Although nano-immunotherapy has advanced dramatically in recent times, there remain two significant hurdles related to immune systems in cancer treatment, such as (namely) inevitable immune elimination of nanoplatforms and severely immunosuppressive microenvironment with low immunogenicity, hampering the performance of nanomedicines. To address these issues, several immune-regulating camouflaged nanocomposites have emerged as prevailing strategies due to their unique characteristics and specific functionalities. In this review, we emphasize the composition, performances, and mechanisms of various immune-regulating camouflaged nanoplatforms, including polymer-coated, cell membrane-camouflaged, and exosome-based nanoplatforms to evade the immune clearance of nanoplatforms or upregulate the immune function against the tumor. Further, we discuss the applications of these immune-regulating camouflaged nanoplatforms in directly boosting cancer immunotherapy and some immunogenic cell death-inducing immunotherapeutic modalities, such as chemotherapy, photothermal therapy, and reactive oxygen species-mediated immunotherapies, highlighting the current progress and recent advancements. Finally, we conclude the article with interesting perspectives, suggesting future tendencies of these innovative camouflaged constructs towards their translation pipeline.
Mepanipyrim, an anilinopyrimidine fungicide, has been extensively used to prevent fungal diseases in fruit culture. Currently, research on mepanipyrim-induced toxicity in organisms is still very scarce, especially visual developmental toxicity. Here, zebrafish larvae were employed to investigate mepanipyrim-induced visual developmental toxicity. Intense light and monochromatic light stimuli-evoked escape experiments were used to investigate vision-guided behaviors. Meanwhile, transcriptomic sequencing and real-time quantitative PCR assays were applied to assess the potential mechanisms of mepanipyrim-induced visual developmental toxicity and vision-guided behavioral alteration. Our results showed that mepanipyrim exposure could induce retinal impairment and vision-guided behavioral alteration in larval zebrafish. In addition, the grk1b gene of the phototransduction signaling pathway was found to be a potential aryl hydrocarbon receptor (AhR)-regulated gene. Mepanipyrim-induced visual developmental toxicity was potentially related to the AhR signaling pathway. Furthermore, mepanipyrim-induced behavioral alteration was guided by the visual function, and the effects of mepanipyrim on long and middle wavelength light-sensitive opsins may be the main cause of vision-guided behavioral alteration. Our results provide insights into understanding the relationship between visual development and vision-guided behaviors induced by mepanipyrim exposure.
Volatile market conditions and resultant market fluctuations have increased the demand for SMEs to adopt a strong brand related marketing communications activity with the support of integrated marketing communication (IMC) elements. IMC elements are critical in terms of building a strong strategic presence, which brings about an improvement in the business performance of SMEs. To examine the relationship of IMC elements to business performance, a quantitative descriptive study design was followed. 384 SME entrepreneurs’ responses from Klang Valley, Selangor, Malaysia were analyzed using PLS-SEM. The results indicate that all five elements of IMC performance have a direct and noteworthy effect on enhancing business performance. Moreover, a moderation result reflects a partial effect of market orientation between IMC elements and business performance. This paper presents IMC and market orientation as critical elements of the SME’s business performance strategy. This study would provide significant information to marketers and Chief Marketing Officers of SME’s in-service sector to adopt these vital managerial processes to enhance business performance.
Chemotherapy is commonly used for the treatment of lung cancer, but strong side effects and low treatment efficacy limit its clinical application. Here, extracellular vesicles (EVs) as natural drug delivery carriers were used to load conventional anticancer drug doxorubicin (DOX) and a chemosensitizer lonidamine (LND). Two types of EVs with different sizes (16k EVs and 120k EVs) were prepared using different centrifugation forces. We found that co-delivery of DOX and LND with both EVs enhanced the cytotoxicity and reduced the dose of the anticancer drug significantly in vitro. Effective delivery of anti-cancer drugs to cancer cells was achieved by direct fusion of EVs with the plasma membrane of cancer cells. On the other hand, DOX and LND inhibited cancer cell proliferation by increasing DNA damage, suppressing ATP production, and accelerating ROS generation synergistically. DOX and LND loaded EVs were also applied to the mouse lung cancer model and exhibited significant anticancer activity. In vivo study showed that smaller EVs exhibited higher anticancer efficiency. In conclusion, the co-delivery of the anticancer drug and the chemosensitizer with EVs may have potential clinical applications for cancer therapy.
Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here, we design a flexible single-cell multimodal analysis framework, called CITEMO, to integrate the transcriptome and antibody-derived tags (ADT) data to capture cell heterogeneity from the multi omics perspective. CITEMO uses Principal Component Analysis (PCA) to obtain a low-dimensional representation of the transcriptome and ADT, respectively, and then employs PCA again to integrate these low-dimensional multimodal data for downstream analysis. To investigate the effectiveness of the CITEMO framework, we apply CITEMO to analyse the cell subtypes of Cord Blood Mononuclear Cells (CBMC) samples. Results show that the CITEMO framework can comprehensively analyse single-cell multimodal samples and accurately identify cell subtypes. Besides, we find some specific immune cells that co-express multiple ADT markers. To better describe the co-expression phenomenon, we introduce the co-expression entropy to measure the heterogeneous distribution of the ADT combinations. To further validate the robustness of the CITEMO framework, we analyse Human Bone Marrow Cell (HBMC) samples and identify different states of the same cell type. CITEMO has an excellent performance in identifying cell subtypes and states for multimodal omics data. We suggest that the flexible design idea of CITEMO can be an inspiration for other single-cell multimodal tasks. The complete source code and dataset of the CITEMO framework can be obtained from https://github.com/studentiz/CITEMO.
Background Therapeutic resistance occurs in most patients with multiple myeloma (MM). One of the key mechanisms for MM drug resistance comes from the interaction between MM cells and adipocytes that inhibits drug-induced apoptosis in MM cells; MM cells reprogram adipocytes to morph into different characterizations, including exosomes, which are important for tumor-stroma cellular communication. However, the mechanism by which exosomes mediate the cellular machinery of the vicious cycle between MM cells and adipocytes remains unclear. Methods Adipocytes were either isolated from bone marrow aspirates of healthy donors or MM patients or derived from mesenchymal stem cells. Co-culturing normal adipocytes with MM cells was used to generate MM-associated adipocytes. Exosomes were collected from the culture medium of adipocytes. Annexin V-binding and TUNEL assays were performed to assess MM cell apoptosis. Methyltransferase activity assay and dot blotting were used to access the m ⁶ A methylation activity of methyltransferase like 7A (METTL7A). RIP, MeRIP-seq, and RNA–protein pull down for assessing the interaction between long non-cording RNAs (LncRNAs) and RNA binding proteins were performed. Adipocyte-specific enhancer of zeste homolog 2 (EZH2) knockout mice and MM-xenografted mice were used for evaluating MM therapeutic response in vivo. Results Exosomes collected from MM patient adipocytes protect MM cells from chemotherapy-induced apoptosis. Two LncRNAs in particular, LOC606724 and SNHG1, are significantly upregulated in MM cells after exposure to adipocyte exosomes. The raised LncRNA levels in MM cells are positively correlated to worse outcomes in patients, indicating their clinical relevancy in MM. The functional roles of adipocyte exosomal LOC606724 or SNHG1 in inhibition of MM cell apoptosis are determined by knockdown in adipocytes or overexpression in MM cells. We discovered the interactions between LncRNAs and RNA binding proteins and identified methyltransferase like 7A (METTL7A) as an RNA methyltransferase. MM cells promote LncRNA package into adipocyte exosomes through METTL7A-mediated LncRNA m ⁶ A methylation. Exposure of adipocytes to MM cells enhances METTL7A activity in m ⁶ A methylation through EZH2-mediated protein methylation. Conclusion This study elucidates an unexplored mechanism of how adipocyte-rich microenvironment exacerbates MM therapeutic resistance and indicates a potential strategy to improve therapeutic efficacy by blocking this vicious exosome-mediated cycle.
In this paper, we propose a spectral vanishing viscosity method for the triangular spectral element computation of high Reynolds number incompressible flows. This can be regarded as an extension of a similar stabilization technique for the standard spectral element method. The difficulty of this extension lies in the fact that a suitable definition of spectral vanishing viscosity operator in non-structured elements does not exist, and it is not clear that if a suitably defined spectral vanishing viscosity provides desirable dissipation for the artificially accumulated energy. The main contribution of the paper includes: 1) a well-defined spectral vanishing viscosity operator is proposed for non-standard spectral element methods for the Navier-Stokes equations based on triangular or tetrahedron partitions; 2) an evaluation technique is introduced to efficiently implement the stabilization term without extra computational cost; 3) the accuracy and efficiency of the proposed method is carefully examined through several numerical examples. Our numerical results show that the proposed method not only preserves the exponential convergence, but also produces improved accuracy when applied to the unsteady Navier-Stokes equations having smooth solutions. Especially, the stabilized triangular spectral element method efficiently stabilizes the simulation of high Reynolds incompressible flows.
