Targeting oncogenic KRAS with molecular brush-conjugated antisense oligonucleotides.

The mutant form of the guanosine triphosphatase (GTPase) KRAS is a key driver in human tumors but remains a challenging therapeutic target, making KRASMUT cancers a highly unmet clinical need. Here, we report a class of bottlebrush polyethylene glycol (PEG)-conjugated antisense oligonucleotides (ASOs) for potent in vivo KRAS depletion. Owing to their highly branched architecture, these molecular nanoconstructs suppress nearly all side effects associated with DNA-protein interactions and substantially enhance the pharmacological properties of the ASO, such as plasma pharmacokinetics and tumor uptake. Systemic delivery to mice bearing human non-small-cell lung carcinoma xenografts results in a significant reduction in both KRAS levels and tumor growth, and the antitumor performance well exceeds that of current popular ASO paradigms, such as chemically modified oligonucleotides and PEGylation using linear or slightly branched PEG. Importantly, these conjugates relax the requirement on the ASO chemistry, allowing unmodified, natural phosphodiester ASOs to achieve efficacy comparable to that of chemically modified ones. Both the bottlebrush polymer and its ASO conjugates appear to be safe and well tolerated in mice. Together, these data indicate that the molecular brush-ASO conjugate is a promising therapeutic platform for the treatment of KRAS-driven human cancers and warrant further preclinical and clinical development.

Bioaugmentation performances with a powerful strain for nitrogen removal without N2O accumulation.

N2O is regarded as an inevitable intermediate during nitrogen removal, especially for wastewater treatment plants where good operating conditions would be required to mitigate N2O releasing, which generally causes a high treatment cost. In this study, a novel bacterium capable of removing nitrogen without N2O accumulation was isolated and identified as Citrobacter freundii XY-1. The nitrogen removal characteristics, nitrogen removal pathway, bioaugmentation in different reactors as well as microbial diversity were investigated. Results showed that 99.42% of NH+ 4-N and 95% of total organic carbon could be removed within 48 h with the corresponding removal rates being 4.03 mg/(L·h) and 39.42 mg/(L·h), respectively. It was inferred that traditional denitrification and N2O generation do not exist in the pathway of removing nitrogen by XY-1 based on isotope analysis and functional genes detection. Bioaugmentations of XY-1 in both sequencing batch reactor and biological aerated filter significantly promoted the performances of nitrogen removal. The microbial diversity indicated that the relative abundance of strain XY-1 ranged from 45% to 66%, predominating throughout the running period. Overall, XY-1 could become an incredibly important candidate for the upgrading of wastewater treatment plants.

Hepatoprotective Effects of Albumin-Encapsulated Nanoparticles of a Curcumin Derivative COP-22 against Lipopolysaccharide/D-Galactosamine-Induced Acute Liver Injury in Mice.

Acute liver injury (ALI) is a severe syndrome and can further develop into acute liver failure (ALF) which can lead to high mortality and cause irreversible liver injuries in the clinic. Liver transplantation is the most common treatment; however, liver donors are lacking, and the progression of ALF is rapid. Nanoparticles can increase the bioavailability and the targeted accumulation of drugs in the liver, so as to significantly improve the therapeutic effect of ALI. Curcumin derivative COP-22 exhibits low cytotoxicity and effective anti-inflammatory activity; however, it has poor water solubility. In this study, COP-22-loaded bovine serum albumin (BSA) nanoparticles (22 NPs) were prepared and characterized. They exhibit effective hepatoprotective effects by inhibiting inflammation, oxidative stress, and apoptosis on Lipopolysaccharide/D-Galactosamine-induced acute liver injury of mice. The anti-inflammatory activity of 22 NPs is related to the regulation of the NF-κB signaling pathways; the antioxidant activity is related to the regulation of the Nrf2 signaling pathways; and the apoptosis activity is related to mitochondrial pathways, involving Bcl-2 family and Caspase-3 protein. These three cellular pathways are interrelated and affected each other. Moreover, 22 NPs could be passively targeted to accumulate in the liver through the retention effect and are more easily absorbed than 22.HCl salt in the liver.

A Long-Circulating Vector for Aptamers Based upon Polyphosphodiester-Backboned Molecular Brushes.

