Comparison of integrative nature conservation in forest policy in Europe: a qualitative pilot study of institutional determinants

In this pilot study, we examine the relationship between the organisation of property rights and the economic importance of forestry on the one hand and the degree to which integrative nature conservation is formally implemented in forest policy on the other hand. Further, we are interested in whether political institutions moderate this relationship. We first offer a conceptualization of integrative nature conservation in forests and how to measure its implementation in law, ordinances and private agreements for a sample of European national and sub-national jurisdictions (Austria, Croatia, Finland, France, the Netherlands, Switzerland, Flanders, Baden-Württemberg and Piedmont). We subsequently try to assess the implementation of these rules and to relate them both to the structural characteristics of forestry and to an appraisal of pluralism in forest policy. Our qualitative analysis reveals that among the jurisdictions with a more centralized and corporatist forest policy, integrative nature conservation in forests tend to be less formally implemented the more corporatism dominates decision-making. It also confirms the expectation that among the more consensual jurisdictions with a strong forestry sector, rules tend to be less formally implemented. Further, the suspicion prevails that in the latter case, such rules are either complemented with exceptions for private forests or higher compensation. A more in-depth comparative examination is needed to further corroborate these findings

Meta-analysis Reveals Genome-Wide Significance at 15q13 for Nonsyndromic Clefting of Both the Lip and the Palate, and Functional Analyses Implicate GREM1 As a Plausible Causative Gene

Nonsyndromic orofacial clefts are common birth defects with multifactorial etiology. The most common type is cleft lip, which occurs with or without cleft palate (nsCLP and nsCLO, respectively). Although genetic components play an important role in nsCLP, the genetic factors that predispose to palate involvement are largely unknown. In this study, we carried out a meta-analysis on genetic and clinical data from three large cohorts and identified strong association between a region on chromosome 15q13 and nsCLP (P = 8.13×10−14 for rs1258763; relative risk (RR): 1.46, 95% confidence interval (CI): 1.32–1.61)) but not nsCLO (P = 0.27; RR: 1.09 (0.94–1.27)). The 5 kb region of strongest association maps downstream of Gremlin-1 (GREM1), which encodes a secreted antagonist of the BMP4 pathway. We show during mouse embryogenesis, Grem1 is expressed in the developing lip and soft palate but not in the hard palate. This is consistent with genotype-phenotype correlations between rs1258763 and a specific nsCLP subphenotype, since a more than two-fold increase in risk was observed in patients displaying clefts of both the lip and soft palate but who had an intact hard palate (RR: 3.76, CI: 1.47–9.61, Pdiff<0.05). While we did not find lip or palate defects in Grem1-deficient mice, wild type embryonic palatal shelves developed divergent shapes when cultured in the presence of ectopic Grem1 protein (P = 0.0014). The present study identified a non-coding region at 15q13 as the second, genome-wide significant locus specific for nsCLP, after 13q31. Moreover, our data suggest that the closely located GREM1 gene contributes to a rare clinical nsCLP entity. This entity specifically involves abnormalities of the lip and soft palate, which develop at different time-points and in separate anatomical regions.Clefts of the lip and palate are common birth defects, and require long-term multidisciplinary management. Their etiology involves genetic factors and environmental influences and/or a combination of both, however, these interactions are poorly defined. Moreover, although clefts of the lip may or may not involve the palate, the determinants predisposing to specific subphenotypes are largely unknown. Here we demonstrate that variations in the non-coding region near the GREM1 gene show a highly significant association with a particular phenotype in which cleft lip and cleft palate co-occ

Adjunctive Volasertib in Patients With Acute Myeloid Leukemia not Eligible for Standard Induction Therapy : A Randomized, Phase 3 Trial

