A key pathological feature of Parkinson’s disease(PD)is that lysosomes are overwhelmed with cellular materials that need to be degraded and cleared.While the build-up of protein is characteristic of neurodegenerative...A key pathological feature of Parkinson’s disease(PD)is that lysosomes are overwhelmed with cellular materials that need to be degraded and cleared.While the build-up of protein is characteristic of neurodegenerative diseases such as PD and Alzheimer’s disease(AD)and is thought to reflect lysosome dysfunction,lipid accumulation may also contribute to and be indicative of severe lysosomal dysfunction.Much is known about the detrimental effects of glucosylceramide accumulation in PD lysosomes.展开更多
The surge in smishing attacks underscores the urgent need for robust,real-time detection systems powered by advanced deep learning models.This paper introduces PhishNet,a novel ensemble learning framework that integra...The surge in smishing attacks underscores the urgent need for robust,real-time detection systems powered by advanced deep learning models.This paper introduces PhishNet,a novel ensemble learning framework that integrates transformer-based models(RoBERTa)and large language models(LLMs)(GPT-OSS 120B,LLaMA3.370B,and Qwen332B)to enhance smishing detection performance significantly.To mitigate class imbalance,we apply synthetic data augmentation using T5 and leverage various text preprocessing techniques.Our system employs a duallayer voting mechanism:weighted majority voting among LLMs and a final ensemble vote to classify messages as ham,spam,or smishing.Experimental results show an average accuracy improvement from 96%to 98.5%compared to the best standalone transformer,and from 93%to 98.5%when compared to LLMs across datasets.Furthermore,we present a real-time,user-friendly application to operationalize our detection model for practical use.PhishNet demonstrates superior scalability,usability,and detection accuracy,filling critical gaps in current smishing detection methodologies.展开更多
Central nervous system(CNS) axons fail to regenerate following brain or spinal cord injury(SCI),which typically leads to permanent neurological deficits.Peripheral nervous system axons,howeve r,can regenerate followin...Central nervous system(CNS) axons fail to regenerate following brain or spinal cord injury(SCI),which typically leads to permanent neurological deficits.Peripheral nervous system axons,howeve r,can regenerate following injury.Understanding the mechanisms that underlie this difference is key to developing treatments for CNS neurological diseases and injuries characterized by axonal damage.To initiate repair after peripheral nerve injury,dorsal root ganglion(DRG) neurons mobilize a pro-regenerative gene expression program,which facilitates axon outgrowth.展开更多
This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to...This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.展开更多
Objective:To analyse the prevalence of serotypes,antibiotic resistance,and virulence genes of Group B Streptococcus(GBS)strains isolated from pregnant women at 35-37 weeks of gestation in Ho Chi Minh City,Vietnam,from...Objective:To analyse the prevalence of serotypes,antibiotic resistance,and virulence genes of Group B Streptococcus(GBS)strains isolated from pregnant women at 35-37 weeks of gestation in Ho Chi Minh City,Vietnam,from January 2022 to January 2023.Methods:GBS strains were isolated through selective culture methods and confirmed by PCR.Serotyping,virulence gene detection,and antibiotic susceptibility testing were performed using PCR,gel electrophoresis techniques and Kirby-Bauer test.Results:Totally,61 GBS isolated from 300 participants have been identified including seven GBS serotypes(Ⅰa,Ⅰb,Ⅱ,Ⅲ,Ⅳ,Ⅴ,andⅥ).SerotypesⅦ,Ⅷ,andⅨwere not detected in the study population.Antibiotic resistance patterns varied:13.1%of isolates were fully susceptible,while the majority showed multi-drug resistance,with 34.4%resistant to three antibiotics.SerotypeⅠa demonstrated high susceptibility(35.7%),while serotypeⅢshowed extensive resistance,with 87.5%being resistant to at least three antibiotics.All strains are susceptible to vancomycin andβ-lactams susceptibility also remained high,but resistance to clindamycin,erythromycin,and tetracycline was high(>65%).The virulence genes scpB,cylB,fbsB,and cfb were highly prevalent(90%-100%),indicating their potential for vaccine and diagnostic development.Conclusions:Our findings provide valuable insights into GBS serotypes,resistance,and virulence factors,contributing to community monitoring,preventive measures,diagnostics,and vaccine development.However,the limited sample size necessitates further research.展开更多
