BACKGROUND:Cannabidiol is effective in ameliorating the body's inflammatory response,but no clear mechanistic studies have been conducted to ameliorate skeletal muscle inflammation induced by exhaustive exercise. OBJECTIVE:To explore the mechanism by which cannabidiol improves skeletal muscle inflammation during exhaustive exercise by using transcriptome sequencing technology. METHODS:Thirty-six Sprague-Dawley rats were randomly divided into six groups:blank control group,exercise coconut oil group,exercise control group,50 mg/kg cannabidiol group,60 mg/kg cannabidiol group,and 70 mg/kg cannabidiol group,with six rats in each group.Except for rats in the blank control group,rats in each group were subjected to swimming exercise for 9 days to produce the exhaustive exercise model.At the end of each swimming exercise,rats in the cannabidiol groups were given 2 mL of fat-soluble cannabidiol at different concentrations(50,60,and 70 mg/kg)by gavage;rats in the exercise coconut oil group were given the same volume of coconut oil by gavage until the end of the exercise on the 9th day;and rats in the blank control group and the exercise control group were not given any special treatment.The levels of inflammatory factors and differentially expressed genes in the skeletal muscle of rats in each group were determined using ELISA and transcriptome sequencing techniques.Differentially expressed genes obtained were subjected to KEGG analysis,and the accuracy of the sequencing data was verified by fluorescence quantitative PCR. RESULTS AND CONCLUSION:The results of ELISA showed that the contents of interleukin-6(P<0.05),tumor necrosis factor-α(P<0.01),interleukin-10 and other inflammatory factors in the exercise group increased significantly compared with the blank control group and the coconut oil group.After cannabidiol intervention,the mass concentrations of interleukin-6 and tumor necrosis factor-α showed a sequential decrease with increasing cannabidiol concentration.By comparing GO and KEGG databases,the functional properties of differentially expressed genes were analyzed,and the results showed that the differentially expressed genes were mainly involved in the tumor necrosis factor signaling pathway and the Toll-like receptor signaling pathway.RT-qPCR results showed that the trends of five randomly selected differentially expressed genes were in agreement with the transcriptome sequencing results.To conclude,cannabidiol can improve skeletal muscle inflammation caused by exhaustive exercise.

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.

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.

ObjectiveTo investigate the mechanism of Huangqi Gegentang （HGT） in the treatment of type 2 diabetes mellitus （T2DM） through the application of proteomic techniques. MethodsThe rat model of T2DM was established by streptozotocin combined with a high-fat， high-sugar diet. Thirty-two male SD rats were randomized into four groups： blank， model， HGT （8.10 g·kg^-1·d^-1）， and positive control （metformin hydrochloride， 76.5 mg·kg^-1·d^-1）. After 6 weeks of drug intervention， the fasting blood glucose level was measured， and an oral glucose tolerance test （OGTT） was performed. The area under the curve （AUC） was calculated. Enzyme-linked immunosorbent assay was performed to assess the level of glycated hemoglobin （GHbA1c） in the serum. The limulus amebocyte lysate assay was employed to measure the serum level of lipopolysaccharide （LPS）. Pathological changes in the colon were observed by hematoxylin-eosin staining. The mRNA levels of pro-inflammatory cytokines including tumor necrosis factor （TNF）-α， interleukin （IL）-6， and IL-1β in the colon tissue were quantified via Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. Additionally， the protein and mRNA levels of zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 in the colon tissue were assessed by Western blot and Real-time PCR， respectively. Label-free quantitative proteomics was employed to identify the differentially expressed proteins between the colon tissue samples from the blank， model， and HGT groups. Key proteins identified were subsequently validated by Western blot and Real-time PCR. Finally， bioinformatics analysis was conducted on the differentially expressed proteins. ResultsCompared with the blank group， the model group exhibited increased fasting blood glucose， AUC， and GHbA1c levels （P<0.01）， damaged colonic mucosal epithelial structure and inflammatory cell infiltration， up-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon and an increase in serum LPS content （P<0.05， P<0.01）， and down-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.01）. Compared with the model group， the HGT group showed reductions in fasting blood glucose， AUC， and GHbA1c （P<0.01）， alleviated damage to the colonic mucosal epithelium， down-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon， a reduction in serum LPS content （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.05， P<0.01）. Proteomics analysis identified 70 differentially expressed proteins that exhibited a downward trend in the model group relative to the blank group and an upward trend in the HGT group relative to the model group. These findings were corroborated by Western blot and Real-time PCR， which confirmed that the protein and mRNA levels of mucin 2 （Muc2） and transforming growth factor （TGF）-beta receptor 1 （Tgfbr1） in the colon tissue were consistent with the proteomic data. Bioinformatics analysis showed that these 70 differentially expressed proteins identified were significantly enriched in multiple signaling pathways， among which the TGF-β and advanced glycation endproduct （AGE）/receptor for advanced glycation endproduct （RAGE） signaling pathways were closely associated with damage to the intestinal mucosal barrier. This suggests that HGT may ameliorate intestinal mucosal barrier damage by regulating these pathways. ConclusionHGT potentially exerts anti-T2DM effects by influencing AGE/RAGE and TGF-β signaling pathways， thereby contributing to the restoration of the intestinal mucosal barrier.

