NUDT2 Disruption Elevates Diadenosine Tetraphosphate (Ap4A) and Down-Regulates Immune Response and Cancer Promotion Genes.

Regulation of gene expression is one of several roles proposed for the stress-induced nucleotide diadenosine tetraphosphate (Ap4A). We have examined this directly by a comparative RNA-Seq analysis of KBM-7 chronic myelogenous leukemia cells and KBM-7 cells in which the NUDT2 Ap4A hydrolase gene had been disrupted (NuKO cells), causing a 175-fold increase in intracellular Ap4A. 6,288 differentially expressed genes were identified with P < 0.05. Of these, 980 were up-regulated and 705 down-regulated in NuKO cells with a fold-change ≥ 2. Ingenuity® Pathway Analysis (IPA®) was used to assign these genes to known canonical pathways and functional networks. Pathways associated with interferon responses, pattern recognition receptors and inflammation scored highly in the down-regulated set of genes while functions associated with MHC class II antigens were prominent among the up-regulated genes, which otherwise showed little organization into major functional gene sets. Tryptophan catabolism was also strongly down-regulated as were numerous genes known to be involved in tumor promotion in other systems, with roles in the epithelial-mesenchymal transition, proliferation, invasion and metastasis. Conversely, some pro-apoptotic genes were up-regulated. Major upstream factors predicted by IPA® for gene down-regulation included NFκB, STAT1/2, IRF3/4 and SP1 but no major factors controlling gene up-regulation were identified. Potential mechanisms for gene regulation mediated by Ap4A and/or NUDT2 disruption include binding of Ap4A to the HINT1 co-repressor, autocrine activation of purinoceptors by Ap4A, chromatin remodeling, effects of NUDT2 loss on transcript stability, and inhibition of ATP-dependent regulatory factors such as protein kinases by Ap4A. Existing evidence favors the last of these as the most probable mechanism. Regardless, our results suggest that the NUDT2 protein could be a novel cancer chemotherapeutic target, with its inhibition potentially exerting strong anti-tumor effects via multiple pathways involving metastasis, invasion, immunosuppression and apoptosis

Sentence-Select: Large-Scale Language Model Data Selection for Rare-Word Speech Recognition

Language model fusion helps smart assistants recognize words which are rare in acoustic data but abundant in text-only corpora (typed search logs). However, such corpora have properties that hinder downstream performance, including being (1) too large, (2) beset with domain-mismatched content, and (3) heavy-headed rather than heavy-tailed (excessively many duplicate search queries such as "weather"). We show that three simple strategies for selecting language modeling data can dramatically improve rare-word recognition without harming overall performance. First, to address the heavy-headedness, we downsample the data according to a soft log function, which tunably reduces high frequency (head) sentences. Second, to encourage rare-word exposure, we explicitly filter for words rare in the acoustic data. Finally, we tackle domain-mismatch via perplexity-based contrastive selection, filtering for examples matched to the target domain. We down-select a large corpus of web search queries by a factor of 53x and achieve better LM perplexities than without down-selection. When shallow-fused with a state-of-the-art, production speech engine, our LM achieves WER reductions of up to 24% relative on rare-word sentences (without changing overall WER) compared to a baseline LM trained on the raw corpus. These gains are further validated through favorable side-by-side evaluations on live voice search traffic.Comment: Interspeech 202

Three-Dimensional Integration of Black Phosphorus Photodetector with Silicon Photonics and Nanoplasmonics

We demonstrate the integration of a black phosphorus photodetector in a hybrid, three-dimensional architecture of silicon photonics and metallic nanoplasmonics structures. This integration approach combines the advantages of the low propagation loss of silicon waveguides, high-field confinement of a plasmonic nanogap, and the narrow bandgap of black phosphorus to achieve high responsivity for detection of telecom-band, near-infrared light. Benefiting from an ultrashort channel (∼60 nm) and near-field enhancement enabled by the nanogap structure, the photodetector shows an intrinsic responsivity as high as 10 A/W afforded by internal gain mechanisms, and a 3 dB roll-off frequency of 150 MHz. This device demonstrates a promising approach for on-chip integration of three distinctive photonic systems, which, as a generic platform, may lead to future nanophotonic applications for biosensing, nonlinear optics, and optical signal processing

Chirality-specific growth of single-walled carbon nanotubes on solid alloy catalysts

Carbon nanotubes have many material properties that make them attractive for applications(1,2). In the context of nanoelectronics(3), interest has focused on single-walled carbon nanotubes(4) (SWNTs) because slight changes in tube diameter and wrapping angle, defined by the chirality indices (n,m), will shift their electrical conductivity from one characteristic of a metallic state to one characteristic of a semiconducting state, and will also change the bandgap. However, this structure-function relationship can be fully exploited only with structurally pure SWNTs. Solution-based separation methods(5) yield tubes within a narrow structure range, but the ultimate goal of producing just one type of SWNT by controlling its structure during growth has proved to be a considerable challenge over the last two decades(6-9). Such efforts aim to optimize the composition(6,10-17) or shape(18-21) of the catalyst particles that are used in the chemical vapour deposition synthesis process to decompose the carbon feedstock and influence SWNT nucleation and growth(22-25). This approach resulted in the highest reported proportion, 55 per cent, of single-chirality SWNTs in an as-grown sample(11). Here we show that SWNTs of a single chirality, (12, 6), can be produced directly with an abundance higher than 92 per cent when using tungsten-based bimetallic alloy nanocrystals as catalysts. These, unlike other catalysts used so far, have such high melting points that they maintain their crystalline structure during the chemical vapour deposition process. This feature seems crucial because experiment and simulation both suggest that the highly selective growth of (12, 6) SWNTs is the result of a good structural match between the carbon atom arrangement around the nanotube circumference and the arrangement of the catalytically active atoms in one of the planes of the nanocrystal catalyst. We anticipate that using high-melting-point alloy nanocrystals with optimized structures as catalysts paves the way for total chirality control in SWNT growth and will thus promote the development of SWNT applications