Outcomes following formation of a dedicated pediatric liver transplant anesthesia team.

BACKGROUND: Given the complex nature of liver transplant surgery, adult centers typically use a dedicated liver transplant anesthesia team, which has improved patient outcomes. AIMS: Our goal was to determine whether a dedicated pediatric liver transplant anesthesia team was associated with improved patient outcomes. METHODS: This retrospective cohort study analyzed patients who underwent liver transplantation from April 2013 to September 2020 at St. Louis Children's Hospital. The general group (April 2013-December 2016) was compared with the liver group (January 2017-September 2020). Outcomes measured included cases per anesthesiologist, early extubation, ventilator days, fluid and blood administration, postoperative events, and intensive care unit and hospital length of stay (LOS). RESULTS: Patients in both groups had similar demographics. The average number of cases/anesthesiologist/year was 2.9 times higher in the liver group (mean (SD) general 0.7 (0.5), liver 2.0 (0.6), and difference in mean [95% CI] 1.3 [0.8, 1.8]). The rate of extubation in the operating room was higher for patients in the liver group (general 56%, liver 80%, and difference in proportion [95% CI] 24.7 [7.0, 42.4]), while the number of ventilator days was lower (mean (SD) general 2.1 (4.4), liver 1.1 (3.6), and difference in proportion [95%CI] -0.9 [-2.6, 0.7]). Colloid administration was higher in the liver group (mean (SD) general 23.9 (14.5) ml/kg, liver 48.4 (37.7) ml/kg, and difference in mean [95% CI] 24.6 [12.7, 36.4]), while fresh frozen plasma administration was lower in the liver group (mean (SD) general 15.3 (23.9) ml/kg, liver 6.2 (14) ml/kg, and difference in mean [95% CI] -9.0 [-16.8, -1.3]). There were no significant differences between the groups in postoperative events including blood product transfusions, vasopressor use, and thromboses, or in the intensive care unit and hospital LOS. CONCLUSIONS: The liver group was associated with increased early extubations, decreased ventilator days, and decreased fresh frozen plasma use.

Predicting forest fire kernel density at multiple scales with geographically weighted regression in Mexico.

Identifying the relative importance of human and environmental drivers on fire occurrence in different regions and scales is critical for a sound fire management. Nevertheless, studies analyzing fire occurrence spatial patterns at multiple scales, covering the regional to national levels at multiple spatial resolutions, both in the fire occurrence drivers and in fire density, are very scarce. Furthermore, there is a scarcity of studies that analyze the spatial stationarity in the relationships of fire occurrence and its drivers at multiple scales. The current study aimed at predicting the spatial patterns of fire occurrence at regional and national levels in Mexico, utilizing geographically weighted regression (GWR) to predict fire density, calculated with two different approaches -regular grid density and kernel density - at spatial resolutions from 5 to 50 km, both in the dependent and in the independent human and environmental candidate variables. A better performance of GWR, both in goodness of fit and residual correlation reduction, was observed for prediction of kernel density as opposed to regular grid density. Our study is, to our best knowledge, the first study utilizing GWR to predict fire kernel density, and the first study to utilize GWR considering multiple scales, both in the dependent and independent variables. GWR models goodness of fit increased with fire kernel density search radius (bandwidths), but saturation in predictive capacity was apparent at 15-20 km for most regions. This suggests that this scale has a good potential for operational use in fire prevention and suppression decision-making as a compromise between predictive capability and spatial detail in fire occurrence predictions. This result might be a consequence of the specific spatial patterns of fire occurrence in Mexico and should be analyzed in future studies replicating this methodology elsewhere.

Modelling the vertical distribution of canopy fuel load using national forest inventory and low-density airbone laser scanning data.

The fuel complex variables canopy bulk density and canopy base height are often used to predict crown fire initiation and spread. Direct measurement of these variables is impractical, and they are usually estimated indirectly by modelling. Recent advances in predicting crown fire behaviour require accurate estimates of the complete vertical distribution of canopy fuels. The objectives of the present study were to model the vertical profile of available canopy fuel in pine stands by using data from the Spanish national forest inventory plus low-density airborne laser scanning (ALS) metrics. In a first step, the vertical distribution of the canopy fuel load was modelled using the Weibull probability density function. In a second step, two different systems of models were fitted to estimate the canopy variables defining the vertical distributions; the first system related these variables to stand variables obtained in a field inventory, and the second system related the canopy variables to airborne laser scanning metrics. The models of each system were fitted simultaneously to compensate the effects of the inherent cross-model correlation between the canopy variables. Heteroscedasticity was also analyzed, but no correction in the fitting process was necessary. The estimated canopy fuel load profiles from field variables explained 84% and 86% of the variation in canopy fuel load for maritime pine and radiata pine respectively; whereas the estimated canopy fuel load profiles from ALS metrics explained 52% and 49% of the variation for the same species. The proposed models can be used to assess the effectiveness of different forest management alternatives for reducing crown fire hazard.

A molecular role for lysyl oxidase in breast cancer invasion.

We identified previously an up-regulation in lysyl oxidase (LOX) expression,an extracellular matrix remodeling enzyme, in a highly invasive/metastatic human breast cancer cell line, MDA-MB-231, compared with MCF-7, a poorly invasive/nonmetastatic breast cancer cell line. In this study, we demonstrate that the mRNA expression of LOX and other LOX family members [lysyl oxidase-like (LOXL), LOXL2, LOXL3, and LOXL4] was observed only in breast cancer cells with a highly invasive/metastatic phenotype but not in poorly invasive/nonmetastatic breast cancer cells. LOX and LOXL2 showed the strongest association with invasive potential in both highly invasive/metastatic breast cancer cell lines tested (MDA-MB-231 and Hs578T). To determine whether LOX is directly involved in breast cancer invasion, LOX antisense oligonucleotides were transfected into MDA-MB-231 and Hs578T cells, and found to inhibit invasion through a collagen IV/laminin/gelatin matrix in vitro compared with LOX sense oligonucleotide-treated and untreated controls. In addition, treatment of MDA-MB-231 and Hs578T cells with beta-aminopropionitrile (an irreversible inhibitor of LOX enzymatic activity) decreased invasive activity. Conversely, MCF-7 cells transfected with the murine LOX gene demonstrated a 2-fold increase in invasiveness that was reversible by the addition of beta-aminopropionitrile in a dose-dependent manner. In addition, endogenous LOX mRNA expression was induced when MCF-7 cells were cultured in the presence of fibroblast conditioned medium or conditioned matrix, suggesting a role for stromal fibroblasts in LOX regulation in breast cancer cells. Moreover, the correlation of LOX up-regulation and invasive/metastatic potential was additionally demonstrated in rat prostatic tumor cell lines, and human cutaneous and uveal melanoma cell lines. These results provide substantial new evidence that LOX is involved in cancer cell invasion.