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Identification of Parkinson's disease (PD) patients at risk for development of dementia is crucial for early intervention. However, diagnosing dementia in PD patients requires the use of a time-consuming and complex battery of psychological tests performed by an experienced psychologist. The study aims to prove the usefulness of convolutional neural networks for the identification of brain areas related to the progress of cognitive impairment by using standard magnetic resonance imaging (MRI) sequences. T1 & T2 sequences of 18 patients were used in the pilot study. Activation maps were generated, and the brain regions most involved in the classification process were identified, showing areas potentially significant in the diagnosis of cognitive impairment severity. The cerebellum was proven significant for distinguishing the above-mentioned classes in relative cerebellum volume (ANOVA p value = 0.0038 with large effect size η 2 = 0.5254) and folding (p value = 0.0031, η 2 = 0.5357), which is consistent with reports by other authors. Our analysis demonstrates that convolutional neural networks combined with a proper image preprocessing pipeline could be used for feature extraction in MRI sequences and can successfully support the identification of disease-specific abnormalities of the brain image. [ABSTRACT FROM AUTHOR]

Individual variability in response to radiation exposure is recognised and has often been reported as important in treatment planning. Despite many efforts to identify biomarkers allowing the identification of radiation sensitive patients, it is not yet possible to distinguish them with certainty before the beginning of the radiotherapy treatment. A comprehensive analysis of genome-wide single-nucleotide polymorphisms (SNPs) and a transcriptional response to ionising radiation exposure in twins have the potential to identify such an individual. In the present work, we investigated SNP profile and CDKN1A gene expression in blood T lymphocytes from 130 healthy Caucasians with a complex level of individual kinship (unrelated, mono- or dizygotic twins). It was found that genetic variation accounts for 66% (95% CI 37–82%) of CDKN1A transcriptional response to radiation exposure. We developed a novel integrative multi-kinship strategy allowing investigating the role of genome-wide polymorphisms in transcriptomic radiation response, and it revealed that rs205543 (ETV6 gene), rs2287505 and rs1263612 (KLF7 gene) are significantly associated with CDKN1A expression level. The functional analysis revealed that rs6974232 (RPA3 gene), involved in mismatch repair (p value = 9.68e−04) as well as in RNA repair (p value = 1.4e−03) might have an important role in that process. Two missense polymorphisms with possible deleterious effect in humans were identified: rs1133833 (AKIP1 gene) and rs17362588 (CCDC141 gene). In summary, the data presented here support the validity of this novel integrative data analysis strategy to provide insights into the identification of SNPs potentially influencing radiation sensitivity. Further investigations in radiation response research at the genomic level should be therefore continued to confirm these findings. [ABSTRACT FROM AUTHOR]

Identification of biomarkers for molecular classification of cancer and for differentiation between cancerous and normal epithelium remains a vital issue in the field of head and neck cancer. Here we aimed to compare the ability of proteome and lipidome components to discriminate oral cancer from normal mucosa. Tissue specimens including squamous cell cancer and normal epithelium were analyzed by MALDI mass spectrometry imaging. Two molecular domains of tissue components were imaged in serial sections—peptides (resulting from trypsin-processed proteins) and lipids (primarily zwitterionic phospholipids), then regions of interest corresponding to cancer and normal epithelium were compared. Heterogeneity of cancer regions was higher than the heterogeneity of normal epithelium, and the distribution of peptide components was more heterogeneous than the distribution of lipid components. Moreover, there were more peptide components than lipid components that showed significantly different abundance between cancer and normal epithelium (median of the Cohen's effect was 0.49 and 0.31 in case of peptide and lipid components, respectively). Multicomponent cancer classifier was tested (vs. normal epithelium) using tissue specimens from three patients and then validated with a tissue specimen from the fourth patient. Peptide-based signature and lipid-based signature allowed cancer classification with a weighted accuracy of 0.85 and 0.69, respectively. Nevertheless, both classifiers had very high precision (0.98 and 0.94, respectively). We concluded that though molecular differences between cancerous and normal mucosa were higher in the proteome domain than in the analyzed lipidome subdomain, imaging of lipidome components also enabled discrimination of oral cancer and normal epithelium. Therefore, both cancer proteome and lipidome are promising sources of biomarkers of oral malignancies. [ABSTRACT FROM AUTHOR]

