Inferred drought-induced plant allocation shifts and their impact on drought legacy at a tropical forest site.

While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long-lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought-induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model-data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5 months. The inferred allocation shifts influenced the post-drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust-boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought-free conditions. Overall, allocation shifts accounted for 65% [45%-75%] of drought legacy effects in modeled NBE. In summary, drought-induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land-atmosphere CO2 exchanges and should be accounted for in ecosystem models.

Impacts of climate timescale on the stability of trait-environment relationships.

Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.

Global net biome CO2 exchange predicted comparably well using parameter-environment relationships and plant functional types.

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.

Synthesis of Distinct Iron Oxide Nanomaterial Shapes Using Lyotropic Liquid Crystal Solvents.

A room temperature reduction-hydrolysis of Fe(III) precursors such as FeCl3 or Fe(acac)3 in various lyotropic liquid crystal phases (lamellar, hexagonal columnar, or micellar) formed by a range of ionic or neutral surfactants in H2O is shown to be an effective and mild approach for the preparation of iron oxide (IO) nanomaterials with several morphologies (shapes and dimensions), such as extended thin nanosheets with lateral dimensions of several hundred nanometers as well as smaller nanoflakes and nanodiscs in the tens of nanometers size regime. We will discuss the role of the used surfactants and lyotropic liquid crystal phases as well as the shape and size differences depending upon when and how the resulting nanomaterials were isolated from the reaction mixture. The presented synthetic methodology using lyotropic liquid crystal solvents should be widely applicable to several other transition metal oxides for which the described reduction-hydrolysis reaction sequence is a suitable pathway to obtain nanoscale particles.

Biodistribution of negatively charged iron oxide nanoparticles (IONPs) in mice and enhanced brain delivery using lysophosphatidic acid (LPA).

Effective treatment of brain disorders requires a focus on improving drug permeability across the blood-brain barrier (BBB). Herein, we examined the pharmacokinetic properties of negatively charged iron oxide nanoparticles (IONPs) and the capability of using lysophosphatidic acid (LPA) to transiently disrupt the tight junctions and allow IONPs to enter the brain. Under normal conditions, IONPs had a plasma half-life of six minutes, with the liver and spleen being the major organs of deposition. Treatment with LPA enhanced accumulation of IONPs in the brain and spleen (approximately 4-fold vs. control). LPA and IONP treated mice revealed no sign of peripheral immune cell infiltration in the brain and no significant activation of microglia or astrocytes. These studies show improved delivery efficiency of IONPs following LPA administration. Our findings suggest transient disruption of the BBB may be a safe and effective method for increasing IONP delivery to the brain.

Differential internalization of brick shaped iron oxide nanoparticles by endothelial cells.

Nanoparticles targeting endothelial cells to treat diseases such as cancer, oxidative stress, and inflammation have traditionally relied on ligand-receptor based delivery. The present studies examined the influence of nanoparticle shape in regulating preferential uptake of nanoparticles in endothelial cells. Spherical and brick shaped iron oxide nanoparticles (IONPs) were synthesized with identical negatively charged surface coating. The nanobricks showed a significantly greater uptake profile in endothelial cells compared to nanospheres. Application of an external magnetic field significantly enhanced the uptake of nanobricks but not nanospheres. Transmission electron microscopy revealed differential internalization of nanobricks in endothelial cells compared to epithelial cells. Given the reduced uptake of nanobricks in endothelial cells treated with caveolin inhibitors, the increased expression of caveolin-1 in endothelial cells compared to epithelial cells, and the ability of IONP nanobricks to interfere with caveolae-mediated endocytosis process, a caveolae-mediated pathway is proposed as the mechanism for differential internalization of nanobricks in endothelial cells.

Aqueous synthesis of polyhedral "brick-like" iron oxide nanoparticles for hyperthermia and T2 MRI contrast enhancement.

A low temperature, aqueous synthesis of polyhedral iron oxide nanoparticles (IONPs) is presented. The modification of the co-precipitation hydrolysis method with Triton X surfactants results in the formation of crystalline polyhedral particles. The particles are herein termed iron oxide "nanobricks" (IONBs) as the variety of particles made are all variations on a simple "brick-like" rhombohedral shape as evaluated by TEM. These IONBs can be easily coated with hydrophilic silane ligands, allowing them to be dispersed in aqueous media. The dispersed particles are investigated for potential applications as hyperthermia and T2 MRI contrast agents. The results demonstrate that the IONBs perform better than comparable spherical IONPs in both applications, and show r2 values amongst the highest for iron oxide based materials reported in the literature.

Detecting, visualizing, and measuring gold nanoparticle chirality using helical pitch measurements in nematic liquid crystal phases.

Chirality at the nanoscale, or more precisely, the chirality or chiroptical effects of chiral ligand-capped metal nanoparticles (NPs) is an intriguing and rapidly evolving field in nanomaterial research with promising applications in catalysis, metamaterials, and chiral sensing. The aim of this work was to seek out a system that not only allows the detection and understanding of NP chirality but also permits visualization of the extent of chirality transfer to a surrounding medium. The nematic liquid crystal phase is an ideal candidate, displaying characteristic defect texture changes upon doping with chiral additives. To test this, we synthesized chiral cholesterol-capped gold NPs and prepared well-dispersed mixtures in two nematic liquid crystal hosts. Induced circular dichroism spectropolarimetry and polarized light optical microscopy revealed that all three gold NPs induce chiral nematic phases, and that those synthesized in the presence of a chiral bias (disulfide) are more powerful chiral inducers than those where the NP was formed in the absence of a chiral bias (prepared by conjugation of a chiral silane to preformed NPs). Helical pitch data here visually show a clear dependence on the NP size and the number of chiral ligands bound to the NP surface, thereby supporting earlier experimental and theoretical data that smaller metal NPs made in the presence of a chiral bias are stronger chiral inducers.

