Evaluating the legacy of landscape history: extinction debt and species credit in bird and small mammal assemblages in the Brazilian Atlantic Forest

There is now an extensive literature on extinction debt following deforestation. However, the potential for species credit in landscapes that have experienced a change from decreasing to expanding forest cover has received little attention. Both delayed responses should depend on current landscape forest cover and on species life-history traits, such as longevity, as short-lived species are likely to respond faster than long-lived species. We evaluated the effects of historical and present-day local forest cover on two vertebrate groups with different longevities understorey birds and non-flying small mammals - in forest patches at three Atlantic Forest landscapes. Our work investigated how the probability of extinction debt and species credit varies (i) amongst landscapes with different proportions of forest cover and distinct trajectories of forest cover change, and (ii) between taxa with different life spans. Our results suggest that the existence of extinction debt and species credit, as well as the potential for their future payment and/or receipt, is not only related to forest cover trajectory but also to the amount of remaining forest cover at the landscape scale. Moreover, differences in bird and small mammal life spans seem to be insufficient to affect differently their probability of showing time-delayed responses to landscape change. Synthesis and applications. Our work highlights the need for considering not only the trajectory of deforestation/regeneration but also the amount of forest cover at landscape scale when investigating time-delayed responses to landscape change. As many landscapes are experiencing a change from decreasing to expanding forest cover, understanding the association of extinction and immigration processes, as well as their interactions with the landscape dynamic, is a key factor to plan conservation and restoration actions in human-altered landscapes.

Acute hypoxia induces hypertriglyceridemia by decreasing plasma triglyceride clearance in mice

Jun JC, Shin MK, Yao Q, Bevans-Fonti S, Poole J, Drager LF, Polotsky VY. Acute hypoxia induces hypertriglyceridemia by decreasing plasma triglyceride clearance in mice. Am J Physiol Endocrinol Metab 303: E377-E388, 2012. First published May 22, 2012; doi:10.1152/ajpendo.00641.2011.-Obstructive sleep apnea (OSA) induces intermittent hypoxia (IH) during sleep and is associated with elevated triglycerides (TG). We previously demonstrated that mice exposed to chronic IH develop elevated TG. We now hypothesize that a single exposure to acute hypoxia also increases TG due to the stimulation of free fatty acid (FFA) mobilization from white adipose tissue (WAT), resulting in increased hepatic TG synthesis and secretion. Male C57BL6/J mice were exposed to FiO(2) = 0.21, 0.17, 0.14, 0.10, or 0.07 for 6 h followed by assessment of plasma and liver TG, glucose, FFA, ketones, glycerol, and catecholamines. Hypoxia dose-dependently increased plasma TG, with levels peaking at FiO(2) = 0.07. Hepatic TG levels also increased with hypoxia, peaking at FiO(2) = 0.10. Plasma catecholamines also increased inversely with FiO(2). Plasma ketones, glycerol, and FFA levels were more variable, with different degrees of hypoxia inducing WAT lipolysis and ketosis. FiO(2) = 0.10 exposure stimulated WAT lipolysis but decreased the rate of hepatic TG secretion. This degree of hypoxia rapidly and reversibly delayed TG clearance while decreasing [H-3]triolein-labeled Intralipid uptake in brown adipose tissue and WAT. Hypoxia decreased adipose tissue lipoprotein lipase (LPL) activity in brown adipose tissue and WAT. In addition, hypoxia decreased the transcription of LPL, peroxisome proliferator-activated receptor-gamma, and fatty acid transporter CD36. We conclude that acute hypoxia increases plasma TG due to decreased tissue uptake, not increased hepatic TG secretion.

Decreasing the number of false positives in sequence classification

Abstract Background A large number of probabilistic models used in sequence analysis assign non-zero probability values to most input sequences. To decide when a given probability is sufficient the most common way is bayesian binary classification, where the probability of the model characterizing the sequence family of interest is compared to that of an alternative probability model. We can use as alternative model a null model. This is the scoring technique used by sequence analysis tools such as HMMER, SAM and INFERNAL. The most prevalent null models are position-independent residue distributions that include: the uniform distribution, genomic distribution, family-specific distribution and the target sequence distribution. This paper presents a study to evaluate the impact of the choice of a null model in the final result of classifications. In particular, we are interested in minimizing the number of false predictions in a classification. This is a crucial issue to reduce costs of biological validation. Results For all the tests, the target null model presented the lowest number of false positives, when using random sequences as a test. The study was performed in DNA sequences using GC content as the measure of content bias, but the results should be valid also for protein sequences. To broaden the application of the results, the study was performed using randomly generated sequences. Previous studies were performed on aminoacid sequences, using only one probabilistic model (HMM) and on a specific benchmark, and lack more general conclusions about the performance of null models. Finally, a benchmark test with P. falciparum confirmed these results. Conclusions Of the evaluated models the best suited for classification are the uniform model and the target model. However, the use of the uniform model presents a GC bias that can cause more false positives for candidate sequences with extreme compositional bias, a characteristic not described in previous studies. In these cases the target model is more dependable for biological validation due to its higher specificity.

