Boolean network model predicts cell cycle sequence of fission yeast

A Boolean network model of the cell-cycle regulatory network of fission yeast (Schizosaccharomyces Pombe) is constructed solely on the basis of the known biochemical interaction topology. Simulating the model in the computer, faithfully reproduces the known sequence of regulatory activity patterns along the cell cycle of the living cell. Contrary to existing differential equation models, no parameters enter the model except the structure of the regulatory circuitry. The dynamical properties of the model indicate that the biological dynamical sequence is robustly implemented in the regulatory network, with the biological stationary state G1 corresponding to the dominant attractor in state space, and with the biological regulatory sequence being a strongly attractive trajectory. Comparing the fission yeast cell-cycle model to a similar model of the corresponding network in S. cerevisiae, a remarkable difference in circuitry, as well as dynamics is observed. While the latter operates in a strongly damped mode, driven by external excitation, the S. pombe network represents an auto-excited system with external damping.Comment: 10 pages, 3 figure

Leflunomide in the treatment of patients with early rheumatoid arthritis—results of a prospective non-interventional study

Leflunomide is effective and well tolerated in the treatment of rheumatoid arthritis (RA), however, data on its use in early RA are scarce. This study seeks to evaluate effectiveness and safety of leflunomide in the treatment of early RA in daily practice. This prospective, open-label, non-interventional, multi-center study was carried out over 24 weeks including adults with early RA (≤1 year since diagnosis). Leflunomide treatment was according to label instructions. Three hundred thirty-four patients were included. Disease activity score in 28 joints (DAS28) response (reduction in DAS28 of >1.2 or reduction of >0.6 and a DAS28 of ≤5.1) was 71.9% at week 12 and 84.6% at week 24. 25.0% of patients achieved clinical remission (DAS28 ≤ 2.6). Most frequently reported adverse drug reactions (ADR) were diarrhea (3.0%), nausea (2.4%), hypertension (1.8%), and headache (1.5%). Serious ADR were reported in four patients (1.2%). Leflunomide showed the effectiveness which was to be expected from controlled studies without revealing any new or hitherto unknown side effects. Onset of action was quick and significant improvement of disease was seen after 12 weeks of therapy and at even higher rates after 24 weeks irrespective of the use of a loading dose. Interestingly, the DAS28-remission rate achieved was similar to the rate seen with methotrexate or biologic therapy in other studies

Early start and stop of biologics: has the time come?

Despite considerable advances in the management of rheumatoid arthritis, results are still not satisfactory for all patients. The treatment goal in rheumatoid arthritis is remission, and there currently are numerous conventional and biological medications available to reach this aim. There are also different treatment strategies but with only limited comparative evidence about their efficacies. More patients now achieve remission while on treatment, but it remains elusive in the majority of patients. Treatment-free remission, the ultimate goal of therapy, is only achieved in very few patients; even when this happens, it is most likely due to the natural course of the disease rather than to any specific therapies. Modern treatment is based on the initiation of aggressive therapy as soon as the diagnosis is established, and on modifying or intensifying therapy guided by frequent assessment of disease activity. In this commentary we will discuss the current treatment paradigm as well as the possibility of an induction-maintenance regimen with biological disease-modifying antirheumatic drugs in early rheumatoid arthriti

Rational design of a ligand-controlled protein conformational switch

Design of a regulatable multistate protein is a challenge for protein engineering. Here we design a protein with a unique topology, called uniRapR, whose conformation is controlled by the binding of a small molecule. We confirm switching and control ability of uniRapR in silico, in vitro, and in vivo. As a proof of concept, uniRapR is used as an artificial regulatory domain to control activity of kinases. By activating Src kinase using uniRapR in single cells and whole organism, we observe two unique phenotypes consistent with its role in metastasis. Activation of Src kinase leads to rapid induction of protrusion with polarized spreading in HeLa cells, and morphological changes with loss of cell–cell contacts in the epidermal tissue of zebrafish. The rational creation of uniRapR exemplifies the strength of computational protein design, and offers a powerful means for targeted activation of many pathways to study signaling in living organisms

Molecular Constraints on Synaptic Tagging and Maintenance of Long-Term Potentiation: A Predictive Model

Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of the enzyme protein kinase M (PKM) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by an stimulus sufficient for LTP and learning can "capture" PKM. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKM, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKM. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKM enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKM. Second, cross capture requires the induction of LTD to induce dendritic PKM synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKM inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.Comment: v3. Minor text edits to reflect published versio