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Simple Summary: Chemotherapy-induced neuropathy is a major clinical problem, with limited treatments available to try to reverse it. Some preliminary data suggested that palmitoylethanolamide (PEA) may effectively treat this condition. Pursuant to this, a placebo-controlled, double-blind, randomized phase 2 clinical trial was developed to look for evidence to support a future, more definitive phase 3 clinical trial. Eighty-nine patients participated in this clinical trial. Unfortunately, the data from the present phase 2 trial did not support the idea that PEA was useful in this situation. Background: Chemotherapy-induced peripheral neuropathy (CIPN) from oxaliplatin and taxane drugs is a bothersome toxicity. Palmitoylethanolamide (PEA) has been reported to improve myelinated nerve fiber function in patients experiencing painful CIPN. We conducted a double-blind, placebo-controlled, randomized trial of PEA in patients with established CIPN. Methods: Eligible patients were adults who had pain, numbness, tingling, or other symptoms of CIPN for at least three months following completion of paclitaxel, oxaliplatin, or cisplatin-based chemotherapy. Study patients were randomized to one of the two treatment groups (PEA versus placebo, both administered either once or twice daily). The CIPN20 questionnaire was assessed weekly. Results: A total of 17 males and 71 females participated in the study; most had neuropathy from paclitaxel. Most (85%) finished 8 weeks of treatment. There was no suggestion that either of the PEA arms did any better than the combined placebo arms. There was no signal of significant toxicity differences between the three study arms. Quality of life outcome measures were similar between the study arms, as were cognitive function evaluations. Discussion: PEA failed to improve established CIPN. Future trials might explore whether PEA may be effective in preventing CIPN or cognitive changes based on data that suggest it may be helpful in this situation. Conclusions: PEA failed to improve established chemotherapy-induced neuropathy. [ABSTRACT FROM AUTHOR]

The carbonate chemistry of sea ice is known to play a role in global carbon cycles, but its importance is uncertain in part due to disparities in reported results. Variability in physical and biological drivers is usually invoked to explain differences between studies. In the Canadian Arctic Archipelago, "invisible polynyas" – areas of strong currents, thin ice, and potentially high biological productivity – are examples of extreme spatial variability. We used an invisible polynya as a natural laboratory to study the effects of inferred initial ice formation conditions, ice growth rate, and algal biomass on the distribution of carbonate species by collecting enough cores to perform a statistical comparison between sites located within, and just outside of, a polynya near Iqaluktuttiaq (Cambridge Bay, Nunavut, Canada). At both sites, the uppermost 10 cm ice horizon showed evidence of CO 2 off-gassing, while carbonate distributions in the middle and bottommost 10 cm horizons largely followed the salinity distribution. In the polynya, the upper ice horizon had significantly higher bulk total inorganic carbon (TIC), total alkalinity (TA), and salinity potentially due to freeze-up conditions that favoured frazil ice production. The middle ice horizons were statistically indistinguishable between sites, suggesting that ice growth rate is not an important factor for the carbonate distribution under mid-winter conditions. The thicker (non-polynya) site experienced higher algal biomass, TIC, and TA in the bottom horizon. Carbonate chemistry in the bottom horizon could largely be explained by the salinity distribution, with the strong currents at the polynya site potentially playing a role in desalinization; biology appeared to exert only a minor control, with some evidence that the ice algae community was net heterotrophic. We did see evidence of calcium carbonate precipitation but with little impact on the TIC:TA ratio and little difference between sites. Because differences were constrained to relatively thin layers at the top and bottom, vertically averaged values of TIC, TA, and especially the TIC:TA ratio were not meaningfully different between sites. This provides some justification for using a single bulk value for each parameter when modelling sea ice effects on ocean chemistry at coarse resolution. Exactly what value to use (particularly for the TIC:TA ratio) likely varies by region but could potentially be approximated from knowledge of the source seawater and sea ice salinity. Further insights await a rigorous intercomparison of existing data. [ABSTRACT FROM AUTHOR]

