Explore the vast range of titles available.

This study aimed to develop a novel, targeted therapy for lumbar facet joint osteoarthritis (LFJ OA) by identifying a potent bone mesenchymal stem cell (BMSC) subpopulation for cartilage regeneration, engineering its exosomes (Exos) for specific delivery, and incorporating them into a sustained-release hydrogel system. The study also aimed to elucidate the underlying molecular mechanism. A CD56+CD271+ BMSCs subpopulation with potent cartilage regeneration potential within the human bone marrow was identified through single-cell RNA sequencing and then isolated. Exos were subsequently extracted from this specific subpopulation and engineered with a chondrocyte-specific antigen peptide (CAP) to generate CAP-CD56+CD271+ BMSCs Exos. A polyvinyl alcohol (PVA)/sodium alginate (SA) composite hydrogel was developed to serve as a sustained-release carrier for these targeted exosomes. Finally, the efficacy of the composite system was rigorously evaluated both in vitro and in vivo, and mechanistic insights were pursued through sequencing and molecular experiments. Compared with conventional BMSCs, the CD56+CD271+ BMSCs subpopulation and its derived exosomes demonstrated significantly enhanced pro-chondrogenic and anti-senescence capabilities compared to conventional BMSCs. CAP modification substantially improved in vivo targeting efficiency to chondrocytes, whereas the PVA/SA hydrogel enabled sustained exosome release, prolonging retention at injury sites. Implantation of the integrated CAP-Exos-PVA/SA system markedly improved osteoarthritis cartilage structure, increased matrix deposition, and suppressed the expression of matrix metalloproteinase-13 (MMP-13) and senescence markers (p16/p21/p53). Mechanistic studies revealed that the Exo-mediated delivery of miR-210-3p inhibited hypoxia-inducible factor-3α (HIF-3α) expression in chondrocytes. These therapeutic effects were abolished upon miR-210-3p blockade or HIF-3α overexpression. The CAP-CD56+CD271+ BMSCs Exos-PVA/SA hydrogel sustained-release system presents a promising and effective therapeutic approach for LFJ OA. [Display omitted] •Identified CD56+CD271+BMSC subpopulation via scRNA-seq with superior chondrogenic potential.•Engineered chondrocyte-targeted exosomes (CAP-Exos) enhancing cellular uptake in vivo.•The PVA/SA hydrogel enhances local drug delivery and sustains exosome release.•CAP-Exos-PVA/SA hydrogel improves chondrocyte senescence in LFJ OA.•Exosomal miR-210-3p inhibits HIF-3α—validated as key regenerative mechanism.

The development of cost-effective and highly sensitive hydrogen peroxide (H2O2) biosensors with robust stability is critical due to the pivotal role of H2O2 in biological processes and its broad utility across various applications. In this work, porous ceria hollow microspheres (CeO2-phm) were synthesized using a solvothermal synthesis method and employed in the construction of an electrochemical biosensor for H2O2 detection. The resulting CeO2-phm featured a uniform pore size centered at 3.4 nm and a high specific surface area of 168.6 m2/g. These structural attributes contribute to an increased number of active catalytic sites and promote efficient electrolyte penetration and charge transport, thereby enhancing its electrochemical sensing performance. When integrated into screen-printed carbon electrodes (CeO2-phm/cMWCNTs/SPCE), the CeO2-phm/cMWCNTs/SPCE-based biosensor exhibited a wide linear detection range from 0.5 to 450 μM, a low detection limit of 0.017 μM, and a high sensitivity of 2070.9 and 2161.6 μA·mM−1·cm−2—surpassing the performance of many previously reported H2O2 sensors. In addition, the CeO2-phm/cMWCNTs/SPCE-based biosensor possesses excellent anti-interference performance, repeatability, reproducibility, and stability. Its effectiveness was further validated through successful application in real sample analysis. Hence, CeO2-phm with solvothermal synthesis has great potential applications as a sensing material for the quantitative determination of H2O2.

