Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory v...Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory versus degenerative dichotomy.This was based on a broad misconception regarding essentially all neurodegenerative conditions,depicting the degenerative process as passive and immune-independent occurring as a late byproduct of active inflammation in the central nervous system(CNS),which is(solely)systemically driven.展开更多
BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning ofte...BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.展开更多
Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained promine...Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.展开更多
Mononuclear macrophage infiltration in the central nervous system is a prominent feature of neuroinflammation. Recent studies on the pathogenesis and progression of multiple sclerosis have highlighted the multiple rol...Mononuclear macrophage infiltration in the central nervous system is a prominent feature of neuroinflammation. Recent studies on the pathogenesis and progression of multiple sclerosis have highlighted the multiple roles of mononuclear macrophages in the neuroinflammatory process. Monocytes play a significant role in neuroinflammation, and managing neuroinflammation by manipulating peripheral monocytes stands out as an effective strategy for the treatment of multiple sclerosis, leading to improved patient outcomes. This review outlines the steps involved in the entry of myeloid monocytes into the central nervous system that are targets for effective intervention: the activation of bone marrow hematopoiesis, migration of monocytes in the blood, and penetration of the blood–brain barrier by monocytes. Finally, we summarize the different monocyte subpopulations and their effects on the central nervous system based on phenotypic differences. As activated microglia resemble monocyte-derived macrophages, it is important to accurately identify the role of monocyte-derived macrophages in disease. Depending on the roles played by monocyte-derived macrophages at different stages of the disease, several of these processes can be interrupted to limit neuroinflammation and improve patient prognosis. Here, we discuss possible strategies to target monocytes in neurological diseases, focusing on three key aspects of monocyte infiltration into the central nervous system, to provide new ideas for the treatment of neurodegenerative diseases.展开更多
BACKGROUND The incidence of malignant gastrointestinal(GI)tumors is increasing,and advancements in medical care have significantly improved patient survival rates.As a result,the number of cases involving multiple pri...BACKGROUND The incidence of malignant gastrointestinal(GI)tumors is increasing,and advancements in medical care have significantly improved patient survival rates.As a result,the number of cases involving multiple primary cancers(MPC)has also increased.The rarity of MPC and the absence of sensitive and specific dia-gnostic markers often lead to missed or incorrect diagnoses.It is,therefore,of vital importance to improve the vigilance of clinicians and the accurate diagnosis of this disease.Patients with GI malignancies face a higher relative risk of deve-loping additional primary malignant tumors compared to those with other systemic tumors.Vigilant monitoring and follow-up are crucial,especially for high-risk groups,which include older adults,men,those with addictions to alcohol and tobacco,those with a family history of tumors,and those who have undergone radiotherapy.CASE SUMMARY In this article,we report three cases of MPC,each involving malignant tumors of the GI tract as the initial primary carcinoma,offering insights that may aid in effectively managing similar cases.CONCLUSION Patients with GI malignancies face a higher MPC risk.Developing screening and follow-up protocols may enhance detection and treatment outcomes.展开更多
Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-targe...Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.展开更多
This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to d...This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.展开更多
In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology bas...In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.展开更多
Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play p...Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.展开更多
Objective:Multiple myeloma(MM)is a hematologically malignant clonal plasma cell disease.This study aims to explore the association between immunophenotypes and prognosis in patients with MM,to determine whether the ex...Objective:Multiple myeloma(MM)is a hematologically malignant clonal plasma cell disease.This study aims to explore the association between immunophenotypes and prognosis in patients with MM,to determine whether the expression of CD45 and CD200 is related to the prognosis of newly diagnosed MM(NDMM)patients,and to evaluate the significance of the combined expression of CD45 and CD200 in NDMM.Methods:A total of 123 NDMM patients admitted to Shengjing Hospital of China Medical University from July 2015 to August 2019 were enrolled.Five key immunophenotypic markers(including CD38,CD138,CD45,CD56,and CD200)were screened through flow cytometry and identified using random forest analysis and univariate Cox regression analysis.Patients were divided into 3 groups:Group A,CD45 and CD200 double-positive;Group B,CD45 or CD200 single-positive;Group C,CD45 and CD200 double-negative.Kaplan-Meier curves were used to analyze overall survival(OS)and progression-free survival(PFS)across groups.Multivariate Cox regression was performed to evaluate prognostic