Добірка наукової літератури з теми "Biochemical and biophysical PTs variability"

Epithelial cells cultured within collagen and laminin gels proliferate to form hollow and polarized spherical structures, recapitulating the formation of a rudimentary epithelial organ. However, the contributions of extracellular matrix (ECM) biochemical and biophysical properties to morphogenesis are poorly understood because of uncontrolled presentation of multiple adhesive ligands, limited control over mechanical properties, and lot-to-lot compositional variability in these natural ECMs. We engineered synthetic ECM-mimetic hydrogels with independent control over adhesive ligand density, mechanical properties, and proteolytic degradation to study the impact of ECM properties on epithelial morphogenesis. Normal cyst growth, polarization, and lumen formation were restricted to a narrow range of ECM elasticity, whereas abnormal morphogenesis was observed at lower and higher elastic moduli. Adhesive ligand density dramatically regulated apicobasal polarity and lumenogenesis independently of cell proliferation. Finally, a threshold level of ECM protease degradability was required for apicobasal polarity and lumen formation. This synthetic ECM technology provides new insights into how cells transduce ECM properties into complex morphogenetic behaviors.

Abstract. We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar/Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry–climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry–climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2= 64–96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 Tg C yr-1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

Abstract. We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64–96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr−1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.

The formation and deposition of fibrils derived from immunglobulin light chains is a hallmark of systemic AL amyloidosis. A particularly remarkable feature of the disease is the diversity and complexity in pathophysiology and clinical manifestations. This is related to the variability of immunoglobulins, as virtually every patient has a variety of mutations resulting in their own unique AL protein and thus a unique fibril deposited in the body. Here, I review recent biochemical and biophysical studies that have expanded our knowledge on how versatile the structure of AL fibrils in patients is and highlight their implications for the molecular mechanism of fibril formation in AL amyloidosis.

Abstract The single-cell resolution of flow cytometry provides a quantitative measurement of the heterogeneity of protein expression within clonal populations of cells. As the biological significance of this variability is becoming more widely appreciated, there is a need for new tools and methodology to analyze and leverage the effects of endogenous variation. These tools can provide alternatives to genetic methods, such as siRNA knockdown or germline knockout, that are commonly used to manipulate protein expression. We introduce such a new tool, named ScatterSlice, that enables rapid quantification of the correlation between heterogeneity in cellular responses (measured by staining of phospho-proteins) and varied expression of signaling molecules. We demonstrate its application to the validation of biochemical models of cellular responses to IL-2, IL-7, and IL-15 in living, unperturbed cells. In addition, we demonstrate that heterogeneous distribution of receptor subunits within a population of lymphocytes results in gradations of sensitivity to each cytokine. Finally, using experimental measurements of error and uncertainty in combination with biochemical models, we demonstrate the robustness of this analysis to experimental noise, and consider both limits and extensions to its use.

Background: Skinboosters represent the latest category of hyaluronan (HA) hydrogels released for aesthetic purposes. Different from originally developed gels, they are intended for more superficial injections, claiming a skin rejuvenation effect through hydration and possibly prompting biochemical effects in place of the conventional volumetric action. Here, three commercial skinboosters were characterized to unravel the scientific basis for such indication and to compare their performances. Methods: Gels were evaluated for water-soluble/insoluble-HA composition, rheology, hydration, cohesivity, stability and effect, in vitro, on human dermal fibroblasts towards the production of extracellular matrix components. Results: Marked differences in the insoluble-hydrogel amount and in the hydrodynamic parameters for water-soluble-HA chains were evidenced among the gels. Hydration, rigidity and cohesivity also varied over a wide range. Sensitivity to hyaluronidases and Reactive Oxygen Species was demonstrated allowing a stability ranking. Slight differences were found in gels’ ability to prompt elastin expression and in ColIV/ColI ratio. Conclusions. A wide panel of biophysical and biochemical parameters for skinboosters was provided, supporting clinicians in the conscious tuning of their use. Data revealed great variability in gels’ behavior notwithstanding the same clinical indication and unexpected similarities to the volumetric formulations. Data may be useful to improve customization of gel design toward specific uses.

