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2. Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

Author

Ahmad, Abrar, Lim, Lee-Ling, Morieri, Mario Luca, Tam, Claudia Ha-ting, Cheng, Feifei, Chikowore, Tinashe, Dudenhöffer-Pfeifer, Monika, Fitipaldi, Hugo, Huang, Chuiguo, Kanbour, Sarah, Sarkar, Sudipa, Koivula, Robert Wilhelm, Motala, Ayesha A., Tye, Sok Cin, Yu, Gechang, Zhang, Yingchai, Provenzano, Michele, Sherifali, Diana, de Souza, Russell J., Tobias, Deirdre Kay, Gomez, Maria F., Ma, Ronald C. W., and Mathioudakis, Nestoras

Published
2024
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4. Adaptability, Personality, and Social Support: Examining Links with Psychological Wellbeing among Chinese High School Students

Author

Holliman, Andrew, Cheng, Feifei, and Waldeck, Daniel

Abstract

The first year of boarding senior high school marks a period of great change for students. The extent to which students are able to adjust to successfully navigate this change (adaptability) likely has an impact on their psychological wellbeing. It has also been theorized that students' personality traits and perceived social support may impact upon their adaptability and, directly and/or indirectly through adaptability, influence their psychological wellbeing. However, the literature examining independent and mediating effects of adaptability on psychological wellbeing is sparse particularly among students from non-Western cultures. In the present study, 102 grade-one high school students in China, were surveyed for their personality, perceived social support, adaptability, and psychological wellbeing (life satisfaction, mental well-being, and psychological distress). Findings showed that adaptability (along with neuroticism, extraversion, and social support) made a significant independent contribution to students' psychological wellbeing. Further, adaptability was found to fully mediate the relationships between personality (conscientiousness and neuroticism) and psychological wellbeing, and to partially mediate the relationships between extraversion and psychological wellbeing, and social support and psychological wellbeing. These findings have important theoretical and practical implications for researchers and educators who are seeking to support students' adjustment to boarding senior high school.

Published
2022

5. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Author

Tobias, Deirdre K, Merino, Jordi, Ahmad, Abrar, Aiken, Catherine, Benham, Jamie L, Bodhini, Dhanasekaran, Clark, Amy L, Colclough, Kevin, Corcoy, Rosa, Cromer, Sara J, Duan, Daisy, Felton, Jamie L, Francis, Ellen C, Gillard, Pieter, Gingras, Véronique, Gaillard, Romy, Haider, Eram, Hughes, Alice, Ikle, Jennifer M, Jacobsen, Laura M, Kahkoska, Anna R, Kettunen, Jarno LT, Kreienkamp, Raymond J, Lim, Lee-Ling, Männistö, Jonna ME, Massey, Robert, Mclennan, Niamh-Maire, Miller, Rachel G, Morieri, Mario Luca, Most, Jasper, Naylor, Rochelle N, Ozkan, Bige, Patel, Kashyap Amratlal, Pilla, Scott J, Prystupa, Katsiaryna, Raghavan, Sridharan, Rooney, Mary R, Schön, Martin, Semnani-Azad, Zhila, Sevilla-Gonzalez, Magdalena, Svalastoga, Pernille, Takele, Wubet Worku, Tam, Claudia Ha-ting, Thuesen, Anne Cathrine B, Tosur, Mustafa, Wallace, Amelia S, Wang, Caroline C, Wong, Jessie J, Yamamoto, Jennifer M, Young, Katherine, Amouyal, Chloé, Andersen, Mette K, Bonham, Maxine P, Chen, Mingling, Cheng, Feifei, Chikowore, Tinashe, Chivers, Sian C, Clemmensen, Christoffer, Dabelea, Dana, Dawed, Adem Y, Deutsch, Aaron J, Dickens, Laura T, DiMeglio, Linda A, Dudenhöffer-Pfeifer, Monika, Evans-Molina, Carmella, Fernández-Balsells, María Mercè, Fitipaldi, Hugo, Fitzpatrick, Stephanie L, Gitelman, Stephen E, Goodarzi, Mark O, Grieger, Jessica A, Guasch-Ferré, Marta, Habibi, Nahal, Hansen, Torben, Huang, Chuiguo, Harris-Kawano, Arianna, Ismail, Heba M, Hoag, Benjamin, Johnson, Randi K, Jones, Angus G, Koivula, Robert W, Leong, Aaron, Leung, Gloria KW, Libman, Ingrid M, Liu, Kai, Long, S Alice, Lowe, William L, Morton, Robert W, Motala, Ayesha A, Onengut-Gumuscu, Suna, Pankow, James S, Pathirana, Maleesa, Pazmino, Sofia, Perez, Dianna, Petrie, John R, Powe, Camille E, Quinteros, Alejandra, Jain, Rashmi, Ray, Debashree, and Ried-Larsen, Mathias

