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Toward mitigating the impact of non-bulk defects on describing water structure in salt aqueous solutions: Characterizing solution density with a network-based structural indicator

Structural indicators, also known as structural descriptors, including order parameters, have been proposed to quantify the structural properties of water to account for its anomalous behaviors. However, these indicators, mainly designed for bulk water, are not naturally transferrable to the vicinity of ions due to disruptions in the immediate neighboring space and a resulting loss of feature completeness. To address these non-bulk defects, we introduced a structural indicator that draws on the concept of clique number from graph theory and the criterion in agglomerative clustering, denoted as the average cluster number. This structural indicator aims to discern intrinsic structural characteristics within the water molecules regardless of the ions occupying the neighboring space, without requiring additional corrections. From molecular dynamics simulation results for neat water and salt aqueous solutions utilizing the TIP4P/2005 water model and the Madrid-2019 force field, we characterized the variations in densities with temperature using this network-based indicator, thereby demonstrating its practical utility. The findings suggest that at lower temperatures, the addition of ions disrupts the intrinsic structure of water molecules, with this effect diminishing as the temperature rises. Cations with larger charge density tend to induce stronger disruptions. This study highlights the importance of mitigating the impact of non-bulk defects before applying the indicators to analyze water’s intrinsic structural properties in solutions. By doing so, the relationship between changes in water structure and solution behaviors can be more accurately assessed.

Multiplicity of type 6 secretion system toxins limits the evolution of resistance

The bacterial type 6 secretion system (T6SS) is a toxin-injecting nanoweapon that mediates competition in plant- and animal-associated microbial communities. Bacteria can evolve de novo resistance against T6SS attacks, but resistance is far from universal in natural communities, suggesting key features of T6SS weaponry may act to limit its evolution. Here, we combine ecoevolutionary modeling and experimental evolution to examine how toxin type and multiplicity in Acinetobacter baylyi attackers shape resistance evolution in susceptible Escherichia coli competitors. In both our models and experiments, we find that combinations of multiple distinct toxins limit resistance evolution by creating genetic bottlenecks, driving resistant lineages extinct before they can reach high frequency. We also show that, paradoxically, single-toxin attackers can drive the evolution of cross-resistance, protecting bacteria against unfamiliar toxin combinations, even though such evolutionary pathways were inaccessible against multitoxin attackers. Our findings indicate that, comparable to antimicrobial and anticancer combination therapies, multitoxin T6SS arsenals function to limit resistance evolution in competing microbes. This helps us to understand why T6SSs remain widespread and effective weapons in microbial communities, and why many T6SS-armed bacteria encode functionally diverse anticompetitor toxins.

Swinging Pendulum Between Risks and Benefits of Antiplatelet Agents: A Call for Consistency in the Interpretation of Evidence and Guideline Recommendations

Thermodynamics of nucleosome breathing and positioning

Nucleosomes are fundamental units of chromatin in which a length of genomic DNA is wrapped around a histone octamer spool in a left-handed superhelix. Large-scale nucleosome maps show a wide distribution of DNA wrapping lengths, which in some cases are tens of base pairs (bp) shorter than the 147 bp canonical wrapping length observed in nucleosome crystal structures. Here, we develop a thermodynamic model that assumes a constant free energy cost of unwrapping a nucleosomal bp. Our model also incorporates linker DNA—short DNA segments between neighboring nucleosomes imposed by the folding of nucleosome arrays into chromatin fibers and other higher-order chromatin structures. We use this model to study nucleosome positioning and occupancy in the presence of nucleosome “breathing”—partial unwrapping and rewrapping of nucleosomal DNA due to interactions with the neighboring particles. We find that, as the unwrapping cost per bp and the chemical potential are varied, the nucleosome arrays are characterized by three distinct states, with low, intermediate, and high densities. The transition between the latter two states proceeds through an equiprobable state in which all nucleosome wrapping lengths are equally likely. We study the equiprobable state theoretically using a mean-field approach, obtaining an excellent agreement with numerical simulations. Finally, we use our model to reproduce S. cerevisiae nucleosome occupancy profiles observed in the vicinity of transcription start sites, as well as genome-wide distributions of nucleosome wrapping lengths. Overall, our results highlight the key role of partial nucleosome unwrapping in shaping the genome-wide patterns of nucleosome positioning and occupancy.

