Background and Aims
No effective treatments are available for liver fibrosis. Angiogenesis is deeply involved in liver fibrogenesis. However, current controversial results suggest it is difficult to ...treat liver fibrosis through vascular targeting. There are three different microvessels in liver: portal vessels, liver sinusoids, and central vessels. The changes and roles for each of the three different vessels during liver fibrogenesis are unclear. We propose that they play different roles during liver fibrogenesis, and a single vascular endothelial cell (EC) regulator is not enough to fully regulate these three vessels to treat liver fibrosis. Therefore, a combined regulation of multiple different EC regulatory signaling pathway may provide new strategies for the liver fibrosis therapy. Herein, we present a proof‐of‐concept strategy by combining the regulation of leukocyte cell‐derived chemotaxin 2 (LECT2)/tyrosine kinase with immunoglobulin‐like and epidermal growth factor–like domains 1 signaling with that of vascular endothelial growth factor (VEGF)/recombinant VEGF (rVEGF) signaling.
Approach and Results
The CCl4‐induced mouse liver fibrosis model and NASH model were both used. During fibrogenesis, vascular changes occurred at very early stage, and different liver vessels showed different changes and played different roles: decreased portal vessels, increased sinusoid capillarization and the increased central vessels the increase of portal vessels alleviates liver fibrosis, the increase of central vessels aggravates liver fibrosis, and the increase of sinusoid capillarization aggravates liver fibrosis. The combinational treatment of adeno‐associated viral vector serotype 9 (AAV9)–LECT2–short hairpin RNA (shRNA) and rVEGF showed improved therapeutic effects, but it led to serious side effects. The combination of AAV9‐LECT2‐shRNA and bevacizumab showed both improved therapeutic effects and decreased side effects.
Conclusions
Liver vascular changes occurred at very early stage of fibrogenesis. Different vessels play different roles in liver fibrosis. The combinational treatment of AAV9‐LECT2‐shRNA and bevacizumab could significantly improve the therapeutic effects on liver fibrosis.
The aim of this study was to investigate the prevalence of sleep problems, depression and anxiety symptoms among conscripted frontline nurses fighting coronavirus disease 2019 (COVID-19) in ...Wuhan.This study was a cross-sectional study conducted with 100 frontline nurses. Sleep quality, depression, and anxiety symptoms were measured using the Pittsburgh sleep quality index (PSQI), the Generalized Anxiety Disorder 7-Item Scale (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9), respectively.Mean sleep duration was 5.71 hours (SD = 1.09) and mean sleep latency was 33.49 minutes (SD = 28.87). A total of 76%, 81%, 45%, and 19% reported difficulty initiating sleep (DIS), difficulty maintaining sleep (DMS) or early morning awakening (EMA), nightmares and using hypnotics respectively. Among 100 participants in this study, 60 (60%) had poor sleep quality, 46 (46%) suffered depression symptoms and 40 (40%) reported anxiety symptoms. Sleep quality (OR = 3.16, 95% CI: 1.17-8.52) and anxiety symptoms (OR = 8.07, 95% CI: 2.92-22.33) were significantly associated with depression symptoms. Depression symptoms (OR = 7.92, 95% CI: 2.89-21.73) were related to anxiety symptoms. Similarly, depression symptoms (OR = 3.24, 95% CI: 1.19-8.79) were associated with poor sleep quality.Sleep disturbance, depression, and anxiety symptoms are very common among frontline nurses who treating patients with COVID-19 in Wuhan, China. Comprehensive measures that involve psychosocial and personal behaviors should be implemented to improve sleep quality and prevent depression and anxiety symptoms.
Synaptic loss is an early pathological event in Alzheimer’s disease (AD), but its underlying molecular mechanisms remain largely unknown. Recently, microRNAs (miRNAs) have emerged as important ...modulators of synaptic function and memory.
We used miRNA array and quantitative polymerase chain reaction to examine the alteration of miRNAs in AD mice and patients as well as the Morris water maze to evaluate learning and memory in the mice. We also used adeno-associated virus or lentivirus to introduce tyrosine-protein phosphatase non-receptor type 1 (PTPN1) expression of silencing RNAs. Long-term potentiation and Golgi staining were used to evaluate the synaptic function and structure. We designed a peptide to interrupt miR-124/PTPN1 interaction.