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Precision Medicine, Diabetes, Minority Health, Good Health and Well Being, Humans, Consensus, Diabetes Mellitus, Evidence-Based Medicine, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Published
2023

12. Relative leucocyte telomere length is associated with incident end-stage kidney disease and rapid decline of kidney function in type 2 diabetes: analysis from the Hong Kong Diabetes Register

Author

Cheng, Feifei, Luk, Andrea O., Wu, Hongjiang, Tam, Claudia H. T., Lim, Cadmon K. P., Fan, Baoqi, Jiang, Guozhi, Carroll, Luke, Yang, Aimin, Lau, Eric S. H., Ng, Alex C. W., Lee, Heung Man, Chow, Elaine, Kong, Alice P. S., Keech, Anthony C., Joglekar, Mugdha V., So, Wing Yee, Hardikar, Anandwardhan A., Chan, Juliana C. N., Jenkins, Alicia J., and Ma, Ronald C. W.

Published
2022
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13. Early emergence of sexual dimorphism in offspring leukocyte telomere length was associated with maternal and children’s glucose metabolism—a longitudinal study

Author

Wong, Kwun Kiu, Cheng, Feifei, Lim, Cadmon K. P., Tam, Claudia H. T., Tutino, Greg, Yuen, Lai Yuk, Wang, Chi Chiu, Hou, Yong, Chan, Michael H. M., Ho, Chung Shun, Joglekar, Mugdha V., Hardikar, Anandwardhan A., Jenkins, Alicia J., Metzger, Boyd E., Lowe, Jr., William L., Tam, Wing Hung, and Ma, Ronald C. W.

Published
2022
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16. Shortened relative leukocyte telomere length is associated with all-cause mortality in type 2 diabetes- analysis from the Hong Kong Diabetes Register

Author

Cheng, Feifei, Luk, Andrea O., Wu, Hongjiang, Lim, Cadmon K.P., Carroll, Luke, Tam, Claudia H.T., Fan, Baoqi, Yang, Aimin, Lau, Eric S.H., Ng, Alex C.W., Lee, Heung Man, Chow, Elaine, Kong, Alice P.S., Keech, Anthony C., Joglekar, Mugdha V., So, Wing Yee, Jenkins, Alicia J., Chan, Juliana C.N., Hardikar, Anandwardhan A., and Ma, Ronald C.W.

Published
2021
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23. Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Author

Ahmad, Abrar, primary, Lim, Lee-Ling, additional, Morieri, Mario, additional, Tam, Claudia, additional, Cheng, Feifei, additional, Chikowore, Tinashe, additional, Dudenhöffer-Pfeifer, Monika, additional, Fitipaldi, Hugo, additional, Huang, Chuiguo, additional, Kanbour, Sarah, additional, Sarkar, Sudipa, additional, Koivula, Robert, additional, Motala, Ayesha, additional, Tye, Sok, additional, Yu, Gechang, additional, Zhang, Yingchai, additional, Provenzano, Michele, additional, Sherifali, Diana, additional, de Souza, Russell, additional, Tobias, Deirdre, additional, Gomez, Maria, additional, Ma, Ronald, additional, PMDI, ADA/EASD, additional, and Mathioudakis, Nestoras, additional

Published
2023
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26. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Author