Background Destruction of the blood–spinal cord barrier (BSCB) following spinal cord injury (SCI) can result in various harmful cytokines, neutrophils, and macrophages infiltrating into the injured site, causing secondary damage. Growing evidence shows that M2 macrophages and their small extracellular vesicles (sEVs) contribute to tissue repair in various diseases. Methods and Results In our previous proteomics‐based analysis of protein expression profiles in M2 macrophages and their sEVs (M2‐sEVs), the proteoglycan perlecan, encoded by HSPG2, was found to be upregulated in M2‐sEVs. Perlecan is a crucial component of basement membranes, playing a vital role in stabilising BSCB homeostasis and functions through its interactions with other matrix components, growth factors, and receptors. Here, we verified the high levels and remarkable therapeutic effect of M2‐sEV‐derived perlecan on the permeability of spinal cord microvascular endothelial cells exposed to oxygen glucose deprivation and reoxygenation in vitro. We also decorated the surface of M2‐sEVs with a fusion protein comprising the N‐terminus of Lamp2 and arginine glycine aspartic acid (RGD) peptides, which have an affinity for integrin αvβ3 and are primarily present on neovascular endothelium surfaces. In SCI model mice, these RGD‐M2‐sEVs accumulated at injured sites, promoting BSCB restoration. Finally, we identified M2‐sEV‐derived perlecan as a key player in regulating BSCB integrity and functional recovery post‐SCI. Conclusion Our results indicate that RGD‐M2‐sEVs promote BSCB restoration by transporting perlecan to neovascular endothelial cells, representing a potential strategy for SCI treatment. Key points Perlecan, a crucial component of basement membranes that plays a vital role in stabilising BSCB homeostasis and functions, was found to be upregulated in M2‐sEVs. M2‐sEVs decorated with RGD peptide can effectively target the neovascular endothelium surfaces at the injured spinal cord site. RGD‐M2‐sEVs promote BSCB restoration by transporting perlecan to neovascular endothelial cells, representing a potential strategy for SCI treatment. Perlecan, a crucial component of basement membranes that plays a vital role in stabilising BSCB homeostasis and functions, was found to be upregulated in M2‐sEVs. M2‐sEVs decorated with RGD peptide can effectively target the neovascular endothelium surfaces at the injured spinal cord site. RGD‐M2‐sEVs promote BSCB restoration by transporting perlecan to neovascular endothelial cells, representing a potential strategy for SCI treatment.

4-Amino- N ′-(4-aminobenzoyl)benzohydrazide (AAPDA), a diamine monomer that contains two amide groups, was synthesised by amidation and reduction, after which it was polymerised with pyromellitic dianhydride (PMDA) to prepare AAPPI, a novel polyimide. AAPPI exhibited excellent barrier performance, with oxygen- and water-vapor-transmission rates (OTR and WVTR, respectively) of only 1.7 cm 3 m −2 d −1 and 1.0 g m −2 d −1 , respectively. This polyimide (PI) also exhibits outstanding thermal properties, with a glass transition temperature (T g ) of 423 °C, a 5% weight-loss temperature (T d5% ) of 509 °C, and a coefficient of thermal expansion (CTE) of 2.58 ppm K −1 under nitrogen. The barrier performance of AAPPI was also compared to that of DABPI, a structurally similar PI. Molecular simulations, wide-angle x-ray diffractometry (WAXD), and positron annihilation lifetime spectroscopy (PALS) revealed that AAPPI forms many more interchain hydrogen bonds than DABPI due to its additional amide groups. Consequently, AAPPI has very tightly packed polymer chains, a high degree of crystallinity, a small free volume, and poor chain mobility. These factors generally inhibit the permeation of small molecules, which explains why AAPPI has better barrier properties than DABPI. This novel PI has broad applications for the packaging of flexible electronics.

The study of the prediction of stock market volatility is of great significance to rationally control financial market risks and increase excessive investment returns and has received extensive attention from academic and commercial circles. However, as a dynamic and complex system, the stock market is affected by multiple factors and has a comprehensive capability to include complex financial data. Given that the explanatory variables of influencing factors are diverse, heterogeneous and complex, the existing intelligent algorithms have great limitations for the analysis and processing of multi-source heterogeneous data in the stock market. Therefore, this study adopts the edge weight and information transmission mechanism suitable for subgraph data to complete node screening, the gate recurrent unit (GRU) and long short-term memory (LSTM) to aggregate subgraph nodes. The compiled data contain the metapaths of three types of index data, and the introduction of the association relationship attention dimension effectively mines the implicit meanings of multi-source heterogeneous data. The metapath attention mechanism is combined with a graph neural network to complete the classification of multi-source heterogeneous graph data, by which the prediction of stock market volatility is realized. The results show that the above method is feasible for the fusion of heterogeneous stock market data and the mining of implicit semantic information of association relations. The accuracy of the proposed method for the prediction of stock market volatility in this study is 16.64% higher than that of the dimensional reduction index and 14.48% higher than that of other methods for the fusion and prediction of heterogeneous data using the same model.

