Nuclear Quantum Effects on the Electronic Structure of Water and Ice.

The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of the hydrogen atoms. Despite numerous previous studies, a comprehensive understanding of the nuclear quantum effects (NQEs) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.

Nonlinear Effects of Hydrophobic Confinement on the Electronic Structure and Dielectric Response of Water.

Fundamental studies of the dielectrics of confined water are critical to understand the ion transport across biological and synthetic nanochannels. The relevance of these fundamental studies, however, surmounts the difficulty of probing water's dielectric constant as a function of a fine variation in confinement. In this work, we explore the computational efficiency of machine learning potentials to derive the confinement effects on the dielectric constant, polarization, and dipole moment of water. Our simulations predict an enhancement of the axial dielectric constant of water under extreme confinement, arising from either the formation of ferroelectric structures of ordered water or larger dipole fluctuations facilitated by the disruption of water's H-bond network. Our study highlights the impact of hydrophobic nanoconfinement on the dielectric constant and on the ionic and electronic structure of water molecules, pointing to the importance of geometric flexibility and electronic polarizability to properly model confinement effects on water.

Confinement Effects on Proton Transfer in TiO2 Nanopores from Machine Learning Potential Molecular Dynamics Simulations.

Improved understanding of proton transfer in nanopores is critical for a wide range of emerging applications, yet experimentally probing mechanisms and energetics of this process remains a significant challenge. To help reveal details of this process, we developed and applied a machine learning potential derived from first-principles calculations to examine water reactivity and proton transfer in TiO2 slit-pores. We find that confinement of water within pores smaller than 0.5 nm imposes strong and complex effects on water reactivity and proton transfer. Although the proton transfer mechanism is similar to that at a TiO2 interface with bulk water, confinement reduces the activation energy of this process, leading to more frequent proton transfer events. This enhanced proton transfer stems from the contraction of oxygen-oxygen distances dictated by the interplay between confinement and hydrophilic interactions. Our simulations also highlight the importance of the surface topology, where faster proton transport is found in the direction where a unique arrangement of surface oxygens enables the formation of an ordered water chain. In a broader context, our study demonstrates that proton transfer in hydrophilic nanopores can be enhanced by controlling pore size, surface chemistry, and topology.

Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia.

Exposure to particulate matter (PM) pollution is a significant health risk, driving the search for innovative metrics that more accurately reflect the potential harm to human health. Among these, oxidative potential (OP) has emerged as a promising health-based metric, yet its application and relevance across different environments remain to be further explored. This study, set in two high-altitude Bolivian cities, aims to identify the most significant sources of PM-induced oxidation in the lungs and assess the utility of OP in assessing PM health impacts. Utilizing two distinct assays, OPDTT and OPDCFH, we measured the OP of PM samples, while also examining the associations between PM mass, OP, and black carbon (BC) concentrations with hospital visits for acute respiratory infections (ARI) and pneumonia over a range of exposure lags (0-2 weeks) using a Poisson regression model adjusted for meteorological conditions. The analysis also leveraged Positive Matrix Factorization (PMF) to link these health outcomes to specific PM sources, building on a prior source apportionment study utilizing the same dataset. Our findings highlight anthropogenic combustion, particularly from traffic and biomass burning, as the primary contributors to OP in these urban sites. Significant correlations were observed between both OPDTT and PM2.5 concentration exposure and ARI hospital visits, alongside a notable association with pneumonia cases and OPDTT levels. Furthermore, PMF analysis demonstrated a clear link between traffic-related pollution and increased hospital admissions for respiratory issues, affirming the health impact of these sources. These results underscore the potential of OPDTT as a valuable metric for assessing the health risks associated with acute PM exposure, showcasing its broader application in environmental health studies.

Leptodelphax maculigera (Hemiptera: Delphacidae) harbors the corn stunt complex pathogens.