This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,5...This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.展开更多
The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduce...The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduces significant vulnerabilities,including fraud,money laundering,and market manipulation.Traditional anomaly detection techniques often fail to capture the relational and dynamic characteristics of financial data.Graph Neural Networks(GNNs),capable of modeling intricate interdependencies among entities,have emerged as a powerful framework for detecting subtle and sophisticated anomalies.However,the high-dimensionality and inherent noise of FinTech datasets demand robust feature selection strategies to improve model scalability,performance,and interpretability.This paper presents a comprehensive survey of GNN-based approaches for anomaly detection in FinTech,with an emphasis on the synergistic role of feature selection.We examine the theoretical foundations of GNNs,review state-of-the-art feature selection techniques,analyze their integration with GNNs,and categorize prevalent anomaly types in FinTech applications.In addition,we discuss practical implementation challenges,highlight representative case studies,and propose future research directions to advance the field of graph-based anomaly detection in financial systems.展开更多
Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-...Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.展开更多
Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstruc...Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.展开更多
Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More r...Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.展开更多
Background:Tandem gene repeats naturally occur as important genomic features and determine many traits in living organisms,like human diseases and microbial productivities of target bioproducts.Methods:Here,we develop...Background:Tandem gene repeats naturally occur as important genomic features and determine many traits in living organisms,like human diseases and microbial productivities of target bioproducts.Methods:Here,we developed a bacterial type-II toxin-antitoxin-mediated method to manipulate genomic integration of tandem gene repeats in Saccharomyces cerevisiae and further visualised the evolutionary trajectories of gene repeats.We designed a tri-vector system to introduce toxin-antitoxin-driven gene amplification modules.Results:This system delivered multi-copy gene integration in the form of tandem gene repeats spontaneously and independently from toxin-antitoxin-mediated selection.Inducing the toxin(RelE)expressing via a copper(II)-inducible CUP1 promoter successfully drove the in-situ gene amplification of the antitoxin(RelB)module,resulting in~40 copies of a green fluorescence reporter gene per copy of genome.Copy-number changes,copy-number increase and copy-number decrease,and stable maintenance were visualised using the green fluorescence protein and blue chromoprotein AeBlue as reporters.Copy-number increases happened spontaneously and independent on a selection pressure.Increased copy number was quickly enriched through toxin-antitoxin-mediated selection.Conclusion:In summary,the bacterial toxin-antitoxin systems provide a flexible mechanism to manipulate gene copy number in eukaryotic cells and can be exploited for synthetic biology and metabolic engineering applications.展开更多
Field training is the backbone of the teacher-preparation process.Its importance stems from the goals that colleges of education aim to achieve,which include bridging the gap between theory and practice and aligning w...Field training is the backbone of the teacher-preparation process.Its importance stems from the goals that colleges of education aim to achieve,which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher training.Currently,trainee students attendance in field training is recordedmanually through signatures on attendance sheets.However,thismethod is prone to impersonation,time wastage,and misplacement.Additionally,traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring processes.Field training also lacks modern technology that the supervisor can use in case of his absence from school to monitor the trainee students’implementation of the required activities and tasks.These shortcomings do not meet the needs of the digital era that universities are currently experiencing.As a result,this paper presents a smart management system for field training based on Internet of Things(IoT)and mobile technology.It includes three