Sesamol is a fat-soluble natural polyphenol compound found in sesame seeds and sesame oil,which is widely used in food.Sesamol can effectively scavenge free radicals in the body,reduce oxidative stress,and protect cells from damage,therefore it plays an important role in the prevention of cardiovas-cular disease,cancer and neurodegenerative diseases.It has been widely studied for its various pharma-cological functions such as antioxidant,antibacterial,anti-inflammatory,neuroprotective,cardioprotec-tive,immunomodulatory and antitumor.In recent years,sesamol,as a safe and non-toxic chemical sub-stance,has received extensive attention in the field of tumor research and is expected to be used as a clinical drug for tumor therapy in the future.In this paper,through the collection and analysis of relevant literature on sesamol at home and abroad,we reviewed the biological functions of sesamol in antioxidant,anti-inflammatory,antibacterial,regulating energy metabolism,cardiovascular protection,and neuropro-tection,etc.as well as its mechanism of action.Furthermore,this review also focused on the role of ses-amol in regulating cellular energy metabolism,inducing apoptosis,blocking the cell cycle,modifying ep-igenetic modifications,promoting cellular autophagy,inhibiting angiogenesis,reducing the tolerance of chemotherapeutic drugs,and so on.In addition,this paper also focused on the anti-tumor effects of sesa-mol by regulating cell energy metabolism,inducing cell apoptosis,modulating epigenetic modification,promoting cell autophagy,inhibiting angiogenesis,and reducing the tolerance of chemotherapeutic drugs,etc.This review aims to provide a new theoretical basis for the development of tumor therapeutic drugs.

The widespread implementation of low-dose computed tomography screening has led to a substantial rise in the detection of pulmonary nodules,with multiple pulmonary nodules(MPNs)now representing a common clinical presentation.Conventional diagnostic and therapeutic paradigms,characterized by sequential,multi-site processes,are often limited by inefficiency,safety concerns,and suboptimal patient outcomes.In contemporary thoracic surgery,a transformative"one-stop"precision management strategy has emerged within hybrid operating theaters.This integrated approach synergizes intraoperative imaging,advanced navigation,and surgical intervention to address these limitations.Cone-beam CT plays a pivotal role in this model by leveraging its maneuverability,low radiation,and high spatial resolution to greatly facilitate the development of precise diagnosis and treatment for MPNs.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

AIM To investigate the effects of Yiqi Juanbi Formula on chondrocyte pyroptosis in rat models of collagen-induced arthritis(CIA).METHODS Fifty rats were subcutaneously injected at the tail base with an emulsion containing equal volumes of bovine type Ⅱ collagen and incomplete Freund's adjuvant(IFA)to establish the CIA models.These rats were then randomly assigned to the model group,the methotrexate group(0.35 mg/kg),and the low-dose,medium-dose,and high-dose Yiqi Juanbi Formula groups(9.4,18.7,37.4 g/kg),in contrast to the ten intact rats serving in the normal control group.Following four weeks of intragastric administration,the rats had their general conditions observed;their joint swelling and arthritis indices measured;their ankle joint pathology assessed by HE staining;their serum levels of IL-1β,IL-18 and TNF-ɑ detected by ELISA;their mRNA expressions of NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ in ankle cartilage quantified by RT-qPCR;their protein expressions of NF-κB,NLRP3 and Caspase-1 in ankle cartilage analyzed by Western blot;and their NLRP3 and GSDMD positive expressions in ankle cartilage examined by immunohistochemistry.RESULTS Compared to the control group,the model group showed significantly increased joint swelling and arthritis indices(P＜0.01);elevated serum levels of IL-1 β,IL-18 and TNF-ɑ(P＜0.01);pathological changes including cartilage surface defects,reduced cell count,altered cellular morphology,irregular cell arrangement,and significant inflammatory cell infiltration in synovial tissue;upregulated mRNA expressions of NF-κB,NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ(P＜0.01)and increased protein expressions of NF-κB,NLRP3 and Caspase-1(P＜0.01)in ankle cartilage;enhanced positive expressions of NLRP3 and GSDMD in ankle cartilage(P＜0.01).Compared to the model group,the groups intervened with methotrexate or medium-or high-dose Yiqi Juanbi Formula exhibited reduced joint swelling and arthritis indices(P＜0.01);alleviated pathological damage in ankle joints;decreased serum levels of IL-1β,IL-18 and TNF-ɑ(P＜0.01);downregulated mRNA expressions of NF-κB,NLRP3,Caspase-1,GSDMD,IL-1β,IL-18 and TNF-ɑ(P＜0.05,P＜0.01),and reduced protein expressions of NF-κB,NLRP3 and Caspase-1(P＜0.05,P＜0.01)in ankle cartilage;and diminished positive expressions of NLRP3 and GSDMD in ankle cartilage(P＜0.01).CONCLUSION Yiqi Juanbi Formula alleviates inflammation in CIA rats,potentially by inhibiting the activation of the NF-κB/NLRP3/Caspase-1 signaling pathway,thereby suppressing chondrocyte pyroptosis.

