Ultrahigh-strength silicone aerogels reinforced by an armor-like epoxy framework via a temperature-controlled sequential reaction strategy

Aerogels with low density and high porosity are extremely attractive for high-performance insulation, but their brittleness, complicated fabrication, and poor mechanical properties greatly limit their practical applications. Herein, we report an ultrahigh-strength silicone aerogel with an armor-like epoxy framework via a temperature-controlled sequential reaction strategy. The key to this synthesis is forming a Si-O-Si framework via the polycondensation of silanes at 100 °C, followed by in-situ armoring an epoxy framework via an intermolecular cyclization at an elevated temperature of 150 °C. Owing to the enhanced framework, the resulting aerogel could withstand capillary tension in the drying process, enabling it to be dried at ambient pressure without shrinkage. The obtained aerogel possesses a tunable density of 0.17-0.45 g/cm3 and ultrahigh-strength with compressive modulus up to 37.8-244.3 MPa, which surpasses other polymer-reinforced silicone aerogels by a factor of five in mechanical properties. It also demonstrates outstanding thermal insulation, with an extremely low thermal conductivity from 0.025 to 0.051 W m-1 K-1 at room temperature, and maintains thermal characteristics across a temperature range of -20 to 300 °C. Furthermore, the aerogel composites prepared by the reinforcement of low-density fiber mats have tunable densities of 0.36-0.87 g/cm3, much enhanced tensile strengths of 15.9-72.3 MPa, and low thermal conductivities at room temperature of 0.042-0.078 W m-1 K-1. This study presents a cost-effective method for enhancing the production of silicone aerogel materials, offering considerable opportunities for their application in insulation, energy transport, and the aerospace sector.

Adaptive Force Field Parameter Optimization for Expanding Reaction Simulations within Wide-Ranged Temperature

Large-scale and long-term simulation of chemical reactions are key research topics in computational chemistry. However, there are still difficulties in simulating high-temperature reactions, such as polymer thermal decomposition. Herein, we introduce an adaptive potential parameter optimization framework designed to automatically fine-tune parameters, and the application of it to optimize ReaxFF parameters enhances the accuracy of chemical reaction simulations conducted at experimental temperatures. To achieve this, we leverage the power of Random Forests and interpretable machine learning techniques that enable the identification and selection of parameters that exert a substantial influence on the target attribute. By training deep neural network (NN) models, we established optimized parameter associations with reference properties. We train deep neural network (NN) models to establish the relationship between the optimized parameters and reference properties. We employ a Genetic Algorithm (GA) to utilize the surrogate NN model and the quantum mechanical targets to speed up the search for the optimal parameters. Our simulation results of resin pyrolysis show that the adaptive optimized ReaxFF can predict the peak temperature more accurately and obtain reasonable product composition under conditions that more closely resemble experimental scenarios. This work facilitates advances in force field parameter optimization for more accurate and universal reaction simulations.

Arbidol attenuates liver fibrosis and activation of hepatic stellate cells by blocking TGF-β1 signaling

Chronic liver diseases (CLD) impact over 800 million people globally, causing about 2 million deaths annually. Arbidol (ARB), an indole-derivative used to treat influenza virus infection, was extensively used during COVID-19 pandemic in China. In recent years, studies have shown that ARB, compared to other antiviral drugs, exhibits greater liver-protective efficacy, indicating a potential hepatoprotective effect beyond its antiviral activity. However, the mechanism remains unclear. In this study, we investigated the impact of ARB on liver injury/fibrosis in bile duct ligated (BDL) mice and its effect on spontaneous and transforming growth factor β1 (TGF-β1)-induced activation of primary cultured hepatic stellate cells (HSCs). Oral administration of ARB significantly ameliorated BDL-induced liver injury/fibrosis as reflected by decreased serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), reduced collagen deposition, and diminished mRNA expression of fibrosis markers. ARB notably inhibited spontaneous and TGF-β1-induced activation of primary cultured HSCs. Moreover, ARB also drastically attenuated mRNA expression levels of platelet-derived growth factor receptor (Pdgfr), transforming growth factor-beta receptor (Tgfbr) 1, Tgfbr2, matrix metalloproteinase (Mmp)-2, and Mmp-9 in activated HSCs. We further demonstrate that ARB mitigated Smad2/3 phosphorylation in both TGF-β1 treated HSCs and BDL mice. These data together demonstrate that the therapeutic efficacy of ARB on liver fibrosis is independent of its antiviral activity and likely is achieved by blocking TGF-β1 signaling-mediated HSC activation.