Aptamers face challenges for use outside the ideal conditions in which they are developed. These difficulties are most palpable in vivo due to nuclease activities, rapid clearance, and off-target binding. Herein, we demonstrate that a polyphosphodiester-backboned molecular brush can suppress enzymatic digestion, reduce non-specific cell uptake, enable long blood circulation, and rescue the bioactivity of a conjugated aptamer in vivo. The backbone along with the aptamer is assembled via solid-phase synthesis, followed by installation of poly(ethylene glycol) (PEG) side chains using a two-step process with near-quantitative efficiency. The synthesis allows for precise control over polymer size and architecture. Consisting entirely of building blocks that are generally recognized as safe for therapeutics, this novel molecular brush is expected to provide a highly translatable route for aptamer-based therapeutics.

Changes in the epidemic of pulmonary tuberculosis in Shanghai from 1992 to 2016.

OBJECTIVE: To estimate whether WHO's End TB Strategy targets can be achieved by analysing the incidence trend of pulmonary tuberculosis in Shanghai during 1992-2016. METHOD: The age-adjusted annual incidence of tuberculosis (TB) was calculated based on data from the national TB registration system. Linear regression was applied to analyse the trend of the epidemic, together with the statistical indicator of annual percent change (APC). RESULTS: The overall age-standardised rate decreased from 34.8/100 000 in 1992 to 21.2/100 000 in 2016, or by 2.15% (t = -13.258, P < 0.05) annually. After rapidly declining between 1999 and 2003 (-5.4% p.a.), the epidemic remained at a stable level with a lower annual declining rate (-1.1% p.a). In 2035, the estimated incidence will be 17.2/100 000 based on the APC in 2004-2016. There were two peaks in average incidence of the total population, 30.9/100 000 in the 20-24 age group and 66.4/100 000 in the 70-74 age group. Overall, the ratio of new to retreated cases continually rose and eventually reached 8.36:1 in 2016. The constituent ratio of smear-positive cases ranged from 35.9% to 47.8% without rising or decreasing trend (P = 0.065). CONCLUSION: The epidemic of TB in Shanghai has steadily declined during last two decades. A new strategy should be developed to rapidly reduce the incidence rate to achieve the WHO Goals in 2035.

State-Interaction Pair-Density Functional Theory Can Accurately Describe a Spiro Mixed Valence Compound.

Mixed-valence compounds with strong couplings between electronic states constitute one of the most challenging types of multireference systems for electronic structure theory. Previous work on a model mixed-valence compound, the 2,2',6,6'-tetrahydro-4 H,4' H-5,5'-spirobi[cyclopenta[ c]pyrrole] cation, showed that multireference perturbation theory (MRPT) can give a physical energy surface for the mixed-valence compound only by going to the third order or by using a scheme involving averaging orbital energies in a way specific to mixed-valence systems. In this study, we show that second-order MRPT methods (CASPT2, MS-CASPT2, and XMS-CASPT2) can give good results by calculating the Fock operator for the zeroth-order Hamiltonian using the state-averaged density matrix. We also show that state-interaction pair-density functional theory (SI-PDFT) is free from the unphysical behavior of previously tested second-order MRPT methods for this prototype mixed-valence compound near the avoided crossing. This is very encouraging because of the much lower cost in applying SI-PDFT to large or complex systems.

Excitation spectra of retinal by multiconfiguration pair-density functional theory.

Retinal is the chromophore in proteins responsible for vision. The absorption maximum of retinal is sensitive to mutations of the protein. However, it is not easy to predict the absorption spectrum of retinal accurately, and questions remain even after intensive investigation. Retinal poses a challenge for Kohn-Sham density functional theory (KS-DFT) because of the charge transfer character in its excitations, and it poses a challenge for wave function theory because the large size of the molecule makes multiconfigurational perturbation theory methods expensive. In this study, we demonstrate that multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient way to predict the vertical excitation energies of 11-Z retinal, and it reproduces the experimentally determined absorption band widths and peak positions better than complete active space second-order perturbation theory (CASPT2). The consistency between complete active space self-consistent field (CASSCF) and KS-DFT dipole moments is demonstrated to be a useful criterion in selecting the active space. We also found that the nature of the terminal groups and the conformations of retinal play a significant role in the absorption spectrum. By considering a thermal distribution of conformations, we predict an absorption spectrum of retinal that is consistent with the experimental gas-phase spectrum. The location of the absorption peak and the spectral broadening based on MC-PDFT calculations agree better with experiments than those of CASPT2.

Extended Hamiltonian molecular dynamics: semiclassical trajectories with improved maintenance of zero point energy.

