Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype

Food-offering calls in wild golden lion tamarins (Leontopithecus rosalia) : evidence for teaching behavior?

Many animals emit calls in the presence of food, but researchers do not always know the function of these calls. Evidence suggests that adult golden lion tamarins (Leontopithecus rosalia) use food-offering calls to teach juveniles which substrate (i.e., microhabitat) to forage on, or in, for food. However, we do not yet know whether juveniles learn from this aspect of the adults’ behavior. Here we examine whether juveniles learn to associate food-offering calls with a foraging substrate, as a step toward assessing whether these calls qualify as teaching behavior. We compared the performance of four wild juvenile golden lion tamarins that were introduced to a novel substrate while exposed to playbacks of food-offering calls (experimental condition) to the performance of three juveniles that were exposed to the novel substrate without the presence of food-offering playbacks (control condition). We varied the location of the novel substrate between trials. We found that food-offering calls had an immediate effect on juveniles’ interactions with the novel substrate, whether they inserted their hands into the substrate and their eating behavior, and a long-term effect on eating behavior at the substrate. The findings imply that juvenile golden lion tamarins can learn through food-offering calls about the availability of food at a substrate, which is consistent with (but does not prove) teaching in golden lion tamarins through stimulus enhancement. Our findings support the hypothesis that teaching might be more likely to evolve in cooperatively breeding species with complex ecological niches.Publisher PDFPeer reviewe

Primate responses to changing environments in the anthropocene

Most primates have slow life-histories and long generation times. Because environmental change is occurring at an unprecedented rate, gene-based adaptations are unlikely to evolve fast enough to offer successful responses to these changes. The paper reviews the most common types of habitat/landscape alterations, the extent of human-primate interactions, and the impact of climate change. It demonstrates how understanding behavioural flexibility as a response to environmental change will be crucial to optimize conservation efforts by constructing informed management plans. Comparisons across species, space, and time can be used to draw generalizations about primate responses to environmental change while considering their behavioural flexibility

Data for: Water storage and irrigation practices associated with cannabis production drive seasonal patterns of water extraction and use in Northern California watersheds

2017 water data from the North Coast Regional Water Quality Control Board Cannabis Progra

Change in disturbance regime facilitates invasion by Bellucia pentamera Naudin (Melastomataceae) at Gunung Palung National Park, Indonesia

In tropical rainforests, gaps created by fallen canopy trees are the primary colonization sites for pioneer species. Selective logging mimics these natural disturbances in that only a single tree is felled, creating a gap of comparable size. Rates of tree felling greatly exceed natural mortality rates, however, changing disturbance regime by increasing the number of gaps in logged areas compared to intact forest. Little is known about whether gaps in logged forests are qualitatively different as well. At Gunung Palung National Park in West Kalimantan, Indonesia, a period of selective logging in areas adjacent to the research station created a natural experiment permitting comparison of populations of the invasive pioneer tree Bellucia pentamera in selectively logged and undisturbed forest. We sought to first establish whether canopy gaps are necessary for invasion by B. pentamera. We then examined whether the type of gap (logging vs. natural treefall) had an effect on recruitment. Finally, we compared populations in natural treefall gaps in logged and undisturbed forest to estimate the effect of logging on population size. Bellucia pentamera was limited to gaps, regardless of canopy tree density. Furthermore, gaps created by selective logging supported significantly more B. pentamera individuals than natural gaps. Finally, natural treefall gaps in the disturbed area contained significantly more individuals than gaps in the undisturbed forest. Therefore, it appears that selective logging not only created more gaps for B. pentamera, these gaps in particular promoted greater abundance of this invader and led to a population increase throughout the disturbed habitat

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype. © 2020, The Author(s).Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]