Taming Two-Dimensional Polymerization by a Machine-Learning Discovered Crystallization Model.

Rapidly synthesizing high-quality two-dimensional covalent organic frameworks (2D COFs) is crucial to their practical applications. Here, we use a machine-learning approach that overcomes the challenges associated with bottom-up model derivation for the non-classical 2D COF crystallization processes. The resulting model, referred to as NEgen1, establishes correlations among the induction time, nucleation rate, growth rate, bond-forming rate constants, and common solution synthesis conditions for 2D COFs that grow by a nucleation-elongation mechanism. The results elucidate the detailed competition between the nucleation and growth dynamics in solution, which has been inappropriately described previously by classical, empirical models with assumptions invalid for 2D COF polymerization. By understanding the dynamic processes at play, the NEgen1 model reveals a simple strategy of gradually increasing monomer addition speed for growing large 2D COF crystals. This insight enables us to rapidly synthesize large COF-5 colloids, which could only be achieved previously by prolonged reaction times or by introducing chemical modulators. These results highlight the potential for systematically improving the crystal quality of 2D COFs, which has wide-reaching relevance for many of the applications for which 2D COFs are speculated to be valuable.

Efficient Silver(I)-Containing i-Motif DNA Hybrid Catalyst for Enantioselective Diels-Alder Reactions.

The inherent chiral structures of DNA serve as attractive scaffolds to construct DNA hybrid catalysts for valuable enantioselective transformations. Duplex and G-quadruplex DNA-based enantioselective catalysis has made great progress, yet novel design strategies of DNA hybrid catalysts are highly demanding and atomistic analysis of active centers is still challenging. DNA i-motif structures could be finely tuned by different cytosine-cytosine base pairs, providing a new platform to design DNA catalysts. Herein, we found that a human telomeric i-motif DNA containing cytosine-silver(I)-cytosine (C-Ag+-C) base pairs interacting with Cu(II) ions (i-motif DNA(Ag+)/Cu2+) could catalyze Diels-Alder reactions with full conversions and up to 95% enantiomeric excess. As characterized by various physicochemical techniques, the presence of Ag+ is proved to replace the protons in hemiprotonated cytosine-cytosine (C:C+) base pairs and stabilize the DNA i-motif to allow the acceptance of Cu(II) ions. The i-motif DNA(Ag+)/Cu2+ catalyst shows about 8-fold rate acceleration compared with DNA and Cu2+. Based on DNA mutation experiments, thermodynamic studies and density function theory calculations, the catalytic center of Cu(II) ion is proposed to be located in a specific loop region via binding to one nitrogen-7 atom of an unpaired adenine and two phosphate-oxygen atoms from nearby deoxythymidine monophosphate and deoxyadenosine monophosphate, respectively.

Extraction of rare earth Eu from waste blue phosphor strengthened by microwave alkali roasting.

Spent phosphor is an important secondary resource for extracting rare earth elements. Microwave absorption properties and enhanced extraction of Eu from blue phosphor by microwave alkali roasting were studied. Dielectric properties of alkali roasting system were measured by resonator perturbation method. Dielectric constant increases linearly from 250 °C until it reaches a peak at 400 °C. The dielectric loss reaches a higher value at 400-550 °C, due to the strong microwave absorption properties of molten alkali and roasted products. Effects of roasting temperature, roasting time and alkali addition amount on Eu leaching were investigated. The phosphor was completely decomposed into Eu2O3, BaCO3 and MgO at 400 °C. The alkaline decomposition process of phosphor is more consistent with diffusion control model with Eα being 28.9 kJ/mol. Effects of the main leaching conditions on Eu leaching were investigated. The leaching kinetic of Eu was in line with diffusion control model with Eα being 5.74 kJ/mol. The leaching rules of rare earths in the mixed phosphor were studied. The results showed that the presence of red and green phosphor affected the recovery of blue phosphor. The optimum process parameters of rare earth recovery in single blue phosphor and mixed phosphor were obtained, and the recovery of Eu were 97.81% and 94.80%, respectively. Microwave alkali roasting promoted the dissociation of phosphor and leaching of rare earths. The results can provide reference for the efficient and selective recovery of rare earths in phosphors.

