Dual-Energy-Barrier Stable Superhydrophobic Structures for Long Icing Delay.

Using superhydrophobic surfaces (SHSs) with the water-repellent Cassie-Baxter (CB) state is widely acknowledged as an effective approach for anti-icing performances. Nonetheless, the CB state is susceptible to diverse physical phenomena (e.g., vapor condensation, gas contraction, etc.) at low temperatures, resulting in the transition to the sticky Wenzel state and the loss of anti-icing capabilities. SHSs with various micronanostructures have been empirically examined for enhancing the CB stability; however, the energy barrier transits from the metastable CB state to the stable Wenzel state and thus the CB stability enhancement is currently not enough to guarantee a well and appliable anti-icing performance at low temperatures. Here, we proposed a dual-energy-barrier design strategy on superhydrophobic micronanostructures. Rather than the typical single energy barrier of the conventional CB-to-Wenzel transition, we introduced two CB states (i.e., CB I and CB II), where the state transition needed to go through CB I and CB II then to Wenzel state, thus significantly improving the entire CB stability. We applied ultrafast laser to fabricate this dual-energy-barrier micronanostructures, established a theoretical framework, and performed a series of experiments. The anti-icing performances were exhibited with long delay icing times (over 27,000 s) and low ice-adhesion strengths (0.9 kPa). The kinetic mechanism underpinning the enhanced CB anti-icing stability was elucidated and attributed to the preferential liquid pinning in the shallow closed structures, enabling the higher CB-Wenzel transition energy barrier to sustain the CB state. Comprehensive durability tests further corroborated the potentials of the designed dual-energy-barrier structures for anti-icing applications.

[Therapeutic mechanism of basic fibroblast growth factor on spinal cord injury in rats based on the Notch/signal transducer and activator of transcription 3 signaling pathway].

Objective: To explore the therapeutic effect of basic fibroblast growth factor (bFGF) on spinal cord injury (SCI) in rats and the influence of Notch/signal transducer and activator of transcription 3 (STAT3) signaling pathway. Methods: A total of 40 10-week-old male Sprague Dawley (SD) rats were selected to establish T 10-segment SCI model by a free falling object. Among them, 32 successful models were randomly divided into model group and bFGF group, with 16 in each group. Another 16 SD rats were selected as sham-operation group, with only T 10 processes, dura mater, and spinal cord exposed. After modeling, the rats in bFGF group were intraperitoneally injected with 100 µg/kg bFGF (once a day for 28 days), and the rats in model group and sham-operation group were injected with normal saline in the same way. The survival of rats in each group were observed after modeling. Basso-Beattie-Bresnahan (BBB) scores were performed before modeling and at immediate, 14 days, and 28 days after modeling to evaluate the functional recovery of hind limbs. Then, the spinal cord tissue at the site of injury was taken at 28 days and stained with HE, Nissl, and propidium iodide (PI) to observe the pathological changes, neuronal survival (number of Nissl bodies) and apoptosis (number of PI red stained cells) of the spinal cord tissue; immunohistochemical staining and ELISA were used to detect the levels of astrocyte activation markers [glial fibrillary acidic protein (GFAP)] and inflammatory factors [interleukin 1ß (IL-1ß), tumor necrosis factor α (TNF-α), interferon γ (IFN-γ)] in tissues, respectively. Western blot was used to detect the expressions of Notch/STAT3 signaling pathway related proteins [Notch, STAT3, phosphoryl-STAT3 (p-STAT3), bone morphogenetic protein 2 (BMP-2)] in tissues. Results: All rats survived until the experiment was completed. At immediate after modeling, the BBB scores in model group and bFGF group significantly decreased when compared to sham-operation group ( P<0.05). At 14 and 28 days after modeling, the BBB scores in model group significantly decreased when compared to sham-operation group ( P<0.05); the bFGF group showed an increase compared to model group ( P<0.05). Compared with before modeling, the BBB scores of model group and bFGF group decreased at immediate after modeling, and gradually increased at 14 and 28 days, the differences between different time points were significant ( P<0.05). The structure of spinal cord tissue in sham-operation group was normal; in model group, there were more necrotic lesions in the spinal cord tissue and fewer Nissl bodies with normal structures; the number of necrotic lesions in the spinal cord tissue of the bFGF group significantly reduced compared to the model group, and some normally structured Nissl bodies were visible. Compared with sham-operation group, the number of Nissl bodies in spinal cord tissue significantly decreased, the number of PI red stained cells, GFAP, IL-1ß, TNF-α, IFN-γ, Notch, p-STAT3 /STAT3, BMP-2 protein expression levels significantly increased in model group ( P<0.05). The above indexes in bFGF group significantly improved when compared with model group ( P<0.05). Conclusion: bFGF can improve motor function and pathological injury repair of spinal cord tissue in SCI rats, improve neuronal survival, and inhibit neuronal apoptosis, excessive activation of astrocytes in spinal cord tissue and inflammatory response, the mechanism of which may be related to the decreased activity of Notch/STAT3 signaling pathway.

