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With the rapid acceleration of industrialization and urbanization in China, PM2.5 pollution has emerged as a major challenge to public health and sustainable development of the society and economy. At the interprovincial level, PM2.5 exhibits a complex spatial correlation network structure. Using data from 31 provinces in China from 2000 to 2023, this study constructed a spatial correlation network of PM2.5 and analyzed its structural characteristics and formation mechanisms. The results reveal that China’s PM2.5 spatial correlation network is both complex and stable, underscoring the severity of the pollution problem. The network demonstrates a distinct ‘core–periphery’ distribution, with provinces such as Jiangsu, Shandong, and Henan occupying central positions and functioning as critical bridges. Block model analysis showed a clear role of differentiation among provinces in the diffusion of pollution. Temporal exponential random graph model suggests that geographical proximity, industrial structure, vehicle ownership, and government intervention are key factors shaping the network. Geographically adjacent provinces are more likely to form close connections, whereas environmental regulation and vehicle ownership tend to constrain the spread of pollution. This study provides a novel theoretical framework for understanding the spatial diffusion pathways of PM2.5 pollution and offers important policy implications for optimizing and implementing cross-regional air quality governance strategies in China.

Periodontitis is an inflammatory disease that affects the periodontal supporting tissues. Its cardinal clinical manifestations encompass gingival inflammation, periodontal pocket formation, and alveolar bone resorption. Urolithin A (UA), a gut microbiota-derived metabolite of ellagitannins, is known for its anti-inflammatory and osseous-protective properties. Nonetheless, the impact of UA on periodontitis remains unknown. To investigate the preventive effect of UA, we employed a lipopolysaccharide (LPS)-induced inflammation model in RAW 264.7 mouse macrophages, a receptor activator of nuclear factor-κB ligand (RANKL)-induced osteoclast differentiation model, and a ligature-induced periodontitis model in mice. The expression of inflammatory factors (tumor necrosis factor-α, TNF-α; interleukin-6, IL-6) was analyzed to assess anti-inflammatory efficacy. Bone loss in mice with periodontitis was assessed through histological and imaging techniques, including haematoxylin and eosin staining to evaluate alveolar bone morphology, Masson’s trichrome staining to visualize collagen fiber distribution, and micro-computed tomography scanning to quantify bone structural parameters. Additionally, we investigated the underlying mechanisms by examining osteoclast activity through tartrate-resistant acid phosphatase staining and the expression levels of proteins RANKL and osteoprotegerin (OPG). We found that UA reduced IL-6 and TNF-α levels in vitro and in vivo, inhibited osteoclast differentiation, and decreased the RANKL/OPG ratio in periodontitis mice.

Facial expression recognition (FER) in-the-wild is challenging due to unconstraint settings such as varying head poses, illumination, and occlusions. In addition, the performance of a FER system significantly degrades due to large intra-class variation and inter-class similarity of facial expressions in real-world scenarios. To mitigate these problems, we propose a novel approach, Discriminative Attention-augmented Feature Learning Convolution Neural Network (DAF-CNN), which learns discriminative expression-related representations for FER. Firstly, we develop a 3D attention mechanism for feature refinement which selectively focuses on attentive channel entries and salient spatial regions of a convolution neural network feature map. Moreover, a deep metric loss termed Triplet-Center (TC) loss is incorporated to further enhance the discriminative power of the deeply-learned features with an expression-similarity constraint. It simultaneously minimizes intra-class distance and maximizes inter-class distance to learn both compact and separate features. Extensive experiments have been conducted on two representative facial expression datasets (FER-2013 and SFEW 2.0) to demonstrate that DAF-CNN effectively captures discriminative feature representations and achieves competitive or even superior FER performance compared to state-of-the-art FER methods.

