Browse Articles

Bioremediation of low-density polyethylene microplastics using red microalga porphyridium purpureum: a biotechnological perspective

EQ-5D outcomes in adults with autoimmune hepatitis: A GRADE-assessed systematic review and meta-analysis

Abstract Autoimmune hepatitis (AIH) is a chronic immune-mediated liver disease that can substantially affect health-related quality of life (HRQoL). Although EQ-5D is widely used as a generic preference-based HRQoL instrument, EQ-5D outcomes in adults with AIH have not previously been synthesized in a focused systematic review. This review aimed to summarize EQ-5D outcomes in adults with AIH and assess the certainty of the available evidence using GRADE. A systematic review and meta-analysis was conducted in accordance with PRISMA and prospectively registered in PROSPERO (CRD420261334849). PubMed/MEDLINE, Scopus, Embase, and CENTRAL were searched from inception to 25 February 2026. Studies reporting EQ-5D utility/index, EQ-VAS, and/or domain-level outcomes in adults with AIH were included. Qualitative synthesis served as the primary interpretive framework, and quantitative synthesis was performed as an exploratory summary when appropriate. Certainty of evidence was assessed using GRADE. Five studies were included. Reported EQ-5D utility values ranged from 0.65 to 0.88, and EQ-VAS values ranged from 67.5 to 77.3 across studies. Exploratory random-effects synthesis yielded a pooled EQ-5D utility estimate of 0.80 (95% CI: 0.71 to 0.89; I² = 99.3%) and a pooled EQ-VAS estimate of 70.87 (95% CI: 67.28 to 74.46; I² = 93.9%). However, these pooled values should be interpreted as descriptive summaries of a highly heterogeneous evidence base rather than as stable benchmark estimates. Domain-level data from two studies suggested that pain/discomfort and anxiety/depression were the most frequently affected EQ-5D dimensions. Certainty of evidence was very low for all synthesized outcome groups. Available EQ-5D evidence in adults with AIH suggests an important HRQoL burden, particularly in the pain/discomfort and anxiety/depression domains. However, the evidence base is sparse, highly heterogeneous, and of very low certainty; therefore, pooled EQ-5D and EQ-VAS values should be interpreted as exploratory descriptive summaries rather than definitive benchmark estimates.

Unified influence estimation through multi-hop reinforcement and diversity-weighted fusion in weighted complex networks

Abstract By depicting items as nodes and their connections as links, networks or graphs attract more attention in complex systems as a way to simulate real-world interactions. Finding influential nodes in human contact networks or other social networks is essential to comprehending disease transmission, which is dependent on the frequency and intensity of contact. Nevertheless, the majority of current research ignores the variability of real-world interactions in favour of uniform connection strength. To address this gap, we propose a unified influence estimation model (uiem) that integrates multi-hop diffusion, local structural reinforcement, and interaction diversity into a single adaptive framework. The model constructs a weighted graph where edge weights reflect interaction frequency/ real weights based on the different scenarios. One-hop and two-hop components capture direct and indirect diffusion influence, while the local structural reinforcement index (lsri) quantifies a node’s connectivity strength and connections within its neighborhood. Additionally, a diversity-weighted fusion (dwf) mechanism combines weighted degree and local clustering entropy (lce) to balance structural intensity and interaction diversity. Experimental results on multiple human contact networks and social networks demonstrate that uiem outperforms existing methods, effectively identifying structurally and functionally influential nodes and providing deeper insights into the dynamics of real-world contact-based spreading processes.

Tunable sign reversal of giant Goos–Hänchen shifts in graphene-covered quantum wells

We theoretically investigate tunable sign reversal of giant Goos–Hänchen shifts in a graphene-covered semiconductor quantum-well cavity. A coherently driven four-subband semiconductor quantum-well medium induces ultra-steep 2π phase wraps of the TM reflection coefficient vs incidence angle, which convert—via the stationary-phase relation—into giant positive or negative lateral displacements reaching 103−104 times the free-space wavelength λ. The shift polarity and magnitude can be independently engineered by varying the incidence angle, the effective cavity thickness, and the control-field strength, while the graphene overlayer enhances confinement and phase sensitivity. Moreover, electrostatic tuning of the graphene Fermi level reconfigures the reflection resonances and enables active switching between large forward and backward beam displacements. These results suggest a compact platform for angle- and voltage-programmable beam steering, optical switching, and position-encoded sensing.

