Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates dise...Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates disease severity,supports effective treatment strategies,and reduces reliance on excessive pesticide use.Traditional machine learning approaches have been applied for automated rice disease diagnosis;however,these methods depend heavily on manual image preprocessing and handcrafted feature extraction,which are labor-intensive and time-consuming and often require domain expertise.Recently,end-to-end deep learning(DL) models have been introduced for this task,but they often lack robustness and generalizability across diverse datasets.To address these limitations,we propose a novel end-toend training framework for convolutional neural network(CNN) and attention-based model ensembles(E2ETCA).This framework integrates features from two state-of-the-art(SOTA) CNN models,Inception V3 and DenseNet-201,and an attention-based vision transformer(ViT) model.The fused features are passed through an additional fully connected layer with softmax activation for final classification.The entire process is trained end-to-end,enhancing its suitability for realworld deployment.Furthermore,we extract and analyze the learned features using a support vector machine(SVM),a traditional machine learning classifier,to provide comparative insights.We evaluate the proposed E2ETCA framework on three publicly available datasets,the Mendeley Rice Leaf Disease Image Samples dataset,the Kaggle Rice Diseases Image dataset,the Bangladesh Rice Research Institute dataset,and a combined version of all three.Using standard evaluation metrics(accuracy,precision,recall,and F1-score),our framework demonstrates superior performance compared to existing SOTA methods in rice disease diagnosis,with potential applicability to other agricultural disease detection tasks.展开更多
Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders...Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.展开更多
Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-de...Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.展开更多
Introduction:One of the main events that regulate a cell’s well-being is cell-to-cell communication.This intercellular mechanism of information transfer is often mediated by vesicular trafficking.Mitochondrial-derive...Introduction:One of the main events that regulate a cell’s well-being is cell-to-cell communication.This intercellular mechanism of information transfer is often mediated by vesicular trafficking.Mitochondrial-derived vesicles(MDVs)are an emerging subpopulation of extracellular vesicle(EV)first discovered in 2008 that allow mitochondria to communicate with their surroundings.展开更多
Contrary to the adult central nervous system,the peripheral nervous system has an intrinsic ability to regenerate that relies on the expression of regenerationassociated genes,such as some kinesin family members.Kines...Contrary to the adult central nervous system,the peripheral nervous system has an intrinsic ability to regenerate that relies on the expression of regenerationassociated genes,such as some kinesin family members.Kinesins contribute to nerve regeneration through the transport of specific cargo,such as proteins and membrane components,from the cell body towards the axon periphery.We show here that KIF4A,associated with neurodevelopmental disorders and previously believed to be only expressed during development,is also expressed in the adult vertebrate nervous system and up-regulated in injured peripheral nervous system cells.KIF4A is detected both in the cell bodies and regrowing axons of injured neurons,consistent with its function as an axonal transporter of cargoes such asβ1-integrin and L1CAM.Our study further demonstrates that KIF4A levels are greatly increased in Schwann cells from injured distal nerve stumps,particularly at a time when they are reprogrammed into an essential proliferative repair phenotype.Moreover,Kif4a m RNA levels were approximately~6-fold higher in proliferative cultured Schwann cells compared with non-proliferative ones.A hypothesized function for Kif4a in Schwann cell proliferation was further confirmed by Kif4a knockdown,as this significantly reduced Schwann cell proliferation in vitro.Our findings show that KIF4A is expressed in adult vertebrate nervous systems and is up-regulated following peripheral injury.The timing of KIF4A up-regulation,its location during regeneration,and its proliferative role,all suggest a dual role for this protein in neuroregeneration that is worth exploring in the future.展开更多
The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreser...The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.展开更多
Staphylococcus aureus(S.aureus)is the third most common pathogen causing 10.6%of bacterial foodborne illnesses in China in 2021[1].Heat-stable Staphylococcal Enterotoxins(SEs)produced by S.aureus are the main contribu...Staphylococcus aureus(S.aureus)is the third most common pathogen causing 10.6%of bacterial foodborne illnesses in China in 2021[1].Heat-stable Staphylococcal Enterotoxins(SEs)produced by S.aureus are the main contributors to staphylococcal food poisoning(SFP),causing vomiting,diarrhea,abdominal pain,headache,muscle cramps,and other acute gastroenteritis symptoms.More than 25 SEs and staphylococcal enterotoxin-like toxins(SE/s)have been described and which together comprise a superfamily of pyrogenic toxin superantigens(SAgs)[2].展开更多
Global brain ischemia and neurological deficit are consequences of cardiac arrest that lead to high mortality.Despite advancements in resuscitation science,our limited understanding of the cellular and molecular mecha...Global brain ischemia and neurological deficit are consequences of cardiac arrest that lead to high mortality.Despite advancements in resuscitation science,our limited understanding of the cellular and molecular mechanisms underlying post-cardiac arrest brain injury have hindered the development of effective neuroprotective strategies.Previous studies primarily focused on neuronal death,potentially overlooking the contributions of non-neuronal cells and intercellular communication to the pathophysiology of cardiac arrest-induced brain injury.To address these gaps,we hypothesized that single-cell transcriptomic analysis could uncover previously unidentified cellular subpopulations,altered cell communication networks,and novel molecular mechanisms involved in post-cardiac arrest brain injury.In this study,we performed a single-cell transcriptomic analysis of the hippocampus from pigs with ventricular fibrillation-induced cardiac arrest at 6 and 24 hours following the return of spontaneous circulation,and from sham control pigs.Sequencing results revealed changes in the proportions of different cell types,suggesting post-arrest disruption in the blood-brain barrier and infiltration of neutrophils.These results were validated through western blotting,quantitative reverse transcription-polymerase chain reaction,and immunofluorescence staining.We also identified and validated a unique subcluster of activated microglia with high expression of S100A8,which increased over time following cardiac arrest.This subcluster simultaneously exhibited significant M1/M2 polarization and expressed key functional genes related to chemokines and interleukins.Additionally,we revealed the post-cardiac arrest dysfunction of oligodendrocytes and the differentiation of oligodendrocyte precursor cells into oligodendrocytes.Cell communication analysis identified enhanced post-cardiac arrest communication between neutrophils and microglia that was mediated by neutrophil-derived resistin,driving pro-inflammatory microglial polarization.Our findings provide a comprehensive single-cell map of the post-cardiac arrest hippocampus,offering potential novel targets for neuroprotection and repair following cardiac arrest.展开更多
Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibi...Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibitory environment for axonal regeneration. Among these inhibitory molecules, myelinassociated inhibitors, including neurite outgrowth inhibitor A, oligodendrocyte myelin glycoprotein, myelin-associated glycoprotein, chondroitin sulfate proteoglycans and repulsive guidance molecule A are of particular importance. Due to their inhibitory nature, they represent exciting molecular targets to study axonal inhibition and regeneration after central injuries. These molecules are mainly produced by neurons, oligodendrocytes, and astrocytes within the scar and in its immediate vicinity. They exert their effects by binding to specific receptors, localized in the membranes of neurons. Receptors for these inhibitory cues include Nogo receptor 1, leucine-rich repeat, and Ig domain containing 1 and p75 neurotrophin receptor/tumor necrosis factor receptor superfamily member 19(that form a receptor complex that binds all myelin-associated inhibitors), and also paired immunoglobulin-like receptor B. Chondroitin sulfate proteoglycans and repulsive guidance molecule A bind to Nogo receptor 1, Nogo receptor 3, receptor protein tyrosine phosphatase σ and leucocyte common antigen related phosphatase, and neogenin, respectively. Once activated, these receptors initiate downstream signaling pathways, the most common amongst them being the Rho A/ROCK signaling pathway. These signaling cascades result in actin depolymerization, neurite outgrowth inhibition, and failure to regenerate after spinal cord injury. Currently, there are no approved pharmacological treatments to overcome spinal cord injuries other than physical rehabilitation and management of the array of symptoms brought on by spinal cord injuries. However, several novel therapies aiming to modulate these inhibitory proteins and/or their receptors are under investigation in ongoing clinical trials. Investigation has also been demonstrating that combinatorial therapies of growth inhibitors with other therapies, such as growth factors or stem-cell therapies, produce stronger results and their potential application in the clinics opens new venues in spinal cord injury treatment.展开更多
Hepatocellular carcinoma(HCC) is an aggressive malignancy,resulting as the third cause of death by cancer each year. The management of patients with HCC is complex,as both the tumour stage and any underlying liver dis...Hepatocellular carcinoma(HCC) is an aggressive malignancy,resulting as the third cause of death by cancer each year. The management of patients with HCC is complex,as both the tumour stage and any underlying liver disease must be considered conjointly. Although surveillance by imaging,clinical and biochemical parameters is routinely performed,a lot of patients suffering from cirrhosis have an advanced stage HCC at the first diagnosis. Advanced stage HCC includes heterogeneous groups of patients with different clinical condition and radiological features and sorafenib is the only approved treatment according to Barcelona Clinic Liver Cancer. Since the introduction of sorafenib in clinical practice,several phase Ⅲ clinical trials have failed to demonstrate any superiority over sorafenib in the frontline setting. Locoregional therapies have also been tested as first line treatment,but their role in advanced HCC is still matter of debate. No single agent or combination therapies have been shown to impact outcomes after sorafenib failure. Therefore this review will focus on the range of experimental therapeutics for patients with advanced HCC and highlights the successes and failures of these treatments as well as areas for future development. Specifics such as dose limiting toxicity and safety profile in patients with liver dysfunction related to the underlying chronic liver disease should be considered when developing therapies in HCC. Finally,robust validated and reproducible surrogate end-points as well as predictive biomarkers should be defined in future randomized trials.展开更多
Advanced stage hepatocellular carcinoma(HCC) is a category of disease defined by radiological, clinical and hepatic function parameters, comprehending a wide range of patients with different general conditions. The ma...Advanced stage hepatocellular carcinoma(HCC) is a category of disease defined by radiological, clinical and hepatic function parameters, comprehending a wide range of patients with different general conditions. The main therapeutic option is represented by sorafenibtreatment, a multi-kinase inhibitor with anti-proliferative and anti-angiogenic effect. Trans-arterial Radio Embolization also represents a promising new approach to intermediate/advanced HCC. Post-marketing clinical studies showed that only a portion of patients actually benefits from sorafenib treatment, and an even smaller percentage of patients treated shows partial/complete response on follow-up examinations, up against relevant costs and an incidence of drug related adverse effects. Although the treatment with sorafenib has shown a significant increase in mean overall survival in different studies, only a part of patients actually shows real benefits, while the incidence of drug related significant adverse effects and the economic costs are relatively high. Moreover, only a small percentage of patients also shows a response in terms of lesion dimensions reduction. Being able to properly differentiate patients who are responding to the therapy from non-responders as early as possible is then still difficult and could be a pivotal challenge for the future; in fact it could spare several patients a therapy often difficult to bear, directing them to other second line treatments(many of which are at the moment still under investigation). For this reason, some supplemental criteria to be added to the standard modified Response Evaluation Criteria in Solid Tumors evaluation are being searched for. In particular, finding some parameters(cellular density, perfusion grade and enhancement rate) able to predict the sensitivity of the lesions to anti-angiogenic agents could help in stratifying patients in terms of treatment responsiveness before the beginning of the therapy itself, or in the first weeks of sorafenib treatment. This would bring a strongly desirable help in clinical managements of these patients.展开更多
Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 tr...Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 trial)showed no additional advantage.The PD-RAD study was set up to understand the immunological effects of RT on the tumor microenvironment(TME)to aid in optimizing sequencing of combination therapies.Methods:The PD-RAD trial(ClinicalTrials.gov identifier:NCT03258788)aimed to enroll thirty NSCLC patients receiving radical-intent RT.Tumor biopsies and blood samples were collected pre-RT and at week 2 during RT and analyzed using multiplex immunohistochemistry(mIHC)and high-dimensional mass cytometry(CyTOF),respectively.Results:Paired biopsies were collected from only three patients(Pts 1,3&4)and blood from four patients(Pts 1-4)before the study was closed early during the COVID-19 pandemic.Programmed Death-Ligand 1(PD-L1)expression in the TME was raised in Patient 1,who responded well to treatment,and unaltered in two patients with progressive disease.CyTOF analysis revealed elevated circulating classical monocytes,highest in the patient with a good response.Conclusions:This study underscores the challenges of integrating advanced immune monitoring during RT delivery and did not meet its primary endpoint.The hypothesis-generating findings highlight PD-L1+macrophages in the TME and classical monocytes in the blood as potential immune biomarkers of RT response,but larger studies are needed to validate these observations and characterize the immune changes following curative-intent RT in patients with NSCLC.展开更多
Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings ...Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.展开更多
In this paper, we studied the process of dissociation unimolecular of the evaporation of H+2n+1 hydrogen clusters according to size, using the Rice-Ramsperger-Kassel-Marcus (RRKM) theory. The rate constants k(E) were ...In this paper, we studied the process of dissociation unimolecular of the evaporation of H+2n+1 hydrogen clusters according to size, using the Rice-Ramsperger-Kassel-Marcus (RRKM) theory. The rate constants k(E) were determined with the use of statistical theory of unimolecular reactions using various approximations. In our work, we used the products frequencies instead of transitions frequencies in the calculation of unimolecular dissociation rates obtained by three models RRKM. The agreement between the experimental cross section ratio and calculated rate ratio with direct count approximation seems to be reasonable.展开更多
This article is the 19th contribution to the fungal diversity notes series,in which 106 taxa distributed in 3 phyla,11 classes,35 orders,and 64 families are treated.Taxa described in the present study include a new fa...This article is the 19th contribution to the fungal diversity notes series,in which 106 taxa distributed in 3 phyla,11 classes,35 orders,and 64 families are treated.Taxa described in the present study include a new family,5 new genera,69 new species,3 new combinations,25 new host,habitat,and geographical records,a new name,a new collection,as well as reinstating a previously suppressed genus.The newly established family is Parasporidesmiaceae and the five new genera described herein are Dematiodidymosporum,Neoacrogenospora,Parasporidesmium,Speluncomyces,and Uniomyces.The 69 new species are Acrocalymma triseptatum,Agaricus darjeelingensis,Annellophorella aquatica,Anteaglonium menghaiense,Balsamia microspora,Bambusicola dehongensis,Barriopsis menglaense,Benjaminiomyces bergonzoi,Camporesiomyces aquaticus,Camporesiomyces wurfbainiae,Cercospora palmata,Chrysomphalina cantharella,Colletotrichum heteropanacicola,Conioscypha guizhouensis,Conioscypha yadongensis,Cora dalfornoae,Cylindromonium brasiliense,Dematiodidymosporum aquaticum,Distoseptispora dinghuensis,Distoseptispora zunyiensis,Ebollia neocarnea,Eudimeromyces aequatorialis,Eudimeromyces euconni,Funalia indica,Fuscosporella ovalis,Fuscosporella yunnanensis,Halobasidium csapodyae,Halokirschsteiniothelia hunanensis,Hongkongmyces xishuangbannaensis,Inocybe ispartaensis,Laboulbenia neofrancoisiana,Lachnella kunmingensis,Lasmenia thailandica,Leptospora cannabini,Lycoperdon sridharii,Myxospora neomasonii,Natipusilla aquatica,Neoacrogenospora aquatica,Neomassaria sinensis,Neovaginatispora juglandis,Niesslia yunnanensis,Ophiocordyceps aseptatospora,Oxneriaria sheosarensis,Paramicrosphaeropsis vitis,Paramyrothecium strychni,Parapaucispora aquatica,Parasporidesmium aquaticum,Parmelia neosaxatilis,Periconia bambusicola,Periconia neohongheensis,Peroneutypa thailandica,Polyozellus albus,Porina magnoliae,Porostereum subspadiceum,Pseudosperma subvolvatum,Pseudothyridariella caseariae,Rhexocercosporidium ferulae,Russula rubroglutinata,Septoriella iranica,Seriascoma asexuale,Sesquicillium flavum,Sirastachys zhongkaiensis,Speluncomyces lunatus,Sporidesmiella yunnanensis,Striaticonidium xishuangbannaensis,Trametopsis indica,Tulostoma hyderabadensis,Uniomyces hakkeijimanus,and Virgaria guizhouensis.The three new combinations are Lycoperdon alpinum,Lycoperdon lloydii,and Lycoperdon macrogemmae.The 25 new records comprise Acremonium sclerotigenum,Agroathelia rolfsii,Alfaria terrestris,Aspergillus cejpii,Colletotrichum brevisporum,Coriolopsis brunneoleuca,Coriolopsis hainanensis,Cytospora tamaricicola,Fomitopsis malicola,Fulvifomes fastuosus,Fulvifomes thailandicus,Funalia cystidiata,Funalia subgallica,Longididymella vitalbae,Lopharia mirabilis,Metarhizium viridulum,Neopestalotiopsis haikouensis,Occultibambusa aquatica,Phaeoacremonium scolyti,Phaeocytostroma virdimurae,Puccinia mysuruensis,Rhizopus stolonifer,Serpula similis,Trametes ellipsospora,and Vamsapriya shiwandashanensis.In addition,the new name is Irpiciporus pseudoxuchilensis,and the new collection is Aspergillus sydowii.The previously suppressed genus Eudimeromyces has been taxonomically reinstated.展开更多
Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To addre...Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.展开更多
