Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability....Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability.In this study,a novel perovskite-based composite with positive sensitivity to temperature was designed and obtained based on its inverse temperature crystallization,demonstrating good flexibility and solution processability.The supercritical drying method was used to address the limitations of annealing drying in preparing high-performance perovskite.Optimizing the precursor composition proved to be an effective approach for achieving high fluorescence and structural integrity in the perovskite material.This perovskite-based composite exhibited a positive temperature sensitivity of 28.563%℃^(-1)for intensity change and excellent temperature cycling reversibility in the range of 25-40℃in an ambient environment.This made it suitable for use as a smart window with rapid response.Furthermore,the perovskite composite was found to offer temperature-sensing photoluminescence and flexible processability due to its components of perovskite-based compounds and polyethylene oxide.The organic precursor solvent could be a promising candidate for use as ink to print or write on various substrates for optoelectronic devices responding to temperature.展开更多
BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors...BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.展开更多
The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functio...The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.展开更多
Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source fo...Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source for NPC survival,but the effects and underlying mechanisms of increased extracellular matrix(ECM)stiffness on NPC glycolysis remain unknown.In this study,hydrogels with different stiffness were established to mimic the mechanical environment of NPCs.Notably,increased matrix stiffness in degenerated NP tissues from IVDD patients was accompanied with impaired glycolysis,and NPCs cultured on rigid substrates exhibited a reduction in glycolysis.展开更多
Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-po...Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction.The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 10^(12)Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector(4.66 × 10^(11)Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.展开更多
Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to p...Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.展开更多
This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh ...This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.展开更多
Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a sim...Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a simultaneous enhancement of permeability and selectivity remains a formidable challenge,due to the difficulty of achieving an optimal match between polymers and fillers.In this study,we incorporate a porous carbon-based zinc oxide composite(C@ZnO)into high-permeability polymers of intrinsic microporosity(PIMs)to fabricate MMMs.The dipole–dipole interaction between C@ZnO and PIMs ensures their exceptional compatibility,mitigating the formation of non-selective voids in the resulting MMMs.Concurrently,C@ZnO with abundant interconnected pores can provide additional low-resistance pathways for gas transport in MMMs.As a result,the CO_(2) permeability of the optimized C@ZnO/PIM-1 MMMs is elevated to 13,215 barrer,while the CO_(2)/N_(2) and CO_(2)/CH_(4) selectivity reached 21.5 and 14.4,respectively,substantially surpassing the 2008 Robeson upper bound.Additionally,molecular simulation results further corroborate that the augmented membrane gas selectivity is attributed to the superior CO_(2) affinity of C@ZnO.In summary,we believe that this work not only expands the application of MMMs for gas separation but also heralds a paradigm shift in the application of porous carbon materials.展开更多
We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of ...We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.展开更多
In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently so...Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently solving linear systems Aα=b.The objective of this paper is to provide one new iterative algorithm based on BCR method to find the symmetric periodic solutions of linear periodic matrix equations.This kind of periodic matrix equations has not been dealt with yet.This iterative method is guaranteed to converge in a finite number of steps in the absence of round-off errors.Some numerical results are performed to illustrate the efficiency and feasibility of new method.展开更多
Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage...Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage transformer errors, particularly minor variations in multi-channel setups, remains challenging. This paper proposes a method for online error tracking of multi-channel capacitive voltage transformers using a Co-Prediction Matrix. The approach leverages the strong correlation between in-phase channels, particularly the invariance of the signal proportions among them. By establishing a co-prediction matrix based on these proportional relationships, The influence of voltage changes on the primary measurements is mitigated. Analyzing the relationships between the co-prediction matrices over time allows for inferring true measurement errors. Experimental validation with real-world data confirms the effectiveness of the method, demonstrating its capability to continuously track capacitive voltage transformer measurement errors online with precision over extended durations.展开更多
Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter...Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter physics,materials science,and mineral separation technologies,these materials are now poised for new opportunities in theoretical research and development.This review provides a comprehensive analysis of these matrices,encompassing their structure,size,shape,composition,properties,and multifaceted applications.These materials,primarily composed of alloys of transition state metasl such as iron(Fe),cobalt(Co),titanium(Ti),and nickel(Ni),exhibit unique attributes like high magnetization rates,low eleastic modulus,and high saturation magnetic field strengths.Furthermore,the studies also delve into the complex mechanical interactions involved in the separation of magnetic particles using magnetic separator matrices,including magnetic,gravitational,centrifugal,and van der Waals forces.The review outlines how size and shape effects influence the magnetic behavior of matrices,offering new perspectives for innovative applications of magnetic matrices in various domains of materials science and magnetic separation.展开更多
The discovery of advanced materials is a cornerstone of human technological development and progress.The structures of materials and their corresponding properties are essentially the result of a complex interplay of ...The discovery of advanced materials is a cornerstone of human technological development and progress.The structures of materials and their corresponding properties are essentially the result of a complex interplay of multiple degrees of freedom such as lattice,charge,spin,symmetry,and topology.This poses significant challenges for the inverse design methods of materials.Humans have long explored new materials through numerous experiments and proposed corresponding theoretical systems to predict new material properties and structures.With the improvement of computational power,researchers have gradually developed various electronic-structure calculation methods,such as the density functional theory and high-throughput computational methods.Recently,the rapid development of artificial intelligence(AI)technology in computer science has enabled the effective characterization of the implicit association between material properties and structures,thus forming an efficient paradigm for the inverse design of functional materials.Significant progress has been achieved in the inverse design of materials based on generative and discriminative models,attracting widespread interest from researchers.Considering this rapid technological progress,in this survey,we examine the latest advancements in AI-driven inverse design of materials by introducing the background,key findings,and mainstream technological development routes.In addition,we summarize the remaining challenges for future directions.This survey provides the latest overview of AI-driven inverse design of materials,which can serve as a useful resource for researchers.展开更多
Vascular endothelial growth factor and its mimic peptide KLTWQELYQLKYKGI(QK)are widely used as the most potent angiogenic factors for the treatment of multiple ischemic diseases.However,conventional topical drug deliv...Vascular endothelial growth factor and its mimic peptide KLTWQELYQLKYKGI(QK)are widely used as the most potent angiogenic factors for the treatment of multiple ischemic diseases.However,conventional topical drug delivery often results in a burst release of the drug,leading to transient retention(inefficacy)and undesirable diffusion(toxicity)in vivo.Therefore,a drug delivery system that responds to changes in the microenvironment of tissue regeneration and controls vascular endothelial growth factor release is crucial to improve the treatment of ischemic stroke.Matrix metalloproteinase-2(MMP-2)is gradually upregulated after cerebral ischemia.Herein,vascular endothelial growth factor mimic peptide QK was self-assembled with MMP-2-cleaved peptide PLGLAG(TIMP)and customizable peptide amphiphilic(PA)molecules to construct nanofiber hydrogel PA-TIMP-QK.PA-TIMP-QK was found to control the delivery of QK by MMP-2 upregulation after cerebral ischemia/reperfusion and had a similar biological activity with vascular endothelial growth factor in vitro.The results indicated that PA-TIMP-QK promoted neuronal survival,restored local blood circulation,reduced blood-brain barrier permeability,and restored motor function.These findings suggest that the self-assembling nanofiber hydrogel PA-TIMP-QK may provide an intelligent drug delivery system that responds to the microenvironment and promotes regeneration and repair after cerebral ischemia/reperfusion injury.展开更多
Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(EC...Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(ECM)genes and microRNAs(miRNAs)in IIRI have garnered widespread attention.This review aims to systematically summarize the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI.First,we review the molecular mechanisms of IIRI,focusing on the dual role of the ECM in tissue injury and repair processes.The expression changes and functions of ECM components such as collagen,elastin,and matrix metalloproteinases during IIRI progression are deeply analyzed.Second,we systematically summarize the regulatory roles of miRNAs in IIRI,particularly the mechanisms and functions of miRNAs such as miR-125b and miR-200a in regulating inflammation,apoptosis,and ECM remodeling.Additionally,this review discusses potential diagnostic biomarkers and treatment strategies based on ECM genes and miRNAs.We extensively evaluate the prospects of miRNA-targeted therapy and ECM component modulation in preventing and treating IIRI,emphasizing the clinical translational potential of these emerging therapies.In conclusion,the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI provides new directions for further research,necessitating additional clinical and basic studies to validate and expand these findings for improving clinical outcomes in IIRI patients.展开更多
Aneurysms and dissections represent some of the most serious cardiovascular diseases.The prevailing theory posits that mechanical overloading of the vessel wall is the underlying cause.Inspired by Barkhordarian et al,...Aneurysms and dissections represent some of the most serious cardiovascular diseases.The prevailing theory posits that mechanical overloading of the vessel wall is the underlying cause.Inspired by Barkhordarian et al,the authors present matrix metalloproteinases(MMPs)and their inhibitors in immunohistological analyses as contributing factors in the pathophysiology of aortic aneurysms(AA).Data analysis of MMP-1,MMP-9,tissue inhibitors of metalloproteinases(TIMPs),including TIMP-1 and TIMP-2 expression reveals a varied distribution between the adventitia and media and a non-uniform expression of the investigated markers.These elements,as key components of the extracellular matrix(ECM),indicate that the formation of AA is not solely driven by endoluminal pressure loading of the aortic wall.Instead,degenerative processes within ECM elements contribute significantly.Importantly,AA do not necessarily imply dissection.Tissue destruction,allowing blood flow entry,arises from reduced oxygen supply to the media,primarily due to incomplete capillarization or neocapillarization.展开更多
Reverse design of highly GeO2-doped silica optical fibers with broadband and flat dispersion profiles is proposed using a neural network(NN) combined with a particle swarm optimization(PSO) algorithm.Firstly,the NN mo...Reverse design of highly GeO2-doped silica optical fibers with broadband and flat dispersion profiles is proposed using a neural network(NN) combined with a particle swarm optimization(PSO) algorithm.Firstly,the NN model designed to predict optical fiber dispersion is trained with an appropriate choice of hyperparameters,achieving a root mean square error(RMSE) of 9.47×10-7on the test dataset,with a determination coefficient(R2) of 0.999.Secondly,the NN is combined with the PSO algorithm for the inverse design of dispersion-flattened optical fibers.To expand the search space and avoid particles becoming trapped in local optimal solutions,the PSO algorithm incorporates adaptive inertia weight updating and a simulated annealing algorithm.Finally,by using a suitable fitness function,the designed fibers exhibit flat group velocity dispersion(GVD) profiles at 1 400—2 400 nm,where the GVD fluctuations and minimum absolute GVD values are below 18 ps·nm-1·km-1and 7 ps·nm-1·km-1,respectively.展开更多
基金the financial support from the National Natural Science Foundation of China(No.61904005,52103010 and 52003200)Guangdong Provincial Department of Education Featured Innovation Project(No.2021KTSCX138)+4 种基金Jiangmen Key Project of Research for Basic and Basic Application(No.2021030102800007443 and 2021030102790006114)the Science Foundation for Young Research Group of Wuyi University(No.2020AL021,2019AL019,and 2020AL016)Wuyi University-Hong Kong/Macao Joint Research Funds(No.2021WGALH05)Youth Innovation Talent Project for the Universities of Guangdong(No.2020KQNCX089)Guangdong Basic and Applied Basic Research Foundation(No.2020A1515110897)
文摘Organic perovskites are promising semiconductor materials for advanced photoelectric applications.Their fluorescence typically shows a negative temperature coefficient due to bandgap change and structural instability.In this study,a novel perovskite-based composite with positive sensitivity to temperature was designed and obtained based on its inverse temperature crystallization,demonstrating good flexibility and solution processability.The supercritical drying method was used to address the limitations of annealing drying in preparing high-performance perovskite.Optimizing the precursor composition proved to be an effective approach for achieving high fluorescence and structural integrity in the perovskite material.This perovskite-based composite exhibited a positive temperature sensitivity of 28.563%℃^(-1)for intensity change and excellent temperature cycling reversibility in the range of 25-40℃in an ambient environment.This made it suitable for use as a smart window with rapid response.Furthermore,the perovskite composite was found to offer temperature-sensing photoluminescence and flexible processability due to its components of perovskite-based compounds and polyethylene oxide.The organic precursor solvent could be a promising candidate for use as ink to print or write on various substrates for optoelectronic devices responding to temperature.
