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210 results on '"Thomas, Andrew M."'

1. Atomic Resolution Observations of Nanoparticle Surface Dynamics and Instabilities Enabled by Artificial Intelligence

Author

Crozier, Peter A., Leibovich, Matan, Haluai, Piyush, Tan, Mai, Thomas, Andrew M., Vincent, Joshua, Mohan, Sreyas, Morales, Adria Marcos, Kulkarni, Shreyas A., Matteson, David S., Wang, Yifan, and Fernandez-Granda, Carlos

Subjects
Condensed Matter - Materials Science
Abstract

Nanoparticle surface structural dynamics is believed to play a significant role in regulating functionalities such as diffusion, reactivity, and catalysis but the atomic-level processes are not well understood. Atomic resolution characterization of nanoparticle surface dynamics is challenging since it requires both high spatial and temporal resolution. Though ultrafast transmission electron microscopy (TEM) can achieve picosecond temporal resolution, it is limited to nanometer spatial resolution. On the other hand, with the high readout rate of new electron detectors, conventional TEM has the potential to visualize atomic structure with millisecond time resolutions. However, the need to limit electron dose rates to reduce beam damage yields millisecond images that are dominated by noise, obscuring structural details. Here we show that a newly developed unsupervised denoising framework based on artificial intelligence enables observations of metal nanoparticle surfaces with time resolutions down to 10 ms at moderate electron dose. On this timescale, we find that many nanoparticle surfaces continuously transition between ordered and disordered configurations. The associated stress fields can penetrate below the surface leading to defect formation and destabilization making the entire nanoparticle fluxional. Combining this unsupervised denoiser with electron microscopy greatly improves spatio-temporal characterization capabilities, opening a new window for future exploration of atomic-level structural dynamics in materials.

Published
2024

2. Convergence of persistence diagrams for discrete time stationary processes

Author

Thomas, Andrew M.

Subjects
Mathematics - Probability, 60G10, 55N31, 60F05, 60F15
Abstract

In this article we establish two fundamental results for the sublevel set persistent homology for stationary processes indexed by the positive integers. The first is a strong law of large numbers for the persistence diagram (treated as a measure "above the diagonal" in the extended plane) evaluated on a large class of sets and functions$\unicode{x2014}$more than just continuous functions with compact support. We prove this result subject to only minor conditions that the sequence is ergodic and the tails of the marginals are not too heavy. The second result is a central limit theorem for the persistence diagram evaluated on the class of all step functions; this result holds as long as a $\rho$-mixing criterion is satisfied and the distributions of the partial maxima do not decay too slowly. Our results greatly expand those extant in the literature to allow for more fruitful use in statistical applications, beyond idealized settings. Examples of distributions and functions for which the limit theory holds are provided throughout., Comment: 30 pages, 1 figure. Versions 1 and 2 uploaded to arXiv should be disregarded as they contained an erroneous proof of the CLT, which has been corrected in Version 3

Published
2024

3. Bayesian changepoint detection via logistic regression and the topological analysis of image series

Author

Thomas, Andrew M., Jauch, Michael, and Matteson, David S.

Subjects
Statistics - Methodology
Abstract

We present a Bayesian method for multivariate changepoint detection that allows for simultaneous inference on the location of a changepoint and the coefficients of a logistic regression model for distinguishing pre-changepoint data from post-changepoint data. In contrast to many methods for multivariate changepoint detection, the proposed method is applicable to data of mixed type and avoids strict assumptions regarding the distribution of the data and the nature of the change. The regression coefficients provide an interpretable description of a potentially complex change. For posterior inference, the model admits a simple Gibbs sampling algorithm based on P\'olya-gamma data augmentation. We establish conditions under which the proposed method is guaranteed to recover the true underlying changepoint. As a testing ground for our method, we consider the problem of detecting topological changes in time series of images. We demonstrate that our proposed method $\mathtt{bclr}$, combined with a topological feature embedding, performs well on both simulated and real image data. The method also successfully recovers the location and nature of changes in more traditional changepoint tasks., Comment: 34 pages (main), 18 pages (supplementary), 12 figures, and 10 tables

Published
2024

4. Large-scale metagenomic analysis of oral microbiomes reveals markers for autism spectrum disorders

Author

Manghi, Paolo, Filosi, Michele, Zolfo, Moreno, Casten, Lucas G., Garcia-Valiente, Albert, Mattevi, Stefania, Heidrich, Vitor, Golzato, Davide, Perini, Samuel, Thomas, Andrew M., Montalbano, Simone, Cancellieri, Samuele, Waldron, Levi, Hall, Jacob B., Xu, Simon, Volfovsky, Natalia, Green Snyder, LeeAnne, Feliciano, Pamela, Asnicar, Francesco, Valles-Colomer, Mireia, Michaelson, Jacob J., Segata, Nicola, and Domenici, Enrico

Published
2024
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5. Dynamic Atomic Column Detection in Transmission Electron Microscopy Videos via Ridge Estimation

Author

Xu, Yuchen, Thomas, Andrew M., Crozier, Peter A., and Matteson, David S.

Subjects
Statistics - Applications, Computer Science - Computer Vision and Pattern Recognition
Abstract

Ridge detection is a classical tool to extract curvilinear features in image processing. As such, it has great promise in applications to material science problems; specifically, for trend filtering relatively stable atom-shaped objects in image sequences, such as Transmission Electron Microscopy (TEM) videos. Standard analysis of TEM videos is limited to frame-by-frame object recognition. We instead harness temporal correlation across frames through simultaneous analysis of long image sequences, specified as a spatio-temporal image tensor. We define new ridge detection algorithms to non-parametrically estimate explicit trajectories of atomic-level object locations as a continuous function of time. Our approach is specially tailored to handle temporal analysis of objects that seemingly stochastically disappear and subsequently reappear throughout a sequence. We demonstrate that the proposed method is highly effective and efficient in simulation scenarios, and delivers notable performance improvements in TEM experiments compared to other material science benchmarks., Comment: 27 pages, 11 figures

Published
2023

6. Feature detection and hypothesis testing for extremely noisy nanoparticle images using topological data analysis

Author

Thomas, Andrew M., Crozier, Peter A., Xu, Yuchen, and Matteson, David S.

Subjects
Statistics - Applications, Electrical Engineering and Systems Science - Image and Video Processing, 62R40, 62P35
Abstract

We propose a flexible algorithm for feature detection and hypothesis testing in images with ultra low signal-to-noise ratio using cubical persistent homology. Our main application is in the identification of atomic columns and other features in transmission electron microscopy (TEM). Cubical persistent homology is used to identify local minima and their size in subregions in the frames of nanoparticle videos, which are hypothesized to correspond to relevant atomic features. We compare the performance of our algorithm to other employed methods for the detection of columns and their intensity. Additionally, Monte Carlo goodness-of-fit testing using real valued summaries of persistence diagrams derived from smoothed images (generated from pixels residing in the vacuum region of an image) is developed and employed to identify whether or not the proposed atomic features generated by our algorithm are due to noise. Using these summaries derived from the generated persistence diagrams, one can produce univariate time series for the nanoparticle videos, thus providing a means for assessing fluxional behavior. A guarantee on the false discovery rate for multiple Monte Carlo testing of identical hypotheses is also established., Comment: 42 pages, 21 figures, 9 tables

Published
2022

7. The VC-dimension of a class of multiples of the primes, and a connection to AdaBoost

Author

Thomas, Andrew M.

