Monoclonal anti-mouse macrophage antibodies recognize the globular portions of C1q, a subcomponent of the first component of complement

One of seven monoclonal antibodies generated against mouse macrophages (M phi) was found to recognize isolated heterologous C1q. This antibody was shown to be cytotoxic and to react in a strain-independent way with mouse M phi derived from bone marrow cells as well as with M phi from the peritoneal cavity; it did not react, however, with mouse granulocytes, thymocytes, or T and B lymphocytes. The hemolytic activity of fluid phase C1q was inhibited to 50% at a 2 X 10(-4) dilution of hybridoma supernatant, whereas a 100-fold higher concentration was required to inhibit C1q bound to immune complexes ( EAC1q ) to the same extent. It was demonstrated that this antibody recognizes the isolated globular, Fc-binding portions of the C1q molecule and reacts with the A and B chains. Because M phi have been shown to synthesize C1q, the Fc-recognizing subcomponent of the first component of complement, evidence was provided that endogeneous C1q can serve as an Fc receptor on M phi during secretion. This fact was demonstrated by a dose-dependent inhibition of Fc-receptor activity for EIgG by the F(ab')2 fragment of this monoclonal antibody. These experiments further support the concept that C1q produced by M phi functions on the surface as an Fc-recognizing molecule before it is released and incorporated into the macromolecular complex of serum C1.     

Shape and location of eukaryotic initiation factor eIF-2 on the 40S ribosomal subunit of rat liver. Immunoelectron-microscopic and hydrodynamic investigations

The location of initiation factor eIF-2 and of its subunits in quaternary initiation complexes (40S-ribosomal-subunit.eIF-2. GuoPP[CH2]P.Met-tRNAf) was investigated by immunoelectron microscopy. Quaternary complexes were fixed with glutaraldehyde and reacted with affinity-purified polyclonal antibodies against eIF-2 alpha, eIF-2 beta or eIF-2 gamma. The dimeric immune complexes obtained by sucrose gradient centrifugation were investigated electron microscopically after negative staining. Antibody-binding sites were observed on the interface side of the 40S ribosomal subunit in the region between the 'head' and the 'body' (neck region) of the 40S ribosomal subunit. Within this region, eIF-2 alpha points to the rear side, whereas eIF-2 beta and eIF-2 gamma point to the frontal side of the 40S subunit indicating an elongated shape of eIF-2 about 15 nm long. By analytical ultracentrifugation of isolated eIF-2 the sedimentation and diffusion coefficients were determined to be 6.54 S and 4.74 x 10(-7) cm2/s respectively. From these data, a molar mass of 122.4 kg/mol and a dry volume of 147.4 nm3 were calculated. For the shape of eIF-2 a prolate ellipsoid of revolution is assumed with a maximal length of about 15 nm and with an axial ratio of about 1:3.5. This conclusion is further confirmed by a calculated frictional ratio of 1.37 and a Stokes radius of about 4.54 nm.     

Data pattern analysis for the individualised pretherapeutic identification of high-risk diffuse large B-cell lymphoma (DLBCL) patients by cytomics.

BACKGROUND: Clinical outcome predictions in phase III studies are mostly derived for patient groups, but not for individual patients, although individualised predictions are an ultimate goal to permit a personalised fine tuning of therapy. This may permit earlier application of target therapies, minimise general damage to the organism, and result in improved complete remission rates in malignant diseases. METHODS: In this study, Lymphochip cDNA microarray gene expression results of DLBCL patients, from a published prospective meta-analysis study on the prediction of group prognosis, were analysed for individualised predictions using a nonstatistical data pattern classification approach. The training set was comprised of the same 160 DLBCL patients as in the prognosis study, with the validation set of 80 patients remaining unknown to the learning process. This permits the assessment of prospective classifier performance towards unknown patients. RESULTS: Pretherapeutic predictions for the training and validation set patients were correct in 98.1% and 78.3% of the cases for nonsurvival and in 67.3% and 45.3% for survival. The discriminatory data pattern consisted of 14 known and 10 unknown gene products. CONCLUSIONS: The better than 95% correct pretherapeutic prediction for about one-half of the ultimately nonsurviving high-risk patients of the training set is promising for clinical considerations about individualised therapy in such cases. Reliable individualised survival predictions are not possible with the information content of the present dataset. It seems necessary to investigate additional gene products, since survival may significantly depend on non-lymphocyte-associated genes that escape to the lymphocyte-oriented Lymphochip gene activation analysis.