830 resultados para high risk population
Resumo:
We used an established seagrass monitoring programme to examine the short and longer-term impacts of an oil spill event on intertidal seagrass meadows. Results for potentially impacted seagrass areas were compared with existing monitoring data and with control seagrass meadows located outside of the oil spill area. Seagrass meadows were not significantly affected by the oil spill. Declines in seagrass biomass and area 1 month post-spill were consistent between control and impact meadows. Eight months post-spill, seagrass density and area increased to be within historical ranges. The declines in seagrass meadows were likely attributable to natural seasonal variation and a combination of climatic and anthropogenic impacts. The lack of impact from the oil spill was due to several mitigating factors rather than a lack of toxic effects to seagrasses. The study demonstrates the value of long-term monitoring of critical habitats in high risk areas to effectively assess impacts.
Resumo:
The aim of this study is to explore whether Australian mineral companies operating in high human rights risk countries provide more human rights disclosures than companies operating in low risk countries. A content analysis instrument containing 88 specific human rights performance items derived from a number of international human rights guidelines has been developed to investigate the annual reports, social responsibility reports and corporate websites of the top 50 Australian mineral companies (2010/2011). The findings show that human rights performance disclosures by companies with operations in high human rights risk countries are significantly higher than companies with operations in the low risk countries. By disclosing extended human rights performance information, companies operating in high risk countries appear to ease community concerns about human rights violations. The finding is consistent with legitimacy theory which posits that organisations respond to community concerns in relation to particular social issues.
Resumo:
Background: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Methods: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. Results: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p < 0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. Conclusion: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.
Resumo:
The acute myeloid leukaemia (AML)14 trial addressed four therapeutic questions in patients predominantly aged over 60 years with AML and High Risk Myelodysplastic Syndrome: (i) Daunorubicin 50 mg/m(2) vs. 35 mg/m(2); (ii) Cytarabine 200 mg/m(2) vs. 400 mg/m(2) in two courses of DA induction; (iii) for part of the trial, patients allocated Daunorubicin 35 mg/m(2) were also randomized to receive, or not, the multidrug resistance modulator PSC-833 in a 1:1:1 randomization; and (iv) a total of three versus four courses of treatment. A total of 1273 patients were recruited. The response rate was 62% (complete remission 54%, complete remission without platelet/neutrophil recovery 8%); 5-year survival was 12%. No benefits were observed in either dose escalation randomization, or from a fourth course of treatment. There was a trend for inferior response in the PSC-833 arm due to deaths in induction. Multivariable analysis identified cytogenetics, presenting white blood count, age and secondary disease as the main predictors of outcome. Although patients with high Pgp expression and function had worse response and survival, this was not an independent prognostic factor, and was not modified by PSC-833. In conclusion, these four interventions have not improved outcomes in older patients. New agents need to be explored and novel trial designs are required to maximise prospects of achieving timely progress.
Resumo:
The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or