The African planthopper Leptodelphax maculigera (Hemiptera: Delphacidae) has been recently reported in many places in Brazil in association with maize. Its occurrence in maize production fields in Brazil has brought concerns to the corn production chain regarding the possibility of this planthopper to be a vector for maize bushy stunt phytoplasma (MBSP), corn stunt spiroplasma (Spiroplasma kunkelii), maize rayado fino virus (MRFV) and maize striate mosaic virus (MSMV). The phytoplasma and spiroplasma, that are bacteria belonging to the Class Mollicutes, and the two viruses are associated with the corn stunt disease complex. Given the presence of the African planthopper species and the corn stunt disease complex in Brazil, we further investigated the abundance of this planthopper species in Santa Catarina state, Brazil, and whether the planthopper can carry the four pathogens. We inspected 12 maize production fields in different municipalities in the state for 20 weeks, using two yellow sticky traps for each maize field. The sticky traps were replaced weekly. A total of 130 specimens of L. maculigera were captured, with a great discrepancy in quantity among locations and weeks. We detected the mollicute MBSP, and the viruses MRFV and MSMV in L. maculigera, whereas S. kunkelii was absent in the assessed African planthopper samples. The molecular detection of the phytoplasma and the viruses in field-collected African planthoppers is a strong evidence that this insect species has the ability of acquiring those pathogens through feeding from phloem of diseased maize plants. Nonetheless, transmission capacity needs to be experimentally proven to assert L. maculigera as a vector for the corn stunting pathogens.

The essential oil of Melaleuca alternifolia incorporated into hydrogel induces antimicrobial and anti-inflammatory effects on infected wounds by Staphylococcus aureus.

Staphylococcus aureus is one of the most common bacterial isolates found in wounds. Thus, innovative dressings, such as hydrogels, are interesting vehicles for incorporating bioactive compounds like those from Melaleuca alternifolia essential oil (MaEO). In this study, we evaluated the antimicrobial and anti-inflammatory potential of MaEO incorporated into an alginate and chitosan hydrogel for treating wounds infected by S. aureus. The hydrogel incorporated with MaEO 1% (HMa 1%) was homogeneous with a bright pale-yellow color and the characteristic smell of Melaleuca. The incorporation of MaEO 1% does not affect the stability of the hydrogel, which was stable up to 90 days of storage. The Scanning electron microscopy analysis revealed that hydrogels showed irregular surfaces and interconnected porous structures with accumulations of oil crystals distributed throughout the formulation. HMa 1% has a high moisture content (95.1%) and can absorb simulated wound fluid. Regarding the antimicrobial effects, HMa 1% reduced the growth of S. aureus ATCC 6538 in both in vitro conditions and in an ex vivo model of wounds using porcine skin. In addition, the dairy topical treatment of murine skin lesions with HMa 1% induced a significant reduction of the wound area, inflammation score, and bacterial load, as well as tissue re-epithelialization and modulation of inflammatory mediators. Therefore, hydrogel incorporated with MaEO 1% has excellent potential to be used in the pharmacotherapy of infected wounds.

Proteomic Analysis of a Rat Streptozotocin Model Shows Dysregulated Biological Pathways Implicated in Alzheimer's Disease.

Alzheimer's Disease (AD) is an age-related neurodegenerative disorder characterized by progressive memory loss and cognitive impairment, affecting 35 million individuals worldwide. Intracerebroventricular (ICV) injection of low to moderate doses of streptozotocin (STZ) in adult male Wistar rats can reproduce classical physiopathological hallmarks of AD. This biological model is known as ICV-STZ. Most studies are focused on the description of behavioral and morphological aspects of the ICV-STZ model. However, knowledge regarding the molecular aspects of the ICV-STZ model is still incipient. Therefore, this work is a first attempt to provide a wide proteome description of the ICV-STZ model based on mass spectrometry (MS). To achieve that, samples from the pre-frontal cortex (PFC) and hippocampus (HPC) of the ICV-STZ model and control (wild-type) were used. Differential protein abundance, pathway, and network analysis were performed based on the protein identification and quantification of the samples. Our analysis revealed dysregulated biological pathways implicated in the early stages of late-onset Alzheimer's disease (LOAD), based on differentially abundant proteins (DAPs). Some of these DAPs had their mRNA expression further investigated through qRT-PCR. Our results shed light on the AD onset and demonstrate the ICV-STZ as a valid model for LOAD proteome description.

Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA-2 data.

The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpreted using PM2.5 data when available. Columnar water vapor derived from ozone soundings at Quito is used to compare against AERONET PW. MERRA-2 data are used to complement analyses. Urban pollution and biomass burning smoke (BBS) dominate the regional aerosol composition. AOD and PM2.5 yearly cycles for coincident measurements correlate linearly at Medellin and Quito. The Andes cordillera's orientation and elevation funnel or block BBS transport into valleys or highlands during the two fire seasons that systematically impact South America. The February-March season north of Colombia and the Colombian-Venezuelan border directly impacts Medellin. Possibly, the March aerosol signal over Quito has a long-range transport component. At Huancayo and La Paz, AOD increases in September due to the influence of BBS in the Amazon. AERONET PW and sounding data correlate linearly but a dry bias with respect to soundings was identified in AERONET. PW and rainfall progressively decrease from north to south due to increasing altitude. This regional diagnosis is an underlying basis to evaluate future changes in aerosol and PW given prevailing conditions of rapidly changing atmospheric composition.

Castor (Ricinus communis L.) differential cell cycle and metabolism reactivation, germinability, and seedling performance under NaCl and PEG osmoticum: Stress tolerance related to genotype-preestablished superoxide dismutase activity.

Castor (Ricinus communis) is a relevant industrial oilseed feedstock for many industrial applications, being globally mainly cultivated by smallholder farmers in semiarid areas, where abiotic stresses predominate. Therefore, susceptible to generating reactive oxygen species (ROS) and subsequent oxidative stress, compromising cell metabolism upon seed imbibition and germination, seedling and crop establishment, and yield. The present study evaluated the consequences of water restriction by Polyethylene glycol (PEG) and Sodium chloride (NaCl) on cell cycle and metabolism reactivation on germinability, seedling growth, and vigor parameters in 2 commercial castor genotypes (Nordestina and Paraguaçu). PEG water restriction inhibited germination completely at -0.23 MPa or higher, presumably due to reduced oxygen availability. The restrictive effects of NaCl saline stress on germination were observed only from -0.46 MPa onwards, affecting dry mass accumulation and the production of normal seedlings. In general, superoxide dismutase (SOD) activity increased in NaCl -0.23 MPa, whereas its modulation during the onset of imbibition (24h) seemed to depend on its initial levels in dry seeds in a genotype-specific manner, therefore, resulting in the higher stress tolerance of Nordestina compared to Paraguaçu. Overall, results show that Castor germination and seedling development are more sensitive to the restrictive effects of PEG than NaCl at similar osmotic potentials, contributing to a better understanding of the responses to water restriction stresses by different Castor genotypes. Ultimately, SOD may constitute a potential marker for characterizing castor genotypes in stressful situations during germination, early seedling, and crop establishment, and a target for breeding for Castor-improved stress tolerance.

Oxidized organic molecules in the tropical free troposphere over Amazonia.

New particle formation (NPF) in the tropical free troposphere (FT) is a globally important source of cloud condensation nuclei, affecting cloud properties and climate. Oxidized organic molecules (OOMs) produced from biogenic volatile organic compounds are believed to contribute to aerosol formation in the tropical FT, but without direct chemical observations. We performed in situ molecular-level OOMs measurements at the Bolivian station Chacaltaya at 5240 m above sea level, on the western edge of Amazonia. For the first time, we demonstrate the presence of OOMs, mainly with 4-5 carbon atoms, in both gas-phase and particle-phase (in terms of mass contribution) measurements in tropical FT air from Amazonia. These observations, combined with air mass history analyses, indicate that the observed OOMs are linked to isoprene emitted from the rainforests hundreds of kilometers away. Based on particle-phase measurements, we find that these compounds can contribute to NPF, at least the growth of newly formed nanoparticles, in the tropical FT on a continental scale. Thus, our study is a fundamental and significant step in understanding the aerosol formation process in the tropical FT.

Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics.

The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H2O) cells. The reversible work to separate the hydroxide and hydronium to a distance [Formula: see text] is found to converge for simulation cells containing more than 500 H2O, and a distance of [Formula: see text] 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.