文摘BACKGROUND One of the main characteristics of oral squamous cell carcinoma(OSCC)is that it metastasizes to cervical lymph nodes frequently with a high degree of local invasiveness.A primary feature of malignant tumors is their penetration of neighboring tissues,such as lymphatic and blood arteries,due to the tumor cells'capacity to break down the extracellular matrix(ECM).Matrix metalloproteinases(MMPs)constitute a family of proteolytic enzymes that facilitate tissue remodeling and the degradation of the ECM.MMP-9 and MMP-13 belong to the group of extracellular matrix degrading enzymes and their expression has been studied in OSCC because of their specific functions.MMP-13,a collagenase family member,is thought to play an essential role in the MMP activation cascade by breaking down the fibrillar collagens,whereas MMP-9 is thought to accelerate the growth of tumors.Elevated MMP-13 expression has been associated with tumor behavior and patient prognosis in a number of malignant cases.AIM To assess the immunohistochemical expression of MMP-9 and MMP-13 in OSCC.METHODS A total of 40 cases with histologically confirmed OSCC by incisional biopsy were included in this cross-sectional retrospective study.The protocols for both MMP-9 and MMP-13 immunohistochemical staining were performed according to the manufacturer’s recommendations along with the normal gingival epithelium as a positive control.All the observations were recorded and Pearson’sχ²test with Fisher exact test was used for statistical analysis.RESULTS Our study showed no significant correlation between MMP-9 and MMP-13 staining intensity and tumor size.The majority of the patients were in advanced TNM stages(III and IV),and showed intense expression of MMP-9 and MMP-13.CONCLUSION The present study suggests that both MMP-9 and MMP-13 play an important and independent role in OSCC progression and invasiveness.Intense expression of MMP-9 and MMP-13,irrespective of histological grade of OSCC,correlates well with TNM stage.Consequently,it is evident that MMP-9 and MMP-13 are important for the invasiveness and progression of tumors.The findings may facilitate the development of new approaches for evaluating lymph node metastases and interventional therapy techniques,hence enhancing the prognosis of patients diagnosed with OSCC.
基金supported by National Institute on Aging(NIH-NIA)R21 AG074152(to KMA)National Institute of Allergy and Infectious Diseases(NIAID)grant DP2 AI171150(to KMA)Department of Defense(DoD)grant AZ210089(to KMA)。
文摘The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.
基金supported by the National Nature Science Foundation of China(No.82002345 to J.D and 81902179 to L.S)the Gusu Talent Program(No.Qngg2022008 and GSWS2021027 to J.D)the Preliminary Research Project of the Second Affiliated Hospital of Soochow University(No.SDFEYBS1905 to J.D).
文摘Increased matrix stiffness of nucleus pulposus(NP)tissue is a main feature of intervertebral disc degeneration(IVDD)and affects various functions of nucleus pulposus cells(NPCs).Glycolysis is the main energy source for NPC survival,but the effects and underlying mechanisms of increased extracellular matrix(ECM)stiffness on NPC glycolysis remain unknown.In this study,hydrogels with different stiffness were established to mimic the mechanical environment of NPCs.Notably,increased matrix stiffness in degenerated NP tissues from IVDD patients was accompanied with impaired glycolysis,and NPCs cultured on rigid substrates exhibited a reduction in glycolysis.
