Data exploration with self-organizing maps in environmental informatics and bioinformatics

The aim of this thesis was to evaluate the usability of self-organizing maps and some other methods of computational intelligence in analysing and modelling problems of environmental informatics and bioinformatics. The concepts of environmental informatics, bioinformatics, computational intelligence and data mining are first defined. There follows an introduction to the data processing chain of knowledge discovery and the methods used in this thesis, namely linear regression, self-organizing maps (SOM), Sammon's mapping, U-matrix representation, fuzzy logic, c-means and fuzzy c-means clustering, multi-layer perceptron (MLP), and regularization and Bayesian techniques. The challenges posed by environmental processes and bioprocesses are then identified, including missing data problems, complex lagged dependencies among variables, non-linear chaotic dynamics, ill-defined inverse problems, and large search space in optimization tasks. The works included in this thesis are then evaluated and discussed. The results show that the combination of SOM and Sammon's mapping has great potential in data exploration, and can be used to reveal important features of the measurement techniques (e.g. separability of compounds), reveal new information about already studied phenomena, speed up research work, act as a hypothesis generator for traditional research, and supply clear and intuitive visualization of the environmental phenomenon studied. The results of regression studies show, as expected, that the MLP network yields better estimates in predicting future values of airborne pollutant concentration of NO2 compared with SOM based regression or the least squares approach using periodic components. Additionally, the use of local MLP models is shown to be slightly better for estimating future values of episodes compared with one MLP model only. However, it can be concluded in general that the architectural issues tested are not able to solve solely model performance problems. Finally, recommendations for future work are laid out. Firstly, the data exploration solution should be enhanced with methods from signal processing to enable the handling of measurements with different time scale and lagged multivariate time-series. The main suggestion, however, is to create an integrated environment for testing different hybrid schemes of computational intelligence for better time-series forecasting in environmental informatics and bioinformatics.reviewe

Clinical factors as prognostic variables among molecular subgroups of endometrial cancer

Background Clinical factors may influence endometrial cancer survival outcomes. We examined the prognostic significance of age, body mass index (BMI), and type 2 diabetes among molecular subgroups of endometrial cancer. Methods This was a single institution retrospective study of patients who underwent surgery for endometrial carcinoma between January 2007 and December 2012. Tumors were classified into four molecular subgroups by immunohistochemistry of mismatch repair (MMR) proteins and p53, and sequencing of polymerase-epsilon (POLE). Overall, cancer-related, and non-cancer-related mortality were estimated using univariable and multivariable survival analyses. Results Age >65 years was associated with increased mortality rates in the whole cohort (n = 515) and in the "no specific molecular profile" (NSMP) (n = 218) and MMR deficient (MMR-D) (n = 191) subgroups during a median follow-up time of 81 months (range 1-136). However, hazard ratios for cancer-related mortality were non-significant for NSMP and MMR-D. Diabetes was associated with increased overall and non-cancer-related mortality in the whole cohort and MMR-D subgroup. Overweight/obesity had no effect on outcomes in the whole cohort, but was associated with decreased overall and cancer-related mortality in the NSMP subgroup, and increased overall and non-cancer-related mortality in the MMR-D subgroup. Overweight/obesity effect on cancer-related mortality in the NSMP subgroup remained unchanged after controlling for confounders. High-risk uterine factors were more common, and estrogen and progesterone receptor expression less common in NSMP subtype cancers of normal-weight patients compared with overweight/obese patients. No clinical factors were associated with outcomes in p53 aberrant (n = 69) and POLE mutant (n = 37) subgroups. No cancer-related deaths occurred in the POLE mutant subgroup. Conclusions The prognostic effects of age, BMI, and type 2 diabetes do not appear to be uniform for the molecular subgroups of endometrial cancer. Our data support further evaluation of BMI combined with genomics-based risk-assessment.Peer reviewe

American Society of Anesthesiologists physical status score as a predictor of long-term outcome in women with endometrial cancer

Objective To study the association of the American Society of Anesthesiologists (ASA) physical status score with long-term outcome in endometrial cancer. Methods Overall, disease-specific and non-cancer-related survival were estimated using simple and multivariable Cox regression analyses and the Kaplan-Meier method. Results A total of 1166 patients were included in the study. Median follow-up time was 76 (range 1-136) months. All-cause and non-cancer-related mortality were increased in patients whose ASA physical status score was III (HRs 2.5 and 8.0, respectively) or IV (HRs 5.7 and 25, respectively), and cancer-related mortality was increased in patients whose score was IV (HR 2.7). Kaplan-Meier analyses demonstrated a worse overall, disease-specific and non-cancer-related survival for patients whose score was >= III (p= III in both subgroups of stages (p=0.003 and p=0.017 for stage I and stages II-IV, respectively). ASA physical status score remained an independent predictor of all-cause mortality (HR 2.2 for scores >= III), cancer-related mortality (HRs 1.7 and 2.2 for scores >= III and IV, respectively) and non-cancer related mortality (HR 3.1 for scores >= III) after adjustment for prognostically relevant clinicopathologic and blood-based covariates. ASA physical status score also remained an independent predictor of cancer-related mortality after exclusion of patients who were at risk for nodal involvement based on features of the primary tumor but who did not undergo lymphadenectomy, and patients with advanced disease who received suboptimal chemotherapy (HRs 1.6 and 2.5 for scores >= III and IV, respectively). Conclusions ASA physical status score independently predicts overall survival, disease-specific survival, and non-cancer-related survival in endometrial cancer.Peer reviewe

