Atomistic molecular dynamics (MD) simulations coupled with potential of mean force (PMF) calculations were employed to investigate the interactions between PVC polymer chains containing 6-20 repeating units and various plasticizers, with the goal of identifying potential replacements for the toxic plasticizer di(2-ethylhexyl)phthalate (DEHP) used in blood bags. The selected plasticizers belong to various chemical families, such as orthophthalates, citrates, adipates, and the terephthalate DEHT. Both the polymer and the plasticizers lack ionizable groups, and their interactions are primarily governed by van der Waals and electrostatic forces. A model correlating PMF profiles with interaction forces was developed and validated across polyvinyl chloride (PVC) polymers of different lengths and all investigated plasticizers. This model provides insight into how structural variations in plasticizers influence their respective PMF values. The study ranks the investigated plasticizers based on binding affinity, identifying TOTM (tris(2-ethylhexyl) trimellitate, TEHTM), BTHC (butyryl trihexyl citrate, Citroflex B-6), ATHC (acetyl trihexyl citrate, Citroflex A-6, CA-6), and DEHT (bis(2-ethylhexyl)terephthalate, DOTP/DEHTP) as promising alternatives for further investigation. This comprehensive study encompasses PVC polymers of four different lengths and 14 plasticizers, with all data averaged over 30 independent simulations. The approach provides a deeper understanding of molecular interactions, enabling the tailoring of polymer-plasticizer systems for diverse applications, including extractables and leachables, with relevance spanning materials science to biomedical engineering, and also serves as a basis for developing coarse-grained simulation protocols. Overall, this study provides valuable insights for designing safer and more efficient plasticizer substitutes and is well supported by other studies.

Ion pair aggregates (IPAs) in olefin polymerization catalysts have attracted growing attention due to their potential influence on catalytic activity and selectivity. In this study, employing (pyridylamido)Hf(IV) as a model system, we investigated the destabilization and structural diversity of IPAs by using the molecular dynamics method. The potential of mean force (PMF) analysis indicates that the growing polymer chains, ethylene, and ZnEt2 destabilize the IPAs. In addition, the energy decomposition analysis demonstrated that not only the dominant electrostatic interaction but also relatively small yet qualitatively different contributions from dispersion and coordination interactions play an essential role in the structures of IPAs. These findings can be regarded as a piece of evidence that chemical species other than the catalyst itself in the reaction medium, through relatively small interactions, should modulate catalytic behaviors. Furthermore, we also found that the growing polymer chains, ethylene, and ZnEt2 induce structural diversity of IPAs, and classified IPAs' structures into three distinct classes: (1) inner-sphere ion pair aggregate (ISIPA), (2) bridged ion pair aggregate (BIPA), and (3) outer-sphere ion pair aggregate (OSIPA). Our findings have laid the groundwork for a broader understanding of IPAs' behaviors in olefin polymerization catalysts across diverse catalytic environments.

We report a molecular dynamics (MD) simulation study of the process of peeling off a single molecular chain from cellulose Iβ crystal models. This study serves as a model for crystal surface decrystallization. We combined two types of extended ensemble MD simulation methods: adaptive steered MD to define the chain peeling-off trajectory along the reaction coordinate and umbrella sampling MD to calculate the potential of the mean force and free-energy change along the chosen reaction coordinate. The crystal models were solvated with water, benzene, 10 wt % aqueous solution of NaOH, N,N-dimethylacetamide with 1 wt % LiCl, N-methylpyrrolidone with 1 wt % LiCl, or 1-allyl-3-methylimidazolium chloride (AMIMCl). Endothermic free-energy changes were required for the chain to peel off in all of the solvents. However, extremely low free-energy values were observed in the AMIMCl solvent over the entire chain peeling-off range. This suggests that the decrystallization scheme for the AMIMCl solvent differs from those of the other solvents. In water, the free-energy change required for the chain to peel off from the reducing end was slightly lower than that required for it to peel off from the nonreducing end. This is consistent with the direction of the chain peel off observed in physical and enzymatic decrystallization at the crystal surface. Other umbrella sampling simulations that allowed for the spatial motion of the peeled-off chain segment revealed that after linearly increasing, the potential of mean force values leveled off for all of the solvent systems except for the AMIMCl system.