factors,and a nomogram was constructed based on these results.Results:The OS and PFS of single-positive groups for CD38,CD138,CD45,CD56,and CD200 were all shorter than those of their respective single-negative groups(all P<0.05).Significant differences were observed in OS(P<0.001)and PFS(P=0.001)among Groups A,B,and C.Group A had shorter OS and PFS(all P=0.001)compared to the Group B+C(cases from Group B and Group C were combined).CD45 and CD200 double-positive was an independent prognostic factor for NDMM[hazard ratio(HR)=2.178,95%confidence interval(CI)1.048 to 4.529;P=0.037].The nomogram and calibration curves constructed from multivariate Cox regression analysis demonstrated good concordance(concordance index=0.706;95%CI 0.661 to 0.751).Conclusion:NDMM patients with double-positive expression of CD45 and CD200 have significantly shorter OS and PFS.Compared with the use of either marker alone,the combined assessment of CD45 and CD200 may provide better prognostic stratification for MM patients.展开更多
The charge carrier transport and recombination dynamics in the quantum dots-based light-emitting diodes(QLEDs)featuring multiple emitting layers(M-EMLs)has a great impact on the device performance.In this work,QLEDs b...The charge carrier transport and recombination dynamics in the quantum dots-based light-emitting diodes(QLEDs)featuring multiple emitting layers(M-EMLs)has a great impact on the device performance.In this work,QLEDs based on M-EMLs separated by polyethyleneimine ethoxylated(PEIE)layer with different stacking sequences of blue(B),green(G),and red(R)QDs layer were used to intuitively explore the injection,transportation and recombination processes of the charge carriers in QLEDs by using the time-resolved electroluminescence(TrEL)spectra.From the TrEL spectra mea-surements,green and red emissions were obtained first in the QLEDs with the EMLs sequences of G/PEIE/B/PEIE/R and B/PEIE/R/PEIE/G along the direction of light emission,respectively.While the QLEDs adopt EMLs sequences of B/PEIE/G/PEIE/R,the blue,green and red emissions were obtained nearly at the same time.The above phenomenon can be attributed to different charge carrier transmission and radiation recombination process in the EMLs due to different valence band offsets and conduction band offsets between R-,G-and B-QDs by using different sequences of EMLs.White emission with coordi-nates of(0.31,0.31)and correlated color temperature(CCT)of 5916 K was obtained in the QLEDs with the EMLs se-quences of B/PEIE/G/PEIE/R,which can be attributed to the relative uniform emission of B-,G-and R-QDs due to the effec-tive injection and radiation recombination of charge carriers in each of the EMLs.The above results have great significance for further understanding and improving the performance of QLEDs with M-EMLs.展开更多
Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate...Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.展开更多
Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant i...Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant importance.The traditional finite element method(FEM)remains one of the primary approaches for addressing such issues.However,the application of FEM typically necessitates the use of a fine finite element mesh to accurately capture the heterogeneous properties of the materials and meet the required computational precision,which inevitably leads to a reduction in computational efficiency.To enhance the computational accuracy and efficiency of the FEM for heterogeneous multi-field coupling problems,this study presents the coupling magneto-electro-elastic multiscale finite element method(CM-MsFEM)for heterogeneous MEE structures.Unlike the conventional multiscale FEM(MsFEM),the proposed algorithm simultaneously constructs displacement,electric,and magnetic potential multiscale basis functions to address the heterogeneity of the corresponding parameters.The macroscale formulation of CM-MsFEM was derived,and the macroscale/microscale responses of the problems were obtained through up/downscaling calculations.Evaluation using numerical examples analyzing the transient behavior of heterogeneous MEE structures demonstrated that the proposed method outperforms traditional FEM in terms of both accuracy and computational efficiency,making it an appropriate choice for numerically modeling the dynamics of heterogeneous MEE structures.展开更多
Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthe...Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthermore,microcracks located in intact rock matrix(IRM)of LR are also critically important for friction and damage dissipation processes.In this paper,we first present a novel multiscale friction-damage(MFD)model using a two-step Mori-Tanaka homogenization scheme,with the aim of describing the multiscale friction-damage mechanics in LR.Physically,the initiation and propagation of flaws at different scales(i.e.microcracks and weakness planes)induced damage,and the plastic deformation is closely associated with frictional sliding along these flaws.In the thermodynamics framework,the macroscopic stress-strain relations,the local driving forces respectively conjuncted with flaws propagation and plastic deformation are derived.An analytical macroscopic strength criterion is subsequently deduced,which takes into account the variation of inclination angle and confining pressure.Notably,the failure mechanisms of IRM shearing and weakness planes sliding are inherent included in the criterion.As an original contribution,a new multisurface semi-implicit return mapping algorithm(MSRM)is developed to integrate the proposed MFD model.The robustness of MSRM algorithm is assessed by numerical tests with different loading steps sizes and convergence conditions.Finally,the effectiveness of the MFD model is confirmed using data from experiments under conventional triaxial compression,all main features of mechanical behaviors of LR are well captured by the proposed model,including initial anisotropy,stress-induced anisotropy and strain hardening/softening.展开更多