TMT-based quantitative proteomics analysis of neuroprotective effects of Forsythoside A on the MPTP-induced Parkinson's disease mouse model

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characteristized by the presence of dyskinesia and the progressive loss of dopaminergic neurons. Although certain drugs can mitigate the symptoms of PD, they are unable to delay the disease progression, and their prolonged use may result in complications. Therefore, there exists an urgent necessity to identify potential agents that can effectively delay PD progression with fewer side effects. Recent research has unveiled that several traditional Chinese medicines (TCM) exhibit neuroprotective properties in various models pertinent to PD. Forsythoside A (FSA), the primary bioactive compound derived from TCM Lianqiao, has undergone extensive research in animal models of Alzheimer's disease and cerebral ischemia. However, the investigation into the impact of FSA on PD is limited in existing research. In this study, we aimed to evaluate the neuroprotective effects of FSA on MPTP-induced PD mouse model. FSA demonstrated significant improvements in the behavioral and neuropathological changes triggered by MPTP in mice. Furthermore, it exerted a suppressive effect on the activations of astrocyte and microglia. Meanwhile, Tandem mass tag (TMT)-based quantitative proteomics of striatal tissue and bioinformatics analysis were performed to elucidate the underlying mechanisms of FSA on PD mouse model. Proteomics demonstrated a total of 68 differentially expressed proteins (DEPs) were identified between HFSA and MPTP groups including 26 upregulated and 42 downregulated. Systematic bioinformatics analysis of the 68 DEPs illustrated that they were predominantly related to estrogen signaling pathway and calcium signaling pathway. The related DEPs (PLCβ4, Grm2, HPAC and Cox4i1) expression levels were verified by Western blot. FSA effectively restored the altered expression of the four DEPs induced by MPTP. Summarily, FSA exerted remarkable neuroprotective effects in MPTP-induced mice. Further, our research may provide proteomics insights that contribute to the further exploration of FSA as a potential treatment for PD.

Intelligent leaching rare earth elements from waste fluorescent lamps

Rare earth elements (REEs), one of the global key strategic resources, are widely applied in electronic information and national defense, etc. The sharply increasing demand for REEs leads to their overexploitation and environmental pollution. Recycling REEs from their second resources such as waste fluorescent lamps (WFLs) is a win-win strategy for REEs resource utilization and environmental production. Pyrometallurgy pretreatment combined with acid leaching is proven as an efficient approach to recycling REEs from WFLs. Unfortunately, due to the uncontrollable components of wastes, many trials were required to obtain the optimal parameters, leading to a high cost of recovery and new environmental risks. This study applied machine learning (ML) to build models for assisting the leaching of six REEs (Tb, Y, Eu, La, and Gd) from WFLs, only needing the measurement of particle size and composition of the waste feed. The feature importance analysis of 40 input features demonstrated that the particle size, Mg, Al, Fe, Sr, Ca, Ba, and Sb content in the waste feed, the pyrometallurgical and leaching parameters have important effects on REEs leaching. Furthermore, their influence rules on different REEs leaching were revealed. Finally, some verification experiments were also conducted to demonstrate the reliability and practicality of the model. This study can quickly get the optimal parameters and leaching efficiency for REEs without extensive optimization experiments, which significantly reduces the recovery cost and environmental risks. Our work carves a path for the intelligent recycling of strategic REEs from waste.

Enhanced Electron Delocalization within Coherent Nano-Heterocrystal Ensembles for Optimizing Polysulfide Conversion in High-Energy-Density Li-S Batteries

Commercialization of high energy density Lithium-Sulfur (Li-S) batteries is impeded by challenges such as polysulfide shuttling, sluggish reaction kinetics, and limited Li+ transport. Herein, a jigsaw-inspired catalyst design strategy that involves in situ assembly of coherent nano-heterocrystal ensembles (CNEs) to stabilize high-activity crystal facets, enhance electron delocalization, and reduce associated energy barriers is proposed. On the catalyst surface, the stabilized high-activity facets induce polysulfide aggregation. Simultaneously, the surrounded surface facets with enhanced activity promote Li2 S deposition and Li+ diffusion, synergistically facilitating continuous and efficient sulfur redox. Experimental and DFT computations results reveal that the dual-component hetero-facet design alters the coordination of Nb atoms, enabling the redistribution of 3D orbital electrons at the Nb center and promoting d-p hybridization with sulfur. The CNE, based on energy level gradient and lattice matching, endows maximum electron transfer to catalysts and establishes smooth pathways for ion diffusion. Encouragingly, the NbN-NbC-based pouch battery delivers a Weight energy density of 357 Wh kg-1 , thereby demonstrating the practical application value of CNEs. This work unveils a novel paradigm for designing high-performance catalysts, which has the potential to shape future research on electrocatalysts for energy storage applications.

