Recommended Terminology for Aerobiological Studies

Aerobiology is an interdisciplinary science where researchers with different backgrounds are involved in different topics related to microorganism, airborne biological particles, e.g. pollen and spores, and phenology. Some concepts, words or expressions used in aerobiology have a clear definition, but are however frequently misused. Therefore, the working group “Quality Control” of the European Aerobiology Society (EAS) and the International Association of Aerobiology (IAA) would like to clarify some of them, their use and presentation

Pharmacology and Surface Electrostatics of the K Channel Outer Pore Vestibule

In spite of a generally well-conserved outer vestibule and pore structure, there is considerable diversity in the pharmacology of K channels. We have investigated the role of specific outer vestibule charged residues in the pharmacology of K channels using tetraethylammonium (TEA) and a trivalent TEA analog, gallamine. Similar to Shaker K channels, gallamine block of Kv3.1 channels was more sensitive to solution ionic strength than was TEA block, a result consistent with a contribution from an electrostatic potential near the blocking site. In contrast, TEA block of another type of K channel (Kv2.1) was insensitive to solution ionic strength and these channels were resistant to block by gallamine. Neutralizing either of two lysine residues in the outer vestibule of these Kv2.1 channels conferred ionic strength sensitivity to TEA block. Kv2.1 channels with both lysines neutralized were sensitive to block by gallamine, and the ionic strength dependence of this block was greater than that for TEA. These results demonstrate that Kv3.1 (like Shaker) channels contain negatively charged residues in the outer vestibule of the pore that influence quaternary ammonium pharmacology. The presence of specific lysine residues in wild-type Kv2.1 channels produces an outer vestibule with little or no net charge, with important consequences for quaternary ammonium block. Neutralizing these key lysines results in a negatively charged vestibule with pharmacological properties approaching those of other types of K channels

Automatic detection of airborne pollen: an overview

Pollen monitoring has traditionally been carried out using manual methods frst developed in the early 1950s. Although this technique has been recently standardised, it sufers from several drawbacks, notably data usually only being available with a delay of 3–9 days and usually delivered at a daily resolution. Several automatic instruments have come on to the market over the past few years, with more new devices also under development. This paper provides a comprehensive overview of all available and developing automatic instruments, how they measure, how they identify airborne pollen, what impacts measurement quality, as well as what potential there is for further advancement in the feld of bioaerosol monitoring.</p

Biomass selection by floods and related timescales: Part 1. Experimental observations

Several research investigations have explored the interaction between morphodynamic and vegetation growth processes from both the modelling and the experimental viewpoints. Results have mainly been concerned with morphologic analyses of the effects of vegetation on long term riverbed evolution without addressing the relative role of the timescales between such processes. This paper presents for the first time the statistics of uprooted biomass obtained while perturbing the vegetation growing in the river bed with periodic disturbances of constant magnitude. That is, we force the biological and hydrological processes to interact and study the related timescales in order to shed light on the role of flood disturbances in selecting the component of the biomass that has a higher chance of survival in relation to its growth stage. A simple interpretative stochastic model is then presented and thoroughly discussed in a companion paper (Biomass selection by floods and related timescales: Part 2. Stochastic modelling). (C) 2011 Elsevier Ltd. All rights reserved.</p

Extracting Dwell Time Sequences from Processive Molecular Motor Data

Processive molecular motors, such as kinesin, myosin, or dynein, convert chemical energy into mechanical energy by hydrolyzing ATP. The mechanical energy is used for moving in discrete steps along the cytoskeleton and carrying a molecular load. Single-molecule recordings of motor position along a substrate polymer appear as a stochastic staircase. Recordings of other single molecules, such as F1-ATPase, RNA polymerase, or topoisomerase, have the same appearance. We present a maximum likelihood algorithm that extracts the dwell time sequence from noisy data, and estimates state transition probabilities and the distribution of the motor step size. The algorithm can handle models with uniform or alternating step sizes, and reversible or irreversible kinetics. A periodic Markov model describes the repetitive chemistry of the motor, and a Kalman filter allows one to include models with variable step size and to correct for baseline drift. The data are optimized recursively and globally over single or multiple data sets, making the results objective over the full scale of the data. Local binary algorithms, such as the t-test, do not represent the behavior of the whole data set. Our method is model-based, and allows rapid testing of different models by comparing the likelihood scores. From data obtained with current technology, steps as small as 8 nm can be resolved and analyzed with our method. The kinetic consequences of the extracted dwell sequence can be further analyzed in detail. We show results from analyzing simulated and experimental kinesin and myosin motor data. The algorithm is implemented in the free QuB software

Maximum Likelihood Estimation of Molecular Motor Kinetics from Staircase Dwell-Time Sequences

Molecular motors, such as kinesin, myosin, or dynein, convert chemical energy into mechanical energy by hydrolyzing ATP. The mechanical energy is used for moving in discrete steps along the cytoskeleton and carrying a molecular load. High resolution single molecule recordings of motor steps appear as a stochastic sequence of dwells, resembling a staircase. Staircase data can also be obtained from other molecular machines such as F(1)-ATPase, RNA polymerase, or topoisomerase. We developed a maximum likelihood algorithm that estimates the rate constants between different conformational states of the protein, including motor steps. We model the motor with a periodic Markov model that reflects the repetitive chemistry of the motor step. We estimated the kinetics from the idealized dwell-sequence by numerical maximization of the likelihood function for discrete-time Markov models. This approach eliminates the need for missed event correction. The algorithm can fit kinetic models of arbitrary complexity, such as uniform or alternating step chemistry, reversible or irreversible kinetics, ATP concentration and mechanical force-dependent rates, etc. The method allows global fitting across stationary and nonstationary experimental conditions, and user-defined a priori constraints on rate constants. The algorithm was tested with simulated data, and implemented in the free QuB software

Recovery times of riparian vegetation

Riparian vegetation is a key element in a number of processes that determine the ecogeomorphological features of the river landscape. Depending on the river water stage fluctuations, vegetation biomass randomly switches between growth and degradation phases and exhibits relevant temporal variations. A full understanding of vegetation dynamics is therefore only possible if the hydrological stochastic forcing is considered. In this vein, we focus on the recovery time of vegetation, namely the typical time taken by vegetation to recover a well-developed state starting from a low biomass value (induced, for instance, by an intense flood). The analytical expression of the plot-dependent recovery time is given, the role of hydrological and biological parameters is discussed, and the impact of river-induced randomness is highlighted. Finally, the effect of man-induced hydrological changes (e.g., river damming or climate changes) is explore

Automatic detection of airborne pollen: an overview

Pollen monitoring has traditionally been carried out using manual methods first developed in the early 1950s. Although this technique has been recently standardised, it suffers from several drawbacks, notably data usually only being available with a delay of 3–9 days and usually delivered at a daily resolution. Several automatic instruments have come on to the market over the past few years, with more new devices also under development. This paper provides a comprehensive overview of all available and developing automatic instruments, how they measure, how they identify airborne pollen, what impacts measurement quality, as well as what potential there is for further advancement in the field of bioaerosol monitoring