Isolation of Staphylococcus aureus is quite common in both the general population and hospital environment. The heterogeneity of the disease and the unique ability of S. aureus to develop resistance to the most recently discovered antibacterial drugs points to its ability to adapt and survive in different conditions. CA-MRSA is different from hospital strains of MRSA by its epidemiological, phenotypic and genotypic characteristics. The emergence of MRSA in the community suggests the need for a new approach to managing the indications and the certification of staphylococcal infections, with special emphasis on the selection of empiric antibiotic therapy. In the study, we analised of MRSA from 4341 samples taken from patients from the general population of Sarajevo Canton in the six-month period of follow-up processed at the Public Health Institute of Sarajevo Canton. We determined the epidemiological characteristics of the isolated strains. Methicillin resistance was determined by phenotypic methods. The following molecular methods were used for the confirmation of methicillin resistance: determination of the mecA gene, PFGE profile, genetic type of MRSA being determined by spa typing, the distribution of SCCmec types being examined, and the detected gene for PVL. The study stresses the need for national monitoring of spreading of the existing epidemic strains, as well as the monitoring of emergence of new strains which would enable the inclusion of our country in the international network of monitoring bacterial resistance.

Simple Summary Gliobastoma is one of the deadliest tumors overall, yet the most common malignant brain tumor. The new World Health Organization Classification of Brain Tumors brought changes in how we look at this type of malignancy. Now we know that glioblastoma is rather a spectrum of similar tumors, but with some distinct characteristics that include molecular footprint, response to therapy and with that overall survival, among others. We hypothesised that by employing phosphorous magnetic resonance we will be able to show differences in cellular energy metabolism in these various subtypes of glioblastoma. For example, we found indices of faster cell reproduction and tumor growth in MGMT-methylated and EGFR-amplified tumors. These tumors also could have reduced energetic state or tissue oxygenation due to the increased necrosis. Tumors with EGFR-amplification could have increased apoptotic activity regardless of their MGMT status. Our study indicated various differences in energetic metabolism in tumors with different molecular characteristics, which could potentially be important in future therapeutic strategies. Abstract The World Health Organisation’s (WHO) classification of brain tumors requires consideration of both histological appearance and molecular characteristics. Possible differences in brain energy metabolism could be important in designing future therapeutic strategies. Forty-three patients with primary, isocitrate dehydrogenase 1 (IDH1) wild type glioblastomas (GBMs) were included in this study. Pre-operative standard MRI was obtained with additional phosphorous magnetic resonance spectroscopy (31-P-MRS) imaging. Following microsurgical resection of the tumors, biopsy specimens underwent neuropathological diagnostics including standard molecular diagnosis. The spectroscopy results were correlated with epidermal growth factor (EGFR) and O6-Methylguanine-DNA methyltransferase (MGMT) status. EGFR amplified tumors had significantly lower phosphocreatine (PCr) to adenosine triphosphate (ATP)-PCr/ATP and PCr to inorganic phosphate (Pi)-PCr/Pi ratios, and higher Pi/ATP and phosphomonoesters (PME) to phosphodiesters (PDE)-PME/PDE ratio than those without the amplification. Patients with MGMT-methylated tumors had significantly higher cerebral magnesium (Mg) values and PME/PDE ratio, while their PCr/ATP and PCr/Pi ratios were lower than in patients without the methylation. In survival analysis, not-EGFR-amplified, MGMT-methylated GBMs showed the longest survival. This group had lower PCr/Pi ratio when compared to MGMT-methylated, EGFR-amplified group. PCr/Pi ratio was lower also when compared to the MGMT-unmethylated, EGFR not-amplified group, while PCr/ATP ratio was lower than all other examined groups. Differences in energy metabolism in various molecular subtypes of wild-type-GBMs could be important information in future precision medicine approach.

