Browse Articles

Development of a high-speed planetary gearbox for an electric vehicle

Threshold-based artefact correction methods influence heart rate variability measurements in individuals with type 2 diabetes mellitus

Impact of sedentary behavior and physical activity on stroke risk in a cohort of patients with silent brain infarction

Linking lipid profile alterations to antibiotic tolerance and natural product synergy in drug-resistant Mycobacterium tuberculosis clinical isolates

Abstract Despite global control efforts, tuberculosis remains the leading infectious cause of death, with rising incidence, pediatric cases, and drug-resistant strains posing major public health challenges. Mycobacteria, including Mycobacterium tuberculosis , possess a lipid-rich, dual-membrane cell envelope that contributes to their impermeability, drug resistance, and unique pathogenic mechanisms. Some lipids play key roles in modulating host immune responses, enabling survival within macrophages, and promoting granuloma formation. Since it is known that lipid remodeling of the cell envelope is correlated with the antibiotics tolerance in mycobacteria we used liquid chromatography coupled to mass spectrometry to analyze the lipid profiles of M. tuberculosis clinical isolates with diverse drug-resistance characteristics in order to investigate if there is any link between Mtb lipids composition, its drugs susceptibility and the antimycobacterial activity of natural small molecules used in combination with first line antibiotics. The results showed that among cross combinations of antibiotics and natural products (piperine and thymoquinone) the potentiation of antimycobacterial activity was obtained in all strains only for rifampicin. Drug-resistant isolates presented the shift in glycerophospholipids building the inner membrane towards molecules with shorter acyl chains, but the decreased membrane hydrophobic thickness was compensated in some strains by increased membrane rigidity. The pXDR/XDR isolates accumulated mycobactins loaded iron and showed dysregulation in the production of phthiocerol/phthiodiolone dimycocerosates and triacylglycerols.

Blasting ore size detection based on efficient dehazing network and multi-dimensional feature fusion

Abstract Ore particle size distribution is an important metric for evaluating blasting outcomes and affects the energy consumption of ore crushing equipment. Faced with dense accumulation of ore, nonuniform size distributions, dust occlusion, and target loss due to motion, using computer vision methods, we propose a blasting ore size detection method based on efficient dehazing network and multi-dimensional feature fusion, which is an improvement to YOLOv8. Firstly, we constructs an efficient defogging backbone network that combines feature attention and composite scalable backbone so that the model can efficiently extract the features of ore images and enhance the robustness of the model to dust interference in the ore crushing process. Secondly, we introduces a new feature fusion network that combines the convolution model and the Vmamba sequence model as well as cross-layer fusion of multi-scale features so that the model can effectively adapt to the dramatic scale change of blasting ore, capture fine ore and large-size ore, avoid ore omission, and improve the accuracy of particle size statistics. Finally, the multi-dimensional feature fusion ability of Dynamic Head was introduced to optimize the target detection head, and the feature fusion was further optimized so that the feature tensor obtained from the ore image was adapted to the detection and positioning task of ore, and the discrimination ability of the model for ore was improved. Experiments were conducted on a manually labeled jaw fracture ore dataset. Compared to the YOLOv8n algorithm, the average precision ( $$\overline{P}$$ ) for detecting eight size categories of ore increased by 7%. On datasets containing interference such as smoke, dust, and wet conditions, the mean average precision at the IoU threshold of 0.5 (mAP50) improved by 7.6%. For fine ores below D5 (72 mm), the detection precision ( $$\overline{P}$$ ) increased by 18.8%, while the recall rate ( $$\overline{R}$$ ) rose by 13.8%. On the total one-class dataset, the recall rate ( $$\overline{R}$$ ) and mAP50 reached 84% and 88.1%, respectively.

