Cross-view geo-localization between drone and satellite images is severely challenged by rapid weather variations, which induce appearance shifts, occlusions, and texture degradation. Inspired by human foveal attention, we propose the Fovea Attention Network (FANet), a robust dual-branch framework comprising: 1) the Weather-Adaptive Global Branch (WAGB) that explicitly injects weather cues (e.g., 'rain/snow') into the feature space via a style-modulation encoder, then captures large-scale structural consistency through a Learnable Region Reassembly (LRR) mechanism; and 2) the Local Semantic Attention Branch (LSAB) that leverages a pretrained segmentation model to generate high-confidence masks, distilling discriminative features from salient regions. An adaptive fusion strategy module fuses global context with fine-grained semantic cues. We further adopt multi-weather adaptive training, treating weather types as related tasks with shared parameters to reduce cross-weather confounding. Extensive experiments on University-1652, SUES-200, and CVUSA show that FANet achieves competitive Recall@1 across all conditions, attaining the highest overall mean with the lowest variance. Notably, it improves Recall@1 by 6.79% under severe low-illumination ('dark') conditions, demonstrating robustness and stability. Our code is available at https://github.com/Jahawn-Wen/FANet.
Somatic mutations accumulate throughout life and have been hypothesized to drive organismal decline. Yet whether these mutations are distributed randomly or whether cells shield their most critical components has remained unresolved. Here we analyze over a million somatic mutations across thirteen human tis-sues, finding that the aging genome exhibits organized vulnerability, captured by the existence of hypo-mutated genes and longevity-associated pathways that have significantly lower mutation burden. Highly connected network hubs are systematically protected from mutation, while peripheral, condition-specific genes accumulate disproportionate burdens. We show that this organized vulnerability arises from the interplay of two independent mechanisms: transcription-coupled repair, and selective filtering. Finally, we validate our findings under experimental mutagenesis, demonstrating intrinsic mechanisms of protection rather than tissue-specific confounders. These findings reframe the somatic mutation hypothesis: organismal decline may not reflect total mutational burden, but where those mutations fall within the cellular network.
The architectural optimization of multifunctional components within MoS2-based nanohybrids demonstrates potential for amplifying cooperative catalytic effects in biomimetic catalytic systems. Employing APTES@MoS2 composites as specialized sorbents, their inherent amine coordination ability and surface negative charge were exploited to investigate their efficacy in adsorbing transition metal ions such as Ni2+, Fe3+, and Co2+ ions. High-temperature carbonization treatment gradually converted the amorphous APTES polymer into N-doped carbon (denoted as CAPTES), while simultaneously enhancing crystallinity and enabling transition metal doping in MoS2 nanosheets (NSs) through thermal treatment, leading to enhanced catalytic performance. Dense decoration of palladium nanoparticles (Pd NPs) is incorporated to amplify the hydrophilicity and the catalytic efficiency of CAPTES@Fe-MoS2 nanocomposites. Benefiting from the hierarchical hollow configuration with extensively exposed edge sites, optimized charge transfer dynamics, and homogeneously distributed active centers, the engineered tubular heterostructures demonstrate exceptional catalytic performance in both 4-nitrophenol (4-NP) reduction and biomimetic enzymatic reactions. This template-directed synthesis strategy provides a scalable platform for manufacturing heterostructured MoS2-based materials with tunable synergistic functionalities, enabling advanced catalytic solutions for environmental and analytical applications.
Modulating intratumoral copper homeostasis to trigger cuproptosis is a promising copper‑based anticancer strategy, but its clinical translation is hindered by the absence of precise spatiotemporal control over intracellular copper levels and ATP7A‑mediated active copper efflux. Here we report an ultrasound-activated copper molybdate nanoregulator, HCu1.5MoO5 (HCMO), that releases copper on demand and reprograms copper flux in tumor cells under ultrasound. Once internalized, ultrasound activates HCMO to release copper ions, providing a sustained intracellular copper supply. In parallel, HCMO also generates reactive oxygen species that impair mitochondrial function and depress cellular ATP, thereby attenuating the activity of the ATP-dependent exporter ATP7A and narrowing copper efflux. This dual-axis imbalance, in situ copper supplement, and efflux limitation significantly disrupt cellular copper homeostasis, interrupt the tricarboxylic-acid cycle, induce mitochondrial dysfunction, further enhance copper accumulation, and eventually cause irreversible cuproptosis. Together with apoptosis and necroptosis, the coordinated damage releases damage-associated molecular patterns and induces immunogenic cell death. Overall, this spatiotemporally programmable strategy links materials, physical fields, and immunity in a closed framework to coordinately disrupt copper homeostasis, offering a generalizable route to on-demand cuproptosis therapy.
