Ensemble candidate classification for the LOTAAS pulsar survey

One of the biggest challenges arising from modern large-scale pulsar surveys is the number of candidates generated. Here, we implemented several improvements to the machine learning (ML) classifier previously used by the LOFAR Tied-Array All-Sky Survey (LOTAAS) to look for new pulsars via filtering the candidates obtained during periodicity searches. To assist the ML algorithm, we have introduced new features which capture the frequency and time evolution of the signal and improved the signal-to-noise calculation accounting for broad profiles. We enhanced the ML classifier by including a third class characterizing RFI instances, allowing candidates arising from RFI to be isolated, reducing the false positive return rate. We also introduced a new training data set used by the ML algorithm that includes a large sample of pulsars misclassified by the previous classifier. Lastly, we developed an ensemble classifier comprised of five different Decision Trees. Taken together these updates improve the pulsar recall rate by 2.5 per cent, while also improving the ability to identify pulsars with wide pulse profiles, often misclassified by the previous classifier. The new ensemble classifier is also able to reduce the percentage of false positive candidates identified from each LOTAAS pointing from 2.5 per cent (∼500 candidates) to 1.1 per cent (∼220 candidates)

Single-pulse classifier for the LOFAR Tied-Array All-sky Survey

Searches for millisecond-duration, dispersed single pulses have become a standard tool used during radio pulsar surveys in the last decade. They have enabled the discovery of two new classes of sources: rotating radio transients and fast radio bursts. However, we are now in a regime where the sensitivity to single pulses in radio surveys is often limited more by the strong background of radio frequency interference (RFI, which can greatly increase the false-positive rate) than by the sensitivity of the telescope itself. To mitigate this problem, we introduce the Single-pulse Searcher (SPS). This is a new machine-learning classifier designed to identify astrophysical signals in a strong RFI environment, and optimized to process the large data volumes produced by the new generation of aperture array telescopes. It has been specifically developed for the LOFAR Tied-Array All-Sky Survey (LOTAAS), an ongoing survey for pulsars and fast radio transients in the northern hemisphere. During its development, SPS discovered seven new pulsars and blindly identified ˜80 known sources. The modular design of the software offers the possibility to easily adapt it to other studies with different instruments and characteristics. Indeed, SPS has already been used in other projects, e.g. to identify pulses from the fast radio burst source FRB 121102. The software development is complete and SPS is now being used to re-process all LOTAAS data collected to date

Pathways to diagnosis of non-small cell lung cancer: a descriptive cohort study

© 2019, Crown. Little has been published on the diagnostic and referral pathway for lung cancer in Australia. This study set out to quantify general practitioner (GP) and lung specialist attendance and diagnostic imaging in the lead-up to a diagnosis of non-small cell lung cancer (NSCLC) and identify common pathways to diagnosis in New South Wales (NSW), Australia. We used linked health data for participants of the 45 and Up Study (a NSW population-based cohort study) diagnosed with NSCLC between 2006 and 2012. Our main outcome measures were GP and specialist attendances, X-rays and computed tomography (CT) scans of the chest and lung cancer-related hospital admissions. Among our study cohort (N = 894), 60% (n = 536) had ≥4 GP attendances in the 3 months prior to diagnosis of NSCLC, 56% (n = 505) had GP-ordered imaging (chest X-ray or CT scan), 39% (N = 349) attended a respiratory physician and 11% (N = 102) attended a cardiothoracic surgeon. The two most common pathways to diagnosis, accounting for one in three people, included GP and lung specialist (respiratory physician or cardiothoracic surgeon) involvement. Overall, 25% of people (n = 223) had an emergency hospital admission. For 14% of people (N = 129), an emergency hospital admission was the only event identified on the pathway to diagnosis. We found little effect of remoteness of residence on access to services. This study identified a substantial proportion of people with NSCLC being diagnosed in an emergency setting. Further research is needed to establish whether there were barriers to the timely diagnosis of these cases

Cardiovascular risk in chronic myeloid leukaemia: A multidisciplinary consensus on screening and management

INTRODUCTION: Tyrosine kinase inhibitors (TKIs) have become the mainstay of treatment for chronic myeloid leukaemia (CML), but cardiovascular (CV) risk and exacerbation of underlying risk factors associated with TKIs have become widely debated. Real-world evidence reveals little application of CV risk factor screening or continued monitoring within UK CML management. This consensus paper presents practical recommendations to assist healthcare professionals in conducting CV screening/comorbidity management for patients receiving TKIs. METHODS: We conducted a multidisciplinary panel meeting and two iterative surveys involving 10 CML specialists: five haematologists, two cardio-oncologists, one vascular surgeon, one haemato-oncology pharmacist and one specialist nurse practitioner. RESULTS: The panel recommended that patients commencing second-/third-generation TKIs undergo formal CV risk assessment at baseline, with additional investigations and involvement of cardiologists/vascular surgeons for those with high CV risk. During treatment, patients should undergo CV monitoring, with the nature and frequency of testing dependent on TKI and baseline CV risk. For patients who develop CV adverse events, decision-making around TKI interruption, cessation or change should be multidisciplinary and balance CV and haematological risk. CONCLUSION: The panel anticipates these recommendations will support healthcare professionals in implementing CV risk screening and monitoring, broadly and consistently, and thereby help optimise TKI treatment for CML