Tobias, Deirdre K., Merino, Jordi, Ahmad, Abrar, Aiken, Catherine, Benham, Jamie L., Bodhini, Dhanasekaran, Clark, Amy L., Colclough, Kevin, Corcoy, Rosa, Cromer, Sara J., Duan, Daisy, Felton, Jamie L., Francis, Ellen C., Gillard, Pieter, Gingras, Véronique, Gaillard, Romy, Haider, Eram, Hughes, Alice, Ikle, Jennifer M., Jacobsen, Laura M., Kahkoska, Anna R., Kettunen, Jarno L.T., Kreienkamp, Raymond J., Lim, Lee Ling, Männistö, Jonna M.E., Massey, Robert, Mclennan, Niamh Maire, Miller, Rachel G., Morieri, Mario Luca, Most, Jasper, Naylor, Rochelle N., Ozkan, Bige, Patel, Kashyap Amratlal, Pilla, Scott J., Prystupa, Katsiaryna, Raghavan, Sridharan, Rooney, Mary R., Schön, Martin, Semnani-Azad, Zhila, Sevilla-Gonzalez, Magdalena, Svalastoga, Pernille, Takele, Wubet Worku, Tam, Claudia Ha ting, Thuesen, Anne Cathrine B., Tosur, Mustafa, Wallace, Amelia S., Wang, Caroline C., Wong, Jessie J., Yamamoto, Jennifer M., Young, Katherine, Amouyal, Chloé, Andersen, Mette K., Bonham, Maxine P., Chen, Mingling, Cheng, Feifei, Chikowore, Tinashe, Chivers, Sian C., Clemmensen, Christoffer, Dabelea, Dana, Dawed, Adem Y., Deutsch, Aaron J., Dickens, Laura T., DiMeglio, Linda A., Dudenhöffer-Pfeifer, Monika, Evans-Molina, Carmella, Fernández-Balsells, María Mercè, Fitipaldi, Hugo, Fitzpatrick, Stephanie L., Gitelman, Stephen E., Goodarzi, Mark O., Grieger, Jessica A., Guasch-Ferré, Marta, Habibi, Nahal, Hansen, Torben, Huang, Chuiguo, Harris-Kawano, Arianna, Ismail, Heba M., Hoag, Benjamin, Johnson, Randi K., Jones, Angus G., Koivula, Robert W., Leong, Aaron, Leung, Gloria K.W., Libman, Ingrid M., Liu, Kai, Long, S. Alice, Lowe, William L., Morton, Robert W., Motala, Ayesha A., Onengut-Gumuscu, Suna, Pankow, James S., Pathirana, Maleesa, Pazmino, Sofia, Perez, Dianna, Petrie, John R., Powe, Camille E., Quinteros, Alejandra, Jain, Rashmi, Ray, Debashree, Ried-Larsen, Mathias, Saeed, Zeb, Santhakumar, Vanessa, Kanbour, Sarah, Sarkar, Sudipa, Monaco, Gabriela S.F., Scholtens, Denise M., Selvin, Elizabeth, Sheu, Wayne Huey Herng, Speake, Cate, Stanislawski, Maggie A., Steenackers, Nele, Steck, Andrea K., Stefan, Norbert, Støy, Julie, Taylor, Rachael, Tye, Sok Cin, Ukke, Gebresilasea Gendisha, Urazbayeva, Marzhan, Van der Schueren, Bart, Vatier, Camille, Wentworth, John M., Hannah, Wesley, White, Sara L., Yu, Gechang, Zhang, Yingchai, Zhou, Shao J., Beltrand, Jacques, Polak, Michel, Aukrust, Ingvild, de Franco, Elisa, Flanagan, Sarah E., Maloney, Kristin A., McGovern, Andrew, Molnes, Janne, Nakabuye, Mariam, Njølstad, Pål Rasmus, Pomares-Millan, Hugo, Provenzano, Michele, Saint-Martin, Cécile, Zhang, Cuilin, Zhu, Yeyi, Auh, Sungyoung, de Souza, Russell, Fawcett, Andrea J., Gruber, Chandra, Mekonnen, Eskedar Getie, Mixter, Emily, Sherifali, Diana, Eckel, Robert H., Nolan, John J., Philipson, Louis H., Brown, Rebecca J., Billings, Liana K., Boyle, Kristen, Costacou, Tina, Dennis, John M., Florez, Jose C., Gloyn, Anna L., Gomez, Maria F., Gottlieb, Peter A., Greeley, Siri Atma W., Griffin, Kurt, Hattersley, Andrew T., Hirsch, Irl B., Hivert, Marie France, Hood, Korey K., Josefson, Jami L., Kwak, Soo Heon, Laffel, Lori M., Lim, Siew S., Loos, Ruth J.F., Ma, Ronald C.W., Mathieu, Chantal, Mathioudakis, Nestoras, Meigs, James B., Misra, Shivani, Mohan, Viswanathan, Murphy, Rinki, Oram, Richard, Owen, Katharine R., Ozanne, Susan E., Pearson, Ewan R., Perng, Wei, Pollin, Toni I., Pop-Busui, Rodica, Pratley, Richard E., Redman, Leanne M., Redondo, Maria J., Reynolds, Rebecca M., Semple, Robert K., Sherr, Jennifer L., Sims, Emily K., Sweeting, Arianne, Tuomi, Tiinamaija, Udler, Miriam S., Vesco, Kimberly K., Vilsbøll, Tina, Wagner, Robert, Rich, Stephen S., Franks, Paul