Membranes with Molecular Gatekeepers for Efficient CO2 Capture and H2 Purification.

The urgent need for CO2 capture and hydrogen energy has attracted great attention owing to greenhouse gas emissions and global warming problems. Efficient CO2 capture and H2 purification with membrane technology will reduce greenhouse gas emissions and help reach a carbon-neutral society. Here, 4-sulfocalix[4]arene (SC), which has an intrinsic cavity, was embedded into the Matrimid membrane as a molecular gatekeeper for CO2 capture and H2 purification. The interactions between SC and the Matrimid polymer chains immobilize SC molecules into the interchain gaps of the Matrimid membrane, and the strong hydrogen and ionic bondings were able to form homogeneous mixed-matrix membranes. The incorporation of the SC molecular gatekeeper with exceptional molecular-sieving properties improved the gas separation performance of the mixed-matrix membranes. Compared with that of the Matrimid membrane, the CO2 permeability of the Matrimid-SC-3% membrane increased from 16.75 to 119.78 Barrer, the CO2/N2 selectivity increased from 29.39 to 106.95, and the CO2/CH4 selectivity increased from 29.91 to 140.92. Furthermore, when the permeability of H2 was increased to 172.20 Barrer, the H2/N2 and H2/CH4 selectivities reached approximately 153.75 and 202.59, respectively, which are far superior to those of most existing Matrimid-based materials. The mixed-matrix membranes also exhibited excellent long-term operation stability, with separation performance for several important gas pairs still overtaking the Robeson upper limit after aging for 400 days.

Incremental high average-utility itemset mining: survey and challenges.

The High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases. However, practical applications like market basket analysis and business decision-making necessitate regular updates of the database with new transactions. As a result, researchers have developed incremental HAUIM (iHAUIM) algorithms to identify HAUIs in a dynamically updated database. Contrary to conventional methods that begin from scratch, the iHAUIM algorithm facilitates incremental changes and outputs, thereby reducing the cost of discovery. This paper provides a comprehensive review of the state-of-the-art iHAUIM algorithms, analyzing their unique characteristics and advantages. First, we explain the concept of iHAUIM, providing formulas and real-world examples for a more in-depth understanding. Subsequently, we categorize and discuss the key technologies used by varying types of iHAUIM algorithms, encompassing Apriori-based, Tree-based, and Utility-list-based techniques. Moreover, we conduct a critical analysis of each mining method's advantages and disadvantages. In conclusion, we explore potential future directions, research opportunities, and various extensions of the iHAUIM algorithm.

Associations of physical activity intensity, frequency, duration, and volume with the incidence of sarcopenia in middle-aged and older adults: a 4-year longitudinal study in China.