Say my name! I'll push through: The name-cue amplification effect on the impact of verbal encouragement in high-intensity exercise.

Influence of storage conditions on the mechanical properties of intermaxillary elastics.

The development of new treatments for neuropsychiatric disorders relies on a deeper understanding of the molecular mechanisms behind psychedelic compounds, particularly how they differentiate between hallucinogenic and antidepressant effects. In this study, we explore by molecular dynamics simulations a series of 25CN-NBx compounds bound to the 5-HT2A receptor. The simulations uncover that bulky substitutions on the N-benzyl ring cause a significant shift in the position of W336, a key toggle switch residue known to influence receptor activation and thought to play a crucial role in mediating psychedelic signaling. This result is confirmed through potential of mean force calculations along the toggle switch's dihedral angle. End-state free energy calculations align closely with experimental data, showing that 25CN-NB-2-OH-3-Me and 25CN-NB-2-OH-5-MeO have the highest and lowest affinities, respectively, for the 5-HT2A receptor. Further analysis indicates that when W336 adopts its negative dihedral state, it establishes stronger van der Waals interactions, stabilizing its contacts with residues F332 and I163─key players previously linked to receptor activation. Our findings provide a framework for understanding receptor activation and can be extended to other G protein-coupled receptors where the toggle switch is central to signal activation.

Nanoporous graphene has emerged as a promising platform for desalination because its atomic thickness and tunable pore chemistry can, in principle, overcome the conventional permeability-selectivity trade-off of polymeric reverse osmosis membranes. Here, we investigate water and ion transport through a single-layer pyridinic-N-doped nanoporous graphene membrane containing sub-nanometer pores with an effective diameter of ~ 2.75Å, separating a saline feed from a pure permeate reservoir under an axial electric field of 0.05VÅ⁻1. Non-equilibrium molecular dynamics simulations reveal that this functionalized membrane supports very high-water throughput while maintaining complete Na⁺/Cl⁻ rejection over multi-nanosecond trajectories. The inferred water permeance is on the hundreds of LMH bar⁻1, and potential of mean force calculations show ion translocation barriers, dominated by steric confinement and dehydration. Structural analysis indicates strong hydrogen bonding between water and pyridinic N at the pore rim, together with field-induced alignment of water dipoles along the transport direction. These synergistic effects enable rapid, selective water transport through sub-nanometer pores, highlighting pyridinic N-doping and modest electric fields as a viable design strategy for next-generation high-flux desalination membranes. We performed non‑equilibrium classical molecular dynamics simulations of a slit‑pore desalination cell containing a pyridinic‑N‑doped nanoporous graphene membrane, explicit water, and NaCl electrolyte. Water was represented by a rigid four‑site TIP4P‑family model, and Na⁺/Cl⁻ parameters were chosen to be compatible with this water model. The N‑doped graphene sheet, patterned with ~ 2.75Å pores and decorated at the rims by pyridinic-N, was modeled using an AIREBO/REBO‑type potential for C-C and C-N bonding. Electrostatics were treated with a particle-particle particle-mesh (PPPM) method under three‑dimensional periodic boundary conditions and van der Waals interactions were described by Lennard-Jones potentials with Lorentz-Berthelot mixing and an appropriate real‑space cutoff. A uniform external electric field of 0.05VÅ⁻1 was applied along the membrane normal, and a pressure‑like driving force was imposed via rigid carbon pistons at the cell ends. Water geometry was constrained using SHAKE/SETTLE, and the equations of motion were integrated with a velocity-Verlet scheme in the NVT ensemble at 300K, controlled by a Nosé-Hoover thermostat. Trajectories on the order of a few nanoseconds were generated using the LAMMPS package and analyzed with in‑house Python tools to obtain fluxes, permeances, z‑resolved densities, mean‑squared displacements, radial distribution functions, orientational order parameters, and accessible‑area‑corrected potentials of mean force.