Tensile Failure Behaviors of Adhesively Bonded Structure Based on In Situ X-ray CT and FEA

Adhesive bonding plays a pivotal role in structural connections, yet the bonding strength is notably affected by the presence of pore defects. However, the invisibility of interior pores severely poses a challenge to understanding their influence on tensile failure behaviors under loading. In this study, we present a pioneering investigation into the real-time micro-failure mechanisms of adhesively bonded structures using in situ X-ray micro-CT. Moreover, the high-precision finite element analysis (FEA) of stress distribution is realized by establishing the real adhesive layer model based on micro-CT slices. The findings unveil that pores induce stress concentration within the adhesive layer during the tensile process, with stress levels significantly contingent upon pore sizes rather than their specific shapes. Consequently, larger pores initiate and propagate cracks along their paths, ultimately culminating in the failure of adhesively bonded structures. These outcomes serve as a significant stride in elucidating how pore defects affect the bonding performance of adhesively bonded structures, offering invaluable insights into their mechanisms.

Influence of bifenthrin exposure at different gestational stages on the neural development

Perinatal exposure to bifenthrin (BF) alters neurodevelopment. However, the most susceptible time period to BF exposure and the possible mechanisms are not clear. In the current study, pregnant female mice were treated with BF (0.5 mg/kg/d) at three different stages [gestational day (GD) 0-5, 6-15 and 16-birth (B)] and neurologic deficits were evaluated in offspring mice. BF exposure at GD 16-B significantly altered the locomotor activity and caused learning and memory impairments in 6-week-old offspring. Gestational BF exposure also caused neuronal loss in the region of cornu ammonis of hippocampi of 6-week-old offspring. Interestingly, neurobehavioral impairments and neuronal loss were not observed in offspring at 10-week-old. BF exposure at GD 16-B also decreased protein levels of VGluT1, NR1 and NR2A while increased the protein levels of NR2B and VGAT1, as well as the gene levels of Il-1β, Il-6 and Tnf-α in hippocampi of 6-week-old offspring. Collectively, these data demonstrate that gestational exposure to a low dose BF causes neurodevelopmental deficits that remit with the age and the late-stage of pregnancy is the most susceptible time window to BF exposure. Imbalance in excitatory/inhibitory neuronal transmission, altered expression levels of NMDA receptors and increased neural inflammation may be associated with BF prenatal exposure-triggered neurobehavioral impairments.

Integrative multilevel exploration of the mechanism by which Er-Zhi-Wan alleviates the Parkinson's disease (PD)-like phenotype in the MPTP-induced PD mouse model

The neuroprotective effects of Er-Zhi-Wan (EZW), a well-known traditional Chinese formulation, in MPTP-induced Parkinson's disease (PD) models are poorly understood and require evaluation. A model of PD induced by MPTP was used to evaluate the neuroprotective effects of EZW in mice. The underlying pharmacological mechanisms of EZW for the prevention and treatment of PD were then explored using a combination of multilevel databases, network pharmacology, biological experiments, and LCMS/MS. In vivo data showed that pretreatment with EZW can be neuroprotective against MPTP-induced motor dysfunction and can effectively rescue dopaminergic neurons from MPTP-induced degeneration in mice. Furthermore, data from combined multilevel databases and network pharmacology analysis strategies suggested that the neuroprotective activity of EZW in the treatment of PD is mediated by a complicated multicomponent, multitarget network. Genes such as Grm2, Grm5, Drd2, and Grik2 were identified as important therapeutic targets. Subsequent experimental validation showed that EZW can broadly regulate the mRNA levels of these receptor genes as well as BDNF, and consequently increase the phosphorylation levels of CREB to stimulate CREB signaling. These targets and signaling systems may be responsible for the reversal of neuronal death by EZW after MPTP exposure. The LC-MS/MS results also identified a wide range of chemical components of EZW, including at least 53 precise compounds, further demonstrating the complexity of the network in which EZW exerts its neuroprotective activity. Our work provides evidence for the mechanism of EZW in MPTP-PD models and supports the neuroprotective function of EZW in neurodegenerative diseases.

