The interaction among leukocytes is at the basis of the innate and adaptive immune-response and it is largely ascribed to direct cell-cell contacts. However, the exchange of a number of chemical stimuli (chemokines) allows also non-contact interaction during the immunological response. We want here to evaluate the extent of the effect of the non-contact interactions on the observed leukocyte-leukocyte kinematics and their interaction duration. To this aim we adopt a simplified mean field description inspired by the Keller-Segel chemotaxis model, of which we report an analytical solution suited for slowly varying sources of chemokines. Since our focus is on the non-contact interactions, leukocyte-leukocyte contact interactions are simulated only by means of a space dependent friction coefficient of the cells. The analytical solution of the Keller-Segel model is then taken as the basis of numerical simulations of interactions between leukocytes and their duration. The mean field interaction force that we derive has a time-space separable form and depends on the chemotaxis sensitivity parameter as well as on the chemokines diffusion coefficient and their degradation rate. All these parameters affect the distribution of the interaction durations. We draw a successful qualitative comparison between simulated data and sets of experimental data for DC-NK cells interaction duration and other kinematic parameters. Remarkably, the predicted percentage of the leukocyte-leukocyte interactions falls in the experimental range and depends (≅25% increase) upon the chemotactic parameter indicating a non-negligible direct effect of the non-contact interaction on the leukocyte interactions.
Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems.
Long-term (1973 to 2010) trends in visibility at Chengdu, China were investigated using meteorological data from the U.S. National Climatic Data Center. The visual range exhibited a declining trend before 1982, a slight increase between 1983 and 1995, a sharp decrease between 1996 and 2005, and some improvements after 2006. The trends in visibility were generally consistent with the economic development and implementation of pollution controls in China. Intensive PM2.5 measurements were conducted from 2009 to 2010 to determine the causes of visibility degradation. An analysis based on a modification of the IMPROVE approach indicated that PM2.5 ammonium bisulfate contributed 27.7% to the light extinction coefficient (bext); this was followed by organic mass (21.7%), moisture (20.6%), and ammonium nitrate (16.3%). Contributions from elemental carbon (9.4%) and soil dust (4.3%) were relatively minor. Anthropogenic aerosol components (sulfate, nitrate, and elemental carbon) and moisture at the surface also were important determinants of the aerosol optical depth (AOD) at 550 nm, and the spatial distributions of both bext and AOD were strongly affected by regional topography. A Positive Matrix Factorization receptor model suggested that coal combustion was the largest contributor to PM2.5 mass (42.3%) and the dry-air light-scattering coefficient (47.7%); this was followed by vehicular emissions (23.4% and 20.5%, respectively), industrial emissions (14.9% and 18.8%), biomass burning (12.8% and 11.9%), and fugitive dust (6.6% and 1.1%). Our observations provide a scientific basis for improving visibility in this area.
The confirmatory diagnosis of Osteogenesis Imperfecta (OI) requires invasive, commonly bone biopsy, time consuming and destructive methods. This paper proposes an alternative method using a combination of two-photon excitation fluorescence (TPEF) and second-harmonic generation (SHG) microscopies from easily obtained human skin biopsies. We show that this method can distinguish subtypes of human OI.
Different aspects of collagen microstructure of skin fresh biopsies and standard H&E-stained sections of normal and OI patients (mild and severe forms) were distinguished by TPEF and SHG images. Moreover, important differences between subtypes of OI were identified using different methods of quantification such as collagen density, ratio between collagen and elastic tissue, and gray-level co-occurrence matrix (GLCM) image-pattern analysis. Collagen density was lower in OI dermis, while the SHG/autofluorescence index of the dermis was significantly higher in OI as compared to that of the normal skin. We also showed that the energy value of GLCM texture analysis is useful to discriminate mild from severe OI and from normal skin.
This work demonstrated that nonlinear microscopy techniques in combination with image-analysis approaches represent a powerful tool to investigate the collagen organization in skin dermis in patients with OI and has the potential to distinguish the different types of OI. The procedure outlined in this paper requires a skin biopsy, which is almost painless as compared to the bone biopsy commonly used in conventional methods. The data presented here complement existing clinical diagnostic techniques and can be used as a diagnostic procedure to confirm the disease, evaluate its severity and treatment efficacy.