In this phase 3 trial, older patients with acute myeloid leukemia ineligible for intensive chemotherapy were randomized 2:1 to receive the polo-like kinase inhibitor, volasertib (V; 350 mg intravenous on days 1 and 15 in 4-wk cycles), combined with low-dose cytarabine (LDAC; 20 mg subcutaneous, twice daily, days 1-10; n = 444), or LDAC plus placebo (P; n = 222). Primary endpoint was objective response rate (ORR); key secondary endpoint was overall survival (OS). Primary ORR analysis at recruitment completion included patients randomized >= 5 months beforehand; ORR was 25.2% for V+LDAC and 16.8% for P+LDAC (n = 371; odds ratio 1.66 [95% confidence interval (CI), 0.95-2.89]; P = 0.071). At final analysis (>= 574 OS events), median OS was 5.6 months for V+LDAC and 6.5 months for P+LDAC (n = 666; hazard ratio 0.97 [95% CI, 0.8-1.2]; P = 0.757). The most common adverse events (AEs) were infections/infestations (grouped term; V+LDAC, 81.3%; P+LDAC, 63.5%) and febrile neutropenia (V+LDAC, 60.4%; P+LDAC, 29.3%). Fatal AEs occurred in 31.2% with V+LDAC versus 18.0% with P+LDAC, most commonly infections/infestations (V+LDAC, 17.1%; P+LDAC, 6.3%). Lack of OS benefit with V+LDAC versus P+LDAC may reflect increased early mortality with V+LDAC from myelosuppression and infections.Peer reviewe

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models\u27 performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe\u27s common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.Peer reviewe

High throughput screening for discovery of materials that control stem cell fate

Insights into the complex stem cell niche have identified the cell–material interface to be a potent regulator of stem cell fate via material properties such as chemistry, topography and stiffness. In light of this, materials scientists have the opportunity to develop bioactive materials for stem cell culture that elicit specific cellular responses. To accelerate materials discovery, high throughput screening platforms have been designed which can rapidly evaluate combinatorial material libraries in two and three-dimensional environments. In this review, we present screening platforms for the discovery of material properties that influence stem cell behavior

Targeting breast cancer stem cells

The cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self‐renewing CSC population that is also capable of differentiating into non‐self‐renewing cell populations that constitute the bulk of the tumor. Although, the CSC hypothesis does not directly address the cell of origin of cancer, it is postulated that tissue‐resident stem or progenitor cells are the most common targets of transformation. Clinically, CSCs are predicted to mediate tumor recurrence after chemo‐ and radiation‐therapy due to the relative inability of these modalities to effectively target CSCs. If this is the case, then CSC must be efficiently targeted to achieve a true cure. Similarities between normal and malignant stem cells, at the levels of cell‐surface proteins, molecular pathways, cell cycle quiescence, and microRNA signaling present challenges in developing CSC‐specific therapeutics. Approaches to targeting CSCs include the development of agents targeting known stem cell regulatory pathways as well as unbiased high‐throughput siRNA or small molecule screening. Based on studies of pathways present in normal stem cells, recent work has identified potential “Achilles heals” of CSC, whereas unbiased screening provides opportunities to identify new pathways utilized by CSC as well as develop potential therapeutic agents. Here, we review both approaches and their potential to effectively target breast CSC.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135704/1/mol2201045404.pd

Fly Photoreceptors Encode Phase Congruency

More than five decades ago it was postulated that sensory neurons detect and selectively enhance behaviourally relevant features of natural signals. Although we now know that sensory neurons are tuned to efficiently encode natural stimuli, until now it was not clear what statistical features of the stimuli they encode and how. Here we reverse-engineer the neural code of Drosophila photoreceptors and show for the first time that photoreceptors exploit nonlinear dynamics to selectively enhance and encode phase-related features of temporal stimuli, such as local phase congruency, which are invariant to changes in illumination and contrast. We demonstrate that to mitigate for the inherent sensitivity to noise of the local phase congruency measure, the nonlinear coding mechanisms of the fly photoreceptors are tuned to suppress random phase signals, which explains why photoreceptor responses to naturalistic stimuli are significantly different from their responses to white noise stimuli