W., Tobias, Deirdre K., Merino, Jordi, Ahmad, Abrar, Aiken, Catherine, Benham, Jamie L., Bodhini, Dhanasekaran, Clark, Amy L., Colclough, Kevin, Corcoy, Rosa, Cromer, Sara J., Duan, Daisy, Felton, Jamie L., Francis, Ellen C., Gillard, Pieter, Gingras, Véronique, Gaillard, Romy, Haider, Eram, Hughes, Alice, Ikle, Jennifer M., Jacobsen, Laura M., Kahkoska, Anna R., Kettunen, Jarno L.T., Kreienkamp, Raymond J., Lim, Lee Ling, Männistö, Jonna M.E., Massey, Robert, Mclennan, Niamh Maire, Miller, Rachel G., Morieri, Mario Luca, Most, Jasper, Naylor, Rochelle N., Ozkan, Bige, Patel, Kashyap Amratlal, Pilla, Scott J., Prystupa, Katsiaryna, Raghavan, Sridharan, Rooney, Mary R., Schön, Martin, Semnani-Azad, Zhila, Sevilla-Gonzalez, Magdalena, Svalastoga, Pernille, Takele, Wubet Worku, Tam, Claudia Ha ting, Thuesen, Anne Cathrine B., Tosur, Mustafa, Wallace, Amelia S., Wang, Caroline C., Wong, Jessie J., Yamamoto, Jennifer M., Young, Katherine, Amouyal, Chloé, Andersen, Mette K., Bonham, Maxine P., Chen, Mingling, Cheng, Feifei, Chikowore, Tinashe, Chivers, Sian C., Clemmensen, Christoffer, Dabelea, Dana, Dawed, Adem Y., Deutsch, Aaron J., Dickens, Laura T., DiMeglio, Linda A., Dudenhöffer-Pfeifer, Monika, Evans-Molina, Carmella, Fernández-Balsells, María Mercè, Fitipaldi, Hugo, Fitzpatrick, Stephanie L., Gitelman, Stephen E., Goodarzi, Mark O., Grieger, Jessica A., Guasch-Ferré, Marta, Habibi, Nahal, Hansen, Torben, Huang, Chuiguo, Harris-Kawano, Arianna, Ismail, Heba M., Hoag, Benjamin, Johnson, Randi K., Jones, Angus G., Koivula, Robert W., Leong, Aaron, Leung, Gloria K.W., Libman, Ingrid M., Liu, Kai, Long, S. Alice, Lowe, William L., Morton, Robert W., Motala, Ayesha A., Onengut-Gumuscu, Suna, Pankow, James S., Pathirana, Maleesa, Pazmino, Sofia, Perez, Dianna, Petrie, John R., Powe, Camille E., Quinteros, Alejandra, Jain, Rashmi, Ray, Debashree, Ried-Larsen, Mathias, Saeed, Zeb, Santhakumar, Vanessa, Kanbour, Sarah, Sarkar, Sudipa, Monaco, Gabriela S.F., Scholtens, Denise M., Selvin, Elizabeth, Sheu, Wayne Huey Herng, Speake, Cate, Stanislawski, Maggie A., Steenackers, Nele, Steck, Andrea K., Stefan, Norbert, Støy, Julie, Taylor, Rachael, Tye, Sok Cin, Ukke, Gebresilasea Gendisha, Urazbayeva, Marzhan, Van der Schueren, Bart, Vatier, Camille, Wentworth, John M., Hannah, Wesley, White, Sara L., Yu, Gechang, Zhang, Yingchai, Zhou, Shao J., Beltrand, Jacques, Polak, Michel, Aukrust, Ingvild, de Franco, Elisa, Flanagan, Sarah E., Maloney, Kristin A., McGovern, Andrew, Molnes, Janne, Nakabuye, Mariam, Njølstad, Pål Rasmus, Pomares-Millan, Hugo, Provenzano, Michele, Saint-Martin, Cécile, Zhang, Cuilin, Zhu, Yeyi, Auh, Sungyoung, de Souza, Russell, Fawcett, Andrea J., Gruber, Chandra, Mekonnen, Eskedar Getie, Mixter, Emily, Sherifali, Diana, Eckel, Robert H., Nolan, John J., Philipson, Louis H., Brown, Rebecca J., Billings, Liana K., Boyle, Kristen, Costacou, Tina, Dennis, John M., Florez, Jose C., Gloyn, Anna L., Gomez, Maria F., Gottlieb, Peter A., Greeley, Siri Atma W., Griffin, Kurt, Hattersley, Andrew T., Hirsch, Irl B., Hivert, Marie France, Hood, Korey K., Josefson, Jami L., Kwak, Soo Heon, Laffel, Lori M., Lim, Siew S., Loos, Ruth J.F., Ma, Ronald C.W., Mathieu, Chantal, Mathioudakis, Nestoras, Meigs, James B., Misra, Shivani, Mohan, Viswanathan, Murphy, Rinki, Oram, Richard, Owen, Katharine R., Ozanne, Susan E., Pearson, Ewan R., Perng, Wei, Pollin, Toni I., Pop-Busui, Rodica, Pratley, Richard E., Redman, Leanne M., Redondo, Maria J., Reynolds, Rebecca M., Semple, Robert K., Sherr, Jennifer L., Sims, Emily K., Sweeting, Arianne, Tuomi, Tiinamaija, Udler, Miriam S., Vesco, Kimberly K., Vilsbøll, Tina, Wagner, Robert, Rich, Stephen S., and Franks, Paul W.