In the last two decades, nano manipulation has been recognized as a potential tool of scientific interest especially in nanotechnology and nano-robotics. Contemporary optical microscopy (super resolution) techniques have also reached the nanometer scale resolution to visualize this and hence a combination of super resolution aided nano manipulation ineluctably gives a new perspective to the scenario. Here we demonstrate how specificity and rapid determination of structures provided by stimulated emission depletion (STED) microscope can aid another microscopic tool with capability of mechanical manoeuvring, like an atomic force microscope (AFM) to get topological information or to target nano scaled materials. We also give proof of principle on how high-resolution real time visualization can improve nano manipulation capability within a dense sample, and how STED-AFM is an optimal combination for this job. With these evidences, this article points to future precise nano dissections and maybe even to a nano-snooker game with an AFM tip and fluorospheres.
In a stimulated emission depletion (STED) microscope the region in which fluorescence markers can emit spontaneously shrinks with continued STED beam action after a singular excitation event. This fact has been recently used to substantially improve the effective spatial resolution in STED nanoscopy using time-gated detection, pulsed excitation and continuous wave (CW) STED beams. We present a theoretical framework and experimental data that characterize the time evolution of the effective point-spread-function of a STED microscope and illustrate the physical basis, the benefits, and the limitations of time-gated detection both for CW and pulsed STED lasers. While gating hardly improves the effective resolution in the all-pulsed modality, in the CW-STED modality gating strongly suppresses low spatial frequencies in the image. Gated CW-STED nanoscopy is in essence limited (only) by the reduction of the signal that is associated with gating. Time-gated detection also reduces/suppresses the influence of local variations of the fluorescence lifetime on STED microscopy resolution.
Large quantities of radionuclides have leaked from the Fukushima Daiichi Nuclear Power Plant into the surrounding environment. Effective prevention of health hazards resulting from radiation exposure will require the development of efficient and economical methods for decontaminating radioactive wastewater and aquatic ecosystems. Here we describe the accumulation of water-soluble radionuclides released by nuclear reactors by a novel strain of alga. The newly discovered green microalgae, Parachlorella sp. binos (Binos) has a thick alginate-containing extracellular matrix and abundant chloroplasts. When this strain was cultured with radioiodine, a light-dependent uptake of radioiodine was observed. In dark conditions, radioiodine uptake was induced by addition of hydrogen superoxide. High-resolution secondary ion mass spectrometry (SIMS) showed a localization of accumulated iodine in the cytosol. This alga also exhibited highly efficient incorporation of the radioactive isotopes strontium and cesium in a light-independent manner. SIMS analysis showed that strontium was distributed in the extracellular matrix of Binos. Finally we also showed the ability of this strain to accumulate radioactive nuclides from water and soil samples collected from a heavily contaminated area in Fukushima. Our results demonstrate that Binos could be applied to the decontamination of iodine, strontium and cesium radioisotopes, which are most commonly encountered after nuclear reactor accidents.
The limited stability of proteins in vitro and in vivo reduces their conversion into effective biopharmaceuticals. To overcome this problem several strategies can be exploited, as the conjugation of the protein of interest with polyethylene glycol, in most cases, improves its stability and pharmacokinetics. In this work, we report a biophysical characterization of the non-pegylated and of two different site-specific mono-pegylated forms of recombinant human methionyl-granulocyte colony stimulating factor (Met-G-CSF), a protein used in chemotherapy and bone marrow transplantation. In particular, we found that the two mono-pegylations of Met-G-CSF at the N-terminal methionine and at glutamine 135 increase the protein thermal stability, reduce the aggregation propensity, preventing also protein precipitation, as revealed by circular dichroism (CD), Fourier transform infrared (FTIR), intrinsic fluorescence spectroscopies and dynamic light scattering (DLS). Interestingly, the two pegylation strategies were found to drastically reduce the polydispersity of Met-G-CSF, when incubated under conditions favouring protein aggregation, as indicated by DLS measurements. Our in vitro results are in agreement with preclinical studies, underlining that preliminary biophysical analyses, performed in the early stages of the development of new biopharmaceutical variants, might offer a useful tool for the identification of protein variants with improved therapeutic values.
