290 resultados para Rubens, Peter Paul, 1577-1640.
Resumo:
Despite the increasing availability of digital slide viewing, and numerous advantages associated with its application, a lack of quality validation studies is amongst the reasons for poor uptake in routine practice. This study evaluated primary digital pathology reporting in the setting of routine subspecialist gastrointestinal pathology, commonplace in most tissue pathology laboratories and representing one of the highest volume specialties in most laboratories. Individual digital and glass slide diagnoses were compared amongst three pathologists reporting in a gastrointestinal subspecialty team, in a prospective series of 100 consecutive diagnostic cases from routine practice in a large teaching hospital laboratory. The study included a washout period of at least 6 months. Discordant diagnoses were classified, and the study evaluated against recent College of American Pathologists (CAP) recommendations for evaluating digital pathology systems for diagnostic use. The study design met all 12 of the CAP recommendations. The 100 study cases generated 300 pairs of diagnoses, comprising 100 glass slide diagnoses and 100 digital diagnoses from each of the three study pathologists. 286 of 300 pairs of diagnoses were concordant, representing intraobserver concordance of 95.3 %, broadly comparable to rates previously published in this field. In ten of the 14 discordant pairs, the glass slide diagnosis was favoured; in four cases, the digital diagnosis was favoured, but importantly, the 14 discordant intraobserver diagnoses were considered to be of minor clinical significance. Interobserver, or viewing modality independent, concordance was found in 94 of the total of 100 study cases, providing a comparable baseline discordance rate expected in any second viewing of pathology material. These overall results support the safe use of digital pathology in primary diagnostic reporting in this setting
Resumo:
Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.
Resumo:
Breast cancer remains a frequent cause of female cancer death despite the great strides in elucidation of biological subtypes and their reported clinical and prognostic significance. We have defined a general cohort of breast cancers in terms of putative actionable targets, involving growth and proliferative factors, the cell cycle, and apoptotic pathways, both as single biomarkers across a general cohort and within intrinsic molecular subtypes.
We identified 293 patients treated with adjuvant chemotherapy. Additional hormonal therapy and trastuzumab was administered depending on hormonal and HER2 status respectively. We performed immunohistochemistry for ER, PR, HER2, MM1, CK5/6, p53, TOP2A, EGFR, IGF1R, PTEN, p-mTOR and e-cadherin. The cohort was classified into luminal (62%) and non-luminal (38%) tumors as well as luminal A (27%), luminal B HER2 negative (22%) and positive (12%), HER2 enriched (14%) and triple negative (25%). Patients with luminal tumors and co-overexpression of TOP2A or IGF1R loss displayed worse overall survival (p=0.0251 and p=0.0008 respectively). Non-luminal tumors had much greater heterogeneous expression profiles with no individual markers of prognostic significance. Non-luminal tumors were characterised by EGFR and TOP2A overexpression, IGF1R, PTEN and p-mTOR negativity and extreme p53 expression.
Our results indicate that only a minority of intrinsic subtype tumors purely express single novel actionable targets. This lack of pure biomarker expression is particular prevalent in the triple negative subgroup and may allude to the mechanism of targeted therapy inaction and myriad disappointing trial results. Utilising a combinatorial biomarker approach may enhance studies of targeted therapies providing additional information during design and patient selection while also helping decipher negative trial results.
Resumo:
Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.
Resumo:
We present the results of a Monte Carlo technique to calculate the absolute magnitudes (H) and slope parameters (G) of about 240,000 asteroids observed by the Pan-STARRS1 telescope during the first 15 months of its 3-year all-sky survey mission. The system's exquisite photometry with photometric errors asteroids rotation period, amplitude and color to derive the most-likely H and G, but its major advantage is in estimating realistic statistical+systematic uncertainties and errors on each parameter. The method was confirmed by comparison with the well-established and accurate results for about 500 asteroids provided by Pravec et al. (2012) and then applied to determining H and G for the Pan-STARRS1 asteroids using both the Muinonen et al. (2010) and Bowell et al. (1989) phase functions. Our results confirm the bias in MPC photometry discovered by ( Jurić et al., 2002).
Resumo:
The characterization of complex cellular responses to diverse stimuli can be studied by the use of emerging chip-based technologies.
The p53 pathway is critical to maintaining the integrity of the genome in multicellular organisms. The p53gene is activated in response to DNA damage and encodes a transcription factor [1], which in turn activates genes that arrest cell growth and induce apoptosis, thereby preventing the propagation of genetically damaged cells. It is the most important known tumor suppressor gene: perhaps half of all human neoplasms have mutations in p53, and there is a remarkable concordance between oncogenic mutation and the loss of p53 transcriptional activity [2]. There is also compelling experimental evidence that loss of p53 function (by whatever means) is one of the key oncogenic steps in human cells, along with altered telomerase activity and expression of mutant ras [3]. So far, however, relatively few of the genes regulated by p53 have been identified and it is not even known how many binding sites there are for p53 in the genome, although an estimate based on the incidence of the canonical p53 consensus binding site (four palindromic copies of the sequence 5'-PuPuPuGA/T-3', where Pu is either purine) in a limited region suggests there may be as many as 200 to 300, possibly representing the same number of p53-responsive genes [4]. This makes the p53 response an attractive target for the emerging techniques for global analysis of gene expression, and two recent reports [5,6] illustrate the ways in which these techniques can be used to elucidate the spectrum of genes regulated by this key transcription factor. Vogelstein and colleagues [5] have used serial analysis of gene expression (SAGE) to identify 34 genes that exhibit at least a 10-fold upregulation in response to inducible expression of p53; Tanaka et al. [6] have used differential display to identify p53R2, a homolog of ribonuclease reductase small subunit (R2) as a target gene, thereby for the first time implicating p53 directly in the repair of DNA damage.
