You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Transcriptome and Metabolome Analyses of Glucosinolates in Two Broccoli Cultivars Following Jasmonate Treatment for the Induction of Glucosinolate Defense to Trichoplusia ni (Hübner) Lepidopteran larvae growth is influenced by host plant glucosinolate (GS) concentrations, which are, in turn, influenced by the phytohormone jasmonate (JA). In order to elucidate insect resistance biomarkers to lepidopteran pests, transcriptome and metabolome analyses following JA treatments were conducted with two broccoli cultivars, Green Magic and VI-158, which have differentially induced indole GSs, neoglucobrassicin and glucobrassicin, respectively. To test these two inducible GSs on growth of cabbage looper (Trichoplusia ni), eight neonate cabbage looper larvae were placed onto each of three plants per JA treatments (0, 100, 200, 400 µM) three days after treatment. After five days of feeding, weight of larvae and their survival rate was found to decrease with increasing JA concentrations in both broccoli cultivars. JA - inducible GSs were measured by high performance liquid chromatography. Neoglucobrassicin in Green Magic and glucobrassicin in VI-158 leaves were increased in a dose-dependent manner. One or both of these glucosinolates and/or their hydrolysis products showed significant inverse correlations with larval weight and survival (five days after treatment) while being positively correlated with the number of days to pupation. This implies that these two JA - inducible glucosinolates can influence the growth and survival of cabbage looper larvae. Transcriptome profiling supported the observed changes in glucosinolate and their hydrolysis product concentrations following JA treatments. Several genes related to GS metabolism differentiate the two broccoli cultivars in their pattern of transcriptional response to JA treatments. Indicative of the corresponding change in indole GS concentrations, transcripts of the transcription factor MYB122, core structure biosynthesis genes (CYP79B2, UGT74B1, SUR1, SOT16, SOT17, and SOT18), an indole glucosinolate side chain modification gene (IGMT1), and several glucosinolate hydrolysis genes (TGG1, TGG2, and ESM1) were significantly increased in Green Magic (statistically significant in most cases at 400 µM) while UGT74B1 and MYB122 were significantly increased in VI-158. Therefore, these metabolite and transcript biomarker results indicate that transcriptome profiling can identify genes associated with the formation of two different indole GS and their hydrolysis products. Therefore, these metabolite and transcript biomarkers could be useful in an effective marker - assisted breeding strategy for resistance to generalist lepidopteran pests in broccoli and potentially other Brassica vegetables.
{"AnatomicalStructure": ["TGG2", "SOT16", "SOT17", "genes", "UGT74B1", "SUR1", "gene", "TGG1", "CYP79B2", "ESM1", "MYB122", "IGMT1", "SOT18"], "Bacterium": [], "BiologicFunction": ["biomarker", "breeding", "marker", "metabolism", "pupation", "biomarkers", "growth", "transcriptional"], "BiomedicalOccupationOrDiscipline": [], "BodySubstance": [], "BodySystem": [], "Chemical": ["Jasmonate", "phytohormone", "Glucosinolate", "GS", "indole GSs", "neoglucobrassicin", "indole GS", "jasmonate", "GSs", "Glucosinolates", "glucosinolate", "glucobrassicin", "glucosinolates", "JA", "Neoglucobrassicin", "metabolite", "transcripts", "MYB122", "transcription factor", "transcript"], "ClinicalAttribute": [], "Eukaryote": ["larvae", "VI-158", "plants", "broccoli", "cabbage looper", "larval", "Broccoli Cultivars", "Trichoplusia ni", "insect", "Lepidopteran", "Green Magic", "broccoli cultivars", "lepidopteran", "cabbage looper larvae", "plant", "leaves"], "Finding": ["positively", "modification"], "Food": ["Brassica vegetables"], "HealthCareActivity": ["Transcriptome profiling", "transcriptome profiling", "high performance liquid chromatography"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": [], "Organization": [], "PopulationGroup": [], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["analyses", "Analyses"], "SpatialConcept": ["transcriptome", "pattern", "Transcriptome"], "Virus": []}