BACKGROUND: Physical activity (PA) plays an important role in the process of several chronic diseases. It may be also associated with the incidence of sarcopenia. This study aimed to determine the association of PA from different components including frequency, duration, intensity, and volume with the incidence of sarcopenia in middle-aged and older adults. METHODS: This study used data from the China Health and Retirement Longitudinal Study in 2011 and 2015. A total of 3,760 individuals aged ≥ 40 years were involved in this study. Sarcopenia was diagnosed using muscle mass, strength and physical performance according to the Asian Working Group for Sarcopenia. PA information including frequency, duration, intensity, and volume was obtained by a self-reported questionnaire. Logistic regression analysis was employed to examine the association between PA and the incidence of sarcopenia at 4-year follow-up. RESULTS: The incidence of sarcopenia was 5.9% during the 4-year follow-up. Compared to sedentary individuals, those taking 1-2 days or more per week, or a minimum of 10 min each time on vigorous-intensity PA (VPA) had a lower incidence of sarcopenia. Adults spending 3 days or more each week, a minimum of 30 min each time, or 150 min or more per week on moderate-intensity PA (MPA) had a lower presence of sarcopenia than sedentary adults. Adults taking 3 days or more per week, at least 30 min each time, or 150 min or more each week on light-intensity PA (LPA) tended to have a lower incidence of sarcopenia than sedentary individuals. Sensitivity analyses confirmed the robustness of the findings after removing persons with hypertension, dyslipidemia, or diabetes. CONCLUSIONS: These findings suggest that the frequency, duration, and volume of VPA or MPA are negatively associated with the presence of sarcopenia. Participation in LPA tends to have a lower incidence of sarcopenia in middle-aged and older adults.

Phoenixin 20 ameliorates pulmonary arterial hypertension via inhibiting inflammation and oxidative stress.

Pulmonary arterial hypertension (PAH) is a severe pathophysiological syndrome resulting in heart failure, which is found to be induced by pulmonary vascular remodeling mediated by oxidative stress (OS) and inflammation. Phoenixin-20 (PNX-20) is a reproductive peptide first discovered in mice with potential suppressive properties against OS and inflammatory response. Our study will explore the possible therapeutic functions of PHN-20 against PAH for future clinical application. Rats were treated with normal saline, PHN-20 (100 ng/g body weight daily), hypoxia, hypoxia+PHN-20 (100 ng/g body weight daily), respectively. A signally elevated RVSP, mPAP, RV/LV + S, and W%, increased secretion of cytokines, enhanced malondialdehyde (MDA) level, repressed superoxide dismutase (SOD) activity, and activated NLRP3 signaling were observed in hypoxia-stimulated rats, which were notably reversed by PHN-20 administration. Pulmonary microvascular endothelial cells (PMECs) were treated with hypoxia with or without PHN-20 (10 and 20 nM). Marked elevation of inflammatory cytokine secretion, increased MDA level, repressed SOD activity, and activated NLRP3 signaling were observed in hypoxia-stimulated PMECs, accompanied by a downregulation of SIRT1. Furthermore, the repressive effect of PHN-20 on the domains-containing protein 3 (NLRP3) pathway in hypoxia-stimulated PMECs was abrogated by sirtuin1 (SIRT1) knockdown. Collectively, PHN-20 alleviated PAH via inhibiting OS and inflammation by mediating the transcriptional function of SIRT1.

Regulating Local Atomic Environment around Vacancies for Efficient Hydrogen Evolution.

Defect engineering is essential for the development of efficient electrocatalysts at the atomic level. While most work has focused on various vacancies as effective catalytic modulators, little attention has been paid to the relation between the local atomic environment of vacancies and catalytic activities. To face this challenge, we report a facile synthetic approach to manipulate the local atomic environments of vacancies in MoS2 with tunable Mo-to-S ratios. Our studies indicate that the MoS2 with more Mo terminated vacancies exhibits better hydrogen evolution reaction (HER) performance than MoS2 with S terminated vacancies and defect-free MoS2. The improved performance originates from the adjustable orbital orientation and distribution, which is beneficial for regulating H adsorption and eventually boosting the intrinsic per-site activity. This work uncovers the underlying essence of the local atomic environment of vacancies on catalysis and provides a significant extension of defect engineering for the rational design of transition metal dichalcogenides (TMDs) catalysts and beyond.

