Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

RasGAP Shields Akt from Deactivating Phosphatases in Fibroblast Growth Factor Signaling but Loses This Ability Once Cleaved by Caspase-3.

Fibroblast growth factor receptors (FGFRs) are involved in proliferative and differentiation physiological responses. Deregulation of FGFR-mediated signaling involving the Ras/PI3K/Akt and the Ras/Raf/ERK MAPK pathways is causally involved in the development of several cancers. The caspase-3/p120 RasGAP module is a stress sensor switch. Under mild stress conditions, RasGAP is cleaved by caspase-3 at position 455. The resulting N-terminal fragment, called fragment N, stimulates anti-death signaling. When caspase-3 activity further increases, fragment N is cleaved at position 157. This generates a fragment, called N2, that no longer protects cells. Here, we investigated in Xenopus oocytes the impact of RasGAP and its fragments on FGF1-mediated signaling during G2/M cell cycle transition. RasGAP used its N-terminal Src homology 2 domain to bind FGFR once stimulated by FGF1, and this was necessary for the recruitment of Akt to the FGFR complex. Fragment N, which did not associate with the FGFR complex, favored FGF1-induced ERK stimulation, leading to accelerated G2/M transition. In contrast, fragment N2 bound the FGFR, and this inhibited mTORC2-dependent Akt Ser-473 phosphorylation and ERK2 phosphorylation but not phosphorylation of Akt on Thr-308. This also blocked cell cycle progression. Inhibition of Akt Ser-473 phosphorylation and entry into G2/M was relieved by PHLPP phosphatase inhibition. Hence, full-length RasGAP favors Akt activity by shielding it from deactivating phosphatases. This shielding was abrogated by fragment N2. These results highlight the role played by RasGAP in FGFR signaling and how graded stress intensities, by generating different RasGAP fragments, can positively or negatively impact this signaling.

Developing a theoretical framework using a nursing perspective to investigate perceived health in the "Sandwich Generation" group

Coexisting workloads from professional, household and family, and caregiving activities for frail parents expose middle-aged individuals, the so-called "Sandwich Generation", to potential health risks. Current trends suggest that this situation will continue or increase. Thus SG health promotion has become a nursing concern. Most existing research considers coexisting workloads a priori pathogenic. Most studies have examined the association of one, versus two, of these three activities with health. Few studies have used a nursing perspective. This article presents the development of a framework based on a nursing model. We integrated Siegrist's Effort-Reward Imbalance middle-range theory into "Neuman Systems Model". The latter was chosen for its salutogenic orientation, its attention to preventive nursing interventions and the opportunity it provides to simultaneously consider positive and negative perceptions of SG health and SG coexisting workloads. Finally, it facilitated a theoretical identification of health protective factors.

Commentary. The ontogeny of human memory : where are we going ?

In their review, Jabe`s and Nelson provide an update of Nelson's 1995 cognitive neuroscience model of human memory development. Here, we highlight the major changes in perspective after 20 years of advances in our understanding of the neural basis of memory, and advocate the need for more systematic investigations of memory processes across the lifespan, which combine different models and levels of analysis: from genes, to brain to behavior.