Joint Modeling of Longitudinal Imaging and Survival Data

This article considers a joint modeling framework for simultaneously examining the dynamic pattern of longitudinal and ultrahigh-dimensional images and their effects on the survival of interest. A functional mixed effects model is considered to describe the trajectories of longitudinal images. Then, a high-dimensional functional principal component analysis (HD-FPCA) is adopted to extract the principal eigenimages to reduce the ultrahigh dimensionality of imaging data. Finally, a Cox regression model is used to examine the effects of the longitudinal images and other risk factors on the hazard. A theoretical justification shows that a naive two-stage procedure that separately analyzes each part of the joint model produces biased estimation even if the longitudinal images have no measurement error. We develop a Bayesian joint estimation method coupled with efficient Markov chain Monte Carlo sampling schemes to perform statistical inference for the proposed joint model. A Monte Carlo dynamic prediction procedure is proposed to predict the future survival probabilities of subjects given their historical longitudinal images. The proposed model is assessed through extensive simulation studies and an application to Alzheimer’s Disease Neuroimaging Initiative, which turns out to hold the promise of accuracy and possess higher predictive capacity for survival outcome compared with existing methods. Supplementary materials for this article are available online.</p

Nickel-Catalyzed C(sp³)–C(sp³) Cross-Electrophile Coupling of In Situ Generated NHP Esters with Unactivated Alkyl Bromides

The formation of C­(sp3)–C­(sp3) bonds by cross-coupling remains a challenge in synthesis. Here, we demonstrate a two-step, one-pot protocol for the in situ generation of N-hydroxyphthalimide esters and their nickel-catalyzed cross-electrophile coupling with unactivated alkyl bromides for the construction of 1°/1 ° C­(sp3)–C­(sp3) bonds. The conditions tolerate an array of functional groups, and mechanistic studies indicate that both substrates are converted to alkyl radicals during the reaction

ProtRAP: Predicting Lipid Accessibility Together with Solvent Accessibility of Proteins in One Run

Solvent accessibility has been extensively used to characterize and predict the chemical properties of the surface residues of soluble proteins. However, there is not yet a widely accepted quantity of the same dimension for the study of lipid-accessible residues of membrane proteins. In this study, we propose that lipid accessibility, defined in a similar way to solvent accessibility, can be used to characterize the lipid-accessible residues of membrane proteins. Moreover, we developed a deep learning-based method, ProtRAP (Protein Relative Accessibility Predictor), to predict the relative lipid accessibility and relative solvent accessibility of residues from a given protein sequence, which can infer which residues are likely accessible to lipids, accessible to solvent, or buried in the protein interior in one run

Impact of carbon cap and carbon credit prices on environmental objective.

Impact of carbon cap and carbon credit prices on environmental objective.</p

Typical Pareto solutions of inventory allocation planning problem.

Typical Pareto solutions of inventory allocation planning problem.</p

The levels for each of the parameters.

The levels for each of the parameters.</p

Impact of carbon emission.

(A) Environmental cost under different carbon caps. (B) Floating of environmental cost with different carbon credit prices.</p

Results of Taguchi experiments.

(A) SNR graph from the Taguchi experiments. (B) Mean graph from Taguchi experiments.</p

The flow of materials in supplier–manufacturer network.

The flow of materials in supplier–manufacturer network.</p