Adherent cells exert traction forces on to their environment which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures during developmental morphogenesis. Traction force microscopy (TFM) enables the measurement of traction forces on an elastic substrate and thereby provides quantitative information on cellular mechanics in a perturbation-free fashion. In TFM, traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular tractions in different conditions.

No abstract

PurposeTo investigate the dosimetric impact of point A definitions on both conventional point A plans and MRI-guided conformal high-dose-rate (HDR) brachytherapy plans.Material and methodsFifty-five HDR plans of 36 patients with FIGO stage I to IV cervical cancer were retrospectively studied; these included 30 conventional treatments and 25 conformal plans. Two different point A definitions were explored: the revised Manchester point A and the new point A as recommended by the American Brachytherapy Society. Conventional plans were produced by varying only the point A definition and the normalized isodose lines. Conformal plans were retrospectively generated per GEC-ESTRO recommendations based upon 3.0 Tesla MRI data.ResultsSmall yet significant variations were found in point A locations (mean: 0.5 cm, maximum: 2.1 cm, p < 0.001). The use of a new point A caused minimal dose variation for both conventional and conformal plans. Conventional plans normalized to the new point A generated up to 12% (avg. 1-3%) higher overall dose in terms of higher total reference air kerma than plans normalized to other points. Dosimetric changes due to point A definitions were up to 11-12% (avg. less than 2%) on target volumes or organs-at-risk.ConclusionsFor both conventional and conformal plans, the new point A definition leads to smaller variations caused during implant and/or differences in patient anatomy. Using the new point A is expected to produce more consistent brachytherapy plans and improve outcome analysis.

We review the construction and applications of exactly Poincaré invariant quantum mechanical models of few-degree of freedom systems. We discuss the construction of dynamical representations of the Poincaré group on few-particle Hilbert spaces, the relation to quantum field theory, the formulation of cluster properties, and practical considerations related to the construction of realistic interactions and the solution of the dynamical equations. Selected applications illustrate the utility of this approach.

We investigate the effects of two-body currents on elastic electron-deuteron scattering in an exactly Poincaré invariant quantum mechanical model with a null-plane kinematic symmetry. While calculations using single-nucleon currents as input produce good qualitative agreement with experiment, the two-body current that we investigate produces a good quantitative agreement between theory and experiment for all three elastic scattering observables.

The purpose of this study was to report the characteristics of an equivalent quality unflattened (eqUF) photon beam in clinical implementation and to provide a generalized method to describe unflattened (UF) photon beam profiles. An unflattened photon beam with a beam quality equivalent to the corresponding flat 6 MV photon beam (WF) was obtained by removing the flattening filter from a Siemens ONCOR Avant‐Garde linear accelerator and adjusting the photon energy. A method independent from the WF beam profile was presented to describe UF beam profiles and other selected beam characteristics were examined. The short‐term beam stability was examined by dynamic beam profiles, recorded every 0.072 s in static and gated delivery, and the long‐term stability was evidenced by the five‐year clinical quality assurance records. The dose rate was raised fivefold using the eqUF beam. The depth of maximum dose (normaldmax) shifted 3 mm deeper, but the percent depth dose beyond dmax was very similar to that of the WF beam. The surface dose and out‐of‐field dose were lower, but the penumbra was slightly wider. The variation in head scatter and phantom scatter with changes in field size was smaller; the variation in the profile shape with change in depth was also smaller. The eqUF beam is stable 0.072 s after the beam is turned on, and the five‐year beam stability was comparable to that of the WF beam. A fivefold dose rate increase was observed in the eqUF beam with similar beam characteristics to other reported UF beam data except for a deeper dmax and a slightly wider penumbra. The initial and long‐term stability of the eqUF beam profile is on parity with the WF beam. The UF beam profile can be described in the generalized method independently without relying on the WF beam profile.PACS number: 87.55.de

Adherent biological cells generate traction forces on a substrate that play a central role for migration, mechanosensing, differentiation, and collective behavior. The established method for quantifying this cell-substrate interaction is traction force microscopy (TFM). In spite of recent advancements, inference of the traction forces from measurements remains very sensitive to noise. However, suppression of the noise reduces the measurement accuracy and the spatial resolution, which makes it crucial to select an optimal level of noise reduction. Here, we present a fully automated method for noise reduction and robust, standardized traction-force reconstruction. The method, termed Bayesian Fourier transform traction cytometry, combines the robustness of Bayesian L2 regularization with the computation speed of Fourier transform traction cytometry. We validate the performance of the method with synthetic and real data. The method is made freely available as a software package with a graphical user-interface for intuitive usage.

This study was conducted to analyze the changes in microbial populations of rectal content of dairy cattle with and without ketosis. The plasma β-hydroxybutyric acid (BHBA) levels of 350 cows were measured and twenty-two post-parturient dairy cows with BHBA levels >1.2 mmol/L were selected and diagnosed with ketosis (KET group). According to statistical pairing rule, 22 dairy cows with BHBA levels <0.60 mmol/l formed the control groups (CON group). The profile of the microbial community of the rectal content samples was detected using high-throughput sequencing analysis of hypervariable V4 region of microbe. The average effective sequences of each sample were 84983, ranging from 64090 to 94470. The Principal Co-ordinates Analysis (PCoA) showed that there were distinctly different clusters of the rectal microbial community between KET and CON cows. Beta diversity analysis was evaluated differences in samples of species complexity. At the phylum level, the percentage of Euryarchaeota of the KET cows was less than (P<0.05) in the CON group. At the genus level, the percentages of Ruminococcaceae-UGG-014, Methanobrevibacter, Erysipelotrichaceae-UGG-009, and Atopobium of the KET cows were less than (P<0.05) those found in the CON group. The percentage of Lachnospiraceae was greater (P<0.05) in KET cows compared with CON cows. Lachnospiraceae is related to butyrate production and an increased amount may be an important causative agent of ketosis in dairy cattle. Our findings give a complete picture of current knowledge of the population structure of the rectal microbial ecosystem between KET and CON cows and enhance our understanding about the rectal microbial ecology that may be useful in the prevention of ketosis. , 2019. The influence of ketosis on the rectal microbiome of Chinese Holstein cows. Pak Vet J, 39(2): 175-180. http://dx.