The prevalence of periodontitis in China is as high as 74.2%, making it the leading cause of tooth loss in adults and severely impacting both oral and overall health. The treatment of periodontitis and periodontal tissue regeneration are global challenges of significant concern. GE Shaohua' s group at School and Hospital of Stomatology, Shandong University has focused on the key scientific issue of "remodeling the periodontal inflammatory microenvironment and optimizing tissue repair and regeneration". They have elucidated the mechanisms underlying the persistence of periodontitis, developed bioactive materials to enhance stem cell regenerative properties, and constructed a series of guided tissue regeneration barrier membranes to promote periodontal tissue repair, leading to the establishment of a comprehensive technology system for the treatment of periodontitis. Specific achievements and progress include: (1) Elucidating the mechanism by which key periodontal pathogens evade antimicrobial autophagy, leading to inflammatory damage; developing intelligent antimicrobial hydrogels and nanosystems, and creating metal-polyphenol network microsphere capsules to reshape the periodontal inflammatory microenvironment; (2) Explaining the mechanisms by which nanomaterial structures and electroactive interfaces regulate stem cell behavior, developing optimized nanostructures and electroactive biomaterials, thereby effectively enhancing the regenerative repair capabilities of stem cells; (3) Creating a series of biphasic heterogeneous barrier membranes, refining guided tissue regeneration and in situ tissue engineering techniques, stimulating the body' s intrinsic repair potential, and synergistically promoting the structural regeneration and functional reconstruction of periodontal tissues. The research outcomes of the group have innovated the fundamental theories of periodontal tissue regeneration, broken through foreign technological barriers and patent blockades, established a cascade repair strategy for periodontal regeneration, and enhanced China' s core competitiveness in the field of periodontal tissue regeneration.
Humans ; Stem Cells/physiology* ; Periodontitis/therapy* ; Guided Tissue Regeneration, Periodontal/methods* ; Regeneration ; Biocompatible Materials ; Tissue Engineering/methods*

OBJECTIVES: We propose a segmented backprojection tensor degradation feature encoding (SBP-MAC) model for motion artifact correction in dental cone beam computed tomography (CBCT) to improve the quality of the reconstructed images. METHODS: The proposed motion artifact correction model consists of a generator and a degradation encoder. The segmented limited-angle reconstructed sub-images are stacked into the tensors and used as the model input. A degradation encoder is used to extract spatially varying motion information in the tensor, and the generator's skip connection features are adaptively modulated to guide the model for correcting artifacts caused by different motion waveforms. The artifact consistency loss function was designed to simplify the learning task of the generator. RESULTS: The proposed model could effectively remove motion artifacts and improve the quality of the reconstructed images. For simulated data, the proposed model increased the peak signal-to-noise ratio by 8.28%, increased the structural similarity index measurement by 2.29%, and decreased the root mean square error by 23.84%. For real clinical data, the proposed model achieved the highest expert score of 4.4221 (against a 5-point scale), which was significantly higher than those of all the other comparison methods. CONCLUSIONS The SBP-MAC model can effectively extract spatially varying motion information in the tensors and achieve adaptive artifact correction from the tensor domain to the image domain to improve the quality of reconstructed dental CBCT images.
Cone-Beam Computed Tomography/methods* ; Artifacts ; Humans ; Motion ; Image Processing, Computer-Assisted/methods* ; Signal-To-Noise Ratio ; Algorithms