Subjects
Mathematics - Number Theory, Mathematics - Combinatorics, Mathematics - Probability, 11B25, 68Q32, 60F15
Abstract

We discuss the VC-dimension of a class of multiples of integers and primes (equivalently indicator functions) and demonstrate connections to prime counting functions. Additionally, we prove limit theorems for the behavior of an empirical risk minimization rule as well as the weights assigned to the output hypothesis in AdaBoost for these "prime-identifying" indicator functions, when we sample $m_n$ i.i.d. points uniformly from the integers $\{2, \dots, n\}$., Comment: 9 pages, 0 figures

Published
2022

8. Central limit theorems and asymptotic independence for local $U$-statistics on diverging halfspaces

Author

Thomas, Andrew M.

Subjects
Mathematics - Probability, 60F05, 60G70, 60E05
Abstract

We consider the stochastic behavior of a class of local $U$-statistics of Poisson processes$-$which include subgraph and simplex counts as special cases, and amounts to quantifying clustering behavior$-$for point clouds lying in diverging halfspaces. We provide limit theorems for distributions with light and heavy tails. In particular, we prove finite-dimensional central limit theorems. In the light tail case we investigate tails that decay at least as slow as exponential and at least as fast as Gaussian. These results also furnish as a corollary that $U$-statistics for halfspaces diverging at different angles are asymptotically independent, and that there is no asymptotic independence for heavy-tailed densities. Using state-of-the-art bounds derived from recent breakthroughs combining Stein's method and Malliavin calculus, we quantify the rate of this convergence in terms of Kolmogorov distance. We also investigate the behavior of local $U$-statistics of a Poisson Process conditioned to lie in diverging halfspace and show how the rate of convergence in the Kolmogorov distance is faster the lighter the tail of the density is., Comment: 25 pages, 3 figures

Published
2022

9. Total serum N-glycans associate with response to immune checkpoint inhibition therapy and survival in patients with advanced melanoma

Author

Visconti, Alessia, Rossi, Niccolò, Deriš, Helena, Lee, Karla A, Hanić, Maja, Trbojević-Akmačić, Irena, Thomas, Andrew M., Bolte, Laura A., Björk, Johannes R., Hooiveld-Noeken, Jahlisa S., Board, Ruth, Harland, Mark, Newton-Bishop, Julia, Harries, Mark, Sacco, Joseph J., Lorigan, Paul, Shaw, Heather M., de Vries, Elisabeth G.E., Fehrmann, Rudolf S.N., Weersma, Rinse K., Spector, Tim D., Nathan, Paul, Hospers, Geke A. P., Sasieni, Peter, Bataille, Veronique, Lauc, Gordan, and Falchi, Mario

Published
2023
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11. Functional strong laws of large numbers for Euler characteristic processes of extreme sample clouds

Author

Thomas, Andrew M. and Owada, Takashi

Subjects
Mathematics - Probability, Primary 60F15, 60G70. Secondary 55U10, 60F17
Abstract

To recover the topology of a manifold in the presence of heavy tailed or exponentially decaying noise, one must understand the behavior of geometric complexes whose points lie in the tail of these noise distributions. This study advances this line of inquiry, and demonstrates functional strong laws of large numbers for the Euler characteristic process of random geometric complexes formed by random points outside of an expanding ball in $\mathbb{R}^d$. When the points are drawn from a heavy tailed distribution with a regularly varying tail, the Euler characteristic process grows at a regularly varying rate, and the scaled process converges uniformly and almost surely to a smooth function. When the points are drawn from a distribution with an exponentially decaying tail, the Euler characteristic process grows logarithmically, and the scaled process converges to another smooth function in the same sense. All of the limit theorems take place when the points inside the expanding ball are densely distributed, so that the simplex counts outside of the ball of all dimensions contribute to the Euler characteristic process., Comment: 21 pages, 3 figures

Published
2020

13. Functional limit theorems for the Euler characteristic process in the critical regime

Author

Thomas, Andrew M. and Owada, Takashi

Subjects
Mathematics - Probability, Primary 60F17. Secondary 55U10, 60C05, 60D05
Abstract

This study presents functional limit theorems for the Euler characteristic of Vietoris-Rips complexes. The points are drawn from a non-homogeneous Poisson process on $\mathbb{R}^d$, and the connectivity radius governing the formation of simplices is taken as a function of time parameter $t$, which allows us to treat the Euler characteristic as a stochastic process. The setting in which this takes place is that of the critical regime, in which the simplicial complexes are highly connected and have non-trivial topology. We establish two "functional-level" limit theorems, a strong law of large numbers and a central limit theorem for the appropriately normalized Euler characteristic process., Comment: 25 pages, 1 figure

Published
2019

14. A physics-based ensemble machine-learning approach to identifying a relationship between lightning indices and binary lightning hazard.

Author

Thomas, Andrew M., Noble, Stephen, Tiwari, Shani, and Pandey, Alok

Subjects
MACHINE learning, ATMOSPHERIC boundary layer, NUMERICAL weather forecasting, LIGHTNING, MICROPHYSICS
Abstract

To convert lightning indices generated by numerical weather prediction experiments into binary lightning hazard, a machine-learning tool was developed. This tool, consisting of parallel multilayer perceptron classifiers, was trained on an ensemble of planetary boundary layer schemes and microphysics parameterizations that generated four different lightning indices over 1 week. In a subsequent week, the multi-physics ensemble was applied and the machinelearning tool was used to evaluate the accuracy. Unintuitively, the machinelearning tool performed better on the testing dataset than the training dataset. Much of the error may be attributed to mischaracterizing the convection. The combination of the machine learning model and simulations could not differentiate between cloud-to-cloud lightning and cloud-to-ground lightning, despite being trained on cloud-to-ground lightning. It was found that the simulation most representative of the local operational model was the most accurate simulation tested. [ABSTRACT FROM AUTHOR]

Published
2024
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18. A probiotic has differential effects on allergic airway inflammation in A/J and C57BL/6 mice and is correlated with the gut microbiome

Author

Casaro, Mateus B., Thomas, Andrew M., Mendes, Eduardo, Fukumori, Claudio, Ribeiro, Willian R., Oliveira, Fernando A., Crisma, Amanda R., Murata, Gilson M., Bizzarro, Bruna, Sá-Nunes, Anderson, Setubal, Joao C., Mayer, Marcia P. A., Martins, Flaviano S., Vieira, Angélica T., Antiorio, Ana T. F. B., Tavares-de-Lima, Wothan, Camara, Niels O. S., Curi, Rui, Dias-Neto, Emmanuel, and Ferreira, Caroline M.

Published
2021
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19. Correction to: A probiotic has differential effects on allergic airway inflammation in A/J and C57BL/6 mice and is correlated with the gut microbiome

Author

Casaro, Mateus B., Thomas, Andrew M., Mendes, Eduardo, Fukumori, Claudio, Ribeiro, Willian R., Oliveira, Fernando A., Crisma, Amanda R., Murata, Gilson M., Bizzarro, Bruna, Sá-Nunes, Anderson, Setubal, Joao C., Mayer, Marcia P. A., Martins, Flaviano S., Vieira, Angélica T., Antiorio, Ana T. F. B., Tavares-de-Lima, Wothan, Camara, Niels O. S., Curi, Rui, Dias-Neto, Emmanuel, and Ferreira, Caroline M.

Published
2021
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20. Maternal supplementation with a synbiotic has distinct outcomes on offspring gut microbiota formation in A/J and C57BL/6 mice, differentially affecting airway inflammatory cell infiltration and mucus production

Author

Fukumori, Claudio, Casaro, Mateus B., Thomas, Andrew M., Mendes, Eduardo, Ribeiro, Willian R., Crisma, Amanda R., Murata, Gilson M., Bizzarro, Bruna, Dias-Neto, Emmanuel, Setubal, Joao C., Oliveira, Maria A., Tavares-de-Lima, Wothan, Curi, Rui, Bordin, Silvana, Sartorelli, Patricia, and Ferreira, Caroline M.