Ultrafine Vacancy-Rich Nb2O5 Semiconductors Confined in Carbon Nanosheets Boost Dielectric Polarization for High-Attenuation Microwave Absorption

The integration of nano-semiconductors into electromagnetic wave absorption materials is a highly desirable strategy for intensifying dielectric polarization loss; achieving high-attenuation microwave absorption and realizing in-depth comprehension of dielectric loss mechanisms remain challenges. Herein, ultrafine oxygen vacancy-rich Nb2O5 semiconductors are confined in carbon nanosheets (ov-Nb2O5/CNS) to boost dielectric polarization and achieve high attenuation. The polarization relaxation, electromagnetic response, and impedance matching of the ov-Nb2O5/CNS are significantly facilitated by the Nb2O5 semiconductors with rich oxygen vacancies, which consequently realizes an extremely high attenuation performance of - 80.8 dB (> 99.999999% wave absorption) at 2.76 mm. As a dielectric polarization center, abundant Nb2O5-carbon heterointerfaces can intensify interfacial polarization loss to strengthen dielectric polarization, and the presence of oxygen vacancies endows Nb2O5 semiconductors with abundant charge separation sites to reinforce electric dipole polarization. Moreover, the three-dimensional reconstruction of the absorber using microcomputer tomography technology provides insight into the intensification of the unique lamellar morphology regarding multiple reflection and scattering dissipation characteristics. Additionally, ov-Nb2O5/CNS demonstrates excellent application potential by curing into a microwave-absorbing, machinable, and heat-dissipating plate. This work provides insight into the dielectric polarization loss mechanisms of nano-semiconductor/carbon composites and inspires the design of high-performance microwave absorption materials.

Research progress on aging mechanism and drugs and the role of stem cells in anti-aging process

There have been many discussions on longevity from ancient times to the present day. In the Laozi, it is said, "Heaven and earth are long and enduring because they do not arise from themselves, so they can live forever." In Zhuangzi - Zai You, it is also said, "Keep your mental peace, and your body will be healthy. Don't strain your body and don't consume your spirit to live a long life." It is clear that people attach importance to anti-aging and the desire for longevity. Throughout human history, we have treated aging as an inevitable process, but with the development of medical science, we have become more aware of the various molecular changes in the human body. In an aging society, more people are suffering from age-related diseases such as osteoporosis, Alzheimer's disease, and cardiovascular disease, which has led to a search for anti-aging. However, by 'living longer' we mean not only living but also living longer in good health. The mechanisms of aging are still unclear and there is a great deal of interest and curiosity in how to combat aging effectively. Some potential criteria exist for the determination of anti-aging drugs: the first criterion is the ability to exert life-extending effects in model organisms, preferably in mammals; the second criterion is the ability to prevent or delay several age-related diseases in mammals; and the third criterion is the ability to inhibit the transition of cells from a quiescent to a senescent state. Based on these criteria, the current anti-aging drugs often involved are rapamycin, metformin, curcumin and other polyphenols, polysaccharides, resveratrol, etc. The most studied and relatively well-understood pathways and factors of aging are currently known to include seven enzymes, six biological factors, and one chemical, which mainly involve more than ten pathways such as Nrf2/SKN-1; NFκB; AMPK; P13K/AKT; IGF; and NAD.

Recycling Hazardous and Valuable Electrolyte in Spent Lithium-Ion Batteries: Urgency, Progress, Challenge, and Viable Approach

