Rapid dynamics of cell-shape recovery in response to local deformations

It is vital that cells respond rapidly to mechanical cues within their microenvironment through changes in cell shape and volume, which rely upon the mechanical properties of cells’ highly interconnected cytoskeletal networks and intracellular fluid redistributions. While previous research has largely investigated deformation mechanics, we now focus on the immediate cell-shape recovery response following mechanical perturbation by inducing large, local, and reproducible cellular deformations using AFM. By continuous imaging within the plane of deformation, we characterize the membrane and cortical response of HeLa cells to unloading, and model the recovery via overdamped viscoelastic dynamics. Importantly, the majority (90%) of HeLa cells recover their cell shape in o1 s. Despite actin remodelling on this time scale, we show that cell-shape recovery time is not affected by load duration, nor magnitude for untreated cells. To further explore this rapid recovery response, we expose cells to cytoskeletal destabilizers and osmotic shock conditions, which uncovers the interplay between actin and osmotic pressure. We show that the rapid dynamics of recovery depend crucially on intracellular pressure, and provide strong evidence that cortical actin is the key regulator in the cell-shape recovery processes, in both cancerous and non-cancerous epithelial cell

The STRS (shortness of breath, tremulousness, racing heart, and sweating): A brief checklist for acute distress with panic-like autonomic indicators; development and factor structure

Background: Peritraumatic response, as currently assessed by Posttraumatic Stress Disorder (PTSD) diagnostic criterion A2, has weak positive predictive value (PPV) with respect to PTSD diagnosis. Research suggests that indicators of peritraumatic autonomic activation may supplement the PPV of PTSD criterion A2. We describe the development and factor structure of the STRS (Shortness of Breath, Tremulousness, Racing Heart, and Sweating), a one page, two-minute checklist with a five-point Likert-type response format based on a previously unpublished scale. It is the first validated self-report measure of peritraumatic activation of the autonomic nervous system.\ud \ud Methods: We selected items from the Potential Stressful Events Interview (PSEI) to represent two latent variables: 1) PTSD diagnostic criterion A, and 2) acute autonomic activation. Participants (a convenience sample of 162 non-treatment seeking young adults) rated the most distressing incident of their lives on these items. We examined the factor structure of the STRS in this sample using factor and cluster analysis.\ud \ud Results: Results confirmed a two-factor model. The factors together accounted for 68% of the variance. The variance in each item accounted for by the two factors together ranged from 41% to 74%. The item loadings on the two factors mapped precisely onto the two proposed latent variables.\ud \ud Conclusion: The factor structure of the STRS is robust and interpretable. Autonomic activation signs tapped by the STRS constitute a dimension of the acute autonomic activation in response to stress that is distinct from the current PTSD criterion A2. Since the PTSD diagnostic criteria are likely to change in the DSM-V, further research is warranted to determine whether signs of peritraumatic autonomic activation such as those measured by this two-minute scale add to the positive predictive power of the current PTSD criterion A2. Additionally, future research is warranted to explore whether the four automatic activation items of the STRS can be useful as the basis for a possible PTSD criterion A3 in the DSM-V

Biopolymer dynamics driven by helical flagella

Microbial flagellates typically inhabit complex suspensions of polymeric material which can impact the swimming speed of motile microbes, filter-feeding of sessile cells, and the generation of biofilms. There is currently a need to better understand how the fundamental dynamics of polymers near active cells or flagella impacts these various phenomena, in particular the hydrodynamic and steric influence of a rotating helical filament on suspended polymers. Our Stokesian dynamics simulations show that as a stationary rotating helix pumps fluid along its long axis, polymers migrate radially inwards while being elongated. We observe that the actuation of the helix tends to increase the probability of finding polymeric material within its pervaded volume. This accumulation of polymers within the vicinity of the helix is stronger for longer polymers. We further analyse the stochastic work performed by the helix on the polymers and show that this quantity is positive on average and increases with polymer contour length.Comment: 14 pages, 6 figure

Lake and catchment-scale determinants of aquatic vegetation across almost 1,000 lakes and the contrasts between lake types