Structural basis for TIR domain–mediated innate immune signaling by Toll-like receptor adaptors TRIF and TRAM

Innate immunity relies on Toll-like receptors (TLRs) to detect pathogen-associated molecular patterns. The TIR (Toll/interleukin-1 receptor) domain-containing TLR adaptors TRIF (TIR domain–containing adaptor-inducing interferon-β) and TRAM (TRIF-related adaptor molecule) are essential for MyD88-independent TLR signaling. However, the structural basis of TRIF and TRAM TIR domain–based signaling remains unclear. Here, we present cryo-EM structures of filaments formed by TRIF and TRAM TIR domains at resolutions of 3.3 Å and 5.6 Å, respectively. Both structures reveal two-stranded parallel helical arrangements. Functional studies underscore the importance of intrastrand interactions, mediated by the BB-loop, and interstrand interactions in TLR4-mediated signaling. We also report the crystal structure of the monomeric TRAM TIR domain bearing the BB loop mutation C117H, which reveals conformational differences consistent with its inactivity. Our findings suggest a unified signaling mechanism by the TIR domains of the four signaling TLR adaptors MyD88, MAL, TRIF, and TRAM and reveal potential therapeutic targets for immunity-related disorders.

Letter by Chen et al Regarding Article, “Piezo1-Mediated Neurogenic Inflammatory Cascade Exacerbates Ventricular Remodeling After Myocardial Infarction”

A partition function estimator

We propose an estimator that allows us to calculate the value of a simple system’s partition function using finite sampling. The core idea is to neglect the contribution from high energy microstates, which are difficult to be sampled properly, and then calculate a volume correction term to compensate for this. As a proof of concept, the estimator is applied to calculate the partition function for several model systems, ranging from a simple harmonic oscillator to a Lennard-Jones fluid with hundreds of particles. Our results agree well with the numerically exact solutions or reference data, demonstrating that efficiently estimating partition functions for the studied example cases is possible and computationally affordable.

Anti-CTLA-4 generates greater memory response than anti-PD-1 via TCF-1

The effects of T cell differentiation arising from immune checkpoint inhibition targeting cytotoxic T lymphocyte–associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) on the immunological memory response remain unclear. Our investigation into the effects of anti-CTLA-4 and anti-PD-1 on memory T cell formation in mice reveals that memory T cells generated by anti-CTLA-4 exhibit greater expansion, cytokine production, and antitumor activity than those from anti-PD-1. Notably, anti-CTLA-4 preserves more T cell factor-1 (TCF-1)+ T cells during priming, while anti-PD-1 leads to more thymocyte selection-associated high mobility group box (TOX)+ T cells. Experiments using conditional Tcf7 - or Tox -knockout mice highlight that TCF-1 is essential for the memory response generated by anti-CTLA-4, whereas TOX deletion alone in T cells has no effect on the response to anti-PD-1. Deepening our understanding of how checkpoint inhibition affects memory response is crucial for advancing our understanding of the enduring impacts of these immunotherapies on the immune system.

Exercise Training in Patients With Hypertrophic Cardiomyopathy Without Left Ventricular Outflow Tract Obstruction: A Randomized Clinical Trial

