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9,295 result(s) for "Zhu, Qiang"
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Optimal frequency for flow energy harvesting of a flapping foil
Inspired by the correlation between the propulsion efficiency of a flapping foil propeller and stability of the wake behind it (which leads to the optimal Strouhal number for propulsion), we numerically simulated a heaving/pitching foil in energy harvesting regime, and investigated the relation between wake stability and the energy harvesting efficiency. The base flow is computed using a Navier–Stokes algorithm and the stability analysis is performed via the Orr–Sommerfeld equation. The wake is found to be convectively unstable and the frequency of the most unstable mode fw is determined. The case when fw ~ f coincides with maximum energy harvesting efficiency of the system (f is the frequency of foil oscillation), suggesting that flow energy extraction is closely related to efficient evolution of the wake. This occurs at a frequency of f ~ 0.15 (f is normalized by the chord length and the flow speed), under the constraint that there is significant vortex shedding from the leading edge at sufficiently large effective angles of attack. Indeed, this ‘foil–wake resonance’ is usually associated with multi-vortex shedding from the leading edge. Furthermore, detailed examination of energy extractions from the heaving and the pitching motions indicates that near the optimal performance point the average energy extraction from the pitching motion is close to zero. This suggests the feasibility of achieving high-efficient energy harvesting through a simple fully passive system we proposed earlier in which no activation is needed.
Targeting miR‐124/Ferroportin signaling ameliorated neuronal cell death through inhibiting apoptosis and ferroptosis in aged intracerebral hemorrhage murine model
Incidence of intracerebral hemorrhage (ICH) and brain iron accumulation increases with age. Excess iron accumulation in brain tissues post‐ICH induces oxidative stress and neuronal damage. However, the mechanisms underlying iron deregulation in ICH, especially in the aged ICH model have not been well elucidated. Ferroportin1 (Fpn) is the only identified nonheme iron exporter in mammals to date. In our study, we reported that Fpn was significantly upregulated in perihematomal brain tissues of both aged ICH patients and mouse model. Fpn deficiency induced by injecting an adeno‐associated virus (AAV) overexpressing cre recombinase into aged Fpn‐floxed mice significantly worsened the symptoms post‐ICH, including hematoma volume, cell apoptosis, iron accumulation, and neurologic dysfunction. Meanwhile, aged mice pretreated with a virus overexpressing Fpn showed significant improvement of these symptoms. Additionally, based on prediction of website tools, expression level of potential miRNAs in ICH tissues and results of luciferase reporter assays, miR‐124 was identified to regulate Fpn expression post‐ICH. Higher serum miR‐124 levels were correlated with poor neurologic scores of aged ICH patients. Administration of miR‐124 antagomir enhanced Fpn expression and attenuated iron accumulation in aged mice model. Both apoptosis and ferroptosis, but not necroptosis, were regulated by miR‐124/Fpn signaling manipulation. Our study demonstrated the critical role of miR‐124/Fpn signaling in iron metabolism and neuronal death post‐ICH in aged murine model. Thus, Fpn upregulation or miR‐124 inhibition might be promising therapeutic approachs for this disease. Brain iron accumulation following ICH induced secondary brain injury and neuronal death. However, the mechanisms underlying iron deregulation in aged ICH model is poorly understood. miR‐124/Fpn signaling was downregulated in aged ICH model mice and patients as a protection mechanism. Higher serum miR‐124 levels were correlated with poor neurologic scores of aged patients. Targeting miR‐124/Fpn signaling could reduce the iron accumulation post‐ICH in aged murine model, thus ameliorated hematoma volume, cell apoptosis and neurologic dysfunction through inhibiting apoptosis and ferroptosis.
The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives
Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.
Aged bone matrix-derived extracellular vesicles as a messenger for calcification paradox
Adipocyte differentiation of bone marrow mesenchymal stem/stromal cells (BMSCs) instead of osteoblast formation contributes to age- and menopause-related marrow adiposity and osteoporosis. Vascular calcification often occurs with osteoporosis, a contradictory association called “calcification paradox”. Here we show that extracellular vesicles derived from aged bone matrix (AB-EVs) during bone resorption favor BMSC adipogenesis rather than osteogenesis and augment calcification of vascular smooth muscle cells. Intravenous or intramedullary injection of AB-EVs promotes bone-fat imbalance and exacerbates Vitamin D3 (VD3)-induced vascular calcification in young or old mice. Alendronate (ALE), a bone resorption inhibitor, down-regulates AB-EVs release and attenuates aging- and ovariectomy-induced bone-fat imbalance. In the VD3-treated aged mice, ALE suppresses the ovariectomy-induced aggravation of vascular calcification. MiR-483-5p and miR-2861 are enriched in AB-EVs and essential for the AB-EVs-induced bone-fat imbalance and exacerbation of vascular calcification. Our study uncovers the role of AB-EVs as a messenger for calcification paradox by transferring miR-483-5p and miR-2861. This study uncovers the role of extracellular vesicles from bone matrix as a messenger in the development of osteoporosis and vascular calcification (calcification paradox) during skeletal aging and menopause by transferring miR-483-5p and miR-2861.
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.
