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973) for NPH patients and good (0.875) for controls. On mal-rotated coronal plane setups, ICC for CA was worse in controls (0.484-0.886) than NPH (0.879-0.981) groups and in clockwise-anticlockwise (0.484-0.956) than anterior-posterior (0.503-0.981) mal-rotations. CA changes secondary to mal-rotations from the true coronal plane were significant in NPH patients (P < 0.0001 to 0.0378) but not in controls (P > 0.1).

This is the first demonstration of how small angular mal-rotations of the coronal plane used for CA measurement affect its value and inter-rater reliability, highlighting the importance of a standardized protocol when measuring the CA in NPH workup.

This is the first demonstration of how small angular mal-rotations of the coronal plane used for CA measurement affect its value and inter-rater reliability, highlighting the importance of a standardized protocol when measuring the CA in NPH workup.

Besides serving as a traditional inflammatory marker, C-reactive protein (CRP) is closely associated with the development of obesity, diabetes and cardiovascular diseases as a metabolic and inflammatory marker. We hypothesise that CRP protein directly participates in the regulation of energy and glucose metabolism rather than just being a surrogate marker, and that genetic deficiency of CRP will lead to resistance to obesity and insulin resistance.

Crp gene deletion was achieved by transcription activator-like effector nuclease (TALEN) technology in rats. The Crp knockout animals were placed on either a standard chow diet or a high-fat diet. Phenotypic changes in body weight, glucose metabolism, insulin sensitivity, energy expenditure and inflammation condition were examined. The central impact of CRP deficiency on leptin and insulin hypothalamic signalling, as well as glucose homeostasis, were examined via intracerebral ventricular delivery of leptin and CRP plus glucose clamp studies in the wild-type anrrogate blood marker for inflammation and metabolic syndromes but directly regulates energy balance, body weight, insulin sensitivity and glucose homeostasis through direct regulation of leptin's central effect and hypothalamic signalling.Chronic metabolic diseases, including diabetes and obesity, have become a major global health threat of the twenty-first century. Maintaining glucose homeostasis is essential for survival in mammals. Complex and highly coordinated interactions between glucose-sensing mechanisms and multiple effector systems are essential for controlling glucose levels in the blood. Rimiducid The central nervous system (CNS) plays a crucial role in regulating glucose homeostasis. Growing evidence indicates that disruption of glucose sensing in selective CNS areas, such as the hypothalamus, is closely interlinked with the pathogenesis of obesity and type 2 diabetes mellitus. However, the underlying intracellular mechanisms of glucose sensing in the hypothalamus remain elusive. Here, we review the current literature on hypothalamic glucose-sensing mechanisms and discuss the impact of alterations of these mechanisms on the pathogenesis of diabetes.

Environmental factors are believed to contribute to the risk of developing type 1 diabetes. The aim of this study was to investigate how size for gestational age affects the risk of developing childhood type 1 diabetes.

Using the Swedish paediatric diabetes quality register and the Swedish medical birth register, children with type 1 diabetes diagnosed between 2000 and 2012 (n = 9376) were matched with four control children (n = 37,504). Small for gestational age (SGA) and large for gestational age (LGA) were defined according to Swedish national standards. Data were initially analysed using Pearson's χ

and thereafter by single and multiple logistic regression models.

An equal proportion of children were born appropriate for gestational age, but children with type 1 diabetes were more often born LGA and less often born SGA than control children (4.7% vs 3.5% and 2.0% vs 2.6%, respectively, p < 0.001). In the multiple logistic regression analysis, being born LGA increased (adjusted OR 1.16 [95% CI 1.02, 1.32]) and SGA decreased (adjusted OR 0.76 [95% CI 0.63, 0.92]) the risk for type 1 diabetes, regardless of maternal BMI and diabetes.

Size for gestational age of Swedish children affects the risk of type 1 diabetes, with increased risk if the child is born LGA and decreased risk if the child is born SGA. Being born LGA is an independent risk factor for type 1 diabetes irrespective of maternal BMI and diabetes. Thus, reducing the risk for a child being born LGA might to some extent reduce the risk for type 1 diabetes.

Size for gestational age of Swedish children affects the risk of type 1 diabetes, with increased risk if the child is born LGA and decreased risk if the child is born SGA. Being born LGA is an independent risk factor for type 1 diabetes irrespective of maternal BMI and diabetes. Thus, reducing the risk for a child being born LGA might to some extent reduce the risk for type 1 diabetes.

This study aims to develop a clinically practical model to predict EGFR mutation in lung adenocarcinoma patients according to radiomics signatures based on PET/CT and clinical risk factors.

This retrospective study included 583 lung adenocarcinoma patients, including 295 (50.60%) patients with EGFR mutation and 288 (49.40%) patients without EGFR mutation. The clinical risk factors associated with lung adenocarcinoma were collected at the same time. We developed PET/CT, CT, and PET radiomics models for the prediction of EGFR mutation using multivariate logistic regression analysis, respectively. We also constructed a combined PET/CT radiomics-clinical model by nomogram analysis. The diagnostic performance and clinical net benefit of this risk-scoring model were examined via receiver operating characteristic (ROC) curve analysis while the clinical usefulness of this model was evaluated by decision curve analysis (DCA).

The ROC analysis showed predictive performance for the PET/CT radiomics model (AUC = 0.ped to predict EGFR mutation. • Combining PET/CT radiomics-clinical model has an advantage to predict EGFR mutation.