Epigenetics refers to a heritable phenomenon that dynamically modulates gene expression without altering the DNA sequence, through molecular mechanisms such as DNA methylation, histone modification, non-coding RNA, chromatin remodeling, and RNA modifications. In plants, these modifications are extensively involved in key biological processes, including flowering time, gametogenesis, stress responses, and immune defenses. Over the past few decades, the research on epigenetics has gradually shifted from fundamental studies primarily conducted in Arabidopsis thaliana to investigations in various crop species such as rice and tomato. This transition has revealed the multifaceted roles of epigenetic regulation in shaping agronomic traits. This review integrates current knowledge of epigenetic regulatory mechanisms and their functions in plant responses to both biotic and abiotic stresses. Epigenetic editing tools such as CRISPR-dCas9 enable targeted DNA methylation or histone acetylation. Emerging transformation technologies, including magnetic nanoparticles and virus-based delivery systems, have the potential to overcome the bottlenecks of plant regeneration, offering new possibilities for precise epigenetic editing. In future agriculture, it is essential to further elucidate multi-layered epigenetic regulatory mechanisms at the single-cell level, develop efficient delivery systems, and leverage artificial intelligence to advance the application of epigenetic breeding for sustainable agricultural development.
Epigenesis, Genetic/genetics* ; Crops, Agricultural/genetics* ; Plant Breeding/methods* ; DNA Methylation/genetics* ; Gene Editing ; Disease Resistance/genetics* ; CRISPR-Cas Systems

Objective:To analyze the influencing factors of pancreatic fistula after pancreaticoduodenectomy (PD), and to construct and evaluate the prediction model of postoperative pancreatic fistula (POPF).Methods:Clinical data of 255 PD patients undergoing PD at the General Surgery Department of the Second Affiliated Hospital of Air Force Military Medical University from January 2016 to January 2023 were retrospectively analyzed as the training set, including 148 males and 107 females, aged 58.0 (52.0, 64.5) years. According to the occurrence of POPF, patiennts were divided into the pancreatic fistula group ( n=65, including grade B and C POPF) and the non-pancreatic fistula group ( n=190). The age, gender, body mass index (BMI), white blood cell (WBC) count and neutrophil/lymphocyte ratio (NLR) before surgery and on the postoperative day (POD) 3, albumin, diameter of pancreatic duct, texture of the pancreas, operation time, and amylase concentration in the drainage fluid on POD3 were compared between the groups. Multivariate logistic regression analyses were conducted to identify the influencing factors of POPF. The nomogram of the pancreatic fistula prediction model was constructed using the rms package. One thousand cases were selected as the test set through the Bootstrap resampling method. And in the test set the receiver operating characteristic (ROC) curve and calibration curve were drawn to evaluate the model. Results:Logistic univariate analysis showed that there were significant differences between the two groups in terms of age, BMI, WBC count and NLR (preoperative and on POD3), the concentration of amylase in drainage fluid on POD3, pancreatic duct diameter, and operation time (all P<0.05). The results of logistic multivariate regression analysis showed age ( OR=1.050, 95% CI: 1.011-1.091), BMI ( OR=1.127, 95% CI: 1.005-1.264) and the amylase concentration of the drainage fluid >367.5 U/L on POD3 ( OR=3.688, 95% CI: 1.849-7.354) were the influencing factors of POPF ( P<0.05). Based on the three influencing factors screened out by multivariate analysis, a histogram for the prediction of pancreatic fistula was constructed using the rms package. The area under the ROC curve of the nomogram for predicting the occurrence of pancreatic fistula after PD was 0.744 (95%CI: 0.679-0.809), with a sensitivity of 69.2% and a specificity of 70.5%. The calibration curve shows that the model's prediction is consistent with the actual situation in the overall trend, indicating a relatively high degree of calibration. Conclusion:Age, BMI and amylase concentration of drainage fluid >367.5 U/L on POD3 are the influencing factors for pancreatic fistula after PD. The nomogram model for predicting pancreatic fistula constructed based on this has good predictive and application value.

Objective:To analyze the influencing factors of pancreatic fistula after pancreaticoduodenectomy (PD), and to construct and evaluate the prediction model of postoperative pancreatic fistula (POPF).Methods:Clinical data of 255 PD patients undergoing PD at the General Surgery Department of the Second Affiliated Hospital of Air Force Military Medical University from January 2016 to January 2023 were retrospectively analyzed as the training set, including 148 males and 107 females, aged 58.0 (52.0, 64.5) years. According to the occurrence of POPF, patiennts were divided into the pancreatic fistula group ( n=65, including grade B and C POPF) and the non-pancreatic fistula group ( n=190). The age, gender, body mass index (BMI), white blood cell (WBC) count and neutrophil/lymphocyte ratio (NLR) before surgery and on the postoperative day (POD) 3, albumin, diameter of pancreatic duct, texture of the pancreas, operation time, and amylase concentration in the drainage fluid on POD3 were compared between the groups. Multivariate logistic regression analyses were conducted to identify the influencing factors of POPF. The nomogram of the pancreatic fistula prediction model was constructed using the rms package. One thousand cases were selected as the test set through the Bootstrap resampling method. And in the test set the receiver operating characteristic (ROC) curve and calibration curve were drawn to evaluate the model. Results:Logistic univariate analysis showed that there were significant differences between the two groups in terms of age, BMI, WBC count and NLR (preoperative and on POD3), the concentration of amylase in drainage fluid on POD3, pancreatic duct diameter, and operation time (all P<0.05). The results of logistic multivariate regression analysis showed age ( OR=1.050, 95% CI: 1.011-1.091), BMI ( OR=1.127, 95% CI: 1.005-1.264) and the amylase concentration of the drainage fluid >367.5 U/L on POD3 ( OR=3.688, 95% CI: 1.849-7.354) were the influencing factors of POPF ( P<0.05). Based on the three influencing factors screened out by multivariate analysis, a histogram for the prediction of pancreatic fistula was constructed using the rms package. The area under the ROC curve of the nomogram for predicting the occurrence of pancreatic fistula after PD was 0.744 (95%CI: 0.679-0.809), with a sensitivity of 69.2% and a specificity of 70.5%. The calibration curve shows that the model's prediction is consistent with the actual situation in the overall trend, indicating a relatively high degree of calibration. Conclusion:Age, BMI and amylase concentration of drainage fluid >367.5 U/L on POD3 are the influencing factors for pancreatic fistula after PD. The nomogram model for predicting pancreatic fistula constructed based on this has good predictive and application value.