Advanced Glycation in macrophages induces intracellular accumulation of 7-ketocholesterol and total sterols by decreasing the expression of ABCA-1 and ABCG-1

Abstract Background Advanced glycation end products (AGE) alter lipid metabolism and reduce the macrophage expression of ABCA-1 and ABCG-1 which impairs the reverse cholesterol transport, a system that drives cholesterol from arterial wall macrophages to the liver, allowing its excretion into the bile and feces. Oxysterols favors lipid homeostasis in macrophages and drive the reverse cholesterol transport, although the accumulation of 7-ketocholesterol, 7alpha- hydroxycholesterol and 7beta- hydroxycholesterol is related to atherogenesis and cell death. We evaluated the effect of glycolaldehyde treatment (GAD; oxoaldehyde that induces a fast formation of intracellular AGE) in macrophages overloaded with oxidized LDL and incubated with HDL alone or HDL plus LXR agonist (T0901317) in: 1) the intracellular content of oxysterols and total sterols and 2) the contents of ABCA-1 and ABCG-1. Methods Total cholesterol and oxysterol subspecies were determined by gas chromatography/mass spectrometry and HDL receptors content by immunoblot. Results In control macrophages (C), incubation with HDL or HDL + T0901317 reduced the intracellular content of total sterols (total cholesterol + oxysterols), cholesterol and 7-ketocholesterol, which was not observed in GAD macrophages. In all experimental conditions no changes were found in the intracellular content of other oxysterol subspecies comparing C and GAD macrophages. GAD macrophages presented a 45% reduction in ABCA-1 protein level as compared to C cells, even after the addition of HDL or HDL + T0901317. The content of ABCG-1 was 36.6% reduced in GAD macrophages in the presence of HDL as compared to C macrophages. Conclusion In macrophages overloaded with oxidized LDL, glycolaldehyde treatment reduces the HDL-mediated cholesterol and 7-ketocholesterol efflux which is ascribed to the reduction in ABCA-1 and ABCG-1 protein level. This may contribute to atherosclerosis in diabetes mellitus.

Partial reconstruction of the trajectories of a discretely observed branching diffusion with immigration and an application to inference

In this treatise we consider finite systems of branching particles where the particles move independently of each other according to d-dimensional diffusions. Particles are killed at a position dependent rate, leaving at their death position a random number of descendants according to a position dependent reproduction law. In addition particles immigrate at constant rate (one immigrant per immigration time). A process with above properties is called a branching diffusion withimmigration (BDI). In the first part we present the model in detail and discuss the properties of the BDI under our basic assumptions. In the second part we consider the problem of reconstruction of the trajectory of a BDI from discrete observations. We observe positions of the particles at discrete times; in particular we assume that we have no information about the pedigree of the particles. A natural question arises if we want to apply statistical procedures on the discrete observations: How can we find couples of particle positions which belong to the same particle? We give an easy to implement 'reconstruction scheme' which allows us to redraw or 'reconstruct' parts of the trajectory of the BDI with high accuracy. Moreover asymptotically the whole path can be reconstructed. Further we present simulations which show that our partial reconstruction rule is tractable in practice. In the third part we study how the partial reconstruction rule fits into statistical applications. As an extensive example we present a nonparametric estimator for the diffusion coefficient of a BDI where the particles move according to one-dimensional diffusions. This estimator is based on the Nadaraya-Watson estimator for the diffusion coefficient of one-dimensional diffusions and it uses the partial reconstruction rule developed in the second part above. We are able to prove a rate of convergence of this estimator and finally we present simulations which show that the estimator works well even if we leave our set of assumptions.

