Ergothioneine Biosynthetic Methyltransferase EgtD Reveals the Structural Basis of Aromatic Amino Acid Betaine Biosynthesis

Ergothioneine is an N‐α‐trimethyl‐2‐thiohistidine derivative that occurs in human, plant, fungal, and bacterial cells. Biosynthesis of this redox‐active betaine starts with trimethylation of the α‐amino group of histidine. The three consecutive methyl transfers are catalyzed by the S‐adenosylmethionine‐dependent methyltransferase EgtD. Three crystal structures of this enzyme in the absence and in the presence of N‐α‐dimethylhistidine and S‐adenosylhomocysteine implicate a preorganized array of hydrophilic interactions as the determinants for substrate specificity and apparent processivity. We identified two active site mutations that change the substrate specificity of EgtD 10⁷‐fold and transform the histidine‐methyltransferase into a proficient tryptophan‐methyltransferase. Finally, a genomic search for EgtD homologues in fungal genomes revealed tyrosine and tryptophan trimethylation activity as a frequent trait in ascomycetous and basidomycetous fungi.     

Load balancing routing with queue overflow prediction for WSNs

The ease of deployment of Wireless Sensor Networks (WSNs) makes them very popular and useful for data collection applications. Nodes often use multihop communication to transmit data to a collector node. The next hop selection in order to reach the final destination is done following a routing policy based on a routing metric. The routing metric value is exchanged via control messages. Control messages transmission frequency can reduce the network bandwidth and affect data transmission. Some approaches like trickle algorithm have been proposed to optimize the network control messages transmission. In this paper, we propose a collaborative load balancing algorithm (CoLBA) with a prediction approach to reduce network overhead. CoLBA is a queuing delay based routing protocol that avoids packet queue overflow and uses a prediction approach to optimize control messages transmission. Simulation results on Cooja simulator show that CoLBA outperforms other existing protocols in terms of delivery ratio and queue overflow while maintaining a similar end-to-end delay.

     

Interference‐aware clustering approach improving QoS for linear WSNs using a token‐based MAC protocol

Wireless sensor networks (WSNs) have received a lot of attention from both academia and industry due to the increasing need for ubiquitous computing for monitoring applications, the continuous advances in miniaturization of electronic devices, and the ultra‐low‐power wireless technologies. These innovations in technology have driven the curiosity to use sensor networks in a new kind of applications such as road track or railway monitoring, border monitoring, oil and gas, or even water pipeline monitoring. Due to the underlying linear topology of these applications, a new type of network, called a linear sensor network (LSN), has emerged. Because of the specific characteristics of this application and the resource constraints of sensors, some of the major challenges faced in LSNs are to reduce end‐to‐end delays, to maximize the packet delivery ratio to a sink, and an even distribution of the load between nodes. To achieve these objectives, it is necessary to control node‐to‐node packet traffic conditions and to manage radio interference created by simultaneously active nodes. This paper addresses these challenges and proposes a new method of clustering LSNs that reduces or controls radio interference risks in order to satisfy these objectives, application needs, and the resource limitations of sensor nodes in the best possible way. This method is applied for LSNs using a token‐passing mechanism to access the medium. The performance evaluation is conducted by using a realistic propagation model in the analytical evaluation and also a NS‐2 simulation process.     

A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS

Many current models of ecosystem carbon exchange based on remote sensing, such as the MODIS product termed MOD17, still require considerable input from ground based meteorological measurements and look up tables based on vegetation type. Since these data are often not available at the same spatial scale as the remote sensing imagery, they can introduce substantial errors into the carbon exchange estimates. Here we present further development of a gross primary production (GPP) model based entirely on remote sensing data. In contrast to an earlier model based only on the enhanced vegetation index (EVI), this model, termed the Temperature and Greenness (TG) model, also includes the land surface temperature (LST) product from MODIS. In addition to its obvious relationship to vegetation temperature, LST was correlated with vapor pressure deficit and photosynthetically active radiation. Combination of EVI and LST in the model substantially improved the correlation between predicted and measured GPP at 11 eddy correlation flux towers in a wide range of vegetation types across North America. In many cases, the TG model provided substantially better predictions of GPP than did the MODIS GPP product. However, both models resulted in poor predictions for sparse shrub habitats where solar angle effects on remote sensing indices were large. Although it may be possible to improve the MODIS GPP product through improved parameterization, our results suggest that simpler models based entirely on remote sensing can provide equally good predictions of GPP.     

The visibility of noise in System I PAL colour television

The results of new subjective tests on the visibility of noise in System I PAL colour television are reported. Three forms of noise are considered: white (flat) noise, de-emphasised triangular noise, and the noise resulting from vestigial sideband demodulation (VSB noise). The results are compared with those given by work published 20 years ago and it is concluded that observers today are more critical of noise in pictures: about 2¹/₂ dB less noise is required to produce the same impairment     

Parameterization of a process-based tree-growth model: Comparison of optimization, MCMC and Particle Filtering algorithms

Finely tuned process-based tree-growth models are of considerable help in understanding the variations of biomass increments measured in the dendrochronological series. Using site and species parameters, as well as daily climate variables, the MAIDEN model computes the water balance at ecosystem level and the daily increment of carbon storage in the stem through photosynthesis processes to reproduce the structure of the tree-ring series. In this paper, we use three techniques to calibrate this model with Pinus halepensis data sampled in the Mediterranean part of France: a standard optimization (PEST), Monte Carlo Markov Chains (MCMC) and Particle Filtering (PF). Contrary to PEST, which tries to find an optimum fit (giving the lowest error between observations and simulations), the principle of MCMC and PF is to walk, from a priori distributions, in the parameter space according to particular statistical rules to compute each parameter distribution. The PEST and MCMC calibrations of our dendrochronological series lead to rather similar adjustments between simulations and observations. PF and MCMC calibrations give different parameter distributions, showing how complementary are these methods, with a better fit for MCMC. Yet, independent validations over 11 independent meteorological years show a higher efficiency of the recent PF method over the others.     