Alteration of DNA methylation level in cancer diseases leads to deregulation of gene expression—silencing of tumor suppressor genes and enhancing of protooncogenes. There are several tools devoted to the problem of identification of CpG sites' demethylation but majority of them focuses on single site level and does not allow for quantification of region methylation changes. The aim was to create an adaptive algorithm supporting detection of differentially methylated CpG sites and genomic regions specific for acute myeloid leukemia. Knowledge on AML methylation fingerprint helps in better understanding the epigenetics of leukemogenesis. Proposed algorithm is data driven and does not use predefined quantification thresholds. Gaussian mixture modeling supports classification of CpG sites to several levels of demethylation. p value integration allows for translation from single site demethylation to the demethylation of gene promoter and body regions. Methylation profiles of healthy controls and AML patients were examined (GEO:GSE63409). The differences in whole genome methylation profiles were observed. The methylation profile differs significantly among genomic regions. The lowest methylation level was observed for promoter regions, while sites from intergenic regions were by average higher methylated. The observed number of AML related down methylated sites has not substantially exceeded the expected number by chance. Intergenic regions were characterized by the highest percentage of AML up methylated sites. Methylation enhancement/diminution is the most frequent for intergenic region while methylation compensation (positive or negative) is specific for promoter regions. Functional analysis performed for AML down methylated or extreme high up methylated genes showed strong connection to the leukemic processes. [ABSTRACT FROM AUTHOR]

While the biological effects of high-dose-ionizing radiation on human health are well characterized, the consequences of low-dose radiation exposure remain poorly defined, even though they are of major importance for radiological protection. Lymphocytes are very radiosensitive, and radiation-induced health effects may result from immune cell loss and/or immune system impairment. To decipher the mechanisms of effects of low doses, we analyzed the modulation of the T-cell receptor gene repertoire in mice exposed to a single low (0.1 Gy) or high (1 Gy) dose of radiation. High-throughput T-cell receptor gene profiling was used to visualize T-lymphocyte dynamics over time in control and irradiated mice. Radiation exposure induces 'aging-like' effects on the T-cell receptor gene repertoire, detectable as early as 1 month post-exposure and for at least 6 months. Surprisingly, these effects are more pronounced in animals exposed to 0.1 Gy than to 1 Gy, where partial correction occurs over time. Importantly, we found that low-dose radiation effects are partially due to the hematopoietic stem cell impairment. Collectively, our findings show that acute low-dose radiation exposure specifically results in long-term alterations of the T-lymphocyte repertoire. [ABSTRACT FROM AUTHOR]

Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments. [ABSTRACT FROM AUTHOR]

