Air pollution as a carcinogen.

Background Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. Results jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization - for example for performing pattern recognition analysis on multicentre/multi-manufacturer magnetic resonance spectroscopy data. Conclusions jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies

Demographics of dogs, cats, and rabbits attending veterinary practices in Great Britain as recorded in their electronic health records

Abstract Background Understanding the distribution and determinants of disease in animal populations must be underpinned by knowledge of animal demographics. For companion animals, these data have been difficult to collect because of the distributed nature of the companion animal veterinary industry. Here we describe key demographic features of a large veterinary-visiting pet population in Great Britain as recorded in electronic health records, and explore the association between a range of animal’s characteristics and socioeconomic factors. Results Electronic health records were captured by the Small Animal Veterinary Surveillance Network (SAVSNET), from 143 practices (329 sites) in Great Britain. Mixed logistic regression models were used to assess the association between socioeconomic factors and species and breed ownership, and preventative health care interventions. Dogs made up 64.8% of the veterinary-visiting population, with cats, rabbits and other species making up 30.3, 2.0 and 1.6% respectively. Compared to cats, dogs and rabbits were more likely to be purebred and younger. Neutering was more common in cats (77.0%) compared to dogs (57.1%) and rabbits (45.8%). The insurance and microchipping relative frequency was highest in dogs (27.9 and 53.1%, respectively). Dogs in the veterinary-visiting population belonging to owners living in least-deprived areas of Great Britain were more likely to be purebred, neutered, insured and microchipped. The same association was found for cats in England and for certain parameters in Wales and Scotland. Conclusions The differences we observed within these populations are likely to impact on the clinical diseases observed within individual veterinary practices that care for them. Based on this descriptive study, there is an indication that the population structures of companion animals co-vary with human and environmental factors such as the predicted socioeconomic level linked to the owner’s address. This ‘co-demographic’ information suggests that further studies of the relationship between human demographics and pet ownership are warranted

Repeatability of quantitative18F-FLT uptake measurements in solid tumors: an individual patient data multi-center meta-analysis

INTRODUCTION: 3'-deoxy-3'-[18F]fluorothymidine (18F-FLT) positron emission tomography (PET) provides a non-invasive method to assess cellular proliferation and response to antitumor therapy. Quantitative18F-FLT uptake metrics are being used for evaluation of proliferative response in investigational setting, however multi-center repeatability needs to be established. The aim of this study was to determine the repeatability of18F-FLT tumor uptake metrics by re-analyzing individual patient data from previously published reports using the same tumor segmentation method and repeatability metrics across cohorts. METHODS: A systematic search in PubMed, EMBASE.com and the Cochrane Library from inception-October 2016 yielded five18F-FLT repeatability cohorts in solid tumors.18F-FLT avid lesions were delineated using a 50% isocontour adapted for local background on test and retest scans. SUVmax, SUVmean, SUVpeak, proliferative volume and total lesion uptake (TLU) were calculated. Repeatability was assessed using the repeatability coefficient (RC = 1.96 × SD of test-retest differences), linear regression analysis, and the intra-class correlation coefficient (ICC). The impact of different lesion selection criteria was also evaluated. RESULTS: Images from four cohorts containing 30 patients with 52 lesions were obtained and analyzed (ten in breast cancer, nine in head and neck squamous cell carcinoma, and 33 in non-small cell lung cancer patients). A good correlation was found between test-retest data for all18F-FLT uptake metrics (R2 ≥ 0.93; ICC ≥ 0.96). Best repeatability was found for SUVpeak(RC: 23.1%), without significant differences in RC between different SUV metrics. Repeatability of proliferative volume (RC: 36.0%) and TLU (RC: 36.4%) was worse than SUV. Lesion selection methods based on SUVmax ≥ 4.0 improved the repeatability of volumetric metrics (RC: 26-28%), but did not affect the repeatability of SUV metrics. CONCLUSIONS: In multi-center studies, differences ≥ 25% in18F-FLT SUV metrics likely represent a true change in tumor uptake. Larger differences are required for FLT metrics comprising volume estimates when no lesion selection criteria are applied

The discerning eye of computer vision: can it measure Parkinson's finger tap bradykinesia?

Objective: The worldwide prevalence of Parkinson's disease is increasing. There is urgent need for new tools to objectively measure the condition. Existing methods to record the cardinal motor feature of the condition, bradykinesia, using wearable sensors or smartphone apps have not reached large-scale, routine use. We evaluate new computer vision (artificial intelligence) technology, DeepLabCut, as a contactless method to quantify measures related to Parkinson's bradykinesia from smartphone videos of finger tapping. Methods: Standard smartphone video recordings of 133 hands performing finger tapping (39 idiopathic Parkinson's patients and 30 controls) were tracked on a frame-by-frame basis with DeepLabCut. Objective computer measures of tapping speed, amplitude and rhythm were correlated with clinical ratings made by 22 movement disorder neurologists using the Modified Bradykinesia Rating Scale (MBRS) and Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Results: DeepLabCut reliably tracked and measured finger tapping in standard smartphone video. Computer measures correlated well with clinical ratings of bradykinesia (Spearman coefficients): -0.74 speed, 0.66 amplitude, -0.65 rhythm for MBRS; -0.56 speed, 0.61 amplitude, -0.50 rhythm for MDS-UPDRS; -0.69 combined for MDS-UPDRS. All p Conclusion: New computer vision software, DeepLabCut, can quantify three measures related to Parkinson's bradykinesia from smartphone videos of finger tapping. Objective 'contactless' measures of standard clinical examinations were not previously possible with wearable sensors (accelerometers, gyroscopes, infrared markers). DeepLabCut requires only conventional video recording of clinical examination and is entirely 'contactless'. This next generation technology holds potential for Parkinson's and other neurological disorders with altered movements

Health insurance enrollment strategies during the Affordable Care Act (ACA): a scoping review on what worked and for whom.

BACKGROUND: The Affordable Care Act (ACA) provided an opportunity for millions of people in the U.S. to get coverage from the publicly funded Medicaid program or private insurance from the newly established marketplace. However, enrolling millions of people for health insurance was an enormous task. The aim of this review was to examine the strategies used to enroll people for health insurance and their effectiveness after implementing the ACA's coverage expansion. METHODS: The PRISMA Extension for Scoping Review (PRISMA-ScR) guided this review. Included studies were empirical studies that met the inclusion criteria and published between 2010 and 2020. Studies were searched mainly from two scholarly databases, CINAHL Plus and Medline (PubMed) using keyword searches. Hand searches from the references of selected journals were also performed. Content analysis was conducted by two authors in which codes were inductively developed to identify themes. RESULTS: There were 2213 potential studies identified from the search, but 10 met the inclusion criteria. The research design of the studies varied. Two studies were randomized trials, one quasi-experimental trial, three mixed-methods, two qualitative and two quantitative. All studies focused on strategies used to inform and help people enroll for either Medicaid or private insurance from the marketplace. This review identified three key strategies used to help enroll people for coverage: 1) individual assistance; 2) community outreach; and 3) health education and promotion (HE&P). CONCLUSION: Community-based organizations were likely to use a combination of the three strategies simultaneously to reach uninsured individuals and directly help them enroll for health insurance. Other organizations that aimed to reach a wider segment of the population used single strategies, such as community outreach or HE&P