基金supported by the National Natural Science Foundation of China (No. 62204079)the Science and Technology Development Project of Henan Province (Nos.202300410048, 202300410057)+2 种基金the China Postdoctoral Science Foundation (No. 2022M711037)the Intelligence Introduction Plan of Henan Province in 2021 (No. CXJD2021008)Henan University Fund。
文摘Quantum dot(QD)-based infrared photodetector is a promising technology that can implement current monitoring,imaging and optical communication in the infrared region. However, the photodetection performance of self-powered QD devices is still limited by their unfavorable charge carrier dynamics due to their intrinsically discrete charge carrier transport process. Herein, we strategically constructed semiconducting matrix in QD film to achieve efficient charge transfer and extraction.The p-type semiconducting CuSCN was selected as energy-aligned matrix to match the n-type colloidal PbS QDs that was used as proof-of-concept. Note that the PbS QD/CuSCN matrix not only enables efficient charge carrier separation and transfer at nano-interfaces but also provides continuous charge carrier transport pathways that are different from the hoping process in neat QD film, resulting in improved charge mobility and derived collection efficiency. As a result, the target structure delivers high specific detectivity of 4.38 × 10^(12)Jones and responsivity of 782 mA/W at 808 nm, which is superior than that of the PbS QD-only photodetector(4.66 × 10^(11)Jones and 338 mA/W). This work provides a new structure candidate for efficient colloidal QD based optoelectronic devices.
基金supported by the Natio`nal Natural Science Foundation of China,No. 81801241a grant from Sichuan Science and Technology Program,No. 2023NSFSC1578Scientific Research Projects of Southwest Medical University,No. 2022ZD002 (all to JX)。
文摘Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.
基金Supported by Natural Science Foundation of HuBei Province(2022CFB299).
文摘This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.
基金financial support from the National Natural Science Foundation of China(Nos.22108258 and 52003251)Program for Science&Technology Innovation Talents in Universities of Henan Province(24HASTIT004)+1 种基金Outstanding Youth Fund of Henan Scientific Committee(222300420085)Science and Technology Joint Project of Henan Province(222301420041)。
文摘Mixed matrix membranes(MMMs)have demonstrated significant promise in energy-intensive gas separations by amalgamating the unique properties of fillers with the facile processability of polymers.However,achieving a simultaneous enhancement of permeability and selectivity remains a formidable challenge,due to the difficulty of achieving an optimal match between polymers and fillers.In this study,we incorporate a porous carbon-based zinc oxide composite(C@ZnO)into high-permeability polymers of intrinsic microporosity(PIMs)to fabricate MMMs.The dipole–dipole interaction between C@ZnO and PIMs ensures their exceptional compatibility,mitigating the formation of non-selective voids in the resulting MMMs.Concurrently,C@ZnO with abundant interconnected pores can provide additional low-resistance pathways for gas transport in MMMs.As a result,the CO_(2) permeability of the optimized C@ZnO/PIM-1 MMMs is elevated to 13,215 barrer,while the CO_(2)/N_(2) and CO_(2)/CH_(4) selectivity reached 21.5 and 14.4,respectively,substantially surpassing the 2008 Robeson upper bound.Additionally,molecular simulation results further corroborate that the augmented membrane gas selectivity is attributed to the superior CO_(2) affinity of C@ZnO.In summary,we believe that this work not only expands the application of MMMs for gas separation but also heralds a paradigm shift in the application of porous carbon materials.
文摘We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
基金Supported by NSFC (No.12371378)NSF of Fujian Province (Nos.2024J01980,2023J01955)。
文摘Analysis and design of linear periodic control systems are closely related to the periodic matrix equations.The biconjugate residual method(BCR for short)have been introduced by Vespucci and Broyden for efficiently solving linear systems Aα=b.The objective of this paper is to provide one new iterative algorithm based on BCR method to find the symmetric periodic solutions of linear periodic matrix equations.This kind of periodic matrix equations has not been dealt with yet.This iterative method is guaranteed to converge in a finite number of steps in the absence of round-off errors.Some numerical results are performed to illustrate the efficiency and feasibility of new method.
