Parameters characterizing the interactions between tumor suppression factors and tumor cells in the CA dormancy model.

<p>Note that the two “critical threshold” parameters themselves do not incorporate any additional CA rules.</p><p>Parameters characterizing the interactions between tumor suppression factors and tumor cells in the CA dormancy model.</p

Fluorescence micrograph of a breast tumor stained to visualize carcinoma cells (phospho-p53, green) surrounded by macrophages (CD11b, red) (a).

<p>Nuclei appear blue (DAPI). Image courtesy of Michael Graham Espey, PhD, National Cancer Institute, NIH (private communication). (b) Representative pictures of dormant and fast-growing tumors and their vascular structure. Reprinted from Cancer Letters, 294, Almog N, Molecular mechanisms underlying tumor dormancy, 139–146, Copyright (2010), with permission from Elsevier.</p

Simulated tumor area <i>A_T</i> normalized by the area <i>A</i>₀ of the growth permitting region of a noninvasive tumor growing in the ECM with different .

<p>Simulated tumor area <i>A_T</i> normalized by the area <i>A</i>₀ of the growth permitting region of a noninvasive tumor growing in the ECM with different .</p

Tumor area <i>A_T</i> normalized by the area <i>A</i>₀ of the growth permitting region of a simulated noninvasive tumor growing in the ECM under different killing rates by microenvironmental suppression factors.

<p>The parameter <i>k</i>₀ is the fraction that the suppression factors from the microenvironment kill the actively dividing proliferative cells when the suppression factors counteract these cells.</p

Snapshots of a simulated noninvasive tumor growing in the ECM with on different days given by the CA dormancy model.

<p>Upper panel: Dormancy period. Lower panel: Regrowth period.</p

The “critical” point at which the noninvasive tumor growing in the ECM with switches from a dormant state to a proliferative state as functions of <i>α</i> and (a).

<p>A schematic phase diagram that characterizes the growth dynamics of a noninvasive tumor growing in the ECM with under different <i>α</i> and (b).</p

Upper panel: statistics of a simulated noninvasive tumor growing in the ECM with and microenvironmental suppression factors, as predicted by the “CA dormancy model”.

<p>(a) Tumor area <i>A_T</i> normalized by the area <i>A</i>₀ of the growth permitting region. (b) Areas of different cell populations normalized by the area <i>A</i>₀ of the growth permitting region. Lower panel: statistics of a simulated noninvasive tumor growing in the ECM with without suppression. (c) Tumor area <i>A_T</i> normalized by the area <i>A</i>₀ of the growth permitting region. (d) Areas of different cell populations normalized by the area <i>A</i>₀ of the growth permitting region.</p

Asymmetric Miktoarm Star Polymers as Polyester Thermoplastic Elastomers

A library of polyester-based A­(BA′)n asymmetric miktoarm star polymers was synthesized with A, A′ = poly­(l-lactide) (PLLA) as the semicrystalline hard blocks and B = poly­(4-methylcaprolactone) (PMCL) as the soft segment using a grafting-through platform known as μSTAR. The synthetic versatility of μSTAR enabled a systematic investigation of architectural design parameters, in particular the number of BA′ arms (n), while holding the A, A′, and B block lengths constant. The value of n has a pronounced impact on the mechanical properties of these high-molecular-weight miktoarm materials. Tensile toughness increases with n, an effect likely related to bridging, as the modulus drops because the hard-block volume fraction decreases. These insights expand our understanding of architecture effects in sustainable thermoplastic elastomers

A General Chemiluminescence Strategy for Measuring Aptamer–Target Binding and Target Concentration

Although much effort has been made for studies on aptamer–target interactions due to promising applications of aptamers in biomedical and analytical fields, measurement of the aptamer–target binding constant and binding site still remains challenging. Herein, we report a sensitive label-free chemiluminescence (CL) strategy to determine the target concentration and, more importantly, to measure the target–aptamer binding constant and binding site. This approach is suitable for multiple types of targets, including small molecules, peptides, and proteins that can enhance the CL initiated by <i>N</i>-(amino­butyl)-<i>N</i>-ethyliso­luminol functionalized gold colloids, making the present method a general platform to investigate aptamer–target interactions. This approach can achieve extremely high sensitivity with nanogram samples for measuring the target–aptamer binding constant. And the measurement could be rapidly performed using a simple and low-cost CL system. It provides an effective tool for studying the binding of biologically important molecules to nucleic acids and the selection of aptamers. Besides, we have also discovered that the 14-mer aptamer fragment itself split from the ATP-binding aptamer could selectively capture ATP. The binding constant, site, and conformation between ATP and the 14-mer aptamer fragment were obtained using such a novel CL strategy and molecular dynamic simulation