Browse Articles

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Concurrent superimposed ice formation and meltwater runoff on Greenland’s ice slabs

Development of a spatial accuracy compensation method based on multi-beam laser interferometer

Learning mappings between equilibrium states of liquid systems using normalizing flows

Generative models and, in particular, normalizing flows are a promising tool in statistical mechanics to address the sampling problem in condensed-matter systems. In this work, we investigate the potential of normalizing flows to learn a transformation to map different liquid systems into each other while allowing at the same time to obtain an unbiased equilibrium distribution. We apply this methodology to the mapping of a small system of fully repulsive disks modeled via the Weeks–Chandler–Andersen potential into a Lennard-Jones system in the liquid phase at different coordinates in the phase diagram. We obtain an improvement in the relative effective sample size of the generated distribution up to a factor of six compared to direct reweighting. We show that this factor can have a strong dependency on the thermodynamic parameters of the source and target system.

Molecular mechanism of thyroxine transport by monocarboxylate transporters

A vision transformer based CNN for underwater image enhancement ViTClarityNet

Abstract Underwater computer vision faces significant challenges from light scattering, absorption, and poor illumination, which severely impact underwater vision tasks. To address these issues, ViT-Clarity, an underwater image enhancement module, is introduced, which integrates vision transformers with a convolutional neural network for superior performance. For comparison, ClarityNet, a transformer-free variant of the architecture, is presented to highlight the transformer’s impact. Given the limited availability of paired underwater image datasets (clear and degraded), BlueStyleGAN is proposed as a generative model to create synthetic underwater images from clear in-air images by simulating realistic attenuation effects. BlueStyleGAN is evaluated against existing state-of-the-art synthetic dataset generators in terms of training stability and realism. Vit-ClarityNet is rigorously tested on five datasets representing diverse underwater conditions and compared with recent state-of-the-art methods as well as ClarityNet. Evaluations include qualitative and quantitative metrics such as UCIQM, UCIQE, and the deep learning-based URanker. Additionally, the impact of enhanced images on object detection and SIFT feature matching is assessed, demonstrating the practical benefits of image enhancement for underwater computer vision tasks.

Δ-model correction of foundation model based on the model’s own understanding

Foundation models of interatomic potentials, the so called universal potentials, may require fine-tuning or residual corrections when applied to specific subclasses of materials. In the present work, we demonstrate how such an augmentation can be accomplished via Δ-learning based on the representation already embedded in the universal potentials. The Δ-model introduced is a Gaussian Process Regression (GPR) model, and various types of aggregation (global, species-separated, and atomic) of the representation vector are discussed. Employing a specific universal potential, CHGNet [Deng et al., Nat. Mach. Intell. 5, 1031 (2023)], in a global structure optimization setting, we find that it correctly describes the energetics of the “8” Cu oxide, which is an ultra-thin oxide film on Cu(111). The universal potential model even predicts a more favorable structure compared with that discussed in recent density functional theory-based literature. Moving to sulfur adatom overlayers on Cu(111), Ag(111), and Au(111), the CHGNet model, however, requires corrections. We demonstrate that these are efficiently provided via the GPR-based Δ-model formulated on CHGNet’s own internal atomic embedding representation. The need for corrections is tracked to the scarcity of metal–sulfur atomic environments in the materials project database that CHGNet is trained on, leading to an overreliance on sulfur–sulfur atomic environments. Other universal potentials trained on the same data, MACE-MP0, SevenNet-0, and ORB-v2-only-MPtrj, show a similar behavior but with varying degrees of error, demonstrating the general need for augmentation schemes for universal potential models.

Energy state guides reward seeking via an extended amygdala to lateral hypothalamus pathway

Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms

Phase behavior and dissociation kinetics of lamins in a polymer model of progeria