It is well known that classical trajectories, even if they are initiated with zero point energy (ZPE) in each mode (trajectories initiated this way are commonly called quasiclassical trajectories), do not maintain ZPE in the final states. The energy of high-frequency modes will typically leak into low-frequency modes or relative translation of subsystems during the time evolution. This can lead to severe problems such as unphysical dissociation of a molecule, production of energetically disallowed reaction products, and unphysical product energy distributions. Here a new molecular dynamics method called extended Hamiltonian molecular dynamics (EHMD) is developed to improve the ZPE problem in classical molecular dynamics. In EHMD, two images of a trajectory are connected by one or more springs. The EHMD method is tested with the Henon-Heiles Hamiltonian in reduced and real units and with a Hamiltonian with quartic anharmonicity in real units, and the method is found to improve zero-point maintenance as intended.

Conformational and Thermodynamic Landscape of GPCR Activation from Theory and Computation.

We present a hybrid computational methodology to predict multiple energetically accessible conformations for G protein-coupled receptors (GPCRs) that might play a role in binding to ligands and different signaling partners. To our knowledge, this method, termed ActiveGEnSeMBLE, enables the first quantitative energy profile for GPCR activation that is consistent with the qualitative profile deduced from experiments. ActiveGEnSeMBLE starts with a systematic coarse grid sampling of helix tilts/rotations (∼13 trillion transmembrane-domain conformations) and selects the conformational landscape based on energy. This profile identifies multiple potential active-state energy wells, with the TM3-TM6 intracellular distance as an approximate activation coordinate. These energy wells are then sampled locally using a finer grid to find locally minimized conformation in each energy well. We validate this strategy using the inactive and active experimental structures of ß2 adrenergic receptor (hß2AR) and M2 muscarinic acetylcholine receptor. Structures of membrane-embedded hß2AR along its activation coordinate are subjected to molecular-dynamics simulations for relaxation and interaction energy analysis to generate a quantitative energy landscape for hß2AR activation. This landscape reveals several metastable states along this coordinate, indicating that for hß2AR, the agonist alone is not enough to stabilize the active state and that the G protein is necessary, consistent with experimental observations. The method's application to somatostatin receptor SSTR5 (no experimental structure available) shows that to predict an active conformation it is better to start from an inactive structure template based on a close homolog than to start from an active template based on a distant homolog. The energy landscape for hSSTR5 activation is consistent with hß2AR in the role of the G protein. These results demonstrate the utility of the ActiveGEnSeMBLE method for predicting multiple conformations along the pathways for activating GPCRs and the corresponding energy landscapes, thereby providing detailed structural insights into the initial molecular events of GPCR function that are not easily accessible by experiments.

Automated Active Space Selection with Dipole Moments.

Multireference calculations can provide accurate information of systems with strong correlation, which have increasing importance in the development of new molecules and materials. However, selecting a suitable active space for multireference calculations is nontrivial, and the selection of an unsuitable active space can sometimes lead to results that are not physically meaningful. Active space selection often requires significant human input, and the selection that leads to reasonable results often goes beyond chemical intuition. In this work, we have developed and evaluated two protocols for automated selection of the active space for multireference calculations based on a simple physical observable, the dipole moment, for molecules with nonzero ground-state dipole moments. One protocol is based on the ground-state dipole moment, and the other is based on the excited-state dipole moments. To evaluate the protocols, we constructed a dataset of 1275 active spaces from 25 molecules, each with 51 active space sizes considered, and have mapped out the relationship between the active space, dipole moments, and vertical excitation energies. We have demonstrated that, within this dataset, our protocols allow one to choose among a number of accessible active spaces one that is likely to give reasonable vertical excitation energies, especially for the first three excitations, with no parameters manually decided by the user. We show that, with large active spaces removed from consideration, the accuracy is similar and the time-to-solution can be reduced by more than 10 fold. We also show that the protocols can be applied to potential energy surface scans and determining the spin states of transition metal oxides.

Investigation of the pharmacological treatment patterns of Chinese patients with major depressive disorder under real-world settings using multi-channel sequence analysis.