Objective To analyze the correlation between lesion volume,lesion mass,and maximum lesion diameter in the assessment of advanced hepatocarcinoma with lung metastasis,and to evaluate the application value of total volume response and total mass response of lung metastatic lesions in efficacy assessment.Methods A retrospective analysis was conducted on the CT imaging data of 20 patients clinically confirmed with hepatocarcinoma and lung metastases,followed by subsequent follow-up to monitor their survival outcomes.Volume measurement software was used to measure the volume of lesions before and after treatment.We recored lesion diameter,volume measurements and CT values,calculated the mass of the lesions.The correlation between lesion volume,mass and diameter was analyzed,as well as the correlation between the change rates of volume,mass and lesion diameter.Additionally,the total volume and total mass of all lesions were calculated.The correlation between the change rates of total volume/total mass and the change rate of pulmonary lesion diameter under the RECIST 1.1 criteria,as well as the correlation with changes in patients'tumor markers,were analyzed.Furthermore,the overall volume response and overall mass response of lesions were evaluated based on changes in total volume and total mass,and their consistencies with the RECIST 1.1 criteria for efficacy evaluation were analyzed.Finally,univariate Cox regression analysis was performed to explore the association between these variables and patient survival outcomes.Results There was strong correlation between lesion volume,mass and tumor diameter(r=0.771,0.775),between the rate of change in mass and the rate of change in lesion diameter(r=0.846),and between the rates of change in total volume/total mass and the rate of change in pulmonary lesion diameter under the RECIST 1.1 criteria(r=0.800,0.896).The correlation between the rates of change in total volume/total mass and patients'tumor markers was not statistically significant.There was moderate correlation between the rate of change in volume and the rate of change in lesion diameter(r=0.692).The evaluation results of total volume response and total mass response for pulmonary lesions in advanced hepatocarcinoma with lung metastasis were generally consistent with the RECIST 1.1 criteria(Kappa=0.486,0.426).Univariate Cox regression analysis revealed that total lesion volume(P=0.047)and total lesion mass(P=0.049)were independent prognostic factors for survival outcomes.Conclusion Lesion volume,mass,and diameter,as well as their respective change rates,were found to be interrelated.Furthermore,total lesion volume and total lesion mass were identified as independent prognostic factors for survival outcomes.The total volume response and total mass response are promising evaluation methods in evaluating the efficacy of lung metastasis of hepatocarcinoma,which are different from the RECIST 1.1 evaluation criteria.

The widespread implementation of low-dose computed tomography screening has led to a substantial rise in the detection of pulmonary nodules,with multiple pulmonary nodules(MPNs)now representing a common clinical presentation.Conventional diagnostic and therapeutic paradigms,characterized by sequential,multi-site processes,are often limited by inefficiency,safety concerns,and suboptimal patient outcomes.In contemporary thoracic surgery,a transformative"one-stop"precision management strategy has emerged within hybrid operating theaters.This integrated approach synergizes intraoperative imaging,advanced navigation,and surgical intervention to address these limitations.Cone-beam CT plays a pivotal role in this model by leveraging its maneuverability,low radiation,and high spatial resolution to greatly facilitate the development of precise diagnosis and treatment for MPNs.