Abstract

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Published
2023

28. Supplementary Figure S1 from MEF2D Transduces Microenvironment Stimuli to ZEB1 to Promote Epithelial–Mesenchymal Transition and Metastasis in Colorectal Cancer

Author

Su, Li, primary, Luo, Yongli, primary, Yang, Zhi, primary, Yang, Jing, primary, Yao, Chao, primary, Cheng, Feifei, primary, Shan, Juanjuan, primary, Chen, Jun, primary, Li, Fangfang, primary, Liu, Limei, primary, Liu, Chungang, primary, Xu, Yanmin, primary, Jiang, Lupin, primary, Guo, Deyu, primary, Prieto, Jesus, primary, Ávila, Matías A., primary, Shen, Junjie, primary, and Qian, Cheng, primary

Published
2023
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29. Supplementary Tables S1-S4 from MEF2D Transduces Microenvironment Stimuli to ZEB1 to Promote Epithelial–Mesenchymal Transition and Metastasis in Colorectal Cancer

Author

Su, Li, primary, Luo, Yongli, primary, Yang, Zhi, primary, Yang, Jing, primary, Yao, Chao, primary, Cheng, Feifei, primary, Shan, Juanjuan, primary, Chen, Jun, primary, Li, Fangfang, primary, Liu, Limei, primary, Liu, Chungang, primary, Xu, Yanmin, primary, Jiang, Lupin, primary, Guo, Deyu, primary, Prieto, Jesus, primary, Ávila, Matías A., primary, Shen, Junjie, primary, and Qian, Cheng, primary

Published
2023
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30. Supplementary Methods and References from MEF2D Transduces Microenvironment Stimuli to ZEB1 to Promote Epithelial–Mesenchymal Transition and Metastasis in Colorectal Cancer

Author

Su, Li, primary, Luo, Yongli, primary, Yang, Zhi, primary, Yang, Jing, primary, Yao, Chao, primary, Cheng, Feifei, primary, Shan, Juanjuan, primary, Chen, Jun, primary, Li, Fangfang, primary, Liu, Limei, primary, Liu, Chungang, primary, Xu, Yanmin, primary, Jiang, Lupin, primary, Guo, Deyu, primary, Prieto, Jesus, primary, Ávila, Matías A., primary, Shen, Junjie, primary, and Qian, Cheng, primary

Published
2023
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31. Supplemental Figure Legends from MEF2D Transduces Microenvironment Stimuli to ZEB1 to Promote Epithelial–Mesenchymal Transition and Metastasis in Colorectal Cancer

