Online Deep Learning from Doubly-Streaming Data

This paper investigates a new online learning problem with doubly-streaming data, where the data streams are described by feature spaces that constantly evolve, with new features emerging and old features fading away. A plausible idea to deal with such data streams is to establish a relationship between the old and new feature spaces, so that an online learner can leverage the knowledge learned from the old features to better the learning performance on the new features. Unfortunately, this idea does not scale up to high-dimensional multimedia data with complex feature interplay, which suffers a tradeoff between onlineness, which biases shallow learners, and expressiveness, which requires deep models. Motivated by this, we propose a novel OLD3S paradigm, where a shared latent subspace is discovered to summarize information from the old and new feature spaces, building an intermediate feature mapping relationship. A key trait of OLD3S is to treat the model capacity as a learnable semantics, aiming to yield optimal model depth and parameters jointly in accordance with the complexity and non-linearity of the input data streams in an online fashion. Both theoretical analysis and empirical studies substantiate the viability and effectiveness of our proposed approach. The code is available online at https://github.com/X1aoLian/OLD3S

Prognostic implications of plasma fibrinogen and serum Creactive protein levels in non-small cell lung cancer resection and survival

Purpose: To investigate the prognostic implications of plasma fibrinogen and serum C-reactive protein (CRP) levels in tumour resection and survival following successful tumour resection in patients with nonsmall cell lung cancer (NSCLC).Methods: One hundred and fifty-three NSCLC patients who underwent surgical resection at a tertiary care hospital from January 2006 through December 2010 were enrolled. Pre-operative serum CRP and plasma fibrinogen levels were  measured. The levels of these biomarkers correlated with tumour size and pathologic TNM stage. The possibility of complete resection and associated findings are reported.Results: Plasma fibrinogen (r = 0.381, p = 0.002) and serum CRP (r = 0.471, p < 0.001) levels were positively associated with tumour diameter. Increased levels of these biomarkers were significantly associated with sex, smoking status, histological type, tumour stage, and clinical stage. Partial tumour resection occurred in 28 % (27/95) of patients with an increased plasma fibrinogen level compared to 10 % (6/58) with a normal fibrinogen level (p = 0.008), and in 30 % (29/97) of patients with an increased serum CRP level compared to 11 % (6/56) with a normal CRP level (p = 0.006). Patients with elevated CRP and fibrinogen concentrations demonstrated higher susceptibility to disease advancement andsurvival compared to patients with normal fibrinogen and CRP levels.Conclusion: Pre-operative functional concentrations of serum CRP and plasma fibrinogen could serve as indicators of tumour resectability wherein a high tumour resection rate is possible in patients with favourable pre-operative levels of these biomarkers. Increased concentrations of serum CRP and plasma fibrinogen are associated with poor overall survival and progression-free survival.Key words: Plasma fibrinogen, serum C-reactive protein, biomarker, non-small cell lung cance

Alcohol intake and associated risk of major cardiovascular outcomes in women compared with men: a systematic review and meta-analysis of prospective observational studies

Adjustment factors of included studies. Figures S1. RR or RRR (female to male) of low alcohol intake and the risk of coronary disease. Figure S2. RR or RRR (female to male) of moderate alcohol intake and the risk of coronary disease. Figure S3. RR or RRR (female to male) of heavy alcohol intake and the risk of coronary disease. Figure S4. RR or RRR (female to male) of low alcohol intake and the risk of total mortality. Figure S5. RR or RRR (female to male) of moderate alcohol intake and the risk of total mortality. Figure S6. RR or RRR (female to male) of heavy alcohol intake and the risk of total mortality. Figure S7. RR or RRR (female to male) of low alcohol intake and the risk of ischemic stroke. Figure S8. RR or RRR (female to male) of low alcohol intake and the risk of cardiac death. Figure S9. RR or RRR (female to male) of low alcohol intake and the risk of stroke. Figure S10. RR or RRR (female to male) of moderate alcohol intake and the risk of cardiac death. Figure S11. RR or RRR (female to male) of moderate alcohol intake and the risk of stroke. Figure S12. RR or RRR (female to male) of moderate alcohol intake and the risk of ischemic stroke. Figure S13. RR or RRR (female to male) of heavy alcohol intake and the risk of cardiac death. Figure S14. RR or RRR (female to male) of heavy alcohol intake and the risk of stroke. Figure S15. RR or RRR (female to male) of heavy alcohol intake and the risk of ischemic stroke. Figure S16. Funnel plot of RRR (female to male) for low alcohol intake. Figure S17. Funnel plot of RRR (female to male) for moderate alcohol intake. Figure S18. Funnel plot of RRR (female to male) for heavy alcohol intake. (DOC 10344 kb