Spirometry is one of the functional tests most used in respiratory medicine to assess lung function in health and disease conditions.Its success is grounded on solid principles of lung mechanics that state that maxima...Spirometry is one of the functional tests most used in respiratory medicine to assess lung function in health and disease conditions.Its success is grounded on solid principles of lung mechanics that state that maximal flow on expiration is limited by the physical properties of airways and lung parenchyma.In contrast,on inspiration,flow depends on the force generated by the inspiratory muscles.Reduced expiratory forced flow and volumes usually reflect a deviation from health conditions.Yet due to a complex interplay of different obstructive and restrictive lung diseases within the multiple structural dimensions of the respiratory system,flows and volumes do not always perfectly reflect the impact of the disease on lung function.The present review is intended to shed light on a series of artefacts and biological phenomena that may confound the clinical interpretation of the main spirometric measurements.Among them is thoracic gas compression volume,the volume and time history of the inspiratory manoeuvre that precedes the forced expiration,the effects of heterogeneous distribution of the disease across the respiratory system,and the changes in lung elastic recoil.展开更多
Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategie...Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.展开更多
The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of d...The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.展开更多
AIM:To test the hypothesis that,in the Southeastern Brazilian population,the GSTT1,GSTM1 and CYP2E1 polymorphisms and putative risk factors are associated with an increased risk for gastric cancer. METHODS:We conducte...AIM:To test the hypothesis that,in the Southeastern Brazilian population,the GSTT1,GSTM1 and CYP2E1 polymorphisms and putative risk factors are associated with an increased risk for gastric cancer. METHODS:We conducted a study on 100 cases of gastric cancer (GC),100 cases of chronic gastritis (CG),and 150 controls (C).Deletion of the GSTT1 and GSTM1 genes was assessed by multiplex PCR.CYP2E1/Pst1 genotyping was performed using a PCR-RFLP assay. RESULTS:No relationship between GSTT1/GSTM1 deletion and the c1/c2 genotype of CYP2E1 was observed among the three groups.However,a significant difference between CG and C was observed,due to a greater number of GSTT1/GSTM1 positive genotypes in the CG group.The GSTT1 null genotype occurred more frequently in Negroid subjects,and the GSTM1 null genotype in Caucasians,while the GSTM1 positive genotype was observed mainly in individuals with chronic gastritis infected with H pylori. CONCLUSION:Our findings indicate that there is no obvious relationship between the GSTT1,GSTM1 and CYP2E1 polymorphisms and gastric cancer.展开更多
基金the Begum Rokeya University,Rangpur,and the United Arab Emirates University,UAE for partially supporting this work。
文摘Rice is one of the most important staple crops globally.Rice plant diseases can severely reduce crop yields and,in extreme cases,lead to total production loss.Early diagnosis enables timely intervention,mitigates disease severity,supports effective treatment strategies,and reduces reliance on excessive pesticide use.Traditional machine learning approaches have been applied for automated rice disease diagnosis;however,these methods depend heavily on manual image preprocessing and handcrafted feature extraction,which are labor-intensive and time-consuming and often require domain expertise.Recently,end-to-end deep learning(DL) models have been introduced for this task,but they often lack robustness and generalizability across diverse datasets.To address these limitations,we propose a novel end-toend training framework for convolutional neural network(CNN) and attention-based model ensembles(E2ETCA).This framework integrates features from two state-of-the-art(SOTA) CNN models,Inception V3 and DenseNet-201,and an attention-based vision transformer(ViT) model.The fused features are passed through an additional fully connected layer with softmax activation for final classification.The entire process is trained end-to-end,enhancing its suitability for realworld deployment.Furthermore,we extract and analyze the learned features using a support vector machine(SVM),a traditional machine learning classifier,to provide comparative insights.We evaluate the proposed E2ETCA framework on three publicly available datasets,the Mendeley Rice Leaf Disease Image Samples dataset,the Kaggle Rice Diseases Image dataset,the Bangladesh Rice Research Institute dataset,and a combined version of all three.Using standard evaluation metrics(accuracy,precision,recall,and F1-score),our framework demonstrates superior performance compared to existing SOTA methods in rice disease diagnosis,with potential applicability to other agricultural disease detection tasks.
基金supported by the NIA/NIH(1K01AG060040).Studies performed by JN were funded by the NICHD/NIH(5R00HD096117)Microscopy Core Facility supported,in part,with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.
文摘Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.
基金funding from Grant No. HIDSS-0002 DASHH (Data Science in Hamburg-Helmholtz Graduate School for the Structure of Matter)partially supported by the Helmholtz Imaging platform through the project “Smart Phase.”
文摘Understanding the complex plasma dynamics in ultra-intense relativistic laser-solid interactions is of fundamental importance for applications of laser-plasma-based particle accelerators,the creation of high-energy-density matter,understanding planetary science,and laser-driven fusion energy.However,experimental efforts in this regime have been limited by the lack of accessibility of over-critical densities and the poor spatiotemporal resolution of conventional diagnostics.Over the last decade,the advent of femtosecond brilliant hard X-ray free-electron lasers(XFELs)has opened new horizons to overcome these limitations.Here,for the first time,we present full-scale spatiotemporal measurements of solid-density plasma dynamics,including preplasma generation with tens of nanometer scale length driven by the leading edge of a relativistic laser pulse,ultrafast heating and ionization at the main pulse arrival,the laser-driven blast wave,and transient surface return current-induced compression dynamics up to hundreds of picoseconds after interaction.These observations are enabled by utilizing a novel combination of advanced X-ray diagnostics including small-angle X-ray scattering,resonant X-ray emission spectroscopy,and propagation-based X-ray phase-contrast imaging simultaneously at the European XFEL-HED beamline station.
基金supported by project Emerging Infectious Diseases One Health Basic and Translational Research Actions addressing Unmet Needs on Emerging Infectious Diseases,INF-ACT,Spoke 1 and Spoke 5,Project number PE00000007,CUP B53C20040570005(to PP and DN).
文摘Introduction:One of the main events that regulate a cell’s well-being is cell-to-cell communication.This intercellular mechanism of information transfer is often mediated by vesicular trafficking.Mitochondrial-derived vesicles(MDVs)are an emerging subpopulation of extracellular vesicle(EV)first discovered in 2008 that allow mitochondria to communicate with their surroundings.
