Perceptions of shared care among survivors of colorectal cancer from non-English-speaking and English-speaking backgrounds: A qualitative study

Background: Colorectal cancer (CRC) survivors experience difficulty navigating complex care pathways. Sharing care between GPs and specialist services has been proposed to improve health outcomes in cancer survivors following hospital discharge. Culturally and Linguistically Diverse (CALD) groups are known to have poorer outcomes following cancer treatment but little is known about their perceptions of shared care following surgery for CRC. This study aimed to explore how non-English-speaking and English-speaking patients perceive care to be coordinated amongst various health practitioners. Methods: This was a qualitative study using data from face to face semi-structured interviews and one focus group in a culturally diverse area of Sydney with non-English-speaking and English-speaking CRC survivors. Participants were recruited in community settings and were interviewed in English, Spanish or Vietnamese. Interviews were recorded, transcribed, and analysed by researchers fluent in those languages. Data were coded and analysed thematically. Results: Twenty-two CRC survivors participated in the study. Participants from non-English-speaking and English-speaking groups described similar barriers to care, but non-English-speaking participants described additional communication difficulties and perceived discrimination. Non-English-speaking participants relied on family members and bilingual GPs for assistance with communication and care coordination. Factors that influenced the care pathways used by participants and how care was shared between the specialist and GP included patient and practitioner preference, accessibility, complexity of care needs, and requirements for assistance with understanding information and navigating the health system, that were particularly difficult for non-English-speaking CRC survivors. Conclusions: Both non-English-speaking and English-speaking CRC survivors described a blend of specialist-led or GP-led care depending on the complexity of care required, informational needs, and how engaged and accessible they perceived the specialist or GP to be. Findings from this study highlight the role of the bilingual GP in assisting CALD participants to understand information and to navigate their care pathways following CRC surgery

Test Damage to the Sand Dollar Mellita tenuis on the Florida Gulf Coast

Disturbance, loss of a part of the body, is an important component of life histories. In contrast to plants, sublethal disturbance is not common in animals. Damage to the test of Mellita is usually attributed to sublethal predation, but hydrodynamics may be a factor. We found test damage to Mellita tenuis on the Florida gulf coast is variable over space and time. Test damage is more frequent in large individuals. This could result from a greater period of time for predation to occur or a decrease in the probability of death from predation. Test damage was variable over space and time, ranging from 0 to \u3e50% of the populations, indicating great variation among locations. Because the test is important in maintenance of position, locomotion, and feeding, damage probably affects the potential for survival, growth, and reproduction

Age Determination in the Sand Dollar Mellita tenuis

Mellita tenuis were collected from six locations along the Florida gulf coast from March 1997 through Sep. 1998. The anterior-posterior length of the test was measured, and growth lines in the interambulacral plates near the ambitus on the aboral surface (which are oldest) were counted. The number of growth lines is size independent as would be expected if seasonality of growth and growth rate were uncoupled. However, a collection of small individuals had many more growth lines and one of the large individuals had many less than would be anticipated. Lines near the ambitus are difficult to count because they are compressed. In addition, gray growth lines occur between the light and dark ones. The number of plates in the petal increases with body size to an asymptote and cannot be used to age M. tenuis

SVM-based prediction of caspase substrate cleavage sites

BACKGROUND: Caspases belong to a class of cysteine proteases which function as critical effectors in apoptosis and inflammation by cleaving substrates immediately after unique sites. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. Recently, different computational methods have been developed to predict the cleavage sites of caspase substrates with varying degrees of success. As the support vector machines (SVM) algorithm has been shown to be useful in several biological classification problems, we have implemented an SVM-based method to investigate its applicability to this domain. RESULTS: A set of unique caspase substrates cleavage sites were obtained from literature and used for evaluating the SVM method. Datasets containing (i) the tetrapeptide cleavage sites, (ii) the tetrapeptide cleavage sites, augmented by two adjacent residues, P(1)' and P(2)' amino acids and (iii) the tetrapeptide cleavage sites with ten additional upstream and downstream flanking sequences (where available) were tested. The SVM method achieved an accuracy ranging from 81.25% to 97.92% on independent test sets. The SVM method successfully predicted the cleavage of a novel caspase substrate and its mutants. CONCLUSION: This study presents an SVM approach for predicting caspase substrate cleavage sites based on the cleavage sites and the downstream and upstream flanking sequences. The method shows an improvement over existing methods and may be useful for predicting hitherto undiscovered cleavage sites

Learning Translation Rules for a Bidirectional English-Filipino Machine Translator

PACLIC 20 / Wuhan, China / 1-3 November, 200

A multi-factor model for caspase degradome prediction

<p>Abstract</p> <p>Background</p> <p>Caspases belong to a class of cysteine proteases which function as critical effectors in cellular processes such as apoptosis and inflammation by cleaving substrates immediately after unique tetrapeptide sites. With hundreds of reported substrates and many more expected to be discovered, the elucidation of the caspase degradome will be an important milestone in the study of these proteases in human health and disease. Several computational methods for predicting caspase cleavage sites have been developed recently for identifying potential substrates. However, as most of these methods are based primarily on the detection of the tetrapeptide cleavage sites - a factor necessary but not sufficient for predicting <it>in vivo </it>substrate cleavage - prediction outcomes will inevitably include many false positives.</p> <p>Results</p> <p>In this paper, we show that structural factors such as the presence of disorder and solvent exposure in the vicinity of the cleavage site are important and can be used to enhance results from cleavage site prediction. We constructed a two-step model incorporating cleavage site prediction and these factors to predict caspase substrates. Sequences are first predicted for cleavage sites using CASVM or GraBCas. Predicted cleavage sites are then scored, ranked and filtered against a cut-off based on their propensities for locating in disordered and solvent exposed regions. Using an independent dataset of caspase substrates, the model was shown to achieve greater positive predictive values compared to CASVM or GraBCas alone, and was able to reduce the false positives pool by up to 13% and 53% respectively while retaining all true positives. We applied our prediction model on the family of receptor tyrosine kinases (RTKs) and highlighted several members as potential caspase targets. The results suggest that RTKs may be generally regulated by caspase cleavage and in some cases, promote the induction of apoptotic cell death - a function distinct from their role as transducers of survival and growth signals.</p> <p>Conclusion</p> <p>As a step towards the prediction of <it>in vivo </it>caspase substrates, we have developed an accurate method incorporating cleavage site prediction and structural factors. The multi-factor model augments existing methods and complements experimental efforts to define the caspase degradome on the systems-wide basis.</p

ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair

Automated generate-and-validate (G&V) program repair techniques typically rely on hard-coded rules, only fix bugs following specific patterns, and are hard to adapt to different programming languages. We propose ENCORE, a new G&V technique, which uses ensemble learning on convolutional neural machine translation (NMT) models to automatically fix bugs in multiple programming languages. We take advantage of the randomness in hyper-parameter tuning to build multiple models that fix different bugs and combine them using ensemble learning. This new convolutional NMT approach outperforms the standard long short-term memory (LSTM) approach used in previous work, as it better captures both local and long-distance connections between tokens. Our evaluation on two popular benchmarks, Defects4J and QuixBugs, shows that ENCORE fixed 42 bugs, including 16 that have not been fixed by existing techniques. In addition, ENCORE is the first G&V repair technique to be applied to four popular programming languages (Java, C++, Python, and JavaScript), fixing a total of 67 bugs across five benchmarks