Biophysical Traits Research Articles

Morpho-Biochemical Characteristics of Brinjal Germplasms Affect the Abundance And Infestation of Jassid

The tropical vegetable, brinjal is cultivated throughout the year in Bangladesh but the crop is infested by a number of insects including jassid. This study investigated the effects of different biophysical and biochemical characteristics of twelve brinjal germplasms on the abundance and infestation of jassid. The experiment was conducted during September 2018 to March 2019 in Gazipur, Bangladesh with twelve brinjal germplasms namely BD-7320, BD-7328, BD-9952, BD-10154, BD-10158, BARI Begun-1, BARI Begun-4, BARI Begun-5, BARI Begun- 6, BARI Begun-7, BARI Begun-8 and BARI Begun-9. The incidence of jassid was recorded from 3rd December to 26th March, and the lowest population was found on BARI Begun- 6. Among the biophysical traits, plant height, number of branch and leaf per plant, and leaf area exerted significant positive correlation; whereas trichome on lower and upper surfaces of leaf, spine per stem and leaf showed significant negative correlation with the abundance of jassid. On the other hand, moisture, reducing sugar, total sugar and protein content of the leaves and fruits, chlorophyll content of the leaves exerts significant positive correlation but ash and pH contents of the leaves and fruits were negatively correlated with the abundance of jassid. Jassids showed the lowest level of leaf infestation on BARI Begun-6, which could be for further analysis to develop jassid resistant brinjal. SAARC J. Agric., 19(1): 81-91 (2021)

Superiority of modified graphene oxide for enhancing the growth, yield, and antioxidant potential of pearl millet (Pennisetum glaucum L.) under salt stress

Soil salinity is a serious global problem that affects the vegetative growth and photosynthesis rates of plants. Additionally, a high salinity facilitates the accumulation of free radicals and reactive oxygen species (ROS), which induces an increase in the malondialdehyde, hydrogen peroxide, and proline contents, and a decrease in the antioxidant activity of enzymes, such as superoxide dismutase and peroxidase, reducing the fodder yield. Owing to limited availability of forage crops, extensive efforts have been devoted to studying the pearl millet (Pennisetum glaucum L.) plant, which is employed as a protein-rich fodder crop in its green and dry forms. Therefore, a field experiment was conducted to explore the effect of graphene oxide, methionine, lysine, methionine@graphene oxide, and lysine@graphene oxide on the growth, biomass accumulation, photosynthetic pigment content, total protein content, oxidative stress, and antioxidant response of the pearl millet plant. Modified graphene oxide (20 mg L−1) was applied two times to the fresh leaves of pearl millet after 30 and 60 days of cultivation. The salt concentrations in the soil and water in the area under consideration were 3.16 d.Sm−1 and 10.29 d.Sm−1, respectively. The treatments induced a significant improvement in plant growth, biomass accumulation, total protein content, photosynthetic pigment content, and yield. Similarly, the generation of ROS was reduced in the plant cells/tissues compared to the case in the plants grown under saline conditions. The foliar application of both graphene oxide and its modified structures enhanced the salinity stress tolerance of pearl millet by modulating its morphological and biophysical traits. This study offers new possibilities for the application of modified materials in agriculture and provides a valuable basis for improving plant tolerance and adaptability to salinity stress.

Manipulating Osteogenic/Adipogenic Balance in Mesenchymal Stromal Cells (MSCs) for Hematopoietic Applications