Recycling spent lithium-ion batteries (LIBs) is becoming a hot global issue due to the huge amount of scrap, hazardous, and valuable materials associated with end-of-life LIBs. The electrolyte, accounting for 10-15 wt % of spent LIBs, is the most hazardous substance involved in recycling spent LIBs. Meanwhile, the valuable components, especially Li-based salts, make recycling economically beneficial. However, studies of electrolyte recycling still account for only a small fraction of the number of spent LIB recycling papers. On the other hand, many more studies about electrolyte recycling have been published in Chinese but are not well-known worldwide due to the limitations of language. To build a bridge between Chinese and Western academic achievements on electrolyte treatments, this Review first illustrates the urgency and importance of electrolyte recycling and analyzes the reason for its neglect. Then, we introduce the principles and processes of the electrolyte collection methods including mechanical processing, distillation and freezing, solvent extraction, and supercritical carbon dioxide. We also discuss electrolyte separation and regeneration with an emphasis on methods for recovering lithium salts. We discuss the advantages, disadvantages, and challenges of recycling processes. Moreover, we propose five viable approaches for industrialized applications to efficiently recycle electrolytes that combine different processing steps, ranging from mechanical processing with heat distillation to mechanochemistry and in situ catalysis, and to discharging and supercritical carbon dioxide extraction. We conclude with a discussion of future directions for electrolyte recycling. This Review will contribute to electrolyte recycling more efficiently, environmentally friendly, and economically.

Atomic Oxygen-Induced Surface Erosion Behavior and Mechanical Degradation of Polyether Ether Ketone via Reactive Molecular Dynamics Simulations

Atomic oxygen (AO) collision is one of the most serious threats to polymeric materials exposed to the space environment, yet understanding the structural changes and degradation of materials caused by AO impact remains a tremendous issue. Herein, we systematically evaluate the erosion collision and mechanical degradation of polyether ether ketone (PEEK) resin under hypervelocity AO impact using reactive molecular dynamics simulations. The interaction process and local evolution mechanism between high-speed AO and PEEK are investigated for the first time, suggesting that AO will either be scattered or adsorbed by PEEK, which is strongly correlated with the main degraded species evolution including O₂, OH, CO, and CO₂. Different AO fluxes and AO incidence angle simulations indicate that high-energy AO collision on the surface transfers kinetic energy to PEEK's thermal energy, thus inducing mass loss and surface penetration mechanisms. Vertically impacted AO causes less erosion on the PEEK matrix, rather than obliquely. Furthermore, PEEK chains modified with functional side groups are comprehensively investigated by 200 AO impact and high strain rate (10¹⁰ s^-1) tensile simulations, demonstrating that the spatial configuration and stable benzene functionality of phenyl side groups can significantly improve the AO resistance and mechanical properties of PEEK at 300 and 800 K. This work revealed useful insights into the interaction mechanisms between AO and PEEK at the atomic scale and may provide a protocol for screening and designing new polymers of high AO tolerance.

Sandwich Structured Metal oxide/Reduced Graphene Oxide/Metal Oxide-Based Polymer Electrolyte Enables Continuous Inorganic-Organic Interphase for Fast Lithium-Ion Transportation

Introducing inorganic fillers into organic poly(ethylene oxide)(PEO)-based electrolyte has attracted substantial attention to enhance its ionic conductivity and mechanical strength, but limited inorganic-organic interphases are always caused by isolated particles agglomeration. Herein, a variety of sandwich structured metal oxide/reduced graphene oxide(rGO)/metal oxide nanocomposites to optimize lithium-ion conduction by interconnected amorphous organic-inorganic interphases in lithium metal batteries, are proposed. With the support of high surface area rGO, the agglomeration of metal oxide particles is precluded, forming continuous amorphous organic-inorganic interphases with stacked layer-by-layer structure, thus creating 3D interconnected lithium-ion transportation channels vertically and laterally. Besides, metal oxide nanoparticles with hydroxyls possess high affinity toward bis(tri-fluoromethanesulfonyl)imide anions by hydrogen bindings between hydroxyls and fluorine and metal-oxygen bonds, releasing more free lithium ions. Consequently, PEO-ZnO/rGO/ZnO electrolyte delivers superior ionic conductivity of 1.02 × 10^-4 S cm^-1 at 25 °C and lithium-ion transference number of 0.38 at 60 °C. Furthermore, ZnO/rGO/ZnO insertion promotes the formation of LiF-rich stable solid electrolyte interface, endowing Li symmetric cells with long-term cycling stability over 900 hours. The corresponding LiFePO₄ cathode possesses a high reversible specific capacity of 130 mAh g^-1 at 0.5C after cycling 300 cycles with a poor capacity fading of 0.05% per cycle.

Imaging diagnosis of intravenous leiomyomatosis: an institutional experience

AIM

To review and summarise the clinical and imaging characteristics of intravenous leiomyomatosis (IVL), a rare smooth muscle tumour originating from the uterus.