Comprehensive agricultural ecological effects of aeration on regenerated liquid fertilizer of mini flush toilet.

The high concentration of organic waste liquid obtained from the mini flush pipeline discharge technology based on source separation has the potential for fertilizer utilization. However, there are concerns about the risk of secondary pollution. This study proposes the idea of aeration treatment for regenerated liquid fertilizers to induce beneficial changes in their material composition and properties. Initially, this study compares the characteristic changes in nitrogen transformation of liquid fertilizer through aeration treatment. Subsequently, it examines the effects of different types of liquid fertilizers on soil properties, plant physiology, and soil microbial communities. Finally, we elucidate the flow and distribution of nitrogen in soil, plants, and nitrogen-containing gas emissions in agricultural ecosystems through material flow accounting. The study found that aeration treatment can reduce the ammonia nitrogen ratio while increasing the proportions of nitrite nitrogen and nitrate nitrogen. The regenerated liquid fertilizer through aeration treatment not only significantly increased the chlorophyll, protein, and polysaccharide content of vegetable leaves (P < 0.05) but also reduced nitrate accumulation. Moreover, it can reduce the risk of soil nitrate nitrogen leaching and increase the diversity of soil bacterial communities, enhancing the ecological functions of bacteria involved in carbon and nitrogen cycling. Material flow accounting indicated that aeration treatment for liquid fertilizer could reduce gaseous nitrogen loss by 50.0 %, improve the nitrogen utilization efficiency of vegetables by 95.5 %, and enhance soil nitrogen retention by 11.4 %. Overall, the results show that aeration treatment can improve the agricultural utilization of liquid fertilizer and reduce the risk of secondary pollution, providing preliminary decision-making support for optimizing resource treatment strategies for mini-flush toilet fecal waste to realize the agricultural cycle.

Role of Plant-Growth-Promoting Rhizobacteria in Plant Machinery for Soil Heavy Metal Detoxification.

Heavy metals migrate easily and are difficult to degrade in the soil environment, which causes serious harm to the ecological environment and human health. Thus, soil heavy metal pollution has become one of the main environmental issues of global concern. Plant-growth-promoting rhizobacteria (PGPR) is a kind of microorganism that grows around the rhizosphere and can promote plant growth and increase crop yield. PGPR can change the bioavailability of heavy metals in the rhizosphere microenvironment, increase heavy metal uptake by phytoremediation plants, and enhance the phytoremediation efficiency of heavy-metal-contaminated soils. In recent years, the number of studies on the phytoremediation efficiency of heavy-metal-contaminated soil enhanced by PGPR has increased rapidly. This paper systematically reviews the mechanisms of PGPR that promote plant growth (including nitrogen fixation, phosphorus solubilization, potassium solubilization, iron solubilization, and plant hormone secretion) and the mechanisms of PGPR that enhance plant-heavy metal interactions (including chelation, the induction of systemic resistance, and the improvement of bioavailability). Future research on PGPR should address the challenges in heavy metal removal by PGPR-assisted phytoremediation.

Dynamical interplay between superconductivity and pseudogap in cuprates as revealed by terahertz third-harmonic generation spectroscopy.

We report on nonlinear terahertz third-harmonic generation (THG) measurements on YBa2Cu3O6+x thin films. Different from conventional superconductors, the THG signal starts to appear in the normal state, which is consistent with the crossover temperature T* of pseudogap over broad doping levels. Upon lowering the temperature, the THG signal shows an anomaly just below Tc in the optimally doped sample. Notably, we observe a beat pattern directly in the measured real-time waveform of the THG signal. We elaborate that the Higgs mode, which develops below Tc, couples to the mode already developed below T*, resulting in an energy level splitting. However, this coupling effect is not evident in underdoped samples. We explore different potential explanations for the observed phenomena. Our research offers valuable insight into the interplay between superconductivity and pseudogap.

