Anterior ankle arthroscopy, distraction or dorsiflexion?

Anterior ankle arthroscopy can basically be performed by two different methods; the dorsiflexion- or distraction method. The objective of this study was to determine the size of the anterior working area for both the dorsiflexion and distraction method. The anterior working area is anteriorly limited by the overlying anatomy which includes the neurovascular bundle. We hypothesize that in ankle dorsiflexion the anterior neurovascular bundle will move away anteriorly from the ankle joint, whereas in ankle distraction the anterior neurovascular bundle is pulled tight towards the joint, thereby decreasing the safe anterior working area. Six fresh frozen ankle specimens, amputated above the knee, were scanned with computed tomography. Prior to scanning the anterior tibial artery was injected with contrast fluid and subsequently each ankle was scanned both in ankle dorsiflexion and in distraction. A special device was developed to reproducibly obtain ankle dorsiflexion and distraction in the computed tomography scanner. The distance between the anterior border of the inferior tibial articular facet and the posterior border of the anterior tibial artery was measured. The median distance from the anterior border of the inferior tibial articular facet to the posterior border of the anterior tibial artery in ankle dorsiflexion and distraction was 0.9 cm (range 0.7–1.5) and 0.7 cm (range 0.5–0.8), respectively. The distance in ankle dorsiflexion significantly exceeded the distance in ankle distraction (P = 0.03). The current study shows a significantly increased distance between the anterior distal tibia and the overlying anterior neurovascular bundle with the ankle in a slightly dorsiflexed position as compared to the distracted ankle position. We thereby conclude that the distracted ankle position puts the neurovascular structures more at risk for iatrogenic damage when performing anterior ankle arthroscopy

Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types

Abstract Background A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results We apply a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16− monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naïve T cells from the same 125 healthy individuals. We discover substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression are found to be implicated in key immune pathways and are associated with cellular properties and environmental exposure. We also observe increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites are enriched at dynamic chromatin regions and active enhancers. Conclusions Our data highlight the importance of transcriptional and epigenetic variability for the key role of neutrophils as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.Peer reviewe

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified