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At least 127 records · Page 7

Coordination of Anle138b to Silver Results in Selective Reduction of a C-terminal truncated Alpha-synuclein Protein and Increased Aggregate Size

Parkinson’s disease (PD) is a prevalent age-related neurodegenerative syndrome, partially thought to be caused by a decrease in alpha-synuclein proteostasis. Anle138b = 5-(1,3-benzodioxol-5-yl)-3-(3-bromophenyl)-1H-pyrazole (HL), is undergoing clinical trials as a promising mitigator of alpha-synuclein aggregation. Because complexation to metals is known to modulate the activity of several drugs, we have prepared and characterized: H2L(ClO4), [CuI(µ-L)]3, and [AgI(µ-L)]3. To better understand the bioviability of these compounds, we monitored their effects in a cell culture model of alpha-synuclein protein aggregation using human alpha-synuclein pre-formed fibrils (PFFs). Using two different anti-alpha-synuclein antibodies, our data suggests that [AgI(µ-L)]3 decreases a C-terminal truncated protein that is approximately 12.4 kDa, as well as increases the size and alters the shape of PFF-induced aggregates. This indicates that [AgI(µ-L)]3 impacts aggregation in a manner different from HL and may serve as a novel tool for studying C-terminal truncation related aggregation chemistry.

Rue, Kelly L.↗

Enhanced Hydrogen Evolution Catalysis of Pentlandite due to the Increases in Coordination Number and Sulfur Vacancy during Cubic‐Hexagonal Phase Transition

Abstract The search for new phases is an important direction in materials science. The phase transition of sulfides results in significant changes in catalytic performance, such as MoS 2 and WS 2 . Cubic pentlandite [cPn, (Fe, Ni) 9 S 8 ] can be a functional material in batteries, solar cells, and catalytic fields. However, no report about the material properties of other phases of pentlandite exists. In this study, the unit‐cell parameters of a new phase of pentlandite, sulfur‐vacancy enriched hexagonal pentlandite (hPn), and the phase boundary between cPn and hPn are determined for the first time. Compared to cPn, the hPn shows a high coordination number, more sulfur vacancies, and high conductivity, which result in significantly higher hydrogen evolution performance of hPn than that of cPn and make the non‐nano rock catalyst hPn superior to other most known nanosulfide catalysts. The increase of sulfur vacancies during phase transition provides a new approach to designing functional materials.

Chemistry↗

Increased inflammation as well as decreased endoplasmic reticulum stress and translation differentiate pancreatic islets from donors with pre-symptomatic stage 1 type 1 diabetes and non-diabetic donors

Aims/hypothesis Progression to type 1 diabetes is associated with genetic factors, the presence of autoantibodies and a decline in beta cell insulin secretion in response to glucose. Very little is known regarding the molecular changes that occur in human insulin-secreting beta cells prior to the onset of type 1 diabetes. Herein, we applied an unbiased proteomics approach to identify changes in proteins and potential mechanisms of islet dysfunction in islet-autoantibody-positive organ donors with pre-symptomatic stage 1 type 1 diabetes (HbA1c ≤42 mmol/mol [6.0%]). We aimed to identify pathways in islets that are indicative of beta cell dysfunction. Methods Multiple islet sections were collected through laser microdissection of frozen pancreatic tissues from organ donors positive for single or multiple islet autoantibodies (AAb + , n=5), and age (±2 years)- and sex-matched non-diabetic (ND) control donors (n=5) obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD). Islet sections were subjected to MS-based proteomics and analysed with label-free quantification followed by pathway and functional annotations. Results Analyses resulted in ~4500 proteins identified with low false discovery rate (<1%), with 2165 proteins reliably quantified in every islet sample. We observed large inter-donor variations that presented a challenge for statistical analysis of proteome changes between donor groups. We therefore focused on only the donors with stage 1 type 1 diabetes who were positive for multiple autoantibodies (mAAb + , n=3) and genetic risk compared with their matched ND controls (n=3) for the final statistical analysis. Approximately 10% of the proteins (n=202) were significantly different (unadjusted p<0.025, q<0.15) for mAAb + vs ND donor islets. The significant alterations clustered around major functions for upregulation in the immune response and glycolysis, and downregulation in endoplasmic reticulum (ER) stress response as well as protein translation and synthesis. The observed proteome changes were further supported by several independent published datasets, including a proteomics dataset from in vitro proinflammatory cytokine-treated human islets and single-cell RNA-seq datasets from AAb + individuals. Conclusions/interpretation In situ human islet proteome alterations in stage 1 type 1 diabetes centred around several major functional categories, including an expected increase in immune response genes (elevated antigen presentation/HLA), with decreases in protein synthesis and ER stress response, as well as compensatory metabolic response. The dataset serves as a proteomics resource for future studies on beta cell changes during type 1 diabetes progression and pathogenesis. Data availability The LC-MS raw datasets that support the findings of this study have been deposited in the online repository: MassIVE (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with accession no. MSV000090212.