Emerging sets of single-cell sequencing data makes it appealing to apply existing tumor phylogeny reconstruction methods to analyze associated intratumor heterogeneity. Unfortunately, tumor phylogeny inference is an NP-hard problem and existing principled methods typically fail to scale up to handle thousands of cells and mutations observed in emerging single-cell data sets. Even though there are greedy heuristics to build hierarchical clustering of cells and mutations, they suffer from well-documented issues in accuracy. Additionally even when “optimal” solutions are feasible, existing approaches only provide a single “most likely” tree to depict the evolutionary processes that may result in an observed collection of cells and mutations. To make matters worse, the vast majority of single-cell sequencing data sets are transcriptomic and as a result, suffer from considerable variation in coverage across mutational loci. In this paper, we introduce Trisicell, a computational toolkit for scalable tumor phylogeny reconstruction and validation from single-cell genomic, exomic or transcriptomic sequencing data. Trisicell has three components: (i) Trisicell-DnC, a new tumor phylogeny reconstruction method from genotype matrices derived from single-cell data, (ii) Trisicell-ConT a new algorithm for constructing the consensus for two or more tumor phylogenies - which may be built through the use of different data types on the same set of cells, or built through the use of different methods on the same data, and (iii) Trisicell-PF, a new partition function method for assessing the likelihood of any user-defined subtree/set of cells to be seeded by a given set of mutations in the phylogeny. Collectively, these tools provide means of identifying and validating robust portions of a tumor phylogeny, offering the ability to focus on the most important (sub)clones and the genomic alterations that seed the associated clonal expansion. We applied Trisicell to a panel of clonal sublines derived from single-cells of a parental mouse melanoma model on which we performed both whole exome and whole transcriptome sequencing. The tumor phylogenies of the clonal sublines built on exomic and transcriptomic mutations by Trisicell-DnC, were shown by Trisicell-ConT to be highly similar and the subtrees comprised of phenotypically similar clonal sublines were shown to be strongly associated by Trisicell-PF to their seeding mutations. In addition, we applied Trisicell to single-cell whole transcriptome sequencing data from a tumor derived from the same parental melanoma cell line, which was subjected to anti-CTLA-4 immunotherapy. The phylogenies generated from both studies featured distinct subtrees, strongly associated with phenotypes including cell differentiation status, tumor growth and therapeutic response. These results suggest that Trisicell can be used for scalable tumor phylogeny reconstruction and validation through both single-cell and clonal-subline sequencing data, which may reveal strong phenotypic associations. In particular, they suggest that the developmental status and phenotypic intratumoral heterogeneity of melanoma originates from observable subclonal variation. Citation Format: Farid Rashidi Mehrabadi, Salem Malikic, Kerrie L. Marie, Eva Perez-Guijarro, Erfan Sadeqi Azer, Howard H. Yang, Can Kizilkale, Charli Gruen, Huaitian Liu, Christina Marcelus, Aydin Buluc, Funda Ergun, Maxwell P. Lee, Glenn Merlino, Chi-Ping Day, S. Cenk Sahinalp. Trisicell: Scalable Tumor Phylogeny Reconstruction and Validation Reveals Developmental Origin and Therapeutic Impact of Intratumoral Heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB019.

