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Article ; Online: Conditional Poisson Regression with Random Effects for the Analysis of Multi-site Time Series Studies.

Barrera-Gómez, Jose / Puig, Xavier / Ginebra, Josep / Basagaña, Xavier

2023 Volume 34, Issue 6, Page(s) 873–878

Abstract: The analysis of time series studies linking daily counts of a health indicator with environmental variables (e.g., mortality or hospital admissions with air pollution concentrations or temperature; or motor vehicle crashes with temperature) is usually ... ...

Abstract	The analysis of time series studies linking daily counts of a health indicator with environmental variables (e.g., mortality or hospital admissions with air pollution concentrations or temperature; or motor vehicle crashes with temperature) is usually conducted with Poisson regression models controlling for long-term and seasonal trends using temporal strata. When the study includes multiple zones, analysts usually apply a two-stage approach: first, each zone is analyzed separately, and the resulting zone-specific estimates are then combined using meta-analysis. This approach allows zone-specific control for trends. A one-stage approach uses spatio-temporal strata and could be seen as a particular case of the case-time series framework recently proposed. However, the number of strata can escalate very rapidly in a long time series with many zones. A computationally efficient alternative is to fit a conditional Poisson regression model, avoiding the estimation of the nuisance strata. To allow for zone-specific effects, we propose a conditional Poisson regression model with a random slope, although available frequentist software does not implement this model. Here, we implement our approach in the Bayesian paradigm, which also facilitates the inclusion of spatial patterns in the effect of interest. We also provide a possible extension to deal with overdispersed data. We first introduce the equations of the framework and then illustrate their application to data from a previously published study on the effects of temperature on the risk of motor vehicle crashes. We provide R code and a semi-synthetic dataset to reproduce all analyses presented.
MeSH term(s)	Humans ; Time Factors ; Bayes Theorem ; Air Pollution/analysis ; Temperature ; Software ; Air Pollutants/analysis
Chemical Substances	Air Pollutants
Language	English
Publishing date	2023-09-14
Publishing country	United States
Document type	Meta-Analysis ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1053263-8
ISSN	1531-5487 ; 1044-3983
ISSN (online)	1531-5487
ISSN	1044-3983
DOI	10.1097/EDE.0000000000001664
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Article ; Online: Analysis of Fecal Microbiota Dynamics in Lupus-Prone Mice using a Simple, Cost-Effective DNA Isolation Method.

Cabana Puig, Xavier / Reilly, Christopher M / Luo, Xin M

Journal of visualized experiments : JoVE

2022 , Issue 183

Abstract: Gut microbiota has an important role in educating the immune system. This relationship is extremely important for understanding autoimmune diseases that are not only driven by genetic factors, but also environmental factors that can trigger the onset and/ ...

Abstract	Gut microbiota has an important role in educating the immune system. This relationship is extremely important for understanding autoimmune diseases that are not only driven by genetic factors, but also environmental factors that can trigger the onset and/or worsen the disease course. A previously published study on the dynamics of the gut microbiota in lupus-prone MRL/lpr female mice showed how changes of the gut microbiota can alter disease progression. Here, a protocol is described for extracting representative samples from the gut microbiota for studies of autoimmunity. Microbiota samples are collected from the anus and processed, from which the DNA is extracted using a phenol-chloroform method and purified by alcohol precipitation. After PCR is performed, purified amplicons are sequenced using a Next Generation Sequencing platform at Argonne National Laboratory. Finally, the 16S ribosomal RNA gene sequencing data is analyzed. As an example, data obtained from gut microbiota comparisons of MRL/lpr mice with or without CX3CR1 are shown. Results showed significant differences in genera containing pathogenic bacteria such as those in the phylum Proteobacteria, as well as the genus Bifidobacterium, which is considered part of the healthy commensal microbiota. In summary, this simple, cost-effective DNA isolation method is reliable and can help the investigation of gut microbiota changes associated with autoimmune diseases.
MeSH term(s)	Animals ; Autoimmune Diseases ; Cost-Benefit Analysis ; DNA ; Feces/microbiology ; Female ; Mice ; Mice, Inbred MRL lpr ; Microbiota ; RNA, Ribosomal, 16S/genetics
Chemical Substances	RNA, Ribosomal, 16S ; DNA (9007-49-2)
Language	English
Publishing date	2022-05-02
Publishing country	United States
Document type	Journal Article ; Video-Audio Media ; Research Support, N.I.H., Intramural
ZDB-ID	2259946-0
ISSN	1940-087X ; 1940-087X
ISSN (online)	1940-087X
ISSN	1940-087X
DOI	10.3791/63623
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analyses of Proteinuria, Renal Infiltration of Leukocytes, and Renal Deposition of Proteins in Lupus-prone MRL/lpr Mice.