subsystems:attendance,monitoring,and evaluation.The attendance subsystem uses an R307 fingerprint sensor to record trainee students’attendance.The Arduino Nano microcontroller transmits attendance data to the proposed Android application via an ESP-12F Wi-Fi module,which then forwards it to the Firebase database for storage.The monitoring subsystem utilizes Global Positioning System(GPS)technology to continually track trainee students’locations,ensuring they remain at the school during training.It also enables remote communication between trainee students and supervisors via audio,video,or text by integrating video call and chat technologies.The evaluation subsystem is based on three items:an online exam,attendance,and implementation of required activities and tasks.Experimental results have demonstrated the accuracy and efficiency of the proposed management system in recording attendance,as well as in monitoring and evaluating trainee students during field traiing.展开更多
近些年,我国光伏与风电装机量和发电量迅猛增长,引发对其生态问题的关注与探讨,而减缓生态影响的措施和工具方法也亟需更多的认识和应用。本文根据陆上集中式光伏和风电电场的生态影响研究,综述了国内外光伏与风电电场的生态影响减缓措...近些年,我国光伏与风电装机量和发电量迅猛增长,引发对其生态问题的关注与探讨,而减缓生态影响的措施和工具方法也亟需更多的认识和应用。本文根据陆上集中式光伏和风电电场的生态影响研究,综述了国内外光伏与风电电场的生态影响减缓措施,发现早期合理规划选址可以有效、低成本地规避不利影响,并从景观角度总结了减缓生态影响的规划方法,包括用于风险筛查的环境和社会影响评估(environmental and social impactassessment,ESIA)和敏感性地图绘制,用于综合空间规划的发展系统规划(Development by Design,DbD)、空间规划和敏感性地图绘制结合及可再生能源与生物资源的兼容性计算等方法,从而依据生态影响和风险进行可再生能源选址。最后,结合我国国情,我们建议通过加强光伏和风电场生态影响研究、简化选址流程、强化跨部门协调优化生态友好选址(如废弃矿区再利用)、建立生态监测体系,并完善政策支持与技术标准,因地制宜推动创新生态友好型可再生能源发展模式,确保生态保护措施贯穿项目全周期。展开更多
Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent bioc...Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.展开更多
Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercom...Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercomparison Project(GeoMIP) framework,utilizing the Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0).This paper briefly describes the basic configuration and experimental design of the CAS-ESM2.0 for G1ext,which involves a sudden reduction in solar irradiance to counterbalance the radiative forcing of an abrupt quadrupling of atmospheric CO_(2) concentration,running for 100 years.Preliminary results show that this model can reproduce well the compensatory effect of a uniform decrease in global solar radiation on the radiative forcing resulting from an abrupt quadrupling of CO_(2) concentration.Like other Earth system models,CAS-ESM2.0 reasonably captures variations in radiative adjustments,surface air temperature,and precipitation patterns,both globally and locally,under the G1ext scenario.The generated datasets have been released on the Earth System Grid Federation data server,providing insight into the potential efficacy and impact of solar geoengineering strategies.展开更多
Low-density lipoprotein receptor-related protein 1(LRP1)is a multifunctional endocytic receptor whose dysfunction is linked to developmental dysplasia of the hip,osteoporosis and osteoarthritis.Our work addresses the ...Low-density lipoprotein receptor-related protein 1(LRP1)is a multifunctional endocytic receptor whose dysfunction is linked to developmental dysplasia of the hip,osteoporosis and osteoarthritis.Our work addresses the critical question of how these skeletal pathologies emerge.Here,we show the abundant expression of LRP1 in skeletal progenitor cells at mouse embryonic stage E10.5 and onwards,especially in the perichondrium,the stem cell layer surrounding developing limbs essential for bone formation.Lrp1 deficiency in these stem cells causes joint fusion,malformation of cartilage/bone template and markedly delayed or lack of primary ossification.展开更多
In recent years, the research advancements have high-lighted the critical role of the A-site cation in determining the optoelectronic and physicochemical properties of organicinorganic lead halide perovskites. Mixed-c...In recent years, the research advancements have high-lighted the critical role of the A-site cation in determining the optoelectronic and physicochemical properties of organicinorganic lead halide perovskites. Mixed-cation perovskites(MCPs) have been extensively used as absorber thin films in perovskite solar cells(PSCs), achieving high power conversion efficiencies(PCE) over 26%^([1, 2]).展开更多
