The Roles of PPARs in the Fetal Origins of Metabolic Health and Disease

Beyond the short-term effects on fertility, there is increasing evidence that obesity or the consumption of an inappropriate diet by the mother during pregnancy adversely affects the long-term health of her offspring. PPAR and RXR isotypes are widely expressed in reproductive tissues and in the developing fetus. Through their interactions with fatty acids, they may mediate adaptive responses to the changes in the maternal diet. In the maturing follicle, PPAR-γ has an important role in the granulosa cells that surround the maturing oocyte. After fertilisation, PPAR-γ and PPAR-β/δ are essential regulators of placentation and the subsequent development of key metabolic tissues such as skeletal muscle and adipose cells. Activation of PPAR-γ and PPAR-β/δ during fetal development has the potential to modify the growth and development of these tissues. PPAR-α is expressed at low levels in the fetal liver, however, this expression may be important, as changes in the methylation of DNA in its promoter region are reported to take place during this period of development. This epigenetic modification then programmes subsequent expression. These findings suggest that two separate PPAR-dependent mechanisms may be involved in the fetal adaptations to the maternal diet, one, mediated by PPAR-γ and PPAR-β/δ, regulating cell growth and differentiation; and another adapting long-term lipid metabolism via epigenetic changes in PPAR-α to optimise postnatal survival

Atomic Resonance and Scattering

Contains research objectives, summary of research and reports on six research projects.Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 28-043-AMC-02536(E)National Science Foundation (Grant GP-13633)National Bureau of Standards (Grant NBS(G)-269

Effect of remission status and induction chemotherapy regimen on outcome of autologous stem cell transplantation for mantle cell lymphoma.

We analysed the outcomes of autologous stem cell transplantation (ASCT) following high-dose therapy with respect to remission status at the time of transplantation and induction regimen used in 56 consecutive patients with mantle cell lymphoma (MCL). Twenty-one patients received induction chemotherapy with HyperCVAD with or without rituximab (+/-R) followed by ASCT in first complete or partial remission (CR1/PR1), 15 received CHOP (+/-R) followed by ASCT in CR1/PR1 and 20 received ASCT following disease progression. Estimates of overall and progression-free survival (PFS) at 3 years among patients transplanted in CR1/PR1 were 93% and 63% compared with 46% and 36% for patients transplanted with relapsed/refractory disease, respectively. The hazard of mortality among patients transplanted with relapsed/refractory disease was 6.09 times that of patients transplanted in CR1/PR1 (P = 0.006). Patients in the CHOP (+/-R) group had a higher risk of failure for PFS compared with patients in the HyperCVAD (+/-R) group, though the difference did not reach statistical significance (hazard ratio 3.67, P = 0.11). These results suggest that ASCT in CR1/PR1 leads to improved survival outcomes for patients with MCL compared to ASCT with relapsed/refractory disease, and a HyperCVAD (+/-R) induction regimen may be associated with an improved PFS among patients transplanted in CR1/PR1

Modeling and synthesis of breast cancer optical property signatures with generative models

Is it possible to find deterministic relationships between optical measurements and pathophysiology in an unsupervised manner and based on data alone? Optical property quantification is a rapidly growing biomedical imaging technique for characterizing biological tissues that shows promise in a range of clinical applications, such as intraoperative breast-conserving surgery margin assessment. However, translating tissue optical properties to clinical pathology information is still a cumbersome problem due to, amongst other things, inter- and intrapatient variability, calibration, and ultimately the nonlinear behavior of light in turbid media. These challenges limit the ability of standard statistical methods to generate a simple model of pathology, requiring more advanced algorithms. We present a data-driven, nonlinear model of breast cancer pathology for real-time margin assessment of resected samples using optical properties derived from spatial frequency domain imaging data. A series of deep neural network models are employed to obtain sets of latent embeddings that relate optical data signatures to the underlying tissue pathology in a tractable manner. These self-explanatory models can translate absorption and scattering properties measured from pathology, while also being able to synthesize new data. The method was tested on a total of 70 resected breast tissue samples containing 137 regions of interest, achieving rapid optical property modeling with errors only limited by current semi-empirical models, allowing for mass sample synthesis and providing a systematic understanding of dataset properties, paving the way for deep automated margin assessment algorithms using structured light imaging or, in principle, any other optical imaging technique seeking modeling. Code is available.This work was supported in part by the National Cancer Institute, US National Institutes of Health, under grants R01 CA192803 and F31 CA196308, by the Spanish Ministry of Science and Innovation under grant FIS2010-19860, by the Spanish Ministry of Science, Innovation and Universities under grants TEC2016-76021-C2-2-R and PID2019-107270RB-C21, by the Spanish Minstry of Economy, Industry and Competitiveness and Instituto de Salud Carlos III via DTS17-00055, by IDIVAL under grants INNVAL 16/02, and INNVAL 18/23, and by the Spanish Ministry of Education, Culture, and Sports with PhD grant FPU16/05705, as well as FEDER funds

