Although, liver transplantation serves as the only curative treatment for patients with end-stage liver diseases, it is burdened with complications, which affect survival rates. In addition to clinical risk factors, contribution of recipient and donor genetic prognostic markers has been extensively studied in order to reduce the burden and improve the outcomes. Determination of single nucleotide polymorphisms (SNPs) is one of the most important tools in development of personalized transplant approach. To provide a better insight in recent developments, we review the studies published in the last three years that investigated an association of recipient or donor SNPs with most common issues in liver transplantation: Acute cellular rejection, development of new-onset diabetes mellitus and non-alcoholic fatty liver disease, hepatocellular carcinoma recurrence, and tacrolimus concentration variability. Reviewed studies confirmed previously established SNP prognostic factors, such as PNPLA3 rs738409 for non-alcoholic fatty liver disease development, or the role of CYP3A5 rs776746 in tacrolimus concentration variability. They also identified several novel SNPs, with a reasonably strong association, which have the potential to become useful predictors of post-transplant complications. However, as the studies were typically conducted in one center on relatively low-to-moderate number of patients, verification of the results in other centers is warranted to resolve these limitations. Furthermore, of 29 reviewed studies, 28 used gene candidate approach and only one implemented a genome wide association approach. Genome wide association multicentric studies are needed to facilitate the development of personalized transplant medicine.

Classification of biological neuron types and networks poses challenges to the full understanding of the brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal types and networks based on the communication metrics of neurons. This presents advantages against the existing approaches since the mutual information or the delay between neurons obtained from spike trains are more abundant data compare to conventional morphological data. We firstly designed two open-access supporting computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then we investigate how the concept of network tomography could be achieved with cortical neuronal circuits for morphological, topological and electrical classification of neurons. We extract the simulated data to many different classifiers (including SVM, Decision Trees, Random Forest, and Artificial Neuron Networks) classifying the specific cell type (and sub-group types) achieving accuracies of up to 70\%. Inference of biological network structures using network tomography reached up to 65\% of accuracy. We also analysed recall, precision and F1score of the classification of five layers, 25 cell m-types, and 14 cell e-types. Our research not only contributes to existing classification efforts but sets the road-map for future usage of cellular-scaled brain-machine interfaces for in-vivo objective classification of neurons as a sensing mechanism of the brain's structure.

Higher education is a key element of prosperous communities, and the quality of education should be a priority in attracting prospective students. Good education implies good academic staff, well-equipped laboratories, facilities, and efficient processes. Maintain efficient processes is challenging abut achievable. One of the possible solutions to improve education processes is to pursue a lean strategy in order to reduce waste and non-value-added activities. The purpose of this paper is to combine paying off strategies from manufacturing companies with higher education institutions (HEI), in order to enhance the quality of education and efficiency of higher education institutions. This research deals with application lean tools in university processes with the aim of investigating the possibility of applying lean concepts in HEI. Processes from the student affairs office from a Bosnian university were taken as a case study. The tools were used for data collections, student satisfaction measurement, process efficiency analysis and assessment whether the university is ready for the implementation of the lean concept. As a result, it was observed that communication channels between university and students are weak, the student information system does not respond to students’ needs, internal communication channels need to be improved and human resources are underused. Overall, it was found that the lean strategy can be applied in HEIs but for the successful implementation of lean thinking, lifestyle from top management to lower management must be adopted.

We present a systematic survey of possible short-distance new-physics effects in (semi)leptonic charged- and neutral-current charmed meson decays. Using the Standard Model Effective Field Theory (SMEFT) to analyze the most relevant experimental data at low and high energies, we demonstrate a striking complementarity between charm decays and high invariant mass lepton tails at the LHC. Interestingly enough, high-pT Drell-Yan data offer competitive constraints on most new physics scenarios. Furthermore, the full set of correlated constraints from K, π and τ decays imposed by SU(2)L gauge invariance is considered. The bounds from D(s) decays, high-pT lepton tails and SU(2)L relations chart the space of the SMEFT affecting semi(leptonic) charm flavor transitions.

