Periimplantitis je jedan od kasnih neuspjeha implantoloske terapije. Za potrebe lijecenja ovog upalnog procesa razvijen je CIST protokol (engl. cumulative interceptive supportive therapy) koji sadrži 5 mjera, od A do E. Navedene se mjere primjenjuju u „paketima“ ovisno o težini klinicke slike. Prikazan je slucaj pacijenta nepusaca starosti 38 god. koji se 4 mjeseca nakon ugradnje implantata javio zbog krvarenja i neugodnog mirisa u podrucju oseointegriranog implantata postavljenog na mjestu zuba 36. Unatoc trendovima koji prednost daju primarno kirurskom pristupu lijecenju periimplantitisa, apsolutno je potrebno je pridržavati se CIST protokola. U njegovom provođenju znacajnu ulogu bi mogli igrati sustavi za svjetlosno aktiviranu dezinfekciju koji vjerojatno kompenziraju nemogucnost potpunog uklanjanja biofilma s povrsine implantata.

Motivation: Despite recent advances in algorithms design to characterize structural variation using high‐throughput short read sequencing (HTS) data, characterization of novel sequence insertions longer than the average read length remains a challenging task. This is mainly due to both computational difficulties and the complexities imposed by genomic repeats in generating reliable assemblies to accurately detect both the sequence content and the exact location of such insertions. Additionally, de novo genome assembly algorithms typically require a very high depth of coverage, which may be a limiting factor for most genome studies. Therefore, characterization of novel sequence insertions is not a routine part of most sequencing projects. There are only a handful of algorithms that are specifically developed for novel sequence insertion discovery that can bypass the need for the whole genome de novo assembly. Still, most such algorithms rely on high depth of coverage, and to our knowledge there is only one method (PopIns) that can use multi‐sample data to “collectively” obtain a very high coverage dataset to accurately find insertions common in a given population. Result: Here, we present Pamir, a new algorithm to efficiently and accurately discover and genotype novel sequence insertions using either single or multiple genome sequencing datasets. Pamir is able to detect breakpoint locations of the insertions and calculate their zygosity (i.e. heterozygous versus homozygous) by analyzing multiple sequence signatures, matching one‐end‐anchored sequences to small‐scale de novo assemblies of unmapped reads, and conducting strand‐aware local assembly. We test the efficacy of Pamir on both simulated and real data, and demonstrate its potential use in accurate and routine identification of novel sequence insertions in genome projects. Availability and implementation: Pamir is available at https://github.com/vpc‐ccg/pamir. Contact: fhach@{sfu.ca, prostatecentre.com} or calkan@cs.bilkent.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online.

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection. Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Predmet istraživanja rada upravljanje je zasticenim prirodnim podrucjima u Bosni i Hercegovini sa svrhom iznalaženja modela održivog upravljanja