Staphylococcus aureus is a major cause of hospital-acquired infections worldwide. Increased frequency of methicillin-resistant Staphylococcus aureus (MRSA) in hospitalized patients and possibility of vancomycin resistance requires rapid and reliable characterization of isolates and control of MRSA spread in hospitals. Typing of isolates helps to understand the route of a hospital pathogen spread. The aim of this study was to investigate and compare genotypic and phenotypic characteristics of MRSA samples on three different geography locations. In addition, our aim was to evaluate three different methods of MRSA typing: spa-typing, agr-typing and GenoType MRSA.  We included 104 samples of MRSA, isolated in 3 different geographical locations in clinical hospitals in Zagreb, Mostar, and Heidelberg, during the period of six months. Genotyping and phenotyping were done by spa-typing, agr-typing and dipstick assay GenoType MRSA. We failed to type all our samples by spa-typing.  The most common spa-type in clinical hospital Zagreb was t041, in Mostar t001, and in Heidelberg t003.We analyzed 102/104 of our samples by agr-typing method. We did not find any agr-type IV in our locations. We analyzed all our samples by the dipstick assay GenoType MRSA. All isolates in our study were MRSA strains. In Zagreb there were no positive strains to PVL gene. In Mostar we have found 5/25 positive strains to PVL gene, in Heidelberg there was 1/49. PVL positive isolates were associated with spa-type t008 and agr-type I, thus, genetically, they were community-associated MRSA (CA-MRSA). Dipstick assay GenoType MRSA has demonstrated sufficient specificity, sensibility, simple performance and low cost, so we could introduce it to work in smaller laboratories. Using this method may expedite MRSA screening, thus preventing its spread in hospitals.

The aims of this study were: 1) To determine the effects of a 12-week recreational soccer training programme and continuous endurance running on body composition of young adult men and 2) to determine which of these two programmes was more effective concerning body composition. Sixty-four participants completed the randomized controlled trial and were randomly assigned to one of three groups: a soccer training group (SOC; n=20), a running group (RUN; n=21) or a control group performing no physical training (CON; n=23). Training programmes for SOC and RUN lasted 12-week with 3 training sessions per week. Soccer sessions consisted of 60 min ordinary five-a-side, six-a-side or seven-a-side matches on a 30-45 m wide and 45-60 m long plastic grass pitch. Running sessions consisted of 60 min of continuous moderate intensity running at the same average heart rate as in SOC (~80% HRmax). All participants, regardless of group assignment, were tested for each of the following dependent variables: body weight, body height, body mass index, percent body fat, body fat mass, fat-free mass and total body water. In the SOC and RUN groups there was a significant decrease (p < 0.05) in body composition parameters from pre- to post-training values for all measures with the exception of fat-free mass and total body water. Body mass index, percent body fat and body fat mass did not differ between groups at baseline, but by week 12 were significantly lower (p < 0.05) in the SOC and RUN groups compared to CON. To conclude, recreational soccer training provides at least the same changes in body composition parameters as continuous running in young adult men when the training intensity is well matched.

We present a combined analysis of LHC Higgs data (signal strengths) together with LEP-2 WW production measurements. To characterize possible deviations from the standard model (SM) predictions, we employ the framework of an effective field theory (EFT) where the SM is extended by higher-dimensional operators suppressed by the mass scale of new physics Λ. The analysis is performed consistently at the order Λ(-2) in the EFT expansion keeping all the relevant operators. While the two data sets suffer from flat directions, together they impose stringent model-independent constraints on the anomalous triple gauge couplings.

