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World Journal of Transplantation 2024年第1期14卷 1-8页

作者： Cristian Lindner Raúl Riquelme Rodrigo San martín Frank Quezada Jorge Valenzuela Juan P Maureira martín Einersen Department of Radiology Faculty of MedicineUniversity of ConcepciónConcepción 4030000Chile Department of Radiology Hospital Clínico Regional Guillermo Grant BenaventeConcepción 4030000Chile Department of Statistics Catholic University of MauleTalca 3460000Chile Neurovascular Unit Department of RadiologyHospital Clínico Regional Guillermo Grant BenaventeConcepción 4030000Chile

Hepatic artery thrombosis(HAT)is a devastating vascular complication following liver transplantation,requiring prompt diagnosis and rapid revascularization treatment to prevent graft *** present,imaging modalities such as ultrasound,computed tomography,and magnetic resonance play crucial roles in diagnosing *** imaging techniques have improved sensitivity and specificity for HAT diagnosis,they have limitations that hinder the timely diagnosis of this *** this sense,the emergence of artificial intelligence(AI)presents a transformative opportunity to address these diagnostic *** development of machine learning algorithms and deep neural networks has demonstrated the potential to enhance the precision diagnosis of liver transplant complications,enabling quicker and more accurate detection of *** article examines the current landscape of imaging diagnostic techniques for HAT and explores the emerging role of AI in addressing future challenges in the diagnosis of HAT after liver transplant.

关键词： Liver transplantation Postoperative complications Hepatic artery Thrombosis Radiology Artificial intelligence

Enhancing Hyper-Spectral Image Classification with Reinforcement Learning and Advanced Multi-Objective Binary Grey Wolf Optimization

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Computers, Materials & Continua 2024年第6期79卷 3469-3493页

作者： Mehrdad Shoeibi Mohammad Mehdi Sharifi Nevisi Reza Salehi Diego martín Zahra Halimi Sahba Baniasadi TheWPI Business School Worcester Polytechnic InstituteWorcesterMassachusetts01609-2280USA Department of Industrial Engineering Iran University of Science and TechnologyNarmakTehran16846-13114Iran ETSI de Telecomunicación Universidad Politécnica de MadridAv.Complutense 30Madrid28040Spain Department of Civil and Environmental Engineering University of MarylandCollege ParkMaryland20742USA Department of Industrial Engineering College of EngineeringUniversity of HoustonHoustonTexas77204USA

Hyperspectral(HS)image classification plays a crucial role in numerous areas including remote sensing(RS),agriculture,and the monitoring of the *** band selection in HS images is crucial for improving the efficiency and accuracy of image *** process involves selecting the most informative spectral bands,which leads to a reduction in data *** on these key bands also enhances the accuracy of classification algorithms,as redundant or irrelevant bands,which can introduce noise and lower model performance,are *** this paper,we propose an approach for HS image classification using deep Q learning(DQL)and a novel multi-objective binary grey wolf optimizer(MOBGWO).We investigate the MOBGWO for optimal band selection to further enhance the accuracy of HS image *** the suggested MOBGWO,a new sigmoid function is introduced as a transfer function to modify the wolves’*** primary objective of this classification is to reduce the number of bands while maximizing classification *** evaluate the effectiveness of our approach,we conducted experiments on publicly available HS image datasets,including Pavia University,Washington Mall,and Indian Pines *** compared the performance of our proposed method with several state-of-the-art deep learning(DL)and machine learning(ML)algorithms,including long short-term memory(LSTM),deep neural network(DNN),recurrent neural network(RNN),support vector machine(SVM),and random forest(RF).Our experimental results demonstrate that the Hybrid MOBGWO-DQL significantly improves classification accuracy compared to traditional optimization and DL ***-DQL shows greater accuracy in classifying most categories in both datasets *** the Indian Pine dataset,the MOBGWO-DQL architecture achieved a kappa coefficient(KC)of 97.68%and an overall accuracy(OA)of 94.32%.This was accompanied by the lowest root mean square error(RMSE)of 0.94,indicating very precise

关键词： Hyperspectral image classification reinforcement learning multi-objective binary grey wolf optimizer band selection

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

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Computers, Materials & Continua 2024年第3期78卷 3971-3991页

