The xylanase introns from Cryptococcus albidus are accurately spliced in transgenic tobacco plants

The xylanase gene from Cryptococcus albidus contains seven introns. Genomic and cDNA clones under the control of the CaMV 35S promoter were transferred into tobacco plants using Agrobacterium-mediated cell transformation. The genes were transcribed and the mRNAs were amplified by the polymerase chain reaction using primers on each side of the intron region. About 90% of the amplification products from plants transformed with the genomic clone corresponded to the size of the pre-mRNA (1.2 kb) and 10% represented the spliced product (0.85 kb). The 0.85 kb fragment was cloned and sequenced and the result indicated that the introns from the xylanase gene were accurately spliced by the plant cells.     

Dermenkephalin and deltorphin I reveal similarities within ligand-binding domains of mu- and delta-opioid receptors and an additional address subsite on the delta-receptor.

Dermorphin (Tyr-D-Ala-Phe-Gly-Tyr-Pro-Ser-NH2), dermenkephalin (Tyr-D-Met-Phe-His-Leu-Met-Asp-NH2) and deltorphin I (Tyr-D-Ala-Phe-Asp-Val-Val-Gly-NH2) are the first naturally occurring peptides highly potent for and almost specific to the mu- and delta-opioid receptors, respectively. The amino-terminal domains Tyr-D-X-Phe (where X is either Ala or Met) of these peptides behave as selective and potent mu-receptor ligands. Routing of Tyr-D-X-Phe to the delta- or the mu- receptor is associated with the presence or the absence at the C-terminus of an additional hydrophobic and negatively charged tetrapeptide by-passing the mu-addressing ability of the amino-terminal moiety. A study of 20 Tyr-D-X-Phe-Y-NH2 analogs with substitution of X and Y by neutral, hydrophobic, aromatic amino acids as well as by charged amino acid residues shows that tetrapeptides maintain high binding affinity and selectivity for the mu-opioid receptor. Although residue in position 4 serves a delta-address function, the tripeptide motif at the C-terminus of dermenkephalin and deltorphin I are critical components for high selectivity at delta-opioid receptor. Results demonstrate that mu- and delta-opioid receptors share topologically equivalent ligand-binding domains, or ligand-binding sequences similarities, that recognized Tyr-D-X-Phe as a consensus message-binding sequence. The delta-receptor additionally contains a unique address subsite at or near the conserved binding domain that accommodates the C-terminal tetrapeptide motif of dermenkephalin and deltorphin I.     

Human glioma tumour-associated antigens

Conclusion From this brief review it appears that at least three categories of human glioma-associated antigens may exist. The first seems to be restricted and common to gliomas. The second is shared between gliomas, normal adult brain, and fetal brain. The third is present on cells from adult and fetal tissue and on cells from tumours derived from the neural crest. The expression of glioma-associated antigens is highly variable from one tumour, or tumour cell line, to another, and reflects the phenotypic heterogeneity of the glioma group. Moreover, this heterogeneity has been found in different clones of individual glioma cell lines [1]. The fact that gliomas share some antigens with normal brain is of critical importance for immunodiagnosis or immunotherapy. It is evident that active immunotherapy for gliomas should be performed with cultured cells and not with tumour extracts, because such extracts may contain MBP.The exact nature of the various glioma-associated antigens remains to be clearly defined, however. They may belong to a group of surface glycoproteins such as those described by Lloyd et al. [24] for melanoma or more recently by Lubitz et al. [25] for glial cells.     

