Schrey et al House Sparrow Kenya Msat

Genpop data file of Kenyan house sparrows. Abbreviations are defined in text

CORTWNVMS_forDryad_Gervasi_6_9_17

Individual sheets for analyses of survival, viremia, cytokine levels, host performance, tolerance, and infectiousnes

Performance management in a rapidly changing world: implications for talent management

Purpose: This conceptual work examines how, in times of post-COVID-19 paradigm shift, the employee performance management (PM) process can help multinational corporations (MNCs) strengthen their talent management and, at the same time, meet their future needs.Design/methodology/approachWe take a conceptual approach and present our perspective on what we see as the most critical trends shaping PM and talent management. Contingency theory and Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) theory provide a sound theoretical framework for understanding and responding to the complex and rapidly changing business context post-COVID-19.Findings: Drawing on these theories, we create a framework providing a means of understanding why and how MNCs can maintain talent and, at the same time, develop new talent through the PM process.Practical implicationsImportantly, our study emphasizes the critical role that project management and talent management techniques play for both practitioners and scholars. In order to gain and sustain a competitive edge in the ever-changing VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) landscape, these processes necessitate ongoing reassessment and adaptation. As Plato eloquently stated, “Our Need Will Be the Real Creator,” encapsulating our vision for the proactive and dynamic nature of effective project management and talent management practices.Originality/value: The study establishes the benefits of an agile and flexible PM approach to help develop talent and pave the way for future research in this increasingly critical area</p

Radioluminescence Microscopy: Measuring the Heterogeneous Uptake of Radiotracers in Single Living Cells

<div><p>Radiotracers play an important role in interrogating molecular processes both <em>in vitro</em> and <em>in vivo</em>. However, current methods are limited to measuring average radiotracer uptake in large cell populations and, as a result, lack the ability to quantify cell-to-cell variations. Here we apply a new technique, termed <em>radioluminescence microscopy</em>, to visualize radiotracer uptake in single living cells, in a standard fluorescence microscopy environment. In this technique, live cells are cultured sparsely on a thin scintillator plate and incubated with a radiotracer. Light produced following beta decay is measured using a highly sensitive microscope. Radioluminescence microscopy revealed strong heterogeneity in the uptake of [¹⁸F]fluoro-deoxyglucose (FDG) in single cells, which was found consistent with fluorescence imaging of a glucose analog. We also verified that dynamic uptake of FDG in single cells followed the standard two-tissue compartmental model. Last, we transfected cells with a fusion PET/fluorescence reporter gene and found that uptake of FHBG (a PET radiotracer for transgene expression) coincided with expression of the fluorescent protein. Together, these results indicate that radioluminescence microscopy can visualize radiotracer uptake with single-cell resolution, which may find a use in the precise characterization of radiotracers.</p> </div

Performance characterization.

<p>FDG aggregates were obtained by evaporating an aqueous solution of FDG between a scintillator and a glass-bottom imaging dish. (<b>A</b>) Fused radioluminescence and brightfield images; (<b>B</b>) Brightfield and (<b>C</b>) radioluminescence images, magnified; (<b>D</b>) Brightfield and (<b>E</b>) radioluminescence images, further magnified, focusing on one particular FDG aggregate; (<b>F</b>,<b>G</b>) 2-D Gaussian fit of (D) and (E), respectively. (<b>H</b>) Radioluminescence microscope sensitivity, obtained by imaging the decay of a drop of FDG (2.6 µCi) over time. <i>Solid line</i>: mean pixel intensity; <i>Dashed line</i>: ideal exponential decay for ¹⁸F. (<b>I</b>) Per-pixel signal-to-noise ratio, defined as the ratio of the average pixel intensity to the noise standard deviation. The sensitivity of the system is defined here as the amount of activity required per area to achieve a SNR of 5 (Rose criterion ).</p

Overview of the radioluminescence microscope.

<p>(<b>A</b>) Radioluminescence is produced within a scintillator plate following the emission of a beta particle from a radiotracer within a cell (yellow glow). The optical photons are captured by a high-numerical-aperture objective coupled to a deep-cooled EM-CCD camera. Emission and excitation filters used in combination with a light source allow for concurrent fluorescence and brightfield microscopy. (<b>B</b>) Photograph of the system showing a glass-bottom dish containing a scintillator plate immersed in cell culture medium and placed into the inverted microscope. (<b>C</b>) Three GFP-expressing HeLa cells located near the corner of a scintillator plate were localized using fluorescence microscopy (<i>arrows</i>). The edge of the scintillator plate is outlined in red. (<b>D</b>) After incubation with FDG (400 µCi, 1 h), these three cells also produced focal radioluminescence signal coincident with the fluorescent emission.</p

Pharmacokinetics analysis in single cells.