Published
2019
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22. LAT1 enables T cell activation under inflammatory conditions

Author

Ogbechi, Joy, primary, Wright, Helen L., additional, Balint, Stefan, additional, Topping, Louise M., additional, Kristina, Zec, additional, Huang, Yi-Shu, additional, Pantazi, Eirini, additional, Swart, Maarten, additional, Windell, Dylan, additional, Marin, Eros, additional, Wempe, Michael F., additional, Endou, Hitoshi, additional, Thomas, Andrew M., additional, Filer, Andrew, additional, Stone, Trevor W., additional, Clarke, Alexander J., additional, Dustin, Michael L., additional, and Williams, Richard O., additional

Published
2023
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23. Faecal microbiota transplantation for the treatment of diarrhoea induced by tyrosine-kinase inhibitors in patients with metastatic renal cell carcinoma

Author

Ianiro, Gianluca, Rossi, Ernesto, Thomas, Andrew M., Schinzari, Giovanni, Masucci, Luca, Quaranta, Gianluca, Settanni, Carlo Romano, Lopetuso, Loris Riccardo, Armanini, Federica, Blanco-Miguez, Aitor, Asnicar, Francesco, Consolandi, Clarissa, Iacovelli, Roberto, Sanguinetti, Maurizio, Tortora, Giampaolo, Gasbarrini, Antonio, Segata, Nicola, and Cammarota, Giovanni

Published
2020
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24. MetaPhlAn 4 profiling of unknown species-level genome bins improves the characterization of diet-associated microbiome changes in mice

Author

Manghi, Paolo, primary, Blanco-Míguez, Aitor, additional, Manara, Serena, additional, NabiNejad, Amir, additional, Cumbo, Fabio, additional, Beghini, Francesco, additional, Armanini, Federica, additional, Golzato, Davide, additional, Huang, Kun D., additional, Thomas, Andrew M., additional, Piccinno, Gianmarco, additional, Punčochář, Michal, additional, Zolfo, Moreno, additional, Lesker, Till R., additional, Bredon, Marius, additional, Planchais, Julien, additional, Glodt, Jeremy, additional, Valles-Colomer, Mireia, additional, Koren, Omry, additional, Pasolli, Edoardo, additional, Asnicar, Francesco, additional, Strowig, Till, additional, Sokol, Harry, additional, and Segata, Nicola, additional

Published
2023
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27. LAT1 enables T cell activation under inflammatory conditions: a new therapeutic target for rheumatoid arthritis

Author

Ogbechi, Joy, primary, Wright, Helen L., additional, Balint, Stefan, additional, Topping, Louise M., additional, Kristina, Zec, additional, Huang, Yi-Shu, additional, Pantazi, Eirini, additional, Swart, Maarten, additional, Windell, Dylan, additional, Marin, Eros, additional, Wempe, Michael F., additional, Endou, Hitoshi, additional, Thomas, Andrew M., additional, Filer, Andrew, additional, Stone, Trevor W., additional, Clarke, Alexander J., additional, Dustin, Michael L., additional, and Williams, Richard O., additional

Published
2022
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28. Additional file 1 of Total serum N-glycans associate with response to immune checkpoint inhibition therapy and survival in patients with advanced melanoma

Author

Visconti, Alessia, Rossi, Niccolò, Deriš, Helena, Lee, Karla A, Hanić, Maja, Trbojević-Akmačić, Irena, Thomas, Andrew M., Bolte, Laura A., Björk, Johannes R., Hooiveld-Noeken, Jahlisa S., Board, Ruth, Harland, Mark, Newton-Bishop, Julia, Harries, Mark, Sacco, Joseph J., Lorigan, Paul, Shaw, Heather M., de Vries, Elisabeth G.E., Fehrmann, Rudolf S.N., Weersma, Rinse K., Spector, Tim D., Nathan, Paul, Hospers, Geke A. P., Sasieni, Peter, Bataille, Veronique, Lauc, Gordan, and Falchi, Mario

Abstract

Additional file 1: Figure 1. Representative chromatogram of total human plasma/serum N-glycome separated byHILIC-UPLC into 39 N-glycan peaks (GP1-GP39). Figure 2. Swimmer plot for the 88 patients with advanced melanoma included in this study. Figure 3. Pearson's correlation among the measured N-glycan and derived traits associated with overall response rate in 88 patients with advanced melanoma. Figure 4. Significant association between directly measured serum N-glycans and overall response rate. Figure 5. Kaplan-Meier progression-free survival curves in 88 patients with advanced melanoma (directly measured N-glycans). Figure 6. Diagnostic plots for Cox proportional hazards regression model of survival time on sex, age at diagnosis of advanced melanoma, BMI, dichotomized LDH levels, and ECOG performance-status. Figure 7. Kaplan-Meier overall survival curves in 88 patients with advanced melanoma (directly measured N-glycans).

Published
2023
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30. Immune system and intestinal microbiota determine efficacy of androgen depletion therapy against prostate cancer.

Author

Terrisse, Safae, primary, Goubet, Anne-Gaëlle, additional, Ueda, Kosuke, additional, Thomas, Andrew M., additional, Quiniou, Valentin, additional, Thelemaque, Cassandra, additional, Dunsmore, Garett, additional, Clave, Emmanuel, additional, Gamat-Huber, Melissa, additional, Yonekura, Satoru, additional, Derosa, Lisa, additional, Culine, Stephane, additional, Opolon, Paule, additional, Ginhoux, Florent, additional, Toubert, Antoine, additional, Segata, Nicola, additional, McNeel, Douglas G., additional, Fizazi, Karim, additional, Kroemer, Guido, additional, and Zitvogel, Laurence, additional

Published
2022
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31. A global metagenomic map of urban microbiomes and antimicrobial resistance

