Encoder-decoder convolutional neural network for simple CT segmentation of COVID-19 infected lungs.

This work presents the application of an Encoder-Decoder convolutional neural network (ED-CNN) model to automatically segment COVID-19 computerised tomography (CT) data. By doing so we are producing an alternative model to current literature, which is easy to follow and reproduce, making it more accessible for real-world applications as little training would be required to use this. Our simple approach achieves results comparable to those of previously published studies, which use more complex deep-learning networks. We demonstrate a high-quality automated segmentation prediction of thoracic CT scans that correctly delineates the infected regions of the lungs. This segmentation automation can be used as a tool to speed up the contouring process, either to check manual contouring in place of a peer checking, when not possible or to give a rapid indication of infection to be referred for further treatment, thus saving time and resources. In contrast, manual contouring is a time-consuming process in which a professional would contour each patient one by one to be later checked by another professional. The proposed model uses approximately 49 k parameters while others average over 1,000 times more parameters. As our approach relies on a very compact model, shorter training times are observed, which make it possible to easily retrain the model using other data and potentially afford "personalised medicine" workflows. The model achieves similarity scores of Specificity (Sp) = 0.996 ± 0.001, Accuracy (Acc) = 0.994 ± 0.002 and Mean absolute error (MAE) = 0.0075 ± 0.0005.

Evaluation of the dataset quality in gamma passing rate predictions using machine learning methods.

OBJECTIVE: Gamma passing rate (GPR) predictions using machine learning methods have been explored for treatment verification of radiotherapy plans. However, these methods presented datasets with unbalanced number of plans having different treatment conditions (heterogeneous datasets), such as anatomical sites or dose per fractions, leading to lower model interpretability and prediction performance. METHODS: We investigated the impact of the dataset composition on GPR binary classification (pass/fail) using random forest (RF), XG-boost, and neural network (NN) models. 945 plans were used to create one reference dataset (randomly assembled) and 24 customized datasets that considered four heterogeneity factors independently (anatomical region, number of arcs, dose per fraction, and treatment unit). 309 predictor features were extracted and calculated from plan parameters, modulation complexity metrics, and radiomic analysis (leave-trajectory maps, 3D dose distributions, and portal dosimetry images). The models' performances were measured using the area under the curve from the receiver operating characteristic (ROC-AUC). RESULTS: Radiomics features for reference models increased ROC-AUC values up to 13%, 15%, and 5% for RF, XG-Boost, and NN, respectively. The datasets with higher heterogeneous conditions presented the lower ROC-AUC values (RF: 0.72 ± 0.11, XG-Boost: 0.67 ± 0.1, NN: 0.89 ± 0.05) compared to models with less heterogeneous treatment conditions (RF: 0.88 ± 0.06, XG-Boost: 0.89 ± 0.07, NN: 0.98 ± 0.01). The ten most important features for each heterogeneity dataset group demonstrated their correlation with the treatments' physical aspects and GPR prediction. CONCLUSION: Improvements in data generalization and model performances can be associated with datasets having similar treatment conditions. This analysis might be implemented to evaluate the dataset quality and model consistency of further ML applications in radiotherapy. ADVANCES IN KNOWLEDGE: Dataset heterogeneities decrease ML model performance and reliability.

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose deliverability. Nevertheless, these metrics might not comprehensively represent the modulation complexity, and automatically extracted features from alternative predictors associated with modulation complexity are needed. For this reason, three convolutional neural networks (CNN) based models were trained to predict GPR values (regression and classification), using respectively three predictors: (1) the modulation maps (MM) from the multi-leaf collimator, (2) the relative monitor units per control point profile (MUcp), and (3) the composite dose image (CDI) used for portal dosimetry, from 1024 anonymized prostate plans. The models' performance was assessed for classification and regression by the area under the receiver operator characteristic curve (AUC_ROC) and Spearman's correlation coefficient (r). Finally, four hybrid models were designed using all possible combinations of the three predictors. The prediction performance for the CNN-models using single predictors (MM, MUcp, and CDI) were AUC_ROC = 0.84 ± 0.03, 0.77 ± 0.07, 0.75 ± 0.04, andr= 0.6, 0.5, 0.7. Contrastingly, the hybrid models (MM + MUcp, MM + CDI, MUcp+CDI, MM + MUcp+CDI) performance were AUC_ROC = 0.94 ± 0.03, 0.85 ± 0.06, 0.89 ± 0.06, 0.91 ± 0.03, andr= 0.7, 0.5, 0.6, 0.7. The MP, MUcp, and CDI are suitable predictors for dose deliverability models implementing ML methods. Additionally, hybrid models are susceptible to improving their prediction performance, including two or more input predictors.