Difference in mortality risk predicted by leukocyte and lymphocyte levels in COVID-19 patients infected with the Wild-type, Delta, and Omicron strains.

This study aimed to investigate the changing trends, level differences, and prognostic performance of the leukocyte and lymphocyte levels of patients infected with the Wild strains, Delta strains and Omicron strains to provide a reference for prognostic assessment. In the current study, we conducted a retrospective cross-sectional study to evaluate the changing trends, level differences, and prognostic performance of leukocyte and lymphocyte of different strains at admission and discharge may already exist in patients with coronavirus disease-2019 (COVID-19) infected with the Wild type, Delta, and Omicron strains. A retrospective cross-sectional study was conducted. We recruited and screened the 243 cases infected with the Wild-type strains in Wuhan, the 629 cases infected with the Delta and 116 cases infected strains with the Omicron strains in Xi'an. The leukocyte and lymphocyte levels were compared the cohort of Wild-type infection with the cohort of Delta and the Omicron. The changes in the levels of leukocytes and lymphocytes exhibit a completely opposite trend in patients with COVID-19 infected with the different strains. The lymphocyte level at admission and discharge in patients with COVID-19 infected with Omicron strains (area under curve [AUC] receiver operating characteristic curve [ROC] 72.8-90.2%, 82.8-97.2%) presented better performance compared patients with COVID-19 infected with Wild type strains (AUC ROC 60.9-80.7%, 82.3-97.2%) and Delta strains (AUC ROC 56.1-84.7%, 40.3-93.3%). Kaplan-Meier curves showed that the leukocyte levels above newly established cutoff values and the lymphocyte levels below newly established cutoff values had a significantly higher risk of in-hospital mortality in COVID-19 patients with Wild-type and Omicron strains (P < .01). The levels of leukocyte and lymphocyte at admission and discharge in patients with COVID-19 infected with the Wild type, Delta, and Omicron strains may be differences among strains, which indicates different death risks. Our research may help clinicians identify patients with a poor prognosis for severe acute respiratory syndrome coronavirus 2 infection.

Polyene phosphatidylcholine enhances the therapeutic response of oxaliplatin in gastric cancer through Nrf2/HMOX1 mediated ferroptosis.

Oxaliplatin (OXA)-based chemotherapy is one of the first-line treatments for advanced gastric cancer. However, the potential risk for chemotherapy-induced hepatic injury can hinder its effectiveness. Polyene phosphatidylcholine (PPC) is often used as a hepatoprotective agent to counter OXA-induced hepatic injury; however, its impact on the antitumour effectiveness of OXA remains uncertain. Our retrospective study examined 98 patients with stage IV gastric cancer to assess the impact of PPC on progression-free survival (PFS) and disease control rate (DCR). Furthermore, in vitro and in vivo assays were conducted to elucidate the combined biological effects of OXA and PPC (OXA+PPC) on gastric cancer. RNA sequencing, luciferase reporter assays, live/dead cell assays, immunofluorescence, and western blotting were used to identify the activated signalling pathways and downstream factors post OXA+PPC treatment. The findings indicated that PPC served as an independent prognostic factor, correlating with prolonged PFS and improved DCR in patients with gastric cancer. The combination of OXA and PPC significantly inhibited tumour cell growth both in vitro and in vivo. RNA sequencing revealed that OXA+PPC treatment amplified reactive oxygen species and ferroptosis signalling pathways. Mechanistically, OXA+PPC upregulated the expression of haem oxygenase-1 by promoting the nuclear migration of nuclear factor erythroid 2-related factor (Nrf2), thereby enhancing its transcriptional activity. Drug-molecule docking analysis demonstrated that PPC competitively bound to the peptide structural domains of both Nrf2 and Kelch-like ECH-associated protein 1 (KEAP1), accounting for the increased translocation of Nrf2. In conclusion, our study reveals the synergistic antitumour potential of PPC and OXA while protecting patients against hepatic injury. This suggests a promising combined treatment approach for patients with advanced gastric cancer.