The Effects of Acceptance and Commitment Therapy (ACT) Intervention on Inflammation and Stress Biomarkers: a Randomized Controlled Trial

Background Psychological processes can be manifested in physiological health. We investigated whether acceptance and commitment therapy (ACT), targeted on psychological flexibility (PF), influences inflammation and stress biomarkers among working-age adults with psychological distress and overweight/obesity. Method Participants were randomized into three parallel groups: (1) ACT-based face-to-face (n = 65; six group sessions led by a psychologist), (2) ACT-based mobile (n = 73; one group session and mobile app), and (3) control (n = 66; only the measurements). Systemic inflammation and stress markers were analyzed at baseline, at 10 weeks after the baseline (post-intervention), and at 36 weeks after the baseline (follow-up). General PF and weight-related PF were measured with questionnaires (Acceptance and Action Questionnaire, Acceptance and Action Questionnaire for Weight-Related Difficulties). Results A group x time interaction (p = .012) was detected in the high-sensitivity C-reactive protein (hsCRP) level but not in other inflammation and stress biomarkers. hsCRP decreased significantly in the face-to-face group from week 0 to week 36, and at week 36, hsCRP was lower among the participants in the face-to-face group than in the mobile group (p = .035, post hoc test). Age and sex were stronger predictors of biomarker levels at follow-up than the post-intervention PF. Conclusion The results suggest that ACT delivered in group sessions may exert beneficial effects on low-grade systemic inflammation. More research is needed on how to best apply psychological interventions for the health of both mind and body among people with overweight/obesity and psychological distress.Peer reviewe

Molecular characterization in the prediction of disease extent in endometrial carcinoma

Objective: Patients with endometrial carcinoma are usually triaged to staging lymphadenectomy selectively based on estimated risk of lymphatic spread. The risk is generally assessed by the presence of uterine risk factors, but their preoperative and intraoperative identification remain a challenge. The objective of this study was to assess the capability of molecular classification, described by The Cancer Genome Atlas (TCGA), to predict the stage of endometrial carcinoma. Study design: Sequencing of polymerase-epsilon (POLE) and immunohistochemistry of mismatch repair (MMR) proteins and p53 were performed to stratify endometrial carcinomas into subgroups of POLE exonuclease domain mutation (EDM), MMR deficiency, abnormal p53 (p53 abn) and 'no specific molecular profile' (NSMP). NSMP was the reference subgroup for comparisons. Associations of molecular subgroups and uterine risk factors with stage were examined in univariable and multivariable analyses. Results: Six hundred and four patients were included in the study. None of the POLE EDM tumours extended beyond the uterine cervix. In an unadjusted analysis, p53 abn was associated with increased risk for stage IIIC-IV disease [odds ratio (OR) 4.6, 95% confidence interval (CI) 2.3-9.2; p <0.0005]. When controlling for uterine risk factors (histotype and grade, depth of myometrial invasion, tumour size, lymphovascular space invasion), p53 was not an independent predictor of advanced disease. In contrast, POLE EDM independently predicted local disease (OR 0.12, 95% CI 0.015-0.99; p = 0.049 for stage II-IV cancer). Of the molecular subgroups, p53 abn was most strongly associated with the presence of high-risk uterine factors (ORs between 2.2 and 19; p Conclusion: Of the TCGA-based molecular subgroups, POLE EDM independently predicted early stage endometrial carcinoma. Although p53 abn was not an independent predictor of advanced disease, its association with uterine risk factors could allow utilization of molecular data in deciding the type of staging surgery if knowledge of uterine factors is deficient. (C) 2020 Elsevier B.V. All rights reserved.Peer reviewe

An open web-based GIS service for biomass data in Finland

Reliable, up-to-date biomass data are needed for climate change mitigation and resource efficiency. Therefore, a calculation and reporting tool with thematic maps and data was developed. A free web-tool, Biomass Atlas, collects the spatial distribution of biomasses in Finland. Over 300 data layers present land use, cultivation, residual biomasses from forest, crop production, animal husbandry, municipalities, and industry at 1 km2 spatial resolution. The service enables calculations of biomass amount in a defined geographical area of interest and examining the opportunities and restrictions to utilise biomasses. The service was evaluated with six test-users in laboratory tests and 20 voluntary pilot test-users. Biomass Atlas shows the regional potential of biomaterials, fertilizer products, and renewable energy, as well as potential targets for utilized, recyclable biomass. Other possible uses include monitoring plant cover on fields and assessing land use diversity. Application enables users with no experience in GIS or biomass assessments to analyse biomass resources, produce maps and data summaries for decision making.© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed