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spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Bone Research 2024年第1期12卷 1-19页

作者： Xiwei Fan Antonia Rujia sun Reuben s.e.Young Isaac O.Afara Brett R.Hamilton Louis Jun Ye Ong Ross Crawford Indira Prasadam Centre for Biomedical Technologies Queensland University of TechnologyBrisbaneQLDAustralia school of Mechanical Medical&Process EngineeringQueensland University of TechnologyBrisbaneQLDAustralia Central Analytical Research Facility Queensland University of TechnologyBrisbaneQLDAustralia Molecular Horizons University of WollongongWollongongNSWAustralia Department of Technical Physics University of Eastern FinlandKuopioFinland school of electrical engineering and Computer science Faculty of EngineeringArchitecture and Information TechnologyUniversity of QueenslandBrisbaneQLDAustralia Centre for Microscopy and Microanalysis University of QueenslandBrisbaneQLDAustralia The Prince Charles Hospital BrisbaneQLDAustralia

Osteoarthritis(OA)is a debilitating degenerative disease affecting multiple joint tissues,including cartilage,bone,synovium,and adipose *** presents diverse clinical phenotypes and distinct molecular endotypes,including inflammatory,metabolic,mechanical,genetic,and synovial ***,innovative technologies are needed to support the development of effective diagnostic and precision therapeutic *** analysis of bulk OA tissue extracts has limitations due to technical constraints,causing challenges in the differentiation between various physiological and pathological phenotypes in joint *** issue has led to standardization difficulties and hindered the success of clinical *** insights into the spatial variations of the cellular and molecular structures in OA tissues,encompassing DNA,RNA,metabolites,and proteins,as well as their chemical properties,elemental composition,and mechanical attributes,can contribute to a more comprehensive understanding of the disease *** resolved biology enables biologists to investigate cells within the context of their tissue microenvironment,providing a more holistic view of cellular *** advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various-omics lenses,such as genomics,transcriptomics,proteomics,and metabolomics,with spatial *** fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial ***,advanced imaging techniques,including high-resolution microscopy,hyperspectral imaging,and mass spectrometry imaging,enable the visualization and analysis of the spatial distribution of biomolecules,cells,and *** these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease *** review summarizes the rec

关键词： insight spatial enable

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effect of biochar on the metabolome of soybean seedlings

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Oil Crop science 2024年第1期9卷 60-68页

作者： Nathalia e.silva Mariana G.Aguilar Osania e.Ferreira Gleicia M.Paulino Jaqueline C.L.Carvalho Lúcia P.s.Pimenta Alan R.T.Machado Programa de Pos-graduaçao em Ciencias Ambientais Universidade do Estado de Minas GeraisFrutalMinas Gerais38202-436Brazil Departamento de Química Universidade Federal de Minas GeraisMinas GeraisBelo Horizonte31270-901Brazil Departamento de engenharia Aplicada e Tecnologias Ambientais Universidade do Estado de Minas GeraisJoao MonlevadeMinas Gerais35930-314Brazil Departamento de Ciencias exatas Universidade do Estado de Minas GeraisJoao MonlevadeMinas Gerais35930-314Brazil

The use of biochar can have several effects on plant germination,depending on raw material,preparation method and application ***,the molecular mechanisms that lead to those results have yet to be *** aim of this research was to improve the understanding of these mechanisms by characterizing the metabolic effects of sugarcane bagasse biochar on soybean *** types of biochars were prepared by pyrolysis at 300℃(sCB300),400℃(sCB400)and 600℃(sCB600).Then,each one was mixed into sand at 1%,3%,5%(w/w)dose,*** experiment was performed in 8 days of incubation,when the number of germinated seeds and the average radicle length were *** evaluate the metabolome,the dry biomass(DB)was subjected to extraction with a mixture of methanol-d4 and D2O(1:1 v/v).The extracts were submitted to metabolomics analysis by Proton Nuclear Magnetic *** Relative Germination,Relative Average Radicle Growth and Germination Index increased in all treatments compared to *** the other hand,the DB increased in all treatments,except for sCB300,at doses of 1%and 3%w/*** metabolites(alanine,asparagine,acetic acid,citric acid,glycerol,fatty acids and sucrose)were identified and quantified in DB extracts as the most influential finding for the separation of *** together,these results strongly suggested that biochars accelerated the catabolism of triacylglycerols to sucrose and induced a slight osmotic stress.

