Cell junctions in the rapidly moving edge of chick and quail blastoderms during gastrulation

Summary The intercellular contacts of the migrating edge of chick and quail blastoderms during gastrulation were studied by transmission electron microscopy of thin sections and of freeze-fracture replicas. Tight junctions and gap junctions as well as desmosomes were found. Tight junctions were organized as single junctional strands or as a complex of numerous junctional strands interposed between the lamellae and the bodies of the cells building up the margin of overgrowth. The function of these intercellular junctions is considered in relation to the locomotion of the margin of overgrowth cells.     

Photon and fluorescence correlation spectroscopy and light scattering of eye-lens proteins at moderate concentrations

The bovine eye-lens protein, alpha L-crystallin, has been studied with photon correlation spectroscopy to obtain the mutual diffusion coefficient, Dm, with fluorescence correlation spectroscopy to determine the tracer diffusion coefficient, DT, and with light scattering to get the isothermal osmotic compressibility (delta pi/delta c) P,T. The concentration dependence of Dm, DT, and (delta pi/delta c) P,T up to a volume fraction phi of the protein of 2.5 x 10(-2) has been interpreted on the basis of four different interaction potentials: (a) an extended hard-sphere potential; (b) a shielded Coulomb potential; (c) a shielded Coulomb interaction where the effect of counterions is included; (d) a simple mixed potential. The three parameters Dm, DT, and (delta pi/delta c) P,T have also been combined in the generalized Stokes-Einstein equation, Dm = [(delta pi/delta c)P,T . (1--phi) . (DT)]/(kappa B . T). Our results indicate that, in the case that photon correlation spectroscopy gives the mutual diffusion coefficient Dm, the applicability of the Stokes-Einstein equation can be questioned; or that, when one assumes the Stokes-Einstein equation to be valid, there is significant discrepancy between the result of photon correlation spectroscopy and Dm.     

Mapping of the variegate porphyria (VP) gene: Contradictory evidence for linkage between VP and microsatellite markers at chromosome 14q32

The gene for variegate porphyria (VP), an autosomal dominant disease with a high prevalence in South Africa, evidently due to a founder effect, was previously mapped to chromosome 14q32. In the current study this localization was evaluated by linkage and haplotype analyses using microsatellite markers spanning a region of more than 20 cM on chromosome 14q32. In many recent studies linkage disequilibrium between disease and marker loci has been utilized to map genes in founder populations, but we could not find any association between VP and the markers used in this study. Our data suggest that the allocation of VP to chromosome 14q32 may be incorrect. Received: 1 September 1995 / Revised: 1 November 1995     

Study of the dynamics of neutralization escape mutants in a chimpanzee naturally infected with the simian immunodeficiency virus SIVcpz-ant.

Here we report on the use of spectral map analysis of time-paired sequential neutralization data of 11 serum samples of a chimpanzee naturally infected with a simian immunodeficiency virus (SIVcpz-ant) and 8 primary consecutive SIVcpz-ant isolates, taken at about 4-month intervals. The analysis reveals the existence of three SIVcpz-ant isolate and serum neutralization clusters. Each cluster groups virus isolates and/or sera based on similarities of their neutralization spectra. On average, neutralization escape mutants emerged after 15 months and mounted a neutralization response approximately 8 months later. The entire gp160 regions of eight consecutive isolates were sequenced and analyzed by a new statistical method called polygram, which allowed the deduction of amino acid sequence motifs of gp160 which were specific for SIVcpz-ant isolates belonging to the same isolate neutralization clusters. Changes in specific amino acid quadruplets in V1, V2, C3, V4, V5, and CD4 domains of gp120 and gp40 were seen to correlate with the neutralization clusters with most of the specific changes occurring in the V4 region. This method of analysis may facilitate an understanding of the study of the dynamic interplay between human immunodeficiency virus (HIV) and host neutralization responses as well as providing possible insights into mechanisms of persistence of HIV-1-related lentiviruses in their natural hosts.     

Afforestation for climate change mitigation: Potentials,risks and trade‐offs

Afforestation is considered a cost‐effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade‐offs with food security are often not considered. Here we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework. In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO₂/year at 200 US$/tCO₂ in 2050 leading to large‐scale application in an SSP2 scenario aiming for 2°C (410 GtCO₂ cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock‐in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub‐Saharan Africa. Afforestation also requires large amounts of land (up to 1,100 Mha) leading to large reductions in agricultural land. The increased competition for land could lead to higher food prices and an increased population at risk of hunger. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade‐offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade‐offs in order to achieve mitigation sustainably.     

Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed

Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).     

Functional changes of the SCN in spontaneous hypertension but not after the induction of hypertension

ABSTRACT

The present study investigates the circadian behavior of spontaneously hypertensive rats (SHRs) during the pre-hypertensive and hypertensive stage, with the aim to gain insight into whether observed changes in the functionality of suprachiasmatic nucleus (SCN) in the hypertensive state are cause or consequence of hypertension. Four types of animals were used in this study: (1) SHRs which develop hypertension genetically; (2) their normotensive controls, Wistar Kyoto rats (WKYs); (3) Wistar rats whereby hypertension was surgically induced (2 Kidney 1 Clamp (2K1C) method); and (4) sham-operated control Wistar rats. Period length and activity levels and amplitude changes of locomotor and wheel running activity were determined, in constant conditions, as a measure of the functionality of the SCN. Hereto two conditions were used, constant darkness (0 lux) and constant dim (5 lux) light. SHRs showed a shortened period of their locomotor and running wheel activity rhythms in constant darkness during both pre-hypertensive and hypertensive stages and exhibited period lengthening in constant dim light conditions, only during hypertensive stages. Total amount as well as the amplitude of daily running wheel rhythms showed an inverse correlation with the period length, and this relation was significantly different in SHRs compared to WKYs. None of the aforementioned changes in circadian rhythms were observed after the surgical induction of hypertension. The present findings suggest early functional changes of the SCN in the etiology of spontaneous hypertension.     

Inertia weight control strategies for particle swarm optimization

Particle swarm optimization (PSO) is a population-based, stochastic optimization technique inspired by the social dynamics of birds. The PSO algorithm is rather sensitive to the control parameters, and thus, there has been a significant amount of research effort devoted to the dynamic adaptation of these parameters. The focus of the adaptive approaches has largely revolved around adapting the inertia weight as it exhibits the clearest relationship with the exploration/exploitation balance of the PSO algorithm. However, despite the significant amount of research efforts, many inertia weight control strategies have not been thoroughly examined analytically nor empirically. Thus, there are a plethora of choices when selecting an inertia weight control strategy, but no study has been comprehensive enough to definitively guide the selection. This paper addresses these issues by first providing an overview of 18 inertia weight control strategies. Secondly, conditions required for the strategies to exhibit convergent behaviour are derived. Finally, the inertia weight control strategies are empirically examined on a suite of 60 benchmark problems. Results of the empirical investigation show that none of the examined strategies, with the exception of a randomly selected inertia weight, even perform on par with a constant inertia weight.