David R. Walt

Conventional approaches to chemical sensors have
\ntraditionally made use of a “lock-and-key” design,
\nwherein a specific receptor is synthesized in order to
\nstrongly and highly selectively bind the analyte of
\ninterest.1-6 A related approach involves exploiting a
\ngeneral physicochemical effect selectively toward a
\nsingle analyte, such as the use of the ionic effect in
\nthe construction of a pH electrode. In the first
\napproach, selectivity is achieved through recognition
\nof the analyte at the receptor site, and in the second,
\nselectivity is achieved through the transduction
\nprocess in which the method of detection dictates
\nwhich species are sensed. Such approaches are appropriate
\nwhen a specific target compound is to be
\nidentified in the presence of controlled backgrounds
\nand interferences. However, this type of approach
\nrequires the synthesis of a separate, highly selective
\nsensor for each analyte to be detected. In addition,
\nthis type of approach is not particularly useful for
\nanalyzing, classifying, or assigning human value
\njudgments to the composition of complex vapor
\nmixtures such as perfumes, beers, foods, mixtures of
\nsolvents, etc.

The diagnosis of postacute sequelae of coronavirus disease 2019 (PASC) poses an ongoing medical challenge. To identify biomarkers associated with PASC we analyzed plasma samples collected from PASC and coronavirus disease 2019 patients to quantify viral antigens and inflammatory markers. We detect severe acute respiratory syndrome coronavirus 2 spike predominantly in PASC patients up to 12 months after diagnosis.