Estimating Age-Dependent Extinction: Contrasting Evidence from Fossils and Phylogenies.

The estimation of diversification rates is one of the most vividly debated topics in modern systematics, with considerable controversy surrounding the power of phylogenetic and fossil-based approaches in estimating extinction. Van Valen's seminal work from 1973 proposed the "Law of constant extinction," which states that the probability of extinction of taxa is not dependent on their age. This assumption of age-independent extinction has prevailed for decades with its assessment based on survivorship curves, which, however, do not directly account for the incompleteness of the fossil record, and have rarely been applied at the species level. Here, we present a Bayesian framework to estimate extinction rates from the fossil record accounting for age-dependent extinction (ADE). Our approach, unlike previous implementations, explicitly models unobserved species and accounts for the effects of fossil preservation on the observed longevity of sampled lineages. We assess the performance and robustness of our method through extensive simulations and apply it to a fossil data set of terrestrial Carnivora spanning the past 40 myr. We find strong evidence of ADE, as we detect the extinction rate to be highest in young species and declining with increasing species age. For comparison, we apply a recently developed analogous ADE model to a dated phylogeny of extant Carnivora. Although the phylogeny-based analysis also infers ADE, it indicates that the extinction rate, instead, increases with increasing taxon age. The estimated mean species longevity also differs substantially, with the fossil-based analyses estimating 2.0 myr, in contrast to 9.8 myr derived from the phylogeny-based inference. Scrutinizing these discrepancies, we find that both fossil and phylogeny-based ADE models are prone to high error rates when speciation and extinction rates increase or decrease through time. However, analyses of simulated and empirical data show that fossil-based inferences are more robust. This study shows that an accurate estimation of ADE from incomplete fossil data is possible when the effects of preservation are jointly modeled, thus allowing for a reassessment of Van Valen's model as a general rule in macroevolution

Familiäre Kavernome des Zentralnervensystems: Eine klinische und genetische Studie an 15 deutsche Familien

Zusammenfassung: 1928 beschrieb Hugo Friedrich Kufs erstmalig eine Familie mit zerebralen, retinalen und kutanen Kavernomen. Mittlerweile wurden über 300 weitere Familien beschrieben. Ebenfalls wurden drei Genloci 7q21-q22 (mit dem Gen CCM1), 7p15-p13 (Gen CCM2) und 3q25.2-q27 (Gen CCM3) beschrieben, in denen Mutationen zu Kavernomen führen. Das Genprodukt von CCM1 ist das Protein Krit1 (Krev Interaction Trapped 1), das über verschiedene Mechanismen mit der Angiogenese interagiert. Das neu entdeckte CCM2-Gen enkodiert ein Protein, das möglicherweise eine dem Krit1 ähnliche Funktion in der Regulation der Angiogenese hat. Das CCM3-Gen wurde noch nicht beschrieben. In dieser Arbeit werden sowohl die klinischen und genetischen Befunde bei 15 deutschen Familien beschriebe

Inherited cavernous malformations of the central nervous system: clinical and genetic features in 19 Swiss families

Cavernous malformations (CCMs) are benign, well-circumscribed, and mulberry-like vascular malformations that may be found in the central nervous system in up to 0.5% of the population. Cavernous malformations can be sporadic or inherited. The common symptoms are epilepsy, hemorrhages, focal neurological deficits, and headaches. However, CCMs are often asymptomatic. The familiar form is associated with three gene loci, namely 7q21-q22 (CCM1), 7p13-p15 (CCM2), and 3q25.2-q27 (CCM3) and is inherited as an autosomal dominant trait with incomplete penetrance. The CCM genes are identified as Krit 1 (CCM1), MGC4607 (CCM2), and PDCD10 (CCM3). Here, we present the clinical and genetic features of CCMs in 19 Swiss families. Furthermore, surgical aspects in such families are also discusse

Long-term efficiency of infliximab in patients with ankylosing spondylitis : real life data confirm the potential for dose reduction

