Finger stick blood test to assess postvaccination SARS-CoV-2 neutralizing antibody response against variants.

There is clinical need for a quantifiable point-of-care (PoC) SARS-CoV-2 neutralizing antibody (nAb) test that is adaptable with the pandemic's changing landscape. Here, we present a rapid and semi-quantitative nAb test that uses finger stick or venous blood to assess the nAb response of vaccinated population against wild-type (WT), alpha, beta, gamma, and delta variant RBDs. It captures a clinically relevant range of nAb levels, and effectively differentiates prevaccination, post first dose, and post second dose vaccination samples within 10 min. The data observed against alpha, beta, gamma, and delta variants agrees with published results evaluated in established serology tests. Finally, our test revealed a substantial reduction in nAb level for beta, gamma, and delta variants between early BNT162b2 vaccination group (within 3 months) and later vaccination group (post 3 months). This test is highly suited for PoC settings and provides an insightful nAb response in a postvaccinated population.

A wireless and battery-free wound infection sensor based on DNA hydrogel.

The confluence of wireless technology and biosensors offers the possibility to detect and manage medical conditions outside of clinical settings. Wound infections represent a major clinical challenge in which timely detection is critical for effective interventions, but this is currently hindered by the lack of a monitoring technology that can interface with wounds, detect pathogenic bacteria, and wirelessly transmit data. Here, we report a flexible, wireless, and battery-free sensor that provides smartphone-based detection of wound infection using a bacteria-responsive DNA hydrogel. The engineered DNA hydrogels respond selectively to deoxyribonucleases associated with pathogenic bacteria through tunable dielectric changes, which can be wirelessly detected using near-field communication. In a mouse acute wound model, we demonstrate that the wireless sensor can detect physiologically relevant amounts of Staphylococcus aureus even before visible manifestation of infection. These results demonstrate strategies for continuous infection monitoring, which may facilitate improved management of surgical or chronic wounds.

Influence of spectral resolution, spectral range and signal-to-noise ratio of Fourier transform infra-red spectra on identification of high explosive substances.

In the contemporary spectroscopy there is a trend to record spectra with the highest possible spectral resolution. This is clearly justified if the spectral features in the spectrum are very narrow (for example infra-red spectra of gas samples). However there is a plethora of samples (in the liquid and especially in the solid form) where there is a natural spectral peak broadening due to collisions and proximity predominately. Additionally there is a number of portable devices (spectrometers) with inherently restricted spectral resolution, spectral range or both, which are extremely useful in some field applications (archaeology, agriculture, food industry, cultural heritage, forensic science). In this paper the investigation of the influence of spectral resolution, spectral range and signal-to-noise ratio on the identification of high explosive substances by applying multivariate statistical methods on the Fourier transform infra-red spectral data sets is studied. All mathematical procedures on spectral data for dimension reduction, clustering and validation were implemented within R open source environment.