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Large language models identify immigration attitudes in online discourse regardless of language
Abstract Large language models (LLMs) offer new opportunities for scalable analysis of online discourse. Yet their use in multilingual social science research remains constrained by model size, cost and linguistic bias. We develop a lightweight, open-source LLM framework using fine-tuned LLaMA 3.2–3B models to classify immigration-related tweets across 13 languages. Unlike prior work relying on BERT-style models or translation pipelines, we combine topic classification with stance detection and demonstrate that LLMs fine-tuned in just one or two languages can generalize topic understanding to unseen languages. Capturing ideological nuance, however, benefits from multilingual fine-tuning. Our approach corrects pretraining biases with minimal data from under-represented languages and avoids reliance on proprietary systems. With 19–96 $$\times$$ faster inference and up to 2,017 $$\times$$ cost savings compared to commercial LLMs, our method supports real-time analysis of billions of tweets. This scale-first framework enables inclusive, reproducible research on public attitudes across linguistic and cultural contexts.
Direct measurement of Criegee intermediates in isoprene ozonolysis
Abstract Isoprene is the most abundant unsaturated hydrocarbon in the troposphere. Carbonyl oxides, also called Criegee intermediates, are highly reactive transient species in the ozonolysis of alkenes that play important roles in tropospheric oxidation. Despite decades of efforts, direct observation of Criegee intermediates in isoprene ozonolysis has not been achieved. Here we show the first direct measurement of Criegee intermediates produced in isoprene ozonolysis. Ultra-violet spectra of Criegee intermediates are captured with cavity ringdown spectroscopy and match oscillatory π* ← π transitions of CH 2 OO. The in-situ concentration time profiles of Criegee intermediates allow direct kinetic studies and benchmark the isoprene ozonolysis reaction network. The results indicate that CH 2 OO dominates stabilized Criegee intermediate chemistry in the low-pressure region, while the role of larger stabilized four-carbon Criegee intermediates could be important in tropospheric oxidation.
TagC-RED: An Infrared-Triggered Retro-Ene Reaction for Deep-Tissue Bioconjugation
Silk fibroin from production wastes, a new raw material for biomaterial applications: physicochemical properties and biological performance
Author Correction: Pharmacological markers of HIV prevention for oral pre-exposure prophylaxis in men who have sex with men
Mechanism of Photoinduced Conformational Changes in the Photoenzyme Fatty Acid Photodecarboxylase Revealed by Light- Footprinting Ion Mobility Mass Spectrometry
Efficient UAV object detection using spectro-spatial synergistic learning and implicit recursive refinement
Long-range electronic interactions of tubular single-atom Cu-N3 catalysts for nanoconfined direct electron transfer oxidation
Multienzyme-Mediated Dynamic Cross-Linking of All-Natural Hydrogels with High Adhesion and Redox Modulation for Rapid Tissue Filling and Repair
Molecular evolution of aspartic protease gene family in vertebrates
Abstract Aspartic proteases are a gene superfamily with diverse functions in vertebrates, including pepsinogens (Pgs), the precursors of the major gastric enzyme pepsin. Despite their physiological importance, the evolutionary history of this gene family has been studied only in a fragmented manner. Here, we conducted comprehensive phylogenetic and genomic synteny analyses using whole-genome data from 75 vertebrate species to systematically elucidate the molecular evolution of aspartic protease genes. We identified Pg genes in cartilaginous fishes (elasmobranchs) for the first time, demonstrating that Pg s originated in the gnathostome ancestor. Pregnancy-associated glycoprotein ( PAG ) genes showed explosive expansion in cetartiodactyla but underwent secondary reduction in cetaceans. Cathepsin E ( ctse ), predicted to be the ancestral gene of Pg s, was also found in cartilaginous fishes and non-teleost ray-finned fishes (e.g., gar, bichir, bowfin), but was independently lost in multiple lineages, including teleosts, ruminants, vampire bats, and several stomach-less species. Our results reveal complex patterns of lineage-specific tandem gene duplication, lineage-specific expansion, and convergent gene loss, providing an evolutionary framework for understanding the functional diversification of aspartic proteases in relation to feeding strategies, digestive physiology, and reproductive adaptations in vertebrates.
Membrane lipid poly-unsaturation selectively affects dopamine D2 receptor endocytosis
Abstract The brain is highly enriched in poly-unsaturated fatty acids (PUFAs) and their deficiency has been associated with several neuropsychiatric disorders. Here, we demonstrate that the Dopamine receptor D2 (D2R), a class A G protein coupled receptor (GPCR) which is a main target of antipsychotics, displays specific sensitivity to membrane PUFA composition. We found that membrane enrichment with either of two distinct PUFAs significantly impairs agonist-induced D2R endocytosis in HEK-293 cells and cortical neurons. This treatment does not affect clathrin-mediated endocytosis or the internalization of several other GPCRs. Moreover, we show that D2R clustering at endocytic pits is not affected, but that recruitment of β-arrestin2 is strongly impaired and endocytic vesicle formation is slowed down. Finally, mutation of key residues in intracellular loop 2 abolishes the sensitivity of D2R endocytosis to PUFA enrichment. We conclude that D2R trafficking is specifically dependent on membrane PUFAs, which could influence its role in the control of brain function and behavior.
