The optical absorption and scattering coefficients have been determined for specimens of normal and diseased human breast tissues over the range of wavelengths from 500 to 1100 nm. Total attenuation coefficients were measured for thin slices of tissue cut on a microtome. The diffuse reflectance and transmittance were measured for 1.0 mm thick samples of these tissues, using standard integrating sphere techniques. Monte Carlo simulations were performed to derive the scattering and absorption coefficients, as well as the mean cosine of the scattering angle. The results indicate that scatter exceeds absorption by at least two orders of magnitude. Absorption is most significant at wavelengths below 600 nm. The scattering coefficients lie in the range 30-90 mm-1 at 500 nm, and fall smoothly with increasing wavelength to between 10 and 50 mm-1 at 1100 nm. The scattering coefficient for adipose tissue differs, in that it is invariant with wavelength over this spectral range. For all tissues examined, the scattered light is highly forward peaked, with the mean cosine of the scattering angle in the range 0.945-0.985. Systematic differences between the optical properties of some tissue types are demonstrated.
Cells respond to many stressors by senescing, acquiring stable growth arrest, morphologic and metabolic changes, and a proinflammatory senescence-associated secretory phenotype. The heterogeneity of senescent cells (SnCs) and senescence-associated secretory phenotype are vast, yet ill characterized. SnCs have diverse roles in health and disease and are therapeutically targetable, making characterization of SnCs and their detection a priority. The Cellular Senescence Network (SenNet), a National Institutes of Health Common Fund initiative, was established to address this need. The goal of SenNet is to map SnCs across the human lifespan to advance diagnostic and therapeutic approaches to improve human health. State-of-the-art methods will be applied to identify, define and map SnCs in 18 human tissues. A common coordinate framework will integrate data to create four-dimensional SnC atlases. Other key SenNet deliverables include innovative tools and technologies to detect SnCs, new SnC biomarkers and extensive public multi-omics datasets. This Perspective lays out the impetus, goals, approaches and products of SenNet.
Interferon lambda (IFNλ) signaling is a promising therapeutic target against viral infection in murine models, yet little is known about its molecular regulation and its cognate receptor, interferon lambda receptor 1 (IFNLR1) in human lung. We hypothesized that the IFNλ signaling axis was active in human lung macrophages. In human alveolar macrophages (HAMs), we observed increased IFNLR1 expression and robust increase in interferon-stimulated gene (ISG) expression in response to IFNλ ligand. While human monocytes express minimal IFNLR1, differentiation of monocytes into macrophages with macrophage colony-stimulating factor (M-CSF) or granulocyte-macrophage colony-stimulating factor (GM-CSF) increased IFNLR1 mRNA, IFNLR1 protein expression, and cellular response to IFNλ ligation. Conversely, in mice, M-CSF or GM-CSF stimulated macrophages failed to produce ISGs in response to related ligands, IFNL2 or IFNL3, suggesting that IFNLR1 signaling in macrophages is species-specific. We next hypothesized that IFNλ signaling was critical in influenza antiviral responses. In primary human airway epithelial cells and precision-cut human lung slices, influenza infection substantially increased IFNλ levels. Pretreatment of both HAMs and differentiated human monocytes with IFNL1 significantly inhibited influenza infection. IFNLR1 knockout in the myeloid cell line, THP-1, exhibited reduced interferon responses to either direct or indirect exposure to influenza infection suggesting the indispensability of IFNLR1 for antiviral responses. These data demonstrate the presence of IFNλ - IFNLR1 signaling axis in human lung macrophages and a critical role of IFNλ signaling in combating influenza infection.
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