1,076 research outputs found
Acceptability and feasibility of peer assisted supervision and support for intervention practitioners: a Q-methodology evaluation
Evidence-based interventions often include quality improvement methods to support fidelity and improve client outcomes. Clinical supervision is promoted as an effective way of developing practitioner confidence and competence in delivery; however, supervision is often inconsistent and embedded in hierarchical line management structures that may limit the opportunity for reflective learning. The Peer Assisted Supervision and Support (PASS) supervision model uses peer relationships to promote the self-regulatory capacity of practitioners to improve intervention delivery. The aim of the present study was to assess the acceptability and feasibility of PASS amongst parenting intervention practitioners. A Q-methodology approach was used to generate data and 30 practitioners volunteered to participate in the study. Data were analyzed and interpreted using standard Q-methodology procedures and by-person factor analysis yielded three factors. There was consensus that PASS was acceptable. Participants shared the view that PASS facilitated an environment of support where negative aspects of interpersonal relationships that might develop in supervision were not evident. Two factors represented the viewpoint that PASS was also a feasible model of supervision. However, the third factor was comprised of practitioners who reported that PASS could be time consuming and difficult to fit into existing work demands. There were differences across the three factors in the extent to which practitioners considered PASS impacted on their intervention delivery. The findings highlight the importance of organizational mechanisms that support practitioner engagement in supervision
Logic programming and artificial neural networks in breast cancer detection
About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013
Identification of target genes of transcription factor activator protein 2 gamma in breast cancer cells
<p>Abstract</p> <p>Background</p> <p>Activator protein 2 gamma (AP-2γ) is a member of the transcription factor activator protein-2 (AP-2) family, which is developmentally regulated and plays a role in human neoplasia. AP-2γ has been found to be overexpressed in most breast cancers, and have a dual role to inhibit tumor initiation and promote tumor progression afterwards during mammary tumorigensis.</p> <p>Methods</p> <p>To identify the gene targets that mediate its effects, we performed chromatin immunoprecipitation (ChIP) to isolate AP-2γ binding sites on genomic DNA from human breast cancer cell line MDA-MB-453.</p> <p>Results</p> <p>20 novel DNA fragments proximal to potential AP-2γ targets were obtained. They are categorized into functional groups of carcinogenesis, metabolism and others. A combination of sequence analysis, reporter gene assays, quantitative real-time PCR, electrophoretic gel mobility shift assays and immunoblot analysis further confirmed the four AP-2γ target genes in carcinogenesis group: ErbB2, CDH2, HPSE and IGSF11. Our results were consistent with the previous reports that ErbB2 was the target gene of AP-2γ. Decreased expression and overexpression of AP-2γ in human breast cancer cells significantly altered the expression of these four genes, indicating that AP-2γ directly regulates them.</p> <p>Conclusion</p> <p>This suggested that AP-2γ can coordinate the expression of a network of genes, involving in carcinogenesis, especially in breast cancer. They could serve as therapeutic targets against breast cancers in the future.</p
Body fatness and physical activity at young ages and the risk of breast cancer in premenopausal women
We examined the relationship between body fatness, sports participation and breast cancer risk in 1560 premenopausal cases and 1548 controls, from three related population-based case–control studies in the UK. Half of the women with breast cancer were aged less than 36 years at diagnosis. Women who perceived themselves as plump at age 10 years had a relative risk of 0.83 (95% confidence interval 0.69–0.99, P=0.03) as compared with those who perceived themselves as thin. Self-reported obesity compared with leanness at diagnosis was associated with a relative risk of 0.78 (95% confidence interval 0.56–1.06, P=0.11). Women who reported having been plump at age 10 years and overweight or obese at diagnosis had a relative risk of 0.75 (95% confidence interval 0.56–1.01, P=0.06) as compared with those who reported being thin at age 10 years and at diagnosis. Findings for three related measures of body fatness suggested that obesity is associated with a reduced risk of premenopausal breast cancer. There was no association between sports participation and breast cancer risk in these premenopausal women. The relative risk for spending an average of more than 1 h per week in sports compared with less from ages 12 to 30 years was 1.00 (95% CI 0.86–1.16, P=0.98)
A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI
Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector
Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente
Hospital service areas – a new tool for health care planning in Switzerland
