bioRxiv Science⌕ Search

bioRxiv · 10.1101/162438

Paper based microfluidic aptasensor for food safety

Abstract

Food analysis is requiring rapid, accurate, sensitive and cost-effective methods to monitor and guarantee the safety and quality to fulfill the strict food legislation and consumer demands. In our study, a nano-materials enhanced multipurpose paper based microfluidic aptasensor was demonstrated as a sensing tool for accurate detection of food allergens and food toxins. Graphene oxide (GO) and specific aptamer-functionalized quantum dots (QDs) were employed as probes, the fluorescence quenching and recovering of the QDs caused by the interaction among GO, aptamer-functionalized QDs and the target protein were investigated to quantitatively analyze the target concentration. The homogenous assay was performed on the paper based microfluidic chip, which significantly decreased the sample and reagent consumptions and reduced the assay time. Egg white lysozyme, {beta}-conglutin lupine and food toxins, okadaic acid and brevetoxin standard solutions and spiked food samples were successfully assayed by the presented aptasensor. Dual-target assay was completed within 5 min, and superior sensitivities were achieved when testing the samples with commercial ELISA kits side by side.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Weng, X., Neethirajan, S.. 2017-07-12. Paper based microfluidic aptasensor for food safety. https://doi.org/10.1101/162438

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

N-GLYcanyzer monitoring of a microperfusion process reveals critical parameters' impact on Trastuzumab biosimilar N-glycoform time evolution

Controlling monoclonal antibody (mAb) N-glycosylation as a critical quality attribute (CQA) remains challenging in continuous and intensified biomanufacturing, where conventional end-point analyses obscure dynamic pathway responses. Here, we deployed the N-GLYcanyzer process analytical technology (PAT) for automated monitoring of a microperfusion process that reveals critical parameters' impact on Trastuzumab biosimilar N-glycoform time evolution across a 20-day culture duration of Chinese Hamster Ovary (CHO) cells in a ~2 mL scale-down microbioreactor perfusion platform. Using offline PAT assays combined with our integrated at-line PAT workflow, we systematically screened six perfusion process parameters: carbon source, viable cell density (VCD), perfusion rate, temperature, and pH. While nutrient limitation and thermal/acidic stress significantly disrupted N-glycans maturation, notably triggering high-mannose (Man5) accumulation and severe productivity penalties under pH 6.7 and 39 {degrees}C operation, targeted feed supplementation with galactose and MnCl2 consistently shifted glycoform profiles away from G0F toward galactosylated species (G1F, G1F', G2F). Crucially, coupling this combined feed strategy with an intensified perfusion rate (1.2 VVD) achieved a sustained, desired galactosylation shift without a productivity cost. These findings demonstrate that nutrient feed composition and perfusion rate are primary levers for steering continuous intensified microperfusion processes for biologics production with desired N-glycoform states and highlight the utility of automated at-line PAT like N-GLYcanyzer for enabling real-time attribute-based control in continuous biomanufacturing.

bioengineering↗

Differential sensing with imprinted and non-imprinted organic electrochemical transistors reduces calibration drift in wearable sweat cortisol sensors

The output of a wearable cortisol sensor drifts over days for reasons unrelated to cortisol, so a calibration made on the first day soon stops being valid. In our differential organic electrochemical transistor, a PEDOT:PSS transistor coated with a molecularly imprinted polymer (MIP) for cortisol is paired with one coated with a non-imprinted polymer (NIP) of the same composition, and the NIP response is subtracted. Over four calibrations in artificial sweat across 14 days, the response of the MIP alone shifted by 15% to 22% of its range on day 1, whereas the differential output shifted by 1% to 10%, and the variation between days at 1 to 10nM fell by 65% to 70% on average for individual pairs. In sweat from one participant, read against the calibration from day 1, both outputs tracked the direction of visible changes in salivary cortisol, while the MIP alone diverged from the differential output, consistent with the laboratory drift.

bioengineering↗

A cytotoxicity dataset for data-driven design of ionizable lipid nanoparticles

Ionizable lipid nanoparticles (LNPs) are widely used to deliver nucleic acid therapeutics, but the design of safe LNPs remains challenging due to the complex activity relationships among structure, composition, and physicochemical properties. Here, we present a curated dataset, the Lipid Nanoparticle Cytotoxicity Database (LNPCD), which aggregates 1,413 LNP cytotoxicity measurements across 1,288 unique ionizable lipids drawn from 11 high-throughput combinatorial studies. Lipid structures were generated computationally from the published libraries and manually verified against the original publications. Each record pairs a machine-readable SMILES representation of the ionizable lipid with its measured viability endpoint and the associated experimental descriptors, including cell line, dose, and cargo type. The dataset provides a traceable resource for examining how ionizable lipid structure and experimental conditions relate to in vitro cell viability, and for developing and evaluating computational models of lipid nanoparticle cytotoxicity.

bioengineering↗