BACKGROUND: Sepsis is a life-threatening inflammatory condition in which the invading pathogen avoids the host's defense mechanisms and continuously stimulates and damages host cells. Consequently, many immune res...BACKGROUND: Sepsis is a life-threatening inflammatory condition in which the invading pathogen avoids the host's defense mechanisms and continuously stimulates and damages host cells. Consequently, many immune responses initially triggered for protection become harmful because of the failure to restore homeostasis, resulting in ongoing hyperinflammation and immunosuppression. METHODS: A literature review was conducted to address bacterial sepsis, describe advances in understanding complex immunological reactions, critically assess diagnostic approaches, and emphasize the importance of studying bacterial bottlenecks in the detection and treatment of sepsis.RESULTS: Diagnosing sepsis via a single laboratory test is not feasible;therefore, multiple key biomarkers are typically monitored, with a focus on trends rather than absolute values. The immediate interpretation of sepsis-associated clinical signs and symptoms, along with the use of specific and sensitive laboratory tests, is crucial for the survival of patients in the early stages. However, long-term mortality associated with sepsis is now recognized, and alongside the progression of this condition, there is an in vivo selection of adapted pathogens.CONCLUSION: Bacterial sepsis remains a significant cause of mortality across all ages and societies. While substantial progress has been made in understanding the immunological mechanisms underlying the inflammatory response, there is growing recognition that the ongoing host-pathogen interactions, including the emergence of adapted virulent strains, shape both the acute and long-term outcomes in sepsis. This underscores the urgent need for novel high-throughput diagnostic methods and a shift toward more pre-emptive, rather than reactive, treatment strategies in sepsis care.展开更多
App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While t...App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.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
文摘A key pathological feature of Parkinson’s disease(PD)is that lysosomes are overwhelmed with cellular materials that need to be degraded and cleared.While the build-up of protein is characteristic of neurodegenerative diseases such as PD and Alzheimer’s disease(AD)and is thought to reflect lysosome dysfunction,lipid accumulation may also contribute to and be indicative of severe lysosomal dysfunction.Much is known about the detrimental effects of glucosylceramide accumulation in PD lysosomes.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under Grant No.(GPIP:1074-612-2024).
文摘The surge in smishing attacks underscores the urgent need for robust,real-time detection systems powered by advanced deep learning models.This paper introduces PhishNet,a novel ensemble learning framework that integrates transformer-based models(RoBERTa)and large language models(LLMs)(GPT-OSS 120B,LLaMA3.370B,and Qwen332B)to enhance smishing detection performance significantly.To mitigate class imbalance,we apply synthetic data augmentation using T5 and leverage various text preprocessing techniques.Our system employs a duallayer voting mechanism:weighted majority voting among LLMs and a final ensemble vote to classify messages as ham,spam,or smishing.Experimental results show an average accuracy improvement from 96%to 98.5%compared to the best standalone transformer,and from 93%to 98.5%when compared to LLMs across datasets.Furthermore,we present a real-time,user-friendly application to operationalize our detection model for practical use.PhishNet demonstrates superior scalability,usability,and detection accuracy,filling critical gaps in current smishing detection methodologies.
基金supported by the Canada Foundation for Innovation (Project#44220)the Natural Sciences and Engineering Research Council of Canada (RGPIN-2024-03986)+3 种基金the Michael Smith Foundation for Health Research BCthe financial support of Health Canada,through the Canada Brain Research Fund,an innovative partnership between the Government of Canada (through Health Canada),Brain Canada Foundationthe Azrieli Foundationsupported by a Canadian Institutes of Health Research (CIHR) Canada Graduate Scholarship–Master’s Award。
文摘Central nervous system(CNS) axons fail to regenerate following brain or spinal cord injury(SCI),which typically leads to permanent neurological deficits.Peripheral nervous system axons,howeve r,can regenerate following injury.Understanding the mechanisms that underlie this difference is key to developing treatments for CNS neurological diseases and injuries characterized by axonal damage.To initiate repair after peripheral nerve injury,dorsal root ganglion(DRG) neurons mobilize a pro-regenerative gene expression program,which facilitates axon outgrowth.
基金Supported by Japan Society for the Promotion of Science,No.24K11935.
文摘This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.