Objective: To investigate the effects of Zuogui Jiangtang Yishen Formula (左归降糖益肾方, ZGJTYSF) in regulating the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) signaling axis on pyroptosis in rats with diabetic kidney disease (DKD). Methods: Fifty male specific pathogen-free (SPF) grade Goto-Kakizaki (GK) rats (12 weeks old) were fed a high-fat diet for one month to establish an early DKD model. Model establishment was confirmed when fasting blood glucose (FBG) ≥ 11.1 mmol/L and urinary albumin-to-creatinine ratio (uACR) ≥ 30 mg/g. The successfully modeled early DKD rats were randomly divided by random number table into five groups (n = 10 per group): model group; dapagliflozin group (1.0 mg/kg, by gavage, served as positive control); and low-, medium-, and high-dose of ZGJTYSF groups (4.9, 9.9, and 19.9 g/kg, respectively, by gavage). Age-matched male SPF Wistar rats (n = 10) served as control group. Rats in control and model groups were gavaged with equivalent volumes of distilled water. Treatment lasted 12 weeks. Changes in uACR, FBG, and renal function were observed in all groups. Hematoxylin-eosin (HE), periodic acid-Schiff (PAS), and Masson staining were used to observe renal histopathological changes. Immunohistochemistry was performed to detect the localization and expression of caspase-1, GSDMD, and NLRP3 in rat renal tissues. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) was utilized to detect pyroptosis in renal tissues. Quantitative real-time polymerase chain reaction (qPCR) and Western blot were applied to detect mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, interleukin (IL)-1β, and IL-18. Results: Compared with model group, all doses of ZGJTYSF showed reductions in FBG, with medium- and high-dose of ZGJTYSF groups demonstrating significant decreases at week 8 and 12 (P < 0.05). For uACR, all doses of ZGJTYSF groups exhibited a decreasing trend, with high-dose of ZGJTYSF group being significantly lower than low- and medium-dose of ZGJTYSF groups at week 12 (P < 0.05) and showing no significant difference from dapagliflozin group (P > 0.05). No significant differences in renal function parameters (serum creatinine, blood urea nitrogen, and uric acid) were observed among groups (P > 0.05). Histopathological examination revealed milder glomerular and tubular lesions in both ZGJTYSF groups and dapagliflozin group, with renal pathological changes in high-dose of ZGJTYSF group resembling those in dapagliflozin group. Immunohistochemistry demonstrated significantly reduced expression of caspase-1, GSDMD, and NLRP3 in renal tissues of dapagliflozin group and high-dose of ZGJTYSF group compared with model group (P < 0.05 or P < 0.01), while the differences in low- and medium-dose of ZGJTYSF groups were not statistically significant (P > 0.05). TUNEL assay showed significantly fewer TUNEL-positive cells in renal tissues of dapagliflozin and high-dose of ZGJTYSF groups (P < 0.01), indicating a marked reduction in pyroptotic cells. Molecular analysis revealed that compared with model group, both dapagliflozin and high-dose of ZGJTYSF groups showed significantly downregulated mRNA and protein expression levels of NLRP3, caspase-1, GSDMD, IL-1β, and IL-18 in renal tissues (P < 0.01), while low- and medium-dose of ZGJTYSF groups showed downward trends without statistical significance (P > 0.05). Conclusion ZGJTYSF may inhibit renal pyroptosis by regulating the NLRP3/caspase-1/GSDMD signaling axis, thereby preventing and treating early renal injury in DKD and delaying the onset and progression of DKD.

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

Sjögren's syndrome (SS) is an autoimmune disease characterized primarily by oral and periocular dryness. Astragalus-Salvia (AS) and Ophiopogon-Dendrobium (OD) represent two frequently utilized herb pairs in SS treatment. While the combination of AS-OD herb pairs demonstrates clinical efficacy in alleviating SS symptoms, its underlying mechanism remains unclear. This investigation sought to assess the therapeutic effects and elucidate the potential mechanisms of AS-OD in non-obese diabetic (NOD)/Ltj mice with SS. The study utilized NOD/Ltj mice as SS models, administering AS-OD treatment for 10 weeks at doses of 113.1, 226.2, and 339.3 mg·d^-1·20 g^-1. Results demonstrated that AS-OD improved SS symptoms, evidenced by enhanced salivary flow rate, decreased anti-SSA/Ro and anti-SSB/La antibody levels, increased swimming duration, and reduced lactate (LA) and blood urea nitrogen (BUN) levels in NOD/Ltj mice. AS-OD reduced lymphocyte infiltration, enhanced Aquaporin-5 (AQP5) expression in the submandibular gland, decreased inflammatory cytokine levels in the submandibular gland, and reduced the T helper type 17/regulatory T lymphocyte (Th17/Treg) cell ratio in the spleen. Transcriptomic and proteomic analyses indicated AS-OD's involvement in regulating phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) and Janus kinase 3/signal transducer and activator of transcription 3 (JAK1/STAT3) pathways, with inhibitory effects validated in both NOD/Ltj mice submandibular gland and A-253 cells. Furthermore, AS-OD enhanced cell viability and reduced A-253 cell apoptosis through the PI3K/AKT pathway. In A-253 cells, AS-OD reduced inflammatory cytokine levels, CXC chemokine ligand 9/10 (CXCL9/10), and T-cell chemotaxis by inhibiting the JAK1/STAT3 pathway. AS-OD mitigates SS by suppressing inflammation and immune responses through the PI3K/AKT and JAK1/STAT3 pathways.
Animals ; STAT3 Transcription Factor/genetics* ; Sjogren's Syndrome/immunology* ; Mice, Inbred NOD ; Proto-Oncogene Proteins c-akt/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Signal Transduction/drug effects* ; Janus Kinase 1/genetics* ; Humans ; Female ; Astragalus Plant/chemistry* ; Male