Boron neutron capture therapy (BNCT) is a binary cancer treatment strategy that relies on the selective delivery of a 10B-containing drug followed by thermal neutron irradiation, generating localized high-LET particles that destroy tumor cells. L-BPA is the most recent and currently the only marketed boron carrier; however, its poor tumor retention and low solubility significantly limit therapeutic efficacy. Thus, developing improved L-BPA derivatives, as well as tools for efficient monitoring of L-BPA biodistribution, is critically important. Herein, we report a turn-on fluorescent probe, WF324, which undergoes rapid and selective fluorescence enhancement upon interaction with L-BPA. WF324 exhibits a pronounced fluorescence turn-on response at 578 nm (λex = 488 nm) along with a obvious Stokes shift of 90 nm, the probe displays a rapid response with a half-response time (t₁/₂) of 12 s and reaching a stable plateau within 150 s in aqueous solution and shows excellent selectivity with minimal interference from metal ions. The probe exhibited a good linear response toward L-BPA in the concentration range of 0-6 μM, with a detection limit as low as 80.48 nM. In real samples, the sensor achieved recoveries of 90.40-103.11% with RSDs of 0.78-3.96% for L-BPA detection in human urine. These properties make WF324 a promising tool for sensitive detection and real-time monitoring of L-BPA, offering valuable support for future BNCT research and development.
The evolution of herbivory is one of the most important ecological events in the evolution of terrestrial vertebrates and impacted the ecosystems they inhabited. Herbivory independently developed in a number of tetrapod clades during the Late Carboniferous and Permian, eventually leading to the establishment of the basic structure of modern terrestrial ecosystems. Here we describe a Late Carboniferous pantylid 'microsaur', Tyrannoroter heberti gen. et sp. nov., with expansive occluding palatal and coronoid dental batteries. The shape of the teeth, as revealed by high-resolution micro-computed tomography data, indicates wear from both shearing and grinding motions consistent with herbivory. New data from historical pantylid fossils show that similar adaptations can be traced back as far as the Bashkirian (~318 million years ago), indicating that terrestrial herbivory was already widespread within this group, and originated rapidly following the terrestrialization of tetrapods. The placement of recumbirostran 'microsaurs' on the amniote stem suggests that terrestrial herbivory is not an amniote innovation, although the phylogenetic position of 'microsaurian' tetrapods remains uncertain. Under any phylogenetic scenario, the data presented here reveal that pantylids acquired adaptations to herbivory independently, probably via durophagous omnivory, feeding on insects, shelled animals and tough plant material.
The advancement of highly efficient, selective catalysts stands as a pivotal challenge in methanol steam reforming (MSR) for hydrogen production. In conventional Ni-based catalysts, metallic Ni0 acts as the active site, synergizing with abundant surface oxygen vacancies of the oxide support and generating the intermediate *OCH₂ tends to directly decompose into CO, which further reacts with *H generated from H₂O activation to form CH₄, resulting in poor product selectivity. Herein, we propose a novel Ni/In₂O₃ catalyst that significantly enhances the selectivity of CO₂, increasing it from less than 10% to 90%. Comprehensive characterizations including XRD, XPS, H₂-TPR, UV-vis and TPSR reveal that, unlike conventional Ni0-based catalysts, the Ni/In₂O₃ catalyst forms a very active and selective Ni₂In₃ alloy phase that enables highly dispersed Ni species while endowing the catalyst with excellent capability for H₂O activation. Combined with further theoretical calculations, the catalytic reaction mechanisms of the CH₃OH and CH₃OH-H₂O systems on the catalyst surface are elucidated in detail. Density functional theory (DFT) calculations demonstrate that the d-p orbital hybridization in the Ni₂In₃ alloy effectively alters the electronic structure of Ni species and tunes the adsorption strength of reaction intermediates and balances the surface coverage of CH₂O* and *OH species, facilitating the critical HO-CH₂O* coupling step for CO₂ generation during methanol steam reforming and thereby improving the CO₂ selectivity of the Ni/In₂O₃ catalyst. The study presented in this work indicates that the formation of Ni-In active alloy phase may effectively overcome the inherent product selectivity issue of conventional Ni-based catalysts by regulating the surface coverage of the critical intermediate and therefore reaction pathway during methanol steam reforming.
