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From prediction to prevention:Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring

World Journal of Gastroenterology 2024年第7期30卷 631-635页

作者： Mariana Michelle Ramírez-mejía Nahum Méndez-Sánchez Plan of Combined Studies in Medicine Faculty of MedicineNational Autonomous University of MexicoDistrito Federal 04510Mexico Liver Research Unit Medica Sur Clinic&FoundationDistrito Federal 14050Mexico Faculty of Medicine National Autonomous University of MexicoDistrito Federal 04510Mexico

In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.

关键词： Hepatocellular carcinoma Early recurrence Machine learning XGBoost model Predictive precision medicine Clinical utility Personalized interventions

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Management of lateral pelvic lymph nodes in rectal cancer:Is it time to reach an Agreement?

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World Journal of Clinical Oncology 2024年第4期15卷 472-477页

作者： Sigfredo E romero-Zoghbi fernando López-Campos Felipe Couñago Department of Radiation Oncology GenesisCareTalavera de la Reina 45600ToledoSpain Department of Radiation Oncology Hospital Universitario Ramón Y CajalMadrid 28034Spain Department of Radiation Oncology GenesisCare-Hospital Universitario Vithas Madrid La MilagrosaMadrid 28010Spain

In this editorial,we proceed to comment on the article by Chua et al,addressing the management of metastatic lateral pelvic lymph nodes(mLLN)in stage II/III rectal cancer patients below the peritoneal reflection.The treatment of this nodal area sparks significant controversy due to the strategic differences followed by Eastern and Western physicians,albeit with a higher degree of convergence in recent years.The dissection of lateral pelvic lymph nodes without neoadjuvant therapy is a standard practice in Eastern countries.In contrast,in the West,preference leans towards opting for neoadjuvant therapy with chemoradiotherapy or radiotherapy,that would cover the treatment of this area without the need to add the dissection of these nodes to the total mesorectal excision.In the presence of high-risk nodal characteristics for mLLN related to radiological imaging and lack of response to neoadjuvant therapy,the risk of lateral local recurrence increases,suggesting the appropriate selection of strategies to reduce the risk of recurrence in each patient profile.Despite the heterogeneous and retrospective nature of studies addressing this area,an international consensus is necessary to approach this clinical scenario uniformly.

关键词： Rectal cancer Lateral pelvic lymph node metastases Pelvic lymph node dissection Total neoadjuvant therapy Selective management of the lateral pelvic nodes Prophylactic management of the lateral pelvic nodes Chemoradiotherapy Total mesorectal excision

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Exploring multifaceted factors in chronic kidney disease risk: A comprehensive analysis of biochemistry, lifestyle, and inflammation in elderly Chinese individuals

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World Journal of Clinical Cases 2024年第5期12卷 1033-1035页

作者： fernando Cardona Unitat de Genètica Molecular Instituto de Biomedicina de Valencia–CSICValencia 46010Spain Centro de investigación Biomédica en Red Enfermedades Neurodegenerativas(CIBERNED) Instituto de Salud Carlos IIIMadrid 28029Spain Departamento de Biotecnología Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural(ETSIAMN)Univeristat Politècnica de ValenciaValencia 46022Spain

This letter praises a recent article in the World Journal of Clinical Cases(Roles of biochemistry data,lifestyle,and inflammation in identifying abnormal renal function in old Chinese),examining factors affecting abnormal renal function in elderly Chinese using advanced machine learning.It highlights the importance of uric acid,age,hemoglobin,body mass index,sport hours,and systolic blood pressure.The study's holistic approach,integrating lifestyle and inflammation,offers a nuanced understanding of chronic kidney disease risk factors.The letter suggests exploring mechanistic pathways of hyperuricemia,the link between anemia and renal function,and the connection between body mass index and estimated glomerular filtration rate.It advocates investigating physical activity's impact on renal health and the independent effects of blood pressure.The study significantly contributes to chronic kidney disease understanding,proposing avenues for further exploration and interventions.Commendations are extended to the authors and the journal.