CA125 is a tumor antigen used to monitor the progression and regression of epithelial ovarian cancer. Despite the widespread use of CA125, the biochemical and molecular nature of this antigen is poorly understood. Analysis of the structure of CA125 is essential for determining the physiological role of this very significant tumor marker. Accumulated experimental evidence has shown that CA125 epitopes reside on a molecule of very complex architecture in terms of both protein backbone and oligosaccharide structures. It is not clear whether the heterogeneity of CA125 molecular characteristics are due to the variability of biological sources from which the molecule was isolated or to the different biophysical methods used for the characterization of all the oligosaccharides linked to CA125 or to the presence of glycoisoforms for this protein. This review attempts to summarize emerging data related to molecular characteristics of CA125 and to compare approaches undertaken to reach a better understanding of molecular features of this tumor marker.

Cell-free extracts from unfertilized Xenopus laevis eggs offer the opportunity for a variety of biochemical and biophysical assays for analyzing essential cell cycle events such as metaphase spindle assembly. However, the extracts often exhibit substantial variation in quality and have low storage stability, factors that hamper their experimental utility. Here we report a simple two-step method for preparing frozen egg extracts that retain spindle assembly activity levels similar to those of freshly prepared extracts. Extract degradation associated with the freeze–thaw process can be substantially reduced by using centrifugal filter-based dehydration and slow sample cooling. Large amounts of frozen extract stocks from single-batch preparations allowed us to collect extensive data in micromanipulation experiments, which are often low-throughput, and thus enabled the clarification of correlations between metaphase spindle size and stiffness. Our method provides an assay platform with minimized biological variability and improves the accessibility of egg extracts for research.

Vegetation indices (VIs) are widely used in optical remote sensing to estimate biophysical variables of vegetated surfaces. With the advent of spectroscopy technology, spectral bands can be combined in numerous ways to extract the desired information. This resulted in a plethora of proposed indices, designed for a diversity of applications and research purposes. However, it is not always clear whether they are sensitive to the variable of interest while at the same time, responding insensitive to confounding factors. Hence, to be able to quantify the robustness of VIs, a systematic evaluation is needed, thereby introducing a widest possible variety of biochemical and structural heterogeneity. Such exercise can be achieved with coupled leaf and canopy radiative transfer models (RTMs), whereby input variables can virtually simulate any vegetation scenario. With the intention of evaluating multiple VIs in an efficient way, this led us to the development of a global sensitivity analysis (GSA) toolbox dedicated to the analysis of VIs on their sensitivity towards RTM input variables. We identified VIs that are designed to be sensitive towards leaf chlorophyll content (LCC), leaf water content (LWC) and leaf area index (LAI) for common sensors of terrestrial Earth observation satellites: Landsat 8, MODIS, Sentinel-2, Sentinel-3 and the upcoming imaging spectrometer mission EnMAP. The coupled RTMs PROSAIL and PROINFORM were used for simulations of homogeneous and forest canopies respectively. GSA total sensitivity results suggest that LCC-sensitive indices respond most robust: for the great majority of scenarios, chlorophyll a + b content (Cab) drives between 75% and 82% of the indices’ variability. LWC-sensitive indices were most affected by confounding variables such as Cab and LAI, although the equivalent water thickness (Cw) can drive between 25% and 50% of the indices’ variability. Conversely, the majority of LAI-sensitive indices are not only sensitive to LAI but rather to a mixture of structural and biochemical variables.