Significance Dicer is a ribonuclease III enzyme in biosynthesis of miRNAs, regulators of gene expression involved in macrophage differentiation. We found a specific truncation of Dicer in monocytic cells resulting from apparently constitutive cleavage by a serine protease. Inhibition of this proteolytic truncation, which occurred during macrophage differentiation in presence of TLR ligands or prostaglandin E2, up-regulates full-length Dicer and promotes miR biosynthesis. Regulation of transcription of pri-miRNA is one mode to regulate biosynthesis of mature miRNA. Inhibition of constitutive proteolysis of Dicer, as described here, provides a second layer of regulation, at the level of miRNA processing. Our data provide insights to Dicer and miRNAs in macrophage polarization/differentiation, a key process in the innate immune response. Dicer is a ribonuclease III enzyme in biosynthesis of micro-RNAs (miRNAs). Here we describe a regulation of Dicer expression in monocytic cells, based on proteolysis. In undifferentiated Mono Mac 6 (MM6) cells, full-length Dicer was undetectable; only an ∼50-kDa fragment appeared in Western blots. However, when MM6 cells were treated with zymosan or LPS during differentiation with TGF-β and 1,25diOHvitD3, full-length Dicer became abundant together with varying amounts of ∼170- and ∼50-kDa Dicer fragments. Mass spectrometry identified the Dicer fragments and showed cleavage about 450 residues upstream from the C terminus. Also, PGE2 (prostaglandin E2) added to differentiating MM6 cells up-regulated full-length Dicer, through EP2/EP4 and cAMP. The TLR stimuli strongly induced miR-146a-5p, while PGE2 increased miR-99a-5p and miR-125a-5p, both implicated in down-regulation of TNFα. The Ser protease inhibitor AEBSF (4-[2-aminoethyl] benzene sulfonyl fluoride) up-regulated full-length Dicer, both in MM6 cells and in primary human blood monocytes, indicating a specific proteolytic degradation. However, AEBSF alone did not lead to a general increase in miR expression, indicating that additional mechanisms are required to increase miRNA biosynthesis. Finally, differentiation of monocytes to macrophages with M-CSF or GM-CSF strongly up-regulated full-length Dicer. Our results suggest that differentiation regimens, both in the MM6 cell line and of peripheral blood monocytes, inhibit an apparently constitutive Dicer proteolysis, allowing for increased formation of miRNAs.

AIM To investigate the possible association between TNFα (-308 G/A) and IL-1β (-511 C/T) single nucleotide polymorphisms (SNPs) and GSTT and GSTM deletion polymorphisms and risk of apical periodontitis (AP) development, and determine the association of different genotypes with the presence of herpesviral infection in AP. METHODOLOGY The study included 120 periapical lesions and 200 control samples. Gene polymorphism analysis was performed using either polymerase chain reaction (PCR) or PCR/ restriction fragment length polymorphism (RFLP). Relative gene expression of TNF-α and IL-1β was analysed using reverse transcriptase - real-time PCR. The presence of Epstein-Barr virus (EBV) and human cytomegalovirus (HCMV) was assessed by nested PCR. Chi square and Fisher exact tests, and logistic regression analyses were done for polymorphisms, while Mann Whitney U-test was performed for the expression analysis. The expected frequency of variants was analysed by the Hardy-Weinberg equilibrium test. RESULTS TNF-α (-308 G/A) SNP increased AP susceptibility for heterozygous (Odds Ratio (OR) = 1.72, 95% Confidence Interval (CI) = 1.06-2.80, P = 0.027) and homozygous (OR = 8.55, 95% CI = 1.77-41.36, P < 0.001) carriers of the variant A allele. On the other hand, IL-1β (-511 C/T) polymorphism exerted a protective effect both in heterozygotes (OR = 0.540, 95% CI = 0.332-0.880, P = 0.013) and homozygotes (OR = 0.114, 95% CI = 0.026-0.501, P < 0.001). In addition, GSTM1 and GSTT1 null genotypes separately, as well as concomitantly were associated with an increased risk for AP development (P < 0.001). The null GSTT1 genotype increased approximately twice the risk of Epstein-Barr infection (EBV) in AP (OR= 2.17, 95% CI=1-4.71, P=0.048), while TNF-α SNP decreased it, both in heterozygotes (OR=0.20, 95% CI= 0.08-0.48, P<0.001) and AA homozygotes (OR=0.07, 95% CI=0.01-0.37, P=0.001). CONCLUSIONS GSTM and GSTT deletion polymorphisms, as well as TNFα (-308 G/A) SNP, are associated with increased risk, whereas IL-1β (-511 C/T) polymorphism decreases the risk of AP development. GSTT and TNFα polymorphisms also appear to modulate the risk of EBV infection in Serbian patients with apical periodontitis.