The heritability of methylation patterns in tumor cells, as shown in recent studies, suggests that tumor heterogeneity and progression can be interpreted and predicted in the context of methylation changes. To elucidate methylation-based evolution trajectory in tumors, we introduce a novel computational method for methylation phylogeny reconstruction leveraging single cell bisulfite treated whole genome sequencing data (scBS-seq), incorporating additional copy number information inferred independently from matched single cell RNA sequencing (scRNA-seq) data, when available. We validate our method with the scBS-seq data of multi-regionally sampled colorectal cancer cells, and demonstrate that the cell lineages constructed by our method strongly correlate with original sampling regions. Our method consists of three components: (i) noise-minimizing site selection, (ii) likelihood-based sequencing error correction, and (iii) pairwise expected distance calculation for cells, all designed to mitigate the effect of noise and uncertainty due to data sparsity commonly observed in scBS-seq data. In (i), we present an integer linear program-based biclustering formulation to select a set of CpG-sites and cells so that the number of CpG-sites with non-zero coverage in the selected cells is maximized. This procedure filters out cells with read information in too few sites and CpG-sites with read information in too few cells. In (ii), we address the sequencing errors commonly encountered in currently available platforms with a maximum log likelihood approach to correct likely sequencing errors in scBS-seq reads, incorporating CpG-site copy number information in case it can be orthogonally obtained. Given the copy number and read information for a site in a cell, together with the overall sequencing error probability, we compute the log likelihood for all possible underlying allele statuses. If the mixed read statuses at the CpG-site for the cell are more likely due to sequencing error on homozygous alleles as opposed to the presence of alleles mixed methylation statuses, we correct the reads of the minority methylation status to the majority one. In (iii), we introduce a formulation to estimate distances between any pair of cells. As scBS-seq data is typically characterized by shallow read coverage, there is rarely read count evidence for two (or more, depending on CNV status) alleles at a CpG-site. Since allele-specific methylation has been shown to have increased frequency in cancer tissues, given the reads at a CpG-site, it is especially important to consider the possibility of unobserved alleles and their methylation status when determining the CpG-site9s possible methylation zygosities. Our method incorporates copy number information when available, and for each CpG-site in a cell, we compute a probability distribution across all possible methylation zygosities. Then, given specific distance values between pairs of distinct zygosities and the likelihood of each possible zygosity for each shared CpG-site in both cells, we compute the expected total distance between any pair of cells as the mean of expected distances across all shared CpG-sites. We leverage such pairwise distances in methylation phylogeny construction. Citation Format: Xuan C. Li, Yuelin Liu, Farid Rashidi, Salem Malikic, Stephen M. Mount, Eytan Ruppin, Kenneth Aldape, Cenk Sahinalp. Epigenomic tumor evolution modeling with single-cell methylation data profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB020.

Summary Stress at the work place was declared by the World Health Organization as a worldwide epidemic. The stress caused by work appears when the balance between one’s own possibilities and the environment demands is disturbed, which leads to a poor mental state. The fact is that the majority of dentists find they are under constant stress, which is caused by the nature of dental work. Literature describes dentistry as an extremely stressful profession. The main stressors include the tendency toward technical perfection, the causation of pain in patients, the lack of patient cooperation during dental treatment, the failure to maintain the given appointments. Adequate education and preparation, even during dental studies, non-neglect of symptoms and difficulties at the work place, adequate and timely response to the identification of the cause and its elimination or balancing, have a key role in solving this great problem in modern dentistry.

Background: The objective of this study was to evaluate the efficacy of modified clinoptilolite (Minazel Plus®, MZ) as a mycotoxin adsorbent for preventing the negative the effects of ochratoxin A (OTA) on performance, pathohistological changes, and OTA residue in the eggs of laying hens. Methods: Forty eight (n = 48) laying hens (27 weeks old) were equally divided into six groups and depending on the type of addition were allocated to the following experimental treatments for 7 weeks: E-I group-1 mg/kg OTA; E-II group 0.25 mg/kg OTA; E-III group 1 mg/kg OTA + 0.2% of MZ; E-IV group 0.25 mg/kg OTA + 0.2% of MZ; MZ group supplemented with 0.2% of the adsorbent; and control (K, without feed additive). Results: Overall, the addition of 0.2% MZ to laying hen feed mitigated the harmful effects of OTA on target organs and reduced the presence of OTA residue in eggs. The groups that received 0.2% of MZ achieved better production results in terms of body weight, number of eggs, and feed consumption, compared to the other treatments. Conclusions: The current findings confirm the efficacy of MZ in preventing performance losses in laying hens exposed to OTA, as well as for improving the welfare and health of food producing animals.

The purpose of this study was to determine the level of gross motor skills in ASD children during the COVID-19 Pandemic. Participants in this study were ASD children with a total of 25 children aged 8-12 years (M = 10.02;SD 1.27), who were selected by random sampling technique. This research instrument is the Test of Gross Motor Development-2 (TGMD-2). Data analysis in this study is descriptive analysis. The results of gross motor skills show that 20 ASD children are in the average standard score of 4-5 (gross motor question = 70-79) in the low assessment category (80.00%) and 5 ASD children are in the average standard score of 1-3 (gross motor question = <70) is included in the very low assessment category (20.00%). Therefore, the majority of the total gross motoric data for ASD children are in the low category, namely 20 children or 80.00%. This research is not without limitations in its implementation. This research contributes to the implementation of future research, namely the need for treatment to optimize Gross Motor skills in Children with Autism Spectrum Disorder during the COVID-19 Pandemic. The urgency for proper and measurable treatment and the limitations of this study are important things to pay attention to for further research. © 2021 by authors, all rights reserved.