Bn2DT3A, a Chelator for 68Ga Positron Emission Tomography: Hydroxide Coordination Increases Biological Stability of [68Ga][Ga(Bn2DT3A)(OH)].

The chelator Bn2DT3A was used to produce a novel 68Ga complex for positron emission tomography (PET). Unusually, this system is stabilized by a coordinated hydroxide in aqueous solutions above pH 5, which confers sufficient stability for it to be used for PET. Bn2DT3A complexes Ga3+ in a hexadentate manner, forming a mer-mer complex with log K([Ga(Bn2DT3A)]) = 18.25. Above pH 5, the hydroxide ion coordinates the Ga3+ ion following dissociation of a coordinated amine. Bn2DT3A radiolabeling displayed a pH-dependent speciation, with [68Ga][Ga(Bn2DT3A)(OH)]- being formed above pH 5 and efficiently radiolabeled at pH 7.4. Surprisingly, [68Ga][Ga(Bn2DT3A)(OH)]- was found to show an increased stability in vitro (for over 2 h in fetal bovine serum) compared to [68Ga][Ga(Bn2DT3A)]. The biodistribution of [68Ga][Ga(Bn2DT3A)(OH)]- in healthy rats showed rapid clearance and excretion via the kidneys, with no uptake seen in the lungs or bones.

Smolyak Algorithm Adapted to a System-Bath Separation: Application to an Encapsulated Molecule with Large-Amplitude Motions.

A Smolyak algorithm adapted to system-bath separation is proposed for rigorous quantum simulations. This technique combines a sparse grid method with the system-bath concept in a specific configuration without limitations on the form of the Hamiltonian, thus achieving a highly efficient convergence of the excitation transitions for the "system" part. Our approach provides a general way to overcome the perennial convergence problem for the standard Smolyak algorithm and enables the simulation of floppy molecules with more than a hundred degrees of freedom. The efficiency of the present method is illustrated on the simulation of H2 caged in an sII clathrate hydrate including two kinds of cage modes. The transition energies are converged by increasing the number of normal modes of water molecules. Our results confirm the triplet splittings of both translational and rotational (j = 1) transitions of the H2 molecule. Furthermore, they show a slight increase of the translational transitions with respect to the ones in a rigid cage.

Ocean Acidification Amplifies the Olfactory Response to 2-Phenylethylamine: Altered Cue Reception as a Mechanistic Pathway?

With carbon dioxide (CO2) levels rising dramatically, climate change threatens marine environments. Due to increasing CO2 concentrations in the ocean, pH levels are expected to drop by 0.4 units by the end of the century. There is an urgent need to understand the impact of ocean acidification on chemical-ecological processes. To date, the extent and mechanisms by which the decreasing ocean pH influences chemical communication are unclear. Combining behaviour assays with computational chemistry, we explore the function of the predator related cue 2-phenylethylamine (PEA) for hermit crabs (Pagurus bernhardus) in current and end-of-the-century oceanic pH. Living in intertidal environments, hermit crabs face large pH fluctuations in their current habitat in addition to climate-change related ocean acidification. We demonstrate that the dietary predator cue PEA for mammals and sea lampreys is an attractant for hermit crabs, with the potency of the cue increasing with decreasing pH levels. In order to explain this increased potency, we assess changes to PEA's conformational and charge-related properties as one potential mechanistic pathway. Using quantum chemical calculations validated by NMR spectroscopy, we characterise the different protonation states of PEA in water. We show how protonation of PEA could affect receptor-ligand binding, using a possible model receptor for PEA (human TAAR1). Investigating potential mechanisms of pH-dependent effects on olfactory perception of PEA and the respective behavioural response, our study advances the understanding of how ocean acidification interferes with the sense of smell and thereby might impact essential ecological interactions in marine ecosystems.

Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator.

OBJECTIVE: High levels of beam modulation complexity (MC) and monitor units (MU) can compromise the plan deliverability of intensity-modulated radiotherapy treatments. Our study evaluates the effect of three treatment planning system (TPS) parameters on MC and MU using different multi-leaf collimator (MLC) architectures. METHODS: 192 volumetric modulated arc therapy plans were calculated using one virtual prostate phantom considering three main settings: (1) three TPS-parameters (Convergence; Aperture Shape Controller, ASC; and Dose Calculation Resolution, DCR) selected from Eclipse v15.6, (2) four levels of dose-sparing priority for organs at risk (OAR), and (3) two treatment units with same nominal conformity resolution and different MLC architectures (Halcyon-v2 dual-layer MLC, DL-MLC & TrueBeam single-layer MLC, SL-MLC). We use seven complexity metrics to evaluate the MC, including two new metrics for DL-MLC, assessed by their correlation with γ passing rate (GPR) analysis. RESULTS: DL-MLC plans demonstrated lower dose-sparing values than SL-MLC plans (p<0.05). TPS-parameters did not change significantly the complexity metrics for either MLC architectures. However, for SL-MLC, significant variations of MU, target volume dose-homogeneity, and dose spillage were associated with ASC and DCR (p<0.05). MU were found to be correlated (highly or moderately) with all complexity metrics (p<0.05) for both MLC plans. Additionally, our new complexity metrics presented a moderate correlation with GPR (r<0.65). An important correlation was demonstrated between MC (plan deliverability) and dose-sparing priority level for DL-MLC. CONCLUSIONS: TPS-parameters selected do not change MC for DL-MLC architecture, but they might have a potential use to control the MU, PTV homogeneity or dose spillage for SL-MLC. Our new DL-MLC complexity metrics presented important information to be considered in future pre-treatment quality assurance programs. Finally, the prominent dependence between plan deliverability and priority applied to OAR dose sparing for DL-MLC needs to be analyzed and considered as an additional predictor of GPRs in further studies. ADVANCES IN KNOWLEDGE: Dose-sparing priority might influence in modulation complexity of DL-MLC.

Finite element assessment of a disc-replacement implant for treating scoliotic deformity.

BACKGROUND: Bracing and spinal fusion surgery have long been the primary methods for idiopathic scoliosis correction; however, there exist multiple limitations with both techniques. Growth modulation techniques have recently been attempted, but are typically performed across multiple vertebral elements. The aim of this study was to quantify the corrective abilities of a dual-angled, wedge shaped, rigid disc implant designed to correct spinal deformity. METHODS: The 3D spinal geometry of four patients was reconstructed using calibrated radiographs, from which personal finite element models were created. Coronal and sagittal Cobb angles and axial stress distribution were calculated pre- and post- simulation of device implantation at the apical vertebral element. FINDINGS: Insertion of a rigid wedged implant resulted in up to 90.1% coronal correction with kyphotic normalization, and reduced axial stress differential within adjacent vertebrae by up to 83.3%. This correction in axial stress differential was seen to propagate to subjacent vertebrae in both rostral and caudal directions. Insertion of two implants yielded greater correction with respect to all three measures. INTERPRETATION: Local Cobb angle correction, increased kyphotic angle, and a decrease in axial stress differential with adjacent and subjacent vertebral levels demonstrate a potential for deformity correction from within the disc space. The decrease in axial stress differential demonstrates a capacity for growth modulation and reversal of the Heuter-Volkmann principle. Based on qualitative views of spinal shape following device implantation, the wedged implant proved more efficacious in correcting single thoracic curves than double major curves.

The first microsolvation step for furans: New experiments and benchmarking strategies.

