Molecular Model Systems in the Lepidoptera

1995 ◽  
Keyword(s):  
Molecular Model ◽  
Model Systems

scholarly journals Tamoxifen-induced ER-α–SRC-3 interaction in HER2 positive human breast cancer; a possible mechanism for ER isoform specific recurrence

2006 ◽  
Vol 13 (4) ◽  
pp. 1135-1145 ◽  
Author(s):  
Marie Mc Ilroy ◽  
Fergal J Fleming ◽  
Yvonne Buggy ◽  
Arnold D K Hill ◽  
Leonie S Young
Keyword(s):  
Breast Cancer ◽  
Growth Factor ◽  
Cell Cultures ◽  
Human Breast Cancer ◽  
Molecular Model ◽  
Steroid Receptor ◽  
Model Systems ◽  
Endocrine Treatment ◽  
Human Breast ◽  
Her2 Positive

Differential signalling between the two oestrogen receptor (ER) isoforms in the presence of tamoxifen has been described. We hypothesise that differential recruitment of the steroid receptor co-activator, SRC-3 to ER-α and ER-β may in part explain associations between ER isoforms and response to endocrine treatment. SRC-3 was localised within epithelial cells of breast tumour tissue and was co-localised with ER-α and ER-β, (n = 112). Expression of SRC-3 was found to be positively associated with ER-α (P = 0.0021) and inversely with ER-β (P < 0.0001). Uniquely, this study utilises primary cell cultures derived from patient tumours, thus providing samples not readily available in most molecular model systems. These samples have enabled us to investigate the influence of growth factor pathways on steroid receptor-co-activator interactions. In HER2 (human epidermal growth factor receptor 2) positive primary tumour cell cultures 17β-estradiol induced a decrease in SRC-3, whereas upregulated SRC-3 expression. Furthermore, treatment with tamoxifen-induced SRC-3 recruitment to the ER-oestrogen response element and enhanced interaction between SRC-3 and ER-α, but not ER-β. Knockdown of SRC-3 results in a concomitant loss of expression of the oestrogen target gene pS2. Furthermore, silencing of SRC-3 resensitizes endocrine resistant, HER2 positive cells to the anti-proliferative effects of tamoxifen. The ability of ER-α, but not ER-β to recruit SRC-3 in the presence of tamoxifen may in part explain the differential ER isoform associations with recurrence in human breast cancer.

Molecular Model Systems in the Lepidoptera

Science ◽  
1995 ◽  
Vol 269 (5231) ◽  
pp. 1743-1743 ◽  
Author(s):  
J. B. Nardi
Keyword(s):  
Molecular Model ◽  
Model Systems

On a Direct Superconducting Pairing Mechanism

1999 ◽  
Vol 54 (12) ◽  
pp. 718-738 ◽  
Author(s):  
Michael C. Böhm ◽  
Christoph Saal
Keyword(s):  
Molecular Model ◽  
Hard Core ◽  
Quantum Statistics ◽  
Model Systems ◽  
Cooper Pairs ◽  
Superconducting Transition ◽  
Electron Phonon Coupling ◽  
The Stability ◽  
Superconducting Pairing ◽  
Two Parameter

Abstract We suggest that superconductivity can be traced back to a first-order interaction between the charge carriers which does not necessarily involve second-order electron-phonon coupling. For small molecular model systems it is demonstrated that the formation of Cooper pairs can lead to an attenuation of the destabilizing influence of the Pauli antisymmetry principle (PAP). We suggest that this attenuation of a fermionic quantum constraint is the driving force for the superconducting transition. Whenever the PAP is activated in single-particle hoppings of electrons, the corresponding moves reduce the electronic derealization; they raise the ensemble energy. The stability of a fermionic system is enhanced with decreasing influence of the PAP. Moves of Cooper pairs are not influenced by any quantum constraint of the intersite type. This behaviour differs from the well-known fermionic constraints. The quantum statistics of Cooper pairs is of a mixed type combining a fermionic on-site and a bosonic intersite behaviour. It coincides with the quantum statistics of so-called hard core bosonic ensembles. In the present work Cooper pair formation has been studied for smaller molecular models. The electronic Hamiltonian employed is of the two-parameter Hubbard-type. The solid state phenomenon superconductivity is correlated with the molecular concepts of “antiaromaticity” and “aromaticity”. Arguments are given which support the present interpretation.

