Browse Articles

Anomalous interplay of confinement, wettability, and salt concentration toward diffusion of saline water in nanochannels

Water, characterized by its anomalous behavior, is a polar fluid whose transport properties can undergo counterintuitive modifications under confinement, especially with solvated microions, resulting in significant deviations from that of bulk pure water. Despite the observation of largely divergent transport phenomena of water induced by confinement-specific effects, the intricate interactions influencing the diffusive behavior of water remain inadequately understood. We bring forth the anomalous interplay of confinement, wettability, and salt concentration on water’s self-diffusive behavior under nanoconfinement using molecular-level investigations. In addition to the markedly different self-diffusive behavior of water compared to bulk, the combined effects of these parameters are not always intuitive, resulting in non-monotonic trends in diffusivity. Our findings reveal that dissolved ionic species induce structural perturbations that alter the hydrogen bonding network and water orientation as well as compress solvation shells in confinement-dependent ways, particularly in extreme confinements. The confined ionic inclusions lead to distinct diffusive behavior that deviates from water’s typical mobility in ion-free environments. These findings reveal the hitherto unexplored inter-coupling of various factors on water’s diffusive characteristics, not only providing valuable insights into the interfacial interactions at the nanoscale but also having far-reaching implications in the fields of ultra-filtration, point-of-care diagnostics, and energy storage devices.

Semantic mapping of Hindi text-to-image generation using CUB dataset

Influence of counterion valency on the scattering properties of highly charged polyelectrolyte solutions revisited

In light of recent simulations showing the importance of hydration in the thermodynamic properties and structural organization of polyelectrolytes in solution, we revisit small-angle neutron scattering measurements examining the influence of charge valence, along with polymer concentration and mass, on the structure of model salt-free polystyrene sulfonate (PSS) solutions and basic scattering features, such as the polyelectrolyte peak and the radius of gyration and persistence length lp of the PSS molecules. In previous companion work, we showed that the replacement of monovalent by divalent counterions leads to a reduced low-angle scattering intensity related to a reduction of chain association, while the interchain correlation length within the clusters becomes larger, indicating that the divalent counterions give rise to a weakening of the interchain attractive interactions and a reduction in the slow mode relaxation time arising from ion solvation rather than enhanced molecular association. In the present work, we show that the scaling exponent describing the polymer concentration dependence of the polyelectrolyte peak position q* correspondingly changes from a magnitude near 1/2 to a value near 1/3 over a wide polymer concentration range below 1M. This change of scaling behavior with counterion valence raises questions about the hypothesis that salt-free long polyelectrolyte chains exhibit a rod-like conformation in the dilute limit. Direct contrast-matching neutron scattering measurements indicate that the polyelectrolyte chains exhibit substantially enhanced chain flexibility with the replacement of monovalent by divalent counterions. Moreover, lp was found correspondingly to scale with the salt concentration with exponents 1/2 to a value near 1/3, providing further evidence of the sensitivity of the polyelectrolyte properties to counterion valence. Collectively, these properties generally point to the importance of counterion valence and ion and polymer hydration in the properties of polyelectrolyte solutions.

Functional organization of the primary motor cortex in psychosis and the potential role of intereffector regions in psychomotor slowing

Altered psychomotor behavior in psychosis is poorly understood. Novel insights into the physiology of the motor cortex prompted a revision of the motor homunculus. Next to core motor effector areas, the primary motor cortex (M1) contains intereffector regions with more integrative connectivity patterns, suggestive of serving psychomotor behavior. Here, we test whether patterns of connectivity differ between patients with and without psychomotor slowing and which cortical areas are associated with aberrant motor behavior in psychosis. This resting-state functional MRI study included 83 patients with psychosis and psychomotor slowing, 43 patients without psychomotor slowing, and 63 matched healthy subjects. We tested group differences in connectivity and regressed motor behavior measures with connectivity in patients with psychomotor slowing. Across subjects, we found distinct rs-fMRI connectivity profiles of the intereffector areas in M1, extending to premotor cortices and cerebellum. Patients with psychomotor slowing had stronger connectivity from the intereffectors than controls or patients without slowing. Finally, motor behavior correlated with connectivity from M1 intereffector regions in patients. Connectivity profiles of intereffectors suggest a role in planning and controlling complex behavioral repertoires. Collectively, these findings in patients with psychomotor slowing stress the importance of intereffector regions in shaping psychomotor behaviors in mental disorders.

Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile

Heterogeneous ice nucleation on model substrates

Ice nucleation is greatly important in areas as diverse as climate change, cryobiology, geology, or food industry. Predicting the ability of a substrate to induce the nucleation of ice from supercooled water is a difficult problem. Here, we use molecular simulations to analyze how the ice nucleating ability is affected by the substrate lattice structure and orientation. We focus on different model lattices, namely, simple cubic, body centered cubic, and face centered cubic, and assess their ability to induce ice nucleation by calculating nucleation rates. Several orientations are studied for the case of the face centered cubic lattice. Curiously, a hexagonal symmetry does not guarantee a better ice nucleating ability. By comparing the body centered cubic and the cubic lattices, we determined that there is a significant role of the underlying crystal plane(s) on ice nucleation. The structure of the liquid layer adjacent to the substrate reveals that more efficient nucleants induce a more structured liquid. The most efficient substrates present a strong sensitivity of their ice nucleating ability to the lattice parameters. Introducing a novel methodological approach, we use classical nucleation theory to estimate the contact angle of the ice nucleus on the studied substrates from the calculated nucleation rates. The method also provides the nucleation free energy barrier height, the kinetic pre-factor, and the critical cluster size. The latter is in agreement with the nucleus size obtained through a microscopic analysis of the nucleation trajectories, which supports the validity of classical nucleation theory down to small critical clusters.

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Distinct roles of amniotic membrane epithelial (hAEC) and mesenchymal stromal cells (hAMSC) in amniotic membrane-driven wound healing

Abstract Human skin wound healing is a complex process involving sequential cellular events to restore skin integrity. Chronic wounds fail to heal due to impaired keratinocyte activation and dysregulated cytokine signaling. The human amniotic membrane (hAM), a perinatal derivative, is widely used in hospitals due to its therapeutic effects on wound healing. hAM contains two main cell types: human Amniotic Epithelial Cells (hAEC) and human Amniotic Mesenchymal Stromal Cells (hAMSC). This study isolated and cultured both cell types, using their conditioned media in assays for cell migration, proliferation, and TGF-β cell-cycle arrest rescue. While hAEC-conditioned media only had similar effects to hAM in cell migration, hAMSC-conditioned media demonstrated superior efficacy in this and other assays. These findings suggest that hAMSC are the primary contributors to AM’s beneficial effects in chronic wound healing, highlighting their potential for targeted therapeutic applications.

The quantification of polyelectrolyte charge density effect on the chain segment dynamics of polymer nanocomposites of ultra-small nanoparticles

The complexation with ultra-small nanoparticles brings in great opportunity in polymer nanocomposite research due to the significantly varied chain dynamics from their extremely high specific surface area; however, the system complexity hinders the quantitative understanding of their structure–property relationship. Herein, polymers with varied quenched charge distribution are ionically complexed with 2 nm anionic metal oxide clusters ([NaP5W30O110]14−), while broadband dielectric spectroscopy is applied to probe the chain segment dynamics to quantify the effect of charge interaction. As suggested by x-ray scattering analysis, the homogeneous and molecular scale distribution of the particles can be achieved with the integrity of the molecular structures. With increased charge densities, no obvious glass transition process can be observed, while the temperature dependence of the chain segment dynamics transitions from Vogel–Fulcher–Tammann to Arrhenius type due to the enhanced confinement from increased ionic attraction strength. The time–charge density superposition of the system is proposed and verified for the unified understanding of chain relaxation dynamics of ionic nanocomposites.

Gating of immune-triggered cell death is a redox rhythm–specific output

Exploring the exact solutions to the nonlinear systems with neural networks method

RANGE: A robust adaptive nature-inspired global explorer of potential energy surfaces

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directly or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. Our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.

Quantifying cell traction forces at the single-fiber scale in 3D: An approach based on deformable photopolymerized fiber arrays

The forces exerted by cells upon the fibers of the extracellular matrix play a decisive role in cell motility in physiopathology. How the local physical properties of the matrix (density, stiffness, orientation) affect cellular forces remains, however, poorly understood. Existing approaches to measure cell three-dimensional (3D) traction forces within fibrous substrates lack control over the local properties and rely on continuum approaches, not suited for measuring forces at the scale of individual fibers. Herein, an approach is proposed to fabricate multilayer arrays of suspended deformable fibers spanning a wide range of fine-tunable geometrical and mechanical properties using two-photon polymerization. Atomic Force Microscopy is used to thoroughly investigate the properties of individual fibers, including Young’s modulus and stiffness. This approach is combined with a reference-free method for measuring traction forces in 3D, which relies on automated segmentation of the fibers coupled with finite element modeling. The force measurement pipeline is applied to study forces exerted by endothelial cells, fibroblasts, or macrophages, and reveals how these forces are influenced by fiber density and stiffness. Additionally, coupling to fast volumetric imaging with lattice light-sheet microscopy enables the measurement of the low-intensity and short-lived tractions exerted by amoeboid cells, such as dendritic cells. Our technology will be instrumental for monitoring and studying cell behavior at the single-fiber level at extracellular matrix density interfaces, which play a crucial role in both physiological and pathological contexts, such as tumor boundaries.

Enhanced nitrate removal from aqueous solutions using amine-functionalized biowaste-derived adsorbent

Abstract Nitrate ions constitute one of the major nitrogen resources for plant growth. However, the large amount of nitrate ions released into nearby waterbodies could cause eutrophication problems. This study developed a bio-based adsorbent from biowaste materials and functionalized it with amine groups through the Mannich reaction. The successful modification was confirmed using FTIR, SEM, and elemental analysis. Batch adsorption experiments were conducted under varying conditions, including contact time, pH, and initial nitrate concentration. Results showed that the amine-functionalized bio-adsorbent exhibited an enhanced capacity for nitrate removal, with a maximum adsorption capacity of 65.79 mg g−1. Electrostatic interactions between amine-functionalized bio-adsorbent and nitrate ions were identified as the dominant sorption mechanism. These findings highlight the potential of this bio-based adsorbent as a sustainable and effective solution for nitrate removal from contaminated water sources.

