Objective To investigate the regulatory role of the programmed cell death protein 1 (PD-1) and its ligand programmed cell death protein ligand 1 (PD-L1) signaling on the subtypes and functions of natural killer (NK) cells at the maternal-fetal interface during the second trimester in mice following Toxoplasma gondii infection during the first trimester. Methods Twelve 6- to 8-week-old female mice of the C57BL/6J strain were divided into a control group and an infection group, of 6 mice in each group. On the 6.5th day of pregnancy (Gd6.5), each pregnant mouse in the infection group was intraperitoneally injected with 150 tachyzoites of the Toxoplasma gondii PRU strain, while mice in the control group were injected with an equal volume of physiological saline. On the 12.5th day of pregnancy (Gd12.5), uterus and placenta tissues were sampled from pregnant mice for pathological observations, and the mRNA expression levels of PD-1, PD-L1, and tumor necrosis factor-α (TNF-α) were quantified in uterus and placenta tissues. The PD-1 and DX5 expression was measured on NK cells at the maternal-fetal interface using flow cytometry. In addition, the in vitro JEG-3 trophoblast cells and NK-92MI cells co-culture system was established as the control group, and the addition of T. gondii tachyzoites in the co-culture system served as the infection group. The PD-1, PD-L1, and DX5 mRNA expression was quantified in cells using real-time fluorescence quantitative reverse transcription PCR (RT-qPCR) assay, and the TNF-α concentration was measured in the cell culture supernatant using enzyme-linked immunosorbent assay (ELISA). Results On Gd12.5, clear and intact cellular structures of placental decidual tissues were seen in pregnant mice in the control group, with no remarkable abnormal changes found in the uterine columnar epithelial cells, and inflammatory cell infiltration and blood stasis at varying degrees were found in uterine and placental tissues from pregnant mice in the infection group. The relative PD-1, PD-L1, and TNF-α mRNA expression was (1.004 ± 0.004), (1.001 ± 0.001), and (1.001 ± 0.001) in uterine tissues from pregnant mice in the control group and (2.480 ± 0.720), (3.355 ± 0.920), and (2.391 ± 0.073) in the infection group, respectively. The relative PD-1, PD-L1, and TNF-α mRNA expression was (1.007 ± 0.010), (1.006 ± 0.006), and (1.001 ± 0.001) in the uterine tissues in the control group and (6.948 ± 1.918), (3.225 ± 1.034), and (1.536 ± 0.150) in the infection group, respectively. The relative PD-1, PD-L1, and TNF-α mRNA expression was higher in both the uterine (t = 3.55, 4.43 and 33.02, all P values < 0.05) and placental tissues (t = 5.36, 3.72 and 6.18, all P values < 0.05) in the infection group than in the control group. Flow cytometry showed that the proportions of PD-1⁺ NK cells, PD-1⁺ DX5⁺ NK cells, and DX5⁺ NK cells were (12.200 ± 1.082)%, (9.373 ± 7.728)%, and (44.000 ± 4.095)% in uterine tissues from pregnant mice in the control group, and (21.733 ± 1.630)%, (18.767 ± 1.242)%, and (73.367 ± 0.611)% in the infection group, respectively. The proportions of PD-1⁺ NK cells, PD-1⁺ DX5⁺ NK cells, and DX5⁺ NK cells were (1.100 ± 0.510)%, (2.277 ± 1.337)%, and (96.167 ± 2.831)% in placental tissues from mice in the control group, and (26.867 ± 9.722)%, (23.433 ± 6.983)%, and (82.467 ± 2.248)% in the infection group, respectively. The proportions of PD-1⁺ NK cells (t = 8.45, P < 0.05) and DX5⁺ NK cells (t = 12.29, P < 0.05) were higher in uterine tissues from pregnant mice in the infection group than in the control group, and no significant difference was seen in the proportion of PD-1⁺ DX5⁺ NK cells (Z = -1.09, P > 0.05). The proportions of PD-1⁺ NK cells (t = 4.58, P < 0.05) and PD-1⁺ DX5⁺ NK cells (t = 5.15, P < 0.05) were higher in placental tissues from pregnant mice in the infection group than in the control group, while the proportion of DX5⁺ NK cells was lower in the infection group than in the control group (t = -6.56, P < 0.05). RT-qPCR assay revealed that the relative PD-1, PD-L1, and DX5 mRNA expression was (1.010 ± 0.005), (1.002 ± 0.003), and (1.001 ± 0.001) in the JEG-3 cells and NK92MI cells co-culture system and (3.638 ± 1.258), (0.397 ± 0.158), and (4.267 ± 1.750) in the control group, and ELISA measured that the TNF-α concentration was higher in the cell culture supernatant in the infection group [(22.056 ± 3.205) pg/mL] than in the control group [(12.441 ± 0.001) pg/mL] (t = 5.20, P < 0.05). The PD-1(t = 3.62, P < 0.05) and DX5 mRNA expression (t = 3.23, P < 0.05) was higher in the infection group than in the control group, and the PD-L1 mRNA expression was lower in the infection group than in the control group (t = -6.63, P < 0.05). Conclusions Following T. gondii infection, both PD-L1 expression and PD-1 expression on DX5⁺ NK cells at the maternal-fetal interface are upregulated in mice during the second trimester; however, the proportion of DX5⁺ NK cells decreases. These findings suggest that PD-1/PD-L1 signaling may suppress NK cell functions by modulating DX5⁺ NK cell subsets.