BACKGROUND: Patients with hypertrophic cardiomyopathy without left ventricular outflow tract obstruction commonly experience reduced exercise capacity. Physical training improves exercise capacity in these patients, but whether the underlying effects of exercise are a result of central hemodynamic or peripheral improvement is unclear. This study assessed whether exercise training reduces left ventricular filling pressure measured during exercise in patients with hypertrophic cardiomyopathy without left ventricular outflow tract obstruction. METHODS: Between March 2019 and June 2022, patients with hypertrophic cardiomyopathy without left ventricular outflow tract obstruction were randomly assigned (1:1) to a 12-week (3 h/wk) supervised, moderate-intensity exercise training program or continued usual activity. The primary outcome was the change in invasively measured pulmonary capillary wedge pressure during mild exercise (25 W) from baseline to week 12. Pressure tracings were analyzed offline by a blinded investigator. Secondary outcomes included changes in peak oxygen consumption, cardiac index, quality of life, echocardiographic indices of diastolic function, and natriuretic peptides. RESULTS: Of 59 patients randomized (mean age, 58.1 [12.2] years; 27% women), 51 (86%) completed all follow-up assessments. At week 12, the change in 25-W pulmonary capillary wedge pressure was –2.8 (6.8) mm Hg in the exercise group, compared with +1.2 (4.9) mm Hg in the usual-activity group (between-group difference, 4.0 mm Hg [95% CI, 0.7–7.3]; P =0.018). Peak oxygen consumption improved by +1.8 (2.0) mL·kg⁻¹·min⁻¹ in the exercise group versus –0.3 (3.1) mL·kg⁻¹·min⁻¹ in the usual-activity group ( P =0.005). Exercise training improved the ventilatory efficiency (V E /VCO 2 ) slope compared with usual activity (between-group difference, 2.0 [95% CI, 0.6–3.5]; P =0.006). Peak cardiac index improved by +0.38 (1.38) L·min⁻¹·m⁻² in exercise versus –0.85 (1.20) L·min⁻¹·m⁻² in the usual-activity group ( P =0.002). Change in overall Kansas City Cardiomyopathy Questionnaire score was similar between groups. However, the change in physical limitation scores (+8.4 [12.0] points in exercise versus +0.7 [6.8] points in usual-activity group; P =0.034) and quality-of-life scores (+8.7 [18.0] points in exercise versus 0.7 [4.0] points in usual-activity group; P =0.01) differed significantly. There were no significant changes in diastolic function assessed by echocardiography or in natriuretic peptides. CONCLUSIONS: In patients with hypertrophic cardiomyopathy without left ventricular outflow tract obstruction, a 12-week moderate-intensity exercise training program resulted in reduced left ventricular filling pressures at mild exertion and improved exercise performance. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03537183.

Electric dipole moment of excited octupolar molecules: Potential qubit implementation

The first excited state of conjugated donor–acceptor molecules of C3 symmetry (octupolar molecules) is doubly degenerate. Such a doublet is known to be isomorphic to a spin 1/2. It is shown that a large electric dipole moment is associated with this spin. Since the mean value of the electric dipole moment of an octupolar molecule is a measure of the symmetry breaking charge transfer, a dimensionless dipole moment called the dissymmetry vector is introduced. The dissymmetry vector operator is constructed. A linear tensor connection between this operator and the Pauli matrices is found. The tensor character is due to the two-dimensionality of the dipole moment. The dipole moment can rotate freely in the plane of the molecule as long as the C3 symmetry is maintained. The rotation is associated only with the rearrangement of the electronic subsystem of the molecule and does not affect the spatial position of the nuclei. This opens up the possibility of changing the dipole moment state on a subpicosecond time scale. The Jahn–Teller effect on the dissymmetry vector is considered in detail. It is shown that the dissymmetry vector can be controlled using electric fields in the same way as three-dimensional spin if both static and alternating electric fields are in the plane of the molecule. The conducted studies indicate that the dipole moment of excited octupolar molecules is a promising candidate for the physical implementation of a qubit.

Cardiac Plasticity in Hypertrophic Cardiomyopathy: Exercise as Medicine?

