46 research outputs found
Thermomechanical consequences of Cretaceous continent-continent collision in the eastern Alps (Austria): insights from two-dimensional modeling.
Single Molecule Statistics and the Polynucleotide Unzipping Transition
We present an extensive theoretical investigation of the mechanical unzipping
of double-stranded DNA under the influence of an applied force. In the limit of
long polymers, there is a thermodynamic unzipping transition at a critical
force value of order 10 pN, with different critical behavior for homopolymers
and for random heteropolymers. We extend results on the disorder-averaged
behavior of DNA's with random sequences to the more experimentally accessible
problem of unzipping a single DNA molecule. As the applied force approaches the
critical value, the double-stranded DNA unravels in a series of discrete,
sequence-dependent steps that allow it to reach successively deeper energy
minima. Plots of extension versus force thus take the striking form of a series
of plateaus separated by sharp jumps. Similar qualitative features should
reappear in micromanipulation experiments on proteins and on folded RNA
molecules. Despite their unusual form, the extension versus force curves for
single molecules still reveal remnants of the disorder-averaged critical
behavior. Above the transition, the dynamics of the unzipping fork is related
to that of a particle diffusing in a random force field; anomalous,
disorder-dominated behavior is expected until the applied force exceeds the
critical value for unzipping by roughly 5 pN.Comment: 40 pages, 18 figure
Single-molecule experiments in biological physics: methods and applications
I review single-molecule experiments (SME) in biological physics. Recent
technological developments have provided the tools to design and build
scientific instruments of high enough sensitivity and precision to manipulate
and visualize individual molecules and measure microscopic forces. Using SME it
is possible to: manipulate molecules one at a time and measure distributions
describing molecular properties; characterize the kinetics of biomolecular
reactions and; detect molecular intermediates. SME provide the additional
information about thermodynamics and kinetics of biomolecular processes. This
complements information obtained in traditional bulk assays. In SME it is also
possible to measure small energies and detect large Brownian deviations in
biomolecular reactions, thereby offering new methods and systems to scrutinize
the basic foundations of statistical mechanics. This review is written at a
very introductory level emphasizing the importance of SME to scientists
interested in knowing the common playground of ideas and the interdisciplinary
topics accessible by these techniques. The review discusses SME from an
experimental perspective, first exposing the most common experimental
methodologies and later presenting various molecular systems where such
techniques have been applied. I briefly discuss experimental techniques such as
atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers
(MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I
then present several applications of SME to the study of nucleic acids (DNA,
RNA and DNA condensation), proteins (protein-protein interactions, protein
folding and molecular motors). Finally, I discuss applications of SME to the
study of the nonequilibrium thermodynamics of small systems and the
experimental verification of fluctuation theorems. I conclude with a discussion
of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond.
Matt
Effects of Inhibition of Interleukin-6 Signalling on Insulin Sensitivity and Lipoprotein (A) Levels in Human Subjects with Rheumatoid Diseases
Interleukin-6 (IL-6) is a pro-inflammatory cytokine that has been found to be increased in type 2 diabetic subjects. However, it still remains unclear if these elevated IL-6 levels are co-incidental or if this cytokine is causally related to the development of insulin resistance and type 2 diabetes in humans. Therefore, in the present study we examined insulin sensitivity, serum adipokine levels and lipid parameters in human subjects before and after treatment with the IL-6 receptor antibody Tocilizumab.11 non-diabetic patients with rheumatoid disease were included in the study. HOMA-IR was calculated and serum levels for leptin, adiponectin, triglycerides, LDL-cholesterol, HDL-cholesterol and lipoprotein (a) (Lp (a)) were measured before as well as one and three months after Tocilizumab treatment. The HOMA index for insulin resistance decreased significantly. While leptin concentrations were not altered by inhibition of IL-6 signalling, adiponectin concentrations significantly increased. Thus the leptin to adiponectin ratio, a novel marker for insulin resistance, exhibited a significant decrease. Serum triglycerides, LDL-cholesterol and HDL-cholesterol tended to be increased whereas Lp (a) levels significantly decreased.Inhibition of IL-6 signalling improves insulin sensitivity in humans with immunological disease suggesting that elevated IL-6 levels in type 2 diabetic subjects might be causally involved in the pathogenesis of insulin resistance. Furthermore, our data indicate that inhibition of IL-6 signalling decreases Lp (a) serum levels, which might reduce the cardiovascular risk of human subjects
Qualitative und quantitative Risikobeurteilung sowie Risikoaggregation : kritische Überlegungen aus der Unternehmenspraxis
PeerReviewe
Demographic, anthropometric and clinical characteristics of the study population.
<p>BMI = body mass index, f = female, m = male. Means ± SEM.</p
Effect of IL-6 inhibition on lipoprotein (a) levels in human subjects.
<p>Data are expressed as Means ± SEM of lipoprotein (a) levels x-fold compared to time point 0 month. * = p<0.05.</p
Effect of IL-6 inhibition on insulin sensitivity of human subject.
<p>Data are expressed as Means ± SEM. * = p<0.05.</p
Effect of IL-6 inhibition on body weight and adipokine serum levels in human subjects.
<p>Data are expressed as Means ± SEM. * = p<0.05.</p