The autofluorescence background of biological samples impedes the detection of single molecules when imaging. The most common method of reducing the background is to use evanescent field excitation, which is incompatible with imaging beyond the surface of biological samples. An alternative would be to use probes that can be excited in the near infra-red region of the spectrum, where autofluorescence is low. Such probes could also increase the number of labels that can be imaged in multicolour single molecule microscopes. Despite being widely used in ensemble imaging, there is a currently a shortage of information available for selecting appropriate commercial near infra-red dyes for single molecule work. It is therefore important to characterise available near infra-red dyes relevant to multicolour single molecule imaging.
A range of commercially available near infra-red dyes compatible with multi-colour imaging was screened to find the brightest and most photostable candidates. Image series of immobilised samples of the brightest dyes (Alexa 700, IRDye 700DX, Alexa 790 and IRDye 800CW) were analysed to obtain the mean intensity of single dye molecules, their photobleaching rates and long period blinking kinetics. Using the optimum dye pair, we have demonstrated for the first time widefield, multi-colour, near infra-red single molecule imaging using a supercontinuum light source in MCF-7 cells.
We have demonstrated that near infra-red dyes can be used to avoid autofluorescence background in samples where restricting the illumination volume of visible light fails or is inappropriate. We have also shown that supercontinuum sources are suited to single molecule multicolour imaging throughout the 470–1000 nm range. Our measurements of near infra-red dye properties will enable others to select optimal dyes for single molecule imaging.
One of the several uses of sucrose detergents, as well as other micelle forming detergents, is the solubilization of different membrane proteins. Accurate knowledge of the micelle properties, including size and shape, are needed to optimize the surfactant conditions for protein purification and membrane characterization. We synthesized sucrose esters having different numbers of methylene subunits on the substituent to correlate the number of methylene groups with the size of the corresponding micelles. We used Fluorescence Correlation Spectroscopy (FCS) and two photon excitation to determine the translational D of the micelles and calculate their corresponding hydrodynamic radius, Rh. As a fluorescent probe we used LAURDAN (6-dodecanoyl-2-dimethylaminonaphthalene), a dye highly fluorescent when integrated in the micelle and non-fluorescent in aqueous media. We found a linear correlation between the size of the tail and the hydrodynamic radius of the micelle for the series of detergents measured.
Many biological systems consist of multiple cells that interact by secretion and binding of diffusing molecules, thus coordinating responses across cells. Techniques for simulating systems coupling extracellular and intracellular processes are very limited. Here we present an efficient method to stochastically simulate diffusion processes, which at the same time allows synchronization between internal and external cellular conditions through a modification of Gillespie's chemical reaction algorithm. Individual cells are simulated as independent agents, and each cell accurately reacts to changes in its local environment affected by diffusing molecules. Such a simulation provides time-scale separation between the intra-cellular and extra-cellular processes. We use our methodology to study how human monocyte-derived dendritic cells alert neighboring cells about viral infection using diffusing interferon molecules. A subpopulation of the infected cells reacts early to the infection and secretes interferon into the extra-cellular medium, which helps activate other cells. Findings predicted by our simulation and confirmed by experimental results suggest that the early activation is largely independent of the fraction of infected cells and is thus both sensitive and robust. The concordance with the experimental results supports the value of our method for overcoming the challenges of accurately simulating multiscale biological signaling systems.
Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.