In vivo real-time imaging of gemcitabine-leaded growth inhibition in the orthotopic transplantation model of human pancreatic tumor

AbstractHuman xenograft mouse models, which have been used in cancer research for over a century, provided significant advances for our understanding of this multifaceted family of diseases. Orthotopic transplantation tumor models are emerging as the preference for cancer research due to the increasing clinical relevance over subcutaneous mouse models. In this study, a stable luciferase-expressed Capan-2 cell line was constructed and the expression of luciferase was tested. The results showed that the luminorescence intensity of Capan-2Luc cells was associated with the number of cells and the minimal detectable cell population was 600cells/well. We established an orthotopic transplantation model of pancreatic cancer using Capan-2Luc cell line in athymic mice and investigated the inhibitory effects of gemcitabine (Gem) in vitro and in vivo. Optical imaging system was applied to evaluate the tumor growth of orthotopic transplantation model in vivo. The results suggested that the orthotopic transplantation model of pancreatic cancer was well established and the luminorescence intensity of Gem-treated group was markedly lower than that of control group with an inhibitory rate of 56.8% (P<0.001). Our orthotopic transplantation model of pancreatic cancer and real-time imaging observation method established in this study could be an ideal model and a useful tool for therapeutic approaches for pancreatic cancers

Effects of Exercise on AMPK Signaling and Downstream Components to PI3K in Rat with Type 2 Diabetes

Exercise can increase skeletal muscle sensitivity to insulin, improve insulin resistance and regulate glucose homeostasis in rat models of type 2 diabetes. However, the potential mechanism remains poorly understood. In this study, we established a male Sprague-Dawley rat model of type 2 diabetes, with insulin resistance and β cell dysfunction, which was induced by a high-fat diet and low-dose streptozotocin to replicate the pathogenesis and metabolic characteristics of type 2 diabetes in humans. We also investigated the possible mechanism by which chronic and acute exercise improves metabolism, and the phosphorylation and expression of components of AMP-activated protein kinase (AMPK) and downstream components of phosphatidylinositol 3-kinase (PI3K) signaling pathways in the soleus. As a result, blood glucose, triglyceride, total cholesterol, and free fatty acid were significantly increased, whereas insulin level progressively declined in diabetic rats. Interestingly, chronic and acute exercise reduced blood glucose, increased phosphorylation and expression of AMPKα1/2 and the isoforms AMPKα1 and AMPKα2, and decreased phosphorylation and expression of AMPK substrate, acetyl CoA carboxylase (ACC). Chronic exercise upregulated phosphorylation and expression of AMPK upstream kinase, LKB1. But acute exercise only increased LKB1 expression. In particular, exercise reversed the changes in protein kinase C (PKC)ζ/λ phosphorylation, and PKCζ phosphorylation and expression. Additionally, exercise also increased protein kinase B (PKB)/Akt1, Akt2 and GLUT4 expression, but AS160 protein expression was unchanged. Chronic exercise elevated Akt (Thr(308)) and (Ser(473)) and AS160 phosphorylation. Finally, we found that exercise increased peroxisome proliferator-activated receptor-γ coactivator 1 (PGC1) mRNA expression in the soleus of diabetic rats. These results indicate that both chronic and acute exercise influence the phosphorylation and expression of components of the AMPK and downstream to PIK3 (aPKC, Akt), and improve GLUT4 trafficking in skeletal muscle. These data help explain the mechanism how exercise regulates glucose homeostasis in diabetic rats

On the Ground State of Two Flavor Color Superconductor

The diquark condensate susceptibility in neutral color superconductor at moderate baryon density is calculated in the frame of two flavor Nambu-Jona-Lasinio model. When color chemical potential is introduced to keep charge neutrality, the diquark condensate susceptibility is negative in the directions without diquark condensate in color space, which may be regarded as a signal of the instability of the conventional ground state with only diquark condensate in the color 3 direction.Comment: 4 pages, 2 figure

Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Time series forecasting has played the key role in different industrial, including finance, traffic, energy, and healthcare domains. While existing literatures have designed many sophisticated architectures based on RNNs, GNNs, or Transformers, another kind of approaches based on multi-layer perceptrons (MLPs) are proposed with simple structure, low complexity, and {superior performance}. However, most MLP-based forecasting methods suffer from the point-wise mappings and information bottleneck, which largely hinders the forecasting performance. To overcome this problem, we explore a novel direction of applying MLPs in the frequency domain for time series forecasting. We investigate the learned patterns of frequency-domain MLPs and discover their two inherent characteristic benefiting forecasting, (i) global view: frequency spectrum makes MLPs own a complete view for signals and learn global dependencies more easily, and (ii) energy compaction: frequency-domain MLPs concentrate on smaller key part of frequency components with compact signal energy. Then, we propose FreTS, a simple yet effective architecture built upon Frequency-domain MLPs for Time Series forecasting. FreTS mainly involves two stages, (i) Domain Conversion, that transforms time-domain signals into complex numbers of frequency domain; (ii) Frequency Learning, that performs our redesigned MLPs for the learning of real and imaginary part of frequency components. The above stages operated on both inter-series and intra-series scales further contribute to channel-wise and time-wise dependency learning. Extensive experiments on 13 real-world benchmarks (including 7 benchmarks for short-term forecasting and 6 benchmarks for long-term forecasting) demonstrate our consistent superiority over state-of-the-art methods

Various criteria in the evaluation of biomedical named entity recognition

BACKGROUND: Text mining in the biomedical domain is receiving increasing attention. A key component of this process is named entity recognition (NER). Generally speaking, two annotated corpora, GENIA and GENETAG, are most frequently used for training and testing biomedical named entity recognition (Bio-NER) systems. JNLPBA and BioCreAtIvE are two major Bio-NER tasks using these corpora. Both tasks take different approaches to corpus annotation and use different matching criteria to evaluate system performance. This paper details these differences and describes alternative criteria. We then examine the impact of different criteria and annotation schemes on system performance by retesting systems participated in the above two tasks. RESULTS: To analyze the difference between JNLPBA's and BioCreAtIvE's evaluation, we conduct Experiment 1 to evaluate the top four JNLPBA systems using BioCreAtIvE's classification scheme. We then compare them with the top four BioCreAtIvE systems. Among them, three systems participated in both tasks, and each has an F-score lower on JNLPBA than on BioCreAtIvE. In Experiment 2, we apply hypothesis testing and correlation coefficient to find alternatives to BioCreAtIvE's evaluation scheme. It shows that right-match and left-match criteria have no significant difference with BioCreAtIvE. In Experiment 3, we propose a customized relaxed-match criterion that uses right match and merges JNLPBA's five NE classes into two, which achieves an F-score of 81.5%. In Experiment 4, we evaluate a range of five matching criteria from loose to strict on the top JNLPBA system and examine the percentage of false negatives. Our experiment gives the relative change in precision, recall and F-score as matching criteria are relaxed. CONCLUSION: In many applications, biomedical NEs could have several acceptable tags, which might just differ in their left or right boundaries. However, most corpora annotate only one of them. In our experiment, we found that right match and left match can be appropriate alternatives to JNLPBA and BioCreAtIvE's matching criteria. In addition, our relaxed-match criterion demonstrates that users can define their own relaxed criteria that correspond more realistically to their application requirements

Detection of a superconducting phase in a two-atom layer of hexagonal Ga film grown on semiconducting GaN(0001)

The recent observation of superconducting state at atomic scale has motivated the pursuit of exotic condensed phases in two-dimensional (2D) systems. Here we report on a superconducting phase in two-monolayer crystalline Ga films epitaxially grown on wide band-gap semiconductor GaN(0001). This phase exhibits a hexagonal structure and only 0.552 nm in thickness, nevertheless, brings about a superconducting transition temperature Tc as high as 5.4 K, confirmed by in situ scanning tunneling spectroscopy, and ex situ electrical magneto-transport and magnetization measurements. The anisotropy of critical magnetic field and Berezinski-Kosterlitz-Thouless-like transition are observed, typical for the 2D superconductivity. Our results demonstrate a novel platform for exploring atomic-scale 2D superconductor, with great potential for understanding of the interface superconductivity