基金supported by the Portuguese Foundation for Science and Technology(FCT),Centro 2020 and Portugol2020 and the EU FEDER program,via the project GoBack to SIV(PTDC/CVT-CVT/32261/2017,CENTRO-01-0145-FEDER-032261)the doctoral grants of PDC(SFRH/BD/139974/2018)and BMS(2020.06525.BD and DOI 10.54499/2020.06525.BD)+5 种基金the post-doctoral grant to JPF(SFRH/BPD/113359/2015-program-contract described in paragraphs 4,5,6 of art.23 of Law no.100157/2016,of August 29,as amended by Law no.57/2017 of July 2019),the project PTDC/MED-NEU/1677/2021 to JBRthe Institute of Biomedicine iBiMED(UIDB/04501/2020 and DOI 10.54499/UIDB/04501/2020,UIDP/04501/2020 and DOI 10.54499/UIDP/04501/2020)its LiM Bioimaging Facility-a PPBI node(POCI-01-0145-FEDER-022122)supported by the Research Commission of the Medical Faculty of the Heinrich-Heine-University(HHU)Düsseldorf,of the Biologisch-Medizinisches Forschungszentrum(BMFZ)of HHUfinanced by the Spanish"Plan Nacional de Investigacion Cientifica,Desarrollo e Innovacion Tecnologica,Ministerio de Economia y Competitividad(Instituto de Salud CarlosⅢ)",co-financed by the European Union(FEDER program),(grant FIS P/20/00318 and FIS P23/00337 to VC)grant CPP2021-009070 to VC by the"Proyectos de colaboracion publico-privada,Plan de Investigacion Cientifica,Tecnica y de inovacion 2021-2023,Ministerio de Ciencia e Innovacion,Union Europea,Agencia Estatal de Investigacion,Espana"。
文摘Contrary to the adult central nervous system,the peripheral nervous system has an intrinsic ability to regenerate that relies on the expression of regenerationassociated genes,such as some kinesin family members.Kinesins contribute to nerve regeneration through the transport of specific cargo,such as proteins and membrane components,from the cell body towards the axon periphery.We show here that KIF4A,associated with neurodevelopmental disorders and previously believed to be only expressed during development,is also expressed in the adult vertebrate nervous system and up-regulated in injured peripheral nervous system cells.KIF4A is detected both in the cell bodies and regrowing axons of injured neurons,consistent with its function as an axonal transporter of cargoes such asβ1-integrin and L1CAM.Our study further demonstrates that KIF4A levels are greatly increased in Schwann cells from injured distal nerve stumps,particularly at a time when they are reprogrammed into an essential proliferative repair phenotype.Moreover,Kif4a m RNA levels were approximately~6-fold higher in proliferative cultured Schwann cells compared with non-proliferative ones.A hypothesized function for Kif4a in Schwann cell proliferation was further confirmed by Kif4a knockdown,as this significantly reduced Schwann cell proliferation in vitro.Our findings show that KIF4A is expressed in adult vertebrate nervous systems and is up-regulated following peripheral injury.The timing of KIF4A up-regulation,its location during regeneration,and its proliferative role,all suggest a dual role for this protein in neuroregeneration that is worth exploring in the future.
文摘The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.
基金supported by the Ministry of Science and Technology of the People’s Republic of China(2022YFD1800400).
文摘Staphylococcus aureus(S.aureus)is the third most common pathogen causing 10.6%of bacterial foodborne illnesses in China in 2021[1].Heat-stable Staphylococcal Enterotoxins(SEs)produced by S.aureus are the main contributors to staphylococcal food poisoning(SFP),causing vomiting,diarrhea,abdominal pain,headache,muscle cramps,and other acute gastroenteritis symptoms.More than 25 SEs and staphylococcal enterotoxin-like toxins(SE/s)have been described and which together comprise a superfamily of pyrogenic toxin superantigens(SAgs)[2].
基金supported by the National Science Foundation of China,Nos.82325031(to FX),82030059(to YC),82102290(to YG),U23A20485(to YC)Noncommunicable Chronic Diseases-National Science and Technology Major Project,No.2023ZD0505504(to FX),2023ZD0505500(to YC)the Key R&D Program of Shandong Province,No.2022ZLGX03(to YC).
文摘Global brain ischemia and neurological deficit are consequences of cardiac arrest that lead to high mortality.Despite advancements in resuscitation science,our limited understanding of the cellular and molecular mechanisms underlying post-cardiac arrest brain injury have hindered the development of effective neuroprotective strategies.Previous studies primarily focused on neuronal death,potentially overlooking the contributions of non-neuronal cells and intercellular communication to the pathophysiology of cardiac arrest-induced brain injury.To address these gaps,we hypothesized that single-cell transcriptomic analysis could uncover previously unidentified cellular subpopulations,altered cell communication networks,and novel molecular mechanisms involved in post-cardiac arrest brain injury.In this study,we performed a single-cell transcriptomic analysis of the hippocampus from pigs with ventricular fibrillation-induced cardiac arrest at 6 and 24 hours following the return of spontaneous circulation,and from sham control pigs.Sequencing results revealed changes in the proportions of different cell types,suggesting post-arrest disruption in the blood-brain barrier and infiltration of neutrophils.These results were validated through western blotting,quantitative reverse transcription-polymerase chain reaction,and immunofluorescence staining.We also identified and validated a unique subcluster of activated microglia with high expression of S100A8,which increased over time following cardiac arrest.This subcluster simultaneously exhibited significant M1/M2 polarization and expressed key functional genes related to chemokines and interleukins.Additionally,we revealed the post-cardiac arrest dysfunction of oligodendrocytes and the differentiation of oligodendrocyte precursor cells into oligodendrocytes.Cell communication analysis identified enhanced post-cardiac arrest communication between neutrophils and microglia that was mediated by neutrophil-derived resistin,driving pro-inflammatory microglial polarization.Our findings provide a comprehensive single-cell map of the post-cardiac arrest hippocampus,offering potential novel targets for neuroprotection and repair following cardiac arrest.
基金a Ph D fellowship by FCT-Fundacao para a Ciência Tecnologia (SFRH/BD/135868/2018)(to SSC)。
文摘Axonal growth inhibitors are released during traumatic injuries to the adult mammalian central nervous system, including after spinal cord injury. These molecules accumulate at the injury site and form a highly inhibitory environment for axonal regeneration. Among these inhibitory molecules, myelinassociated inhibitors, including neurite outgrowth inhibitor A, oligodendrocyte myelin glycoprotein, myelin-associated glycoprotein, chondroitin sulfate proteoglycans and repulsive guidance molecule A are of particular importance. Due to their inhibitory nature, they represent exciting molecular targets to study axonal inhibition and regeneration after central injuries. These molecules are mainly produced by neurons, oligodendrocytes, and astrocytes within the scar and in its immediate vicinity. They exert their effects by binding to specific receptors, localized in the membranes of neurons. Receptors for these inhibitory cues include Nogo receptor 1, leucine-rich repeat, and Ig domain containing 1 and p75 neurotrophin receptor/tumor necrosis factor receptor superfamily member 19(that form a receptor complex that binds all myelin-associated inhibitors), and also paired immunoglobulin-like receptor B. Chondroitin sulfate proteoglycans and repulsive guidance molecule A bind to Nogo receptor 1, Nogo receptor 3, receptor protein tyrosine phosphatase σ and leucocyte common antigen related phosphatase, and neogenin, respectively. Once activated, these receptors initiate downstream signaling pathways, the most common amongst them being the Rho A/ROCK signaling pathway. These signaling cascades result in actin depolymerization, neurite outgrowth inhibition, and failure to regenerate after spinal cord injury. Currently, there are no approved pharmacological treatments to overcome spinal cord injuries other than physical rehabilitation and management of the array of symptoms brought on by spinal cord injuries. However, several novel therapies aiming to modulate these inhibitory proteins and/or their receptors are under investigation in ongoing clinical trials. Investigation has also been demonstrating that combinatorial therapies of growth inhibitors with other therapies, such as growth factors or stem-cell therapies, produce stronger results and their potential application in the clinics opens new venues in spinal cord injury treatment.