Recurrent oncogenic mutations of MyD88 have been identified in a variety of lymphoid malignancies. Gain-of-function mutations of MyD88 constitutively activate downstream NF-κB signaling pathways, resulting in increased cellular proliferation and survival. However, whether MyD88 activity can be aberrantly regulated in MyD88-wild-type lymphoid malignancies remains poorly understood. SPOP is an adaptor protein of CUL3-based E3 ubiquitin ligase complex and frequently mutated genes in prostate and endometrial cancers. In this study, we reveal that SPOP binds to and induces the nondegradative ubiquitination of MyD88 by recognizing an atypical SPOP-binding motif in MyD88. This modification blocks Myddosome assembly and downstream NF-κB activation. SPOP is mutated in a subset of lymphoid malignancies, including diffuse large B-cell lymphoma (DLBCL). Lymphoid malignancies-associated SPOP mutants exhibited impaired binding to MyD88 and suppression of NF-κB activation. The DLBCL-associated, SPOP-binding defective mutants of MyD88 escaped from SPOP-mediated ubiquitination, and their effect on NF-κB activation is stronger than that of wild-type MyD88. Moreover, SPOP suppresses DLBCL cell growth in vitro and tumor xenograft in vivo by inhibiting the MyD88/NF-κB signaling. Therefore, SPOP acts as a tumor suppressor in DLBCL. Mutations in the SPOP–MyD88 binding interface may disrupt the SPOP–MyD88 regulatory axis and promote aberrant MyD88/NF-κB activation and cell growth in DLCBL.

A Pickering emulsion was prepared using β-cyclodextrin (β-CD) and a cinnamaldehyde (CA)/β-CD composite as emulsifiers and corn oil, camellia oil, lard oil, and fish oil as oil phases. It was confirmed that Pickering emulsions prepared with β-CD and CA/β-CD had good storage stability. The rheological experiments showed that all emulsions had G′ values higher than G″, thus confirming their gel properties. The results of temperature scanning rheology experiments revealed that the Pickering emulsion prepared with β-CD and CA/β-CD composites had high stability, in the range of 20–65 °C. The chewing properties of Pickering emulsions prepared by β-CD and corn oil, camellia oil, lard, and herring oil were 8.02 ± 0.24 N, 7.94 ± 0.16 N, 36.41 ± 1.25 N, and 5.17 ± 0.13 N, respectively. The chewing properties of Pickering emulsions made with the CA/β-CD composite and corn oil, camellia oil, lard, and herring oil were 2.51 ± 0.05 N, 2.56 ± 0.05 N, 22.67 ± 1.70 N, 3.83 ± 0.29 N, respectively. The texture properties confirmed that the CA/β-CD-composite-stabilized-emulsion had superior palatability. After 28 days at 50 °C, malondialdehyde (MDA) was detected in the emulsion. Compared with the β-CD and CA + β-CD emulsion, the CA/β-CD composite emulsion had the lowest content of MDA (182.23 ± 8.93 nmol/kg). The in vitro digestion results showed that the free fatty acid (FFA) release rates of the CA/β-CD composite emulsion (87.49 ± 3.40%) were higher than those of the β-CD emulsion (74.32 ± 2.11%). This strategy provides ideas for expanding the application range of emulsifier particles and developing food-grade Pickering emulsions with antioxidant capacity.

Objective Analyse the correlation between the changes in joint space of TMJ and the displacement and degree of articular disc for clinical diagnosis. Methods Two hundred sixteen TMJs of 108 temporomandibular disorders (TMD) patients with clinical symptoms and MRI examination were included in the study. 30 of these patients had undergone CBCT before MRI. According to the degree of articular disc displacement, the 216 joints are divided into five groups. Group A: no disc displacement (40 cases); group B: mild anterior disc displacement (44 cases); group C: moderate anterior disc displacement (36 cases); group D: severe anterior disc displacement (52 cases); group E: posterior displacement (44 cases). The 132 sides of these anteriorly displaced discs (ADD) were further divided into two groups, anterior disc displacement with reduction (ADDwR) and anterior disc displacement without reduction (ADDwoR). We analysed the concordance of the joint space measured by MRI and CBCT, and explored the relationship between joint space, ln(P/A) values and joint disc displacement. Results There was no statistically significant difference between the joint spaces measured by CBCT and MRI ( P  > 0.05). The anterior joint space in group B (2.7 ± 0.72 mm) and C (2.82 ± 0.88 mm) was larger than group A (1.82 ± 0.50 mm) ( P  < 0.05), and ln(P/A) value in group B (-0.52 ± 0.34) and C (-0.62 ± 0.43) was smaller than group A (0.04 ± 0.15) ( P  < 0.05). The posterior joint space (3.33 ± 1.28 mm) and ln(P/A) value (0.74 ± 0.33) in group E was larger than group A ( P  < 0.05). There was no significant difference in the anterior, superior and posterior joint space and ln(P/A) value between group D and A ( P  > 0.05). The ADDwR group had a larger anterior joint space (2.72 ± 0.83 mm) than group A ( P  < 0.05), while having a smaller posterior joint space (1.61 ± 0.49 mm) and ln(P/A) value (-0.52 ± 0.39 mm) ( P  < 0.05). Compared with group A, there was no significant difference in the anterior joint space and ln(P/A) value in the ADDwoR group( P  > 0.05). Conclusion There is no significant change in anterior, supra, and posterior joint space in severe anterior disc displacement. The anterior joint space increases in mild to moderate anterior disc displacement, but does not change in severe anterior disc displacement—the posterior joint space increases when the joint disc is displaced posteriorly. The position of the joint disc cannot be accurately inferred by observing the joint space through CBCT, and a combination of MRI and clinical examination is required to make a definitive judgement.