Highlights from ASCO 2015 demonstrate the impasse we face in solid tumour oncology: the compelling novel immune and targeted therapies are often associated with cost–benefit ratios significantly above the thresholds for reimbursement. This is at least in part a consequence of our incomplete understanding of the mechanisms of response and resistance to these agents. For example, ipilimumab is associated with durable clinical benefit in 15%–20% of unselected advanced melanoma patients (∼£75 000 per patient treated), and while the responses to single-agent targeted therapies such as vemurafenib are higher, they are often relatively short-lived (∼£42 000 per median PFS of 6–7 months). New trial design strategies such as basket and umbrella studies have improved upon patient selection, but have not yielded detailed biological understanding of the drug targets, nor polygenic mechanisms of resistance within or between patients. Academically led studies have the opportunity and the responsibility to prioritize biological insights as trial end points, maximising research gain, increasing patient benefit/safety and ultimately, improving cost-effectiveness. Collection of tumour material is fundamental to these aims but the timing, handling and sample analysis are of critical importance (Figure ​(Figure11). Figure 1. A schematic for biological sample collection throughout the course of disease and treatment. TILs, tumour-infiltrating lymphocytes; cfDNA, cell-free tumour DNA; PBMCs, peripheral mononuclear blood cells; PK, pharmacokinetic; PD, pharmacodynamic; PDX, ... Resistance to targeted therapies can be mediated by pre-existing rather than de novo alterations. High resolution tracking of cancer cells in vitro demonstrated that only 10% of resistant clones arise de novo [1], while mathematical models of tumour growth suggest that radiographically detectable lesions harbour at least 10 resistant sub-clones [2]. Thus, comprehensive upfront tumour profiling could anticipate the genetic composition of such clone(s), while taking into account spatial and temporal tumour heterogeneity. Extensive sampling of metastatic sites at autopsy revealed 10 distinct PTEN alterations emerging under the selective pressure of PI(3)Kα inhibition [3], and five independent reversion events in a germline BRCA2 mutant carrier who progressed on olaparib and carboplatin [4]. Distinct mechanisms of BRAF and EGFR inhibitor resistance were detected across multiple metastases within individual patients with melanoma [5] and colorectal cancer [6], respectively. The benefit of combination strategies can be limited by excess toxicity (combined targeting of the PI3K and MAPK pathways [7]), cross-resistance (BRAF and MEK inhibitors in melanoma [8]) and the persistent role of intra-tumour heterogeneity (targeting of the T790M EGFR mutation in lung cancer [9]). Informed by pre-clinical models, such as discontinuous dosing in BRAF-mutant melanoma [10], academically led trials can address more finely tuned ways of managing treatment resistance. In colorectal cancer cell-free tumour DNA (cfDNA) shows pulsatile levels of mutant KRAS in response to intermittent EGFR inhibition [11], providing the molecular rationale for re-challenge with targeted therapy. Similar frameworks are required to prospectively evaluate alternative or sequential scheduling as well as the role of cfDNA in tracking tumour progression. PD-L1 expression, a putative predictive marker for PD1/PDL1 inhibition, is also spatially heterogeneous [12]. Genomic data are a promising alternative biomarker in this area [13]. Mutational data, integrated with HLA typing, and tumour and peripheral T-cell profiling can define individual neo-antigenic repertoires. Academically led studies of immunotherapeutic agents must evaluate the ability of this approach to predict responses, inform immunotherapy/targeted combinations, and ultimately, facilitate adoptive T-cell therapy. Non-genetic causes of treatment resistance have been largely overlooked but studies that incorporate longitudinal biological sample collection and novel imaging techniques are well placed to examine tumour drug exposure (including heterogeneity of drug distribution [14]) and individual variation in drug metabolising enzymes, receptors, and transporters. Patient-derived xenografts can provide a useful platform for investigating personalised therapy in co-clinical trials [15], but only if robustly characterised and used in the full knowledge of their limitations (e.g. immunosuppressed host, mouse stroma and disparities in tumour burden between mouse and patient). There clearly are challenges to implementation of such complex studies but they can be overcome through close interdisciplinary work of academic/clinical consortia as illustrated by the Lung TRACERx programme [16], the use of measures such as one-time consent [17], post-mortem studies and stakeholder engagement (patient and public). In summary, we argue for a change of emphasis in drug development from learning little from many patients towards biologically rich clinical studies focussed on gleaning the maximum amount of biological information that might inform drug response and resistance for every patient entered into academic trial protocols.

Tendo como base o conceito de modernizacao territorial proposto por Milton Santos, a pesquisa em curso analisa os impactos economico, social e ambiental causados pela implantacao de um projeto imobiliario tipo resort denominado Complexo Turistico-Residencial Fazenda de Sao Bento da Lagoa em uma Area de Protecao Ambiental (APA) no municipio de Marica/Rio de Janeiro. Trata-se de espaco de extrema relevância, pois ali ocorre tanto a pesca artesanal da comunidade tradicional de Zacarias quanto uma serie pesquisas cientificas coordenadas por biologos de todo o pais. Resgatando a situacao dos atingidos e a conjuntura que envolve tal implantacao, examinamos tambem os Estudos de Impacto Ambiental (EIA) apresentado pelo grupo imobiliario ao Instituto Estadual do Ambiente (INEA), bem como a posicao do governo do Estado do Rio de Janeiro nas audiencias publicas ocorridas para a aprovacao do resort.

We read with great interest the article by Serman LJ et al. [1] about evaluation of the structural changes in the rat placenta during the last third of gestation, assessed by stereology. The authors concluded that the absolute volume of the whole placenta as well as the labyrinth had increased from day 16 to day 19 of gestation. In contrast, the volume density of glycogenic cells and trophoblast giant cells was higher on gestation day 16 than on day 19, probably due to the intensive trophoblast invasion during that time. Since stereological analysis assigns numerical values to analyzed structures, such outcomes ensure valid and exact comparison of healthy and pathologically altered tissue. In addition, comparison can be done between the tissues in different developing phases of an organ, as it was represented in this article.