Development of erosion hazard index-based land suitability criteria for sustainable agriculture in the Nilgiris hills of India

Interface-driven enhancement of spin–orbit magnetic readout at a ferromagnetic Rashba–Edelstein interface in Co/Pd

Magneto-electric spin–orbit logic requires efficient spin–charge interconversion in scalable geometries. Here, we use Co/Pd heterostructures as a model system to demonstrate local spin–orbit readout at a ferromagnetic Rashba–Edelstein interface, where conversion occurs directly at the magnetic boundary without non-local diffusion. After removing spurious Hall and geometric contributions, the readout signal exceeds that expected from the bulk spin Hall effect of Pd and obeys Onsager reciprocity, indicating a dominant interfacial origin. Modest interfacial pre-activation reproducibly enhances the signal by nearly a factor of two. The enhancement underscores the strong interfacial sensitivity of the induced spin–charge conversion, while ferromagnetic resonance and harmonic spin–orbit torque measurements show only minor changes in magnetic and torque properties, consistent with reduced interfacial spin-memory loss being a contributing factor.

Numerical investigation of the flexural behaviour and composite action of reinforced concrete sandwich panels (RCSP) with EPS core: parametric study using FEA

MoS2 field-effect transistors gated with quasi-1D metallic TaSe3 crystal

The extensive exploration of two-dimensional (2D) materials for field-effect transistors (FETs) scaling has imposed stringent requirements on next-generation interconnects with excellent electrical reliability. In this work, we investigated the electrical transport properties of metallic TaSe3 crystals, which possess a typical quasi-1D van der Waals (vdW) atomic structure. Our findings establish quasi-1D TaSe3 as a promising interconnect material for 2D electronics. It demonstrates dimension-independent resistivity and high current-carrying capacity, with a maximum breakdown current density exceeding 9 MA cm−2 and an average resistivity of 494 μΩ cm remaining stable with feature sizes down to ∼20 nm. Gated with atomic-thin TaSe3 nanobelts, the MoS2 FET with a short gate length delivers a remarkable on/off current ratio surpassing 107 and a subthreshold swing of 90 mV dec−1, and the inverter shows rapid inversion behavior with a high voltage gain of 7 at VDD = 2 V. These findings demonstrate the significant promise of quasi-1D vdW metallic TaSe3 crystal for advancing future logic circuit interconnection.

Research on dynamic analysis and optimization algorithms for large-scale power systems

A generalist precision medication framework using temporal causal inference based on treatment-free physiological profiles

Melt front visualization and flow prediction in dynamic phase change materials on finned heat sinks

Dynamic phase change materials (dynPCMs) offer high heat transfer rates over extended times due to a force applied to the PCM that pumps away melted liquid and maintains a thin melt layer. The melt layer dynamics governs the system behavior; however, little is known about how the melt layer forms and flows, especially when the heat source has a complex three-dimensional shape. This study investigates heat transfer and fluid flow during dynPCM cooling of heated finned copper heat sinks. Melt flow is visualized using computer vision, and these results are coupled with thermal measurements and simulations to gain a fundamental understanding of the flow physics. By measuring the shape of the liquid–solid interface, we resolve the coupling between the heat transfer and melt flow. Four extended surface designs are investigated consisting of fins with varying tip shapes and spacings. Experiments show a reduction in thermal resistance up to 36% with sharp-tip fins compared with rectangular fins, with the thinnest melt layer forming at the fin tips. Using experimental observations as inputs, a three-dimensional simulation investigates heat transfer and fluid flow in the liquid PCM. Simulations show that liquid drainage is a key limitation to dynPCM performance and that the melt layer is thinnest in the center of the heat sink, growing as the melted PCM flows out. The results demonstrate that dynPCM heat transfer is governed by the interplay of surface area, fin geometry, and liquid drainage. The outcomes presented here may be used to design higher-performing dynPCM systems.