This study presents a hybrid experimental–numerical methodology for the preliminary design and optimization of a CFRP crash box intended for high-performance automotive applications. An initial experimental campaign was conducted on frustum-shaped crash boxes manufactured by Pagani Automobili S.p.A., comparing constant and variable thickness configurations through drop tower impact tests to evaluate energy absorption, crushing stability, and failure mechanisms. A lightweight finite element model was developed in Abaqus/Explicit using shell elements and Hashin-based damage criteria, achieving calibration errors below 10% for most parameters and under 15% for peak forces. Geometric enhancements, including continuous flanges, removal of the top surface, and an internal cruciform reinforcement, significantly improved energy absorption (up to 110%) but introduced trade-offs in stroke efficiency and mean force levels. To mitigate these effects, a genetic algorithm was employed to optimize laminate layup by varying ply orientations, resulting in improved stroke efficiency and reduced peak and average forces while maintaining crushing stability. The proposed approach demonstrates that integrating experimental validation with efficient numerical modeling and optimization accelerates the development of lightweight, high-performance crash absorbers, offering a robust framework for motorsport and automotive applications that balances safety, efficiency, and manufacturability.

Graphene oxide (GO) membranes have emerged as promising candidates for water desalination as a result of their structural and transport properties. In this study, we employ fully atomistic classical molecular dynamics simulations to investigate the performance of monolayer GO membranes featuring pore- and slit-like nanostructures. We analyze the influence of the width of the slits, ranging from 0.8 to 1.5nm, on water transport and salt rejection by monitoring the spatial and temporal distributions of water molecules and ions. Furthermore, we assess the effect of applied pressure on water density profiles and compute the potential of mean force for water molecules traversing the slits. Our results reveal that slits offer tunable transport characteristics and that nanopores generally outperform slits in the combined metrics of water flux and ion exclusion at low pressures. At higher pressures, however, 1.0-1.5nm slits exhibit a permeability gain that can exceed comparable nanopore systems, with a reduction in salt rejection, whereas 0.8nm slits retain near-complete ion exclusion over the range examined. These findings delineate operating regimes in which each architecture is advantageous and guide the optimization of nanostructure design for advanced desalination technologies.

Coarse-grained (CG) modeling enables molecular simulations to reach time and length scales inaccessible to fully atomistic methods. For classical CG models, the choice of mapping, that is, how atoms are grouped into CG sites, is a major determinant of accuracy and transferability. At the same time, the emergence of machine learning potentials (MLPs) offers new opportunities to build CG models that can in principle learn the true potential of the mean force for any mapping. In this work, we systematically investigate how the choice of mapping influences the representations learned by equivariant MLPs by studying liquid hexane, amino acids, and polyalanine. We find that when the length scales of bonded and nonbonded interactions overlap, unphysical bond permutations can occur. We also demonstrate that correctly encoding species and maintaining stereochemistry are crucial, as neglecting either introduces unphysical symmetries. Our findings provide practical guidance for selecting CG mappings compatible with modern architectures and guide the development of transferable CG models.

ABSTRACTBackgroundNasolabial folds, or “smile lines,” result from the interaction of several anatomical structures, including the levator labii superioris alaeque nasi and the zygomaticus major and minor muscles, which place continuous tension on the dermis. Although the deep pyriform space is a common target for treating these folds, filler migration from this space can cause undesirable outcomes.AimsTo examine the anatomical characteristics and potential benefits of using a newly identified medial space: the perialar space, adjacent to the deep pyriform space, for nasolabial fold volumization to facilitate more effective and stable filler placement.MethodsTwenty‐two fresh cadavers were used (44 hemifaces: 13 male, 9 female; mean age 81.98 years) without trauma, surgery, or major deformities. Dyed injectate was administered into the deep pyriform and perialar spaces. Cannula resistance during insertion was measured, and injectate distribution was assessed through comprehensive dissection.ResultsThe mean forces at the first and second puncture sites were 1.70 ± 0.58 N and 3.29 ± 1.35 N, respectively. Dissection confirmed injectate placement in a space adjacent to, but distinct from, the deep pyriform space. Statistical analysis showed significant differences in tissue resistance between sites (p < 0.05). The perialar space thus represents a useful alternative for nasolabial fold volumization. Histological evaluation confirmed distinct boundaries, supporting its suitability as a stable and reliable site for filler injection.ConclusionsThis study shows the potential of the perialar space for enhancing aesthetic outcomes; reducing complications and filler migration; and achieving more stable enhancements in facial rejuvenation procedures than existing techniques.