This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity fa...This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.展开更多
Cryptocurrency is a remarkable financial innovation that has affected the financial system in fundamental ways.Its increasingly complex interactions with the conventional financial market make precisely forecasting it...Cryptocurrency is a remarkable financial innovation that has affected the financial system in fundamental ways.Its increasingly complex interactions with the conventional financial market make precisely forecasting its volatility increasingly challenging.To this end,we propose a novel framework based on the evolving multiscale graph neural network(EMGNN).Specifically,we embed a graph that depicts the interactions between the cryptocurrency and conventional financial markets into the predictive process.Furthermore,we employ hierarchical evolving graph structure learners to model the dynamic and scale-specific interactions.We also evaluate our framework’s robustness and discuss its interpretability by extracting the learned graph structure.The empirical results show that(i)cryptocurrency volatility is not isolated from the conventional market,and the embedded graph can provide effective information for prediction;(ii)the EMGNN-based forecasting framework generally yields outstanding and robust performance in terms of multiple volatility estimators,cryptocurrency samples,forecasting horizons,and evaluation criteria;and(iii)the graph structure in the predictive process varies over time and scales and is well captured by our framework.Overall,our work provides new insights into risk management for market participants and into policy formulation for authorities.展开更多
Multiple evanescent white dot syndrome(MEWDS)is an inflammatory fundus disease primarily affecting the outer retina.It is characterized by transient yellow-white dots on the outer retina.Although the exact pathogenesi...Multiple evanescent white dot syndrome(MEWDS)is an inflammatory fundus disease primarily affecting the outer retina.It is characterized by transient yellow-white dots on the outer retina.Although the exact pathogenesis remains unclear,the progress in multimodal imaging(MMI)has enhanced our understanding of MEWDS.Most cases of MEWDS are idiopathic,lacking a definite cause,and can spontaneously recover;these are what we term classic MEWDS.Consequently,MEWDS is often referred to as the“common cold of the retina”.Simultaneously,patients with other disorders may present with varying degrees of manifestations similar to MEWDS.The resemblance in clinical or imaging findings can lead to misdiagnosis and inappropriate treatment.These MEWDS-like presentations are actually caused by other systemic or ocular disorders with diverse mechanisms.Thus,they differ from classic MEWDS in certain aspects.Using the keywords“MEWDSlike”and“Secondary MEWDS”,we searched for all relevant studies published in the PubMed database from January 2021 to January 2024.Subsequently,we retrospectively summarized the clinical and imaging characteristics of MEWDS,along with the manifestations in other diseases that resembled those of MEWDS,and compared classic MEWDS with these similar presentations.Based on our review,we classified such similar presentations under other conditions into two categories and summarized their features for differential diagnosis.We recommend paying close attention to patients suspected of having MEWDS,as there may be more serious systemic or ocular disorders that require prompt treatment.展开更多
Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock st...Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock structural degradation.This may lead to problems in the evaluation of rock structure stability and safe life.Multiscale numerical modeling is regarded as an effective way to gain insight into factors affecting rock properties from a cross-scale view.This study compiles the history of theoretical developments and numerical techniques related to rock multiscale issues according to different modeling architectures,that is,the homogenization theory,the hierarchical approach,and the concurrent approach.For these approaches,their benefits,drawbacks,and application scope are underlined.Despite the considerable attempts that have been made,some key issues still result in multiple challenges.Therefore,this study points out the perspectives of rock multiscale issues so as to provide a research direction for the future.The review results show that,in addition to numerical techniques,for example,high-performance computing,more attention should be paid to the development of an advanced constitutive model with consideration of fine geometrical descriptions of rock to facilitate solutions to multiscale problems in rock mechanics and rock engineering.展开更多
The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus...The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.展开更多
文摘Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory versus degenerative dichotomy.This was based on a broad misconception regarding essentially all neurodegenerative conditions,depicting the degenerative process as passive and immune-independent occurring as a late byproduct of active inflammation in the central nervous system(CNS),which is(solely)systemically driven.
