Activation of ß2-adrenergic Receptor Ameliorates Amyloid-ß-induced Mitophagy Defects and Tau Pathology in Mice.

Defective mitophagy and mitochondrial dysfunction have been linked to aging and Alzheimer's disease (AD). ß2-Adrenergic receptor (ADRB2) is critical for mitochondrial and cognitive function. However, researchers have not clearly determined whether ADRB2 activation ameliorates defective mitophagy and cognitive deficits in individuals with AD. Here, we observed that the activation of ADRB2 by clenbuterol (Clen, ADRB2 agonist, 2 mg/kg/day) ameliorated amyloid-ß-induced (Aß1-42 bilateral intracerebral infusion, 2 µl, 5 µg/µl) memory deficits. Activation of ADRB2 also attenuated Aß-induced mitochondrial dysfunction, as revealed by increased ATP levels, mitochondrial membrane potential (MMP/Δψm) and complex I activity. Further studies revealed that ADRB2 activation restored mitophagy deficits, as revealed by the increased light chain 3 (LC3)-II/LC3-I ratio, Atg5 levels, and Atg7 levels and decreased p62 levels, along with the upregulation of PTEN-induced putative kinase 1 (PINK1), Parkin and NAD+ levels. Activation of ADRB2 rescued Aß-induced oxidative stress and neuronal death. ADRB2 activation also attenuated Aß-induced tau hyperphosphorylation by regulating glycogen synthase kinase-3ß expression in the hippocampus. Finally, we established that Clen improved mitophagy and attenuated mitochondrial dysfunction, and tau pathology in mice by activating the ADRB2/Akt/PINK1 signaling pathway. Conversely, the inhibition of ADRB2 by propranolol (ßAR antagonist, 10 µM) blocked the Clen-mediated improvements in pathological changes in N2a cells. The results from the present study indicate that ADRB2 activation may be a therapeutic strategy for AD.

Development and Validation of a 18F-FDG PET/CT-Based Clinical Prediction Model for Estimating Malignancy in Solid Pulmonary Nodules Based on a Population With High Prevalence of Malignancy.

PURPOSE: To develop a prediction model based on 18F-fludeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) for solid pulmonary nodules (SPNs) with high malignant probability. PATIENTS AND METHODS: We retrospectively reviewed the records of CT-undetermined SPNs, which were further evaluated by PET/CT between January 2008 and December 2015. A total of 312 cases were included as a training set and 159 as a validation set. Logistic regression was applied to determine independent predictors, and a mathematical model was deduced. The area under the receiver operating characteristic curve (AUC) was compared to other models. Model fitness was assessed based on the American College of Chest Physicians guidelines. RESULTS: There were 215 (68.9%) and 127 (79.9%) malignant lesions in the training and validation sets, respectively. Eight independent predictors were identified: age [odds ratio (OR) = 1.030], male gender (OR = 0.268), smoking history (OR = 2.719), lesion diameter (OR = 1.067), spiculation (OR = 2.530), lobulation (OR = 2.614), cavity (OR = 2.847), and standardized maximum uptake value of SPNs (OR = 1.229). Our AUCs (training set, 0.858; validation set, 0.809) was better than those of previous models (Mayo: 0.685, P = .0061; Peking University People's Hospital: 0.646, P = .0180; Herder: 0.708, P = .0203; Zhejiang University: 0.757, P = .0699). The C index of the nomogram was 0.858. Our model reduced the diagnosis of indeterminate nodules (26.4% vs. 79.2%, 53.5%, 39.6%, and 34.0%, respectively) while improved sensitivity (81.3% vs. 16.4%, 49.2%, 62.5%, and 68.0%, respectively) and accuracy (65.4% vs. 16.4%, 39.6%, 52.8%, and 58.5%, respectively). CONCLUSION: Our model could permit accurate diagnoses and may be recommended to identify malignant SPNs with high malignant probability, as our data pertain to a very high-prevalence cohort only.