Notes

[Whiplash injury in the cervical spine].
The antinuclear antibody (ANA) test is a screening test for systemic autoimmune rheumatic disease (SARD). We hypothesised that the presence of anti-DFS70 in ANA-positive samples was associated with a false-positive ANA test and negatively associated with SARD.

A retrospective analysis of patient samples received for ANA testing from 1 January 2016 to 30 June 2016 was performed. Patient samples underwent ANA testing via indirect immunofluorescence method and anti-DFS70 testing using enzyme-linked immunosorbent assay.

Among a total of 645 ANA-positive samples, the majority (41.7%) was positive at a titre of 180. The commonest nuclear staining pattern was speckled (65.5%). Only 9.5% of ANA-positive patients were diagnosed with SARD. Anti-DFS70 was found to be present in 10.0% of ANA-positive patients. The majority (51/59 patients, 86.4%) of patients did not have SARD. Seven patients had positive ANA titre > 1640, presence of anti-double stranded DNA and/or anti-Ro60. The presence of anti-DFS70 in ANA-positive patients was not associated with the absence of SARD (Fisher's exact test, p = 0.245).

The presence of anti-DFS70 was associated with a false-positive ANA test in 8.6% of our patients. Anti-DFS70 was not associated with the absence of SARD.
The presence of anti-DFS70 was associated with a false-positive ANA test in 8.6% of our patients. Anti-DFS70 was not associated with the absence of SARD.Raine (2019) reviewed previous research on the neural correlates of antisocial, violent, and psychopathic behavior based on previous studies of neuroscience of morality. The author identified neural circuitries associated with the aforementioned types of antisocial behaviors. However, in the review, Raine acknowledged a limitation in his arguments, the lack of evidence supporting the presence of the neural circuitries. In this correspondence, I intend to show that some of his concerns, particularly those about the insula and cingulate cortex, can be addressed with additional evidence from recent neuroimaging research. find more In addition, I will propose that the additional evidence can also provide some insights about how to design future neuroimaging studies to examine the functionality of the striatum in the circuitries.Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with a number of popular R packages for single-cell expression, such as Seurat. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.In general, National Football League (NFL) players tend to live longer than the general population. However, little information exists about the long-term mortality risk in this population. Frequent, yet mild, head trauma may be associated with early mortality in this group of elite athletes. Therefore, career playing statistics can be used as a proxy for frequent head trauma. Using data from Pro Football Reference, we analyzed the association between age-at-death, position, and NFL seasons-played among 6,408 NFL players that were deceased as of July 1, 2018. The linear regression model allowing for a healthy worker effect demonstrated the best fit statistics (F-statistic = 9.95, p-value = 0.0016). The overall association of age-at-death and seasons-played is positive beginning at the 10.75 and 10.64 seasons-played point in our two models that feature seasons-played and seasons-played squared as explanatory variables. Previous research that does not account for this survivorship bias/healthy worker effect may not adequately describe mortality risk among NFL players.Background Diseases such as hypertrophic cardiomyopathy (HCM) can lead to severe outcomes including sudden death. The generation of human induced pluripotent stem cell (hiPSC) reporter lines can be useful for disease modelling and drug screening by providing physiologically relevant in vitro models of disease. The AAVS1 locus is cited as a safe harbour that is permissive for stable transgene expression, and hence is favoured for creating gene targeted reporter lines. Methods We generated hiPSC reporters using a plasmid-based CRISPR/Cas9 nickase strategy. The first intron of PPP1R12C, the AAVS1 locus, was targeted with constructs expressing a genetically encoded calcium indicator (R-GECO1.0) or HOXA9-T2A-mScarlet reporter under the control of a pCAG or inducible pTRE promoter, respectively. Transgene expression was compared between clones before, during and/or after directed differentiation to mesodermal lineages. Results Successful targeting to AAVS1 was confirmed by PCR and sequencing. Of 24 hiPSC clones targene silencing requires careful attention by researchers seeking robust reporter gene expression.
Indirect imaging problems in biomedical optics generally require repeated evaluation of forward models of radiative transport, for which Monte Carlo is accurate yet computationally costly. We develop an approach to reduce this bottleneck, which has significant implications for quantitative tomographic imaging in a variety of medical and industrial applications.

Our aim is to enable computationally efficient image reconstruction in (hybrid) diffuse optical modalities using stochastic forward models.

Using Monte Carlo, we compute a fully stochastic gradient of an objective function for a given imaging problem. Leveraging techniques from the machine learning community, we then adaptively control the accuracy of this gradient throughout the iterative inversion scheme to substantially reduce computational resources at each step.

For example problems of quantitative photoacoustic tomography and ultrasound-modulated optical tomography, we demonstrate that solutions are attainable using a total computational expense that is comparable to (or less than) that which is required for a single high-accuracy forward run of the same Monte Carlo model.
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