Author

Danko, David, primary, Bezdan, Daniela, additional, Afshin, Evan E., additional, Ahsanuddin, Sofia, additional, Bhattacharya, Chandrima, additional, Butler, Daniel J., additional, Chng, Kern Rei, additional, Donnellan, Daisy, additional, Hecht, Jochen, additional, Jackson, Katelyn, additional, Kuchin, Katerina, additional, Karasikov, Mikhail, additional, Lyons, Abigail, additional, Mak, Lauren, additional, Meleshko, Dmitry, additional, Mustafa, Harun, additional, Mutai, Beth, additional, Neches, Russell Y., additional, Ng, Amanda, additional, Nikolayeva, Olga, additional, Nikolayeva, Tatyana, additional, Png, Eileen, additional, Ryon, Krista A., additional, Sanchez, Jorge L., additional, Shaaban, Heba, additional, Sierra, Maria A., additional, Thomas, Dominique, additional, Young, Ben, additional, Abudayyeh, Omar O., additional, Alicea, Josue, additional, Bhattacharyya, Malay, additional, Blekhman, Ran, additional, Castro-Nallar, Eduardo, additional, Cañas, Ana M., additional, Chatziefthimiou, Aspassia D., additional, Crawford, Robert W., additional, De Filippis, Francesca, additional, Deng, Youping, additional, Desnues, Christelle, additional, Dias-Neto, Emmanuel, additional, Dybwad, Marius, additional, Elhaik, Eran, additional, Ercolini, Danilo, additional, Frolova, Alina, additional, Gankin, Dennis, additional, Gootenberg, Jonathan S., additional, Graf, Alexandra B., additional, Green, David C., additional, Hajirasouliha, Iman, additional, Hastings, Jaden J.A., additional, Hernandez, Mark, additional, Iraola, Gregorio, additional, Jang, Soojin, additional, Kahles, Andre, additional, Kelly, Frank J., additional, Knights, Kaymisha, additional, Kyrpides, Nikos C., additional, Łabaj, Paweł P., additional, Lee, Patrick K.H., additional, Leung, Marcus H.Y., additional, Ljungdahl, Per O., additional, Mason-Buck, Gabriella, additional, McGrath, Ken, additional, Meydan, Cem, additional, Mongodin, Emmanuel F., additional, Moraes, Milton Ozorio, additional, Nagarajan, Niranjan, additional, Nieto-Caballero, Marina, additional, Noushmehr, Houtan, additional, Oliveira, Manuela, additional, Ossowski, Stephan, additional, Osuolale, Olayinka O., additional, Özcan, Orhan, additional, Paez-Espino, David, additional, Rascovan, Nicolás, additional, Richard, Hugues, additional, Rätsch, Gunnar, additional, Schriml, Lynn M., additional, Semmler, Torsten, additional, Sezerman, Osman U., additional, Shi, Leming, additional, Shi, Tieliu, additional, Siam, Rania, additional, Song, Le Huu, additional, Suzuki, Haruo, additional, Court, Denise Syndercombe, additional, Tighe, Scott W., additional, Tong, Xinzhao, additional, Udekwu, Klas I., additional, Ugalde, Juan A., additional, Valentine, Brandon, additional, Vassilev, Dimitar I., additional, Vayndorf, Elena M., additional, Velavan, Thirumalaisamy P., additional, Wu, Jun, additional, Zambrano, María M., additional, Zhu, Jifeng, additional, Zhu, Sibo, additional, Mason, Christopher E., additional, Abdullah, Natasha, additional, Abraao, Marcos, additional, Adel, Ait-hamlat, additional, Afaq, Muhammad, additional, Al-Quaddoomi, Faisal S., additional, Alam, Ireen, additional, Albuquerque, Gabriela E., additional, Alexiev, Alex, additional, Ali, Kalyn, additional, Alvarado-Arnez, Lucia E., additional, Aly, Sarh, additional, Amachee, Jennifer, additional, Amorim, Maria G., additional, Ampadu, Majelia, additional, Amran, Muhammad Al-Fath, additional, An, Nala, additional, Andrew, Watson, additional, Andrianjakarivony, Harilanto, additional, Angelov, Michael, additional, Antelo, Verónica, additional, Aquino, Catharine, additional, Aranguren, Álvaro, additional, Araujo, Luiza F., additional, Vasquez Arevalo, Hitler Francois, additional, Arevalo, Jenny, additional, Arnan, Carme, additional, Alvarado Arnez, Lucia Elena, additional, Arredondo, Fernanda, additional, Arthur, Matthew, additional, Asenjo, Freddy, additional, Aung, Thomas Saw, additional, Auvinet, Juliette, additional, Aventin, Nuria, additional, Ayaz, Sadaf, additional, Baburyan, Silva, additional, Bakere, Abd-Manaaf, additional, Bakhl, Katrin, additional, Bartelli, Thais F., additional, Batdelger, Erdenetsetseg, additional, Baudon, François, additional, Becher, Kevin, additional, Bello, Carla, additional, Benchouaia, Médine, additional, Benisty, Hannah, additional, Benoiston, Anne-Sophie, additional, Benson, Joseph, additional, Benítez, Diego, additional, Bernardes, Juliana, additional, Bertrand, Denis, additional, Beurmann, Silvia, additional, Bitard-Feildel, Tristan, additional, Bittner, Lucie, additional, Black, Christina, additional, Blanc, Guillaume, additional, Blyther, Brittany, additional, Bode, Toni, additional, Boeri, Julia, additional, Boldgiv, Bazartseren, additional, Bolzli, Kevin, additional, Bordigoni, Alexia, additional, Borrelli, Ciro, additional, Bouchard, Sonia, additional, Bouly, Jean-Pierre, additional, Boyd, Alicia, additional, Branco, Gabriela P., additional, Breschi, Alessandra, additional, Brindefalk, Björn, additional, Brion, Christian, additional, Briones, Alan, additional, Buczansla, Paulina, additional, Burke, Catherine M., additional, Burrell, Aszia, additional, Butova, Alina, additional, Buttar, Irvind, additional, Bynoe, Jalia, additional, Bönigk, Sven, additional, Bøifot, Kari O., additional, Caballero, Hiram, additional, Cai, Xiao Wen, additional, Calderon, Dayana, additional, Cantillo, Angela, additional, Carbajo, Miguel, additional, Carbone, Alessandra, additional, Cardenas, Anais, additional, Carrillo, Katerine, additional, Casalot, Laurie, additional, Castro, Sofia, additional, Castro, Ana V., additional, Castro, Astred, additional, Castro, Ana Valeria B., additional, Cawthorne, Simone, additional, Cedillo, Jonathan, additional, Chaker, Salama, additional, Chalangal, Jasna, additional, Chan, Allison, additional, Chasapi, Anastasia I., additional, Chatziefthimiou, Starr, additional, Chaudhuri, Sreya Ray, additional, Chavan, Akash Keluth, additional, Chavez, Francisco, additional, Chem, Gregory, additional, Chen, Xiaoqing, additional, Chen, Michelle, additional, Chen, Jenn-Wei, additional, Chernomoretz, Ariel, additional, Chettouh, Allaeddine, additional, Cheung, Daisy, additional, Chicas, Diana, additional, Chiu, Shirley, additional, Choudhry, Hira, additional, Chrispin, Carl, additional, Ciaramella, Kianna, additional, Cifuentes, Erika, additional, Cohen, Jake, additional, Coil, David A., additional, Collin, Sylvie, additional, Conger, Colleen, additional, Conte, Romain, additional, Corsi, Flavia, additional, Cossio, Cecilia N., additional, Costa, Ana