Search

Your search keyword '"Subbarao, Padmaja"' showing total 13 results
13 results on '"Subbarao, Padmaja"'

4. Divergent maturational patterns of the infant bacterial and fungal gut microbiome in the first year of life are associated with inter-kingdom community dynamics and infant nutrition

Author

Mercer, Emily M., Ramay, Hena R., Moossavi, Shirin, Laforest-Lapointe, Isabelle, Reyna, Myrtha E., Becker, Allan B., Simons, Elinor, Mandhane, Piush J., Turvey, Stuart E., Moraes, Theo J., Sears, Malcolm R., Subbarao, Padmaja, Azad, Meghan B., and Arrieta, Marie-Claire

Published
2024
Full Text
View/download PDF

5. Early sex-dependent differences in metabolic profiles of overweight and adiposity in young children: a cross-sectional analysis

Author

Azab, Sandi M, Shanmuganathan, Meera, de Souza, Russell J, Kroezen, Zachary, Desai, Dipika, Williams, Natalie C, Morrison, Katherine M, Atkinson, Stephanie A, Teo, Koon K, Azad, Meghan B, Simons, Elinor, Moraes, Theo J, Mandhane, Piush J, Turvey, Stuart E, Subbarao, Padmaja, Britz-McKibbin, Philip, and Anand, Sonia S

Published
2023
Full Text
View/download PDF

10. Ethnic and diet-related differences in the healthy infant microbiome.

Author

Stearns, Jennifer C., Zulyniak, Michael A., de Souza, Russell J., Campbell, Natalie C., Fontes, Michelle, Shaikh, Mateen, Sears, Malcolm R., Becker, Allan B., Mandhane, Piushkumar J., Subbarao, Padmaja, Turvey, Stuart E., Gupta, Milan, Beyene, Joseph, Surette, Michael G., and Anand, Sonia S.

Subjects
HUMAN microbiota, BREASTFEEDING, HEALTH, DIET, QUALITY of life
Abstract

Background: The infant gut is rapidly colonized by microorganisms soon after birth, and the composition of the microbiota is dynamic in the first year of life. Although a stable microbiome may not be established until 1 to 3 years after birth, the infant gut microbiota appears to be an important predictor of health outcomes in later life. Methods: We obtained stool at one year of age from 173 white Caucasian and 182 South Asian infants from two Canadian birth cohorts to gain insight into how maternal and early infancy exposures influence the development of the gut microbiota. We investigated whether the infant gut microbiota differed by ethnicity (referring to groups of people who have certain racial, cultural, religious, or other traits in common) and by breastfeeding status, while accounting for variations in maternal and infant exposures (such as maternal antibiotic use, gestational diabetes, vegetarianism, infant milk diet, time of introduction of solid food, infant birth weight, and weight gain in the first year). Results: We demonstrate that ethnicity and infant feeding practices independently influence the infant gut microbiome at 1 year, and that ethnic differences can be mapped to alpha diversity as well as a higher abundance of lactic acid bacteria in South Asians and a higher abundance of genera within the order Clostridiales in white Caucasians. Conclusions: The infant gut microbiome is influenced by ethnicity and breastfeeding in the first year of life. Ethnic differences in the gut microbiome may reflect maternal/infant dietary differences and whether these differences are associated with future cardiometabolic outcomes can only be determined after prospective follow-up. [ABSTRACT FROM AUTHOR]

