Rajmund L. Somorjai

Retrograde cerebral perfusion provides limited distribution of blood to the brain: A study in pigs

OBJECTIVE The objective of this study was to investigate flow distribution during retrograde and antegrade cerebral perfusion with India ink as a marker. METHODS Ten pigs received cerebral perfusion with a solution containing 50% filtered India ink for 5 minutes either antegradely through both internal carotid arteries at a flow of 180 to 200 ml/min (n = 5) or retrogradely via the superior vena cava at a flow of 300 to 500 ml/min (n = 5). The brains were then fixed for quantitative measurement of the density of ink-filled capillaries (reported as a percentage of the total selected area). The assessment was done with the use of an in-house software program. RESULTS In the antegrade cerebral perfusion group, the intracranial arterial and venous systems were completely filled with ink. The gray matter was colored uniformly black, and light coloring was observed in the white matter. During retrograde cerebral perfusion, the majority of ink was returned to the inferior vena cava, and only a small amount of ink was found in the innominate artery draining from the brain. Massive ink filling was observed in the sagittal sinus and other venous sinuses in all the pigs. Vessels on the surface of the brain and large vessels in the brain were also well filled with ink. However, only 10% of capillaries were filled with ink during retrograde cerebral perfusion relative to the number observed with antegrade cerebral perfusion. CONCLUSIONS Retrograde cerebral perfusion supplies a limited amount of blood to brain tissue, which flows mainly through superficial and large deep cerebral vessels.

Fuzzy C-means clustering and principal component analysis of time series from near-infrared imaging of forearm ischemia

Fuzzy C-means clustering and principal components analysis were used to analyze a temporal series of near-IR images taken of a human forearm during periods of venous outflow restriction and complete forearm ischemia. The principal component eigen-time course analysis provided no useful information and the principal component eigen-image analysis gave results that correlated poorly with anatomical features. The fuzzy C-means clustering analysis, on the other hand, showed distinct regional differences in the hemodynamic response and scattering properties of the tissue, which correlated well with the anatomical features of the forearm.

MRS-based Metabolomics in Cancer Research

Metabolomics is a relatively new technique that is gaining importance very rapidly. MRS-based metabolomics, in particular, is becoming a useful tool in the study of body fluids, tissue biopsies and whole organisms. Advances in analytical techniques and data analysis methods have opened a new opportunity for such technology to contribute in the field of diagnostics. In the MRS approach to the diagnosis of disease, it is important that the analysis utilizes all the essential information in the spectra, is robust, and is non-subjective. Although some of the data analytic methods widely used in chemical and biological sciences are sketched, a more extensive discussion is given of a 5-stage Statistical Classification Strategy. This proposes powerful feature selection methods, based on, for example, genetic algorithms and novel projection techniques. The applications of MRS-based metabolomics in breast cancer, prostate cancer, colorectal cancer, pancreatic cancer, hepatobiliary cancers, gastric cancer, and brain cancer have been reviewed. While the majority of these applications relate to body fluids and tissue biopsies, some in vivo applications have also been included. It should be emphasized that the number of subjects studied must be sufficiently large to ensure a robust diagnostic classification. Before MRS-based metabolomics can become a widely used clinical tool, however, certain challenges need to be overcome. These include manufacturing user-friendly commercial instruments with all the essential features, and educating physicians and medical technologists in the acquisition, analysis, and interpretation of metabolomics data.

Antigen-antibody recognition. Model calculations

Free energy of antigen-antibody binding has been calculated for HyHEL-5, HyHEL-10, and D1.3 complexes. We also have calculated free energies of binding per residue of L- and H- chains of the antibodies, and those of the antigen (lysozyme). The results of the calculations provide support for the notion that TYR and TRP residues may confer on the CDRs of antibodies an enhanced capacity for binding antigens. It was shown also that the composition of residues that provide major part of the binding free energy differs for antibodies and antigens.

13NMR Studies on Opioid Peptides; 13C-Enriched Methionine-Enkephalin and α-Endorphin

13C NMR spectroscopy is becoming increasingly useful in the study of dynamical aspects of peptide conformation (Deslauriers and Smith, 1976; Bleich et al. 1976) as well as in the study of interactions between peptide hormones and macromolecules (Blumenstein and Hruby, 1977; Convert et al. 1977). We report here studies of the relative mobilities of moieties within the recently-discovered opiate agonists, the enkephalins (Hughes et al. 1975) and endorphins (Li and Chung, 1976a; and Lazarus et al. 1976), the first peptides reported to have morphine-like activity. The enkephalins are pentapeptides (Tyr-Gly-Gly-Phe-Met or Tyr-Gly-Gly-Phe-Leu) which can be extracted from brain tissue; the larger endorphins are thought to be enzyme-cleavage products of β-lipotropin, a 91-residue peptide synthesized in the pituitary (Li and Chung, 1976b). α-Endorphin comprises residues [61–76] of β-lipotropin, and the first five amino acids of α-endorphin are identical in sequence to methionine-enkephalin. It was thought that comparison of the dynamical properties of enkephalin and a-endorphin might provide insight into the structure-activity relations of these peptides (Ronai et al. 1977).