F., additional, Cuebas, Delisia, additional, D’Alessandro, Bruno, additional, Dahlhausen, Katherine E., additional, Darling, Aaron E., additional, Das, Pujita, additional, Davenport, Lucinda B., additional, David, Laurent, additional, Davidson, Natalie R., additional, Dayama, Gargi, additional, Delmas, Stéphane, additional, Deng, Chris K., additional, Dequeker, Chloé, additional, Desert, Alexandre, additional, Devi, Monika, additional, Dezem, Felipe S., additional, Dias, Clara N., additional, Donahoe, Timothy Ryan, additional, Dorado, Sonia, additional, Dorsey, LaShonda, additional, Dotsenko, Valeriia, additional, Du, Steven, additional, Dutan, Alexandra, additional, Eady, Naya, additional, Eisen, Jonathan A., additional, Elaskandrany, Miar, additional, Epping, Lennard, additional, Escalera-Antezana, Juan P., additional, Ettinger, Cassie L., additional, Faiz, Iqra, additional, Fan, Luice, additional, Farhat, Nadine, additional, Faure, Emile, additional, Fauzi, Fazlina, additional, Feigin, Charlie, additional, Felice, Skye, additional, Ferreira, Laís Pereira, additional, Figueroa, Gabriel, additional, Fleiss, Aubin, additional, Flores, Denisse, additional, Velasco Flores, Jhovana L., additional, Fonseca, Marcos A.S., additional, Foox, Jonathan, additional, Forero, Juan Carlos, additional, Francis, Aaishah, additional, French, Kelly, additional, Fresia, Pablo, additional, Friedman, Jacob, additional, Fuentes, Jaime J., additional, Galipon, Josephine, additional, Garcia, Mathilde, additional, Garcia, Laura, additional, García, Catalina, additional, Geiger, Annie, additional, Gerner, Samuel M., additional, Ghose, Sonia L., additional, Giang, Dao Phuong, additional, Giménez, Matías, additional, Giovannelli, Donato, additional, Githae, Dedan, additional, Gkotzis, Spyridon, additional, Godoy, Liliana, additional, Goldman, Samantha, additional, Gonnet, Gaston H., additional, Gonzalez, Juana, additional, Gonzalez, Andrea, additional, Gonzalez-Poblete, Camila, additional, Gray, Andrew, additional, Gregory, Tranette, additional, Greselle, Charlotte, additional, Guasco, Sophie, additional, Guerra, Juan, additional, Gurianova, Nika, additional, Haehr, Wolfgang, additional, Halary, Sebastien, additional, Hartkopf, Felix, additional, Hawkins-Zafarnia, Arya, additional, Hazrin-Chong, Nur Hazlin, additional, Helfrich, Eric, additional, Hell, Eva, additional, Henry, Tamera, additional, Hernandez, Samuel, additional, Hernandez, Pilar Lopez, additional, Hess-Homeier, David, additional, Hittle, Lauren E., additional, Hoan, Nghiem Xuan, additional, Holik, Aliaksei, additional, Homma, Chiaki, additional, Hoxie, Irene, additional, Huber, Michael, additional, Humphries, Elizabeth, additional, Hyland, Stephanie, additional, Hässig, Andrea, additional, Häusler, Roland, additional, Hüsser, Nathalie, additional, Petit, Robert A., additional, Iderzorig, Badamnyambuu, additional, Igarashi, Mizuki, additional, Iqbal, Shaikh B., additional, Ishikawa, Shino, additional, Ishizuka, Sakura, additional, Islam, Sharah, additional, Islam, Riham, additional, Ito, Kohei, additional, Ito, Sota, additional, Ito, Takayuki, additional, Ivankovic, Tomislav, additional, Iwashiro, Tomoki, additional, Jackson, Sarah, additional, Jacobs, JoAnn, additional, James, Marisano, additional, Jaubert, Marianne, additional, Jerier, Marie-Laure, additional, Jiminez, Esmeralda, additional, Jinfessa, Ayantu, additional, De Jong, Ymke, additional, Joo, Hyun Woo, additional, Jospin, Guilllaume, additional, Kajita, Takema, additional, Ahmad Kassim, Affifah Saadah, additional, Kato, Nao, additional, Kaur, Amrit, additional, Kaur, Inderjit, additional, de Souza Gomes Kehdy, Fernanda, additional, Khadka, Vedbar S., additional, Khan, Shaira, additional, Khavari, Mahshid, additional, Ki, Michelle, additional, Kim, Gina, additional, Kim, Hyung Jun, additional, Kim, Sangwan, additional, King, Ryan J., additional, KoLoMonaco, Giuseppe, additional, Koag, Ellen, additional, Kobko-Litskevitch, Nadezhda, additional, Korshevniuk, Maryna, additional, Kozhar, Michael, additional, Krebs, Jonas, additional, Kubota, Nanami, additional, Kuklin, Andrii, additional, Kumar, Sheelta S., additional, Kwong, Rachel, additional, Kwong, Lawrence, additional, Lafontaine, Ingrid, additional, Lago, Juliana, additional, Lai, Tsoi Ying, additional, Laine, Elodie, additional, Laiola, Manolo, additional, Lakhneko, Olha, additional, Lamba, Isha, additional, de Lamotte, Gerardo, additional, Lannes, Romain, additional, De Lazzari, Eleonora, additional, Leahy, Madeline, additional, Lee, Hyunjung, additional, Lee, Yunmi, additional, Lee, Lucy, additional, Lemaire, Vincent, additional, Leong, Emily, additional, Lewandowska, Dagmara, additional, Li, Chenhao, additional, Liang, Weijun, additional, Lin, Moses, additional, Lisboa, Priscilla, additional, Litskevitch, Anna, additional, Liu, Eric Minwei, additional, Liu, Tracy, additional, Livia, Mayra Arauco, additional, Lo, Yui Him, additional, Losim, Sonia, additional, Loubens, Manon, additional, Lu, Jennifer, additional, Lykhenko, Olexandr, additional, Lysakova, Simona, additional, Mahmoud, Salah, additional, Majid, Sara Abdul, additional, Makogon, Natalka, additional, Maldonado, Denisse, additional, Mallari, Krizzy, additional, Malta, Tathiane M., additional, Mamun, Maliha, additional, Manoir, Dimitri, additional, Marchandon, German, additional, Marciniak, Natalia, additional, Marinovic, Sonia, additional, Marques, Brunna, additional, Mathews, Nicole, additional, Matsuzaki, Yuri, additional, Matthys, Vincent, additional, May, Madelyn, additional, McComb, Elias, additional, Meagher, Annabelle, additional, Melamed, Adiell, additional, Menary, Wayne, additional, Mendez, Katterinne N., additional, Mendez, Ambar, additional, Mendy, Irène Mauricette, additional, Meng, Irene, additional, Menon, Ajay, additional, Menor, Mark, additional, Meoded, Roy, additional, Merino, Nancy, additional, Miah, Karishma, additional, Mignotte, Mathilde, additional, Miketic, Tanja, additional, Miranda, Wilson, additional, Mitsios, Athena, additional, Miura, Ryusei, additional, Miyake, Kunihiko, additional, Moccia, Maria D., additional, Mohan, Natasha, additional, Mohsin, Mohammed, additional, Moitra, Karobi, additional, Moldes, Mauricio, additional, Molina, Laura, additional, Molinet, Jennifer, additional, Molomjamts, Orgil-Erdene, additional, Moniruzzaman, Eftar, additional, Moon, Sookwon, additional, de Oliveira Moraes, Isabelle, additional, Moreno, Mario, additional, Mosella, Maritza S., additional, Moser, Josef W., additional, Mozsary, Christopher, additional, Muehlbauer, Amanda