Dynamically Reconstructed Triple-Copper-Vacancy Associates Confined in Cu Nanowires Enabling High-Rate and Selective CO2 Electroreduction to C2+ Products.

Electrochemically reconstructed Cu-based catalysts always exhibit enhanced CO2  electroreduction performance; however, it still remains ambiguous whether the reconstructed Cu vacancies have a substantial impact on CO2 -to-C2+ reactivity. Herein, Cu vacancies are first constructed through electrochemical reduction of Cu-based nanowires, in which high-angle annular dark-field scanning transmission electron microscopy image manifests the formation of triple-copper-vacancy associates with different concentrations, confirmed by positron annihilation lifetime spectroscopy. In situ attenuated total reflection-surface enhanced infrared absorption spectroscopy discloses the triple-copper-vacancy associates favor *CO adsorption and fast *CO dimerization. Moreover, density-functional-theory calculations unravel the triple-copper-vacancy associates endow the nearby Cu sites with enriched and disparate local charge density, which enhances the *CO adsorption and reduces the CO-CO coupling barrier, affirmed by the decreased *CO dimerization energy barrier by 0.4 eV. As a result, the triple-copper-vacancy associates confined in Cu nanowires achieve a high Faradaic efficiency of over 80% for C2+ products in a wide current density range of 400-800 mA cm-2 , outperforming most reported Cu-based electrocatalysts.

MAHyNet: Parallel Hybrid Network for RNA-Protein Binding Sites Prediction Based on Multi-Head Attention and Expectation Pooling.

RNA-binding proteins (RBPs) can regulate biological functions by interacting with specific RNAs, and play an important role in many life activities. Therefore, the rapid identification of RNA-protein binding sites is crucial for functional annotation and site-directed mutagenesis. In this work, a new parallel network that integrates the multi-head attention mechanism and the expectation pooling is proposed, named MAHyNet. The left-branch network of MAHyNet hybrids convolutional neural networks (CNNs) and gated recurrent neural network (GRU) to extract the features of one-hot. The right-branch network is a two-layer CNN network to analyze physicochemical properties of RNA base. Specifically, the multi-head attention mechanism is a computational collection of multiple independent layers of attention, which can extract feature information from multiple dimensions. The expectation pooling combines probabilistic thinking with global pooling. This approach helps to reduce model parameters and enhance the model performance. The combination of CNN and GRU enables further extraction of high-level features in sequences. In addition, the study shows that appropriate hyperparameters have a positive impact on the model performance. Physicochemical properties can be used to supplement characterization information to improving model performance. The experimental results show that MAHyNet has better performance than other models. The source code and data are available at https://github.com/HNUBioinformatics/MAHyNet.

Mechanically robust, self-reporting and healable polyurethane elastomers by incorporating symmetric/asymmetric chain extenders.

Self-healing elastomers usually show poor mechanical properties and environmental stability, and they cannot self-report mechanical/chemical damage. Herein, an innovative design strategy is reported that combines symmetric/asymmetric chain extenders to create large yet disordered hard domains within polyurethane (PU) elastomers, enabling the integration of mechanical robustness and self-reporting and self-healing capabilities to overcome both mechanical and chemical damage. Specifically, large yet disordered hard domains were created by governing the molar contents of asymmetric fluorescent 2-(4-aminophenyl)-5-aminobenzimidazole (PABZ) and symmetric 4-aminophenyl disulfide (APDS). Such a structural feature led to a small free-volume fraction, prominent strain-induced crystallization (SIC), and high energy of dissipation, enabling the PU elastomer to display outstanding mechanical strength (60.7 MPa) and toughness (177.9 MJ m-3). Meanwhile, the loose stacking of disordered hard domains imposed small restriction on network chains and imparted the network with high relaxation dynamics, leading to high healing efficiency (97.8%). More importantly, the fluorescence intensity was stimulus-responsive and thus the PU elastomer could self-report mechanical/chemical damage and healing processes. The PU elastomer also showed potential application prospects in information encoding and encryption. Furthermore, selecting polydimethylsiloxane as one of the soft segments could effectively endow the PU elastomer with intrinsic hydrophobicity. Therefore, this work provides valuable guidance for designing multi-functional materials with anti-counterfeiting, self-reporting, and healing properties as well as high mechanical properties and hydrophobicity.