There exist several methods for calculating the fractal dimension of objects represented as 2D digital images. For example, Box counting, Minkowski dilation or Fourier analysis can be employed. However, there appear to be some limitations. It is not possible to calculate only the fractal dimension of an irregular region of interest in an image or to perform the calculations in a particular direction along a line on an arbitrary angle through the image. The calculations must be made for the whole image. In this paper, a new method to overcome these limitations is proposed. 2D images are appropriately prepared in order to apply 1D signal analyses, originally developed to investigate nonlinear time series. The Higuchi dimension of these 1D signals is calculated using Higuchi's algorithm, and it is shown that both regions of interests and directional dependencies can be evaluated independently of the whole picture. A thorough validation of the proposed technique and a comparison of the new method to the Fourier dimension, a common two dimensional method for digital images, are given. The main result is that Higuchi's algorithm allows a direction dependent as well as direction independent analysis. Actual values for the fractal dimensions are reliable and an effective treatment of regions of interests is possible. Moreover, the proposed method is not restricted to Higuchi's algorithm, as any 1D method of analysis, can be applied.
When CdSe/ZnS-polyethyleneimine (PEI) quantum dots (QDs) are microencapsulated in polymeric microcapsules, human fibroblasts are protected from acute cytotoxic effects. Differences in cellular morphology, uptake, and viability were assessed after treatment with either microencapsulated or unencapsulated dots. Specifically, QDs contained in microcapsules terminated with polyethylene glycol (PEG) mitigate contact with and uptake by cells, thus providing a tool to retain particle luminescence for applications such as extracellular sensing and imaging. The microcapsule serves as the “first line of defense” for containing the QDs. This enables the individual QD coating to be designed primarily to enhance the function of the biosensor.
In forensic science, age determination of bloodstains can be crucial in reconstructing crimes. Upon exiting the body, bloodstains transit from bright red to dark brown, which is attributed to oxidation of oxy-hemoglobin (HbO2) to met-hemoglobin (met-Hb) and hemichrome (HC). The fractions of HbO2, met-Hb and HC in a bloodstain can be used for age determination of bloodstains. In this study, we further analyze the conversion of HbO2 to met-Hb and HC, and determine the effect of temperature and humidity on the conversion rates.
The fractions of HbO2, met-Hb and HC in a bloodstain, as determined by quantitative analysis of optical reflectance spectra (450–800 nm), were measured as function of age, temperature and humidity. Additionally, Optical Coherence Tomography around 1300 nm was used to confirm quantitative spectral analysis approach.
The oxidation rate of HbO2 in bloodstains is biphasic. At first, the oxidation of HbO2 is rapid, but slows down after a few hours. These oxidation rates are strongly temperature dependent. However, the oxidation of HbO2 seems to be independent of humidity, whereas the transition of met-Hb into HC strongly depends on humidity. Knowledge of these decay rates is indispensable for translating laboratory results into forensic practice, and to enable bloodstain age determination on the crime scene.
A hallmark of positive-feedback regulation is bistability, which gives rise to distinct cellular states with high and low expression levels, and that stochasticity in gene expression can cause random transitions between two states, yielding bimodal population distribution (Kaern et al., 2005, Nat Rev Genet 6: 451-464). In this paper, the probability transition rate and first-passage time in an autoactivating positive-feedback loop with bistability are investigated, where the gene expression is assumed to be disturbed by both additive and multiplicative external noises, the bimodality in the stochastic gene expression is due to the bistability, and the bistability determines that the potential of the Fokker-Planck equation has two potential wells. Our main goal is to illustrate how the probability transition rate and first-passage time are affected by the maximum transcriptional rate, the intensities of additive and multiplicative noises, and the correlation of additive and multiplicative noises. Our main results show that (i) the increase of the maximum transcription rate will be useful for maintaining a high gene expression level; (ii) the probability transition rate from one potential well to the other one will increase with the increase of the intensity of additive noise; (iii) the increase of multiplicative noise strength will increase the amount of probability in the left potential well; and (iv) positive (or negative) cross-correlation between additive and multiplicative noises will increase the amount of probability in the left (or right) potential well.