Here we report that neuronal miR-124 is dramatically increased in the hippocampus of Tg2576 mice, a recognized AD mouse model. Similar changes were observed in specific brain regions of affected AD individuals. We further identified PTPN1 as a direct target of miR-124. Overexpression of miR-124 or knockdown of PTPN1 recapitulated AD-like phenotypes in mice, including deficits in synaptic transmission and plasticity as well as memory by impairing the glutamate receptor 2 membrane insertion. Most importantly, rebuilding the miR-124/PTPN1 pathway by suppression of miR-124, overexpression of PTPN1, or application of a peptide that disrupts the miR-124/PTPN1 interaction could restore synaptic failure and memory deficits.
Taken together, these results identified the miR-124/PTPN1 pathway as a critical mediator of synaptic dysfunction and memory loss in AD, and the miR-124/PTPN1 pathway could be considered as a promising novel therapeutic target for AD patients.
For a long time, hydrogen sulfide (H
S) has been considered as merely a toxic by product of cell metabolism, but nowadays is emerging as a novel gaseous signal molecule, which participates in seed ...germination, plant growth and development, as well as the acquisition of stress tolerance including cross-adaptation in plants. Cross-adaptation, widely existing in nature, is the phenomenon in which plants expose to a moderate stress can induce the resistance to other stresses. The mechanism of cross-adaptation is involved in a complex signal network consisting of many second messengers such as Ca
, abscisic acid, hydrogen peroxide and nitric oxide, as well as their crosstalk. The cross-adaptation signaling is commonly triggered by moderate environmental stress or exogenous application of signal molecules or their donors, which in turn induces cross-adaptation by enhancing antioxidant system activity, accumulating osmolytes, synthesizing heat shock proteins, as well as maintaining ion and nutrient balance. In this review, based on the current knowledge on H
S and cross-adaptation in plant biology, H
S homeostasis in plant cells under normal growth conditions; H
S signaling triggered by abiotic stress; and H
S-induced cross-adaptation to heavy metal, salt, drought, cold, heat, and flooding stress were summarized, and concluded that H
S might be a candidate signal molecule in plant cross-adaptation. In addition, future research direction also has been proposed.
Population growth and industrial development have exacerbated environmental pollution of both land and aquatic environments with toxic and harmful materials. Luminescence-based chemical sensors ...crafted for specific hazardous substances operate on host-guest interactions, leading to the detection of target molecules down to the nanomolar range. Particularly, the luminescence-based sensors constructed on the basis of metal-organic frameworks (MOFs) are of increasing interest, as they can not only compensate for the shortcomings of traditional detection techniques, but also can provide more sensitive detection for analytes. Recent years have seen MOFs-based fluorescent sensors show outstanding advantages in the field of hazardous substance identification and detection. Here, we critically discuss the application of MOFs for the detection of a broad scope of hazardous substances, including hazardous gases, heavy metal ions, radioactive ions, antibiotics, pesticides, nitro-explosives, and some harmful solvents as well as luminous and sensing mechanisms of MOF-based fluorescent sensors. The outlook and several crucial issues of this area are also discussed, with the expectation that it may help arouse widespread attention on exploring fluorescent MOFs (LMOFs) in potential sensing applications.
Sodium dual‐ion batteries (Na‐DIBs) have attracted increasing attention due to their high operative voltages and low‐cost raw materials. However, the practical applications of Na‐DIBs are still ...hindered by the issues, such as low capacity and poor Coulombic efficiency, which is highly correlated with the compatibility between electrode and electrolyte but rarely investigated. Herein, fluoroethylene carbonate (FEC) is introduced into the electrolyte to regulate cation/anion solvation structure and the stability of cathode/anode‐electrolyte interphase of Na‐DIBs. The FEC modulates the environment of PF6− solvation sheath and facilitates the interaction of PF6− on graphite. In addition, the NaF‐rich interphase caused by the preferential decomposition of FEC effectively inhibits side reactions and pulverization of anodes with the electrolyte. Consequently, Sb||graphite full cells in FEC‐containing electrolyte achieve an improved capacity, cycling stability and Coulombic efficiency. This work elucidates the underlying mechanism of bifunctional FEC and provides an alternative strategy of building high‐performance dual ion batteries.
