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Background Due to the diverse histopathologic features and variable survival rates seen in sinonasal undifferentiated carcinoma (SNUC), it is likely that this diagnostic entity is comprised of a heterogonous group of morphologically undifferentiated tumors. As advancements in molecular testing have led to a better understanding of tumor biology, it has become increasingly evident that SNUC may actually encompass several tumor subtypes with different clinical behavior. As a result, it is also likely that all SNUC patients cannot be treated in the same fashion. Recent investigations have identified loss of the tumor suppressor SMARCB1 (INI1) expression in a subset of undifferentiated sinonasal tumors and extrasinonasal tumors and, studies have suggested that this genetic aberration may be a poor prognostic marker. The objective of this study was to identify differential expression of SMARCB1 in SNUC and to analyze and compare the survival outcomes in SNUC patients with and without SMARCB1 expression. Methods All cases of undifferentiated or poorly differentiated neoplasms of the sinonasal tract treated between 2007 and 2018 at a single tertiary care institution were selected. All cases of SNUC were tested for SMARCB1 status by immunohistochemistry (IHC). Clinical parameters were analyzed using Student's t -test and Fischer's test. Kaplan-Meier methods were used to estimate survival durations, while comparison between both the subgroups was done using the log-rank test. Statistical analysis was performed with the use of SPSS software, Version 25 (IBM, New York, NY, United States). Results Fourteen cases of SNUC were identified. Approximately two-thirds (64%; n = 9) of patients were male and the majority (79%; n = 11) were between fifth to seventh decade. Skull base and orbital invasion were seen in 79% ( n = 11) and 93% ( n = 13) of cases, respectively. Fifty-seven percent of tumors ( n = 8) retained SMARCB1 expression by IHC (SR-SNUC), while the remaining 43% ( n = 6) showed loss of SMARCB1 expression and, thus, were considered as SMARCB1 -deficient (SD-SNUC). Although clinicopathological features and treatment modalities were similar, SD-SNUC showed poorer (OS: p = 0.07; disease free survival [DFS]: p = 0.02) overall survival (OS) and DFS on Kaplan-Meier curves. Additionally, SD-SNUC showed higher recurrence (75 vs. 17%) and mortality (67 vs. 14%) (hazard rate = 8.562; p = 0.05) rates. Both OS (28.82 ± 31.15 vs. 53.24 ± 37.50) and DFS durations (10.62 ± 10.26 vs. 43.79 ± 40.97) were consistently worse for SD-SNUC. Five-year survival probabilities were lower for SD-SNUC (0.33 vs. 0.85). Conclusion SNUC represents a heterogeneous group of undifferentiated sinonasal malignancies. Based on the status of SMARCB1 expression, the two subgroups SD-SNUC and SR-SNUC appear to represent distinct clinical entities, with loss of SMARCB1 expression conferring an overall worse prognosis.
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Changing climates are altering wildlife habitats and wildlife behavior in complex ways. Here, we examine how changing spring snow cover dynamics and early season forage availability are altering grizzly bear (Ursus arctos) behavior postden emergence. Telemetry data were used to identify spring activity dates for 48 individuals in the Yellowhead region of Alberta, Canada. Spring activity date was related to snow cover dynamics using a daily percent snow cover dataset. Snow melt end date, melt rate, and melt consistency explained 45% of the variation in spring activity date. We applied this activity date model across the entire Yellowhead region from 2000 to 2016 using simulated grizzly bear home ranges. Predicted spring activity date was then compared with a daily spring forage availability date dataset, resulting in "wait time" estimates for four key early season forage species. Temporal changes in both spring activity date and early season forage "wait times" were assessed using non-parametric regression. Grizzly bear activity date was found to have either remained constant (95%) or become earlier (5%) across the study area; virtually no areas with significantly later spring activity dates were detected. Similarly, the majority of "wait times" did not change (85%); however, the majority of significant changes in "wait times" for the four early season forage species indicated that "wait times" were lessening where changes were detected. Our results show that spring activity date is largely dictated by snow melt characteristics and that changing snow melt conditions may result in earlier spring activity. However, early season food stress conditions are likely to remain unchanged or improve as vegetation phenology also becomes earlier. Our findings extend the recent work examining animal movement in response to changing phenology from migratory birds and ungulates to an apex predator, further demonstrating the potential effects of changing climates on wildlife species.
Asunto(s)
Nieve , Ursidae , Alberta , Animales , Ecosistema , Estaciones del AñoRESUMEN
Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines grizzly bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and temporal scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.