A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty.

Introduction: Knee osteoarthritis is a prevalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantially. Partial knee arthroplasty (PKA) offers advantages over total knee arthroplasty (TKA), yet its utilisation remains low despite guidance recommending consideration alongside TKA in shared decision making. Radiographic decision aids exist but are underutilised due to clinician time constraints.

Blinding Is Seeing: A Single-Centre Study Into the Viability of Auto-Injectors for Blinded-Drug Administration in Randomised Controlled Trials.

Objective The aim of the study was to assess the viability of auto-injector systems (A-INJ) for preserving investigator blinding in randomized controlled trials (RCT). Background Blinding refers to the concealment of group allocation from one or more individuals involved in a clinical research study. In the dosing of subcutaneous (SC) and intramuscular (IM) investigational medicinal products (IMP), specific challenges arise in maintaining investigator blinding.

The Reliability of Auto-Injectors in Clinical Use: A Systematic Review.

Auto-injectors are medical devices designed for the self-administration of injections by patients and for easy administration by healthcare professionals in emergency situations. Although they vary in design and application, auto-injectors are typically built around a spring-loaded syringe. Despite their widespread use in a variety of clinical settings, there have been limited attempts to assess their reliability.

Robotic-assisted knee replacement surgery & infection: A historical foundation, systematic review and meta-analysis.

Background: An increasing proportion of Knee arthroplasty is performed using robotic-assisted surgical techniques. This study sought to use a meta-analytical approach to establish summary rates of surgical site infection in robotic-assisted procedures and compare the rate of deep infections to those seen in conventional knee arthroplasty.

Methods: This study performed a literature search across four online databases to establish a summary rate of surgical site infection across two categories: deep infection and superficial and pin-site infections.

Clinician and computer: a study on doctors' perceptions of artificial intelligence in skeletal radiography.

Background: Traumatic musculoskeletal injuries are a common presentation to emergency care, the first-line investigation often being plain radiography. The interpretation of this imaging frequently falls to less experienced clinicians despite well-established challenges in reporting. This study presents novel data of clinicians' confidence in interpreting trauma radiographs, their perception of AI in healthcare, and their support for the development of systems applied to skeletal radiography.

Reporting errors in plain radiographs for lower limb trauma-a systematic review and meta-analysis.

Introduction: Plain radiographs are a globally ubiquitous means of investigation for injuries to the musculoskeletal system. Despite this, initial interpretation remains a challenge and inaccuracies give rise to adverse sequelae for patients and healthcare providers alike. This study sought to address the limited, existing meta-analytic research on the initial reporting of radiographs for skeletal trauma, with specific regard to diagnostic accuracy of the most commonly injured region of the appendicular skeleton, the lower limb.

Clinician and computer: a study on patient perceptions of artificial intelligence in skeletal radiography.

Background: Up to half of all musculoskeletal injuries are investigated with plain radiographs. However, high rates of image interpretation error mean that novel solutions such as artificial intelligence (AI) are being explored.

Objectives: To determine patient confidence in clinician-led radiograph interpretation, the perception of AI-assisted interpretation and management, and to identify factors which might influence these views.

Seasonal and climatic variation in the incidence of adult acute appendicitis: a seven year longitudinal analysis.

Background: Acute appendicitis represents an extremely common surgical emergency, yet its aetiology remains uncertain. A multifactorial understanding of its causation has emerged along with increasing evidence of seasonal variation. This study seeks to find evidence for such a circannual trend within the United Kingdom (UK), and further assess key meteorological indicators which may be causative of any such variation.

Independent evolution of ancestral and novel defenses in a genus of toxic plants (, Brassicaceae).

Phytochemical diversity is thought to result from coevolutionary cycles as specialization in herbivores imposes diversifying selection on plant chemical defenses. Plants in the speciose genus (Brassicaceae) produce both ancestral glucosinolates and evolutionarily novel cardenolides as defenses. Here we test macroevolutionary hypotheses on co-expression, co-regulation, and diversification of these potentially redundant defenses across this genus.

Reporting Discrepancy Resolved by Findings and Time in 2947 Emergency Department Ankle X-rays.

Aims: To identify common errors in ankle X-ray reporting between initial interpretation and final assessment at the virtual fracture clinic. Also, to assess time of initial reporting as a causative factor for discrepancy.

Methods: Two thousand nine hundred forty-seven final reports were reviewed by standard of agreement to the initial interpretation.

Genes conserved for arbuscular mycorrhizal symbiosis identified through phylogenomics.

Arbuscular mycorrhizal symbiosis (AMS), a widespread mutualistic association of land plants and fungi(1), is predicted to have arisen once, early in the evolution of land plants(2-4). Consistent with this notion, several genes required for AMS have been conserved throughout evolution(5) and their symbiotic functions preserved, at least between monocot and dicot plants(6,7). Despite its significance, knowledge of the plants' genetic programme for AMS is limited.

Comparative genomics and phylogenetic discordance of cultivated tomato and close wild relatives.

Background. Studies of ancestry are difficult in the tomato because it crosses with many wild relatives and species in the tomato clade that have diverged very recently. As a result, the phylogeny in relation to its closest relatives remains uncertain.

Auto-validating von Neumann rejection sampling from small phylogenetic tree spaces.

Background: In phylogenetic inference one is interested in obtaining samples from the posterior distribution over the tree space on the basis of some observed DNA sequence data. One of the simplest sampling methods is the rejection sampler due to von Neumann. Here we introduce an auto-validating version of the rejection sampler, via interval analysis, to rigorously draw samples from posterior distributions over small phylogenetic tree spaces.

Estimation of 2Nes from temporal allele frequency data.

We develop a new method for estimating effective population sizes, Ne, and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications.

Genome-wide patterns of nucleotide polymorphism in domesticated rice.

Domesticated Asian rice (Oryza sativa) is one of the oldest domesticated crop species in the world, having fed more people than any other plant in human history. We report the patterns of DNA sequence variation in rice and its wild ancestor, O. rufipogon, across 111 randomly chosen gene fragments, and use these to infer the evolutionary dynamics that led to the origins of rice.

Dependence of paracentric inversion rate on tract length.

Background: We develop a Bayesian method based on MCMC for estimating the relative rates of pericentric and paracentric inversions from marker data from two species. The method also allows estimation of the distribution of inversion tract lengths.

Results: We apply the method to data from Drosophila melanogaster and D.

Bayesian and maximum likelihood estimation of genetic maps.

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods that makes the Bayesian method applicable to large data sets.

Comparative genome analyses of Arabidopsis spp.: inferring chromosomal rearrangement events in the evolutionary history of A. thaliana.

Comparative genome analysis is a powerful tool that can facilitate the reconstruction of the evolutionary history of the genomes of modern-day species. The model plant Arabidopsis thaliana with its n = 5 genome is thought to be derived from an ancestral n = 8 genome. Pairwise comparative genome analyses of A.

Bayesian estimation of genomic distance.

We present a Bayesian approach to the problem of inferring the number of inversions and translocations separating two species. The main reason for developing this method is that it will allow us to test hypotheses about the underlying mechanisms, such as the distribution of inversion track lengths or rate constancy among lineages. Here, we apply these methods to comparative maps of eggplant and tomato, human and cat, and human and cattle with 170, 269, and 422 markers, respectively.

Bayesian estimation of the number of inversions in the history of two chromosomes.

We present a Bayesian approach to the problem of inferring the history of inversions separating homologous chromosomes from two different species. The method is based on Markov Chain Monte Carlo (MCMC) and takes full advantage of all the information from marker order. We apply the method both to simulated data and to two real data sets.