Two satellite datasets are used to characterize winter landfast first-year sea-ice (FYI), deformed FYI (DFYI) and multiyear sea-ice (MYI) roughness in the Canadian Arctic Archipelago (CAA): (1) optical Multi-angle Imaging SpectroRadiometer (MISR) and (2) synthetic aperture radar Sentinel-1. The Normalized Difference Angular Index (NDAI) roughness proxy derived from MISR, and backscatter from Sentinel-1 are intercompared. NDAI and backscatter are also compared to surface roughness derived from an airborne LiDAR track covering a subset of FYI and MYI (no DFYI). Overall, NDAI and backscatter are significantly positively correlated when all ice type samples are considered. When individual ice types are evaluated, NDAI and backscatter are only significantly correlated for DFYI. Both NDAI and backscatter are correlated with LiDAR-derived roughness (r = 0.71 and r = 0.74, respectively). The relationship between NDAI and roughness is greater for MYI than FYI, whereas for backscatter and ice roughness, the relationship is greater for FYI than MYI. Linear regression models are created for the estimation of FYI and MYI roughness from NDAI, and FYI roughness from backscatter. Results suggest that using a combination of Sentinel-1 backscatter for FYI and MISR NDAI for MYI may be optimal for mapping winter sea-ice roughness in the CAA. [ABSTRACT FROM AUTHOR]

In an inflammatory setting, macrophages can be polarized to an inflammatory M1 phenotype or to an anti-inflammatory M2 phenotype, as well as existing on a spectrum between these two extremes. Dysfunction of this phenotypic switch can result in a population imbalance that leads to chronic wounds or disease due to unresolved inflammation. Therapeutic interventions that target macrophages have therefore been proposed and implemented in diseases that feature chronic inflammation such as diabetes mellitus and atherosclerosis. We have developed a model for the sequential influx of immune cells in the peritoneal cavity in response to a bacterial stimulus that includes macrophage polarization, with the simplifying assumption that macrophages can be classified as M1 or M2. With this model, we were able to reproduce the expected timing of sequential influx of immune cells and mediators in a general inflammatory setting. We then fit this model to in vivo experimental data obtained from a mouse peritonitis model of inflammation, which is widely used to evaluate endogenous processes in response to an inflammatory stimulus. Model robustness is explored with local structural and practical identifiability of the proposed model a posteriori. Additionally, we perform sensitivity analysis that identifies the population of apoptotic neutrophils as a key driver of the inflammatory process. Finally, we simulate a selection of proposed therapies including points of intervention in the case of delayed neutrophil apoptosis, which our model predicts will result in a sustained inflammatory response. Our model can therefore provide hypothesis testing for therapeutic interventions that target macrophage phenotype and predict outcomes to be validated by subsequent experimentation. [ABSTRACT FROM AUTHOR]

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Abstract: Spring melt pond fraction (fp) has been shown to influence September sea ice extent and, with a growing need to improve melt pond physics in climate and forecast models, observations at large spatial scales are needed. We present a novel technique for estimating fp on sea ice at high spatial resolution from the Sentinel‐1 satellite during the winter period leading up to spring melt. A strong correlation (r = −0.85) is found between winter radar backscatter and fp from first‐year and multiyear sea ice data collected in the Canadian Arctic Archipelago (CAA) in 2015. Observations made in the CAA in 2016 are used to validate a fp retrieval algorithm, and a fp prediction for the CAA in 2017 is made. The method is effective using the horizontal transmit and receive polarization channel only and shows promise for providing seasonal, pan‐Arctic, fp maps for improved understanding of melt pond distributions and forecast model skill. [ABSTRACT FROM AUTHOR]

