Unveiling the Potential of Diffraction Gratings for Precision Separation of Higher-Harmonics in Non-Linear Acoustics.

Diffraction gratings, with their periodically ordered structures, have been critical components in acoustics, optics, and spectroscopy for over a century. The classical grating equation describes the emergence of diffraction phenomena by gratings, considering the groove periodicity and the characteristics of the incident wave. These gratings find extensive applications in communication, spectroscopy, architectural acoustics, and underwater research, and they are foundational to pioneering investigations in Phononic Crystals and Meta-materials. While much attention has been given to understanding the diffraction behavior of linear acoustics concerning gratings, the literature lacks research regarding the influence of high-amplitude ultrasonic waves, which introduce observable non-linear effects. This experimental inquiry presents a pioneering methodology for isolating higher harmonics from these non-linear phenomena. We have developed a spatial filtering apparatus with a single-frequency transducer and a specially designed grating profile, enabling precise frequency selection or rejection.

A Gauss-Newton method for iterative optimization of memory kernels for generalized Langevin thermostats in coarse-grained molecular dynamics simulations.

In molecular dynamics simulations, dynamically consistent coarse-grained (CG) models commonly use stochastic thermostats to model friction and fluctuations that are lost in a CG description. While Markovian, i.e., time-local, formulations of such thermostats allow for an accurate representation of diffusivities/long-time dynamics, a correct description of the dynamics on all time scales generally requires non-Markovian, i.e., non-time-local, thermostats. These thermostats typically take the form of a Generalized Langevin Equation (GLE) determined by a memory kernel. In this work, we use a Markovian embedded formulation of a position-independent GLE thermostat acting independently on each CG degree of freedom. Extracting the memory kernel of this CG model from atomistic reference data requires several approximations. Therefore, this task is best understood as an inverse problem. While our recently proposed approximate Newton scheme allows for the iterative optimization of memory kernels (IOMK), Markovian embedding remained potentially error-prone and computationally expensive. In this work, we present an IOMK-Gauss-Newton scheme (IOMK-GN) based on IOMK that allows for the direct parameterization of a Markovian embedded model.

Transferable local density-dependent friction in tert-butanol/water mixtures.

Coarse-grained (CG) models informed from molecular dynamics simulations provide a way to represent the structure of an underlying all-atom (AA) model by deriving an effective interaction potential. However, this leads to a speed-up in dynamics due to the lost friction, which is especially pronounced in CG implicit solvent models. Applying a thermostat based on the Langevin equation (LE) provides a way to represent the long-time dynamics of CG particles by reintroducing friction to the system. To improve the representability CG models of heterogeneous molecular mixtures and their transferability over the mixture compositions, we parameterize an LE thermostat in which the friction coefficient depends on the local particle density (LD). The thermostat friction was iteratively optimized with a Markovian variant of the recently introduced Iterative Optimization of Memory Kernels (IOMK) method. We simulated tert-butanol/water mixtures over a range of compositions, which show a distinct clustering behavior. Our model with LD-dependent friction reproduces the AA diffusion coefficients well over the full range of mixtures and is, therefore, transferable with respect to dynamics.

Interactions of adsorbing cosolutes with hydrophobic hydration shells.

The analysis of water density fluctuations in the hydration shell of nonpolar solutes provides insights into water-mediated interactions, especially hydrophobic interactions. These fluctuations are sensitive to small perturbations due to changes in thermodynamic conditions, such as temperature and pressure, but also to the presence of cosolutes, such as salts or small organic molecules. Herein, we investigate the effect of two classes of adsorbing cosolutes, using urea and methanol as representatives, on the fluctuations in energy and solvent density within the solvation shell of a model extended hydrophobic solute. We focus on the interactions of the cosolutes with the hydrophobic hydration shell, rather than with the solute itself, which though important remain largely unexplored. We calculate and analyze the interfacial partial molar energy of the cosolute, using a methodology based on the small system method. This approach provides correlated solvent density and energy fluctuations and allows us to decompose them into contributions due to interactions between the different components present in the solvation shell of the solute. The results show that adsorbed urea molecules interact more favorably with water than nonadsorbed urea molecules, which leads to the attenuation of interfacial density fluctuations and thus to the stabilization of the solvation shell. By contrast, the adsorbed methanol molecules interact preferably with other methanol molecules in the solvation shell, leading to a nano-phase segregated structure, which enhances interfacial fluctuations.