Author

Su, Li, primary, Luo, Yongli, primary, Yang, Zhi, primary, Yang, Jing, primary, Yao, Chao, primary, Cheng, Feifei, primary, Shan, Juanjuan, primary, Chen, Jun, primary, Li, Fangfang, primary, Liu, Limei, primary, Liu, Chungang, primary, Xu, Yanmin, primary, Jiang, Lupin, primary, Guo, Deyu, primary, Prieto, Jesus, primary, Ávila, Matías A., primary, Shen, Junjie, primary, and Qian, Cheng, primary

Published
2023
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32. Data from MEF2D Transduces Microenvironment Stimuli to ZEB1 to Promote Epithelial–Mesenchymal Transition and Metastasis in Colorectal Cancer

Author

Su, Li, primary, Luo, Yongli, primary, Yang, Zhi, primary, Yang, Jing, primary, Yao, Chao, primary, Cheng, Feifei, primary, Shan, Juanjuan, primary, Chen, Jun, primary, Li, Fangfang, primary, Liu, Limei, primary, Liu, Chungang, primary, Xu, Yanmin, primary, Jiang, Lupin, primary, Guo, Deyu, primary, Prieto, Jesus, primary, Ávila, Matías A., primary, Shen, Junjie, primary, and Qian, Cheng, primary

Published
2023
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34. Additional file 2 of Early emergence of sexual dimorphism in offspring leukocyte telomere length was associated with maternal and children’s glucose metabolism—a longitudinal study

Author

Wong, Kwun Kiu, Cheng, Feifei, Lim, Cadmon K. P., Tam, Claudia H. T., Tutino, Greg, Yuen, Lai Yuk, Wang, Chi Chiu, Hou, Yong, Chan, Michael H. M., Ho, Chung Shun, Joglekar, Mugdha V., Hardikar, Anandwardhan A., Jenkins, Alicia J., Metzger, Boyd E., Lowe, William L., Tam, Wing Hung, and Ma, Ronald C. W.

Abstract

Additional file 2: Supplementary table 1. Univariate associations between cord and children’s LTL with their basic characteristics. Supplementary table 2. Offspring LTL at follow up and associations with glucose and insulin related traits. Supplementary table 3. Basic characteristics offspring at follow-up traits stratified according to children’s LTL tertiles. Supplementary table 4. Regression result for Cord blood LTL association with newborn and maternal glycaemic traits. Supplementary table 5. Sex-stratified maternal and offspring characteristics. Supplementary table 6. Glucose and insulin traits stratified according to LTL change group. Supplementary table 7. Sex -stratified children’s LTL associations with maternal and newborn characteristics. Supplementary table 8. Sex -stratified cord blood LTL associations with maternal and newborn characteristics. Supplementary table 9. Baseline characteristics between mothers returned for follow-up to mothers without follow-up. Supplementary figure 1. Diagram for HAPO and HAPO follow-up recruitment and mother-child pair excluded with reasons. Supplementary figure 2. The Heatmap showing the correlations between maternal (MA) and offspring (OS) glucose and insulin traits. Supplementary figure 3. Telomere length percentage change histogram. Supplementary figure 4. Schematic illustration on the conceptual associations between glucose and LTL. Supplementary figure 5. Correlations between maternal (MA) and offspring (OS) glucose levels. Supplementary figure 6. The calculation of glucose area under the curve.

Published
2023
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35. Additional file 1 of Early emergence of sexual dimorphism in offspring leukocyte telomere length was associated with maternal and children’s glucose metabolism—a longitudinal study

Author

Wong, Kwun Kiu, Cheng, Feifei, Lim, Cadmon K. P., Tam, Claudia H. T., Tutino, Greg, Yuen, Lai Yuk, Wang, Chi Chiu, Hou, Yong, Chan, Michael H. M., Ho, Chung Shun, Joglekar, Mugdha V., Hardikar, Anandwardhan A., Jenkins, Alicia J., Metzger, Boyd E., Lowe, William L., Tam, Wing Hung, and Ma, Ronald C. W.

Abstract

Additional file 1.