Objective To propose a low-dose CT reconstruction algorithm across different scanners based on federated feature learning(FedCT)to improve the generalization of deep learning models for multiple CT scanners and protect data privacy.Methods In the proposed FedCT framework,each client is assigned an inverse Radon transform-based reconstruction model to serve as a local network model that participates in federated learning.A projection-domain specific learning strategy is adopted to preserve the geometry specificity in the local projection domain.Federated feature learning is introduced in the model,which utilizes conditional parameters to mark the local data and feed the conditional parameters into the network for encoding to enhance the generalization of the model in the image domain.Results In the cross-client,multi-scanner,and multi-protocol low-dose CT reconstruction experiments,FedCT achieved the highest PSNR(+2.8048,+2.7301,and +2.7263 compared to the second best federated learning method),the highest SSIM(+0.0009,+0.0165,and +0.0131 in the same comparison),and the lowest RMSE(-0.6687,-1.5956,and-0.9962).In the ablation experiment,compared with the general federated learning strategy,the model with projection-specific learning strategy showed an average improvement by 1.18 on Q1 of the PSNR and an average decrease by 1.36 on Q3 of the RMSE on the test set.The introduction of federated feature learning in FedCT further improved the Q1 of the PSNR on the test set by 3.56 and reduced the Q3 of the RMSE by 1.80.Conclusion FedCT provides an effective solution for collaborative construction of CT reconstruction models,which can enhance model generalization and further improve the reconstruction performance on global data while protecting data privacy.

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Objective We propose a dual-domain cone beam computed tomography(CBCT)reconstruction framework DualCBR-Net based on improved differentiable domain transform for cone-angle artifact correction.Methods The proposed CBCT dual-domain reconstruction framework DualCBR-Net consists of 3 individual modules:projection preprocessing,differentiable domain transform,and image post-processing.The projection preprocessing module first extends the original projection data in the row direction to ensure full coverage of the scanned object by X-ray.The differentiable domain transform introduces the FDK reconstruction and forward projection operators to complete the forward and gradient backpropagation processes,where the geometric parameters correspond to the extended data dimension to provide crucial prior information in the forward pass of the network and ensure the accuracy in the gradient backpropagation,thus enabling precise learning of cone-beam region data.The image post-processing module further fine-tunes the domain-transformed image to remove residual artifacts and noises.Results The results of validation experiments conducted on Mayo's public chest dataset showed that the proposed DualCBR-Net framework was superior to other comparison methods in terms of artifact removal and structural detail preservation.Compared with the latest methods,the DualCBR-Net framework improved the PSNR and SSIM by 0.6479 and 0.0074,respectively.Conclusion The proposed DualCBR-Net framework for cone-angle artifact correction allows effective joint training of the CBCT dual-domain network and is especially effective for large cone-angle region.

Objective We propose a motion artifact correction algorithm(DMBL)for reducing motion artifacts in reconstructed dental cone-beam computed tomography(CBCT)images based on deep blur learning.Methods A blur encoder was used to extract motion-related degradation features to model the degradation process caused by motion,and the obtained motion degradation features were imported in the artifact correction module for artifact removal.The artifact correction module adopts a joint learning framework for image blur removal and image blur simulation for treatment of spatially varying and random motion patterns.Comparative experiments were conducted to verify the effectiveness of the proposed method using both simulated motion data sets and clinical data sets.Results The experimental results with the simulated dataset showed that compared with the existing methods,the PSNR of the proposed method increased by 2.88%,the SSIM increased by 0.89%,and the RMSE decreased by 10.58%.The results with the clinical dataset showed that the proposed method achieved the highest expert level with a subjective image quality score of 4.417(in a 5-point scale),significantly higher than those of the comparison methods.Conclusion The proposed DMBL algorithm with a deep blur joint learning network structure can effectively reduce motion artifacts in dental CBCT images and achieve high-quality image restoration.