Are patient volume and care level in teaching hospitals variables affecting clinical outcomes in adult intensive care units?

Teixeira et al. showed that patients admitted to the intensive care unit of a teaching hospital in a non-metropolitan region needed more support, had worse prognostic indices, and had a higher nursing workload in the first 24 hours of admission. In addition, worse outcomes, including mortality, need for dialysis, pressure injury, infection, prolonged mechanical ventilation, and prolonged hospital stay, were observed in the teaching hospital. Worse outcomes were more prevalent in the teaching hospital. Understanding the importance of teaching hospitals to implement well-established care protocols is critical. OBJECTIVE: To compare the clinical outcomes of patients admitted to the intensive care unit of teaching (HI) and nonteaching (without an academic affiliation; H2) hospitals. METHODS: In this prospective cohort study, adult patients hospitalized between August 2018 and July 2019, with a minimum length of stay of 24 hours in the intensive care unit, were included. Patients with no essential information in their medical records to evaluate the study outcomes were excluded. Resuslts: Overall, 219 patients participated in this study. The clinical and demographic characteristics of patients in H1 and H2 were similar. The most prevalent clinical outcomes were death, need for dialysis, pressure injury, length of hospital stay, mechanical ventilation >48 hours, and infection, all of which were more prevalent in the teaching hospital. CONCLUSION: Worse outcomes were more prevalent in the teaching hospital. There was no difference between the institutions concerning the survival rate of patients as a function of length of hospital stay; however, a difference was observed in intensive care unit admissions.

Elucidating the water-anatase TiO2(101) interface structure using infrared signatures and molecular dynamics.

The structure and dynamics of water on solid surfaces critically affect the chemistry of materials in ambient and aqueous environments. Here, we investigate the hydrogen bonding network of water adsorbed on the majority (101) surface of anatase TiO2, a widely used photocatalyst, using polarization- and azimuth-resolved infrared spectroscopy combined with neural network potential molecular dynamics simulations. Our results show that one monolayer of water saturates the undercoordinated titanium (Ti5c) sites, forming one-dimensional chains of molecule hydrogen bonded to surface undercoordinated bridging oxygen (O2c) atoms. As the coverage increases, water adsorption on O2c sites leads to significant restructuring of the water monolayer and the formation of a two-dimensional hydrogen bond network characterized by tightly bound pairs of water molecules on adjacent Ti5c and O2c sites. This structural motif likely persists at ambient conditions, influencing the reactions occurring there. The results reported here provide critical details of the structure of the water-anatase (101) interface that were previously hypothesized but unconfirmed experimentally.

Enhanced hydrogen bonding via epoxide-functionalization restricts mobility in poly(ethylenimine) for CO2 capture.

Free energy sampling, deep potential molecular dynamics, and characterizations provide insights into the impact of epoxide-functionalization on the hydrogen bonding and mobility of poly(ethylenimine), a promising CO2 sorbent. These findings rationalize the anti-degradation effects of epoxide functionalization and open up new avenues for designing more durable CO2 sorbents.

Total and regional body composition are related with aerobic fitness performance in elite futsal players.

Body composition (i.e., fat and lean mass profile) has been related to aerobic performance, an essential capacity for futsal athletes. The present study aimed to verify the relationship between total and regional body composition (percentage of fat and lean mass) with aerobic performance in elite futsal players. Male professional futsal athletes (n = 44) from two Brazilian National Futsal League teams and athletes representing the National team participated in this study. Body composition was evaluated using DXA (Dual-Energy X-ray Absorptiometry) and aerobic fitness by ergospirometry. There was a negative (p < 0.05) correlation between maximum oxygen uptake and maximal velocity reached with total body (r = -0.53; r = -0.58), trunk (r = -0.52; r = -0.56) and lower-limb (r = -0.46; r = -0.55) fat mass percentage. Lower-limb lean mass percentage had a positive (p < 0.05) correlation with maximum oxygen uptake (r = 0.46) and maximal velocity (r = 0.55). In conclusion, total and regional body composition present a relationship with aerobic performance in professional futsal players.

