ObjectiveTo determine the rates of asymptomatic viral carriage and seroprevalence of SARS-CoV-2 antibodies in healthcare workers.DesignA cross-sectional study of asymptomatic healthcare workers undertaken on 24/25 April 2020.SettingUniversity Hospitals Birmingham NHS Foundation Trust (UHBFT), UK.Participants545 asymptomatic healthcare workers were recruited while at work. Participants were invited to participate via the UHBFT social media. Exclusion criteria included current symptoms consistent with COVID-19. No potential participants were excluded.InterventionParticipants volunteered a nasopharyngeal swab and a venous blood sample that were tested for SARS-CoV-2 RNA and anti-SARS-CoV-2 spike glycoprotein antibodies, respectively. Results were interpreted in the context of prior illnesses and the hospital departments in which participants worked.Main outcome measureProportion of participants demonstrating infection and positive SARS-CoV-2 serology.ResultsThe point prevalence of SARS-CoV-2 viral carriage was 2.4% (n=13/545). The overall seroprevalence of SARS-CoV-2 antibodies was 24.4% (n=126/516). Participants who reported prior symptomatic illness had higher seroprevalence (37.5% vs 17.1%, χ2=21.1034, p<0.0001) and quantitatively greater antibody responses than those who had remained asymptomatic. Seroprevalence was greatest among those working in housekeeping (34.5%), acute medicine (33.3%) and general internal medicine (30.3%), with lower rates observed in participants working in intensive care (14.8%). BAME (Black, Asian and minority ethnic) ethnicity was associated with a significantly increased risk of seropositivity (OR: 1.92, 95% CI 1.14 to 3.23, p=0.01). Working on the intensive care unit was associated with a significantly lower risk of seropositivity compared with working in other areas of the hospital (OR: 0.28, 95% CI 0.09 to 0.78, p=0.02).Conclusions and relevanceWe identify differences in the occupational risk of exposure to SARS-CoV-2 between hospital departments and confirm asymptomatic seroconversion occurs in healthcare workers. Further investigation of these observations is required to inform future infection control and occupational health practices.

Summer annuals overwinter as seeds in the soil seed bank. This is facilitated by a cold-induced increase in dormancy during seed maturation followed by a switch to a state during seed imbibition in which cold instead promotes germination. Here, we show that the seed maturation transcriptome in Arabidopsis thaliana is highly temperature sensitive and reveal that low temperature during seed maturation induces several genes associated with dormancy, including DELAY OF GERMINATION1 (DOG1), and influences gibberellin and abscisic acid levels in mature seeds. Mutants lacking DOG1, or with altered gibberellin or abscisic acid synthesis or signaling, in turn show reduced ability to enter the deeply dormant states in response to low seed maturation temperatures. In addition, we find that DOG1 promotes gibberellin catabolism during maturation. We show that C-REPEAT BINDING FACTORS (CBFs) are necessary for regulation of dormancy and of GA2OX6 and DOG1 expression caused by low temperatures. However, the temperature sensitivity of CBF transcription is markedly reduced in seeds and is absent in imbibed seeds. Our data demonstrate that inhibition of CBF expression is likely a critical feature allowing cold to promote rather than inhibit germination and support a model in which CBFs act in parallel to a low-temperature signaling pathway in the regulation of dormancy.

ObjectiveComplex phenotypes captured on histological slides represent the biological processes at play in individual cancers, but the link to underlying molecular classification has not been clarified or systematised. In colorectal cancer (CRC), histological grading is a poor predictor of disease progression, and consensus molecular subtypes (CMSs) cannot be distinguished without gene expression profiling. We hypothesise that image analysis is a cost-effective tool to associate complex features of tissue organisation with molecular and outcome data and to resolve unclassifiable or heterogeneous cases. In this study, we present an image-based approach to predict CRC CMS from standard H&E sections using deep learning.DesignTraining and evaluation of a neural network were performed using a total of n=1206 tissue sections with comprehensive multi-omic data from three independent datasets (training on FOCUS trial, n=278 patients; test on rectal cancer biopsies, GRAMPIAN cohort, n=144 patients; and The Cancer Genome Atlas (TCGA), n=430 patients). Ground truth CMS calls were ascertained by matching random forest and single sample predictions from CMS classifier.ResultsImage-based CMS (imCMS) accurately classified slides in unseen datasets from TCGA (n=431 slides, AUC)=0.84) and rectal cancer biopsies (n=265 slides, AUC=0.85). imCMS spatially resolved intratumoural heterogeneity and provided secondary calls correlating with bioinformatic prediction from molecular data. imCMS classified samples previously unclassifiable by RNA expression profiling, reproduced the expected correlations with genomic and epigenetic alterations and showed similar prognostic associations as transcriptomic CMS.ConclusionThis study shows that a prediction of RNA expression classifiers can be made from H&E images, opening the door to simple, cheap and reliable biological stratification within routine workflows.

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Objectives To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay. Patients and Methods A panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed. Results The panel comprised SMs in 23 genes: TERT (promoter), FGFR3, PIK3CA, TP53, ERCC2, RHOB, ERBB2, HRAS, RXRA, ELF3, CDKN1A, KRAS, KDM6A, AKT1, FBXW7, ERBB3, SF3B1, CTNNB1, BRAF, C3orf70, CREBBP, CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P < 0.05). MAFs in urinary cfDNA and cpDNA were highly correlated; using a capture‐based approach, >94% of tumour SMs were detected in both cpDNA and cfDNA. Conclusions SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC.