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NASA NTRS2021

Validation Assessment for the Soil Moisture Active Passive (SMAP) Level 4 Carbon (L4_C) Data Product Version 5

The post-launch Cal/Val phase of the SMAP mission is guided by two primary objectives for each science product team: 1) to calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the SMAP Level-1 mission science requirements. Algorithm science and product maintenance activities during the SMAP extended mission phase have also involved periodic algorithm calibration and product refinements to maintain or enhance product consistency and performance as well as science utility. This report provides an assessment of the latest (Version 5) SMAP Level 4 Carbon (L4_C) product. The L4_C Version 5 (v5) global record now spans more than six years (March 2015 – present) of SMAP operations and has benefited from five major reprocessing updates to the operational product. These reprocessing events and L4_C product release updates have incorporated various algorithm refinements and calibration adjustments to account for similar refinements to the upstream GEOS land model assimilation system, SMAP brightness temperatures, and MODIS vegetation inputs used for L4_C processing. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by daily surface and root zone soil moisture information contributed from the SMAP Level 4 Soil Moisture (L4_SM) product along with optical remote sensing-based (e.g. MODIS-based) land cover and canopy fractional photosynthetic active radiation (fPAR), and other ancillary biophysical data. The carbon flux model estimates global daily net ecosystem CO2 exchange (NEE) and the component carbon fluxes, namely, vegetation gross primary production (GPP) and soil heterotrophic respiration (Rh). Other L4_C product elements include surface (~0-5 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture-related controls on GPP and ecosystem respiration (Kimball et al. 2014, Jones et al. 2017). The L4_C product addresses SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying freeze/thaw and soil moisture-related constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity. The SMAP L4_C algorithms and operational product are mature and at a CEOS Validation Stage 4 level (Jackson et al. 2012) based on extensive validation of the multi-year record against a diverse array of independent benchmarks, well characterized global performance, and systematic refinements gained from five major reprocessing events. There are no Level-1 mission science requirements for the L4_C product; however, self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications (e.g., Liu et al. 2019, Endsley et al. 2020); however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased root-mean-square error (ubRMSE, or standard deviation of the error) for NEE of 1.6 g C m-2 d-1 and 30 g C m-2 yr-1, emphasizing northern (≥45°N) boreal and arctic ecosystems; this accuracy is similar to that of tower eddy covariance measurement-based observations (Baldocchi 2008). Methods used for the latest v5 L4_C product performance and validation assessment have been established from the SMAP Cal/Val plan and previous studies (Jackson et al. 2012, Jones et al. 2017) and include: 1) consistency evaluations of the product fields against earlier product releases (version 4 or earlier); 2) comparisons of daily carbon flux estimates with independent tower eddy 4covariance measurement-based daily carbon (CO2) flux observations from core tower validation sites (CVS); and 3) consistency checks against other global carbon products, including soil carbon inventory records, global GPP records derived from tower observation upscaling methods, and satellite-based observations of canopy solar induced chlorophyll fluorescence (SIF) as a surrogate for GPP. Metrics used to evaluate relative agreement between L4_C product fields and observational benchmarks include correlation (r-value), RMSE differences, bias and model sensitivity diagnostics. Following these validation criteria, the present report provides a validation assessment of the latest L4_C product release (v5). Detailed descriptions of the L4_C algorithm and additional global product accuracy and performance results are given elsewhere (Jones et al. 2017, Endsley et al. 2020). The v5 L4_C product replaces earlier product versions and continues to show: (i) accuracy and performance levels meeting or exceeding SMAP L4_C science requirements; (ii) improvement over the previous product version (version 4); and (iii) suitability for a diversity of science applications. Example L4_C applications from the recent literature include clarifying environmental trends and controls on the northern terrestrial carbon sink (Liu et al. 2019), diagnosing drought-related impacts on ecosystem productivity (Li et al. 2020), and regional monitoring of cropland conditions for projecting annual yields (Wurster et al. 2020). 2EXPECTED L4_C ALGORITHM AND PRODUCTPERFORMANCE The L4_C algorithm performance, including variance and uncertainty estimates of model outputs, was determined during the mission pre-launch phase through spatially explicit model sensitivity studies using available model inputs similar to those currently being used for operational production and evaluating the resulting model simulations over the observed range of northern (≥45 °N) and global conditions (Kimball et al. 2012, Entekhabi et al. 2014). The L4_C algorithm options were also evaluated during the mission prelaunch phase, including deriving canopy fPAR from lower order NDVI (Normalized Difference Vegetation Index) inputs in lieu of using MODIS (MOD15) fPAR; and including an explicit model representation of boreal fire disturbance recovery impacts. These results indicated that the L4_C accuracy requirements (i.e., NEE ubRMSE ≤ 30 g C m-2 yr-1or ≤ 1.6 g C m-2 d-1) could be met from the baseline algorithms over more than 82% and 89% of global and northern vegetated land areas, respectively (Yi et al. 2013, Kimball et al. 2014). The global L4_C algorithm error budget for NEE derived during the mission prelaunch phase indicated that the estimated NEE ubRMSE uncertainty is proportional to GPP and is therefore larger in higher biomass productivity areas, including forests and croplands (Kimball et al. 2014). Likewise, NEE ubRMSE uncertainty is expected to be lower in less-productive areas, including grasslands and shrublands. Expected model NEE ubRMSE levels were also generally within targeted accuracy levels for characteristically less-productive boreal and Arctic biomes, even though relative model error as a proportion of total productivity (NEE RMSE / GPP) may be large in these areas. The estimated NEE uncertainty was lower than expected in some warmer tropical high biomass productivity areas (e.g. Amazon rainforest) because of reduced low temperature and moisture constraints to the L4_C respiration calculations so that the bulk of model uncertainty is contributed by GPP in these areas. Model NEE uncertainty in the African Congo was estimated to

SMAP↗
DOE OSTI2015

Interaction potentials of anisotropic nanocrystals from the trajectory sampling of particle motion using in situ liquid phase transmission electron microscopy

We demonstrate a generalizable strategy to use the relative trajectories of pairs and groups of nanocrystals, and potentially other nanoscale objects, moving in solution which can now be obtained by in situ liquid phase transmission electron microscopy (TEM) to determine the interaction potentials between nanocrystals. Such nanoscale interactions are crucial for collective behaviors and applications of synthetic nanocrystals and natural biomolecules, but have been very challenging to measure in situ at nanometer or sub-nanometer resolution. Here we use liquid phase TEM to extract the mathematical form of interaction potential between nanocrystals from their sampled trajectories. We show the power of this approach to reveal unanticipated features of nanocrystal–nanocrystal interactions by examining the anisotropic interaction potential between charged rod-shaped Au nanocrystals (Au nanorods); these Au nanorods assemble, in a tip-to-tip fashion in the liquid phase, in contrast to the well-known side-by-side arrangements commonly observed for drying-mediated assembly. These observations can be explained by a long-range and highly anisotropic electrostatic repulsion that leads to the tip-selective attachment. As a result, Au nanorods stay unassembled at a lower ionic strength, as the electrostatic repulsion is even longer-ranged. Our study not only provides a mechanistic understanding of the process by which metallic nanocrystals assemble but also demonstrates a method that can potentially quantify and elucidate a broad range of nanoscale interactions relevant to nanotechnology and biophysics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Collisions of deformable cells lead to collective migration

Collective migration of eukaryotic cells plays a fundamental role in tissue growth, wound healing and immune response. The motion, arising spontaneously or in response to chemical and mechanical stimuli, is also important for understanding life-threatening pathologies, such as cancer and metastasis formation. We present a phase-field model to describe the movement of many self-organized, interacting cells. The model takes into account the main mechanisms of cell motility – acto-myosin dynamics, as well as substrate-mediated and cell-cell adhesion. It predicts that collective cell migration emerges spontaneously as a result of inelastic collisions between neighboring cells: collisions lead to a mutual alignment of the cell velocities and to the formation of coherently-moving multi-cellular clusters. Small cell-to-cell adhesion, in turn, reduces the propensity for large-scale collective migration, while higher adhesion leads to the formation of moving bands. Our study provides valuable insight into biological processes associated with collective cell motility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗
NASA NTRS1987

Estimation of biophysical properties of forest canopies using C-band microwave data

A scatterometer ranging experiment is described in which C-band data and boresight photography were collected using a helicopter so as to provide a capability to study scattering processes in forest canopies in the Superior National Forest in Minnesota. An inversion scheme is used to determine C-band volume extinction and scattering coefficients for high density aspen sites. Analysis of data through the season indicates that VV, HH, and VH volume extinction coefficients change during the year and are presumably affected by the emergence and senescence of leaves. A linear relationship was observed between sigma(0) (VV) and leaf area index for low and medium density aspen sites, but a large decrease occurred in sigma(0) for both high density sites. Calculations using the Fung disk model, which accounts only for the leaves, shows an underestimate of sigma(0) by a factor of two or three indicating that scattering by branches and soil background may be important at C-band.

