Improved sensitivity and automation of a multi-step upconversion lateral flow immunoassay using a 3D-printed actuation mechanism.

The development of sensitive point-of-care (POC) assay platforms is of interest for reducing the cost and time of diagnostics. Lateral flow assays (LFAs) are the gold standard for POC systems, but their sensitivity as such is inadequate, for example, in the case of cardiac diagnostics. The performance can be improved by incorporating different steps, such as pre-incubation to prolong the interaction time between sample and reporter for immunocomplex formation, and washing steps for background reduction. However, for POC assays, manual steps by the assay conductor are not desired. In this research, upconverting nanoparticles (UCNPs) were coated with poly(acrylic acid) (PAA) and conjugated to anti-cTnI antibodies, yielding non-clustering particles with low non-specific binding. The performance of cTnI-LFA in the PAA-anti-cTnI-UCNPs was compared to the same UCNPs with a commercial carboxyl surface. A kitchen-timer mechanism was embedded in a 3D-printed housing to produce a low-cost actuator facilitating a timed pre-incubation step for reporter and sample, and a washing step, to enable a multi-step cTnI-LFA with minimized manual labour. PAA-UCNPs showed improved mobility on nitrocellulose compared to those with a commercial surface. The mechanical actuator system was shown to improve sensitivity compared to a labour-intensive multi-step dipstick method, despite pre-incubation occurring during shaking and heating in the dipstick method. The limit of detection decreased from 7.6 to 1.5 ng/L cTnI in human plasma. The presented actuator can be easily modified for sensitivity improvement in the LFA for different analytes via pre-incubation and washing steps.

Cough and cold medicine prescription rates can be significantly reduced by active intervention.

Our aim was to construct and test an intervention programme to eradicate cough and cold medicine (CCM) prescriptions for children treated in a nationwide healthcare service company. The study was carried out in the largest private healthcare service company in Finland with a centralised electronic health record system allowing for real-time, doctor-specific practice monitoring. The step-by-step intervention consisted of company-level dissemination of educational materials to doctors and families, educational staff meetings, continuous monitoring of prescriptions, and targeted feedback. Outreach visits were held in noncompliant units. Finally, those physicians who most often prescribed CCM were directly contacted. During the intervention period (2017-2020), there were more than one million paediatric visits. Prescriptions of CCMs to children were completely eradicated in 41% of units and the total number of CCM prescriptions decreased from 6738 to 744 (89%). During the fourth intervention year, CCMs containing opioid derivatives were prescribed for only 0.2% of children aged < 2 years. The decrease in prescriptions was greatest in general practitioners (5.2 to 1.1%). In paediatricians, the prescription rates decreased from 1.5 to 0.2%. The annual costs of CCMs decreased from €183,996 to €18,899 (89.7%). For the intervention, the developers used 343 h and the attended doctors used 684 h of work time during the 4-year intervention. The costs used for developing, implementing, reporting, evaluating, communicating, and data managing formed approximately 11% of total intervention costs. CONCLUSION: The study showed that a nationwide systematic intervention to change cough medicine prescription practices is feasible and requires only modest financial investments. WHAT IS KNOWN: • Cough and cold medicines (CCM) are not effective or safe, especially for children aged 6 years. • Although the use of CCMs has been declining, caregivers continue to administer CCMs to children, and some physicians still prescribe them even for preschool children. WHAT IS NEW: • A nationwide systematic intervention can significantly and cost effectively change CCM prescription habits of paediatricians, general practitioners, and other specialists. • Electronic health records provide additional tools for operative guideline implementation and real-time quality monitoring, including recommendations of useless or harmful treatments.

Unbiased probabilistic taxonomic classification for DNA barcoding.

MOTIVATION: When targeted to a barcoding region, high-throughput sequencing can be used to identify species or operational taxonomical units from environmental samples, and thus to study the diversity and structure of species communities. Although there are many methods which provide confidence scores for assigning taxonomic affiliations, it is not straightforward to translate these values to unbiased probabilities. We present a probabilistic method for taxonomical classification (PROTAX) of DNA sequences. Given a pre-defined taxonomical tree structure that is partially populated by reference sequences, PROTAX decomposes the probability of one to the set of all possible outcomes. PROTAX accounts for species that are present in the taxonomy but that do not have reference sequences, the possibility of unknown taxonomical units, as well as mislabeled reference sequences. PROTAX is based on a statistical multinomial regression model, and it can utilize any kind of sequence similarity measures or the outputs of other classifiers as predictors. RESULTS: We demonstrate the performance of PROTAX by using as predictors the output from BLAST, the phylogenetic classification software TIPP, and the RDP classifier. We show that PROTAX improves the predictions of the baseline implementations of TIPP and RDP classifiers, and that it is able to combine complementary information provided by BLAST and TIPP, resulting in accurate and unbiased classifications even with very challenging cases such as 50% mislabeling of reference sequences. AVAILABILITY AND IMPLEMENTATION: Perl/R implementation of PROTAX is available at http://www.helsinki.fi/science/metapop/Software.htm CONTACT: panu.somervuo@helsinki.fi SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.