关键词： Biochemistry data Lifestyle Machine learning Renal function

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Loggerhead Sea Turtles Hand-Reared in Captivity: Isotopic Insights into Their Inherent Dietary Variation

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Open Journal of Ecology 2024年第5期14卷 435-454页

作者： Brenda Natasha mejía-Guarnizo Carlos Julio Polo-Silva Guiomar Aminta Jauregui-romero Antonio Delgado-Huertas Centro de Investigaciones en Ciencias Marinas (CICIMAR-IPN) La Paz M&#233xico Marine Biology Program Faculty of Natural Sciences and Engineering Jorge Tadeo Lozano University Santa Marta Colombia Sharky Management and Consulting Oldsmar FL USA Programa de Conservació n de Tortugas y Mam&#237feros Marinos (ProCTMM) Santa Marta Colombia Instituto Andaluz de Ciencias de la Tierra (CSIC-UGR) Armilla Spain

Stable isotope analysis is a widely used method for gathering ecological insights into the diet and feeding habitats of various species. While captive studies often limit lethal sampling and differ from wild conditions, they offer valuable insights into inherent isotopic variations among individuals, which are often assumed to reflect differences between natural populations. In the Sea Turtle Conservation Program, loggerhead turtle hatchlings from different nests were fed. Necropsies were conducted on turtles that died during this period, obtaining bone fragments for analysis. We evaluated the isotopic variation of carbon (δ13C) and nitrogen (δ15N) in bone tissue across six turtle nests (n = 66 samples) and assessed differences in Straight Carapace Length (SCL, n = 71 samples). Using SIBER and nicheROVER in R, we calculated niche width and overlap, while the simmr package determined primary prey assimilation. Despite feeding the hatchlings the same prey, we observed variations in nitrogen isotope assimilation between nests. Nests 4 and 6 had a niche width >1.8‰, indicating consistent consumption frequencies across all prey and >70% niche overlap with other nests. In contrast, nests 1 and 2 showed a narrower niche width (Mugil sp. constituted the primary diet component (>40%) across all groups. This study demonstrates how factors like competition or prey preference can influence the assimilation of diet, even when the source remains constant (inherent variation).

关键词： Stable Isotopes Caretta caretta Head-Starting Nests Straight Carapace Length

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Predicting outcomes after kidney transplantation: Can Pareto’s rules help us to do so?

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World Journal of Transplantation 2024年第1期14卷 9-11页

作者： fernando M Gonzalez Francisca Gonzalez Cohens Department of Nephrology Faculty of MedicineUniversidad de ChileSantiago 7500922Chile Web Intelligence Centre Faculty of Physics and Mathematical SciencesSantiago 7500922Chile

Kidney transplantation is the best option for kidney replacement therapy,even considering that most of the times the grafts do not survive as long as their recipients.In the Khalil et al's experience,published in this issue of the Journal,they analyze their second kidney graft survival and describe those significant predictors of early loss.This editorial comments on the results and put in perspective that most of the times,long-term graft survival could be inadvertently jeopardized if the immunosuppressive therapy is reduced or withdrawn for any reason,and that it could happen frequently if the transplant physician intends to innovate with the clinical care without proper evidence-based data.

关键词： Kidney transplantation Graft survival Acute rejection Interstitial fibrosis and tubular atrophy Immunosuppression

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Failure to Rescue as a Quality Metric in Congenital Heart Surgeries in a High-Complexity Service Provider Institution Located in a Middle-Income Country

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Congenital Heart Disease 2024年第2期19卷 207-218页

作者： Gustavo Cruz Santiago Pedroza Juan F.Vélez Jessica Largo Juan F.Tejada Jorge H.mejía-Mantilla Departamento de Anestesiología Fundación Valle del LiliCali760032Colombia Centro de Investigaciones Clínicas Fundación Valle del LiliCali760032Colombia Departamento de Cardiología Pediátrica Fundación Valle del LiliCali760032Colombia Facultad de Medicina Universidad IcesiCali760031Colombia Unidad de Cuidado Intensivo Fundación Valle del LiliCali760032Colombia

