A lightweight classification of adaptor proteins using transformer networks.

BACKGROUND: Adaptor proteins play a key role in intercellular signal transduction, and dysfunctional adaptor proteins result in diseases. Understanding its structure is the first step to tackling the associated conditions, spurring ongoing interest in research into adaptor proteins with bioinformatics and computational biology. Our study aims to introduce a small, new, and superior model for protein classification, pushing the boundaries with new machine learning algorithms. RESULTS: We propose a novel transformer based model which includes convolutional block and fully connected layer. We input protein sequences from a database, extract PSSM features, then process it via our deep learning model. The proposed model is efficient and highly compact, achieving state-of-the-art performance in terms of area under the receiver operating characteristic curve, Matthew's Correlation Coefficient and Receiver Operating Characteristics curve. Despite merely 20 hidden nodes translating to approximately 1% of the complexity of previous best known methods, the proposed model is still superior in results and computational efficiency. CONCLUSIONS: The proposed model is the first transformer model used for recognizing adaptor protein, and outperforms all existing methods, having PSSM profiles as inputs that comprises convolutional blocks, transformer and fully connected layers for the use of classifying adaptor proteins.

Efficacy, patterns of use and cost of Pertuzumab in the treatment of HER2+ metastatic breast cancer in Singapore: The National Cancer Centre Singapore experience.

BACKGROUND: Pertuzumab is a humanized anti-human epidermal growth factor receptor 2 (HER2) monoclonal antibody found in a Phase III clinical trial to significantly improve median survival in HER2 positive metastatic breast cancer (MBC) when used in combination with a taxane and Trastuzumab, and its clinical efficacy has transformed the therapeutic landscape of HER2-positive breast cancer. There are currently few reports on the pattern of use and value of Pertuzumab in real world settings. Our study describes the clinical efficacy and treatment costs of Pertuzumab in HER2-positive MBC treated in a tertiary cancer centre in Singapore in a predominantly Asian population. AIM: To investigate the clinical efficacy and treatment costs of Pertuzumab in HER2-positive MBC in an Asian population in Singapore. METHODS: A retrospective study of 304 HER2-positive MBC patients seen at National Cancer Centre Singapore between 2011-2017 was conducted. Demographic and clinical data were extracted from electronic medical records. Clinical characteristics and billing data of patients who received Pertuzumab were compared with those who did not. RESULTS: Thirty-one (62.0%) of the fifty (16.4%) patients who received Pertuzumab as first-line therapy. With a median follow-up of 21.5 mo, there was a statistically significant difference in the median overall survival between Pertuzumab and non-Pertuzumab groups [51.5 (95%CI: 35.8-60.0) vs 32.9 (95%CI: 28.1-37.5) mo; P = 0.0128]. Two (4.88%) patients in the Pertuzumab group experienced grade 3 (G3) cardiotoxicity. The median treatment cost incurred for total chemotherapy for the Pertuzumab group was 130456 Singapore Dollars compared to 34523 Singapore Dollars for the non-Pertuzumab group. The median percentage of total chemotherapy costs per patient in the Pertuzumab group spent on Pertuzumab was 50.3%. CONCLUSION: This study shows that Pertuzumab use in the treatment of metastatic breast cancer is associated with a significantly better survival and a low incidence of serious cardiotoxicity. However, the proportionate cost of Pertuzumab therapy remains high and further cost-effectiveness studies should be conducted.

Impact of Knowledge and Attitudes on Lifestyle Practices in Preventing Type 2 Diabetes Mellitus.

INTRODUCTION: Diabetes mellitus is a major public health issue in Singapore. To shape healthcare policies for the primary prevention of diabetes, it is crucial to understand Singaporeans' knowledge, attitudes and practices related to diabetes and its prevention. This study aimed to assess the knowledge, attitudes and lifestyles of individuals without diabetes. MATERIALS AND METHODS: A cross-sectional household survey was performed between 31 January to 3 February 2019 to examine knowledge, attitudes and practices related to diabetes. Inclusion criteria of the participants included: 1) Singaporeans/permanent residents, 2) between 30 to 64 years old, and 3) who did not have a diagnosis of diabetes. Logistic and linear regression models were used to analyse the association of knowledge and attitudes with physical activity and diet habits, respectively. RESULTS: Among 806 participants, 72.2% did not meet the Health Promotion Board's physical activity recommendation. Physical activity was associated with better diabetes knowledge (odds ratio [OR] 5.38, 95% confidence interval [CI] = 1.65-17.53, P = 0.049), stronger beliefs in diabetes prevention (OR 3.36, 95% CI = 1.02-11.12, P = 0.047) and lower levels of worry about diabetes (OR 0.41, 95% CI 0.17-1.00, P = 0.049). Neither knowledge nor beliefs or worries about diabetes was associated with diet. CONCLUSION: There is a need to reinforce the importance of physical activity and healthy diet in preventing diabetes. Although improving the knowledge level of diabetes may increase physical activity of the population, it is unlikely to improve dietary choices without effective behavior change interventions.