Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Introducing polymer conductance in diagnostically relevant transduction.

ABSTRACT: In this work we demonstrate that an impedance derived capacitance method is able to cleanly resolve the resonant conductance characteristics of an electrode-confined polymer film. In decorating the film with receptors, this conductance is thereafter modulated by the capturing of specific targets, demonstrated herein with C-reactive protein. This entirely reagentless and single step marker quantification is relevant to the drive of moving assays to a scaleable format requiring minimal user intervention.

SUBMITTER: Baradoke A

PROVIDER: S-EPMC7581358 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Introducing polymer conductance in diagnostically relevant transduction.

Baradoke Ausra A Santos Adriano A Bueno Paulo R PR Davis Jason J JJ

Biosensors & bioelectronics 20201022

In this work we demonstrate that an impedance derived capacitance method is able to cleanly resolve the resonant conductance characteristics of an electrode-confined polymer film. In decorating the film with receptors, this conductance is thereafter modulated by the capturing of specific targets, demonstrated herein with C-reactive protein. This entirely reagentless and single step marker quantification is relevant to the drive of moving assays to a scaleable format requiring minimal user interv ...[more]

PMID: 33166803

Similar Datasets

Diagnostically relevant facial gestalt information from ordinary photos.

Project description:Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

| S-EPMC4067075 | biostudies-literature

Forgotten features of head zones and their relation to diagnostically relevant acupuncture points.

Project description:In the 1890s Sir Henry Head discovered certain areas of the skin that develop tenderness (allodynia) in the course of visceral disease. These areas were later termed "Head zones". In addition, he also emphasized the existence of specific points within these zones, that he called "maximum points", a finding that seems to be almost forgotten today. We hypothesized that two important groups of acupuncture points, the diagnostically relevant Mu and Shu points, spatially and functionally coincide with these maximum points to a large extent. A comparison of Head's papers with the Huang Di Neijing (Yellow Thearch's Inner Classic) and the Zhen Jiu Jia Yi Jing (Systematic Classic of Acupuncture and Moxibustion), two of the oldest still extant Chinese sources on acupuncture, revealed astonishing parallels between the two concepts regarding both point locations and functional aspects. These findings suggest that the Chinese discovery of viscerocutaneous reflexes preceded the discovery in the West by more than 2000 years. Furthermore, the fact that Chinese medicine uses Mu and Shu points not only diagnostically but also therapeutically may give us new insights into the underlying mechanisms of acupuncture.

| S-EPMC3135114 | biostudies-literature

A BERT model generates diagnostically relevant semantic embeddings from pathology synopses with active learning.

Project description:BackgroundPathology synopses consist of semi-structured or unstructured text summarizing visual information by observing human tissue. Experts write and interpret these synopses with high domain-specific knowledge to extract tissue semantics and formulate a diagnosis in the context of ancillary testing and clinical information. The limited number of specialists available to interpret pathology synopses restricts the utility of the inherent information. Deep learning offers a tool for information extraction and automatic feature generation from complex datasets.MethodsUsing an active learning approach, we developed a set of semantic labels for bone marrow aspirate pathology synopses. We then trained a transformer-based deep-learning model to map these synopses to one or more semantic labels, and extracted learned embeddings (i.e., meaningful attributes) from the model's hidden layer.ResultsHere we demonstrate that with a small amount of training data, a transformer-based natural language model can extract embeddings from pathology synopses that capture diagnostically relevant information. On average, these embeddings can be used to generate semantic labels mapping patients to probable diagnostic groups with a micro-average F1 score of 0.779 Â ± 0.025.ConclusionsWe provide a generalizable deep learning model and approach to unlock the semantic information inherent in pathology synopses toward improved diagnostics, biodiscovery and AI-assisted computational pathology.

| S-EPMC9053264 | biostudies-literature

Nanodisco balls: control over surface versus core loading of diagnostically active nanocrystals into polymer nanoparticles.

