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Aims: To compare the effectiveness and safety of 2 high-intensity atorvastatin doses (40 mg vs 80 mg) among acute coronary syndrome (ACS) patients. Methods: This retrospective observational cohort study using real-world data included patients admitted with ACS to the Heart Hospital in Qatar between 1 January 2017 and 31 December 2018. The primary endpoint was a composite of cardiovascular disease-associated death, nonfatal ACS and nonfatal stroke. Cox proportional hazard regression analysis was used to determine the association between the 2 high-intensity atorvastatin dosing regimens and the primary outcome at 1 month and 12 months postdischarge. Results: Of the 626 patients included in the analyses, 475 (75.9%) received atorvastatin 40 mg, while 151 (24.1%) received atorvastatin 80 mg following ACS. Most of the patients were Asian (73%), male (97%) with a mean age of 50 years and presented with ST-elevation myocardial infarction (60%). The incidence of the primary effectiveness outcome did not differ between the atorvastatin 40-and 80-mg groups at 1 month (0.8 vs 1.3%; adjusted hazard ratio = 0.59, 95% confidence interval 0.04-8.13, P =.690) and at 12 months (3.2 vs 4%; adjusted hazard ratio = 0.57, 95% confidence interval 0.18-1.80, P =.340). Similarly, the use of the 2 doses of atorvastatin resulted in comparable safety outcomes, including liver toxicity, myopathy and rhabdomyolysis with an event rate of

Glucocorticoid stress hormones are powerful modulators of brain function and can affect mood and cognitive processes. The hippocampus is a prominent glucocorticoid target and expresses both the glucocorticoid receptor (GR: Nr3c1) and the mineralocorticoid receptor (MR: Nr3c2). These nuclear steroid receptors act as ligand-dependent transcription factors. Transcriptional effects of glucocorticoids have often been deduced from bulk mRNA measurements or spatially informed individual gene expression. However, only sparse data exists allowing insights on glucocorticoid-driven gene transcription at the cell type level. Here, we used publicly available single-cell RNA sequencing data to assess the cell-type specificity of GR and MR signaling in the adult mouse hippocampus. The data confirmed that Nr3c1 and Nr3c2 expression differs across neuronal and non-neuronal cell populations. We analyzed co-expression with sex hormones receptors, transcriptional coregulators, and receptors for neurotransmitters and neuropeptides. Our results provide insights in the cellular basis of previous bulk mRNA results and allow the formulation of more defined hypotheses on the effects of glucocorticoids on hippocampal function.

Mass cytometry by time‐of‐flight (CyTOF) is a valuable technology for high‐dimensional analysis at the single cell level. Identification of different cell populations is an important task during the data analysis. Many clustering tools can perform this task, which is essential to identify “new” cell populations in explorative experiments. However, relying on clustering is laborious since it often involves manual annotation, which significantly limits the reproducibility of identifying cell‐populations across different samples. The latter is particularly important in studies comparing different conditions, for example in cohort studies. Learning cell populations from an annotated set of cells solves these problems. However, currently available methods for automatic cell population identification are either complex, dependent on prior biological knowledge about the populations during the learning process, or can only identify canonical cell populations. We propose to use a linear discriminant analysis (LDA) classifier to automatically identify cell populations in CyTOF data. LDA outperforms two state‐of‐the‐art algorithms on four benchmark datasets. Compared to more complex classifiers, LDA has substantial advantages with respect to the interpretable performance, reproducibility, and scalability to larger datasets with deeper annotations. We apply LDA to a dataset of ~3.5 million cells representing 57 cell populations in the Human Mucosal Immune System. LDA has high performance on abundant cell populations as well as the majority of rare cell populations, and provides accurate estimates of cell population frequencies. Further incorporating a rejection option, based on the estimated posterior probabilities, allows LDA to identify previously unknown (new) cell populations that were not encountered during training. Altogether, reproducible prediction of cell population compositions using LDA opens up possibilities to analyze large cohort studies based on CyTOF data. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Myasthenia gravis (MG) is an acquired autoimmune disorder caused by autoantibodies binding acetylcholine receptors (AChR), muscle‐specific kinase (MuSK), agrin or low‐density lipoprotein receptor‐related protein 4 (Lrp4). These autoantibodies inhibit neuromuscular transmission by blocking the function of these proteins and thereby cause fluctuating skeletal muscle weakness. Several reports suggest that these autoantibodies might also affect the central nervous system (CNS) in MG patients. A comprehensive overview of the timing and localization of the expression of MG‐related antigens in other organs is currently lacking. To investigate the spatio‐temporal expression of MG‐related genes outside skeletal muscle, we used in silico tools to assess public expression databases. Acetylcholine esterase, nicotinic AChR α1 subunit, agrin, collagen Q, downstream of kinase‐7, Lrp4, MuSK and rapsyn were included as MG‐related genes because of their well‐known involvement in either congenital or autoimmune MG. We investigated expression of MG‐related genes in (1) all human tissues using GTEx data, (2) specific brain regions, (3) neurodevelopmental stages, and (4) cell types using datasets from the Allen Institute for Brain Sciences. MG‐related genes show heterogenous spatio‐temporal expression patterns in the human body as well as in the CNS. For each of these genes, several (new) tissues, brain areas and cortical cell types with (relatively) high expression were identified suggesting a potential role for these genes outside skeletal muscle. The possible presence of MG‐related antigens outside skeletal muscle suggests that autoimmune MG, congenital MG or treatments targeting the same proteins may affect MG‐related protein function in other organs., Many of the proteins involved in organizing and maintaining neuromuscular signalling cause (congenital) myasthenia gravis (MG) when their function is impaired. However, little is known on the presence and function of these proteins outside skeletal muscle. We generated a comprehensive overview of spatio‐temporal MG‐related gene expression from public human‐based databases, with a focus on the brain. These data provide a guide on tissues at risk for non‐motor symptoms in MG patients and upon MG‐related genes targeted therapy.

With the use of available liver magnetic resonance contrast agents, such as mangafodipir (Mn-DPDP), liver metastases do not exhibit enhancement on T1-weighted images. This absence of enhancement is due to the lack of hepatocytes within these tumors. The purpose of this report is to demonstrate an unexpected enhancement on T1-weighted images 30 minutes after injection of mangafodipir, in the case of endocrine liver metastases from a non-hyperfunctioning neuroendocrine pancreatic tumor. Different hypotheses could explain this unexpected enhancement, such as increased arterial tumoral flow or high metabolic activity. Contrary to liver metastases of other origins, Mn-DPDP enhancement can be present in neuroendocrine metastases. J. Magn. Reson. Imaging 1999;10:193-195.