Comparative analysis of metagenomic classifiers for long-read sequencing datasets.

BACKGROUND: Long reads have gained popularity in the analysis of metagenomics data. Therefore, we comprehensively assessed metagenomics classification tools on the species taxonomic level. We analysed kmer-based tools, mapping-based tools and two general-purpose long reads mappers. We evaluated more than 20 pipelines which use either nucleotide or protein databases and selected 13 for an extensive benchmark. We prepared seven synthetic datasets to test various scenarios, including the presence of a host, unknown species and related species. Moreover, we used available sequencing data from three well-defined mock communities, including a dataset with abundance varying from 0.0001 to 20% and six real gut microbiomes. RESULTS: General-purpose mappers Minimap2 and Ram achieved similar or better accuracy on most testing metrics than best-performing classification tools. They were up to ten times slower than the fastest kmer-based tools requiring up to four times less RAM. All tested tools were prone to report organisms not present in datasets, except CLARK-S, and they underperformed in the case of the high presence of the host's genetic material. Tools which use a protein database performed worse than those based on a nucleotide database. Longer read lengths made classification easier, but due to the difference in read length distributions among species, the usage of only the longest reads reduced the accuracy. The comparison of real gut microbiome datasets shows a similar abundance profiles for the same type of tools but discordance in the number of reported organisms and abundances between types. Most assessments showed the influence of database completeness on the reports. CONCLUSION: The findings indicate that kmer-based tools are well-suited for rapid analysis of long reads data. However, when heightened accuracy is essential, mappers demonstrate slightly superior performance, albeit at a considerably slower pace. Nevertheless, a combination of diverse categories of tools and databases will likely be necessary to analyse complex samples. Discrepancies observed among tools when applied to real gut datasets, as well as a reduced performance in cases where unknown species or a significant proportion of the host genome is present in the sample, highlight the need for continuous improvement of existing tools. Additionally, regular updates and curation of databases are important to ensure their effectiveness.

[Ovarian cancer - screening and diagnosis]. / Karcinom jajnika - probir i dijagnoza.

Despite advances in gynecologic oncology, ovarian cancer is still mostly diagnosed very late or in advanced stages, which leads to adverse outcome of the disease. The pathogenesis of this disease as well as the risk factors for its development are not completely understood, while symptoms in the early stage of disease are sometimes nonspecific and delay earlier diagnosis. The aim is to present recent knowledge about the screening and diagnosis of ovarian cancer, with sp6cial reference to the role of ultrasound in recognizing the disease and referring patients for further consultation.

The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review.

The role of digital technologies (DTs) in humanitarian supply chains (HSC) has become an increasingly researched topic in the operations literature. While numerous publications have dealt with this convergence, most studies have focused on examining the implementation of individual DTs within the HSC context, leaving relevant literature, to date, dispersed and fragmented. This study, through a systematic literature review of 110 articles on HSC published between 2015 and 2020, provides a unified overview of the current state-of-the-art DTs adopted in HSC operations. The literature review findings substantiate the growing significance of DTs within HSC, identifying their main objectives and application domains, as well as their deployment with respect to the different HSC phases (i.e., Mitigation, Preparedness, Response, and Recovery). Furthermore, the findings also offer insight into how participant organizations might configure a technological portfolio aimed at overcoming operational difficulties in HSC endeavours. This work is novel as it differs from the existing traditional perspective on the role of individual technologies on HSC research by reviewing multiple DTs within the HSC domain.

Gorski Kotar--an endemic region for primary gastric non-hodgkin lymphoma?

Primary gastric non Hodgkin lymphoma (PGNHL) is a distinct group of extranodal lymphomas with interesting geographical distribution and variable prevalence in different countries. We analysed epidemiological data of our patients with PGNHL in Primorsko-goranska County. Clinical data of 30 patients with PGNHL diagnosed and treated in Clinical Hospital Center of Rijeka, Croatia between January 1995 and December 2005 were prospectively analyzed. We used statistical analysis (t-test, chi2-test) for small groups. Out of 30 pts with PGNHL, 19 were born in Primorsko-goranska County, part of Croatia situated by the Adriatic sea which consists of three regions: City of Rijeka, Islands and Gorski Kotar. 6 of 19 patients (31.6%) were originally from Gorski Kotar which made incidence rate of PGNHL in Gorski Kotar 7 times higher than in other two regions. Many authors emphasized that relative frequency of PGNHL is very variable in various countries and regions. Geographical distribution of our patients was very surprising because Gorski Kotar is the region with lowest number of citizens, rural area without any known pollutants, and ecologically one of the most preserved microsystem in this part of Croatia. Gorski Kotar is known to be an endemic region for multiple sclerosis and lyme borreliosis. Is it for PGNHL too?