基金Supported by Chongqing Medical Scientific Research Project(Joint Project of Chongqing Health Commission and Science and Technology Bureau),No.2023MSXM060.
文摘BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.
基金supported by the National Natural Science Foundation of China(No.52277055).
文摘Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.
基金supported by the National Natural Science Foundation of China,Nos.82060219,82271234the Natural Science Foundation of Jiangxi Province,Nos.20212ACB216009,20212BAB216048+1 种基金Jiangxi Province Thousands of Plans,No.jxsq2019201023Youth Team Project of the Second Affiliated Hospital of Nanchang University,No.2019YNTD12003(all to FH)。
文摘Mononuclear macrophage infiltration in the central nervous system is a prominent feature of neuroinflammation. Recent studies on the pathogenesis and progression of multiple sclerosis have highlighted the multiple roles of mononuclear macrophages in the neuroinflammatory process. Monocytes play a significant role in neuroinflammation, and managing neuroinflammation by manipulating peripheral monocytes stands out as an effective strategy for the treatment of multiple sclerosis, leading to improved patient outcomes. This review outlines the steps involved in the entry of myeloid monocytes into the central nervous system that are targets for effective intervention: the activation of bone marrow hematopoiesis, migration of monocytes in the blood, and penetration of the blood–brain barrier by monocytes. Finally, we summarize the different monocyte subpopulations and their effects on the central nervous system based on phenotypic differences. As activated microglia resemble monocyte-derived macrophages, it is important to accurately identify the role of monocyte-derived macrophages in disease. Depending on the roles played by monocyte-derived macrophages at different stages of the disease, several of these processes can be interrupted to limit neuroinflammation and improve patient prognosis. Here, we discuss possible strategies to target monocytes in neurological diseases, focusing on three key aspects of monocyte infiltration into the central nervous system, to provide new ideas for the treatment of neurodegenerative diseases.
基金Supported by Gansu Provincial Natural Science Foundation,No.21JR1RA010In-Hospital Research Fund of Gansu Provincial Hospital,No.23GSSYD-5.
文摘BACKGROUND The incidence of malignant gastrointestinal(GI)tumors is increasing,and advancements in medical care have significantly improved patient survival rates.As a result,the number of cases involving multiple primary cancers(MPC)has also increased.The rarity of MPC and the absence of sensitive and specific dia-gnostic markers often lead to missed or incorrect diagnoses.It is,therefore,of vital importance to improve the vigilance of clinicians and the accurate diagnosis of this disease.Patients with GI malignancies face a higher relative risk of deve-loping additional primary malignant tumors compared to those with other systemic tumors.Vigilant monitoring and follow-up are crucial,especially for high-risk groups,which include older adults,men,those with addictions to alcohol and tobacco,those with a family history of tumors,and those who have undergone radiotherapy.CASE SUMMARY In this article,we report three cases of MPC,each involving malignant tumors of the GI tract as the initial primary carcinoma,offering insights that may aid in effectively managing similar cases.CONCLUSION Patients with GI malignancies face a higher MPC risk.Developing screening and follow-up protocols may enhance detection and treatment outcomes.
