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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 541 records · Page 30Linked to original sources

bioRxiv2018

An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs)

Multiplexed bioassays, in which multiple analytes of interest are probed in parallel within a single small volume, have greatly accelerated the pace of biological discovery. Bead-based multiplexed bioassays have many technical advantages, including near solution-phase kinetics, small sample volume requirements, many within-assay replicates to reduce measurement error, and, for some bead materials, the ability to synthesize analytes directly on beads via solid-phase synthesis. To allow bead-based multiplexing, analytes can be synthesized on spectrally encoded beads with a 1:1 linkage between analyte identity and embedded codes. Bead-bound analyte libraries can then be pooled and incubated with a fluorescently-labeled macromolecule of interest, allowing downstream quantification of interactions between the macromolecule and all analytes simultaneously via imaging alone. Extracting quantitative binding data from these images poses several computational image processing challenges, requiring the ability to identify all beads in each image, quantify bound fluorescent material associated with each bead, and determine their embedded spectral code to reveal analyte identities. Here, we present a novel open-source Python software package (the mrbles analysis package) that provides the necessary tools to: (1) find encoded beads in a bright-field microscopy image; (2) quantify bound fluorescent material associated with bead perimeters; (3) identify embedded ratiometric spectral codes within beads; and (4) return data aggregated by embedded code and for each individual bead. We demonstrate the utility of this package by applying it towards analyzing data generated via multiplexed measurement of calcineurin protein binding to MRBLEs (Microspheres with Ratiometric Barcode Lanthanide Encoding) containing known and mutant binding peptide motifs. We anticipate that this flexible package should be applicable to a wide variety of assays, including simple bead or droplet finding analysis, quantification of binding to non-encoded beads, and analysis of multiplexed assays that use ratiometric, spectrally encoded beads.

bioengineering↗

bioRxiv2018

Small Data Challenge: Structural Analysis and Optimization of Convolutional Neural Networks with a Small Sample Size

Deep neural networks have gained immense popularity in the Big Data problem; however, the availability of training samples can be relatively limited in certain application domains, particularly medical imaging, and consequently leading to overfitting problems. This \"Small Data\" challenge may need a mindset that is entirely different from the existing Big Data paradigm. Here, under the small data setting, we examined whether the network structure has a substantial influence on the performance and whether the optimal structure is predominantly determined by sample size or data nature. To this end, we listed all possible combinations of layers given an upper bound of the VC-dimension to study how structural hyperparameters affected the performance. Our results showed that structural optimization improved accuracy by 27.99%, 16.44%, and 13.11% over random selection for a sample size of 100, 500, and 1,000 in the MNIST dataset, respectively, suggesting that the importance of the network structure increases as the sample size becomes smaller. Furthermore, the optimal network structure was mostly determined by the data nature (photographic, calligraphic, or medical images), and less affected by the sample size, suggesting that the optimal network structure is data-driven, not sample size driven. After network structure optimization, the conventional convolutional neural network could achieve 91.13% in accuracy with only 500 samples, 93.66% in accuracy with only 1000 samples for the MNIST dataset and 94.10% in accuracy with only 3300 samples for the Mitosis (microscopic) dataset. These results indicate the primary importance of the network structure and the nature of the data in facing the Small Data challenge.

bioengineering↗

bioRxiv2018

Implantable electrical stimulation bioreactor with liquid crystal polymer based electrodes for enhanced bone regeneration at mandibular large defects in rabbit

The osseous regeneration of large bone defects is still a major clinical challenge in maxillofacial and orthopedic surgery. Our previous studies demonstrated that electrical stimulation (ES) with biphasic current pulse showed proliferative effects on bone cells and enhanced secretion of bone-forming growth factors. This study presents an implantable electrical stimulation bioreactor with electrodes based on liquid crystal polymer (LCP), which has excellent bone-binding property. The bioreactor was implanted into a critical sized bone defect and subjected to ES for one week, where bone regeneration was evaluated four weeks after surgery using micro-CT. The effect of ES via bioreactor was compared with a sham control group and positive control group that received recombinant human bone morphogenetic protein (rhBMP)-2 (20 g). New bone volume per tissue volume (BV/TV) in the ES and rhBMP-2 groups increased to 171% (p < 0.001) and 210% (p < 0.001), respectively, compared to that in the sham control group. In the histological evaluation, there was no inflammation within bone defects and adjacent to LCP in all groups. This study showed that the ES bioreactor with LCP electrodes could enhance bone regeneration at large bone defects, where LCP can act as a mechanically resistant outer box without inflammation.

bioengineering↗

bioRxiv2018

Extracellular matrix stiffness regulates force transmission pathways in multicellular ensembles of human airway smooth muscle cells.