Pitts, David E.↗
DOE OSTI2019

X-ray phase contrast imaging of Vitis spp. buds shows freezing pattern and correlation between volume and cold hardiness

Grapevine (Vitis spp.) buds must survive winter temperatures in order to resume growth when suitable conditions return in spring. They do so by developing cold hardiness through deep supercooling, but the mechanistic process of supercooling in buds remains largely unknown. Here we use synchrotron X-ray phase contrast imaging to study cold hardiness-related characteristics of V. amurensis, V. riparia, and V. vinifera buds: time-resolved 2D imaging was used to visualize freezing; and microtomography was used to evaluate morphological changes during deacclimation. Bud cold hardiness was determined (low temperature exotherms; LTEs) using needle thermocouples during 2D imaging as buds were cooled with a N 2 gas cryostream. Resolution in 2D imaging did not allow for ice crystal identification, but freezing was assessed by movement of tissues coinciding with LTE values. Freezing was observed to propagate from the center of the bud toward the outer bud scales. The freezing events observed lasted several minutes. Additionally, loss of supercooling ability appears to be correlated with increases in bud tissue volume during the process of deacclimation, but major increases in volume occur after most of the supercooling ability is lost, suggesting growth resumption processes are limited by deacclimation state.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The first crystal structures of hybrid and parallel four-tetrad intramolecular G-quadruplexes

Abstract G-quadruplexes (GQs) are non-canonical DNA structures composed of stacks of stabilized G-tetrads. GQs play an important role in a variety of biological processes and may form at telomeres and oncogene promoters among other genomic locations. Here, we investigate nine variants of telomeric DNA from Tetrahymena thermophila with the repeat (TTGGGG)n. Biophysical data indicate that the sequences fold into stable four-tetrad GQs which adopt multiple conformations according to native PAGE. Excitingly, we solved the crystal structure of two variants, TET25 and TET26. The two variants differ by the presence of a 3′-T yet adopt different GQ conformations. TET25 forms a hybrid [3 + 1] GQ and exhibits a rare 5′-top snapback feature. Consequently, TET25 contains four loops: three lateral (TT, TT, and GTT) and one propeller (TT). TET26 folds into a parallel GQ with three TT propeller loops. To the best of our knowledge, TET25 and TET26 are the first reported hybrid and parallel four-tetrad unimolecular GQ structures. The results presented here expand the repertoire of available GQ structures and provide insight into the intricacy and plasticity of the 3D architecture adopted by telomeric repeats from T. thermophila and GQs in general.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

W Photoprotection in Tropical Marine Organisms

Increasing levels of ultraviolet (UV) radiation reaching the earth's surface which results from stratospheric ozone depletions could have serious implications for terrestrial plants and for aquatic organisms within the euphotic zone. A documented 9% decline in ozone at mid-latitudes is considered to produce a 12% increase in harmful UV radiation. The biologically damaging effects of higher UV levels, particularly W-B (280-320 rim), could manifest earlier in the tropics because of the relative thinness of the earth's equatorial ozone layer. Tropical marine organisms are also living close to their upper tolerance levels of water temperature, However, despite the large potential effects on plants and animals, little is known about UV effects on tropical ecosystems. Long-term ecological studies are needed to quantify the effects of increased UV radiation on terrestrial and marine ecosystems and to produce reliable data for prediction. Plants have developed several mechanisms to protect themselves from harmful UV radiation, one of which is the production of secondary leaf pigments that absorb W-B radiation (screening pigments). A higher concentration of screening pigments (e.g. flavonoids) in leaves may be interpreted as a natural response to increased W radiation. If higher concentrations of flavonoids filter out the excessive W radiation, no damage will occur, as suggested by Caldwell et al. (1989) and Tevini (1993). Failure to screen all W-B may result in deleterious effects on photosynthesis, plant genetic material, and plant and leaf morphology and growth. Eventually this will have an impact on ecosystem processes, structure, species composition, and productivity. This paper describes an ongoing project that is assessing the responses of mangroves, seagrasses and corals to W radiation by studying pigment concentrations, biophysical parameters, and variations in spectral reflectance in the field and in W-reduction experiments. Preliminary results on the distribution of W-absorbing flavonoid compounds in red mangroves (Rhizophora mangle) and the seagrass Thalassia testudinum, are presented. This research also provides, for the first time, a permanent record of daily W irradiance measurements at a tropical -location.