MATERIALS AND METHODS

Twenty-seven patients with a histopathological diagnosis of IVL who underwent surgery were reviewed retrospectively. All patients underwent pelvic ultrasonography, inferior vena cava (IVC) ultrasonography, and echocardiography before surgery. Computed tomography (CT) with contrast enhancement was performed in patients with extrapelvic IVL. Some patients underwent pelvic magnetic resonance imaging (MRI).

RESULTS

Mean age was 44.81 years. Clinical symptoms were non-specific. IVL was intrapelvic in seven patients and extrapelvic in 20. Preoperative pelvic ultrasonography missed the diagnosis in 85.7% of patients with intrapelvic IVL. Pelvic MRI was useful to evaluate the parauterine vessels. Incidence of cardiac involvement was 59.26%. Echocardiography showed a highly mobile sessile mass in the right atrium with moderate-to-low echogenicity that originates from the IVC. Ninety per cent of extrapelvic lesions showed unilateral growth. The most common growth pattern was via the right uterine vein-internal iliac vein-IVC pathway.

CONCLUSION

The clinical symptoms of IVL are non-specific. For patients with intrapelvic IVL, early diagnosis is difficult. Pelvic ultrasound should focus on the parauterine vessels, the iliac and ovarian veins should be explored carefully. MRI has obvious advantages in evaluating parauterine vessel involvement, which is helpful for early diagnosis. For patients with extrapelvic IVL, CT should be performed before surgery as part of a comprehensive evaluation. IVC ultrasonography and echocardiography are recommended when IVL is highly suspected.

A GHz Silicon-Based Width Extensional Mode MEMS Resonator with Q over 10,000

This work presents a silicon-based capacitively transduced width extensional mode (WEM) MEMS rectangular plate resonator with quality factor (Q) of over 10,000 at a frequency of greater than 1 GHz. The Q value, determined by various loss mechanisms, was analyzed and quantified via numerical calculation and simulation. The energy loss of high order WEMs is dominated by anchor loss and phonon-phonon interaction dissipation (PPID). High-order resonators possess high effective stiffness, resulting in large motional impedance. To suppress anchor loss and reduce motional impedance, a novel combined tether was designed and comprehensively optimized. The resonators were batch fabricated based on a reliable and simple silicon-on-insulator (SOI)-based fabrication process. The combined tether experimentally contributes to low anchor loss and motional impedance. Especially in the 4th WEM, the resonator with a resonance frequency of 1.1 GHz and a Q of 10,920 was demonstrated, corresponding to the promising f × Q product of 1.2 × 10¹³. By using combined tether, the motional impedance decreases by 33% and 20% in 3rd and 4th modes, respectively. The WEM resonator proposed in this work has potential application for high-frequency wireless communication systems.

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

Significance

Rapid diagnosis and analysis of human keloid scar tissues in an automated manner are essential for understanding pathogenesis and formulating treatment solutions.

Aim

Our aim is to resolve the features of the extracellular matrix in human keloid scar tissues automatically for accurate diagnosis with the aid of machine learning.

Approach

Multiphoton microscopy was utilized to acquire images of collagen and elastin fibers. Morphological features, histogram, and gray-level co-occurrence matrix-based texture features were obtained to produce a total of 28 features. The minimum redundancy maximum relevancy feature selection approach was implemented to rank these features and establish feature subsets, each of which was employed to build a machine learning model through the tree-based pipeline optimization tool (TPOT).

Results

The feature importance ranking was obtained, and 28 feature subsets were acquired by incremental feature selection. The subset with the top 23 features was identified as the most accurate. Then stochastic gradient descent classifier optimized by the TPOT was generated with an accuracy of 96.15% in classifying normal, scar, and adjacent tissues. The area under curve of the classification results (scar versus normal and adjacent, normal versus scar and adjacent, and adjacent versus normal and scar) was 1.0, 1.0, and 0.99, respectively.

Conclusions

The proposed approach has great potential for future dermatological clinical diagnosis and analysis and holds promise for the development of computer-aided systems to assist dermatologists in diagnosis and treatment.

