Talaromyces marneffei is a rare opportunistic pathogen.Talaromyces marneffei infection is characterized by insidious onset,atypical clinical manifestations,low early diagnosis rate,and high misdiagnosis and fatality,and has received widespread attention in recent years.Organ transplant recipients become a high-risk group for Talaromyces marneffei infection due to postoperative immunosuppressive therapy.Metagenomic next-generation sequencing,targeted antifungal therapy,and immunosuppression regimen adjustment are key to improving the prognosis of Talaromyces marneffei infection patients.This article reviews the epidemiology,pathogenesis,diagnosis and treatment of Talaromyces marneffei infection in organ transplant recipients,explores current challenges and future research directions,and aims to inform the diagnosis and treatment of Talaromyces marneffeiinfection.

Talaromyces marneffei is a rare opportunistic pathogen.Talaromyces marneffei infection is characterized by insidious onset,atypical clinical manifestations,low early diagnosis rate,and high misdiagnosis and fatality,and has received widespread attention in recent years.Organ transplant recipients become a high-risk group for Talaromyces marneffei infection due to postoperative immunosuppressive therapy.Metagenomic next-generation sequencing,targeted antifungal therapy,and immunosuppression regimen adjustment are key to improving the prognosis of Talaromyces marneffei infection patients.This article reviews the epidemiology,pathogenesis,diagnosis and treatment of Talaromyces marneffei infection in organ transplant recipients,explores current challenges and future research directions,and aims to inform the diagnosis and treatment of Talaromyces marneffeiinfection.

This report presents two cases of penicillium marneffei infection occurring after kidney transplantation. Both recipients presented initially with gastrointestinal symptoms and were diagnosed early by metagenomic next generation sequencing (mNGS). Treatment included amphotericin B combined with voriconazole, adjustment of immunosuppressive therapy, and nutritional support, resulting in favorable outcomes. This study aims to characterize the clinical presentation, diagnostic challenges, and individualized treatment strategies for penicillium marneffei infection in kidney transplant recipients, providing valuable insights for clinical management.

This report presents two cases of penicillium marneffei infection occurring after kidney transplantation. Both recipients presented initially with gastrointestinal symptoms and were diagnosed early by metagenomic next generation sequencing (mNGS). Treatment included amphotericin B combined with voriconazole, adjustment of immunosuppressive therapy, and nutritional support, resulting in favorable outcomes. This study aims to characterize the clinical presentation, diagnostic challenges, and individualized treatment strategies for penicillium marneffei infection in kidney transplant recipients, providing valuable insights for clinical management.

Objective To study an accurate prediction algorithm for irregular respiratory movements,effectively compensate for the time delay of radiotherapy systems,so as to improve the target accuracy of imageguided tracking or gated radiotherapy for thoracic and abdominal tumors.Methods A prediction algorithm based on an adaptive neuro-fuzzy inference system (ANFIS) was proposed to precisely predict irregular respiratory motion.The ANFIS model structure adopted the position and velocity of respiratory motion as input parameters to construct an N×N fuzzy set that combines position and velocity,and to establish a training set through historical data.In the prediction,if the position or velocity in the latest input signal was out of the range of the training set,the position or velocity would be adjusted accordingly and treated as the input parameter of the ANFIS model for prediction.The ANFIS was evaluated using 20 cases of irregular respiratory clinical data from CyberKnife-treated thoracic and abdominal tumors patients.The accuracy of the four typical prediction algorithms,including ANFIS,neural network (NN),support vector machine (SVM),and CyberKnife Synchrony,was compared by retrospective offline analysis.Results The ANFIS algorithm showed better performance than NN,SVM and Synchrony in normalized root mean square error (nRMSE),the maximum error (Max),and the number of errors greater than 1 mm.Conclusions The accuracy and robustness of the ANFIS algorithm are superior to NN,SVM and CyberKnife Synchrony.The ANFIS can better predict irregular respiratory signals.