Future of Dutch NGS-Based Newborn Screening: Exploring the Technical Possibilities and Assessment of a Variant Classification Strategy.

In this study, we compare next-generation sequencing (NGS) approaches (targeted panel (tNGS), whole exome sequencing (WES), and whole genome sequencing (WGS)) for application in newborn screening (NBS). DNA was extracted from dried blood spots (DBS) from 50 patients with genetically confirmed inherited metabolic disorders (IMDs) and 50 control samples. One hundred IMD-related genes were analyzed. Two data-filtering strategies were applied: one to detect only (likely) pathogenic ((L)P) variants, and one to detect (L)P variants in combination with variants of unknown significance (VUS). The variants were filtered and interpreted, defining true/false positives (TP/FP) and true/false negatives (TN/FN). The variant filtering strategies were assessed in a background cohort (BC) of 4833 individuals. Reliable results were obtained within 5 days. TP results (47 patient samples) for tNGS, WES, and WGS results were 33, 31, and 30, respectively, using the (L)P filtering, and 40, 40, and 38, respectively, when including VUS. FN results were 11, 13, and 14, respectively, excluding VUS, and 4, 4, and 6, when including VUS. The remaining FN were mainly samples with a homozygous VUS. All controls were TN. Three BC individuals showed a homozygous (L)P variant, all related to a variable, mild phenotype. The use of NGS-based workflows in NBS seems promising, although more knowledge of data handling, automated variant interpretation, and costs is needed before implementation.

Anion Competition at Positively Charged Surfactant Monolayers.

Interactions of anions with hydrophobic surfaces of proteins and water-soluble polymers depend on the ability of the ions to shed their hydration shells. At positively charged surfactant monolayers, the interactions of anions are less well understood. Due to the interplay of electrostatic surface forces, hydration effects, and ion-ion interactions in the electrostatic double layer, a comprehensive microscopic picture remains elusive. Herein, we study the interactions of chloride, bromide, and a mixture of these two anions at the aqueous interface of dihexadecyldimethylammonium (DHDA+) and dioctadecyldimethylammonium (DODA+) cationic monolayers. Using molecular dynamics simulations and three surface-sensitive X-ray scattering techniques, we demonstrate that bromide interacts preferentially over chloride with both monolayers. The structure of the two monolayers and their interfacial electron density profiles obtained from the simulations quantitatively reproduce the experimental data. We observe that chloride and bromide form contact ion pairs with the quaternary ammonium groups on both monolayers. However, ion pairing with bromide leads to a greater reduction in the number of water molecules hydrating the anion, resulting in more energetically stable ion pairs. This leads to long-range (>3 nm) lateral correlations between bromide ions on the structured DODA+ monolayer. These observations indicate that ion hydration is the dominant factor determining the interfacial electrolyte structure.

Solvation Behavior of Elastin-like Polypeptides in Divalent Metal Salt Solutions.

The effects of CaCl2 and MgCl2 on the cloud point temperature of two different elastin-like polypeptides (ELPs) were studied using a combination of cloud point measurements, molecular dynamics simulations, and infrared spectroscopy. Changes in the cloud point for the ELPs in aqueous divalent metal cation solutions were primarily governed by two competing interactions: the cation-amide oxygen electrostatic interaction and the hydration of the cation. In particular, Ca2+ cations can more readily shed their hydration shells and directly contact two amide oxygens by the formation of ion bridges. By contrast, Mg2+ cations were more strongly hydrated and preferred to partition toward the amide oxygens along with their hydration shells. In fact, although hydrophilic ELP V5A2G3 was salted-out at low concentrations of MgCl2, it was salted-in at higher salt concentrations. By contrast, CaCl2 salted the ELP sharply out of solution at higher salt concentrations because of the bridging effect.

Anions and Cations Affect Amino Acid Dissociation Equilibria via Distinct Mechanisms.

