Compatibility of Popular Three-Dimensional Printed Microfluidics Materials with In Vitro Enzymatic Reactions.

3D printed microfluidics offer several advantages over conventional planar microfabrication techniques including fabrication of 3D microstructures, rapid prototyping, and inertness. While 3D printed materials have been studied for their biocompatibility in cell and tissue culture applications, their compatibility for in vitro biochemistry and molecular biology has not been systematically investigated. Here, we evaluate the compatibility of several common enzymatic reactions in the context of 3D-printed microfluidics: (1) polymerase chain reaction (PCR), (2) T7 in vitro transcription, (3) mammalian in vitro translation, and (4) reverse transcription. Surprisingly, all the materials tested significantly inhibit one or more of these in vitro enzymatic reactions. Inclusion of BSA mitigates only some of these inhibitory effects. Overall, inhibition appears to be due to a combination of the surface properties of the resins as well as soluble components (leachate) originating in the matrix.

Enabling Flow-Based Kinetic Off-Rate Selections Using a Microfluidic Enrichment Device.

Modern genomic sequencing efforts are identifying potential diagnostic and therapeutic targets more rapidly than existing methods can generate the peptide- and protein-based ligands required to study them. To address this problem, we have developed a microfluidic enrichment device (MFED) enabling kinetic off-rate selection without the use of exogenous competitor. We tuned the conditions of the device (bed volume, flow rate, immobilized target) such that modest, readily achievable changes in flow rates favor formation or dissociation of target-ligand complexes based on affinity. Simple kinetic equations can be used to describe the behavior of ligand binding in the MFED and the kinetic rate constants observed agree with independent measurements. We demonstrate the utility of the MFED by showing a 4-fold improvement in enrichment compared to standard selection. The MFED described here provides a route to simultaneously bias pools toward high-affinity ligands while reducing the demand for target-protein to less than a nanomole per selection.

Accounting for measurement error in log regression models with applications to accelerated testing.

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.

RasIns: Genetically Encoded Intrabodies of Activated Ras Proteins.

K- and H-Ras are the most commonly mutated genes in human tumors and are critical for conferring and maintaining the oncogenic phenotype in tumors with poor prognoses. Here, we design genetically encoded antibody-like ligands (intrabodies) that recognize active, GTP-bound K- and H-Ras. These ligands, which use the 10th domain of human fibronectin as their scaffold, are stable inside the cells and when fused with a fluorescent protein label, the constitutively active G12V mutant H-Ras. Primary selection of ligands against Ras with mRNA display resulted in an intrabody (termed RasIn1) that binds with a KD of 2.1µM to H-Ras(G12V) (GTP), excellent state selectivity, and remarkable specificity for K- and H-Ras. RasIn1 recognizes residues in the Switch I region of Ras, similar to Raf-RBD, and competes with Raf-RBD for binding. An affinity maturation selection based on RasIn1 resulted in RasIn2, which binds with a KD of 120nM and also retains excellent state selectivity. Both of these intrabodies colocalize with H-Ras, K-Ras, and G12V mutants inside the cells, providing new potential tools to monitor and modulate Ras-mediated signaling. Finally, RasIn1 and Rasin2 both display selectivity for the G12V mutants as compared with wild-type Ras providing a potential route for mutant selective recognition of Ras.

1H and 13C NMR assignments for the cyanine dyes SYBR Safe and thiazole orange.

Analysis of (1)H and (13)C NMR and mass spectral data for the fluorescent nucleic acid stain SYBR Safe indicates that it contains a cyanine-based cationic core structure identical to thiazole orange. The difference between these two compounds is the type of N-substitution on the quinolinium ring system (SYBR Safe, n-Pr; thiazole orange, Me). The (1)H and (13)C NMR resonances for both compounds were assigned on the basis of one- and two-dimensional (COSY, ROESY, HSQC, and HMBC) experiments. The preferred conformation of these compounds was computed by ab initio methods and found to be consistent with the NMR data.

Synthesis and characterization of photoluminescent In-doped CdSe nanoparticles.

Indium-doped CdSe nanoparticles have been synthesized and characterized. Their light absorption, photoluminescence, and structure are similar to undoped CdSe nanoparticles. The greater part of the In associated with the nanoparticles is removed when the nanoparticles undergo ligand exchange by pyridine. As observed with undoped nanoparticles, a ZnS capping layer on the indium-doped nanoparticles results in enhanced nanocrystal photoluminescence. Also, the ZnS cap enhances the retention of In by the nanoparticles. Elemental analysis shows ligand exchange causes CdSe to be lost and capping with ZnS results in the loss of Se. We conclude that In-doped nanoparticles have most of the In on their surface, capping helps the nanoparticles retain the In, and they do not have altered electronic properties.

Generalized emissivity inverse problem.

Inverse problems have recently drawn considerable attention from the physics community due to of potential widespread applications [K. Chadan and P. C. Sabatier, Inverse Problems in Quantum Scattering Theory, 2nd ed. (Springer Verlag, Berlin, 1989)]. An inverse emissivity problem that determines the emissivity g(nu) from measurements of only the total radiated power J(T) has recently been studied [Tao Wen, DengMing Ming, Xianxi Dai, Jixin Dai, and William E. Evenson, Phys. Rev. E 63, 045601(R) (2001)]. In this paper, a new type of generalized emissivity and transmissivity inverse (GETI) problem is proposed. The present problem differs from our previous work on inverse problems by allowing the unknown (emissivity) function g(nu) to be temperature dependent as well as frequency dependent. Based on published experimental information, we have developed an exact solution formula for this GETI problem. A universal function set suggested for numerical calculation is shown to be robust, making this inversion method practical and convenient for realistic calculations.

Functional integral approach: a third formulation of quantum statistical mechanics.

Quantum statistical mechanics has developed primarily through two approaches, pioneered by Gibbs and Feynman, respectively. In Gibbs' method one calculates partition functions from phase-space integrations or sums over stationary states. Alternatively, in Feynman's approach, the focus is on the path-integral formulation. The Hubbard-Stratonovich transformation leads to a functional-integral formulation for calculating partition functions. We outline here the functional integral approach to quantum statistical mechanics, including generalizations and improvements to Hubbard's formulation. We show how the dimensionality of the integrals is reduced exactly, how the problem of assuming an unknown canonical transformation is avoided, how the reality of the partition function in the complex representation is guaranteed, and how the extremum conditions are simplified. This formulation can be applied to general systems, including superconductors.