For an airway or a blood vessel to narrow, there must be a connected path that links the smooth muscle (SM) cells with each other, and transmits forces around the organ, causing it to constrict. Currently, we know very little about the mechanisms that regulate force transmission pathways in a multicellular SM ensemble. Here, we used extracellular matrix (ECM) micropatterning to study force transmission in a two-cell ensemble of SM cells. Using the two-SM cell ensemble, we demonstrate (a) that ECM stiffness acts as a switch that regulates whether SM force is transmitted through the ECM or through cell-cell connections. (b) Fluorescent imaging for adherens junctions and focal adhesions show the progressive loss of cell-cell borders and the appearance of focal adhesions with the increase in ECM stiffness (confirming our mechanical measurements). (c) At the same ECM stiffness, we show that the presence of a cell-cell border substantially decreases the overall contractility of the SM cell ensemble. Our results demonstrate that connectivity among SM cells is a critical factor to consider in the development of diseases such as asthma and hypertension.

bioengineering↗

bioRxiv2018

A wrappable microwire electrode for awake, chronic interfacing with small diameter autonomic peripheral nerves

Bioelectronic medicine requires the ability to monitor and modulate nerve activity in awake patients over time. The vagus nerve is a promising stimulation target, and preclinical models often use mice. However, an awake, chronic mouse vagus nerve interface has yet to be demonstrated. Here, we developed a functional wrappable microwire electrode to chronically interface with the small diameter mouse cervical vagus nerve ([~]100 m). In an acute setting, the wrappable microwire had similar recording performance to commercially available electrodes. A chronic, awake mouse model was then developed to record spontaneous compound action potentials (CAPs). Viable signal-to-noise ratios (SNRs) were obtained from the wrappable microwires between 30 and 60 days (n = 8). Weekly impedance measurements showed no correlation between SNR or time. The wrappable microwires successfully interfaced with small diameter nerves and has been validated in a chronic, awake preclinical model, which can better facilitate clinical translation for bioelectronic medicine.

bioengineering↗

bioRxiv2018

Construction and Characterization of a Synthetic Baculovirus-inducible 39K Promoter

The low expression activity and specificity of natural promoters limit the applications of genetic engineering. To construct a highly efficient synthetic inducible promoter in the Bombyx mori (Lepidoptera), we analyzed the regulatory elements and functional regions of the B. mori nucleopolyhedrovirus (BmNPV) 39K promoter. The results of truncated mutation analysis of the 39K promoter showed that the transcriptional regulatory region spanning positions -573 to -274 and +1 to +62 is essential for virus-inducible promoter activity. Further investigation using electrophoretic mobility shift assay (EMSA) revealed that the baculovirus IE-1 protein binds to the 39K promoter at the -310 to -355 region, and transcription activates the expression of 39K promoter assay. Finally, we successfully constructed a synthetic inducible promoter that increase the virus-inducing activity of other promoters using the baculovirus-inducible transcriptional activation region that binds to specific core elements of 39K (i.e., spanning the region -310 to -355). In summary, we describes a novel, synthetic, and highly efficient biological tool, namely, a virus-inducible 39K promoter, which provides endless possibilities for future gene function research, gene therapy, and pest control in genetic engineering.

bioengineering↗

bioRxiv2018

Silk assembly integrates cells into a 3D fibrillar network that promotes cell spreading and proliferation

Tissues are built of cells integrated in an extracellular matrix (ECM) which provides a three-dimensional (3D) fibrillar network with specific sites for cell anchorage. By genetic engineering, motifs from the ECM can be functionally fused to recombinant silk proteins. Such a silk protein, FN-silk, which harbours a motif from fibronectin, has the ability to self-assemble into fibrillar networks under physiological-like conditions. Herein we describe a method by which mammalian cells are added to the silk solution before assembly, and thereby get uniformly integrated between the formed fibrils. In the resulting 3D scaffold, the cells proliferate and spread out with tissue-like morphology. Elongated cells containing filamentous actin and defined focal adhesion points confirm proper cell attachment to the FN-silk. The cells remain viable in culture for at least 90 days. The method is also scalable to macro-sized 3D cultures. Silk fibers with integrated cells are both strong and extendable, with mechanical properties similar to that of artery walls. The described method enables both differentiation of stem- or precursor cells in 3D and facile co-culture of several different cell types. We show that inclusion of endothelial cells leads to the formation of vessel-like structures throughout the tissue constructs. Hence, silk-assembly in presence of cells constitutes a viable option for 3D culture of cells integrated in a fibrillary ECM-like network, with potential as base for engineering of functional tissue.

