Effects of growth factors on the differentiation of murine ESC into type II pneumocytes

We have previously shown that embryonic stem cells (ESC) can be directed to differentiate into alveolar type II cells by provision of a serum-free medium designed for in vitro maintenance of mature alveolar epithelial cells (small airway growth medium: SAGM), although the target cell yield was low. SAGM comprises a basal serum-free medium (SABM) plus a series of defined supplements. In order to try increase the proportion of pneumocytes in differentiated cultures, we aimed in this study to determine the effects on murine ESC of each of the individual growth factors in SAGM. In accordance with our previous reports, expression of surfactant protein C (SPC) and its mRNA was used to monitor differentiation of type II pneumocytes. Surprisingly, we found that addition of each factor separately to SABM decreased the expression of SPC mRNA when compared with the effect of SABM alone. Thus, it seems that the observed enhancement by SAGM of pneumocyte differentiation from murine ESC can, in fact, be attributed to the provision of a serum-free environment. © Mary Ann Liebert, Inc. 2007

Well-Posed Initial-Boundary Evolution in General Relativity

Maximally dissipative boundary conditions are applied to the initial-boundary value problem for Einstein's equations in harmonic coordinates to show that it is well-posed for homogeneous boundary data and for boundary data that is small in a linearized sense. The method is implemented as a nonlinear evolution code which satisfies convergence tests in the nonlinear regime and is robustly stable in the weak field regime. A linearized version has been stably matched to a characteristic code to compute the gravitational waveform radiated to infinity.Comment: 5 pages, 6 figures; added another convergence plot to Fig. 2 + minor change

Development and external validation study of a melanoma risk prediction model incorporating clinically assessed naevi and solar lentigines

Background: Melanoma risk prediction models could be useful for matching preventive interventions to patients’ risk. Objectives: To develop and validate a model for incident first‐primary cutaneous melanoma using clinically assessed risk factors. Methods: We used unconditional logistic regression with backward selection from the Australian Melanoma Family Study (461 cases and 329 controls) in which age, sex and city of recruitment were kept in each step, and we externally validated it using the Leeds Melanoma Case–Control Study (960 cases and 513 controls). Candidate predictors included clinically assessed whole‐body naevi and solar lentigines, and self‐assessed pigmentation phenotype, sun exposure, family history and history of keratinocyte cancer. We evaluated the predictive strength and discrimination of the model risk factors using odds per age‐ and sex‐adjusted SD (OPERA) and the area under curve (AUC), and calibration using the Hosmer–Lemeshow test. Results: The final model included the number of naevi ≥ 2 mm in diameter on the whole body, solar lentigines on the upper back (a six‐level scale), hair colour at age 18 years and personal history of keratinocyte cancer. Naevi was the strongest risk factor; the OPERA was 3·51 [95% confidence interval (CI) 2·71–4·54] in the Australian study and 2·56 (95% CI 2·23–2·95) in the Leeds study. The AUC was 0·79 (95% CI 0·76–0·83) in the Australian study and 0·73 (95% CI 0·70–0·75) in the Leeds study. The Hosmer–Lemeshow test P‐value was 0·30 in the Australian study and < 0·001 in the Leeds study. Conclusions: This model had good discrimination and could be used by clinicians to stratify patients by melanoma risk for the targeting of preventive interventions. What's already known about this topic? Melanoma risk prediction models may be useful in prevention by tailoring interventions to personalized risk levels. For reasons of feasibility, time and cost many melanoma prediction models use self‐assessed risk factors. However, individuals tend to underestimate their naevus numbers. What does this study add? We present a melanoma risk prediction model, which includes clinically‐assessed whole‐body naevi and solar lentigines, and self‐assessed risk factors including pigmentation phenotype and history of keratinocyte cancer. This model performs well on discrimination, the model's ability to distinguish between individuals with and without melanoma, and may assist clinicians to stratify patients by melanoma risk for targeted preventive interventions

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (ly-. ing bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine -learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sen-sitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential

Improved numerical stability of stationary black hole evolution calculations

We experiment with modifications of the BSSN form of the Einstein field equations (a reformulation of the ADM equations) and demonstrate how these modifications affect the stability of numerical black hole evolution calculations. We use excision to evolve both non-rotating and rotating Kerr-Schild black holes in octant and equatorial symmetry, and without any symmetry assumptions, and obtain accurate and stable simulations for specific angular momenta J/M of up to about 0.9M.Comment: 13 pages, 11 figures, 1 typo in Eq. (20) correcte

Onset of Superfluidity in 4He Films Adsorbed on Disordered Substrates

We have studied 4He films adsorbed in two porous glasses, aerogel and Vycor, using high precision torsional oscillator and DC calorimetry techniques. Our investigation focused on the onset of superfluidity at low temperatures as the 4He coverage is increased. Torsional oscillator measurements of the 4He-aerogel system were used to determine the superfluid density of films with transition temperatures as low as 20 mK. Heat capacity measurements of the 4He-Vycor system probed the excitation spectrum of both non-superfluid and superfluid films for temperatures down to 10 mK. Both sets of measurements suggest that the critical coverage for the onset of superfluidity corresponds to a mobility edge in the chemical potential, so that the onset transition is the bosonic analog of a superconductor-insulator transition. The superfluid density measurements, however, are not in agreement with the scaling theory of an onset transition from a gapless, Bose glass phase to a superfluid. The heat capacity measurements show that the non-superfluid phase is better characterized as an insulator with a gap.Comment: 15 pages (RevTex), 21 figures (postscript

Quantum magnetism in two dimensions: From semi-classical N\'eel order to magnetic disorder

This is a review of ground-state features of the s=1/2 Heisenberg antiferromagnet on two-dimensional lattices. A central issue is the interplay of lattice topology (e.g. coordination number, non-equivalent nearest-neighbor bonds, geometric frustration) and quantum fluctuations and their impact on possible long-range order. This article presents a unified summary of all 11 two-dimensional uniform Archimedean lattices which include e.g. the square, triangular and kagome lattice. We find that the ground state of the spin-1/2 Heisenberg antiferromagnet is likely to be semi-classically ordered in most cases. However, the interplay of geometric frustration and quantum fluctuations gives rise to a quantum paramagnetic ground state without semi-classical long-range order on two lattices which are precisely those among the 11 uniform Archimedean lattices with a highly degenerate ground state in the classical limit. The first one is the famous kagome lattice where many low-lying singlet excitations are known to arise in the spin gap. The second lattice is called star lattice and has a clear gap to all excitations. Modification of certain bonds leads to quantum phase transitions which are also discussed briefly. Furthermore, we discuss the magnetization process of the Heisenberg antiferromagnet on the 11 Archimedean lattices, focusing on anomalies like plateaus and a magnetization jump just below the saturation field. As an illustration we discuss the two-dimensional Shastry-Sutherland model which is used to describe SrCu2(BO3)2.Comment: This is now the complete 72-page preprint version of the 2004 review article. This version corrects two further typographic errors (three total with respect to the published version), see page 2 for detail