Kinetics of binding and geometry of cells on molecular biochips

We examine how the shape of cells and the geometry of experiment affect the reaction-diffusion kinetics at the binding between target and probe molecules on molecular biochips. In particular, we compare the binding kinetics for the probes immobilized on surface of the semispherical and flat circular cells, the limit of thin slab of analyte solution over probe cell as well as hemispherical gel pads and cells printed in gel slab over a substrate. It is shown that hemispherical geometry provides significantly faster binding kinetics and ensures more spatially homogeneous distribution of local (from a pixel) signals over a cell in the transient regime. The advantage of using thin slabs with small volume of analyte solution may be hampered by the much longer binding kinetics needing the auxiliary mixing devices. Our analysis proves that the shape of cells and the geometry of experiment should be included to the list of essential factors at biochip designing.Comment: 10 pages, 1 figur

Abnormally high risk of stroke in Brugada syndrome

BACKGROUND The present study sought to evaluate the incidence of cerebrovascular events in a large cohort of patients with Brugada syndrome (BrS) analysing possible predictors, clinical characteristics and prognosis of cardioembolic events secondary to atrial fibrillation. METHODS A total of 671 consecutive patients (age 42.1 ± 17.0 years; men 63%) with a diagnosis of BrS were retrospectively analysed over a mean follow-up period of 10.8 ± 5.5 years. The diagnosis of ischemic stroke was made according to the AHA/ASA guidelines using computed tomography (CT) and angio-CT in the emergency department. RESULTS Among 671 patients with BrS, 79 (11.8%) had atrial fibrillation. The incidence of cardioembolic stroke in patients with BrS and atrial fibrillation was 13.9% (11 events). These patients had a low CHA2DS2Vasc score (82%, 0 and 1). Patients with transient ischemic attack/stroke were more frequently asymptomatic (91 vs. 25%; P < 0.0001) and older (59.4 ± 11.2 vs. 43.9 ± 16.7; P = 0.004) as compared with those without cerebrovascular events. CONCLUSION The incidence of cardioembolic stroke in patients with BrS and atrial fibrillation was unexpectedly high. The cerebrovascular accidents were often the presenting clinical manifestation and were significantly associated with asymptomatic atrial fibrillation and older age. CHADS2 and CHA2DS2Vasc scores did not predict the unexpectedly high risk of thromboembolic events in this group of patients. The use of more invasive diagnostic tools might be useful in order to increase the rate of atrial fibrillation detection

Segmentation and intensity estimation for microarray images with saturated pixels

<p>Abstract</p> <p>Background</p> <p>Microarray image analysis processes scanned digital images of hybridized arrays to produce the input spot-level data for downstream analysis, so it can have a potentially large impact on those and subsequent analysis. Signal saturation is an optical effect that occurs when some pixel values for highly expressed genes or peptides exceed the upper detection threshold of the scanner software (2¹⁶- 1 = 65, 535 for 16-bit images). In practice, spots with a sizable number of saturated pixels are often flagged and discarded. Alternatively, the saturated values are used without adjustments for estimating spot intensities. The resulting expression data tend to be biased downwards and can distort high-level analysis that relies on these data. Hence, it is crucial to effectively correct for signal saturation.</p> <p>Results</p> <p>We developed a flexible mixture model-based segmentation and spot intensity estimation procedure that accounts for saturated pixels by incorporating a censored component in the mixture model. As demonstrated with biological data and simulation, our method extends the dynamic range of expression data beyond the saturation threshold and is effective in correcting saturation-induced bias when the lost information is not tremendous. We further illustrate the impact of image processing on downstream classification, showing that the proposed method can increase diagnostic accuracy using data from a lymphoma cancer diagnosis study.</p> <p>Conclusions</p> <p>The presented method adjusts for signal saturation at the segmentation stage that identifies a pixel as part of the foreground, background or other. The cluster membership of a pixel can be altered versus treating saturated values as truly observed. Thus, the resulting spot intensity estimates may be more accurate than those obtained from existing methods that correct for saturation based on already segmented data. As a model-based segmentation method, our procedure is able to identify inner holes, fuzzy edges and blank spots that are common in microarray images. The approach is independent of microarray platform and applicable to both single- and dual-channel microarrays.</p