Synthesis and characterization of bi-functional Co-Ag MOF@CuO nanorods as an innovative robust heterogeneous catalytic material for the fabrication of fused 1,4-dihydropyridine derivatives

Abstract This study used the co-precipitation method to produce novel nanorods from bi-functional Co-Ag metal-organic frameworks (BF Co-Ag MOF). CuO was then immobilized onto the BF Co-Ag MOF to create a new heterogeneous catalytic material (BF Co-Ag MOF@CuO). This material was thoroughly examined using several analytical methods, including field-emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), X-ray diffraction (XRD), N 2 adsorption-desorption, vibrating-sample magnetometry (VSM), and Fourier transform infrared spectroscopy (FT-IR). The one-pot, multi-component Hantzsch fabrication of biologically significant fused 1,4-dihydropyridines (1,4-DHPs) was used to assess the synthesized nanorods’ catalytic efficiency. Dimedone, commercially available aldehydes, and ammonium acetate as a nitrogen source were used in this chemical reaction at 60 °C in aqueous media. 1 H-NMR and 13  C-NMR spectroscopy were used to thoroughly analyze the obtained products. The quick fabrication of a wide variety of 1,4-DHPs with short chemical transformation times, straightforward experimental and work-up processes, simple catalytic material preparation, outstanding catalytic performance, notable product outputs, an eco-friendly solvent, and reusability are just a few benefits of the suggested approach.

Mpi-driven N-glycosylation orchestrates mucin O-glycosylation and intestinal homeostasis

Abstract The intestinal mucus barrier physically separates the epithelium from the dense microbial community of the gut and is essential for intestinal homeostasis. The principal component, the gel-forming mucin MUC2, is extensively glycosylated, yet how different classes of glycans regulate mucin function remains unclear. Here we show that N-glycosylation is required for proper MUC2 maturation and mucus barrier integrity. Using mouse models with hypomorphic or intestinal epithelial–specific loss of the mannose-generating enzyme MPI, which is required for N-glycan synthesis, we find that impaired N-glycosylation disrupts mucin processing and secretion. MPI deficiency results in severe susceptibility to dextran sulfate sodium–induced colitis or spontaneous intestinal inflammation, accompanied by endoplasmic reticulum stress, microbial dysbiosis, and defects in Paneth cells. These findings demonstrate N-glycosylation is critical for mucus barrier function and reveal an unexpected link between N-glycosylation and intestinal inflammatory disease.

Spin reorientation and multi-physical field control in high-entropy orthoferrite single crystals

The high-entropy design strategy offers a route to control the spin order in rare-earth orthoferrites (RFeO3). In this work, a high-entropy perovskite single crystal of Y0.2Nd0.2Sm0.2Er0.2Tm0.2FeO3 (5RFeO) was grown using the optical floating zone method. Its high crystalline quality and precise orientation were confirmed by x-ray and Laue diffraction. The effects of temperature, magnetic field, and hydrostatic pressure on the spin reorientation (SR) behavior were systematically investigated. Our measurements reveal that under low magnetic fields, the crystal exhibits a Γ4 → Γ4 + Γ2 → Γ2 transition sequence within the temperature range of 125–160 K. The applied magnetic field suppresses the SR, broadening the transition temperature window. Furthermore, hydrostatic pressure above ∼0.80 GPa reconstructs the transition pathway in a manner that points to a Γ1-like intermediate state, leading to a complex and multi-step transition sequence. The magnetic moment along the b axis remains insensitive to both the magnetic field and pressure. This study demonstrates the tunability of spin reorientation to multiple physical stimuli in a chemically disordered high-entropy system, elucidates the underlying spin structure evolution mechanism, and highlights the application potential of such high-entropy orthoferrites in spin-based devices.

Scalable and sustainable manufacturing of functional DNA nanoassemblies via self-folding circular single-stranded DNA

Inside Back Cover: Catalysis AI Agent Guides Discovering the Universal Design Principle of Cu‐Based Single‐Atom Alloy Catalysts for CO ₂ Electroreduction (Angew. Chem. Int. Ed. 21/2026)

Coherently grown AlN/GaN HEMT heterostructures on AlN buffer on SiC substrate—Impact of coherent growth on electrical and thermal characteristics