Automatic and dynamic network establishment for linear WSNs

The deployment of wireless sensor networks (WSNs) in the mostly linear large structures, such as rivers, pipelines, etc, suffers from being the worst case for classical addressing schemes, e.g. distributed address assignment mechanism (DAAM) or stochastic addressing for Zigbee. Using DAAM for physical topologies composed of long lines of nodes connected together wastes addresses and generates orphan nodes. We show in this paper the inherent limitations of classical (DAAM, stochastic) and specialized (usually cluster-orientated) addressing schemes for Linear WSNs. DiscoProto, is an addressing and routing scheme which builds a logical network corresponding to a corresponding physical linear network without any knowledge of physical topology. In this paper, we show thanks to a realistic simulation using Castalia (Omnet based simulator) that DiscoProto avoids waste of addresses and allows a high association ratio. We also propose a dynamic version of our protocol called Dynamic DiscoProto in the second part of the paper. Dynamic DiscoProto allows to add new nodes or new branches in an existing linear network.

     

Implementation and performance evaluation of IEEE 802.15.4 unslotted CSMA/CA protocol on Contiki OS

In the wireless sensor networks domain, one of the most used standards is IEEE 802.15.4. This standard has been made available on many low power operating systems such as TinyOS and Contiki OS. It is crucial for the implementation to be compliant with the specifications of the standard. In the case of Contiki OS, the provided version of the main medium access algorithm, unslotted Carrier Sensing Multiple Access with Collision Avoidance (CSMA/CA), presents many flaws. In this paper, we discuss the implementation of the provided CSMA/CA algorithm and we point out to the parts that do not respect the standard specifications. We also propose and implement a compliant version of this algorithm and show through simulation the correctness of the implementation.     

The reliability of the lateral radiograph in determination of the optimal transarticular C1-C2 screw length

STUDY DESIGN: This study assessed the value of using lateral radiographs in evaluating the optimal screw length in transarticular C1-C2 screw fixation. OBJECTIVES: To assess the reliability of the lateral radiograph in determining the optimal transarticular C1-C2 screw length. SUMMARY OF BACKGROUND DATA: Transarticular C1-C2 screw placement is usually performed using anatomic landmarks and fluoroscopy. A lateral fluoroscopic image is valuable when directing screws in the sagittal plane, but its exact role in determining screw length has not been investigated. METHODS: Eight cervical spine specimens were used in this study. Screw placements were performed in each specimen, fixed in the exact lateral position and under direct visualization. After each placement, a lateral radiograph was taken. The odontoid process was divided into three equal portions. Another portion anterior to the odontoid process was called the anterior tubercle region. The number of screw tips appearing in each portion on the radiograph was then recorded for each placement. In addition, 30 C1 specimens were measured to evaluate the anterior part of C1. RESULTS: The results showed that 12.5% of the screws placed 2 mm short of reaching the ventral cortex and 0 mm overpenetrating the ventral cortex of the lateral mass of C1 projected in the radiograph on the anterior tubercle region, 37.5% on the anterior region of the odontoid process, and 50% on the middle region of the odontoid process. Twenty-five percent of the screws that were placed to overpenetrate, by 2 or 4 mm, the ventral cortex of the lateral mass of C1 were projected on the anterior tubercle region in the radiograph, and 50% and 62.5% were projected on the anterior region of the odontoid process, respectively. The mean vertical distance between the anteriormost point of the anterior tubercle of the anterior ring and the middle of the ventral cortex of the lateral in all specimens was 5.6 +/- 1 mm, and the mean transverse angle of the anterior ring relative to the frontal plane was 21.1 +/- 3.5 degrees. CONCLUSIONS: This results in this study indicate that a lateral radiograph may not be reliable in determining the optimal screw length, although it is valuable in directing accurate screw angle in the sagittal plane. Preoperative computed tomographic evaluation of the C1-C2 region may be helpful in estimating the location of the screw tip on the lateral radiograph during surgery.     

Short- and long-term dynamics of the toxic potential and genotypic structure in benthic populations of Microcystis

Microcystis colonies are known to overwinter on the surface of the sediment of freshwater ecosystems. However, little is known about the genotypic and toxicological dynamics of Microcystis populations during this benthic life stage. In this study, we report a two-year-long survey of benthic populations of Microcystis, which had spent from a few days to more than six years in the sediment. In order to avoid any interaction with the planktonic proliferations, we chose two deeply buried benthic populations, which could be easily dated. Quantitative PCR on mcyB gene and protein phosphatase inhibition assays were performed to measure their toxic potential, and their genotypic structure was assessed by Capillary Electrophoresis-Single Strand Conformation Polymorphism (CE-SSCP), based on 16S-23S Intergenic Transcribed Spacer (ITS). The microcystin content of the cells seemed to change sharply during the first few months of benthic survival, whereas this content was low and decreased steadily after several years of benthic life. No genetic selection was observed in either the proportion of potentially toxic clones or the ITS sequences for any of the populations considered. From these results, the benthic life stage of Microcystis appears to preserve the structure and the composition of the population over a far larger time scale than classical overwintering period. Finally, some genotypes were common in both of the benthic populations, even though they originated from planktonic blooms that had developed five years apart, suggesting a major overlap of planktonic proliferations in successive years.