OBJECTIVE To screen out the pharmacodynamic substances of Cistanches Herba aqueous extracts, explore the basis of the pharmacodynamic substances and their mechanism of action in the treatment of diabetic nephropathy(DN), based on the spectral relationship between the mass spectral peak areas of different elution sites of Cistanches Herba aqueous extracts and their anti-DN effects. METHODS UPLC-Orbitrap-MS/MS technique was used to characterise the chromatographic peaks; MTT method was used to detect the effects of different elution sites of Cistanches Herba aqueous extract on the proliferation of high glucose and high fat HK-2 cells; grey correlation analysis and partial least squares method were used to analyse the spectral relationship between mass spectrometry peak area and anti-DN activity. MTT method was used to determine the anti-DN activities of the individual components of Cistanches Herba aqueous extract; biochemical kit and ELISA were used to determine the levels of oxidative indicators(SOD, GSH-P) and inflammatory factors(IL-1β, TNF-α, TGF-β); Western blotting was used to detect the expression of apoptosis-related proteins. RESULTS UPLC-Orbitrap-MS/MS technique speculated and identified 72 common compounds; In Cistanches Herba aqueous extracts, water, 20% ethanol, and 40% ethanol-eluted sites differentially increased the proliferation rate of HK-2 cells in a high-sugar, high-fat environment; Partial least squares and grey correlation analyses showed that the constituents of the aqueous extracts of Cistanches Herba with greater anti-DN contributions were 8-epideoxymatricinic acid, geniposidic acid, pinoresinol, betaine and syringin, et al. MTT assay reveals that 8-epi-deoxystrychnic acid and geniposidic acid had significant proliferative effects on HK-2 cells in a high glucose and high fat environment; Biochemical kit and ELISA showed that 8-epideoxystrychnic acid and geniposidic acid were able to up-regulate the activity of SOD and GSH-Px, and at the same time they had an inhibitory effect on the expression of inflammatory factors IL-1β, TNF-α and TGF-β. Western blotting results showed that 8-epideoxystrychnic acid and geniposidic acid were able to down-regulate and up-regulate the markers of dermal mesenchymal transition: α-SMA, Collagen Ⅰ and E-cadherin, and they could exert anti-DN effects by inhibiting the PI3K-Akt pathway. CONCLUSION The two compounds, 8-epideoxystrychnic acid and geniposidic acid, which are screened by the spectroeffective relationship of anti-DN among the many chemical constituents contained in Cistanches Herba, can affect oxidative stress, inflammation and epithelial-mesenchymal transformation of renal tubular cells by inhibiting the PI3K-Akt signalling pathway, and improve renal pathology, degree of fibrosis and renal function, which will be useful for the in-depth study of aqueous extracts of Cistanches Herba in the treatment of DN.

BACKGROUND:Total knee arthroplasty is an effective treatment for late-stage osteoarthritis,but postoperative pain and joint function recovery are the main challenges.Nerve block and mixed drug injection are two common pain relief methods,but the effect of their combined use is still unclear. OBJECTIVE:To investigate the effects of ultrasound-guided continuous adductor canal block+single sciatic nerve block+"cocktail"mixed drug analgesia on postoperative pain relief and joint function recovery in total knee arthroplasty. METHODS:120 patients with osteoarthritis admitted to Hebei Province Cangzhou Hospital of Integrated Traditional and Western Medicine from January to May 2022 were randomly divided into two groups(n=60).The observation group received ultrasound-guided continuous adductor canal block+single sciatic nerve block+"cocktail"mixed drug analgesia.The control group received ultrasound-guided continuous adductor canal block+single sciatic nerve block.The differences in visual analog scale score,hospital for special surgery score,pain mediators,expression levels of inflammatory factors,the occurrence of adverse reactions,and postoperative barehanded muscle strength test were compared between the two groups. RESULTS AND CONCLUSION:(1)The visual analog scale scores at rest and exercise were lower in the observation group than those in the control group at 6,8,12,24,48,and 72 hours postoperatively(P<0.05).(2)Hospital for special surgery scores at 1 and 3 months postoperatively were significantly higher in the observation group than those in the control group(P<0.05).(3)In terms of pain mediators and inflammatory factors,the expression levels were significantly lower in the observation group than those in the control group(P<0.05).(4)There was no statistically significant difference in terms of adverse effects and postoperative barehanded muscle strength examination between the two groups(P>0.05).(5)In total knee arthroplasty,ultrasound-guided continuous adductor canal block and single sciatic nerve block,together with a"cocktail"mixed drug analgesia injected into the joint cavity,can provide excellent analgesia,facilitate the recovery of joint function,and relieve postoperative pain and inflammation with a high degree of safety.