Probing Confinement Effects on the Infrared Spectra of Water with Deep Potential Molecular Dynamics Simulations.

The hydrogen-bond network of confined water is expected to deviate from that of the bulk liquid, yet probing these deviations remains a significant challenge. In this work, we combine large-scale molecular dynamics simulations with machine learning potential derived from first-principles calculations to examine the hydrogen bonding of water confined in carbon nanotubes (CNTs). We computed and compared the infrared spectrum (IR) of confined water to existing experiments to elucidate confinement effects. For CNTs with diameters >1.2 nm, we find that confinement imposes a monotonic effect on the hydrogen-bond network and on the IR spectrum of water. In contrast, confinement below 1.2 nm CNT diameter affects the water structure in a complex fashion, leading to a strong directional dependence of hydrogen bonding that varies nonlinearly with the CNT diameter. When integrated with existing IR measurements, our simulations provide a new interpretation for the IR spectrum of water confined in CNTs, pointing to previously unreported aspects of hydrogen bonding in this system. This work also offers a general platform for simulating water in CNTs with quantum accuracy on time and length scales beyond the reach of conventional first-principles approaches.

High-Throughput Condensed-Phase Hybrid Density Functional Theory for Large-Scale Finite-Gap Systems: The SeA Approach.

High-throughput electronic structure calculations (often performed using density functional theory (DFT)) play a central role in screening existing and novel materials, sampling potential energy surfaces, and generating data for machine learning applications. By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal DFT and furnish a more accurate description of the underlying electronic structure, albeit at a computational cost that often prohibits such high-throughput applications. To address this challenge, we have constructed a robust, accurate, and computationally efficient framework for high-throughput condensed-phase hybrid DFT and implemented this approach in the PWSCF module of Quantum ESPRESSO (QE). The resulting SeA approach (SeA = SCDM + exx + ACE) combines and seamlessly integrates: (i) the selected columns of the density matrix method (SCDM, a robust noniterative orbital localization scheme that sidesteps system-dependent optimization protocols), (ii) a recently extended version of exx (a black-box linear-scaling EXX algorithm that exploits sparsity between localized orbitals in real space when evaluating the action of the standard/full-rank V^xx operator), and (iii) adaptively compressed exchange (ACE, a low-rank V^xx approximation). In doing so, SeA harnesses three levels of computational savings: pair selection and domain truncation from SCDM + exx (which only considers spatially overlapping orbitals on orbital-pair-specific and system-size-independent domains) and low-rank V^xx approximation from ACE (which reduces the number of calls to SCDM + exx during the self-consistent field (SCF) procedure). Across a diverse set of 200 nonequilibrium (H2O)64 configurations (with densities spanning 0.4-1.7 g/cm3), SeA provides a 1-2 order-of-magnitude speedup in the overall time-to-solution, i.e., ≈8-26× compared to the convolution-based PWSCF(ACE) implementation in QE and ≈78-247× compared to the conventional PWSCF(Full) approach, and yields energies, ionic forces, and other properties with high fidelity. As a proof-of-principle high-throughput application, we trained a deep neural network (DNN) potential for ambient liquid water at the hybrid DFT level using SeA via an actively learned data set with ≈8,700 (H2O)64 configurations. Using an out-of-sample set of (H2O)512 configurations (at nonambient conditions), we confirmed the accuracy of this SeA-trained potential and showcased the capabilities of SeA by computing the ground-truth ionic forces in this challenging system containing >1,500 atoms.

Mechanistic Insights on Permeation of Water over Iron Cations in Nanoporous Silicon Oxide Films for Selective H2 and O2 Evolution.