The effect of the number of single door segments in the posterior cervical canal on the traction of the cervical 5 nerve root.

In solution, electrically like-charged particles can experience a strong and long-ranged attraction that leads to the formation of stable, slowly reorganizing clusters. The attractive force underpinning this spontaneous organization process has been shown to depend on both the sign of charge of the particle and the nature of the solvent medium. The origin of the attraction has been ascribed to the preferential orientation of solvent molecules at the object-electrolyte interface. Here, we use optical imaging to directly measure the spatial profile of the potential of mean force between isolated pairs of charged microspheres. Working with particles carrying a variety of surface chemistries we find that the range of the electrosolvation attraction is substantially longer than previously held. In particular we show that particles carrying strongly anionic surface coatings composed of DNA or phospholipid bilayers display long-range attraction. We further find that the length scale governing the decay of the attractive force can depend on the properties of the interacting particles. This contrasts with the canonical expectation that the screening length governing the interaction of charged particles in solution depends exclusively on the properties of the intervening electrolyte medium. The observations point to significant departures from current thinking, and the likely need for a model of interactions that accounts for the molecular nature of the solvent, its interfacial behaviour, and spatial correlations. Finally, a strong and long-ranged attraction mediated by anionic matter constituting lipid membranes and chromatin could carry far-reaching implications for organization and structure formation in biology.

To describe contact forces of 3 pulse oximeter clips and to evaluate, in healthy anesthetized dogs and cats, if perfusion index (PI) or peripheral arterial blood oxygen saturation (SpO2) is influenced by lingual clip location or weight category. Benchtop investigation of 3 clips occurred in February 2024 to determine contact force with increasing opening distances. In live animals, 1 clip was evaluated at 2 lingual locations. Enrollment of client-owned dogs and cats occurred from March 13, 2024, through June 21, 2024, including 10 each of dogs < 10 kg, dogs > 20 kg, and cats. Data included SpO2, PI, and magnitude of clip-induced lingual compression. Clips exhibited a positive relationship between opening distance and mean force generation. Clip location and weight category in dogs influenced SpO2 and PI values. At thicker tongue locations, median SpO2 values in dogs < 10 kg and cats were 5% and 2% greater, respectively, compared to thinner locations. Dogs > 20 kg displayed a median SpO2 value 1% lower at the thicker tongue location compared to the thinner location. Median PI values were lower at the thinner tongue site in dogs and cats. Pulse oximeter clip opening distance and contact force exhibited a positive relationship. Thicker lingual sites generated higher SpO2 and PI values in cats and dogs < 10 kg. Pulse oximeter position at 2 different locations on the tongue influence SpO2 and PI values in healthy anesthetized dogs < 10 kg, dogs > 20 kg, and cats.

Mukandi, I. Influence of competitive match play on countermovement jump performance, lower-limb isometric strength, and self-reported subjective measures 40 hours postmatch in professional soccer. J Strength Cond Res 40(2): 206-217, 2026-This study investigated the impact of competitive match play on countermovement jump (CMJ) performance, hamstrings and adductor isometric strength, and subjective self-reported measures 40 hours postcompetitive match play in professional soccer players. Twenty-eight professional players completed baseline assessments during preseason. Assessment 40 hours postmatch was limited to players who played ≥60 minutes, with players grouped into 2 categories based on minutes played: 60-89 minutes or 90-110 minutes. Baseline measures for subjective self-reported measures were collected 24 hours before each match. Across both groups, significant reductions ( p < 0.05) were observed in all outcome, ratio, and driver metrics except for eccentric mean force. All strategy metrics significantly increased ( p < 0.05). Minutes played and match demands were not significantly associated with CMJ performance (τ b = -0.07 to 0.16 and τ b = -0.28 to 0.00, respectively). Prone isometric 0° showed nonsignificant reductions ( p > 0.05) in both conditions with trivial to small effects. Significant reductions ( p < 0.05) were observed for both conditions for the supine 90° hamstring test, however minutes played, and match demands were not significantly associated with a reduction in performance (τ b = -0.04 to -0.01 and τ b = -0.27 to 0.21). Short lever hip adduction results showed nonsignificant reductions ( p > 0.05) in the 60-89 minutes group, but significant decreases ( p < 0.001) were observed for the dominant limb, nondominant limb, and total score in the 90-110 minutes condition. However, minutes played and match demands were not significantly associated with reduction in adductor isometric strength (τ b = 0.18-0.22 and τ b = -0.15 to 0.11). Subjective measures revealed significant reductions in sleep quality ( p < 0.05) and composite scores ( p < 0.001), and significant increases in muscle soreness ( p < 0.001) across both conditions. Mood was only significantly reduced ( p < 0.05) in the 90-110 minutes condition. No significant associations were found between minutes played, match demand, and self-reported subjective scores (τ b = -0.07 to 0.05 and τ b = -0.09 to 0.00).