Autoantibody-positive↗

Increased AGE Cross-Linking Reduces the Mechanical Properties of Osteons

Abstract The osteon is the primary structural component of bone, contributing significantly to its unique toughness and strength. Despite extensive research on osteonal structure, the properties of osteons have not been fully investigated, particularly within the context of bone fragility diseases like type 2 diabetes mellitus (T2DM). This study aims to isolate osteons from bovine bone, simulate the effects of increased advanced glycation end-products (AGEs) in T2DM through ribosylation, and evaluate the mechanical properties of isolated osteons. Osteons extracted from the posterior section of bovine femur mid-diaphysis were processed to achieve a sub-millimeter scale for microscale imaging. Subsequently, synchrotron radiation micro-computed tomography was employed to precisely localize and isolate the osteon internally. While comparable elastic properties were observed between control and ribosylated osteons, the presence of AGEs led to decreased strain to failure. Young’s modulus was quantified (9.9 ± 4.9 GPa and 8.7 ± 3 GPa, respectively), aligning closely with existing literature. This study presents a novel method for the extraction and isolation of osteons from bone and shows the detrimental effect of AGEs at the osteonal level.

Materials Science↗

Alkaloids are associated with increased microbial diversity and metabolic function in poison frogs

Shifts in host-associated microbiomes can impact both host and microbes. It is of interest to understand how perturbations, like the introduction of exogenous chemicals, impact microbiomes. In poison frogs (family Dendrobatidae), the skin microbiome is exposed to alkaloids that the frogs sequester for defense. These alkaloids are antimicrobial; however, their effect on the frogs’ skin microbiome is unknown. To test this, we characterized microbial communities from field-collected dendrobatid frogs. Then, we conducted a laboratory experiment to monitor the effect of the alkaloid decahydroquinoline (DHQ) on the microbiome of two frog species with contrasting alkaloid loads in nature. In both datasets, we found that alkaloid-exposed microbiomes were more phylogenetically diverse, with an increase in diversity among rare taxa. Further, to better understand the isolate-specific response to alkaloids, we cultured microbial isolates from poison frog skin and found that many isolates exhibited enhanced growth or were not impacted by the addition of DHQ. To further explore the microbial response to alkaloids, we sequenced the metagenomes from high- and low-alkaloid frogs and observed a greater diversity of genes associated with nitrogen and carbon metabolism in high-alkaloid frogs. From these data, we hypothesized that some strains may metabolize the alkaloids. We used stable isotope tracing coupled to nanoSIMS (nanoscale secondary ion mass spectrometry), which supported the idea that some of these isolates are able to metabolize DHQ. Together, these data suggest that poison frog alkaloids open new niches for skin-associated microbes with specific adaptations, such as alkaloid metabolism, that enable survival in this environment.

59 BASIC BIOLOGICAL SCIENCES↗

Intelligent industrial demand response to increase grid flexibility and reliability: A review

The rapid transition toward renewable energy has introduced challenges in grid stability due to the intermittency of non-dispatchable sources like solar and wind. Industrial Demand Response (IDR) offers a promising, cost-effective solution that adjusts energy consumption patterns to align with supply, increases renewable utilization, and reduces costs. This review provides an updated analysis of IDR, sorting technologies into five categories: energy storage, scheduled energy usage, operational flexibility, on-site generation, and intelligent operations. Energy storage solutions, while requiring little flexibility, often have the longest payback periods. While slightly better, on-site generation also has longer payback periods, ranging from 5 to 20 years or more. Scheduled energy usage, operational flexibility, and intelligent operations allow significant peak reduction at lower capital costs but require greater flexibility. While 15–20 % peak reduction is within the range of all five categories, scheduled energy use and on-site energy generation are shown to have reductions of up to 70–80 % in select scenarios. Combining multiple IDR strategies from these five categories maximizes both financial and operational benefits. Synergistic approaches are shown to enhance grid stability while reducing costs. As the grid evolves, IDR will enable a more flexible, renewable-powered future that will benefit industrial facilities and the broader energy system.

Demand flexibility↗

Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method that converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.

Harwood, Thomas V. [USDOE Joint Genome Institute (↗

Ambient Synthesis for Fe(II) Polypyridyl Complexes with an Order of Magnitude Increase in Charge-Transfer Excited-State Lifetimes over [Fe(bpy) 3 ] 2+

Replacing precious metals with abundant metals is an important research focus in photochemical energy conversion and storage to meet global energy demands. However, transition metal complexes (TMCs) based on abundant 3d metals typically possess photochemical disadvantages─such as short charge-transfer excited-state lifetimes─and molecular modifications have focused on optimizing the interplay of structure, dynamics, and energetics to overcome their limitations. One strategy to do so is the use of bespoke ligands that can extend the lifetimes of chemically useful excited states. Here, in this study, we report the synthesis and characterization of novel Fe(II) complexes featuring lengthy polypyridyl ligands that can be readily synthesized. Steady-state and transient absorption spectroscopies indicate that these complexes have desirable properties and their excited metal-to-ligand charge-transfer states live an order of magnitude longer than in the benchmark [Fe(bpy) 3 ] 2+ . This lifetime is largely preserved in the heteroleptic complexes, thereby enabling the preparation of asymmetric complexes. Additionally, we apply nonradiative transition theory to explain the long-time decay kinetics. In light of their ease of preparation and reasonable excited-state lifetimes, we suggest the use of these complexes in Fe(II) dye-sensitized solar cells, where the rate of charge injection would be competitive with increased lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Increasing Branching and Functionalization Decreases Crystallinity and Crystallization Rate in Linear EVOH

Here, we report the crystallization behavior of a linear poly(ethylene-co-vinyl alcohol) (LEVOH) under isothermal crystallization as a function of both OH incorporation and undercooling, and compare the results to conventional branched EVOH. This LEVOH is synthesized by post-polymerization functionalization of polycyclooctene, and it exhibits a half-crystallization time and primary crystallization rate nearly an order of magnitude faster than branched EVOH at ~ 6 mol% OH incorporation. While the LEVOH obtains approximately twice the extent of crystallization compared to the branched equivalent, as OH incorporation increases, the crystallization kinetics and crystallinity of LEVOH decrease. The crystal structure of LEVOH is orthorhombic at low functionalization (≤ 11 mol% OH), a mixture of orthorhombic and hexagonal at moderate functionalization (17 - 21 mol%), and hexagonal at high functionalization (23 %). The LEVOH crystallizes into plates, with crystallite widths ~ 20 - 60 times the crystallite thickness. Ultimately, we show LEVOH crystallizes faster and to a greater extent than commercial branched EVOH, a potential advantage of post-polymerization functionalization as part of polymer-to-polymer upcycling.

