Most gels and elastomers introduce sacrificial bonds in the covalent network to dissipate energy. However, long‐term cyclic loading caused irreversible fatigue damage and crack propagation cannot be ...prevented. Furthermore, because of the irreversible covalent crosslinked networks, it is a huge challenge to implement reversible mechanical interlocking and reorganize the polymer segments to realize the recycling and reuse of ionogels. Here, covalent crosslinking of host materials is replaced with entanglement. The entangled microdomains are used as physical crosslinking while introducing reversible bond interactions. The interpenetrating, entangled, and elastic microdomains of linear segments and covalent‐network microspheres provide mechanical stability, eliminate stress concentration at the crack tip under load, and achieve unprecedented tear and fatigue resistance of ionogels in any load direction. Moreover, reversible entanglements and noncovalent interactions can be disentangled and recombined to achieve recycling and mechanical regeneration, and the recyclability of covalent‐network microdomains is realized.
Irreversible covalent crosslinking in the matrix polymer network is avoided. The reversible entangled microdomains of the microspheres and linear segments in tough ionogels act as elastic physical crosslinking points to provide mechanical stability, dissipate stress concentration, and prevent crack propagation in any load direction. The entangled networks can be disentangled to restore the damaged mechanical properties and realize recycling.
•Cationic Gemini surfactant was first used as a soft template to synthesize NMHCSs.•The mechanism of interfacial reaction by Gemini surfactant was explored.•Resultant NMHCSs reveal interconnected ...microstructure of internal cavities.•Resultant NMHCSs own uniform and precisely tuned particle size (30–140 nm) and shell thickness.
A series of N-doped porous carbon materials with open interconnected mesoporous shells and various mesoscopic morphology were synthesized by using the cationic Gemini surfactant pentane-1,5-bis(dimethylcetyl ammonium bromide) as the soft template through a sol-gel method and the mechanism of interfacial reaction was explored. The controllable morphological structure (particle size, shell thickness and interconnected structure of internal cavities in carbon nanospheres) can be easily achieved by simply adjusting the volume of ethanol and the amount of cationic Gemini surfactant. The synthesized N-doped mesoporous hollow carbon spheres (NMHCSs) exhibit the characteristics of small and tunable particle size (30–140 nm), ultrahigh surface area (1215–1517 cm2 g−1) and large pore volume (1.12–3.22 cm3 g−1), open interconnected hierarchical mesoporous (5–20 nm), high proportion doping of heteroatoms N (4.16–6.74 at.%) and O (6.17–8.68 at.%). The representative NMHCSs as electrical double layer capacitors electrodes in 6 M KOH electrolyte display an excellent electrochemical specific capacitance (240 F g−1 at 0.2 A g−1), superb capacitance retention (161 F g−1 at 20 A g−1), and excellent cycle stability (92% capacitance retention at 10 A g−1 after 5000 cycles). This research develops a simple synthesis strategy for a series of N-enriched carbon materials which exhibit promising application prospects for high-performance supercapacitors.
Colorectal cancer (CRC) is one of the most common cancers worldwide and a leading cause of carcinogenic death. To date, surgical resection is regarded as the gold standard by the operator for ...clinical decisions. Because conventional tissue biopsy is invasive and only a small sample can sometimes be obtained, it is unable to represent the heterogeneity of tumor or dynamically monitor tumor progression. Therefore, there is an urgent need to find a new minimally invasive or noninvasive diagnostic strategy to detect CRC at an early stage and monitor CRC recurrence. Over the past years, a new diagnostic concept called "liquid biopsy" has gained much attention. Liquid biopsy is noninvasive, allowing repeated analysis and real-time monitoring of tumor recurrence, metastasis or therapeutic responses. With the advanced development of new molecular techniques in CRC, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, and tumor-educated platelet (TEP) detection have achieved interesting and inspiring results as the most prominent liquid biopsy markers. In this review, we focused on some clinical applications of CTCs, ctDNA, exosomes and TEPs and discuss promising future applications to solve unmet clinical needs in CRC patients.
Obesity has been identified as an independent risk factor for cholelithiasis. As a treatment for obesity, bariatric surgery may increase the incidence of cholelithiasis. The risk factors for ...cholelithiasis after bariatric surgery remain uncertain. The purpose of this study was to explore the risk factors for postoperative cholelithiasis after weight-loss surgery and propose suggestions for clinical decision making.
Four databases, PubMed, EMBASE, Web of Science and Cochrane, were systematically searched for all reports about cholelithiasis after bariatric surgery, and literature screening was performed following prespecified inclusion criteria. The included studies were all evaluated for quality according to the NOS scale. Data extraction was followed by analysis using Reviewer Manager 5.4 and StataSE 15.
A total of 19 articles were included in this meta-analysis, and all studies were of high quality. A total of 20,553 patients were included in this study. Sex OR = 0.62, 95% CI (0.55, 0.71), P < 0.00001 and race OR = 1.62, 95% CI (1.19, 2.19), P = 0.002 were risk factors for cholelithiasis after bariatric surgery. Surgical procedure, preoperative BMI, weight-loss ratio, smoking, hypertension, diabetes mellitus, and dyslipidemia were neither protective nor risk factors for cholelithiasis after bariatric surgery.
