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2. Detecting Activities of Daily Living and Routine Behaviours in Dementia Patients Living Alone Using Smart Meter Load Disaggregation

Author

Chalmers, C., Fergus, P., Montanez, C. Aday Curbelo, Sikdar, S., Ball, F., and Kendall, B.

Subjects
Computer Science - Computers and Society, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The emergence of an ageing population is a significant public health concern. This has led to an increase in the number of people living with progressive neurodegenerative disorders like dementia. Consequently, the strain this is places on health and social care services means providing 24-hour monitoring is not sustainable. Technological intervention is being considered, however no solution exists to non-intrusively monitor the independent living needs of patients with dementia. As a result many patients hit crisis point before intervention and support is provided. In parallel, patient care relies on feedback from informal carers about significant behavioural changes. Yet, not all people have a social support network and early intervention in dementia care is often missed. The smart meter rollout has the potential to change this. Using machine learning and signal processing techniques, a home energy supply can be disaggregated to detect which home appliances are turned on and off. This will allow Activities of Daily Living (ADLs) to be assessed, such as eating and drinking, and observed changes in routine to be detected for early intervention. The primary aim is to help reduce deterioration and enable patients to stay in their homes for longer. A Support Vector Machine (SVM) and Random Decision Forest classifier are modelled using data from three test homes. The trained models are then used to monitor two patients with dementia during a six-month clinical trial undertaken in partnership with Mersey Care NHS Foundation Trust. In the case of load disaggregation for appliance detection, the SVM achieved (AUC=0.86074, Sen=0.756 and Spec=0.92838). While the Decision Forest achieved (AUC=0.9429, Sen=0.9634 and Spec=0.9634). ADLs are also analysed to identify the behavioural patterns of the occupant while detecting alterations in routine.

Published
2019

11. Understanding factors associated with continuation of use of injectable contraceptives in Karnataka and Maharashtra, India: a cross-sectional household study

Author

Singal, Sunita, primary, Sikdar, S K, additional, Kaushik, S, additional, Kniss, Jennifer, additional, Singh, Pragati, additional, Bhatt, Nidhi, additional, Samandari, Ghazaleh, additional, Pal, Manoj, additional, Dere, Harshwardhan, additional, Cagatay, Levent, additional, and O’Connell, Kathryn A, additional

Published
2022
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15. In this issue

Author

Rath, Satyajit and Sikdar, S. K.

Published
2001

39. Catharanthus roseus (L.) G. Don counteracts the ampicillin resistance in multiple antibiotic-resistant Staphylococcus aureus by downregulation of PBP2a synthesis

Author

Shil Aparna, Mukherjee Sushmit, Biswas Prerona, Majhi Sudipta, Sikdar Sima, Bishayi Biswadev, and Sikdar née Bhakta Mausumi

Subjects
staphylococcus aureus, ethanol extract of catharanthus roseus root, ampicillin resistance, penicillin-binding protein 2a, comet assay, Biology (General), QH301-705.5
Published
2023
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41. Epigenome-wide meta-analysis of DNA methylation and childhood asthma

Author

Reese, S. E. (Sarah E.), Xu, C.-J. (Cheng-Jian), den Dekker, H. T. (Herman T.), Lee, M. K. (Mi Kyeong), Sikdar, S. (Sinjini), Ruiz-Arenas, C. (Carlos), Merid, S. K. (Simon K.), Rezwan, F. I. (Faisal I.), Page, C. M. (Christian M.), Ullemar, V. (Vilhelmina), Melton, P. E. (Phillip E.), Oh, S. S. (Sam S.), Yang, I. V. (Ivana V.), Burrows, K. (Kimberley), Söderhäll, C. (Cilla), Jima, D. D. (Dereje D.), Gao, L. (Lu), Arathimos, R. (Ryan), Küpers, L. K. (Leanne K.), Wielscher, M. (Matthias), Rzehak, P. (Peter), Lahti, J. (Jari), Laprise, C. (Catherine), Madore, A.-M. (Anne-Marie), Ward, J. (James), Bennett, B. D. (Brian D.), Wang, T. (Tianyuan), Bell, D. A. (Douglas A.), T. B. (The BIOS consortium), Vonk, J. M. (Judith M.), Håberg, S. E. (Siri E.), Zhao, S. (Shanshan), Karlsson, R. (Robert), Hollams, E. (Elysia), Hu, D. (Donglei), Richards, A. J. (Adam J.), Bergström, A. (Anna), Sharp, G. C. (Gemma C.), Felix, J. F. (Janine F.), Bustamante, M. (Mariona), Gruzieva, O. (Olena), Maguire, R. L. (Rachel L.), Gilliland, F. (Frank), Baïz, N. (Nour), Nohr, E. A. (Ellen A.), Corpeleijn, E. (Eva), Sebert, S. (Sylvain), Karmaus, W. (Wilfried), Grote, V. (Veit), Kajantie, E. (Eero), Magnus, M. C. (Maria C.), Örtqvist, A. K. (Anne K.), Eng, C. (Celeste), Liu, A. H. (Andrew H.), Kull, I. (Inger), Jaddoe, V. W. (Vincent W.V.), Sunyer, J. (Jordi), Kere, J. (Juha), Hoyo, C. (Cathrine), Annesi-Maesano, I. (Isabella), Arshad, S. H. (Syed Hasan), Koletzko, B. (Berthold), Brunekreef, B. (Bert), Binder, E. B. (Elisabeth B.), Räikkönen, K. (Katri), Reischl, E. (Eva), Holloway, J. W. (John W.), Järvelin, M.-R. (Marjo-Riitta), Snieder, H. (Harold), Kazmi, N. (Nabila), Breton, C. V. (Carrie V.), Murphy, S. K. (Susan K.), Pershagen, G. (Göran), Anto, J. M. (Josep Maria), Relton, C. L. (Caroline L.), Schwartz, D. A. (David A.), Burchard, E. G. (Esteban G.), Huang, R.-C. (Rae-Chi), Nystad, W. (Wenche), Almqvist, C. (Catarina), Henderson, A. J. (A. John), Melén, E. (Erik), Duijts, L. (Liesbeth), Koppelman, G. H. (Gerard H.), and London, S. J. (Stephanie J.)