The low-carbon pilot city policy is an important initiative to explore the path of a win-win situation for both the economy and the environment. Since 2010, China has established 87 low-carbon pilot cities. This policy implementation aims to encourage green technology innovation among listed companies, thereby achieving sustainable corporate growth through the promotion of energy efficiency and renewable energy. This paper aims to unveil the relationship between low-carbon pilot city policies and green technology innovation. This paper explores the impact of policy implementation based on patent data of Chinese listed companies from 2007 to 2019. Empirical results show that the policy can promote green technology innovation among listed companies in the pilot cities. This finding still holds in the parallel trend test and the PSM-Multi-period DID test. Second, the policy has a greater effect on the green-technology innovation of non-state enterprises and can promote more green technology innovation activities of enterprises in the eastern region compared with other areas. Furthermore, in terms of different stock sectors, the low-carbon pilot city policy can significantly promote GEM-affiliated enterprises’ green technology innovation activities. Finally, listed companies with a high degree of digital transformation are more active in green technology innovation in the context of low-carbon pilot city policy.

With growing attention to the protection of circuit design, the demand of black polyimide (BPI) for flexible printed circuit board (FPCB) is increasing. However, the existing BPIs suffer from problems of poor mechanical and electrical properties, low solubility and masking capacity. To address these issues, a diamine monomer (TPCPODA) containing tetraphenylcyclopentadienone (TPCP) connected with phenyl ether unit was designed and prepared, which was subsequently reacted with 4,4'-(hexafluoroisopropylidene) diphthalic anhydride (6FDA) to prepare a soluble intrinsic BPI (TPCPOPI). TPCP grafted with phenyl ether acts as chromophores that shift the absorption scope of PI to the long wave direction. The resulted TPCPOPI shows a cut-off wavelength ( λ cut ) high to 673 nm. Theoretical calculations suggest that the visible absorption of TPCPOPI is mostly resulted from the electrons transitions of HOMO to LUMO within diamines moiety, in which the charges chiefly migrate from the aryl units at 2, 5-position to cyclopentadienone. Moreover, TPCPOPI shows outstanding electrical, mechanical and thermal properties and excellent solubility. Further investigation shows that the TPCPOPI-based two-layer flexible copper clad laminates (2L-FCCLs) has high peeling strength due to the incorporation of ketone and ether units. This work offers a prospective solution for the property improvement of BPIs for FPCBs. Graphical abstract

As an important part of financial market, stock market price volatility analysis has been the focus of academic and industry attention. Candlestick chart, as the most widely used indicator for evaluating stock market price volatility, has been intensively studied and explored. With the continuous development of computer technology, the stock market analysis method based on candlestick chart is gradually changed from manual to intelligent algorithm. However, how to effectively use stock market graphical indicators to analyze stock market price fluctuations has been pending solution, and deep learning algorithms based on structured data such as deep neural networks (DNN) and recurrent neural networks (RNNs) always have the problems of making it difficult to capture the laws and low generalization ability for stock market graphical indicators data processing. Therefore, this paper proposes a quantification method of stock market candlestick chart based on Hough variation, using the graph structure embedding method to represent candlestick chart features and multiple attention graph neural network for stock market price fluctuation prediction. The experimental results show that the proposed method can interpret the candlestick chart features more accurately and has superiority performance over state-of-the-art deep learning methods, including SVM, CNN, LSTM, and CNN-LSTM. Relative to these algorithms, the proposed method achieves an average performance improvement of 20.51% in terms of accuracy and further achieves at least 26.98% improvement in strategy returns in quantitative investment experiments.

Media-aware stock performance has been well recognized in recent studies. Previous research, however, focused on the content influence of the media, ignoring the manner in which the media is delivered. Based on the trust theory, this study argues that the media platforms, as media distribution vehicles and trust endorsement for news, are themselves influential on the stock market. This paper collected news data from seven Chinese mainstream media platforms and classified them into official, professional, and mass media platforms to investigate the impact of different platforms. The authors find that high official and professional media coverage predict increased abnormal returns, while high mass media coverage predicts the opposite. In addition, this paper systematically explores the mechanism of media platforms on stock performance from the perspectives of platform content, audience, and publication timeliness. The findings include that investors' attention to media platforms has a moderating effect on the stock performance, and such an effect is more salient in bear markets.