基金supported by the National Natural Science Foundation of China(Grant Nos.:32271292,31872723,32200778,and 22377089)the Jiangsu Students Innovation and Entrepre-neurship Training Program,China(Program No.:202210285081Z)+6 种基金the Project of MOE Key Laboratory of Geriatric Diseases and Immunology,China(Project No.:JYN202404)Proj-ect Funded by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions,Natural Science Foundation of Jiangsu Province,China(Project No.:BK20220494)Suzhou Medical and Health Technology Innovation Project,China(Grant No.:SKY2022107)the Clinical Research Center of Neuro-logical Disease in The Second Affiliated Hospital of Soochow University,China(Grant No.:ND2022A04)State Key Laboratory of Drug Research(Grant No.:SKLDR-2023-KF-05)Jiangsu Shuang-chuang Program for Doctor,Young Science Talents Promotion Project of Jiangsu Science and Technology Association(Program No.:TJ-2023-019)Young Science Talents Promotion Project of Suzhou Science and Technology Association,Suzhou International Joint Laboratory for Diagnosis and Treatment of Brain Diseases,and startup funding(Grant Nos.:NH21500221,NH21500122,and NH21500123)to Qifei Cong.
文摘Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the“therapeutic module”of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.
基金supported by DST-FIST(Government of India)(Grant No.SR/FIST/MS-1/2017/13)and Seed Money Project(Grant No.DoRDC/733).
文摘This study numerically examines the heat and mass transfer characteristics of two ternary nanofluids via converging and diverg-ing channels.Furthermore,the study aims to assess two ternary nanofluids combinations to determine which configuration can provide better heat and mass transfer and lower entropy production,while ensuring cost efficiency.This work bridges the gap be-tween academic research and industrial feasibility by incorporating cost analysis,entropy generation,and thermal efficiency.To compare the velocity,temperature,and concentration profiles,we examine two ternary nanofluids,i.e.,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O and TiO_(2)+SiO_(2)+Cu/H_(2)O,while considering the shape of nanoparticles.The velocity slip and Soret/Dufour effects are taken into consideration.Furthermore,regression analysis for Nusselt and Sherwood numbers of the model is carried out.The Runge-Kutta fourth-order method with shooting technique is employed to acquire the numerical solution of the governed system of ordinary differential equations.The flow pattern attributes of ternary nanofluids are meticulously examined and simulated with the fluc-tuation of flow-dominating parameters.Additionally,the influence of these parameters is demonstrated in the flow,temperature,and concentration fields.For variation in Eckert and Dufour numbers,TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher temperature than TiO_(2)+SiO_(2)+Cu/H_(2)O.The results obtained indicate that the ternary nanofluid TiO_(2)+SiO_(2)+Al_(2)O_(3)/H_(2)O has a higher heat transfer rate,lesser entropy generation,greater mass transfer rate,and lower cost than that of TiO_(2)+SiO_(2)+Cu/H_(2)O ternary nanofluid.
基金financially supported by National Key R&D Program(2021YFF0701905)。
文摘In order to save manpower and time costs,and to achieve simultaneous detection of multiple animal-derived components in meat and meat products,this study used multiple nucleotide polymorphism(MNP)marker technology based on the principle of high-throughput sequencing,and established a multi-locus 10 animalderived components identification method of cattle,goat,sheep,donkey,horse,chicken,duck,goose,pigeon,quail in meat and meat products.The specific loci of each species could be detected and the species could be accurately identified,including 5 loci for cattle and duck,3 loci for sheep,9 loci for chicken and horse,10 loci for goose and pigeon,6 loci for quail and 1 locus for donkey and goat,and an adulteration model was established to simulate commercially available samples.The results showed that the method established in this study had high throughput,good repeatability and accuracy,and was able to identify 10 animalderived components simultaneously with 100%repeatability accuracy.The detection limit was 0.1%(m/m)in simulated samples of chicken,duck and horse.Using the method established in this study to test commercially available samples,4 samples from 14 commercially available samples were detected to be inconsistent with the labels,of which 2 did not contain the target ingredient and 2 were adulterated with small amounts of other ingredients.
基金supported by the National Natural Science Foundation of China(No.82171599 and No.32270901)the National Key Research and Developmental Program of China(2022YFC2702601 and 2022YFA0806303)the Global Select Project(DJKLX-2022010)of the Institute of Health and Medicine,Hefei Comprehensive National Science Center.
文摘Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.
