Lincoln University entomological expedition to Pitt Island

The expedition had two objectives: 1. To search for the Pitt Island longhorn beetle, Xylotoles costatus and determine its distribution, abundance and conservation status. 2. To undertake general entomological survey work, particularly in the orders Coleoptera, Diptera, Lepidoptera and Hymenoptera by using trapping methods not previously used on Pitt Island

The challenge of overdiagnosis begins with its definition

Overdiagnosis means different things to different people. S M Carter and colleagues argue that we should use a broad term such as too much medicine for advocacy and develop precise, case by case definitions of overdiagnosis for research and clinical purposes The implicit social contract underpinning healthcare is that it will reduce illness and preventable death and improve quality of life. But sometimes these promises are not delivered. Sometimes health services take people who don’t need intervention, subject them to tests, label them as sick or at risk, provide unnecessary treatments, tell them to live differently, or insist on monitoring them regularly.1 These interventions don’t improve things for people; they produce complications or illness, reduce quality of life, or even cause premature death. Active health intervention is not always a good thing: it can be “too much medicine,” or produce what is often called overdiagnosis. Although the concept of overdiagnosis has been described in the literature for nearly 50 years in relation to cancer screening,2 3 it was Welch and colleagues’ 2011 book, Overdiagnosed: Making People Sick in the Pursuit of Health, that popularised the term.4 Overdiagnosis is now an acknowledged problem for patients, clinicians, researchers, and policymakers; it is discussed in journals5 6 7 and at specialist conferences8 and addressed through policy and practice initiatives.9 10 11 There is, however, no formal, agreed definition of overdiagnosis. Rather, the word has become a banner under which disparate people with similar general concerns can unite. This vagueness and breadth allows the appearance of unity but does not serve the more exacting demands of research and healthcare. Here we examine the meanings of overdiagnosis more closely and discuss related challenges for healthcare professionals, patients, and researchers. If overdiagnosis is to be understood and mitigated, the broad concept should be subdivided into different problems and its ethical dimensions better acknowledged.NHMR

Results of an international drug testing service for cryptomarket users

Introduction: User surveys indicate that expectations of higher drug purity are a key reason for cryptomarket use. In 2014-2015, Spain's NGO Energy Control conducted a 1-year pilot project to provide a testing service to cryptomarket drug users using the Transnational European Drug Information (TEDI) guidelines. In this paper, we present content and purity data from the trial. Methods: 219 samples were analyzed by gas chromatography associated with mass spectrometry (GC/MS). Users were asked to report what substance they allegedly purchased. Results: 40 different advertised substances were reported, although 77.6% were common recreational drugs (cocaine, MDMA, amphetamines, LSD, ketamine, cannabis). In 200 samples (91.3%), the main result of analysis matched the advertised substance. Where the advertised compound was detected, purity levels (m. ±. SD) were: cocaine 71.6. ±. 19.4%; MDMA (crystal) 88.3. ±. 1.4%; MDMA (pills) 133.3. ±. 38.4. mg; Amphetamine (speed) 51.3. ±. 33.9%; LSD 123.6. ±. 40.5. µg; Cannabis resin THC: 16.5. ±. 7.5% CBD: 3.4. ±. 1.5%; Ketamine 71.3. ±. 38.4%. 39.8% of cocaine samples contained the adulterant levamisole (11.6. ±. 8%). No adulterants were found in MDMA and LSD samples. Discussion: The largest collection of test results from drug samples delivered from cryptomarkets are reported in this study. Most substances contained the advertised ingredient and most samples were of high purity. The representativeness of these results is unknown

NiftyNet: a deep-learning platform for medical imaging

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this application requires substantial implementation effort. Thus, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on TensorFlow and supports TensorBoard visualization of 2D and 3D images and computational graphs by default. We present 3 illustrative medical image analysis applications built using NiftyNet: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. NiftyNet enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new applications.Comment: Wenqi Li and Eli Gibson contributed equally to this work. M. Jorge Cardoso and Tom Vercauteren contributed equally to this work. 26 pages, 6 figures; Update includes additional applications, updated author list and formatting for journal submissio

Technical Note: Error metrics for estimating the accuracy of needle/instrument placement during transperineal MR/US-guided prostate interventions

