Evaluation of the initial implementation of a nationwide diabetic retinopathy screening programme in primary care: A multimethod study

Objectives The Australian Government funded a nationwide diabetic retinopathy screening programme to improve visual outcomes for people with diabetes. This study examined the benefits and barriers of the programme, image interpretation pathways and assessed the characteristics of people who had their fundus photos graded by a telereading service which was available as a part of the programme. Design Multimethod: survey and retrospective review of referral forms. Setting Twenty-two primary healthcare facilities from urban, regional, rural and remote areas of Australia, and one telereading service operated by a referral-only eye clinic in metropolitan Sydney, Australia. Participants Twenty-seven primary healthcare workers out of 110 contacted completed a survey, and 145 patient referrals were reviewed. Results Manifest qualitative content analysis showed that primary healthcare workers reported that the benefits of the screening programme included improved patient outcomes and increased awareness and knowledge of diabetic retinopathy. Barriers related to staffing issues and limited referral pathways. Image grading was performed by a variety of primary healthcare workers, with one responder indicating the utilisation of a diabetic retinopathy reading service. Of the people with fundus photos graded by the reading service, 26.2% were reported to have diabetes. Overall, 12.3% of eyes were diagnosed with diabetic retinopathy. Photo quality was rated as excellent in 46.2% of photos. Referral to an optometrist for diabetic retinopathy was recommended in 4.1% of cases, and to an ophthalmologist in 6.9% of cases. Conclusions This nationwide diabetic retinopathy screening programme was perceived to increase access to diabetic retinopathy screening in regional, rural and remote areas of Australia. The telereading service has diagnosed diabetic retinopathy and other ocular pathologies in images it has received. Key barriers, such as access to ophthalmologists and optometrists, must be overcome to improve visual outcomes

Attitude towards psychiatric treatment and referral pattern in the University of Maiduguri Teaching Hospital- A preliminary report

Objective: There is a paucity of literature on consultation-liaison psychiatry, in northern Nigeria. This study aimed to determine both the pattern of psychiatric referrals, and the attitudes of doctors toward the treatment of mental disorders in a teaching hospital, in northeast Nigeria. Method: In this cross-sectional survey, we used a modified version of the self-rated Kumar 12-item questionnaire and a basic socio-demographic questionnaire to assess a non-random convenient sample of 100 postgraduate resident doctors (with a response rate of 70%) from the University of Maiduguri Teaching Hospital (UMTH). We subjected the dataobtained to descriptive statistical analysis, using EPI info (2003), to report averages. Results: A relatively low percentage (57.1%) of doctors acknowledged treating patients with mental disorders in their practice, with a higher proportion acknowledging referral (75%). Nearly one in five (17.6%) of the respondents were unaware that patients with functional illness could have psychological disorders. We found more awareness for psychotherapy (44.1%) than other non-pharmacological treatment interventions, while10.3% were ignorant of non-pharmacological forms of treatment for psychological problems. Conclusion: Although this is a preliminary report, the research reported here demonstrated that doctors in the teaching hospital concerned recognized the need for psychiatric consultation and referral. It is difficult to draw further conclusions because of the limitations of this study.Keywords: Consultation; Liaison; Psychiatry; northern Nigeri

Reliable microsatellite genotyping of the Eurasian badger (Meles meles) using faecal DNA

The potential link between badgers and bovine tuberculosis has made it vital to develop accurate techniques to census badgers. Here we investigate the potential of using genetic profiles obtained from faecal DNA as a basis for population size estimation. After trialling several methods we obtained a high amplification success rate (89%) by storing faeces in 70% ethanol and using the guanidine thiocyanate/silica method for extraction. Using 70% ethanol as a storage agent had the advantage of it being an antiseptic. In order to obtain reliable genotypes with fewer amplification reactions than the standard multiple-tubes approach, we devised a comparative approach in which genetic profiles were compared and replication directed at similar, but not identical, genotypes. This modified method achieved a reduction in polymerase chain reactions comparable with the maximumlikelihood model when just using reliability criteria, and was slightly better when using reliability criteria with the additional proviso that alleles must be observed twice to be considered reliable. Our comparative approach would be best suited for studies that include multiple faeces from each individual. We utilized our approach in a well-studied population of badgers from which individuals had been sampled and reliable genotypes obtained. In a study of 53 faeces sampled from three social groups over 10 days, we found that direct enumeration could not be used to estimate population size, but that the application of mark–recapture models has the potential to provide more accurate results

PTHrP Induces Autocrine/Paracrine Proliferation of Bone Tumor Cells through Inhibition of Apoptosis

Giant Cell Tumor of Bone (GCT) is an aggressive skeletal tumor characterized by local bone destruction, high recurrence rates and metastatic potential. Previous work in our lab has shown that the neoplastic cell of GCT is a proliferating pre-osteoblastic stromal cell in which the transcription factor Runx2 plays a role in regulating protein expression. One of the proteins expressed by these cells is parathryroid hormone-related protein (PTHrP). The objectives of this study were to determine the role played by PTHrP in GCT of bone with a focus on cell proliferation and apoptosis. Primary stromal cell cultures from 5 patients with GCT of bone and one lung metastsis were used for cell-based experiments. Control cell lines included a renal cell carcinoma (RCC) cell line and a human fetal osteoblast cell line. Cells were exposed to optimized concentrations of a PTHrP neutralizing antibody and were analyzed with the use of cell proliferation and apoptosis assays including mitochondrial dehydrogenase assays, crystal violet assays, APO-1 ELISAs, caspase activity assays, flow cytometry and immunofluorescent immunohistochemistry. Neutralization of PTHrP in the cell environment inhibited cell proliferation in a consistent manner and induced apoptosis in the GCT stromal cells, with the exception of those obtained from a lung metastasis. Cell cycle progression was not significantly affected by PTHrP neutralization. These findings indicate that PTHrP plays an autocrine/paracrine neoplastic role in GCT by allowing the proliferating stromal cells to evade apoptosis, possibly through non-traditional caspase-independent pathways. Thus PTHrP neutralizing immunotherapy is an intriguing potential therapeutic strategy for this tumor

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

A new hammer to crack an old nut : interspecific competitive resource capture by plants is regulated by nutrient supply, not climate

Peer reviewedPublisher PD