Multiprotein complexes present at the MIF motifs flanking the promoter of the human c-myc gene

The activated c-myc allele in Burkitt's lymphoma is associated with a clustering of somatic mutations within a discrete domain of intron I that define protein recognition sequences, designated as myc intron factors (MIF-1, MIF-2 and MIF-3). We have previously shown that MIF-1 binding activity consists of two polypeptides, myc intron binding polypeptide (MIBP1) and RFX1. In the present study we identified two polypeptides, p105 and p115, and showed that these proteins give rise to a DNA-protein complex at the MIF-2 as well as the adjacent MIF-1 site. In addition, we demonstrated that all four proteins interact with a novel MIF-1 like motif upstream from the c-myc promoter region, designated 5'MIF. These data suggest a model, where the interactions of MIBP1/RFX1 and p105/p115 with the MIF-like sites may play a role in the promoter topology of the c-myc gene. © 2000 Federation of European Biochemical Societies

Prognostic Value of Thymidylate Synthase, Ki-67 and p53 in Patients with Dukes' B and C Colon Cancer: a National Cancer Institute - National Surgical Ajuvant Breast and Bowel Project Collaborative Study

Purpose: To define the value of thymidylate synthase (TS), Ki-67, and p53 as prognostic markers in patients with stage II and III colon carcinoma. Patients and Methods: We retrospectively analyzed the prognostic value of TS, Ki-67, and p53 in 706 patients with Dukes\u27 B (291 patients) or Dukes\u27 C (415 patients) colon carcinoma who were treated with either surgery alone (275 patients) or surgery plus fluorouracil (FU)-leucovorin chemotherapy (431 patients) in National Surgical Adjuvant Breast and Bowel Project (NSABP) protocols C01-C04. All three markers were assayed using immunohistochemical techniques. Results: Using 5 years of follow-up data, our retrospective analysis demonstrated an association between TS intensity (relapse-free survival [RFS]: risk ratio [RR] = 1.46, P = .01; overall survival [OS]: RR = 1.54, P = .002), Ki-67 (RFS: RR = 0.76, P = .05; OS: RR = 0.62, P = .001), and p53 (RFS: RR = 1.49, P = .01; OS: RR = 1.21, P = .18) for RFS and OS. High TS intensity levels and positive p53 staining were associated with a worse outcome. Tumors containing a high percentage of Ki-67-positive cells enjoyed an improved outcome compared with those patients whose tumors contained relatively few positive cells. An interaction with treatment was not identified for any of the markers. Conclusion: This retrospective investigation demonstrated that TS, Ki-67, and p53 staining each had significant prognostic value for patients with Dukes\u27 B and C colon carcinoma. However, none of the markers could be used to clearly discern groups of individuals who would be predicted to derive greater or lesser benefit from the use of adjuvant chemotherapy. © 2003 by American Society of Clinical Oncology

Expanded measurements from station Lindenberg (2016-08)

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM—Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF–ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging.Peer reviewe