Aim The factors controlling macrophyte (aquatic plant) composition are complex, recent research having shown that the well-studied effects of lake environmental factors (the so-called “environmental filter”) can be constrained by hydrological and landscape factors. We investigated the factors determining macrophyte composition in lakes over water body and catchment- scales and the transferability of this pattern across lake types. Location Almost 1000 lakes distributed across Britain. Taxon Lake macrophytes Methods Lakes were partitioned into five types based on subdivision of alkalinity and elevation gradients. Data from botanical surveys were used to compare the spatial turnover and nestedness components of beta diversity between lake types. The relative importance of lake environment (based on local physicochemical data), hydrology (e.g. lake and stream density), landscape (e.g. fragmentation indices, land cover) and spatial autocorrelation in explaining variation in macrophyte composition were derived from variance partitioning. Results Species composition showed strong spatial structuring, suggestive of overland dispersal, enhanced by spatially-correlated abiotic factors such as alkalinity and elevation. Catchment-scale factors (e.g. land use, connectivity) promoted the establishment of different communities (more or less diverse, or differing in composition) but were of secondary importance. Turnover in composition between upland lakes was lower than in other lake types, reflecting a more specialist flora and increased potential for propagule exchange due to spatial aggregation and higher hydrological connectivity. Main conclusions Vegetation composition in lakes is more spatially-structured than previously appreciated, consistent with the importance of dispersal limitation, but this does not apply evenly to all lakes, being most acute in lowland high alkalinity lakes. Thus, spatially-structured abiotic factors, such as alkalinity, influence macrophyte composition most (suggestive of niche filtering) in high alkalinity lakes where human impacts tend to be greatest, although nestedness was also lowest in such lakes. By contrast, hydrological connectivity has a proportionally stronger structuring role in upland lakes

A 3D-Hybrid-Shot Spiral Sequence for Hyperpolarized 13^{13}C Imaging

Purpose: Hyperpolarized imaging experiments have conflicting requirements of high spatial, temporal, and spectral resolution. Spectral-Spatial RF excitation has been shown to form an attractive magnetization-efficient method for hyperpolarized imaging, but the optimum readout strategy is not yet known. Methods: In this work we propose a novel 3D hybrid-shot spiral sequence which features two constant density regions that permit the retrospective reconstruction of either high spatial or high temporal resolution images post hoc, (adaptive spatiotemporal imaging) allowing greater flexibility in acquisition and reconstruction. Results: We have implemented this sequence, both via simulation and on a pre-clinical scanner, to demonstrate its feasibility, in both a 1H phantom and with hyperpolarized 13C pyruvate in vivo. Conclusion: This sequence forms an attractive method for acquiring hyperpolarized imaging datasets, providing adaptive spatiotemporal imaging to ameliorate the conflict of spatial and temporal resolution, with significant potential for clinical translation

International advocacy for education and safety

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93654/1/pan12008.pd

Smectic Layering: Landau theory for a complex-tensor order parameter

Composed of microscopic layers that stack along one direction while maintaining fluid-like positional disorder within layers, smectics are excellent systems for exploring topology, defects and geometric memory in complex confining geometries. However, the coexistence of crystalline-like characteristics in one direction and fluid-like disorder within layers makes lamellar liquid crystals notoriously difficult to model—especially in the presence of defects and large distortions. Nematic properties of smectics can be comprehensively described by the Q ̲ ̲ -tensor; however, lamellar order can exist independent of nematic alignment. To capture the features of the smectic layering alone, we develop a phenomenological Landau theory for a complex-tensor order parameter E ̲ ̲ , which is capable of describing the local degree of lamellar ordering, layer displacement, and orientation of the layers. This theory accounts for both parallel and perpendicular elastic contributions. In addition to resolving the potential ambiguities inherent to complex scalar order parameter models, this model reduces to previously employed models of simple smectics, and opens new possibilities for numerical studies on smectics possessing many defects, within complex geometries and under extreme confinement

Data Fusion of Remote-sensing and In-lake chlorophyll a Data Using Statistical Downscaling

Chlorophyll a is a green pigment, used as an indirect measure of lake water quality. Its strong absorption of blue and red light allows for quantification through satellite images, providing better spatial coverage than traditional in-lake samples. However, grid-cell scale imagery must be calibrated spatially using in-lake point samples, presenting a change-of-support problem. This paper presents a method of statistical downscaling, namely a Bayesian spatially-varying coefficient regression, which assimilates remotely-sensed and in-lake data, resulting in a fully calibrated spatial map of chlorophyll a with associated uncertainty measures. The model is applied to a case study dataset from Lake Balaton, Hungary