Dilated FCN: Listening Longer to Hear Better

Deep neural network solutions have emerged as a new and powerful paradigm for speech enhancement (SE). The capabilities to capture long context and extract multi-scale patterns are crucial to design effective SE networks. Such capabilities, however, are often in conflict with the goal of maintaining compact networks to ensure good system generalization. In this paper, we explore dilation operations and apply them to fully convolutional networks (FCNs) to address this issue. Dilations equip the networks with greatly expanded receptive fields, without increasing the number of parameters. Different strategies to fuse multi-scale dilations, as well as to install the dilation modules are explored in this work. Using Noisy VCTK and AzBio sentences datasets, we demonstrate that the proposed dilation models significantly improve over the baseline FCN and outperform the state-of-the-art SE solutions.Comment: 5 pages; will appear in WASPAA conferenc

Interferon regulatory factor 4 sustains CD8+ T cell expansion and effector differentiation

Upon infection, CD8(+) T cells undergo a stepwise process of early activation, expansion, and differentiation into effector cells. How these phases are transcriptionally regulated is incompletely defined. Here, we report that interferon regulatory factor 4 (IRF4), dispensable for early CD8(+) T cell activation, was vital for sustaining the expansion and effector differentiation of CD8(+) T cells. Mechanistically, IRF4 promoted the expression and function of Blimp1 and T-bet, two transcription factors required for CD8(+) T cell effector differentiation, and simultaneously repressed genes that mediate cell cycle arrest and apoptosis. Selective ablation of Irf4 in peripheral CD8(+) T cells impaired antiviral CD8(+) T cell responses, viral clearance, and CD8(+) T cell-mediated host recovery from influenza infection. IRF4 expression was regulated by T cell receptor (TCR) signaling strength via mammalian target of rapamycin (mTOR). Our data reveal that IRF4 translates differential strength of TCR signaling into different quantitative and qualitative CD8(+) T cell respons

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits

Erratum for Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits. [BMC Med Genomics. 2019

Folding-competent and folding-defective forms of Ricin A chain have different fates following retrotranslocation from the endoplasmic reticulum

We report that a toxic polypeptide retaining the potential to refold upon dislocation from the endoplasmic reticulum (ER) to the cytosol (ricin A chain; RTA) and a misfolded version that cannot (termed RTAΔ), follow ER-associated degradation (ERAD) pathways in Saccharomyces cerevisiae that substantially diverge in the cytosol. Both polypeptides are dislocated in a step mediated by the transmembrane Hrd1p ubiquitin ligase complex and subsequently degraded. Canonical polyubiquitylation is not a prerequisite for this interaction because a catalytically inactive Hrd1p E3 ubiquitin ligase retains the ability to retrotranslocate RTA, and variants lacking one or both endogenous lysyl residues also require the Hrd1p complex. In the case of native RTA, we established that dislocation also depends on other components of the classical ERAD-L pathway as well as an ongoing ER–Golgi transport. However, the dislocation pathways deviate strikingly upon entry into the cytosol. Here, the CDC48 complex is required only for RTAΔ, although the involvement of individual ATPases (Rpt proteins) in the 19S regulatory particle (RP) of the proteasome, and the 20S catalytic chamber itself, is very different for the two RTA variants. We conclude that cytosolic ERAD components, particularly the proteasome RP, can discriminate between structural features of the same substrate

Regulation of IL-2 gene expression by Siva and FOXP3 in human T cells

<p>Abstract</p> <p>Background</p> <p>Severe autoinflammatory diseases are associated with mutations in the <it>Foxp3 </it>locus in both mice and humans. <it>Foxp3 </it>is required for the development, function, and maintenance of regulatory T cells (T_regs), a subset of CD4 cells that suppress T cell activation and inflammatory processes. <it>Siva </it>is a pro-apoptotic gene that is expressed across a range of tissues, including CD4 T cells. Siva interacts with three tumor necrosis factor receptor (TNFR) family members that are constitutively expressed on T_regcells: CD27, GITR, and OX40.</p> <p>Results</p> <p>Here we report a biophysical interaction between FOXP3 and Siva. We mapped the interaction domains to Siva's C-terminus and to a central region of FOXP3. We showed that <it>Siva </it>repressed IL-2 induction by suppressing <it>IL-2 </it>promoter activity during T cell activation. Siva-1's repressive effect on <it>IL-2 </it>gene expression appears to be mediated by inhibition of NFkappaB, whereas FOXP3 repressed both NFkappaB and NFAT activity.</p> <p>Conclusions</p> <p>In summary, our data suggest that both <it>FOXP3 </it>and <it>Siva </it>function as negative regulators of IL-2 gene expression in T_regcells, via suppression of NFAT by <it>FOXP3 </it>and of NFkappaB by both <it>FOXP3 </it>and <it>Siva</it>. Our work contributes evidence for <it>Siva's </it>role as a T cell signalling mediator in addition to its known pro-apoptotic function. Though further investigations are needed, evidence for the biophysical interaction between FOXP3 and Siva invites the possibility that Siva may be important for proper T_regcell function.</p

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Extraordinary clinical benefit to sequential treatment with targeted therapy and immunotherapy of a BRAF V600E and PD-L1 positive metastatic lung adenocarcinoma

Abstract Background The treatment algorithm for metastatic non-small cell lung cancers (NSCLCs) has been evolving rapidly due to the development of new therapeutic agents. Although guidelines are provided by National Comprehensive Cancer Network (NCCN) for treatment options according to biomarker testing results, sequentially applying the three main modalities (chemotherapy, targeted therapy and immunotherapy) remains an ad hoc practice in clinic. In light of recent FDA approval of dabrafenib and trametinib combination for metastatic NSCLCs with BRAF V600E mutation, one question arises due to insufficient clinical data is if the targeted therapy should be used before immunotherapy in patients with both BRAF V600E and PD-L1 expression. Case presentation We present a case of 74-year-old female, former smoker with metastatic lung adenocarcinoma. The BRAF V600E mutation among other abnormalities was identified by comprehensive genomic profiling. The patient had an excellent 2-year response to the combination of pemetrexed and sorafenib. The patient was then treated with dabrafenib due to the presence of the BRAF V600E mutation and intolerance to cytotoxic chemotherapy. Not only the patient had an 18-month durable response to dabrafenib, she experienced outstanding quality of life with no serious adverse effects. At the time of symptomatic progression, the patient was then treated with two cycles of pembrolizumab based on her positive PD-L1 staining (90%). She had early response and came off pembrolizumab due to side effects. Seven months after initiation of pembrolizumab, the patient is off all the therapy and is currently asymptomatic. The patient is surviving with metastatic disease for over 7 years as of to date. Conclusions By appropriately sequencing the three main modalities of systemic therapies, we are able to achieve long-term disease control with minimal side effects even in a geriatric patient with multiple comorbidities. We argue that it is reasonable to first use a BRAF inhibitor before considering immunotherapy for NSCLCs positive for both BRAF V600E and PD-L1

Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease), and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA) for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI) database, and pathway enrichment from the human pathway database (HPD). We use a recently-published microarray dataset (GSE24215) related to insulin resistance and type 2 diabetes (T2D) as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures