IntroductionPatients with rheumatoid arthritis (RA) are at an increased risk of malignancies compared with the general population. This has raised concerns regarding these patients, particularly with the widespread use of immunomodulating therapies, including biologic disease-modifying antirheumatic drugs (DMARDs). We performed a systematic literature review and analysis to quantify the incidence of malignancies in patients with RA and the general population to update previously published data.MethodsA literature search was conducted that was consistent with and similar to that in a meta-analysis published in 2008. MEDLINE, BIOSIS Previews, Embase, Derwent Drug File and SciSearch databases were searched using specified search terms. Predefined inclusion criteria identified the relevant observational studies published between 2008 and 2014 that provided estimates of relative risk of malignancy in patients with RA compared with the general population. Risk data on overall malignancy and site-specific malignancies (lymphoma, melanoma and lung, colorectal, breast, cervical and prostate cancer) were extracted. The standardized incidence ratios (SIRs; a measure of risk) relative to the general population were evaluated and compared with published rates.ResultsA total of nine publications met the inclusion criteria. Seven of these reported SIRs for overall malignancy; eight for lymphoma, melanoma, and lung, colorectal and breast cancer; seven for prostate cancer; and four for cervical cancer. Compared with those in the general population, the SIR estimates for patients with RA suggest a modest increased risk in overall malignancy, as previously observed. Patients with RA continued to show an increased risk of lymphoma and lung cancer compared with the general population. Overall, SIR estimates for colorectal and breast cancers continued to show a decrease in risk, whereas cervical cancer, prostate cancer and melanoma appeared to show no consistent trend in risk among patients with RA compared with the general population.ConclusionsThe additional data evaluated here are consistent with previously reported data. Patients with RA are at an increased risk of lung and lymphoma malignancies compared with the general population. Quantifying differences in malignancy rates between non-biologic and biologic DMARD-treated patients with RA may further highlight which malignancies may be related to treatment rather than to the underlying disease.
Abstract. In this review, the use of x-ray computed tomography (XCT) is examined, identifying the requirement for volumetric dimensional measurements in industrial verification of additively manufactured (AM) parts. The XCT technology and AM processes are summarised, and their historical use is documented. The use of XCT and AM as tools for medical reverse engineering is discussed, and the transition of XCT from a tool used solely for imaging to a vital metrological instrument is documented. The current states of the combined technologies are then examined in detail, separated into porosity measurements and general dimensional measurements. In the conclusions of this review, the limitation of resolution on improvement of porosity measurements and the lack of research regarding the measurement of surface texture are identified as the primary barriers to ongoing adoption of XCT in AM. The limitations of both AM and XCT regarding slow speeds and high costs, when compared to other manufacturing and measurement techniques, are also noted as general barriers to continued adoption of XCT and AM.
Fiber waviness is one of the most significant defects that occurs in composites due to the severe knockdown in mechanical properties that it causes. This paper investigates the mechanisms for the generation of fiber path defects during processing of composites prepreg materials and proposes new predictive numerical models. A key focus of the work was on thick sections, where consolidation of the ply stack leads to out of plane ply movement. This deformation can either directly lead to fiber waviness or can cause excess fiber length in a ply that in turn leads to the formation of wrinkles. The novel predictive model, built on extensive characterization of prepregs in small-scale compaction tests, was implemented in the finite element software ABAQUS as a bespoke user-defined material. A number of industrially relevant case studies were investigated to demonstrate the formation of defects in typical component features. The validated numerical model was used to extend the understanding gained from manufacturing trials to isolate the influence of various material, geometric, and process parameters on defect formation.
To investigate the reliability of different methods of quantifying retinal ganglion cells (RGCs) in rat retinal sections and wholemounts from eyes with either intact optic nerves or those axotomised after optic nerve crush (ONC). Adult rats received a unilateral ONC and after 21 days the numbers of Brn3a+, βIII-tubulin+ and Islet-1+ RGCs were quantified in either retinal radial sections or wholemounts in which FluoroGold (FG) was injected 48 h before harvesting. Phenotypic antibody markers were used to distinguish RGCs from astrocytes, macrophages/microglia and amacrine cells. In wholemounted retinae, counts of FG+ and Brn3a+ RGCs were of similar magnitude in eyes with intact optic nerves and were similarly reduced after ONC. Larger differences in RGC number were detected between intact and ONC groups when images were taken closer to the optic nerve head. In radial sections, Brn3a did not stain astrocytes, macrophages/microglia or amacrine cells, whereas βIII-tubulin and Islet-1 did localize to amacrine cells as well as RGCs. The numbers of βIII-tubulin+ RGCs was greater than Brn3a+ RGCs, both in retinae from eyes with intact optic nerves and eyes 21 days after ONC. Islet-1 staining also overestimated the number of RGCs compared to Brn3a, but only after ONC. Estimates of RGC loss were similar in Brn3a-stained radial retinal sections compared to both Brn3a-stained wholemounts and retinal wholemounts in which RGCs were backfilled with FG, with sections having the added advantage of reducing experimental animal usage.
