In order to better match the teaching hours of clinical anesthesiology with the teaching content of modem anesthesia, the teachers must take full advantage of various supplementary teaching methods in the limited teaching hours to help enhance the students' enthusiasm in active learning, help the students concentrate on the crucial points and apply their knowledge and ultimately improve the teaching quality.

Objective : To evaluate the prognostic value of a radiomics model based on the peritumoral region of gli- oma． Methods : 138 patients with glioma were retrospectively analyzed ，medical imaging interaction toolkit ( MITK) software was used to obtain the magnetic resonance imaging (MRI) images of peritumoral area 5 mm，10 mm and 20 mm from the tumor edge and extract texture features．The texture features were screened the radiomics model was established and the radiomic score was calculated．A clinical prediction model and a combined predic- tion model along with Rad-score and clinical risk factors were established．The combined prediction model was dis- played as a nomogram，and the predictive performance of the model for survival in glioma patients was evaluated. Results : In the validation set，the C-index value of the radiomics model based on the peritumoral region 10 mm a- way from the tumor edge based on T2 weighted image (T2WI) images was 0. 663 (95% CI = 0. 72－0. 78) ，resul- ting in the best prediction performance．On the training set and validation set，the C-index of the nomogram was 0. 770 and 0. 730，respectively，indicating that the prediction performance of nomogram was better than those of the radiomics model and clinical prediction model．The model had the highest prediction effect on the 3-year survival rate of glioma patients (training set area under curve (AUC) = 0. 93，95% CI = 0. 83 － 0. 98 ; validation set AUC = 0. 88，95% CI = 0. 76 －0. 99) ．The calibration curve showed that the joint prediction nomogram in both the training set and the validation set had good performance． Conclusion The combined prediction model based on the preoperative T2WI images in the peritumoral region 10 mm from the tumor edge and the clinicopathological risk factors can accurately predict the prognosis of glioma，providing the best effect of prediction on the 3-year survival rate of glioma.

Histone lysine methyltransferases (HKMTs) deposit methyl groups onto lysine residues on histones and play important roles in regulating chromatin structure and gene expression. The structures and functions of HKMTs have been extensively investigated in recent decades, significantly advancing our understanding of the dynamic regulation of histone methylation. Here, we review the recent progress in structural studies of representative HKMTs in complex with nucleosomes (H3K4, H3K27, H3K36, H3K79, and H4K20 methyltransferases), with emphasis on the molecular mechanisms of nucleosome recognition and trans-histone crosstalk by these HKMTs. These structural studies inform HKMTs' roles in tumorigenesis and provide the foundations for developing new therapeutic approaches targeting HKMTs in cancers.
Nucleosomes ; Histones/metabolism* ; Histone-Lysine N-Methyltransferase/metabolism* ; Lysine/metabolism* ; Methyltransferases/metabolism* ; Methylation