Cabana-Puig, Xavier / Luo, Xin M

Journal of visualized experiments : JoVE

2022 , Issue 184

Abstract: Systemic lupus erythematosus (SLE) is an autoimmune disorder with no known cure and is characterized by persistent inflammation in many organs, including the kidneys. Under such circumstances, the kidney loses its ability to clean waste from the blood ... ...

Abstract	Systemic lupus erythematosus (SLE) is an autoimmune disorder with no known cure and is characterized by persistent inflammation in many organs, including the kidneys. Under such circumstances, the kidney loses its ability to clean waste from the blood and regulate salt and fluid concentrations, eventually leading to renal failure. Women, particularly those of childbearing age, are diagnosed nine times more often than men. Kidney disease is the leading cause of mortality in SLE patients. The present protocol describes a quick and simple method to measure excreted protein levels in collected urine, tracking lupus progression over time. In addition, an approach to isolate kidney mononuclear cells is provided based on size and density selection to investigate renal infiltration of leukocytes. Furthermore, an immunohistochemical method has been developed to characterize protein deposition in the glomeruli and leukocyte infiltration in the tubulointerstitial space. Together, these methods can help investigate the progression of chronic inflammation associated with the kidneys of lupus-prone MRL/lpr mice.
MeSH term(s)	Animals ; Female ; Humans ; Inflammation/metabolism ; Kidney/metabolism ; Leukocytes/metabolism ; Lupus Erythematosus, Systemic/complications ; Mice ; Mice, Inbred MRL lpr ; Proteinuria/complications ; Proteinuria/metabolism
Language	English
Publishing date	2022-06-08
Publishing country	United States
Document type	Journal Article ; Video-Audio Media ; Research Support, N.I.H., Extramural
ZDB-ID	2259946-0
ISSN	1940-087X ; 1940-087X
ISSN (online)	1940-087X
ISSN	1940-087X
DOI	10.3791/63506
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Article ; Online: A Smart Home Digital Twin to Support the Recognition of Activities of Daily Living.

Bouchabou, Damien / Grosset, Juliette / Nguyen, Sao Mai / Lohr, Christophe / Puig, Xavier

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 17

Abstract: One of the challenges in the field of human activity recognition in smart homes based on IoT sensors is the variability in the recorded data. This variability arises from differences in home configurations, sensor network setups, and the number and ... ...

Abstract	One of the challenges in the field of human activity recognition in smart homes based on IoT sensors is the variability in the recorded data. This variability arises from differences in home configurations, sensor network setups, and the number and habits of inhabitants, resulting in a lack of data that accurately represent the application environment. Although simulators have been proposed in the literature to generate data, they fail to bridge the gap between training and field data or produce diverse datasets. In this article, we propose a solution to address this issue by leveraging the concept of digital twins to reduce the disparity between training and real-world data and generate more varied datasets. We introduce the Virtual Smart Home, a simulator specifically designed for modeling daily life activities in smart homes, which is adapted from the Virtual Home simulator. To assess its realism, we compare a set of activity data recorded in a real-life smart apartment with its replication in the VirtualSmartHome simulator. Additionally, we demonstrate that an activity recognition algorithm trained on the data generated by the VirtualSmartHome simulator can be successfully validated using real-life field data.
MeSH term(s)	Humans ; Activities of Daily Living ; Pattern Recognition, Automated ; Algorithms ; Records ; Habits
Language	English
Publishing date	2023-09-01
Publishing country	Switzerland
Document type	Dataset ; Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23177586
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Article: LPDynR: A new tool to calculate the land productivity dynamics indicator