Armstrong, Roy A.↗
DOE OSTI2016

Phenotype heterogeneity in cancer cell populations

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a few results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as “bet hedging” of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to represent evolution towards heterogeneity, possibly polyclonal, in cancer cell populations and propose innovative directions for therapeutic strategies based on such frameworks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Protein drift-diffusion dynamics and phase separation in curved cell membranes and dendritic spines: Hybrid discrete-continuum methods

We develop methods for investigating protein drift-diffusion dynamics in heterogeneous cell membranes and the roles played by geometry, diffusion, chemical kinetics, and phase separation. Our hybrid stochastic numerical methods combine discrete particle descriptions with continuum-level models for tracking the individual protein drift-diffusion dynamics when coupled to continuum fields. We show how our approaches can be used to investigate phenomena motivated by protein kinetics within dendritic spines. The spine geometry is hypothesized to play an important biological role regulating synaptic strength, protein kinetics, and self-assembly of clusters. We perform simulation studies for model spine geometries varying the neck size to investigate how phase-separation and protein organization is influenced by different shapes. We also show how our methods can be used to study the roles of geometry in reaction-diffusion systems including Turing instabilities. Furthermore, our methods provide general approaches for investigating protein kinetics and drift-diffusion dynamics within curved membrane structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Empirical and process-based approaches to climate-induced forest mortality models

Globally, forests store ~45% of carbon sequestered terrestrially, contribute more to the terrestrial sink per area than any other land cover type, and assimilate an important portion of anthropogenic emissions. Forests exert strong biophysical control on climate via surface energy balance, and the hydrological cycle. Widespread forest mortality in response to drought, increased temperatures, and infestation of tree pests has been observed globally, potentially threatening forests' regulation of climate. This threat has prompted great interest in understanding and predicting tree mortality due to climate variability and change, especially drought. Initial tests of hydraulic failure (mortality caused by irreversible loss of xylem conductivity from air embolism), carbon starvation (mortality due to carbohydrate limitation), insect attacks, wildfire, and their interdependence, suggest proximal causes of mortality are likely complex, co-occurring, interrelated, and variable with tree species. While the interdependent roles of carbon and water in plant mortality are consistently observed, this work is continuously prompting new questions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions

Abstract. Permafrost soils in arctic and boreal ecosystems store twice the amount of current atmospheric carbon that may be mobilized and released to the atmosphere as greenhouse gases when soils thaw under a warming climate. This permafrost carbon climate feedback is among the most globally important terrestrial biosphere feedbacks to climate warming, yet its magnitude remains highly uncertain. This uncertainty lies in predicting the rates and spatial extent of permafrost thaw and subsequent carbon cycle processes. Terrestrial ecosystem influences on surface energy partitioning exert strong control on permafrost soil thermal dynamics and are critical for understanding permafrost soil responses to climate change and disturbance. Here we review how arctic and boreal ecosystem processes influence permafrost soils and characterize key ecosystem changes that regulate permafrost responses to climate. While many of the ecosystem characteristics and processes affecting soil thermal dynamics have been examined in isolation, interactions between processes are less well understood. In particular connections between vegetation, soil moisture, and soil thermal properties affecting permafrost conditions could benefit from additional research. In particular, connections between vegetation, soil moisture, and soil thermal properties affecting permafrost could benefit from additional research. Changes in ecosystem distribution and vegetation characteristics will alter spatial patterns of interactions between climate and permafrost. In addition to shrub expansion, other vegetation responses to changes in climate and disturbance regimes will all affect ecosystem surface energy partitioning in ways that are important for permafrost. Lastly, changes in vegetation and ecosystem distribution will lead to regional and global biophysical and biogeochemical climate feedbacks that may compound or offset local impacts on permafrost soils. Consequently, accurate prediction of the permafrost carbon climate feedback will require detailed understanding of changes in terrestrial ecosystem distribution and function and the net effects of multiple feedback processes operating across scales in space and time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The interactions of peripheral membrane proteins with biological membranes

