Bacterial inner membrane remodelling by force generation of FtsZ fibres

In this work, we aim to understand the behaviour of filaments and bundles of filaments in the presence of diffusible cross-linkers; we posit that these are analogues of the structures present in the Z-ring, with special focus on E. coli. Then, we study these structures by constructing a mathematical model based on statistical mechanics, and analysing its behaviour under different ranges of parameters. We show that the ring-like geometry of the division plane is conducive to constriction, and that this effect can be potentialised by the dynamics of depolymerisation. Furthermore, we show that percolating bundles of filaments are also capable of constriction, and that percolation is necessary but not sufficient for a contractile force to arise. Finally, we investigate how such a model can originate percolating bundles of filaments and how to maximise the contractile potential of such bundles. Concomitantly, we investigate the mutant ftsZ84, an E. coli mutant with uncommon properties that might help us understand the relationship between FtsZ assembly and bacterial cell division, by using a new experimental approach. Though the results prove inconclusive, we were able to confirm that the activity of this mutant agrees with the published literature

Touching proteins with virtual bare hands : visualizing protein–drug complexes and their dynamics in self-made virtual reality using gaming hardware

The ability to precisely visualize the atomic geometry of the interactions between a drug and its protein target in structural models is critical in predicting the correct modifications in previously identified inhibitors to create more effective next generation drugs. It is currently common practice among medicinal chemists while attempting the above to access the information contained in three-dimensional structures by using two-dimensional projections, which can preclude disclosure of useful features. A more accessible and intuitive visualization of the three-dimensional configuration of the atomic geometry in the models can be achieved through the implementation of immersive virtual reality (VR). While bespoke commercial VR suites are available, in this work, we present a freely available software pipeline for visualising protein structures through VR. New consumer hardware, such as the HTC Vive and the Oculus Rift utilized in this study, are available at reasonable prices. As an instructive example, we have combined VR visualization with fast algorithms for simulating intramolecular motions of protein flexibility, in an effort to further improve structure-led drug design by exposing molecular interactions that might be hidden in the less informative static models. This is a paradigmatic test case scenario for many similar applications in computer-aided molecular studies and design

erickmartins/L0Smoothing: 0.0.0

Preliminary release specifically for Zenodo

erickmartins/auto_qc: 0.10.0

Added support to multiseries files

erickmartins/auto_qc: 0.12.0 - OMERO is here!

All routines now have OMERO functionality - retrieve data from OMERO automatically, process it, save results back to the server

Collective behavior and the identification of phases in bicycle pelotons

As an aggregate of cyclists, a peloton exhibits collective behavior similar to flocking birds or schooling fish. Positional analysis of cyclists in mass-start velodrome races allows quantitative descriptions of peloton phases based on observational data. Data from two track races are analyzed. Peloton density correlates well with cyclists’ collective power output in two clear phases, one of low density, and one of high density. The low density “stretched” phase generally indicates low frequency positional-change and single-file synchronization. The high density “compact” phase may be further divided into two phases, one of which is a laterally synchronized phase, and another is a high frequency and magnitude positional-change phase. Phases may be sub-divided further into acceleration and deceleration regimes, but these are not quantified here. A basic model of peloton division and its implications for general flocking behavior are discussed

ome/omero-cli-transfer: 0.8.0 - new `--simple` option in `pack`

What's Changed Human readable pack by @erickmartins in https://github.com/ome/omero-cli-transfer/pull/65 Full Changelog: https://github.com/ome/omero-cli-transfer/compare/0.7.3...0.8.