Prognostic Molecular Markers of Response to Radiotherapy in Rectal Cancer

Colorectal cancer (CRC) is the second most deadly cancer globally, and 30% of these cancers occur in the rectum. The primary treatment for CRC is surgery, often radiotherapy with adjuvant chemotherapy is used before or following surgical resection. Treatment carries with it a high cost and side effect burden while response rates remain unpredictable. Approximately 20% of patients have total tumour regression post chemoradiotherapy; however, most patients receive only partial or no benefit from treatment. The ability to predict which patients would benefit from standard treatment and those who should be directed to an alternative treatment or an accelerated pathway to surgery would potentially avoid lengthy and costly treatments that may only cause side effects for patients, improving survival rates and quality of life. In this study, the microbiome, immune cells and patient gene expression were evaluated for their use as predictive biomarkers for response to chemoradiotherapy in rectal cancer patients. Tumour and adjacent normal tissue biopsies were taken before treatment and had DNA and RNA extracted and sequenced. First, the methodology for analysing microbiomes via shotgun sequencing data was evaluated and improved, increasing taxonomic assignment accuracy by 11% and potentially decreasing analysis time more than nine-fold. Secondly, the sequencing technologies, Oxford Nanopore, 16S rRNA and RNA-sequencing, were evaluated for their ability to assess the microbiome. The results demonstrated that platforms had concordance with one another; however, this was reduced at the species level. Third, microbial transcription was used to assess rectal cancer microbiomes, correlating them with response rates. The results showed that microbial diversity did not contribute to radiotherapy response, but that individual microbes may influence response. It was hypothesised that species such as Hungatella hathewayi, Fusobacterium nucleatum, Butyricimonas faecalis, Alistipes finegoldii, Bacteroides thetaiotaomicron, and B. fragilis may contribute to tumour regression by modulating metabolism and immune responses. Third, the abundance of infiltrating immune cells was predicted using RNA-Sequencing data. Analysis indicated that the abundance of M1 macrophages and resting mast cells were correlated with response, while microbial transcription was correlated with the abundance of allergic and anti-tumour effector cells, as well as antigen-presenting cells. It was hypothesised that the microbiome might modulate anti-tumour immune responses directly, and indirectly by altering the tumour microenvironment. Microbes may help maintain a population of anti-tumour effector and antigen-presenting cells for tumour-antigen presentation during tumour cell death and neo-antigen uptake, which may be otherwise exhausted by targeting aspects of the inflammatory tumour microenvironment (i.e., lipid phagocytosis, anti-bacterial and allergic responses). Lastly, machine-learning was employed to establish a panel of molecular biomarkers predictive of response, including microbial transcription, immune cells and gene expression. The final model demonstrated the ability to predict response with a 7% overall error rate, and that predicting response relied mostly on normal and tumour tissue gene expression, and tumour infiltrating immune cells. This study provides a panel of prognostic biomarkers which could be utilised to predict patient response. Additionally, it provides evidence for microbial-immune interactions that could be manipulated to enhance treatment and increase response rates

Sher 25: pulsating but apparently alone

The blue supergiant Sher25 is surrounded by an asymmetric, hourglass-shaped circumstellar nebula, which shows similarities to the triple-ring structure seen around SN1987A. From optical spectroscopy over six consecutive nights, we detect periodic radial velocity variations in the stellar spectrum of Sher25 with a peak-to-peak amplitude of ~12 km/s on a timescale of about 6 days, confirming the tentative detec-tion of similar variations by Hendry et al. From consideration of the amplitude and timescale of the signal, coupled with observed line profile variations, we propose that the physical origin of these variations is related to pulsations in the stellar atmosphere, rejecting the previous hypothesis of a massive, short-period binary companion. The radial velocities of two other blue supergiants with similar bipolar nebulae, SBW1 and HD 168625, were also monitored over the course of six nights, but these did not display any significant radial velocity variations.Comment: 9 pages, 7 figures. Accepted for publication in MNRA

The Need For Speed: Rapid Refitting Techniques for Bayesian Spectral Characterization of the Gravitational Wave Background Using PTAs

Current pulsar timing array (PTA) techniques for characterizing the spectrum of a nanohertz-frequency stochastic gravitational-wave background (SGWB) begin at the stage of timing data. This can be slow and memory intensive with computational scaling that will worsen PTA analysis times as more pulsars and observations are added. Given recent evidence for a common-spectrum process in PTA data sets and the need to understand present and future PTA capabilities to characterize the SGWB through large-scale simulations, we have developed efficient and rapid approaches that operate on intermediate SGWB analysis products. These methods refit SGWB spectral models to previously-computed Bayesian posterior estimations of the timing power spectra. We test our new methods on simulated PTA data sets and the NANOGrav $12.5$-year data set, where in the latter our refit posterior achieves a Hellinger distance from the current full production-level pipeline that is $\lesssim 0.1$. Our methods are $\sim10^2$--$10^4$ times faster than the production-level likelihood and scale sub-linearly as a PTA is expanded with new pulsars or observations. Our methods also demonstrate that SGWB spectral characterization in PTA data sets is driven by the longest-timed pulsars with the best-measured power spectral densities which is not necessarily the case for SGWB detection that is predicated on correlating many pulsars. Indeed, the common-process spectral properties found in the NANOGrav $12.5$-year data set are given by analyzing only the $\sim10$ longest-timed pulsars out of the full $45$ pulsar array, and we find that the ``shallowing'' of the common-process power-law model occurs when gravitational-wave frequencies higher than $\sim 50$~nanohertz are included. The implementation of our methods is openly available as a software suite to allow fast and flexible PTA SGWB spectral characterization and model selection.Comment: 19 pages, 12 figures. Submitting to Physical Review

