Histamine production during the anti-allograft response. Demonstration of a new lymphokine enhancing histamine synthesis

Histamine production is greatly increased during culture of allograft recipient spleen cells in the presence of immunizing cells (secondary mixed leukocyte cultures [MLC]) as compared to that found in primary MLC (i.e., without previous allograft). This phenomenon appears after 24 h of culture and reaches its maximum at 48 h. Optimal increased histamine production is observed when MLC is performed with spleen cells removed from mice during rejection. This increased production of histamine during secondary MLC results from the action of a lymphokine: the histamine-producing cell stimulating factor (HCSF). This factor is released by T lymphocytes. Its production requires specific stimulation of the recipient lymphocytes because increase in histamine production during secondary MLC can be only observed when recipient cells are cultured with stimulating cells bearing at least one homology at K or D loci with immunizing cells. HCSF acts on a cell which is present in bone marrow, spleen, blood, and peritoneal cells but absent in thymus or lymph node cells. This target cell is found in the less-dense layer of a discontinuous Ficoll-gradient of bone marrow cells. HCSF is heat stable, destroyed by trypsin treatment, and has a molecular weight between 50,000 and 100,000. It acts on its target cells by increasing histidine decarboxylase activity

Reconstruction of thermally-symmetrized quantum autocorrelation functions from imaginary-time data

In this paper, I propose a technique for recovering quantum dynamical information from imaginary-time data via the resolution of a one-dimensional Hamburger moment problem. It is shown that the quantum autocorrelation functions are uniquely determined by and can be reconstructed from their sequence of derivatives at origin. A general class of reconstruction algorithms is then identified, according to Theorem 3. The technique is advocated as especially effective for a certain class of quantum problems in continuum space, for which only a few moments are necessary. For such problems, it is argued that the derivatives at origin can be evaluated by Monte Carlo simulations via estimators of finite variances in the limit of an infinite number of path variables. Finally, a maximum entropy inversion algorithm for the Hamburger moment problem is utilized to compute the quantum rate of reaction for a one-dimensional symmetric Eckart barrier.Comment: 15 pages, no figures, to appear in Phys. Rev.

Inversion of Randomly Corrugated Surfaces Structure from Atom Scattering Data

The Sudden Approximation is applied to invert structural data on randomly corrugated surfaces from inert atom scattering intensities. Several expressions relating experimental observables to surface statistical features are derived. The results suggest that atom (and in particular He) scattering can be used profitably to study hitherto unexplored forms of complex surface disorder.Comment: 10 pages, no figures. Related papers available at http://neon.cchem.berkeley.edu/~dan

Elastic Scattering by Deterministic and Random Fractals: Self-Affinity of the Diffraction Spectrum

The diffraction spectrum of coherent waves scattered from fractal supports is calculated exactly. The fractals considered are of the class generated iteratively by successive dilations and translations, and include generalizations of the Cantor set and Sierpinski carpet as special cases. Also randomized versions of these fractals are treated. The general result is that the diffraction intensities obey a strict recursion relation, and become self-affine in the limit of large iteration number, with a self-affinity exponent related directly to the fractal dimension of the scattering object. Applications include neutron scattering, x-rays, optical diffraction, magnetic resonance imaging, electron diffraction, and He scattering, which all display the same universal scaling.Comment: 20 pages, 11 figures. Phys. Rev. E, in press. More info available at http://www.fh.huji.ac.il/~dani

Fractal Analysis of Protein Potential Energy Landscapes

The fractal properties of the total potential energy V as a function of time t are studied for a number of systems, including realistic models of proteins (PPT, BPTI and myoglobin). The fractal dimension of V(t), characterized by the exponent \gamma, is almost independent of temperature and increases with time, more slowly the larger the protein. Perhaps the most striking observation of this study is the apparent universality of the fractal dimension, which depends only weakly on the type of molecular system. We explain this behavior by assuming that fractality is caused by a self-generated dynamical noise, a consequence of intermode coupling due to anharmonicity. Global topological features of the potential energy landscape are found to have little effect on the observed fractal behavior.Comment: 17 pages, single spaced, including 12 figure

Apparent Fractality Emerging from Models of Random Distributions

The fractal properties of models of randomly placed $n$-dimensional spheres ($n$=1,2,3) are studied using standard techniques for calculating fractal dimensions in empirical data (the box counting and Minkowski-sausage techniques). Using analytical and numerical calculations it is shown that in the regime of low volume fraction occupied by the spheres, apparent fractal behavior is observed for a range of scales between physically relevant cut-offs. The width of this range, typically spanning between one and two orders of magnitude, is in very good agreement with the typical range observed in experimental measurements of fractals. The dimensions are not universal and depend on density. These observations are applicable to spatial, temporal and spectral random structures. Polydispersivity in sphere radii and impenetrability of the spheres (resulting in short range correlations) are also introduced and are found to have little effect on the scaling properties. We thus propose that apparent fractal behavior observed experimentally over a limited range may often have its origin in underlying randomness.Comment: 19 pages, 12 figures. More info available at http://www.fh.huji.ac.il/~dani

