Lesion detection and Grading of Diabetic Retinopathy via Two-stages Deep Convolutional Neural Networks

We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages deep convolutional neural networks (DCNN). Compared to existing DCNN-based DR detection methods, the proposed algorithm have the following advantages: (1) Our method can point out the location and type of lesions in the fundus images, as well as giving the severity grades of DR. Moreover, since retina lesions and DR severity appear with different scales in fundus images, the integration of both local and global networks learn more complete and specific features for DR analysis. (2) By introducing imbalanced weighting map, more attentions will be given to lesion patches for DR grading, which significantly improve the performance of the proposed algorithm. In this study, we label 12,206 lesion patches and re-annotate the DR grades of 23,595 fundus images from Kaggle competition dataset. Under the guidance of clinical ophthalmologists, the experimental results show that our local lesion detection net achieve comparable performance with trained human observers, and the proposed imbalanced weighted scheme also be proved to significantly improve the capability of our DCNN-based DR grading algorithm

BCR-ABL1 mutation development during first-line treatment with dasatinib or imatinib for chronic myeloid leukemia in chronic phase

BCR-ABL1 mutations are a common, well-characterized mechanism of resistance to imatinib as first-line treatment of chronic myeloid leukemia in chronic phase (CML-CP). Less is known about mutation development during first-line treatment with dasatinib and nilotinib, despite increased use because of higher response rates compared with imatinib. Retrospective analyses were conducted to characterize mutation development in patients with newly diagnosed CML-CP treated with dasatinib (n=259) or imatinib (n=260) in DASISION (Dasatinib versus Imatinib Study in Treatment-Naive CML-CP), with 3-year minimum follow-up. Mutation screening, including patients who discontinued treatment and patients who had a clinically relevant on-treatment event (no confirmed complete cytogenetic response (cCCyR) and no major molecular response (MMR) within 12 months; fivefold increase in BCR-ABL1 with loss of MMR; loss of CCyR), yielded a small number of patients with mutations (dasatinib, n=17; imatinib, n=18). Dasatinib patients had a narrower spectrum of mutations (4 vs 12 sites for dasatinib vs imatinib), fewer phosphate-binding loop mutations (1 vs 9 mutations), fewer multiple mutations (1 vs 6 patients) and greater occurrence of T315I (11 vs 0 patients). This trial was registered at www.clinicaltrials.gov as NCT00481247.T P Hughes, G Saglio, A Quintás-Cardama, M J Mauro, D-W Kim, J H Lipton6, M B Bradley-Garelik, J Ukropec and A Hochhau

Ponatinib for Treating Acute Lymphoblastic Leukaemia: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

As part of its single technology appraisal (STA) process, the UK National Institute for Health and Care Excellence (NICE) invited the manufacturer (Incyte Corporation) of ponatinib (Inclusig®) to submit evidence of its clinical and cost effectiveness for previously treated Philadelphia-chromosome-positive acute lymphoblastic leukaemia (Ph+ ALL) and chronic myeloid leukaemia. This paper focusses on Ph+ ALL. The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent evidence review group (ERG). This article presents the critical review of the company's submission by the ERG and the outcome of the NICE guidance. The clinical-effectiveness evidence in the company's submission was derived from a phase II, single-arm, open-label, non-comparative study. Given the lack of comparative evidence, a naïve indirect comparison was performed against re-induction chemotherapy comparing major cytogenetic response and complete remission. Best supportive care (BSC) was assumed to produce no disease response. Despite the limited evidence and potential for biases, this study demonstrated that ponatinib was likely to be an effective treatment for patients with Ph+ ALL. The company submitted a state transition model that analysed the incremental cost effectiveness of ponatinib versus re-induction therapy and BSC for the treatment of Ph+ ALL in patients whose disease is resistant to dasatinib, who are intolerant to dasatinib and for whom subsequent treatment with imatinib is not clinically appropriate or who have the threonine-315-isoleucine mutation. This population was further subdivided into those who were suitable for allogeneic stem cell transplant (allo-SCT) and those who were not. The company's revised economic evaluation, following the clarification process, estimated incremental cost-effectiveness ratios (ICERs) in those suitable for allo-SCT of £31,123 per quality-adjusted life-year (QALY) gained for ponatinib compared with re-induction chemotherapy and £26,624 per QALY gained compared with BSC. For those for whom allo-SCT was unsuitable, the company-estimated ICER compared with BSC was £33,954 per QALY gained. Following a critique of the model, the ERG undertook exploratory analyses that, when combined, produced a range in ICERs (due to uncertainty of the most appropriate overall survival function) of dominant (being less expensive and providing more QALYs) to £11,727 per QALY gained compared with re-induction chemotherapy and between £7892 and £31,696 per QALY gained compared with BSC for those in whom allo-SCT was suitable. For those in whom allo-SCT was not suitable, the ERG estimated that ponatinib was dominant. During the consultation period, the company agreed a revised patient access scheme (PAS) that reduced the ICER ranges to £7156 to £29,995 per QALY gained versus BSC and to less than £5000 per QALY gained versus re-induction chemotherapy. In people for whom allo-SCT was unsuitable, ponatinib dominated BSC. The NICE appraisal committee concluded that ponatinib is a cost-effective use of UK NHS resources in the considered population, subject to the company providing the agreed discount in the PAS

