The development of molecularly imprinted polymer nanoparticles (MIP-NPs), which specifically bind biomolecules, is of great interest in the area of biosensors, sample purification, therapeutic agents and biotechnology. Polymerisation techniques such as precipitation polymerisation, solid phase synthesis and core shell surface imprinting have allowed for significant improvements to be made in developing MIP-NPs which specifically recognise proteins. However, the development of MIP-NPs for protein templates (targets) still require lengthy optimisation and characterisation using different ratios of monomers in order to control their size, binding affinity and specificity. In this work we successfully demonstrated that differential scanning fluorimetry (DSF) can be used to rapidly determine the optimum imprinting conditions and monomer composition required for MIP-NP design and polymerisation. This is based on the stability of the protein template and shift in apparent melting points (Tm) upon interaction with different functional acrylic monomers. The method allows for the characterisation of molecularly imprinted nanoparticles (MIP-NPs) due to the observed differences in melting point profiles between, protein-MIP-NPs complexes, pre-polymerisation mixtures and non-imprinted nanoparticles (NIP-NPs) without the need for prior purification. The technique is simple, rapid and can be carried out on most quantitative polymerase chain reaction (qPCR) thermal cyclers which have the required filters for SYPRO
Substantial variability exists with regard to autism service provision around the world. Service disparities observed in many low- and middle-income countries may be driven, in part, by limited autism knowledge; however, measurement limitations have made it difficult to quantify autism knowledge across countries. The current study uses the autism stigma and knowledge questionnaire (ASK-Q) to quantify autism knowledge and stigma between different countries and demographics. The current study compiled data from 6830 participants collected using adapted versions of the ASK-Q administered in 13 different countries, representing four different continents. Structural equation modeling was used to examine how autism knowledge varied across country and individual factors. Results reveal cross country variability with a large, 17-point difference between the countries with the highest knowledge (Canada) and the lowest knowledge (Lebanon). As expected, countries with higher economies had higher levels of knowledge. We also documented differences based on country worldview, participant occupation, gender, age, and education level. These results help to identify specific regions and populations that might most need greater information about autism.
Food recalls due to undeclared allergens or contamination are costly to the food manufacturing industry worldwide. As the industry strives for better manufacturing efficiencies over a diverse range of food products, there is a need for the development of new analytical techniques to improve monitoring of the presence of unintended food allergens during the food manufacturing process. In particular, the monitoring of wash samples from cleaning in place systems (CIP), used in the cleaning of food processing equipment, would allow for the effective removal of allergen containing ingredients in between food batches. Casein proteins constitute the biggest group of proteins in milk and hence are the most common milk protein allergen in food ingredients. As such, these proteins could present an ideal analyte for cleaning validation. In this work, molecularly imprinted polymer nanoparticles (nanoMIPs) with high affinity toward bovine α-casein were synthesized using a solid-phase imprinting method. The nanoMIPs were then characterized and incorporated into label free surface plasmon resonance (SPR) based sensor. The nanoMIPs demonstrated good binding affinity and selectivity toward α-casein (KD ∼ 10 × 10-9 M). This simple affinity sensor demonstrated the quantitative detection of α-casein achieving a detection limit of 127 ± 97.6 ng mL-1 (0.127 ppm) which is far superior to existing commercially available ELISA kits. Recoveries from spiked CIP wastewater samples were within the acceptable range (87-120%). The reported sensor could allow food manufacturers to adequately monitor and manage food allergen risk in food processing environments while ensuring that the food produced is safe for the consumer.