Objective To investigate the diagnostic value of serum soluble fms-like tyrosine kinase 1(sFlt-1)and soluble differentiation cluster 14(sCD14)in stroke-associated pneumonia(SAP).Methods A total of 67 SAP patients admitted to the hospital from March 2022 to January 2023 were selected as the study group,and 50 stroke patients without pneumonia during the same period were selected as the control group.Enzyme-linked immunosorbent assay was used to measure serum sFlt-1 and sCD14 levels.Pearson correlation analysis was used to analyze the correlation between serum sFlt-1,sCD14 levels and clinical data.Multivariate Logistic regression was used to analyze the influencing factors of SAP in patients with stroke.Receiver operating char-acteristic(ROC)curve was used to analyze the diagnostic value of serum sFlt-1 and sCD14 levels in predicting SAP in patients with stroke.Results The serum levels of sFlt-1 and sCD14 in SAP patients were higher than those in stroke patients without pneumonia and stroke patients with pneumonia alone(P＜0.05).SAP in stroke patients was associated with age,atrial fibrillation,heart failure,aspiration,dysphagia,brain stem stroke,proton pump inhibitor use,fever,cough,dyspnea,low-density lipoprotein cholesterol,procalcitonin(PCT),C-reactive protein,white blood cell count,national institutes of health stroke scale(NIHSS)score,clinical pulmonary infection(CPIS)score(P＜0.05).Correlation analysis showed that serum sFlt-1 level was positively correlated with sCD14(r=0.439,P＜0.001),and serum sFlt-1 and sCD14 levels were positively correlated with NIHSS score and CPIS score(P＜0.05).Multivariate Logistic regression analysis showed that sFlt-1,sCD14,proton pump inhibitor use,PCT,dysphagia,and age were the influencing factors of SAP in stroke patients(P＜0.05).ROC curve results showed that the area under the curve of serum sFlt-1 and sCD14 combined to evaluate SAP in stroke patients was higher than that of single detection(ZsFlt-1-combined=2.194,P=0.028,ZscD14-combined=2.310,P=0.002).Conclusion The serum levels of sFlt-1 and sCD14 are in-creased in SAP patients,and the combination of the two has a good diagnostic value for predicting the occur-rence of SAP.

Objective:To observe the proteomic changes in vitreous fluid samples from patients with rhegmatogenous retinal detachment combined with choroidal detachment (RRDCD).Methods:A prospective cross-sectional clinical study. Vitreous fluid samples were collected from 35 patients with RRDCD (RRDCD group) and 40 patients with rhegmatogenous retinal detachment (RRD group) who were diagnosed at Wuhan Aier Eye Hospital between November 2021 and December 2023. Prior to vitrectomy, 0.3-0.5 ml of vitreous fluid was collected from the affected eyes. Differentially expressed proteins were analyzed using Data-Independent Acquisition (DIA). Three of these proteins were randomly selected for validation using enzyme-linked immunosorbent assay (ELISA). Bioinformatics analyses, including gene ontology functional enrichment and kyoto encyclopedia of genes and genomes pathway enrichment, were performed to explore the functions of the differentially expressed proteins.Results:Significant differences were observed between the RRDCD and RRD groups in intraocular pressure ( t=-12.795), the number of retinal tears ( t=4.601), the extent of retinal detachment ( χ2=39.642), axial length ( t=0.840), postoperative proliferative vitreoretinopathy incidence ( χ2=4.730), single-surgery reattachment rate ( χ2=7.717), and best-corrected visual acuity ( t=7.033) at 6 months postoperatively ( P<0.05). A total of 237 differentially expressed proteins were identified between the RRDCD and RRD groups, with 63 upregulated and 174 downregulated. These proteins were involved in pathways such as extracellular matrix-receptor interaction, complement activation, coagulation, and lysosomal pathways. ELISA validation results showed that the expression trends of the three selected proteins in the RRDCD and RRD groups were consistent with the DIA proteomic analysis. Compared to the RRD group, proteins such as fibrin, coagulation factors, cathepsins, and trypsin inhibitors were significantly upregulated in the RRDCD group. Conclusions:The protein expression profile in vitreous fluid samples from RRDCD patients show significant alterations compared to the RRD group. These differential changes suggest that RRDCD is closely associated with complement and coagulation cascade activation, lysosomal pathways, and extracellular matrix remodeling.