Interactions among mitochondrial proteins altered in glioblastoma

Mitochondrial dysfunction is putatively central to glioblastoma (GBM) pathophysiology but there has been no systematic analysis in GBM of the proteins which are integral to mitochondrial function. Alterations in proteins in mitochondrial enriched fractions from patients with GBM were defined with label-free liquid chromatography mass spectrometry. 256 mitochondrially-associated proteins were identified in mitochondrial enriched fractions and 117 of these mitochondrial proteins were markedly (fold-change ≥2) and significantly altered in GBM (p ≤ 0.05). Proteins associated with oxidative damage (including catalase, superoxide dismutase 2, peroxiredoxin 1 and peroxiredoxin 4) were increased in GBM. Protein–protein interaction analysis highlighted a reduction in multiple proteins coupled to energy metabolism (in particular respiratory chain proteins, including 23 complex-I proteins). Qualitative ultrastructural analysis in GBM with electron microscopy showed a notably higher prevalence of mitochondria with cristolysis in GBM. This study highlights the complex mitochondrial proteomic adjustments which occur in GBM pathophysiology

Bicultural identity among economical migrants from three south European countries living in Switzerland. Adaptation and validation of a new psychometric instrument

<p>Abstract</p> <p>Background</p> <p>Acculturation is one of the determinants of mental health among immigrants. Evaluating adaptation to the host culture is insufficient, since immigrants will develop various degrees of bi- or multicultural identity. However, mental health professionals lack simple and easy to use instruments to guide them with bicultural identity evaluation in their practice. Our aim was to develop such an instrument to be used for clinical purposes among economical migrants from three South European countries living in Geneva, Switzerland.</p> <p>Methods</p> <p>We adapted from existing instruments a 24 item bi-dimensional scale to assess involvement in both culture of origin and host culture. The study included 93 immigrant adults from three south European countries (Italy, Portugal and Spain). Thirty-eight patients were recruited in an outpatient treatment program for alcohol-related problems and 55 participants were hospital employees.</p> <p>Results</p> <p>The questionnaire was rated as easy or rather easy by 97.8% of participants. Median time to complete it was 5 minutes. The instrument allowed discriminating between patients and healthy subjects, with scores for Swiss culture significantly higher among hospital workers. The subscales related to culture of origin and host culture displayed adequate internal consistency (Cronbach's alpha 0.77 and 0.73 respectively).</p> <p>Conclusion</p> <p>It is possible to assist clinicians' assessment of cultural identity of Italian, Portuguese and Spanish economical immigrants in Switzerland with a single and easy to use instrument.</p

Ponatinib for Treating Chronic Myeloid Leukaemia: An Evidence Review Group Perspective of a NICE Single Technology Appraisal

