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As human visitation to recreational areas increases, wildlife can alter their space use or activity periods to avoid humans. Short-term or gradual variation in human visitation within and across years makes it challenging to assess species responses. We used data from 156 cameras deployed on and off trails (within 50 m) in Isle Royale National Park (IRNP), Michigan, USA, during 2020–2021 to assess diel activity, temporal overlap, and space use of four wildlife species in response to human visitation and wolves. While visitation in both years was greatest in June–August, there were 338 % more human visitors in 2021 than when COVID-19 pandemic visitor restrictions were active in 2020. Space use for all species decreased within and between years as human visitation increased. From 2020–2021, on-trail animal detections decreased while off-trail detections remained constant. As visitation declined late season, red fox (Vulpes vulpes) and wolf (Canis lupus) detection rates increased on trails while snowshoe hare (Lepus americanus) and moose (Alces alces) remained low or declined further. Moose, snowshoe hare, and red fox diel overlap with humans decreased with increasing visitation as animals became more nocturnal. Red fox and moose overlap with humans and wolves decreased from 2020 to 2021. On-trail detections declined when human activity intensity increased while off-trail detections remained relatively constant, suggesting human activity influenced species’ space use along trails only. Reducing visitation during the peak visitor season or redistributing the number of visitors across the overall visitor season could reduce mammalian responses to human visitation.

Herbivores affect plants via direct consumption, but also indirectly via changes in the vegetation. These indirect effects may only manifest after decades of exposure and, as a result, their impact is rarely accounted for. To better understand the direct and indirect impacts of a large herbivore, moose (Alces alces), on forests, we measured tree growth in areas that were both subjected to and excluded from herbivory for over 80 years. Growth data were gathered from five tree species, ranging from low to high palatability. We found that at small sizes, Betula papyrifera, a preferred species, benefited from herbivore exclusion. However, larger individuals grew more when exposed to herbivory, a response we attribute to lower competition in heavily browsed conditions. Populus tremuloides, a highly preferred tree, did not show any differences between levels of herbivory. Abies balsamea, a preferred winter browsed, was only marginally affected by browsing at smaller sizes. The two non- preferred species, Picea glauca and Picea mariana, did not show differential growth between herbivory levels. We conclude that herbivores can impact forests through both direct and indirect effects, that these effects are size specific, and that effects vary among species in ways not always predicted by consumption patterns. Key words: Abies, Alces alces, Betula, Isle Royale National Park, Picea, Populus, Introduction Understanding the forces impacting ecological communities is critical for evaluating their current and future functioning. In the case of forest ecosystems, which are essential for humans in terms of [...]

Abstract Background Imatinib mesylate, a selective inhibitor of Abl tyrosine kinase, is efficacious in treating chronic myeloid leukaemia (CML) and Ph+ acute lymphoblastic leukaemia (ALL). However, most advanced-phase CML and Ph+ ALL patients relapse on Imatinib therapy. Several mechanisms of refractoriness have been reported, including the activation of the Src-family kinases (SFK). Here, we investigated the biological effect of the new specific dual Src/Abl kinase inhibitor AZD0530 on Ph+ leukaemic cells. Methods Cell lines used included BV173 (CML in myeloid blast crisis), SEM t(4;11), Ba/F3 (IL-3 dependent murine pro B), p185Bcr-Abl infected Ba/F3 cells, p185Bcr-Abl mutant infected Ba/F3 cells, SupB15 (Ph+ ALL) and Imatinib resistant SupB15 (RTSupB15) (Ph+ ALL) cells. Cells were exposed to AZD0530 and Imatinib. Cell proliferation, apoptosis, survival and signalling pathways were assessed by dye exclusion, flow cytometry and Western blotting respectively. Results AZD0530 specifically inhibited the growth of, and induced apoptosis in CML and Ph+ ALL cells in a dose dependent manner, but showed only marginal effects on Ph- ALL cells. Resistance to Imatinib due to the mutation Y253F in p185Bcr-Abl was overcome by AZD0530. Combination of AZD0530 and Imatinib showed an additive inhibitory effect on the proliferation of CML BV173 cells but not on Ph+ ALL SupB15 cells. An ongoing transphosphorylation was demonstrated between SFKs and Bcr-Abl. AZD0530 significantly down-regulated the activation of survival signalling pathways in Ph+ cells, resistant or sensitive to Imatinib, with the exception of the RTSupB15. Conclusion Our results indicate that AZD0530 targets both Src and Bcr-Abl kinase activity and reduces the leukaemic maintenance by Bcr-Abl.

Due to the disproportionate role that large carnivores can have on communities and their global decline over the last century, carnivores are increasingly being repatriated across their historic ranges. The reintroduction of gray wolves (Canis lupus) can precipitate substantive changes to communities and ecosystems. Notably, wolves could have strong effects on smaller and subordinate carnivores, especially in altering their foraging behavior and prey selection. Past studies investigating wolf effects on other carnivores, however, have generally been conducted in relatively complex communities featuring a diverse assemblage of carnivores and prey and have lacked baseline (i.e. pre-repatriation) data. Consequently, researchers have quantified what a community looks like after wolf return, with little information on how the community behaved before. To better understand the effect of large carnivore repatriation on the foraging ecology of a carnivore community, we investigated the impact of reintroduced gray wolves on 2 meso-carnivores: Red Fox (Vulpes vulpes); and American Marten (Martes americana) within an insular and simple vertebrate community at Isle Royale National Park before and after wolf reintroduction. We analyzed >600 scats from 20 individual martens and 63 individual foxes as well as the stable isotopes of 9 and 22 tissue samples from martens and foxes, respectively, at both individual and population levels. We found that the wolf reintroduction had little effect on marten diet but strongly influenced fox diet depending on the analysis conducted. At the population level, our analysis revealed that both foxes and martens were dietary generalists consuming an array of food items including small prey, berries, and human food regardless of wolf presence. However, at the individual level, we found that prior to wolf repatriation foxes primarily consumed berries and small prey but following wolf repatriation the diet of foxes shifted to berries and human foods as well as large carrion. This post-wolf reintroduction shift in diet increased the dietary overlap between foxes and martens. Our work provides new insights into how the return of a large carnivore can alter the foraging ecology of small-bodied carnivores and act both to provision carrion resources as well drive other carnivores to consume more human food and increase dietary overlap. [ABSTRACT FROM AUTHOR]

Abstract Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective tool to monitor these levels in order to make appropriate decisions regarding insulin administration and food intake to keep BG levels in target range. Effectively and accurately predicting future BG levels at multi-time steps ahead benefits a patient with diabetes by helping them decrease the risks of extremes in BG including hypo- and hyperglycemia. In this study, we present a novel multi-component deep learning model BG-Predict that predicts the BG levels in a multi-step look ahead fashion. The model is evaluated both quantitatively and qualitatively on actual blood glucose data for 97 patients. For the prediction horizon (PH) of 30 mins, the average values for root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and normalized mean squared error (NRMSE) are $$23.22 \pm 6.39$$ 23.22 ± 6.39 mg/dL, 16.77 ± 4.87 mg/dL, $$12.84 \pm 3.68$$ 12.84 ± 3.68 and $$0.08 \pm 0.01$$ 0.08 ± 0.01 respectively. When Clarke and Parkes error grid analyses were performed comparing predicted BG with actual BG, the results showed average percentage of points in Zone A of $$80.17 \pm 9.20$$ 80.17 ± 9.20 and $$84.81 \pm 6.11,$$ 84.81 ± 6.11 , respectively. We offer this tool as a mechanism to enhance the predictive capabilities of algorithms for patients with T1D.