The site-specific first microsolvation step of furan and some of its derivatives with methanol is explored to benchmark the ability of quantum-chemical methods to describe the structure, energetics, and vibrational spectrum at low temperature. Infrared and microwave spectra in supersonic jet expansions are used to quantify the docking preference and some relevant quantum states of the model complexes. Microwave spectroscopy strictly rules out in-plane docking of methanol as opposed to the top coordination of the aromatic ring. Contrasting comparison strategies, which emphasize either the experimental or the theoretical input, are explored. Within the harmonic approximation, only a few composite computational approaches are able to achieve a satisfactory performance. Deuteration experiments suggest that the harmonic treatment itself is largely justified for the zero-point energy, likely and by design due to the systematic cancellation of important anharmonic contributions between the docking variants. Therefore, discrepancies between experiment and theory for the isomer abundance are tentatively assigned to electronic structure deficiencies, but uncertainties remain on the nuclear dynamics side. Attempts to include anharmonic contributions indicate that for systems of this size, a uniform treatment of anharmonicity with systematically improved performance is not yet in sight.

Biomechanical analysis of sagittal correction parameters for surgical instrumentation with pedicle subtraction osteotomy in adult spinal deformity.

BACKGROUND: High complication rate has been documented in spinal instrumentation with pedicle subtraction osteotomy. The objective was to analyze the biomechanics of spinal instrumentation with pedicle subtraction osteotomy as functions of three instrumentation parameters. METHODS: Patient-specific biomechanical computer models of 3 adult patients who were instrumented with pedicle subtraction osteotomy were used to simulate the actual instrumentations and alternative instrumentations derived by varying instrumentation parameters: pedicle subtraction osteotomy wedge angle and rod contouring angle, location of the osteotomy, and number of rods (2 vs. 4). FINDINGS: A change of the sagittal correction by +7.5° (-7.5°) resulted in a change in the screw axial forces and rods bending loads around the osteotomy by +38% (-19%) and +28% (-11%), respectively. The bending moments in the rods were 31% lower at the osteotomy site when it was located at one level above, and 20% higher when it was located at a level below. Additional rods allowed the rod bending and screw axial loads to be reduced by 24% and 22%, respectively. INTERPRETATION: The amount of sagittal correction was positively correlated with loads sustained by the screws and rods. Rods were subjected to higher bending loads at the pedicle subtraction osteotomy site when it was done at a lower level. A 4-rod construct is an effective way to reduce the risk of rod breakage by reducing the loads sustained by the rods.

Intramolecular stretching vibrational states and frequency shifts of (H2)2 confined inside the large cage of clathrate hydrate from an eight-dimensional quantum treatment using small basis sets.

We report the results of calculations pertaining to the HH intramolecular stretching fundamentals of (p-H2)2 encapsulated in the large cage of structure II clathrate hydrate. The eight-dimensional (8D) quantum treatment assumes rotationless (j = 0) H2 moieties and a rigid clathrate structure but is otherwise fully coupled. The (H2)2-clathrate interaction is constructed in a pairwise-additive fashion, by combining the ab initio H2-H2O pair potential for flexible H2 and rigid H2O [D. Lauvergnat et al., J. Chem. Phys. 150, 154303 (2019)] and the six-dimensional (6D) H2-H2 potential energy surface [R. J. Hinde, J. Chem. Phys. 128, 154308 (2008)]. The calculations are performed by first solving for the eigenstates of a reduced-dimension 6D "intermolecular" Hamiltonian extracted from the full 8D Hamiltonian by taking the H2 moieties to be rigid. An 8D contracted product basis for the solution of the full problem is then constructed from a small number of the lowest-energy 6D intermolecular eigenstates and two discrete variable representations covering the H2-monomer internuclear distances. Converged results are obtained already by including just the two lowest intermolecular eigenstates in the final 8D basis of dimension 128. The two HH vibrational stretching fundamentals are computed for three hydrate domains having an increasing number of H2O molecules. For the largest domain, the two fundamentals are found to be site-split by ∼0.5 cm-1 and to be redshifted by about 24 cm-1 from the free-H2 monomer stretch frequency, in excellent agreement with the experimental value of 26 cm-1. A first-order perturbation theory treatment gives results that are nearly identical to those of the 8D quantum calculations.