bioengineering↗

bioRxiv2018

Effect of methylene blue on the formation of oxidized phospholipid vesicles

Soybean phosphatidylcholine, which is rich in linoleic acid, was oxidized with singlet oxygen through photosensitization with methylene blue. This compound facilitates the oxidation of phospholipids relative to the reaction with free unsaturated fatty acids. A response surface methodology was used to control oxidation, with methylene blue concentration and the amount of available air as independent variables. The conjugated diene-to triene ratio was then monitored. Hydroperoxide yield dependent principally on the amount of air, whereas photosensitizer concentration strongly influenced the size and zeta potential of vesicles formed by the sonication of oxidized phospholipids in water. Methylene blue plays an important role in the surface charge expression and ion permeability of these vesicles.

bioengineering↗

bioRxiv2018

Optimization of swelling response of pH sensitive hydrogels using Box-Behnken design

Hydrogels are three-dimensional crosslinked hydrophilic polymer networks capable of swelling or de-swelling reversibly in water and retaining a large volume of liquid in swollen state. Hydrogels can be designed with controllable responses to shrink or expand with changes in external environmental conditions. Among stimulisensitive hydrogels, the pH-sensitive ones are widely-studied and used. Despite these advances, we currently lack a systematic way to optimize the synthesis protocols. Here we propose to use techniques from chemometrics, namely Box-Behnken statistical screening design to optimize the chemical composition of pH-responsive hydrogels for an improved responsiveness as quantified by swelling index. Polymer blends were prepared by mixing different suitable volume of pvp (poly vinyl pyrrolidone) and chitosan aqueous solution in order to obtain a mixture, glutardialdehyde solution was added as crosslinkers to the chitosan/pvp mixture to form semi-IPN(semi-interpenetrating polymeric hydrogel). The pH-dependent swelling properties have been measured and used to obtain a regression model. We characterized the descriptive and predictive abilities of our model. We found a remarkable correlation (correlation coefficient = 0.954) between the observed responses and the responses predicted by the model. Our results demonstrate that Box-Behnken is an appropriate statistical design that can be successfully used in the development of pH-sensitive hydrogels with a predictable swelling ratio. This technology will remarkably reduce the time and cost that is needed for chemical synthesis of hydrogels with a desired pH-sensitivity.

bioengineering↗

bioRxiv2018

Compressive strengths of PEG gels with glycerol and bioglass particles

Poly(ethylene glycol) (PEG)-based materials can potentially be used as biomechanical matrices for regenerative medicine implants including the replacement of intervertebral (IV) discs. Glycerol and other plasticizers (low-MW PEG, propylene glycol, and sorbitol) were added to the bulk PEG matrix, gelled using chemical and photochemical methods at different temperature and pressure settings, and compression properties acquired and analyzed. Incorporation of surface bioactive glass particles shortened the blood clotting time, while alginate and laponite additives improved the gels mechanical properties to 645 kPa compressive modulus, 12% yield strain, and 79 kPa yield strength. This IV disc-modeled system endured the cyclic loading and unloading test indicative of an elastic response; but required improvement of its biomechanical tolerance.

bioengineering↗

bioRxiv2018

Aperture Phase Modulation with Adaptive Optics: A Novel Approach for Speckle Reduction and Structure Extraction in Optical Coherence Tomography

AbstractSpeckle is an inevitable consequence of the use of coherent light in optical coherence tomography (OCT), and often acts as noise that obscures micro-structures of biological tissue. We here present a novel method of suppressing speckle noise intrinsically compatible with adaptive optics (AO) in OCT system: by modulating the phase inside the imaging system pupil aperture with a segmented deformable mirror, thus producing minor perturbations in the point spread function (PSF) to create un-correlated speckle pattern between B-scans, and further averaging to wash out the speckle but maintain the structures. It is a well-controlled and universal method which can efficiently determine the optimal range of phase modulation that minimizing speckle noise while maximizing image resolution and signal strength for different systems and/or samples. As an active method, its effectiveness and efficiency were demonstrated by both ex-vivo non-biological and in-vivo biological applications.

bioengineering↗

bioRxiv2018

The influence of cyclic tensile strain on multi-compartment collagen-GAG scaffolds for tendon-bone junction regeneration