Background: Despite many treatment guidelines available now, the treatment patterns of major depressive disorder (MDD) in China haven't been well-understood due to complexity and diversity. Aim: To describe pharmacological treatment patterns of MDD patients in real-world settings using electronic health records from a major psychiatric hospital in China. Methods: MDD patients (18-65 years, ICD-10: F32.x, F33.x) newly initiated single antidepressant (AD) in 2015 were enrolled, the date of first AD prescription during the study period was defined as index date, and eligible patients were followed up to 1 year. Treatment patterns were revealed and analyzed using multi-channel sequence analysis (MCSA), considering patients' chronological sequences (in days) of AD prescription, cumulative treatment step(s), and polypharmacy usage during the follow-up. Results: This study (n = 5,003) identified four types of MDD treatment patterns. The first type (1-time treatment) represents the largest proportion of patients (73.6%, n = 3,686), followed by the second type (6-month consistent treatment) and third type (long-term, consistent treatment) collectively accounted for 20.6% (n = 1,031) of patients, by contrast the last type (long-term, inconsistent treatment) made up the rest 5.7% (n = 286) of patients while exhibiting the most complicated treatments patterns. The choice of AD was dominated by selective serotonin reuptake inhibitors (SSRIs), while treatment duration spent in polypharmacy spanned at 2.8%, 16.4%, 2.0%, and 36.5% over the four types, respectively. Conclusion: Treatment patterns reflecting real-world pharmacological treatment practices of MDD in China were revealed using MCSA. The observed discrepancies between real-world practice and treatment guidelines provided additional insights in improving the clinical management of MDD.

CFD-based pesticide selection for a nozzle used in a six-rotor UAV in hover mode for tea spraying.

BACKGROUND: A key challenge for unmanned aerial vehicle (UAV) spraying sometimes used in tea plantations is the downwash flow structure there stronger than in crops. In addition, the UAV spray is affected by the relationship between the nozzle design and the pesticide. However, there is little current research on this aspect. As a preliminary step this study focuses on the most appropriate pesticide for a designated nozzle in a six-rotor UAV according to the nozzle-pesticide relationship using a three-dimensional computational fluid dynamics model. This model considers the downwash flow structure effect and nozzle spray performance in hover. Nozzle FVP110-02, widely used in six-rotor UAVs, is used as a representative nozzle and bifenthrin and tea saponin water, commonly used in tea plantations, are used as the pesticides. RESULTS: The downwash flow structure of the six-rotor UAV in hover was conveniently controlled by the flight height and rotational speed, thereby causing the turbulence to be more stable. For nozzle FVP110-02, bifenthrin was more appropriate than tea saponin water at the same concentration, whilst bifenthrin and tea saponin water at a concentration of 1:1000 showed the best performance under identical working conditions. CONCLUSION: The numerical model developed here was shown to be effective for investigating the relationship between nozzle and pesticide. Our findings will help to not only improve UAV spraying for tea cultivation but also provide guidelines for pesticide selection in crops. Further work will address the comparison of the rigorous qualification of the numerical simulations with the measurements by the field test. © 2023 Society of Chemical Industry.

A mechanistic study on the cellular uptake, intracellular trafficking, and antisense gene regulation of bottlebrush polymer-conjugated oligonucleotides.

We have developed a non-cationic transfection vector in the form of bottlebrush polymer-antisense oligonucleotide (ASO) conjugates. Termed pacDNA (polymer-assisted compaction of DNA), these agents show improved biopharmaceutical characteristics and antisense potency in vivo while suppressing non-antisense side effects. Nonetheless, there still is a lack of the mechanistic understanding of the cellular uptake, subcellular trafficking, and gene knockdown with pacDNA. Here, we show that the pacDNA enters human non-small cell lung cancer cells (NCI-H358) predominantly by scavenger receptor-mediated endocytosis and macropinocytosis and trafficks via the endolysosomal pathway within the cell. The pacDNA significantly reduces a target gene expression (KRAS) in the protein level but not in the mRNA level, despite that the transfection of certain free ASOs causes ribonuclease H1 (RNase H)-dependent degradation of KRAS mRNA. In addition, the antisense activity of pacDNA is independent of ASO chemical modification, suggesting that the pacDNA always functions as a steric blocker.

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry.

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments span a wide range of topics in computational chemistry and are presented in thematic sections: electronic structure theory, electronic spectroscopy simulations, analytic gradients and molecular structure optimizations, ab initio molecular dynamics, and other new features. This report offers an overview of the chemical phenomena and processes OpenMolcas can address, while showing that OpenMolcas is an attractive platform for state-of-the-art atomistic computer simulations.

One-year incidence rate of Treatment Resistant Depression (TRD) and treatment characteristics in China.