Double-hit lymphoma is one of the most aggressive and refractory lymphoma subtypes with recurrent genetic abnormalities of MYC and BCL-2 or BCL6 rearrangement, leading to a poor prognosis in the present clinical practice. Therefore, new therapeutic strategies for eliminating double-hit lymphomas are urgently needed. Here, we reported that HZX-02-059, a novel PIKfyve and tubulin dual-target inhibitor, showed a highly cytotoxic activity against double-hit lymphoma cell lines in vitro and in vivo through a noncanonical caspase-independent cell death, methuosis. Mechanistically, the cytotoxicity triggered by HZX-02-059 was contributed to the PIKfyve/TFEB axis-induced cell death of methuosis, as well as the inhibition of tubulin and mTOR/Myc axis-induced cell cycle arrest. In summary, the present findings suggest that HZX-02-059 represents a good starting point for developing targeted therapeutics against double-hit lymphomas.
Background Gastric mucosal lesions (GML) are common in gastric diseases and seriously affect the quality of life. There are inevitable side effects in drug therapy. Acupuncture is an important part of traditional Chinese medicine. Electro-acupuncture (EA) has unique curative effect in treatment of GML. However, there are still few reports on the central mechanism of electro-acupuncture in treatment of GML. In this study, NMR metabonomics was used to explore the central metabolic change mechanism of electro-acupuncture in treatment of GML. Methods SD rats were randomly divided into Control, GML and EA groups. According to different intervention time, each group was further divided into 3 subgroups. This study mainly established GML model rats by 75% ethanol. Dynamic expressions of metabolites in cerebral cortex and medulla were observed by 1D ¹ H Nuclear Magnetic Resonance (NMR) metabolomics, combined with gastric mucosal histopathological examination to evaluate the time-effect relationship of electro-acupuncture at Zusanli (ST36) and Liangmen (ST21) points for 1 day, 4 days and 7 days treatment of GML. Results The results showed that the repair effect of electro-acupuncture on gastric mucosal injury was the most obvious in 4 days and stable in 7 days, and 4 days electro-acupuncture can effectively inhibit GML gastric mucosal inflammation and the expression of inflammatory cells. Meanwhile, the NMR spectrum results of medulla and cerebral cortex showed that, 21 potential metabolites were identified to participate in the mechanism of pathogenesis of GML and the regulation of electro-acupuncture, including 15 in medulla and 10 in cerebral cortex. Metabolic pathway analysis showed that the differential metabolites involved 19 metabolic pathways, which could be divided into energy, neurotransmitters, cells and cell membrane and antioxidation according to their functions. The correlation analysis of stomach, medulla and cerebral cortex shows that the stimulation signal of GML may reach the cerebral cortex from the stomach through medulla, and electro-acupuncture can treat GML by regulating the central nervous system (CNS). Conclusions 4 days electro-acupuncture treatment can significantly improve gastric mucosal injury, and the curative effect tends to be stable in 7 days treatment. Meanwhile, the pathogenesis of GML and the efficacy of electro-acupuncture involve metabolic pathways such as energy, neurotransmitters, cells and antioxidation, and electro-acupuncture can treat GML by regulating CNS.
Background Tumor cells tend to utilize glycolysis rather than aerobic respiration even under aerobic conditions. OVOL2, an inhibitory C2H2 zinc finger transcription factor, is a potential tumor suppressor in cancers. However, the association between OVOL2 and tumor energy metabolism is unknown. Methods Western blotting was used to determine the expression of OVOL2 in different non-small cell lung cancer (NSCLC) cell lines and mouse models. The metabolic parameters in NSCLC cells following overexpression or knockdown OVOL2 were examined. To define the mechanism by which OVOL2 regulates aerobic glycolysis, interacting protein of OVOl2 and downstream molecular events were identified by luciferase assay and co-immunoprecipitation. We documented the regulatory mechanism in mouse xenograft models. Finally, clinical relevance of OVOL2, NF-κB signaling and GLUT1 was measured by immunostaining. Results OVOL2 is downregulated in NSCLC and overexpression of OVOL2 inhibits the survival of cancer cells. Moreover, OVOL2 directly binds to P65 and inhibits the recruitment of P300 but facilitates the binding of HDAC1 to P65, which in turn negatively regulates NF-κB signaling to suppress GLUT1 translocation and glucose import. In contrast, OVOL2 expression is negatively regulated by NF-κB signaling in NSCLC cells via the ubiquitin–proteasome pathway. Re-expression of OVOL2 significantly compromise NF-κB signaling-induced GLUT1 translocation, aerobic glycolysis in NSCLC cells and mouse models. Immunostaining revealed inverse correlations between the OVOL2 and phosphorylated P65 levels and between the OVOL2 and membrane GLUT1 levels, and a strong correlation between the phosphorylated P65 and membrane GLUT1 levels. Conclusions These results suggest a regulatory circuit linking NF-κB and OVOL2, which highlights the role of NF-κB signaling and OVOL2 in the modulation of glucose metabolism in NSCLC.