Predicting FOX gene candidates for oxic nitrogen fixation using multi-omic machine learning and comparative bioinformatics

IoT framework for sports activity safety monitoring based on wearable sensors and CRNN spatiotemporal analysis

Molecular conical intersections with odd electron number are realizations of the topological Yang monopole

The two-level conical intersection of a molecule with an odd electron number in the absence of a magnetic field obeys time-reversal symmetry T2 = −1 (referred to as the T2 = −1 conical intersection) and has a five-dimensional branching space due to the Kramer degeneracy. Similar to how the conical intersection of a molecule in a magnetic field (T2 = 0) behaves as the Dirac monopole, the T2 = −1 conical intersection behaves as the Yang monopole, a mathematical generalization of the Dirac monopole with SU(2) gauge field and SO(5) symmetry. This implies that we can study the topological properties of T2 = −1 conical intersections in chemistry based on what is known about the Yang monopole in high energy physics. In this work, we present a few mathematical tools to study this connection. First, we show that geometric algebra and quaternion numbers together provide a natural way to utilize the T2 = −1 time reversal symmetry and the SO(5) symmetry in scaled coordinates, making it simple to derive eigenfunctions, Berry connection, and Berry curvature of T2 = −1 conical intersection. In particular, this approach provides a simple proof that when viewed from the upper or lower states, the T2 = −1 conical intersection behaves as the self-dual or self-antidual Yang monopole with second Chern number C2=+122 or −122, respectively. In addition, we propose a visualization method for the SU(2) Berry connection of T2 = −1 conical intersection. This is achieved by showing that the non-zero part of the Berry connection induces a Hopf-fibration on the S3 longitude space, which is further visualized through stereographic projection.

Energy-dependent selective bond cleavage induced by low-energy electrons in DNA films deposited from buffered solutions: Insights from XPS

In this study, we investigated chemical modifications caused by low-energy electrons (LEEs) in DNA films deposited from Tris-EDTA (TE) buffered solutions, using x-ray photoelectron spectroscopy (XPS). DNA samples were exposed to 9.2, 4.2, and 0.2 eV electrons for up to 8 h. XPS revealed the energy- and site-specific selective cleavage of chemical bonds as observed in C 1s, N 1s, O 1s, and P 2p spectra. At 9.2 and 4.2 eV, LEE irradiation significantly induced the cleavage of C–N bonds in N-glycosidic linkages and C–O bonds in the sugar-phosphate backbone. The selective cleavage of C–N and C–O bonds may lead to the generation of apurinic/apyrimidinic sites and produce damage to the sugar–phosphate backbone and sugar moiety. In contrast, other structures, including the phosphate groups (P=O) within the DNA backbone, remained relatively stable. Non-significant spectral or compositional changes were observed at 0.2 eV. The TE components remain chemically stable during irradiation; however, experimental results suggest that it may help increase the yield of selective DNA damage. Our findings contribute to a deeper mechanistic understanding of LEE-induced biomolecular damage and support the development of LEE-based cancer radiotherapy.

Thermodynamics of hard-sphere plus square-well trimer fluids. A small mystery

The aim of this work is to show that the thermodynamics of some simple fluids, composed of molecules formed by only three atoms—trimers—presents a challenge when confronted with molecular simulation results. Thermodynamic perturbation theory (TPT), coupled to statistical associating fluid theory (SAFT), has successfully accounted for the properties of quite complicated and realistic fluids, both pure and mixed. It is then surprising that simple fluids, formed by trimers with square-well (SW) and hard-sphere (HS) atoms, reveal severe limitations of such theories. TPT1 and SAFT show how to calculate the free energy of the trimer fluid involving HS and SW atoms. The reference system in TPT-SAFT is a fluid made of isolated atoms. Its free energy is dealt with by the well-known high-temperature expansion (HTE), treated here to the fourth order. The trimerization contribution according to TPT—called the chain term—accounts for the change in free energy as the atoms bind and depends on the cavity function, which is determined here by a novel and consistent procedure. We studied the SW–SW–SW and SW–HS–SW trimers. The main properties analyzed are vapor–liquid (VL) coexistence and critical points. The theory presented here accounts very well for the VL coexistence of the SW–SW–SW trimers but fails for the SW–HS–SW trimer, for which a strong disagreement appears. We analyze the cause of this flaw in the theory and introduce a successful semi-empirical correction to it. The possible cause is pointed out and is currently being investigated.