Successive chiral transfer from molecular to mesoscopic scale in a controlled 2D hierarchical nanostructure on Ag(111)

The understanding of the transferring of chiral information across wide dimensions is vital for both fundamental chemistry and biological processes. In this article, we successfully synthesized large-scale hierarchical structures on Ag(111). The order of the hierarchical structure can be precisely modulated by adjusting the stoichiometric ratio of components, which overcomes the long-term remaining challenge. Scanning tunneling microscopy observations reveal that the ordered networks exhibit intrinsic chirality. More importantly, we observed the successive transfer of the chiral information from molecular to supramolecular and eventually to mesoscopic scale in real space at single-molecular resolution. This study not only presents a strategy for the controlled synthesis of two-dimensional chiral hierarchical superstructures but also offers fundamental insights into the mechanism of successive chiral transfer at different length scales.

Apusomonad rhodopsins: A new family of ultraviolet to blue light–absorbing rhodopsin channels

Apusomonads are sediment-dwelling bacterivorous protists that are sister to all Opisthokonta. They have been found to show a negative phototactic response to blue light, mediated by an as-yet unidentified photoreceptive system. Here, by screening available apusomonad omics data we found genes of a distinct group of microbial rhodopsins, apusomonad rhodopsins (ApuRs). ApuRs, heterologously expressed in mammalian cells, absorbed near-UV or violet light, suggesting that ApuRs could be involved in apusomonads’ photoavoidance response toward short-wavelength light. Electrophysiological measurements indicate that ApuRs are anion-selective rhodopsin channels which evolved independently of the family of channelrhodopsins widespread in other unicellular eukaryotes. In ApuRs, channel opening is triggered by photoisomerization of the retinal from its all- trans form to 13- cis and 11- cis forms. We found that intracellular proton transfer is involved in channel opening and determines the channel’s open/close kinetics. These findings expand our understanding of the photobiology of heterotrophic flagellates and demonstrate that UV-absorbing ApuRs are in fact the most blue-shifted rhodopsin channels known to date.

Identification of a novel bacteriophage attachment site into ffs, the 4.5S non-coding RNA component of the signal recognition particle

Impact of ligand (OH) deformation on LuOH+ rovibrational spectra

Triatomic cation 175LuOH+, featuring near-degenerate, opposite-parity l-doublets, offers enhanced sensitivity to P- and T-violating interactions. We present ab initio calculations of its electronic structure and rovibrational structure beyond the rigid-ligand approximation by explicitly including OH-ligand deformation together with bending and stretching motions. Potential-energy surfaces are computed at the relativistic coupled cluster level of theory. The nuclear Schrodinger equation in Jacobi coordinates is solved by means of a coupled-channel expansion. Ligand deformation reduces the bending frequency by a few percent and increases the l-doubling constant q, while the stretching frequencies and rotational constants remain largely unchanged. For the first excited bending level, we predict ΔEJ=1 = 2q ≈ 24.9–26.4 MHz. These results establish LuOH+ as a viable platform for precision searches for CP-violating physics via the electron electric dipole moment and the nuclear magnetic quadrupole moment.

A species interaction kick-starts ecological speciation in allopatry

Adaptation to different environments is thought to play a key role in speciation. However, speciation typically begins in allopatry, where reproductive isolation can also arise through neutral processes or selection unrelated to ecological differences. Disentangling the role of adaptive ecological divergence in the early stages of speciation therefore remains an important challenge in understanding the origin of new species. Here, we study threespine stickleback populations that have recently evolved in isolated postglacial lakes either in the presence or absence of prickly sculpin—a resource competitor that also shares ubiquitous trout predators with stickleback. We simulated secondary contact between several stickleback populations from these two ecological contexts in large, seminatural ponds, and genotyped offspring from 411 mating events to assess the strength of premating isolation associated with this biotic factor. Assortative mating between populations of the same ecological type (i.e., both sculpin-sympatric or both solitary) was moderate on average but ranged from weak to complete. Strikingly, and in line with a central premise of ecological speciation, the strength of premating isolation increased with increasing morphological and genomic population divergence shaped by sculpin-mediated selection. In contrast, overall phenotypic and genomic population divergence agnostic to sculpin presence/absence only poorly explained premating isolation, highlighting how ecological speciation in allopatry can be obscured by other sources of divergence. More broadly, our findings demonstrate how interactions with other ecologically similar species can play a major role in initiating and driving evolutionary trajectories toward new species, even in allopatry.

Whale optimization-based fractional order control for high-performance grid-connected photovoltaic multilevel inverters: diode-clamped versus T-type MLIs