Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

GateFinder: projection-based gating strategy optimization for flow and mass cytometry

Motivation: High-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging.Results: Here, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology

The DNA damage checkpoint protein ATM promotes hepatocellular apoptosis and fibrosis in a mouse model of non-alcoholic fatty liver disease

Steatoapoptosis is a hallmark of non-alcoholic fatty liver disease (NAFLD) and is an important factor in liver disease progression. We hypothesized that increased reactive oxygen species resulting from excess dietary fat contribute to liver disease by causing DNA damage and apoptotic cell death, and tested this by investigating the effects of feeding mice high fat or standard diets for 8 weeks. High fat diet feeding resulted in increased hepatic H2O2, superoxide production, and expression of oxidative stress response genes, confirming that the high fat diet induced hepatic oxidative stress. High fat diet feeding also increased hepatic steatosis, hepatitis and DNA damage as exemplified by an increase in the percentage of 8-hydroxyguanosine (8-OHG) positive hepatocytes in high fat diet fed mice. Consistent with reports that the DNA damage checkpoint kinase Ataxia Telangiectasia Mutated (ATM) is activated by oxidative stress, ATM phosphorylation was induced in the livers of wild type mice following high fat diet feeding. We therefore examined the effects of high fat diet feeding in Atm-deficient mice. The prevalence of apoptosis and expression of the pro-apoptotic factor PUMA were significantly reduced in Atm-deficient mice fed the high fat diet when compared with wild type controls. Furthermore, high fat diet fed Atm−/− mice had significantly less hepatic fibrosis than Atm+/+ or Atm+/− mice fed the same diet. Together, these data demonstrate a prominent role for the ATM pathway in the response to hepatic fat accumulation and link ATM activation to fatty liver-induced steatoapoptosis and fibrosis, key features of NAFLD progression

Absorption Troughs of Lyman Alpha Emitters in HETDEX

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is designed to detect and measure the redshifts of more than one million Ly$\alpha$ emitting galaxies (LAEs) between $1.88 < z < 3.52$. In addition to its cosmological measurements, these data enable studies of Ly$\alpha$ spectral profiles and the underlying radiative transfer. Using the roughly half a million LAEs in the HETDEX Data Release 3, we stack various subsets to obtain the typical Ly$\alpha$ profile for the $z \sim 2-3$ epoch and to understand their physical properties. We find clear absorption wings around Ly$\alpha$ emission, which extend $\sim 2000$ km $\mathrm{s}^{-1}$ both redward and blueward of the central line. Using far-UV spectra of nearby ($0.002 < z < 0.182$) LAEs in the CLASSY treasury and optical/near-IR spectra of $2.8 < z < 6.7$ LAEs in the MUSE-Wide survey, we observe absorption profiles in both redshift regimes. Dividing the sample by volume density shows that the troughs increase in higher density regions. This trend suggests that the depth of the absorption is dependent on the local density of objects near the LAE, a geometry that is similar to damped Lyman-$\alpha$ systems. Simple simulations of Ly$\alpha$ radiative transfer can produce similar troughs due to absorption of light from background sources by HI gas surrounding the LAEs.Comment: 15 pages, 10 figures, accepted for publication in The Astrophysical Journa

Absorption Troughs of Lyα Emitters in HETDEX

The Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) is designed to detect and measure the redshifts of more than 1 million Lyα emitting galaxies (LAEs) 1.88 < z < 3.52. In addition to its cosmological measurements, these data enable studies of Lyα spectral profiles and the underlying radiative transfer. Using the roughly half a million LAEs in the HETDEX Data Release 3, we stack various subsets to obtain the typical Lyα profile for the z ∼ 2-3 epoch and to understand their physical properties. We find clear absorption wings around Lyα emission, which extend ∼2000 km s−1 both redward and blueward of the central line. Using far-UV spectra of nearby (0.002 < z < 0.182) LAEs in the COS Legacy Archive Spectroscopic Survey treasury and optical/near-IR spectra of 2.8 < z < 6.7 LAEs in the Multi Unit Spectroscopic-Wide survey, we observe absorption profiles in both redshift regimes. Dividing the sample by volume density shows that the troughs increase in higher-density regions. This trend suggests that the depth of the absorption is dependent on the local density of objects near the LAE, a geometry that is similar to damped Lyα systems. Simple simulations of Lyα radiative transfer can produce similar troughs due to absorption of light from background sources by H i gas surrounding the LAEs

Tissue-Specific Genetic Control of Splicing: Implications for the Study of Complex Traits

Numerous genome-wide screens for polymorphisms that influence gene expression have provided key insights into the genetic control of transcription. Despite this work, the relevance of specific polymorphisms to in vivo expression and splicing remains unclear. We carried out the first genome-wide screen, to our knowledge, for SNPs that associate with alternative splicing and gene expression in human primary cells, evaluating 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. We identified 23 high confidence associations with total expression and 80 with alternative splicing as reflected by expression levels of specific exons. Fewer than 50% of the implicated SNPs however show effects in both tissue types, reflecting strong evidence for distinct genetic control of splicing and expression in the two tissue types. The data generated here also suggest the possibility that splicing effects may be responsible for up to 13 out of 84 reported genome-wide significant associations with human traits. These results emphasize the importance of establishing a database of polymorphisms affecting splicing and expression in primary tissue types and suggest that splicing effects may be of more phenotypic significance than overall gene expression changes

HETDEX Public Source Catalog 1 -- Stacking 50K Lyman Alpha Emitters

We describe the ensemble properties of the $1.9 < z < 3.5$ Lyman Alpha Emitters (LAEs) found in the HETDEX survey's first public data release, HETDEX Public Source Catalog 1 (Mentuch Cooper et al. 2023). Stacking the low-resolution ($R \sim$ 800) spectra greatly increases the signal-to-noise ratio, revealing spectral features otherwise hidden by noise, and we show that the stacked spectrum is representative of an average member of the set. The flux limited, Ly$\alpha$ signal-to-noise ratio restricted stack of 50K HETDEX LAEs shows the ensemble biweight ``average" $z \sim 2.6$ LAE to be a blue (UV continuum slope $\sim -2.4$ and E(B-V) $< 0.1$), moderately bright (M$_{\text{UV}} \sim -19.7$) star forming galaxy with strong Ly$\alpha$ emission (log $L_{Ly\alpha}$ $\sim$ 42.8 and $W_{\lambda}$(Ly$\alpha$) $\sim$ 114\AA), and potentially significant leakage of ionizing radiation. The restframe UV light is dominated by a young, metal poor stellar population with an average age 5-15 Myr and metallicity of 0.2-0.3 Z$_{\odot}$.Comment: 17 pages, 11 figures, 2 data files (ApJ Accepted