The hypothalamo-hypophysial system in Acipenseridae

Summary The proximal neurosecretory contact region (PCR) of Acipenseridae, a homologue of the tetrapod median eminence, has been studied by light, fluorescence and electron microscopy. It occupies the rostral and chiefly the ventral surfaces of the hypothalamic tuber cinereum. PAF-positive fibres occur in the zone of the preoptico-hypophysial tract but their terminal enlargements are concentrated mainly in the external zone. They make contact with the primary portal capillaries situated in the pia mater. Monoaminergic fibres and terminals with an intense green fluorescence are localized in the same regions. The fibres of some bipolar monoaminergic neurons of the PCR make contact both with the third ventricle and the primary portal capillaries.Three types of granule-containing neurosecretory fibres and terminals have been recognized in the PCR. Fibres of types A₁ (d=120–300 nm) and A₂ (d=100–170 nm) are peptidergic PAF-positive, although some fibres, including some of type A₁; belong possibly to PAF-negative type. Monoaminergic type B fibres have granules 80–100 nm in diameter. Neurosecretory terminals and vascular endfeet of tanycytes make contact with the 70 nm thick outer basement membrane of the primary portal capillaries. Several laminae of thin horizontally oriented tanycyte processes form a boundary between the external zone and the preoptico-hypophysial tract. Few neuroglial cells with pale cytoplasm, numerous lysosomes and lipofuscin granules are seen in this region. It is hypothesized that, as in other vertebrates, both peptide hypophysiotropic neurohormones and monoamines are discharged from the PCR into the portal circulation and affect the activity of the glandular cells of the pars distalis.Dedicated to Prof. Dr. Drs. h.c. W. Bargmann on the occasion of his 70th birthday     

LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions

LncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA‐miRNA interactions from CLIP‐seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA‐miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA‐miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k‐fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 ± 0.0032, 0.8960 ± 0.0015 and 0.9069 ± 0.0014 on 2‐fold, 5‐fold and 10‐fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA‐miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non‐coding RNA regulation network that lncRNA and miRNA are involved in.     

Fusion protein of the hyaluronan binding domain from human TSG-6 with luciferase for assay of hyaluronan

The gene expression plasmid, pET-Lmluc, for the fusion protein of the hyaluronan binding domain from human TSG-6 [product of tumor necrosis factor (TNF)-stimulated gene-6] and luciferase from Renilla reniformis was constructed. The fused gene was expressed in Escherichia coli and the resulted insoluble Lm-luc fusion protein was purified and refolded to recover both the hyaluronan binding capability and the luciferase activity. Hyaluronan as low as 1 ng ml^–1 was detected by using the indirect enzymatic immunological assay with the refolded Lm-luc fusion protein.     

Functional response of the small multidrug resistance protein EmrE to mutations in transmembrane helix 2

Escherichia coli EmrE is a small multidrug resistance protein encompassing four transmembrane (TM) sequences that oligomerizes to confer resistance to antimicrobials. Here we examined the effects on in vivo protein accumulation and ethidium resistance activity of single residue substitutions at conserved and variable positions in EmrE transmembrane segment 2 (TM2). We found that activity was reduced when conserved residues localized to one TM2 surface were replaced. Our findings suggest that conserved TM2 positions tolerate greater residue diversity than conserved sites in other EmrE TM sequences, potentially reflecting a source of substrate polyspecificity.     

Association Models for Clustered Data with Binary and Continuous Responses

Summary .  We consider analysis of clustered data with mixed bivariate responses, i.e., where each member of the cluster has a binary and a continuous outcome. We propose a new bivariate random effects model that induces associations among the binary outcomes within a cluster, among the continuous outcomes within a cluster, between a binary outcome and a continuous outcome from different subjects within a cluster, as well as the direct association between the binary and continuous outcomes within the same subject. For the ease of interpretations of the regression effects, the marginal model of the binary response probability integrated over the random effects preserves the logistic form and the marginal expectation of the continuous response preserves the linear form. We implement maximum likelihood estimation of our model parameters using standard software such as PROC NLMIXED of SAS . Our simulation study demonstrates the robustness of our method with respect to the misspecification of the regression model as well as the random effects model. We illustrate our methodology by analyzing a developmental toxicity study of ethylene glycol in mice.