Insulin-Like Growth Factor, Inflammation, and MRI Markers of Alzheimer's Disease in Predominantly Middle-Aged Adults.

BACKGROUND: Insulin-like growth factor 1 (IGF-1) signaling has been implicated in Alzheimer's disease pathogenesis, and further evidence suggests inflammation can be a moderator of this association. However, most research to date has been conducted on older adults. OBJECTIVE: To investigate the association of serum IGF-1 and IGF binding protein 3 (IGFBP-3) concentrations with MRI markers of Alzheimer's disease in predominantly middle-aged adults, and further assess moderation by chronic inflammation. METHODS: We included participants from the Framingham Heart Study (n = 1,852, mean age 46±8, 46% men) and the Study of Health in Pomerania (n = 674, mean age 50±13, 42% men) with available serum IGF-1, IFGBP-3, as well as brain MRI. IGF-1 and IFGBP-3 were related to MRI outcomes (i.e., total brain, cortical gray matter, white matter, white matter hyperintensities (WMH), and hippocampal volumes) using multivariable regression models adjusting for potential confounders. Subgroup analyses by C-reactive protein (CRP) concentrations were also performed. Cohort-specific summary statistics were meta-analyzed using random-effects models and corrected for multiple comparisons. RESULTS: Meta-analysis results revealed that higher IGF-1 concentrations were associated with lower WMH (estimate [ß] [95% CI], -0.05 [-0.09, -0.02], p = 0.006) and larger hippocampal volumes (0.07 [0.02, 0.12], p = 0.01), independent of vascular risk factors. These associations occurred predominantly in individuals with CRP concentrations < 75th percentile. We did not observe associations between IGFBP-3 and MRI outcomes. CONCLUSION: Our findings suggest that IGF-1-related signaling may be implicated in brain health as early as midlife.

Investigating response time and accuracy in online classifier learning for multimedia publish-subscribe systems.

The enormous growth of multimedia content in the field of the Internet of Things (IoT) leads to the challenge of processing multimedia streams in real-time. Event-based systems are constructed to process event streams. They cannot natively consume multimedia event types produced by the Internet of Multimedia Things (IoMT) generated data to answer multimedia-based user subscriptions. Machine learning-based techniques have enabled rapid progress in solving real-world problems and need to be optimised for the low response time of the multimedia event processing paradigm. In this paper, we describe a classifier construction approach for the training of online classifiers, that can handle dynamic subscriptions with low response time and provide reasonable accuracy for the multimedia event processing. We find that the current object detection methods can be configured dynamically for the construction of classifiers in real-time, by tuning hyperparameters even when training from scratch. Our experiments demonstrate that deep neural network-based object detection models, with hyperparameter tuning, can improve the performance within less training time for the answering of previously unknown user subscriptions. The results from this study show that the proposed online classifier training based model can achieve accuracy of 79.00% with 15-min of training and 84.28% with 1-hour training from scratch on a single GPU for the processing of multimedia events.

Identification of Inhibitors of Integrin Cytoplasmic Domain Interactions With Syk.

Leukocyte inflammatory responses require integrin cell-adhesion molecule signaling through spleen tyrosine kinase (Syk), a non-receptor kinase that binds directly to integrin ß-chain cytoplasmic domains. Here, we developed a high-throughput screen to identify small molecule inhibitors of the Syk-integrin cytoplasmic domain interactions. Screening small molecule compound libraries identified the ß-lactam antibiotics cefsulodin and ceftazidime, which inhibited integrin ß-subunit cytoplasmic domain binding to the tandem SH2 domains of Syk (IC50 range, 1.02-4.9 µM). Modeling suggested antagonist binding to Syk outside the pITAM binding site. Ceftazidime inhibited integrin signaling via Syk, including inhibition of adhesion-dependent upregulation of interleukin-1ß and monocyte chemoattractant protein-1, but did not inhibit ITAM-dependent phosphorylation of Syk mediated by FcγRI signaling. Our results demonstrate a novel means to target Syk independent of its kinase and pITAM binding sites such that integrin signaling via this kinase is abrogated but ITAM-dependent signaling remains intact. As integrin signaling through Syk is essential for leukocyte activation, this may represent a novel approach to target inflammation.