Plant-pollinator communities responsive to local and landscape level factors in grassland restorations.

As humans continue to degrade natural ecosystems via greenhouse gas emissions and habitat destruction, many species are being pushed to the brink of extinction. In hopes to offset this degradation, habitat restoration attempts to restore ecosystem function to an improved state resembling intact, remnant values. This is a difficult, but important, undertaking with factors to consider at multiple spatial and temporal scales. The restoration and conservation of pollinator communities has garnered heightened attention because of the valuable ecosystem services they provide. This dissertation investigates the local and landscape level factors of grassland restorations that influence plant-pollinator communities. I used a combination of approaches, including large dataset compilation, and field surveys of local plant and animal communities. This work tells a nuanced story of how plant-pollinator communities are influenced by humans, but also how we can offset the most detrimental effects. Specifically, grassland restorations have the potential to increase pollinator abundance and species richness values compared to degraded grasslands. Furthermore, the surrounding land usage and quality of these restorations play an important role in their functionality. Restorations with higher plant richness and a higher proportion of native plants were able to support more robust plant and pollinator communities. Additionally, restorations nested within urban areas experienced increased stress, indicating increased support may be warranted. This work highlights the importance of high-quality restorations for the preservation of our pollinator communities. If we are to protect some of the most important species in the world, we must effectively restore the ecosystems they rely on

Developing Sustainable International Library Exchange Programs: The CUNY-Shanghai Library Faculty Exchange Model

This article describes the City University of New York ( CUNY)-Shanghai Librarian Faculty Exchange Program. By observing and working in academic library services at CUNY, Shanghai University (SU), and Shanghai Normal University (SNU), participants were able to teach and learn from their colleagues, bringing their experiences back to further share with their home library patrons, colleagues, and colleges

The CUNY-Shanghai Library Faculty Exchange Program: Participants Remember, Reflect, and Reshape

This chapter recounts the outcomes and experiences of six American librarians who participated in an international librarian exchange program that ran from spring 2010 through fall 2011. The exchange brought together the City University of New York (CUNY) and two universities in Shanghai, China: Shanghai University (SU) and Shanghai Normal University (SNU). The program was inspired, in part, by recognition of the diversity of CUNY’s student body and growing awareness of the increasing globalization of information and education. For the Chinese librarians, the exchange offered an opportunity to learn from the West and showcase their own innovations. The traveling participants – eight librarians from six of the CUNY colleges and six librarians from SU and SNU – benefited from individual opportunities for learning and the collective development of new visions for academic library services

Discovery and Follow-up Observations of the Young Type Ia Supernova 2016coj

The Type~Ia supernova (SN~Ia) 2016coj in NGC 4125 (redshift $z=0.004523$) was discovered by the Lick Observatory Supernova Search 4.9 days after the fitted first-light time (FFLT; 11.1 days before $B$-band maximum). Our first detection (pre-discovery) is merely $0.6\pm0.5$ day after the FFLT, making SN 2016coj one of the earliest known detections of a SN Ia. A spectrum was taken only 3.7 hr after discovery (5.0 days after the FFLT) and classified as a normal SN Ia. We performed high-quality photometry, low- and high-resolution spectroscopy, and spectropolarimetry, finding that SN 2016coj is a spectroscopically normal SN Ia, but with a high velocity of \ion{Si}{2} $\lambda$6355 ($\sim 12,600$\,\kms\ around peak brightness). The \ion{Si}{2} $\lambda$6355 velocity evolution can be well fit by a broken-power-law function for up to a month after the FFLT. SN 2016coj has a normal peak luminosity ($M_B \approx -18.9 \pm 0.2$ mag), and it reaches a $B$-band maximum \about16.0~d after the FFLT. We estimate there to be low host-galaxy extinction based on the absence of Na~I~D absorption lines in our low- and high-resolution spectra. The spectropolarimetric data exhibit weak polarization in the continuum, but the \ion{Si}{2} line polarization is quite strong ($\sim 0.9\% \pm 0.1\%$) at peak brightness.Comment: Submitte

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

What Does the Geometry of the HβBLR Depend On?

We combine our dynamical modeling black-hole mass measurements from the Lick AGN Monitoring Project 2016 sample with measured cross-correlation time lags and line widths to recover individual scale factors, f, used in traditional reverberation-mapping analyses. We extend our sample by including prior results from Code for AGN Reverberation and Modeling of Emission Lines (CARAMEL) studies that have utilized our methods. Aiming to improve the precision of black-hole mass estimates, as well as uncover any regularities in the behavior of the broad-line region (BLR), we search for correlations between f and other AGN/BLR parameters. We find (i) evidence for a correlation between the virial coefficient log10(fmean,σ) and black-hole mass, (ii) marginal evidence for a similar correlation between log10( frms,σ) and black-hole mass, (iii) marginal evidence for an anticorrelation of BLR disk thickness with log10( fmean,FWHM) and log10( frms,FWHM), and (iv) marginal evidence for an anticorrelation of inclination angle with log10( fmean,FWHM), log10( frms,σ), and log10( fmean,σ). Last, we find marginal evidence for a correlation between line-profile shape, when using the root-mean-square spectrum, log10(FWHM/σ)rms, and the virial coefficient, log10( frms,σ), and investigate how BLR properties might be related to line-profile shape using CARAMEL models

Proteomics and in silico approaches to extend understanding of the glutathione transferase superfamily of the tropical liver fluke Fasciola gigantica

Fasciolosis is an important foodborne, zoonotic disease of livestock and humans, with global annual health and economic losses estimated at several billion US$. Fasciola hepatica is the major species in temperate regions, while F. gigantica dominates in the tropics. In the absence of commercially available vaccines to control fasciolosis, increasing reports of resistance to current chemotherapeutic strategies and the spread of fasciolosis into new areas, new functional genomics approaches are being used to identify potential new drug targets and vaccine candidates. The glutathione transferase (GST) superfamily is both a candidate drug and vaccine target. This study reports the identification of a putatively novel Sigma class GST, present in a water-soluble cytosol extract from the tropical liver fluke F. gigantica. The GST was cloned and expressed as an enzymically active recombinant protein. This GST shares a greater identity with the human schistosomiasis GST vaccine currently at Phase II clinical trials than previously discovered F. gigantica GSTs, stimulating interest in its immuno-protective properties. In addition, in silico analysis of the GST superfamily of both F. gigantica and F. hepatica has revealed an additional Mu class GST, Omega class GSTs, and for the first time, a Zeta class member