Benchmark computations of nearly degenerate singlet and triplet states of N-heterocyclic chromophores. II. Density-based methods

In this paper, we demonstrate the performance of several density-based methods in predicting the inversion of S1 and T1 states of a few N-heterocyclic triangulene based fused ring molecules (popularly known as INVEST molecules) with an eye to identify a well performing but cost-effective preliminary screening method. Both conventional linear-response time-dependent density functional theory (LR-TDDFT) and ΔSCF methods (namely maximum overlap method, square-gradient minimization method, and restricted open-shell Kohn–Sham) are considered for excited state computations using exchange–correlation (XC) functionals from different rungs of Jacob’s ladder. A well-justified systematism is observed in the performance of the functionals when compared against fully internally contracted multireference configuration interaction singles and doubles and/or equation of motion coupled-cluster singles and doubles (EOM-CCSD), with the most important feature being the capture of spin-polarization in the presence of correlation. A set of functionals with the least mean absolute error is proposed for both the approaches, LR-TDDFT and ΔSCF, which can be more cost-effective alternatives for computations on synthesizable larger derivatives of the templates studied here. We have based our findings on extensive studies of three cyclazine-based molecular templates, with additional studies on a set of six related templates. Previous benchmark studies for subsets of the functionals were conducted against the domain-based local pair natural orbital-similarity transformed EOM-CCSD (STEOM-CCSD), which resulted in an inadequate evaluation due to deficiencies in the benchmark theory. The role of exact-exchange, spin-contamination, and spin-polarization in the context of DFT comes to the forefront in our studies and supports the numerical evaluation of XC functionals for these applications. Suitable connections are drawn to two and three state exciton models, which identify the minimal physics governing the interactions in these molecules.

Epistatic hotspots organize antibody fitness landscape and boost evolvability

The course of evolution is strongly shaped by interaction between mutations. Such epistasis can yield rugged sequence–function maps and constrain the availability of adaptive paths. While theoretical intuition is often built on global statistics of large, homogeneous model landscapes, mutagenesis measurements necessarily probe a limited neighborhood of a reference genotype. It is unclear to what extent local topography of a real epistatic landscape represents its global shape. Here, we demonstrate that epistatic landscapes can be heterogeneously rugged and this heterogeneity may render biomolecules more evolvable. By characterizing a multipeaked fitness landscape of a SARS-CoV-2 antibody mutant library, we show that heterogeneous ruggedness arises from sparse epistatic hotspots, whose mutation impacts the fitness effect of numerous sequence sites. Surprisingly, mutating an epistatic hotspot may enhance, rather than reduce, the accessibility of the fittest genotype, while increasing the overall ruggedness. Further, migratory constraints in real space alleviate mutational constraints in sequence space, which not only diversify direct paths taken but may also turn a road-blocking fitness peak into a stepping stone leading toward the global optimum. Our results suggest that a hierarchy of epistatic hotspots may organize the fitness landscape in such a way that path-orienting ruggedness confers global smoothness.

Adverse Pregnancy Outcomes and Coronary Artery Disease Risk: A Negative Control Mendelian Randomization Study

Accuracy of approximate methods for the calculation of fluorescence-type linear spectra with a complex system–bath coupling

Much can be learned about molecular aggregates by modeling their fluorescence-type spectra. In this study, we systematically describe the accuracy of various methods for simulating fluorescence-type linear spectra in a dimer system with a complex system–environment interaction, which serves as a model for various molecular aggregates, including most photosynthetic light-harvesting complexes (LHCs). We consider the approximate full cumulant expansion (FCE), complex time-dependent Redfield (ctR), time-independent Redfield, and modified Redfield methods and calculate their accuracy as a function of the site energy gap and coupling, excitonic energy gap, and dipole factor (i.e., type of spectrum). We find that the FCE method is the most accurate method for couplings smaller than 300 cm−1 at 300 K, but this method fails for very strong couplings or low temperatures due to inaccurate modeling of the equilibrium initial state. The ctR method performs well for the calculation of fluorescence and linear anisotropy spectra but poorer for circularly polarized fluorescence spectra or for all spectra when the coupling is strong (∼100cm−1). The Redfield and modified Redfield methods generally perform much more poorly than the ctR and FCE methods—especially for small excitonic energy gaps and strong couplings. We show that accurate modeling of the Stokes shift is crucial and present a version of the ctR method that treats both the Stokes shift and initial state correctly for the parameter ranges in plant LHCs. Apart from the application to LHCs, our results will be useful for the spectral characterization and design of organic molecular aggregates.