The interactions of peripheral proteins with membrane surfaces are critical to many biological processes, including signaling, recognition, membrane trafficking, cell division and cell structure. On a molecular level, peripheral membrane proteins can modulate lipid composition, membrane dynamics and protein-protein interactions. Biochemical and biophysical studies have shown that these interactions are in fact highly complex, dominated by several different types of interactions, and have an interdependent effect on both the protein and membrane. Here we examine three major mechanisms underlying the interactions between peripheral membrane proteins and membranes: electrostatic interactions, hydrophobic interactions, and fatty acid modification of proteins. While experimental approaches continue to provide critical insights into specific interaction mechanisms, emerging bioinformatics resources and tools contribute to a systems-level picture of protein-lipid interactions. Through these recent advances, we begin to understand the pivotal role of protein-lipid interactions underlying complex biological functions at membrane interfaces.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The dimeric form of bacterial l ‐asparaginase YpAI is fully active

l ‐asparaginases from mesophilic bacteria (ASNases), including two enzymes very successfully used in the treatment of leukaemia, have been consistently described as homotetramers. On the contrary, structural studies show that homodimers of these enzymes should be sufficient to carry out the catalytic reaction. In this report, we investigated whether the type I Yersinia pestis asparaginase (YpAI) is active in a dimeric form or whether the tetrameric quaternary structure is critical for its activity. Using multiple biophysical techniques that investigate enzymatic properties and quaternary structure at either high or low protein concentration, we found that dimeric YpAI is fully active, suggesting that the tetrameric form of this subfamily of enzymes does not bear significant enzymatic relevance. In this process, we extensively characterized YpAI, showing that it is a cooperative enzyme, although the mechanism of allostery is still not definitely established. We showed that, like most type I ASNases, the substrate affinity of YpAI is low and this enzyme is very similar in terms of both the structure and enzymatic properties to homologous type I ASNase from Escherichia coli (EcAI). We extended these studies to more medically relevant type II ASNases, used as anti‐leukaemia drugs. We confirmed that type II ASNases are not allosteric, and that they might also be functional in a dimeric form. However, the determination of the accurate tetramer⇆dimer dissociation constants of these enzymes that most likely lie in the picomolar range is not possible with currently available biophysical techniques.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Design of a thrombin resistant human acidic fibroblast growth factor (hFGF1) variant that exhibits enhanced cell proliferation activity

Acidic fibroblast growth factors (FGF1s) are heparin binding proteins that regulate a wide array of key cellular processes and are also candidates for promising biomedical applications. FGF1-based therapeutic applications are currently limited due to their inherent thermal instability and susceptibility to proteases. Using a wide range of biophysical and biochemical techniques, we demonstrate that reversal of charge on a well-conserved positively charged amino acid, R136, in the heparin binding pocket drastically increases the resistance to proteases, thermal stability, and cell proliferation activity of the human acidic fibroblast growth factor (hFGF1). Two-dimensional NMR data suggest that the single point mutations at position-136 (R136G, R136L, R136Q, R136K, and R136E) did not perturb the backbone folding of hFGF1. Results of the differential scanning calorimetry experiments show that of all the designed R136 mutations only the charge reversal mutation, R136E, significantly increases (ΔT m = 7 °C) the thermal stability of the protein. Limited trypsin and thrombin digestion results reveal that the R136E mutation drastically increases the resistance of hFGF1 to the action of the serine proteases. Isothermal titration calorimetry data show that the R136E mutation markedly decreases the heparin binding affinity of hFGF1. Interestingly, despite lower heparin binding affinity, the cell proliferation activity of the R136E variant is more than double of that exhibited by either the wild type or the other R136 variants. The R136E variant due to its increased thermal stability, resistance to proteases, and enhanced cell proliferation activity are expected to provide valuable clues for the development of hFGF1- based therapeutics for the management of chronic diabetic wounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