Nearly complete 1H, 13C, and 15N resonance assignments have been obtained for the protein HU from Bacillus stearothermophilus (dimer, 19.5 kDa) using double- and triple-resonance 2D and 3D NMR experiments. This has resulted in assignments of 91% of the observable protons, 98% of all 13C, and 92% of all 15N nuclei. NOEs obtained from a 3D time-shared NOESY-(13C,15N)-HSQC spectrum, exchange data of amide protons, and chemical shifts of the 1H alpha, 1HN, 13C beta, 13C alpha, 13CO, and 15N nuclei have been used to identify the secondary structure elements. Three alpha-helices (residues 3-13, 18-37, and 83-90) and three extended strands (residues 40-45, 48-62, and 67-82) have been found in HU. The arrangement of these elements of secondary structure is very similar to the X-ray structure [Tanaka et al. (1984) Nature 310, 376-381; White et al. (1989) Proteins 5, 281-288]. The conformation of the proposed DNA-binding region of HU, i.e., an antiparallel beta-hairpin, was not observed previously in the X-ray structure. In the NMR structure long range NOEs in the beta-arm region (residues 53-76) suggest a distortion between residue Pro-72 and Ala-73 and between Pro-63 and Gln-64 with concomitant distortions in the opposite strand. The NOE data indicate further that the loop region in the DNA-binding arms of HU is arranged as a type I beta-turn from Pro-63 to Gly-66.
Brain tissue analysis is highly desired in neurosurgery, such as tumor resection. To guarantee best life quality afterward, exact navigation within the brain during the surgery is essential. So far, no method has been established that perfectly fulfills this need. Optical coherence tomography (OCT) is a promising three-dimensional imaging tool to support neurosurgical resections. We perform a preliminary study toward in vivo brain tumor removal assistance by investigating meningioma, healthy white, and healthy gray matter. For that purpose, we utilized a commercially available OCT device (Thorlabs Callisto) and measured eight samples of meningioma, three samples of healthy white, and two samples of healthy gray matter ex vivo directly after removal. Structural variations of different tissue types, especially meningioma, can already be seen in the raw OCT images. Nevertheless, an automated differentiation approach is desired, so that neurosurgical guidance can be delivered without a-priori knowledge of the surgeon. Therefore, we employ different algorithms to extract texture features and apply pattern recognition methods for their classification. With these postprocessing steps, an accuracy of nearly 98% was found.
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