Clustering Gene Expression Data Based on Predicted Differential Effects of GV Interaction

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent “noise” within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation

Effects of inhibitors of Toll-like receptors, protease-activated receptor-2 signalings and trypsin on influenza A virus replication and upregulation of cellular factors in cardiomyocytes

Severe influenza sometimes causes myocarditis. We recently found that influenza A virus (IAV) infection induces various cellular factors, such as proinflammatory cytokines IL-6, IL-1β and TNF-α, matrix metalloproteinases (MMPs) and ectopic trypsin in mice hearts and in H9c2 cardiomyocytes. The induction of these cellular factors in turn promotes viral replication, myocardial inflammation and cellular damage through their intracellular signal transductions in cooperation with the IAV-induced Toll-like receptors (TLRs) and proteinase-activated receptor-2 (PAR-2) signallings, although the precise nature of these interactions remain obscure. By using specific inhibitors of TLRs and PAR-2 signalings and trypsin inhibitor aprotinin, we analyzed the role of TLR signaling and PAR-2 signaling in the IAV-induced pathological changes in cardiomyocytes. Inhibitors of TLR7/8-Myeloid Differentiation factor 88-nuclear factor-B signaling and aprotinin effectively suppressed IAV-induced upregulation of proinflammatory cytokines, MMPs, trypsinogen and viral replication. Inhibitor of TLR3-Toll/interleukin-1 receptor domain-containing adaptor inducing interferons-dependent signaling predominantly suppressed the upregulation of interferon-β, a key intracellular host immune response factor. In contrast to the suppressive effect of trypsin inhibitor aprotinin on IAV replication, PAR-2 inhibitor FSY-NH2, induced marginal upregulation of trypsinogen and subsequent stimulation of IAV replication

A New Method for Estimation of the Sensible Heat Flux Under Unstable Conditions Using Satellite Vector Winds

It has been difficult to estimate the sensible heat flux at the air - sea interface using satellite data because of the difficulty in remotely observing the sea level air temperature. In this study, a new method is developed for estimating the sensible heat flux using satellite observations under unstable conditions. The basic idea of the method is that the air - sea temperature difference is related to the atmospheric convergence. Employed data include the wind convergence, sea level humidity, and sea surface temperature. These parameters can be derived from the satellite wind vectors, Special Sensor Microwave Imager (SSM/I) precipitable water, and Advanced Very High Resolution Radiometer (AVHRR) observations, respectively. The authors selected a region east of Japan as the test area where the atmospheric convergence appears all year. Comparison between the heat fluxes derived from the satellite data and from the National Centers for Environmental Prediction (NCEP) data suggests that the rms difference between the two kinds of sensible heat fluxes has low values in the sea area east of Japan with a minimum of 10.0 W m(-2). The time series of the two kinds of sensible heat fluxes at 10 locations in the area are in agreement, with rms difference ranging between 10.0 and 14.1 W m(-2) and correlation coefficient being higher than 0.7. In addition, the National Aeronautics and Space Administration ( NASA) Goddard Satellite-Based Surface Turbulent Flux (GSSTF) was used for a further comparison. The low-rms region with high correlation coefficient (\u3e0.7) was also found in the region east of Japan with a minimum of 12.2 W m(-2). Considering the nonlinearity in calculation of the sensible monthly means, the authors believe that the comparison with GSSTF is consistent with that with NCEP data

Broadband energy-efficient optical modulation by hybrid integration of silicon nanophotonics and organic electro-optic polymer

Silicon-organic hybrid integrated devices have emerging applications ranging from high-speed optical interconnects to photonic electromagnetic-field sensors. Silicon slot photonic crystal waveguides (PCWs) filled with electro-optic (EO) polymers combine the slow-light effect in PCWs with the high polarizability of EO polymers, which promises the realization of high-performance optical modulators. In this paper, a broadband, power-efficient, low-dispersion, and compact optical modulator based on an EO polymer filled silicon slot PCW is presented. A small voltage-length product of V{\pi}*L=0.282Vmm is achieved, corresponding to an unprecedented record-high effective in-device EO coefficient (r33) of 1230pm/V. Assisted by a backside gate voltage, the modulation response up to 50GHz is observed, with a 3-dB bandwidth of 15GHz, and the estimated energy consumption is 94.4fJ/bit at 10Gbit/s. Furthermore, lattice-shifted PCWs are utilized to enhance the optical bandwidth by a factor of ~10X over other modulators based on non-band-engineered PCWs and ring-resonators.Comment: 12 pages, 4 figures, SPIE Photonics West Conference 201

Interleukin-11-induced capillary leak syndrome in primary hepatic carcinoma patients with thrombocytopenia