L., additional, Muner, Oasima, additional, Munia, Muntaha, additional, Munim, Naimah, additional, Muscat, Maureen, additional, Mustac, Tatjana, additional, Muñoz, Cristina, additional, Nadalin, Francesca, additional, Naeem, Areeg, additional, Nagy-Szakal, Dorottya, additional, Nakagawa, Mayuko, additional, Narce, Ashanti, additional, Nasu, Masaki, additional, Navarrete, Irene González, additional, Naveed, Hiba, additional, Nazario, Bryan, additional, Nedunuri, Narasimha Rao, additional, Neff, Thomas, additional, Nesimi, Aida, additional, Ng, Wan Chiew, additional, Ng, Synti, additional, Nguyen, Gloria, additional, Ngwa, Elsy, additional, Nicolas, Agier, additional, Nicolas, Pierre, additional, Nika, Abdollahi, additional, Noorzi, Hosna, additional, Nosrati, Avigdor, additional, Nunes, Diana N., additional, O’Brien, Kathryn, additional, O’Hara, Niamh B., additional, Oken, Gabriella, additional, Olawoyin, Rantimi A., additional, Oliete, Javier Quilez, additional, Olmeda, Kiara, additional, Oluwadare, Tolulope, additional, Oluwadare, Itunu A., additional, Ordioni, Nils, additional, Orpilla, Jenessa, additional, Orrego, Jacqueline, additional, Ortega, Melissa, additional, Osma, Princess, additional, Osuolale, Israel O., additional, Osuolale, Oluwatosin M., additional, Ota, Mitsuki, additional, Oteri, Francesco, additional, Oto, Yuya, additional, Ounit, Rachid, additional, Ouzounis, Christos A., additional, Pakrashi, Subhamitra, additional, Paras, Rachel, additional, Pardo-Este, Coral, additional, Park, Young-Ja, additional, Pastuszek, Paulina, additional, Patel, Suraj, additional, Pathmanathan, Jananan, additional, Patrignani, Andrea, additional, Perez, Manuel, additional, Peros, Ante, additional, Persaud, Sabrina, additional, Peters, Anisia, additional, Phillips, Adam, additional, Pineda, Lisbeth, additional, Pizzi, Melissa P., additional, Plaku, Alma, additional, Plaku, Alketa, additional, Pompa-Hogan, Brianna, additional, Portilla, María Gabriela, additional, Posada, Leonardo, additional, Priestman, Max, additional, Prithiviraj, Bharath, additional, Priya, Sambhawa, additional, Pugdeethosal, Phanthira, additional, Pugh, Catherine E., additional, Pulatov, Benjamin, additional, Pupiec, Angelika, additional, Pyrshev, Kyrylo, additional, Qing, Tao, additional, Rahiel, Saher, additional, Rahmatulloev, Savlatjon, additional, Rajendran, Kannan, additional, Ramcharan, Aneisa, additional, Ramirez-Rojas, Adan, additional, Rana, Shahryar, additional, Ratnanandan, Prashanthi, additional, Read, Timothy D., additional, Rehrauer, Hubert, additional, Richer, Renee, additional, Rivera, Alexis, additional, Rivera, Michelle, additional, Robertiello, Alessandro, additional, Robinson, Courtney, additional, Rodríguez, Paula, additional, Rojas, Nayra Aguilar, additional, Roldán, Paul, additional, Rosario, Anyelic, additional, Roth, Sandra, additional, Ruiz, Maria, additional, Boja Ruiz, Stephen Eduard, additional, Russell, Kaitlan, additional, Rybak, Mariia, additional, Sabedot, Thais S., additional, Sabina, Mahfuza, additional, Saito, Ikuto, additional, Saito, Yoshitaka, additional, Malca Salas, Gustavo Adolfo, additional, Salazar, Cecilia, additional, San, Kaung Myat, additional, Sanchez, Jorge, additional, Sanchir, Khaliun, additional, Sankar, Ryan, additional, de Souza Santos, Paulo Thiago, additional, Saravi, Zulena, additional, Sasaki, Kai, additional, Sato, Yuma, additional, Sato, Masaki, additional, Sato, Seisuke, additional, Sato, Ryo, additional, Sato, Kaisei, additional, Sayara, Nowshin, additional, Schaaf, Steffen, additional, Schacher, Oli, additional, Schinke, Anna-Lena M., additional, Schlapbach, Ralph, additional, Schori, Christian, additional, Schriml, Jason R., additional, Segato, Felipe, additional, Sepulveda, Felipe, additional, Serpa, Marianna S., additional, De Sessions, Paola F., additional, Severyn, Juan C., additional, Shakil, Maheen, additional, Shalaby, Sarah, additional, Shari, Aliyah, additional, Shim, Hyenah, additional, Shirahata, Hikaru, additional, Shiwa, Yuh, additional, Da Silva, Ophélie, additional, Silva, Jordana M., additional, Simon, Gwenola, additional, Singh, Shaleni K., additional, Sluzek, Kasia, additional, Smith, Rebecca, additional, So, Eunice, additional, Andreu Somavilla, Núria, additional, Sonohara, Yuya, additional, Rufino de Sousa, Nuno, additional, Souza, Camila, additional, Sperry, Jason, additional, Sprinsky, Nicolas, additional, Stark, Stefan G., additional, La Storia, Antonietta, additional, Suganuma, Kiyoshi, additional, Suliman, Hamood, additional, Sullivan, Jill, additional, Supie, Arif Asyraf Md, additional, Suzuki, Chisato, additional, Takagi, Sora, additional, Takahara, Fumie, additional, Takahashi, Naoya, additional, Takahashi, Kou, additional, Takeda, Tomoki, additional, Takenaka, Isabella K., additional, Tanaka, Soma, additional, Tang, Anyi, additional, Man Tang, Yuk, additional, Tarcitano, Emilio, additional, Tassinari, Andrea, additional, Taye, Mahdi, additional, Terrero, Alexis, additional, Thambiraja, Eunice, additional, Thiébaut, Antonin, additional, Thomas, Sade, additional, Thomas, Andrew M., additional, Togashi, Yuto, additional, Togashi, Takumi, additional, Tomaselli, Anna, additional, Tomita, Masaru, additional, Tomita, Itsuki, additional, Toth, Oliver, additional, Toussaint, Nora C., additional, Tran, Jennifer M., additional, Truong, Catalina, additional, Tsonev, Stefan I., additional, Tsuda, Kazutoshi, additional, Tsurumaki, Takafumi, additional, Tuz, Michelle, additional, Tymoshenko, Yelyzaveta, additional, Urgiles, Carmen, additional, Usui, Mariko, additional, Vacant, Sophie, additional, Vann, Laura E., additional, Velter, Fabienne, additional, Ventorino, Valeria, additional, Vera-Wolf, Patricia, additional, Vicedomini, Riccardo, additional, Suarez-Villamil, Michael A., additional, Vincent, Sierra, additional, Vivancos-Koopman, Renee, additional, Wan, Andrew, additional, Wang, Cindy, additional, Warashina, Tomoro, additional, Watanabe, Ayuki, additional, Weekes, Samuel, additional, Werner, Johannes, additional, Westfall, David, additional, Wieler, Lothar H., additional, Williams, Michelle, additional, Wolf, Silver A., additional, Wong, Brian, additional, Wong, Yan Ling, additional, Wong, Tyler, additional, Wright, Rasheena, additional, Wunderlin, Tina, additional, Yamanaka, Ryota, additional, Yang, Jingcheng, additional, Yano, Hirokazu, additional, Yeh, George C., additional, Yemets, Olena, additional, Yeskova, Tetiana, additional, Yoshikawa, Shusei, additional, Zafar, Laraib, additional, Zhang, Yang, additional, Zhang, Shu, additional, Zhang, Amy, additional, Zheng, Yuanting, additional, and Zubenko, Stas, additional