BACKGROUND: Little is known about the characteristics of Treatment-Resistant Depression (TRD) in China. In previous studies various identification approaches have led to a wide range of results, and it is unclear how Chinese patients compare to those in other studies. METHODS: This is a retrospective cohort study using electronic health records (EHR) from two major psychiatric hospitals in China. Adult major depressive disorder (MDD) patients who initiated pharmaceutical treatment during 2010-2018 were enrolled and follow-up was 1 year. TRD was primarily identified by consensus definition of two failures of adequate (≥4 weeks) regimens. Alternative regimens of 2-weeks and 6-weeks duration, and a data-driven definition were also applied. RESULTS: In the two hospitals, 12,257 (mean age: 40.8y, 63.6% female) and 8314 (mean age: 42.4y, 68.4% female) eligible patients were included. The 1-year incidence rate of TRD was estimated to be 5.2%-7.7% using the primary definition. TRD patients had mean treatment duration of 302.5 days and 285.7 days; had 3.6 and 3.7 treatment steps on average; 94.0% and 72.6% were prescribed polypharmacy regimens, which were all marginally greater than that of non-TRD patients. Alternative definitions resulted in a wide range of incidence estimates (0.5%-20.0%). LIMITATIONS: Medications were assumed to be consumed as prescribed and lack of rating scales from EHRs may limit our TRD identification. CONCLUSIONS: The incidence of TRD among Chinese MDD patients was comparable to other countries under similar settings and more complex treatment characteristics were observed among TRD patients. Alternative TRD definitions revealed the need for better treatment management in practices.

Concordance of the treatment patterns for major depressive disorders between the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm and real-world practice in China.

Background: Antidepressant (AD) algorithm is an important tool to support treatment decision-making and improve management of major depressive disorder (MDD). However, little is known about its concordance with real-world practice. This study aimed to assess the concordance between the longitudinal treatment patterns and AD algorithm recommended by a clinical practice guideline in China. Methods: Data were obtained from the electronic medical records of Shanghai Mental Health Center (SMHC), one of the largest mental health institutions in China. We examined the concordance between clinical practice and the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm among a cohort composed of 19,955 MDD patients. The longitudinal characteristics of treatment regimen and duration were described to identify the specific inconsistencies. Demographics and health utilizations of the algorithm-concordant and -discordant subgroups with optimized treatment were measured separately. Results: The overall proportion of algorithm-concordant treatment significantly increased from 84.45% to 86.03% during the year of 2015-2017. Among the patients who received recommended first-line drugs with subsequent optimized treatment (n = 2977), the concordance proportion was 27.24%. Mirtazapine and trazodone were the most used drugs for adjunctive strategy. Inadequate or extended duration before optimized treatment are common inconsistency. The median length of follow-up for algorithm-concordant (n = 811) and algorithm-discordant patients (n = 2166) were 153 days (Q1-Q3 = 79-328) and 368 days (Q1-Q3 = 181-577) respectively, and the average number of clinical visits per person-year was 13.07 and 13.08 respectively. Conclusion: Gap existed between clinical practice and AD algorithm. Improved access to evidence-based treatment is required, especially for optimized strategies during outpatient follow-up.

Highly efficient and diastereoselective gold(I)-catalyzed synthesis of tertiary amines from secondary amines and alkynes: substrate scope and mechanistic insights.

An efficient method for the synthesis of tertiary amines through a gold(I)-catalyzed tandem reaction of alkynes with secondary amines has been developed. In the presence of ethyl Hantzsch ester and [{(tBu)(2)(o-biphenyl)P}AuCl]/AgBF(4) (2 mol %), a variety of secondary amines bearing electron-deficient and electron-rich substituents and a wide range of alkynes, including terminal and internal aryl alkynes, aliphatic alkynes, and electron-deficient alkynes, underwent a tandem reaction to afford the corresponding tertiary amines in up to 99 % yield. For indolines bearing a preexisting chiral center, their reactions with alkynes in the presence of ethyl Hantzsch ester catalyzed by [{(tBu)(2)(o-biphenyl)P}AuCl]/AgBF(4) (2 mol %) afforded tertiary amines in excellent yields and with good to excellent diastereoselectivity. All of these organic transformations can be conducted as a one-pot reaction from simple and readily available starting materials without the need of isolation of air/moisture-sensitive enamine intermediates, and under mild reaction conditions (mostly room temperature and mild reducing agents). Mechanistic studies by NMR spectroscopy, ESI-MS, isotope labeling studies, and DFT calculations on this gold(I)-catalyzed tandem reaction reveal that the first step involving a monomeric cationic gold(I)-alkyne intermediate is more likely than a gold(I)-amine intermediate, a three-coordinate gold(I) intermediate, or a dinuclear gold(I)-alkyne intermediate. These studies also support the proposed reaction pathway, which involves a gold(I)-coordinated enamine complex as a key intermediate for the subsequent transfer hydrogenation with a hydride source, and reveal the intrinsic stereospecific nature of these transformations observed in the experiments.