作者： Mohammad Mehdi Sharifi Nevisi Elnaz Bashir Diego martín Seyedkian Rezvanjou Farzaneh Shoushtari Ehsan Ghafourian Department of Industrial Engineering Iran University of Science and TechnologyNarmakTehran16846-13114Iran Department of Computer Science Iowa State UniversityAmesIowaIA50011USA ETSI de Telecomunicación Universidad Politécnica de MadridMadrid28040Spain Department of Engineering California State University East BayHaywardCalifornia94542USA Department of Industrial Engineering Bu-Ali Sina UniversityHamedan65178-38695Iran

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited *** main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these *** SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is *** proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration *** core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and *** is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO *** IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability *** comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP *** paper compares nine methods for predicting outage probability in wireless-powered *** IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance *** contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

关键词： Wireless-powered communications secrecy outage probability improved biogeography-based optimization recurrent neural network

Autoantibodies against beta cells to predict early insulin requirements in pediatric patients with clinically diagnosed type 2 diabetes

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World Journal of Diabetes 2024年第8期15卷 1717-1725页

作者： Jorge M Molina Patricia G Medina Rita A Gomez Julia R Herrera Nancy L martínez Brenda Hernández Yesenia García Department of Endocrinology Children’s Hospital Federico GomezMexico 06720Mexico National Medical Center"Siglo XXI" UMAE Hosp EspecialidadesUnidad Invest Med Epidemiol ClinMexican Social Security InstituteMexico 06720Mexico Research Division UMAE Hospital de EspecialidadesCentro Médico Nacional Siglo XXIMexican Institute of Social SecurityMexico 06720Mexico Epidemiology Research Unit in Endocrinology and Nutrition Federico Gómez Children’s HospitalMexico 06720Mexico Department of Endocrinology Comprehensive Health Unit for Trans PersonsMexico 11340Mexico

BACKGROUND Autoimmunity has emerged as a probable disease modifier in patients with clinically diagnosed type 2 diabetes mellitus(T2DM),that is,patients who have insulin resistance,obesity,and other cardiovascular risk factors,suggesting that the presence of glutamic acid decarboxylase(anti-GAD65),islet antigen 2(anti-IA2),and zinc transporter 8(anti-Zn8T)antibodies could have deleterious effects on beta cell function,causing failure and earlier requirement for insulin *** To evaluate anti-GAD65,anti-IA2 and anti-Zn8T as predictors of early insulin requirement in adolescents with a clinical diagnosis of *** This was a case–control study in patients with clinically diagnosed with T2DM(68 cases and 64 controls with and without early insulin dependence respectively),male and female,aged 12–18 ***,blood pressure,glucose,insulin,C-peptide,glycated hemoglobin A1c,and lipid profiles were *** was used to measure anti-GAD65,anti-IA2,and anti-Zn8T *** statistics,Pearson'sχ2 test,Student's t test,and logistic regression was performed.P<0.05 was considered statistically *** There were 132 patients(53.8%female),with a mean age was 15.9±1.3 years,and there was a disease evolution time of 4.49±0.88 *** presence of anti-GAD65,anti-IA2,and anti-Zn8T positivity was found in 29.5%,18.2%,and 15.9%,*** the groups by early or no insulin dependence showed that the group with insulin had a higher frequency of antibody positivity:anti-GAD65 odds ratio(OR):2.42(1.112–5.303,P=0.026);anti-IA2:OR:1.55(0.859–2.818,P=0.105);and anti-Zn8T:OR:7.32(2.039–26.279,P=0.002).CONCLUSION Anti-GAD65 positivity was high in our ***-GAD65 and anti-Zn8T positivity showed a significantly depleted beta cell reserve phenotype,leading to an increased risk of early insulin dependence.

关键词： Diabetes Obesity Adolescents Autoimmunity Beta cell Insulin requirements

A Systematic Review of Cannabidiol Effects in Coronary Syndromes: Challenges to Clinical Translation

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Journal of Biosciences and Medicines 2024年第4期12卷 246-263页

作者： Mario E. Zuñiga-Ayala Alejandra Meaney-martínez Alejandro Alcocer-Chauvet Vidal Gonzalez-Coronado Nestor Rubio-Infante Gerardo Garcia-Rivas Department of Cardiology Instituto de Seguridad Social and Trabajadores del Estado (ISSSTE) Hospital Regional Primero de Octubre Mexico City Mexico Department of Interventional Cardiology Instituto de Seguridad Social y Trabajadores del Estado (ISSSTE) Hospital Regional Primero de Octubre Mexico City Mexico Instituto Tecnó logico de Monerrey Escuela de Medicina and Ciencias de la Salud C&#225tedra de Cardiolog&#237a and Medicina Vascular Monterrey Mexico