基金supported by the National Natural Science Foundation,China(81870166).
文摘Objective:Multiple myeloma(MM)is a hematologically malignant clonal plasma cell disease.This study aims to explore the association between immunophenotypes and prognosis in patients with MM,to determine whether the expression of CD45 and CD200 is related to the prognosis of newly diagnosed MM(NDMM)patients,and to evaluate the significance of the combined expression of CD45 and CD200 in NDMM.Methods:A total of 123 NDMM patients admitted to Shengjing Hospital of China Medical University from July 2015 to August 2019 were enrolled.Five key immunophenotypic markers(including CD38,CD138,CD45,CD56,and CD200)were screened through flow cytometry and identified using random forest analysis and univariate Cox regression analysis.Patients were divided into 3 groups:Group A,CD45 and CD200 double-positive;Group B,CD45 or CD200 single-positive;Group C,CD45 and CD200 double-negative.Kaplan-Meier curves were used to analyze overall survival(OS)and progression-free survival(PFS)across groups.Multivariate Cox regression was performed to evaluate prognostic factors,and a nomogram was constructed based on these results.Results:The OS and PFS of single-positive groups for CD38,CD138,CD45,CD56,and CD200 were all shorter than those of their respective single-negative groups(all P<0.05).Significant differences were observed in OS(P<0.001)and PFS(P=0.001)among Groups A,B,and C.Group A had shorter OS and PFS(all P=0.001)compared to the Group B+C(cases from Group B and Group C were combined).CD45 and CD200 double-positive was an independent prognostic factor for NDMM[hazard ratio(HR)=2.178,95%confidence interval(CI)1.048 to 4.529;P=0.037].The nomogram and calibration curves constructed from multivariate Cox regression analysis demonstrated good concordance(concordance index=0.706;95%CI 0.661 to 0.751).Conclusion:NDMM patients with double-positive expression of CD45 and CD200 have significantly shorter OS and PFS.Compared with the use of either marker alone,the combined assessment of CD45 and CD200 may provide better prognostic stratification for MM patients.
文摘The charge carrier transport and recombination dynamics in the quantum dots-based light-emitting diodes(QLEDs)featuring multiple emitting layers(M-EMLs)has a great impact on the device performance.In this work,QLEDs based on M-EMLs separated by polyethyleneimine ethoxylated(PEIE)layer with different stacking sequences of blue(B),green(G),and red(R)QDs layer were used to intuitively explore the injection,transportation and recombination processes of the charge carriers in QLEDs by using the time-resolved electroluminescence(TrEL)spectra.From the TrEL spectra mea-surements,green and red emissions were obtained first in the QLEDs with the EMLs sequences of G/PEIE/B/PEIE/R and B/PEIE/R/PEIE/G along the direction of light emission,respectively.While the QLEDs adopt EMLs sequences of B/PEIE/G/PEIE/R,the blue,green and red emissions were obtained nearly at the same time.The above phenomenon can be attributed to different charge carrier transmission and radiation recombination process in the EMLs due to different valence band offsets and conduction band offsets between R-,G-and B-QDs by using different sequences of EMLs.White emission with coordi-nates of(0.31,0.31)and correlated color temperature(CCT)of 5916 K was obtained in the QLEDs with the EMLs se-quences of B/PEIE/G/PEIE/R,which can be attributed to the relative uniform emission of B-,G-and R-QDs due to the effec-tive injection and radiation recombination of charge carriers in each of the EMLs.The above results have great significance for further understanding and improving the performance of QLEDs with M-EMLs.
基金supported in part by the National Natural Science Foundation of China(62173051)the Fundamental Research Funds for the Central Universities(2024CDJCGJ012,2023CDJXY-010)+1 种基金the Chongqing Technology Innovation and Application Development Special Key Project(CSTB2022TIADCUX0015,CSTB2022TIAD-KPX0162)the China Postdoctoral Science Foundation(2024M763865)
文摘Dear Editor,This letter addresses the impulse game problem for a general scope of deterministic,multi-player,nonzero-sum differential games wherein all participants adopt impulse controls.Our objective is to formulate this impulse game problem with the modified objective function including interaction costs among the players in a discontinuous fashion,and subsequently,to derive a verification theorem for identifying the feedback Nash equilibrium strategy.