Orthopedic injuries often occur at the interface between soft tissues and bone. The tendon-bone junction (TBJ) is a classic example of such an interface. Current clinical strategies for TBJ injuries prioritize mechanical reattachment over regeneration of the native interface, resulting in poor outcomes. The need to promote regenerative healing of spatially-graded tissues inspires our effort to develop new tissue engineering technologies that replicate features of the spatially-graded extracellular matrix and strain profiles across the native TBJ. We recently described a biphasic collagen-glycosaminoglycan (CG) scaffold containing distinct compartment with divergent mineral content and structural alignment (isotropic vs. anisotropic) linked by a continuous interface zone to mimic structural and compositional features of the native TBJ. Here, we report application of physiologically relevant levels of cyclic tensile strain (CTS) to the scaffold via a bioreactor leads to non-uniform strain profiles across the spatially-graded scaffold. Further, combinations of CTS and matrix structural features promote rapid, spatially-distinct differentiation profiles of human bone marrow-derived mesenchymal stem cells (MSCs) down multiple osteotendinous lineages. CTS preferentially upregulates MSC activity and tenogenic differentiation in the anisotropic region of the scaffold. Further, there are no negative effects of CTS on MSC osteogenic potential in the mineralized region previously shown to promote robust bone regeneration. Together, this work demonstrates a tissue engineering approach that couples instructive biomaterials with physiological stimuli as a mean to promote regenerative healing of orthopedic interfaces.

bioengineering↗

bioRxiv2018

Frame Rate Up-Conversion in Echocardiography Images, Using Manifold-Learning and Image Registration

In this paper, we propose a new temporal frame interpolation algorithm for frame rate up-conversion (FRUC) in echocardiography images. This algorithm employs a combination of dimension reduction techniques and image registration to increase frame rate.\n\nIf the distance between two successive frames of a video be great, motion jerkiness will appear between them and visual quality of the video will decrease. Some parts of heart have a very high speed motion, and echocardiography videos, obtained by available systems cant take enough number of frames to show them well. So, to achieve an echocardiography image set with a better visual quality, more frames are necessary between two frames at a great distance. Here, we use dimension reduction techniques to find out the number of suitable frames between two consecutive frames to show the fast motions better, but dont take much time. We project images to a 3-dimentional space by this way. Greater difference between the frames, results greater distance between corresponding embedded points. Thus, the distance between the embedded points is a scale for the suitable number of frames, needed between two successive frames. These frames are produced with the registration techniques.\n\nOn the other hand, heart doesnt have a constant speed during a cycle, but echocardiography images are recorded with constant speed. So, frames at a greater distance show fast motions of the heart, and frames at a lower distance show slow motions of the heart. While, we put unequal number of frames between successive frames, and in this way remove temporal coordination of the image set. To solve this problem, we put efficient number of linear average of available frames, in places that the number of inserted frames in between available frames is less than maximum to obtain an equal number of frames between all successive frames.

bioengineering↗

bioRxiv2018

Studying 3D cell cultures in a microfluidic droplet array under multiple time-resolved conditions

The relevance of traditional cell cultures to cellular behavior in vivo is limited, since the two-dimensional (2D) format does not appropriately reproduce the microenvironment that regulates cell functions. In this context, spheroids are an appealing 3D cell culture format to complement standard techniques, by combining a high level of biological relevance with simple production protocols. However the methods for spheroid manipulation are still labor intensive, which severely limits the complexity of operations that can be performed on statistically relevant numbers of individual spheroids. Here we show how to apply hundreds of different conditions on spheroids in a single microfluidic chip, where each spheroid is produced and immobilized in an anchored droplet. By using asymmetric anchor shapes, a second drop can be merged with the spheroid-containing drop at a later time. This time-delayed merging uniquely enables two classes of applications that we demonstrate: (1) the initiation of cell-cell interactions on demand, either for building micro-tissues within the device or for observing antagonistic cell-cell interactions with applications in immuno-therapy or host-pathogen interactions, (2) a detailed dose-response curve obtained by exposing an array of hepatocyte-like spheroids to droplets containing a wide range of acetaminophen concentrations. The integrated microfluidic format allows time-resolved measurements of the response of hundreds of spheroids with a single-cell resolution. The data shows an internally regulated evolution of each spheroid, in addition to a heterogeneity of the responses to the drug that the single-cell analysis correlates with the initial presence and location of dead cells within each spheroid.