Published
2021
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32. Additional file 1 of A probiotic has differential effects on allergic airway inflammation in A/J and C57BL/6 mice and is correlated with the gut microbiome

Author

Casaro, Mateus B., Thomas, Andrew M., Mendes, Eduardo, Fukumori, Claudio, Ribeiro, Willian R., Oliveira, Fernando A., Crisma, Amanda R., Murata, Gilson M., Bizzarro, Bruna, Sá-Nunes, Anderson, Setubal, Joao C., Mayer, Marcia P. A., Martins, Flaviano S., Vieira, Angélica T., Antiorio, Ana T. F. B., Tavares-de-Lima, Wothan, Camara, Niels O. S., Curi, Rui, Dias-Neto, Emmanuel, and Ferreira, Caroline M.

Subjects
respiratory system
Abstract

Additional file 1:. Figure S1. High-fiber diet do not prevent airway inflammation in B6 mice. (A) Schematic representation of the OVA-inducing airway inflammation protocol and High-fiber diet in C57BL/6 mice. (B) Measurement of airway responsiveness (AHR) as assessed by Newtonian airway resistance (Rn) to increasing doses of methacholine in Control diet (CD) and High-fiber diet (HFD) of naive and OVA groups (n=4-5). (C) Total and differential (Eos: eosinophils; Neut: neutrophils; Mono: mononuclear) number of cells in the bronchoalveolar lavage (BALF) of OVA/Control Diet and OVA/High-fiber Diet groups (n=3-5 mice per group); (D) Concentrations (pg/ml) of interleukin (IL)-4 and interferon (INF)-γ in the BALF of OVA/Control Diet and OVA/High-fiber Diet groups (n=4-5); (E) Total amount of OVA-specific IgE in the serum of OVA/Control Diet and OVA/High-fiber Diet groups (n=5); (F) Representative PAS-stained bronchial structure of OVA/Control Diet and OVA/High-fiber Diet groups, scale bar represents 50 μm (200x magnification, one representative of at least five). Results are shown as mean ± SEM. Statistical significance was determined using Student’s t-test and ANOVA (with Tukey post-test) where appropriated. Panels provide compiled data of two independent experiments. Figure S2. Heatmap showing log transformed relative abundances of differentially abundant bacterial genera found between naive and probiotic administered mice. Figure S3. Principal component analysis (PCoA) on UnWeighted UniFrac distances.

Published
2021
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33. Stochastic Process Limits for Topological Functionals of Geometric Complexes

Author

Thomas, Andrew M

Subjects
10112 Topology, Statistics, FOS: Mathematics, Probability
Abstract

This dissertation establishes limit theory for topological functionals of geometric complexes from a stochastic process viewpoint. Standard filtrations of geometric complexes, such as the Čech and Vietoris-Rips complexes, have a natural parameter r which governs the formation of simplices: this is the basis for persistent homology. However, the parameter r may also be considered the time parameter of an appropriate stochastic process which summarizes the evolution of the filtration.Here we examine the stochastic behavior of two of the foremost classes of topological functionals of such filtrations: the Betti numbers and the Euler characteristic. There are also two distinct setups in which the points underlying the complexes are generated, where the points are distributed randomly in Rd according to a general density (the traditional setup) and where the points lie in the tail of a heavy-tailed or exponentially-decaying “noise” distribution (the extreme-value theory (EVT) setup).These results constitute some of the first results combining topological data analysis (TDA) and stochastic process theory. The first collection of results establishes stochastic process limits for Betti numbers of Čech complexes of Poisson and binomial point processes for two specific regimes in the traditional setup: the sparse regime—when the parameter r governing the formation of simplices causes the Betti numbers to concentrate on components of the lowest order; and the critical regime—when the parameter r is of the order n-1/d and the geometric complex becomes highly connected with topological holes of every dimension. The second collection of results establishes a functional strong law of large numbers and a functional central limit theorem for the Euler characteristic of a random geometric complex for the critical regime in the traditional setup. The final collection of results establishes functional strong laws of large numbers for geometric complexes in the EVT setup for the two classes of “noise” densities mentioned above.

Published
2021
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34. Intestinal Akkermansia muciniphila predicts overall survival in advanced non-small cell lung cancer patients treated with anti-PD-1 antibodies: Results a phase II study.

Author

Derosa, Lisa, primary, Routy, Bertrand, additional, Zitvogel, Laurence, additional, Thomas, Andrew M., additional, Zalcman, Gerard, additional, Friard, Sylvie, additional, Mazieres, Julien, additional, Audigier-Valette, Clarisse, additional, Moro-Sibilot, Denis, additional, Goldwasser, Francois, additional, Richard, Corentin, additional, Ghiringhelli, François, additional, Barlesi, Fabrice, additional, Elkrief, Arielle, additional, Alves Costa Silva, Carolina, additional, Planchard, David, additional, Segata, Nicola, additional, Martinez, Stéphanie, additional, Soria, Jean-Charles, additional, and Besse, Benjamin, additional

Published
2021
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37. Gut Microbiota Profile of Obese Diabetic Women Submitted to Roux-en-Y Gastric Bypass and Its Association with Food Intake and Postoperative Diabetes Remission

Author

Al Assal, Karina, Prifti, Edi, Belda, Eugeni, Sala, Priscila, Clement, Karine, Dao, Maria-Carlota, Dore, Joel, Levenez, Florence, Taddei, Carla R., Fonseca, Danielle Cristina, Rocha, Ilanna Marques, Balmant, Bianca Depieri, Thomas, Andrew M., Santo, Marco A., Dias-Neto, Emmanuel, Setubal, Joao Carlos, Zucker, Jean-Daniel, Belarmino, Giliane, Torrinhas, Raquel Susana, Waitzberg, Dan L., Al Assal, Karina, Prifti, Edi, Belda, Eugeni, Sala, Priscila, Clement, Karine, Dao, Maria-Carlota, Dore, Joel, Levenez, Florence, Taddei, Carla R., Fonseca, Danielle Cristina, Rocha, Ilanna Marques, Balmant, Bianca Depieri, Thomas, Andrew M., Santo, Marco A., Dias-Neto, Emmanuel, Setubal, Joao Carlos, Zucker, Jean-Daniel, Belarmino, Giliane, Torrinhas, Raquel Susana, and Waitzberg, Dan L.

Abstract

Gut microbiota composition is influenced by environmental factors and has been shown to impact body metabolism. Objective: To assess the gut microbiota profile before and after Roux-en-Y gastric bypass (RYGB) and the correlation with food intake and postoperative type 2 diabetes remission (T2Dr). Design: Gut microbiota profile from obese diabetic women was evaluated before (n = 25) and 3 (n = 20) and 12 months (n = 14) after RYGB, using MiSeq Illumina-based V4 bacterial 16S rRNA gene profiling. Data on food intake (7-day record) and T2Dr (American Diabetes Association (ADA) criteria) were recorded. Results: Preoperatively, the abundance of five bacteria genera differed between patients with (57%) and without T2Dr (p < 0.050). Preoperative gut bacteria genus signature was able to predict the T2Dr status with 0.94 accuracy ROC curve (receiver operating characteristic curve). Postoperatively (vs. preoperative), the relative abundance of some gut bacteria genera changed, the gut microbial richness increased, and the Firmicutes to Bacteroidetes ratio (rFB) decreased (p < 0.05) regardless of T2Dr. Richness levels was correlated with dietary profile pre and postoperatively, mainly displaying positive and inverse correlations with fiber and lipid intakes, respectively (p < 0.05). Conclusions: Gut microbiota profile was influenced by RYGB and correlated with diet and T2Dr preoperatively, suggesting the possibility to assess its composition to predict postoperative T2Dr.

Published
2020
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44. Butyrate Protects Mice from Clostridium difficile-Induced Colitis through an HIF-1-Dependent Mechanism

Author

Fachi, Jose Luis, Felipe, Jaqueline de Souza, Pral, Lais Passariello, da Silva, Bruna Karadi, Correa, Renan Oliveira, Pereira de Andrade, Mirella Cristiny, da Fonseca, Denise Morais, Basso, Paulo Jose, Saraiva Camara, Niels Olsen, de Sales e Souza, Ericka Lorenna, Martins, Flaviano dos Santos, Sato Guima, Suzana Eiko, Thomas, Andrew M., Setubal, Joao Carlos, Magalhaes, Yuli Thamires, Forti, Fabio Luis, Candreva, Thamiris, Rodrigues, Hosana Gomes, de Jesus, Marcelo Bispo, Consonni, Silvio Roberto, Farias, Alessandro dos Santos, Varga-Weisz, Patrick, Ramirez Vinolo, Marco Aurelio, Fachi, Jose Luis, Felipe, Jaqueline de Souza, Pral, Lais Passariello, da Silva, Bruna Karadi, Correa, Renan Oliveira, Pereira de Andrade, Mirella Cristiny, da Fonseca, Denise Morais, Basso, Paulo Jose, Saraiva Camara, Niels Olsen, de Sales e Souza, Ericka Lorenna, Martins, Flaviano dos Santos, Sato Guima, Suzana Eiko, Thomas, Andrew M., Setubal, Joao Carlos, Magalhaes, Yuli Thamires, Forti, Fabio Luis, Candreva, Thamiris, Rodrigues, Hosana Gomes, de Jesus, Marcelo Bispo, Consonni, Silvio Roberto, Farias, Alessandro dos Santos, Varga-Weisz, Patrick, and Ramirez Vinolo, Marco Aurelio

