Functional regression models in the frame work of reproducing kernel Hilbert space

The aim of this thesis is to systematically investigate some functional regression models for accurately quantifying the effect of functional predictors. In particular, three functional models are studied: functional linear regression model, functional Cox model, and function-on-scalar model. Both theoretical properties and numerical algorithms are studied in depth. The new models find broad applications in many areas. For the functional linear regression model, the focus is on testing the nullity of the slope function, and a generalized likelihood ratio test based on easily implementable data-driven estimate is proposed. The quality of the test is measured by the minimal distance between the null and the alternative space that still allows a possible test. The lower bound of the minimax decay rate of this distance is derived, and test with a distance that decays faster than the lower bound would be impossible. It is shown that the minimax optimal rate is jointly determined by the reproducing kernel and the covariance kernel and our test attains this optimal rate. Later, the test is applied to the effect of the trajectories of oxides of nitrogen (NOx) on the level of ozone (O3). In the functional Cox model, the aim is to study the Cox model with right-censored data in the presence of both functional and scalar covariates. Asymptotic properties of the maximum partial likelihood estimator is established and it is shown that the estimator achieves the minimax optimal rate of convergence under a weighted L2-risk. Implementation of the estimation approach and the selection of the smoothing parameter are discussed in detail. The finite sample performance is illustrated by simulated examples and a real application. The function-on-scalar model concentrates on developing the simultaneous model selection and estimation technique. A novel regularization method called the Grouped Smoothly Clipped Absolute Deviation (GSCAD) is proposed. The initial problem can be transferred into a dictionary learning problem, where the GSCAD can be directly applied to simultaneously learn a sparse dictionary and select the appropriate dictionary size. Efficient algorithm is designed based on the alternative direction method of multipliers (ADMM) which decomposes the joint non-convex problem with the non-convex penalty into two convex optimization problems. Several examples are presented for image denoising and image inpainting, which are competitive with the state of the art methods

Mapping global acceptance and uptake of COVID-19 vaccination: A systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic exit strategies depend on widespread acceptance of COVID-19 vaccines. We aim to estimate the global acceptance and uptake of COVID-19 vaccination, and their variations across populations, countries, time, and sociodemographic subgroups. METHODS: We searched four peer-reviewed databases (PubMed, EMBASE, Web of Science, and EBSCO) for papers published in English from December 1, 2019 to February 27, 2022. This review included original survey studies which investigated acceptance or uptake of COVID-19 vaccination, and study quality was assessed using the Appraisal tool for Cross-Sectional Studies. We reported the pooled acceptance or uptake rates and 95% confidence interval (CI) using meta-analysis with a random-effects model. RESULTS: Among 15690 identified studies, 519 articles with 7,990,117 participants are eligible for meta-analysis. The global acceptance and uptake rate of COVID-19 vaccination are 67.8% (95% CI: 67.1-68.6) and 42.3% (95% CI: 38.2-46.5), respectively. Among all population groups, pregnant/breastfeeding women have the lowest acceptance (54.0%, 46.3-61.7) and uptake rates (7.3%, 1.7-12.8). The acceptance rate varies across countries, ranging from 35.9% (34.3-37.5) to 86.9% (81.4-92.5) for adults, and the lowest acceptance is found in Russia, Ghana, Jordan, Lebanon, and Syria (below 50%). The acceptance rate declines globally in 2020, then recovers from December 2020 to June 2021, and further drops in late 2021. Females, those aged < 60 years old, Black individuals, those with lower education or income have the lower acceptance than their counterparts. There are large gaps (around 20%) between acceptance and uptake rates for populations with low education or income. CONCLUSION: COVID-19 vaccine acceptance needs to be improved globally. Continuous vaccine acceptance monitoring is necessary to inform public health decision making

Self‐Assembly of Therapeutic Peptide into Stimuli‐Responsive Clustered Nanohybrids for Cancer‐Targeted Therapy