Magnetic field enhanced convective diffusion of iron oxide nanoparticles in an osmotically disrupted cell culture model of the blood-brain barrier.

PURPOSE: The present study examines the use of an external magnetic field in combination with the disruption of tight junctions to enhance the permeability of iron oxide nanoparticles (IONPs) across an in vitro model of the blood-brain barrier (BBB). The feasibility of such an approach, termed magnetic field enhanced convective diffusion (MFECD), along with the effect of IONP surface charge on permeability, was examined. METHODS: The effect of magnetic field on the permeability of positively (aminosilane-coated [AmS]-IONPs) and negatively (N-(trimethoxysilylpropyl)ethylenediaminetriacetate [EDT]-IONPs) charged IONPs was evaluated in confluent monolayers of mouse brain endothelial cells under normal and osmotically disrupted conditions. RESULTS: Neither IONP formulation was permeable across an intact cell monolayer. However, when tight junctions were disrupted using D-mannitol, flux of EDT-IONPs across the bEnd.3 monolayers was 28%, increasing to 44% when a magnetic field was present. In contrast, the permeability of AmS-IONPs after osmotic disruption was less than 5%. The cellular uptake profile of both IONPs was not altered by the presence of mannitol. CONCLUSIONS: MFECD improved the permeability of EDT-IONPs through the paracellular route. The MFECD approach favors negatively charged IONPs that have low affinity for the brain endothelial cells and high colloidal stability. This suggests that MFECD may improve IONP-based drug delivery to the brain.

One-pot synthesis of iron oxide nanoparticles with functional silane shells: a versatile general precursor for conjugations and biomedical applications.

Iron oxide nanoparticles (IONPs) and their surface modifications with therapeutic or diagnostic (theranostic, TN) agents are of great interest. Here we present a novel one-pot synthesis of a versatile general TN precursor (aminosilane-coated IONPs [IONP-Sil(NH2)]) with surface amine groups. Surface functional group conversion to carboxylic acid was accomplished by conjugating poly(ethylene glycol) diacid to IONP-Sil(NH2). The NPs were characterized using powder X-ray diffraction (XRD), transmission electron microscopy (TEM), high-resolution TEM, selected area electron diffraction (SAED), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared (FT-IR) spectroscopy. Biocompatibility and cell uptake profile of the nanoparticles were evaluated in-vitro using cultured liver cells (HepG2). Oleylamine (hydrophobic) and bovine serum albumin (BSA) as model drugs were attached to IONP-Sil-PEG(COOH). The ability of IONP-Sil(NH2) to bind small interfering RNA (siRNA) is also shown.

Characterization of cellular uptake and toxicity of aminosilane-coated iron oxide nanoparticles with different charges in central nervous system-relevant cell culture models.

BACKGROUND: Aminosilane-coated iron oxide nanoparticles (AmS-IONPs) have been widely used in constructing complex and multifunctional drug delivery systems. However, the biocompatibility and uptake characteristics of AmS-IONPs in central nervous system (CNS)-relevant cells are unknown. The purpose of this study was to determine the effect of surface charge and magnetic field on toxicity and uptake of AmS-IONPs in CNS-relevant cell types. METHODS: The toxicity and uptake profile of positively charged AmS-IONPs and negatively charged COOH-AmS-IONPs of similar size were examined using a mouse brain microvessel endothelial cell line (bEnd.3) and primary cultured mouse astrocytes and neurons. Cell accumulation of IONPs was examined using the ferrozine assay, and cytotoxicity was assessed by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. RESULTS: No toxicity was observed in bEnd.3 cells at concentrations up to 200 µg/mL for either AmS-IONPs or COOH-AmS-IONPs. AmS-IONPs at concentrations above 200 µg/mL reduced neuron viability by 50% in the presence or absence of a magnetic field, while only 20% reductions in viability were observed with COOH-AmS-IONPs. Similar concentrations of AmS-IONPs in astrocyte cultures reduced viability to 75% but only in the presence of a magnetic field, while exposure to COOH-AmS-IONPs reduced viability to 65% and 35% in the absence and presence of a magnetic field, respectively. Cellular accumulation of AmS-IONPs was greater in all cell types examined compared to COOH-AmS-IONPs. Rank order of cellular uptake for AmS-IONPs was astrocytes > bEnd.3 > neurons. Accumulation of COOH-AmS-IONPs was minimal and similar in magnitude in different cell types. Magnetic field exposure enhanced cellular accumulation of both AmS- and COOH-AmS-IONPs. CONCLUSION: Both IONP compositions were nontoxic at concentrations below 100 µg/mL in all cell types examined. At doses above 100 µg/mL, neurons were more sensitive to AmS-IONPs, whereas astrocytes were more vulnerable toward COOH-AmS-IONPs. Toxicity appears to be dependent on the surface coating as opposed to the amount of iron-oxide present in the cell.