A well 6-month-old infant with coronavirus disease 2019 (COVID-19) had persistently positive nasopharyngeal swabs up to day 16 of admission. This case highlights the difficulties in establishing the true incidence of COVID-19, as asymptomatic individuals can excrete the virus. These patients may play important roles in human-to-human transmission in the community.

A new type of lightly crosslinked shape‐memory polymer that contains reversibly associating side‐groups is reported. H‐bonding interactions stabilize mechanically strained states at low temperatures. The materials' shape recovery rate exhibits Arrhenius‐like temperature dependence due to the dynamics of H‐bond dissociation.

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Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop and validate visual biomarkers for new digital pathology datasets. We summarize the results of MoNuSeg 2018 Challenge whose objective was to develop generalizable nuclei segmentation techniques in digital pathology. The challenge was an official satellite event of the MICCAI 2018 conference in which 32 teams with more than 80 participants from geographically diverse institutes participated. Contestants were given a training set with 30 images from seven organs with annotations of 21,623 individual nuclei. A test dataset with 14 images taken from seven organs, including two organs that did not appear in the training set was released without annotations. Entries were evaluated based on average aggregated Jaccard index (AJI) on the test set to prioritize accurate instance segmentation as opposed to mere semantic segmentation. More than half the teams that completed the challenge outperformed a previous baseline [1]. Among the trends observed that contributed to increased accuracy were the use of color normalization as well as heavy data augmentation. Additionally, fully convolutional networks inspired by variants of U-Net [2], FCN [3], and Mask- RCNN [4] were popularly used, typically based on ResNet [5] or VGG [6] base architectures. Watershed segmentation on predicted semantic segmentation maps was a popular post-processing strategy. Several of the top techniques compared favorably to an individual human annotator and can be used with confidence for nuclear morphometrics.

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Abstract Transmission risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in schools is unknown. Our investigations, especially in preschools, could not detect SARS-CoV-2 transmission despite screening of symptomatic and asymptomatic children. The data suggest that children are not the primary drivers of SARS-CoV-2 transmission in schools and could help inform exit strategies for lifting of lockdowns.

Fluorescent conjugated polymers are an attractive basis for the design of low detection limit sensing devices owing to their intrinsic signal amplification capability. A simple and universal method to rationally control or fine-tune the chemodetection selectivity of conjugated polymer materials toward a desired analytical target would further benefit their applications. In a quest of such a method we investigated a general approach to cross-linked molecularly imprinted fluorescent conjugated polymer (MICP) materials that possess an intrinsic capability for signal transduction and have potential to enhance selectivity and sensitivity of sensor devices based on conjugated polymers. To study these capabilities, we prepared an MICP material for the detection of 2,4,6-trinitrotoluene and related nitroaromatic compounds. We found the imprinting effect in this material to be based on analyte shape/size recognition being substantial and generally overcoming other competing thermodynamically determined trends. The described molecularly imprinted fluorescent conjugated polymers show remarkable air stability and photostability, high fluorescence quantum yield, and reversible analyte binding and therefore are advantageous for sensing applications due to the ability to "preprogram" their detection selectivity through a choice of an imprinted template.