文摘Objective:To analyse the prevalence of serotypes,antibiotic resistance,and virulence genes of Group B Streptococcus(GBS)strains isolated from pregnant women at 35-37 weeks of gestation in Ho Chi Minh City,Vietnam,from January 2022 to January 2023.Methods:GBS strains were isolated through selective culture methods and confirmed by PCR.Serotyping,virulence gene detection,and antibiotic susceptibility testing were performed using PCR,gel electrophoresis techniques and Kirby-Bauer test.Results:Totally,61 GBS isolated from 300 participants have been identified including seven GBS serotypes(Ⅰa,Ⅰb,Ⅱ,Ⅲ,Ⅳ,Ⅴ,andⅥ).SerotypesⅦ,Ⅷ,andⅨwere not detected in the study population.Antibiotic resistance patterns varied:13.1%of isolates were fully susceptible,while the majority showed multi-drug resistance,with 34.4%resistant to three antibiotics.SerotypeⅠa demonstrated high susceptibility(35.7%),while serotypeⅢshowed extensive resistance,with 87.5%being resistant to at least three antibiotics.All strains are susceptible to vancomycin andβ-lactams susceptibility also remained high,but resistance to clindamycin,erythromycin,and tetracycline was high(>65%).The virulence genes scpB,cylB,fbsB,and cfb were highly prevalent(90%-100%),indicating their potential for vaccine and diagnostic development.Conclusions:Our findings provide valuable insights into GBS serotypes,resistance,and virulence factors,contributing to community monitoring,preventive measures,diagnostics,and vaccine development.However,the limited sample size necessitates further research.
文摘This study explores the thin-layer convective solar drying of Marrubium vulgare L.leaves under conditions typical of sun-rich semi-arid climates.Drying experiments were conducted at three inlet-air temperatures(40℃,50℃,60℃)and two air velocities(1.5 and 2.5 m·s^(-1))using an indirect solar dryer with auxiliary temperature control.Moisture-ratio data were fitted with eight widely used thin-layer models and evaluated using correlation coefficient(r),root-mean-square error(RMSE),and Akaike information criterion(AIC).A complementary heattransfer analysis based on Reynolds and Prandtl numbers with appropriate Nusselt correlations was used to relate flow regime to drying performance,and an energy balance quantified the relative contributions of solar and auxiliary heat.The logarithmic model consistently achieved the lowest RMSE/AIC with r>0.99 across all conditions.Higher temperature and air velocity significantly reduced drying time during the decreasing-rate period,with no constantrate stage observed.On average,solar input supplied the large majority of the thermal demand,while the auxiliary heater compensated short irradiance drops to maintain setpoints.These findings provide a reproducible dataset and a modelling benchmark for M.vulgare leaves,and they support energy-aware design of hybrid solar dryers formedicinal plants in sun-rich regions.
基金supported by Ho Chi Minh City Open University,Vietnam under grant number E2024.02.1CD and Suan Sunandha Rajabhat University,Thailand.
文摘The Financial Technology(FinTech)sector has witnessed rapid growth,resulting in increasingly complex and high-volume digital transactions.Although this expansion improves efficiency and accessibility,it also introduces significant vulnerabilities,including fraud,money laundering,and market manipulation.Traditional anomaly detection techniques often fail to capture the relational and dynamic characteristics of financial data.Graph Neural Networks(GNNs),capable of modeling intricate interdependencies among entities,have emerged as a powerful framework for detecting subtle and sophisticated anomalies.However,the high-dimensionality and inherent noise of FinTech datasets demand robust feature selection strategies to improve model scalability,performance,and interpretability.This paper presents a comprehensive survey of GNN-based approaches for anomaly detection in FinTech,with an emphasis on the synergistic role of feature selection.We examine the theoretical foundations of GNNs,review state-of-the-art feature selection techniques,analyze their integration with GNNs,and categorize prevalent anomaly types in FinTech applications.In addition,we discuss practical implementation challenges,highlight representative case studies,and propose future research directions to advance the field of graph-based anomaly detection in financial systems.
