AIM:To observe the therapeutic effect of dihydromyricetin on experimental schistosoma japonicum hepatic fibrosis in mice. METHODS:60 mice infected with schistosma japonicum cercariae percutanoeusly were divided into 3 groups:model group,praziquantel group, praziquantel plus dihydromyricetin group and other 20 normal mice were used as control group.After treatment with medicine for 8 weeks,the liver was removed and weighed.The contents of ALT and AST in serum were assayed using the corresponding kits.Moreover, the degree of hepatic fibrosis was observed Via HE and was scored.The expression of collagenⅠprotein and collagenⅢprotein were measured by immunohistochernical method.RESULTS: The mice that infected with schistosoma japonicum, had a featuring increment in liver weights,serum ALT,AST contents,the expression of collagenⅠprotein,collagenⅢprotein (P

To identify the original plant of Daturae Flos from its adulterants by DNA barcoding, the sequences of ITS2, psbA-trnH, matK, rbcL of four species including Datura metel, Darura innoxia, Darura stramonium and Brugmansia arborea were compared and analyzed. The PCR and sequencing success rate of the four regions (ITS2, psbA-trnH, matK, rbcL) was 100%, 90%, 100% and 85%, respectively. Sequences were assembled with CodonCode Aligner. K2P distances were calculated and NJ tree was performed by MEGA 4.1. Thirty SNPs were found among ITS2 sequences, and 33 insert/deletes were found among psbA-trnH intergenic regions. The interspecific K2P distance of ITS2 and psbA-trnH was obviously higher than that of the intraspecific one. As to matK and rbcL, there was no "Barcoding Gap" existing between inter- and intra-specific distances. The NJ trees of the four regions/combinations were built separately. Samples of Brugmansia arborea were clustered into one clade, and the other species of Datura L. formed another clade. The results showed that either ITS2 or psbA-trnH was useful to identify Daturae Flos from its adulterants.

Objective To investigate the prevalence and severity of symptoms and to construct symptom networks in head and neck cancer patients during treatment to identify core symptoms and symptom clusters.Methods 366 patients who were hospitalized in 3 tertiary hospitals in Changsha were selected using convenience sampling from March to October 2022 and asked to complete the M.D.Anderson Symptom Inventory-Head & Neck.Exploratory factors analysis was used to extract the symptom clusters,and R packages were used to construct the symptom severity network and symptom clusters network.The centrality indexes of the networks,including strength,closeness,and betweenness,were analyzed to identify core symptoms and core symptom cluster.Results The most common symptoms in head and neck cancer patients during treatment were dry mouth(93.44％),fatigue(89.07％),loss of appetite(86.34％),and difficulty swallowing or chewing(85.79％),and the most severe symptoms were dry mouth,loss of appetite,oral or pharyngeal mucus,and difficulty swallowing or chewing.4 symptom clusters were extracted,namely oral-pharyngeal,gastrointestinal,emotional-sleep,and sickness-sensing behavioral,which could explain 67.415％of the total variance.In the symptom severity network,oral or pharyngeal mucus(rs=9.60)was a symptom with the highest strength.In the symptom clusters network,oral or pharyngeal mucus(rs=1.20),nausea(rs=1.00),fatigue(rs=1.10),and drowsiness(rs=0.97)were the symptoms with the highest strength across 4 symptom clusters.Conclusion Oral or pharyngeal mucus,nausea,fatigue,and drowsiness are the core symptoms of symptom clusters in head and neck cancer patients during treatment.Oral-pharyngeal symptom cluster is the core symptom cluster.It is recommended that clinical staff should develop interventions based on the core symptoms and symptom cluster to implement precise symptom management and improve symptom management efficiency.

OBJECTIVE To investigate the predictive value of prognostic nutritional index(PNI) and lymphocyte-monocyte ratio(LMR) in severe radiotherapy-induced oral mucositis(RIOM) during treatment of patients with head and neck cancer,and to construct a risk prediction model and test the prediction effect. METHODS A total of 502 patients with head and neck cancer who underwent radiotherapy were recruited from September 2021 to October 2023 in Xiangya Hospital Central South University. The participants were randomly divided into training group and validation group at a ratio of 7:3. According to whether severe RIOM occurred,they were divided into severe RIOM group and non-severe RIOM group. Univariate analysis and logistic regression analysis were used to screen the risk factors of severe RIOM. The receiver operating characteristic(ROC) curve was used to evaluate its prediction effect and R4.3.2 software was used to draw nomograms and decision curve. RESULTS The risk prediction model for patients with head and neck cancer during treatment had five factors,including the number of comorbidities(OR=2.221,95％CI=1.185-4.165),surgical history(OR=2.938,95％CI=1.393-6.198),the degree of tumor differentiation(OR=1.511,95％CI=1.090-2.094),PNI(OR=0.892,95％CI=0.852-0.934),LMR(OR=0.512,95％CI=0.254-1.030). Model formula:Y=2.102+0.413×degree of differentiation+0.798×number of comorbidities+1.078×surgical history-0.114×PNI-0.669×LMR. The validation results of the prediction model showed that the area under the ROC curve of the training group was 0.847(P<0.001),the area under the curve of the validation group was 0.808(P<0.001),and the P values of the Hosmer-Lemeshow test of the modeling group and the validation group were both greater than 0.05. The decision curve was above the reference line within most of the high-risk thresholds. CONCLUSION The risk prediction model constructed in this study has good effect,which can predict the risk of severe RIOM during radiotherapy in patients with head and neck cancer,providing the reference for taking preventive intervention measures for high-risk patients.

In fixed prosthodontics, clear exposure of the preparation margin is the prerequisite for obtaining accurate digital impressions and improving the marginal fit of restorations. To resolve the issues associated with the cord retraction technique, such as pain, acute injury, and prolonged procedural time, this study proposes a new technology for intraoral digital impression taking with pneumatic gingival retraction. The new scanning head blows a high-speed airflow that instantaneously separates the free gingiva, locally exposing the subgingival preparation margin. Combined with the farthest point preservation stitching algorithm based on the distance from the normal vector and high-speed laser scanning photography, it achieves global preparation edge data and gingival reconstruction, realizing painless, non-invasive, and efficient precise acquisition of the preparation margin. Using this new technique, a patient with a full porcelain crown restoration on a posterior tooth was treated. The digital impression revealed a clear margin of the preparation, and the crown made from this data has a good marginal fit.