SUMMARY Bacteria regularly encounter widely varying metal concentrations in their surrounding environment. As metals become depleted, or, conversely, accrue to toxicity, microbes will activate cellular responses that act to maintain metal homeostasis. A suite of metal-sensing regulatory (‘metalloregulatory’) proteins orchestrate these responses by allosterically coupling the selective binding of target metals to the activity of DNA-binding domains. However, we report here the discovery, validation and structural details of a widespread class of riboswitch RNAs, whose members selectively and tightly bind the low abundance transition metals, Ni2+ and Co2+. These riboswitches bind metal cooperatively, and with affinities in the low micromolar range. The structure of a Co2+-bound RNA reveals a network of molecular contacts that explain how it achieves cooperative binding between adjacent sites. These findings reveal that bacteria have evolved to utilize highly selective metalloregulatory riboswitches, in addition to metalloregulatory proteins, for detecting and responding to toxic levels of heavy metals.

ObjectiveThis study aimed to predict recurrence after coil embolization of unruptured cerebral aneurysms with computational fluid dynamics (CFD) using porous media modeling (porous media CFD).MethodA total of 37 unruptured cerebral aneurysms treated with coiling were analyzed using follow-up angiograms, simulated CFD prior to coiling (control CFD), and porous media CFD. Coiled aneurysms were classified into stable or recurrence groups according to follow-up angiogram findings. Morphological parameters, coil packing density, and hemodynamic variables were evaluated for their correlations with aneurysmal recurrence. We also calculated residual flow volumes (RFVs), a novel hemodynamic parameter used to quantify the residual aneurysm volume after simulated coiling, which has a mean fluid domain > 1.0 cm/s.ResultFollow-up angiograms showed 24 aneurysms in the stable group and 13 in the recurrence group. Mann-Whitney U test demonstrated that maximum size, dome volume, neck width, neck area, and coil packing density were significantly different between the two groups (P < 0.05). Among the hemodynamic parameters, aneurysms in the recurrence group had significantly larger inflow and outflow areas in the control CFD and larger RFVs in the porous media CFD. Multivariate logistic regression analyses demonstrated that RFV was the only independently significant factor (odds ratio, 1.06; 95% confidence interval, 1.01–1.11; P = 0.016).ConclusionThe study findings suggest that RFV collected under porous media modeling predicts the recurrence of coiled aneurysms.

No abstract

Background & purposeHyperplastic remodeling (HR) lesions are sometimes found on cerebral aneurysm walls. Atherosclerosis is the results of HR, which may cause an adverse effect on surgical treatment for cerebral aneurysms. Previous studies have demonstrated that atherosclerotic changes had a correlation with certain hemodynamic characteristics. Therefore, we investigated local hemodynamic characteristics of HR lesions of cerebral aneurysms using computational fluid dynamics (CFD).MethodsTwenty-four cerebral aneurysms were investigated using CFD and intraoperative video recordings. HR lesions and red walls were confirmed on the intraoperative images, and the qualification points were determined on the center of the HR lesions and the red walls. The qualification points were set on the virtual operative images for evaluation of wall shear stress (WSS), normalized WSS (NWSS), oscillatory shear index (OSI), relative residence time (RRT), and aneurysm formation indicator (AFI). These hemodynamic parameters at the qualification points were compared between HR lesions and red walls.ResultsHR lesions had lower NWSS, lower AFI, higher OSI and prolonged RRT compared with red walls. From analysis of the receiver-operating characteristic curve for hemodynamic parameters, OSI was the most optimal hemodynamic parameter to predict HR lesions (area under the curve, 0.745; 95% confidence interval, 0.603–0.887; cutoff value, 0.00917; sensitivity, 0.643; specificity, 0.893; P<0.01). With multivariate logistic regression analyses using stepwise method, NWSS was significantly associated with the HR lesions.ConclusionsAlthough low NWSS was independently associated with HR lesions, OSI is the most valuable hemodynamic parameter to distinguish HR lesions from red walls.

OBJECT Histopathological examination has revealed that ruptured cerebral aneurysms have different hemostatic patterns depending on the location of the clot formation. In this study, the authors investigated whether the hemostatic patterns had specific hemodynamic features using computational fluid dynamics (CFD) analysis. METHODS Twenty-six ruptured middle cerebral artery aneurysms were evaluated by 3D CT angiography and harvested at the time of clipping. The hemostatic patterns at the rupture points were assessed by means of histopathological examination, and morphological parameters were obtained. Transient analysis was performed, and wall shear stress-related hemodynamic parameters and invariant Q (vortex core region) were calculated. The morphological and hemodynamic parameters were compared among the hemostatic patterns. RESULTS Hematoxylin and eosin staining of the aneurysm wall showed 13 inside-pattern, 9 outside-pattern, and 4 other-pattern aneurysms. Three of the 26 aneurysms were excluded from further analysis, because their geometry models could not be generated due to low vascular CT values. Mann-Whitney U-tests showed that lower dome volume (0.04 cm vs 0.12 cm, p = 0.014), gradient oscillatory number (0.0234 vs 0.0289, p = 0.023), invariant Q (-0.801 10/sec vs -0.124 10/sec, p = 0.045) and higher aneurysm formation indicator (0.986 vs 0.963, p = 0.041) were significantly related to inside-pattern aneurysms when compared with outside-pattern aneurysms. CONCLUSIONS Inside-pattern aneurysms may have simpler flow patterns and less flow stagnation than outside-pattern aneurysms. CFD may be useful to characterize the hemostatic pattern of ruptured cerebral aneurysms.