Perspective of Thermal Analysis and Management for Permanent Magnet Machines, with Particular Reference to Hotspot Temperatures
Permanent magnet (PM) machines have been extensively used for various applications. Nevertheless, thermal effect, particularly hotspot temperature, not only severely restricts power/torque density but also leads to deteriorations in electromagnetic performance, service life, and reliability. Starting with foundations of PM machines and heat transfer mechanisms, this paper reviews the development of thermal analysis methods over the last thirty years and the state-of-the-art research achievements, and the hotspot temperatures of winding and PM are particularly evaluated. In the overview, various machine losses and cooling techniques are first introduced, which are the essential reasons for temperature rise and the most straightforward way to remove the generated heat. Afterwards, the mainstream thermal analysis techniques, i.e., numerical techniques, lumped-parameter thermal model, and hybrid thermal models, as well as the online electrical parameter-based and thermal model-based temperature monitoring techniques, are reviewed and assessed in depth. In addition, this paper also reviews the analytical thermal modelling methods for winding and PM. Finally, future research trends are highlighted.
miR-135a-5p mediates memory and synaptic impairments via the Rock2/Adducin1 signaling pathway in a mouse model of Alzheimer’s disease
Aberrant regulation of microRNAs (miRNAs) has been implicated in the pathogenesis of Alzheimer’s disease (AD), but most abnormally expressed miRNAs found in AD are not regulated by synaptic activity. Here we report that dysfunction of miR-135a-5p/Rock2/Add1 results in memory/synaptic disorder in a mouse model of AD. miR-135a-5p levels are significantly reduced in excitatory hippocampal neurons of AD model mice. This decrease is tau dependent and mediated by Foxd3. Inhibition of miR-135a-5p leads to synaptic disorder and memory impairments. Furthermore, excess Rock2 levels caused by loss of miR-135a-5p plays an important role in the synaptic disorder of AD via phosphorylation of Ser726 on adducin 1 (Add1). Blocking the phosphorylation of Ser726 on Add1 with a membrane-permeable peptide effectively rescues the memory impairments in AD mice. Taken together, these findings demonstrate that synaptic-related miR-135a-5p mediates synaptic/memory deficits in AD via the Rock2/Add1 signaling pathway, illuminating a potential therapeutic strategy for AD. Several micro RNAs have been shown to be deregulated in brain tissue or sera from individuals with Alzheimer’s disease and in AD mouse models. The authors show that miR-135a-5p is downregulated in excitatory pyramidal neurons from AD mice and that dysfunction of miR-135a-5p/Rock2/Add1 results in memory/synaptic disorder in AD.
Discrete element modeling of particles sphericity effect on sand direct shear performance
Particle surface morphology is an important factor influencing sand structure and mechanical properties. In this study, the effect of sand particle sphericity on sand direct shear performance is investigated by using the discrete element method (DEM). Two ways are adapted to simulate different approaching methods from round particles to irregular sand. The macroresponse shows that irregular sand has a higher shear strength at lower normal stress than round particles. The shape of the particle has less influence on shear strength at higher normal stress. The irregular shape of sand leads to an increase in the shear band proportion. However, the shear band proportion is not related to the sphericity. Under all conditions, particles within the shear band have a larger average rotation angle than those outside the shear band. When the particle shape approaches round (regardless of the round particle proportion and particle shape), the average rotation angle of particles within and without shear bands increase, while the coordinate number and contact anisotropy decrease.
Loss of ferroportin induces memory impairment by promoting ferroptosis in Alzheimer’s disease
Iron homeostasis disturbance has been implicated in Alzheimer’s disease (AD), and excess iron exacerbates oxidative damage and cognitive defects. Ferroptosis is a nonapoptotic form of cell death dependent upon intracellular iron. However, the involvement of ferroptosis in the pathogenesis of AD remains elusive. Here, we report that ferroportin1 (Fpn), the only identified mammalian nonheme iron exporter, was downregulated in the brains of APPswe/PS1dE9 mice as an Alzheimer’s mouse model and Alzheimer’s patients. Genetic deletion of Fpn in principal neurons of the neocortex and hippocampus by breeding Fpn fl/fl mice with NEX-Cre mice led to AD-like hippocampal atrophy and memory deficits. Interestingly, the canonical morphological and molecular characteristics of ferroptosis were observed in both Fpn fl/fl/NEXcre and AD mice. Gene set enrichment analysis (GSEA) of ferroptosis-related RNA-seq data showed that the differentially expressed genes were highly enriched in gene sets associated with AD. Furthermore, administration of specific inhibitors of ferroptosis effectively reduced the neuronal death and memory impairments induced by Aβ aggregation in vitro and in vivo. In addition, restoring Fpn ameliorated ferroptosis and memory impairment in APPswe/PS1dE9 mice. Our study demonstrates the critical role of Fpn and ferroptosis in the progression of AD, thus provides promising therapeutic approaches for this disease.
Predicting phase behavior of grain boundaries with evolutionary search and machine learning
The study of grain boundary phase transitions is an emerging field until recently dominated by experiments. The major bottleneck in the exploration of this phenomenon with atomistic modeling has been the lack of a robust computational tool that can predict interface structure. Here we develop a computational tool based on evolutionary algorithms that performs efficient grand-canonical grain boundary structure search and we design a clustering analysis that automatically identifies different grain boundary phases. Its application to a model system of symmetric tilt boundaries in Cu uncovers an unexpected rich polymorphism in the grain boundary structures. We find new ground and metastable states by exploring structures with different atomic densities. Our results demonstrate that the grain boundaries within the entire misorientation range have multiple phases and exhibit structural transitions, suggesting that phase behavior of interfaces is likely a general phenomenon. The atomic structure of grain boundary phases remains unknown and is difficult to investigate experimentally. Here, the authors use an evolutionary algorithm to computationally explore interface structures in higher dimensions and predict low-energy configurations, showing interface phases may be ubiquitous.