基金supported by the Natural Science Foundation of Hubei Provincial Department of Education(D20232101)Shandong Second Medical University 2024 Affiliated Hospital(Teaching Hospital)Scientific Research Development Fund Project(2024FYQ026)+3 种基金the innovative Research Programme of Xiangyang No.1 People’s Hospital(XYY2023ZY01)Faculty Development Grants of Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine(XYY2023D05)Joint supported by Hubei Provincial Natural Science Foundation and Xiangyang of China(2025AFD091)Traditional Chinese Medicine Scientific Research Project of Hubei Provincial Administration of Traditional Chinese Medicine(ZY2025D019).
文摘Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.
基金funded by the Directorate of Research and Community Service,Directorate General of Research and Development,Ministry of Higher Education,Science and Technologyin accordance with the Implementation Contract for the Operational Assistance Program for State Universities,Research Program Number:109/C3/DT.05.00/PL/2025.
文摘Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.
基金supported by the National Natural Science Foundation of China,Nos.82404892(to QY),82061160374(to ZZ)the Science and Technology Development Fund,Macao Special Administrative Region,China,Nos.0023/2020/AFJ,0035/2020/AGJ+2 种基金the University of Macao Research Grant,Nos.MYRG2022-00248-ICMS,MYRG-CRG2022-00010-ICMS(to MPMH)the Natural Science Foundation of Guangdong Province,No.2024A1515012818(to ZZ)the Fundamental Research Funds for the Central Universities,No.21623114(to ZZ).
文摘Drug development for Alzheimer’s disease is extremely challenging,as demonstrated by the repeated failures of amyloid-β-targeted therapeutics and the controversies surrounding the amyloid-βcascade hypothesis.More recently,advances in the development of Lecanemab,an anti-amyloid-βmonoclonal antibody,have shown positive results in reducing brain A burden and slowing cognitive decline in patients with early-stage Alzheimer’s disease in the Phase Ⅲ clinical trial(Clarity Alzheimer’s disease).Despite these promising results,side effects such as amyloid-related imaging abnormalities(ARIA)may limit its usage.ARIA can manifest as ARIA-E(cerebral edema or effusions)and ARIA-H(microhemorrhages or superficial siderosis)and is thought to be caused by increased vascular permeability due to inflammatory responses,leading to leakages of blood products and protein-rich fluid into brain parenchyma.Endothelial dysfunction is an early pathological feature of Alzheimer’s disease,and the blood-brain barrier becomes increasingly leaky as the disease progresses.In addition,APOE4,the strongest genetic risk factor for Alzheimer’s disease,is associated with higher vascular amyloid burden,increased ARIA incidence,and accelerated blood-brain barrier disruptions.These interconnected vascular abnormalities highlight the importance of vascular contributions to the pathophysiology of Alzheimer’s disease.Here,we will closely examine recent research evaluating the heterogeneity of brain endothelial cells in the microvasculature of different brain regions and their relationships with Alzheimer’s disease progression.
基金supported partially by the Australian Government through the Australian Research Council Centres of Excellence funding scheme(project CE200100029)。
文摘Background:Tandem gene repeats naturally occur as important genomic features and determine many traits in living organisms,like human diseases and microbial productivities of target bioproducts.Methods:Here,we developed a bacterial type-II toxin-antitoxin-mediated method to manipulate genomic integration of tandem gene repeats in Saccharomyces cerevisiae and further visualised the evolutionary trajectories of gene repeats.We designed a tri-vector system to introduce toxin-antitoxin-driven gene amplification modules.Results:This system delivered multi-copy gene integration in the form of tandem gene repeats spontaneously and independently from toxin-antitoxin-mediated selection.Inducing the toxin(RelE)expressing via a copper(II)-inducible CUP1 promoter successfully drove the in-situ gene amplification of the antitoxin(RelB)module,resulting in~40 copies of a green fluorescence reporter gene per copy of genome.Copy-number changes,copy-number increase and copy-number decrease,and stable maintenance were visualised using the green fluorescence protein and blue chromoprotein AeBlue as reporters.Copy-number increases happened spontaneously and independent on a selection pressure.Increased copy number was quickly enriched through toxin-antitoxin-mediated selection.Conclusion:In summary,the bacterial toxin-antitoxin systems provide a flexible mechanism to manipulate gene copy number in eukaryotic cells and can be exploited for synthetic biology and metabolic engineering applications.