Background: Myocardial ischemia in addition to other several cardiac syndromes represent a pathological proinflammatory state alongside a complex cellular microenvironment that can be modified by using cannabinoids. Cannabidiol (CBD), a non-psychoactive compound of cannabis has been recently proposed as an immudomodulatory and cardioprotective drug. Objectives: In this systematic review we sought to clarify and summarize the clinical and preclinical evidence of potential benefit of the use of CBD in coronary syndromes. Methods: We conducted a systematic search and review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Review of Animal Data from Experimental Studies (CAMARADES) guidelines, in the electronic database from PubMed, Web of Science and Scopus up to April 2022 using predefined search terms. Pre-specified exclusion and inclusion criteria were considered, finally 11 articles were chosen to be included for this peer review. Results: Currently there are no good-quality clinical trials with the use of CBD in acute or chronic coronary syndromes. A total of 11 preclinical studies where prescreened and 5 demonstrated reproducible positive cardiovascular outcomes on in-vivo models treated with CBD. Mechanisms of CBD cardioprotection observed: 1) reduction in oxidative stress and inflammation, 2) activation of adenosine receptors and 3) increased expression of angiotensin type 2-receptor. Experimental models included ischemia/reperfusion injury, myocardial infarction, arrhythmias, and metabolic syndrome-like conditions. Conclusion: No clinical recommendation can be issued with the current evidence, on the use of CBD in acute and chronic coronary syndromes. Based on preclinical evidence, we considered there is enough evidence to propose the development of well-designed clinical trials that include CBD in the management of coronary syndromes.

关键词： Cannabis Cannabidiol Acute Coronary Syndromes Myocardial Infarction Myocardial Ischemia and Oxidative Stress

Deregulation of interferon-gamma receptor 1 expression and its implications for lung adenocarcinoma progression

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World Journal of Clinical Oncology 2024年第2期15卷 195-207页

作者： Angeles C Tecalco-Cruz Karen H Medina-Abreu Enrique Oropeza-martínez Jesus Zepeda-Cervantes AleidaVázquez-Macías Marina Macías-Silva Posgrado en Ciencias Genómicas Universidad Autónoma de la Ciudad de MéxicoCDMX 03100Mexico Facultad de Medicina Veterinaria y Zootecnia Universidad Nacional Autónoma de MéxicoCDMX 04510Mexico Colegio de Ciencias y Humanidades Universidad Autónoma de la Ciudad de MéxicoCDMX 03100Mexico Instituo de Fisiología Celular Universidad Nacional Autónoma de MéxicoCDMX 04510Mexico

Interferon-gamma(IFN-γ)plays a dual role in cancer;it is both a pro-and an antitumorigenic cytokine,depending on the type of *** deregulation of the IFN-γcanonic pathway is associated with several disorders,including vulner-ability to viral infections,inflammation,and cancer *** particular,the interplay between lung adenocarcinoma(LUAD)and viral infections appears to exist in association with the deregulation of IFN-γ*** this mini-review,we investigated the status of the IFN-γsignaling pathway and the expression level of its components in ***,a reduction in IFNGR1 expression seems to be associated with LUAD progression,affecting defenses against viruses such as severe acute respiratory syndrome coronavirus *** addition,alterations in the expression of IFNGR1 may inhibit the antiproliferative action of IFN-γsignaling in LUAD.

关键词： Interferon-gamma IFNGR1 JAK1 Antiviral Anti-tumor Lung adenocarcinoma

Soil organic carbon stocks in native forest of Argentina:a useful surrogate for mitigation and conservation planning under climate variability

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Ecological Processes 2024年第1期13卷 3-24页