Crocetin inhibits mast cell-dependent immediate-type allergic reactions through Ca2+/PLC/IP3 and TNF pathway.

Crocetin is a kind of glycocone naturally occurring in Crocus sativus L.. It is an active metabolite produced by biohydrolysis of Crocus sativus L.. Crocetin has anti-cardiovascular diseases and antioxidant effects, but its anti-allergic effect has not been reported. In this study, the inhibitory effect of crocetin on immunoglobulin E (IgE) - mediated allergic reaction and the mechanism of action were investigated. The passive cutaneous anaphylaxis (PCA) was used to elucidate the anti-allergic effects of crocetin in vivo. Degranulation assay, calcium imaging, and cytokine release assay were to evaluate the anti-allergic effect of crocetin in vitro. We found that crocetin IgE-mediated RBL-2H3 cell degranulation and allergy both in vitro and in vivo. The TNF pathway was inhibited by crocetin in our RNA-seq sequences, Furthermore, crocetin inhibits IgE-mediated calcium influx, and PLC / IP3 phosphorylation in RBL-2H3 cells. Our findings suggested that crocetin revealed prominent anti-allergy activity through TNF and Ca2+/PLC/IP3 pathway.

Molecular Basis and Genome Editing Applications of a Compact Eubacterium ventriosum CRISPR-Cas9 System.

CRISPR-Cas9 systems have been widely harnessed for diverse genome editing applications because of their ease of use and high efficiency. However, the large molecular sizes and strict PAM requirements of commonly used CRISPR-Cas9 systems restrict their broad applications in therapeutics. Here, we report the molecular basis and genome editing applications of a novel compact type II-A Eubacterium ventriosum CRISPR-Cas9 system (EvCas9) with 1107 residues and distinct 5'-NNGDGN-3' (where D represents A, T, or G) PAM specificity. We determine the cryo-EM structure of EvCas9 in a complex with an sgRNA and a target DNA, revealing the detailed PAM recognition and sgRNA and target DNA association mechanisms. Additionally, we demonstrate the robust genome editing capacity of EvCas9 in bacteria and human cells with superior fidelity compared to SaCas9 and SpCas9, and we engineer it to be efficient base editors by fusing a cytidine or adenosine deaminase. Collectively, our results facilitate further understanding of CRISPR-Cas9 working mechanisms and expand the compact CRISPR-Cas9 toolbox.

Radical chemistry in polymer science: an overview and recent advances.

Radical chemistry is one of the most important methods used in modern polymer science and industry. Over the past century, new knowledge on radical chemistry has both promoted and been generated from the emergence of polymer synthesis and modification techniques. In this review, we discuss radical chemistry in polymer science from four interconnected aspects. We begin with radical polymerization, the most employed technique for industrial production of polymeric materials, and other polymer synthesis involving a radical process. Post-polymerization modification, including polymer crosslinking and polymer surface modification, is the key process that introduces functionality and practicality to polymeric materials. Radical depolymerization, an efficient approach to destroy polymers, finds applications in two distinct fields, semiconductor industry and environmental protection. Polymer chemistry has largely diverged from organic chemistry with the fine division of modern science but polymer chemists constantly acquire new inspirations from organic chemists. Dialogues on radical chemistry between the two communities will deepen the understanding of the two fields and benefit the humanity.

Revealing the frequency-dependent oscillations in the nonlinear terahertz response induced by the Josephson current.