β-Catenin-treated peptides effectively inhibit the proliferation of colorectal cancer

To verify the inhibitory mechanism of β-catenin-designed peptides in colorectal cancer(CRC) tumors, the following experiments were performed. In vitro colony formation, Transwell assays, and flow cytometry were performed to assess the biological effects of designed peptides (F18KD, F20A4-7k, F20A4-10k, and F20A3-9k + F20A4-10k + F20A5-9k) in HT-29 cells. In vivo xenograft experiments were performed and treated with peptides. Next, tumors were subjected to Hematoxylin and eosin staining (HE), immunohistochemical, and terminal deoxynucleotidyl transferase dUTP nick end labeling staining assays to evaluate the inhibitory effect of peptides on tumors. β-Catenin levels were quantified via western blotting (WB) and quantitative real-time polymerase chain reaction, and β-catenin was located using confocal laser scanning microscopy. T-cell factor-4 (TCF-4), C-myc, and CCND1 levels were quantified via WB. Results were obtained as following. First, the peptides reduced viability, migration, and invasion; promoted apoptosis; and stabilized the S phase of HT-29 cells. Second, peptides suppressed tumor growth and downregulated the expression of CD34, vascular endothelial growth factor, and β-catenin in tumors. Furthermore, we found that peptides downregulated β-catenin expression in both the cytoplasm and nucleus; TCF-4, C-myc, and CCND1 expression was also downregulated. Notably, β-catenin-targeting peptides had a better inhibitory effect on CRC than non-β-catenin-target peptides, and a combination of peptides exerted a more potent inhibitory effect on CRC than single peptides. It suggested that β-Catenin-targeting peptides promote apoptosis in CRC tumors by inhibiting activation of the Wnt/β-catenin pathway.

Exploring the mechanisms underlying the therapeutic effect of the Radix Bupleuri-Rhizoma Cyperi herb pair on hepatocellular carcinoma using multilevel data integration and molecular docking

Traditional Chinese medicine (TCM) is a promising and effective treatment for cancer with minimal side effects through a multi-active ingredient multitarget network. Radix Bupleuri and Rhizoma Cyperi are listed as herbs dispersing stagnated liver Qi in China. They have been used clinically to treat liver diseases for many years and recent pharmacological studies have shown that they inhibit the proliferation of hepatocellular carcinoma (HCC). However, the pharmacological mechanisms, potential targets, and clinical value of the Radix Bupleuri-Rhizoma Cyperi herb pair (CXP) for suppressing HCC growth have not been fully elucidated. We identified 44 CXP targets involved in the treatment of HCC using the GEO dataset and HERB database. An analysis of the Traditional Chinese Medicine System Pharmacology Database (TCMSP) showed that CXP exerts synergistic effects through 4 active ingredients, including quercetin, stigmasterol, isorhamnetin, and kaempferol. GO and KEGG analyses revealed that CXP mainly regulates HCC progression through metabolic pathways, the p53 signaling pathway, and the cell cycle. Additionally, we applied The Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma (LIHC) database to perform the expression patterns, clinical features, and prognosis of 6 genes (CCNB1, CDK1, CDK4, MYC, CDKN2A, and CHEK1) in cell cycle pathways to reveal that CXP suppresses HCC clinical therapeutic value. Moreover, based on molecular docking, we further verified that CXP exerts its anti-HCC activity through the interaction of multiple active components with cell cycle-related genes. We systematically revealed the potential pharmacological mechanisms and targets of CXP in HCC using multilevel data integration and molecular docking strategies.

Advances and challenges in anode graphite recycling from spent lithium-ion batteries

Spent lithium-ion batteries (LIBs) have been one of the fast-growing and largest quantities of solid waste in the world. Spent graphite anode, accounting for 12-21 wt% of batteries, contains metals, binders, toxic, and flammable electrolytes. The efficient recovery of spent graphite is urgently needed for environmental protection and resource sustainability. Recently, more and more studies have been focused on spent graphite recycling, while the advance and challenges are rarely summarized. Hence, this study made a comprehensive review of graphite recycling including separation, regeneration, and synthesis of functional materials. Firstly, the pretreatment of graphite separation was overviewed. Then, the spent graphite regeneration methods such as leaching, pyrometallurgy, their integration processes, etc. were systematically introduced. Furthermore, the modification strategies to enhance the electrochemical performance were discussed. Subsequently, we reviewed in detail the synthesis of functional materials using spent graphite for energy and environmental applications including graphene, adsorbents, catalysts, capacitors, and graphite/polymer composites. Meanwhile, we briefly compared the economic and environmental benefits of graphite regeneration and other functional materials production. Finally, the technical bottlenecks and challenges for spent graphite recycling were summarized and some future research directions were proposed. This review contributes to spent LIBs recycling more efficiently and profitably in the future.

