Long-term effects of once-only flexible sigmoidoscopy screening after 17 years of follow-up: the UK Flexible Sigmoidoscopy Screening randomised controlled trial

National Institute for Health Research Efficacy and Mechanism Evaluation

Diffusion of e-health innovations in 'post-conflict' settings: a qualitative study on the personal experiences of health workers.

BACKGROUND: Technological innovations have the potential to strengthen human resources for health and improve access and quality of care in challenging 'post-conflict' contexts. However, analyses on the adoption of technology for health (that is, 'e-health') and whether and how e-health can strengthen a health workforce in these settings have been limited so far. This study explores the personal experiences of health workers using e-health innovations in selected post-conflict situations. METHODS: This study had a cross-sectional qualitative design. Telephone interviews were conducted with 12 health workers, from a variety of cadres and stages in their careers, from four post-conflict settings (Liberia, West Bank and Gaza, Sierra Leone and Somaliland) in 2012. Everett Roger's diffusion of innovation-decision model (that is, knowledge, persuasion, decision, implementation, contemplation) guided the thematic analysis. RESULTS: All health workers interviewed held positive perceptions of e-health, related to their beliefs that e-health can help them to access information and communicate with other health workers. However, understanding of the scope of e-health was generally limited, and often based on innovations that health workers have been introduced through by their international partners. Health workers reported a range of engagement with e-health innovations, mostly for communication (for example, email) and educational purposes (for example, online learning platforms). Poor, unreliable and unaffordable Internet was a commonly mentioned barrier to e-health use. Scaling-up existing e-health partnerships and innovations were suggested starting points to increase e-health innovation dissemination. CONCLUSIONS: Results from this study showed ICT based e-health innovations can relieve information and communication needs of health workers in post-conflict settings. However, more efforts and investments, preferably driven by healthcare workers within the post-conflict context, are needed to make e-health more widespread and sustainable. Increased awareness is necessary among health professionals, even among current e-health users, and physical and financial access barriers need to be addressed. Future e-health initiatives are likely to increase their impact if based on perceived health information needs of intended users

Lithocholic Acid Is an Eph-ephrin Ligand Interfering with Eph-kinase Activation

Eph-ephrin system plays a central role in a large variety of human cancers. In fact, alterated expression and/or de-regulated function of Eph-ephrin system promotes tumorigenesis and development of a more aggressive and metastatic tumour phenotype. In particular EphA2 upregulation is correlated with tumour stage and progression and the expression of EphA2 in non-trasformed cells induces malignant transformation and confers tumorigenic potential. Based on these evidences our aim was to identify small molecules able to modulate EphA2-ephrinA1 activity through an ELISA-based binding screening. We identified lithocholic acid (LCA) as a competitive and reversible ligand inhibiting EphA2-ephrinA1 interaction (Ki = 49 µM). Since each ephrin binds many Eph receptors, also LCA does not discriminate between different Eph-ephrin binding suggesting an interaction with a highly conserved region of Eph receptor family. Structurally related bile acids neither inhibited Eph-ephrin binding nor affected Eph phosphorylation. Conversely, LCA inhibited EphA2 phosphorylation induced by ephrinA1-Fc in PC3 and HT29 human prostate and colon adenocarcinoma cell lines (IC50 = 48 and 66 µM, respectively) without affecting cell viability or other receptor tyrosine-kinase (EGFR, VEGFR, IGFR1β, IRKβ) activity. LCA did not inhibit the enzymatic kinase activity of EphA2 at 100 µM (LANCE method) confirming to target the Eph-ephrin protein-protein interaction. Finally, LCA inhibited cell rounding and retraction induced by EphA2 activation in PC3 cells. In conclusion, our findings identified a hit compound useful for the development of molecules targeting ephrin system. Moreover, as ephrin signalling is a key player in the intestinal cell renewal, our work could provide an interesting starting point for further investigations about the role of LCA in the intestinal homeostasis

Eph/Ephrin Profiling in Human Breast Cancer Reveals Significant Associations between Expression Level and Clinical Outcome

Pre-clinical studies provide compelling evidence that Eph family receptor tyrosine kinases (RTKs) and ligands promote cancer growth, neovascularization, invasion, and metastasis. Tumor suppressive roles have also been reported for the receptors, however, creating a potential barrier for clinical application. Determining how these observations relate to clinical outcome is a crucial step for translating the biological and mechanistic data into new molecularly targeted therapies. We investigated eph and ephrin expression in human breast cancer relative to endpoints of overall and/or recurrence-free survival in large microarray datasets. We also investigated protein expression in commercial human breast tissue microarrays (TMA) and Stage I prognostic TMAs linked to recurrence outcome data. We found significant correlations between ephA2, ephA4, ephA7, ephB4, and ephB6 and overall and/or recurrence-free survival in large microarray datasets. Protein expression in TMAs supported these trends. While observed no correlation between ephrin ligand expression and clinical outcome in microarray datasets, ephrin-A1 and EphA2 protein co-expression was significantly associated with recurrence in Stage I prognostic breast cancer TMAs. Our data suggest that several Eph family members are clinically relevant and tractable targets for intervention in human breast cancer. Moreover, profiling Eph receptor expression patterns in the context of relevant ligands and in the context of stage may be valuable in terms of diagnostics and treatment

