Allopurinol and risk of benign prostatic hyperplasia in a Finnish population-based cohort

Hyperurikemiaan liittyvän oksidatiivisen stressin on esitetty edistävän prostatan hyvänlaatuista liikakasvua (BPH). Ei tiedetä, olisiko antihyperurikemisella lääkityksellä vaikutusta BPH riskiin. Tutkimme BPH:n ja antihyperurikemisen allopurinolin käytön yhteyttä. Kohortin muodostavat 74,745 miestä, jotka on alun perin identifioitu suomalaiseen eturauhassyövän seulontatutkimukseen (FinRSPC). Suljimme pois miehet, joilla oli BPH seurannan alussa. Käytimme Cox:n regressiomallia verrataksemme BPH lääkityksen, diagnoosin tai leikkauksen riskiä allopurinolin käytön mukaan. Lääkekäyttöä analysoitiin aikariippuvaisena muuttujana minimoidaksemme kuolemattomuusharhan vaikutusta. Allopurinolin käyttäjillä oli ei-käyttäjiä pienempi riski kaikille BPH päätetapahtumille: monivakioidussa analyysissä BPH lääkityksen (HR 0.81; 95% CI 0.75-0.88), kirjatun BPH diagnoosin (HR 0.78; 95% CI 0.71-0.86) ja BPH leikkauksen (HR 0.67; 95% CI 0.58-0.76) riskit olivat alhaisemmat ei-käyttäjiin verrattuna. Painoindeksi (BMI) muokkasi riskisuhdetta; allopurinolin käyttö oli yhteydessä madaltuneeseen BPH riskiin vain miehillä, joiden painoindeksi oli tutkimusväestön mediaanin (27,3 kg/m2) yläpuolella; interaktioiden p-arvo < 0.05 kaikille päätetapahtumille. Mahdollinen selitys voisi olla antihyperurikemisen allopurinolin antioksidatiivinen vaikutus tai ksantiinioksidaasientsyymin toiminnan esto.Tutkielmaan liittyvät artikkelit / Articles related to the thesis: Allopurinol and risk of benign prostatic hyperplasia in a Finnish population-based cohort. Prostate Cancer Prostatic Diseases. 2018 Sep;21(3):373-378. doi: 10.1038/s41391-017-0031-8 Allopurinolilääkityksellä yhteys eturauhasen hyvänlaatuisen liikakasvun riskin pienentymiseen. Lääketieteellinen aikakauskirja Duodecim, 2018;134(19):196

Examining Changes in Stem Taper and Volume Growth with Two-Date 3D Point Clouds

Exact knowledge over tree growth is valuable information for decision makers when considering the purposes of sustainable forest management and planning or optimizing the use of timber, for example. Terrestrial laser scanning (TLS) can be used for measuring tree and forest attributes in very high detail. The study aims at characterizing changes in individual tree attributes (e.g., stem volume growth and taper) during a nine year-long study period in boreal forest conditions. TLS-based three-dimensional (3D) point cloud data were used for identifying and quantifying these changes. The results showed that observing changes in stem volume was possible from TLS point cloud data collected at two different time points. The average volume growth of sample trees was 0.226 m3 during the study period, and the mean relative change in stem volume was 65.0%. In addition, the results of a pairwise Student’s t-test gave strong support (p-value 0.0001) that the used method was able to detect tree growth within the nine-year period between 2008–2017. The findings of this study allow the further development of enhanced methods for TLS-based single tree and forest growth modeling and estimation, which can thus improve the accuracy of forest inventories and offer better tools for future decision-making processes

Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.Peer reviewe

Examining Changes in Stem Taper and Volume Growth with Two-Date 3D Point Clouds

Exact knowledge over tree growth is valuable information for decision makers when considering the purposes of sustainable forest management and planning or optimizing the use of timber, for example. Terrestrial laser scanning (TLS) can be used for measuring tree and forest attributes in very high detail. The study aims at characterizing changes in individual tree attributes (e.g., stem volume growth and taper) during a nine year-long study period in boreal forest conditions. TLS-based three-dimensional (3D) point cloud data were used for identifying and quantifying these changes. The results showed that observing changes in stem volume was possible from TLS point cloud data collected at two different time points. The average volume growth of sample trees was 0.226 m(3) during the study period, and the mean relative change in stem volume was 65.0%. In addition, the results of a pairwise Student's t-test gave strong support (p-value 0.0001) that the used method was able to detect tree growth within the nine-year period between 2008-2017. The findings of this study allow the further development of enhanced methods for TLS-based single tree and forest growth modeling and estimation, which can thus improve the accuracy of forest inventories and offer better tools for future decision-making processes

Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies

Modelling the effect of moose Alces alces population density and regional forest structure on the amount of damage in forest seedling stands

BACKGROUND: Moose (Alces alces L.) populations and moose damage in forests are debated in Nordic countries with dense moose populations. Moose populations and food resources vary greatly, both spatially and temporally, and reliable data covering both variables simultaneously at the same scale have seldom been available. We modelled the effect of moose population density and forest resources on the area of moose damage at regional scale, referring to moose management areas (MMA). For-est data and moose damage data originated from the Finnish National Forest Inventory, and the moose population data came from a Bayesian moose model. For modelling, average values of moose population, damage and forest variables were calculated for the periods 2004–2008 and 2009–2013 for each MMA. The MMAs were further classified into one of four larger geographical zones. The area of moose damage was used as a dependent variable, and the proportions of different types off forests and moose population densities per land area or area of seedling stands as explanatory variables. The relationships were modelled with a linear mixed-effects model with an exponential spatial correlation structure. RESULTS: The area of moose damage was best explained by total forest area, proportions of plantations and mature forests, and moose population density per land area or the proportion of plantations. There were differences among the biogeographical zones in how different variables explained the amount of damage. CONCLUSION: The results provide tools for analyzing the regional effects of moose population density and the amount of food resources on the amount of moose damage. This information can be used in reconciling sustainable moose population levels and the amount of damage.202

Allopurinol and prostate cancer survival in a Finnish population-based cohort

BACKGROUND: Allopurinol is gout medication that inhibits uric acid formation. Its possible anti-carcinogenic properties have been under research in past years. Studies based on Taiwanese registries showed that long term allopurinol use might reduce prostate cancer (PCa) incidence. However, our studies based on Finnish registries did not support those findings. In this study, we evaluate whether allopurinol use is associated with prostate cancer-specific survival (CSS) or overall survival (OS) in a Finnish population-based cohort. METHODS: The study cohort was originally enrolled for the Finnish Randomized Study of Screening for Prostate Cancer (FinRSPC). We included all newly diagnosed PCa cases during 1996-2015, 9252 men in total. Information on allopurinol purchases was from the national prescription registry of the Social Insurance Institution of Finland. Information about deaths, treatments, and use of other medications was obtained from registries, and tumor stage and PSA at diagnosis from medical records. Follow-up started at diagnosis, and we analysed separately two endpoints: PCa-specific death and overall death. We used an extended Cox regression with adjustment for age at diagnosis, Charlson comorbidity index, FinRSPC trial arm, use of other drugs and EAU PCa risk group. RESULTS: During a median follow-up of 9.86 years, 2942 deaths occurred, including 883 from PCa. There was no difference in CSS between allopurinol user and non-users, but allopurinol users had lower OS (multivariable-adjusted hazard ratio 1.77; 95% CI: 1.57-2.00). However, this decrease in OS was mitigated along with increasing intensity of allopurinol use. CONCLUSIONS: We found no marked difference in CSS by allopurinol use. Allopurinol users had lower OS but there were no significant differences by duration or intensity of allopurinol use. Allopurinol use may not have anticancer effects against prostate cancer; instead, it may be a surrogate for metabolic problems causing shorter OS among men with PCa.publishedVersionPeer reviewe

Airborne laser scanning outperforms the alternative 3D techniques in capturing variation in tree height and forest density in southern boreal forests.