Parameterschätzung in Verzweigungsprozessen mit Immigration

Im Verzweigungsprozess mit Immigration werden Schätzer für die erwartete Nachkommenzahl m eines Individuums und die erwartete Immigration λ pro Generation konstruiert. Sie sind nur aufgrund der beobachteten Populationsgröße einer jeden Generation konsistent, ohne Vorkenntnis darüber, ob der Prozess subkritisch (m<1), kritisch (m=1) oder superkritisch (m>1) ist. Im superkritischen Fall ist der Schätzer für λ jedoch nicht konsistent. Dies ist aber keine Einschränkung, denn es wird gezeigt, dass in diesem Fall kein konsistenter Schätzer für λ existiert. Des Weiteren werden Konvergenzgeschwindigkeit der Schätzer und asymptotische Verteilungen der Schätzfehler untersucht. Dabei werden die Fälle (m<1), (m>1) und (m=1) unterschieden, was gänzlich verschiedene Vorgehensweisen erfordert (Ergodizität, Martingalmethoden, Diffusionsapproximationen). Diese hier vorliegende Diplomarbeit orientiert sich an den Ideen und Ergebnissen von Wei und Winnicki (1989/90).

Ergodicity and regularity of invariant measure for branching Markov processes with immigration

In this thesis we consider systems of finitely many particles moving on paths given by a strong Markov process and undergoing branching and reproduction at random times. The branching rate of a particle, its number of offspring and their spatial distribution are allowed to depend on the particle's position and possibly on the configuration of coexisting particles. In addition there is immigration of new particles, with the rate of immigration and the distribution of immigrants possibly depending on the configuration of pre-existing particles as well. In the first two chapters of this work, we concentrate on the case that the joint motion of particles is governed by a diffusion with interacting components. The resulting process of particle configurations was studied by E. Löcherbach (2002, 2004) and is known as a branching diffusion with immigration (BDI). Chapter 1 contains a detailed introduction of the basic model assumptions, in particular an assumption of ergodicity which guarantees that the BDI process is positive Harris recurrent with finite invariant measure on the configuration space. This object and a closely related quantity, namely the invariant occupation measure on the single-particle space, are investigated in Chapter 2 where we study the problem of the existence of Lebesgue-densities with nice regularity properties. For example, it turns out that the existence of a continuous density for the invariant measure depends on the mechanism by which newborn particles are distributed in space, namely whether branching particles reproduce at their death position or their offspring are distributed according to an absolutely continuous transition kernel. In Chapter 3, we assume that the quantities defining the model depend only on the spatial position but not on the configuration of coexisting particles. In this framework (which was considered by Höpfner and Löcherbach (2005) in the special case that branching particles reproduce at their death position), the particle motions are independent, and we can allow for more general Markov processes instead of diffusions. The resulting configuration process is a branching Markov process in the sense introduced by Ikeda, Nagasawa and Watanabe (1968), complemented by an immigration mechanism. Generalizing results obtained by Höpfner and Löcherbach (2005), we give sufficient conditions for ergodicity in the sense of positive recurrence of the configuration process and finiteness of the invariant occupation measure in the case of general particle motions and offspring distributions.

Non-parametric estimation of the diffusion coefficient of a branching diffusion with immigration

Wir betrachten Systeme von endlich vielen Partikeln, wobei die Partikel sich unabhängig voneinander gemäß eindimensionaler Diffusionen [dX_t = b(X_t),dt + sigma(X_t),dW_t] bewegen. Die Partikel sterben mit positionsabhängigen Raten und hinterlassen eine zufällige Anzahl an Nachkommen, die sich gemäß eines Übergangskerns im Raum verteilen. Zudem immigrieren neue Partikel mit einer konstanten Rate. Ein Prozess mit diesen Eigenschaften wird Verzweigungsprozess mit Immigration genannt. Beobachten wir einen solchen Prozess zu diskreten Zeitpunkten, so ist zunächst nicht offensichtlich, welche diskret beobachteten Punkte zu welchem Pfad gehören. Daher entwickeln wir einen Algorithmus, um den zugrundeliegenden Pfad zu rekonstruieren. Mit Hilfe dieses Algorithmus konstruieren wir einen nichtparametrischen Schätzer für den quadrierten Diffusionskoeffizienten $sigma^2(cdot),$ wobei die Konstruktion im Wesentlichen auf dem Auffüllen eines klassischen Regressionsschemas beruht. Wir beweisen Konsistenz und einen zentralen Grenzwertsatz.

Increasing echogenicity of diffuse circumferential thickening ("macaroni sign") of the carotid artery wall with decreasing inflammatory activity of takayasu arteritis

We report a case of sonographic follow-up showing brightening of the diffuse circumferential thickening (halo) of the carotid artery wall (the so-called "macaroni sign") in a patient with decreasing inflammatory activity of Takayasu arteritis over a 6-month period. Sonographic follow-up in patients with Takayasu arteritis may be a useful complementary tool for evaluation of inflammatory activity. Besides a reduction of halo diameter, an increase in wall echogenicity appears to be a sign of decreasing inflammation.