The change of coordination environments induced by vacancy defects in hematite leads to a contrasting difference between cation Pb(II) and oxyanion As(V) immobilization.

Hematite is an iron oxide commonly found in terrestrial environments and plays an essential role in controlling the migration of heavy metal(loid)s in groundwater and sediments. Although defects were shown to exist both in naturally occurring and laboratory-synthesized hematite, their influences on the immobilization of heavy metal(loid)s remain poorly understood. In this study, hematite samples with tunable vacancy defect concentrations were synthesized to evaluate their adsorption capacities for the cation Pb(II) and for the oxyanion As(V). The defects in hematite were characterized using XRD, TEM-EDS mapping, position annihilation lifetime spectroscopy, and XAS. The surface charge characteristics in defective hematite were investigated using zeta potential measurements. We found that Fe vacancies were the primary defect type in the hematite structure. Batch experiments confirmed that Fe vacancies in hematite promoted As(V) adsorption, while they decreased Pb(II) adsorption. The reason for the opposite effects of Fe vacancies on Pb(II) and As(V) immobilization was investigated using DFT calculations and EXAFS analysis. The results revealed that Fe vacancies altered As-Fe coordination from a monodentate to a bidentate complex and increased the length of the Pb-Fe bond on the hematite surface, thereby leading to an increase in As(V) bonding strength, while decreasing Pb(II) adsorption affinity. In addition, the zeta potential analysis demonstrated that the presence of Fe vacancies led to an increase in the isoelectric point (IEP) of hematite samples, which therefore decreased the attraction for the cation Pb(II) and increased the attraction for the oxyanion As(V). The combination of these two effects caused by defects contributed to the contrasting difference between cation Pb(II) and oxyanion As(V) immobilization by defective hematite. Our study therefore provides new insights into the migration and fate of toxic heavy metal(loid)s controlled by iron minerals.

Deciphering the influencing mechanism of hydraulic retention time on purification performance of a mixotrophic system from the perspective of reaction kinetics.

At present, eutrophication is increasingly serious, so it is necessary to effectively reduce nitrogen and phosphorus in water bodies. In this study, a pyrite/polycaprolactone-based mixotrophic denitrification (PPMD) system using pyrite and polycaprolactone (PCL) as electron donors was developed and compared with pyrite-based autotrophic denitrification (PAD) system and PCL-based heterotrophic denitrification (PHD) system through continuous flow experiment. The removal efficiency of NO3--N (NRE) and PO43--P (PRE) and the contribution proportion of PAD in the PPMD system were significantly increased by prolonging hydraulic retention time (HRT, from 1 to 48 h). When HRT was equal to 24 h, the PPMD system conformed to the zero-order kinetic model, so NRE and PRE were mainly limited by the PAD process. When HRT was equal to 48 h, the PPMD system met the first-order kinetic model with NRE and PRE reaching 98.9 ± 1.1% and 91.8 ± 4.5%, respectively. When HRT = 48 h, the NRE and PRE by PAD system were 82.7 ± 9.1% and 88.5 ± 4.7%, respectively, but the effluent SO42- concentration was as high as 152.1 ± 13.7 mg/L (the influent SO42- concentration was 49.2 ± 3.3 mg/L); the NRE by PHD system was 98.5 ± 1.7%, but the PO43--P could not be removed ideally. The concentrations of NO3--N, total nitrogen, PO43--P, and SO42- in the PPMD system also showed distinct changes along the reactor column. In addition, the microbial diversity analysis showed that prolonging HRT (from 24 to 48 h) increased the abundance of autotrophic denitrifying microorganisms in the PPMD system, ultimately increasing the contribution proportion of PAD.

Improved adaptive-phase fuzzy high utility pattern mining algorithm based on tree-list structure for intelligent decision systems.

With the rapid development of AI and big data mining technologies, computerized medical decision-making has become increasingly prominent. The aim of high-utility pattern mining (HUPM) is to discover meaningful patterns in medical databases that contribute to maximizing the utility from the perspective of diagnosis. However, HUPM pays less attention to the interpretability and explainability of these patterns in medical decision-making scenarios. This paper proposes a novel algorithm called the Improved fuzzy high-utility pattern mining (IF-HUPM) to address this problem. First, the paper applies a fuzzy preprocessing method to divide the fuzzy intervals of a medical quantitative data set, which enhances the fuzziness and interpretability of the data. Next, in the process of IF-HUPM, both fuzzy tree and list structures are employed to calculate fuzzy high-utility values. By combining the characteristics of the one-stage and two-stage algorithms of HUPM, an adaptive-phase Fuzzy HUPM hybrid frame is proposed. The experimental results demonstrate that the proposed IF-HUPM algorithm enhances both accuracy and efficiency and the mining process requires less time and space on average.

Ultrastrong and High-Tough Thermoset Epoxy Resins from Hyperbranched Topological Structure and Subnanoscaled Free Volume.

The strength and toughness of thermoset epoxy resins are generally mutually exclusive, as are the high performance and rapid recyclability. Experimentally determined mechanical strength values are usually much lower than their theoretical values. The preparation of thermoset epoxy resins with high modulus, high toughness, ultrastrong strength, and highly efficient recyclability is still a challenge. Here, novel hyperbranched epoxy resins (Bn, n = 6, 12, 24) with imide structures by a thiol-ene click reaction. Bn shows an excellent comprehensive function in simultaneously improving the strength, modulus, toughness, low-temperature resistance, and degradability of diglycidyl ether of bisphenol-A (DGEBA). All the mechanical properties first increase and then decrease with minimization of the free volume properties. The improvement is attributable to uniform molecular holes or free volume by a molecular mixture of linear and hyperbranched topological structures. The precise measurement and controllability of the molecular free volume properties of epoxy resins is first discovered, as well as the imide structure degradation of crosslinked epoxy resins. The two conflicts are successfully resolved between strength and toughness and between high performance during service and high efficiency during degradation. These findings provide a route for designing ultrastrong, tough, and recyclable thermoset epoxy resins.

SMGCN: Multiple Similarity and Multiple Kernel Fusion Based Graph Convolutional Neural Network for Drug-Target Interactions Prediction.

Accurately identifying potential drug-target interactions (DTIs) is a critical step in accelerating drug discovery. Despite many studies that have been conducted over the past decades, detecting DTIs remains a highly challenging and complicated process. Therefore, we propose a novel method called SMGCN, which combines multiple similarity and multiple kernel fusion based on Graph Convolutional Network (GCN) to predict DTIs. In order to capture the features of the network structure and fully explore direct or indirect relationships between nodes, we propose the method of multiple similarity, which combines similarity fusion matrices with Random Walk with Restart (RWR) and cosine similarity. Then, we use GCN to extract multi-layer low-dimensional embedding features. Unlike traditional GCN methods, we incorporate Multiple Kernel Learning (MKL). Finally, we use the Dual Laplace Regularized Least Squares method to predict novel DTIs through combinatorial kernels in drug and target spaces. We conduct experiments on a golden standard dataset, and demonstrate the effectiveness of our proposed model in predicting DTIs through showing significant improvements in Area Under the Curve (AUC) and Area Under the Precision-Recall Curve (AUPR). In addition, our model can also discover some new DTIs, which can be verified by the KEGG BRITE Database and relevant literature.

