paths and iteratively ...constructing line graphs starting from splicing graphs. TransLiG is shown to be significantly superior to all the salient de novo assemblers in both accuracy and computing resources when tested on artificial and real RNA-seq data. TransLiG is freely available at https://sourceforge.net/projects/transcriptomeassembly/files/ .
PDF
