Estudo de famílias wavelets para aplicação na análise em DOAS

Trace gases are important to our environment even though their presence comes only by ‘traces’, but their concentrations must be monitored, so any necessary interventions can be done at the right time. There are some lower and upper boundaries which produce nice conditions for our lives and then monitoring trace gases comes as an essential task nowadays to be accomplished by many techniques. One of them is the differential optical absorption spectroscopy (DOAS), which consists mathematically on a regression - the classical method uses least-squares - to retrieve the trace gases concentrations. In order to achieve better results, many works have tried out different techniques instead of the classical approach. Some have tried to preprocess the signals to be analyzed by a denoising procedure - e.g. discrete wavelet transform (DWT). This work presents a semi-empirical study to find out the most suitable DWT family to be used in this denoising. The search seeks among many well-known families the one to better remove the noise, keeping the original signal’s main features, then by decreasing the noise, the residual left after the regression is done decreases too. The analysis take account the wavelet decomposition level, the threshold to be applied on the detail coefficients and how to apply them - hard or soft thresholding. The signals used come from an open and online data base which contains characteristic signals from some trace gases usually studied.

Estudo de famílias wavelets para aplicação na análise em DOAS

Trace gases are important to our environment even though their presence comes only by ‘traces’, but their concentrations must be monitored, so any necessary interventions can be done at the right time. There are some lower and upper boundaries which produce nice conditions for our lives and then monitoring trace gases comes as an essential task nowadays to be accomplished by many techniques. One of them is the differential optical absorption spectroscopy (DOAS), which consists mathematically on a regression - the classical method uses least-squares - to retrieve the trace gases concentrations. In order to achieve better results, many works have tried out different techniques instead of the classical approach. Some have tried to preprocess the signals to be analyzed by a denoising procedure - e.g. discrete wavelet transform (DWT). This work presents a semi-empirical study to find out the most suitable DWT family to be used in this denoising. The search seeks among many well-known families the one to better remove the noise, keeping the original signal’s main features, then by decreasing the noise, the residual left after the regression is done decreases too. The analysis take account the wavelet decomposition level, the threshold to be applied on the detail coefficients and how to apply them - hard or soft thresholding. The signals used come from an open and online data base which contains characteristic signals from some trace gases usually studied.

Control of pattern formation by time-delay feedback with global and local contributions

We consider the suppression of spatiotemporal chaos in the complex GinzburgLandau equation by a combined global and local time-delay feedback. Feedback terms are implemented as a control scheme, i.e., they are proportional to the difference between the time-delayed state of the system and its current state. We perform a linear stability analysis of uniform oscillations with respect to space-dependent perturbations and compare with numerical simulations. Similarly, for the fixed-point solution that corresponds to amplitude death in the spatially extended system, a linear stability analysis with respect to space-dependent perturbations is performed and complemented by numerical simulations. © 2010 Elsevier B.V. All rights reserved.

Geographic Expansion of Lyme Disease in the Southeastern United States, 2000-2014.

Background.  The majority of Lyme disease cases in the United States are acquired on the east coast between northern Virginia and New England. In recent years the geographic extent of Lyme disease has been expanding, raising the prospect of Lyme disease becoming endemic in the southeast. Methods.  We collected confirmed and probable cases of Lyme disease from 2000 through 2014 from the Virginia Department of Health and North Carolina Department of Public Health and entered them in a geographic information system. We performed spatial and spatiotemporal cluster analyses to characterize Lyme disease expansion. Results.  There was a marked increase in Lyme disease cases in Virginia, particularly from 2007 onwards. Northern Virginia experienced intensification and geographic expansion of Lyme disease cases. The most notable area of expansion was to the southwest along the Appalachian Mountains with development of a new disease cluster in the southern Virginia mountain region. Conclusions.  The geographic distribution of Lyme disease cases significantly expanded in Virginia between 2000 and 2014, particularly southward in the Virginia mountain ranges. If these trends continue, North Carolina can expect autochthonous Lyme disease transmission in its mountain region in the coming years.