bioengineering↗

bioRxiv2018

Versatile Multi-Detector Scheme for Adaptive Optics Scanning Laser Ophthalmoscopy

Adaptive Optics Scanning Laser Ophthalmoscopy (AOSLO) is a powerful tool for imaging the retina at high spatial and temporal resolution. In this paper, we present a multi-detector scheme for AOSLO which has two main configurations: pixel reassignment and offset aperture imaging. In this detection scheme, the single element detector of the standard AOSLO is replaced by a fiber bundle which couples the detected light into multiple detectors. The pixel reassignment configuration allows for more light throughput while maintaining optimal confocal resolution. The increase in signal-to-noise ratio (SNR) from this configuration can improve the accuracy of motion registration techniques. The offset aperture imaging configuration enhances the detection of multiply scattered light, which improves the contrast of retinal vasculature and inner retinal layers similar to methods such as nonconfocal split-detector imaging and multi-offset aperture imaging.

bioengineering↗

bioRxiv2018

Optimal diameter reduction ratio of acinar airways in human lungs

In the airway network of a human lung, the airway diameter gradually decreases through multiple branching. The diameter reduction ratio of the conducting airways that transport gases without gas exchange is 0.79, but this reduction ratio changes to 0.94 in acinar airways beyond transitional bronchioles. While the reduction in the conducting airways was previously rationalized on the basis of Murrays law, our understanding of the design principle behind the acinar airways has been far from clear. Here we elucidate that the change in gas transfer mode is responsible for the transition in the diameter reduction ratio. The oxygen transfer rate per unit surface area is maximized at the observed geometry of acinar airways, which suggests the minimum cost for the construction and maintenance of the acinar airways. The results revitalize and extend the framework of Murrays law over an entire human lung.

bioengineering↗

bioRxiv2018

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures, A Machine Learning Approach

BackgroundBalance impairment affects over 75% of individuals with multiple sclerosis (MS), and leads to an increased risk of falling. Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guidelines concerning the most appropriate postural sway metrics to monitor impairment. This investigation implemented a machine learning approach to assess the accuracy and feature importance of various postural sway metrics to differentiate individuals with MS from healthy controls as a function of physiological fall risk.\n\nMethodsThis secondary data analysis included 153 participants (50 controls and 103 individuals with MS) who underwent posturography based balance assessment (30s eyes open standing on a force platform) and physiological fall risk assessment (Physiological Profile Assessment - PPA). Participants were further classified into four subgroups based on fall risk: controls (n=50, 64.9 {+/-} 4.9 years old, PPA < 1); low-risk MS (n=34, 54.0 {+/-} 13.1 years old, PPA < 1); moderate-risk MS (n=27, 58.3 {+/-} 8.3 years old, 1 [≤] PPA < 2); high-risk MS (n=42, 56.8 {+/-} 9.7 years old, PPA [≥] 2). Twenty common sway metrics were derived following standard procedures, and subsequently used to train a machine learning algorithm (random forest - RF, with 10-fold cross validation) to predict individuals fall risk grouping. The feature importance from the RF algorithms was used to select the strongest sway metric for fall risk prediction.\n\nResults and DiscussionThe sway-metric based RF classifier had high classification accuracy in discriminating controls from MS individuals (> 86%). Sway sample entropy, a sway regularity metric, was identified as the strongest feature for classification of low-risk MS individuals from healthy controls. Whereas for all other comparisons, mediolateral sway amplitude was identified as the strongest predictor for fall risk groupings. These findings may set the foundation for the development of guidelines for reporting balance impairment in individuals with MS.

bioengineering↗

bioRxiv2018

Comparative Performance of the Finite Element Method and the Boundary Element Fast Multipole Method for a Test Problem Mimicking Transcranial Magnetic Stimulation (TMS)

A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics. We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2.1.1 environment. In the second case, a high-end commercial FEM software package ANSYS Maxwell 3D is used. The BEM-FMM method runs in the MATLAB(R) 2018a environment.\n\nIn the first case, we observe that the BEM-FMM algorithm gives a smaller solution error for all mesh resolutions and runs significantly faster for high-resolution meshes when the number of triangular facets exceeds approximately 0.25 M. We present other relevant simulation results such as volumetric mesh generation times for the FEM, time necessary to compute the potential integrals for the BEM-FMM, and solution performance metrics for different hardware/operating system combinations. In the second case, we observe an excellent agreement for electric field distribution across different cranium compartments and, at the same time, a speed improvement of three orders of magnitude when the BEM-FMM algorithm used.\n\nThis study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.

bioengineering↗