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Release of ATP from astrocytes is required for Ca2+ wave propagation among astrocytes and for feedback modulation of synaptic functions. However, the mechanism of ATP release and the source of ATP in astrocytes are still not known. Here we show that incubation of astrocytes with FM dyes leads to selective labelling of lysosomes. Time-lapse confocal imaging(More)
Multi-modal retrieval is emerging as a new search paradigm that enables seamless information retrieval from various types of media. For example, users can simply snap a movie poster to search relevant reviews and trailers. To solve the problem, a set of mapping functions are learned to project high-dimensional features extracted from data of different media(More)
Deep learning has shown outstanding performance in various machine learning tasks. However, the deep complex model structure and massive training data make it expensive to train. In this paper, we present a distributed deep learning system, called SINGA, for training big models over large datasets. An intuitive programming model based on the layer(More)
The objective of this study was to correlate the expression pattern of candidate genes with the intramuscular fat (IMF) content and fatty acid composition of the Longissimus dorsi muscle of Duroc × Shanzhu commercial crossbred pigs. Animals of both sexes were slaughtered at a body weight of about 90 kg. The IMF content and fatty acid composition of the(More)
BACKGROUND MicroRNAs (miRNAs) are small, endogenously expressed non-coding RNAs that regulate mRNAs post-transcriptionally. Previous studies have explored miRNA evolutionary trend, but evolutionary history and pattern in the miRNA world are still not fully clear. In the paper, we intended to analyze miRNA haplotype distribution and evolutionary network by(More)
Recently, deep learning techniques have enjoyed success in various multimedia applications, such as image classification and multi-modal data analysis. Two key factors behind deep learning's remarkable achievement are the immense computing power and the availability of massive training datasets, which enable us to train large models to capture complex(More)
Multi-modal retrieval is emerging as a new search paradigm that enables seamless information retrieval from various types of media. For example, users can simply snap a movie poster to search for relevant reviews and trailers. The mainstream solution to the problem is to learn a set of mapping functions that project data from different modalities into a(More)
To determine the role of the pandemic influenza A/H1N1 2009 (A/H1N1 2009pdm) in acute respiratory tract infections (ARTIs) and its impact on the epidemic of seasonal influenza viruses and other common respiratory viruses, nasal and throat swabs taken from 7,776 patients with suspected viral ARTIs from 2006 through 2010 in Beijing, China were screened by(More)
Although much is known about microRNAs' regulation in gene expression and their contributions in cell fate, to date, globally lineage-(cell-) specific identification of the binding events between a transcription factor and its targeting microRNA genes is still waiting for elucidation. In this paper, we performed a ChIP-Seq experiment to find the targeting(More)
Cross-media hashing, which conducts cross-media retrieval by embedding data from different modalities into a common low-dimensional hamming space, has attracted intensive attention in recent years. This is motivated by the facts a) the multi-modal data is widespread, e.g., the web images on Flickr are associated with tags, and b) hashing is an effective(More)