High levels of untreated distress and fatigue in cancer patients

The purpose of the study was to assess a large representative sample of cancer patients on distress levels, common psychosocial problems, and awareness and use of psychosocial support services. A total of 3095 patients were assessed over a 4-week period with the Brief Symptom Inventory-18 (BSI-18), a common problems checklist, and on awareness and use of psychosocial resources. Full data was available on 2776 patients. On average, patients were 60 years old, Caucasian (78.3%), and middle class. Approximately, half were attending for follow-up care. Types of cancer varied, with the largest groups being breast (23.5%), prostate (16.9%), colorectal (7.5%), and lung (5.8%) cancer patients. Overall, 37.8% of all patients met criteria for general distress in the clinical range. A higher proportion of men met case criteria for somatisation, and more women for depression. There were no gender differences in anxiety or overall distress severity. Minority patients were more likely to be distressed, as were those with lower income, cancers other than prostate, and those currently on active treatment. Lung, pancreatic, head and neck, Hodgkin's disease, and brain cancer patients were the most distressed. Almost half of all patients who met distress criteria had not sought professional psychosocial support nor did they intend to in the future. In conclusion, distress is very common in cancer patients across diagnoses and across the disease trajectory. Many patients who report high levels of distress are not taking advantage of available supportive resources. Barriers to such use, and factors predicting distress and use of psychosocial care, require further exploration

Prognostic Breast Cancer Signature Identified from 3D Culture Model Accurately Predicts Clinical Outcome across Independent Datasets

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer

Attention bias to emotional faces varies by IQ and anxiety in Williams syndrome

Individuals with Williams syndrome (WS) often experience significant anxiety. A promising approach to anxiety intervention has emerged from cognitive studies of attention bias to threat. To investigate the utility of this intervention in WS, this study examined attention bias to happy and angry faces in individuals with WS (N=46). Results showed a significant difference in attention bias patterns as a function of IQ and anxiety. Individuals with higher IQ or higher anxiety showed a significant bias toward angry, but not happy faces, whereas individuals with lower IQ or lower anxiety showed the opposite pattern. These results suggest that attention bias interventions to modify a threat bias may be most effectively targeted to anxious individuals with WS with relatively high IQ

Menstrual Cycle and Facial Preferences Reconsidered

Two previous articles reported that women prefer less feminized male faces during the fertile phase of their menstrual cycle, supposedly reflecting an evolved mating strategy whereby women choose mates of maximum genetic quality when conception is likely. The current article contends this theory rests on several questionable assumptions about human ancestral mating systems. A new empirical test also was conducted: 853 adults, primarily from North America, evaluated facial attractiveness of photos. The study included more complete evaluation of ovulatory status and a greater number (n = 258) of target women than past research. The results did not suggest any greater preference for masculine faces when fertilization was likely. The article concludes with general comments about evolutionary theorizing and interpersonal relationships

Transcriptional Profiling of Non-Small Cell Lung Cancer Cells with Activating EGFR Somatic Mutations

Activating somatic mutations in epidermal growth factor receptor (EGFR) confer unique biologic features to non-small cell lung cancer (NSCLC) cells, but the transcriptional mediators of EGFR in this subgroup of NSCLC have not been fully elucidated.Here we used genetic and pharmacologic approaches to elucidate the transcriptomes of NSCLC cell lines. We transcriptionally profiled a panel of EGFR-mutant and -wild-type NSCLC cell lines cultured in the presence or absence of an EGFR tyrosine kinase inhibitor. Hierarchical analysis revealed that the cell lines segregated on the basis of EGFR mutational status (mutant versus wild-type), and expression signatures were identified by supervised analysis that distinguished the cell lines based on mutational status (wild-type versus mutant) and type of mutation (L858R versus Delta746-750). Using an EGFR mutation-specific expression signature as a probe, we mined the gene expression profiles of two independent cohorts of NSCLC patients and found the signature in a subset. EGFR tyrosine kinase inhibitor treatment regulated the expression of multiple genes, and pharmacologic inhibition of the protein products of two of them (PTGS2 and EphA2) inhibited anchorage-independent growth in EGFR-mutant NSCLC cells.We have elucidated genes not previously associated with EGFR-mutant NSCLC, two of which enhanced the clonogenicity of these cells, distinguishing these mediators from others previously shown to maintain cell survival. These findings have potential clinical relevance given the availability of pharmacologic tools to inhibit the protein products of these genes

Should the Arteriovenous Fistula Be Created before Starting Dialysis?: A Decision Analytic Approach

Background: An arteriovenous fistula (AVF) is considered the vascular access of choice, but uncertainty exists about the\ud optimal time for its creation in pre-dialysis patients. The aim of this study was to determine the optimal vascular access\ud referral strategy for stage 4 (glomerular filtration rate ,30 ml/min/1.73 m2) chronic kidney disease patients using a decision\ud analytic framework.\ud Methods: A Markov model was created to compare two strategies: refer all stage 4 chronic kidney disease patients for an\ud AVF versus wait until the patient starts dialysis. Data from published observational studies were used to estimate the\ud probabilities used in the model. A Markov cohort analysis was used to determine the optimal strategy with life expectancy\ud and quality adjusted life expectancy as the outcomes. Sensitivity analyses, including a probabilistic sensitivity analysis, were\ud performed using Monte Carlo simulation.\ud Results: The wait strategy results in a higher life expectancy (66.6 versus 65.9 months) and quality adjusted life expectancy\ud (38.9 versus 38.5 quality adjusted life months) than immediate AVF creation. It was robust across all the parameters except\ud at higher rates of progression and lower rates of ischemic steal syndrome.\ud Conclusions: Early creation of an AVF, as recommended by most guidelines, may not be the preferred strategy in all predialysis\ud patients. Further research on cost implications and patient preferences for treatment options needs to be done\ud before recommending early AVF creation