ABSTRACT Introduction The need to individualize a drug dosage and adjust it to a patient’s physiological and/or pathophysiological status is rarely satisfied in routine clinical practice, primarily because of complexity of the adjustment task. Areas covered The aim of this article is to shed light to basic principles of drug dosage individualization in the most frequent clinical states that affect pharmacokinetics of drugs. The principles are derived from published clinical studies conducted on diverse patient populations, using non-compartmental pharmacokinetic model. Expert opinion Simple, but sufficiently exact, way to calculate appropriate drug dose for a patient is the one based on target average steady-state concentration and non-compartmental pharmacokinetic model. If target steady-state drug concentration and dosage interval are considered fixed, maintenance dose could be adjusted on the basis of expected changes of total drug clearance and bioavailability, while loading dose should be related to changes of volume of distribution and bioavailability. Relative increase or decrease of these pharmacokinetic parameters in regard to normal values in healthy persons is translated to relative (percentual) increase or decrease of maintenance and loading doses recommended in the drug monograph.

Abstract:This paper analyses impact of aircraft noise on community around Podgorica Airport, Montenegro. The airport is located 12 km from the city centre of the Montenegro capital, Podgorica. It served 1.3 million passengers and 7.5 thousand operations in 2019. The noise impact assessment is conducted in IMPACT web-based modelling platform using the distribution of operations by aircraft types, time of the day, and radar tracks for the busiest day (August 15) in 2019. Noise contours are assessed for Lden and Lnight indicators. They were merged with the Global Human Settlement Layer to assess the number of people exposed to different noise levels. In addition, based on the World Health Organization recommended exposure levels related to their health implications, the percentages of the population highly annoyed and highly sleep-disturbed are estimated. Furthermore, facilities of public importance (schools, hospitals, churches, etc.) are assessed against compatibility with the requirements set for the Zones with increased noise protection in national regulations. The results show that the exposure of community around Podgorica Airport to aircraft noise is still not a serious issue. The near vicinity of the airport is industrial zone and the number of people highly annoyed by noise is approximately 3.2% of the total city population. Nevertheless, it is crucial to draw attention to planners to preserve airport neighbourhood from potential inhabiting, to avoid problems that some airports in the region are facing nowadays.

Chronic inflammatory lung diseases are characterized by uncontrolled immune response in the airways as their main pathophysiological manifestation. The lack of specific diagnostic and therapeutic biomarkers for many pulmonary diseases represents a major challenge for pulmonologists. The majority of the currently approved therapeutic approaches are focused on achieving disease remission, although there is no guarantee of complete recovery. It is known that angiotensin-converting enzyme 2 (ACE2), an important counter-regulatory component of the renin–angiotensin–aldosterone system (RAAS), is expressed in the airways. It has been shown that ACE2 plays a role in systemic regulation of the cardiovascular and renal systems, lungs and liver by acting on blood pressure, electrolyte balance control mechanisms and inflammation. Its protective role in the lungs has also been presented, but the exact pathophysiological mechanism of action is still elusive. The aim of this study is to review and discuss recent findings about ACE2, including its potential role in the pathophysiology of chronic inflammatory lung diseases:, i.e., chronic obstructive pulmonary disease, asthma, and pulmonary hypertension. Additionally, in the light of the coronavirus 2019 disease (COVID-19), we will discuss the role of ACE2 in the pathophysiology of this disease, mainly represented by different grades of pulmonary problems. We believe that these insights will open up new perspectives for the future use of ACE2 as a potential biomarker for early diagnosis and monitoring of chronic inflammatory lung diseases.