Grasslands are one of the most important ecosystems on Earth, covering approximately one-third of the Earth’s surface. Grassland biodiversity is important as many services provided by such ecosystems are crucial for the human economy and well-being. Given the importance of grasslands ecosystems, in recent years research has been carried out on the potential to monitor them with novel remote sensing techniques. Improved detectors technology and novel sensors providing fine-scale hyperspectral imagery have been enabling new methods to monitor plant traits (PTs) and biodiversity. The aims of the work were to study different approaches to monitor key grassland PTs such as Leaf Area Index (LAI) and biodiversity-related traits. The thesis consists of 3 parts: 1) Evaluating the performance of remote sensing methods to estimate LAI in grassland ecosystems, 2) Estimating plant biodiversity by using the optical diversity approach in grassland ecosystems, and 3) Investigating the relationship between PTs variability with alpha and beta diversity for the applicability of the optical diversity approach in a subalpine grassland of the Italian Alps To evaluate the performance of remote sensing methods to estimate LAI, temporal and spatial observations of hyperspectral reflectance and LAI were analyzed at a grassland site in Monte Bondone, Italy (IT-MBo). In 2018, ground temporal observations of hyperspectral reflectance and LAI were carried out at a grassland site in Neustift, Austria (AT-NEU). To estimate biodiversity, in 2018 and 2019 a floristics survey was conducted to determine species composition and hyperspectral data were acquired at two grassland sites: IT-MBo and University of Padova’s Experimental Farm, Legnaro, Padua, Italy (IT-PD) respectively. Furthermore, in 2018, biochemistry analysis of the biomass samples collected from the grassland site IT-MBo was carried out to determine the foliar biochemical PTs variability. The results of the thesis demonstrated that the grassland spectral response across different spectral regions (Visible: VIS, red-edge: RE, Near-infrared: NIR) showed to be both site-specific and scale-dependent. In the first part of the thesis, the performance of spectral vegetation indices (SVIs) based on visible, red-edge (RE), and NIR bands alongside SVIs solely based or NIR-shoulder bands (wavelengths 750 - 900 nm) was evaluated. A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), it was demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. In the second part, the applicability of the spectral variability hypothesis (SVH) was questioned and highlighted the challenges to use high-resolution hyperspectral images to estimate biodiversity in complex grassland ecosystems. It was reported that the relationship between biodiversity (Shannon, Richness, Simpson, and Evenness) and optical diversity metrics (Coefficient of variation (CV) and Standard deviation (SD)) is not consistent across plant communities. The results of the second part suggested that biodiversity in terms of species richness could be estimated by optical diversity metrics with an R2 = 0.4 at the IT-PD site where the grassland plots were artificially established and are showing a lower structure and complexity from the natural grassland plant communities. On the other hand, in the natural ecosystems at IT-MBo, it was more difficult to estimate biodiversity indices, probably due to structural and biochemical PTs co-variation. The effects of canopy non-vegetative elements (flowers and dead material), shadow pixels, and overexposed pixels on the relationship between optical diversity metrics and biodiversity indices were highlighted. In the third part, we examined the relationship between PTs variability (at both local and community scales, measured by standard deviation and by the Euclidean distances of the biochemical and biophysical PTs respectively) and taxonomic diversity (both α-diversity and β-diversity, measured by Shannon’s index and by Jaccard dissimilarity index of the species, families, and functional groups percent cover respectively) in Monte Bondone, Trentino province, Italy. The results of the study showed that the PTs variability metrics at alpha scale were not correlated with α-diversity. However, the results at the community scale (β-diversity) showed that some of the investigated biochemical and biophysical PTs variations metrics were associated with β-diversity. The SVH approach was also tested to estimate β-diversity and we found that spectral diversity calculated by spectral angular mapper (SAM) showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity failed to estimate alpha diversity, this leading to the conclusion that the link between functional and species diversity may be an indicator of the applicability of optical sampling methods to estimate biodiversity. The findings of the thesis highlighted that grassland structural heterogeneity strongly affects the ability to retrieve both LAI and biodiversity, with high uncertainties due to structural and biochemical PTs co-variation at complex grassland ecosystems. In this context, the uncertainties of satellite-based products (e.g., LAI) in monitoring grassland canopies characterized by either spatially or temporally varying structure need to be carefully taken into account. The results of the study highlighted that the poor performance of optical diversity proxies in estimating biodiversity in structurally heterogeneous grasslands might be due to the complex relationships between functional diversity and biodiversity, rather than the impossibility to detect functional diversity with spectral proxies.