Nonlinear responses of superconductors to intense terahertz radiation has been an active research frontier. Using terahertz pump-terahertz probe spectroscopy, we investigate the c-axis nonlinear optical response of a high-temperature superconducting cuprate. After excitation by a single-cycle terahertz pump pulse, the reflectivity of the probe pulse oscillates as the pump-probe delay is varied. Interestingly, the oscillatory central frequency scales linearly with the probe frequency, a fact widely overlooked in pump-probe experiments. By theoretically solving the nonlinear optical reflection problem on the interface, we show that our observation is well explained by the Josephson-type third-order nonlinear electrodynamics, together with the emission coefficient from inside the material into free space. The latter results in a strong enhancement of the emitted signal whose physical frequency is around the Josephson plasma edge. Our result offers a benchmark for and new insights into strong-field terahertz spectroscopy of related quantum materials.

Single-channel system for joint unambiguous measurement of DFS and AOA based on serrodyne modulation.

In this paper, a photonic-assisted system for simultaneous and unambiguous measurement of the Doppler frequency shift (DFS) and angle-of-arrival (AOA) using a dual-parallel dual-drive Mach-Zehnder modulator (DP-DDMZM) is proposed and investigated. The echo signals received by two receiving antennas are applied to the radio frequency ports of one sub-DDMZM of the DP-DDMZM. The bias port of the sub-DDMZM is fed by a binary electrical signal that is used to construct two different mapping curves on the relationship between the phase difference and the power of the output intermediate frequency (IF) signal. Therefore, unambiguous AOA measurement with extended range can be realized. The transmitted signal is input into the other sub-DDMZM to implement single-sideband modulation, which is then frequency shifted based on serrodyne modulation. Both the value and direction of DFS can be derived intuitively from the frequency of the output IF signal. Simulation results show that the measurement error of unambiguous DFS measurement is no more than ±0.008H z in the range of -100k H z to 100 kHz, and the measurement error of unambiguous AOA is less than ±0.2∘ in the range of -70.8∘ to 70.8°. Moreover, since the scheme does not involve the construction of multi-channels or use of any filter or polarization dependent device, the system has concise structure, high accuracy, large operating bandwidth, and strong robustness, and can be considered as a very promising solution for actual applications.

Tuning Crystallinity and Stacking of Two-Dimensional Covalent Organic Frameworks through Side-Chain Interactions.

Two-dimensional covalent organic frameworks (2D COFs) form as layered 2D polymers whose sheets stack through high-surface-area, noncovalent interactions that can give rise to different interlayer arrangements. Manipulating the stacking of 2D COFs is crucial since it dictates the effective size and shape of the pores as well as the specific interactions between functional aromatic systems in adjacent layers, both of which will strongly influence the emergent properties of 2D COFs. However, principles for tuning layer stacking are not yet well understood, and many 2D COFs are disordered in the stacking direction. Here, we investigate effects of pendant chain length through a series of 2D imine-linked COFs functionalized with n-alkyloxy chains varying in length from one carbon (C1 COF) to 11 carbons (C11 COF). This series reveals previously unrecognized and unanticipated trends in both the stacking geometry and crystallinity. C1 COF adopts an averaged eclipsed geometry with no apparent offset between layers. In contrast, all subsequent chain lengths lead to some degree of unidirectional slip stacking. As pendant chain length is increased, trends show average layer offset increasing to a maximum of 2.07 Å in C5 COF and then decreasing as chain length is extended through C11 COF. Counterintuitively, shorter chains (C2-C4) give rise to lower yields of weakly crystalline materials, while longer chains (C6-C9) produce greater yields of highly crystalline materials, as confirmed by powder X-ray diffraction and scanning electron microscopy. Molecular dynamics simulations corroborate these observations, suggesting that long alkyl chains can interact favorably to promote the self-assembly of sheets. In situ proton NMR spectroscopy provides insights into the reaction equilibrium as well as the relationship between low COF yields and low crystallinity. These results provide fundamental insights into principles of supramolecular assembly in 2D COFs, demonstrating an opportunity for harnessing favorable side-chain interactions to produce highly crystalline materials.