BDNF-TrkB Signaling in Single-Spine Structural Plasticity

Multiple lines of evidence reveal that activation of the tropomyosin related kinase B (TrkB) receptor is a critical molecular mechanism underlying status epilepticus (SE) induced epilepsy development. However, the cellular consequences of such signaling remain unknown. To this point, localization of SE-induced TrkB activation to CA1 apical dendritic spines provides an anatomic clue pointing to Schaffer collateral-CA1 synaptic plasticity as one potential cellular consequence of TrkB activation. Here, we combine two-photon glutamate uncaging with two photon fluorescence lifetime imaging microscopy (2pFLIM) of fluorescence resonance energy transfer (FRET)-based sensors to specifically investigate the roles of TrkB and its canonical ligand brain derived neurotrophic factor (BDNF) in dendritic spine structural plasticity (sLTP) of CA1 pyramidal neurons in cultured hippocampal slices of rodents. To begin, we demonstrate a critical role for post-synaptic TrkB and post-synaptic BDNF in sLTP. Building on these findings, we develop a novel FRET-based sensor for TrkB activation that can report both BDNF and non-BDNF activation in a specific and reversible manner. Using this sensor, we monitor the spatiotemporal dynamics of TrkB activity during single-spine sLTP. In response to glutamate uncaging, we report a rapid (onset less than 1 minute) and sustained (lasting at least 20 minutes) activation of TrkB in the stimulated spine that depends on N-methyl-D-aspartate receptor (NMDAR)-Ca2+/Calmodulin dependent kinase II (CaMKII) signaling as well as post-synaptically synthesized BDNF. Consistent with these findings, we also demonstrate rapid, glutamate uncaging-evoked, time-locked release of BDNF from single dendritic spines using BDNF fused to superecliptic pHluorin (SEP). Finally, to elucidate the molecular mechanisms by which TrkB activation leads to sLTP, we examined the dependence of Rho GTPase activity - known mediators of sLTP - on BDNF-TrkB signaling. Through the use of previously described FRET-based sensors, we find that the activities of ras-related C3 botulinum toxin substrate 1 (Rac1) and cell division control protein 42 (Cdc42) require BDNF-TrkB signaling. Taken together, these findings reveal a spine-autonomous, autocrine signaling mechanism involving NMDAR-CaMKII dependent BDNF release from stimulated dendritic spines leading to TrkB activation and subsequent activation of the downstream molecules Rac1 and Cdc42 in these same spines that proves critical for sLTP. In conclusion, these results highlight structural plasticity as one cellular consequence of CA1 dendritic spine TrkB activation that may potentially contribute to larger, circuit-level changes underlying SE-induced epilepsy.

A Mechanical Analysis of Suspensory Locomotion in Primates and Other Mammals

For primates, and other arboreal mammals, adopting suspensory locomotion represents one of the strategies an animal can use to prevent toppling off a thin support during arboreal movement and foraging. While numerous studies have reported the incidence of suspensory locomotion in a broad phylogenetic sample of mammals, little research has explored what mechanical transitions must occur in order for an animal to successfully adopt suspensory locomotion. Additionally, many primate species are capable of adopting a highly specialized form of suspensory locomotion referred to as arm-swinging, but few scenarios have been posited to explain how arm-swinging initially evolved. This study takes a comparative experimental approach to explore the mechanics of below branch quadrupedal locomotion in primates and other mammals to determine whether above and below branch quadrupedal locomotion represent neuromuscular mirrors of each other, and whether the patterns below branch quadrupedal locomotion are similar across taxa. Also, this study explores whether the nature of the flexible coupling between the forelimb and hindlimb observed in primates is a uniquely primate feature, and investigates the possibility that this mechanism could be responsible for the evolution of arm-swinging.