Salts reduce the pKa of weak acids by a mechanism sensitive to ion identity and concentration via charge screening of the deprotonated state. In this study, we utilize constant pH molecular dynamics simulations to understand the molecular mechanism behind the salt-dependent dissociation of aspartic acid (Asp). We calculate the pKa of Asp in the presence of a monovalent salt and investigate Hofmeister ion effects by systematically varying the ionic radii. We observe that increasing the anion size leads to a monotonic decrease in Asp pKa. Conversely, the cation size affects the pKa nonmonotonically, interpretable in the context of the law of matching water affinity. The net effect of salt on Asp acidity is governed by an interplay of solvation and competing ion interactions. The proposed mechanism is rather general and can be applicable to several problems in Hofmeister ion chemistry, such as pH effects on protein stability and soft matter interfaces.

Dynamical coarse-grained models of molecular liquids and their ideal and non-ideal mixtures.

Coarse-grained (CG) simulation models of condensed-phase systems can be derived with well-established methods that perform coarse-graining in space and provide an effective Hamiltonian with which some of the structural and thermodynamic properties of the underlying fine-grained (FG) reference system can be represented. Coarse-graining in time potentially provides CG models that furthermore represent dynamic properties. However, systematic efforts in this direction have so far been limited, especially for moderately coarse-grained, chemistry-specific systems with complicated conservative interactions. With the aim of representing structural, thermodynamic, and dynamic properties in CG simulations of multi-component molecular systems, we investigated a recently introduced method in which the force on a CG particle originates from conservative interactions with surrounding particles and non-Markovian dissipative interactions, the latter introduced by means of a colored-noise thermostat. We examined two different methods to derive isotropic memory kernels required for integrating the corresponding generalized Langevin equation (GLE) of motion, based on the orthogonal dynamics of the FG forces and on an iterative optimization scheme. As a proof of concept, we coarse-grain single-component molecular liquids (cyclohexane, tetrachloromethane) and ideal and non-ideal binary mixtures of cyclohexane/tetrachloromethane and ethanol/tetrachloromethane, respectively. We find that for all systems, the FG single particle velocity auto-correlation functions and, consequently, both the short time and long time diffusion coefficients can be quantitatively reproduced with the CG-GLE models. We furthermore demonstrate that the present GLE-approach leads to an improved description of the rate with which the spatial correlations decay, which is artificially accelerated in the absence of dissipation.

Ultrasonic examination of a thin, textured metal plate with Penrose tile structure consisting of pitched indentations.

A feasibility study is presented on the experimental application of ultrasound to examine rolled stainless steel plates having equidistant surface textures in two directions in the form of Penrose tiles. The specific problem of interest is investigating surface profile quality in terms of its equidistance and depth to monitor the manufacturing process. The goal is to eventually replace current time-consuming optical examination procedures with a reliable and rapid ultrasonic inspection technique. Two practical experimental setups are discussed and compared in this work: examining frequency spectra obtained from normal incidence pulse-echo measurements, and those obtained at Laue angle incidence. A thorough survey of ultrasonic methods precedes the experimental results to investigate such surfaces from a historical perspective.

Ultrasonic testing of the biomechanical properties of donation blood.

Background.Donated blood is routinely preserved for about six weeks. After that, a considerable amount of unused blood is discarded for safety. We carried out sequential measurements of the ultrasonic parameters (Velocity of propagation of ultrasound, its attenuation, and relative nonlinearity coefficient B/A) for red blood cells (RBCs) bags in their physiological preserving conditions in the blood bank, in a given experimental setup, to investigate the gradual deteriorations in the biomechanical properties of RBCs.Materials and Methods. We discuss our primary findings, which indicate the applicability of ultrasound techniques as a quantitative quick, non-invasive routine check for the validity of sealed blood bags. The technique can be applied during and beyond the regular preservation period, thus enabling deciding for each bag to either further preserve or withdraw.Results and Discussion. Considerable increases in the velocity of propagation (ΔV = 966 m s-1) and ultrasound attenuation (Δα= 0.81 dB C-1m-1) were detected to take place during the preservation time. Likewise, the relative nonlinearity coefficient showed a generally rising trend during the preservation period (Δ(B/A) = 0.0129). At the same time, a distinctive feature characteristic of a specific blood group type is realized in all cases. Due to the complex stress-strain relations and their reflection on the hydrodynamics and flow rate of non-Newtonian fluids, the increased viscosity of long-preserved blood may justify the known post-transfusion flow complications.

