We describe the algorithm for selecting quasar candidates for optical spectroscopy in the Sloan Digital Sky Survey. Quasar candidates are selected via their nonstellar colors in ugriz broadband photometry and by matching unresolved sources to the FIRST radio catalogs. The automated algorithm is sensitive to quasars at all redshifts lower than z $ 5:8. Extended sources are also targeted as low-redshift quasar candidates in order to investigate the evolution of active galactic nuclei (AGNs) at the faint end of the luminosity function. Nearly 95% of previously known quasars are recovered (based on 1540 quasars in 446 deg 2 ). The overall completeness, estimated from simulated quasars, is expected to be over 90%, whereas the overall efficiency (quasars/quasar candidates) is better than 65%. The selection algorithm targets ultraviolet excess quasars to i à ¼ 19:1 and higher redshift (ze3) quasars to i à ¼ 20:2, yielding approximately 18 candidates deg À2 . In addition to selecting '' normal '' quasars, the design of the algorithm makes it sensitive to atypical AGNs such as broad absorption line quasars and heavily reddened quasars.

Purpose: Glioblastomas (GBMs), neoplasms derived from glia and neuroglial progenitor cells, are the most common and lethal malignant primary brain tumors diagnosed in adults, with a median survival of 14 months. GBM tumorigenicity is often driven by genetic aberrations in receptor tyrosine kinases, such as amplification and mutation of EGFR. Experimental Design: Using a Drosophila glioma model and human patient–derived GBM stem cells and xenograft models, we genetically and pharmacologically tested whether the YAP and TAZ transcription coactivators, effectors of the Hippo pathway that promote gene expression via TEA domain (TEAD) cofactors, are key drivers of GBM tumorigenicity downstream of oncogenic EGFR signaling. Results: YAP and TAZ are highly expressed in EGFR-amplified/mutant human GBMs, and their knockdown in EGFR-amplified/mutant GBM cells inhibited proliferation and elicited apoptosis. Our results indicate that YAP/TAZ-TEAD directly regulates transcription of SOX2, C-MYC, and EGFR itself to create a feedforward loop to drive survival and proliferation of human GBM cells. Moreover, the benzoporphyrin derivative verteporfin, a disruptor of YAP/TAZ-TEAD–mediated transcription, preferentially induced apoptosis of cultured patient-derived EGFR-amplified/mutant GBM cells, suppressed expression of YAP/TAZ transcriptional targets, including EGFR, and conferred significant survival benefit in an orthotopic xenograft GBM model. Our efforts led us to design and initiate a phase 0 clinical trial of Visudyne, an FDA-approved liposomal formulation of verteporfin, where we used intraoperative fluorescence to observe verteporfin uptake into tumor cells in GBM tumors in human patients. Conclusions: Together, our data suggest that verteporfin is a promising therapeutic agent for EGFR-amplified and -mutant GBM.

A promising strategy to limit cholera severity involves blockers mimicking the canonical cholera toxin ligand (CT) ganglioside GM1. However, to date the efficacies of most of these blockers have been evaluated in noncellular systems that lack ligands other than GM1. Importantly, the CT B subunit (CTB) has a noncanonical site that binds fucosylated structures, which in contrast to GM1 are highly expressed in the human intestine. Here we evaluate the capacity of norbornene polymers displaying galactose and/or fucose to block CTB binding to immobilized protein-linked glycan structures and also to primary human and murine small intestine epithelial cells (SI ECs). We show that the binding of CTB to human SI ECs is largely dependent on the noncanonical binding site, and interference with the canonical site has a limited effect while the opposite is observed with murine SI ECs. The galactose−fucose polymer blocks binding to fucosylated glycans but not to GM1. However, the preincubation of CT with the galactose−fucose polymer only partially blocks toxic effects on cultured human enteroid cells, while preincubation with GM1 completely blocks CT-mediated secretion. Our results support a model whereby the binding of fucose to the noncanonical site places CT in close proximity to scarcely expressed galactose receptors such as GM1 to enable binding via the canonical site leading to CT internalization and intoxication. Our finding also highlights the importance of complementing CTB binding studies with functional intoxication studies when assessing the efficacy inhibitors of CT.

There is considerable need for new modeling approaches in the study of combined antimicrobial effects. Current methods based on the Loewe additivity and Bliss independence models are associated with implicit assumptions about the interacting system. To circumvent these limitations, we propose an alternative approach to the quantification of pharmacodynamic drug interaction (PDI). Pilot time-kill studies were performed with 10 8 CFU of Pseudomonas aeruginosa/ml at baseline with meropenem or tobramycin alone. The studies were repeated with 25 concentration combinations of meropenem (0 to 64 mg/liter) and tobramycin (0 to 32 mg/liter) in a five-by-five array. The data were modeled with a three-dimensional response surface using effect summation as the basis of null interaction. The interaction index (Ii) is defined as the ratio of the volumes under the planes (VUP) of the observed and expected surfaces: VUP observed /VUP expected . Synergy and antagonism are defined as Ii values of <1 and >1, respectively. In all combinations, an enhanced killing effect was seen compared to that of either drug at the same concentration. The most significant synergism was observed between 1 and 5 mg/liter of meropenem and between 1 and 4 mg/liter of tobramycin; seven out of nine combinations had a >2-log drop compared to the more potent agent. The Ii was found to be 0.76 (95% confidence interval, 0.65 to 0.91) for the concentration ranges of the agents. The results corroborate previous data indicating that meropenem is synergistic with an aminoglycoside when used in combination against P. aeruginosa. Our parametric approach to quantifying PDI appears robust and warrants further investigations.The ability to describe combined drug effects objectively is one of the major challenges in anti-infective pharmacology and is of paramount importance in the study of combination therapy. The pharmacodynamic drug interaction (PDI) of antimicrobials is typically described by qualitative terms, such as synergy, additivity (indifference), or antagonism. It is increasingly recognized that these standard approaches lack the sensitivity to capture various kinds of important information, such as the variability of the interacting system, extent of interaction, and emergence of resistance. Consequently, it is difficult to compare different combinations in a rational and robust manner.When attempting to evaluate pharmacodynamic interaction (synergism and antagonism), one typically constructs an expected null interaction model, which predicts the effect of multiple drugs in the absence of interaction. Without a physically and theoretically founded null interaction model, it would be difficult to make any reasonable evaluations of the combined action of multiple pharmacological agents. Two main metrics which are widely adopted exist for pharmacodynamic interactions, each presenting a consistent and well-supported perspective on the expected effect of noninteracting agents. They are the Loewe additivity and Bliss independence models. Each of these methodol...

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