Correction to: Perceived economic self-sufficiency: a country- and generation-comparative approach

After online first publication of the article, it was noticed that the family name of author Panos Tsakloglou was erroneously misspelt as Tsakoglou

Z-Spec: a broadband direct-detection millimeter-wave spectrometer -- instrument status and first results

We report on the status of Z-Spec, including preliminary results of our first astronomical measurements. Z-Spec is a cryogenic, broadband, millimeter-wave grating spectrometer designed for molecular line surveys of galaxies, including carbon monoxide redshift measurements of high-redshift submillimeter sources. With an instantaneous bandwidth of 185-305 GHz, Z-Spec covers the entire 1 mm atmospheric transmission window with a resolving power of 200-400. The spectrometer employs the Waveguide Far-Infrared Spectrometer (WaFIRS) architecture, in which the light propagation is confined within a parallel-plate waveguide, resulting in a minimum mechanical envelope. Its array of 160 silicon-nitride micromesh bolometers is cooled to below 100 mK for background-limited performance. With its sensitivity, broad bandwidth, and compactness, Z-Spec serves as a prototype for a future far-IR spectrometer aboard a cold telescope in space. Z-Spec successfully demonstrated functionality with a partial array of detectors and warm electronics during a week-long engineering run at the Caltech Submillimeter Observatory in June, 2005. We describe the instrument performance evaluated at the telescope and in subsequent laboratory tests and compare these results with design specifications. Following several modifications we returned to the telescope in April, 2006. We present a preliminary astronomical spectrum and discuss our plans to improve sensitivity and throughput to achieve our ultimate science goals

Canvass: a crowd-sourced, natural-product screening library for exploring biological space