To address these research goals, kinetic, kinematic, and spatiotemporal gait variables were collected from five species of primate (Cebus capucinus, Daubentonia madagascariensis, Lemur catta, Propithecus coquereli, and Varecia variegata) walking quadrupedally above and below branches. Data from these primate species were compared to data collected from three species of non-primate mammals (Choloepus didactylus, Pteropus vampyrus, and Desmodus rotundus) and to three species of arm-swinging primate (Hylobates moloch, Ateles fusciceps, and Pygathrix nemaeus) to determine how varying forms of suspensory locomotion relate to each other and across taxa.

From the data collected in this study it is evident the specialized gait characteristics present during above branch quadrupedal locomotion in primates are not observed when walking below branches. Instead, gait mechanics closely replicate the characteristic walking patterns of non-primate mammals, with the exception that primates demonstrate an altered limb loading pattern during below branch quadrupedal locomotion, in which the forelimb becomes the primary propulsive and weight-bearing limb; a pattern similar to what is observed during arm-swinging. It is likely that below branch quadrupedal locomotion represents a “mechanical release” from the challenges of moving on top of thin arboreal supports. Additionally, it is possible, that arm-swinging could have evolved from an anatomically-generalized arboreal primate that began to forage and locomote below branches. During these suspensory bouts, weight would have been shifted away from the hindlimbs towards forelimbs, and as the frequency of these boats increased the reliance of the forelimb as the sole form of weight support would have also increased. This form of functional decoupling may have released the hindlimbs from their weight-bearing role during suspensory locomotion, and eventually arm-swinging would have replaced below branch quadrupedal locomotion as the primary mode of suspensory locomotion observed in some primate species. This study provides the first experimental evidence supporting the hypothetical link between below branch quadrupedal locomotion and arm-swinging in primates.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Direct In Vivo Manipulation and Imaging of Calcium Transients in Neutrophils Identify a Critical Role for Leading-Edge Calcium Flux.

Calcium signaling has long been associated with key events of immunity, including chemotaxis, phagocytosis, and activation. However, imaging and manipulation of calcium flux in motile immune cells in live animals remain challenging. Using light-sheet microscopy for in vivo calcium imaging in zebrafish, we observe characteristic patterns of calcium flux triggered by distinct events, including phagocytosis of pathogenic bacteria and migration of neutrophils toward inflammatory stimuli. In contrast to findings from ex vivo studies, we observe enriched calcium influx at the leading edge of migrating neutrophils. To directly manipulate calcium dynamics in vivo, we have developed transgenic lines with cell-specific expression of the mammalian TRPV1 channel, enabling ligand-gated, reversible, and spatiotemporal control of calcium influx. We find that controlled calcium influx can function to help define the neutrophil's leading edge. Cell-specific TRPV1 expression may have broad utility for precise control of calcium dynamics in other immune cell types and organisms.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Bridging the Scale Gap from Leaf to Canopy in Biosphere-Atmosphere Gas and Particle Exchanges

Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as

`biological valves' in regulating the anthropogenic emissions of atmospheric aerosol

particles and greenhouse gases (GHGs) as responses to their surrounding environments.

While the signicance of quantifying the exchange rates of GHGs and atmospheric

aerosol particles between the terrestrial biosphere and the atmosphere is

hardly questioned in many scientic elds, the progress in improving model predictability,

data interpretation or the combination of the two remains impeded by

the lack of precise framework elucidating their dynamic transport processes over a

wide range of spatiotemporal scales. The diculty in developing prognostic modeling

tools to quantify the source or sink strength of these atmospheric substances

can be further magnied by the fact that the climate system is also sensitive to the

feedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,

the emergent need is to reduce uncertainties when assessing this complex and dynamic

feedback cycle that is necessary to support the decisions of mitigation and

adaptation policies associated with human activities (e.g., anthropogenic emission

controls and land use managements) under current and future climate regimes.

