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Considering that ozone is essential to understanding air quality and climate change, this study presents a deep learning method for predicting atmospheric ozone concentrations. The method combines an attention mechanism with a convolutional neural network (CNN) and long short-term memory (LSTM) network to address the nonlinear nature of multivariate time-series data. It employs CNN and LSTM to extract features from short time series, enhanced by the attention mechanism to improved short-term prediction accuracy. It takes eight meteorological and environmental parameters from 16,806 records (2018–2019) as input, which are selected principal component analysis (PCA). It features an attention-based CNN-LSTM hybrid deep learning model with specific settings: a time step of 5, a batch size of 25, 15 units in the LSTM layer, the ReLU activation function, 25 epochs, and an overfitting avoidance strategy with a dropout rate of 0.15. Experimental results demonstrate that this hybrid model outperforms individual models and the CNN-LSTM model, especially in forward prediction with a multi-hour time lag. The model exhibits a high coefficient of determination (R 2  = 0.971) and a root mean square error of 3.59 for a 1-hour time lag. It also exhibits consistent accuracy across different seasons, highlighting its robustness and superior time-series prediction capabilities for ozone concentrations.

Against the backdrop of the rapid diffusion of Artificial Intelligence Generated Content (AIGC) and the rise of the “surprise economy,” trendy blind-box toys have emerged as a consumption context characterized by emotional stimulation and community-based diffusion. Focusing on the question of “conformity or identification,” this study integrates the Stimulus-Organism-Response (SOR) framework and the Theory of Planned Behavior (TPB) to construct a comprehensive model. The model incorporates Psychological Expectation (PE)—including Novelty (NO), Scarcity (SC), Aesthetic Perception (AP), Emotional Value (EV), and Product Identification (PID)—as well as AI Creation Perception (AICP) and Conformity Psychology (CP), with Community Belongingness (CB) introduced as a moderating variable. Based on 514 valid responses, Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) analyses were conducted. The results indicate that NO, AP, EV, PID, AICP, and SC significantly enhance Subjective Norm (SN). With the exception of SC, these variables, together with CP, also significantly strengthen Perceived Behavioral Control (PBC). Both SN and PBC positively influence Attitude (AT), with SN exerting a stronger effect. Furthermore, AT, SN, and PBC all significantly promote Purchase Intention (PI), among which AT demonstrates the greatest impact. CB significantly and positively moderates the relationships between SN and PI, as well as between PBC and PI. The ANN results further highlight the critical roles of NO, PID, and CP along key causal paths. These findings suggest that consumers’ PI are jointly driven by community norms and conformity tendencies, as well as by aesthetic preferences and psychological identification with AI-generated content. Theoretically, this study integrates PE, technology perception, and community mechanisms, supporting 20 of the 21 proposed hypotheses. Practically, it proposes conversion strategies centered on leveraging AIGC to enhance novelty-driven aesthetics, strengthen IP identification, and optimize community operations.

The poverty alleviation relocation program (PAR) is a milestone project in breaking spatial poverty traps in ethnic mountainous regions and provides a key solution for eradicating global absolute poverty. As direct participants in the restructuring of environmental and livelihood systems, the livelihood adaptation of relocated households is fundamental to the sustainable development of human-land systems in resettlement sites and the consolidation of the success of poverty alleviation. This research constructs an adaptive integration analysis framework of “external disturbance-adaptation process-adaptation outcome”, by utilizing questionnaire data from relocated households in the Liangshan Yi minority area of Southwest China, and employing a formative structural equation model to investigate the transmission mechanisms and heterogeneous effects of PAR on livelihood adaptation across different resettlement characteristics. The results indicate that: (1) External disturbance of PAR facilitates positive adaptation outcomes, with follow-up supportive policy as the most significant determinant, which contributes directly to adaptation outcomes and indirectly through improved learning and self-organization capacity. Conversely, risk perception has a negative impact on adaptation outcomes and further exacerbates adverse impacts by reducing buffering capacity. (2) The pathways influencing subjective and objective adaptation outcomes demonstrate heterogeneity. PAR has a positive impact on subjective adaptation, but a non-significant effect on objective adaptation, self-organization capacity and buffering capacity are the most important direct drivers and mediating variables affecting both, respectively. (3) Resettlement characteristics exert a moderating effect on livelihood adaptation. The positive effect of follow-up supportive policy on learning capacity and the marginal contribution of learning capacity to adaptative strategies being greater in mid-to-long-term resettlements. Buffering capacity of village resettlements and subjective adaptation of town resettlements are more beneficial from follow-up supportive policy.