Short- and Medium-Term Exposure to Ocean Acidification Reduces Olfactory Sensitivity in Gilthead Seabream.

The effects of ocean acidification on fish are only partially understood. Studies on olfaction are mostly limited to behavioral alterations of coral reef fish; studies on temperate species and/or with economic importance are scarce. The current study evaluated the effects of short- and medium-term exposure to ocean acidification on the olfactory system of gilthead seabream (Sparus aurata), and attempted to explain observed differences in sensitivity by changes in the protonation state of amino acid odorants. Short-term exposure to elevated PCO2 decreased olfactory sensitivity to some odorants, such as L-serine, L-leucine, L-arginine, L-glutamate, and conspecific intestinal fluid, but not to others, such as L-glutamine and conspecific bile fluid. Seabream were unable to compensate for high PCO2 levels in the medium term; after 4 weeks exposure to high PCO2, the olfactory sensitivity remained lower in elevated PCO2 water. The decrease in olfactory sensitivity in high PCO2 water could be partly attributed to changes in the protonation state of the odorants and/or their receptor(s); we illustrate how protonation due to reduced pH causes changes in the charge distribution of odorant molecules, an essential component for ligand-receptor interaction. However, there are other mechanisms involved. At a histological level, the olfactory epithelium contained higher densities of mucus cells in fish kept in high CO2 water, and a shift in pH of the mucus they produced to more neutral. These differences suggest a physiological response of the olfactory epithelium to lower pH and/or high CO2 levels, but an inability to fully counteract the effects of acidification on olfactory sensitivity. Therefore, the current study provides evidence for a direct, medium term, global effect of ocean acidification on olfactory sensitivity in fish, and possibly other marine organisms, and suggests a partial explanatory mechanism.

H2, HD, and D2 in the small cage of structure II clathrate hydrate: Vibrational frequency shifts from fully coupled quantum six-dimensional calculations of the vibration-translation-rotation eigenstates.

We report the first fully coupled quantum six-dimensional (6D) bound-state calculations of the vibration-translation-rotation eigenstates of a flexible H2, HD, and D2 molecule confined inside the small cage of the structure II clathrate hydrate embedded in larger hydrate domains with up to 76 H2O molecules, treated as rigid. Our calculations use a pairwise-additive 6D intermolecular potential energy surface for H2 in the hydrate domain, based on an ab initio 6D H2-H2O pair potential for flexible H2 and rigid H2O. They extend to the first excited (v = 1) vibrational state of H2, along with two isotopologues, providing a direct computation of vibrational frequency shifts. We show that obtaining a converged v = 1 vibrational state of the caged molecule does not require converging the very large number of intermolecular translation-rotation states belonging to the v = 0 manifold up to the energy of the intramolecular stretch fundamental (≈4100 cm-1 for H2). Only a relatively modest-size basis for the intermolecular degrees of freedom is needed to accurately describe the vibrational averaging over the delocalized wave function of the quantum ground state of the system. For the caged H2, our computed fundamental translational excitations, rotational j = 0 → 1 transitions, and frequency shifts of the stretch fundamental are in excellent agreement with recent quantum 5D (rigid H2) results [A. Powers et al., J. Chem. Phys. 148, 144304 (2018)]. Our computed frequency shift of -43 cm-1 for H2 is only 14% away from the experimental value at 20 K.

The inhibitory subunit of cardiac troponin (cTnI) is modified by arginine methylation in the human heart.