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

OBJECTIVE: To elucidate the molecular mechanisms underlying sepsis-induced injury in mouse intestinal organoids and investigate the possible mechanisms or potential drug targets of myeloid differentiation factor 88 inhibitor [TJ-M2010-5 (TJ5)] on this condition. METHODS: Small intestinal organoids from C57BL/6 mice aged 6-8 weeks were established and characterized using immunofluorescence for cell growth and proliferation marker nuclear antigen Ki-67, goblet cell marker mucin-2 (MUC-2), epithelial cell marker E-cadherin, and Paneth cell marker lysozyme (Lyz). Small intestinal organoids after 3 days of passaging were divided into different groups: a normal control group treated with culture medium containing 0.2% dimethyl sulfoxide (DMSO) for 10 hours, a lipopolysaccharide (LPS) group treated with culture medium containing 200 mg/L LPS and 0.2% DMSO for 10 hours, and a TJ5 group pre-treated with 10 mmol/L TJ5 for 2 hours followed by treatment with culture medium containing 200 mg/L LPS for 10 hours. Real-time fluorescence quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to measure the expression levels of interleukin-6 (IL-6) and zonula occludens-1 (ZO-1) in the small intestinal organoids. RNA transcriptome sequencing was performed on the small intestinal organoids from each group to analyze differentially expressed genes between groups, and significant enrichment was analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: By the 7th day of primary culture, mature organoids had formed, and their growth rate increased after passaging. Immunofluorescence identification showed expressions of Ki-67, MUC-2, E-cadherin, and Lyz, indicating that the mouse small intestinal organoids maintained their cellular composition and functional characteristics under in vitro culture conditions. RT-qPCR results showed that compared with the normal control group, the mRNA expression of IL-6 in the small intestinal organoids of the LPS group was significantly increased (2^-ΔΔCT: 1.83±0.16 vs. 1.02±0.28, P < 0.05), while the mRNA expression of ZO-1 was significantly decreased (2^-ΔΔCT: 0.53±0.11 vs. 1.01±0.18, P < 0.05). In contrast, the mRNA expression trends of both IL-6 and ZO-1 were reversed in the TJ5 group, showing statistically significant differences as compared with the LPS group (2^-ΔΔCT: IL-6 mRNA was 1.24±0.01 vs. 1.83±0.16, ZO-1 mRNA was 1.97±0.29 vs. 0.53±0.11, both P < 0.05). RNA transcriptome sequencing showed 49 differentially expressed genes in the LPS group compared to the normal control group, with 42 upregulated and 7 downregulated. Compared to the LPS group, the TJ5 group showed 84 differentially expressed genes, with 47 upregulated and 37 downregulated. GO enrichment analysis of these differentially expressed genes showed that the significantly enriched biological processes of the differentially expressed genes between the normal control group and the LPS group included responses to LPS, responses to molecule of bacterial origin and responses to bacterium. The significantly enriched biological processes of the differentially expressed genes between the LPS group and the TJ5 group included glutathione metabolic processes, responses to stress cellular and responses to chemical stimulus. In molecular function groups, glutathione binding and oligopeptide binding were significantly enriched by the differentially expressed genes. In cellular component classifications, the enrichment of the differentially expressed genes was mainly observed in the cytoplasm, endoplasmic reticulum, and microsomes. KEGG pathway enrichment analysis indicated that the differentially expressed genes between the normal control group and LPS group were enriched in IL-17 signaling pathways, tumor necrosis factor (TNF) signaling pathways, viral protein interactions with cytokines and cytokine receptors signaling pathways, and cytokine-cytokine receptor interaction signaling pathways. In contrast, the differentially expressed genes between the LPS and TJ5 groups were mainly enriched in atherosclerosis signaling pathways, ferroptosis signaling pathways, glutathione metabolism signaling pathways, and cytochrome P450-mediated drug metabolism signaling pathways. CONCLUSIONS Mouse small intestinal organoids were successfully extracted and cultured. TJ5 may exert its protective effects by regulating gene expression and related signaling pathways (fluid shear stress and atherosclerosis, ferroptosis, glutathione metabolism, cytochrome P450 drug metabolism, etc.) in sepsis-injured mouse small intestinal organoids. These genes and signaling pathways may be key targets for treating sepsis-induced intestinal injury.
Animals ; Mice ; Sepsis/genetics* ; Organoids/drug effects* ; Mice, Inbred C57BL ; Intestine, Small/metabolism* ; Gene Expression Profiling ; Transcriptome ; Lipopolysaccharides

Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.