<p>Abstract</p> <p>Background</p> <p>Capillary leak syndrome (CLS) is a rare condition characterized by recurrent episodes of generalized edema and severe hypotension associated with hypoproteinemia. Interleukin-11 (IL-11) is a promising therapeutic agent for thrombocytopenia. A direct correlation between IL-11 and CLS has never been reported previously, particularly in patients with hepatic carcinoma.</p> <p>Case presentation</p> <p>We describe two cases of CLS after IL-11 administration in two males with thrombocytopenia. Case 1 was a 46-year-old man with recurrence of hepatic carcinoma who was treated with IL-11 (3 mg per day). After four days of therapy, hypotension and hypoproteinemia were detected. The chest X-ray and B ultrasound of the abdomen showed pleural effusion and ascites. IL-11 was then discontinued, fluid resuscitation was performed, and fresh frozen plasma and packed red blood cells were transfused into this patient. The patient had recovered after 19 days of treatment.</p> <p>Case 2 was a 66-year-old man who had undergone radiofrequency ablation (RFA) for hepatic carcinoma. He was treated with IL-11 (3 mg per day) for thrombocytopenia. After two days of therapy, this patient complained of dyspnea with bilateral edema of the hands. Laboratory values showed hypoproteinemia. IL-11 was stopped and human albumin was transfused at a rate of 10 g per day. On the 4^thday, fluid resuscitation was performed. The patient had recovered after treatment for two weeks.</p> <p>Conclusions</p> <p>The detection of IL-11-induced CLS supports the hypothesis that CLS could be a severe side effect of IL-11 treatment in some patients. These two case reports also demonstrate that patients with hepatic carcinoma who experience this rare form of CLS after treatment with IL-11 seem to respond to a therapeutic regimen that involves hydroxyethyl starch, albumin, and diuretic therapy. Liver cancer patients might be more susceptible to CLS because of poor liver function and hypersplenia. In addition, bleeding after RFA might be a further inducer of CLS.</p

Multi-Agent Deep Reinforcement Learning for Multi-Object Tracker

Multi-object tracking has been a key research subject in many computer vision applications. We propose a novel approach based on multi-agent deep reinforcement learning (MADRL) for multi-object tracking to solve the problems in the existing tracking methods, such as a varying number of targets, non-causal, and non-realtime. At first, we choose YOLO V3 to detect the objects included in each frame. Unsuitable candidates were screened out and the rest of detection results are regarded as multiple agents and forming a multi-agent system. Independent Q-Learners (IQL) is used to learn the agents' policy, in which, each agent treats other agents as part of the environment. Then, we conducted offline learning in the training and online learning during the tracking. Our experiments demonstrate that the use of MADRL achieves better performance than the other state-of-art methods in precision, accuracy, and robustness

Source attack of decoy-state quantum key distribution using phase information

Quantum key distribution (QKD) utilizes the laws of quantum mechanics to achieve information-theoretically secure key generation. This field is now approaching the stage of commercialization, but many practical QKD systems still suffer from security loopholes due to imperfect devices. In fact, practical attacks have successfully been demonstrated. Fortunately, most of them only exploit detection-side loopholes which are now closed by the recent idea of measurement-device-independent QKD. On the other hand, little attention is paid to the source which may still leave QKD systems insecure. In this work, we propose and demonstrate an attack that exploits a source-side loophole existing in qubit-based QKD systems using a weak coherent state source and decoy states. Specifically, by implementing a linear-optics unambiguous-state-discrimination measurement, we show that the security of a system without phase randomization --- which is a step assumed in conventional security analyses but sometimes neglected in practice --- can be compromised. We conclude that implementing phase randomization is essential to the security of decoy-state QKD systems under current security analyses.Comment: 12 pages, 5 figure

A disulfidptosis-related lncRNA prognostic model to predict survival and response to immunotherapy in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and has a poor prognosis. Disulfidptosis is a novel regulated cell death form characterized by aberrant disulfide stress and actin network collapse. This study aimed to identify disulfidptosis-related lncRNAs, and predict LUAD patients’ prognosis and response to antitumor therapies by establishing a disulfidptosis-related lncRNA model.Methods: Transcriptome and clinical data of LUAD patients were obtained from the TCGA database. Pearson correlation and Cox regression analysis was used to identify disulfidptosis-related lncRNAs associated with overall survival. LASSO regression analysis was adopted to construct the prognostic model. GO, KEGG and GSEA analysis was used to identify cellular pathways related to this model. Immune cell infiltration was investigated by ESTIMATE and CIBERSORT algorithms. Tumor mutational burden (TMB) and its association with model-derived risk score were analyzed using simple nucleotide variation data. Patients’ response to immunotherapy and other antineoplastic drugs was predicted by the TIDE algorithm and GDSC tool, respectively.Results: We identified 127 disulfidptosis-related lncRNAs, and a prognostic model that consists eight of them (KTN1-AS1, AL365181.3, MANCR, LINC01352, AC090559.1, AC093673.1, AP001094.3, and MHENCR) was established and verified. The prognostic model could stratify LUAD patients into two distinct risk-score groups. A high risk score was an independent prognosis factor indicating poor overall survival, and correlated with reduced immune cell infiltration, high TMB, and lower activity of tumor immune response. Immune checkpoint blockade might bring more survival benefits to the high-risk LUAD patients, whereas low-risk patients might be more responsive to targeted therapy and diverse kinase inhibitors.Conclusion: We established a disulfidptosis-related lncRNA model that can be exploited to predict the prognosis, tumor mutational burden, immune cell infiltration landscape, and response to immunotherapy and targeted therapy in LUAD patients