Aims: Bone marrow-derived mesenchymal stromal cells (BM-MSCs) have the potential to improve hematopoietic transplantation by supporting hematopoietic stem and progenitor cell (HSPC) expansion as well as by promoting HSPC engraftment to the BM. However, culture expanded MSCs becomes a mixture of progenitor cells committed to different cell lineages, each with different potencies for any one desired application. Clinically, the accumulation of adipogenic MSCs in the BM is believed to contribute towards age-related impairment of regeneration and hematopoiesis; this observation, together with our understanding of the inverse relationship between MSC osteogenic and adipogenic differentiation prompted a more in depth study of the ability of these different MSC lineages to support hematopoietic clinical applications. Clinically relevant methods for engineering a pure cell population from heterogeneous MSC culture will also be discussed.Methods: MSCs were derived from the healthy BM of patients aged 30-50 years. At various stages of osteogenic and adipogenic differentiation in vitro , cultures were evaluated for their ability to support cord blood (CB) CD34+ HSC expansion and stimulate regenerative processes such as angiogenesis and cell proliferation. qPCR, coupled with secretome analysis was performed to discover gene expression markers for MSCs with potent hematopoietic supportive capabilities. Finally, due to the lack of unique surface markers for identification of MSC subpopulations, we utilized multivariate biophysical analysis (microfluidic sorting, atomic force microscopy, etc.), correlating these quantitative measures with biomolecular markers as well as in vitro and in vivo functionality. Novel label-free cell separation strategies that take advantage of unique biophysical traits in a potent MSC subpopulation for HSPC transplantation was also developed to enable clinical translation.Results: Differentiated osteoblasts (OB) as well as pre-OB demonstrated a higher ability to support CB CD34+ HSC expansion compared to undifferentiated MSCs or MSCs in the adipogenic state. Over a period of 10 days, the total HSPC fold expansion was 44.4 ± 4.83, 57.8 ± 10.67, 40.2 ± 4.65, 34.2 ± 6.18 and 13.8 ± 5.50 for OB, pre-OB, MSCs, pre-AD and AD, respectively (n = 5). Absolute expanded CD34+ HSCs was highest with pre-OB cultures (~1.7 fold, n = 5) compared to undifferentiated MSCs. Adipogenic MSCs had much reduced capabilities for supporting HSPC expansion. In vitro angiogenic and proliferation assays showed the greatest degree of HUVEC sprouting and proliferation (~ 2.6 fold greater than undifferentiated MSCs) when exposed to a pre-OB secretome. Pre-OBs are distinct in their transcriptome (up-regulated osteopontin, runx2, angiopoietin-1, FGF1, etc) but no surface marker reliably distinguishes them from other MSCs. We subsequently found a minimal set of three biophysical markers: cell diameter, membrane stiffness and nuclear membrane fluctuations, which collectively are predictive of MSC subpopulations (multipotent vs committed progenitors). We hypothesized and experimentally verified that a biophysically derived pre-OB subpopulation, defined biophysically as MSCs with >20 μm diameter, >375Pa stiffness and <1.2 % nuclear fluctuation, exhibits significantly greater efficacy over other MSC subpopulations for promoting bone marrow repair (~2-3 fold improvements in medial survival following BM injury) and expansion of HSPCs (~1.5-2 fold increase in HSPC numbers). Following co-transplantation with HSPCs, biophysically derived pre-OB promoted faster engraftment of donor cells in the peripheral blood by week 4 (~ 9% vs < 5% in other MSC groups, P<0.05).Conclusion: These results demonstrate a correlation between MSCs with high osteogenic activity and the capabilities for BM repair as well as hematopoietic support, making such cells ideal for augmentation of HSC transplantations. In the absence of reliable surface markers for isolation of these pre-OBs, we developed a clinically relevant biophysical isolation strategy for derivation of pre-OBs that can markedly improve the efficacy of MSC-based approaches for augmentation of hematopoietic transplants. DisclosuresNo relevant conflicts of interest to declare.

Survival of the thickest? Impacts of extreme wave‐forcing on marsh seedlings are mediated by species morphology

AbstractAlthough tidal marshes are known for their coastal defense function during storm surges, the impact of extreme wave forcing on tidal marsh development is poorly understood. Seedling survival in the first season after germination, which may involve exposure to extreme wave events, is crucial for the natural establishment and human restoration of marshes. We hypothesize that species‐specific plant traits plays a significant role in seedlings survival and response to wave induced stress, i.e., through stem bending and uprooting. To test this hypothesis, seedlings of pioneer species (Bolboschoenus maritimus, Schoenoplectus tabernaemontani, Spartina anglica, and Puccinellia maritima) with contrasting biophysical traits were placed in the Large Wave Flume in Hannover (Germany) and exposed to storm wave conditions. Seedlings of P. maritima and S. anglica experienced a lower loss rate and bending angle after wave exposure compared to S. tabernaemontani and especially B. maritimus. The higher loss rates of B. maritimus and S. tabernaemontani result from deeper scouring around the stem base. Scouring depth was larger around stems of greater diameter and higher resistance to bending. Here, B. maritimus and S. tabernaemontani have both thicker and stiffer stems than S. anglica and P. maritima. Our results show that especially seedlings with thicker stems suffer from erosion and scouring, and have the highest risk of being lost during extreme wave events. This implies that for successful seedling establishment and eventually the establishment of a mature tidal marsh vegetation, the species composition and their capacity to cope with storm wave disturbances is crucial.