<p>(<b>A</b>) Two-tissue compartmental model describing FDG pharmacokinetics, including influx (<i>K</i>₁), efflux (<i>k</i>₂), phosphorylation to FDG-6-phosphate (<i>k</i>₃), and dephosphorylation (<i>k</i>₄). (<b>B</b>) Patlak analysis modeling FDG influx kinetics for a single cell (highlighted by a red circle in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046285#pone-0046285-g003" target="_blank">Figure 3A</a>). (<b>C</b>,<b>D</b>) Rate of efflux (<i>k</i>₂) and phosphorylation (<i>k</i>₃) plotted as a function of rate of influx (<i>K</i>₁) for all the cells in the microscope’s field of view. (<b>E</b>) Compartmental analysis modeling FDG efflux kinetics from a single cell (highlighted by a red circle in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0046285#pone-0046285-g003" target="_blank">Figure 3C</a>) after withdrawal of FDG, presenting a fast and a slow component. (<b>F</b>) The model for FDG efflux is the sum of a fast and a slow component (rates <i>λ</i>₁ and <i>λ</i>₂, respectively), which are plotted for all the cells in the field of view.</p

Dynamic radioluminescence imaging of FDG in single cells.

<p>Micrographs (brightfield and radioluminescence) were acquired every 6 min for 8 h for three experiments. (<b>A</b>) MDA-MB-231 cells are imaged while being incubated with FDG (5 µCi). (<b>B</b>) Glucose (25 mM) is added 2 h after the beginning of the incubation with FDG (5 µCi). (<b>C</b>) FDG is withdrawn at the start of imaging after incubation (1 h, 400 µCi). Scale bar: 100 µm. (<b>E–F</b>) Time-activity curves plotted for individual cells (light red lines) and 10 control ROIs manually selected in the background (light blue lines), for all three experiments. The thick red and blue lines represent the average for cells and control ROIs, respectively.</p

Radioluminescence imaging of FDG uptake in single cells.

<p>Human breast cancer cells (MDA-MB-231) were deprived of glucose for 1 h, incubated for 1 h with FDG (400 µCi) and 2-NBDG (100 µM), and then washed. (<b>A</b>) Brightfield (scale bar, 100 µm.), radioluminescence (FDG), and fluorescence (2-NBDG) micrographs (Objective: 40X/1.3 NA). Overlay, showing co-localized radioluminescence (green) and fluorescence (red). (<b>B</b>) Scatter plot comparing FDG and 2-NBDG uptake, computed over 140 cells (light red dots) and 26 control ROIs (blue dots). The green line was obtained by linear regression (correlation, r = 0.74). Arbitrary units (A.U.). (<b>C</b>) Radioluminescence (FDG) and fluorescence (2-NBDG) intensity shown along a line profile [red dashed line in (A)].</p

Radioluminescence imaging of gene expression in single cells.

<p>Human cervical cancer cells (HeLa) transfected with a fusion PET/fluorescence reporter gene were incubated with FHBG (300 µCi, 2 h). (<b>A</b>) Brightfield (scale bar, 50 µm), radioluminescence (FHBG), and fluorescence (RFP) micrographs (objective, 100X/1.35 NA). Overlay shows FHBG radioluminescence (green), RFP fluorescence (red), and cell outline segmented from brightfield. Cells negative for RFP are also negative for FHBG (red arrows). (<b>B</b>) Same as (A), but with a 40X/1.3 NA objective (scale bar, 100 µm). White arrows indicate cells with weak fluorescence intensity but substantial radioluminescence intensity. The green arrow points to a cell with no RFP expression but ambiguous radioluminescence intensity. (<b>C</b>) Scatter plot of FHBG vs. RFP uptake, computed for 245 cells (light red dots) and 100 control ROIs (blue dots). Arbitrary units. (<b>D</b>) Radioluminescence and fluorescence shown along a line profile [red dashed line in (A)]. (<b>E</b>) Same experiment as (A,B), but using control wild-type HeLa cells (scale bar, 100 µm).</p