Bottom-Up Informed and Iteratively Optimized Coarse-Grained Non-Markovian Water Models with Accurate Dynamics.

Molecular dynamics (MD) simulations based on coarse-grained (CG) particle models of molecular liquids generally predict accelerated dynamics and misrepresent the time scales for molecular vibrations and diffusive motions. The parametrization of Generalized Langevin Equation (GLE) thermostats based on the microscopic dynamics of the fine-grained model provides a promising route to address this issue, in conjunction with the conservative interactions of the CG model obtained with standard coarse graining methods, such as iterative Boltzmann inversion, force matching, or relative entropy minimization. We report the application of a recently introduced bottom-up dynamic coarse graining method, based on the Mori-Zwanzig formalism, which provides accurate estimates of isotropic GLE memory kernels for several CG models of liquid water. We demonstrate that, with an additional iterative optimization of the memory kernels (IOMK) for the CG water models based on a practical iterative optimization technique, the velocity autocorrelation function of liquid water can be represented very accurately within a few iterations. By considering the distinct Van Hove function, we demonstrate that, with the presented methods, an accurate representation of structural relaxation can be achieved. We consider several distinct CG potentials to study how the choice of the CG potential affects the performance of bottom-up informed and iteratively optimized models.

Stability, Speed, and Constraints for Structural Coarse-Graining in VOTCA.

Structural coarse-graining involves the inverse problem of deriving pair potentials that reproduce target radial distribution functions. Despite its clear mathematical formulation, there are open questions about the existing methods concerning speed, stability, and physical representability of the resulting potentials. In this work, we make progress on several aspects of iterative methods used to solve the inverse problem. Based on integral equation theory, we derive fast Gauss-Newton schemes applicable to very general systems, including molecules with bonds and mixtures. Our methods are similar to inverse Monte Carlo in terms of convergence speed and have a similar cost per iteration as iterative Boltzmann inversion. We investigate stability problems in our schemes and in the inverse Monte Carlo method and propose modifications to fix them. Furthermore, we establish how the pair potential can be constrained at each iteration to reproduce the pressure, Kirkwood-Buff integral, or the enthalpy of vaporization. We demonstrate the potential of our approach in deriving coarse-grained force fields for nine different solvents and their mixtures. All methods described are implemented in the free and open VOTCA software framework for systematic coarse-graining.

Comparative evaluation of SARS-CoV-2 serological tests shows significant variability in performance across different years of infection and between the tests.

Introduction: While the global COVID-19 pandemic is slowly coming under control, current efforts are focused on understanding the epidemiology of endemic SARS-CoV-2. The tool of choice for doing so remains serological tests that detect SARS-CoV-2 induced antibodies. However, the performance of these tests should be evaluated to ensure they comply with the specific performance criteria desired by each country that they are used in. Methods: Here, we use pre-COVID-19 plasma and plasma from SARS-CoV-2-infected individuals collected in 2020, 2021 and 2022 to evaluate the performance of two commercial Rapid Lateral Flow (RLF) tests (the PANBIO™ COVID-19 IgG/IgM rapid test and the LABNOVATION™ COVID-19 (SARS-CoV-2) IgG/IgM rapid test) and one commercial ELISA test (the PLATELIA™ SARS-CoV-2 total Ab). Results: We find that whereas the specificity of the two RLF tests is ≥ 95%, it was 91% for the ELISA tests. However, at 14 days post-COVID-19 date of diagnosis (DoD), only the ELISA test constantly achieved a sensitivity of ≥80% over all the three years. In addition, the rate of detection of the two RLF tests varied across the years with a sensitivity ranging from <80% in 2021 to >80% in 2022. More importantly the capacity of these two RLF tests to detect IgG antibodies decreased with time. On the contrary, the sensitivity of the ELISA test was still above 80% more than six months post DoD. Conclusion: We recommend that sero-epidemiological surveys focused on testing antibodies should not rely on performances reported by the assay manufacturers. They should include a formal evaluation of the selected assays to ensure its limitations and strengths conform with the data-accuracy requirements of the surveys.

