Search

• 3D MOFs CrCl 2 (pyz) 2 has a fully spin-polarized nodal chain. • Fully spin-polarized drumhead surface states corresponding to these nodal loops are identified on the material's surfaces. • Fully spin-polarized nodal chain of 3D CrCl 2 (pyz) 2 has excellent resistance to perturbations. • Its SOC effect can be almost ignored. The identification of fully spin-polarized topological phases in magnetic inorganic materials has attracted significant attention. In this study, through first-principles calculations, we characterize CrCl 2 (pyz) 2 , a metal-organic framework (MOF), as a nodal chain semimetal. Our results reveal a ferromagnetic ground state in this material, presenting as a half-metal with a single spin channel near the Fermi level. Specifically, the spin-down states form a nodal chain close to the Fermi level, consisting of three nodal loops protected by glide mirror symmetry on distinct planes. Furthermore, fully spin-polarized drumhead surface states corresponding to these nodal loops are identified on the material's surfaces. Remarkably, we observe the persistence of the fully spin-polarized nodal chain even when tuning the ligand rotation angle of the MOF. Furthermore, our investigation delves into the influence of spin-orbit coupling (SOC) on the system, revealing that it has minimal impact on the nodal chain. The robustness of the nodal chain in the presence of SOC underscores its intriguing and resilient nature, indicating its potential utility in various electronic applications. Ultimately, the robust realization of a fully spin-polarized nodal chain in this magnetic MOF system holds promise for applications in the realm of spintronics. [Display omitted] [ABSTRACT FROM AUTHOR]

Amidst the rapid propagation of multimodal fake news across social media platforms, the detection of fake news has emerged as a prime research pursuit. To detect heightened level of meticulous fabrications, propagation paths are introduced to provide nuanced social context that enhances the basic semantic analysis of the news content. However, existing propagation-enhanced models encounter a dilemma between detection efficacy and social hazard. In this paper, we explore the innovative problem of early fake news detection through the generation of propagation paths, capable of benefiting from the extensive social context within propagation paths while mitigating potential social hazards. To address these challenges, we propose a novel Reinforced Propagation Path Generation Fake News Detection model, RPPG-Fake. Departing from conventional discriminative approaches, RPPG-Fake captures the propagation topology pattern from a heterogeneous social graph and generates the propagation paths to detect fake news effectively under a reinforcement learning paradigm. Our proposal is extensively evaluated over three popular datasets, and experimental results demonstrate the superiority of our proposal.

Through a quantitative analysis of saltiness perception, favorable enzymatic hydrolysis parameters were confirmed for the preparation of saltiness-enhancing peptide mixtures from Coprinus comatus. The enzymatic hydrolysate was fractionated into four fractions (F1–F4) by gel chromatography, with F3 exhibiting the strongest saltiness-enhancing effect (22% increase). LC-MS/MS analysis of F3 identified 36 peptides, and their secondary structures and interactions with the TMC4 receptor were examined through circular dichroism spectroscopy and molecular docking. Molecular docking analysis revealed Asn588, Ser165, Asp5, and Arg168 as key amino acid residues, with the peptide GDNVGF showing the lowest binding energy. Synthetic GDNVGF (0.01%) in 70 mmol/L NaCl enhanced saltiness by 17%. When 0.7% GDNVGF was added to the aqueous solution, its saltiness was equivalent to that of 36.89 mmol/L NaCl, which suggested that GDNVGF functions both as a saltiness-enhancing peptide and a salty peptide. The taste changes of peptides during thermal reactions were further investigated. The thermal stability of Coprinus comatuspeptides was good, but their saltiness-enhancing effect slightly reduced due to thermal degradation. The Maillard reaction further diminished this effect, though the umami level remained satisfactory, offering new insights into using Coprinus comatuspeptides as low-sodium salt substitutes.

Clinical decision-making is driven by multimodal data, including clinical notes and pathological characteristics. Artificial intelligence approaches that can effectively integrate multimodal data hold significant promise in advancing clinical care1,2. However, the scarcity of well-annotated multimodal datasets in clinical settings has hindered the development of useful models. In this study, we developed the Multimodal transformer with Unified maSKed modeling (MUSK), a vision–language foundation model designed to leverage large-scale, unlabelled, unpaired image and text data. MUSK was pretrained on 50 million pathology images from 11,577 patients and one billion pathology-related text tokens using unified masked modelling. It was further pretrained on one million pathology image–text pairs to efficiently align the vision and language features. With minimal or no further training, MUSK was tested in a wide range of applications and demonstrated superior performance across 23 patch-level and slide-level benchmarks, including image-to-text and text-to-image retrieval, visual question answering, image classification and molecular biomarker prediction. Furthermore, MUSK showed strong performance in outcome prediction, including melanoma relapse prediction, pan-cancer prognosis prediction and immunotherapy response prediction in lung and gastro-oesophageal cancers. MUSK effectively combined complementary information from pathology images and clinical reports and could potentially improve diagnosis and precision in cancer therapy.

Two-dimensional covalent organic frameworks (2D COFs), a family of crystalline materials with abundant porous structures offering nanochannels for molecular transport, have enormous potential in the applications of separation, energy storage, and catalysis. However, 2D COFs remain limited by relatively large pore sizes (>1 nm) and weak interlayer interactions between 2D nanosheets, making it difficult to achieve efficient membranes to meet the selective sieving requirements for water molecules (0.3 nm) and hydrated salt ions (>0.7 nm). Here, we report a high-performance 2D COF membrane with narrowed channels (0.7 × 0.4 nm2) and excellent mechanical performance constructed by the staggered stacking of cationic and anionic 2D COF nanosheets for selectively sieving of water molecules and hydrated salt ions. The mechanical performance has been improved by two times than that of single-phase 2D COF membranes due to the enhanced interlayer interactions between nanosheets. The stacked 2D COF membranes exhibit significantly improved monovalent salt ions rejection ratio (up to 77.9%) compared with single-phase COF membranes (∼49.2%), while maintaining comparable water permeability. The design of stacked 2D COF membranes provides a potential strategy for constructing high-performance nanoporous membranes to achieve precise molecular and ionic sieving.

Bemisia tabaci(Gennadius), a major pest that can adversely affect economies and agriculture globally, is particularly sensitive to climate change-induced temperature fluctuations, which can intensify its outbreaks. Orius similisZheng, a primary natural predator of B. tabaci, also experiences temperature-related effects that influence its biocontrol efficacy. Thus, understanding the response of O. similisto temperature changes is pivotal for optimizing its biocontrol potential. Herein, our investigations showed that the functional response of O. similisto both high- and low-instar nymphs of B. tabaciadheres to the type II model at temperatures of 19, 22, 25, 28, and 31 °C. At 28 °C, O. similisexhibits the highest instantaneous attack rate (high-instar: 1.1580, low-instar: 1.2112), and the shortest handling time per prey (high-instar: 0.0218, low-instar: 0.0191). The efficacy of O. similisin controlling B. tabacinymphs follows the sequence: 28 °C > 25 °C > 31 °C > 22 °C > 19 °C. Additionally, search efficiency inversely correlates with prey density. Simulations using the Hessell–Varley interference model indicate that increased density of O. similisunder any temperature condition leads to reduced predation rates. Moreover, O. similisshows a predation preference for low-instar nymphs of B. tabaci, with higher predation level observed at the same temperature. In conclusion, for effective control of B. tabaciin field releases, O. similisshould be optimally released at temperatures between 25 and 28 °C to preferably target the egg or early nymph stages of B. tabaciand determining the appropriate number of O. similisis important to minimize interference among individuals and enhance biocontrol efficacy.Graphical Abstract