Electronic structures of Group 9 metallocorroles with axial ammines.

The electronic structures of metallocorroles (tpfc)M(NH(3))(2) and (tfc)M(NH(3))(2) (tpfc is the trianion of 5,10,15-(tris)pentafluorophenylcorrole, tfc is the trianion of 5,10,15-trifluorocorrole, and M = Co, Rh, Ir) have been computed using first principles quantum mechanics [B3LYP flavor of Density Functional Theory (DFT) with Poisson-Boltzmann continuum solvation]. The geometry was optimized for both the neutral systems (formal M(III) oxidation state) and the one-electron oxidized systems (formally M(IV)). As expected, the M(III) systems have a closed shell d(6) configuration; for all three metals, the one-electron oxidation was calculated to occur from a ligand-based orbital (highest occupied molecular orbital (HOMO) of B(1) symmetry). The ground state of the formal M(IV) system has M(III)-Cπ character, indicating that the metal remains d(6), with the hole in the corrole π system. As a result the calculated M(IV/III) reduction potentials are quite similar (0.64, 0.67, and 0.56 V vs SCE for M = Ir, Rh and Co, respectively), whereas the differences would have been large for purely metal-based oxidations. Vertically excited states with substantial metal character are well separated from the ground state in one-electron-oxidized cobalt (0.27 eV) and rhodium (0.24 eV) corroles, but become closer in energy in the iridium (0.15 eV) analogues. The exact splittings depend on the chosen functional and basis set combination and vary by ~0.1 eV.

Machine learning dielectric screening for the simulation of excited state properties of molecules and materials.

Accurate and efficient calculations of absorption spectra of molecules and materials are essential for the understanding and rational design of broad classes of systems. Solving the Bethe-Salpeter equation (BSE) for electron-hole pairs usually yields accurate predictions of absorption spectra, but it is computationally expensive, especially if thermal averages of spectra computed for multiple configurations are required. We present a method based on machine learning to evaluate a key quantity entering the definition of absorption spectra: the dielectric screening. We show that our approach yields a model for the screening that is transferable between multiple configurations sampled during first principles molecular dynamics simulations; hence it leads to a substantial improvement in the efficiency of calculations of finite temperature spectra. We obtained computational gains of one to two orders of magnitude for systems with 50 to 500 atoms, including liquids, solids, nanostructures, and solid/liquid interfaces. Importantly, the models of dielectric screening derived here may be used not only in the solution of the BSE but also in developing functionals for time-dependent density functional theory (TDDFT) calculations of homogeneous and heterogeneous systems. Overall, our work provides a strategy to combine machine learning with electronic structure calculations to accelerate first principles simulations of excited-state properties.

The Dissolution Rate of CaCO3 in the Ocean.

The dissolution of CaCO3 minerals in the ocean is a fundamental part of the marine alkalinity and carbon cycles. While there have been decades of work aimed at deriving the relationship between dissolution rate and mineral saturation state (a so-called rate law), no real consensus has been reached. There are disagreements between laboratory- and field-based studies and differences in rates for inorganic and biogenic materials. Rates based on measurements on suspended particles do not always agree with rates inferred from measurements made near the sediment-water interface of the actual ocean. By contrast, the freshwater dissolution rate of calcite has been well described by bulk rate measurements from a number of different laboratories, fit by basic kinetic theory, and well studied by atomic force microscopy and vertical scanning interferometry to document the processes at the atomic scale. In this review, we try to better unify our understanding of carbonate dissolution in the ocean via a relatively new, highly sensitive method we have developed combined with a theoretical framework guided by the success of the freshwater studies. We show that empirical curve fits of seawater data as a function of saturation state do not agree, largely because the curvature is itself a function of the thermodynamics. Instead, we show that models that consider both surface energetic theory and the complicated speciation of seawater and calcite surfaces in seawater are able to explain most of the most recent data.This new framework can also explain features of the historical data that have not been previously explained. The existence of a kink in the relationship between rate and saturation state, reflecting a change in dissolution mechanism, may be playing an important role in accelerating CaCO3 dissolution in key sedimentary environments.