| 1. |
- McWhinney, Sean R, et al.
(author)
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Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.
- 2024
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In: Human brain mapping. - 1097-0193. ; 45:8
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Journal article (peer-reviewed)abstract
- Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
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| 2. |
- Kalman, JL, et al.
(author)
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Investigating the phenotypic and genetic associations between personality traits and suicidal behavior across major mental health diagnoses
- 2022
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In: European archives of psychiatry and clinical neuroscience. - : Springer Science and Business Media LLC. - 1433-8491 .- 0940-1334. ; 272:8, s. 1611-1620
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Journal article (peer-reviewed)abstract
- Personality traits influence risk for suicidal behavior. We examined phenotype- and genotype-level associations between the Big Five personality traits and suicidal ideation and attempt in major depressive, bipolar and schizoaffective disorder, and schizophrenia patients (N = 3012) using fixed- and random-effects inverse variance-weighted meta-analyses. Suicidal ideations were more likely to be reported by patients with higher neuroticism and lower extraversion phenotypic scores, but showed no significant association with polygenic load for these personality traits. Our findings provide new insights into the association between personality and suicidal behavior across mental illnesses and suggest that the genetic component of personality traits is unlikely to have strong causal effects on suicidal behavior.
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| 4. |
- Khadhraoui, S., et al.
(author)
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A new approach for modelling and control of dephosphorization in BOF converter
- 2018
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In: La Metallurgia Italiana. - : Associazione Italiana di Metallurgia. - 0026-0843. ; 110:11-12, s. 5-16
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Journal article (peer-reviewed)abstract
- In the BOF process, the accurate control of Phosphorous removal up to ultra-low values is very important to ensure a high quality of the end–product. This has proven to be associated with several challenges, leading to a preferred usage of high priced low P iron ores. Thus, in the scope of the European BOFdePhos project, important thermodynamic and kinetic aspects of the dephosphorisation reaction such as the effect of solid phases on Phosphorous distribution and lime dissolution in a foamy slag were investigated. It was found that BOF slags are heterogeneous during a large period of the blow and also at the end of blow in most cases. The type and amount of solid phases is strongly affected by temperature and minor oxides content such as MgO-, MnO- and Al2O3-content. The consideration of solid phases formation in the slag, especially the P dissolving C2S_C3P phase, is crucial for a successful modelling and control of dephosphorisation. However, most of the Phosphorous distribution equations available in the literature were developed for homogeneous slags. Thus, a new approach for thermodynamic modelling of the P-distribution between a heterogeneous slag and liquid iron covering the total blowing period in converter was developed and incorporated in a kinetic dephosphorisation model. It was found that while the P distribution in a fully liquid slag was a strong function of temperature, CaO- and FeO-content, the P distribution in a heterogeneous slag depended further on temperature but also on the amount of solid phase as well as the basicity of the liquid slag phase. Even though the C2S_C3P phase can dissolve high amount of Phosphorous, the P-dissolution in the solid phase in the industrial process is associated with strong kinetic limitations. New strategies for the enhancement of dephosphorization control in the BOF converter, focusing on using the potential of the solid phase in removing Phosphorous, were developed.
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| 5. |
- Li, JH, et al.
(author)
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IL-17B/RB Activation in Pancreatic Stellate Cells Promotes Pancreatic Cancer Metabolism and Growth
- 2021
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In: Cancers. - : MDPI AG. - 2072-6694. ; 13:21
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Journal article (peer-reviewed)abstract
- In pancreatic ductal adenocarcinoma (PDAC), the tumor stroma constitutes most of the cell mass and contributes to therapy resistance and progression. Here we show a hitherto unknown metabolic cooperation between pancreatic stellate cells (PSCs) and tumor cells through Interleukin 17B/Interleukin 17B receptor (IL-17B/IL-17RB) signaling. Tumor-derived IL-17B carrying extracellular vesicles (EVs) activated stromal PSCs and induced the expression of IL-17RB. PSCs increased oxidative phosphorylation while reducing mitochondrial turnover. PSCs activated tumor cells in a feedback loop. Tumor cells subsequently increased oxidative phosphorylation and decreased glycolysis partially via IL-6. In vivo, IL-17RB overexpression in PSCs accelerated tumor growth in a co-injection xenograft mouse model. Our results demonstrate a tumor-to-stroma feedback loop increasing tumor metabolism to accelerate tumor growth under optimal nutritional conditions.
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