36 MATERIALS SCIENCE↗

Electrolyte Immersion Increases Photoconductivity in a Model Polymer Photocathode

Immersing polymer solar cells in aqueous electrolyte for photoelectrochemical (PEC) hydrogen production is likely to cause photophysical changes that could present both challenges and opportunities for engineering functional and durable devices. Herein we study the bulk heterojunction blend poly(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene-2,6-diyl)-alt-(2-(((2-ethylhexyl)oxy)carbonyl)-3-fluorothieno[3,4-b]thiophene-4,6-diyl):poly(N,N'-di(2-octyldodecyl)naphthalene-1,8:4,5-bis(dicarboximide)-2,6-diyl)-alt-(2,2-bithiophene-5,5'-diyl) (PTB7-Th:N2200) excited-state dynamics in electrolyte from femtosecond to millisecond time scales using pump-probe microwave conductivity and absorption spectroscopy. While the blend swells very little, electrolyte exposure increases the microwave-frequency mobility and possibly the yield of photogenerated charges while also decreasing crystallinity. These results indicate an enhancement in key performance metrics, implying that any limitations on the performance of PEC test devices do not arise from active layer-electrolyte interactions. For the PTB7-Th:N2200 blend or similar photocathode systems, our results indicate that improving the interfacial kinetics and/or the carrier lifetime should be prioritized, not protecting the active layer from the electrolyte. Since this observation may not be universal to all polymer systems, future research should focus on identifying their limiting photophysical processes. electrolyte.

14 SOLAR ENERGY↗

Ion Correlations Decrease Particle Aggregation Rate by Increasing Hydration Forces at Interfaces

The connection between solution structure, particle forces, and emergent phenomena at solid–liquid interfaces remains ambiguous. In this case study on boehmite aggregation, we established a connection between interfacial solution structure, emerging hydration forces between two approaching particles, and the resulting structure and kinetics of particle aggregation. In contrast to expectations from continuum-based theories, we observed a nonmonotonic dependence of the aggregation rate on the concentration of sodium chloride, nitrate, or nitrite, decreasing by 15-fold in 4 molal compared to 1 molal solutions. These results are accompanied by an increase in repulsive hydration forces and interfacial oscillatory features from 0.27–0.31 nm in 0.01 molal to 0.38–0.52 nm in 2 molal. Moreover, molecular dynamics (MD) simulations indicated that these changes correspond to enhanced ion correlations near the interface and produced loosely bound aggregates that retain electrolyte between the particles. In conclusion, we anticipate that these results will enable the prediction of particle aggregation, attachment, and assembly, with broad relevance to interfacial phenomena.

36 MATERIALS SCIENCE↗

Depletion of the Protein Hydration Shell with Increasing Temperature Observed by Small-Angle X-ray Scattering and Molecular Simulations

The hydration shell is an integral part of proteins since it plays key roles in conformational transitions, molecular recognition, and enzymatic activity. While the dynamics of the hydration shell have been described by spectroscopic techniques, the structure of the hydration shell remains less understood due to the lack of hydration shell-sensitive structural probes with high spatial resolution. We combined temperature-ramp small-angle X-ray scattering (T-ramp SAXS) from 255 to 335 K with molecular simulations to demonstrate that the hydration shells of the IgG-binding domain of Protein G (GB3) and the villin headpiece are remarkably temperature-sensitive. For proteins in the folded state, T-ramp SAXS data and explicit-solvent SAXS predictions consistently demonstrate decays of protein contrasts and radii of gyration with increasing temperature, which are shown to reflect predominantly temperature-sensitive, depleting hydration shells. The depletion is caused not merely by enhanced disorder within the hydration shells but also by partial displacements of surface-coordinated water molecules. Together, T-ramp SAXS and explicit-solvent SAXS calculations provide a novel structural view of the protein hydration shell, which underlies temperature-dependent processes such as cold denaturation, thermophoresis, or biomolecular phase separation.

electron density↗

A Mesopore-Confined and Graphene Oxide-Localized Ruthenium Catalyst Increases Rates of Mid-Chain Polyolefin Hydrogenolysis