Discovery of novel JAK1 inhibitors through combining machine learning, structure-based pharmacophore modeling and bio-evaluation.

BACKGROUND: Janus kinase 1 (JAK1) plays a critical role in most cytokine-mediated inflammatory, autoimmune responses and various cancers via the JAK/STAT signaling pathway. Inhibition of JAK1 is therefore an attractive therapeutic strategy for several diseases. Recently, high-performance machine learning techniques have been increasingly applied in virtual screening to develop new kinase inhibitors. Our study aimed to develop a novel layered virtual screening method based on machine learning (ML) and pharmacophore models to identify the potential JAK1 inhibitors. METHODS: Firstly, we constructed a high-quality dataset comprising 3834 JAK1 inhibitors and 12,230 decoys, followed by establishing a series of classification models based on a combination of three molecular descriptors and six ML algorithms. To further screen potential compounds, we constructed several pharmacophore models based on Hiphop and receptor-ligand algorithms. We then used molecular docking to filter the recognized compounds. Finally, the binding stability and enzyme inhibition activity of the identified compounds were assessed by molecular dynamics (MD) simulations and in vitro enzyme activity tests. RESULTS: The best performance ML model DNN-ECFP4 and two pharmacophore models Hiphop3 and 6TPF 08 were utilized to screen the ZINC database. A total of 13 potentially active compounds were screened and the MD results demonstrated that all of the above molecules could bind with JAK1 stably in dynamic conditions. Among the shortlisted compounds, the four purchasable compounds demonstrated significant kinase inhibition activity, with Z-10 being the most active (IC50 = 194.9 nM). CONCLUSION: The current study provides an efficient and accurate integrated model. The hit compounds were promising candidates for the further development of novel JAK1 inhibitors.

Shared genetic architecture of blood eosinophil counts and asthma in UK Biobank.

Rationale: Asthma is a complex, heterogeneous disease strongly associated with type 2 inflammation, and blood eosinophil counts guide therapeutic interventions in moderate and severe asthma. Eosinophils are leukocytes involved in type 2 immune responses. Despite these critical associations between asthma and blood eosinophil counts, the shared genetic architecture of these two traits remains unknown. The objective of the present study was to characterise the genetic architecture of blood eosinophil counts and asthma in the UK Biobank. Methods: We performed genome-wide association studies (GWAS) of doctor-diagnosed asthma, blood eosinophil, neutrophil, lymphocyte and monocyte counts in the UK Biobank. Genetic correlation analysis was performed on GWAS results and validated in the Trans-National Asthma Genetic Consortium (TAGC) study of asthma. Results: GWAS of doctor-diagnosed asthma and blood eosinophil counts in the UK Biobank identified 585 and 3429 significant variants, respectively. STAT6, a transcription factor involved in interleukin-4 signalling, was a key shared pathway between asthma and blood eosinophil counts. Genetic correlation analysis demonstrated a positive correlation between doctor-diagnosed asthma and blood eosinophil counts (r=0.38±0.10, correlation±se; p=4.7×10-11). As a validation of this association, we found a similar correlation between TAGC and blood eosinophil counts in the UK Biobank (0.37±0.08, correlation±se; p=1.2×10-6). Conclusions: These findings define the shared genetic architecture between blood eosinophil counts and asthma risk in subjects of European ancestry and point to a genetic link to the STAT6 signalling pathway in these two traits.

Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations.