With the goal to improve the predictions for the biosphere-atmosphere exchange

of biologically active gases and atmospheric aerosol particles, the main focus of this

dissertation is on revising and up-scaling the biotic and abiotic transport processes

from leaf to canopy scales. The validity of previous modeling studies in determining

iv

the exchange rate of gases and particles is evaluated with detailed descriptions of their

limitations. Mechanistic-based modeling approaches along with empirical studies

across dierent scales are employed to rene the mathematical descriptions of surface

conductance responsible for gas and particle exchanges as commonly adopted by all

operational models. Specically, how variation in horizontal leaf area density within

the vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributes

and thereby the ultrane particle collection eciency at the leaf/branch scale

is explored using wind tunnel experiments with interpretations by a porous media

model and a scaling analysis. A multi-layered and size-resolved second-order closure

model combined with particle

uxes and concentration measurements within and

above a forest is used to explore the particle transport processes within the canopy

sub-layer and the partitioning of particle deposition onto canopy medium and forest

oor. For gases, a modeling framework accounting for the leaf-level boundary layer

eects on the stomatal pathway for gas exchange is proposed and combined with sap

ux measurements in a wind tunnel to assess how leaf-level transpiration varies with

increasing wind speed. How exogenous environmental conditions and endogenous

soil-root-stem-leaf hydraulic and eco-physiological properties impact the above- and

below-ground water dynamics in the soil-plant system and shape plant responses

to droughts is assessed by a porous media model that accommodates the transient

water

ow within the plant vascular system and is coupled with the aforementioned

leaf-level gas exchange model and soil-root interaction model. It should be noted

that tackling all aspects of potential issues causing uncertainties in forecasting the

feedback cycle between terrestrial ecosystem and the climate is unrealistic in a single

dissertation but further research questions and opportunities based on the foundation

derived from this dissertation are also brie

y discussed.

RNA Localization and Translational Regulation on the Endoplasmic Reticulum

mRNA localization is emerging as a critical cellular mechanism for the spatiotemporal regulation of protein expression and serves important roles in oogenesis, embryogenesis, cell fate specification, and synapse formation. Signal sequence-encoding mRNAs are localized to the endoplasmic reticulum (ER) membrane by either of two mechanisms, a canonical mechanism of translation on ER-bound ribosomes (signal recognition particle pathway), or a poorly understood direct ER anchoring mechanism. In this study, we identify that the ER integral membrane proteins function as RNA-binding proteins and play important roles in the direct mRNA anchoring to the ER. We report that one of the ER integral membrane RNA-binding protein, AEG-1 (astrocyte elevated gene-1), functions in the direct ER anchoring and translational regulation of mRNAs encoding endomembrane transmembrane proteins. HITS-CLIP and PAR-CLIP analyses of the AEG-1 mRNA interactome of human hepatocellular carcinoma cells revealed a high enrichment for mRNAs encoding endomembrane organelle proteins, most notably encoding transmembrane proteins. AEG-1 binding sites were highly enriched in the coding sequence and displayed a signature cluster enrichment downstream of encoded transmembrane domains. In overexpression and knockdown models, AEG-1 expression markedly regulates translational efficiency and protein functions of two of its bound transcripts, MDR1 and NPC1. This study reveals a molecular mechanism for the selective localization of mRNAs to the ER and identifies a novel post-transcriptional gene regulation function for AEG-1 in membrane protein expression.

Global surface net-radiation at 5 km from MODIS Terra

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott’s index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W∙m−2 in boreal to 72.0 ± 4.1 W∙m−2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° × 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth’s Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W•m−2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth’s surface.