AlN/GaN high-electron mobility transistor (HEMT) heterostructures are advantageous for developing high-frequency and high-power devices, owing to their thinner barrier layers and high polarization-induced two-dimensional electron gas (2DEG) densities. Coherently grown AlN/GaN HEMT heterostructures on AlN substrates with intentional high Si δ-doping at the GaN/AlN interface have previously demonstrated enhanced electron mobility due to reduced dislocation densities and a lower electric field in the GaN channel. However, simultaneously implementing Si δ-doping and achieving a coherently grown GaN channel on AlN buffers on SiC substrates remains challenging because of the high dislocation density in the buffer layer. In this work, coherent growth of a GaN channel on an AlN buffer on SiC substrates is achieved using thin AlGaN and AlN/GaN superlattice-based stress transition layers (STLs). The resulting coherent AlN/GaN HEMT heterostructures with AlGaN-STLs exhibit a 2DEG mobility of 626 cm2 V−1 s−1, representing the highest value reported to date for a coherently grown GaN channel on an AlN buffer on SiC substrates. In contrast, AlN/GaN HEMTs with relaxed GaN channels exhibit significantly lower sheet resistance and reduced thermal resistance compared with devices with coherently strained channels. These results indicate that, provided device performance is not limited by misfit formation, relaxed GaN channels offer advantages for AlN/GaN HEMTs on SiC substrates. Otherwise, a trade-off emerges between thermal–electrical and misfit-induced degradation in device performance, governed by the choice between coherent and relaxed GaN channels.

Hybrid reasoning for perception, explanation, and autonomous action in manufacturing

Abstract Industrial processes must operate robustly in unpredictable environments, where errors are costly and difficult to detect. AI-based control systems offer a path forward but typically rely on large, labeled datasets, limiting their generalization to variable, data-scarce settings. Foundation models promise broader reasoning and knowledge integration yet struggle to deliver the quantitative precision required in engineering. Here, we introduce Control and Interpretation of Production via Hybrid Expertise and Reasoning (CIPHER): a systems-level vision-language-action (VLA) framework designed for industrial perception, explanation and control. CIPHER integrates a process expert for quantitative characterization of system states with retrieval-augmented reasoning grounded in process physics and knowledge. This hybrid design enables strong generalization to out-of-distribution tasks, allowing the agent to interpret textual or visual inputs, explain its decisions, and autonomously generate precise machine instructions without explicit supervision. In this work, CIPHER is deployed within multiple manufacturing systems, demonstrating precise, context-aware, and transparent control, with potential for deployment in real industrial environments.

All-optical ultrafast tunable linear absorption with a VO2 based metamaterial

The phase-dependent plasmonic response of a metamaterial platform composed of VO2 nanocrystals (NCs) embedded in an SiO2 matrix was investigated using ultrafast time-resolved spectroscopic ellipsometry. Localized surface plasmon resonances (LSPR) emerged upon excitation with 35 fs laser pulses at λ = 500 nm, which triggered the insulator-to-metal transition in the VO2 NCs. The study reveals the ultrafast dynamics mapped at the LSPR underlying the photoinduced optical tunability of the system, highlighting the potential of VO2 NCs for reconfigurable photonic applications such as tunable linear switching.

Diverse mechanisms of translation arrest by a Clostridia ribosome stalling peptide CliM

Abstract Ribosome arrest peptides undergo programmed translational stalling in response to changes in the cellular environment to feedback-regulate gene expression. CliM, an arrest peptide in Clostridia, is encoded upstream of the YidC membrane protein insertase gene, but its function and mechanism remain unclear. Here we show that CliM monitors YidC activity to maintain adequate cellular YidC capacity. Interestingly, Clostridium kluyveri CliM induces elongation arrest at multiple sense codons, whereas Clostridioides difficile CliM causes termination arrest. Cryo-EM-based structural and mutational analyses demonstrate that C. difficile CliM adopts multiple α-helices within the nascent polypeptide exit tunnel, where it forms extensive arrest-essential interactions with the ribosome. The residue immediately N-terminal to the stalling site contributes to arrest by sterically interfering with full accommodation of the release factor or aminoacyl-tRNA in the A-site. Molecular dynamics simulations suggest that membrane insertion of CliM induces sequential unwinding of these α-helical structures and relocation of the penultimate residue, thereby triggering arrest release. These findings provide a unified mechanistic framework that explains the distinct arrest behaviors of CliM homologs.