Characterization and simulation of cDNA microarray spots using a novel mathematical model

<p>Abstract</p> <p>Background</p> <p>The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images.</p> <p>Results</p> <p>We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated.</p> <p>Conclusion</p> <p>This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications involving cDNA microarrays.</p

Nanomaterial-Assisted Signal Enhancement of Hybridization for DNA Biosensors: A Review

Detection of DNA sequences has received broad attention due to its potential applications in a variety of fields. As sensitivity of DNA biosensors is determined by signal variation of hybridization events, the signal enhancement is of great significance for improving the sensitivity in DNA detection, which still remains a great challenge. Nanomaterials, which possess some unique chemical and physical properties caused by nanoscale effects, provide a new opportunity for developing novel nanomaterial-based signal-enhancers for DNA biosensors. In this review, recent progress concerning this field, including some newly-developed signal enhancement approaches using quantum-dots, carbon nanotubes and their composites reported by our group and other researchers are comprehensively summarized. Reports on signal enhancement of DNA biosensors by non-nanomaterials, such as enzymes and polymer reagents, are also reviewed for comparison. Furthermore, the prospects for developing DNA biosensors using nanomaterials as signal-enhancers in future are also indicated

Synergism between particle-based multiplexing and microfluidics technologies may bring diagnostics closer to the patient

In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick high-throughput assays. On the one hand, recent progress in microfluidics technologies is expected to strongly support the development of miniaturized analytical devices, which will speed up (bio)analytical assays. On the other hand, a higher throughput can be obtained by the simultaneous screening of one sample for multiple targets (multiplexing) by means of encoded particle-based assays. Multiplexing at the macro level is now common in research labs and is expected to become part of clinical diagnostics. This review aims to debate on the “added value” we can expect from (bio)analysis with particles in microfluidic devices. Technologies to (a) decode, (b) analyze, and (c) manipulate the particles are described. Special emphasis is placed on the challenges of integrating currently existing detection platforms for encoded microparticles into microdevices and on promising microtechnologies that could be used to down-scale the detection units in order to obtain compact miniaturized particle-based multiplexing platforms

The quest for the ideal dew retting promoting micro-organism

Dew retting of hemp stems lying on the field is a spontaneous microbiological process in which pectin and hemicellulose are degraded in order to release the cellulose bast fibers from its stem. The process is weather dependent and strongly affects the desired fiber quality needed for textile applications. Adding specific bacteria or consortia on the stems during retting might achieve a more controlled process. We set out to isolate, characterize and identify the ideal retting micro-organism, which will degrade hemicellulose and pectin without degrading cellulose, of which the hemp fiber is made. In 2021 samples of both hemp stems and underlying soil were taken from field trials in Bottelare, Belgium. Bacteria were isolated using the dilution to extinction method and identified through 16s rRNA gene sequencing. After identification, the bacteria were screened for their ability to degrade pectin, hemicellulose and cellulose. In total 57 bacteria were successfully isolated and identified. These bacteria belonged to 4 main phyla; 29% Actinobacteria, 27% Bacteroidota, 12% Firmicutes and 32% Proteobacteria. After screening for degradation of the plant biopolymers, six isolates with the right characteristics were found, namely the potential of degrading hemicellulose and pectin without degrading cellulose, belonging to the genera Clavibacter, Microbacterium, Rhodococcus, Flavobacterium, Pedobacter and Luteimonas sp. These isolates are being screened further through in-vitro mini-rettingexperiments to assess the extent to which they are able to release the fibres without damaging them