Molecular engineering improves antigen quality and enables integrated manufacturing of a trivalent subunit vaccine candidate for rotavirus

BackgroundVaccines comprising recombinant subunit proteins are well-suited to low-cost and high-volume production for global use. The design of manufacturing processes to produce subunit vaccines depends, however, on the inherent biophysical traits presented by an individual antigen of interest. New candidate antigens typically require developing custom processes for each one and may require unique steps to ensure sufficient yields without product-related variants.ResultsWe describe a holistic approach for the molecular design of recombinant protein antigens—considering both their manufacturability and antigenicity—informed by bioinformatic analyses such as RNA-seq, ribosome profiling, and sequence-based prediction tools. We demonstrate this approach by engineering the product sequences of a trivalent non-replicating rotavirus vaccine (NRRV) candidate to improve titers and mitigate product variants caused by N-terminal truncation, hypermannosylation, and aggregation. The three engineered NRRV antigens retained their original antigenicity and immunogenicity, while their improved manufacturability enabled concomitant production and purification of all three serotypes in a single, end-to-end perfusion-based process using the biotechnical yeast Komagataella phaffii.ConclusionsThis study demonstrates that molecular engineering of subunit antigens using advanced genomic methods can facilitate their manufacturing in continuous production. Such capabilities have potential to lower the cost and volumetric requirements in manufacturing vaccines based on recombinant protein subunits.

Sensing Solvent in the Collapsed State of Glutamine‐Rich Domains

Intrinsically disordered proteins (IDPs) challenge the widely accepted structure to function paradigm of protein behavior and are associated with important biological functions. These disordered domains are estimated to account for at least 30% of the proteome in eukaryotic genomes and are correlated with signal transduction and gene regulation, as well as certain disorders including some types of cancers, amyloidosis, heart disease, and neurodegenerative disease. While many IDPs perform their functions by folding with a partner protein, a subclass is prone to collapsed states, disordered interactions, and aggregation. We need to obtain a higher understanding of the biophysical attributes—level of structures versus collapse and behavior with water in comparison to sequences and biological traits—to characterize these IDPs and to extrapolate their functions. This project takes on two modes: We are (1) developing methods on a model protein known to form a collapsed state that traps water and (2) evaluating a small library of IDPs with distinct roles in transcription by the method developed. Studying these aggregation-prone disordered domains is challenging experimentally. We utilize fluorescence methods to reach low concentrations, an environmentally-sensitive fluorophore to evaluate the presence of water, and collisional quenching to follow the flow into the interior of the collapsed domain. Our studies of the control protein kappa-casein demonstrate that water is present in the collapsed state but is not able to freely exchange with the bulk solution. Our experimental library of IDPs were selected from auxin response factors (ARFs) from Arabidopsis thaliana. This family of transcription factors have three distinguishable sections: a DNA-binding domain, a low complexity middle region, and a structured protein:protein interaction domain. My work is centered on the middle region as it is predicted to be disordered across the family but is distinct in abundance of glutamine depending on function. Transcription activators are consistently higher in glutamine than their repressive counterparts. After cloning select sequences from cDNA, we have optimized expression, purification, and fluorophore labeling of four proteins from both transcription activators and repressors. Our final goal is to further investigate the function of these glutamine-rich domains by attaching fluorophores to the cysteines of the protein in order to compare the natural and denatured states across our selected proteins. Our comparisons of these will expand our understanding of the sequence-dependent biophysical traits in the context of their differing biological roles within the context of auxin response in plants. To complement our experimental studies, we have analyzed characteristics of these disordered regions using a suite of sequence-based prediction algorithms. Again, we evaluated the proteins against a known set of control proteins.