Objective The chief aim of this study was to confirm the accuracy and repeatability of digital indirect bonding (IDB) by simulating customized clinical orthodontic procedures with personalized typodonts from the perspective of orthodontic outcomes. Methods Five personalized typodonts were produced with 3D-printing technology to mimic straight-wire orthodontic procedures. The digital IDB was employed to position the customized brackets. After treatment, the PAR index, the ABO-OGS index and the occlusal contact area were analyzed. The matching degree between the target position and the posttreatment position on typodonts was assessed with Geomagic Control X. Results The mean arch discrepancy between the personalized typodonts and the initial intraoral scan model was 0.15 mm ± 0.01 mm in the maxilla and 0.20 mm ± 0.01 mm in the mandible. Following customized orthodontic therapy, the PAR Index decreased from 29 to 1, the ABO-OGS Index was 13.8 ± 0.84, and the occlusal contact area increased 4.04mm 2  ± 1.14mm 2 , with the bilateral occlusal contact area becoming equally distributed. The mean arch discrepancy between the target position and the actual posttreatment positions was 0.15 mm ± 0.01 mm in the maxilla and 0.16 mm ± 0.01 mm in the mandible. Conclusions Digital IDB is conducive to locating the brackets in the target position to precisely achieve the ideal therapeutic outcome of customized orthodontic systems on the personalized typodont. The customized bracket design and the digital IDB can lead orthodontics in a more accurate, visual, and predictable direction.

ObjectivesTo develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.MethodsEight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without.ResultsPET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit.Conclusion18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best.Critical relevance statement18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.Key points• 18F-FDG PET/CT radiomics signature is valuable to identify the presence of MP/S components in lung adenocarcinoma non-invasively.• Gender and N stage are independent predictors of differentiation in patients with or without MP/S components.• The nomogram integrating 18F-FDG PET/CT radiomics and clinical characteristics improves predictive performance.

Native soy protein isolate (N-SPI) has a low denaturation point and low solubility, limiting its industrial application. The influence of different industrial modification methods (heat (H), alkaline (A), glycosylation (G), and oxidation (O)) on the structure of SPI, the properties of the gel, and the gel properties of soy protein isolate (SPI) in myofibril protein (MP) was evaluated. The study found that four industrial modifications did not influence the subunit composition of SPI. However, the four industrial modifications altered SPI’s secondary structure and disulfide bond conformation content. A-SPI exhibits the highest surface hydrophobicity and I850/830 ratio but the lowest thermal stability. G-SPI exhibits the highest disulfide bond content and the best gel properties. Compared with MP gel, the addition of H-SPI, A-SPI, G-SPI, and O-SPI components significantly improved the properties of the gel. Additionally, MP-ASPI gel exhibits the best properties and microstructure. Overall, the four industrial modification effects may impact SPI’s structure and gel properties in different ways. A-SPI could be a potential functionality-enhanced soy protein ingredient in comminuted meat products. The present study results will provide a theoretical basis for the industrialized production of SPI.