Charting a biological atlas of an organ, such as the brain, requires us to spatially-resolve whole transcriptomes of single cells, and to relate such cellular features to the histological and anatomical scales. Single-cell and single-nucleus RNA-Seq (sc/snRNA-seq) can map cells comprehensively5,6, but relating those to their histological and anatomical positions in the context of an organ’s common coordinate framework remains a major challenge and barrier to the construction of a cell atlas7–10. Conversely, Spatial Transcriptomics allows for in-situ measurements11–13 at the histological level, but at lower spatial resolution and with limited sensitivity. Targeted in situ technologies1–3 solve both issues, but are limited in gene throughput which impedes profiling of the entire transcriptome. Finally, as samples are collected for profiling, their registration to anatomical atlases often require human supervision, which is a major obstacle to build pipelines at scale. Here, we demonstrate spatial mapping of cells, histology, and anatomy in the somatomotor area and the visual area of the healthy adult mouse brain. We devise Tangram, a method that aligns snRNA-seq data to various forms of spatial data collected from the same brain region, including MERFISH1, STARmap2, smFISH3, and Spatial Transcriptomics4 (Visium), as well as histological images and public atlases. Tangram can map any type of sc/snRNA-seq data, including multi-modal data such as SHARE-seq data5, which we used to reveal spatial patterns of chromatin accessibility. We equipped Tangram with a deep learning computer vision pipeline, which allows for automatic identification of anatomical annotations on histological images of mouse brain. By doing so, Tangram reconstructs a genome-wide, anatomically-integrated, spatial map of the visual and somatomotor area with ∼30,000 genes at single-cell resolution, revealing spatial gene expression and chromatin accessibility patterning beyond current limitation of in-situ technologies.
Background: Underreporting of medication administering errors (MAEs) is a threat to the quality of nursing care. The reasons for MAEs are complex and vary by health professional and institution. Aims: The purpose of this study was to explore the prevalence of MAEs and the willingness of nurses to report them. Methods: A cross‐sectional study was conducted involving a survey of 14 medical surgical hospitals in southern Taiwan. Nurses voluntarily participated in this study. A structured questionnaire was completed by 605 participants. Data were collected from February 1, 2005 to March 15, 2005 using the following instruments: MAEs Unwillingness to Report Scale, Medication Errors Etiology Questionnaire, and Personal Features Questionnaire. One additional question was used to identify the willingness of nurses to report medication errors: “When medication errors occur, should they be reported to the department?” This question helped to identify the willingness or lack thereof, to report incident errors. Results: The results indicated that 66.9% of the nurses reported experiencing MAEs and 87.7% of the nurses had a willingness to report the MAEs if there were no consequences for reporting. The nurses' willingness to report MAEs differed by job position, nursing grade, type of hospital, and hospital funding. The final logistic regression model demonstrated hospital funding to be the only statistically significant factor. The odds of a willingness to report MAEs increased 2.66‐fold in private hospitals (p = 0.032, CI = 1.09 to 6.49), and 3.28 in nonprofit hospitals (p = 0.00, CI = 1.73 to 6.21) when compared to public hospitals. Conclusions: This study demonstrates that reporting of MAEs should be anonymous and without negative consequences in order to monitor and guide improvements in hospital medication systems.
Purpose To explore the usefulness of liver stiffness measurements (LSMs) by sound touch elastography (STE) and sound touch quantification (STQ) in chronic hepatitis B (CHB) patients for staging fibrosis. Methods This prospective multicenter study recruited normal volunteers and CHB patients between May 2018 and October 2019. The volunteers underwent LSM by STE and supersonic shear imaging (SSI) or by STQ and acoustic radiation force impulse imaging (ARFI). CHB patients underwent liver biopsy and LSM by both STE/STQ. The areas under the receiver operating characteristic curves (AUCs) for staging fibrosis were calculated. Results Overall, 97 volunteers and 524 CHB patients were finally eligible for the study. The successful STE and STQ measurement rates were both 100 % in volunteers and 99.4 % in CHB patients. The intraclass correlation coefficients (ICCs) for the intra-observer stability of STE and STQ (0.94; 0.90) were similar to those of SSI and ARFI (0.95; 0.87), respectively. STE and STQ showed better accuracy than the aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) (AUC: 0.87 vs 0.86 vs 0.73 vs 0.77) in staging cirrhosis. However, both STE and STQ were not superior to APRI and FIB-4 in staging significant fibrosis (AUC: 0.76 vs 0.73 vs 0.70 vs 0.71, all P-values > 0.05). Conclusion STE and STQ are convenient techniques with a reliable LSM value. They have a similar diagnostic performance and are superior to serum biomarkers in staging cirrhosis in CHB patients.
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