文摘Field training is the backbone of the teacher-preparation process.Its importance stems from the goals that colleges of education aim to achieve,which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher training.Currently,trainee students attendance in field training is recordedmanually through signatures on attendance sheets.However,thismethod is prone to impersonation,time wastage,and misplacement.Additionally,traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring processes.Field training also lacks modern technology that the supervisor can use in case of his absence from school to monitor the trainee students’implementation of the required activities and tasks.These shortcomings do not meet the needs of the digital era that universities are currently experiencing.As a result,this paper presents a smart management system for field training based on Internet of Things(IoT)and mobile technology.It includes three subsystems:attendance,monitoring,and evaluation.The attendance subsystem uses an R307 fingerprint sensor to record trainee students’attendance.The Arduino Nano microcontroller transmits attendance data to the proposed Android application via an ESP-12F Wi-Fi module,which then forwards it to the Firebase database for storage.The monitoring subsystem utilizes Global Positioning System(GPS)technology to continually track trainee students’locations,ensuring they remain at the school during training.It also enables remote communication between trainee students and supervisors via audio,video,or text by integrating video call and chat technologies.The evaluation subsystem is based on three items:an online exam,attendance,and implementation of required activities and tasks.Experimental results have demonstrated the accuracy and efficiency of the proposed management system in recording attendance,as well as in monitoring and evaluating trainee students during field traiing.
文摘近些年,我国光伏与风电装机量和发电量迅猛增长,引发对其生态问题的关注与探讨,而减缓生态影响的措施和工具方法也亟需更多的认识和应用。本文根据陆上集中式光伏和风电电场的生态影响研究,综述了国内外光伏与风电电场的生态影响减缓措施,发现早期合理规划选址可以有效、低成本地规避不利影响,并从景观角度总结了减缓生态影响的规划方法,包括用于风险筛查的环境和社会影响评估(environmental and social impactassessment,ESIA)和敏感性地图绘制,用于综合空间规划的发展系统规划(Development by Design,DbD)、空间规划和敏感性地图绘制结合及可再生能源与生物资源的兼容性计算等方法,从而依据生态影响和风险进行可再生能源选址。最后,结合我国国情,我们建议通过加强光伏和风电场生态影响研究、简化选址流程、强化跨部门协调优化生态友好选址(如废弃矿区再利用)、建立生态监测体系,并完善政策支持与技术标准,因地制宜推动创新生态友好型可再生能源发展模式,确保生态保护措施贯穿项目全周期。
基金supported by the grants from University of Macao,China,Nos.MYRG2022-00221-ICMS(to YZ)and MYRG-CRG2022-00011-ICMS(to RW)the Natural Science Foundation of Guangdong Province,No.2023A1515010034(to YZ)。
文摘Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on society.Extracellular vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic stroke.However,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery efficiency.By utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly improved.Furthermore,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic stroke.Small extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke therapy.In this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification methodologies.Given the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment process.Moreover,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.
基金supported by the National Natural Science Foundation of China(Grant No.41875126)the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility”(EarthLab)。
文摘Solar radiation modification,a scheme aimed at mitigating rapid global warming triggered by anthropogenic greenhouse gas emissions,has been explored through the G1ext experiment under the Geoengineering Model Intercomparison Project(GeoMIP) framework,utilizing the Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0).This paper briefly describes the basic configuration and experimental design of the CAS-ESM2.0 for G1ext,which involves a sudden reduction in solar irradiance to counterbalance the radiative forcing of an abrupt quadrupling of atmospheric CO_(2) concentration,running for 100 years.Preliminary results show that this model can reproduce well the compensatory effect of a uniform decrease in global solar radiation on the radiative forcing resulting from an abrupt quadrupling of CO_(2) concentration.Like other Earth system models,CAS-ESM2.0 reasonably captures variations in radiative adjustments,surface air temperature,and precipitation patterns,both globally and locally,under the G1ext scenario.The generated datasets have been released on the Earth System Grid Federation data server,providing insight into the potential efficacy and impact of solar geoengineering strategies.
