Association Rule Discovery from Collaborative Mobile Data

Sophisticated mobile devices have rapidly become essential tools for various daily activities of billions of people worldwide. Subsequently, the demand for longer battery lives is constantly increasing. The Carat project is advancing the understanding of mobile energy consumption by using collaborative mobile data to estimate and model energy consumption of mobile devices. This thesis presents a method for estimating mobile application energy consumption from mobile device system settings and context factors using association rules. These settings and factors include CPU usage, device travel distance, battery temperature, battery voltage, screen brightness, used mobile networking technology, network type, WiFi signal strength, and WiFi connection speed. The association rules are mined using Apache Spark cluster-computing framework from collaborative mobile data collected by the Carat project. Additionally, this thesis presents a prototype of a web based API for discovering these association rules. The web service integrates Apache Spark based analysis engine with a user friendly front-end allowing an aggregated view of the dataset to be accessible without revealing data of individual participants of the Carat project. This thesis shows that association rules can be used effectively in modelling mobile device energy consumption. Example rules are presented and the performance of the implementation is evaluated experimentally

Exome and immune cell score analyses reveal great variation within synchronous primary colorectal cancers

BACKGROUND: Approximately 4% of colorectal cancer (CRC) patients have at least two simultaneous cancers in the colon. Due to the shared environment, these synchronous CRCs (SCRCs) provide a unique setting to study colorectal carcinogenesis. Understanding whether these tumours are genetically similar or distinct is essential when designing therapeutic approaches. METHODS: We performed exome sequencing of 47 primary cancers and corresponding normal samples from 23 patients. Additionally, we carried out a comprehensive mutational signature analysis to assess whether tumours had undergone similar mutational processes and the first immune cell score analysis (IS) of SCRC to analyse the interplay between immune cell invasion and mutation profile in both lesions of an individual. RESULTS: The tumour pairs shared only few mutations, favouring different mutations in known CRC genes and signalling pathways and displayed variation in their signature content. Two tumour pairs had discordant mismatch repair statuses. In majority of the pairs, IS varied between primaries. Differences were not explained by any clinicopathological variable or mutation burden. CONCLUSIONS: The study shows major diversity within SCRCs. Rather than rely on data from one tumour, our study highlights the need to evaluate both tumours of a synchronous pair for optimised targeted therapy.Peer reviewe

Exome-wide somatic mutation characterization of small bowel adenocarcinoma

Small bowel adenocarcinoma (SBA) is an aggressive disease with limited treatment options. Despite previous studies, its molecular genetic background has remained somewhat elusive. To comprehensively characterize the mutational landscape of this tumor type, and to identify possible targets of treatment, we conducted the first large exome sequencing study on a population-based set of SBA samples from all three small bowel segments. Archival tissue from 106 primary tumors with appropriate clinical information were available for exome sequencing from a patient series consisting of a majority of confirmed SBA cases diagnosed in Finland between the years 2003-2011. Paired-end exome sequencing was performed using Illumina HiSeq 4000, and OncodriveFML was used to identify driver genes from the exome data. We also defined frequently affected cancer signalling pathways and performed the first extensive allelic imbalance (Al) analysis in SBA. Exome data analysis revealed significantly mutated genes previously linked to SBA (TP53, KRAS, APC, SMAD4, and BRAF), recently reported potential driver genes (SOX9, ATM, and ARID2), as well as novel candidate driver genes, such as ACVR2A, ACVR1B, BRCA2, and SMARCA4. We also identified clear mutation hotspot patterns in ERBB2 and BRAF. No BRAF V600E mutations were observed. Additionally, we present a comprehensive mutation signature analysis of SBA, highlighting established signatures 1A, 6, and 17, as well as U2 which is a previously unvalidated signature. Finally, comparison of the three small bowel segments revealed differences in tumor characteristics. This comprehensive work unveils the mutational landscape and most frequently affected genes and pathways in SBA, providing potential therapeutic targets, and novel and more thorough insights into the genetic background of this tumor type.Peer reviewe

The adoption of IFRS 3: the effects of managerial discretion and stock market reactions

Original article can be found at : http://tandfprod.literatumonline.com/ Copyright Taylor & FrancisIn recent years, several accounting standards, including IFRS 3, issued by the IASB, substitute historical cost with fair value measures and so provide managers with increased discretion to determine fair value without an actual market for the asset. Using Swedish data, we document the accounting consequences of the adoption of IFRS 3 and the stock market's reaction. After the adoption of this standard in January 2005 the amount of capitalized goodwill increased substantially. Goodwill impairments under IFRS are considerably lower than goodwill amortizations and impairments made under Swedish GAAP. Consequently, the adoption of IFRS 3 increased reported earnings. An analysis of economic incentives influencing the impairment decision at the initial adoption of IFRS 3 shows that tenured management is negatively associated with the impairment decision. However, most firms did not reclassify goodwill or make additional impairments. Firms with substantial amounts of goodwill yielded abnormally high returns despite abnormally low earnings. Investors seem to, correctly or incorrectly, have viewed the accrual-based increase in earnings stemming from IFRS 3 as an indication of higher future cash flows.Peer reviewedFinal Accepted Versio

Comprehensive Evaluation of Protein Coding Mononucleotide Microsatellites in Microsatellite-Unstable Colorectal Cancer

Approximately 15% of colorectal cancers exhibit microsatellite instability (MSI), which leads to accumulation of large numbers of small insertions and deletions (indels). Genes that provide growth advantage to cells via loss-of-function mutations in micro-satellites are called MSI target genes. Several criteria to define these genes have been suggested, one of them being simple mutation frequency. Microsatellite mutation rate, however, depends on the length and nucleotide context of the microsatellite. Therefore, assessing the general impact of mismatch repair deficiency on the likelihood of mutation events is paramount when following this approach. To identify MSI target genes, we developed a statistical model for the somatic background indel mutation rate of microsatellites to assess mutation significance. Exome sequencing data of 24 MSI colorectal cancers revealed indels at 54 million mononucleotide microsatellites of three or more nucleotides in length. The top 105 microsatellites from 71 genes were further analyzed in 93 additional MSI colorectal cancers. Mutation significance and estimated clonality of mutations determined the most likely MSI target genes to be the aminoadipate-semialdehyde dehydrogenase AASDH and the solute transporter SLC9A8. Our findings offer a systematic profiling of the somatic background mutation rate in protein-coding mononucleotide microsatellites, allowing a full cataloging of the true targets of MSI in colorectal cancer. (C) 2017 AACR.Peer reviewe

Clinicopathologic features of the patient cohort.

<p>Clinicopathologic features of the patient cohort.</p

Overview of AI events in SBA.

<p>Frequency of gains and losses in 106 SBA samples.</p

Mutation pattern in ERBB receptor family.

<p>Mutations in <i>ERBB2</i> (ENST00000269571) grouped into four hotspots (top). Samples (n = 29) with a mutated member of ERBB receptor family are presented in columns (below). In addition to a hotspot mutation, some samples displayed simultaneously a non-hotspot mutation in the same gene, thus all mutations are not shown in the figure. Recep_L = Receptor L domain; Furin-like = Furin-like cysteine rich region; GF_recep = Growth factor receptor domain; Pkinase_Tyr = Protein tyrosine kinase.</p