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Huanglongbing (HLB) or "citrus greening" is the most destructive citrus disease worldwide. In this work, we studied host responses of citrus to infection with Candidatus Liberibacter asiaticus (CaLas) using next-generation sequencing technologies. A deep mRNA profile was obtained from peel of healthy and HLB-affected fruit. It was followed by pathway and(More)
Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young(More)
OBJECTIVE This paper introduces a modified artificial immune system (AIS)-based pattern recognition method to enhance the recognition ability of the existing conventional AIS-based classification approach and demonstrates the superiority of the proposed new AIS-based method via two case studies of breast cancer diagnosis. METHODS AND MATERIALS(More)
BACKGROUND An important challenge to pulmonary arterial hypertension (PAH) diagnosis and treatment is early detection of occult pulmonary vascular pathology. Symptoms are frequently confused with other disease entities that lead to inappropriate interventions and allow for progression to advanced states of disease. There is a significant need to develop new(More)
Volatile organic compounds (VOCs) are emitted from all plants and these VOCs are important means of communication between plants and insects. It has been documented that pathogen infections alter VOC profiles rendering infected plants more attractive to specific vectors transmitting these pathogens than uninfected plants, thus potentially aiding in pathogen(More)
Cluster analysis of aerosol time-of-flight mass spectrometry (ATOFMS) data has been an effective tool for the identification of possible sources of ambient aerosols. In this study, the clustering results of two typical methods, adaptive resonance theory-based neural networks-2a (ART-2a) and density-based clustering of application with noise (DBSCAN), on(More)
The aerosol time-of-flight mass spectrometry (ATOFMS) has not generally been used to provide a quantitative estimation of chemical compositions of ambient aerosols. In an initial study, the possibility of developing a calibration model to predict chemical compositions from ATOFMS data was demonstrated, but because of the limited number of samples (only 12),(More)