Cantwell, CJ, Schroeder, ZS, Marshall-Ciochon, LK, Campbell, BA, Taber, CB, and Suchomel, TJ. Force production and barbell velocity characteristics across multiple sets of different accentuated eccentric loading conditions. J Strength Cond Res 40(2): 127-135, 2026-The purpose of this study was to examine the impact that multiple accentuated eccentric loaded (AEL) back squat sets have on force production and barbell velocity characteristics within 2 different loading conditions. Sixteen resistance-trained men performed 3 sets of 3 back squat repetitions while using 100% of their 1 repetition maximum (1RM) during the eccentric phase of the first repetition and either 60% (100-60) or 80% (100-80) 1RM on the concentric phase of the first repetition and the eccentric-concentric phases of the subsequent 2 repetitions. Braking and propulsion net mean force, duration, and net impulse as well as mean and peak barbell velocity were compared between loading schemes and sets using a series of 2-way repeated measures ANOVA. Significantly greater propulsion net mean force and mean barbell velocity were produced during the 100-60 condition than during the 100-80 condition across all sets ( p < 0.001). In addition, significantly greater ( p < 0.001) set-averaged braking net mean force and net impulse and peak barbell velocity were produced during the 100-60 condition while greater braking and propulsion duration ( p < 0.001) and net impulse ( p = 0.031) were produced during the 100-80 condition. Within each loading condition, trivial-small differences existed across sets for all variables ( g ≤ 0.39). Multiple sets of AEL back squats can be prescribed using 100-60 and 100-80 loading schemes without negatively affecting force or velocity characteristics. Strength and conditioning practitioners may prescribe 100-60 to enhance rapid force production characteristics and 100-80 to provide a strength stimulus to enhance force development.

Tallis, J, Bolt, L, Morris, OR, Suchomel, TJ, and Eustace, SJ. Between session reliability of traditional and temporal bilateral and unilateral dynamic strength index calculations and association with sprint and change of direction performance. J Strength Cond Res 40(2): 167-179, 2026-The present study aimed to (a) evaluate the between session reliability of traditional and temporal based bilateral and unilateral dynamic strength index (DSI); (b) determine the association between DSI and sprint and change of direction performance in participants clustered by DSI root metrics. Thirty-eight recreationally active male participants (age: 23.4 ± 3.4 years) completed 20-m sprints, 5-0-5 change of direction test, bilateral and unilateral countermovement jumps (CMJ), and isometric midthigh pulls (IMTP) on 2 occasions. Vertical ground reaction force profiles were assessed to determine traditional DSI (DSI T ), DSI based on mean force achieved after 100 milliseconds (DSI 100 ), 150 milliseconds (DSI 150 ), the entire CMJ propulsive phase (DSI P ), and CMJ propulsive impulse (DSI I ). Bayesian interclass correlation coefficients and multiple linear regression after K-means clustering were used to analyze the data. Between session reliability of DSI was poor-moderate (interclass correlation coefficient [ICC] = 0.24-0.76) and highest for DSI T measures, albeit with some uncertainty (95% Higher Density Intervals [HDI]: 0.53-0.87). Bilateral temporal based DSI reliability was greater compared with unliteral equivalents, and temporal based DSI calculated for the nondominant limb, and those determined over a small-time epoch for the dominant limb were poor. There was limited association across DSI measures and straight-line 20-m sprint and 5-0-5 change of direction performance test. DSI 100 for the dominant side had the strongest association with the performance outcomes ( R2 = 0.33-0.36) and was improved in participants that expressed higher CMJ peak propulsive force. Dynamic strength index should be used with caution with respect to exercise prescription for the intention of improving tasks requiring rapid horizontal center of mass translation.