文摘Hepatocellular carcinoma(HCC) is an aggressive malignancy,resulting as the third cause of death by cancer each year. The management of patients with HCC is complex,as both the tumour stage and any underlying liver disease must be considered conjointly. Although surveillance by imaging,clinical and biochemical parameters is routinely performed,a lot of patients suffering from cirrhosis have an advanced stage HCC at the first diagnosis. Advanced stage HCC includes heterogeneous groups of patients with different clinical condition and radiological features and sorafenib is the only approved treatment according to Barcelona Clinic Liver Cancer. Since the introduction of sorafenib in clinical practice,several phase Ⅲ clinical trials have failed to demonstrate any superiority over sorafenib in the frontline setting. Locoregional therapies have also been tested as first line treatment,but their role in advanced HCC is still matter of debate. No single agent or combination therapies have been shown to impact outcomes after sorafenib failure. Therefore this review will focus on the range of experimental therapeutics for patients with advanced HCC and highlights the successes and failures of these treatments as well as areas for future development. Specifics such as dose limiting toxicity and safety profile in patients with liver dysfunction related to the underlying chronic liver disease should be considered when developing therapies in HCC. Finally,robust validated and reproducible surrogate end-points as well as predictive biomarkers should be defined in future randomized trials.
基金Supported by Protocollo TESORM by Regione Toscana,Universitàdegli Studi di Firenze and Bayer Health Care s.p.a
文摘Advanced stage hepatocellular carcinoma(HCC) is a category of disease defined by radiological, clinical and hepatic function parameters, comprehending a wide range of patients with different general conditions. The main therapeutic option is represented by sorafenibtreatment, a multi-kinase inhibitor with anti-proliferative and anti-angiogenic effect. Trans-arterial Radio Embolization also represents a promising new approach to intermediate/advanced HCC. Post-marketing clinical studies showed that only a portion of patients actually benefits from sorafenib treatment, and an even smaller percentage of patients treated shows partial/complete response on follow-up examinations, up against relevant costs and an incidence of drug related adverse effects. Although the treatment with sorafenib has shown a significant increase in mean overall survival in different studies, only a part of patients actually shows real benefits, while the incidence of drug related significant adverse effects and the economic costs are relatively high. Moreover, only a small percentage of patients also shows a response in terms of lesion dimensions reduction. Being able to properly differentiate patients who are responding to the therapy from non-responders as early as possible is then still difficult and could be a pivotal challenge for the future; in fact it could spare several patients a therapy often difficult to bear, directing them to other second line treatments(many of which are at the moment still under investigation). For this reason, some supplemental criteria to be added to the standard modified Response Evaluation Criteria in Solid Tumors evaluation are being searched for. In particular, finding some parameters(cellular density, perfusion grade and enhancement rate) able to predict the sensitivity of the lesions to anti-angiogenic agents could help in stratifying patients in terms of treatment responsiveness before the beginning of the therapy itself, or in the first weeks of sorafenib treatment. This would bring a strongly desirable help in clinical managements of these patients.
基金the National Institute for Health and Care Research(NHR)Manchester Biomedical Research Centre(BRC)(NIHR203308,NIHR-BRC-1215-20007)Astra-Zeneca(ESR-14-10711)+2 种基金CRUK RadNet(C19941/A27801)TMI and CFF are the recipient of an NIHR Senior Investigator Award(NIHR205054 and NIHR205061)CTH is supported by the NIHR University College London Hospitals NHS Foundation Trust BRC,the City of London CRUK RadNet and the CRUK Lung Cancer Centre of Excellence.
文摘Objectives:The PACIFIC trial established the benefit of durvalumab following chemo-radiotherapy for stage III non-small cell lung cancer(NSCLC).However,the concurrent use of radiotherapy(RT)and durvalumab(PACIFIC-2 trial)showed no additional advantage.The PD-RAD study was set up to understand the immunological effects of RT on the tumor microenvironment(TME)to aid in optimizing sequencing of combination therapies.Methods:The PD-RAD trial(ClinicalTrials.gov identifier:NCT03258788)aimed to enroll thirty NSCLC patients receiving radical-intent RT.Tumor biopsies and blood samples were collected pre-RT and at week 2 during RT and analyzed using multiplex immunohistochemistry(mIHC)and high-dimensional mass cytometry(CyTOF),respectively.Results:Paired biopsies were collected from only three patients(Pts 1,3&4)and blood from four patients(Pts 1-4)before the study was closed early during the COVID-19 pandemic.Programmed Death-Ligand 1(PD-L1)expression in the TME was raised in Patient 1,who responded well to treatment,and unaltered in two patients with progressive disease.CyTOF analysis revealed elevated circulating classical monocytes,highest in the patient with a good response.Conclusions:This study underscores the challenges of integrating advanced immune monitoring during RT delivery and did not meet its primary endpoint.The hypothesis-generating findings highlight PD-L1+macrophages in the TME and classical monocytes in the blood as potential immune biomarkers of RT response,but larger studies are needed to validate these observations and characterize the immune changes following curative-intent RT in patients with NSCLC.
文摘Numerous sectors,such as education,the IT sector,and corporate organizations,transitioned to virtual meetings after the COVID-19 crisis.Organizations now seek to assess participants’fatigue levels in online meetings to remain competitive.Instructors cannot effectively monitor every individual in a virtual environment,which raises significant concerns about participant fatigue.Our proposed system monitors fatigue,identifying attentive and drowsy individuals throughout the online session.We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only,offering a more detailed analysis for predicting eye opening and closing of the eyes,rather than focusing on the entire face.We introduce an Eye Polygon Area(EPA)formula,which computes eye activity from Dlib eye landmarks by measuring the polygonal area of the eye opening.Unlike the Eye Aspect Ratio(EAR),which relies on a single distance ratio,EPA adapts to different eye shapes(round,narrow,or wide),providing a more reliable measure for fatigue detection.The VMFD system issues a warning if a participant remains in a fatigued condition for 36 consecutive frames.The proposed technology is tested under multiple scenarios,including low-to high-lighting conditions(50-1400 lux)and both with and without glasses.This study builds an OpenCV application in Python,evaluated using the iBUG 300-W dataset,achieving 97.5%accuracy in detecting active participants.We compare VMFD with conventional methods relying on the EAR and show that the EPA technique performs significantly better.