文摘Capacitive voltage transformers (CVTs) are essential in high-voltage systems. An accurate error assessment is crucial for precise energy metering. However, tracking real-time quantitative changes in capacitive voltage transformer errors, particularly minor variations in multi-channel setups, remains challenging. This paper proposes a method for online error tracking of multi-channel capacitive voltage transformers using a Co-Prediction Matrix. The approach leverages the strong correlation between in-phase channels, particularly the invariance of the signal proportions among them. By establishing a co-prediction matrix based on these proportional relationships, The influence of voltage changes on the primary measurements is mitigated. Analyzing the relationships between the co-prediction matrices over time allows for inferring true measurement errors. Experimental validation with real-world data confirms the effectiveness of the method, demonstrating its capability to continuously track capacitive voltage transformer measurement errors online with precision over extended durations.
基金Project(52174245)supported by the National Natural Science Foundation of ChinaProject(2021J01640)supported by the Natural Science Foundation of Fujian Province,ChinaProject(BGRIMM-KJSKL2022-03)supported by Open Foundation of the State Key Laboratory of Mineral Processing,China。
文摘Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter physics,materials science,and mineral separation technologies,these materials are now poised for new opportunities in theoretical research and development.This review provides a comprehensive analysis of these matrices,encompassing their structure,size,shape,composition,properties,and multifaceted applications.These materials,primarily composed of alloys of transition state metasl such as iron(Fe),cobalt(Co),titanium(Ti),and nickel(Ni),exhibit unique attributes like high magnetization rates,low eleastic modulus,and high saturation magnetic field strengths.Furthermore,the studies also delve into the complex mechanical interactions involved in the separation of magnetic particles using magnetic separator matrices,including magnetic,gravitational,centrifugal,and van der Waals forces.The review outlines how size and shape effects influence the magnetic behavior of matrices,offering new perspectives for innovative applications of magnetic matrices in various domains of materials science and magnetic separation.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.62476278,12434009,and 12204533)supported by the National Key R&D Program of China(Grant No.2024YFA1408601)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0302402)。
文摘The discovery of advanced materials is a cornerstone of human technological development and progress.The structures of materials and their corresponding properties are essentially the result of a complex interplay of multiple degrees of freedom such as lattice,charge,spin,symmetry,and topology.This poses significant challenges for the inverse design methods of materials.Humans have long explored new materials through numerous experiments and proposed corresponding theoretical systems to predict new material properties and structures.With the improvement of computational power,researchers have gradually developed various electronic-structure calculation methods,such as the density functional theory and high-throughput computational methods.Recently,the rapid development of artificial intelligence(AI)technology in computer science has enabled the effective characterization of the implicit association between material properties and structures,thus forming an efficient paradigm for the inverse design of functional materials.Significant progress has been achieved in the inverse design of materials based on generative and discriminative models,attracting widespread interest from researchers.Considering this rapid technological progress,in this survey,we examine the latest advancements in AI-driven inverse design of materials by introducing the background,key findings,and mainstream technological development routes.In addition,we summarize the remaining challenges for future directions.This survey provides the latest overview of AI-driven inverse design of materials,which can serve as a useful resource for researchers.
基金supported by the Natural Science Foundation of Shandong Province,No.ZR2023MC168the National Natural Science Foundation of China,No.31670989the Key R&D Program of Shandong Province,No.2019GSF107037(all to CS).
文摘Vascular endothelial growth factor and its mimic peptide KLTWQELYQLKYKGI(QK)are widely used as the most potent angiogenic factors for the treatment of multiple ischemic diseases.However,conventional topical drug delivery often results in a burst release of the drug,leading to transient retention(inefficacy)and undesirable diffusion(toxicity)in vivo.Therefore,a drug delivery system that responds to changes in the microenvironment of tissue regeneration and controls vascular endothelial growth factor release is crucial to improve the treatment of ischemic stroke.Matrix metalloproteinase-2(MMP-2)is gradually upregulated after cerebral ischemia.Herein,vascular endothelial growth factor mimic peptide QK was self-assembled with MMP-2-cleaved peptide PLGLAG(TIMP)and customizable peptide amphiphilic(PA)molecules to construct nanofiber hydrogel PA-TIMP-QK.PA-TIMP-QK was found to control the delivery of QK by MMP-2 upregulation after cerebral ischemia/reperfusion and had a similar biological activity with vascular endothelial growth factor in vitro.The results indicated that PA-TIMP-QK promoted neuronal survival,restored local blood circulation,reduced blood-brain barrier permeability,and restored motor function.These findings suggest that the self-assembling nanofiber hydrogel PA-TIMP-QK may provide an intelligent drug delivery system that responds to the microenvironment and promotes regeneration and repair after cerebral ischemia/reperfusion injury.