One of the key structural proteins in the eukaryotic cell nucleus is lamin. Lamins can assemble into a two-dimensional protein meshwork at the nuclear periphery, known as the nuclear lamina, which provides rigidity and shape to the nucleus. Mutations in lamin proteins that alter the structure of the nuclear lamina underlie laminopathic diseases, including Hutchinson–Gilford Progeria Syndrome (HGPS). Experiments have shown that, compared to healthy cells, lamin supramolecular structures (e.g., protofilaments) assemble into a thicker lamina in HGPS, where they form highly stable nematic microdomains at the nuclear periphery, reminiscent of liquid crystals. This significantly alters the morphological and mechanical properties of the nucleus. In this study, we investigate the aggregation of lamin fibrous structures and their dissociation kinetics from the nuclear periphery by modeling them as coarse-grained, rod-like polymer chains confined within a rigid spherical shell. Our model reproduces the formation of multidirectional nematic domains at the nuclear surface and the reduced lamin dissociation observed in HGPS nuclei by adjusting lamin concentration, lamin–lamin (head–tail), and lamin–shell association strengths. While nematic phase formation requires relatively strong lamin–shell affinity under any non-vanishing inter-lamin attraction, the thickness of the lamina layer is primarily controlled by the head–tail association strength in the model. Furthermore, the unbinding kinetics of lamin chains from the lamina exhibit a concentration-dependent facilitated dissociation, suppressed by strong intra-lamin interactions, reminiscent of diseased nuclei. Overall, our calculations reveal the physical mechanisms by which mutations affecting native lamin interactions and concentration could lead to an abnormal nuclear lamina in laminopathic diseases.

Intermittent fasting reduces alpha-synuclein pathology and functional decline in a mouse model of Parkinson’s disease

Abstract Parkinson’s disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron degeneration and α-synuclein (aSyn) accumulation. Environmental factors play a significant role in PD progression, highlighting the potential of non-pharmacological interventions. This study investigates the therapeutic effects of intermittent fasting (IF) in an rAAV-aSyn mouse model of PD. IF, initiated four weeks post-induction of aSyn pathology, improved motor function and reduced dopaminergic neuron and axon terminal degeneration. Additionally, IF preserved dopamine levels and synaptic integrity in the striatum. Mechanistically, IF enhanced autophagic activity, promoting phosphorylated-aSyn clearance and reducing its accumulation in insoluble brain fractions. Transcriptome analysis revealed IF-induced modulation of inflammation-related genes and microglial activation. Validation in primary cultures confirmed that autophagy activation and inflammatory modulators (CCL17, IL-36RN) mitigate aSyn pathology. These findings suggest that IF exerts neuroprotective effects, supporting further exploration of IF and IF-mimicking therapies as potential PD treatments.

Robust hierarchical co-clustering for exploring toxicogenomic biomarkers and their chemical regulators

Abstract Toxicity measurement of doses of chemicals (DCs) is one of the most important tasks in toxicology studies and the drug discovery and development process. In this issue, toxicogenomic biomarkers are now playing a vital role in measuring the toxicity of DCs. Differentially expressed genes (DEGs) between DCs-treatment and control groups are considered toxicogenomic biomarkers, and associated chemicals are the regulators of DEGs. The co-clustering technique is now used extensively in toxicogenomic research to investigate co-clusters between genomic biomarkers and their chemical regulators. In the literature, there are few approaches to exploring co-clusters. The hierarchical co-clustering (HCoClust) approach is faster, simpler, and more flexible. Nevertheless, it is not robust against outlier data and there is no instruction about separating upregulatory or downregulatory co-clusters, a crucial goal of toxicogenomic data analysis. Therefore, in this article, we proposed a robust HCoClust (rHCoClust) approach and developed an r-package called “rhcoclust” for its implementation. Simulation results showed that the conventional HCoClust and the proposed rHCoClust performed equally well in detecting co-clusters in the absence of outliers, while rHCoClust performed much better than HCoClust in the presence of outliers. However, rHCoClust outperformed the bi-clustering approaches in detecting co-clusters, since bi-clustering methods only work when row and column clusters are equal, and they have no criterion for detecting upregulatory and downregulatory co-clusters. Then rHCoClust was compared with HCoClust through real data analysis and found that rHCoClust performed better than HCoClust. In the case of real data analysis, the proposed method rHCoClust identified top-ranked two DEGs-clusters (GSTA5, MGST2, GCLC, GCLM, G6PD) and (EHHADH, CYP4A1, ANGPT14, CPT1A) that were significantly expressed by the influence of top-ranked two DCs-clusters (acetaminophen_High _24.hr, nitrofurazone_High_24.hr, methapyrilene_High_24.hr) and (WY.14643_High_24.hr, clofibrate_High_24.hr, gemfibrozil_High_24.hr, benzbromarone_High_24.hr, aspirin_High_24.hr) through the glutathione metabolism (GMP) and PPAR signaling pathway (PPAR-SP) respectively. The literature review also supported these results. Thus, the proposed method would be useful to explore toxicogenomic biomarkers and their chemical regulators from the robustness point of view.