Environmental characterization and yield gap analysis to tackle genotype-by-environment-by-management interactions and map region-specific agronomic and breeding targets in groundnut

• Genotype by Environment by Management (GxExM) interactions hampers crop improvement. • Crop simulation revealed large/variable yield gaps (∼70 %). • Filling 80 % of yield gap would increase production by 8 M tons. • Modelling output and biophysical traits were clustered (HPU). • Grouping by HPU reduced GxExM interactions and will help refine breeding targets. The high degree of Genotype by Environment by Management (GxExM) interactions is a serious challenge for production and crop improvement efforts. This challenge is especially true for a crop like groundnut that is often grown as a rainfed crop in diverse environments and management, leading to considerable production fluctuations among regions and seasons. Developing a means to characterize the drivers of variable yield and to identify region specific breeding objectives were the main motivations for this research, using groundnut production in India, as a case study for rainfed crops. Historically, five groundnut production areas have been considered by Indian crop improvement programs. Our objectives were to assess the relevance of this zonation system and possibly to re-define production areas with a higher degree of similarities into homogeneous production units (HPUs). Towards this, we used yield gap analysis and the geo-biophysical characters of the production region to understand and deal with GxExM interactions. Weather and soil data, crop parameters, and management information data were collected and groundnut production was simulated at the district scale over 30 consecutive years. Consequently, the geographic distribution of the potential yields and the yield gaps were first estimated to understand the main production limitations in a given region. Large and variable yield gaps (with a mean of ∼70 %) were observed and results revealed a readily exploitable production gap (∼ 8 M tons), which might be bridged by following recommended agronomic practices. Water deficit limited the yield potential by an average of 40 %, although with large variability among districts. However, large and variable yield gaps remained. To resolve the unexplained variation, principal component and cluster analysis of agronomic model output together with geo-biophysical indicators for each district were carried out. This resulted in seven HPUs, having well-defined production-limiting constraints. Grouping by HPU greatly reduced variance in actual and simulated yields, as compared to grouping across all groundnut production zones in India. The HPU based approach delimited precise geographic regions within which HPU-specific GxM products could be designed by crop improvement programs to boost productivity.

A new analytical tool for a more deliberate implementation of Sustainable Drainage Systems

This paper presents a new analytical tool for a more deliberate qualitative assessment of and guidance for the way Sustainable Drainage Systems (SuDS) are governed and technically implemented. It is the result of a combination of concepts from various alternative “sustainability” approaches and provides for the first time a set of detailed but not exhaustive aspects and sub-aspects that are critical for holistic implementation. A wide range of topics relevant for the attainment of radical change are embraced that had been rarely simultaneously considered in practice and research until now. Analyses at neighbourhood level in the solarCity (Linz, Austria) and Monges-Croix du Sud (Cornebarrieu, France), where SuDS have been comprehensively deployed, demonstrate the suitability of the tool for the provision of a more holistic perspective and direction for further change. Both projects represent the accomplishment of important steps towards sustainable stormwater management, but wider perspectives are required if the positive effects achieved are to be extended. Efforts have been made to understand the bio-physical traits of place prior to design and subsequently fulfil some technical demands, but reticence remains to: a) explore “closer to nature” solutions and transformative social considerations, and b) enter a continuous cycle of co-evolution.

Remote Sensing Energy Balance Model for the Assessment of Crop Evapotranspiration and Water Status in an Almond Rootstock Collection.

One of the objectives of many studies conducted by breeding programs is to characterize and select rootstocks well-adapted to drought conditions. In recent years, field high-throughput phenotyping methods have been developed to characterize plant traits and to identify the most water use efficient varieties and rootstocks. However, none of these studies have been able to quantify the behavior of crop evapotranspiration in almond rootstocks under different water regimes. In this study, remote sensing phenotyping methods were used to assess the evapotranspiration of almond cv. “Marinada” grafted onto a rootstock collection. In particular, the two-source energy balance and Shuttleworth and Wallace models were used to, respectively, estimate the actual and potential evapotranspiration of almonds grafted onto 10 rootstock under three different irrigation treatments. For this purpose, three flights were conducted during the 2018 and 2019 growing seasons with an aircraft equipped with a thermal and multispectral camera. Stem water potential (Ψstem) was also measured concomitant to image acquisition. Biophysical traits of the vegetation were firstly assessed through photogrammetry techniques, spectral vegetation indices and the radiative transfer model PROSAIL. The estimates of canopy height, leaf area index and daily fraction of intercepted radiation had root mean square errors of 0.57 m, 0.24 m m–1 and 0.07%, respectively. Findings of this study showed significant differences between rootstocks in all of the evaluated parameters. Cadaman® and Garnem® had the highest canopy vigor traits, evapotranspiration, Ψstem and kernel yield. In contrast, Rootpac® 20 and Rootpac® R had the lowest values of the same parameters, suggesting that this was due to an incompatibility between plum-almond species or to a lower water absorption capability of the rooting system. Among the rootstocks with medium canopy vigor, Adesoto and IRTA 1 had a lower evapotranspiration than Rootpac® 40 and Ishtara®. Water productivity (WP) (kg kernel/mm water evapotranspired) tended to decrease with Ψstem, mainly in 2018. Cadaman® and Garnem® had the highest WP, followed by INRA GF-677, IRTA 1, IRTA 2, and Rootpac® 40. Despite the low Ψstem of Rootpac® R, the WP of this rootstock was also high.