Purpose: Image-guided systems that fuse magnetic resonance imaging (MRI) with three-dimensional (3D) ultrasound (US) images for performing targeted prostate needle biopsy and minimally-invasive treatments for prostate cancer are of increasing clinical interest. To date, a wide range of different accuracy estimation procedures and error metrics have been reported, which makes comparing the performance of different systems difficult. Methods: A set of 9 measures are presented to assess the accuracy of MRI-US image registration, needle positioning, needle guidance, and overall system error, with the aim of providing a methodology for estimating the accuracy of instrument placement using a MR/US-guided transperineal approach. Results: Using the SmartTarget fusion system, an MRI-US image alignment error was determined to be 2.0±1.0 mm (mean ± SD), and an overall system instrument targeting error of 3.0±1.2 mm. Three needle deployments for each target phantom lesion was found to result in a 100% lesion hit rate and a median predicted cancer core length of 5.2 mm. Conclusions: The application of a comprehensive, unbiased validation assessment for MR/TRUS guided systems can provide useful information on system performance for quality assurance and system comparison. Furthermore, such an analysis can be helpful in identifying relationships between these errors, providing insight into the technical behaviour of these systems

Use of QSARs in international decision-making frameworks to predict health effects of chemical substances

This article is a review of the use of quantitative (and qualitative) structure-activity relationships (QSARs and SARs) by regulatory agencies and authorities to predict acute toxicity, mutagenicity, carcinogenicity, and other health effects. A number of SAR and QSAR applications, by regulatory agencies and authorities, are reviewed. These include the use of simple QSAR analyses, as well as the use of multivariate QSARs, and a number of different expert system approaches

Prostate Radiofrequency Focal Ablation (ProRAFT) Trial: A Prospective Development Study Evaluating a Bipolar Radiofrequency Device to Treat Prostate Cancer

PURPOSE: To determine early efficacy of bipolar radiofrequency ablation with a coil design (bRFA) for focal ablation of clinically significant localised prostate cancer (sPCa)visible at mpMRI. MATERIAL AND METHODS: A prospective IDEAL phase 2 development study (NCT02294903) recruited treatment naive patients with a single focus of localised sPCa (Gleason 7 or 4 mm or more of Gleason 6) concordant with a lesion visible on multi-parametric MRI. Intervention was a focal ablation with a bRFA system (Encage®, Trod Medical) encompassing the lesion and a predefined margin using nonrigid MRI-ultrasound fusion. Primary outcome was the proportion of men with absence of sPCa on biopsy at 6 months. Trial follow up comprised serum PSA, mpMRI at 1 week, 6 and 12 months post ablation. Validated patient reported outcome measures (PROMs) for urinary, erectile and bowel functions and adverse events monitoring system were used. Analyses were done on a per-protocol basis. RESULTS: 20 of 21 patients recruited received the intervention. Baseline characteristics were a median age of 66 years (IQR 63-69), pre-operative median PSA of 7.9 ng/ml (5.3-9.6), 18 (90%) had Gleason 7 with median maximum cancer of 7 mm (IQR 5-10) for a median 2.8 cc mpMRI lesions (IQR 1.4-4.8). Targeted biopsy of the treated area (median number of cores=6, IQR 5-8) showed absence of sPCa in 16/20 men (80%), concordant with mpMRI. There was a low profile of side effects at PROMs analysis and no serious adverse events. CONCLUSIONS: Focal therapy of sPCa associated with an MRI lesion using bRFA showed early efficacy to ablate cancer with low rates of genitourinary and rectal side-effects

The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010

We have analysed the sensitivity of the tropospheric ozone distribution over North America and the North Atlantic to boreal biomass burning emissions during the summer of 2010 using the GEOS-Chem 3-D global tropospheric chemical transport model and observations from in situ and satellite instruments. We show that the model ozone distribution is consistent with observations from the Pico Mountain Observatory in the Azores, ozonesondes across Canada, and the Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Instrument (IASI) satellite instruments. Mean biases between the model and observed ozone mixing ratio in the free troposphere were less than 10 ppbv. We used the adjoint of GEOS-Chem to show the model ozone distribution in the free troposphere over Maritime Canada is largely sensitive to NO<sub>x</sub> emissions from biomass burning sources in Central Canada, lightning sources in the central US, and anthropogenic sources in the eastern US and south-eastern Canada. We also used the adjoint of GEOS-Chem to evaluate the Fire Locating And Monitoring of Burning Emissions (FLAMBE) inventory through assimilation of CO observations from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. The CO inversion showed that, on average, the FLAMBE emissions needed to be reduced to 89% of their original values, with scaling factors ranging from 12% to 102%, to fit the MOPITT observations in the boreal regions. Applying the CO scaling factors to all species emitted from boreal biomass burning sources led to a decrease of the model tropospheric distributions of CO, PAN, and NO<sub>x</sub> by as much as −20 ppbv, −50 pptv, and −20 pptv respectively. The modification of the biomass burning emission estimates reduced the model ozone distribution by approximately −3 ppbv (−8%) and on average improved the agreement of the model ozone distribution compared to the observations throughout the free troposphere, reducing the mean model bias from 5.5 to 4.0 ppbv for the Pico Mountain Observatory, 3.0 to 0.9 ppbv for ozonesondes, 2.0 to 0.9 ppbv for TES, and 2.8 to 1.4 ppbv for IASI