Project description:Nanoparticles of complex architectures can have unique properties. Self-assembly of spherical nanocrystals is a high yielding route to such systems. In this study, we report the self-assembly of a polymer and nanocrystals into aggregates, where the location of the nanocrystals can be controlled to be either at the surface or in the core. These nanospheres, when surface decorated with nanocrystals, resemble disco balls, thus the term nanodisco balls. We studied the mechanism of this surface loading phenomenon and found it to be Ca(2+) dependent. We also investigated whether excess phospholipids could prevent nanocrystal adherence. We found surface loading to occur with a variety of nanocrystal types including iron oxide nanoparticles, quantum dots, and nanophosphors, as well as sizes (10-30 nm) and shapes. Additionally, surface loading occurred over a range of polymer molecular weights (∼30-3000 kDa) and phospholipid carbon tail length. We also show that nanocrystals remain diagnostically active after loading onto the polymer nanospheres, i.e., providing contrast in the case of magnetic resonance imaging for iron oxide nanoparticles and fluorescence for quantum dots. Last, we demonstrated that a fluorescently labeled protein model drug can be delivered by surface loaded nanospheres. We present a platform for contrast media delivery, with the unusual feature that the payload can be controllably localized to the core or the surface.

| S-EPMC4174093 | biostudies-literature

Foreground Detection Analysis of Ultrasound Image Sequences Identifies Markers of Motor Neurone Disease across Diagnostically Relevant Skeletal Muscles.

Project description:Diagnosis of motor neurone disease (MND) includes detection of small, involuntary muscle excitations, termed fasciculations. There is need to improve diagnosis and monitoring of MND through provision of objective markers of change. Fasciculations are visible in ultrasound image sequences. However, few approaches that objectively measure their occurrence have been proposed; their performance has been evaluated in only a few muscles; and their agreement with the clinical gold standard for fasciculation detection, intramuscular electromyography, has not been tested. We present a new application of adaptive foreground detection using a Gaussian mixture model (GMM), evaluating its accuracy across five skeletal muscles in healthy and MND-affected participants. The GMM provided good to excellent accuracy with the electromyography ground truth (80.17%-92.01%) and was robust to different ultrasound probe orientations. The GMM provides objective measurement of fasciculations in each of the body segments necessary for MND diagnosis and hence could provide a new, clinically relevant disease marker.

| S-EPMC6481588 | biostudies-literature

Disease-relevant proteostasis regulation of cystic fibrosis transmembrane conductance regulator.

Project description:Mismanaged protein trafficking by the proteostasis network contributes to several conformational diseases, including cystic fibrosis, the most frequent lethal inherited disease in Caucasians. Proteostasis regulators, as cystamine, enable the beneficial action of cystic fibrosis transmembrane conductance regulator (CFTR) potentiators in ?F508-CFTR airways beyond drug washout. Here we tested the hypothesis that functional CFTR protein can sustain its own plasma membrane (PM) stability. Depletion or inhibition of wild-type CFTR present in bronchial epithelial cells reduced the availability of the small GTPase Rab5 by causing Rab5 sequestration within the detergent-insoluble protein fraction together with its accumulation in aggresomes. CFTR depletion decreased the recruitment of the Rab5 effector early endosome antigen 1 to endosomes, thus reducing the local generation of phosphatidylinositol-3-phosphate. This diverts recycling of surface proteins, including transferrin receptor and CFTR itself. Inhibiting CFTR function also resulted in its ubiquitination and interaction with SQSTM1/p62 at the PM, favoring its disposal. Addition of cystamine prevented the recycling defect of CFTR by enhancing BECN1 expression and reducing SQSTM1 accumulation. Our results unravel an unexpected link between CFTR protein and function, the latter regulating the levels of CFTR surface expression in a positive feed-forward loop, and highlight CFTR as a pivot of proteostasis in bronchial epithelial cells.

| S-EPMC3705602 | biostudies-literature

Light-induced Conductance Switching in Photomechanically Active Carbon Nanotube-Polymer Composites.