基金Supported by Health Science and Technology Programme of Zhejiang Province,No.2022KY1391.
文摘Intestinal ischemia-reperfusion injury(IIRI)is a complex and severe pathophysiological process characterized by oxidative stress,inflammation,and apoptosis.In recent years,the critical roles of extracellular matrix(ECM)genes and microRNAs(miRNAs)in IIRI have garnered widespread attention.This review aims to systematically summarize the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI.First,we review the molecular mechanisms of IIRI,focusing on the dual role of the ECM in tissue injury and repair processes.The expression changes and functions of ECM components such as collagen,elastin,and matrix metalloproteinases during IIRI progression are deeply analyzed.Second,we systematically summarize the regulatory roles of miRNAs in IIRI,particularly the mechanisms and functions of miRNAs such as miR-125b and miR-200a in regulating inflammation,apoptosis,and ECM remodeling.Additionally,this review discusses potential diagnostic biomarkers and treatment strategies based on ECM genes and miRNAs.We extensively evaluate the prospects of miRNA-targeted therapy and ECM component modulation in preventing and treating IIRI,emphasizing the clinical translational potential of these emerging therapies.In conclusion,the diagnostic and therapeutic potential of ECM gene sets and miRNA regulatory networks in IIRI provides new directions for further research,necessitating additional clinical and basic studies to validate and expand these findings for improving clinical outcomes in IIRI patients.
文摘Aneurysms and dissections represent some of the most serious cardiovascular diseases.The prevailing theory posits that mechanical overloading of the vessel wall is the underlying cause.Inspired by Barkhordarian et al,the authors present matrix metalloproteinases(MMPs)and their inhibitors in immunohistological analyses as contributing factors in the pathophysiology of aortic aneurysms(AA).Data analysis of MMP-1,MMP-9,tissue inhibitors of metalloproteinases(TIMPs),including TIMP-1 and TIMP-2 expression reveals a varied distribution between the adventitia and media and a non-uniform expression of the investigated markers.These elements,as key components of the extracellular matrix(ECM),indicate that the formation of AA is not solely driven by endoluminal pressure loading of the aortic wall.Instead,degenerative processes within ECM elements contribute significantly.Importantly,AA do not necessarily imply dissection.Tissue destruction,allowing blood flow entry,arises from reduced oxygen supply to the media,primarily due to incomplete capillarization or neocapillarization.
基金supported by the Fundamental Research Funds for the Central Universities (No.2024JBZY021)the National Natural Science Foundation of China (No.61575018)。
文摘Reverse design of highly GeO2-doped silica optical fibers with broadband and flat dispersion profiles is proposed using a neural network(NN) combined with a particle swarm optimization(PSO) algorithm.Firstly,the NN model designed to predict optical fiber dispersion is trained with an appropriate choice of hyperparameters,achieving a root mean square error(RMSE) of 9.47×10-7on the test dataset,with a determination coefficient(R2) of 0.999.Secondly,the NN is combined with the PSO algorithm for the inverse design of dispersion-flattened optical fibers.To expand the search space and avoid particles becoming trapped in local optimal solutions,the PSO algorithm incorporates adaptive inertia weight updating and a simulated annealing algorithm.Finally,by using a suitable fitness function,the designed fibers exhibit flat group velocity dispersion(GVD) profiles at 1 400—2 400 nm,where the GVD fluctuations and minimum absolute GVD values are below 18 ps·nm-1·km-1and 7 ps·nm-1·km-1,respectively.