Revealing the microhydration mechanisms of <i>α</i> -hydroxy carboxylic acids: Identification of large-amplitude torsional and librational motion

The molecular recognition mechanisms associated with the self-aggregation and microhydration processes of two different bifunctional α-hydroxy carboxylic acids, prototypical glycolic acid [CH2OHCOOH] and the doubly methylated variant 2-hydroxyisobutyric acid [(CH3)2C(OH)COOH], have been investigated by low-temperature mid- and far-infrared cluster spectroscopy of doped low polarizability neon matrices at 4 K, complemented by systematic theoretical conformational sampling refined with high-level electronic structure theory at the DLPNO-CCSD(T)/aug-cc-pV5Z level. Several mid-infrared perturbed vibrational fundamentals together with specific far-infrared vibrational fundamentals associated with large-amplitude, anharmonic hindered intramolecular torsional and intermolecular librational (hindered overall rotational) motion of the α-hydroxy carboxylic acid monohydrates are unambiguously assigned based on a combination of mixing ratio dependencies, thermal annealing, and the use of isotopically enriched H218O and D2O samples. These direct experimental spectroscopic probes of the formed intermolecular hydrogen bond motifs validate high-level quantum chemical predictions that the global intermolecular potential energy minima configurations involve six-membered cyclic cooperatively hydrogen-bonded C=O⋯H–Owater⋯H–Oacid “insertion” sequences in the monohydrate species of both α-hydroxy carboxylic acid analogues.

Spin localization in intermolecular complexes: A challenge for semi-local approximants for the embedding potential

Regardless of how the electron correlation is treated, all methods based on frozen-density embedding theory rely on approximations to the non-additive kinetic potential bi-functional ṽtnad[ρA,ρB](r)≈vtnad[ρA,ρB](r). Open shell systems, in which the spin is localized on a specific molecular fragment, are particularly prone to incorrect redistribution of charge depending on the used ṽtnad[ρA,ρB]. In this work, we present a systematic analysis of spin densities obtained with several semi-local approximations to vtnad[ρA,ρB], with the aim of delimiting their respective domains of applicability. We show that spin distributions obtained using decomposable semi-local ṽtnad[ρA,ρB] fall into two distinct categories: they are either qualitatively incorrect or reasonably accurate and consistent with trends previously observed for other properties computed using the same approximants. In neither case do gradient-dependent corrections, although crucial for improving the corresponding energy bi-functional (Tsnad[ρA,ρB]), resolve the deficiencies observed for spin densities. We propose a simple criterion based on orbital energies that allows one to identify a priori the situations in which a given approximant is likely to fail. Finally, we show that a recently developed non-decomposable approximant ṽtnad(NDCS)[ρA,ρB] extends the range of applicability of FDET-based methods to embedded radicals that are inaccessible to semi-local approximants. Moreover, ṽtnad(NDCS)[ρA,ρB] yields improved spin densities even in cases where decomposable semi-local approximants already perform reasonably well.

On the importance of numerical integration details for homogeneous flow simulation

The Sllod equations of motion enable modeling of homogeneous flow at the atomic scale and are commonly used to predict fluid properties such as viscosity. However, few publicly available codes support such simulations, and those that do often include subtle problems in the numerical integration scheme or related aspects, which result in a failure to conserve the energy of the extended system. Here, we demonstrate a reversible and energy-conserving integration scheme for the Sllod equations of motion with error on the order of δt3, in line with typical operator splitting integrators used in standard molecular dynamics simulations. We discuss various implementation details and implement the scheme in LAMMPS, where we find that our changes enable more accurate simulation of transient responses, mixed flows, and steady states, especially at high rates of flow. Importantly, we show that a lack of energy conservation can manifest as a systematic error in the direct ensemble average of the pressure tensor, leading to an error in the calculated viscosity which becomes significant at high flow rates.

Regional chemical potential analysis for material surfaces

We propose a local regional chemical potential (RCP) analysis method based on an energy window scheme to quantitatively estimate the selectivity of atomic and molecular adsorption on surfaces, as well as the strength of chemical bonding forces between a probe tip and a surface in atomic force microscopy (AFM) measurements. In particular, focusing on the local picture of covalent bonding, we use a simple H2 molecular model to demonstrate a clear relationship between chemical bonding forces and the local RCP. Moreover, density functional theory calculations on molecular systems and diamond C(001) surfaces reveal that the local RCP at the surfaces successfully visualizes electron-donating regions such as dangling bonds and double bonds. These results suggest that the local RCP can serve as an effective measure to analyze high-resolution non-contact or near-contact AFM images enhanced by chemical bonding forces. Analogous to the Tersoff–Hamann approach widely used for simulating scanning tunneling microscopy images, the RCP analysis method provides a practical and computationally efficient framework for interpreting AFM images.