Background Diesel exhaust is carcinogenic and exposure to diesel particles cause health effects. We investigated the toxicity of diesel exhaust particles designed to have varying physicochemical properties in order to attribute health effects to specific particle characteristics. Particles from three fuel types were compared at 13% engine intake O 2 concentration: MK1 ultra low sulfur diesel (DEP13) and the two renewable diesel fuels hydrotreated vegetable oil (HVO13) and rapeseed methyl ester (RME13). Additionally, diesel particles from MK1 ultra low sulfur diesel were generated at 9.7% (DEP9.7) and 17% (DEP17) intake O 2 concentration. We evaluated physicochemical properties and histopathological, inflammatory and genotoxic responses on day 1, 28, and 90 after single intratracheal instillation in mice compared to reference diesel particles and carbon black. Results Moderate variations were seen in physical properties for the five particles: primary particle diameter: 15–22 nm, specific surface area: 152–222 m 2 /g, and count median mobility diameter: 55–103 nm. Larger differences were found in chemical composition: organic carbon/total carbon ratio (0.12–0.60), polycyclic aromatic hydrocarbon content (1–27 μg/mg) and acid-extractable metal content (0.9–16 μg/mg). Intratracheal exposure to all five particles induced similar toxicological responses, with different potency. Lung particle retention was observed in DEP13 and HVO13 exposed mice on day 28 post-exposure, with less retention for the other fuel types. RME exposure induced limited response whereas the remaining particles induced dose-dependent inflammation and acute phase response on day 1. DEP13 induced acute phase response on day 28 and inflammation on day 90. DNA strand break levels were not increased as compared to vehicle, but were increased in lung and liver compared to blank filter extraction control. Neutrophil influx on day 1 correlated best with estimated deposited surface area, but also with elemental carbon, organic carbon and PAHs. DNA strand break levels in lung on day 28 and in liver on day 90 correlated with acellular particle-induced ROS. Conclusions We studied diesel exhaust particles designed to differ in physicochemical properties. Our study highlights specific surface area, elemental carbon content, PAHs and ROS-generating potential as physicochemical predictors of diesel particle toxicity.

Introduction While medicine shortages are complex, their mitigation is more of a challenge. Prospective risk assessment as a means to mitigate possible shortages, has yet to be applied equally across healthcare settings. The aims of this study have been to: 1) gain insight into risk-prevention against possible medicine shortages among healthcare experts; 2) review existing strategies for minimizing patient-health risks through applied risk assessment; and 3) learn from experiences related to application in practice. Methodology A semi-structured questionnaire focusing on medicine shortages was distributed electronically to members of the European Cooperation in Science and Technology (COST) Action 15105 (28 member countries) and to hospital pharmacists of the European Association of Hospital Pharmacists (EAHP) (including associated healthcare professionals). Their answers were subjected to both qualitative and quantitative analysis (Microsoft Office Excel 2010 and IBM SPSS Statistics®) with descriptive statistics based on the distribution of responses. Their proportional difference was tested by the chi-square test and Fisher's exact test for independence. Differences in the observed ordinal variables were tested by the Mann-Whitney or Kruskal-Wallis test. The qualitative data were tabulated and recombined with the quantitative data to observe, uncover and interpret meanings and patterns. Results The participants (61.7%) are aware of the use of risk assessment procedures as a coping strategy for medicine shortages, and named the particular risk assessment procedure they are familiar with failure mode and effect analysis (FMEA) (26.4%), root cause analysis (RCA) (23.5%), the healthcare FMEA (HFMEA) (14.7%), and the hazard analysis and critical control point (HACCP) (14.7%). Only 29.4% report risk assessment as integrated into mitigation strategy protocols. Risk assessment is typically conducted within multidisciplinary teams (35.3%). Whereas 14.7% participants were aware of legislation stipulating risk assessment implementation in shortages, 88.2% claimed not to have reported their findings to their respective official institutions. 85.3% consider risk assessment a useful mitigation strategy. Conclusion The study indicates a lack of systematically organized tools used to prospectively analyze clinical as well as operationalized risk stemming from medicine shortages in healthcare. There is also a lack of legal instruments and sufficient data confirming the necessity and usefulness of risk assessment in mitigating medicine shortages in Europe.