Competition among cities for export trade brings diversification: The experience of China’s urban export trade development

Market competition is considered to have a significant impact on product diversification, but related issues are rarely discussed on a city scale. To analyze the diversification of export commodities and export market of 270 Chinese cities, this study uses data from 2000 to 2017 based on the commodity concentration index, market concentration index, export similarity index, spatial stratified heterogeneity, and the Almon lag model. The study’s findings are: (1) The diversification of exports in most Chinese cities increased, which was higher in more developed cities in the southeast than in less developed ones in the northwest. With time, the degree of commodity and market diversification in some developed southeast Chinese cities (e.g., Shanghai) declined. This indicates the difference in and complexity of the evolution of export development in hundreds of Chinese cities between 2000 and 2017. (2) The export competition between cities became increasingly fierce, which effectively urged most of them to improve their export diversification levels. Facing increasing export competition pressure, 81.11% of the total number of cities will enhance the diversification of export commodities to cope with challenges posed by other cities. But only 56.67% will further expand the export market when the pressure of export competition increases. The biggest contribution of this study is the finding that for most Chinese cities, when export competition from other domestic cities increases, increasing diversification of products becomes a wise choice. However, the influence of competition on the diversification degree of the city’s export market is relatively weak. This study provides not only a new perspective for existing research on urban export trade, but also valuable information for cities to form a more profitable and robust trading system.

Unraveling the Mechanisms of Clinical Drugs-Induced Neural Tube Defects Based on Network Pharmacology and Molecular Docking Analysis

Chemotherapeutic agents such as methotrexate (MTX), raltitrexed (RTX), 5-fluorouracil (5-FU), hydroxyurea (HU), and retinoic acid (RA), and valproic acid (VPA), an antiepileptic drug, all can cause malformations in the developing central nervous system (CNS), such as neural tube defects (NTDs). However, the common pathogenic mechanisms remain unclear. This study aimed to explore the mechanisms of NTDs caused by MTX, RTX, 5-FU, HU, RA, and VPA (MRFHRV), based on network pharmacology and molecular biology experiments. The MRFHRV targets were integrated with disease targets, to find the potential molecules related to MRFHRV-induced NTDs. Protein-protein interaction analysis and molecular docking were performed to analyze these common targets. Utilizing the kyoto encyclopedia of genes and genomes (KEGG) signaling pathways, we analyzed and searched the possible causative pathogenic mechanisms by crucial targets and the signaling pathway. Results showed that MRFHRV induced NTDs through several key targets (including TP53, MAPK1, HSP90AA1, ESR1, GRB2, HDAC1, EGFR, PIK3CA, RXRA, and FYN) and multiple signaling pathways such as PI3K/Akt pathway, suggesting that abnormal proliferation and differentiation could be critical pathogenic contributors in NTDs induced by MRFHRV. These results were further validated by CCK8 assay in mouse embryonic stem cells and GFAP staining in embryonic brain tissue. This study indicated that chemotherapeutic and antiepileptic agents induced NTDs might through predicted targets TP53, MAPK1, GRB2, HDAC1, EGFR, PIK3CA, RXRA, and FYN and multiple signaling pathways. More caution was required for the clinical administration for women with childbearing potential and pregnant.

Wetting-Induced Water Promoted Flow on Tunable Liquid-Liquid Interface-Based Nanopore Membrane System

Membrane separation provides effective methods for solving the global water crisis. Contemporary membrane systems depend on interfacial interactions between liquid and solid membrane matrixes. However, it may lead to a limiting permeate flux due to the large flow resistance at hydrophobic liquid-solid interfaces. Herein, the liquid-liquid interface with improved interface energy is reversibly introduced in membrane systems to boost wetting and reduce transport resistance. A series of interfaces were systematically explored to reveal mechanisms of wetting and boosted flow performances, which are further supported by simulations. Findings of this study highlight that interfacial liquids with lower surface energies, lower viscosities, and higher solubilities can effectively improve water flow without sacrificing rejection performance, achieving by transforming a solid-liquid interface into liquid-liquid interface interaction. It provides a concept to design advanced membrane systems for water purification (e.g., desalination and oil-water separation) and energy conversion processes.