sbml4md: A computational platform for system–bath modeling via molecular dynamics powered by machine learning

We introduce sbml4md, a newly developed algorithm implemented as a software package to extract parameters of multimode anharmonic Brownian models from molecular dynamics (MD) trajectories for simulating nonlinear vibrational spectra of intramolecular modes of molecular liquids. By leveraging machine learning (ML) techniques to capture vibrational anharmonicity, intermolecular couplings, and bath correlation functions for each mode, sbml4md obviates empirical fitting and enables the modeling of environments with spatial and temporal heterogeneity. This work provides a set of parameters specifically tailored for the Hierarchical Equations of Motion (HEOM) framework, enabling numerically “exact” simulations of nonlinear vibrational spectra. Building upon our previous implementation for intramolecular vibrational modes [K. Park, J.-Y. Jo, and Y. Tanimura, J. Chem. Phys. 163, 214104 (2025)], the present code enhances optimization efficiency by explicitly accounting for intermolecular vibrational contributions. This extension enables sbml4md to broaden the applicability of HEOM-based dynamical modeling by seamlessly integrating classical MD approaches, thereby providing a flexible and scalable framework for simulating both linear and nonlinear spectra under realistic conditions with minimal empirical input. The accompanying ML code, written in Python, is provided as the supplementary material.

Physical mechanisms of nanoparticle–membrane interactions: A coarse-grained study

Nanoparticles are promising drug carriers for targeted therapies, diagnostic imaging, and advanced vaccines. However, their clinical translation is limited by complex biological barriers that reduce cellular uptake and efficacy. In particular, the interaction with the cellular membrane controls nanoparticle adhesion, wrapping, or full engulfment, which ultimately governs nanoparticle internalization efficiency. Flexible nanocarriers (e.g., liposomes, polymeric nanogels, and micelles) are particularly attractive because their deformability could help them enhance the probability of successful cellular entry. To understand the physical mechanisms associated with cellular uptake, we investigate the interaction of semi-flexible nanocarriers with a symmetric lipid bilayer using coarse-grained simulations. We represent a flexible nanoparticle using the previously introduced metaparticle model and the membrane using the Cooke–Deserno model. By systematically varying nanoparticle properties, i.e., adhesion strength and topology, we identify distinct interaction regimes ranging from surface adhesion and trapping to complete wrapping and endocytosis. These regimes correlate with nanoparticle shape, size, and surface properties, providing quantitative design principles for optimizing cellular uptake. Overall, this framework offers predictive insight into how the interplay between nanoparticle properties and membrane interaction governs cellular internalization, informing the rational design of next-generation soft nanocarriers and smart materials.

Pressure-induced p <i>K</i> a variations influence conformations of pH-sensitive polymers

Conformations of aqueous macromolecules depend on a delicate balance of hydrophobic, electrostatic, and hydrogen-bonding interactions, all of which are influenced by environmental factors such as pressure and pH. Understanding how these factors modulate structural stability is critical for both biological and material science applications. Here, we use constant-pH molecular dynamics simulations to investigate the pressure response of a short, pH-sensitive polymer in explicit solvent. Our results reveal that increasing pressure unfolds both neutral and charged polymers, but the degree of unfolding is markedly reduced when the polymer carries a charge, demonstrating the coupling of pressure and charge regulation. At pH = pKa, we observe a pressure-dependent transition from neutral-like behavior at low pressure to charged-like behavior at high pressure, a signature of pressure-induced pKa shifts. Additionally, pressure-induced unfolding is enhanced at this pH. Extending our study to a model polyampholyte with one acidic and one basic monomer, we find clear evidence of non-additive acid–base coupling that stabilizes collapsed states at low pressure, as well as pressure-induced salt-bridge denaturation at high pressure. This behavior reveals a competition between electrostatic stabilization and pressure-driven hydration effects. These findings shed some light on the pressure-modulated macromolecular behavior of charged and neutral polymers and provide insights relevant to both synthetic polymers and pressure-adapted biological systems.

