Use of a Bayesian Network Model to predict psychiatric illness in individuals with ‘at risk mental states’ from a general population cohort

2021 ◽  
pp. 136358
Author(s):  
Alexandre Andrade Loch ◽  
Anderson Ara ◽  
Lucas Hortêncio ◽  
Julia Hatagami Marques ◽  
Leda Leme Talib ◽  
...  
Keyword(s):  
At Risk ◽  
General Population ◽  
Bayesian Network ◽  
Network Model ◽  
Psychiatric Illness ◽  
Mental States ◽  
Bayesian Network Model ◽  
Population Cohort ◽  
General Population Cohort ◽  
At Risk Mental States

scholarly journals Endocannabinoid system mediates the association between gut-microbial diversity and anhedonia/amotivation in a general population cohort

2021 ◽  
Author(s):  
Amedeo Minichino ◽  
Matthew A. Jackson ◽  
Marta Francesconi ◽  
Claire J. Steves ◽  
Cristina Menni ◽  
...  
Keyword(s):  
General Population ◽  
Microbial Diversity ◽  
Gut Microbiome ◽  
Endocannabinoid System ◽  
Alpha Diversity ◽  
Serum Levels ◽  
Population Cohort ◽  
Random Intercept ◽  
General Population Cohort ◽  
Antidepressant Use

AbstractAnhedonia and amotivation are debilitating symptoms and represent unmet therapeutic needs in a range of clinical conditions. The gut-microbiome-endocannabinoid axis might represent a potential modifiable target for interventions. Based on results obtained from animal models, we tested the hypothesis that the endocannabinoid system mediates the association between gut-microbiome diversity and anhedonia/amotivation in a general population cohort. We used longitudinal data collected from 786 volunteer twins recruited as part the TwinsUK register. Our hypothesis was tested with a multilevel mediation model using family structure as random intercept. The model was set using alpha diversity (within-individual gut-microbial diversity) as predictor, serum and faecal levels of the endocannabinoid palmitoylethanolamide (PEA) as mediator, and anhedonia/amotivation as outcome. PEA is considered the endogenous equivalent of cannabidiol, with increased serum levels believed to have anti-depressive effects, while increased stool PEA levels, reflecting increased excretion, are believed to have opposite, detrimental, effects on mental health. We therefore expected that either reduced serum PEA or increased stool PEA would mediate the association between microbial diversity and anhedonia amotivation. Analyses were adjusted for obesity, diet, antidepressant use, sociodemographic and technical covariates. Data were imputed using multiple imputation by chained equations. Mean age was 65.2 ± 7.6; 93% of the sample were females. We found a direct, significant, association between alpha diversity and anhedonia/amotivation (β = −0.37; 95%CI: −0.71 to −0.03; P = 0.03). Faecal, but not serum, levels of the endocannabinoid palmitoylethanolamide (PEA) mediated this association: the indirect effect was significant (β = −0.13; 95%CI: −0.24 to −0.01; P = 0.03), as was the total effect (β = −0.38; 95%CI: −0.72 to −0.04; P = 0.03), whereas the direct effect of alpha diversity on anhedonia/amotivation was attenuated fully (β = −0.25; 95%CI: −0.60 to 0.09; P = 0.16). Our results suggest that gut-microbial diversity might contribute to anhedonia/amotivation via the endocannabinoid system. These findings shed light on the biological underpinnings of anhedonia/amotivation and suggest the gut microbiota-endocannabinoid axis as a promising therapeutic target in an area of unmet clinical need.

scholarly journals Predicting the risk of GenX contamination in private well water using a machine-learned Bayesian network model

2021 ◽  
pp. 125075
Author(s):  
Javad Roostaei ◽  
Sarah Colley ◽  
Riley Mulhern ◽  
Andrew A. May ◽  
Jacqueline MacDonald Gibson
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Well Water ◽  
Bayesian Network Model

scholarly journals Impact Mechanism of the Ecological Vulnerability of Highly Developed Islands Based on the Bayesian Network Model—Applied to the Changshan Islands

2021 ◽  
Vol 18 (8) ◽  
pp. 4150
Author(s):  
Keyu Qin ◽  
Haijun Huang ◽  
Jingya Liu ◽  
Liwen Yan ◽  
Yanxia Liu ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Geographical Information ◽  
Global Changes ◽  
Bayesian Network Model ◽  
Island Ecosystems ◽  
Impact Mechanism ◽  
The North ◽  
Ecological Vulnerability ◽  
The Impact

Islands are one of the most sensitive interfaces between global changes and land and sea dynamic effects, with high sensitivity and low stability. Therefore, under the dynamic coupling effect of human activities and frequent natural disasters, the vulnerability of the ecological environment of islands shows the characteristics of complexity and diversity. For the protection of island ecosystems, a system for the assessment of island ecosystems and studies on the mechanism of island ecological vulnerability are highly crucial. In this study, the North and South Changshan Islands of China were selected as the study area. Considering various impact factors of island ecological vulnerability, the geographical information systems (GIS) spatial analysis, field surveys, data sampling were used to evaluate island ecological vulnerability. The Bayesian network model was used to explore the impact mechanism of ecological vulnerability. The results showed that the ecological vulnerability of the North Changshan Island is higher than that of the South Changshan Island. Among all the indicators, the proportion of net primary productivity (NPP) and the steep slope has the strongest correlation with ecological vulnerability. This study can be used as references in the relevant departments to formulate management policies and promote the sustainable development of islands and their surrounding waters

scholarly journals Misper-Bayes: A Bayesian Network Model for Missing Person Investigations

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Denis Reilly ◽  
Mark Taylor ◽  
Paul Fergus ◽  
Carl Chalmers ◽  
Steven Thompson
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Bayesian Network Model

scholarly journals Testing the validity of national drug surveys: comparison between a general population cohort and household surveys

Addiction ◽  
2021 ◽  
Author(s):  
Hannah Charles ◽  
Jon Heron ◽  
Matthew Hickman ◽  
Jamie Brown ◽  
Lindsey Hines
Keyword(s):  
General Population ◽  
Household Surveys ◽  
Population Cohort ◽  
National Drug ◽  
General Population Cohort

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

ApoE and vascular disease – resequencing and genotyping in a general population cohort

2021 ◽  
Vol 331 ◽  
pp. e53-e54
Author(s):  
K.L. Rasmussen ◽  
A. Tybjærg-Hansen ◽  
B.G. Nordestgaard ◽  
R. Frikke-Schmidt
Keyword(s):  
General Population ◽  
Vascular Disease ◽  
Population Cohort ◽  
General Population Cohort
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