Subjects
epigenetics, newborn, methylation, asthma, drug development, childhood
Abstract

Background: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. Objective: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. Methods: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. Results: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. Conclusion: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Published
2019

47. Epigenome-wide meta-analysis of DNA methylation and childhood asthma

Author

Reese, S., Xu, C., den Dekker, H., Lee, M., Sikdar, S., Ruiz-Arenas, C., Merid, S., Rezwan, F., Page, C., Ullemar, V., Melton, Phillip, Oh, S., Yang, I., Burrows, K., Söderhäll, C., Jima, D., Gao, L., Arathimos, R., Küpers, L., Wielscher, M., Rzehak, P., Lahti, J., Laprise, C., Madore, A., Ward, J., Bennett, B., Wang, T., Bell, D., Vonk, J., Håberg, S., Zhao, S., Karlsson, R., Hollams, E., Hu, D., Richards, A., Bergström, A., Sharp, G., Felix, J., Bustamante, M., Gruzieva, O., Maguire, R., Gilliland, F., Baïz, N., Nohr, E., Corpeleijn, E., Sebert, S., Karmaus, W., Grote, V., Kajantie, E., Magnus, M., Örtqvist, A., Eng, C., Liu, A., Kull, I., Jaddoe, V., Sunyer, J., Kere, J., Hoyo, C., Annesi-Maesano, I., Reese, S., Xu, C., den Dekker, H., Lee, M., Sikdar, S., Ruiz-Arenas, C., Merid, S., Rezwan, F., Page, C., Ullemar, V., Melton, Phillip, Oh, S., Yang, I., Burrows, K., Söderhäll, C., Jima, D., Gao, L., Arathimos, R., Küpers, L., Wielscher, M., Rzehak, P., Lahti, J., Laprise, C., Madore, A., Ward, J., Bennett, B., Wang, T., Bell, D., Vonk, J., Håberg, S., Zhao, S., Karlsson, R., Hollams, E., Hu, D., Richards, A., Bergström, A., Sharp, G., Felix, J., Bustamante, M., Gruzieva, O., Maguire, R., Gilliland, F., Baïz, N., Nohr, E., Corpeleijn, E., Sebert, S., Karmaus, W., Grote, V., Kajantie, E., Magnus, M., Örtqvist, A., Eng, C., Liu, A., Kull, I., Jaddoe, V., Sunyer, J., Kere, J., Hoyo, C., and Annesi-Maesano, I.

Abstract

Background: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. Objective: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. Methods: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. Results: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. Conclusion: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

Published
2019

49. Abstracts

Author

Grilc, Sonja, Kuster, Vlasta, Zorec, Robert, Japelj, Irena, Ilievski, Vladimir, Budihna, Metka V., Marhl, Marko, Brumen, Milan, Schuster, Stefan, Heinrich, Reinhart, Martin, T. F. J., Pozzan, Tullio, Rupnik, M., Kreft, M., Sikdar, S. K., Zorec, R., Sikdar, Sujit K., Kreft, Marko, Smith, S. M., Namkung, Y., Foletti, D., Klingauf, J., Shin, H. S., Scheller, R. H., Tsien, R. W., and Zupančič, Gregor

Published
2000
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