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Träfflista för sökning "WFRF:(Rial Manuel J.) "

Sökning: WFRF:(Rial Manuel J.)

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1.
  • Martínez-Sánchez, Noelia, et al. (författare)
  • Hypothalamic AMPK-ER Stress-JNK1 Axis Mediates the Central Actions of Thyroid Hormones on Energy Balance
  • 2017
  • Ingår i: Cell Metabolism. - Cambridge, MA, United States : Cell Press. - 1550-4131 .- 1932-7420. ; 26:1, s. 212-229.e12
  • Tidskriftsartikel (refereegranskat)abstract
    • Thyroid hormones (THs) act in the brain to modulate energy balance. We show that central triiodothyronine (T3) regulates de novo lipogenesis in liver and lipid oxidation in brown adipose tissue (BAT) through the parasympathetic (PSNS) and sympathetic nervous system (SNS), respectively. Central T3 promotes hepatic lipogenesis with parallel stimulation of the thermogenic program in BAT. The action of T3 depends on AMP-activated protein kinase (AMPK)-induced regulation of two signaling pathways in the ventromedial nucleus of the hypothalamus (VMH): decreased ceramide-induced endoplasmic reticulum (ER) stress, which promotes BAT thermogenesis, and increased c-Jun N-terminal kinase (JNK) activation, which controls hepatic lipid metabolism. Of note, ablation of AMPKα1 in steroidogenic factor 1 (SF1) neurons of the VMH fully recapitulated the effect of central T3, pointing to this population in mediating the effect of central THs on metabolism. Overall, these findings uncover the underlying pathways through which central T3 modulates peripheral metabolism.
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2.
  • Matabuena, Marcos, et al. (författare)
  • Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis
  • 2023
  • Ingår i: Archivos de Bronconeumologia. - : Elsevier BV. - 0300-2896. ; 59:4, s. 223-231
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. Methods: We performed a multicentre prospective cohort study, including adult patients with asthma (N = 512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. Results: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. Conclusion: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps.
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