In Europe, mixed mountain forests, primarily comprised of Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.), and European beech (Fagus sylvatica L.), cover about 10 × 106 ha at elevations between ∼600 and 1600 m a.s.l. These forests provide invaluable ecosystem services. However, the growth of these forests and the competition among their main species are expected to be strongly affected by climate warming. In this study, we analyzed the growth development of spruce, fir, and beech in moist mixed mountain forests in Europe over the last 300 years. Based on tree-ring analyses on long-term observational plots, we found for all three species (i) a nondecelerating, linear diameter growth trend spanning more than 300 years; (ii) increased growth levels and trends, the latter being particularly pronounced for fir and beech; and (iii) an elevation-dependent change of fir and beech growth. Whereas in the past, the growth was highest at lower elevations, today’s growth is superior at higher elevations. This spatiotemporal pattern indicates significant changes in the growth and interspecific competition at the expense of spruce in mixed mountain forests. We discuss possible causes, consequences, and silvicultural implications of these distinct growth changes in mixed mountain forests.

Klebsiella pneumoniae is the second most prevalent gram-negative rod that causes nosocomial infections in hospitalized or otherwise immunocompromised patients. It can develop multiple drug resistance that results in limited treatment options and increased use of carbapenems. Various mechanisms are related to the development of carbapenem resistance in K. pneumoniae. The aim of this study was to perform phenotypic and molecular characterization of clinical isolates of carbapenemase-producing K. pneumoniae from two outbreaks recorded in 2017 and 2018 in Clinical Center University of Sarajevo, Bosnia and Herzegovina. Identification of K. pneumoniae isolates was carried out on the basis of morphological, cultural, and biochemical characteristics. Interpretation of antimicrobial resistance was performed according to EUCAST breakpoints. There were four different resistotypes of carbapenemase-producing K. pneumoniae in this study and all were confirmed positive for blaOXA-48 carbapenemase. Rep-PCR fingerprinting of these strains showed the presence of the two different genetic patterns with no similarity between them. The monitoring, surveillance, and molecular typing are essential to control the emergence of multidrug-resistant strains in nosocomial settings, and to reduce the frequency of outbreak occurrence.

In this paper, a new fuzzy multi-criteria decision-making model for traffic risk assessment was developed. A part of a main road network of 7.4 km with a total of 38 Sections was analyzed with the aim of determining the degree of risk on them. For that purpose, a fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (fuzzy MARCOS) method was developed. In addition, a new fuzzy linguistic scale quantified into triangular fuzzy numbers (TFNs) was developed. The fuzzy PIvot Pairwise RElative Criteria Importance Assessment—fuzzy PIPRECIA method—was used to determine the criteria weights on the basis of which the road network sections were evaluated. The results clearly show that there is a dominant section with the highest risk for all road participants, which requires corrective actions. In order to validate the results, a comprehensive validity test was created consisting of variations in the significance of model input parameters, testing the influence of dynamic factors—of reverse rank, and applying the fuzzy Simple Additive Weighing (fuzzy SAW) method and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS). The validation test show the stability of the results obtained and the justification for the development of the proposed model.