Compound Heterozygous KCNQ1 Mutations Causing Recessive Romano-Ward Syndrome: Functional Characterization by Mutant Co-expression.

Next Generation Sequencing has identified many KCNQ1 genetic variants associated with type 1 long QT or Romano-Ward syndrome, most frequently inherited in an autosomal dominant fashion, although recessive forms have been reported. Particularly in the case of missense variants, functional studies of mutants are of aid to establish variant pathogenicity and to understand the mechanistic basis of disease. Two compound heterozygous KCNQ1 mutations (p.A300T and p.P535T) were previously found in a child who suffered sudden death. To provide further insight into the clinical significance and basis for pathogenicity of these variants, different combinations of wildtype, A300T and P535T alleles were co-expressed with the accessory β-subunit minK in HEK293 cells, to analyze colocalization with the plasma membrane and some biophysical phenotypes of homo and heterotetrameric channels using the patch-clamp technique. A300T homotetrameric channels showed left-shifted activation V1/2 as previously observed in Xenopus oocytes, decreased maximum conductance density, slow rise-time300ms, and a characteristic use-dependent response. A300T slow rise-time300ms and use-dependent response behaved as dominant biophysical traits for all allele combinations. The P535T variant significantly decreased maximum conductance density and Kv7.1-minK-plasma membrane colocalization. P535T/A300T heterotetrameric channels showed decreased colocalization with plasma membrane, slow rise-time300ms and the A300T characteristic use-dependent response. While A300T left shifted activation voltage dependence behaved as a recessive trait when co-expressed with WT alleles, it was dominant when co-expressed with P535T alleles.Conclusions: The combination of P535T/A300T channel biophysical properties is compatible with recessive Romano Ward syndrome. Further analysis of other biophysical traits may identify other mechanisms involved in the pathophysiology of this disease.

Exploring the Impact of Noise on Hybrid Inversion of PROSAIL RTM on Sentinel-2 Data

Remote sensing (RS) of biophysical variables plays a vital role in providing the information necessary for understanding spatio-temporal dynamics in ecosystems. The hybrid approach to retrieve biophysical variables from RS by combining Machine Learning (ML) algorithms with surrogate data generated by Radiative Transfer Models (RTM). The susceptibility of the ill-posed solutions to noise currently constrains further application of hybrid approaches. Here, we explored how noise affects the performance of ML algorithms for biophysical trait retrieval. We focused on synthetic Sentinel-2 (S2) data generated using the PROSAIL RTM and four commonly applied ML algorithms: Gaussian Processes (GPR), Random Forests (RFR), and Artificial Neural Networks (ANN) and Multi-task Neural Networks (MTN). After identifying which biophysical variables can be retrieved from S2 using a Global Sensitivity Analysis, we evaluated the performance loss of each algorithm using the Mean Absolute Percentage Error (MAPE) with increasing noise levels. We found that, for S2 data, Carotenoid concentrations are uniquely dependent on band 2, Chlorophyll is almost exclusively dependent on the visible ranges, and Leaf Area Index, water, and dry matter contents are mostly dependent on infrared bands. Without added noise, GPR was the best algorithm (&lt;0.05%), followed by the MTN (&lt;3%) and ANN (&lt;5%), with the RFR performing very poorly (&lt;50%). The addition of noise critically affected the performance of all algorithms (&gt;20%) even at low levels of added noise (≈5%). Overall, both neural networks performed significantly better than GPR and RFR when noise was added with the MTN being slightly better when compared to the ANN. Our results imply that the performance of the commonly used algorithms in hybrid-RTM inversion are pervasively sensitive to noise. The implication is that more advanced models or approaches are necessary to minimize the impact of noise to improve near real-time and accurate RS monitoring of biophysical trait retrieval.