Current advanced laser, optics and electronics technology allows sensitive recording of molecular dynamics, from single resonance to multi-colour and multi-pulse experiments. Extracting the occurring (bio-) physical relevant pathways via global analysis of experimental data requires a systematic investigation of connectivity schemes. Here we present a Matlab-based toolbox for this purpose. The toolbox has a graphical user interface which facilitates the application of different reaction models to the data to generate the coupled differential equations. Any time-dependent dataset can be analysed to extract time-independent correlations of the observables by using gradient or direct search methods. Specific capabilities (i.e. chirp and instrument response function) for the analysis of ultrafast pump-probe spectroscopic data are included. The inclusion of an extra pulse that interacts with a transient phase can help to disentangle complex interdependent pathways. The modelling of pathways is therefore extended by new theory (which is included in the toolbox) that describes the finite bleach (orientation) effect of single and multiple intense polarised femtosecond pulses on an ensemble of randomly oriented particles in the presence of population decay. For instance, the generally assumed flat-top multimode beam profile is adapted to a more realistic Gaussian shape, exposing the need for several corrections for accurate anisotropy measurements. In addition, the (selective) excitation (photoselection) and anisotropy of populations that interact with single or multiple intense polarised laser pulses is demonstrated as function of power density and beam profile. Using example values of real world experiments it is calculated to what extent this effectively orients the ensemble of particles. Finally, the implementation includes the interaction with multiple pulses in addition to depth averaging in optically dense samples. In summary, we show that mathematical modelling is essential to model and resolve the details of physical behaviour of populations in ultrafast spectroscopy such as pump-probe, pump-dump-probe and pump-repump-probe experiments.
Internal motions enable proteins to explore a range of conformations, even in the vicinity of native state. The role of conformational fluctuations in the designated function of a protein is widely debated. Emerging evidence suggests that sub-groups within the range of conformations (or sub-states) contain properties that may be functionally relevant. However, low populations in these sub-states and the transient nature of conformational transitions between these sub-states present significant challenges for their identification and characterization.
Methods and Findings
To overcome these challenges we have developed a new computational technique, quasi-anharmonic analysis (QAA). QAA utilizes higher-order statistics of protein motions to identify sub-states in the conformational landscape. Further, the focus on anharmonicity allows identification of conformational fluctuations that enable transitions between sub-states. QAA applied to equilibrium simulations of human ubiquitin and T4 lysozyme reveals functionally relevant sub-states and protein motions involved in molecular recognition. In combination with a reaction pathway sampling method, QAA characterizes conformational sub-states associated with cis/trans peptidyl-prolyl isomerization catalyzed by the enzyme cyclophilin A. In these three proteins, QAA allows identification of conformational sub-states, with critical structural and dynamical features relevant to protein function.
Overall, QAA provides a novel framework to intuitively understand the biophysical basis of conformational diversity and its relevance to protein function.
One striking feature of chromatin organization is that chromosomes are compartmentalized into distinct territories during interphase, the degree of intermingling being much smaller than expected for linear chains. A growing body of evidence indicates that the formation of loops plays a dominant role in transcriptional regulation as well as the entropic organization of interphase chromosomes. Using a recently proposed model, we quantitatively determine the entropic forces between chromosomes. This Dynamic Loop Model assumes that loops form solely on the basis of diffusional motion without invoking other long-range interactions. We find that introducing loops into the structure of chromatin results in a multi-fold higher repulsion between chromosomes compared to linear chains. Strong effects are observed for the tendency of a non-random alignment; the overlap volume between chromosomes decays fast with increasing loop number. Our results suggest that the formation of chromatin loops imposes both compartmentalization as well as order on the system without requiring additional energy-consuming processes.
In biophotonics, the light absorption in a tissue is usually modeled by the Helmholtz equation with two constant parameters, the scattering coefficient and the absorption coefficient. This classic approximation of “haemoglobin diluted everywhere” (constant absorption coefficient) corresponds to the classical homogenization approach. The paper discusses the limitations of this approach. The scattering coefficient is supposed to be constant (equal to one) while the absorption coefficient is equal to zero everywhere except for a periodic set of thin parallel strips simulating the blood vessels, where it is a large parameter The problem contains two other parameters which are small: , the ratio of the distance between the axes of vessels to the characteristic macroscopic size, and , the ratio of the thickness of thin vessels and the period. We construct asymptotic expansion in two cases: and and prove that in the first case the classical homogenization (averaging) of the differential equation is true while in the second case it is wrong. This result may be applied in the biomedical optics, for instance, in the modeling of the skin and cosmetics.