AIM To investigate the characteristics of meticillin-resistant S. aureus (MRSA), extended-spectrum (ESBL), and plasmid-mediated AmpC beta-lactamase producing Gram-negative bacteria causing skin and soft tissue infections (SSTIs) in hospital and outpatient settings of Zenica-Doboj Canton, Bosnia and Herzegovina. METHODS Antibiotic susceptibility was determined by disc-diffusion and broth microdillution methods according to CLSI guidelines. MecA gene was detected by PCR, and genetic characterization of MRSA was performed using spa-typing and the algorithm based upon repeat patterns (BURP). Double-disk-synergy test was used to screen for ESBLs. PCR was used to detect blaESBL alleles. Genetic relatedness of the strains was tested by PFGE. RESULTS Seventeen in-patients with MRSA, 13 with ESBL-producing Gram-negative bacteria and three patients co-infected with both, were detected. Five MRSA and 16 ESBL-producing Gram-negative bacteria were found in outpatient samples. Klebsiella spp. was isolated in 11 in- and seven outpatients. MLST CC152 was the most prevalent MRSA. Seven (38.9%) Klebsiella spp. yielded amplicons with primers specific for SHV, TEM-1 and CTX-M group 1 β-lactamases. Eight K. pneumonia (44.4%) and 16 (64%) MRSA (including the in- and outpatient) strains were clonally related. CONCLUSION The presence of MRSA and ESBL-producing organisms causing SSTIs in the community poses a substantial concern, due to the high morbidity and mortality associated with possible consequent hospital infections.

Accidental falls are a major problem in later life, reducing the overall well-being, independence, mobility and quality of life of the elderly and those who care for them. The social and economic burden of falls is becoming unsustainable, considering the huge direct and indirect costs associated with each fall and the progressive ageing of the population in industrialised countries. Falls are related to complex and dynamic interactions between intrinsic, subject-specific, and extrinsic, circumstance-related, risk factors. Therefore, the prevention and management of falls in later life still represents a critical challenge for active and healthy ageing. Many healthcare technologies have been proposed to address this in recent years, ranging from fall risk screening and assessment to fall detection and, in more recent studies, fall prediction. However, several critical issues remain, mainly regarding the effectiveness of the proposed solutions, their usability in real environments, sustainability, performance, assessment and technological limitations. The lack of specificity in fall risk assessment, a limited effectiveness in fall prediction and the inability to reliably monitor spontaneous falls in real life conditions with un-obstructive technological solutions remain key unsolved problems. This special issue collects a selection of works across these healthcare technologies giving a snapshot of the latest research in this area. The first paper is an invited literature review on automatic methods for the assessment of fall risk based on statistical machine learning approaches applied to features extracted from wearable accelerometers and/or gyroscopes. This study identified five major recurrent limits identified among the 30 studies included in this review, which the reader of this special issue may consider while designing future studies: publication bias, limited/inadequate sample size, poor model validation, inappropriate model complexity with respect to the available data and poor outcome definition. The second paper in this issue reports a collaborative research effort between Italy, UK and Croatia, investigating the associations between depressed heart rate variability (HRV) and the risk of falling in patients suffering from hypertension. This cross section study enrolled 170 patients over two years, concluding that there is a significant association between depressed HRV and risk of falling, suggesting that it is possible to automatically detect autonomous nervous system states that may lead to falls. The third paper investigates the impact of various parameters on the accuracy vs. energy efficiency of a wearable activity recognition system, based on accelerometers. This study proved that sampling frequency, transmission rate, and method of nodal processing can impact significantly in satisfying the requirement of an activity recognition system. The final paper proposes a framework for fall detection based on wearable accelerometric sensors and machine learning techniques. The paper offers an interesting perspective and reports promising results, although preliminarily tested on a small sample of simulated falls. We hope that you will enjoy reading this special issue, in which some of the challenges of healthcare technologies for fall prediction, detection and risk assessment are examined through a range of different applications.

We show how leading radiative corrections can be implemented in the general description of h→4ℓ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h\rightarrow 4\ell $$\end{document} decays by means of pseudo observables (PO). With the inclusion of such corrections, the PO description of h→4ℓ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h\rightarrow 4\ell $$\end{document} decays can be matched to next-to-leading-order electroweak calculations both within and beyond the Standard Model (SM). In particular, we demonstrate that with the inclusion of such corrections the complete next-to-leading-order SM prediction for the h→2e2μ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$h\rightarrow 2e2\mu $$\end{document} dilepton mass spectrum is recovered within 1%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1\,\%$$\end{document} accuracy. The impact of radiative corrections for non-standard PO is also briefly discussed.