As part of its single technology appraisal process, the National Institute for Health and Care Excellence (NICE) invited the company that manufactures ponatinib (Inclusig®; Incyte Corporation) to submit evidence for the clinical and cost effectiveness for previously treated chronic myeloid leukaemia (CML) and Philadelphia-chromosome-positive acute lymphoblastic leukaemia (Ph+ ALL). This paper focusses on the three phases of CML: the chronic phase (CP), the accelerated phase (AP) and the blast crisis phase (BP). The School of Health and Related Research Technology Appraisal Group at the University of Sheffield was commissioned to act as the independent Evidence Review Group (ERG). This article presents the critical review of the company's submission by the ERG and the outcome of the NICE guidance. Clinical evidence for ponatinib was derived from a phase II, industry-sponsored, single-arm, open-label, multicentre, non-comparative study. Despite the limited evidence and potential for biases, this study demonstrated that ponatinib was likely to be an effective treatment (in terms of major cytogenetic response and major haematological response) with an acceptable safety profile for patients with CML. Given the absence of any head-to-head studies comparing ponatinib with other relevant comparators, the company undertook a matching-adjusted indirect comparison (MAIC) of ponatinib with bosutinib. The approach was only used for patients with CP-CML because comprehensive data were not available for the AP- or BP-CML groups to allow the matching technique to be used. Despite the uncertainty about the MAIC approach, ponatinib was considered likely to offer advantages over bosutinib in the third-line setting, particularly for complete cytogenetic response. The company developed two health economic models to assess the cost effectiveness of ponatinib for the treatment of patients in CP-CML or in advanced CML (AP- or BP-CML, which were modelled separately). The company did not adequately explore the uncertainty in the survivor functions. As a result, the ERG believed the uncertainty in the decision problem was underestimated. Exploratory analyses undertaken by the ERG produced the following results for ponatinib. In CP-CML, from £18,246 to £27,667 per quality-adjusted life-year (QALY) gained compared with best supportive care (BSC), from £19,680 to £37,381 per QALY gained compared with bosutinib and from £18,279 per QALY gained to dominated compared with allogeneic stem cell transplant (allo-SCT). In AP-CML, the cost per QALY gained for ponatinib ranged from £7123 to £17,625 compared with BSC, and from dominating to £61,896 per QALY gained compared with allo-SCT. In BP-CML, the cost effectiveness of ponatinib ranged from £5033 per QALY gained to dominated compared with allo-SCT, although it was likely to be at the more favourable end of this range, and dominant in all scenarios compared with BSC. The NICE appraisal committee concluded that ponatinib is a cost-effective use of NHS resources in the considered population, subject to the company providing the agreed discount in the Patient Access Scheme

Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies

Background: Several models for mortality prediction have been constructed for critically ill patients with haematological malignancies in recent years. These models have proven to be equally or more accurate in predicting hospital mortality in patients with haematological malignancies than ICU severity of illness scores such as the APACHE II or SAPS II [1]. The objective of this study is to compare the accuracy of predicting hospital mortality in patients with haematological malignancies admitted to the ICU between models based on multiple logistic regression (MLR) and support vector machine (SVM) based models. Methods: 352 patients with haematological malignancies admitted to the ICU between 1997 and 2006 for a life-threatening complication were included. 252 patient records were used for training of the models and 100 were used for validation. In a first model 12 input variables were included for comparison between MLR and SVM. In a second more complex model 17 input variables were used. MLR and SVM analysis were performed independently from each other. Discrimination was evaluated using the area under the receiver operating characteristic (ROC) curves (+/- SE). Results: The area under ROC curve for the MLR and SVM in the validation data set were 0.768 (+/- 0.04) vs. 0.802 (+/- 0.04) in the first model (p = 0.19) and 0.781 (+/- 0.05) vs. 0.808 (+/- 0.04) in the second more complex model (p = 0.44). SVM needed only 4 variables to make its prediction in both models, whereas MLR needed 7 and 8 variables in the first and second model respectively. Conclusion: The discriminative power of both the MLR and SVM models was good. No statistically significant differences were found in discriminative power between MLR and SVM for prediction of hospital mortality in critically ill patients with haematological malignancies

A framework for protein structure classification and identification of novel protein structures

BACKGROUND: Protein structure classification plays a central role in understanding the function of a protein molecule with respect to all known proteins in a structure database. With the rapid increase in the number of new protein structures, the need for automated and accurate methods for protein classification is increasingly important. RESULTS: In this paper we present a unified framework for protein structure classification and identification of novel protein structures. The framework consists of a set of components for comparing, classifying, and clustering protein structures. These components allow us to accurately classify proteins into known folds, to detect new protein folds, and to provide a way of clustering the new folds. In our evaluation with SCOP 1.69, our method correctly classifies 86.0%, 87.7%, and 90.5% of new domains at family, superfamily, and fold levels. Furthermore, for protein domains that belong to new domain families, our method is able to produce clusters that closely correspond to the new families in SCOP 1.69. As a result, our method can also be used to suggest new classification groups that contain novel folds. CONCLUSION: We have developed a method called proCC for automatically classifying and clustering domains. The method is effective in classifying new domains and suggesting new domain families, and it is also very efficient. A web site offering access to proCC is freely available a