Spatial and temporal specificity of Ca2+signalling inChlamydomonas reinhardtiiin response to osmotic stress

Ca2+-dependent signalling processes enable plants to perceive and respond to diverse environmental stressors, such as osmotic stress. A clear understanding of the role of spatiotemporal Ca2+ signalling in green algal lineages is necessary in order to understand how the Ca2+ signalling machinery has evolved in land plants. We used single-cell imaging of Ca2+-responsive fluorescent dyes in the unicellular green alga Chlamydomonas reinhardtii to examine the specificity of spatial and temporal dynamics of Ca2+ elevations in the cytosol and flagella in response to salinity and osmotic stress. We found that salt stress induced a single Ca2+ elevation that was modulated by the strength of the stimulus and originated in the apex of the cell, spreading as a fast Ca2+ wave. By contrast, hypo-osmotic stress induced a series of repetitive Ca2+ elevations in the cytosol that were spatially uniform. Hypo-osmotic stimuli also induced Ca2+ elevations in the flagella that occurred independently from those in the cytosol. Our results indicate that the requirement for Ca2+ signalling in response to osmotic stress is conserved between land plants and green algae, but the distinct spatial and temporal dynamics of osmotic Ca2+ elevations in C. reinhardtii suggest important mechanistic differences between the two lineages.

Spatial and temporal specificity of Ca2+signalling inChlamydomonas reinhardtiiin response to osmotic stress

Ca2+-dependent signalling processes enable plants to perceive and respond to diverse environmental stressors, such as osmotic stress. A clear understanding of the role of spatiotemporal Ca2+ signalling in green algal lineages is necessary in order to understand how the Ca2+ signalling machinery has evolved in land plants. We used single-cell imaging of Ca2+-responsive fluorescent dyes in the unicellular green alga Chlamydomonas reinhardtii to examine the specificity of spatial and temporal dynamics of Ca2+ elevations in the cytosol and flagella in response to salinity and osmotic stress. We found that salt stress induced a single Ca2+ elevation that was modulated by the strength of the stimulus and originated in the apex of the cell, spreading as a fast Ca2+ wave. By contrast, hypo-osmotic stress induced a series of repetitive Ca2+ elevations in the cytosol that were spatially uniform. Hypo-osmotic stimuli also induced Ca2+ elevations in the flagella that occurred independently from those in the cytosol. Our results indicate that the requirement for Ca2+ signalling in response to osmotic stress is conserved between land plants and green algae, but the distinct spatial and temporal dynamics of osmotic Ca2+ elevations in C. reinhardtii suggest important mechanistic differences between the two lineages.

Historical comparisons reveal multiple drivers of decadal change of an ecosystem engineer at the range edge

Biogenic reefs are important for habitat provision and coastal protection. Long-term datasets on the distribution and abundance of Sabellaria alveolata (L.) are available from Britain. The aim of this study was to combine historical records and contemporary data to (1) describe spatiotemporal variation in winter temperatures, (2) document short-term and long-term changes in the distribution and abundance of S. alveolata and discuss these changes in relation to extreme weather events and recent warming, and (3) assess the potential for artificial coastal defense structures to function as habitat for S. alveolata. A semi-quantitative abundance scale (ACFOR) was used to compare broadscale, long-term and interannual abundance of S. alveolata near its range edge in NW Britain. S. alveolata disappeared from the North Wales and Wirral coastlines where it had been abundant prior to the cold winter of 1962/1963. Population declines were also observed following the recent cold winters of 2009/2010 and 2010/2011. Extensive surveys in 2004 and 2012 revealed that S. alveolata had recolonized locations from which it had previously disappeared. Furthermore, it had increased in abundance at many locations, possibly in response to recent warming. S. alveolata was recorded on the majority of artificial coastal defense structures surveyed, suggesting that the proliferation of artificial coastal defense structures along this stretch of coastline may have enabled S. alveolata to spread across stretches of unsuitable natural habitat. Long-term and broadscale contextual monitoring is essential for monitoring responses of organisms to climate change. Historical data and gray literature can be invaluable sources of information. Our results support the theory that Lusitanian species are responding positively to climate warming but also that short-term extreme weather events can have potentially devastating widespread and lasting effects on organisms. Furthermore, the proliferation of coastal defense structures has implications for phylogeography, population genetics, and connectivity of coastal populations.