With the addition of FEC, a robust electrode‐electrolyte interphase formed on the surface of Sb anode and graphite cathode, inhibiting the pulverization of Sb and the expansion of graphite. The formation of FEC‐rich anions solvation structure facilitates the insertion of PF6−, which significantly improves the reversible capacity. Thus, guaranteeing the greatly enhanced performance of high voltage and power density Sb||graphite dual‐ion batteries.
Multi-label support vector machine (Rank-SVM) is a classic and effective algorithm for multi-label classification. The pivotal idea is to maximize the minimum margin of label pairs, which is extended ...from SVM. However, recent studies disclosed that maximizing the minimum margin does not necessarily lead to better generalization performance, and instead, it is more crucial to optimize the margin distribution. Inspired by this idea, in this paper, we first introduce margin distribution to multi-label learning and propose multi-label Optimal margin Distribution Machine (mlODM), which optimizes the margin mean and variance of all label pairs efficiently. Extensive experiments in multiple multi-label evaluation metrics illustrate that mlODM outperforms SVM-style multi-label methods. Moreover, empirical study presents the best margin distribution and verifies the fast convergence of our method.
Developing a precise and reproducible bandgap tuning method that enables tailored design of materials is of crucial importance for optoelectronic devices. Towards this end, we report a sphere ...diameter engineering (SDE) technique to manipulate the bandgap of two-dimensional (2D) materials. A one-to-one correspondence with an ideal linear working curve is established between the bandgap of MoS
and the sphere diameter in a continuous range as large as 360 meV. Fully uniform bandgap tuning of all the as-grown MoS
crystals is realized due to the isotropic characteristic of the sphere. More intriguingly, both a decrease and an increase of the bandgap can be achieved by constructing a positive or negative curvature. By fusing individual spheres in the melted state, post-synthesis bandgap adjustment of the supported 2D materials can be realized. This SDE technique, showing good precision, uniformity and reproducibility with high efficiency, may further accelerate the potential applications of 2D materials.
The learnware paradigm was recently proposed by Zhou (
2016
) with the wish of developing the learnware market to help users build models more efficiently by reusing existing well-performed models ...rather than starting from scratch. Specifically, a learnware in the learnware market is a well-performed pre-trained model with a specification describing its specialty and utility, and the market identifies helpful learnware(s) for the user’s task based on the specification. Recent studies have attempted to realize a homogeneous prototype learnware market initially through Reduced Kernel Mean Embedding (RKME) specification, which requires all models in the market to share the same feature space. However, this limits the application scope of the learnware paradigm because various pre-trained models are often obtained from different feature spaces in real-world scenarios. In this paper, we make the first attempt to enable the learnware to handle heterogeneous feature spaces. We propose a more powerful specification to manage heterogeneous learnwares by integrating subspace learning in the specification design, along with a practical approach for identifying and reusing helpful learnwares for the user’s task. Empirical studies on both synthetic data and real-world tasks validate the efficacy of our approach.
Metasurfaces, composed of 2-D planar arrays of sub-wavelength metallic or dielectric scatterers, have provided unprecedented freedoms in manipulating electromagnetic (EM) waves upon interfaces. The ...development of metasurface has always been closely related to antennas. On the one hand, metasurface was developed from reflect arrays/transmit arrays that are used as reflectors/lens of antennas, and most fundamental theories of metasurfaces are directly borrowed from antenna array theories; on the other hand, the development of antennas was flourished and expedited by progresses in metasurfaces. Many emerging antenna configurations have been constructed based on unique functional metasurfaces. In this article, we will review briefly the development roadmap of both metasurfaces and metasurface-based antennas, including antenna-inspired metasurfaces, metasurface-assisted antennas, and metasurface antennas. In particular, the recent fusion of metasurface and antenna as metantenna will bring significant impacts on methodologies of functional metasurface, antenna design, and radio-frequency device miniaturization.
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