A predictive framework for evaluating the thermophysical properties of multi-walled carbon nanotube nanofluids dispersed in a water–ethylene glycol 50:50 base fluid
Abstract This study presented a predictive optimization framework for evaluating the thermophysical properties of multi-walled carbon nanotube NFs dispersed in a 50:50 water–ethylene glycol base fluid. The main objective was to simultaneously predict TC and dynamic µ nf , addressing a key limitation of previous studies that focused primarily on TC alone. A feedforward artificial neural network with two hidden layers was developed and validated using experimental data. The dataset covered nanoparticle volume concentrations between 0.025% and 0.1% and temperatures ranging from 25 °C to 80 °C. The proposed model demonstrated strong predictive capability across all evaluation metrics. Under 10-fold cross-validation, the root mean square error for TC varied from 1.31 × 10⁻⁴ to 3.71 × 10⁻⁴ W/m·°C, while the corresponding values for µ nf range from 0.010 to 0.031 mPa·s. Low mean-squared error values across the training, validation, and test datasets confirmed the robustness of the learning process. Optimal performance was achieved at epoch 5 for TC and at epoch 8 for µ nf . In all cases, the coefficient of determination exceeded 0.99, indicating excellent agreement between predictions and experimental measurements. Relative errors remained limited to 0.32–1.57% for TC and 0.12–0.25% for µ nf , while absolute errors were also tightly bounded. A complementary sensitivity analysis further supported the model stability. A 10% variation in Temperature led to maximum deviations of 2.636% in TC and 0.623% in µ nf , whereas the same variation in nanoparticle concentration produced larger deviations of 5.744% and 0.893%, respectively. Despite this difference, mean deviations remained modest for both properties, confirming the robustness of the proposed framework under input perturbations.
Ultrafast switching and high-endurance nonvolatile memory enabled by intrinsic switchable polarization in semiconducting Janus monolayers
Predicting the Thermodynamic Limits of Metal–Organic Framework Metastability
Nrf2 attenuates neuroinflammatory injury in intracerebral hemorrhage via an ASK1/JNK-related signaling pathway
Cellular and subcellular heterogeneity of astrocytic Na⁺ homeostasis tuning astrocytes into functionally distinct subgroups in the mouse brain
Abstract Astrocytes maintain extracellular ion and transmitter homeostasis, with the Na⁺ inward gradient playing a crucial role. Earlier studies suggested a rather low, uniform Na⁺ distribution in astrocytes, consistent with the view that these basic homeostatic properties are well-protected. Here, we employed multi-photon fluorescence lifetime imaging to quantitatively determine astrocytic [Na + ] in mouse brain tissue slices and in vivo. Our data reveals a significant subcellular and cellular heterogeneity in astrocytic [Na + ], accompanied by differences in the capacity for Na + /K + -ATPase (NKA)-mediated uptake of extracellular K + . RNAscope and immunohistochemistry indicate differential spatial expression patterns of NKA ß1 and ß2 subunits in astrocytes. Biophysical modeling of differential NKA expression together with varying strength of Na + influx replicate the experimentally observed heterogeneity in astrocytic [Na + ]. Altogether, our results suggest the existence of functionally distinct astrocytes and astrocyte subdomains in which Na + homeostasis is locally adapted to the specific requirements of surrounding neural networks.
Non-Enzymatic MGO-Glycation of SRSF2 Drives RNA Mis-Splicing
Spatiotemporal variations in b-value suggest an evolving mechanical state of the crust in the southeastern Alps
Abstract Understanding whether and how the mechanical state of the crust evolves is a central challenge in intraplate regions. We investigate the southeastern Alps region by analyzing the frequency-magnitude distribution of ten years of seismicity (14776 earthquakes) with magnitudes in the range 0 ≤ M L ≤ 4.5. We analyze the spatio-temporal evolution of the b-value, a proxy for crustal stress and strength. Using the b-positive method and Singular Spectrum Analysis, we observe a persistent b-value decrease since 2020 in the Friuli region, which we interpret as evidence of the evolving stress state of the system towards crustal weakening. . By linking b-value trends to the Hoek–Brown failure criterion, we interpret the crustal stress evolution in terms of rock mass disturbance. Our results suggest that, even under low loading rates, distinct crustal volumes may evolve differently over time, with some potentially approaching critical conditions while others remain stable. Whitin this framework, b-value variations may provide a physically grounded approach to monitor fault weakening and assess seismic hazard in slowly deforming continental regions.
Economic costs of global forest protection may be overstated
Abstract Protecting the world’s remaining forests is central to climate and biodiversity goals, but is often assumed to impose large opportunity costs on forest-land producers. These costs are typically estimated by summing local foregone production, without accounting for market feedback. Here, we applied partial-equilibrium models to three scenarios protecting an additional 471–863 million hectares of forest, assuming a global 30% protection target by 2030. Despite reductions in harvestable area and roundwood production, global net output value in the forestry sector increases modestly, driven by price increases under reduced supply. Most countries experience gains, although some incur losses. Despite broader economic impacts, including consumer welfare, substitution effects, and cross-sector response not being captured in this analysis, these results may indicate that approaches ignoring price adjustments may overestimate producer-side opportunity costs of large-scale forest protection.