A catalyst architecture with mesoporous silica coating Ru nanoparticles on reduced graphene oxide (mSiO 2 /Ru/rGO) localizes the 2 nm Ru solely at the closed bottoms of 2.9 nm diameter mesopores. mSiO 2 /Ru/rGO catalyzes the rapid, selective hydrogenolysis of polyolefins at wax formation rates (ν wax ) up to 1700 g wax ·g Ru –1 ·h –1 and a turnover frequency (TOF) for C–C bond cleavage of 130 ± 8 min –1 . The ν wax and TOF for mSiO 2 /Ru/rGO are 23× and 16× those of nonporous Ru/rGO, respectively, indicating that faster chain cleavage is also more selective inside mesopores. The methane yield from mSiO 2 /Ru/rGO is ca. 30% of the value obtained from Ru/rGO. Methane decreases, and wax selectivity improves with narrow-pore (2.3 nm) mSiO 2 /Ru/rGO. The reaction rate decreases at lower and higher H 2 pressures from its maximum at 37 bar. Log(TOF)-log(P H2 ) plots reveal rates ∝ [P H2 ] 2.8 or [P H2 ] −2.0 in the lower or higher pressure ranges, respectively. Corresponding plots for Ru/C give rates ∝ [P H2 ] 1 or [P H2 ] −2.4 . Ru is hydrocarbon-covered at low pressure; thus, the higher H 2 order for mSiO 2 /Ru/rGO indicates that mesopores increase the density of cleavable unsaturated moieties on the Ru surface. The lower H 2 order on Ru/C implies a lower density of cleavable groups because saturated segments occupy a larger fraction of the Ru surface. Higher surface occupancy by the hydrocarbon reactant correlates with more methane formation. Therefore, pore confinement, narrower pore diameter in mSiO 2 /Ru/rGO, or higher H 2 pressure leads to lower methane yields. Ru nanoparticles in mSiO 2 /Ru/rGO maintain equivalent activity and selectivity over five recycling tests.

Catalysts↗

Increasing Mosquito Abundance Under Global Warming

Mosquitoes are a key virus vector that poses significant health threats globally, affecting 700 million individuals and causing 1 million deaths annually. Accurately predicting mosquito abundance and dispersion remains a challenge. Complex interactions between mosquito dynamics and various environmental factors, notably hydrology, contribute to this challenge. Existing models typically focus on precipitation and temperature and often overlook further impacts of hydrological variables within mosquito modeling. In this study, we developed an artificial intelligence‐based model for mosquito dynamics, explicitly accounting for different hydrological variables, such as precipitation, soil moisture and streamflow. Using Toronto, Canada, as a case study, we identified causal relationships between changes in mosquito populations, hydrological factors, vegetation (e.g., leaf area index), and climate variables (e.g., daylight length, precipitation, and temperature). We embedded these relationships into a Long Short‐Term Memory (LSTM) Neural Network Model capable of accurately detecting mosquito dynamics across annual, seasonal, and monthly time scales. The LSTM is able to explain, on average, approximately 40% of the variance in the observed mosquito abundance data. Using the calibrated model, we predicted that the summer season mosquito abundance would increase by ∼16% and ∼19% under an intermediate greenhouse emission scenario, Shared Socioeconomic Pathway (SSP) 2–4.5, and a high greenhouse emission scenario, SSP5‐8.5, respectively. We expect that this model can serve as a valuable tool and inform science‐based decisions affecting mosquito dynamics and public health. It can also build a foundation for future risk analysis at the regional and larger scales.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Recent Increase in Landfalling Tropical Cyclones Over Florida's Gulf Coast

Unlike Florida's Atlantic Coast, the Gulf Coast of Florida has seen heightened tropical cyclone (TC) activity in recent decades with several destructive landfalls. Here, we attempt to understand this regional contrast using a suite of observations for the period 1979–2024. First, we demonstrate that while the El Niño Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) can explain ~23% of the interannual variability in landfalls over the Gulf Coast, the variance explained by them for the Atlantic Coast is statistically insignificant. Next, we show that this striking difference may be attributed to the regional patterns of wind shear, steering flow and air-sea thermodynamic state excited by those modes of variability. The differential control exerted by ENSO, AMO, and NAO on landfalling Florida TCs, in combination with decadal trends in those modes, is likely responsible for the observed increases in landfalls over Florida's Gulf Coast.

