Lung Cancers: Parenchymal Biochemistry and Mechanics.

Parenchyma of pulmonary cancers acquires contractile properties that resemble those of muscles but presents some particularities. These non-muscle contractile tissues could be stimulated either electrically or chemically (KCl). They present the Frank-Starling mechanism, the Hill hyperbolic tension-velocity relationship, and the tridimensional time-independent tension-velocity-length relationship. Relaxation could be obtained by the inhibition of crossbridge molecular motors or by a decrease in the intracellular calcium concentration. They differ from muscles in that their kinetics are ultraslow as evidenced by their low shortening velocity and myosin ATPase activity. Contractility is generated by non-muscle myosin type II A and II B. The activation of the ß-catenin/WNT pathway is accompanied by the high level of the non-muscle myosin observed in lung cancers.

A Bi-Spectral Microbolometer Sensor for Wildfire Measurement.

This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of the fire radiative power (FRP; W) retrievals suggest that this novel system is highly reliable for use in collecting radiometric measurements of biomass burning. As such, this study provides clear experimental evidence that mid-wave infrared microbolometers are capable of collecting FRP measurements. Furthermore, given the low resource nature of this detector type, it presents a suitable option for monitoring wildfire behaviour from low resource platforms such as unmanned aerial vehicles (UAVs) or nanosats.

An observation-based scaling model for climate sensitivity estimates and global projections to 2100.

We directly exploit the stochasticity of the internal variability, and the linearity of the forced response to make global temperature projections based on historical data and a Green's function, or Climate Response Function (CRF). To make the problem tractable, we take advantage of the temporal scaling symmetry to define a scaling CRF characterized by the scaling exponent H, which controls the long-range memory of the climate, i.e. how fast the system tends toward a steady-state, and an inner scale τ ≈ 2   years below which the higher-frequency response is smoothed out. An aerosol scaling factor and a non-linear volcanic damping exponent were introduced to account for the large uncertainty in these forcings. We estimate the model and forcing parameters by Bayesian inference which allows us to analytically calculate the transient climate response and the equilibrium climate sensitivity as: 1 . 7 - 0.2 + 0.3   K and 2 . 4 - 0.6 + 1.3   K respectively (likely range). Projections to 2100 according to the RCP 2.6, 4.5 and 8.5 scenarios yield warmings with respect to 1880-1910 of: 1 . 5 - 0.2 + 0.4 K , 2 . 3 - 0.5 + 0.7   K and 4 . 2 - 0.9 + 1.3   K. These projection estimates are lower than the ones based on a Coupled Model Intercomparison Project phase 5 multi-model ensemble; more importantly, their uncertainties are smaller and only depend on historical temperature and forcing series. The key uncertainty is due to aerosol forcings; we find a modern (2005) forcing value of [ - 1.0 , - 0.3 ] Wm - 2 (90 % confidence interval) with median at - 0.7 Wm - 2 . Projecting to 2100, we find that to keep the warming below 1.5 K, future emissions must undergo cuts similar to RCP 2.6 for which the probability to remain under 1.5 K is 48 %. RCP 4.5 and RCP 8.5-like futures overshoot with very high probability.

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting?

In theory, the same sea-ice models could be used for both research and operations, but in practice, differences in scientific and software requirements and computational and human resources complicate the matter. Although sea-ice modeling tools developed for climate studies and other research applications produce output of interest to operational forecast users, such as ice motion, convergence, and internal ice pressure, the relevant spatial and temporal scales may not be sufficiently resolved. For instance, sea-ice research codes are typically run with horizontal resolution of more than 3 km, while mariners need information on scales less than 300 m. Certain sea-ice processes and coupled feedbacks that are critical to simulating the Earth system may not be relevant on these scales; and therefore, the most important model upgrades for improving sea-ice predictions might be made in the atmosphere and ocean components of coupled models or in their coupling mechanisms, rather than in the sea-ice model itself. This paper discusses some of the challenges in applying sea-ice modeling tools developed for research purposes for operational forecasting on short time scales, and highlights promising new directions in sea-ice modeling.

Projected polar bear sea ice habitat in the Canadian Arctic Archipelago.

BACKGROUND: Sea ice across the Arctic is declining and altering physical characteristics of marine ecosystems. Polar bears (Ursus maritimus) have been identified as vulnerable to changes in sea ice conditions. We use sea ice projections for the Canadian Arctic Archipelago from 2006 - 2100 to gain insight into the conservation challenges for polar bears with respect to habitat loss using metrics developed from polar bear energetics modeling. PRINCIPAL FINDINGS: Shifts away from multiyear ice to annual ice cover throughout the region, as well as lengthening ice-free periods, may become critical for polar bears before the end of the 21st century with projected warming. Each polar bear population in the Archipelago may undergo 2-5 months of ice-free conditions, where no such conditions exist presently. We identify spatially and temporally explicit ice-free periods that extend beyond what polar bears require for nutritional and reproductive demands. CONCLUSIONS/SIGNIFICANCE: Under business-as-usual climate projections, polar bears may face starvation and reproductive failure across the entire Archipelago by the year 2100.

Cerebral ischemia during carotid artery cross-clamping: predictive value of phase-contrast magnetic resonance imaging.

The goal of this prospective study was to determine the utility of preoperative cerebral magnetic resonance imaging (MRI) in predicting cerebral ischemia during carotid artery cross-clamping for endarterectomy. Between January 2000 and December 2003, a total of 121 patients (95 men, 26 women) underwent three-dimensional phase-contrast MRI to assess collateral function prior to carotid endarterectomy. During regional anesthesia, patients were monitored to detect ischemic events and their timing in relation to cross-clamping and to determine mean intraoperative arterial pressure. These findings were then correlated with the collateral variations observed in the circle of Willis on preoperative MRI. Patients were classified into three groups according to neurological tolerance: normal tolerance (n = 106), immediate severe deficit (n = 9), and late deficit associated with arterial hypotension (n = 6). In the second group, a significant correlation was found between the absence of collateral circulation and neurological deficit (p < .0001). These results indicated that three-dimensional phase-contrast MRI is useful for predicting cerebral ischemia during carotid cross-clamping and selecting indications for shunting. Absence of visible collaterals of the circle of Willis on MRI is significantly predictive of early ischemia and an indication for systematic shunt placement.