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Your search keyword '"McCarthy, Noel A."' showing total 347 results
Start Over Author "McCarthy, Noel A." Publication Type Academic Journals
347 results on '"McCarthy, Noel A."'

8. Trends in invasive bacterial diseases during the first 2 years of the COVID-19 pandemic: analyses of prospective surveillance data from 30 countries and territories in the IRIS Consortium

Author

Shaw, David, Abad, Raquel, Amin-Chowdhury, Zahin, Bautista, Adriana, Bennett, Desiree, Broughton, Karen, Cao, Bin, Casanova, Carlo, Choi, Eun Hwa, Chu, Yiu-Wai, Claus, Heike, Coelho, Juliana, Corcoran, Mary, Cottrell, Simon, Cunney, Robert, Cuypers, Lize, Dalby, Tine, Davies, Heather, de Gouveia, Linda, Deghmane, Ala-Eddine, Demczuk, Walter, Desmet, Stefanie, Domenech, Mirian, Drew, Richard, du Plessis, Mignon, Duarte, Carolina, Erlendsdóttir, Helga, Fry, Norman K, Fuursted, Kurt, Hale, Thomas, Henares, Desiree, Henriques-Normark, Birgitta, Hilty, Markus, Hoffmann, Steen, Humphreys, Hilary, Ip, Margaret, Jacobsson, Susanne, Johnson, Christopher, Johnston, Jillian, Jolley, Keith A, Kawabata, Aníbal, Kozakova, Jana, Kristinsson, Karl G, Krizova, Pavla, Kuch, Alicja, Ladhani, Shamez, Lâm, Thiên-Trí, León, María Eugenia, Lindholm, Laura, Litt, David, Maiden, Martin C J, Martin, Irene, Martiny, Delphine, Mattheus, Wesley, McCarthy, Noel D, Meehan, Mary, Meiring, Susan, Mölling, Paula, Morfeldt, Eva, Morgan, Julie, Mulhall, Robert, Muñoz-Almagro, Carmen, Murdoch, David, Murphy, Joy, Musilek, Martin, Mzabi, Alexandre, Novakova, Ludmila, Oftadeh, Shahin, Perez-Argüello, Amaresh, Pérez-Vázquez, Maria, Perrin, Monique, Perry, Malorie, Prevost, Benoit, Roberts, Maria, Rokney, Assaf, Ron, Merav, Sanabria, Olga Marina, Scott, Kevin J, Sheppard, Carmen, Siira, Lotta, Sintchenko, Vitali, Skoczyńska, Anna, Sloan, Monica, Slotved, Hans-Christian, Smith, Andrew J, Steens, Anneke, Taha, Muhamed-Kheir, Toropainen, Maija, Tzanakaki, Georgina, Vainio, Anni, van der Linden, Mark P G, van Sorge, Nina M, Varon, Emmanuelle, Vohrnova, Sandra, von Gottberg, Anne, Yuste, Jose, Zanella, Rosemeire, Zhou, Fei, and Brueggemann, Angela B

Published
2023
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27. Changes in the incidence of invasive disease due to Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis during the COVID-19 pandemic in 26 countries and territories in the Invasive Respiratory Infection Surveillance Initiative: a prospective analysis of surveillance data

Author

Brueggemann, Angela B, Jansen van Rensburg, Melissa J, Shaw, David, McCarthy, Noel D, Jolley, Keith A, Maiden, Martin C J, van der Linden, Mark P G, Amin-Chowdhury, Zahin, Bennett, Désirée E, Borrow, Ray, Brandileone, Maria-Cristina C, Broughton, Karen, Campbell, Ruth, Cao, Bin, Casanova, Carlo, Choi, Eun Hwa, Chu, Yiu Wai, Clark, Stephen A, Claus, Heike, Coelho, Juliana, Corcoran, Mary, Cottrell, Simon, Cunney, Robert J, Dalby, Tine, Davies, Heather, de Gouveia, Linda, Deghmane, Ala-Eddine, Demczuk, Walter, Desmet, Stefanie, Drew, Richard J, du Plessis, Mignon, Erlendsdottir, Helga, Fry, Norman K, Fuursted, Kurt, Gray, Steve J, Henriques-Normark, Birgitta, Hale, Thomas, Hilty, Markus, Hoffmann, Steen, Humphreys, Hilary, Ip, Margaret, Jacobsson, Susanne, Johnston, Jillian, Kozakova, Jana, Kristinsson, Karl G, Krizova, Pavla, Kuch, Alicja, Ladhani, Shamez N, Lâm, Thiên-Trí, Lebedova, Vera, Lindholm, Laura, Litt, David J, Martin, Irene, Martiny, Delphine, Mattheus, Wesley, McElligott, Martha, Meehan, Mary, Meiring, Susan, Mölling, Paula, Morfeldt, Eva, Morgan, Julie, Mulhall, Robert M, Muñoz-Almagro, Carmen, Murdoch, David R, Murphy, Joy, Musilek, Martin, Mzabi, Alexandre, Perez-Argüello, Amaresh, Perrin, Monique, Perry, Malorie, Redin, Alba, Roberts, Richard, Roberts, Maria, Rokney, Assaf, Ron, Merav, Scott, Kevin J, Sheppard, Carmen L, Siira, Lotta, Skoczyńska, Anna, Sloan, Monica, Slotved, Hans-Christian, Smith, Andrew J, Song, Joon Young, Taha, Muhamed-Kheir, Toropainen, Maija, Tsang, Dominic, Vainio, Anni, van Sorge, Nina M, Varon, Emmanuelle, Vlach, Jiri, Vogel, Ulrich, Vohrnova, Sandra, von Gottberg, Anne, Zanella, Rosemeire C, and Zhou, Fei

