Smooth(er) Stellar Mass Maps in CANDELS: Constraints on the Longevity of Clumps in High-redshift Star-forming Galaxies

We perform a detailed analysis of the resolved colors and stellar populations of a complete sample of 323 star-forming galaxies at 0.5 < z < 1.5, and 326 star-forming galaxies at 1.5 < z < 2.5 in the ERS and CANDELS-Deep region of GOODS-South. Galaxies were selected to be more massive than 10^10 Msun and have specific star formation rates above 1/t_H. We model the 7-band optical ACS + near-IR WFC3 spectral energy distributions of individual bins of pixels, accounting simultaneously for the galaxy-integrated photometric constraints available over a longer wavelength range. We analyze variations in rest-frame color, stellar surface mass density, age, and extinction as a function of galactocentric radius and local surface brightness/density, and measure structural parameters on luminosity and stellar mass maps. We find evidence for redder colors, older stellar ages, and increased dust extinction in the nuclei of galaxies. Big star-forming clumps seen in star formation tracers are less prominent or even invisible on the inferred stellar mass distributions. Off-center clumps contribute up to ~20% to the integrated SFR, but only 7% or less to the integrated mass of all massive star-forming galaxies at z ~ 1 and z ~ 2, with the fractional contributions being a decreasing function of wavelength used to select the clumps. The stellar mass profiles tend to have smaller sizes and M20 coefficients, and higher concentration and Gini coefficients than the light distribution. Our results are consistent with an inside-out disk growth scenario with brief (100 - 200 Myr) episodic local enhancements in star formation superposed on the underlying disk. Alternatively, the young ages of off-center clumps may signal inward clump migration, provided this happens efficiently on the order of an orbital timescale.Comment: Accepted by The Astrophysical Journal, 27 pages, 1 table, 16 figure

A physical and regulatory map of host-influenza interactions reveals pathways in H1N1 infection

available in PMC 2010 June 28.During the course of a viral infection, viral proteins interact with an array of host proteins and pathways. Here, we present a systematic strategy to elucidate the dynamic interactions between H1N1 influenza and its human host. A combination of yeast two-hybrid analysis and genome-wide expression profiling implicated hundreds of human factors in mediating viral-host interactions. These factors were then examined functionally through depletion analyses in primary lung cells. The resulting data point to potential roles for some unanticipated host and viral proteins in viral infection and the host response, including a network of RNA-binding proteins, components of WNT signaling, and viral polymerase subunits. This multilayered approach provides a comprehensive and unbiased physical and regulatory model of influenza-host interactions and demonstrates a general strategy for uncovering complex host-pathogen relationships.National Institutes of Health (U.S.) (grant U01 AI074575)National Institutes of Health (U.S.) (grant U54 AI057159)National Institutes of Health (U.S.) (NIH New Innovator Award)Ford Foundation (Predoctoral Fellowship)Ellison Medical FoundationNational Institutes of Health (U.S.) (NIH grant R01 HG001715)National Institutes of Health (U.S.) (grant P50 HG004233)National Institutes of Health (U.S.) (PIONEER award)Howard Hughes Medical InstituteBurroughs Wellcome Fund (Career Award at the Scientific Interface)Alfred P. Sloan Foundatio

USPIO-enhanced MR imaging for visualization of synovial hyperperfusion and detection of synovial macrophages: preliminary results in an experimental model of antigen-induced arthritis

PURPOSE: To evaluate whether ultrasmall superparamagnetic iron particles (USPIO)-enhanced MRI is capable of assessing both synovial perfusion characteristics and the presence of synovial macrophages in a model of antigen-induced arthritis. MATERIALS AND METHODS: Unilateral arthritis was induced in six knees of six rabbits. The contralateral knees of the rabbits served as control knees. After onset of arthritis, all 12 knees were scanned prior to and immediately following intravenous administration of USPIO using a multiphase T1-weighted (T1w) fast gradient-echo (FGRE) sequence, and T1w spin-echo (SE), T2-weighted (T2w) FSE, T2*w GRE, and short-tau inversion recovery (STIR) sequences prior to and 24 hours following USPIO administration. SI-vs.-time curves (STCs) and the early enhancement rate during the first 56 seconds (REE(56)) were calculated from SI measurements within the synovial tissue of all knees on dynamic T1w images. MR findings were correlated to histopathology. RESULTS: REE(56) was significantly higher in the synovial tissue of arthritic knees than in the control knees (P < 0.01). Significant T1-, T2-, and T2* effects (P = 0.03-0.04) and multiple synovial vessels were visually detectable within the arthritic synovial tissue 24 hours after administration of USPIO, whereas no signal changes or synovial vessels were seen in the control knees. Histopathology revealed widened synovial blood vessels in the arthritic knees, and confirmed iron uptake by macrophages in the arthritic knees. CONCLUSION: USPIO-enhanced MRI is capable of both assessing synovial hyperperfusion and detecting macrophages in antigen-induced arthritis in rabbits

Cancer screening: a mathematical model relating secreted blood biomarker levels to tumor sizes.