Wood-based hydrogel with a unique anisotropic structure is an attractive soft material, but the presence of rigid crystalline cellulose in natural wood makes the hydrogel less flexible. In this study, an all-wood hydrogel was constructed by cross-linking cellulose fibers, polyvinyl alcohol (PVA) chains, and lignin molecules through the Hofmeister effect. The all-wood hydrogel shows a high tensile strength of 36.5 MPa and a strain up to ~ 438% in the longitudinal direction, which is much higher than its tensile strength (~ 2.6 MPa) and strain (~ 198%) in the radial direction, respectively. The high mechanical strength of all-wood hydrogels is mainly attributed to the strong hydrogen bonding, physical entanglement, and van der Waals forces between lignin molecules, cellulose nanofibers, and PVA chains. Thanks to its excellent flexibility, good conductivity, and sensitivity, the all-wood hydrogel can accurately distinguish diverse macroscale or subtle human movements, including finger flexion, pulse, and swallowing behavior. In particular, when “An Qi” was called four times within 15 s, two variations of the pronunciation could be identified. With recyclable, biodegradable, and adjustable mechanical properties, the all-wood hydrogel is a multifunctional soft material with promising applications, such as human motion monitoring, tissue engineering, and robotics materials.
The first carbon dot (CD)-based organic long persistent luminescence (OLPL) system exhibiting more than 1 h of duration was developed. In contrast to the established OLPL systems, herein, the reported CDs-based system (named m-CDs@CA) can be facilely and effectively fabricated using a household microwave oven, and more impressively, its LPL can be observed under ambient conditions and even in aqueous media. XRD and TEM characterizations, afterglow decay, time-resolved spectroscopy, and ESR analysis were performed, showing the successful composition of CDs and CA, the formation of exciplexes and long-lived charged-separated states. Further studies suggest that the production of covalent bonds between CA and CDs plays pivotal roles in activating LPL and preventing its quenching from oxygen and water. To the best of our knowledge, this is a very rare example of an OLPL system that exhibits hour-level afterglow under ambient conditions. Finally, applications of m-CDs@CA in glow-in-the-dark paints for emergency signs and multicolored luminous pearls were preliminarily demonstrated. This work may provide new insights for the development of rare-earth-free and robust OLPL materials.
In numerical simulations of complex flows with discontinuities, it is necessary to use nonlinear schemes. The spectrum of the scheme used has a significant impact on the resolution and stability of the computation. Based on the approximate dispersion relation method, we combine the corresponding spectral property with the dispersion relation preservation proposed by De and Eswaran (J Comput Phys 218:398–416, 2006) and propose a quasi-linear dispersion relation preservation (QL-GRP) analysis method, through which the group velocity of the nonlinear scheme can be determined. In particular, we derive the group velocity property when a high-order Runge–Kutta scheme is used and compare the performance of different time schemes with QL-GRP. The rationality of the QL-GRP method is verified by a numerical simulation and the discrete Fourier transform method. To further evaluate the performance of a nonlinear scheme in finding the group velocity, new hyperbolic equations are designed. The validity of QL-GRP and the group velocity preservation of several schemes are investigated using two examples of the equation for one-dimensional wave propagation and the new hyperbolic equations. The results show that the QL-GRP method integrated with high-order time schemes can determine the group velocity for nonlinear schemes and evaluate their performance reasonably and efficiently.
In the era of smart Internet-of-Things, convolutional neural network (CNN) models with low computational overhead are crucial for low-latency applications in resource-constrained embedded devices. The performance and efficiency of multiplication operations play a vital role in accelerating and optimizing CNN computation. In this article, we propose the MA4C technique, which reduces CNN computation overhead by converting a pretrained CNN’s parameters into approximated minimum signed digit (MSD) representations. MSD representation contains fewer non-zero digits on average compared to the binary representation of a number. The proposed scheme approximates the MSD representations by only considering a specified number of most significant digits. The MA4C technique reduces the computational complexity of multipliers by reducing the number of partial sums. The proposed MSD approximation was applied on various DNN models, and their performance was analyzed for different datasets, varying CNN depth, and network configuration. Implementation of our proposed method on FPGA reduced the logic circuits and multiplier latency by up to 4.2× and 1.2× respectively compared to an 8-bit Booth multiplier for most CNN models.
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