Published
2021
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41. Highly Pathogenic Clone of Shiga Toxin--Producing Escherichia coli O157:H7, England and Wales

Author

Byrne, Lisa, Dallman, Timothy J., Adams, Natalie, Mikhail, Amy F.W., McCarthy, Noel, and Jenkins, Claire

Subjects
Escherichia coli -- Research, DNA sequencing -- Usage, Signs and symptoms -- Research, Health
Abstract

Shiga toxin-producing Escherichia coli (STEC) O157:H7 cause a wide range of gastrointestinal symptoms, including mild gastroenteritis, abdominal pain, vomiting, and bloody diarrhea (1). A subset of patients, most commonly the [...]

Published
2018
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43. Water Effective Diffusion Coefficient in Dairy Powder Calculated by Digital Image Processing and through Machine Learning Algorithms of CLSM Micrographs.

Author

Maidannyk, Valentyn A., Simonov, Yuriy, McCarthy, Noel A., and Ho, Quang Tri

Subjects
MACHINE learning, DIGITAL image processing, DIFFUSION coefficients, DIFFUSION measurements, IMAGE analysis, POWDERS
Abstract

Rehydration of dairy powders is a complex and essential process. A relatively new quantitative mechanism for monitoring powders' rehydration process uses the effective diffusion coefficient. This research focused on modifying a previously used labor-intensive method that will be able to automatically measure the real-time water diffusion coefficient in dairy powders based on confocal microscopy techniques. Furthermore, morphological characteristics and local hydration of individual particles were identified using an imaging analysis procedure written in Matlab©—R2023b and image analysis through machine learning algorithms written in Python™-3.11. The first model includes segmentation into binary images and labeling particles during water diffusion. The second model includes the expansion of data set selection, neural network training and particle markup. For both models, the effective diffusion follows Fick's second law for spherical geometry. The effective diffusion coefficient on each particle was computed from the dye intensity during the rehydration process. The results showed that effective diffusion coefficients for water increased linearly with increasing powder particle size and are in agreement with previously used methods. In summary, the models provide two independent machine measurements of effective diffusion coefficient based on the same set of micrographs and may be useful in a wide variety of high-protein powders. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Shedding and exclusion from childcare in children with Shiga toxin-producing Escherichia coli , 2018–2022.

Author

Vusirikala, Amoolya, Rowell, Sam, Dabke, Girija, Fox, Georgina, Bell, Jade, Manuel, Rohini, Jenkins, Claire, Love, Nicola, McCarthy, Noel, Sumilo, Dana, and Balasegaram, Sooria

Abstract

Excluding children with Shiga toxin-producing Escherichia coli (STEC) from childcare until microbiologically clear of the pathogen, disrupts families, education, and earnings. Since PCR introduction, non-O157 STEC serotype detections in England have increased. We examined shedding duration by serotype and transmission risk, to guide exclusion advice. We investigated STEC cases aged <6 years, residing in England and attending childcare, with diarrhoea onset or sample date from 31 March 2018 to 30 March 2022. Duration of shedding was the interval between date of onset or date first positive specimen and earliest available negative specimen date. Transmission risk was estimated from proportions with secondary cases in settings attended by infectious cases. There were 367 cases (STEC O157 n  = 243, 66.2%; STEC non-O157 n  = 124, 33.8%). Median shedding duration was 32 days (IQR 20–44) with no significant difference between O157 and non-O157; 2% (n  = 6) of cases shed for ≥100 days. Duration of shedding was reduced by 17% (95% CI 4–29) among cases reporting bloody diarrhoea. Sixteen settings underwent screening; four had secondary cases (close contacts' secondary transmission rate = 13%). Shedding duration estimates were consistent with previous studies (median 31 days, IQR 17–41). Findings do not warrant guidance changes regarding exclusion and supervised return of prolonged shedders, despite serotype changes. [ABSTRACT FROM AUTHOR]

Published
2024
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48. pH, the Fundamentals for Milk and Dairy Processing: A Review.

Author

Aydogdu, Tugce, O'Mahony, James A., and McCarthy, Noel A.

Subjects
DAIRY processing, MEASUREMENT of viscosity, ENERGY industries, DAIRY industry, MILK quality, MILKING, CASEINS
Abstract

The ability to measure and capture real-time unit operational data has significant benefits during dairy processing, whether it is the basics, such as measuring temperature, pressure, and flow rates, or more recent developments in the case of in-line viscosity and product-compositional measurements. This rapid data collection has helped increase profitability by reducing energy costs, minimizing product loss, and allowing automated control. Advances in technology have allowed for in-line measurements of the composition and some physical attributes such as particle size and viscosity; however, an attribute that spans both compositional and physical attributes is pH, directly influenced by composition but also environments, such as temperature and dry matter content. pH is measured for a plethora of reasons, such as a measure of milk quality (microbial spoilage), acidification of casein, cheese production, maintaining optimum conditions during protein hydrolysis, etc. However, very little is published on the fundamentals of pH and pH measurement in dairy processing; rather, it is usually a cause-and-effect phenomenon. This review visits one of the oldest analytical considerations in the dairy industry and re-examines how it is affected by product composition and processing conditions. [ABSTRACT FROM AUTHOR]

Published
2023
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