Electrocatalysts encapsulated by an ultrathin and semipermeable oxide layer offer a promising avenue for efficient, selective, and cost-effective production of hydrogen through photoelectrochemical water splitting. This architecture is especially attractive for Z-scheme water splitting, for which a nanoporous oxide film can be leveraged to mitigate undesired, yet kinetically facile, reactions involving redox shuttles, such as aqueous iron cations, by limiting transport of these species to catalytically active sites. In this work, molecular dynamics simulations were combined with electrochemical measurements to provide a mechanistic understanding of permeation of water and Fe(III)/Fe(II) redox shuttles through nanoporous SiO2 films. It is shown that even for SiO2 pores with a width as small as 0.8 nm, water does not experience any energy barrier for permeating into the pores due to a favorable interaction with hydrophilic silanol groups on the oxide surface. In contrast, permeation of Fe(III) and Fe(II) into microporous SiO2 pores is limited due to high energy barriers, which stem from a combination of distortion and dehydration of the second and third ion solvation shells. Our simulations and experimental results show that SiO2 coatings can effectively mitigate undesired Fe(III)/Fe(II) redox reactions at underlying electrodes by attenuating permeation of iron cations, while allowing water to permeate and thus participate in water splitting reactions. In a broader context, our study demonstrates that selectivity of solvated cations can be manipulated by controlling the pore size and surface chemistry of oxide films.

Melatonin reduces ß-amyloid accumulation and improves short-term memory in streptozotocin-induced sporadic Alzheimer's disease model.

Melatonin is a hormone secreted by the pineal gland, it can be associated with circadian rhythms, aging and neuroprotection. Melatonin levels are decreased in sporadic Alzheimer's disease (sAD) patients, which suggests a relationship between the melatonergic system and sAD. Melatonin may reduce inflammation, oxidative stress, TAU protein hyperphosphorylation, and the formation of ß-amyloid (Aß) aggregates. Therefore, the objective of this work was to investigate the impact of treatment with 10 mg/kg of melatonin (i.p) in the animal model of sAD induced by the intracerebroventricular (ICV) infusion of 3 mg/kg of streptozotocin (STZ). ICV-STZ causes changes in the brain of rats similar to those found in patients with sAD. These changes include; progressive memory decline, the formation of neurofibrillary tangles, senile plaques, disturbances in glucose metabolism, insulin resistance and even reactive astrogliosis characterized by the upregulation of glucose levels and glial fibrillary acidic protein (GFAP). The results show that ICV-STZ caused short-term spatial memory impairment in rats after 30 days of STZ infusion without locomotor impairment which was evaluated on day 27 post-injury. Furthermore, we observed that a prolonged 30-day treatment with melatonin can improve the cognitive impairment of animals in the Y-maze test, but not in the object location test. Finally, we demonstrated that animals receiving ICV-STZ have high levels of Aß and GFAP in the hippocampus and that treatment with melatonin reduces Aß levels but does not reduce GFAP levels, concluding that melatonin may be useful to control the progression of amyloid pathology in the brain.

Water dissociation at the water-rutile TiO2(110) interface from ab initio-based deep neural network simulations.

The interaction of water with TiO2 surfaces is of crucial importance in various scientific fields and applications, from photocatalysis for hydrogen production and the photooxidation of organic pollutants to self-cleaning surfaces and bio-medical devices. In particular, the equilibrium fraction of water dissociation at the TiO2-water interface has a critical role in the surface chemistry of TiO2, but is difficult to determine both experimentally and computationally. Among TiO2 surfaces, rutile TiO2(110) is of special interest as the most abundant surface of TiO2's stable rutile phase. While surface-science studies have provided detailed information on the interaction of rutile TiO2(110) with gas-phase water, much less is known about the TiO2(110)-water interface, which is more relevant to many applications. In this work, we characterize the structure of the aqueous TiO2(110) interface using nanosecond timescale molecular dynamics simulations with ab initio-based deep neural network potentials that accurately describe water/TiO2(110) interactions over a wide range of water coverages. Simulations on TiO2(110) slab models of increasing thickness provide insight into the dynamic equilibrium between molecular and dissociated adsorbed water at the interface and allow us to obtain a reliable estimate of the equilibrium fraction of water dissociation. We find a dissociation fraction of 22 ± 6% with an associated average hydroxyl lifetime of 7.6 ± 1.8 ns. These quantities are both much larger than corresponding estimates for the aqueous anatase TiO2(101) interface, consistent with the higher water photooxidation activity that is observed for rutile relative to anatase.