基金The Andor dragonfly Spinning Disk microscope in the CCI was funded by the BBSRC(BB/R01390X/1)This work was supported by the ministry of education of the Kingdom of Saudi Arabia(to M.Alhashmi)+6 种基金Libyan Ministry of Higher Education and Scientific Research and ECMage(to A.M.E.Gremida)Qatar National Research Fund(to N.A.Al-Maslamani)European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement(860635 to M.Antonaci and A.Kerr)BBSRC Grants(BB/T00715X/1 to S.K.Maharana and G.N.WheelerBB/X000907/1 to D.A.Turner)Versus Arthritis Career Development Fellowship(21447 to K.Yamamoto)Versus Arthritis Bridging Fellowship(23137 to K.Yamamoto).
文摘Low-density lipoprotein receptor-related protein 1(LRP1)is a multifunctional endocytic receptor whose dysfunction is linked to developmental dysplasia of the hip,osteoporosis and osteoarthritis.Our work addresses the critical question of how these skeletal pathologies emerge.Here,we show the abundant expression of LRP1 in skeletal progenitor cells at mouse embryonic stage E10.5 and onwards,especially in the perichondrium,the stem cell layer surrounding developing limbs essential for bone formation.Lrp1 deficiency in these stem cells causes joint fusion,malformation of cartilage/bone template and markedly delayed or lack of primary ossification.
基金financially supported by the National Natural Science Foundation of China (52462032, 62274018, 52462031)Natural Science Foundation of Yunnan Province (202501AT070353, 202101BE070001-049)+2 种基金the Xinjiang Construction Corps Key Areas of Science and Technology Research Project (2023AB029)the Tianchi Talent Program of Xinjiang Uygur Autonomous Region (2024, Jiangzhao Chen)the Key Project of Chongqing Overseas Students Returning to China Entrepreneurship and Innovation Support Plan (cx2023006)。
文摘In recent years, the research advancements have high-lighted the critical role of the A-site cation in determining the optoelectronic and physicochemical properties of organicinorganic lead halide perovskites. Mixed-cation perovskites(MCPs) have been extensively used as absorber thin films in perovskite solar cells(PSCs), achieving high power conversion efficiencies(PCE) over 26%^([1, 2]).
基金funded by the Deanship of Scientific Research (DSR) at King Abdulaziz UniversityJeddah+1 种基金Saudi Arabiaunder grant number G-150-248-1443。
文摘BACKGROUND: Sepsis is a life-threatening inflammatory condition in which the invading pathogen avoids the host's defense mechanisms and continuously stimulates and damages host cells. Consequently, many immune responses initially triggered for protection become harmful because of the failure to restore homeostasis, resulting in ongoing hyperinflammation and immunosuppression. METHODS: A literature review was conducted to address bacterial sepsis, describe advances in understanding complex immunological reactions, critically assess diagnostic approaches, and emphasize the importance of studying bacterial bottlenecks in the detection and treatment of sepsis.RESULTS: Diagnosing sepsis via a single laboratory test is not feasible;therefore, multiple key biomarkers are typically monitored, with a focus on trends rather than absolute values. The immediate interpretation of sepsis-associated clinical signs and symptoms, along with the use of specific and sensitive laboratory tests, is crucial for the survival of patients in the early stages. However, long-term mortality associated with sepsis is now recognized, and alongside the progression of this condition, there is an in vivo selection of adapted pathogens.CONCLUSION: Bacterial sepsis remains a significant cause of mortality across all ages and societies. While substantial progress has been made in understanding the immunological mechanisms underlying the inflammatory response, there is growing recognition that the ongoing host-pathogen interactions, including the emergence of adapted virulent strains, shape both the acute and long-term outcomes in sepsis. This underscores the urgent need for novel high-throughput diagnostic methods and a shift toward more pre-emptive, rather than reactive, treatment strategies in sepsis care.
基金supported by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant no.(GPIP:13-612-2024).
文摘App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.
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.