基金supported by the National Natural Science Foundation of China(Grant Nos.42102346,42172301).
文摘Magneto-electro-elastic(MEE)materials are widely utilized across various fields due to their multi-field coupling effects.Consequently,investigating the coupling behavior of MEE composite materials is of significant importance.The traditional finite element method(FEM)remains one of the primary approaches for addressing such issues.However,the application of FEM typically necessitates the use of a fine finite element mesh to accurately capture the heterogeneous properties of the materials and meet the required computational precision,which inevitably leads to a reduction in computational efficiency.To enhance the computational accuracy and efficiency of the FEM for heterogeneous multi-field coupling problems,this study presents the coupling magneto-electro-elastic multiscale finite element method(CM-MsFEM)for heterogeneous MEE structures.Unlike the conventional multiscale FEM(MsFEM),the proposed algorithm simultaneously constructs displacement,electric,and magnetic potential multiscale basis functions to address the heterogeneity of the corresponding parameters.The macroscale formulation of CM-MsFEM was derived,and the macroscale/microscale responses of the problems were obtained through up/downscaling calculations.Evaluation using numerical examples analyzing the transient behavior of heterogeneous MEE structures demonstrated that the proposed method outperforms traditional FEM in terms of both accuracy and computational efficiency,making it an appropriate choice for numerically modeling the dynamics of heterogeneous MEE structures.
基金jointly supported by Science and Technology Projects in Guangzhou(Grant No.SL2023A04J01079)Zhejiang ProvincialWater Conservancy Science and Technology Plan Project(Grant No.RC2405)Thematic Five of the Second Scientific Expedition of Qinghai-Tibet Plateau(Grant No.2019QZKK0905).
文摘Layered rocks(LR)exhibit inherent anisotropic stiffness and strength induced by oriented rough weakness planes,along with stress induced anisotropy and friction related plastic deformation occurs during loading.Furthermore,microcracks located in intact rock matrix(IRM)of LR are also critically important for friction and damage dissipation processes.In this paper,we first present a novel multiscale friction-damage(MFD)model using a two-step Mori-Tanaka homogenization scheme,with the aim of describing the multiscale friction-damage mechanics in LR.Physically,the initiation and propagation of flaws at different scales(i.e.microcracks and weakness planes)induced damage,and the plastic deformation is closely associated with frictional sliding along these flaws.In the thermodynamics framework,the macroscopic stress-strain relations,the local driving forces respectively conjuncted with flaws propagation and plastic deformation are derived.An analytical macroscopic strength criterion is subsequently deduced,which takes into account the variation of inclination angle and confining pressure.Notably,the failure mechanisms of IRM shearing and weakness planes sliding are inherent included in the criterion.As an original contribution,a new multisurface semi-implicit return mapping algorithm(MSRM)is developed to integrate the proposed MFD model.The robustness of MSRM algorithm is assessed by numerical tests with different loading steps sizes and convergence conditions.Finally,the effectiveness of the MFD model is confirmed using data from experiments under conventional triaxial compression,all main features of mechanical behaviors of LR are well captured by the proposed model,including initial anisotropy,stress-induced anisotropy and strain hardening/softening.
文摘This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.
基金financial support from the National Natural Science Foundation of China(Grant Nos.71971079,72271087,and 71871088)the Major Projects of the National Social Science Foundation of China(Grant No.21ZDA114)+1 种基金the National Social Science Foundation of China(Grant No.19BTJ018)the Hunan Provincial Natural Science Foundation of China(Grant No.21JJ20019).
文摘Cryptocurrency is a remarkable financial innovation that has affected the financial system in fundamental ways.Its increasingly complex interactions with the conventional financial market make precisely forecasting its volatility increasingly challenging.To this end,we propose a novel framework based on the evolving multiscale graph neural network(EMGNN).Specifically,we embed a graph that depicts the interactions between the cryptocurrency and conventional financial markets into the predictive process.Furthermore,we employ hierarchical evolving graph structure learners to model the dynamic and scale-specific interactions.We also evaluate our framework’s robustness and discuss its interpretability by extracting the learned graph structure.The empirical results show that(i)cryptocurrency volatility is not isolated from the conventional market,and the embedded graph can provide effective information for prediction;(ii)the EMGNN-based forecasting framework generally yields outstanding and robust performance in terms of multiple volatility estimators,cryptocurrency samples,forecasting horizons,and evaluation criteria;and(iii)the graph structure in the predictive process varies over time and scales and is well captured by our framework.Overall,our work provides new insights into risk management for market participants and into policy formulation for authorities.
文摘Multiple evanescent white dot syndrome(MEWDS)is an inflammatory fundus disease primarily affecting the outer retina.It is characterized by transient yellow-white dots on the outer retina.Although the exact pathogenesis remains unclear,the progress in multimodal imaging(MMI)has enhanced our understanding of MEWDS.Most cases of MEWDS are idiopathic,lacking a definite cause,and can spontaneously recover;these are what we term classic MEWDS.Consequently,MEWDS is often referred to as the“common cold of the retina”.Simultaneously,patients with other disorders may present with varying degrees of manifestations similar to MEWDS.The resemblance in clinical or imaging findings can lead to misdiagnosis and inappropriate treatment.These MEWDS-like presentations are actually caused by other systemic or ocular disorders with diverse mechanisms.Thus,they differ from classic MEWDS in certain aspects.Using the keywords“MEWDSlike”and“Secondary MEWDS”,we searched for all relevant studies published in the PubMed database from January 2021 to January 2024.Subsequently,we retrospectively summarized the clinical and imaging characteristics of MEWDS,along with the manifestations in other diseases that resembled those of MEWDS,and compared classic MEWDS with these similar presentations.Based on our review,we classified such similar presentations under other conditions into two categories and summarized their features for differential diagnosis.We recommend paying close attention to patients suspected of having MEWDS,as there may be more serious systemic or ocular disorders that require prompt treatment.
基金National Natural Science Foundation of China,Grant/Award Numbers:52192691,52192690。
文摘Rock is geometrically and mechanically multiscale in nature,and the traditional phenomenological laws at the macroscale cannot render a quantitative relationship between microscopic damage of rocks and overall rock structural degradation.This may lead to problems in the evaluation of rock structure stability and safe life.Multiscale numerical modeling is regarded as an effective way to gain insight into factors affecting rock properties from a cross-scale view.This study compiles the history of theoretical developments and numerical techniques related to rock multiscale issues according to different modeling architectures,that is,the homogenization theory,the hierarchical approach,and the concurrent approach.For these approaches,their benefits,drawbacks,and application scope are underlined.Despite the considerable attempts that have been made,some key issues still result in multiple challenges.Therefore,this study points out the perspectives of rock multiscale issues so as to provide a research direction for the future.The review results show that,in addition to numerical techniques,for example,high-performance computing,more attention should be paid to the development of an advanced constitutive model with consideration of fine geometrical descriptions of rock to facilitate solutions to multiscale problems in rock mechanics and rock engineering.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12275179,11875042,and 12150410309)the Natural Science Foundation of Shanghai(Grant No.21ZR1443900).
文摘The suprachiasmatic nucleus in the hypothalamus is the master circadian clock in mammals,coordinating physiological processes with the 24-hour day–night cycle.Comprising various cell types,the suprachiasmatic nucleus(SCN)integrates environmental signals to maintain complex and robust circadian rhythms.Understanding the complexity and synchrony within SCN neurons is essential for effective circadian clock function.Synchrony involves coordinated neuronal firing for robust rhythms,while complexity reflects diverse activity patterns and interactions,indicating adaptability.Interestingly,the SCN retains circadian rhythms in vitro,demonstrating intrinsic rhythmicity.This study introduces the multiscale structural complexity method to analyze changes in SCN neuronal activity and complexity at macro and micro levels,based on Bagrov et al.’s approach.By examining structural complexity and local complexities across scales,we aim to understand how tetrodotoxin,a neurotoxin that inhibits action potentials,affects SCN neurons.Our method captures critical scales in neuronal interactions that traditional methods may overlook.Validation with the Goodwin model confirms the reliability of our observations.By integrating experimental data with theoretical models,this study provides new insights into the effects of tetrodotoxin(TTX)on neuronal complexities,contributing to the understanding of circadian rhythms.