Rotllan-Puig, Xavier / Ivits, Eva / Cherlet, Michael

Ecological indicators. 2021 Dec., v. 133

2021

Abstract: The United Nations Sustainable Development Goal 15 (Life on Land), adopted the indicator 15.3.1 to measure the Land Degradation Neutrality. This indicator is based on three sub-indicators: (1) Trends in Land Cover, (2) Land Productivity and (3) Carbon ... ...

Abstract	The United Nations Sustainable Development Goal 15 (Life on Land), adopted the indicator 15.3.1 to measure the Land Degradation Neutrality. This indicator is based on three sub-indicators: (1) Trends in Land Cover, (2) Land Productivity and (3) Carbon Stocks. The Land Productivity sub-indicator refers to the total above-ground Net Primary Production and reflects changes in health and productive capacity of the land. It can be calculated using the Land Productivity Dynamics approach, which performs a combined assessment of the long term tendency of change of land productivity and its current level relative to homogeneous land areas.Here, we present the R-based tool LPDynR, which implements the Land Productivity Dynamics approach for the calculation of the Land Productivity sub-indicator. LPDynR ingests vegetation-related indices derived from time series of remote sensed imagery. The final indicator is a 5-class map, ranging from declining to increasing land productivity. As an example of LPDynR functionalities and applicability, we present a case study for Europe. First, we show the general way to calculate the indicator for the entire time series (2000–2019), explained in a step by step process. Secondly, we show how to alternatively calculate the indicator based only on the long term tendency of change, but we evidence the added value of including the current level of productivity to refine the final indicator. Finally, we present some code for the calculation of “partial indicators” in terms of time scale along the observation period, which may help the user to understand the land productivity dynamics within the time series, as well as to assess the stability of the final product. While the indicator shows a general positive dynamics across Europe during the period 2000–2019, some of the partial maps show more negative trends, demonstrating the highly fluctuating character of vegetation.
Keywords	carbon ; case studies ; economic productivity ; land cover ; land degradation ; land productivity ; net primary productivity ; remote sensing ; sustainable development ; time series analysis ; vegetation ; Europe
Language	English
Dates of publication	2021-12
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	2036774-0
ISSN	1872-7034 ; 1470-160X
ISSN (online)	1872-7034
ISSN	1470-160X
DOI	10.1016/j.ecolind.2021.108386
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Generating Continual Human Motion in Diverse 3D Scenes

Mir, Aymen / Puig, Xavier / Kanazawa, Angjoo / Pons-Moll, Gerard

2023

Abstract: We introduce a method to synthesize animator guided human motion across 3D scenes. Given a set of sparse (3 or 4) joint locations (such as the location of a person's hand and two feet) and a seed motion sequence in a 3D scene, our method generates a ... ...

Abstract	We introduce a method to synthesize animator guided human motion across 3D scenes. Given a set of sparse (3 or 4) joint locations (such as the location of a person's hand and two feet) and a seed motion sequence in a 3D scene, our method generates a plausible motion sequence starting from the seed motion while satisfying the constraints imposed by the provided keypoints. We decompose the continual motion synthesis problem into walking along paths and transitioning in and out of the actions specified by the keypoints, which enables long generation of motions that satisfy scene constraints without explicitly incorporating scene information. Our method is trained only using scene agnostic mocap data. As a result, our approach is deployable across 3D scenes with various geometries. For achieving plausible continual motion synthesis without drift, our key contribution is to generate motion in a goal-centric canonical coordinate frame where the next immediate target is situated at the origin. Our model can generate long sequences of diverse actions such as grabbing, sitting and leaning chained together in arbitrary order, demonstrated on scenes of varying geometry: HPS, Replica, Matterport, ScanNet and scenes represented using NeRFs. Several experiments demonstrate that our method outperforms existing methods that navigate paths in 3D scenes.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2023-04-04
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: NOPA