文摘In this paper, we studied the process of dissociation unimolecular of the evaporation of H+2n+1 hydrogen clusters according to size, using the Rice-Ramsperger-Kassel-Marcus (RRKM) theory. The rate constants k(E) were determined with the use of statistical theory of unimolecular reactions using various approximations. In our work, we used the products frequencies instead of transitions frequencies in the calculation of unimolecular dissociation rates obtained by three models RRKM. The agreement between the experimental cross section ratio and calculated rate ratio with direct count approximation seems to be reasonable.
基金the National Natural Science Foundation of China(Grant No.32200015)the Foundation of Guangzhou Municipal Science and Technology Bureau(Grant No.2023A04J1425)+46 种基金the Foundation of Guangzhou Municipal Science and Technology Bureau(Grant No.2023A04J1426)the National Research Council of Thailand(NRCT)Grant“Total fungal diversity in a given forest area with implications towards species numbers,chemical diversity and biotechnology”(Grant No.N42A650547)the Mushroom Research Foundation,Thailand for funding this workthe Distinguished Scientist Fellowship Program(DSFP),King Saud University,Kingdom of Saudi Arabia.Huang Zhang thanks the National Natural Science Foundation of Shandong(Project ID ZR2022MC071 to Huang Zhang)Taishan Scholar Foundation of Shandong Province(tsqn202306276)supported by the Sichuan Science and Technology Program of China(No.2022NSFSC1011)the Scientific and Technical Research Council of Türkiye(TUBİTAK)for the 2219 International Postdoctoral Research Fellowship Programme(Grant No.1059B192202880)the National Science,Research and Innovation Fund:Thailand Science Research Innovation(Basic Research Fund 2021,2022 and 2023)“Biodiversity,taxonomy,phylogeny and evolution of Colletotrichum on avocado,citrus,durian and mango in northern Thailand”,Grant No.652A01003“Biodiversity,taxonomy and phylogeny of Colletotrichum on Citrus and Mango in Northern Thailand”,Grant No.662A01002 and 672A010002the National Natural Science Foundation of China(No.32060012)SERB(CRG/2020/006053),DST,New DelhiInstitution of Eminence(R/Dev./D/IoE/Incentive/2021-22/32387)BHU,Varanasi and Bridge Grant(No.SRICC/Bridge Grant/2024-25/3151),BHU,Varanasi for providing the financial supportsfinancially supported by the“Iranian Mycological Society”the National Natural Science Foundation of China(32260004)the Yunnan Revitalization Talents Support Plan(High-End Foreign Experts Program)Yunnan Provincial Department of Science and Technology“Zhihui Yunnan”Plan(202403AM140023)the Key Laboratory of Yunnan Provincial Department of Education of the Deep-Time Evolution on Biodiversity from the Origin of the Pearl River for their supportthe International Research Support Initiative Program(IRSIP)Schemegrateful to JSPS for an Award of a Postdoctoral Fellowship and the Research Grants No.185701000001 and No.18-06620Extramural Research-SERB,DST(EMR/2016/003078),Government of India for the financial assistancegrateful to‘The PCCF’of Tamil Nadu Forest Department for providing permission(E2/20458/2017),assistance and support during field visit in Eastern Ghats of Tamil NaduRUSA 2.0(Theme-1,Group-1/2021/49)for providing GrantTamil Nadu State Council for Higher Education,Chennai(RGP/2019-20/MU/HECP-0040)for financial assistanceCSIR,New Delhi,India(09/0115(13300)/2022-EMR-I)for the financial assistancethe Beijing Natural Science Foundation-International Scientist Project(Project Number 1S24085)for the financial supportgrateful to DST-PURSE Programme PhaseⅡ,University of Calcutta,India for financial supportChiang Mai University for providing financial support and laboratory facilitiesgrateful to the UP System Balik PhD Program(OVPAA-BPhD2022-02)Grant entitled“Unraveling the hidden diversity of aquatic fungi from Panay Island,Philippines”Govt.of India for financial assistance(BT/PR29521/FCB/125/15/2018)financial support provided by DGAPA-PAPIIT,UNAM(Grant Number IN203524)the Department of Science and Technology,Govt.of India for the Award of the JC Bose Fellowship(Grant No.JCB/2017/000053),DBT-BUILDER(BT/INF/22/SP41176/2020)grant to School of life Sciences,Ministry of EducationGovt.of India and Institution of Excellence Directorate,University of Hyderabad for the award of the Project(Grant No.UOH-IOE-RC3-21-065)and Fellowship(RA)to PVSRN Sarmathe IOE-PDRF(UOH/IOE/SEST/PDRF/1)Grant from University of Hyderabadthe Yunnan Provincial Department of Science and Technology“Zhihui Yunnan”Plan(202403AM140023)the High-Level Talent Recruitment Plan of Yunnan Provinces(High-End Foreign Experts Programs and“Young Talents”)the National Natural Science Foundation of China(No.32460002)the Meemann Chang Academician Workstation in Yunnan Province(202225AF150002)Yunnan Province Young and Middle-aged Academic and Technical Leaders Reserve Talents Program(202305AC350252)Fundacao Arthur Bernardes(FUNARBE)for financial support.the CMU Proactive Researcher,Chiang Mai University(Grant Numbers 796/2567 and EX010059)the Doi Tung Development Project for Sample Collection(Permission Number 7700/17142 with the title‘The diversity of saprobic fungi on selected hosts in forest northern Thailand’),Chiang Rai,ThailandChiang Mai University for partially supportthe support from the Agency of Innovative Development under the Ministry of Higher Education,Science and Innovation of the Republic of Uzbekistan(Project No.AL-8724052922)the National Key R&D Program of China(Project No.2025YFE0104500)The Slovak Grant Agency VEGA(grant No.1/0295/20)for financial supportfinancial support from the Institute of Botany,Jagiellonian University,scientific funds(N18/DBS/000002)financial support by the statutory funds of the W.Szafer Institute of Botany,Polish Academy of Sciences.