Project description:Novel, optically responsive devices with a host of potential applications have been demonstrated by coupling carbon nanomaterials with photochromic molecules. For light-induced conductance switching in particular, we have recently shown that carbon nanotube-polymer nanocomposites containing azobenzene are very attractive and provide stable and non-degradable changes in conductivity over time at standard laboratory conditions. In these composites, the photoswitching mechanisms are based on light-induced changes in electronic properties and related to the Pool-Frenkel conduction mechanism. However, no link between conductivity switching and the molecular motion of azobenzene chromophores could be found due to application of high elastic modulus polymer matrices. Here we report on single wall carbon nanotube-polymer nanocomposites with a soft polycaprolactone polymer host. Such a system clearly shows the transfer of light-induced, nano-sized molecular motion to macroscopic thickness changes of the composite matrix. We demonstrate that these photomechanical effects can indeed overshadow the electronic effects in conductivity switching behavior and lead to a reversion of the conductivity switching direction near the percolation threshold.

| S-EPMC5575261 | biostudies-literature

Long- and Short-Term Conductance Control of Artificial Polymer Wire Synapses.

Project description:Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources. A possible solution to this issue is the development of processing circuits that physically resemble an artificial brain, which can offer low-energy loss and high-speed processing. This study demonstrated the synaptic functions of conductive polymer wires linking arbitrary electrodes in solution. By controlling the conductance of the wires, synaptic functions such as long-term potentiation and short-term plasticity were achieved, which are similar to the manner in which a synapse changes the strength of its connections. This novel organic artificial synapse can be used to construct information-processing circuits by wiring from scratch and learning efficiently in response to external stimuli.

| S-EPMC7835966 | biostudies-literature

Energy storage in structural composites by introducing CNT fiber/polymer electrolyte interleaves.

Project description:This work presents a method to produce structural composites capable of energy storage. They are produced by integrating thin sandwich structures of CNT fiber veils and an ionic liquid-based polymer electrolyte between carbon fiber plies, followed by infusion and curing of an epoxy resin. The resulting structure behaves simultaneously as an electric double-layer capacitor and a structural composite, with flexural modulus of 60 GPa and flexural strength of 153 MPa, combined with 88 mF/g of specific capacitance and the highest power (30 W/kg) and energy (37.5 mWh/kg) densities reported so far for structural supercapacitors. In-situ electrochemical measurements during 4-point bending show that electrochemical performance is retained up to fracture, with minor changes in equivalent series resistance for interleaves under compressive stress. En route to improving interlaminar properties we produce grid-shaped interleaves that enable mechanical interconnection of plies by the stiff epoxy. Synchrotron 3D X-ray tomography analysis of the resulting hierarchical structure confirms the formation of interlaminar epoxy joints. The manuscript discusses encapsulation role of epoxy, demonstrated by charge-discharge measurements of composites immersed in water, a deleterious agent for ionic liquids. Finally, we show different architectures free of current collector and electrical insulators, in which both CNT fiber and CF act as active electrodes.

| S-EPMC5821880 | biostudies-literature

Clinical Resistome Screening of 1,110 <i>Escherichia coli</i> Isolates Efficiently Recovers Diagnostically Relevant Antibiotic Resistance Biomarkers and Potential Novel Resistance Mechanisms.

Project description:Multidrug-resistant pathogens represent one of the biggest global healthcare challenges. Molecular diagnostics can guide effective antibiotics therapy but relies on validated, predictive biomarkers. Here we present a novel, universally applicable workflow for rapid identification of antimicrobial resistance (AMR) biomarkers from clinical Escherichia coli isolates and quantitatively evaluate the potential to recover causal biomarkers for observed resistance phenotypes. For this, a metagenomic plasmid library from 1,110 clinical E. coli isolates was created and used for high-throughput screening to identify biomarker candidates against Tobramycin (TOB), Ciprofloxacin (CIP), and Trimethoprim-Sulfamethoxazole (TMP-SMX). Identified candidates were further validated in vitro and also evaluated in silico for their diagnostic performance based on matched genotype-phenotype data. AMR biomarkers recovered by the metagenomics screening approach mechanistically explained 77% of observed resistance phenotypes for Tobramycin, 76% for Trimethoprim-Sulfamethoxazole, and 20% Ciprofloxacin. Sensitivity for Ciprofloxacin resistance detection could be improved to 97% by complementing results with AMR biomarkers that are undiscoverable due to intrinsic limitations of the workflow. Additionally, when combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached promising positive and negative predictive values of up to 97 and 99%, respectively. Finally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms.

| S-EPMC6700387 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data