Statistical Inferences for Complex Dependence of Multimodal Imaging Data.

Statistical analysis of multimodal imaging data is a challenging task, since the data involves high-dimensionality, strong spatial correlations and complex data structures. In this paper, we propose rigorous statistical testing procedures for making inferences on the complex dependence of multimodal imaging data. Motivated by the analysis of multitask fMRI data in the Human Connectome Project (HCP) study, we particularly address three hypothesis testing problems: (a) testing independence among imaging modalities over brain regions, (b) testing independence between brain regions within imaging modalities, and (c) testing independence between brain regions across different modalities.

EGFL7 affects the migration of epidermal stem cells in refractory diabetic wounds by regulating Notch signaling pathway.

This study aimed to explore the role of EGFL7 in the healing process of refractory diabetic wounds. Epidermal stem cells (ESCs) were isolated from healthy mice and diabetic mice, identified by immunofluorescence, transfected with EGFL7 overexpression and silencing lentiviral vectors, and treated with Notch pathway inhibitor (DAPT). SiEGFL7 significantly inhibited the proliferation, invasion and migration of ESCs of healthy mice.

Identification of the Key Active Pharmaceutical Ingredients of Yishen Qutong Granule, A Chinese Medicine Formula, In The Treatment of Primary Lung Cancer.

Background: Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Traditional Chinese medicine (TCM) reportedly has potential therapeutic effects against LC.

Objective: This study aimed to investigate the antitumor efficacy of Yishen Qutong granule (YSQTG) in primary LC treatment, to identify its key active pharmaceutical ingredients (APIs), and to explore its possible mechanism of action.

Integrating transcriptomics and network analysis-based multiplexed drug repurposing to screen drug candidates for M2 macrophage-associated castration-resistant prostate cancer bone metastases.

Metastatic castration-resistant prostate cancer (CRPC) has long been considered to be associated with patient mortality. Among metastatic organs, bone is the most common metastatic site, with more than 90% of advanced patients developing bone metastases (BMs) before 24 months of death. Although patients were recommended to use bone-targeted drugs represented by bisphosphonates to treat BMs of CRPC, there was no significant improvement in patient survival.

Network Pharmacology and in vitro Experimental Verification on Intervention of Quercetin, Present in Chinese Medicine Yishen Qutong Granules, on Esophageal Cancer.

Objective: To explore the potential mechanism of Yishen Qutong Granules (YSQTG) for the treatment of esophageal cancer using network pharmacology and experimental research.

Methods: The effective components and molecular mechanism of YSQTG in treating esophageal cancer were expounded based on network pharmacology and molecular docking. The key compound was identified by high-performance liquid chromatography and mass spectrometry (HPLC-MS) to verify the malignant phenotype of the key compounds in the treatment of esophageal cancer.

The Molecular Mechanism of Traditional Chinese Medicine Prescription: Gu-tong Formula in Relieving Osteolytic Bone Destruction.

Bone metastasis is a common complication in patients with advanced tumors, causing pain and bone destruction and affecting their quality of life. Typically, complementary and alternative medicine (CAM), with unique theoretical guidance, has played key roles in the treatment of tumor-related diseases. Gu-tong formula (GTF), as a representative prescription of traditional Chinese medicine, has been demonstrated to be an effective clinical medication for the relief of cancer pain.

Investigating the Multitarget Mechanism of Traditional Chinese Medicine Prescription for Cancer-Related Pain by Using Network Pharmacology and Molecular Docking Approach.

Gu-tong formula (GTF) has achieved good curative effects in the treatment of cancer-related pain. However, its potential mechanisms have not been explored. We used network pharmacology and molecular docking to investigate the molecular mechanism and the effective compounds of the prescription.

Effect of Oral Chinese Medicine Combined with Western Medicine on Cancer Pain: A Meta-Analysis.

Objective: To assess the effect of oral Chinese medicine (OCM) combined with Western medicine (WM) on cancer pain.

Methods: PubMed, Embase, Cochrane Library, Clinical Trials Registry Platform, Chinese National Knowledge Infrastructure (CNKI), Wanfang and VIP databases were searched from their inception to September {dy2019}. Randomized controlled trials (RCTs) treating cancer pain by Chinese medicine (CM) combined with WM were included.

Closed Rhinoplasty with a Mushroom-Shaped Costal Cartilage Graft in East Asian Patients.

Background: The most challenging part of rhinoplasty is nasal tip management. For East Asian patients with a bulbous under projected nasal tip with thick skin, autologous cartilage is considered the gold-standard graft material to provide strong support to the nasal tip and effectively increase tip projection. The present study aimed to evaluate the outcomes of closed rhinoplasty with a mushroom-shaped costal cartilage graft in East Asian patients.

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity.

In this article, we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases. The proposed testing procedures employ maximum-type statistics and the parametric bootstrap techniques to compute the critical values. Different from the existing tests that heavily rely on the structural conditions on the unknown covariance matrices, the proposed tests allow general covariance structures of the data and therefore enjoy wide scope of applicability in practice.

Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering.

Comparing large covariance matrices has important applications in modern genomics, where scientists are often interested in understanding whether relationships (e.g., dependencies or co-regulations) among a large number of genes vary between different biological states.

LOCAL INDEPENDENCE FEATURE SCREENING FOR NONPARAMETRIC AND SEMIPARAMETRIC MODELS BY MARGINAL EMPIRICAL LIKELIHOOD.

We consider an independence feature screening technique for identifying explanatory variables that locally contribute to the response variable in high-dimensional regression analysis. Without requiring a specific parametric form of the underlying data model, our approach accommodates a wide spectrum of nonparametric and semiparametric model families. To detect the local contributions of explanatory variables, our approach constructs empirical likelihood locally in conjunction with marginal nonparametric regressions.

MARGINAL EMPIRICAL LIKELIHOOD AND SURE INDEPENDENCE FEATURE SCREENING.

We study a marginal empirical likelihood approach in scenarios when the number of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the parameters of interest are systematically examined, and we find that the marginal empirical likelihood ratio evaluated at zero can be used to differentiate whether an explanatory variable is contributing to a response variable or not. Based on this finding, we propose a unified feature screening procedure for linear models and the generalized linear models.