Online Kernel Sliced Inverse Regression

Online dimension reduction is a common method for high-dimensional streaming data processing. Online principal component analysis, online sliced inverse regression, online kernel principal component analysis and other methods have been studied in depth, but as far as we know, online supervised nonlinear dimension reduction methods have not been fully studied. In this article, an online kernel sliced inverse regression method is proposed. By introducing the approximate linear dependence condition and dictionary variable sets, we address the problem of increasing variable dimensions with the sample size in the online kernel sliced inverse regression method, and propose a reduced-order method for updating variables online. We then transform the problem into an online generalized eigen-decomposition problem, and use the stochastic optimization method to update the centered dimension reduction directions. Simulations and the real data analysis show that our method can achieve close performance to batch processing kernel sliced inverse regression

Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression

Federated learning has become a popular tool in the big data era nowadays. It trains a centralized model based on data from different clients while keeping data decentralized. In this paper, we propose a federated sparse sliced inverse regression algorithm for the first time. Our method can simultaneously estimate the central dimension reduction subspace and perform variable selection in a federated setting. We transform this federated high-dimensional sparse sliced inverse regression problem into a convex optimization problem by constructing the covariance matrix safely and losslessly. We then use a linearized alternating direction method of multipliers algorithm to estimate the central subspace. We also give approaches of Bayesian information criterion and hold-out validation to ascertain the dimension of the central subspace and the hyper-parameter of the algorithm. We establish an upper bound of the statistical error rate of our estimator under the heterogeneous setting. We demonstrate the effectiveness of our method through simulations and real world applications

The association of physical activity and sedentary behavior with depression in US adults: NHANES 2007–2018

ObjectivesDepression is largely preventable, and strategies that can effectively suppress its development are imperative. We aimed to examine whether physical activity and sedentary behavior were associated with depression and explore the possible mediatory role of complete blood count in this association.MethodsIn this cross-sectional study, data were integrated from the National Health and Nutrition Examination Study (2007–2018). Depression was defined using the Patient Health Questionnaire-9. The risk for depression, expressed as odds ratio (OR) and 95% confidence interval (CI), was quantified by survey-weighted logistic regression analyses.ResultsA total of 31,204 respondents were analyzed. Significance was identified for all, except walking or bicycling per week, types of physical activity, and sedentary behavior. Per 1 standard deviation (SD) increment in metabolic equivalent of task (MET) of weekly vigorous recreational physical activity was associated with 31.3% decreased depression risk (adjusted OR: 0.687, 95% CI: 0.5663–0.840). Per 1 SD increment in sitting time can increase depression risk by 22.4% (adjusted OR: 1.224, 95% CI: 1.131–1.325). In subsidiary analyses, the association with depression was reinforced in respondents aged ≤65 years and those overweight or obese. Mediation analyses revealed significant effects for red blood cell (RBC) on total MET (19.4%) and moderate work-related physical activity (MWPA) (22.0%), and for red cell distribution wide (RCDW) on vigorous work-related physical activity (17.7%), moderate work-related physical activity (13.1%), total MET (11.2%), and sitting time (16.4%) (p < 0.01).ConclusionOur findings indicate that more physical activity and less sitting time were associated with a lower likelihood of having depression among US adults, and this association was probably mediated by RBC and RCDW

Insights into Resistance Mechanisms of Inhibitors to Mps1 C604Y Mutation via a Comprehensive Molecular Modeling Study

Mono-polar spindle 1 (Mps1/TTK) represents a protein kinase reported to be vital for cell division processes and is generally regarded as an attractive target for the treatment of hepatocellular carcinoma, breast carcinoma, and colon cancer. However, the C604Y mutation has been linked to acquired resistance. Recently, three potential small-molecule inhibitors of Mps1 (i.e., reversine, NMS-P715, and its derivative Cpd-5) were reported for the C604Y mutation that exhibit significant resistance to NMS-P715 and Cpd-5, but retain affinity for reversine. In this study, classical molecular dynamic (MD) simulations, accelerated MD (aMD) simulations, and umbrella sampling (US) simulations were performed to illustrate the resistance mechanisms of inhibitors to Mps1. The classical MD simulations combined with free energy calculations revealed that reversine features similar binding affinity characteristics to both Mps1WT and Mps1C604Y, but both NMS-P715 and Cpd-5 feature much higher binding affinities to Mps1WT than to Mps1C604Y. The major variations were shown to be controlled by electrostatic energy and the conformational change of A-loop-induced entropy increased. The large conformational changes of Mps1C604Y bound to NMS-P715 and Cpd-5 were also observed in aMD simulations. The US simulation results further suggest that reversine and Cpd-5 both exhibit similar dissociation processes from both Mps1WT and Mps1C604Y, but Cpd-5 and NMS-P715 were found to dissociate more easily from Mps1C604Y than from Mps1WT, thus a reduced residence time was responsible for the inhibitors resistance to the C604Y mutation. The physical principles provided by the present study may provide important clues for the discovery and rational design of novel inhibitors to combat the C604Y mutation of Mps1