Foliage Biophysical Trait Prediction from Laboratory Spectra in Norway Spruce Is More Affected by Needle Age Than by Site Soil Conditions

Scaling leaf-level optical signals to the canopy level is essential for airborne and satellite-based forest monitoring. In evergreen trees, biophysical and optical traits may change as foliage ages. This study aims to evaluate the effect of age in Norway spruce needle on biophysical trait-prediction based on laboratory leaf-level spectra. Mature Norway spruce trees were sampled at forest stands in ten headwater catchments with different soil properties. Foliage biophysical traits (pigments, phenolics, lignin, cellulose, leaf mass per area, water, and nitrogen content) were assessed for three needle-age classes. Complementary samples for needle reflectance and transmittance were measured using an integrating sphere. Partial least square regression (PLSR) models were constructed for predicting needle biophysical traits from reflectance—separating needle age classes and assessing all age classes together. The ten study sites differed in soil properties rather than in needle biophysical traits. Optical properties consistently varied among age classes; however, variation related to the soil conditions was less pronounced. The predictive power of PLSR models was needle-age dependent for all studied traits. The following traits were predicted with moderate accuracy: needle pigments, phenolics, leaf mass per area and water content. PLSR models always performed better if all needle age classes were included (rather than individual age classes separately). This also applied to needle-age independent traits (water and lignin). Thus, we recommend including not only current but also older needle traits as a ground truth for evergreen conifers with long needle lifespan.

Leveraging Image Analysis to Compute 3D Plant Phenotypes Based on Voxel-Grid Plant Reconstruction.

High throughput image-based plant phenotyping facilitates the extraction of morphological and biophysical traits of a large number of plants non-invasively in a relatively short time. It facilitates the computation of advanced phenotypes by considering the plant as a single object (holistic phenotypes) or its components, i.e., leaves and the stem (component phenotypes). The architectural complexity of plants increases over time due to variations in self-occlusions and phyllotaxy, i.e., arrangements of leaves around the stem. One of the central challenges to computing phenotypes from 2-dimensional (2D) single view images of plants, especially at the advanced vegetative stage in presence of self-occluding leaves, is that the information captured in 2D images is incomplete, and hence, the computed phenotypes are inaccurate. We introduce a novel algorithm to compute 3-dimensional (3D) plant phenotypes from multiview images using voxel-grid reconstruction of the plant (3DPhenoMV). The paper also presents a novel method to reliably detect and separate the individual leaves and the stem from the 3D voxel-grid of the plant using voxel overlapping consistency check and point cloud clustering techniques. To evaluate the performance of the proposed algorithm, we introduce the University of Nebraska-Lincoln 3D Plant Phenotyping Dataset (UNL-3DPPD). A generic taxonomy of 3D image-based plant phenotypes are also presented to promote 3D plant phenotyping research. A subset of these phenotypes are computed using computer vision algorithms with discussion of their significance in the context of plant science. The central contributions of the paper are (a) an algorithm for 3D voxel-grid reconstruction of maize plants at the advanced vegetative stages using images from multiple 2D views; (b) a generic taxonomy of 3D image-based plant phenotypes and a public benchmark dataset, i.e., UNL-3DPPD, to promote the development of 3D image-based plant phenotyping research; and (c) novel voxel overlapping consistency check and point cloud clustering techniques to detect and isolate individual leaves and stem of the maize plants to compute the component phenotypes. Detailed experimental analyses demonstrate the efficacy of the proposed method, and also show the potential of 3D phenotypes to explain the morphological characteristics of plants regulated by genetic and environmental interactions.

Mechanical and Physical Behavior of Fibrin Clot Formation and Lysis in Combined Oral Contraceptive Users.