A unique piezolyte mechanism of TMAO: Hydrophobic interactions under extreme pressure conditions.

We report a computer simulation study of the effect of trimethylamine N-oxide (TMAO) on the pressure stability of the hydrophobic contact interaction of two nonpolar α-helices. We found that TMAO counterbalanced the disruptive effect of pressure destabilization on account of an earlier reported electronic polarization effect that led to an increased TMAO dipole moment under compression of the solvent. This direct stabilization mechanism became ineffective when the dipole polarization of TMAO was not considered and was linked to nonspecific van der Waals interactions of TMAO with the nonpolar surfaces of the two helices, which became weaker as TMAO became stronger polarized at high pressure. The corresponding thermodynamic driving forces are discussed and should be generic for hydrophobic interactions under high pressure. The proposed mechanism suggests that TMAO stands out as a piezolyte among stabilizing osmolytes, potentially protecting biological assemblies formed by hydrophobic interactions under extreme pressure conditions.

Influence of TMAO and Pressure on the Folding Equilibrium of TrpCage.

Trimethylamine-N-oxide (TMAO) is an osmolyte known for its ability to counteract the pressure denaturation of proteins. Computational studies addressing the molecular mechanisms of TMAO's osmolyte action have however focused exclusively on its protein-stabilizing properties at ambient pressure, neglecting the changes that may occur under high-pressure conditions where TMAO's hydration structure changes to that of increased water binding. Here, we present the first study on the combined effect of pressure and TMAO on a mini-protein, TrpCage. The results showed that at high pressures, nonpolar residues packed less tightly and the salt bridge of TrpCage was destabilized. This effect was mitigated by TMAO which was found to be strongly depleted from the protein/water interface at 1 kbar than at 1 bar ambient pressure, thus counterbalancing the thermodynamically unfavorable effect of elevated pressure in the free energy of folding. TMAO was depleted from charged groups, like the salt bridge-forming ones, and accumulated around hydrophobic groups. Still, it stabilized both kinds of interactions. Furthermore, enthalpically favorable TrpCage-water hydrogen bonds were reduced in the presence of TMAO, causing a stronger destabilization of the unfolded state than the folded state. This shifted the protein-folding equilibrium toward the folded state. Therefore, TMAO showed stabilizing effects on different kinds of groups, which were partially enhanced at high pressures.

Cosolvent Exclusion Drives Protein Stability in Trimethylamine N-Oxide and Betaine Solutions.

Using a combination of molecular dynamics simulation, dialysis experiments, and electronic circular dichroism measurements, we studied the solvation thermodynamics of proteins in two osmolyte solutions, trimethylamine N-oxide (TMAO) and betaine. We showed that existing force fields are unable to capture the solvation properties of the proteins lysozyme and ribonuclease T1 and that the inaccurate parametrization of protein-osmolyte interactions in these force fields promoted an unphysical strong thermal denaturation of the trpcage protein. We developed a novel force field for betaine (the KBB force field) which reproduces the experimental solution Kirkwood-Buff integrals and density. We further introduced appropriate scaling to protein-osmolyte interactions in both the betaine and TMAO force fields which led to successful reproduction of experimental protein-osmolyte preferential binding coefficients for lysozyme and ribonuclease T1 and prevention of the unphysical denaturation of trpcage in osmolyte solutions. Correct parametrization of protein-TMAO interactions also led to the stabilization of the collapsed conformations of a disordered elastin-like peptide, while the uncorrected parameters destabilized the collapsed structures. Our results establish that the thermodynamic stability of proteins in both betaine and TMAO solutions is governed by osmolyte exclusion from proteins.

Cross-correlation corrected friction in generalized Langevin models: Application to the continuous Asakura-Oosawa model.