We present the results of large scale, three-dimensional magneto-hydrodynamics simulations of disc-winds for different initial magnetic field configurations. The jets are followed from the source to 90 AU scale, which covers several pixels of HST images of nearby protostellar jets. Our simulations show that jets are heated along their length by many shocks. We compute the emission lines that are produced, and find excellent agreement with observations. The jet width is found to be between 20 and 30 AU while the maximum velocities perpendicular to the jet is found to be up to above 100km/s. The initially less open magnetic field configuration simulations results in a wider, two-component jet; a cylindrically shaped outer jet surrounding a narrow and much faster, inner jet. These simulations preserve the underlying Keplerian rotation profile of the inner jet to large distances from the source. However, for the initially most open magnetic field configuration the kink mode creates a narrow corkscrewlike jet without a clear Keplerian rotation profile and even regions where we observe rotation opposite to the disc (counter-rotating). The RW Aur jet is narrow, indicating that the disc field in that case is very open meaning the jet can contain a counterrotating component that we suggests explains why observations of rotation in this jet has given confusing results. Thus magnetized disc winds from underlying Keplerian discs can develop rotation profiles far down the jet that are not Keplerian.
DNA double-strand breaks are a feature of many acute and long-term neurological disorders, including neurodegeneration, following neurotrauma and after stroke. Persistent activation of the DNA damage response in response to double-strand breaks contributes to neural dysfunction and pathology as it can force post-mitotic neurons to re-enter the cell cycle leading to senescence or apoptosis. Mature, non-dividing neurons may tolerate low levels of DNA damage, in which case muting the DNA damage response might be neuroprotective. Here, we show that attenuating the DNA damage response by targeting the meiotic recombination 11, Rad50, Nijmegen breakage syndrome 1 complex, which is involved in double-strand break recognition, is neuroprotective in three neurodegeneration models in Drosophila and prevents Aβ1-42-induced loss of synapses in embryonic hippocampal neurons. Attenuating the DNA damage response after optic nerve injury is also neuroprotective to retinal ganglion cells and promotes dramatic regeneration of their neurites both in vitro and in vivo. Dorsal root ganglion neurons similarly regenerate when the DNA damage response is targeted in vitro and in vivo and this strategy also induces significant restoration of lost function after spinal cord injury. We conclude that muting the DNA damage response in the nervous system is neuroprotective in multiple neurological disorders. Our results point to new therapies to maintain or repair the nervous system.
Constructing activity budgets for marine animals when they are at sea and cannot be directly observed is challenging, but recent advances in bio-logging technology offer solutions to this problem. Accelerometers can potentially identify a wide range of behaviours for animals based on unique patterns of acceleration. However, when analysing data derived from accelerometers, there are many statistical techniques available which when applied to different data sets produce different classification accuracies. We investigated a selection of supervised machine learning methods for interpreting behavioural data from captive otariids (fur seals and sea lions). We conducted controlled experiments with 12 seals, where their behaviours were filmed while they were wearing 3-axis accelerometers. From video we identified 26 behaviours that could be grouped into one of four categories (foraging, resting, travelling and grooming) representing key behaviour states for wild seals. We used data from 10 seals to train four predictive classification models: stochastic gradient boosting (GBM), random forests, support vector machine using four different kernels and a baseline model: penalised logistic regression. We then took the best parameters from each model and cross-validated the results on the two seals unseen so far. We also investigated the influence of feature statistics (describing some characteristic of the seal), testing the models both with and without these. Cross-validation accuracies were lower than training accuracy, but the SVM with a polynomial kernel was still able to classify seal behaviour with high accuracy (>70%). Adding feature statistics improved accuracies across all models tested. Most categories of behaviour -resting, grooming and feeding—were all predicted with reasonable accuracy (52–81%) by the SVM while travelling was poorly categorised (31–41%). These results show that model selection is important when classifying behaviour and that by using animal characteristics we can strengthen the overall accuracy.
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