Objective: To analyse the treatment outcome of patients with ankylosing spondylitis (AS) in the European AS infliximab cohort (EASIC) study after a total period of 8 years with specific focus on dosage and the duration of intervals between infliximab infusions. Methods: EASIC included patients with AS who had received infliximab for 2 years as part of the ASSERT trial. After that period, rheumatologists were free to change the dose or the intervals of infliximab. Clinical data were status at baseline, end of ASSERT and for a total of 8 years of follow-up. Results: Of the initially 71 patients with AS from EASIC, 55 patients (77.5%) had completed the 8th year of anti-tumour necrosis factor (TNF) treatment. Of those, 48 patients (87.3%) still continued on infliximab. The mean infusion interval increased slightly from 6 to 7.1 +/- 1.5 weeks, while 45.8% patients had increased the intervals up to a maximum of 12 weeks. The mean infliximab dose remained stable over time, with a minimum of 3.1 mg/kg and a maximum of 6.4 mg/kg. In patients receiving <5 mg/kg infliximab, the mean infusion interval increased to 7.0 +/- 1.2 weeks. In total, the mean cumulative dose per patient and per year decreased from 3566.30 to 2973.60 mg. Conclusions: We could observe that over a follow-up of 8 years of treatment with infliximab, >85% patients still remained on the same treatment, without any major safety events. Furthermore, both the infusion intervals and also the mean infliximab dose were modestly reduced in >= 70% of the patients without the loss of clinical efficiency

Estimating Alpha, Beta, and Gamma Diversity Through Deep Learning

The reliable mapping of species richness is a crucial step for the identification of areas of high conservation priority, alongside other value and threat considerations. This is commonly done by overlapping range maps of individual species, which requires dense availability of occurrence data or relies on assumptions about the presence of species in unsampled areas deemed suitable by environmental niche models. Here, we present a deep learning approach that directly estimates species richness, skipping the step of estimating individual species ranges. We train a neural network model based on species lists from inventory plots, which provide ground truth data for supervised machine learning. The model learns to predict species richness based on spatially associated variables, including climatic and geographic predictors, as well as counts of available species records from online databases. We assess the empirical utility of our approach by producing independently verifiable maps of alpha, beta, and gamma plant diversity at high spatial resolutions for Australia, a continent with highly heterogeneous diversity patterns. Our deep learning framework provides a powerful and flexible new approach for estimating biodiversity patterns, constituting a step forward toward automated biodiversity assessments

Impact of transient groundwater storage on the discharge of Himalayan rivers

International audienceIn the course of the transfer of precipitation into rivers, water is temporarily stored in reservoirs with different residence times such as soils, groundwater, snow and glaciers. In the central Himalaya, the water budget is thought to be primarily controlled by monsoon rainfall, snow and glacier melt, and secondarily by evapotranspiration. An additional contribution from deep groundwater has been deduced from the chemistry of Himalayan rivers, but its importance in the annual water budget remains to be evaluated. Here we analyse records of daily precipitation and discharge within twelve catchments in Nepal over about 30 years. We observe annual hysteresis loops--that is, a time lag between precipitation and discharge--in both glaciated and unglaciated catchments and independent of the geological setting. We infer that water is stored temporarily in a reservoir with characteristic response time of about 45 days, suggesting a diffusivity typical of fractured basement aquifers. We estimate this transient storage capacity at about 28km3 for the three main Nepal catchments; snow and glacier melt contribute around 14km3yr-1, about 10% of the annual river discharge. We conclude that groundwater storage in a fractured basement influences significantly the Himalayan river discharge cycle

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

The past and future human impact on mammalian diversity

To understand the current biodiversity crisis, it is crucial to determine how humans have affected biodiversity in the past. However, the extent of human involvement in species extinctions from the Late Pleistocene onward remains contentious. Here, we apply Bayesian models to the fossil record to estimate how mammalian extinction rates have changed over the past 126,000 years, inferring specific times of rate increases. We specifically test the hypothesis of human-caused extinctions by using posterior predictive methods. We find that human population size is able to predict past extinctions with 96% accuracy. Predictors based on past climate, in contrast, perform no better than expected by chance, suggesting that climate had a negligible impact on global mammal extinctions. Based on current trends, we predict for the near future a rate escalation of unprecedented magnitude. Our results provide a comprehensive assessment of the human impact on past and predicted future extinctions of mammals