Puig, Xavier / Shu, Tianmin / Tenenbaum, Joshua B. / Torralba, Antonio

Neurally-guided Online Probabilistic Assistance for Building Socially Intelligent Home Assistants

2023

Abstract: In this work, we study how to build socially intelligent robots to assist people in their homes. In particular, we focus on assistance with online goal inference, where robots must simultaneously infer humans' goals and how to help them achieve those ... ...

Abstract	In this work, we study how to build socially intelligent robots to assist people in their homes. In particular, we focus on assistance with online goal inference, where robots must simultaneously infer humans' goals and how to help them achieve those goals. Prior assistance methods either lack the adaptivity to adjust helping strategies (i.e., when and how to help) in response to uncertainty about goals or the scalability to conduct fast inference in a large goal space. Our NOPA (Neurally-guided Online Probabilistic Assistance) method addresses both of these challenges. NOPA consists of (1) an online goal inference module combining neural goal proposals with inverse planning and particle filtering for robust inference under uncertainty, and (2) a helping planner that discovers valuable subgoals to help with and is aware of the uncertainty in goal inference. We compare NOPA against multiple baselines in a new embodied AI assistance challenge: Online Watch-And-Help, in which a helper agent needs to simultaneously watch a main agent's action, infer its goal, and help perform a common household task faster in realistic virtual home environments. Experiments show that our helper agent robustly updates its goal inference and adapts its helping plans to the changing level of uncertainty. Comment: Project website: https://www.tshu.io/online_watch_and_help. Code: https://github.com/xavierpuigf/online_watch_and_help
Keywords	Computer Science - Robotics ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Computer Science - Multiagent Systems
Subject code	629
Publishing date	2023-01-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Alcohol as a trigger of migraine attacks in people with migraine. Results from a large prospective cohort study in English-speaking countries.

Vives-Mestres, Marina / Casanova, Amparo / Puig, Xavier / Ginebra, Josep / Rosen, Noah

Headache

2022 Volume 62, Issue 10, Page(s) 1329–1338

Abstract: Objective: To assess whether alcohol intake is associated with the onset of migraine attacks up to 2 days after consumption in individuals with episodic migraine (EM).: Background: Although alcohol has long been suspected to be a common migraine ... ...

Abstract	Objective: To assess whether alcohol intake is associated with the onset of migraine attacks up to 2 days after consumption in individuals with episodic migraine (EM). Background: Although alcohol has long been suspected to be a common migraine trigger, studies have been inconclusive in proving this association. Methods: This was an observational prospective cohort study among individuals with migraine who registered to use a digital health platform for headache. Eligible individuals were aged ≥18 years with EM who consumed alcohol and had tracked their headache symptoms and alcohol intake for ≥90 days. People who did not drink any alcohol were excluded. The association of alcohol intake ("Yes/No") and of the number of alcoholic beverages in the 2 days preceding a migraine attack was assessed accounting for the presence of migraine on day-2 and its interaction with alcohol intake on day-2, and further adjusted for sex, age, and average weekly alcohol intake. Results: Data on 487 individuals reporting 5913 migraine attacks and a total of 40,165 diary days were included in the analysis. Presence of migraine on day-2 and its interaction with alcohol intake on day-2 were not significant and removed from the model. At the population level, alcohol intake on day-2 was associated with a lower probability of migraine attack (OR [95% CI] = 0.75 [0.68, 0.82]; event rate 1006/4679, 21.5%), while the effect of alcohol intake on day-1 was not significant (OR [95% CI] = 1.01 [0.91, 1.11]; event rate 1163/4679, 24.9%) after adjusting for sex, age, and average weekly alcohol intake. Similar results were obtained with the number of beverages as exposure. Conclusions: In this English-speaking cohort of individuals with EM who identified themselves as mostly low-dose alcohol consumers, there was no significant effect on the probability of a migraine attack in the 24 h following consumption, and a slightly lower likelihood of a migraine attack from 24 to 48 h following use.
MeSH term(s)	Humans ; Adolescent ; Adult ; Prospective Studies ; Migraine Disorders/epidemiology ; Precipitating Factors ; Headache ; Alcohol Drinking/adverse effects ; Alcohol Drinking/epidemiology
Language	English
Publishing date	2022-11-27
Publishing country	United States
Document type	Observational Study ; Journal Article
ZDB-ID	410130-3
ISSN	1526-4610 ; 0017-8748
ISSN (online)	1526-4610
ISSN	0017-8748
DOI	10.1111/head.14428
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Article ; Online: Bayesian model selection for the study of Hardy-Weinberg proportions and homogeneity of gender allele frequencies.

