Tuberculosis incidence in foreign-born people residing in European countries in 2020.

BackgroundEuropean-specific policies for tuberculosis (TB) elimination require identification of key populations that benefit from TB screening.AimWe aimed to identify groups of foreign-born individuals residing in European countries that benefit most from targeted TB prevention screening.MethodsThe Tuberculosis Network European Trials group collected, by cross-sectional survey, numbers of foreign-born TB patients residing in European Union (EU) countries, Iceland, Norway, Switzerland and the United Kingdom (UK) in 2020 from the 10 highest ranked countries of origin in terms of TB cases in each country of residence. Tuberculosis incidence rates (IRs) in countries of residence were compared with countries of origin.ResultsData on 9,116 foreign-born TB patients in 30 countries of residence were collected. Main countries of origin were Eritrea, India, Pakistan, Morocco, Romania and Somalia. Tuberculosis IRs were highest in patients of Eritrean and Somali origin in Greece and Malta (both > 1,000/100,000) and lowest among Ukrainian patients in Poland (3.6/100,000). They were mainly lower in countries of residence than countries of origin. However, IRs among Eritreans and Somalis in Greece and Malta were five times higher than in Eritrea and Somalia. Similarly, IRs among Eritreans in Germany, the Netherlands and the UK were four times higher than in Eritrea.ConclusionsCountry of origin TB IR is an insufficient indicator when targeting foreign-born populations for active case finding or TB prevention policies in the countries covered here. Elimination strategies should be informed by regularly collected country-specific data to address rapidly changing epidemiology and associated risks

Artificial Intelligence-based methods in head and neck cancer diagnosis : an overview

Background This paper reviews recent literature employing Artificial Intelligence/Machine Learning (AI/ML) methods for diagnostic evaluation of head and neck cancers (HNC) using automated image analysis. Methods Electronic database searches using MEDLINE via OVID, EMBASE and Google Scholar were conducted to retrieve articles using AI/ML for diagnostic evaluation of HNC (2009–2020). No restrictions were placed on the AI/ML method or imaging modality used. Results In total, 32 articles were identified. HNC sites included oral cavity (n = 16), nasopharynx (n = 3), oropharynx (n = 3), larynx (n = 2), salivary glands (n = 2), sinonasal (n = 1) and in five studies multiple sites were studied. Imaging modalities included histological (n = 9), radiological (n = 8), hyperspectral (n = 6), endoscopic/clinical (n = 5), infrared thermal (n = 1) and optical (n = 1). Clinicopathologic/genomic data were used in two studies. Traditional ML methods were employed in 22 studies (69%), deep learning (DL) in eight studies (25%) and a combination of these methods in two studies (6%). Conclusions There is an increasing volume of studies exploring the role of AI/ML to aid HNC detection using a range of imaging modalities. These methods can achieve high degrees of accuracy that can exceed the abilities of human judgement in making data predictions. Large-scale multi-centric prospective studies are required to aid deployment into clinical practice

Pollen dispersal and gene flow within and into a population of the alpine monocarpic plant Campanula thyrsoides

BACKGROUND AND AIMS: Gene flow by seed and pollen largely shapes the genetic structure within and among plant populations. Seed dispersal is often strongly spatially restricted, making gene flow primarily dependent on pollen dispersal within and into populations. To understand distance-dependent pollination success, pollen dispersal and gene flow were studied within and into a population of the alpine monocarpic perennial Campanula thyrsoides. METHODS: A paternity analysis was performed on sampled seed families using microsatellites, genotyping 22 flowering adults and 331 germinated offspring to estimate gene flow, and pollen analogues were used to estimate pollen dispersal. The focal population was situated among 23 genetically differentiated populations on a subalpine mountain plateau (<10 km(2)) in central Switzerland. KEY RESULTS: Paternity analysis assigned 110 offspring (33·2 %) to a specific pollen donor (i.e. ‘father’) in the focal population. Mean pollination distance was 17·4 m for these offspring, and the pollen dispersal curve based on positive LOD scores of all 331 offspring was strongly decreasing with distance. The paternal contribution from 20–35 offspring (6·0–10·5 %) originated outside the population, probably from nearby populations on the plateau. Multiple potential fathers were assigned to each of 186 offspring (56·2 %). The pollination distance to ‘mother’ plants was negatively affected by the mothers' degree of spatial isolation in the population. Variability in male mating success was not related to the degree of isolation of father plants. CONCLUSIONS: Pollen dispersal patterns within the C. thyrsoides population are affected by spatial positioning of flowering individuals and pollen dispersal may therefore contribute to the course of evolution of populations of this species. Pollen dispersal into the population was high but apparently not strong enough to prevent the previously described substantial among-population differentiation on the plateau, which may be due to the monocarpic perenniality of this species