Guilt, shame and expressed emotion in carers of people with long-term mental health difficulties:a systematic review

Expressed emotion (EE) is a global index of familial emotional climate, whose primary components are emotional over-involvement (EOI) and critical comments (CC)/hostility. There is a strong theoretical rationale for hypothesising that carers’ guilt and shame may be differentially associated with their EOI and CC/hostility respectively. This systematic review investigates the magnitude of these theorised associations in carers of people with long-term mental health difficulties. Electronic searches (conducted in May 2016 across Medline, CINAHL, Embase, PsycINFO and ProQuest) were supplemented with iterative hand searches. Ten papers, reporting data from eight studies, were included. Risk of bias was assessed using a standardised checklist. Relevant data were extracted and synthesised narratively. EOI was positively associated with both guilt and shame, whereas CC/hostility was positively associated with shame. The strength of associations varied depending on whether or not guilt and shame were assessed within the context of the caring relationship. Based on these data, an argument can be made for the refinement, development and evaluation of systemic and individual interventions designed to target carers’ guilt and shame. However, more research is needed to clarify the strength of these associations and their direction of effect before firm conclusions can be drawn

Wheelchair Modification

This document outlines the design process for a wheelchair modification. This wheelchair modification is the Senior Capstone Project for five undergraduate students studying Biomedical Engineering at The University of Akron, Team 14. The team was directed to compose a team name, which was chosen to be EnGenious Design Solutions (EDS). The project was provided by Dr. James Keszenheimer who is a professor at The University of Akron. This document focuses on the project results as well as business conclusions

Causes of prehospital misinterpretations of ST elevation myocardial infarction

Objectives: To determine the causes of software misinterpretation of ST elevation myocardial infarction (STEMI) compared to clinically identified STEMI to identify opportunities to improve prehospital STEMI identification. Methods: We compared ECGs acquired from July 2011 through June 2012 using the LIFEPAK 15 on adult patients transported by the Los Angeles Fire Department. Cases included patients ≥18 years who received a prehospital ECG. Software interpretation of the ECG (STEMI or not) was compared with data in the regional EMS registry to classify the interpretation as true positive (TP), true negative (TN), false positive (FP), or false negative (FN). For cases where classification was not possible using registry data, 3 blinded cardiologists interpreted the ECG. Each discordance was subsequently reviewed to determine the likely cause of misclassification. The cardiologists independently reviewed a sample of these discordant ECGs and the causes of misclassification were updated in an iterative fashion. Results: Of 44,611 cases, 50% were male (median age 65; inter-quartile range 52–80). Cases were classified as 482 (1.1%) TP, 711 (1.6%) FP, 43371 (97.2%) TN, and 47 (0.11%) FN. Of the 711 classified as FP, 126 (18%) were considered appropriate for, though did not undergo, emergent coronary angiography, because the ECG showed definite (52 cases) or borderline (65 cases) ischemic ST elevation, a STEMI equivalent (5 cases) or ST-elevation due to vasospasm (4 cases). The sensitivity was 92.8% [95% CI 90.6, 94.7%] and the specificity 98.7% [95% CI 98.6, 98.8%]. The leading causes of FP were ECG artifact (20%), early repolarization (16%), probable pericarditis/myocarditis (13%), indeterminate (12%), left ventricular hypertrophy (8%), and right bundle branch block (5%). There were 18 additional reasons for FP interpretation (<4% each). The leading causes of FN were borderline ST-segment elevations less than the algorithm threshold (40%) and tall T waves reducing the ST/T ratio below threshold (15%). There were 11 additional reasons for FN interpretation occurring ≤3 times each. Conclusion: The leading causes of FP automated interpretation of STEMI were ECG artifact and non-ischemic causes of ST-segment elevation. FN were rare and were related to ST-segment elevation or ST/T ratio that did not meet the software algorithm threshold

A Parallelized Bayesian Approach To Accelerated Gravitational-Wave Background Characterization

The characterization of nanohertz-frequency gravitational waves (GWs) with pulsar-timing arrays requires a continual expansion of datasets and monitored pulsars. Whereas detection of the stochastic GW background is predicated on measuring a distinctive pattern of inter-pulsar correlations, characterizing the background's spectrum is driven by information encoded in the power spectra of the individual pulsars' time series. We propose a new technique for rapid Bayesian characterization of the stochastic GW background that is fully parallelized over pulsar datasets. This Factorized Likelihood (FL) technique empowers a modular approach to parameter estimation of the GW background, multi-stage model selection of a spectrally-common stochastic process and quadrupolar inter-pulsar correlations, and statistical cross-validation of measured signals between independent pulsar sub-arrays. We demonstrate the equivalence of this technique's efficacy with the full pulsar-timing array likelihood, yet at a fraction of the required time. Our technique is fast, easily implemented, and trivially allows for new data and pulsars to be combined with legacy datasets without re-analysis of the latter.Comment: 14 pages, 6 figures. Matches version accepted by PR

Lower Levels of Cervicovaginal Tryptophan are Associated with Natural Clearance of Chlamydia in Women

Chlamydiatrachomatis (Ct) infection causes significant morbidity. In vitro studies demonstrate that Ct growth inhibition occurs by interferon-gamma (IFN-γ)–mediated depletion of intracellular tryptophan, and some Ct strains utilize extracellular indole to restore tryptophan levels. Whether tryptophan levels are associated with Ct infection clearance in humans remains unknown. We evaluated tryptophan, indole, and IFN-γ levels in cervicovaginal lavages from women with either naturally cleared or persisting Ct infection. Women who cleared infection had significantly lower tryptophan levels and trended toward lower IFN-γ levels compared to women with persisting infection. Due to its volatility, indole was not measurable in either group