Combined oral contraceptives (COCs) are commonly prescribed and increase the risk of venous thromboembolism (VTE). We have previously found that two COCs, both containing drospirenone (DRSP) and ethinyl estradiol (EE), cause spontaneous fibrin formation in whole blood. The aim of this study was, therefore, to use platelet-poor plasma (PPP) from the same cohort of DRSP/EE users to determine the impact of these COCs on the fibrin component, specifically the fibrin clot viscoelasticity, turbidimetry, and biophysical traits. PPP from 25 females per test group and a control group (n = 25) were analyzed using thromboelastography (TEG), turbidimetry, and scanning electron microscopy. The results highlight abnormal fibrin clot formation, lysis, and architecture; DRSP/20EE showed the greatest effect. DRSP/EE use increased the fibrin fiber diameter and showed dense matted clots. Only when the influence of COCs on the structural properties and behavior of fibrin fibers during thrombus formation and lysis is better understood are we able to predict and prevent coagulopathies associated with these synthetic hormones. Clinical practitioners should take this into consideration for female patients that either have comorbidities, which could burden the coagulation system, or may be exposed to external factors that could increase their risk for VTE.

Crown structural properties, wood density, and liana load: influence on growth and mortality in subtropical forests

Wood density (WD) and other wood mechanical and structural properties may have a strong functional relationship with demographic patterns and allometry of trees. We analyzed the influence of WD, structural properties, architectural traits, and community-level attributes on growth rates (GRs) and mortality modes of canopy tree species in a subtropical forest of Argentina. Stem WD and the WD, strength, stiffness, toughness, and hardness of branches were measured in 10 canopy species. Architectural traits and liana load were also determined. Strength and hardness of branches were linearly correlated to branch WD, and GRs were linearly correlated to stem WD across species. At the individual level, trees with greater hardness and toughness in branches died mostly uprooted, and trees with greater branch stiffness and susceptibility to colonization by lianas were mostly broken. At the community level, the suppressed trees died mostly broken. The dominant trees with high local tree density died mostly broken, whereas more isolated trees died mostly uprooted. Mortality modes were determined not only by mechanical properties, but also by community properties such as liana load, crown canopy position, and number of neighboring trees. Other biophysical traits besides WD are important explanatory variables when dry wood is used to describe functional characteristics of trees.

Utilising variable sorting for normalisation to correct illumination effects in close-range spectral images of potato plants

Visible and near-infrared spectral imaging is a key non-destructive technique for rapid assessment of biophysical traits of plants. A major challenge with close-range spectral imaging of plants is spectral variation arising from illumination effects, which may mask the signals due to physiochemical differences. In the present work, we describe a new scatter correction technique called variable sorting for normalisation (VSN) and compare its efficiency with that of the commonly used standard normal variate (SNV) technique for the removal of unwanted illumination effects. Spectral images of potato plants were used for testing the correction. The results showed that the VSN outperformed SNV in removing illumination effects from the images of plants. The results show that the VSN approach to illumination correction can support high-throughput plant phenotyping where spectral imaging is used as a continuous monitoring tool.

Stability and Folding of the Unusually Stable Hemoglobin from Synechocystis is Subtly Optimized and Dependent on the Key Heme Pocket Residues.

The aim of our study is to understand the biophysical traits that govern the stability and folding of Synechocystis hemoglobin, a unique cyanobacterial globin that displays unusual traits not observed in any of the other globins discovered so far. For the past few decades, classical hemoglobins such as vertebrate hemoglobin and myoglobin have been extensively studied to unravel the stability and folding mechanisms of hemoglobins. However, the expanding wealth of hemoglobins identified in all life forms with novel properties, like heme coordination chemistry and globin fold, have added complexity and challenges to the understanding of hemoglobin stability, which has not been adequately addressed. Here, we explored the unique truncated and hexacoordinate hemoglobin from the freshwater cyanobacterium Synechocystis sp. PCC 6803 known as "Synechocystis hemoglobin (SynHb)". The "three histidines" linkages to heme are novel to this cyanobacterial hemoglobin. Mutational studies were employed to decipher the residues within the heme pocket that dictate the stability and folding of SynHb. Site-directed mutants of SynHb were generated and analyzed using a repertoire of spectroscopic and calorimetric tools. The results revealed that the heme was stably associated to the protein under all denaturing conditions with His117 playing the anchoring role. The studies also highlighted the possibility of existence of a "molten globule" like intermediate at acidic pH in this exceptionally thermostable globin. His117 and other key residues in the heme pocket play an indispensable role in imparting significant polypeptide stability. Synechocystis hemoglobin presents an important model system for investigations of protein folding and stability in general. The heme pocket residues influenced the folding and stability of SynHb in a very subtle and specific manner and may have been optimized to make this Hb the most stable known as of date. Other: The knowledge gained hereby about the influence of heme pocket amino acid side chains on stability and expression is currently being utilized to improve the stability of recombinant human Hbs for efficient use as oxygen delivery vehicles.