Background:Failure to rescue has been an effective quality metric in congenital heart surgery.Conversely,mor-bidity and mortality depend greatly on non-modifiable individual factors and have a weak correlation with better-quality performance.We aim to measure the complications,mortality,and risk factors in pediatric patients undergoing congenital heart surgery in a high-complexity institution located in a middle-income country and compare it with other institutions that have conducted a similar study.Methods:A retrospective observational study was conducted in a high-complexity service provider institution,in Cali,Colombia.All pediatric patients undergoing any congenital heart surgery between 2019 and 2022 were included.The main outcomes evaluated in the study were complication,mortality,and failure to rescue rate.Univariate and multivariate logistic regression analysis was performed with mortality as the outcome variable.Results:We evaluated 308 congenital heart sur-geries.Regarding the outcomes,201(65%)complications occurred,23(7.5%)patients died,and the FTR of the entire cohort was 11.4%.The presence of a postoperative complication(OR 14.88,CI 3.06–268.37,p=0.009),age(OR 0.79,CI 0.57–0.96,p=0.068),and urgent/emergent surgery(OR 8.14,CI 2.97–28.66,p<0.001)were the most significant variables in predicting mortality.Conclusions:Failure to rescue is an effective and comparable quality measure in healthcare institutions and is the major contributor to postoperative mortality in congenital heart surgeries.Despite our higher mortality and complication rate,we obtained a comparable failure to rescue rate to high-income countries’health institutions.

关键词： Congenital heart surgery complication mortality failure to rescue quality metric

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A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 1-21页

作者： Mina Haghighat Mehdi Niroomand Hossein Dehghani Tafti Christopher D.Townsend Tyrone fernando the Department of Electrical Engineering University of IsfahanIsfahanIran the Department of Electrical Electronic and Computer EngineeringUniversity of Western AustraliaCrawley WA 6009Australia

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)mode.However,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power grid.Therefore,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid requirements.Hence,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing literature.The purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage systems.This paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var control.Each of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT algorithms.The three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also provided.This paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

关键词： Maximum power point tracking(MPPT) flexi ble power point tracking(FPPT) power reserve control(PRC) power ramp rate control(PRRC) low voltage ride-through(LVRT) constant power generation(CPG)

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Personality Trait Detection via Transfer Learning

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Computers, Materials & Continua 2024年第2期78卷 1933-1956页

作者： Bashar Alshouha Jesus Serrano-Guerrero Francisco Chiclana Francisco P.romero Jose A.Olivas Department of Information Technologies and Systems University of Castilla-La ManchaCiudad Real13071Spain Institute of Artificial Intelligence School of Computer Science and InformaticsDe Montfort UniversityThe GatewayLeicesterLE19BHUK

Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains,including education,e-commerce,or human resources.Tra-ditional machine learning techniques have been broadly employed for personality trait identification;nevertheless,the development of new technologies based on deep learning has led to new opportunities to improve their performance.This study focuses on the capabilities of pre-trained language models such as BERT,RoBERTa,ALBERT,ELECTRA,ERNIE,or XLNet,to deal with the task of personality recognition.These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making th

关键词： Personality trait detection pre-trained language model big five model transfer learning

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Going deep:Roots,carbon,and analyzing subsoil carbon dynamics

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Molecular Plant 2024年第1期17卷 1-3页

作者： Ezhilmathi Angela Joseph fernando Michael Selvaraj Yusaku Uga Wolfgang Busch Hunt Bowers Joe Tohme Alliance of Bioversity International and CIAT Km 17 Recta Cali-PalmiraAprtado Aereo 6713Cali 763537Colombia National Institute of Agrobiological Sciences(NIAS) TsukubaIbaraki 305-0856Japan Salk Institute for Biological Studies 10010 N Torrey Pines RoadLa JollaCA 92037USA Earth Optics Suite 840ArlingtonVA 22202USA

Agricultural practices currently contribute to the emission of approximately 10%–12%atmospheric greenhouse gasses,with tillage agriculture accelerating soil disruption and carbon dioxide release.Nevertheless,various options exist,such as converting new lands for agriculture,promoting healthier plant-based diets,adopting advanced management technologies,and minimizing food loss.However,these measures alone are insufficient to ensure environmental sustainability within planetary boundaries.

关键词： soil measures carbon

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Metabolomics for the diagnosis of bladder cancer: A systematic review

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Asian Journal of Urology 2024年第2期11卷 221-241页

作者： Herney Andrés García-Perdomo Angélica María Dávila-Raigoza fernando Korkes Division of Urology/Urooncology Department of SurgerySchool of MedicineUniversidad del ValleCaliColombia UROGIV Research Group School of MedicineUniversidad del ValleCaliColombia Urologic Oncology Division of UrologyABC Medical SchoolSao PauloBrazil

Objective: Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.Methods: A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.Results: The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.Conclusion: The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.

关键词： Metabolite Metabolomics Bladder cancer Metabolomicsprofile

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