Food waste fermentation liquid, rich in volatile fatty acids (VFAs) and carbohydrates, serves as a sustainable electron donor for biological nitrogen removal. However, the compositional fluctuation of fermentation liquid often leads to unstable denitrification, and the mechanistic influence of mixed VFA-saccharide interactions on microbial ecology remains poorly understood. In this study, four carbon-source systems-three simulating typical mixed fermentation products (acetate + sucrose, propionate + sucrose, butyrate + sucrose) and one single-carbon control (acetate alone)-were systematically evaluated in sequencing batch reactors (SBRs). Results indicated that the butyrate-sucrose system (A3) exhibited superior performance, achieving a nitrate removal efficiency of 98.5%, which was 13.5% and 8.2% higher than that of the acetate-sucrose (A1) and propionate-sucrose (A2) systems, respectively. Furthermore, A3 maintained the lowest nitrite accumulation (<0.5 mg/L). Mechanistically, A3 facilitated the selective enrichment of functional genera Ferruginibacter and Terrimonas. PICRUSt2 functional predictions revealed that this specific combination significantly enhanced KEGG pathways related to membrane transport (ABC transporters) and energy metabolism, suggesting a synergistic effect that accelerates electron transfer and metabolic turnover. This study demonstrates that regulating acidogenic fermentation towards a butyrate-dominant composition is a promising strategy to maximize the utility of food waste as a carbon source, ensuring robust nitrogen removal in wastewater treatment.
Lactic acid (LA) production from food waste fermentation offers a promising route for organic waste valorization and aligns with a circular economy concept. However, the microbial metabolic interactions remain poorly understood. This study demonstrates that regulating indigenous microbiota with eggshell (EG) buffer can achieve efficient LA production (33.2 ± 2.6 g COD/L), a yield only 3.6 % lower than that obtained with anaerobic sludge inoculation. Metabolic pathway analysis indicated that EG addition not only stabilized fermentative pH but also redirected the carbon flux toward LA. High-throughput sequencing showed that homofermentative LA bacteria (Streptococcus and Enterococcus) accounted for 37.3 % of the microbial community under EG addition alone. Additionally, EG modulated genes in the Embden-Meyerhof-Parnas, the hexose monophosphate, and the hexokinase pathway. This study confirms that an EG-buffered fermentation system can activate indigenous microbiota for high-efficiency LA production, demonstrating that exogenous inoculation is non-essential and offering a cost-effective approach for sustainable LA synthesis.
Drug-target affinity (DTA) prediction is a pivotal task in computational drug discovery, enabling the estimation of binding affinities between small molecules and their target proteins. This process is essential for reducing the costs, development time, and risks inherent in traditional drug development pipelines. Current DTA prediction models primarily rely on separate extraction and concatenation of drug and protein features. However, these models often fail to account for the complex semantic relationships within protein sequences, which limits their ability to accurately predict affinity. In response to these challenges, we propose MDM-DTA, a novel framework leveraging a Mixture of Experts (MoE) strategy to integrate diverse molecular and protein representations. For drug representation, MDM-DTA utilizes molecular graphs, which are processed via Message Passing Neural Networks (MPNNs), alongside molecular descriptors that are passed through a three-layer convolutional neural network (CNN). Protein features are extracted using a deep convolutional network enhanced with Squeeze-and-Excitation (SE) mechanisms to capture inter-channel dependencies. Furthermore, protein sequence semantics are encoded through pre-trained embeddings from a knowledge-guided Bidirectional Encoder Representations from Transformers (BERT) model and the Evolutionary Scale Modeling 2 (ESM2) model, enabling the model to capture contextual relationships within protein sequences. Extensive experiments on three benchmark datasets demonstrate that MDM-DTA consistently outperforms state-of-the-art models of similar complexity in terms of predictive accuracy. The incorporation of both structural and semantic features significantly enhances the model's ability to predict drug-target binding affinities, highlighting the importance of a multi-modal representation approach. The proposed MDM-DTA framework effectively integrates both molecular and semantic protein representations, providing superior performance in DTA prediction tasks. The results underscore the potential of MDM-DTA to improve the accuracy of computational drug discovery models, facilitating the identification of novel drug candidates and advancing the field of in silico drug development.
