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The challenges encountered in performing minimally invasive approaches, such as supraorbital minicraniotomy (SOMC), in services without adequate equipment are rarely reported in the literature. This study analyzes the viability of SOMC in the treatment of cerebral aneurysms, using exactly the same resources as pterional craniotomy (PC). The results of these two techniques are compared. 35 patients underwent SOMC, compared to 50 patients underwent CP (100 aneurysms in total), using the same microsurgical instruments. The following variables were compared: operative time, angiographic cure, length of intensive care unit stay during the post-operative period, surgical complications, length of hospital stay after surgery until hospital discharge, intraoperative aneurysm rupture, aesthetic satisfaction with the scar, and neurological status at discharge. SOMC had a significantly shorter operative time in relation to PC (213.9 ± 11.09 min and 268.6 ± 15.44 min, respectively) (p = 0.0081).With respect to the cosmetic parameters assessed by the Visual Analog Scale, the average for SOMC was 94.12 ± 1.92 points, and the average for PC was 83.57 ± 4.75 points (p = 0.036). SOMC was as effective as PC in relation to successful aneurysm clipping (p = 0.77). The SOMC technique did not show advantages over PC in any other variable. Even in a general neurosurgery service lacking a specific structure for minimally invasive surgeries, SOMC was feasible and effective for treating intracranial aneurysms, using the same set of microsurgical instruments used for PC, obtaining better results in operating time and cosmetic satisfaction.
Pubmed ID: 33692472
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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