Puig, Xavier / Ginebra, Josep / Graffelman, Jan

Heredity

2019 Volume 123, Issue 5, Page(s) 549–564

Abstract: Standard statistical tests for Hardy-Weinberg equilibrium assume the equality of allele frequencies in the sexes, whereas tests for the equality of allele frequencies in the sexes assume Hardy-Weinberg equilibrium. This produces a circularity in the ... ...

Abstract	Standard statistical tests for Hardy-Weinberg equilibrium assume the equality of allele frequencies in the sexes, whereas tests for the equality of allele frequencies in the sexes assume Hardy-Weinberg equilibrium. This produces a circularity in the testing of genetic variants, which has recently been resolved with new frequentist likelihood and exact procedures. In this paper, we tackle the same problem by posing it as a Bayesian model comparison problem. We formulate an exhaustive set of ten alternative scenarios for biallelic genetic variants. Using Dirichlet and Beta priors for genotype and allele frequencies, we derive marginal likelihoods for all scenarios, and select the most likely scenario using the posterior probabilities that each of these scenarios is the one in place. Different from the usual frequentist testing approach, the Bayesian approach allows one to compare any number of models, and not just two at a time, and the models compared do not have to be nested. We illustrate our Bayesian approach with genetic data from the 1,000 genomes project and through a simulation study.
MeSH term(s)	Alleles ; Animals ; Female ; Gene Frequency ; Genotype ; Humans ; Male ; Models, Genetic
Language	English
Publishing date	2019-05-29
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2423-5
ISSN	1365-2540 ; 0018-067X
ISSN (online)	1365-2540
ISSN	0018-067X
DOI	10.1038/s41437-019-0232-0
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Article ; Online: Combined dilute alkali and milling process enhances the functionality and gut microbiota fermentability of insoluble corn fiber.

Jin, Qing / Feng, Yiming / Cabana-Puig, Xavier / Chau, Tran N / Difulvio, Ronnie / Yu, Dajun / Hu, Anyang / Li, Song / Luo, Xin M / Ogejo, Jactone / Lin, Feng / Huang, Haibo

Food chemistry

2024 Volume 446, Page(s) 138815

Abstract: In this study, we developed a process combining dilute alkali (NaOH or ... ...

Abstract	In this study, we developed a process combining dilute alkali (NaOH or NaHCO
MeSH term(s)	Animals ; Swine ; Dietary Fiber/analysis ; Zea mays/chemistry ; Gastrointestinal Microbiome ; Alkalies ; Sodium Hydroxide ; Animal Feed/analysis ; Feces/chemistry ; Fatty Acids, Volatile/analysis ; Water/analysis ; Fermentation
Chemical Substances	Dietary Fiber ; Alkalies ; Sodium Hydroxide (55X04QC32I) ; Fatty Acids, Volatile ; Water (059QF0KO0R)
Language	English
Publishing date	2024-02-22
Publishing country	England
Document type	Journal Article
ZDB-ID	243123-3
ISSN	1873-7072 ; 0308-8146
ISSN (online)	1873-7072
ISSN	0308-8146
DOI	10.1016/j.foodchem.2024.138815
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