Deriving effective electrode–ion interactions from free-energy profiles at electrochemical interfaces

Understanding ion adsorption at electrified metal–electrolyte interfaces is essential for accurate modeling of electrochemical systems. Here, we systematically investigate the free energy profiles of Na+, Cl−, and F− ions at the Au(111)–water interface using enhanced sampling molecular dynamics with both classical force fields and machine-learned interatomic potentials (MLIPs). Our classical metadynamics results reveal a strong dependence of predicted ion adsorption on the Lennard-Jones parameters, highlighting that—without due care—standard mixing rules can lead to qualitatively incorrect descriptions of ion–metal interactions. We present a systematic methodology for tuning the cross term LJ parameters to control adsorption energetics in agreement with more accurate models. As a surrogate for an ab initio model, we employed the recently released Universal Models for Atoms MLIP, which validates classical trends and displays strong specific adsorption for chloride, weak adsorption for fluoride, and no specific adsorption for sodium, in agreement with experimental and theoretical expectations. By integrating molecular-level adsorption free energies into continuum models of the electric double layer, we show that specific ion adsorption substantially alters the interfacial ion population, the potential of zero charge, and the differential capacitance of the system. Our results underscore the critical importance of force field parameterization and advanced interatomic potentials for the predictive modeling of ion-specific effects at electrified interfaces and provide a robust framework for bridging molecular simulations and continuum electrochemical models.

Many roads to the seam: How conformational flexibility drives nonadiabatic relaxation in a prototypical tetrapyrrolic chromophore

Large and structurally flexible chromophores pose challenges for in silico modeling of photodeactivation due to the many vibrational modes that can funnel the system toward energy degeneracy. In this work, we examine how the multiple degrees of freedom in biliverdin, a prototypical tetrapyrrolic chromophore, cooperate to drive access to the S1/S0 intersection seam in vacuo. We begin by mapping the ground-state potential energy surface to identify representative biliverdin conformers relevant to photoexcitation. We then use a CASSCF-based framework to map the excited-state landscape and characterize the intersection seam, identifying distinct conical-intersection types. Finally, we employ ab initio multiple spawning to resolve the dynamical pathways by which the system accesses these regions. DFT potential-energy and free-energy mappings indicate that, although several conformers are relevant, the “locked-helix” ZsZsZs conformer predominates in the ground state. The intersection seam comprises numerous geometrically distinct regions characterized by varying degrees and combinations of dihedral torsion, pyramidalization, and bond-length alternation. Yet only select regions lie within energetic reach, and moderate barriers separate them from the S1 minimum. Nonadiabatic dynamics combined with multivariate analyses show that, despite extensive mode coupling during deactivation that guides the system toward multiple regions of the seam, a single dihedral torsion, together with bond-length alternation, predominantly drives energy degeneracy. This work offers new insight into biliverdin’s intrinsic photochemical response and underscores a general feature of flexible chromophores: many modes may participate during photorelaxation, but only a limited subset ultimately dictates seam accessibility.

Sequence-encoded patterning of stickers modulates biomolecular condensate reconfiguration in IDP systems

Intrinsically disordered proteins (IDPs) exert pivotal roles in Phase Separation Coupled to Percolation (PSCP), a process that drives the formation of functional biomolecular condensates linked to diverse cellular physiological activities. In this study, we investigate how sequence-encoded mesoscopic patterning modulates PSCP in IDP systems by leveraging the classic stickers-and-spacers framework, combined with coarse-grained molecular dynamics simulations. Intriguingly, our analysis demonstrates that the distribution of stickers plays important roles: compactness of sticker arrangement on IDPs exerts a substantial influence on IDP clustering process, while the patterning heterogeneity of the arrangement additionally impacts the morphology of the resulting aggregations. Subsequent findings elucidate that sparse and homogeneous stickers facilitate the emergence of robust aggregation, whereas proximal sequential organization directly induces dispersed and small clusters. These discoveries are validated through the statistical quantification of void volume fraction ϕvoid (serving as a referential measure for condensate maturation) in conjunction with the quantification of the total stickers present on the cluster surfaces. Collectively, this work may shed new lights on the underlying mechanism for regulating IDP-mediated phase separation.