ABSTRACT Hexapods, commonly known as insects, are a neglected taxonomic group in the Fernando de Noronha archipelago, with unanswered questions about their species richness and the ecological processes in which they are involved (e.g., colonization, introduction, establishment, and extinction). Herein, we provide an updated Hexapod checklist with current nomenclatural combinations. The entomofauna of the Fernando de Noronha archipelago is currently composed of 453 species in 21 orders. The orders, and their respective number of species, are: Blattaria (9), Coleoptera (118), Collembola (29), Dermaptera (3), Diplura (1), Diptera (134), Embioptera (1), Hemiptera (29), Hymenoptera (59), Isoptera (2), Lepidoptera (25), Mantodea (1), Neuroptera (3), Odonata (5), Orthoptera (11), Phasmatodea (1), Phthiraptera (6), Psocoptera (3), Siphonaptera (1), Thysanoptera (10), and Zygentoma (2). The archipelago has 263 new taxon records (family + genera + species). Thirty-eight species (3.39%) were described from local specimens and most of them are likely endemic species. This study more than doubles our knowledge (from the previous 190 records) of the entomofauna in this large Brazilian archipelago. This study also provides a baseline for studies on its conservation status and for implementing future environmental management programs.
OBJECTIVES: This study aimed to evaluate several methods to estimate glucose consumption in the male Wister rat brain as measured by PET. METHODS: Fourteen male Wistar normoglycemic rats were studied. The input function consisted of seventeen blood samples drawn manually from the femoral artery. Glucose uptake values were calculated using the input function resulting from the arterial blood samples and the tissue time-activity curve derived from the PET images. The estimated glucose consumption rate (Ki) based on the 2-tissue compartment model (2TCM) served as the standard for comparisons with the values calculated by the Patlak analysis and with the fractional uptake rate (FUR), standardized uptake value (SUV) and glucose corrected SUV (SUVglu). RESULTS: No significant difference between the standard Ki and the Patlak Ki was observed. The standard Ki was also found to have strong correlations and concordance with the Ki value estimated by the Patlak analysis. The FUR method presented an excellent correlation with the Ki value obtained by the 2TCM/Patlak analyses, in contrast to the SUV or SUVglu. CONCLUSIONS: From a methodological point of view, the present findings confirm the theoretical limitations of the cerebral SUV and SUVglu as a substitute for Ki in the estimation of glucose consumption in the brain. Our data suggest that the FUR is the surrogate to Ki.