Bacillus methanolicus is a thermophilic methylotrophic bacterium that grows quickly on methanol in sea water–based media. It has been engineered for chemical bioproduction from methanol, but its efficiency needs improvement for industrialization. Synthetic biology approaches such as metabolic modeling and genome editing can reprogram B. methanolicus for low-carbon biomanufacturing. Bacillus methanolicus is a thermophilic methylotrophic bacterium that grows quickly on methanol in sea water–based media. It has been engineered for chemical bioproduction from methanol, but its efficiency needs improvement for industrialization. Synthetic biology approaches such as metabolic modeling and genome editing can reprogram B. methanolicus for low-carbon biomanufacturing.

Exosomes derived from stem cells, as an alternative to stem cells themselves, have been employed for dental pulp regeneration. However, it is not known whether exosomes can recruit host cells to the regeneration process. In this study, we built a \"cell homing\" model to determine whether exosomes derived from dental pulp tissue (DPT-exos) can regenerate dental pulp by recruiting the stem cells from the apical dental papilla (SCAPs). Exosomes were isolated from the dental pulp tissue (DPT-exos) and dental pulp stem cells (DPC-exos) of swine. The effects of the exosomes on SCAPs were compared using CKK-8, Transwell, angiogenesis, and odontogenic induction assays. DPT-exos and DPC-exos were investigated in an in vivo \"cell homing\" model using swine teeth to compare their roles in pulp regeneration. To build the model, we placed SCAP-containing collagen gel at the root tip and filled the cavity of the treated dental matrix (TDM) with DPT-exos and DPC-exos-laden scaffolds, which would be expected to recruit SCAPs to the pulp cavity. The complex was then implanted subcutaneously into immunodeficient nude mice. After eight weeks, tissue samples were taken and analyzed histologically to determine whether the DPT-exos contributed to pulp regeneration through \"cell homing\". Exosomes were successfully extracted from dental pulp tissue and confirmed to be exosomes. In vitro tests confirmed that DPT-exos performed better than DPC-exos in promoting the migration, proliferation, and differentiation of SCAPs. Furthermore, DPT-exos recruited SCAPs to regenerate dental pulp-like connective tissue in vivo containing collagen, odontoblasts, and enriched predentin-like tissue. Blood vessel growth was demonstrated by immunofluorescence. This study demonstrated the ability of DPT-exos to induce SCAPs to regenerate connective tissue similar to natural dental pulp. This technique has the potential for treating pulp deficiency caused by various pulp diseases.

Malachite green (MG), a recalcitrant, carcinogenic, and mutagenic triphenylmethane dye, was decolorized and detoxified using crude manganese peroxidase (MnP) prepared from the white rot fungus Irpex lacteus F17. In this study, the key factors (pH, temperature, MG, Mn 2+ , H 2 O 2 , MnP) in these processes were investigated. Under optimal conditions, 96 % of 200 mg L −1 of MG was decolorized when 66.32 U L −1 of MnP was added for 1 h. The K m , V max , and k cat values were 109.9 μmol L −1 , 152.8 μmol L −1  min −1 , and 44.5 s −1 , respectively. The decolorization of MG by MnP followed first-order reaction kinetics with a kinetic rate constant of 0.0129 h −1 . UV–vis and UPLC analysis revealed degradation of MG. Furthermore, seven different intermediates formed during the MnP treatment of 0.5 h were identified by LC-TOF-MS. These degradation products were generated via two different routes by either N -demethylation of MG or the oxidative cleavage of the C–C double bond in MG. Based on ecotoxicity analyses performed on bacteria and algae, it was confirmed that MG metabolites produced by the MnP-catalyzed system were appreciably less toxic than the parent compound. These studies indicate the potential use of this enzyme system in the clean-up of aquatic and terrestrial environments.

Background The regeneration of bone loss that occurs after periodontal diseases is a significant challenge in clinical dentistry. Extracellular vesicles (EVs)-based cell-free regenerative therapies represent a promising alternative for traditional treatments. Developmental biology suggests matrix vesicles (MVs), a subtype of EVs, contain mineralizing-related biomolecules and play an important role in osteogenesis. Thus, we explore the therapeutic benefits and expect to find an optimized strategy for MV application. Methods Healthy human dental follicle cells (DFCs) were cultured with the osteogenic medium to generate MVs. Media MVs (MMVs) were isolated from culture supernatant, and collagenase-released MVs (CRMVs) were acquired from collagenase-digested cell suspension. We compared the biological features of the two MVs and investigated their induction of cell proliferation, migration, mineralization, and the modulation of osteogenic genes expression. Furthermore, we investigated the long-term regenerative capacity of MMVs and CRMVs in an alveolar bone defect rat model. Results We found that both DFC-derived MMVs and CRMVs effectively improved the proliferation, migration, and osteogenic differentiation of DFCs. Notably, CRMVs showed better bone regeneration capabilities. Compared to MMVs, CRMVs-induced DFCs exhibited increased synthesis of osteogenic marker proteins including ALP, OCN, OPN, and MMP-2. In the treatment of murine alveolar bone defects, CRMV-loaded collagen scaffold brought more significant therapeutic outcomes with less unhealing areas and more mature bone tissues in comparison with MMVs and acquired the effects resembling DFCs-based treatment. Furthermore, the western blotting results demonstrated the activation of the PLC/PKC/MAPK pathway in CRMVs-induced DFCs, while this cascade was inhibited by MMVs. Conclusions In summary, our findings revealed a novel cell-free regenerative therapy for repairing alveolar bone defects by specific MV subtypes and suggest that PLC/PKC/MAPK pathways contribute to MVs-mediated alveolar bone regeneration.

