Statistical design of position-encoded microsphere arrays

We propose a microsphere array device with microspheres having controllable positions for error-free target identification. We conduct a statistical design analysis to select the optimal distance between the microspheres as well as the optimal temperature. Our design simplifies the imaging and ensures a desired statistical performance for a given sensor cost. Specifically, we compute the posterior Cramér-Rao bound on the errors in estimating the unknown target concentrations. We use this performance bound to compute the optimal design variables. We discuss both uniform and sparse concentration levels of targets, and replace the unknown imaging parameters with their maximum likelihood estimates. We illustrate our design concept using numerical examples. The proposed microarray has high sensitivity, efficient packing, and guaranteed imaging performance. It simplifies the imaging analysis significantly by identifying targets based on the known positions of the microspheres. Potential applications include molecular recognition, specificity of targeting molecules, protein-protein dimerization, high throughput screening assays for enzyme inhibitors, drug discovery, and gene sequencing.     

In vitro frictional behavior and wear patterns between contemporary and aesthetic composite orthodontic brackets and archwires

This study evaluates the effects of surface roughness, saliva and bracket materials on in vitro frictional resistance of contemporary and aesthetic orthodontic brackets during the sliding of archwires against elastomeric ligature. Eight various brackets were investigated together with stainless steel (SS) archwires of several shapes. The sliding force involved in a ligated bracket-archwire combination was measured in an Instron by a self-designed jig. The interfaces were also examined using scanning electron microscope (SEM) to simulate sliding mechanics and abrasive/adhesive wear of the bottom surfaces of the bracket slots, which were observed under dry condition. Round SS archwires (SRO-OR) demonstrated the lower frictional force compared to coated round SS archwire (SRO-AW) and the flat SS archwire (rectangular and square) surfaces for most of the brackets. Braided composite bracket without a metal slot had the least resistance when sliding with SRO-OR archwire whilst the composite bracket (Spirit MB) with a metal slot demonstrated the lower resistance. Ceramic bracket (Inspire) without a metal slot, which also reflected severe wear patterns produced a significantly larger frictional force for SRO-AW. The presence of saliva had a consistent effect in increasing the friction, which counters the inconsistency reported in the literature. The soft-coated surface of SRO-AW archwire confirms sliding difficulty in sliding on the hard surface of bracket slot. A smoother surface correlates with a lower frictional force according to the surface roughness values.     

Estimating gene signals from noisy microarray images

In oligonucleotide microarray experiments, noise is a challenging problem, as biologists now are studying their organisms not in isolation but in the context of a natural environment. In low photomultiplier tube (PMT) voltage images, weak gene signals and their interactions with the background fluorescence noise are most problematic. In addition, nonspecific sequences bind to array spots intermittently causing inaccurate measurements. Conventional techniques cannot precisely separate the foreground and the background signals. In this paper, we propose analytically based estimation technique. We assume a priori spot-shape information using a circular outer periphery with an elliptical center hole. We assume Gaussian statistics for modeling both the foreground and background signals. The mean of the foreground signal quantifies the weak gene signal corresponding to the spot, and the variance gives the measure of the undesired binding that causes fluctuation in the measurement. We propose a foreground-signal and shape-estimation algorithm using the Gibbs sampling method. We compare our developed algorithm with the existing Mann-Whitney (MW)- and expectation maximization (EM)/iterated conditional modes (ICM)-based methods. Our method outperforms the existing methods with considerably smaller mean-square error (MSE) for all signal-to-noise ratios (SNRs) in computer-generated images and gives better qualitative results in low-SNR real-data images. Our method is computationally relatively slow because of its inherent sampling operation and hence only applicable to very noisy-spot images. In a realistic example using our method, we show that the gene-signal fluctuations on the estimated foreground are better observed for the input noisy images with relatively higher undesired bindings.     

Fluorescence lifetime imaging microscopy using near-infrared contrast agents

Although single-photon fluorescence lifetime imaging microscopy (FLIM) is widely used to image molecular processes using a wide range of excitation wavelengths, the captured emission of this technique is confined to the visible spectrum. Here, we explore the feasibility of utilizing near-infrared (NIR) fluorescent molecular probes with emission >700 nm for FLIM of live cells. The confocal microscope is equipped with a 785 nm laser diode, a red-enhanced photomultiplier tube, and a time-correlated single photon counting card. We demonstrate that our system reports the lifetime distributions of NIR fluorescent dyes, cypate and DTTCI, in cells. In cells labelled separately or jointly with these dyes, NIR FLIM successfully distinguishes their lifetimes, providing a method to sort different cell populations. In addition, lifetime distributions of cells co-incubated with these dyes allow estimate of the dyes' relative concentrations in complex cellular microenvironments. With the heightened interest in fluorescence lifetime-based small animal imaging using NIR fluorophores, this technique further serves as a bridge between in vitro spectroscopic characterization of new fluorophore lifetimes and in vivo tissue imaging.     

Swimming of microbes in entropy optimized nano-bioconvective flow of Prandtl–Erying fluid

Microbes swimming in a fluid that contains nanoparticles is an intriguing characteristic having ramifications in biomedicine, petroleum science, biofuels, and biotechnology applications. This study gives a theoretical evaluation of the bioconvection phenomena with swimming microorganisms in a Prandtl–Erying nanofluid constructed by an exponential stretched surface, given the amazing applications of bioconvection and nanoparticles. Additionally, the problem is modeled by considering intriguing phenomena such as thermophoretic particle deposition, Darcy–Forchheimer medium, exothermic/endothermic process, and activation energy vitality. The leading problem comprises nonlinear, coupled, partial differential expressions. To run the appraisal process, the controlling problem is transfigured into dimensionless patterns through the usual transformations. A computational finite difference approach is used to quantify the numerical evaluation of fabricated flow problems. To obtain the parametric constraints, stability and convergency were also assessed. Improved visualizations (streamlines, isothermal line, iso-concentration, iso-microorganisms) of ongoing flow fields are also illustrated. It is unveiled that the augmentation in velocity ratio factor improves nanofluid velocity and its related boundary layer wideness. The concentration of microbes and nanoparticles is reduced against the bio-Lewis number and Lewis number precisely. The rate of change in heat transfer is the highest for the presence/absence of the thermophoresis factor. Moreover, Entropy production and Bejan number display the reverse impact for the Brinkman number. The change in entropy rate is 30.60% for the presence/absence of microbes' diffusion parameter. This evaluation could help reduce energy waste and improve the performance and efficiency of industrial and engineering appliances like nuclear power plants, and solar energy production.