Probing intrinsic noise correlation time in non-Markovian diffusive systems

The generalized Langevin equation describes molecular motion in complex systems using memory and random noise terms. Memory effects, the inherent time correlation in random noise, significantly influence molecular diffusive behaviors. However, estimating the intrinsic noise correlation time remains challenging because of difficulties in measuring the memory term. We propose a metric to probe the noise correlation time based on the deviation between characteristic times of configurational diffusion and “diffusion motion” in the kinetic energy space. This approach stems from the observation that memory effects delay relaxation time between displacement and velocity response functions. Our metric relies solely on the velocity autocorrelation function, commonly used in experimental model parameterization. Both analytical and numerical results for various physical models demonstrate its effectiveness in probing noise correlation time. Furthermore, we apply this metric to study complex diffusive phenomena, including non-exponential relaxation in molecular hydrodynamics and anomalous diffusion in crowded environments. By comparing with system’s relaxation time, we reveal that long-range noise correlations play a key role in these non-trivial diffusive phenomena.

3,4-Dihydroxyphenylacetaldehyde synthase evolved an ordered structure to deliver oxygen to pyridoxal 5’-phosphate for cuticle assembly in the mosquito Aedes aegypti

Excess A-subunits of Shiga toxin 2a are produced in enterohemorrhagic Escherichia coli

Abstract Shiga toxins (Stx) produced by Shiga toxin-producing Escherichia coli (STEC) and enterohemorrhagic E. coli (EHEC) are ribosome-inactivating AB5 proteins that consist of one enzymatic active A-subunit (StxA) and a pentamer of non-covalently linked B-subunits (StxB). The description of Stx as an AB5 protein and the observation that A-subunits without their corresponding B-subunits also intoxicate eukaryotic cells, led to the question whether A- and B-subunits are produced in the bacteria in a 1:5 ratio or whether the A-subunit of the clinically most prominent subtype Stx2a is transcribed in excess revealing free A-subunits released in the bacterial environment. The aim of this study was therefore, to investigate the genetic and protein-based background for this observation in six Stx2a-encoding STEC and EHEC wildtype strains. For this purpose, transcriptional analysis of the Stx2a subunit genes, stxA2a and stxB2a, was performed by quantitative real-time PCR in one foodborne O113:H21 STEC isolate (strain TS18/08) and five HUS-associated EHEC strains with the serotypes O157:H7/H− (HUSEC003, HUSEC004), O103:H− (HUSEC008), O26:H11 (HUSEC018), and O104:H4 (LB226692). Contrary to the hypothesis that the A- and B-subunit genes are expressed in a ratio of 1:5 comparable to the holotoxin structure or in a ratio of 1:1 based on the operon structure, the results showed that stxA2a was expressed 1.90 ± 0.55-times stronger than the gene encoding the B-subunit, possibly indicating the presence of free A-subunits. In addition, strain-specific differences regarding the mRNA fold-changes of the A-subunit gene were observed. By use of native polyacrylamide gel electrophoresis and subsequent Western blot analysis, those single A-subunits were indeed detected in the culture supernatants of all six strains. To investigate whether the transcription ratios between A- and B-subunits observed are in a similar range as the amount of subunit proteins present after translation, a quantitative ELISA specific for StxA2a and StxB2a was established. Quantification of the subunits on protein level by use of ELISA revealed that the subunit ratio of StxA2a:StxB2a is 1.10 ± 0.20 for the strains HUSEC003, HUSEC004 and HUSEC008, but 4.63 ± 0.31 for the strains TS18/08, LB226692, and HUSEC018. The results of this study demonstrated that on both, the transcriptional and the translational level, the established 1:5 subunit ratio is not present in all investigated strains. In addition, the ratios observed after translation indicate that in some strains StxA2a subunits are even produced in higher amounts than B-subunits.