Grasslands are one of the most important ecosystems on Earth, covering approximately onethird of the Earth’s surface. Grassland biodiversity is important as many services provided by such ecosystems are crucial for the human economy and well-being. Given the importance of grasslands ecosystems, in recent years research has been carried out on the potential to monitor them with novel remote sensing techniques. Improved detectors technology and novel sensors providing finescale hyperspectral imagery have been enabling new methods to monitor plant traits (PTs) and biodiversity. The aims of the work were to study different approaches to monitor key grassland PTs such as Leaf Area Index (LAI) and biodiversity-related traits. The thesis consists of 3 parts: 1) Evaluating the performance of remote sensing methods to estimate LAI in grassland ecosystems, 2) Estimating plant biodiversity by using the optical diversity approach in grassland ecosystems, and 3) Investigating the relationship between PTs variability with alpha and beta diversity for the applicability of the optical diversity approach in a subalpine grassland of the Italian Alps To evaluate the performance of remote sensing methods to estimate LAI, temporal and spatial observations of hyperspectral reflectance and LAI were analyzed at a grassland site in Monte Bondone, Italy (IT-MBo). In 2018, ground temporal observations of hyperspectral reflectance and LAI were carried out at a grassland site in Neustift, Austria (AT-NEU). To estimate biodiversity, in 2018 and 2019 a floristics survey was conducted to determine species composition and hyperspectral data were acquired at two grassland sites: IT-MBo and University of Padova’s Experimental Farm, Legnaro, Padua, Italy (IT-PD) respectively. Furthermore, in 2018, biochemistry analysis of the biomass samples collected from the grassland site IT-MBo was carried out to determine the foliar biochemical PTs variability. The results of the thesis demonstrated that the grassland spectral response across different spectral regions (Visible: VIS, red-edge: RE, Near-infrared: NIR) showed to be both site-specific and scale-dependent. In the first part of the thesis, the performance of spectral vegetation indices (SVIs) based on visible, red-edge (RE), and NIR bands alongside SVIs solely based or NIRshoulder bands (wavelengths 750 - 900 nm) was evaluated. A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), it was demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. In the second part, the applicability of the spectral variability hypothesis (SVH) was questioned and highlighted the challenges to use high-resolution hyperspectral images to estimate biodiversity in complex grassland ecosystems. It was reported that the relationship between biodiversity (Shannon, Richness, Simpson, and Evenness) and optical diversity metrics (Coefficient of variation (CV) and Standard deviation (SD)) is not consistent across plant communities. The results of the second part suggested that biodiversity in terms of species richness could be estimated by optical diversity metrics with an R2 = 0.4 at the IT-PD site where the grassland plots were artificially established and are showing a lower structure and complexity from the natural grassland plant communities. On the other hand, in the natural ecosystems at IT-MBo, it was more difficult to estimate biodiversity indices, probably due to structural and biochemical PTs co-variation. The 18 effects of canopy non-vegetative elements (flowers and dead material), shadow pixels, and overexposed pixels on the relationship between optical diversity metrics and biodiversity indices were highlighted. In the third part, we examined the relationship between PTs variability (at both local and community scales, measured by standard deviation and by the Euclidean distances of the biochemical and biophysical PTs respectively) and taxonomic diversity (both α-diversity and βdiversity, measured by Shannon’s index and by Jaccard dissimilarity index of the species, families, and functional groups percent cover respectively) in Monte Bondone, Trentino province, Italy. The results of the study showed that the PTs variability metrics at alpha scale were not correlated with α-diversity. However, the results at the community scale (β-diversity) showed that some of the investigated biochemical and biophysical PTs variations metrics were associated with β-diversity. The SVH approach was also tested to estimate β-diversity and we found that spectral diversity calculated by spectral angular mapper (SAM) showed to be a better proxy of biodiversity in the same ecosystem where the spectral diversity failed to estimate alpha diversity, this leading to the conclusion that the link between functional and species diversity may be an indicator of the applicability of optical sampling methods to estimate biodiversity. The findings of the thesis highlighted that grassland structural heterogeneity strongly affects the ability to retrieve both LAI and biodiversity, with high uncertainties due to structural and biochemical PTs co-variation at complex grassland ecosystems. In this context, the uncertainties of satellite-based products (e.g., LAI) in monitoring grassland canopies characterized by either spatially or temporally varying structure need to be carefully taken into account. The results of the study highlighted that the poor performance of optical diversity proxies in estimating biodiversity in structurally heterogeneous grasslands might be due to the complex relationships between functional diversity and biodiversity, rather than the impossibility to detect functional diversity with spectral proxies

The nucleus is a regulation center for cellular gene expression 1. Mechanical forces transfer to the nucleus directly and indirectly through cellular cytoskeletal structures and pathways 2, 3. The transmitted strains often cause nuclear deformation which is thought to trigger mechanosensitive gene expression within the nucleus 4. Protein dynamics inside the nucleus are additionally important for maintaining the nuclear structure and in facilitating gene expression at the transcription level 5. Probing spatiotemporal relationships between mechanical forces and localized gene expression (i.e. biophysical and biochemical factors) in the nuclei of cells is important in order to clarify variability observed in large and heterogeneous cell populations within complex tissues. This requires the development of innovative methods for intranuclear strain measurements of cells in situ, and the further capability to quantify associated biochemical responses. This abstract describes a method combining the simultaneous measurement of newly synthesized RNA with spatiotemporal intranuclear strain mapping in single cells embedded in native tissue.