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"Zhu, Hong"
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Cancer associated-fibroblast-derived exosomes in cancer progression
To identify novel cancer therapies, the tumor microenvironment (TME) has received a lot of attention in recent years in particular with the advent of clinical successes achieved by targeting immune checkpoint inhibitors (ICIs). The TME consists of multiple cell types that are embedded in the extracellular matrix (ECM), including immune cells, endothelial cells and cancer associated fibroblasts (CAFs), which communicate with cancer cells and each other during tumor progression. CAFs are a dominant and heterogeneous cell type within the TME with a pivotal role in controlling cancer cell invasion and metastasis, immune evasion, angiogenesis and chemotherapy resistance. CAFs mediate their effects in part by remodeling the ECM and by secreting soluble factors and extracellular vesicles. Exosomes are a subtype of extracellular vesicles (EVs), which contain various biomolecules such as nucleic acids, lipids, and proteins. The biomolecules in exosomes can be transmitted from one to another cell, and thereby affect the behavior of the receiving cell. As exosomes are also present in circulation, their contents can also be explored as biomarkers for the diagnosis and prognosis of cancer patients. In this review, we concentrate on the role of CAFs-derived exosomes in the communication between CAFs and cancer cells and other cells of the TME. First, we introduce the multiple roles of CAFs in tumorigenesis. Thereafter, we discuss the ways CAFs communicate with cancer cells and interplay with other cells of the TME, and focus in particular on the role of exosomes. Then, we elaborate on the mechanisms by which CAFs-derived exosomes contribute to cancer progression, as well as and the clinical impact of exosomes. We conclude by discussing aspects of exosomes that deserve further investigation, including emerging insights into making treatment with immune checkpoint inhibitor blockade more efficient.
Journal Article
Atomistic simulation of quantum transport in nanoelectronic devices
\"Computational nanoelectronics is an emerging multi-disciplinary field covering condensed matter physics, applied mathematics, computer science, and electronic engineering. In recent decades, a few state-of-the-art software packages have been developed to carry out first-principle atomistic device simulations. Nevertheless those packages are either black boxes (commercial codes) or accessible only to very limited users (private research codes). The purpose of this book is to open one of the commercial black boxes, and to demonstrate the complete procedure from theoretical derivation, to numerical implementation, all the way to device simulation. Meanwhile the affiliated source code constitutes an open platform for new researchers. This is the first book of its kind. We hope the book will make a modest contribution to the field of computational nanoelectronics\"-- Provided by publisher.
Book
PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction
In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases. Instead of only depending on expensive and time-consuming biological experiments, computational prediction models are effective by predicting potential miRNA-disease associations, prioritizing candidate miRNAs for the investigated diseases, and selecting those miRNAs with higher association probabilities for further experimental validation. In this study, Path-Based MiRNA-Disease Association (PBMDA) prediction model was proposed by integrating known human miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases. This model constructed a heterogeneous graph consisting of three interlinked sub-graphs and further adopted depth-first search algorithm to infer potential miRNA-disease associations. As a result, PBMDA achieved reliable performance in the frameworks of both local and global LOOCV (AUCs of 0.8341 and 0.9169, respectively) and 5-fold cross validation (average AUC of 0.9172). In the cases studies of three important human diseases, 88% (Esophageal Neoplasms), 88% (Kidney Neoplasms) and 90% (Colon Neoplasms) of top-50 predicted miRNAs have been manually confirmed by previous experimental reports from literatures. Through the comparison performance between PBMDA and other previous models in case studies, the reliable performance also demonstrates that PBMDA could serve as a powerful computational tool to accelerate the identification of disease-miRNA associations.
Journal Article
Gravitational memory effects and Bondi-Metzner-Sachs symmetries in scalar-tensor theories
A
bstract
The relation between gravitational memory effects and Bondi-Metzner-Sachs symmetries of the asymptotically flat spacetimes is studied in the scalar-tensor theory. For this purpose, the solutions to the equations of motion near the future null infinity are obtained in the generalized Bondi-Sachs coordinates with a suitable determinant condition. It turns out that the Bondi-Metzner-Sachs group is also a semi-direct product of an infinite dimensional supertranslation group and the Lorentz group as in general relativity. There are also degenerate vacua in both the tensor and the scalar sectors in the scalar-tensor theory. The supertranslation relates the vacua in the tensor sector, while in the scalar sector, it is the Lorentz transformation that transforms the vacua to each other. So there are the tensor memory effects similar to the ones in general relativity, and the scalar memory effect, which is new. The evolution equations for the Bondi mass and angular momentum aspects suggest that the null energy fluxes and the angular momentum fluxes across the null infinity induce the transition among the vacua in the tensor and the scalar sectors, respectively.