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Machine learning accelerated nonadiabatic dynamics simulations of materials with excitonic effects

This study presents an efficient methodology for simulating nonadiabatic dynamics of complex materials with excitonic effects by integrating machine learning (ML) models with simplified Tamm–Dancoff approximation (sTDA) calculations. By leveraging ML models, we accurately predict ground-state wavefunctions using unconverged Kohn–Sham (KS) Hamiltonians. These ML-predicted KS Hamiltonians are then employed for sTDA-based excited-state calculations (sTDA/ML). The results demonstrate that excited-state energies, time-derivative nonadiabatic couplings, and absorption spectra from sTDA/ML calculations are accurate enough compared with those from conventional density functional theory based sTDA (sTDA/DFT) calculations. Furthermore, sTDA/ML-based nonadiabatic molecular dynamics simulations on two different materials systems, namely chloro-substituted silicon quantum dot and monolayer black phosphorus, achieve more than 100 times speedup than the conventional linear response time-dependent DFT simulations. This work highlights the potential of ML-accelerated nonadiabatic dynamics simulations for studying the complicated photoinduced dynamics of large materials systems, offering significant computational savings without compromising accuracy.

Mutational analysis of an antimalarial drug target, <i>Pf</i> ATP4

Among new antimalarials discovered over the past decade are multiple chemical scaffolds that target Plasmodium falciparum P-type ATPase ( Pf ATP4). This essential protein is a Na + pump responsible for the maintenance of Na + homeostasis. Pf ATP4 belongs to the type 2D subfamily of P-type ATPases, for which no structures have been determined. To gain better insight into the structure/function relationship of this validated drug target, we generated a homology model of Pf ATP4 based on sarco/endoplasmic reticulum Ca 2+ ATPase, a P2A-type ATPase, and refined the model using molecular dynamics in its explicit membrane environment. This model predicted several residues in Pf ATP4 critical for its function, as well as those that impart resistance to various Pf ATP4 inhibitors. To validate our model, we developed a genetic system involving merodiploid states of Pf ATP4 in which the endogenous gene was conditionally expressed, and the second allele was mutated to assess its effect on the parasite. Our model predicted residues involved in Na + coordination as well as the phosphorylation cycle of Pf ATP4. Phenotypic characterization of these mutants involved assessment of parasite growth, localization of mutated Pf ATP4, response to treatment with known Pf ATP4 inhibitors, and evaluation of the downstream consequences of Na + influx. Our results were consistent with modeled predictions of the essentiality of the critical residues. Additionally, our approach confirmed the phenotypic consequences of resistance-associated mutations as well as a potential structural basis for the fitness cost associated with some mutations. Taken together, our approach provides a means to explore the structure/function relationship of essential genes in haploid organisms.

CG modeling of nucleosome arrays reveals the salt-dependent chromatin fiber conformational variability

Eukaryotic DNA is packaged in the cell nucleus into chromatin, composed of arrays of DNA–histone protein octamer complexes, the nucleosomes. Over the past decade, it has become clear that chromatin structure in vivo is not a hierarchy of well-organized folded nucleosome fibers but displays considerable conformational variability and heterogeneity. In vitro and in vivo studies, as well as computational modeling, have revealed that attractive nucleosome–nucleosome interaction with an essential role of nucleosome stacking defines chromatin compaction. The internal structure of compacted nucleosome arrays is regulated by the flexible and dynamic histone N-terminal tails. Since DNA is a highly negatively charged polyelectrolyte, electrostatic forces make a decisive contribution to chromatin formation and require the histones, particularly histone tails, to carry a significant positive charge. This also results in an essential role of mobile cations of the cytoplasm (K+, Na+, Mg2+) in regulating electrostatic interactions. Building on a previously successfully established bottom-up coarse-grained (CG) nucleosome model, we have developed a CG nucleosome array (chromatin fiber) model with the explicit presence of mobile ions and studied its conformational variability as a function of Na+ and Mg2+ ion concentration. With progressively elevated ion concentrations, we identified four main conformational states of nucleosome arrays characterized as extended, flexible, nucleosome-clutched, and globular fibers.