ArticleBaltic Forestry. 24(2): 268-277. (2018)journal articl

Airborne Laser Scanning Outperforms the Alternative 3D Techniques in Capturing Variation in Tree Height and Forest Density in Southern Boreal Forests

The objective of this study is to better understand the relationship between forest structure and point cloud features generated from certain airborne and space borne sensors. Point cloud features derived from airborne laser scanning (ALS), aerial imagery (AI), WorldView-2 imagery (WV2), TerraSAR-X, and Tandem-X (TDX) data were classified as features characterizing forest height and density as well as variation in tree height. Correlations between these features and field-measured attributes describing forest height, density and tree height variation were investigated at plot scale. From the field-measured attributes, basal area (G) and the number of trees per unit area (N) were used as forest density indicators whereas maximum tree height (H-max) and standard deviation in tree height (H-std) were used as indicators for forest height and tree height variation, respectively. In the analyses, field observations from 91 sample plots (32 m x 32 m) located in southern Finland were used. Even though ALS was found to be the most accurate data source in characterizing forest structure, AI, WV2, and TDX were also capable of characterizing forest height at plot scale with correlation coefficients stronger than 0.85. However, ALS was the only data source capable of providing separate features for characterizing also the variation in tree height and forest density. Features related to forest height, generated from the other data sources besides ALS, also provided strongest correlation with the forest density attributes and variation in tree height, in addition to H-max. Due to these more diverse characterization capabilities, forest structural attributes can be predicted more accurately by using ALS, also in the areas where the relation between the attributes of interest is not solely dependent on forest height, compared to the other investigated 3D remote sensing data sources.Peer reviewe

Feasibility of Terrestrial laser scanning for collecting stem volume information from single trees

Interest in measuring forest biomass and carbon stock has increased as a result of the United Nations Framework Convention on Climate Change, and sustainable planning of forest resources is therefore essential. Biomass and carbon stock estimates are based on the large area estimates of growing stock volume provided by national forest inventories (NFIs). The estimates for growing stock volume based on the NFIs depend on stem volume estimates of individual trees. Data collection for formulating stem volume and biomass models is challenging, because the amount of data required is considerable, and the fact that the detailed destructive measurements required to provide these data are laborious. Due to natural diversity, sample size for developing allometric models should be rather large. Terrestrial laser scanning (TLS) has proved to be an efficient tool for collecting information on tree stems. Therefore, we investigated how TLS data for deriving stem volume information from single trees should be collected. The broader context of the study was to determine the feasibility of replacing destructive and laborious field measurements, which have been needed for development of empirical stem volume models, with TLS. The aim of the study was to investigate the effect of the TLS data captured at various distance (i.e. corresponding 25%, 50%, 75% and 100% of tree height) on the accuracy of the stem volume derived. In addition, we examined how multiple TLS point cloud data acquired at various distances improved the results. Analysis was carried out with two ways when multiple point clouds were used: individual tree attributes were derived from separate point clouds and the volume was estimated based on these separate values (multiple scan A), and point clouds were georeferenced as a combined point cloud from which the stem volume was estimated (multiple-scan B). This permitted us to deal with the practical aspects of TLS data collection and data processing for development of stem volume equations in boreal forests. The results indicated that a scanning distance of approximately 25% of tree height would be optimal for stem volume estimation with TLS if a single scan was utilized in boreal forest conditions studied here and scanning resolution employed. Larger distances increased the uncertainty, especially when the scanning distance was greater than approximately 50% of tree height, because the number of successfully measured diameters from the TLS point cloud was not sufficient for estimating the stem volume. When two TLS point clouds were utilized, the accuracy of stem volume estimates was improved: RMSE decreased from 12.4% to 6.8%. When two point clouds were processed separately (i.e. tree attributes were derived from separate point clouds and then combined) more accurate results were obtained; smaller RMSE and relative error were achieved compared to processing point clouds together (i.e. tree attributes were derived from a combined point cloud). TLS data collection and processing for the optimal setup in this study required only one sixth of time that was necessary to obtain the field reference. These results helped to further our knowledge on TLS in estimating stem volume in boreal forests studied here and brought us one step closer in providing best practices how a phase-shift TLS can be utilized in collecting data when developing stem volume models. (C) 2016 The Authors. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).Peer reviewe