scholarly journals Chemotactic network responses to live bacteria show independence of phagocytosis from chemoreceptor sensing

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Netra Pal Meena ◽  
Alan R Kimmel
Keyword(s):  
Intracellular Signaling ◽  
Molecular Model ◽  
High Sensitivity ◽  
Signal Propagation ◽  
Model Systems ◽  
Food Sources ◽  
Signaling Networks ◽  
Live Bacteria ◽  
Unicellular Organisms ◽  
Multiple Ligands

Aspects of innate immunity derive from characteristics inherent to phagocytes, including chemotaxis toward and engulfment of unicellular organisms or cell debris. Ligand chemotaxis has been biochemically investigated using mammalian and model systems, but precision of chemotaxis towards ligands being actively secreted by live bacteria is not well studied, nor has there been systematic analyses of interrelationships between chemotaxis and phagocytosis. The genetic/molecular model Dictyostelium and mammalian phagocytes share mechanistic pathways for chemotaxis and phagocytosis; Dictyostelium chemotax toward bacteria and phagocytose them as food sources. We quantified Dictyostelium chemotaxis towards live gram positive and gram negative bacteria and demonstrate high sensitivity to multiple bacterially-secreted chemoattractants. Additive/competitive assays indicate that intracellular signaling-networks for multiple ligands utilize independent upstream adaptive mechanisms, but common downstream targets, thus amplifying detection at low signal propagation, but strengthening discrimination of multiple inputs. Finally, analyses of signaling-networks for chemotaxis and phagocytosis indicate that chemoattractant receptor-signaling is not essential for bacterial phagocytosis.

scholarly journals In vivo inducible reverse genetics in patients’ tumors to identify individual therapeutic targets

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michela Carlet ◽  
Kerstin Völse ◽  
Jenny Vergalli ◽  
Martin Becker ◽  
Tobias Herold ◽  
...  
Keyword(s):  
Value Chain ◽  
Reverse Genetics ◽  
High Throughput Sequencing ◽  
Molecular Model ◽  
Therapeutic Targets ◽  
Model Systems ◽  
Precision Oncology ◽  
Acute Leukemias ◽  
Anti Cancer

AbstractHigh-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ERT2-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator MCL1 (myeloid cell leukemia sequence 1) correlates to pharmacological MCL1 inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the MLL-AF4 (mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation. DUX4 (double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described DUX4-IGH (immunoglobulin heavy chain) translocation, while the downstream mediator DDIT4L (DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.

The Origin of Biological Information

1997 ◽  
Vol 161 ◽  
pp. 443-453 ◽  
Author(s):  
Manfred Eigen
Keyword(s):  
Natural Selection ◽  
Genetic Information ◽  
Charles Darwin ◽  
Molecular Model ◽  
Molecular Complexes ◽  
Living System ◽  
Model Systems ◽  
Biological Information ◽  
Equilibrium Process ◽  
Controlled Reproduction

What is the distinguishing feature of a living system that singularizes it from every non-living chemical ensemble, regardless of the extent of the complexity? The differentiable characteristic of the living system is information. Information assures the controlled reproduction of all the constituents, thereby ensuring the conservation of viability. Information – unlike energy – is not subject to a conservation law. Hence the fundamental question behind the origin of life is: How can information originate?Information theory, which was pioneered by Claude Shannon, cannot answer this question: this theory is most successful in dealing with problems of coding and transmission. In principle, the answer was formulated 130 years ago by Charles Darwin: The information that is unique for life evolves by virtue of natural selection. Today we can be more specific: natural selection is a non-equilibrium process. It is an inherent consequence of mutagenous self-replication at several levels of organization: for instance it is evident in molecules such as nucleic acids, in molecular complexes such as viruses and in autonomous formes of life such as micro- or higher organisms. New physical concepts have been introduced in order to deal quantitatively with the dynamics of the molecular generation of genetic information. They provide a physical foundation for Darwinian behaviour, yet they introduce major modifications in its interpretation. The lecture deals with these physical concepts, such as «sequence space», «quasi-species» and «hypercycles» and will scrutinize their adequacy for rationalizing experimental results obtained with molecular model systems and with viruses under natural conditions. Elucidating the principles of molecular self-organization has made possible to construct automated machines that make it possible for genetic information to evolve under controlled conditions in an abridged time scale.

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