The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010

We have analysed the sensitivity of the tropospheric ozone distribution over North America and the North Atlantic to boreal biomass burning emissions during the summer of 2010 using the GEOS-Chem 3-D global tropospheric chemical transport model and observations from in situ and satellite instruments. We show that the model ozone distribution is consistent with observations from the Pico Mountain Observatory in the Azores, ozonesondes across Canada, and the Tropospheric Emission Spectrometer (TES) and Infrared Atmospheric Sounding Instrument (IASI) satellite instruments. Mean biases between the model and observed ozone mixing ratio in the free troposphere were less than 10 ppbv. We used the adjoint of GEOS-Chem to show the model ozone distribution in the free troposphere over Maritime Canada is largely sensitive to NOx emissions from biomass burning sources in Central Canada, lightning sources in the central US, and anthropogenic sources in the eastern US and south-eastern Canada. We also used the adjoint of GEOS-Chem to evaluate the Fire Locating And Monitoring of Burning Emissions (FLAMBE) inventory through assimilation of CO observations from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. The CO inversion showed that, on average, the FLAMBE emissions needed to be reduced to 89% of their original values, with scaling factors ranging from 12% to 102%, to fit the MOPITT observations in the boreal regions. Applying the CO scaling factors to all species emitted from boreal biomass burning sources led to a decrease of the model tropospheric distributions of CO, PAN, and NOx by as much as -20 ppbv, -50 pptv, and -20 pptv respectively. The modification of the biomass burning emission estimates reduced the model ozone distribution by approximately -3 ppbv (-8%) and on average improved the agreement of the model ozone distribution compared to the observations throughout the free troposphere, reducing the mean model bias from 5.5 to 4.0 ppbv for the Pico Mountain Observatory, 3.0 to 0.9 ppbv for ozonesondes, 2.0 to 0.9 ppbv for TES, and 2.8 to 1.4 ppbv for IASI

ICU-acquired pneumonia in immunosuppressed patients with acute hypoxemic respiratory failure: A post-hoc analysis of a prospective international cohort study

Objective: Intensive Care Units (ICU) acquired Pneumonia (ICU-AP) is one of the most frequent nosocomial infections in critically ill patients. Our aim was to determine the effects of having an ICU-AP in immunosuppressed patients with acute hypoxemic respiratory failure. Design: Post-hoc analysis of a multinational, prospective cohort study in 16 countries. Settings: ICU. Patients: Immunosuppressed patients with acute hypoxemic respiratory failure. Intervention: None. Measurements and main results: The original cohort had 1611 and in this post-hoc analysis a total of 1512 patients with available data on hospital mortality and occurrence of ICU-AP were included. ICU-AP occurred in 158 patients (10.4%). Hospital mortality was higher in patients with ICU-AP (14.8% vs. 7.1% p < 0.001). After adjustment for confounders and centre effect, use of vasopressors (Odds Ratio (OR) 2.22; 95%CI 1.46-.39) and invasive me-chanical ventilation at day 1 (OR 2.12 vs. high flow oxygen; 95%CI 1.07-4.20) were associated with increased risk of ICU-AP while female gender (OR 0.63; 95%CI 0.43-94) and chronic kidney disease (OR 0.43; 95%CI 0.22-0.88) were associated with decreased risk of ICU-AP. After adjustment for confounders and centre effect, ICU-AP was independently associated with mortality (Hazard Ratio 1.48; 95%CI 14.-1.91; P = 0.003). Conclusions: The attributable mortality of ICU-AP has been repetitively questioned in immunosuppressed pa-tients with acute respiratory failure. This manuscript found that ICU-AP represents an independent risk factor for hospital mortality.(c) 2020 Elsevier Inc. All rights reserved.Peer reviewe