Bimodality of local structural ordering in extremely confined hard disks

By combining computer simulations and a unit cell model approach, we study the apparent bimodality of local structural ordering in a system of confined hard disks. It is shown that a two-dimensional (2D) array of hard disks being confined laterally within a quasi-1D hard wall channel of the width commensurate the bulk 2D triangular lattice at disks close packing, possesses a bimodal probability distribution for the distance between the disk’s left and right nearest neighbors. The observed feature aligns with the concept of locally favored structures intensively exploited in the studies of anomalous thermodynamic and kinetic behavior of hydrogen-bonding fluids, except that the reported case is driven by entropic bonding only. The bimodality is observed in a range of densities associated with the vicinity of freezing transition in bulk 2D hard disks, indicating a crossover from the “gas-like” to “liquid-like” state in confined quasi-1D hard disks. Such a phenomenon was not reported for bulk 2D hard disks and is physically unexpected for confined q1D hard disks.

Harnessing the β-boron effect for regioselective Ru-catalyzed hydrosilylation of internal alkynes

Abstract Metal-catalyzed hydrosilylation of alkynes is recognized as a straightforward and atom economic method for synthesizing alkenylsilanes. While substantial advancements have been made with terminal alkynes, achieving precise regio- and stereocontrol with unsymmetrical internal alkynes remains a significant challenge. In this study, we report the utilization of an intriguing β-boron effect in metal catalysis, enabling an exclusively regioselective Ru-catalyzed hydrosilylation of propargylic N-methyliminodiacetic acid boronates (B(MIDA)) to synthesize alkenylsilanes. Variations in the Ru catalyst can lead to stereo-divergency without compromising regioselectivity. Density functional theory (DFT) calculations indicate that the hyperconjugative effect of the σ(C–B) bond, which stabilizes the electrophilic metallacyclopropene intermediate with Fischer carbene character, is crucial for achieving high regioselectivity. The observed switch in stereoselectivity is attributed to the different steric effects of 1,2,3,4,5-pentamethylcyclopenta-1,3-diene (Cp*) and cyclopenta-1,3-diene (Cp) ligands in the catalyst. This method produces a diverse array of regio- and stereodefined products incorporating boryl, silyl, and alkene functionalities, each of which serves as a valuable handle for further functionalization.

Photoluminescence study of optical transitions in spinel zinc gallium oxide thin films

Macrophage-augmented intestinal organoids model virus-host interactions in enteric viral diseases and facilitate therapeutic development

Abstract The pathogenesis of enteric viral infections is attributed to both viral replication and the resultant immune-inflammatory response. To recapitulate this complex pathophysiology, we engineer macrophage-augmented organoids (MaugOs) by integrating human macrophages into primary intestinal organoids. Echovirus 1, echovirus 6, rotavirus, seasonal coronavirus OC43 and SARS-CoV-2— known to directly invade the intestine— are used as disease modalities. We demonstrate that these viruses efficiently propagate in MaugOs and stimulate the host antiviral response. However, rotavirus, coronavirus OC43 and SARS-CoV-2, but not the two echoviruses, trigger inflammatory responses. Acetate, a microbial metabolite abundantly present in the intestine, potently inhibits virus-induced inflammatory responses in MaugOs, while differentially affecting viral replication in macrophages and organoids. Furthermore, we provide a proof-of-concept of combining antiviral agent with either anti-inflammatory regimen or acetate to simultaneously inhibit viral infection and inflammatory response in MaugOs. Collectively, these findings demonstrate that MaugOs are innovative tools for studying the complex virus-host interactions and advancing therapeutic development.

Dispositional empathy as a driver of inter-individual neural phase synchrony

Abstract In social neuroscience inter-individual neural phase synchrony has become a widely studied phenomenon, and has been linked to a variety of social outcomes. However, the cognitive processes underlying the emergence of this synchrony remain largely unknown. In this study, we used a two-person face-to-face collaborative task to investigate the potential of dispositional empathy—the general tendency of an individual to imagine and experience the feelings and experiences of others—as a driver of inter-individual neural synchrony during collaboration. Electroencephalography from 46 participants was used to examine phase synchrony, measured as circular correlation coefficients, between the two interacting individuals’ brain signals. We found significant inter-brain synchrony in the high alpha, beta, and gamma frequency bands. This synchrony was particularly prominent in the inter-brain connectivity measured between central regions and a range of other regions. Furthermore, a specific dimension of dispositional empathy, namely the collaborators’ tendency to transpose themselves imaginatively into the feelings and actions of others, predicted the level of synchrony in the beta and gamma frequency bands. Hence, we demonstrate that dispositional empathy plays a significant role in the emergence of inter-individual neural phase synchrony.