Molecular dynamics simulations were employed to investigate the transfer and detachment energies of graphene oxide (GO) and pristine graphene sheets at liquid-liquid and solid-liquid interfaces. Using the umbrella sampling technique, the potential of mean force profiles were calculated to assess how the degree of oxidation of the GO sheets, the chemistry of the surface of a sandstone rock, and the nature of reservoir fluids influence these processes. Water and toluene were selected as the aqueous and crude oil models of the reservoir fluids, respectively, while the (001) crystallographic plane of the α-quartz at Q3 and Q4 saturations was used to mimic the sandstone surface. The results revealed that the Q3 surface, rich in silanol groups, is hydrophilic while the Q4 surface, composed of siloxane, exhibits hydrophobic behavior. GO sheets display interfacial activity that increases with the degree of oxidation, promoting solubility in the aqueous model and reducing the affinity for the crude oil model. Conversely, pristine graphene is non-interfacially active and preferentially resides in the toluene. On the other hand, the detachment of the sheets from the rock surface is strongly dependent on its surface chemistry, the degree of oxidation of the sheet, and the characteristics of the reservoir fluid. The detachment of GO and pristine graphene is energetically most favorable from the Q3-aqueous model interface (free energy of less than 12.8 kcal/mol), followed by the Q4-crude oil model interface (free energy of less than 53.8 kcal/mol). The highest detachment energies occur from the Q3-crude oil model and Q4-aqueous model interfaces (free energy of less than 90.7 kcal/mol), with inverse trends in sheet behavior, highlighting the complex interplay of interfacial interactions.

The use of generative machine learning models, trained on the experimentally resolved structures deposited in the protein data bank, is an attractive approach to sampling conformational ensembles of proteins. However, the ensembles generated by these models lack time scale or causal information. We use the structural ensembles generated from AlphaFold2 at a range of MSA depths to parametrize the potential of mean force of an overdamped, memory-free, coarse-grained Langevin equation. This approach couples the AlphaFold2 ensembles to a causal model, allowing us to estimate the time scales spanned by the ensembles generated at each MSA depth. Performing this analysis on six variants of HIV-1 protease, we confirm an inverse relationship between MSA depth and the time scale of an ensemble's conformational fluctuations. The MSA depth essentially serves as a conformational restraint, and AlphaFold2 is generally able to probe time scales at or below those seen in microsecond-long, unbiased molecular dynamics simulations. We conclude by generalizing this approach to other generative structural ensemble-prediction methods as well as cofolding models, in this case, the biologically functional HIV-1 protease dimer.

We have formulateda Riemannian framework for describing the geometryof collective variable (CV) spaces in molecular simulations and demonstrateits applicability through both toy model potentials and a biomolecularexample. This formalism addresses significant theoretical challengesarising from the inherent nonlinearity of CV transformations, ensuringcritical quantities such as the potential of mean force (PMF), minimumfree energy path (MFEP), and rate constant remain invariant undercoordinate transformations. Our framework identifies and addressesthe noninvariance issues of conventional PMF definitions, clearlyillustrating their limitations through simple illustrative examples.To overcome these issues, we introduce invariant definitions of PMFand MFEP using Riemannian geometry. Moreover, we propose a generalizedRiemannian diffusion model applicable to diffusive dynamics withinCV spaces, allowing rigorous estimation of kinetic properties. Throughthis model, we derive practical numerical methods for determiningthe PMF, diffusion constant, metric tensor, and transition rates fromunbiased simulations conducted along identified transition pathways.By integrating Bayesian approaches with the Riemannian framework,our method provides a statistically robust technique for accuratelycalculating free energy landscapes and transition kinetics, therebyenhancing the reliability and interpretability of biomolecular simulations.