Identification of responsible amino acid residues in staphylococcal superantigen-like 12 for the activation of mast cells.

Staphylococcal superantigen-like 12 (SSL12) is reported to evoke the degranulation in murine mast cells. The allelic variant of SSL12 in the genome of reference strain NCTC8325 induced the degranulation of murine mast cells, that of MRSA252 strain did not, nevertheless relatively high sequence similarity (82%). To identify responsible amino acid residues of SSL12 for mast cell activation, we created a series of domain swap mutants and amino acid substitution mutants between the active and inactive variants. The mutants that harbored oligonucleotide/oligosaccharide binding (OB)-fold domain of the active variant activated mast cells. The replacement at position 56 (L56F) in the OB-fold domain diminished the mast cell stimulatory activity, and the combinatorial substitutions L56F/K92E, L56F/D95S, and L56F/S100V abolished the stimulatory activities of the mutant that harbored OB-fold domain of the active variant and the intact active variant. These indicate that the responsive elements of SSL12 for mast cell activation are in the OB-fold of SSL12, and L56 would be an essential amino acid residue for the activation of mast cells. The findings would contribute to the understanding of the molecular mechanism of SSL12 for mast cell activation and the development of toxoids preventing allergic inflammations associated with Staphylococcus aureus.

Quantitative analysis of computed tomography images and early detection of cerebral edema for pediatric traumatic brain injury patients: retrospective study.

BACKGROUND: The purpose of this study was to identify whether the distribution of Hounsfield Unit (HU) values across the intracranial area in computed tomography (CT) images can be used as an effective diagnostic tool for determining the severity of cerebral edema in pediatric traumatic brain injury (TBI) patients. METHODS: CT images, medical records and radiology reports on 70 pediatric patients were collected. Based on radiology reports and the Marshall classification, the patients were grouped as mild edema patients (n=37) or severe edema patients (n=33). Automated quantitative analysis using unenhanced CT images was applied to eliminate artifacts and identify the difference in HU value distribution across the intracranial area between these groups. RESULTS: The proportion of pixels with HU=17 to 24 was highly correlated with the existence of severe cerebral edema (P<0.01). This proportion was also able to differentiate patients who developed delayed cerebral edema from mild TBI patients. A significant difference between deceased patients and surviving patients in terms of the HU distribution came from the proportion of pixels with HU=19 to HU=23 (P<0.01). CONCLUSIONS: The proportion of pixels with an HU value of 17 to 24 in the entire cerebral area of a non-enhanced CT image can be an effective basis for evaluating the severity of cerebral edema. Based on this result, we propose a novel approach for the early detection of severe cerebral edema.