Pathways to diagnosis of non-small cell lung cancer: a descriptive cohort study

Little has been published on the diagnostic and referral pathway for lung cancer in Australia. This study set out to quantify general practitioner (GP) and lung specialist attendance and diagnostic imaging in the lead-up to a diagnosis of non-small cell lung cancer (NSCLC) and identify common pathways to diagnosis in New South Wales (NSW), Australia. We used linked health data for participants of the 45 and Up Study (a NSW population-based cohort study) diagnosed with NSCLC between 2006 and 2012. Our main outcome measures were GP and specialist attendances, X-rays and computed tomography (CT) scans of the chest and lung cancer-related hospital admissions. Among our study cohort (N = 894), 60% (n = 536) had ≥4 GP attendances in the 3 months prior to diagnosis of NSCLC, 56% (n = 505) had GP-ordered imaging (chest X-ray or CT scan), 39% (N = 349) attended a respiratory physician and 11% (N = 102) attended a cardiothoracic surgeon. The two most common pathways to diagnosis, accounting for one in three people, included GP and lung specialist (respiratory physician or cardiothoracic surgeon) involvement. Overall, 25% of people (n = 223) had an emergency hospital admission. For 14% of people (N = 129), an emergency hospital admission was the only event identified on the pathway to diagnosis. We found little effect of remoteness of residence on access to services. This study identified a substantial proportion of people with NSCLC being diagnosed in an emergency setting. Further research is needed to establish whether there were barriers to the timely diagnosis of these cases

Pathways to diagnosis of non-small cell lung cancer : a descriptive cohort study

Little has been published on the diagnostic and referral pathway for lung cancer in Australia. This study set out to quantify general practitioner (GP) and lung specialist attendance and diagnostic imaging in the lead-up to a diagnosis of non-small cell lung cancer (NSCLC) and identify common pathways to diagnosis in New South Wales (NSW), Australia. We used linked health data for participants of the 45 and Up Study (a NSW population-based cohort study) diagnosed with NSCLC between 2006 and 2012. Our main outcome measures were GP and specialist attendances, X-rays and computed tomography (CT) scans of the chest and lung cancer-related hospital admissions. Among our study cohort (N = 894), 60% (n = 536) had ≥4 GP attendances in the 3 months prior to diagnosis of NSCLC, 56% (n = 505) had GP-ordered imaging (chest X-ray or CT scan), 39% (N = 349) attended a respiratory physician and 11% (N = 102) attended a cardiothoracic surgeon. The two most common pathways to diagnosis, accounting for one in three people, included GP and lung specialist (respiratory physician or cardiothoracic surgeon) involvement. Overall, 25% of people (n = 223) had an emergency hospital admission. For 14% of people (N = 129), an emergency hospital admission was the only event identified on the pathway to diagnosis. We found little effect of remoteness of residence on access to services. This study identified a substantial proportion of people with NSCLC being diagnosed in an emergency setting. Further research is needed to establish whether there were barriers to the timely diagnosis of these cases

Spermatogenesis and sertoli cell activity in mice lacking Sertoli cell receptors for follicle stimulating hormone and androgen

Spermatogenesis in the adult male depends on the action of FSH and androgen. Ablation of either hormone has deleterious effects on Sertoli cell function and the progression of germ cells through spermatogenesis. In this study we generated mice lacking both FSH receptors (FSHRKO) and androgen receptors on the Sertoli cell (SCARKO) to examine how FSH and androgen combine to regulate Sertoli cell function and spermatogenesis. Sertoli cell number in FSHRKO-SCARKO mice was reduced by about 50% but was not significantly different from FSHRKO mice. In contrast, total germ cell number in FSHRKO-SCARKO mice was reduced to 2% of control mice (and 20% of SCARKO mice) due to a failure to progress beyond early meiosis. Measurement of Sertoli cell-specific transcript levels showed that about a third were independent of hormonal action on the Sertoli cell, whereas others were predominantly androgen dependent or showed redundant control by FSH and androgen. Results show that FSH and androgen act through redundant, additive, and synergistic regulation of spermatogenesis and Sertoli cell activity. In addition, the Sertoli cell retains a significant capacity for activity, which is independent of direct hormonal regulation