Dataset Information

The ectomycorrhizal community of urban linden trees in Gdansk, Poland.

ABSTRACT: The linden tree (Tilia spp.) is a popular tree for landscaping and urban environments in central and northwest European countries, and it is one of the most popular in cities in Poland. Ectomycorrhizal fungi form a symbiosis with many urban tree species and protect the host plant from heavy metals and against salinity. The aim of this study was to characterise the ECM fungal community of urban linden trees along the tree damage gradient. The study was performed on two sites located in the centre of the city of Gdańsk, in northern Poland. The vitality assessment of urban linden trees was made according to Roloff's classification. Tree damage classes were related to soil characteristics using principal component analysis. The five ectomycorrhizal fungal species were shared among all four tree damage classes, and Cenococcum geophilum was found to be the most abundant and frequent ectomycorrhizal fungal species in each class. Soil samples collected in the vicinity of trees belonging to the R0 class had significantly lower pH Na, Cl and Pb content than other soils. Our knowledge of ectomycorrhizal communities in urban areas is still limited, and these findings provide new insights into ectomycorrhizal distribution patterns in urban areas.

SUBMITTER: Olchowik J

PROVIDER: S-EPMC8075230 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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The ectomycorrhizal community of urban linden trees in Gdańsk, Poland.

Olchowik Jacek J Suchocka Marzena M Jankowski Paweł P Malewski Tadeusz T Hilszczańska Dorota D

PloS one 20210426 4

The linden tree (Tilia spp.) is a popular tree for landscaping and urban environments in central and northwest European countries, and it is one of the most popular in cities in Poland. Ectomycorrhizal fungi form a symbiosis with many urban tree species and protect the host plant from heavy metals and against salinity. The aim of this study was to characterise the ECM fungal community of urban linden trees along the tree damage gradient. The study was performed on two sites located in the centre ...[more]

PMID: 33901193

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Project description:BackgroundOptimal selection criteria for the lung cancer screening programme remain a matter of an open debate. We performed a validation study of the three most promising lung cancer risk prediction models in a large lung cancer screening cohort of 6,631 individuals from a single European centre.MethodsA total of 6,631 healthy volunteers (aged 50-79, smoking history ≥30 pack-years) were enrolled in the MOLTEST BIS programme between 2016 and 2018. Each participant underwent a low-dose computed chest tomography scan, and selected participants underwent a further diagnostic work-up. Various lung cancer prediction models were applied to the recruited screenees, i.e., (I) Tammemagi's Prostate, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012), (II) Liverpool Lung Project (LLP) model, and (III) Bach's lung cancer risk model. Patients (I) with 6-year lung cancer probability ≥1.3% were considered as high risk in PLCOm2012 model, (II) in LLP model with 5-year lung cancer probability ≥5.0%, and (III) in Bach's model with 5-year lung cancer probability ≥2.0%. The particular model cut-off values were employed to the cohort to evaluate each model's performance in the screened population.ResultsLung cancer was diagnosed in 154 (2.3%) participants. Based on the risk estimates by PLCOm2012, LLP and Bach's models there were 82.4%, 50.3% and 19.8% of the MOLTEST BIS participants, respectively, who fulfilled the above-mentioned threshold criteria of a lung cancer development probability. Of those detected with lung cancer, 97.4%, 74.0% and 44.8% were eligible for screening by PLCOm2012, LLP and Bach's model criteria, respectively. In Tammemagi's risk prediction model only four cases (2.6%) would have been missed from the group of 154 lung cancer patients primarily detected in the MOLTEST BIS.ConclusionsLung cancer screening enrollment based on the risk prediction models is superior to NCCN Group 1 selection criteria and offers a clinically significant reduction of screenees with a comparable proportion of detected lung cancer cases. Tammemagi's risk prediction model reduces the proportion of patients eligible for inclusion to a screening programme with a minimal loss of detected lung cancer cases.

Dataset Information

The ectomycorrhizal community of urban linden trees in Gdansk, Poland.

Publications

The ectomycorrhizal community of urban linden trees in Gdańsk, Poland.

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