Non-monotonic effects of GABAergic synaptic inputs on neuronal firing

GABA is generally known as the principal inhibitory neurotransmitter in the nervous system, usually acting by hyperpolarizing membrane potential. However, GABAergic currents sometimes exhibit non-inhibitory effects, depending on the brain region, developmental stage or pathological condition. Here, we investigate the diverse effects of GABA on the firing rate of several single neuron models, using both analytical calculations and numerical simulations. We find that GABAergic synaptic conductance and output firing rate exhibit three qualitatively different regimes as a function of GABA reversal potential, E_GABA: monotonically decreasing for sufficiently low E_GABA (inhibitory), monotonically increasing for E_GABA above firing threshold (excitatory); and a non-monotonic region for intermediate values of E_GABA. In the non-monotonic regime, small GABA conductances have an excitatory effect while large GABA conductances show an inhibitory effect. We provide a phase diagram of different GABAergic effects as a function of GABA reversal potential and glutamate conductance. We find that noisy inputs increase the range of E_GABA for which the non-monotonic effect can be observed. We also construct a micro-circuit model of striatum to explain observed effects of GABAergic fast spiking interneurons on spiny projection neurons, including non-monotonicity, as well as the heterogeneity of the effects. Our work provides a mechanistic explanation of paradoxical effects of GABAergic synaptic inputs, with implications for understanding the effects of GABA in neural computation and development.     

Modelling the Human Immune System by Combining Bioinformatics and Systems Biology Approaches

Over the past decade a number of bioinformatics tools have been developed that use genomic sequences as input to predict to which parts of a microbe the immune system will react, the so-called epitopes. Many predicted epitopes have later been verified experimentally, demonstrating the usefulness of such predictions. At the same time, simulation models have been developed that describe the dynamics of different immune cell populations and their interactions with microbes. These models have been used to explain experimental findings where timing is of importance, such as the time between administration of a vaccine and infection with the microbe that the vaccine is intended to protect against. In this paper, we outline a framework for integration of these two approaches. As an example, we develop a model in which HIV dynamics are correlated with genomics data. For the first time, the fitness of wild type and mutated virus are assessed by means of a sequence-dependent scoring matrix, derived from a BLOSUM matrix, that links protein sequences to growth rates of the virus in the mathematical model. A combined bioinformatics and systems biology approach can lead to a better understanding of immune system-related diseases where both timing and genomic information are of importance.     

Targeting head and neck tumoral stem cells: From biological aspects to therapeutic perspectives

Head and neck squamous cell cancer(HNSCC) is the sixth most common cancer in the world. Effective therapeutic modalities such as surgery, radiation, chemotherapy and combinations of each are used in the management of the disease. In most cases, treatment fails to obtain total cancer cure. In recent years, it appears that one of the key determinants of treatment failure may be the presence of cancer stem cells(CSCs) that escape currently available therapies. CSCs form a small portion of the total tumor burden but may play a disproportionately important role in determining outcomes. CSCs have stem features such as self-renewal, high migration capacity, drug resistance, high proliferation abilities. A large body of evidence points to the fact that CSCs are particularly resistant to radiotherapy and chemotherapy. In HNSCC, CSCs have been increasingly shown to have an integral role in tumor initiation, disease progression, metastasis and treatment resistance. In the light of such observations, the present review summarizes biological characteristics of CSCs in HNSCC, outlines targeted strategies for the successful eradication of CSCs in HNSCC including targeting the self-renewal controlling pathways, blocking epithelial mesenchymal transition, niche targeting, immunotherapy approaches and highlights the need to better understand CSCs biology for new treatments modalities.     

How life‐history traits affect ecosystem properties: effects of dispersal in meta‐ecosystems

The concept of life‐history traits and the study of these traits are the hallmark of population biology. Acknowledging their variability and evolution has allowed us to understand how species adapt in response to their environment. The same traits are also involved in how species alter ecosystems and shape their dynamics and functioning. Some theories, such as the metabolic theory of ecology, ecological stoichiometry or pace‐of‐life theory, already recognize this junction, but only do so in an implicitly non‐spatial context. Meanwhile, for a decade now, it has been argued that ecosystem properties have to be understood at a larger scale using meta‐ecosystem theory because source–sink dynamics, community assembly and ecosystem stability are all modified by spatial structure. Here, we argue that some ecosystem properties can be linked to a single life‐history trait, dispersal, i.e. the tendency of organisms to live, compete and reproduce away from their birth place. By articulating recent theoretical and empirical studies linking ecosystem functioning and dynamics to species dispersal, we aim to highlight both the known connections between life‐history traits and ecosystem properties and the unknown areas, which deserve further empirical and theoretical developments.