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"Zhao, Ren"
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The hospitality and tourism industry in ASEAN and East Asian destinations : new growth, trends, and developments
\"This new volume addresses the growing interest to understand tourism and hospitality in Southeast and South Asia, two regions that have seen tremendous growth in international tourists in recent years. It explores the current development of hospitality and tourism industry in the regions of Hong Kong, Macao and Taiwan as well as other key countries in Southeast and South Asia. The Hospitality and Tourism Industry in ASEAN and East Asian Destinations: New Growth, Trends, and Developments provides updated findings and case studies that highlight opportunities and issues of tourism and hospitality development in ASEAN. Chapters cover such diverse topics as online marketing strategies, sustainable hospitality development, diversification efforts of the tourism industry Innovations in independent hotels, wildlife tourism in urban destinations, the Vietnamese national park system, consumers' positive and negative images of certain destinations. While academicians will benefit from the updated research findings summarized by the respected scholars, hospitality professionals will also find the book a valuable source of information as the chapters delve into the most recent topical and industry focused issues.\"-- Provided by publisher.
Book
ROBUST COVARIANCE AND SCATTER MATRIX ESTIMATION UNDER HUBER’S CONTAMINATION MODEL
Covariance matrix estimation is one of the most important problems in statistics. To accommodate the complexity of modern datasets, it is desired to have estimation procedures that not only can incorporate the structural assumptions of covariance matrices, but are also robust to outliers from arbitrary sources. In this paper, we define a new concept called matrix depth and then propose a robust covariance matrix estimator by maximizing the empirical depth function. The proposed estimator is shown to achieve minimax optimal rate under Huber’s ε-contamination model for estimating covariance/scatter matrices with various structures including bandedness and sparsity.
Journal Article
Exosomal MicroRNA MiR-1246 Promotes Cell Proliferation, Invasion and Drug Resistance by Targeting CCNG2 in Breast Cancer
Background/Aims: Treatment of breast cancer remains a clinical challenge. This study aims to validate exosomal microRNA-1246 (miR-1246) as a serum biomarker for breast cancer and understand the underlying mechanism in breast cancer progression. Methods: The expression levels of endogenous and exosomal miRNAs were examined by real time PCR, and the expression level of the target protein was detected by western blot. Scanning electron and confocal microscopy were used to characterize exosomes and to study their uptake and transfer. Luciferase reporter plasmids and its mutant were used to confirm direct targeting. Furthermore, the functional significance of exosomal miR-1246 was estimated by invasion assay and cell viability assay. Results: In this study, we demonstrate that exosomes carrying microRNA can be transferred among different cell lines through direct uptake. miR-1246 is highly expressed in metastatic breast cancer MDA-MB-231 cells compared to non-metastatic breast cancer cells or non-malignant breast cells. Moreover, miR-1246 can suppress the expression level of its target gene, Cyclin-G2 (CCNG2), indicating its functional significance. Finally, treatment with exosomes derived from MDA-MB-231 cells could enhance the viability, migration and chemotherapy resistance of non-malignant HMLE cells. Conclusions: Together, our results support an important role of exosomes and exosomal miRNAs in regulating breast tumor progression, which highlights their potential for applications in miRNA-based therapeutics.
Journal Article
Deep nitrogen fertilizer placement improves the yield of summer maize (Zea mays L.) by enhancing its photosynthetic performance after silking
Background
Effective nitrogen (N) fertilizer management can improve photosynthetic performance of maize and enhance the grain yield. However, the effects of the deep placement of N on post-silking photosynthetic performance in maize and its relationship with grain filling are limited. The study was a split-plot design with N application rates as the main plots and N placement depths as sub-plots. The N application rates consisted of 225, 191.25, and 157.5 kg ha
− 1
and N placement depths consisted of 5 and 15 cm, respectively. The growth parameters, photosynthetic capacity, subcellular ultrastructure, antioxidant system in maize leaves, and grain filling characteristics were measured.