文摘This article is the 19th contribution to the fungal diversity notes series,in which 106 taxa distributed in 3 phyla,11 classes,35 orders,and 64 families are treated.Taxa described in the present study include a new family,5 new genera,69 new species,3 new combinations,25 new host,habitat,and geographical records,a new name,a new collection,as well as reinstating a previously suppressed genus.The newly established family is Parasporidesmiaceae and the five new genera described herein are Dematiodidymosporum,Neoacrogenospora,Parasporidesmium,Speluncomyces,and Uniomyces.The 69 new species are Acrocalymma triseptatum,Agaricus darjeelingensis,Annellophorella aquatica,Anteaglonium menghaiense,Balsamia microspora,Bambusicola dehongensis,Barriopsis menglaense,Benjaminiomyces bergonzoi,Camporesiomyces aquaticus,Camporesiomyces wurfbainiae,Cercospora palmata,Chrysomphalina cantharella,Colletotrichum heteropanacicola,Conioscypha guizhouensis,Conioscypha yadongensis,Cora dalfornoae,Cylindromonium brasiliense,Dematiodidymosporum aquaticum,Distoseptispora dinghuensis,Distoseptispora zunyiensis,Ebollia neocarnea,Eudimeromyces aequatorialis,Eudimeromyces euconni,Funalia indica,Fuscosporella ovalis,Fuscosporella yunnanensis,Halobasidium csapodyae,Halokirschsteiniothelia hunanensis,Hongkongmyces xishuangbannaensis,Inocybe ispartaensis,Laboulbenia neofrancoisiana,Lachnella kunmingensis,Lasmenia thailandica,Leptospora cannabini,Lycoperdon sridharii,Myxospora neomasonii,Natipusilla aquatica,Neoacrogenospora aquatica,Neomassaria sinensis,Neovaginatispora juglandis,Niesslia yunnanensis,Ophiocordyceps aseptatospora,Oxneriaria sheosarensis,Paramicrosphaeropsis vitis,Paramyrothecium strychni,Parapaucispora aquatica,Parasporidesmium aquaticum,Parmelia neosaxatilis,Periconia bambusicola,Periconia neohongheensis,Peroneutypa thailandica,Polyozellus albus,Porina magnoliae,Porostereum subspadiceum,Pseudosperma subvolvatum,Pseudothyridariella caseariae,Rhexocercosporidium ferulae,Russula rubroglutinata,Septoriella iranica,Seriascoma asexuale,Sesquicillium flavum,Sirastachys zhongkaiensis,Speluncomyces lunatus,Sporidesmiella yunnanensis,Striaticonidium xishuangbannaensis,Trametopsis indica,Tulostoma hyderabadensis,Uniomyces hakkeijimanus,and Virgaria guizhouensis.The three new combinations are Lycoperdon alpinum,Lycoperdon lloydii,and Lycoperdon macrogemmae.The 25 new records comprise Acremonium sclerotigenum,Agroathelia rolfsii,Alfaria terrestris,Aspergillus cejpii,Colletotrichum brevisporum,Coriolopsis brunneoleuca,Coriolopsis hainanensis,Cytospora tamaricicola,Fomitopsis malicola,Fulvifomes fastuosus,Fulvifomes thailandicus,Funalia cystidiata,Funalia subgallica,Longididymella vitalbae,Lopharia mirabilis,Metarhizium viridulum,Neopestalotiopsis haikouensis,Occultibambusa aquatica,Phaeoacremonium scolyti,Phaeocytostroma virdimurae,Puccinia mysuruensis,Rhizopus stolonifer,Serpula similis,Trametes ellipsospora,and Vamsapriya shiwandashanensis.In addition,the new name is Irpiciporus pseudoxuchilensis,and the new collection is Aspergillus sydowii.The previously suppressed genus Eudimeromyces has been taxonomically reinstated.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.
文摘Spirometry is one of the functional tests most used in respiratory medicine to assess lung function in health and disease conditions.Its success is grounded on solid principles of lung mechanics that state that maximal flow on expiration is limited by the physical properties of airways and lung parenchyma.In contrast,on inspiration,flow depends on the force generated by the inspiratory muscles.Reduced expiratory forced flow and volumes usually reflect a deviation from health conditions.Yet due to a complex interplay of different obstructive and restrictive lung diseases within the multiple structural dimensions of the respiratory system,flows and volumes do not always perfectly reflect the impact of the disease on lung function.The present review is intended to shed light on a series of artefacts and biological phenomena that may confound the clinical interpretation of the main spirometric measurements.Among them is thoracic gas compression volume,the volume and time history of the inspiratory manoeuvre that precedes the forced expiration,the effects of heterogeneous distribution of the disease across the respiratory system,and the changes in lung elastic recoil.
基金funding from the China National Key Research and Development Program(No.2023YFC3603104)the National Natural Science Foundation of China(Nos.82472243 and 82272180)+6 种基金the Fundamental Research Funds for the Central Universities(No.226-2025-00024)the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(No.LHDMD24H150001)the Key Research&Development Project of Zhejiang Province(No.2024C03240)a collaborative scientific project co-established by the Science and Technology Department of the National Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine(No.GZY-ZJ-KJ-24082)he General Health Science and Technology Program of Zhejiang Province(No.2024KY1099)the Project of Zhejiang University Longquan Innovation Center(No.ZJDXLQCXZCJBGS2024016)Wu Jieping Medical Foundation Special Research Grant(No.320.6750.2024-23-07).
文摘Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through project number RI-44-0833.
文摘The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.
文摘AIM:To test the hypothesis that,in the Southeastern Brazilian population,the GSTT1,GSTM1 and CYP2E1 polymorphisms and putative risk factors are associated with an increased risk for gastric cancer. METHODS:We conducted a study on 100 cases of gastric cancer (GC),100 cases of chronic gastritis (CG),and 150 controls (C).Deletion of the GSTT1 and GSTM1 genes was assessed by multiplex PCR.CYP2E1/Pst1 genotyping was performed using a PCR-RFLP assay. RESULTS:No relationship between GSTT1/GSTM1 deletion and the c1/c2 genotype of CYP2E1 was observed among the three groups.However,a significant difference between CG and C was observed,due to a greater number of GSTT1/GSTM1 positive genotypes in the CG group.The GSTT1 null genotype occurred more frequently in Negroid subjects,and the GSTM1 null genotype in Caucasians,while the GSTM1 positive genotype was observed mainly in individuals with chronic gastritis infected with H pylori. CONCLUSION:Our findings indicate that there is no obvious relationship between the GSTT1,GSTM1 and CYP2E1 polymorphisms and gastric cancer.