NCATS thanks Dingyin Tao for assistance with compound characterization. This research was supported by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH). R.B.A. acknowledges support from NSF (CHE-1665145) and NIH (GM126221). M.K.B. acknowledges support from NIH (5R01GM110131). N.Z.B. thanks support from NIGMS, NIH (R01GM114061). J.K.C. acknowledges support from NSF (CHE-1665331). J.C. acknowledges support from the Fogarty International Center, NIH (TW009872). P.A.C. acknowledges support from the National Cancer Institute (NCI), NIH (R01 CA158275), and the NIH/National Institute of Aging (P01 AG012411). N.K.G. acknowledges support from NSF (CHE-1464898). B.C.G. thanks the support of NSF (RUI: 213569), the Camille and Henry Dreyfus Foundation, and the Arnold and Mabel Beckman Foundation. C.C.H. thanks the start-up funds from the Scripps Institution of Oceanography for support. J.N.J. acknowledges support from NIH (GM 063557, GM 084333). A.D.K. thanks the support from NCI, NIH (P01CA125066). D.G.I.K. acknowledges support from the National Center for Complementary and Integrative Health (1 R01 AT008088) and the Fogarty International Center, NIH (U01 TW00313), and gratefully acknowledges courtesies extended by the Government of Madagascar (Ministere des Eaux et Forets). O.K. thanks NIH (R01GM071779) for financial support. T.J.M. acknowledges support from NIH (GM116952). S.M. acknowledges support from NIH (DA045884-01, DA046487-01, AA026949-01), the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program (W81XWH-17-1-0256), and NCI, NIH, through a Cancer Center Support Grant (P30 CA008748). K.N.M. thanks the California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board for support. B.T.M. thanks Michael Mullowney for his contribution in the isolation, elucidation, and submission of the compounds in this work. P.N. acknowledges support from NIH (R01 GM111476). L.E.O. acknowledges support from NIH (R01-HL25854, R01-GM30859, R0-1-NS-12389). L.E.B., J.K.S., and J.A.P. thank the NIH (R35 GM-118173, R24 GM-111625) for research support. F.R. thanks the American Lebanese Syrian Associated Charities (ALSAC) for financial support. I.S. thanks the University of Oklahoma Startup funds for support. J.T.S. acknowledges support from ACS PRF (53767-ND1) and NSF (CHE-1414298), and thanks Drs. Kellan N. Lamb and Michael J. Di Maso for their synthetic contribution. B.S. acknowledges support from NIH (CA78747, CA106150, GM114353, GM115575). W.S. acknowledges support from NIGMS, NIH (R15GM116032, P30 GM103450), and thanks the University of Arkansas for startup funds and the Arkansas Biosciences Institute (ABI) for seed money. C.R.J.S. acknowledges support from NIH (R01GM121656). D.S.T. thanks the support of NIH (T32 CA062948-Gudas) and PhRMA Foundation to A.L.V., NIH (P41 GM076267) to D.S.T., and CCSG NIH (P30 CA008748) to C.B. Thompson. R.E.T. acknowledges support from NIGMS, NIH (GM129465). R.J.T. thanks the American Cancer Society (RSG-12-253-01-CDD) and NSF (CHE1361173) for support. D.A.V. thanks the Camille and Henry Dreyfus Foundation, the National Science Foundation (CHE-0353662, CHE-1005253, and CHE-1725142), the Beckman Foundation, the Sherman Fairchild Foundation, the John Stauffer Charitable Trust, and the Christian Scholars Foundation for support. J.W. acknowledges support from the American Cancer Society through the Research Scholar Grant (RSG-13-011-01-CDD). W.M.W.acknowledges support from NIGMS, NIH (GM119426), and NSF (CHE1755698). A.Z. acknowledges support from NSF (CHE-1463819). (Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH); CHE-1665145 - NSF; CHE-1665331 - NSF; CHE-1464898 - NSF; RUI: 213569 - NSF; CHE-1414298 - NSF; CHE1361173 - NSF; CHE1755698 - NSF; CHE-1463819 - NSF; GM126221 - NIH; 5R01GM110131 - NIH; GM 063557 - NIH; GM 084333 - NIH; R01GM071779 - NIH; GM116952 - NIH; DA045884-01 - NIH; DA046487-01 - NIH; AA026949-01 - NIH; R01 GM111476 - NIH; R01-HL25854 - NIH; R01-GM30859 - NIH; R0-1-NS-12389 - NIH; R35 GM-118173 - NIH; R24 GM-111625 - NIH; CA78747 - NIH; CA106150 - NIH; GM114353 - NIH; GM115575 - NIH; R01GM121656 - NIH; T32 CA062948-Gudas - NIH; P41 GM076267 - NIH; R01GM114061 - NIGMS, NIH; R15GM116032 - NIGMS, NIH; P30 GM103450 - NIGMS, NIH; GM129465 - NIGMS, NIH; GM119426 - NIGMS, NIH; TW009872 - Fogarty International Center, NIH; U01 TW00313 - Fogarty International Center, NIH; R01 CA158275 - National Cancer Institute (NCI), NIH; P01 AG012411 - NIH/National Institute of Aging; Camille and Henry Dreyfus Foundation; Arnold and Mabel Beckman Foundation; Scripps Institution of Oceanography; P01CA125066 - NCI, NIH; 1 R01 AT008088 - National Center for Complementary and Integrative Health; W81XWH-17-1-0256 - Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program; P30 CA008748 - NCI, NIH, through a Cancer Center Support Grant; California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board; American Lebanese Syrian Associated Charities (ALSAC); University of Oklahoma Startup funds; 53767-ND1 - ACS PRF; PhRMA Foundation; P30 CA008748 - CCSG NIH; RSG-12-253-01-CDD - American Cancer Society; RSG-13-011-01-CDD - American Cancer Society; CHE-0353662 - National Science Foundation; CHE-1005253 - National Science Foundation; CHE-1725142 - National Science Foundation; Beckman Foundation; Sherman Fairchild Foundation; John Stauffer Charitable Trust; Christian Scholars Foundation)Published versionSupporting documentatio

allogeneic hematopoietic cell transplantation hct in the eighth decade of life how much does age matter

n/

Investigation of the obscuring circumnuclear torus in the active galaxy Mrk231

Here we report on observations of powerful hydroxyl (OH) line emissions that trace the obscuring material within the circumnuclear environment of the galaxy Markarian 231. The hydroxyl (mega)-maser emission shows the characteristics of a rotating, dusty, molecular torus (or thick disk) located between 30 and 100 pc from the central engine. We now have a clear view of the physical conditions, the kinematics and the spatial structure of this material on intermediate size scales, confirming the main tenets of unification models.Comment: 10 pages, including 3 Figures, published in Nature Vol 421 2003; the published pdf--file and higher quality images are available at http://www.astro.rug.nl/~hrkloeck/np/pubmrk231.htm