Objective The aims of the study were to investigate the effects of human islet amyloid polypeptide (hIAPP) on autophagy in INS-1 cells and its underlying mechanism,and to explore the role of autophagy in hIAPP-induced cytotoxicity and oxidative stress.Methods INS-1 cells were treated with hIAPP (10 μmol/L) for 24 h in the presence or absence of N-acetyl-L-cysteine (NAC),compound C,5-aminoimidazole-4-carboxamide-1-β-D-ribofuranoside (AICAR) and 3-methyladenine (3-MA),respectively.Transmission electron microscopy was used to observe the number of autophagosome in cells.Cell viability was determined by methyl thiazolyl tetrazolium (MTT) test.2',7'-dichlorofluorescin diacetate (DCFH-DA) assay was used to measure the relative levels of reactive oxygen species (ROS).Western blot was used to detect expression of adenosine monophosphate-activated protein kinase (AMPK) and autophagic markers p62 and microtubule associated protein 1 light chain3 (LC3).Results Treatment of INS-1 cells with hIAPP resulted in a significant increase in the number of autophagosomes and the expression of LC3-Ⅱ/LC3-Ⅰ (both P＜0.05).Meanwhile,treatment of INS-1 cells with hIAPP enhanced the level of ROS to 1.76 times of control cells (P＜0.01).Co-treatment with NAC,an antioxidant,inhibited hIAPP-induced ROS generation,and the expression of LC3-Ⅱ/LC3-Ⅰ and p-AMPK in the INS-1 cells (all P＜0.05).Pretreatment of INS-1 cells with AMPK inhibitor compound C suppressed hIAPP and AICAR,an activator of AMPK,induced expression of LC3-Ⅱ/LC3-Ⅰ and p-AMPK (all P＜0.05).Autophagic inhibitor 3-MA and compound C aggravated the hIAPP-induced cell death and ROS generation in INS-1 cells (All P＜0.05).The cytotoxic effects of hIAPP were significantly attenuated by co-treatment with AICAR (P＜0.05).Conclusion Autophagy may act as an adaptive mechanism to alleviate hIAPP-induced oxidative damage and toxicity in INS-1 cells.

OBJECTIVE To identify the key genes associated with lymph node metastasis in head and neck squamous carcinoma(HNSCC)and construct a prognostic model based on The Cancer Genome Atlas(TCGA)database.METHODS Differentially expressed genes(DEGs)between tumor tissues and normal tissues in the HNSCC dataset in the TCGA database were screened by R software,and gene modules related to lymph node metastasis were screened by weighted gene co-expression network(weighted gene co-expression network analysis,WGCNA).Prognostic risk models were constructed by univariate cox regression and Lasso regression analyses.Survival analyses and ROC curves were performed to verify the Reliability of prognostic models.CIBERSORT,TIMER and ESTIMATE algorithms analysed the differences in the tumor micro environment(TME)of different risk groups.RESULTS There were 2 565 DEGs screened,and a set of gene modules highly correlated with disease prognosis and lymph node metastasis were obtained by WGCNA analysis,and correlation analysis verified that the expression of genes in this gene module was highly correlated with lymph node metastasis.Univariate cox regression and Lasso regression were used to identify 6 key prognostic genes:CDKN2A,CCNE2,KNSTRN,AURKA,KPNA2,and ORC1.A prognostic model was constructed based on the 6 genes,and survival analysis showed that the prognosis of the high-risk group was significantly worse than that of the low-risk group(P<0.0001).The ROC curves demonstrated the good predictive performance of this prognostic model.CIBERSORT analyses revealed differences in the immune microenvironment of tumors in different risk groups.CONCLUSION The 6 key prognostic genes screened were helpful in predicting the prognosis of HNSCC patients and were closely associated with the immune microenvironment of HNSCC,suggesting that they may serve as potential therapeutic targets.

The regulatory role of long non-coding RNA(lncRNA)in cancer radiosensitivity has obtained increasing attention.Radiotherapy is one of the primary treatment methods for cancer,yet some patients experience disease progression or recurrence due to radioresistance.Exploring the regu-latory mechanisms of radiosensitivity during cancer radiotherapy and identifying new molecular thera-peutic targets are crucial for enhancing the efficacy of cancer radiotherapy.LncRNA can participate in the response of cancer to radiotherapy and regulate cancer radiosensitivity through various pathways,including modulation of the DNA damage response,apoptosis,cancer stem cells,and epithelial-mesen-chymal transition(EMT).This study discussed the research progress on the mechanisms of lncRNA in the field of cancer radiotherapy,highlighting their important roles in enhancing tumor radiosensitivity.

The regulatory role of long non-coding RNA(lncRNA)in cancer radiosensitivity has obtained increasing attention.Radiotherapy is one of the primary treatment methods for cancer,yet some patients experience disease progression or recurrence due to radioresistance.Exploring the regu-latory mechanisms of radiosensitivity during cancer radiotherapy and identifying new molecular thera-peutic targets are crucial for enhancing the efficacy of cancer radiotherapy.LncRNA can participate in the response of cancer to radiotherapy and regulate cancer radiosensitivity through various pathways,including modulation of the DNA damage response,apoptosis,cancer stem cells,and epithelial-mesen-chymal transition(EMT).This study discussed the research progress on the mechanisms of lncRNA in the field of cancer radiotherapy,highlighting their important roles in enhancing tumor radiosensitivity.

Objective To discuss the distribution characteristics of the Bragg peak in proton therapy using the SRIM code. Methods Based on the SRIM code, the transport processes of a high-energy proton beam injecting into different materials (H₂O, C₂H₆O、C₈H₈、Al and Fe)with incident energies of 50 MeV～250 MeV have been simulated and analyzed. And the relationship between the incident energies, different materials and thickness, and the depth of the Bragg peak was also discussed when the protons injected into different materials and compared with the simulation results of professional Monte Carlo code, such as Fluka 2011 and MCNPX. Results The simulation results indicate that the depths of the Bragg peak increase gradually and the peaks broaden with the increase of incident proton energies for different materials; The ratio of the depth of the Bragg peak in different materials to that in water under the same incident energy changes little and is approximately a constant which doesn’t depend on the proton incident energy. A good consistency was found between the results and those obtained using Fluka and MCNPX programs. Conclusion The simulation accuracy of the SRIM on the proton beam transport is acceptable, and is suitable for the beginning learners.