Background Paeonia section Moutan DC. is a significant perennial subshrub, the ornamental value of which heavily depends on the type of flower it possesses. MADS-box transcription factors have a particular impact on the intricate process of floral organ development and differentiation. The release of the whole-genome data from Paeonia ostii now allows us to conduct a thorough investigation of the tree peony MADS-box gene family. Results In this study, we identified 110 MADS-box genes in Paeonia ostii that were classified into 5 subgroups. Gene structure, domain and motif analyses revealed the conservation of the structure of these subgroups. Analysis of the cis -acting elements revealed that the 110 PoMADS genes contained different kinds of hormones and stress-related cis -acting elements in their promoter regions. Quantitative real-time PCR analysis was employed to validate the expression patterns of some PoMADS genes related to floral organ development. Genome collinearity analysis with Arabidopsis and grape revealed the conservation of PoMADS genes during evolution. A total of 857 SSRs were identified by analysing the genome sequences of identified genes. We additionally created protein‒protein interaction networks for PoMADS proteins and analysed proteins that could interact among PoMADSs in Arabidopsis thaliana and grape. Conclusion These findings offer fundamental insights for understanding the function of the MADS-box gene family, which can aid in the selection and breeding of tree peony varieties with high ornamental value in addition to supporting the understanding of the process of tree peony floral organogenesis.

Cold-climate cities remain poorly studied, yet their spontaneous flora is strongly shaped by severe winters and short growing seasons. Heilongjiang Province, the northernmost region of China, provides a valuable case study given its rapid urbanization. As an important component of urban biodiversity, the diversity distribution patterns of spontaneous plants and their underlying causes remain underexplored from multi-scale and multi-dimensional perspectives. Therefore, this study aimed to test how climatic subzones and habitat types jointly influence spontaneous plant diversity across urban landscapes in 14 cities of Heilongjiang Province. Based on vegetation surveys, we applied calculations of α- and β-diversity, along with hierarchical clustering, across climatic subzones, cities, and habitat types to elucidate the diversity patterns and their multi-scale driving mechanisms. The results showed the following: (1) A total of 778 spontaneous plant species were recorded, belonging to 98 families and 395 genera. Native plants accounted for 58.7%, and non-native plants accounted for 41.3% (including 77 invasive species). (2) Perennial herbs dominated overall (45.2%), consistent with winter filtering, whereas annual/biennial herbs were more common in warmer subzones such as II B2. (3) Forest gaps (FG) and shrub–grassland gaps (SG) supported the most diverse spontaneous plant communities, highlighting habitat heterogeneity. (4) Species richness peaked in subzone II B2 and was lowest in subzone I A1, while abandoned land (SA) and shrub–grassland gaps (SG) supported the richest communities. (5) β-diversity analyses indicated homogenization under extreme cold in subzone I A1 and greater turnover in warmer subzone II B2, reflecting contrasting climatic filters. The “light patches” in FG habitats and the “disturbance filtering” in LA habitats further shaped the differences in local communities. This study reveals the diversity distribution patterns and adaptation strategies of spontaneous plants in cold cities, emphasizing their integration into urban planning while addressing the dominance of invasive species.

Against the intensifying global climate change, rural tourism destinations in plateau areas are confronted with the dilemma of balancing economic development with ecological conservation. Pro-environmental behavior (PEB)has become pivotal to achieving regional environmental and tourism sustainability. This study proposes a conceptual model using a sample of 230 rural residents grounded in the Stimulus–Organism–Response (S-O-R) theory. A mediation model incorporating place attachment (PA) is constructed to examine the effects of climate change perception (CCP) and perceived value of tourism (PV) on pro-environmental behavior. Results from structural equation modeling (SEM) reveal the following: (1) Climate change perception directly and positively influences pro-environmental behavior. (2) Place attachment not only directly promotes pro-environmental behavior but also mediates the relationship between perceived value of tourism and pro-environmental behavior. (3) Perceived value of tourism exerts a direct positive effect on pro-environmental behavior in life, whereas its influence on pro-environmental behavior in agricultural production is indirect, mediated through place attachment. These findings suggest that strengthening residents’ emotional and functional connections to the local environment can effectively encourage pro-environmental actions in tourism areas, providing a theoretical basis for formulating environmental policies in high-altitude tourism destinations.