BACKGROUND: The description of patient travel patterns and variations in health care utilization may guide a sound health care planning process. In order to accurately describe these differences across regions with homogeneous populations, small area analysis (SAA) has proved as a valuable tool to create appropriate area models. This paper presents the methodology to create and characterize population-based hospital service areas (HSAs) for Switzerland. METHODS: We employed federal hospital discharge data to perform a patient origin study using small area analysis. Each of 605 residential regions was assigned to one of 215 hospital provider regions where the most frequent number of discharges took place. HSAs were characterized geographically, demographically, and through health utilization indices and rates that describe hospital use. We introduced novel planning variables extracted from the patient origin study and investigated relationships among health utilization indices and rates to understand patient travel patterns for hospital use. Results were visualized as maps in a geographic information system (GIS). RESULTS: We obtained 100 HSAs using a patient origin matrix containing over four million discharges. HSAs had diverse demographic and geographic characteristics. Urban HSAs had above average population sizes, while mountainous HSAs were scarcely populated but larger in size. We found higher localization of care in urban HSAs and in mountainous HSAs. Half of the Swiss population lives in service areas where 65% of hospital care is provided by local hospitals. CONCLUSION: Health utilization indices and rates demonstrated patient travel patterns that merit more detailed analyses in light of political, infrastructural and developmental determinants. HSAs and health utilization indices provide valuable information for health care planning. They will be used to study variation phenomena in Swiss health care
Enhancement of crystallization with nucleotide ligands identified by dye-ligand affinity chromatography
Ligands interacting with Mycobacterium tuberculosis recombinant proteins were identified through use of the ability of Cibacron Blue F3GA dye to interact with nucleoside/nucleotide binding proteins, and the effects of these ligands on crystallization were examined. Co-crystallization with ligands enhanced crystallization and enabled X-ray diffraction data to be collected to a resolution of at least 2.7 Å for 5 of 10 proteins tested. Additionally, clues about individual proteins’ functions were obtained from their interactions with each of a panel of ligands
Eukaryotic Evolutionary Transitions Are Associated with Extreme Codon Bias in Functionally-Related Proteins
Codon bias in the genome of an organism influences its phenome by changing the speed and efficiency of mRNA translation and hence protein abundance. We hypothesized that differences in codon bias, either between-species differences in orthologous genes, or within-species differences between genes, may play an evolutionary role. To explore this hypothesis, we compared the genome-wide codon bias in six species that occupy vital positions in the Eukaryotic Tree of Life. We acquired the entire protein coding sequences for these organisms, computed the codon bias for all genes in each organism and explored the output for relationships between codon bias and protein function, both within- and between-lineages. We discovered five notable coordinated patterns, with extreme codon bias most pronounced in traits considered highly characteristic of a given lineage. Firstly, the Homo sapiens genome had stronger codon bias for DNA-binding transcription factors than the Saccharomyces cerevisiae genome, whereas the opposite was true for ribosomal proteins – perhaps underscoring transcriptional regulation in the origin of complexity. Secondly, both mammalian species examined possessed extreme codon bias in genes relating to hair – a tissue unique to mammals. Thirdly, Arabidopsis thaliana showed extreme codon bias in genes implicated in cell wall formation and chloroplast function – which are unique to plants. Fourthly, Gallus gallus possessed strong codon bias in a subset of genes encoding mitochondrial proteins – perhaps reflecting the enhanced bioenergetic efficiency in birds that co-evolved with flight. And lastly, the G. gallus genome had extreme codon bias for the Ciliary Neurotrophic Factor – which may help to explain their spontaneous recovery from deafness. We propose that extreme codon bias in groups of genes that encode functionally related proteins has a pathway-level energetic explanation
Development of a heptaplex PCR assay for identification of Staphylococcus aureus and CoNS with simultaneous detection of virulence and antibiotic resistance genes
Background
Staphylococcal toxicity and antibiotic resistance (STAAR) have been menacing public health. Although vancomycin-resistant Staphylococcus aureus (VRSA) is currently not as widespread as methicillin-resistant S. aureus (MRSA), genome evolution of MRSA into VRSA, including strains engineered within the same patient under anti-staphylococcal therapy, may build up to future public health concern. To further complicate diagnosis, infection control and anti-microbial chemotherapy, non-sterile sites such as the nares and the skin could contain both S. aureus and coagulase-negative staphylococci (CoNS), either of which could harbour mecA the gene driving staphylococcal methicillin-resistance and required for MRSA-VRSA evolution.
Results
A new heptaplex PCR assay has been developed which simultaneously detects seven markers for: i) eubacteria (16S rRNA), ii) Staphylococcus genus (tuf), iii) Staphylococcus aureus (spa), iv) CoNS (cns), v) Panton-Valentine leukocidin (pvl), vi) methicillin resistance (mecA), and vii) vancomycin resistance (vanA). Following successful validation using 255 reference bacterial strains, applicability to analyse clinical samples was evaluated by direct amplification in spiked blood cultures (n = 89) which returned 100 % specificity, negative and positive predictive values. The new assay has LoD of 1.0x103 CFU/mL for the 16S rRNA marker and 1.0x104 CFU/mL for six other markers and completes cycling in less than one hour.
Conclusion
The speed, sensitivity (100 %), NPV (100 %) and PPV (100 %) suggest the new heptaplex PCR assay could be easily integrated into a routine diagnostic microbiology workflow. Detection of the cns marker allows for unique identification of CoNS in mono-microbial and in poly-microbial samples containing mixtures of CoNS and S. aureus without recourse to the conventional elimination approach which is ambiguous. In addition to the SA-CoNS differential diagnostic essence of the new assay, inclusion of vanA primers will allow microbiology laboratories to stay ahead of the emerging MRSA-VRSA evolution. To the best of our knowledge, the new heptaplex PCR assay is the most multiplexed among similar PCR-based assays for simultaneous detection of STAAR
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