Florida↗

Diamine chelates for increased stability in mixed Sn–Pb and all-perovskite tandem solar cells

Perovskite tandem solar cells show promising performance but non-radiative recombination and its progressive worsening with time, especially in the mixed Sn–Pb low-bandgap layer, limit performance and stability. Here, in this study, we find that mixed Sn–Pb perovskite thin films exhibit a compositional gradient, with an excess of Sn on the surface – and we show this gradient exacerbates oxidation and increases the recombination rate. We find that diamines preferentially chelate Sn atoms, removing them from the film surface and achieving a more balanced Sn:Pb stoichiometry, making the surface of the film resistive to the oxidation of Sn. The process forms an electrically resistive low-dimensional barrier layer, passivating defects and reducing interface recombination. Further improving the homogeneity of the barrier layer using 1,2-diaminopropane results in more uniform distribution and passivation. Tandems achieve a power conversion efficiency of 28.8%. As a result, encapsulated tandems retain 90% of initial efficiency following 1000 hours of operating at the maximum power point under simulated one-sun illumination in air without cooling.

14 SOLAR ENERGY↗

Increasing extreme hourly precipitation risk for New York City after Hurricane Ida

The remnants of Hurricane Ida caused major damage and death in the United States on September 1st, 2021, and 11 people drowned in flooded basement apartments within New York City (NYC). It was catastrophic because the maximum hourly precipitation intensity, recorded as 3.47 inches (88.1 mm) per hour at Central Park, was unprecedentedly high for the NYC region. The stormwater infrastructure in NYC is built for 1.75 inches (44.5 mm) per hour, and so understanding the dynamic risk associated with Ida can inform city planning efforts for climate change’s impact on short duration extreme precipitation events. We contextualize this storm’s record-breaking hourly intensity within the historical record as well as project its risk in the near- to medium-term future using nonstationary stochastic models. These models are conditioned on average temperature (T avg ) and cooling degree day (CDD) projections from three climate models as a covariate, each with a SSP 126 and SSP 370 scenario. The likelihood of such a storm was slowly increasing even before Ida happened, but the projected aggregate reoccurrence risk of an event of Ida’s magnitude over time from the non-stationary models ranges from 4 to 52 times higher than the risk given by the stationary model. Using CDD as a covariate resulted in risks that were more than twice the magnitude than when using T avg . Presenting both covariates provides a broader envelope of uncertainty, which highlights the importance and nuances in the choice of a regionally appropriate covariate for non-stationary risk analysis.

Mossel, Carolien↗

Robust increase in South Asian monsoon rainfall under warming driven by extratropical clouds and ocean

The responses of South Asian Monsoon (SAM) circulation under global warming are known to be highly uncertain, leading to the wide spread of SAM rainfall projections among models. Here, we show that the uncertain SAM circulation in Coupled Model Intercomparison Project Phase 6 models consists of two robust components that partly offset each other: a weakening component linked to a global thermodynamic constraint and a northward shift component understood through a regional 2D energetic perspective. We further attribute the robust northward shift of SAM circulation to positive cloud feedback over the Eurasia Continent and heat uptake in the Southern Ocean. A set of climate model simulations supports the finding that SAM rainfall increase is primarily due to the northward shift of circulation driven by extratropical processes. This energetic perspective opens new avenues for predicting monsoon rainfall by connecting circulation changes to radiative forcing, feedbacks, and ocean heat uptake.

54 ENVIRONMENTAL SCIENCES↗