Published
2017
Full Text
View/download PDF

11. AllerGen’s 8th research conference

Author

Arrieta, Marie-Claire, Arevalos, Andrea, Stiemsma, Leah, Chico, Marta E., Sandoval, Carlos, Jin, Minglian, Walter, Jens, Cooper, Phil, Finlay, Brett, Bernatchez, Emilie, Gold, Matthew J., Langlois, Anick, Blais-Lecours, Pascale, Duchaine, Caroline, Marsolais, David, McNagny, Kelly M., Blanchet, Marie-Renée, Brubacher, Jordan, Chhetri, Bimal, Sabaliauskas, Kelly, Bassil, Kate, Kwong, Jeff, Coates, Frances, Takaro, Tim K., Chow, Angela, Miller, Gregory E., Chen, Edith, Mandhane, Piushkumar J., Turvey, Stuart E., Elliott, Susan J., Becker, Allan B., Subbarao, Padmaja, Sears, Malcolm R., Kozyrskyj, Anita L., Dubeau, Aimée, Lu, Zihang, Balkovec, Susan, Kowalik, Krzysztof, Gustafsson, Per, Ratjen, Felix, Edgar, Rachel D., Bush, Nicole R., MacIssac, Julie L., McEwen, Lisa M., Boyce, Thomas W., Kobor, Michael S., Emmerson, Melanie, Shen, Bingqing, Moraes, Theo J., Gabrielli, Sofianne, Clarke, Ann, Eisman, Harley, Morris, Judy, Joseph, Lawrence, LaVieille, Sebastien, Ben-Shoshan, Moshe, Islam, Sumaiya A., Brückmann, Christof, Nieratschker, Vanessa, Jamieson, Kyla C., Proud, David, Kanagaratham, Cynthia, Camateros, Pierre, Kopriva, Frantisek, Henri, Jennifer, Hajduch, Marian, Radzioch, Danuta, Kang, Liane J., Koleva, Petya T., Field, Catherine J., Konya, Tedd, Scott, James A., Konya, Theodore, Azad, Meghan B., Brook, Jeff, Guttman, David, Kumari, Manjeet, Bridgman, Sarah L., Tun, Mon H., Mandal, Rupasri, Wishart, David S., Lee, Amy H. Y., Xia, Jeff, Gill, Erin, Hancock, Bob, Maestre, Danay, Sutherland, Darren, Hirota, Jeremy, Pena, Olga, Carlsten, Christopher, Jones, Meaghan J., MacIsaac, Julia L., Dow, William H., Rosero-Bixby, Luis, Rehkopf, David H., Morimoto, Takeshi, Smith, Steven G., Oliveria, John-Paul, Beaudin, Suzanne, Schlatman, Abbey, Howie, Karen, Obminski, Caitlin, Nusca, Graeme, Sehmi, Roma, Gauvreau, Gail M., O’Byrne, Paul M., North, Michelle, Peng, Cheng, Sanchez-Guerra, Marco, Byun, Hyang-Min, Ellis, Anne K., Baccarelli, Andrea A., Okeme, Joseph O., Dhal, Suman, Saini, Aman, Diamond, Miriam L., Olesovsky, Christopher J., Salter, Brittany M., Wang, Michael, Lacy, Paige, O’Sullivan, Michael J., Park, Chan Y., Fredberg, Jeffrey J., Lauzon, Anne-Marie, Martin, James G., Ryu, Min Hyung, Mookherjee, Neeloffer, Simons, Elinor, Lefebvre, Diana, Dai, David, Singh, Amrit, Shannon, Casey P., Kim, Young Woong, Yang, Chen Xi, Mark FitzGerald, J., Boulet, Louis-Philippe, Tebbutt, Scott J., Singhera, Gurpreet K., JasemineYang, S., Dorscheid, Delbert R., Sinnock, Hasantha, Goruk, Susan, Tavakoli, Hamid, Lynd, Larry D., Sadatsafavi, Mohsen, Tenn, Mark W., Thiele, Jenny, Adams, Daniel E., Steacy, Lisa M., Torabi, Bahar, De Schryver, Sarah, Lejtenyi, Duncan, Baerg, Ingrid, Chan, Edmond S., Mazer, Bruce D., Tran, Maxwell M., Dai, Wei Hao, Lou, Wendy, Chari, Radha S., Conway, Edward M., Neighbour, Helen, Larché, Mark, and Tebbutt, Scott J

Published
2016
Full Text
View/download PDF

12. A new exposure metric for traffic-related air pollution?An analysis of determinants of hopanes in settled indoor house dust.