Journal Article
Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water
Nature uses organic molecules for light harvesting and photosynthesis, but most man-made water splitting catalysts are inorganic semiconductors. Organic photocatalysts, while attractive because of their synthetic tunability, tend to have low quantum efficiencies for water splitting. Here we present a crystalline covalent organic framework (COF) based on a benzo-bis(benzothiophene sulfone) moiety that shows a much higher activity for photochemical hydrogen evolution than its amorphous or semicrystalline counterparts. The COF is stable under long-term visible irradiation and shows steady photochemical hydrogen evolution with a sacrificial electron donor for at least 50 hours. We attribute the high quantum efficiency of fused-sulfone-COF to its crystallinity, its strong visible light absorption, and its wettable, hydrophilic 3.2 nm mesopores. These pores allow the framework to be dye-sensitized, leading to a further 61% enhancement in the hydrogen evolution rate up to 16.3 mmol g−1 h−1. The COF also retained its photocatalytic activity when cast as a thin film onto a support.
Journal Article
Precision cosmology from future lensed gravitational wave and electromagnetic signals
The standard siren approach of gravitational wave cosmology appeals to the direct luminosity distance estimation through the waveform signals from inspiralling double compact binaries, especially those with electromagnetic counterparts providing redshifts. It is limited by the calibration uncertainties in strain amplitude and relies on the fine details of the waveform. The Einstein telescope is expected to produce 10
4
–10
5
gravitational wave detections per year, 50–100 of which will be lensed. Here, we report a waveform-independent strategy to achieve precise cosmography by combining the accurately measured time delays from strongly lensed gravitational wave signals with the images and redshifts observed in the electromagnetic domain. We demonstrate that just 10 such systems can provide a Hubble constant uncertainty of 0.68% for a flat lambda cold dark matter universe in the era of third-generation ground-based detectors.
Gravitational wave sources can be used as cosmological probes through a direct distance luminosity relation. Here, the authors demonstrate that the time delay between lensed gravitational wave signals and their electromagnetic counterparts can reduce the uncertainty in the Hubble constant.
Journal Article
Reconstructed covalent organic frameworks
Covalent organic frameworks (COFs) are distinguished from other organic polymers by their crystallinity
1
–
3
, but it remains challenging to obtain robust, highly crystalline COFs because the framework-forming reactions are poorly reversible
4
,
5
. More reversible chemistry can improve crystallinity
6
–
9
, but this typically yields COFs with poor physicochemical stability and limited application scope
5
. Here we report a general and scalable protocol to prepare robust, highly crystalline imine COFs, based on an unexpected framework reconstruction. In contrast to standard approaches in which monomers are initially randomly aligned, our method involves the pre-organization of monomers using a reversible and removable covalent tether, followed by confined polymerization. This reconstruction route produces reconstructed COFs with greatly enhanced crystallinity and much higher porosity by means of a simple vacuum-free synthetic procedure. The increased crystallinity in the reconstructed COFs improves charge carrier transport, leading to sacrificial photocatalytic hydrogen evolution rates of up to 27.98 mmol h
−1
g
−1
. This nanoconfinement-assisted reconstruction strategy is a step towards programming function in organic materials through atomistic structural control.
A protocol in which monomers are pre-organized using a reversible and removable urea linkage enables the production of covalent organic frameworks with higher crystallinity and porosity than those produced using standard approaches with randomly aligned monomers.
Journal Article
High-performance particulate matter including nanoscale particle removal by a self-powered air filter
Particulate matter (PM) pollutants, including nanoscale particles (NPs), have been considered serious threats to public health. In this work, a self-powered air filter that can be used in high-efficiency removal of PM, including NPs, is presented. An ionic liquid–polymer (ILP) composite is irregularly distributed onto a sponge network to form an ILP@MF filter. Enabled by its unique electrochemical properties, the ILP@MF filter can remove PM
2.5
and PM
10
with high efficiencies of 99.59% and 99.75%, respectively, after applying a low voltage. More importantly, the charged ILP@MF filter realizes a superior removal for NPs with an efficiency of 93.77%. A micro-button lithium cell or silicon-based solar panel is employed as a power supply platform to fabricate a portable and self-powered face mask, which exhibits excellent efficacy in particulate removal compared to commercial masks. This work shows a great promise for high-performance purification devices and facile mask production to remove particulate pollutants.
Particulate matter (PM) pollutants have been considered serious threats to public health but effective removal of nanoscale particles (NPs) by filter materials is challenging. Here, the authors fabricate an ionic liquid based self-powered air filter that can be used in high-efficiency removal of PM, including NPs.
Journal Article
Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study
Background
Evidence from observational studies and clinical trials suggests that the gut microbiota is associated with cancer. However, the causal association between gut microbiota and cancer remains to be determined.
Methods
We first identified two sets of gut microbiota based on phylum, class, order, family, and genus level information, and cancer data were obtained from the IEU Open GWAS project. We then performed two-sample Mendelian randomisation (MR) to determine whether the gut microbiota is causally associated with eight cancer types. Furthermore, we performed a bi-directional MR analysis to examine the direction of the causal relations.
Results
We identified 11 causal relationships between genetic liability in the gut microbiome and cancer, including those involving the genus
Bifidobacterium
. We found 17 strong associations between genetic liability in the gut microbiome and cancer. Moreover, we found 24 associations between genetic liability in the gut microbiome and cancer using multiple datasets.
Conclusions
Our MR analysis revealed that the gut microbiota was causally associated with cancers and may be useful in providing new insights for further mechanistic and clinical studies of microbiota-mediated cancer.
Journal Article