TRPV1: Structure, Endogenous Agonists, and Mechanisms.

The Transient Receptor Potential Vanilloid 1 (TRPV1) channel is a polymodal protein with functions widely linked to the generation of pain. Several agonists of exogenous and endogenous nature have been described for this ion channel. Nonetheless, detailed mechanisms and description of binding sites have been resolved only for a few endogenous agonists. This review focuses on summarizing discoveries made in this particular field of study and highlighting the fact that studying the molecular details of activation of the channel by different agonists can shed light on biophysical traits that had not been previously demonstrated.

Cancer Stem Cell Plasticity - A Deadly Deal.

Intratumoral heterogeneity is a major ongoing challenge in the effective therapeutic targeting of cancer. Accumulating evidence suggests that a fraction of cells within a tumor termed Cancer Stem Cells (CSCs) are primarily responsible for this diversity resulting in therapeutic resistance and metastasis. Adding to this complexity, recent studies have shown that there can be different subpopulations of CSCs with varying biochemical and biophysical traits resulting in varied dissemination and drug-resistance potential. Moreover, cancer cells can exhibit a high level of plasticity or the ability to dynamically switch between CSC and non-CSC states or among different subsets of CSCs. In addition, CSCs also display extensive metabolic plasticity. The molecular mechanisms underlying these different interconnected axes of plasticity has been under extensive investigation and the trans-differentiation process of Epithelial to Mesenchymal transition (EMT) has been identified as a major contributing factor. Besides genetic and epigenetic factors, CSC plasticity is also shaped by non-cell-autonomous effects such as the tumor microenvironment (TME). In this review, we discuss the latest developments in decoding mechanisms and implications of CSC plasticity in tumor progression at biochemical and biophysical levels, and the latest in silico approaches being taken for characterizing cancer cell plasticity. These efforts can help improve existing therapeutic approaches by taking into consideration the contribution of cellular plasticity/heterogeneity in enabling drug resistance.

Sensing Solvent in the Collapsed State of Glutamine‐Rich Domains

Intrinsically disordered proteins (IDPs) challenge the widely accepted structure to function paradigm of protein behavior and are associated with important biological functions. These disordered domains are estimated to account for at least 30% of the proteome in eukaryotic genomes and are correlated with signal transduction and gene regulation, as well as certain disorders including some types of cancers, amyloidosis, heart disease, and neurodegenerative disease. While many IDPs perform their functions by folding with a partner protein, a subclass is prone to collapsed states, disordered interactions, and aggregation. We need to obtain a higher understanding of the biophysical attributes—level of structures versus collapse and behavior with water in comparison to sequences and biological traits—to characterize these IDPs and to extrapolate their functions. This project takes on two modes: We are (1) developing methods on a model protein known to form a collapsed state that traps water and (2) evaluating a small library of IDPs with distinct roles in transcription by the method developed. Studying these aggregation‐prone disordered domains is challenging. We utilize fluorescence methods to reach low concentrations, an environmentally‐sensitive fluorophore to evaluate the presence of water, and collisional quenching to follow the flow into the interior of the collapsed domain. Our studies of the control protein κ‐casein demonstrate that water is present in the collapsed state but is not able to freely exchange with the bulk solution. Our experimental library of IDPs were selected from auxin response factors (ARFs) from Arabidopsis thaliana. This family of transcription factors have three distinguishable sections: a DNA‐binding domain, a low complexity middle region, and a structured protein:protein interaction domain. My work is centered on the middle region as it is predicted to be disordered across the family but is distinct in abundance of glutamine depending on function. Transcription activators are consistently higher in glutamine than their repressive counterparts. Our final goal is to further investigate this thought by attaching fluorophores to the cysteines of the protein in order to compare the natural and denatured states across our selected proteins. After cloning select sequences from cDNA, we have optimized expression, purification, and fluorophore labeling of four proteins from both transcription activators and repressors. Our comparisons of these will expand our understanding of the sequence‐dependent biophysical traits in the context of their differing biological roles within the context of auxin response in plants.