Author

Sbihi, Hind, Brook, Jeffrey R., Allen, Ryan W., Curran, Jason H., Dell, Sharon, Mandhane, Piush, Scott, James A., Sears, Malcolm R., Subbarao, Padmaja, Takaro, Timothy K., Turvey, Stuart E., Wheeler, Amanda J., and Brauer, Michael

Subjects
AIR pollution, DUST, LAND use, LUBRICATING oils, GAS chromatography, MASS spectrometry, SPATIOTEMPORAL processes
Abstract

Background: Exposure to traffic-related air pollution (TRAP) can adversely impact health but epidemiologic studies are limited in their abilities to assess long-term exposures and incorporate variability in indoor pollutant infiltration. Methods: In order to examine settled house dust levels of hopanes, engine lubricating oil byproducts found in vehicle exhaust, as a novel TRAP exposure measure, dust samples were collected from 171 homes in five Canadian cities and analyzed by gas chromatography-mass spectrometry. To evaluate source contributions, the relative abundance of the highest concentration hopane monomer in house dust was compared to that in outdoor air. Geographic variables related to TRAP emissions and outdoor NO2 concentrations from city-specific TRAP land use regression (LUR) models were calculated at each georeferenced residence location and assessed as predictors of variability in dust hopanes. Results: Hopanes relative abundance in house dust and ambient air were significantly correlated (Pearson's r=0.48, p<0.05), suggesting that dust hopanes likely result from traffic emissions. The proportion of variance in dust hopanes concentrations explained by LUR NO2 was less than 10% in Vancouver, Winnipeg and Toronto while the correlations in Edmonton and Windsor explained 20 to 40% of the variance. Modeling with household factors such as air conditioning and shoe removal along with geographic predictors related to TRAP generally increased the proportion of explained variability (10-80%) in measured indoor hopanes dust levels. Conclusions: Hopanes can consistently be detected in house dust and may be a useful tracer of TRAP exposure if determinants of their spatiotemporal variability are well-characterized, and when home-specific factors are considered. [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

13. A new exposure metric for traffic-related air pollution? An analysis of determinants of hopanes in settled indoor house dust.

Author

Sbihi, Hind, Brook, Jeffrey R, Allen, Ryan W, Curran, Jason H, Dell, Sharon, Mandhane, Piush, Scott, James A, Sears, Malcolm R, Subbarao, Padmaja, Takaro, Timothy K, Turvey, Stuart E, Wheeler, Amanda J, and Brauer, Michael

Abstract

Background: Exposure to traffic-related air pollution (TRAP) can adversely impact health but epidemiologic studies are limited in their abilities to assess long-term exposures and incorporate variability in indoor pollutant infiltration.Methods: In order to examine settled house dust levels of hopanes, engine lubricating oil byproducts found in vehicle exhaust, as a novel TRAP exposure measure, dust samples were collected from 171 homes in five Canadian cities and analyzed by gas chromatography-mass spectrometry. To evaluate source contributions, the relative abundance of the highest concentration hopane monomer in house dust was compared to that in outdoor air. Geographic variables related to TRAP emissions and outdoor NO2 concentrations from city-specific TRAP land use regression (LUR) models were calculated at each georeferenced residence location and assessed as predictors of variability in dust hopanes.Results: Hopanes relative abundance in house dust and ambient air were significantly correlated (Pearson's r=0.48, p<0.05), suggesting that dust hopanes likely result from traffic emissions. The proportion of variance in dust hopanes concentrations explained by LUR NO2 was less than 10% in Vancouver, Winnipeg and Toronto while the correlations in Edmonton and Windsor explained 20 to 40% of the variance. Modeling with household factors such as air conditioning and shoe removal along with geographic predictors related to TRAP generally increased the proportion of explained variability (10-80%) in measured indoor hopanes dust levels.Conclusions: Hopanes can consistently be detected in house dust and may be a useful tracer of TRAP exposure if determinants of their spatiotemporal variability are well-characterized, and when home-specific factors are considered. [ABSTRACT FROM AUTHOR]

Published
2013
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results