Increasing efforts and financial resources are being invested in early cancer detection research. Blood assays detecting tumor biomarkers promise noninvasive and financially reasonable screening for early cancer with high potential of positive impact on patients' survival and quality of life. For novel tumor biomarkers, the actual tumor detection limits are usually unknown and there have been no studies exploring the tumor burden detection limits of blood tumor biomarkers using mathematical models. Therefore, the purpose of this study was to develop a mathematical model relating blood biomarker levels to tumor burden.Using a linear one-compartment model, the steady state between tumor biomarker secretion into and removal out of the intravascular space was calculated. Two conditions were assumed: (1) the compartment (plasma) is well-mixed and kinetically homogenous; (2) the tumor biomarker consists of a protein that is secreted by tumor cells into the extracellular fluid compartment, and a certain percentage of the secreted protein enters the intravascular space at a continuous rate. The model was applied to two pathophysiologic conditions: tumor biomarker is secreted (1) exclusively by the tumor cells or (2) by both tumor cells and healthy normal cells. To test the model, a sensitivity analysis was performed assuming variable conditions of the model parameters. The model parameters were primed on the basis of literature data for two established and well-studied tumor biomarkers (CA125 and prostate-specific antigen [PSA]). Assuming biomarker secretion by tumor cells only and 10% of the secreted tumor biomarker reaching the plasma, the calculated minimally detectable tumor sizes ranged between 0.11 mm(3) and 3,610.14 mm(3) for CA125 and between 0.21 mm(3) and 131.51 mm(3) for PSA. When biomarker secretion by healthy cells and tumor cells was assumed, the calculated tumor sizes leading to positive test results ranged between 116.7 mm(3) and 1.52 x 10(6) mm(3) for CA125 and between 27 mm(3) and 3.45 x 10(5) mm(3) for PSA. One of the limitations of the study is the absence of quantitative data available in the literature on the secreted tumor biomarker amount per cancer cell in intact whole body animal tumor models or in cancer patients. Additionally, the fraction of secreted tumor biomarkers actually reaching the plasma is unknown. Therefore, we used data from published cell culture experiments to estimate tumor cell biomarker secretion rates and assumed a wide range of secretion rates to account for their potential changes due to field effects of the tumor environment.This study introduced a linear one-compartment mathematical model that allows estimation of minimal detectable tumor sizes based on blood tumor biomarker assays. Assuming physiological data on CA125 and PSA from the literature, the model predicted detection limits of tumors that were in qualitative agreement with the actual clinical performance of both biomarkers. The model may be helpful in future estimation of minimal detectable tumor sizes for novel proteomic biomarker assays if sufficient physiologic data for the biomarker are available. The model may address the potential and limitations of tumor biomarkers, help prioritize biomarkers, and guide investments into early cancer detection research efforts

Pharmacokinetic modeling of targeted ultrasound contrast agents for quantitative assessment of anti-angiogenic therapy: a longitudinal case-control study in colon cancer

Purpose: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice. Procedures: Colon cancer was established in 17 mice by injection of LS174T (Nr = 9) or CT26 (Nn = 8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; Nrt = Nnt = 5) or control treatment (saline; Nrc = 4, Nnc = 3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (kb), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed. Results: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value < 0.05). Prediction of the response to therapy as early as 1 day after treatment was achieved by the quantitative parameter kb (p-value < 0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value << 0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value << 0.01). Conclusion: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers

Pharmacokinetic Modeling of Targeted Ultrasound Contrast Agents for Quantitative Assessment of Anti-Angiogenic Therapy: a Longitudinal Case-Control Study in Colon Cancer

Purpose: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice. Procedures: Colon cancer was established in 17 mice by injection of LS174T (Nr = 9) or CT26 (Nn = 8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; Nrt = Nnt = 5) or control treatment (saline; Nrc = 4, Nnc = 3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (kb), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed. Results: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value < 0.05). Prediction of the response to therapy as early as 1 day after treatment was achieved by the quantitative parameter kb (p-value < 0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value << 0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value << 0.01). Conclusion: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers

Pharmacokinetic modeling of targeted ultrasound contrast agents for quantitative assessment of anti-angiogenic therapy:a longitudinal case-control study in colon cancer

\u3cp\u3ePurpose: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice. Procedures: Colon cancer was established in 17 mice by injection of LS174T (N\u3csub\u3er\u3c/sub\u3e = 9) or CT26 (N\u3csub\u3en\u3c/sub\u3e = 8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; N\u3csub\u3ert\u3c/sub\u3e = N\u3csub\u3ent\u3c/sub\u3e = 5) or control treatment (saline; N\u3csub\u3erc\u3c/sub\u3e = 4, N\u3csub\u3enc\u3c/sub\u3e = 3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (k\u3csub\u3eb\u3c/sub\u3e), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed. Results: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value &lt; 0.05). Prediction of the response to therapy as early as 1 day after treatment was achieved by the quantitative parameter k\u3csub\u3eb\u3c/sub\u3e (p-value &lt; 0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value &lt;&lt; 0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value &lt;&lt; 0.01). Conclusion: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers.\u3c/p\u3

Targeted Microbubbles for Imaging Tumor Angiogenesis: Assessment of Whole-Body Biodistribution with Dynamic Micro-PET in Mice

Purpose: To evaluate in vivo whole-body biodistribution of microbubbles (MBs) targeted to tumor angiogenesis–related vascular endothelial growth factor (VEGF) receptor 2 (VEGFR2) by using dynamic micro–positron emission tomography (PET) in living mice