Conventional mandibular reconstruction frequently results in stress shielding, compromised osteotomy site healing, or bone resorption. This study introduces an Embedded Polygonal Bone Reconstruction Structure (EPBRS) that eliminates titanium plate dependency, enhanced through fillet-based topological optimization. A computational model of the Embedded Polygonal Bone Reconstruction Structure (EPBRS) was developed from CT scans. Four variants with fillet radii (0.2, 0.4, 0.6, and 0.8 mm) were designed. Physiological masticatory loading was simulated under identical conditions. The values of the von Mises stress and peak displacements were calculated for all configurations. With increasing fillet radius: The Maximum von Mises stress in the fibula graft decreased from 87.21 MPa to 37.59 MPa. The Maximum von Mises stress in the mandible decreased from 100.73 MPa to 23.9 MPa. The Maximum von Mises stress in titanium screws remained statistically invariant (170-185 MPa). Peak displacement (fibula graft, screws, mandible) decreased by approximately 0.1 mm between 0 mm and 0.2 mm fillet radii, remaining stable with further increases CONCLUSION: The embedded polygonal reconstruction demonstrates significant biomechanical safety and reliability. Fillet optimization substantially reduced the Maximum von Mises stress and improved deformation resistance.
Cardiac fibrosis represents the terminal pathological progression of diverse cardiovascular diseases, characterized by aberrant activation and migration of cardiac fibroblasts, as well as excessive and disordered deposition of the extracellular matrix. Our previous study showed that NAP1L1 is an important regulator of cardiac fibrosis and is upregulated in ischemic cardiomyopathy patient hearts. Accordingly, discovery of NAP1L1 inhibitors and elucidating their underlying mechanisms of anti-cardiac fibrosis should be urgently needed. Herein, we identified a new NAP1L1 small molecule inhibitor Z1149421873 (named Z11) by the structure-based drug design strategy. Z11 was shown to inhibit cardiac fibroblasts activation, deposition of collagen hypersecretion, and alleviate cardiac fibrosis in both in vitro models induced by TGF-β1 and in vivo myocardial infarction (MI) mouse models. Mechanistically, Z11 interfered with the interaction between NAP1L1 and YAP1, which in turn promotes the ubiquitination degradation of YAP1, thereby inhibiting the AKT/mTOR signaling pathway, and attenuating myofibroblast activity and cardiac fibrosis, and improving cardiac function after MI. This finding may provide new insights for the development of promising candidate drugs for the treatment of cardiac fibrosis related diseases in the future.
Nucleosome assembly protein 1-like 1 (NAP1L1), a canonical member of the NAP1 family, orchestrates chromatin architecture and nucleosome dynamics to regulate cell cycle progression, development and proliferation. NAP1L1 is mainly expressed in actively growing cells, and its dysregulation is closely associated with the occurrence of a variety of diseases, including neurodevelopmental disorders, cardiovascular diseases and cancers. Recent studies have revealed that NAP1L1 can influence disease progression by modulating multiple classic signaling pathways such as cGAS-STING, PI3K/AKT and WNT pathways, highlighting its complex involvement in cellular signaling networks. In this review, we systematically summarized the discovery, structural features, and multifaceted biological functions of NAP1L1, with a particular focus on its pathogenic roles in cancer and cardiovascular diseases. We evaluated its potential as a druggable target by integrating computational biology approaches with structural and pharmacological evidence, identifying conserved ligandable pockets and predicting plausible interactions with known bioactive compounds. These findings position NAP1L1 as a potential druggable target with promising prospects at the intersection of chromatin plasticity and signal transduction, and provide comprehensive insights into the therapeutic potential of targeting NAP1L1, providing information and advancement for future clinical strategies.
Aqueous sodium-ion batteries (ASIBs) have surfaced as viable solutions for grid-scale applications characterized by exceptional safety, cost efficiency and eco-friendliness. However, the high freezing point severely restricts low-temperature viability. To overcome this issue, the dimethylacetamide (DMAC) is employed as a co-solvent for the inorganic and cheap 2 m NaCl (m: mol kg-1) electrolyte, achieving a freezing point below -45 °C with remarkable ionic conductivity (2.93 mS cm-1 under -30 °C). Theoretical calculations and experimental measurements reveal that carbonyl group in DMAC engages hydroxyl group from H2O molecules to primarily form 1H₂O-DMAC conformation, disrupting the intrinsic hydrogen bonds interaction of H2O molecules, effectively lowering freezing point of hybrid system. Using optimized electrolyte, the assembled Na2CoFe(CN)6//activated carbon (AC) batteries deliver 70.7 mAh g-1 at 1C (1 C = 150 mA g-1)，with 95 % capacity retention over 10,000 cycles at 10C at -30 °C. Notably, ASIBs successfully power light emitting diodes (1.8 V) at -40 °C. The electrolyte engineering strategy not only significantly enhances the performance of aqueous batteries in cold environments but also underscores their substantial potential for energy storage.