Aggregation and cytotoxicity of mutant proteins containing an expanded number of polyglutamine (polyQ) repeats is a hallmark of several diseases, including Huntington's disease (HD). Within cells, mutant Huntingtin (mHtt) and other polyglutamine expansion mutant proteins exist as monomers, soluble oligomers, and insoluble inclusion bodies (IBs). Determining which of these forms constitute a toxic species has proven difficult. Recent studies support a role for IBs as a cellular coping mechanism to sequester levels of potentially toxic soluble monomeric and oligomeric species of mHtt.
When fused to a fluorescent reporter (GFP) and expressed in cells, the soluble monomeric and oligomeric polyglutamine species are visually indistinguishable. Here, we describe two complementary biophysical fluorescence microscopy techniques to directly detect soluble polyglutamine oligomers (using Htt exon 1 or Httex1) and monitor their fates in live cells. Photobleaching analyses revealed a significant reduction in the mobilities of mHttex1 variants consistent with their incorporation into soluble microcomplexes. Similarly, when fused to split-GFP constructs, both wildtype and mHttex1 formed oligomers, as evidenced by the formation of a fluorescent reporter. Only the mHttex1 split-GFP oligomers assembled into IBs. Both FRAP and split-GFP approaches confirmed the ability of mHttex1 to bind and incorporate wildtype Htt into soluble oligomers. We exploited the irreversible binding of split-GFP fragments to forcibly increase levels of soluble oligomeric mHttex1. A corresponding increase in the rate of IBs formation and the number formed was observed. Importantly, higher levels of soluble mHttex1 oligomers significantly correlated with increased mutant cytotoxicity, independent of the presence of IBs.
Our study describes powerful and sensitive tools for investigating soluble oligomeric forms of expanded polyglutamine proteins, and their impact on cell viability. Moreover, these methods should be applicable for the detection of soluble oligomers of a wide variety of aggregation prone proteins.
In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.
Crustose lichen communities on rocks exhibit fascinating spatial mosaics resembling political maps of nations or municipalities. Although the establishment and development of biological populations are important themes in ecology, our understanding of the formation of such patterns on the rocks is still in its infancy. Here, we present a novel model of the concurrent growth, establishment and interaction of lichens. We introduce an inverse technique based on Monte Carlo simulations to test our model on field samples of lichen communities. We derive an expression for the time needed for a community to cover a surface and predict the historical spatial dynamics of field samples. Lichens are frequently used for dating the time of exposure of rocks in glacial deposits, lake retreats or rock falls. We suggest our method as a way to improve the dating.
The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.
Microscopic techniques enable real-space imaging of complex biological events and processes. They have become an essential tool to confirm and complement hypotheses made by biomedical scientists and also allow the re-examination of existing models, hence influencing future investigations. Particularly imaging live cells is crucial for an improved understanding of dynamic biological processes, however hitherto live cell imaging has been limited by the necessity to introduce probes within a cell without altering its physiological and structural integrity. We demonstrate herein that this hurdle can be overcome by effective cytosolic delivery.
We show the delivery within several types of mammalian cells using nanometre-sized biomimetic polymer vesicles (a.k.a. polymersomes) that offer both highly efficient cellular uptake and endolysomal escape capability without any effect on the cellular metabolic activity. Such biocompatible polymersomes can encapsulate various types of probes including cell membrane probes and nucleic acid probes as well as labelled nucleic acids, antibodies and quantum dots.
We show the delivery of sufficient quantities of probes to the cytosol, allowing sustained functional imaging of live cells over time periods of days to weeks. Finally the combination of such effective staining with three-dimensional imaging by confocal laser scanning microscopy allows cell imaging in complex three-dimensional environments under both mono-culture and co-culture conditions. Thus cell migration and proliferation can be studied in models that are much closer to the in vivo situation.