作者： Pablo L.Peri Juan Gaitán Matías Mastrangelo Marcelo Nosetto Pablo E.Villagra Ezequiel Balducci martín Pinazo Roxana P.Eclesia Alejandra Von Wallis Sebastián Villarino Francisco Alaggia Marina González Polo Silvina Manrique Pablo A.Meglioli Julián Rodríguez-Souilla martín Mónaco Jimena E.Chaves Ariel Medina Ignacio Gasparri Eugenio Alvarez Arnesi María Paula Barral Axel von Müller Norberto M.Pahr Josefina Uribe Echevarria Pedro Fernández Marina Morsucci Dardo López Juan Manuel Cellini Leandro Alvarez Ignacio Barberis Hernán Colomb Ludmila La Manna Sebastián Barbaro Cecilia Blundo Ximena Sirimarco Laura Cavallero Gualberto Zalazar Guillermo martínez Pastur Instituto Nacional de Tecnología Agropecuaria (INTA) Universidad Nacional de la Patagonia Austral (UNPA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad Nacional de Luján Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas(CONICET ) CCT San Luis Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto Argentino de Nivología Glaciología y Ciencias Ambientales (IANIGLA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Universidad Nacional de Cuyo Instituto de Investigaciones en Biodiversidad y Medioambiente (INIBIOMA) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Instituto de Investigaciones en Energía No Convencional CCT Salta-JujuyConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Recursos Agroforestales Centro Austral de Investigaciones Científicas (CADIC) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Dirección Nacional de Bosques Ministerio de Ambiente y Desarrollo Sostenible de la Nación Instituto de Ecología Regional Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )Universidad Nacional de Tucumán Universidad Nacional de Rosario Instituto de Investigaciones en Ciencias Agrarias de Rosario Centro Científico Tecnológico CONICET Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP) Universidad Nacional de Mar del Plata Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET ) Laboratorio de Investigaciones en Maderas (LIMAD) Universidad Nacional de La Plata (UNLP) Administración de Parques Nacionales (APN) Parque Nacional Los Alerces Centro de Estudios Ambientales Integrados (CEAI) Universidad Nacional de la Patagonia San Juan Bosco (UNPASJB) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET )

Background The nationally determined contribution（NDC） presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Conven-tion on Climate Change（UNFCCC） on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation（REDD+）. In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon（SOC） stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under cli-mate variability due to a lack of information. The objectives of this study were:（i） to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and（ii） to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate *** We used 1040 forest soil samples（0–30 cm） to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covari-ates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index（EVI） and land surface temperature（LST） images from Landsat *** SOC model（0–30 cm depth） prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C（2.71–2.84 Pg C with a probability of 90%） for a total area of 460,790 km2,

关键词： Soil organic carbon Biodiversity Native forest Climate change mitigation Modelling Resilience

Global paleobiogeography of Albian—Cenomanian(mid-Cretaceous)marine ostracods

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Journal of Palaeogeography 2024年第2期13卷 212-236页

作者： Bernardo Vázquez-García Jorge Villegas-martín Gerson Fauth Leonardo Borghi Aristóteles De Moraes Rios Netto Post-Graduate Program in Geology Unisinos UniversitySao LeopoldoRSBrazil Technological Institute of Paleoceanography and Climate Change-Itt Oceaneon Unisinos UniversitySao LeopoldoRSBrazil Laboratory of Sedimentary Geology(Lagesed) Department of GeologyInstitute of GeosciencesUFRJ-Federal Universityof Riode JaneiroBrazil Labmicro Department of GeologyInstitute of GeosciencesUFRJ-Federal University of Rio de JaneiroBrazil

Despite their potential for providing important information for paleobiogeography,studies using ostracod assemblages compiled from global datasets have been scarce so *** this study,the paleogeographic implications of the relationship between different ostracod assemblages are analyzed and discussed for the Albian and *** compiled an ostracod dataset at the genus level,with 168 genera for the Albian and 174 for the Cenomanian,to which different multivariate statistical methods of grouping were *** affinity between different ostracod assemblages from different regions allowed for the delineation of 30 operational geographic units(OGUs)for the Albian,and 32 OGUs for the Cenomanian,grouped in three paleobiogeographic units(PBUs;Megatethys,Persia,and Austral)and one sub-unit(PBSU;Maghreb associated to the Megatethys).The Maghreb PBSU showed minor changes between the Albian and *** relationship among the OGUs grouped in each PBU is related to different factors,such as eustatic sea level events,similar climatic zones,and marine current circulation patterns.A relationship was observed between the Gabon and Nigeria OGUs with the Persia PBU,which suggests a direct east—west connection between them during the *** affinity observed in the Austral PBU between the South American,South African,and Australian regions during the Albian can be explained by their relative geographic isolation due to the Walvis Ridge *** eventual flooding of this barrier led to the relationship observed between the SE Brazilian and Bolivian regions with the Austral ***,the data also suggested that the separation of the Indian subcontinent from the Austral PBU took place during the Cenomanian.