Nodule Organogenesis and Symbiotic Mutants of the Model Legume \u3ci\u3eLotus japonicus\u3c/i\u3e

A detailed microscopical analysis of the morphological features that distinguish different developmental stages of nodule organogenesis in wild-type Lotus japonicus ecotype Gifu B-129-S9 plants was performed, to provide the necessary framework for the evaluation of altered phenotypes of L. japonicus symbiotic mutants. Subsequently, chemical ethyl methanesulfonate (EMS) mutagenesis of L. japonicus was carried out. The analysis of approximately 3,000 M1 plants and their progeny yielded 20 stable L. japonicus symbiotic variants, consisting of at least 14 different symbiosis- associated loci or complementation groups. Moreover, a mutation affecting L. japonicus root development was identified that also conferred a hypernodulation response when a line carrying the corresponding allele (LjEMS102) was inoculated with rhizobia. The phenotype of the LjEMS102 line was characterized by the presence of nodule structures covering almost the entire root length (Nod++), and by a concomitant inhibition of both root and stem growth. A mutation in a single nuclear gene was shown to be responsible for both root and symbiotic phenotypes observed in the L. japonicus LjEMS102 line, suggesting that (a) common mechanism(s) regulating root development and nodule formation exists in legumes

Identification of plant-derived alkaloids with therapeutic potential for myotonic dystrophy type I

Myotonic dystrophy type I (DM1) is a disabling neuromuscular disease with no causal treatment available. This disease is caused by expanded CTG trinucleotide repeats in the 3 UTR of the dystrophia myotonica protein kinase gene. On the RNA level, expanded (CUG)n repeats form hairpin structures that sequester splicing factors such as muscleblind-like 1 (MBNL1). Lack of availableMBNL1leads to misregulated alternative splicing of many target pre-mRNAs, leading to the multisystemic symptoms in DM1. Many studies aiming to identify small molecules that target the (CUG)n-MBNL1 complex focused on synthetic molecules. In an effort to identify new small molecules that liberate sequesteredMBNL1from (CUG)n RNA, we focused specifically on small molecules of natural origin. Natural products remain an important source for drugs and play a significant role in providing novel leads and pharmacophores for medicinal chemistry. In a new DM1 mechanism-based biochemical assay, we screened a collection of isolated natural compounds and a library of over 2100 extracts from plants and fungal strains. HPLC-based activity profiling in combination with spectroscopic methods were used to identify the active principles in the extracts. The bioactivity of the identified compounds was investigated in a human cell model and in a mouse model of DM1.We identified several alkaloids, including the -carboline harmine and the isoquinoline berberine, that ameliorated certain aspects of theDM1pathology in these models. Alkaloids as a compound class may have potential for drug discovery in other RNA-mediated diseases

Counting flags in triangle-free digraphs

Motivated by the Caccetta-Haggkvist Conjecture, we prove that every digraph on n vertices with minimum outdegree 0.3465n contains an oriented triangle. This improves the bound of 0.3532n of Hamburger, Haxell and Kostochka. The main new tool we use in our proof is the theory of flag algebras developed recently by Razborov.Comment: 19 pages, 7 figures; this is the final version to appear in Combinatoric

Hopping Conductivity of a Nearly-1d Fractal: a Model for Conducting Polymers

We suggest treating a conducting network of oriented polymer chains as an anisotropic fractal whose dimensionality D=1+\epsilon is close to one. Percolation on such a fractal is studied within the real space renormalization group of Migdal and Kadanoff. We find that the threshold value and all the critical exponents are strongly nonanalytic functions of \epsilon as \epsilon tends to zero, e.g., the critical exponent of conductivity is \epsilon^{-2}\exp (-1-1/\epsilon). The distribution function for conductivity of finite samples at the percolation threshold is established. It is shown that the central body of the distribution is given by a universal scaling function and only the low-conductivity tail of distribution remains $\epsilon$-dependent. Variable range hopping conductivity in the polymer network is studied: both DC conductivity and AC conductivity in the multiple hopping regime are found to obey a quasi-1d Mott law. The present results are consistent with electrical properties of poorly conducting polymers.Comment: 27 pages, RevTeX, epsf, 5 .eps figures, to be published in Phys. Rev.