Localized in-situ deposition: a new dimension to control in fabricating surface micro/nano structures via ultrafast laser ablation.

Controllable fabrication of surface micro/nano structures is the key to realizing surface functionalization for various applications. As a versatile approach, ultrafast laser ablation has been widely studied for surface micro/nano structuring. Increasing research efforts in this field have been devoted to gaining more control over the fabrication processes to meet the increasing need for creation of complex structures. In this paper, we focus on the in-situ deposition process following the plasma formation under ultrafast laser ablation. From an overview perspective, we firstly summarize the different roles that plasma plumes, from pulsed laser ablation of solids, play in different laser processing approaches. Then, the distinctive in-situ deposition process within surface micro/nano structuring is highlighted. Our experimental work demonstrated that the in-situ deposition during ultrafast laser surface structuring can be controlled as a localized micro-additive process to pile up secondary ordered structures, through which a unique kind of hierarchical structure with fort-like bodies sitting on top of micro cone arrays were fabricated as a showcase. The revealed laser-matter interaction mechanism can be inspiring for the development of new ultrafast laser fabrication approaches, adding a new dimension and more flexibility in controlling the fabrication of functional surface micro/nano structures.

1000 °C High-Temperature Wetting Behaviors of Molten Metals on Laser-Microstructured Metal Surfaces.

The melting of metals at high temperatures is common and important in many fields, e.g., metallurgy, refining, casting, welding, brazing, even newly developed batteries, and nuclear fusion, which is thus of great value in modern industrialization. However, the knowledge of the wetting behaviors of molten metals on various substrate surfaces remains insufficient, especially when the temperature is over 1000 °C and with microstructured metal substrate surfaces. Herein, we selected molten cerium (Ce) on a tantalum (Ta) substrate as an example and investigated in detail its wetting at temperatures up to 1000 °C by modulating the microstructures of the substrate surfaces via laser processing. We discovered that the wetting states of molten Ce on Ta surfaces at temperatures over 900 °C could be completely altered by modifying the laser-induced surface microstructures and the surface compositions. The molten Ce turned superlyophilic with its contact angle (CA) below 10° on the only laser-microstructured surfaces, while it exhibited lyophobicity with a CA of about 135° on the laser-microstructured plus oxidized ones, which demonstrated remarkably enhanced resistance against the melt with only tiny adhesion in this circumstance. In contrast, the CA of molten Ce on Ta substrate surfaces only changed from ∼25 to ∼95° after oxidization without laser microstructuring. We proved that modulating the substrate surface microstructures via laser together with oxidization was capable of efficiently controlling various molten metals' wetting behaviors even at very high temperatures. These findings not only enrich the understanding of molten metal high-temperature wettability but also enable a novel practical approach to control the wetting states for relevant applications.

OGT-1 regulates synaptic assembly through the insulin signaling pathway.

The formation and maintenance of synapses are precisely regulated, and the misregulation often leads to neurodevelopmental or neurodegenerative disorders. Besides intrinsic genetically encoded signaling pathways, synaptic structure and function are also regulated by extrinsic factors, such as nutrients. O-GlcNAc transferase (OGT), a nutrient sensor, is abundant in the nervous system and required for synaptic plasticity, learning, and memory. However, whether OGT is involved in synaptic development and the mechanism underlying the process are largely unknown. In this study, we found that OGT-1, the OGT homolog in C. elegans, regulates the presynaptic assembly in AIY interneurons. The insulin receptor DAF-2 acts upstream of OGT-1 to promote the presynaptic assembly by positively regulating the expression of ogt-1. This insulin-OGT-1 axis functions most likely by regulating neuronal activity. In this study, we elucidated a novel mechanism for synaptic development, and provided a potential link between synaptic development and insulin-related neurological disorders.