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.e. sequence pre-training-based graph neural network (SPGNN), that combines pre-training and fine-tuning stages to predict lncRNA-miRNA associations from RNA sequences and the existing interactions represented as a graph. First, we utilize a sequence-to-vector technique to generate pre-trained embeddings based on the sequences of all RNAs during the pre-training stage. In the fine-tuning stage, we use Graph Neural Network to learn node representations from the heterogeneous graph constructed using lncRNA-miRNA association information. We evaluate our proposed scheme SPGNN on our newly collected animal lncRNA-miRNA association dataset and demonstrate that combining the $k$-mer technique and Doc2vec model for pre-training with the Simple Graph Convolution Network for fine-tuning is effective in predicting lncRNA-miRNA associations. Our approach outperforms state-of-the-art baselines across various evaluation metrics. We also conduct an ablation study and hyperparameter analysis to verify the effectiveness of each component and parameter of our scheme. The complete code and dataset are available on GitHub: https://github.com/zixwang/SPGNN.

What is the Real Need for Scene Text Removal? Exploring the Background Integrity and Erasure Exhaustivity Properties.

As a crucial application in privacy protection, scene text removal (STR) has received amounts of attention in recent years. However, existing approaches coarsely erasing texts from images ignore two important properties: the background texture integrity (BI) and the text erasure exhaustivity (EE). These two properties directly determine the erasure performance, and how to maintain them in a single network is the core problem for STR task. In this paper, we attribute the lack of BI and EE properties to the implicit erasure guidance and imbalanced multi-stage erasure respectively. To improve these two properties, we propose a new ProgrEssively Region-based scene Text eraser (PERT). There are three key contributions in our study. First, a novel explicit erasure guidance is proposed to enhance the BI property. Different from implicit erasure guidance modifying all the pixels in the entire image, our explicit one accurately performs stroke-level modification with only bounding-box level annotations. Second, a new balanced multi-stage erasure is constructed to improve the EE property. By balancing the learning difficulty and network structure among progressive stages, each stage takes an equal step towards the text-erased image to ensure the erasure exhaustivity. Third, we propose two new evaluation metrics called BI-metric and EE-metric, which make up the shortcomings of current evaluation tools in analyzing BI and EE properties. Compared with previous methods, PERT outperforms them by a large margin in both BI-metric ( ↑ 6.13 %) and EE-metric ( ↑ 1.9 %), obtaining SOTA results with high speed (71 FPS) and at least 25% lower parameter complexity. Code will be available at https://github.com/wangyuxin87/PERT.

Scraping Therapy Improved Muscle Regeneration through Regulating GLUT4/Glycolytic and AMPK/mTOR/4EBP1 Pathways in Rats with Lumbar Multifidus Injury.

Background: High morbidity of nonspecific low back pain (NLBP) and large consumption of medical resources caused by it have become a heavy social burden. There are many factors inducing NLBP, among which the damage and atrophy of multifidus (MF) are most closely related to NLBP. Scraping therapy can have significant treatment effects on NLBP with fewer adverse reactions and less medical fund input than other modalities or medications. However, the mechanism of scraping therapy treating NLBP remains unclarified. Here, we wanted to investigate the effects of scraping therapy on promoting MF regeneration and the underlying mechanisms. Methods: A total of 54 male rats (SD, 6-7 weeks old) were randomly divided into nine groups, namely, K, M6h, M1d, M2d, M3d, G6h, G1d, G2d, and G3d, with six rats in each group. They were injected with bupivacaine (BPVC) to intentionally induce MF injury. We then performed scraping therapy on the rats that had been randomly chosen and compared treatment effects at different time points. In vitro data including skin temperature and tactile allodynia threshold were collected and histological sections were analyzed. mRNA sequencing was applied to distinguish the genes or signaling pathways that had been altered due to scraping therapy, and the results were further verified through reverse transcription polymerase chain reaction and Western blot analysis. Results: Transitory petechiae and ecchymosis both on and beneath the rats' skin raised by scraping therapy gradually faded in about 3 d. Cross-sectional area (CSA) of MF was significantly smaller 30 h, 2 d, and 4 d after modeling (P=0.007, P=0.001, and P=0.015, respectively, vs. the blank group) and was significantly larger in the scraping group 1 d after treatment (P=0.002 vs. the model 1d group). Skin temperature significantly increased immediately after scraping (P < 0.001) and hindlimb pain threshold increased on the 2nd day after scraping (P=0.046 and P=0.028, respectively). 391 differentially expressed genes and 8 signaling pathways were characterized 6 h after scraping; only 3 differentially expressed genes and 3 signaling pathways were screened out 2 d after treatment. The amounts of mRNAs or proteins for GLUT4, HK2, PFKM, PKM, LDHA (which belong to the GLUT4/glycolytic pathway), p-mTOR, p-4EBP1 (which belong to the AMPK/mTOR/4EBP1 pathway), and BDH1 were enhanced, and p-AMPKα was decreased after scraping therapy. Conclusions: Scraping therapy has therapeutic effects on rats with multifidus injury by promoting muscle regeneration via regulating GLUT4/glycolytic and AMPK/mTOR/4EBP1 signaling pathways.