Objective:To evaluate the efficacy of gadolinium ethoxybenzyl- diethy-lenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI features in the preoperative prediction of tertiary lymphoid structures (TLS) within hepatocellular carcinoma (HCC) lesions.Methods:This retrospective cross-sectional study included clinical and pathological data from 297 HCC patients treated at the Southwest Hospital, Army Medical University between June 2021 and November 2022. Based on postoperative pathology, patients were categorized into TLS-negative ( n=93) and TLS-positive ( n=204) groups. MRI features of HCC lesions using Gd-EOB-DTPA enhancement and relevant clinical data were analyzed. Intergroup comparisons of imaging features and laboratory findings were performed using independent sample t-test, Mann-Whitney U test, χ2 test, or Fisher exact test, as appropriate. The logistic regression analysis was conducted to identify independent predictors of TLS positivity. A predictive model was constructed and visualized using a nomogram. The model′s predictive performance and clinical utility were assessed using the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The area under the ROC curve (AUC) was compared using the DeLong test. Results:Significant differences were observed between the TLS-negative and TLS-positive groups in alpha-fetoprotein (AFP) levels, intratumoral hemorrhage, and peritumoral satellite nodules in the hepatobiliary phase ( P<0.05). Multivariate logistic regression identified intratumoral hemorrhage ( OR=0.123, 95% CI 0.070-0.216, P<0.001) and peritumoral satellite nodules in the hepatobiliary phase ( OR=0.236, 95% CI 0.093-0.596, P=0.002) as independent predictive factors for TLS-positivity. The imaging model based on these two features yielded an AUC of 0.764 (95% CI 0.709-0.809) for predicting TLS-positivity. When combined with AFP levels, the resulting clinical-imaging model achieved a superior AUC of 0.784 (95% CI 0.732-0.829), which was significantly higher than that of the imaging model alone ( Z=2.20, P=0.028). A nomogram was constructed based on the clinical-imaging model. The calibration curve demonstrated good predictive performance of the nomogram, and the DCA showed that the curve remained above the default line across a range of reasonable threshold probabilities, indicating that patients could derive clinical benefit. Conclusion:A nomogram model based on Gd-EOB-DTPA enhanced MRI features combined with AFP levels can effectively predict the presence of TLS in HCC.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

OBJECTIVE: To explore clinical efficacy of autologous platelet-rich plasma(PRP) in treating Rockwood type Ⅲ acromioclavicular dislocation. METHODS: From January 2019 to July 2021, 32 patients with Rockwood type Ⅲ acromioclavicular dislocation were treated with minimally invasive adjustable titanium plate internal fixation, and were divided into PRP group and control group according to whether PRP treatment was performed, with 16 patients in each group. In PRP group, there were 10 males and 6 females, aged from 28 to 47 years old with an average of (36.75±7.14) years old;the time from injury to surgery ranged from 1 to 31 h with an average of (26.13±3.98) h;5 patients on the left side and 11 patients on the right side;PRP was injected once during operation and the 4th and 8th weeks after operation respectively. In control group, there were 8 males and 8 females, aged from 30 to 52 years old with an average of (38.50±5.48) years old; the time from injury to surgery ranged from 1 to 29 h with an average of (25.48±3.11) h;7 patients on the left side and 9 patients on the right side; minimally invasive surgical treatment was performed. Visual analogue scale(VAS) was used to evaluate pain and Constant-Murley score for shoulder joint function was used to evaluate the recovery of shoulder joint movement function before operation and 1, 3, 6, and 12 months after operation respectively. RESULTS: All patients were followed up for 12 to 28 months with an average of (18.3±5.2) months. All incisions patients healed well without adverse events such as infection. Postoperative VAS of PRP group at 1, 3, and 6 months were (5.5±1.2), (3.7±1.6), and (2.4±1.2), respectively, while were lower than those of control group (6.6±1.4), (4.9±1.1), and (3.7±1.3), respectively;and had statistical differences between two groups (P<0.05). There was no statistically significant difference in VAS between two groups before operation and 12 months after operation (P>0.05). Postoperative Constant-Murley scores of PRP group at 1, 3, and 6 months were (64.09±11.61), (73.19±12.89), and (82.61±14.81) points, respectively, which were higher than those of control group were (52.32±17.42), (61.65±14.43), and (72.52±11.04) respectively;and the differences were statistically significant (P<0.05). There was no statistically significant difference in Constant-Murley scores at 12 months after operation between two groups (P>0.05). In PRP group, there was no statistically significant difference at 6 months and 12 months after operation (P>0.05), while there were statistically significant differences at the other time points (1 month after operation compared with before operation, 3 months after operation compared with 6 months after operation, and 3 months after operation compared with 1 month after operation) (P<0.05). In control group, there was no statistically significant difference when comparing 1 month and 3 months after operation (P>0.05), while at the other time points (1 month after operation with before operation, 3 months after operation with 6 months after operation, and 6 months after operation with 12 months after operation), the differences were all statistically significant (P<0.05). CONCLUSION Adjustable titanium plate fixation combined with postoperative injection of PRP for the treatment of Rockwood type III acromioclavicular joint dislocation has effect of promoting the recovery of shoulder joint function and reducing pain.
Humans ; Male ; Female ; Adult ; Middle Aged ; Platelet-Rich Plasma ; Acromioclavicular Joint/surgery* ; Bone Plates ; Titanium ; Joint Dislocations/therapy* ; Fracture Fixation, Internal/methods*