Results
Increasing the N placement depth counteracted the adverse effects of reduced N availability on the leaf area index, leaf area duration, and photosynthetic performance of plants. Compared to 225 kg N ha
− 1
applied underground at 5 cm, a 15% reduction in the N application rate at 15 cm reduced oxidative stress through the activation of antioxidative enzymes, which enabled plants to maintain their chloroplast ultrastructure, achieving 20.7% higher chlorophyll content, 7.8% higher photosynthetic rate per unit of leaf area, and 5.6% higher leaf area index during the later growth period. It also facilitated enhancing the growth rate during maximum filling and extending the active filling duration of grains.
Conclusions
Overall, reducing the recommended N application rate of 225 kg ha
− 1
by 15% but applying it at a depth of 15 cm might delay plant senescence and extend grain filling active time, improved photosynthetic performance in late growth period, and finally increased grain weight and grain yield of maize.
Journal Article
SILGGM: An extensive R package for efficient statistical inference in large-scale gene networks
Gene co-expression network analysis is extremely useful in interpreting a complex biological process. The recent droplet-based single-cell technology is able to generate much larger gene expression data routinely with thousands of samples and tens of thousands of genes. To analyze such a large-scale gene-gene network, remarkable progress has been made in rigorous statistical inference of high-dimensional Gaussian graphical model (GGM). These approaches provide a formal confidence interval or a p-value rather than only a single point estimator for conditional dependence of a gene pair and are more desirable for identifying reliable gene networks. To promote their widespread use, we herein introduce an extensive and efficient R package named SILGGM (Statistical Inference of Large-scale Gaussian Graphical Model) that includes four main approaches in statistical inference of high-dimensional GGM. Unlike the existing tools, SILGGM provides statistically efficient inference on both individual gene pair and whole-scale gene pairs. It has a novel and consistent false discovery rate (FDR) procedure in all four methodologies. Based on the user-friendly design, it provides outputs compatible with multiple platforms for interactive network visualization. Furthermore, comparisons in simulation illustrate that SILGGM can accelerate the existing MATLAB implementation to several orders of magnitudes and further improve the speed of the already very efficient R package FastGGM. Testing results from the simulated data confirm the validity of all the approaches in SILGGM even in a very large-scale setting with the number of variables or genes to a ten thousand level. We have also applied our package to a novel single-cell RNA-seq data set with pan T cells. The results show that the approaches in SILGGM significantly outperform the conventional ones in a biological sense. The package is freely available via CRAN at https://cran.r-project.org/package=SILGGM.
Journal Article
T cells, NK cells, and tumor-associated macrophages in cancer immunotherapy and the current state of the art of drug delivery systems
The immune system provides full protection for the body by specifically identifying ‘self’ and removing ‘others’; thus protecting the body from diseases. The immune system includes innate immunity and adaptive immunity, which jointly coordinate the antitumor immune response. T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are the main tumor-killing immune cells active in three antitumor immune cycle. Cancer immunotherapy focusses on activating and strengthening immune response or eliminating suppression from tumor cells in each step of the cancer-immunity cycle; thus, it strengthens the body’s immunity against tumors. In this review, the antitumor immune cycles of T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are discussed. Co-stimulatory and co-inhibitory molecules in the three activity cycles and the development of drugs and delivery systems targeting these molecules are emphasized, and the current state of the art of drug delivery systems for cancer immunotherapy are summarized.
Journal Article
Advances in Antibody-Based Immune-Stimulating Drugs: Driving Innovation in Cancer Therapy
Antibody-based immune-stimulating drugs (ABIs) represent a transformative frontier in cancer immunotherapy, designed to reshape the tumor microenvironment and overcome immune suppression. This study highlighted recent advances in ABIs, including immune-stimulating antibody conjugates (ISACs), bispecific antibodies (BsAbs), and checkpoint blockade enhancers, with a focus on their mechanisms of action, clinical advancements, and challenges. Preclinical findings revealed that ISACs effectively boost overall anti-cancer immunity by reprogramming tumor-associated macrophages, enhancing T cell activation, and engaging other immune pathways. Similarly, BsAbs effectively redirect immune cells to tumors, achieving significant tumor regression. Additionally, artificial intelligence (AI) is revolutionizing the development of ABIs by optimizing drug design, identifying novel targets, and accelerating preclinical validation, enabling personalized therapeutic strategies. Despite these advancements, significant challenges remain, including immune resistance and off-target effects. Future research should prioritize next-generation multifunctional antibodies, AI-driven innovations, and combination therapies to enhance efficacy and expand therapeutic applications. Connecting these gaps could unlock the full potential of ABIs, upgrading cancer treatment and improving outcomes for patients with refractory or resistant tumors.
