The induction of α-helical structure in partially unfolded HypF-N does not affect its aggregation propensity

The conversion of proteins into structured fibrillar aggregates is a central problem in protein chemistry, biotechnology, biology and medicine. It is generally accepted that aggregation takes place from partially structured states of proteins. However, the role of the residual structure present in such conformational states is not yet understood. In particular, it is not yet clear as to whether the α-helical structure represents a productive or counteracting structural element for protein aggregation. We have addressed this issue by studying the aggregation of pH-unfolded HypF-N. It has previously been shown that the two native α-helices of HypF-N retain a partial α-helical structure in the pH-unfolded state and that these regions are also involved in the formation of the cross-β structure of the aggregates. We have introduced mutations in such stretches of the sequence, with the aim of increasing the α-helical structure in the key regions of the pH-unfolded state, while minimizing the changes of other factors known to influence protein aggregation, such as hydrophobicity, β-Sheet propensity, etc. The resulting HypF-N mutants have higher contents of α-helical structure at the site(s) of mutation in their pH-unfolded states, but such an increase does not correlate with a change of aggregation rate. The results suggest that stabilisation of α-helical structure in amyloidogenic regions of the sequence of highly dynamic states does not have remarkable effects on the rate of protein aggregation from such conformational states. Comparison with other protein systems indicate that the effect of increasing α-helical propensity can vary if the stabilised helices are in non-amyloidogenic stretches of initially unstructured peptides (accelerating effect), in amyloidogenic stretches of initially unstructured peptides (no effect) or in amyloidogenic stretches of initially stable helices (decelerating effect

Spintronic magnetic anisotropy

An attractive feature of magnetic adatoms and molecules for nanoscale applications is their superparamagnetism, the preferred alignment of their spin along an easy axis preventing undesired spin reversal. The underlying magnetic anisotropy barrier --a quadrupolar energy splitting-- is internally generated by spin-orbit interaction and can nowadays be probed by electronic transport. Here we predict that in a much broader class of quantum-dot systems with spin larger than one-half, superparamagnetism may arise without spin-orbit interaction: by attaching ferromagnets a spintronic exchange field of quadrupolar nature is generated locally. It can be observed in conductance measurements and surprisingly leads to enhanced spin filtering even in a state with zero average spin. Analogously to the spintronic dipolar exchange field, responsible for a local spin torque, the effect is susceptible to electric control and increases with tunnel coupling as well as with spin polarization.Comment: 6 pages with 4 figures + 26 pages of Supplementary Informatio

Background results for robust minmax control of linear dynamical systems

The purpose of this note is to summarize the arguments required to derive the results appearing in robust minmax control of linear dynamical systems using a quadratic stage cost. The main results required in robust minmax control are Corollary 19 and Proposition 20. Moreover, the solution to the trust-region problem given in Proposition 15 and Lemma 16 may be of more general interest

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

Proteome-wide observation of the phenomenon of life on the edge of solubility

To function effectively proteins must avoid aberrant aggregation, and hence they are expected to be expressed at concentrations safely below their solubility limits. By analyzing proteome-wide mass spectrometry data of Caenorhabditis elegans, however, we show that the levels of about three-quarters of the nearly 4, 000 proteins analyzed in adult animals are close to their intrinsic solubility limits, indeed exceeding them by about 10% on average. We next asked how aging and functional self-assembly influence these solubility limits. We found that despite the fact that the total quantity of proteins within the cellular environment remains approximately constant during aging, protein aggregation sharply increases between days 6 and 12 of adulthood, after the worms have reproduced, as individual proteins lose their stoichiometric balances and the cellular machinery that maintains solubility undergoes functional decline. These findings reveal that these proteins are highly prone to undergoing concentration-dependent phase separation, which on aging is rationalized in a decrease of their effective solubilities, in particular for proteins associated with translation, growth, reproduction, and the chaperone system