关键词： Germination Metabolomics 1H NMR Pyrolysis sugarcane bagasse

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A rat model of multicompartmental traumatic injury and hemorrhagic shock induces bone marrow dysfunction and profound anemia

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Animal Models and experimental Medicine 2024年第3期7卷 367-376页

作者： Lauren s.Kelly Jennifer A.Munley erick e.Pons Kolenkode B.Kannan elizabeth M.Whitley Letitia e.Bible Philip A.efron Alicia M.Mohr Department of surgery and sepsis and Critical Illness Research Center University of Florida College of MedicineGainesvilleFloridaUSA Pathogenesis LLCGainesvilleFloridaUSA

Background:severe trauma is associated with systemic inflammation and organ *** rodent trauma models are the mainstay of postinjury research but have been criticized for not fully replicating severe human *** aim of this study was to create a rat model of multicompartmental injury which recreates profound traumatic ***:Male sprague-Dawley rats were subjected to unilateral lung contusion and hemorrhagic shock(LCHs),multicompartmental polytrauma(PT)(unilateral lung contusion,hemorrhagic shock,cecectomy,bifemoral pseudofracture),or na?ve ***,plasma toll-l ike receptor 4(TLR4),hemoglobin,spleen to body weight ratio,bone marrow(BM)erythroid progenitor(CFU-GeMM,BFU-e,and CFU-e)growth,plasma granulocyte colony-stimulating factor(G-CsF)and right lung histologic injury were assessed on day 7,with significance defined as p valuesesults:Polytrauma resulted in markedly more profound inhibition of weight gain compared to LCHs(p=0.0002)along with elevated plasma TLR4(per hemoglobin(penlarged spleen to body weight ratios(p=0.004).Both LCHs and PT demonstrated suppression of CFU-e and BFU-e growth compared to naive(psma G-CsF was elevated in PT compared to both na?ve and LCHs(ps and PT demonstrated significant histologic right lung injury with poor alveolar wall integrity and interstitial ***:Multicompartmental injury as described here establishes a reproducible model of multicompartmental injury with worsened anemia,splenic tissue enlargement,weight loss,and increased inflammatory activity compared to a less severe *** may serve as a more effective model to recreate profound traumatic injury to replicate the human inflammatory response postinjury.

关键词： anemia i nflammation polytrauma pseudofracture shock

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.e.Al-Atroush A.e.Aboelela ezz el-Din Hemdan Civil and environmental engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer science and engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LssVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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Ren-integrable and ren-symmetric integrable systems

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Communications in Theoretical Physics 2024年第3期76卷 62-69页

作者： s Y Lou school of Physical science and Technology Ningbo UniversityNingbo315211China

A new type of symmetry,ren-symmetry,describing anyon physics and corresponding topological physics,is ***-symmetry is a generalization of super-symmetry which is widely applied in super-symmetric physics such as super-symmetric quantum mechanics,super-symmetric gravity,super-symmetric string theory,super-symmetric integrable systems and so *** and Grassmann numbers are,in some sense,dual conceptions,and it turns out that these conceptions coincide for the ren situation,that is,a similar conception of ren-number(R-number)is devised for *** particular,some basic results of the R-number and ren-symmetry are exposed which allow one to derive,in principle,some new types of integrable systems including ren-integrable models and ren-symmetric integrable *** examples of ren-integrable KdV-type systems and ren-symmetric KdV equations are explicitly given.

关键词： symmetries integrable systems anyon physics extended supersymmetry ren-symmetry

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Converting TRex-RGB green-channel data to 557.7 nm auroral intensity:Methodology and initial results

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earth and Planetary Physics 2024年第1期8卷 258-274页

作者： Jun Liang D.M.Gillies e.spanswick e.F.Donovan University of Calgary CalgaryT2N 1N4Canada

The recently deployed Transition Region explorer(TRex)-RGB(red-green-blue)all-sky imager(AsI)is designed to capture“true color”images of the aurora and *** the 557.7 nm green line is usually the brightest emission line in visible auroras,the green channel of a TRex-RGB camera is usually dominated by the 557.7 nm *** this rationale,the TRex mission does not include a specific 557.7 nm imager and is designed to use the RGB green-channel data as a proxy for the 557.7 nm *** this study,we present an initial effort to establish the conversion ratio or formula linking the RGB green-channel data to the absolute intensity of 557.7 nm auroras,which is crucial for quantitative uses of the RGB *** illustrate two approaches:(1)through a comparison with the collocated measurement of green-line auroras from the TRex spectrograph,and(2)through a comparison with the modeled green-line intensity according to realistic electron precipitation flux measurements from low-earth-orbit satellites,with the aid of an auroral transport *** demonstrate the procedures and provide initial results for the TRex-RGB AsIs at the Rabbit Lake and Lucky Lake *** RGB response is found to be *** conversion ratios or formulas between RGB green-channel data and the green-line auroral intensity are given and can be applied immediately by TRex-RGB data *** methodology established in this study will also be applicable to the upcoming sMILe AsI mission,which will adopt a similar RGB camera system in its deployment.