Electroacupuncture Alleviates Neuropathic Pain by Suppressing Ferroptosis in Dorsal Root Ganglion via SAT1/ALOX15 Signaling.

Neuropathic pain affects globally about 7-10% of the general population. Electroacupuncture (EA) effectively relieves neuropathic pain symptoms without causing any side effects; however, the underlying molecular mechanisms remain unclear. We established a chronic constriction injury (CCI)-induced rat model of neuropathic pain. RNA sequencing was used to screen for differentially expressed genes in the dorsal root ganglion after CCI and EA treatment. We identified gene markers of ferroptosis spermidine/spermine N1-acetyltransferase 1 (Sat1) and arachidonate 15-lipoxygenase (Alox15) to be dysregulated in the CCI-induced neuropathic pain model. Furthermore, EA relieved CCI-induced pain as well as ferroptosis-related symptoms in the dorsal root ganglion, including lipid peroxidation and iron overload. Finally, SAT1 knockdown also alleviated mechanical and thermal pain hypersensitivity and reversed ferroptosis damage. In conclusion, we showed that EA inhibited ferroptosis by regulating the SAT1/ALOX15 pathway to treat neuropathic pain. Our findings provide insight into the mechanisms of EA and suggest a novel therapeutic target for neuropathic pain.

Implantation of hydrogel-liposome nanoplatform inhibits glioblastoma relapse by inducing ferroptosis.

Glioblastoma is acknowledged as the most aggressive cerebral tumor in adults. However, the efficacy of current standard therapy is seriously undermined by drug resistance and suppressive immune microenvironment. Ferroptosis is a recently discovered form of iron-dependent cell death that may have excellent prospect as chemosensitizer. The utilization of ferropotosis inducer Erastin could significantly mediate chemotherapy sensitization of Temozolomide and exert anti-tumor effects in glioblastoma. In this study, a combination of hydrogel-liposome nanoplatform encapsulated with Temozolomide and ferroptosis inducer Erastin was constructed. The αvß3 integrin-binding peptide cyclic RGD was utilized to modify codelivery system to achieve glioblastoma targeting strategy. As biocompatible drug reservoirs, cross-linked GelMA (gelatin methacrylamide) hydrogel and cRGD-coated liposome realized the sustained release of internal contents. In the modified intracranial tumor resection model, GelMA-liposome system achieved slow release of Temozolomide and Erastin in situ for more than 14 d. The results indicated that nanoplatform (T+E@LPs-cRGD+GelMA) improved glioblastoma sensitivity to chemotherapeutic temozolomide and exerted satisfactory anti-tumor effects. It was demonstrated that the induction of ferroptosis could be utilized as a therapeutic strategy to overcome drug resistance. Furthermore, transcriptome sequencing was conducted to reveal the underlying mechanism that the nanoplatform (T+E@LPs-cRGD+GelMA) implicated in. It is suggested that GelMA-liposome system participated in the immune response and immunomodulation of glioblastoma via interferon/PD-L1 pathway. Collectively, this study proposed a potential combinatory therapeutic strategy for glioblastoma treatment.