BACKGROUND: The inhibitory subunit of cardiac troponin (cTnI) is a gold standard cardiac biomarker and also an essential protein in cardiomyocyte excitation-contraction coupling. The interactions of cTnI with other proteins are fine-tuned by post-translational modification of cTnI. Mutations in cTnI can lead to hypertrophic cardiomyopathy. METHODS AND RESULTS: Here we report, for the first time, that cTnI is modified by arginine methylation in human myocardium. Using Western blot, we observed reduced levels of cTnI arginine methylation in human hypertrophic cardiomyopathy compared to dilated cardiomyopathy biopsies. Similarly, using a rat model of cardiac hypertrophy we observed reduced levels of cTnI arginine methylation compared to sham controls. Using mass spectrometry, we identified cTnI methylation sites at R74/R79 and R146/R148 in human cardiac samples. R146 and R148 lie at the boundary between the critical cTnI inhibitory and switch peptides; PRMT1 methylated an extended inhibitory peptide at R146 and R148 in vitro. Mutations at R145 that have been associated with hypertrophic cardiomyopathy hampered R146/R148 methylation by PRMT1 in vitro. H9c2 cardiac-like cells transfected with plasmids encoding for a methylation-deficient R146A/R148A cTnI protein developed cell hypertrophy, with a 32% increase in cell size after 72 h, compared to control cells. DISCUSSION: Our results provide evidence for a novel and significant cTnI post-translational modification. Our work opens the door to translational investigations of cTnI arginine methylation as a biomarker of disease, which can include e.g. cardiomyopathies, myocardial infarction and heart failure, and offers a novel way to investigate the effect of cTnI mutations in the inhibitory/switch peptides.

Does cage quantum delocalisation influence the translation-rotational bound states of molecular hydrogen in clathrate hydrate?

In this study, we examine the effect of a flexible description of the clathrate hydrate framework on the translation-rotation (TR) eigenstates of guest molecules such as molecular hydrogen. Traditionally, the water cage structure is assumed to be rigid, thus ignoring the quantum nature of hydrogen nuclei in the water framework. However, it has been shown that protons in a water molecule possess a marked delocalised character in many situations, ranging from water clusters to proton transfer in the bulk. In the case of water clathrates, all previous TR bound-state calculations of guest molecules consider that the caging water molecules are fixed at their equilibrium geometry. Only recently, a static investigation of the role of proton configurations was performed by Bacic and co-workers by sampling a very large number of different static structures of water clathrates. Here, we investigate the importance of the rotational degrees of freedom of the water cage on the TR levels of the guest molecule using an efficient adiabatic decoupling scheme. Our approach combines rigid body diffusion Monte Carlo calculations for the description of the rotational degree of freedom of water molecules surrounding the guest molecular hydrogen to an efficient Smolyak sparse-grid technique for the calculation of the TR levels. This approach allows us to take into account the highly anharmonic nature of the rotational water motions in a high-dimensional system. The clathrate-induced splittings of the j = 1 rotational levels are much more sensitive to the quantum hydrogen delocalisation than the translational transitions. This result is in good agreement with the previous static study of Bacic and co-workers.

Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling.

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult-to-detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species-specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.

The effect of the condensed-phase environment on the vibrational frequency shift of a hydrogen molecule inside clathrate hydrates.

We report a theoretical study of the frequency shift (redshift) of the stretching fundamental transition of an H2 molecule confined inside the small dodecahedral cage of the structure II clathrate hydrate and its dependence on the condensed-phase environment. In order to determine how much the hydrate water molecules beyond the confining small cage contribute to the vibrational frequency shift, quantum five-dimensional (5D) calculations of the coupled translation-rotation eigenstates are performed for H2 in the v=0 and v=1 vibrational states inside spherical clathrate hydrate domains of increasing radius and a growing number of water molecules, ranging from 20 for the isolated small cage to over 1900. In these calculations, both H2 and the water domains are treated as rigid. The 5D intermolecular potential energy surface (PES) of H2 inside a hydrate domain is assumed to be pairwise additive. The H2-H2O pair interaction, represented by the 5D (rigid monomer) PES that depends on the vibrational state of H2, v=0 or v=1, is derived from the high-quality ab initio full-dimensional (9D) PES of the H2-H2O complex [P. Valiron et al., J. Chem. Phys. 129, 134306 (2008)]. The H2 vibrational frequency shift calculated for the largest clathrate domain considered, which mimics the condensed-phase environment, is about 10% larger in magnitude than that obtained by taking into account only the small cage. The calculated splittings of the translational fundamental of H2 change very little with the domain size, unlike the H2 j = 1 rotational splittings that decrease significantly as the domain size increases. The changes in both the vibrational frequency shift and the j = 1 rotational splitting due to the condensed-phase effects arise predominantly from the H2O molecules in the first three complete hydration shells around H2.