Intraalveolar foam cells associated with lipidosis-like alterations in lung and liver of rats treated with tricyclic psychotropic drugs.

Histological, histochemical, and ultrastructural examinations were performed on pulmonary and hepatic tissues of rats after prolonged oral treatment with several tricyclic antidepressants and two neuroleptics, which are all of amphiphilic character. The antidepressants ipindole, imipramine, clomipramine, 1-chloro-amitriptyline, and 1-chloro-10,11-dehydro-amitriptyline were found to cause an accumulation of intraalveolar foam cells accompanied by the formation of abnormal lamellated and crystalloid cytoplasmic inclusions in most pulmonary and hepatic cell types. The ultrastructural and histochemical findings in both tissues point to generalized, abnormal intracellular storage of polar lipids, i.e. to drug-induced lipidosis. The foam cells are not regarded as an isolated pulmonary alteration but rather as an easily obtainable indication of generalized lipidosis, under the present conditions. They are thought to represent alveolar macrophages stuffed with non-digestible phospholipids. On the other hand, the tricyclic antidepressants noxiptiline and amitriptyline, and the neuroleptics chlorpromazine and thioridazine caused neither formation of foam cells nor of any lipidosis-like ultrastructural alterations. These negative results are tentatively ascribed to a more rapid biotransformation of the amphiphilic drug molecules into more hydrophilic metabolites which no longer have a high affinity to polar lipids. Two main conclusions can be drawn from the present ovservations: (1) Intraalveolar foam cells must not be regarded as a fortuitous alteration but rather as a first indication of generalized phospholipidosis, when they are found in animals treated with an amphiphilic drug. (2) Closely related compounds of amphiphilic character do not necessarily have the same potency to induce a phospholipidosis under in vivo conditions.     

Direct effect of complement factor C5a on the contractile state of isolated smooth muscle cells

The complement-(C) derived factor C5a has long been recognized as a potent contractile agonist in smooth muscle (1,2); however, controversy remains as to whether the effects of this anaphylatoxin are direct or secondary to the release of histamine (3) and/or other mediators (4-8) from nonmuscle cells within the tissue. To resolve this controversy, we have assessed the contractile effects of purified human C5a and C5a des Arg in a homogeneous preparation of enzymatically dispersed smooth muscle cells derived from the stomach of the toad, Bufo marinus. This preparation, which is insensitive to histamine at concentrations as high as 10(-4) M, responds normally to a variety of electrical (9), mechanical (10), and pharmacologic (11, 12) stimuli. These smooth muscle cells also respond to purified human anaphylatoxin; exposure to the cells to purified human C5a or C5a des Arg produce contractions of the smooth muscle cells that are accompanied by increased Ca2+ influx. The contractile response was unaffected by antagonists to histamine or acetylcholine but was reduced by 30% by pretreatment with the leukotriene antagonist FPL55712. A direct contractile effect of C5a on amphibian smooth muscle cells is suggested.     

Edible Lepidoptera in Mexico: Geographic distribution, ethnicity, economic and nutritional importance for rural people

In this paper, we reported the butterflies and moths that are consumed in Mexico. We identified 67 species of Lepidoptera that are eaten principally in their larval stage in 17 states of Mexico. These species belong to 16 families: Arctiidae, Bombycidae, Castniidae, Cossidae, Geometridae, Hepialidae, Hesperiidae, Lasiocampidae, Noctuidae, Nymphalidae, Papilionidae, Pieridae, Pyralidae, Saturniidae, Sesiidae, and Sphingidae. Saturniidae, Pieridae, Noctuidae and Nymphalidae were the more species consumed with 16, 11, 9, and 8 species, respectively. The genera with the largest numbers of species were: Phassus, Phoebis, Hylesia and Spodoptera, with three species. Their local distribution, corresponding to each state of Mexico, is also presented.     

Evaluation of a sophisticated SCFG design for RNA secondary structure prediction

Predicting secondary structures of RNA molecules is one of the fundamental problems of and thus a challenging task in computational structural biology. Over the past decades, mainly two different approaches have been considered to compute predictions of RNA secondary structures from a single sequence: the first one relies on physics-based and the other on probabilistic RNA models. Particularly, the free energy minimization (MFE) approach is usually considered the most popular and successful method. Moreover, based on the paradigm-shifting work by McCaskill which proposes the computation of partition functions (PFs) and base pair probabilities based on thermodynamics, several extended partition function algorithms, statistical sampling methods and clustering techniques have been invented over the last years. However, the accuracy of the corresponding algorithms is limited by the quality of underlying physics-based models, which include a vast number of thermodynamic parameters and are still incomplete. The competing probabilistic approach is based on stochastic context-free grammars (SCFGs) or corresponding generalizations, like conditional log-linear models (CLLMs). These methods abstract from free energies and instead try to learn about the structural behavior of the molecules by learning (a manageable number of) probabilistic parameters from trusted RNA structure databases. In this work, we introduce and evaluate a sophisticated SCFG design that mirrors state-of-the-art physics-based RNA structure prediction procedures by distinguishing between all features of RNA that imply different energy rules. This SCFG actually serves as the foundation for a statistical sampling algorithm for RNA secondary structures of a single sequence that represents a probabilistic counterpart to the sampling extension of the PF approach. Furthermore, some new ways to derive meaningful structure predictions from generated sample sets are presented. They are used to compare the predictive accuracy of our model to that of other probabilistic and energy-based prediction methods. Particularly, comparisons to lightweight SCFGs and corresponding CLLMs for RNA structure prediction indicate that more complex SCFG designs might yield higher accuracy but eventually require more comprehensive and pure training sets. Investigations on both the accuracies of predicted foldings and the overall quality of generated sample sets (especially on an abstraction level, called abstract shapes of generated structures, that is relevant for biologists) yield the conclusion that the Boltzmann distribution of the PF sampling approach is more centered than the ensemble distribution induced by the sophisticated SCFG model, which implies a greater structural diversity within generated samples. In general, neither of the two distinct ensemble distributions is more adequate than the other and the corresponding results obtained by statistical sampling can be expected to bare fundamental differences, such that the method to be preferred for a particular input sequence strongly depends on the considered RNA type.     

Optimized labeling of bone marrow mesenchymal cells with superparamagnetic iron oxide nanoparticles and <Emphasis Type="Italic">in vivo</Emphasis> visualization by magnetic resonance imaging

Background  

Stem cell therapy has emerged as a promising addition to traditional treatments for a number of diseases. However, harnessing the therapeutic potential of stem cells requires an understanding of their fate in vivo. Non-invasive cell tracking can provide knowledge about mechanisms responsible for functional improvement of host tissue. Superparamagnetic iron oxide nanoparticles (SPIONs) have been used to label and visualize various cell types with magnetic resonance imaging (MRI). In this study we performed experiments designed to investigate the biological properties, including proliferation, viability and differentiation capacity of mesenchymal cells (MSCs) labeled with clinically approved SPIONs.