The development of dynamically consistent coarse-grained models for molecular simulations is often based on generalized Langevin equations, motivated by the application of the projection operator formalism (Mori-Zwanzig theory). While Mori's projection operator yields linear generalized Langevin equations that can be computationally efficiently implemented in numerical simulations, the downside is that Mori's generalized Langevin equation does not encompass the multi-body potential of mean force required to correctly encode structural and thermodynamic properties in coarse-grained many-body systems. Zwanzig's projection operator yields nonlinear generalized Langevin equations including the multi-body potential of mean force, while the remaining force contributions are not as cheap to implement in molecular simulation without making it formally hard to justify approximations. For many-particle coarse-grained models, due to computational and conceptual simplicity, an often used approach is to combine nonlinear conservative interactions with linear expressions to model dissipation. In a previous study [V. Klippenstein and N. F. A. van der Vegt, J. Chem. Phys. 154, 191102 (2021)], we proposed a method to parameterize such models to achieve dynamic consistency in coarse-grained models, allowing us to reconcile Mori's and Zwanzig's approach for practical purposes. In the current study, by applying the same strategy, we develop coarse-grained implicit solvent models for the continuous Asakura-Oosawa model, which under certain conditions allows us to develop very accurate coarse-grained potentials. By developing coarse-grained models for different reference systems with varying parameters, we test the broader applicability of the proposed procedure and demonstrate the relevance of accurate coarse-grained potentials in bottom-up derived dissipative models. We study how different system parameters affect the dynamic representability of the coarse-grained models. In particular, we find that the quality of the coarse-grained potential is crucial to correctly model the backscattering effect due to collisions on the coarse-grained scale. As hydrodynamic interactions are not explicitly modeled in the presented coarse-graining approach, deviations are observed in the long-time dynamics. The Asakura-Oosawa model allows for the tuning of system parameters to gain an improved understanding of this limitation. We also propose three new iterative optimization schemes to fine-tune the generalized Langevin thermostat to exactly match the reference velocity-autocorrelation function.

Temperature induced change of TMAO effects on hydrophobic hydration.

The effect of trimethylamine-N-oxide (TMAO) on hydrophobic solvation and hydrophobic interactions of methane has been studied with Molecular Dynamics simulations in the temperature range between 280 and 370 K at 1 bar ambient pressure. We observe a temperature transition in the effect of TMAO on the aqueous solubility of methane. At low temperature (280 K), methane is preferentially hydrated, causing TMAO to reduce its solubility in water, while above 320 K, methane preferentially interacts with TMAO, causing TMAO to promote its solubility in water. Based on a statistical-mechanical analysis of the excess chemical potential of methane, we find that the reversible work of creating a repulsive methane cavity opposes the solubility of methane in TMAO/water solution more than in pure water. Below 320 K, this solvent-excluded volume effect overcompensates the contribution of methane-TMAO van der Waals interactions, which promote the solvation of methane and are observed at all temperatures. These van der Waals interactions with the methyl groups of TMAO tip the balance above 320 K where the effect of TMAO on solvent-excluded volume is smaller. We furthermore find that the effective attraction between dissolved methane solutes increases with the increasing TMAO concentration. This observation correlates with a reduction in the methane solubility below 320 K but with an increase in methane solubility at higher temperatures.

Solvation shell thermodynamics of extended hydrophobic solutes in mixed solvents.

The ability of various cosolutes and cosolvents to enhance or quench solvent density fluctuations at solute-water interfaces has crucial implications on the conformational equilibrium of macromolecules such as polymers and proteins. Herein, we use an extended hydrophobic solute as a model system to study the effect of urea and methanol on the density fluctuations in the solute's solvation shell and the resulting thermodynamics. On strengthening the solute-water/cosolute repulsive interaction, we observe distinct trends in the mutual affinities between various species in, and the thermodynamic properties of, the solvation shell. These trends strongly follow the respective trends in the preferential adsorption of urea and methanol: solute-water/cosolute repulsion strengthens, urea accumulation decreases, and methanol accumulation increases. Preferential accumulation of urea is found to quench the density fluctuations around the extended solute, leading to a decrease in the compressibility of the solvation shell. In contrast, methanol accumulation enhances the density fluctuations, leading to an increase in the compressibility. The mode of action of urea and methanol seems to be strongly coupled to their hydration behavior. The observations from this simple model is discussed in relation to urea driven swelling and methanol induced collapse of some well-known thermo-responsive polymers.