Clinical translation of therapeutic peptides, particularly those targeting intracellular protein–protein interactions (PPIs), has been hampered by their inefficacious cellular internalization in diseased tissue. Therapeutic peptides engineered into nanostructures with stable spatial architectures and smart disease targeting ability may provide a viable strategy to overcome the pharmaceutical obstacles of peptides. This study describes a strategy to assemble therapeutic peptides into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to tumor microenvironment. As a proof of concept, an anticancer peptide termed β‐catenin/Bcl9 inhibitors is copolymerized with gold ion and assembled into a cluster of nanohybrids (pCluster). Through a battery of in vitro and in vivo tests, it is demonstrated that pClusters potently inhibit tumor growth and metastasis in several animal models through the impairment of the Wnt/β‐catenin pathway, while maintaining a highly favorable biosafety profile. In addition, it is also found that pClusters synergize with the PD1/PD‐L1 checkpoint blockade immunotherapy. This new strategy of peptide delivery will likely have a broad impact on the development of peptide‐derived therapeutic nanomedicine and reinvigorate efforts to discover peptide drugs that target intracellular PPIs in a great variety of human diseases, including cancer.A strategy for clinical translation of therapeutic peptides by assembling them into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to the tumor microenvironment, is presented. An anticancer peptide termed β‐catenin/Bcl9 inhibitor is assembled into a cluster of nanohybrids termed pCluster, which potently inhibits tumor growth as well as metastasis, and synergizes with immunotherapy, while maintaining a highly favorable biosafety profile.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/1/adfm201807736.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/2/adfm201807736-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/3/adfm201807736_am.pd

Rapid inactivation of human respiratory RNA viruses by deep ultraviolet irradiation from light-emitting diodes on a high-temperature-annealed AlN/Sapphire template

Efficient and eco-friendly disinfection of air-borne human respiratory RNA viruses is pursued in both public environment and portable usage. The AlGaN-based deep ultraviolet (DUV) light-emission diode (LED) has high practical potentials because of its advantages of variable wavelength, rapid sterilization, environmental protection, and miniaturization. Therefore, whether the emission wavelength has effects on the disinfection as well as whether the device is feasible to sterilize various respiratory RNA viruses under portable conditions is crucial. Here, we fabricate AlGaN-based DUV LEDs with different wavelength on high-temperature-annealed (HTA) AlN/Sapphire templates and investigate the inactivation effects for several respiratory RNA viruses. The AlN/AlGaN superlattices are employed between the template and upper n-AlGaN to release the strong compressive stress (SCS), improving the crystal quality and interface roughness. DUV LEDs with the wavelength of 256, 265, and 278 nm, corresponding to the light output power of 6.8, 9.6, and 12.5 mW, are realized, among which the 256 nm-LED shows the most potent inactivation effect in human respiratory RNA viruses, including SARS-CoV-2, influenza A virus (IAV), and human parainfluenza virus (HPIV), at a similar light power density (LPD) of ~0.8 mW/cm2 for 10 s. These results will contribute to the advanced DUV LED application of disinfecting viruses with high potency and broad spectrum in a portable and eco-friendly use

Radix Scutellariae Ameliorates Stress-Induced Depressive-Like Behaviors via Protecting Neurons through the TGFβ3-Smad2/3-Nedd9 Signaling Pathway

Chronic stress can impair hippocampal neurogenesis, increase neuronal apoptosis, and cause depressive-like behaviors. Our previous studies found that Radix Scutellariae (RS) can rescue the stress-induced neuronal injury, but the mechanism is not clear. Here, we continued to investigate the underlying antidepressant mechanisms of the RS extract. A 7-week chronic unpredictable mild stress (CUMS) procedure was used to establish a murine depression model. 0.75 g/kg or 1.5 g/kg RS was administered daily to the mice during the last 4 weeks. Depressive-like behaviors were evaluated by the sucrose preference test (SPT), forced swimming test (FST), open field test (OFT), and tail suspension test (TST). The neuroprotective effect of RS was evaluated with the expression of hippocampal neuron-related markers and apoptosis-associated proteins by Nissl staining, immunohistochemistry, and western blot. Transforming growth factor-β3 (TGFβ3) pathway-related proteins were detected by western blot. Results showed that RS could ameliorate depressive-like behaviors, increase the expression of the antiapoptotic protein B-cell lymphoma 2 (BCL-2), reduce the expression of the proapoptotic protein BCL-2-associated X (BAX), and increase the number of doublecortin- (DCX-), microtubule-associated protein 2- (MAP2-), and neuronal nucleus- (NeuN-) positive cells in the hippocampus. Moreover, RS could reverse the CUMS-induced decrease of TGFβ3 protein, promote the phosphorylation of SMAD2/3, and increase the expression of downstream NEDD9 protein. These results suggest that RS could exert antidepressant effects via protecting neurons. And the molecular mechanism might be related to the regulation of the TGFβ3-SMAD2/3-NEDD9 pathway