Caucasian race and female sex are risk factors for developing cholelithiasis after bariatric surgery; surgical procedure, BMI, weight loss ratio, hypertension, diabetes mellitus, dyslipidemia, and smoking are not risk factors for cholelithiasis after bariatric surgery.
Type 2 diabetes (T2D) onset is a complex, organized biological process with multilevel regulation, and its physiopathological mechanisms are yet to be elucidated. This study aims to find out the key ...drivers and pathways involved in the pathogenesis of T2D through multi-omics analysis.
The datasets used in the experiments comprise three groups: (1) genomic (2) transcriptomic, and (3) epigenomic categories. Then, a series of bioinformatics technologies including Marker set enrichment analysis (MSEA), weighted key driver analysis (wKDA) was performed to identify key drivers. The hub genes were further verified by the Receiver Operator Characteristic (ROC) Curve analysis, proteomic analysis, and Real-time quantitative polymerase chain reaction (RT-qPCR). The multi-omics network was applied to the Pharmomics pipeline in Mergeomics to identify drug candidates for T2D treatment. Then, we used the drug-gene interaction network to conduct network pharmacological analysis. Besides, molecular docking was performed using AutoDock/Vina, a computational docking program.
Module-gene interaction network was constructed using MSEA, which revealed a significant enrichment of immune-related activities and glucose metabolism. Top 10 key drivers (PSMB9, COL1A1, COL4A1, HLA-DQB1, COL3A1, IRF7, COL5A1, CD74, HLA-DQA1, and HLA-DRB1) were selected by wKDA analysis. Among these, COL5A1, IRF7, CD74, and HLA-DRB1 were verified to have the capability to diagnose T2D, and expression levels of PSMB9 and CD74 had significantly higher in T2D patients. We further predict the co-expression network and transcription factor (TF) binding specificity of the key driver. Besides, based on module interaction networks and key driver networks, 17 compounds are considered to possess T2D-control potential, such as sunitinib.
We identified signature genes, biomolecular processes, and pathways using multi-omics networks. Moreover, our computational network analysis revealed potential novel strategies for pharmacologic interventions of T2D.
Leaf area is an important plant canopy structure parameter with important ecological significance. Light detection and ranging technology (LiDAR) with the application of a terrestrial laser scanner ...(TLS) is an appealing method for accurately estimating leaf area; however, the actual utility of this scanner depends largely on the efficacy of point cloud data (PCD) analysis. In this paper, we present a novel method for quantifying total leaf area within each tree canopy from PCD. Firstly, the shape, normal vector distribution and structure tensor of PCD features were combined with the semi-supervised support vector machine (SVM) method to separate various tree organs, i.e., branches and leaves. In addition, the moving least squares (MLS) method was adopted to remove ghost points caused by the shaking of leaves in the wind during the scanning process. Secondly, each target tree was scanned using two patterns, i.e., one scan and three scans around the canopy, to reduce the occlusion effect. Specific layer subdivision strategies according to the acquisition ranges of the scanners were designed to separate the canopy into several layers. Thirdly, 10% of the PCD was randomly chosen as an analytic dataset (ADS). For the ADS, an innovative triangulation algorithm with an assembly threshold was designed to transform these discrete scanning points into leaf surfaces and estimate the fractions of each foliage surface covered by the laser pulses. Then, a novel ratio of the point number to leaf area in each layer was defined and combined with the total number of scanned points to retrieve the total area of the leaves in the canopy. The quantified total leaf area of each tree was validated using laborious measurements with a LAI-2200 Plant Canopy Analyser and an LI-3000C Portable Area Meter. The results showed that the individual tree leaf area was accurately reproduced using our method from three registered scans, with a relative deviation of less than 10%. Nevertheless, estimations from only one scan resulted in a deviation of >25% in the retrieved individual tree leaf area due to the occlusion effect. Indeed, this study provides a novel connection between leaf area estimates and scanning sensor configuration and supplies an interesting method for estimating leaf area based on PCD.
In this paper, an algorithm is proposed to optimize the network connectivity efficiency of a network with nodes of different energy harvesting rates by using the fewest RNs while ensuring a high ...success rate of data transmission. The algorithm calculates the weight of each node based on the energy harvesting capacity and then uses it to calculate the edge weight. Next, based on the edge weight, the Kruskal algorithm is used to create a minimum spanning tree (MST). Finally, the quantity of non-leaf nodes of the MST is inspected to verify that it meets the transmission requirements for data flow. If not, such nodes will be deemed as nodes with a low energy capacity. The support of RNs is required for these nodes to guarantee network connectivity. As shown by experimental data, the algorithm can be used to maintain network connectivity with the fewest RNs, which reduces the cost and increases the transmission success rate of data packages.
A series of bowl-shaped porous carbon materials was successfully synthesized by the use of didodecyldimethylammonium bromide as the soft template agent. By controlling the dosage of the soft template ...agent and the water/ethanol ratio of the solvent, the size and structure of the carbon materials can be precisely controlled. The prepared carbon materials with stacked bowl structure have good specific surface area (1,380.20 m
2
g
−1
), large pore volume (1.27 cm
3
g
−1
) and high heteroatom N doping amount (6.68 at.%). Moreover, electrochemical tests in 6 M KOH demonstrated impressive electrochemical performance, where the specific capacity of the typical materials was measured to be 191.0 F g
−1
(at the current density of 1 A g
−1
), and the capacity retention rate of typical materials was 80% (at the current density of 10 A g
−1
).
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