关键词： Operational geographic units Paleobiogeographic units Albian Cenomanian Marine ostracods

New Rotative Radiofrequency Technology: A Multicenter Retrospective Study on Efficacy and Safety

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Journal of Cosmetics, Dermatological Sciences and Applications 2024年第1期14卷 69-83页

作者： José Antonio Ferrández martínez Gregorio Viera Mármol Fabrizio Vignoli Joanet Perera Agustin Blanch Mara Suárez Alicia Robledo Jorge Reyna Vargas Lamas Sinclair Barcelona Spain Studio Vignoli Bologna Italy Clinica Perla Medic Alicante Spain Dr. Agustin Blanch Clinica Barcelona Spain Intek Medical Technology S.L.U. Barcelona Spain

Background: Non-ablative radiofrequency (RF) technology is widely used for the treatment of signs of aging, skin laxity, localized fat and cellulite. However, many RF devices suffer from technical limitations that make the results highly dependent on the user’s experience or clinical limitations that compromise safety, efficacy and comfort. Objective: To evaluate the efficacy and safety of a novel semi-automatic non-ablative RF device for skin tightening, body shaping and cellulite reduction. Materials and methods: A retrospective multicenter study was performed using a novel rotative RF device with temperature and impedance control (Sculpt&Shape®, Sinclair, Spain). 58 subjects underwent a minimum of 4 treatments every 1-2 weeks. A total of 120 treatments (56.7% body and 43.3% facial) and 1034 sessions were performed. Efficacy was evaluated by 3 researchers using the Global Aesthetic Improvement Scale (GAIS) and anthropometric measurements were collected. Subject and practitioner satisfaction were recorded. Safety was evaluated by analyzing the perception of pain during the treatment and the side and adverse effects immediately after treatment and over the next 48 hours. Results: Between 25% and 50% improvement was achieved according to the GAIS. Statistically significant (p < 0.01) abdominal fold reduction of 5.1 mm and circumference reduction of 32.0 mm, 16.4 mm and 13.9 mm were recorded for the abdomen, legs and arms, respectively. 77.5% of subjects and 94.9% of practitioners were either satisfied or very satisfied. Minor adverse effects were found in 0.97% of the sessions. Conclusion: This novel semi-automatic rotative RF device has been found to provide treatments that are effective, safe and comfortable for both practitioners and subjects. .

关键词： Rotative Radiofrequency RF Cellulite Skin Tightening Body Shaping

A Deep Reinforcement Learning-Based Technique for Optimal Power Allocation in Multiple Access Communications

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Intelligent Automation & Soft Computing 2024年第1期39卷 93-108页

作者： Sepehr Soltani Ehsan Ghafourian Reza Salehi Diego martín Milad Vahidi Department of Industrial Engineering College of EngineeringUniversity of HoustonHoustonTX77204USA Department of Computer Science Iowa State UniversityAmesIowaUSA ETSI de Telecomunicación Universidad Politécnica de MadridMadridSpain Faculty of School of Plant and Environmental Sciences Virginia Polytechnic Institute and StateUniversityBlacksburgVirginia24060USA

Formany years,researchers have explored power allocation(PA)algorithms driven bymodels in wireless networks where multiple-user communications with interference are ***,data-driven machine learning methods have become quite popular in analyzing wireless communication systems,which among them deep reinforcement learning(DRL)has a significant role in solving optimization issues under certain *** this purpose,in this paper,we investigate the PA problem in a k-user multiple access channels(MAC),where k transmitters(e.g.,mobile users)aim to send an independent message to a common receiver(e.g.,base station)through wireless *** this end,we first train the deep Q network(DQN)with a deep Q learning(DQL)algorithm over the simulation environment,utilizing offline ***,the DQN will be used with the real data in the online training method for the PA issue by maximizing the sumrate subjected to the source ***,the simulation results indicate that our proposedDQNmethod provides better performance in terms of the sumrate compared with the available DQL training approaches such as fractional programming(FP)and weighted minimum mean squared error(WMMSE).Additionally,by considering different user densities,we show that our proposed DQN outperforms benchmark algorithms,thereby,a good generalization ability is verified over wireless multi-user communication systems.

关键词： Deep reinforcement learning deep Q learning multiple access channel power allocation