Published
2023
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40. Non-subsampled shearlet transform remote sensing image fusion combined with parameter-adaptive PCNN

Author

CHENG Feifei, FU Zhitao, HUANG Liang, CHEN Pengdi, and HUANG Kun

Subjects
multispectral image, panchromatic image, Computer Science::Computer Vision and Pattern Recognition, Mathematical geography. Cartography, non-subsampled shearlet transform, GA1-1776, image fusion, parameter-adaptive pulse-coupled neural network
Abstract

In order to solve the problem that the parameters of pulse-coupled neural network can't be adjusted adaptively in pan-sharpening image fusion, a non-subsampled shearlet transform remote sensing image fusion method based on the combination of parametric-adaptive pulse coupled neural network model and energy-attributing fusion strategy is proposed. First, the high and low frequency coefficients are obtained by extracting the Y luminance component of the multispectral image YUV color space transform and transforming it with the panchromatic image. Then, aiming at the low-frequency sub-band coefficients are fused by the EA method, the high-frequency sub-band coefficients are obtained by the PA-PCNN model to determine the optimal PCNN model, and then the high-frequency sub-band coefficients are fused; finally, the fusion image is obtained by inverse transformation of NSST and YUV. In this paper, six objective quality indexes, such as spatial frequency, relative dimensionless global error, ERGAS, correlation coefficient, visual information fidelity for fusion, gradient-based fusion performance and structural similarity index, are selected to evaluate the spectral and spatial detail information of the fused images, compared with SE, DGIF, COF and PA-PCNN fusion methods, the proposed method is validated by using multiple sets of high-and low-resolution panchromatic and multispectral remote sensing images, the results show that this method is generally superior to the traditional fusion method of panchromatic and multispectral remote sensing images in objective evaluation and visual perception.

Published
2021

42. Identifying human islet microRNAs associated with donor sex, age and body mass index

Author

Wong, Wilson K.M., primary, Joglekar, Mugdha V., additional, Cheng, Feifei, additional, Jiang, Guozhi, additional, Sørensen, Anja E., additional, Chew, Yi Vee, additional, Loudovaris, Thomas, additional, Thomas, Helen E., additional, Ma, Ronald C.W., additional, Hawthorne, Wayne J., additional, Dalgaard, Louise T., additional, and Hardikar, Anandwardhan A., additional

Published
2022
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44. A pansharpening method combining iterative filtering and NSST-NSML-PAPCNN to optimize spatial detail extraction and injection.

Author

Song, Jiawen, Zhu, Daming, Fu, Zhitao, Cheng, Feifei, Zuo, Xiaoqing, and Chen, Sijing

Subjects
FILTERS & filtration, INFORMATION resources, MULTISPECTRAL imaging
Abstract

Spatial injection-based pansharpening methods are prone to spatial or spectral distortions in pansharpening images due to insufficient extraction of spatial details and a mismatch between the amount of spatial detail information injected and the required amount. To this end, this paper proposes a pansharpening method that optimizes spatial detail extraction and injection. Firstly, a method to optimize the amount of spatial detail injection is proposed, that is, to extract the high-frequency information of the image through iterative filtering and determine the optimal number of iterations based on the global analysis of the method. Then, to fully extract and combine the spatial detail information of the source image, the detailed high-frequency image extracted corresponding to the optimal iterative filtering times is decomposed by non-subsampled shearlet transform (NSST), and a new multi-scale sum-modified-Laplacian (NSML) as an external stimulus to a parameter-adaptive pulse-coupled neural network model (PAPCNN). A fusion rule based on multi-scale morphological gradients is designed to extract a small amount of detailed information for the low-frequency subband. The fused spatial detail image can be obtained by combining the fused low-frequency and high-frequency subbands and inverse NSST transformation. Finally, pansharpening can be realized by combining spatial detail image, injection coefficient, and MS image. In this paper, many experiments are carried out on the QuickBird, GeoEye-1, and WorldView-4 datasets, and quantitative and qualitative comparisons are made with eight advanced methods. Experimental results show that the method proposed in this paper can achieve better fusion results. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Vitamin D Levels During Pregnancy Are Associated With Offspring Telomere Length: A Longitudinal Mother-Child Study

Author

Wong, Kwun Kiu, primary, Cheng, Feifei, additional, Mao, Di, additional, Lim, Cadmon K P, additional, Tam, Claudia H T, additional, Wang, Chi Chiu, additional, Yuen, Lai Yuk, additional, Chan, Michael H M, additional, Ho, Chung Shun, additional, Joglekar, Mugdha V, additional, Hardikar, Anandwardhan A, additional, Jenkins, Alicia J, additional, Metzger, Boyd E, additional, Lowe, William L, additional, Tam, Wing Hung, additional, and Ma, Ronald C W, additional

Published
2022
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