Journal Article
Britanin relieves ferroptosis-mediated myocardial ischaemia/reperfusion damage by upregulating GPX4 through activation of AMPK/GSK3β/Nrf2 signalling
Ferroptosis was described as an important contributor to the myocardial ischaemia/reperfusion (MIR) injury, and britanin (Bri) was reported to exert antitumor and anti-inflammatory activities.
Our study explores the effect and mechanism of Bri on MIR damage.
The rat model of MIR was established by ligation of the left anterior descending coronary artery. Male Sprague-Dawley (SD) rats were divided into three groups: sham group (n = 6), MIR group (n = 6) and MIR + Bri group (n = 6; 50 mg/kg). Rats were intragastrically pre-treated with Bri or normal saline once daily for 3 days. To further verify the role and mechanism of Bri, H9C2 cells were subjected to hypoxia plus reoxygenation (H/R) to induce the in vitro model of MIR.
Compared with MIR rats, Bri significantly decreased infarct area (22.50% vs. 38.67%), myocardial apoptosis (23.00% vs. 41.5%), creatine phosphokinase (0.57 U/mL vs. 0.76 U/mL), and lactate dehydrogenase levels (3.18 U/mL vs. 5.17 U/mL), concomitant with alleviation of ferroptosis. Mechanistically, Bri treatment induced the activation of the adenosine monophosphate activated protein kinase (AMPK)/glycogen synthase kinase 3β (GSK3β)/nuclear factor erythroid 2-related factor 2 (Nrf2) pathway in vivo. In addition, the AMPK/GSK3β/Nrf2 pathway participated in the regulation of glutathione peroxidase 4 (GPX4) expression, and silencing of Nrf2 attenuated the effect of Bri on H/R-induced cell injury.
Bri protected against ferroptosis-mediated MIR damage by upregulating GPX4 through activation of the AMPK/GSK3β/Nrf2 signalling, suggesting that Bri might become a novel therapeutic agent for MIR.
Journal Article
Noncommutative geometry inspired black holes in Rastall gravity
Under two different metric ansatzes, the noncommutative geometry inspired black holes (NCBH) in the framework of Rastall gravity are derived and analyzed. We consider the fluid-type matter with the Gaussian-distribution smeared mass density. Taking a Schwarzschild-like metric ansatz, it is shown that the noncommutative geometry inspired Schwarzschild black hole (NCSBH) in Rastall gravity, unlike its counterpart in general relativity (GR), is not a regular black hole. It has at most one event horizon. After showing a finite maximal temperature, the black hole will leave behind a point-like massive remnant at zero temperature. Considering a more general metric ansatz and a special equation of state of the matter, we also find a regular NCBH in Rastall gravity, which has a similar geometric structure and temperature to that of NCSBH in GR.
Journal Article
Nitrogen placement at sowing affects root growth, grain yield formation, N use efficiency in maize
Aims
Grain yields of summer maize are significantly affected by different nitrogen (N) rates and depths through regulating root growth and distribution in soil. Understanding of effects of the deep placement of N on the root and shoot growth, grain yield and N use efficiency in summer maize are limited.
Methods
In this study, four N rates: 225, 191.25, 157.5 and 0 kg ha
−1
applied at four depths: 5, 10, 15, and 20 cm were studied. Soil N content, root dry weight, root length density, biomass, grain yield and N use efficiency of maize were measured.
Results
Compared to 225 kg N ha
−1
applied at a depth of 5 cm, a 15% reduction in the N application rate at a depth of 15 cm induced a larger root length density in the subsoil, as well as a larger rooting depth. It also facilitated maintaining a higher level of biomass and N accumulation during the later growth period, which increased the N assimilation of grain and enhanced grain yield by 3.9%, N recovery efficiency by 66.7%, N agronomic efficiency by 38.5%, and partial factor productivity of N by 22.1%.
Conclusions
Overall, this study demonstrates that reducing the recommended N application rate of 225 kg ha
−1
by 15% but applying it at a depth of 15 cm might be considered an efficient fertilization method that increases agricultural productivity and N use efficiency.
Journal Article