Abstract

Antibiotic-induced dysbiosis is a key factor predisposing intestinal infection by Clostridium difficile. Here, we show that interventions that restore butyrate intestinal levels mitigate clinical and pathological features of C. difficile-induced colitis. Butyrate has no effect on C. difficile colonization or toxin production. However, it attenuates intestinal inflammation and improves intestinal barrier function in infected mice, as shown by reduced intestinal epithelial permeability and bacterial translocation, effects associated with the increased expression of components of intestinal epithelial cell tight junctions. Activation of the transcription factor HIF-1 in intestinal epithelial cells exerts a protective effect in C. difficile-induced colitis, and it is required for butyrate effects. We conclude that butyrate protects intestinal epithelial cells from damage caused by C. difficile toxins via the stabilization of HIF-1, mitigating local inflammatory response and systemic consequences of the infection.

Published
2019
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45. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer

Author

Wirbel, Jakob, Pyl, Paul Theodor, Kartal, Ece, Zych, Konrad, Kashani, Alireza, Milanese, Alessio, Fleck, Jonas S, Voigt, Anita Y, Palleja, Albert, Ponnudurai, Ruby, Sunagawa, Shinichi, Coelho, Luis Pedro, Schrotz-King, Petra, Vogtmann, Emily, Habermann, Nina, Niméus, Emma, Thomas, Andrew M, Manghi, Paolo, Gandini, Sara, Serrano, Davide, Mizutani, Sayaka, Shiroma, Hirotsugu, Shiba, Satoshi, Shibata, Tatsuhiro, Yachida, Shinichi, Yamada, Takuji, Waldron, Levi, Naccarati, Alessio, Segata, Nicola, Sinha, Rashmi, Ulrich, Cornelia M, Brenner, Hermann, Arumugam, Manimozhiyan, Bork, Peer, Zeller, Georg, Wirbel, Jakob, Pyl, Paul Theodor, Kartal, Ece, Zych, Konrad, Kashani, Alireza, Milanese, Alessio, Fleck, Jonas S, Voigt, Anita Y, Palleja, Albert, Ponnudurai, Ruby, Sunagawa, Shinichi, Coelho, Luis Pedro, Schrotz-King, Petra, Vogtmann, Emily, Habermann, Nina, Niméus, Emma, Thomas, Andrew M, Manghi, Paolo, Gandini, Sara, Serrano, Davide, Mizutani, Sayaka, Shiroma, Hirotsugu, Shiba, Satoshi, Shibata, Tatsuhiro, Yachida, Shinichi, Yamada, Takuji, Waldron, Levi, Naccarati, Alessio, Segata, Nicola, Sinha, Rashmi, Ulrich, Cornelia M, Brenner, Hermann, Arumugam, Manimozhiyan, Bork, Peer, and Zeller, Georg

Abstract

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

Published
2019

47. Priming in response to pro-inflammatory cytokines is a feature of adult synovial but not dermal fibroblasts

Author

Crowley, Thomas, O'Neil, John D., Adams, Holly, Thomas, Andrew M., Filer, Andrew, Buckley, Christopher D., and Clark, Andrew R.

Subjects
Inflammation, musculoskeletal diseases, Interleukin-6, Blotting, Western, Synovial Membrane, NF-kappa B, Fluorescent Antibody Technique, Enzyme-Linked Immunosorbent Assay, Stromal memory, Fibroblasts, Synoviocytes, NF-κB, Arthritis, Rheumatoid, Fibroblast, Cytokines, Humans, Rheumatoid arthritis, Cytokine, Cells, Cultured, Research Article, Skin
Abstract

Background It has been hypothesized that chronic inflammatory diseases such as rheumatoid arthritis (RA) may be caused by a failure of negative feedback mechanisms. This study sought to examine negative feedback mechanisms in fibroblast-like synoviocytes (FLS), one of the most abundant cell types in the joint. We hypothesized that prior exposure of healthy FLS to an inflammatory stimulus would attenuate their responses to a second inflammatory stimulus, in the same way that negative feedback mechanisms desensitize macrophages to repeated stimulation by lipopolysaccharide. We further hypothesized that such negative feedback mechanisms would be defective in FLS derived from the joints in RA. Methods Synovial fibroblasts and dermal fibroblasts from non-inflamed joints and joints affected by RA and a fibroblast cell line from neonatal foreskin were stimulated twice with tumour necrosis factor (TNF) α or interleukin (IL)-1α, with a 24-h rest period between the two 24-h stimulations. Differences between response to the first and second dose of cytokine were examined by assessing secretion of inflammatory factors and intracellular signalling activity. Results FLS from both non-inflamed joints and joints affected by RA mounted an augmented response to re-stimulation. This response was site-specific, as primary dermal fibroblasts did not alter their response between doses. The fibroblast priming was also gene-specific and transient. Assessment of signalling events and nuclear localization showed prolonged activation of nuclear factor (NF)-κB during the second stimulation. Conclusion This study aimed to examine mechanisms of negative regulation of inflammatory responses in FLS. Instead, we found a pro-inflammatory stromal memory in FLS obtained from both non-inflamed joints and joints affected by RA. This suggests the joint is an area at high risk of chronic inflammation, and may provide a piece in the puzzle of how chronic inflammation is established in RA. Electronic supplementary material The online version of this article (doi:10.1186/s13075-017-1248-6) contains supplementary material, which is available to authorized users.

Published
2018

48. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer

Author

Wirbel, Jakob, primary, Pyl, Paul Theodor, additional, Kartal, Ece, additional, Zych, Konrad, additional, Kashani, Alireza, additional, Milanese, Alessio, additional, Fleck, Jonas S., additional, Voigt, Anita Y., additional, Palleja, Albert, additional, Ponnudurai, Ruby, additional, Sunagawa, Shinichi, additional, Coelho, Luis Pedro, additional, Schrotz-King, Petra, additional, Vogtmann, Emily, additional, Habermann, Nina, additional, Niméus, Emma, additional, Thomas, Andrew M., additional, Manghi, Paolo, additional, Gandini, Sara, additional, Serrano, Davide, additional, Mizutani, Sayaka, additional, Shiroma, Hirotsugu, additional, Shiba, Satoshi, additional, Shibata, Tatsuhiro, additional, Yachida, Shinichi, additional, Yamada, Takuji, additional, Waldron, Levi, additional, Naccarati, Alessio, additional, Segata, Nicola, additional, Sinha, Rashmi, additional, Ulrich, Cornelia M., additional, Brenner, Hermann, additional, Arumugam, Manimozhiyan, additional, Bork, Peer, additional, and Zeller, Georg, additional

Published
2019
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50. Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification over Land.

Author

JINWOONG YOO, SANTANELLO JR., JOSEPH A., SHEPHERD, MARSHALL, KUMAR, SUJAY, LAWSTON, PATRICIA, and THOMAS, ANDREW M.

Subjects
TROPICAL cyclones, VERTICAL wind shear, HUMIDITY, PRECIPITABLE water, SOIL moisture, SOLAR cycle, SOLAR radiation
Abstract

An investigation of Tropical Cyclone (TC) Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the brown ocean effect (BOE) and to develop a comprehensive analysis framework for landfalling TCs in the process. NASA's Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e., all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs. [ABSTRACT FROM AUTHOR]

Published
2020
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