With the development of large language models (LLMs), numerous studies have demonstrated their vulnerability to carefully crafted jailbreak attacks. However, existing mitigation measures rarely balance model usability with significant protective effects, raising concerns about model abuse. To address this, we introduce CoT Defender. It preemptively occupies the model's first few generated tokens with a chain-of-thought analysis that hinders attackers from steering the output towards harmful content. We designed a two-stage training framework that strengthens security while preserving usability. Stage 1 fine-tunes the model to follow a structured chain-of-thought format before answering. Stage 2 employs reinforcement learning to refine this reasoning. An auxiliary attacker model continuously synthesizes new jailbreak prompts, and a lightweight evaluator-Probabilistic Structured Output Evaluation (PSOE)-supplies fine-grained rewards by scoring both sentence-level intent capture and token-level format fidelity. We conducted a series of experiments on four models and six attack methods. Across all models, we successfully reduced the average attack success rate to below 8.0 %, with no more than a 7.0 % impact on the response rate for benign requests. Code is available here. Warning: This paper contains red-team data that may be offensive!
Here, we reported a novel and efficient method for the synthesis of S-alkyl substituted sulfilimines by employing a base-promoted ring-opening reaction of sulfonium salts with sulfenamides. This reaction proceeds smoothly under transition metal-free conditions and under an air atmosphere, allowing facile access to the corresponding products in good to excellent yields through selective C-S bond cleavage and simultaneous formation of a new C-S bond. This strategy features a broad substrate scope and holds promise for applications in late-stage functionalization.
Cardiac fibrosis is a major pathological feature of cardiovascular diseases and a key driver of ventricular remodeling and heart failure, yet effective therapeutic strategies remain limited due to incomplete mechanistic understanding. Heme oxygenase-1 (HO-1), a key redox-regulating enzyme, has recently been implicated in cardiac injury. However, its role in cardiac fibrosis, particularly through the regulation of ferroptosis, remains poorly understood. This study systematically investigated the effects of HO-1-mediated ferroptosis on the progression of cardiac fibrosis. Myocardial infarction was induced by ligation of the left anterior descending coronary artery, and cardiac fibroblasts were stimulated with transforming growth factor-β1 (TGF-β1) to induce fibrosis. Ferroptosis was markedly activated, accompanied by increased ferrous iron (Fe2+) accumulation, enhanced reactive oxygen species (ROS) generation, and elevated levels of lipid peroxidation. Inhibition of ferroptosis significantly alleviated fibrotic responses and improved cardiac function. Mechanistically, ferroptosis suppression restored autophagic flux by correcting lysosomal abnormalities and normalizing LC3B and p62 accumulation. Furthermore, HO-1 was markedly upregulated in fibrotic conditions, promoting ferroptosis and myocardial fibrosis. Activation of HO-1 induced myocardial fibrosis by triggering ferroptosis-associated autophagic dysfunction, whereas HO-1 inhibition mitigated ferroptotic injury, restored autophagic homeostasis, and attenuated fibrosis. Blocking autophagy abolished the protective effects of HO-1 suppression, demonstrating that the antifibrotic role of HO-1-mediated ferroptosis is dependent on autophagic activity. These findings reveal a novel mechanism by which HO-1-mediated ferroptosis impairs autophagic homeostasis to drive cardiac fibrosis, highlighting HO-1 inhibition as a potential therapeutic strategy for attenuating cardiac fibrosis.
Recovery of medium-chain carboxylic acids (MCCA) from food waste is constrained by low efficiency and instability. This study validated a short-term aerobic pretreatment (AP) strategy to enhance fungi-bacteria synergy. In batch tests, AP (0.2 vvm) achieved optimal caproate titers of 22.32 ± 1.56 g COD/L. The pretreatment enriched ethanol-producing yeasts and lactate-producing bacteria, establishing a robust co-electron donor pool. Metagenomic analysis revealed that this synergy suppressed the competing tricarboxylic acid cycle, redirecting carbon flux towards reverse β-oxidation (RBO) pathway and providing essential precursors for Clostridium_sensu_stricto_12. In a 134-day semi-continuous operation, AP sustained high titers (17.2-22.1 g COD/L) through a specialized guild dominated by the Ruminococcaceae bacterium BL-6, avoiding the systemic performance deterioration observed in controls. Life cycle assessment (LCA) confirmed a >60% carbon footprint reduction compared to conventional routes. Short-term aerobic pretreatment effectively regulates microbial succession to stabilize low-carbon MCCA production from food waste.
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