In this work, we present a mathematical model, which accounts for two fundamental processes involved in the repair of an acute dermal wound. These processes include the inflammatory response and fibroplasia. Our system describes each of these events through the time evolution of four primary species or variables. These include the density of initial damage, inflammatory cells, fibroblasts and deposition of new collagen matrix. Since it is difficult to populate the equations of our model with coefficients that have been empirically derived, we fit these constants by carrying out a large number of simulations until there is reasonable agreement between the time response of the variables of our system and those reported by the literature for normal healing. Once a suitable choice of parameters has been made, we then compare simulation results with data obtained from clinical investigations. While more data is desired, we have a promising first step towards describing the primary events of wound repair within the confines of an implantable system. [ABSTRACT FROM PUBLISHER]

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance. [ABSTRACT FROM AUTHOR]

The complex interactions that characterize acute wound healing have stymied the development of effective therapeutic modalities. The use of computational models holds the promise to improve our basic approach to understanding the process. By modifying an existing ordinary differential equation model of systemic inflammation to simulate local wound healing, we expect to improve the understanding of the underlying complexities of wound healing and thus allow for the development of novel, targeted therapeutic strategies. The modifications in this local acute wound healing model include: evolution from a systemic model to a local model, the incorporation of fibroblast activity, and the effects of tissue oxygenation. Using these modifications we are able to simulate impaired wound healing in hypoxic wounds with varying levels of contamination. Possible therapeutic targets, such as fibroblast death rate and rate of fibroblast recruitment, have been identified by computational analysis. This model is a step toward constructing an integrative systems biology model of human wound healing. [ABSTRACT FROM AUTHOR]

Certain inhaled chemicals, such as reactive, water-soluble gases, are readily absorbed by the nasal mucosa upon inhalation and may cause damage to the nasal epithelium. Comparisons of the spatial distribution of nasal lesions in laboratory animals exposed to formaldehyde with gas uptake rates predicted by computational models reveal that lesions usually occur in regions of the susceptible epithelium where gas absorption is highest. Since the uptake patterns are influenced by air currents in the nose, interindividual variability in nasal anatomy and ventilation rates due to age, body size, and gender will affect the patterns of gas absorption in humans, potentially putting some age groups at higher risk when exposed to toxic gases. In this study, interhuman variability in the nasal dosimetry of reactive, water-soluble gases was investigated by means of computational fluid dynamics (CFD) models in 5 adults and 2 children, aged 7 and 8 years old. Airflow patterns were investigated for allometrically scaled inhalation rates corresponding to resting breathing. The spatial distribution of uptake at the airway walls was predicted to be nonuniform, with most of the gas being absorbed in the anterior portion of the nasal passages. Under the conditions of these simulations, interhuman variability in dose to the whole nose (mass per time per nasal surface area) due to differences in anatomy and ventilation was predicted to be 1.6-fold among the 7 individuals studied. Children and adults displayed very similar patterns of nasal gas uptake; no significant differences were noted between the two age groups. [ABSTRACT FROM AUTHOR]

Ice-marginal glaciated landscapes demarcate former boundaries of the continental ice sheets. Throughout circumpolar regions, permafrost has preserved relict ground ice and glacigenic sediments, delaying the sequence of postglacial landscape change that transformed temperate environments millennia earlier. Here we show that within 7 × 106 km2 of glaciated permafrost terrain, extensive landscapes remain poised for major climate-driven change. Across northwestern Canada, 60-100-km-wide concentric swaths of thaw slump-affected terrain delineate the maximum and recessional positions of the Laurentide Ice Sheet. These landscapes comprise ~17% of continuous permafrost terrain in a 1.27 × 106 km2 study area, indicating widespread preservation of late Pleistocene ground ice. These thaw slump, relict ground ice, and glacigenic terrain associations are also evident at the circumpolar scale. Recent intensification of thaw slumping across northwestern Canada has mobilized primary glacial sediments, triggering a cascade of fluvial, lacustrine, and coastal effects. These geologically significant processes, highlighted by the spatial distribution of thaw slumps and patterns of fluvial sediment mobilization, signal the climate-driven renewal of deglaciation and postglacial permafrost landscape evolution. [ABSTRACT FROM AUTHOR]