关键词： TRex RGB green-line aurora auroral transport model

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A hybrid machine-learning model for solar irradiance forecasting

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Clean energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf Tarek H.M.el-Fouly Vasileios e.Katzourakis Mohamed s.el Moursi Constantinos V.Chrysikopoulos Department of Industrial and systems engineering Khalifa UniversityAbu DhabiPO Box 127788UAE electrical engineering and Computer science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and environmental engineering Khalifa UniversityAbu DhabiPO Box 127788UAE school of Chemical and environmental engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in seattle and Medford,UsA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

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AutoRhythmAI: A Hybrid Machine and Deep Learning Approach for Automated Diagnosis of Arrhythmias

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Computers, Materials & Continua 2024年第2期78卷 2137-2158页

作者： s.Jayanthi s.Prasanna Devi Department of Computer science and engineering SRM Institute of Science and Technology-Vadapalani CampusChennaiTamil NaduIndia

In healthcare,the persistent challenge of arrhythmias,a leading cause of global mortality,has sparked extensive research into the automation of detection using machine learning(ML)***,traditional ML and AutoML approaches have revealed their limitations,notably regarding feature generalization and automation *** glaring research gap has motivated the development of AutoRhythmAI,an innovative solution that integrates both machine and deep learning to revolutionize the diagnosis of *** approach encompasses two distinct pipelines tailored for binary-class and multi-class arrhythmia detection,effectively bridging the gap between data preprocessing and model *** validate our system,we have rigorously tested AutoRhythmAI using a multimodal dataset,surpassing the accuracy achieved using a single dataset and underscoring the robustness of our *** the first pipeline,we employ signal filtering and ML algorithms for preprocessing,followed by data balancing and split for *** second pipeline is dedicated to feature extraction and classification,utilizing deep learning ***,we introduce the‘RRI-convoluted trans-former model’as a novel addition for binary-class *** ensemble-based approach then amalgamates all models,considering their respective weights,resulting in an optimal model *** our study,the VGGRes Model achieved impressive results in multi-class arrhythmia detection,with an accuracy of 97.39%and firm performance in precision(82.13%),recall(31.91%),and F1-score(82.61%).In the binary-class task,the proposed model achieved an outstanding accuracy of 96.60%.These results highlight the effectiveness of our approach in improving arrhythmia detection,with notably high accuracy and well-balanced performance metrics.

关键词： Automated machine learning neural networks deep learning arrhythmias

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Machine learning-enhanced Monte Carlo and subset simulations for advanced risk assessment in transportation infrastructure

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Journal of Mountain science 2024年第2期21卷 690-717页

作者： Furquan AHMAD Pijush sAMUI s.s.MIsHRA Department of Civil engineering National Institute of TechnologyPatna 800006India

The maintenance of safety and dependability in rail and road embankments is of utmost importance in order to facilitate the smooth operation of transportation *** study introduces a comprehensive methodology for soil slope stability evaluation,employing Monte Carlo simulation(MCs)and subset simulation(ss)with the"UPss 3.0 Add-in"in *** on an 11.693-meter embankment with a soil slope(inclination ratio of 2H:1V),the investigation considers earthquake coefficients(kh)and pore water pressure ratios(ru)following Indian zoning *** chance of slope failure showed a considerable increase as the Coefficient of Variation(COV),seismic coefficients(kh),and pore water pressure ratios(ru)experienced an *** ss approach showed exceptional efficacy in calculating odds of failure that are notably *** computational modeling,the study optimized the worst-case scenario using ANFIs-GA,ANFIs-GWO,ANFIs-PsO,and ANFIs-BBO *** ANFIs-PsO model exhibits exceptional accuracy(training R2=0.9011,RMse=0.0549;testing R2=0.8968,RMse=0.0615),emerging as the most *** study highlights the significance of conducting thorough risk assessments and offers practical insights into evaluating and improving the stability of soil slopes in transportation *** findings contribute to the enhancement of safety and reliability in real-world situations.

关键词： Monte Carlo simulation subset simulation Machine Learning seismic coefficient

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Advances in spinal cord injury:insights from non-human primates

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Neural Regeneration Research 2024年第11期19卷 2354-2364页

作者： Gaetan Poulen Florence e.Perrin University of Montpellier INSERMEPHEMontpellierFrance Department of Neurosurgery Gui de Chauliac HospitalMontpellier University Medical CenterMontpellierFrance Institut Universitaire de France(IUF) ParisFrance

spinal cord injury results in significant sensorimotor deficits,currently,there is no curative treatment for the symptoms induced by spinal cord *** and pre-clinical research on spinal cord injury relies on the development and characterization of appropriate animal *** models should replicate the symptoms observed in human,allowing for the exploration of functional deficits and investigation into various aspects of physiopathology of spinal cord ***-human primates,due to their close phylogenetic association with humans,share more neuroanatomical,genetic,and physiological similarities with humans than ***,the responses to spinal cord injury in nonhuman primates most likely resemble the responses to traumatism in *** this review,we will discuss nonhuman primate models of spinal cord injury,focusing on in vivo assessments,including behavioral tests,magnetic resonance imaging,and electrical activity recordings,as well as ex vivo histological ***,we will present therapeutic strategies developed in non-human primates and discuss the unique specificities of non-human primate models of spinal cord injury.

关键词： behavior cellular analysis non-human primates spinal cord injury tissue analysis

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