Aims: The incidence of pediatric type 1 diabetes mellitus (T1DM) in Poland is intermediate relative to the rest of the world. T1DM prevalence in the region of Silesia approximates national estimates for all of Poland. This epidemiologic study aimed to analyze the changes in incidence rates of T1DM among children ages 0-14 years from 1989 to 2012 in this region. Methods: Data collection methods for the registry followed EURODIAB criteria. To estimate overall population size, data from the Central and regional Statistical Office in Katowice were used. T1DM incidence rates/100,000 children ages 0-14 years/annum and their 95 % CI were calculated for all children and in age subgroups (0-4, 5-9, 10-14 years). For comparative analysis incidence rates were age and sex standardized to the population of Poland in 2005. For statistical analyses open source R Bioconductor software was used. Results: During this 24-year period, 2,215 new cases (1,146 boys) were diagnosed. The standardized incidence rate rose about 7 % annually. The mean standardized incidence rates estimated in four 6-year time periods (1989-1994, 1995-2000, 2001-2006, 2007-2012) separately showed significant increases from 5.80/100,000/year (1989-1994) through 10.44/100,000/year (1995-2000) and 15.05/100,000/year (2001-2006) to 18.94/100,000/year (2007-2012). From 1989 to 2012, the greatest relative rise in annual incidence (/100,000/year) was among the very young: 2.58-14.00 (0-4 years); 4.96-19.43 (5-9 years); 8.84-22.15 (10-14 years). The highest average annual increment of the incidence rate was in the middle age subgroup (5-9 years). No significant sex difference was observed. Conclusions: The overall incidence rate increased 3.8 times, suggesting an epidemic of pediatric T1DM in Silesia, Poland. These temporal changes confirm that Poland currently has one of the highest incidence rates of pediatric T1DM in Europe. [ABSTRACT FROM AUTHOR]

Transition from pediatric to the adult care system is an important issue for diabetes management. The objective was to evaluate the transition of young adults with type 1 diabetes (T1DM) from pediatric to adult diabetes care. Questionnaires were sent to all T1DM patients (166), who left pediatric diabetes care in Katowice, Poland (2003-2007). Analyzed parameters included: date of first visit and visit frequency in adult care, HbA1c (mean and final at pediatric care, HbA1c_M and F respectively, reported in questionnaire - HbA1c_Q), and history of acute complications. 132(82.5 %) responses were received. 96(73 %) patients undertook their first visit at adult clinic ≤3 months after finishing pediatric care, 8(6 %) - after 4-6 months, 10(7 %) >6 months, and 12(9 %) remained under the observation of a GP. Subgroup >6 months differed significantly by HbA1c_Q from the <3 months subgroup (10.5 ±3.34 vs. 7.53 ±1.50, P = 0.041). The later the patients take up adult care, the less often they attend visits ( P < 0.001). Visit frequency also decreased with age and diabetes duration ( P = 0.034 and P = 0.032 respectively). Additionally, patients with fewer visits annually, at all times had poorer glycemic control (HbA1c_M: P = 0.015; HbA1c_F: P = 0.016; and HbA1c_Q: P = 0.012). Changes of HbA1c(d = HbA1c_Q-HbA1c_F) were higher in patients treated with insulin pump therapy compared to multiple daily injections (0.77 ± 1.65 vs. -0.06 ± 1.84; P = 0.045). Nearly 25 % of young adults with T1DM discontinue systematic specialist care after transfer in adult clinics. Patients with poorer glycemic control and fewer visits during pediatric care, as well as those treated with a personal insulin pump, require additional attention during the transition process. [ABSTRACT FROM AUTHOR]

The aim of this study was to estimate the present Polish incidence rate of diabetes mellitus type 1 in children aged 0–14. The research was conducted between 1989 and 2005 among the children of Upper Silesia region (Poland), being the part of the EURODIAB program, according to all criteria of this project. During this period, 1,385 new cases (720 boys) of diabetes mellitus type 1 were recognized. The analysis of the standardized incidence rates performed after dividing into shorter periods (1989–1994, 1995–1999, 2000–2005) showed a sharp increase from 5.80/105/year through 9.54/105/year to 15.26/105/year, respectively, in the periods. Analysis of age subgroups showed the greatest increase in the incidence rate among the younger children: 3.59 times for children aged 0–4, 3.40 times for children aged 5–9 and 2.08 times for children aged 10–14. No significant difference of incidence rate between boys and girls was established. Such high increase of incidence rate of diabetes mellitus type 1 (above 260%) noted since 1989 shows a secular trend of an epidemic of diabetes mellitus type 1 in Poland and a conversion from countries with the lower incidence rates in Europe to the countries with the highest incidence rates. [ABSTRACT FROM AUTHOR]