“Inflammation-cancer” transformation of chronic atrophic gastritis （CAG） refers to the process in which the gastric mucosa， in the context of CAG， progresses through stages of precancerous lesions of gastric cancer （PLGC）， such as intestinal metaplasia and dysplasia， and eventually develops into gastric cancer （GC）. In China， the incidence and mortality rates of GC rank among the highest in the world， and the proportion of GC cases caused by gastric mucosal infection and inflammation has been increasing. Modern medical treatments for CAG and PLGC mainly rely on drug therapy， endoscopic resection， and regular surveillance. Although these disease management strategies are relatively mature， they present limitations in early lesion prevention and recurrence risk control. Therefore， it is imperative to identify therapeutic approaches for CAG and PLGC that offer preventive， reversible， and recurrence-reducing benefits. With advances in research on the mechanisms underlying inflammation-cancer transformation and the integration of traditional Chinese and Western medicine， the advantages of TCM in preventing and even reversing early-stage CAG and PLGC have gradually become apparent. This review explored the mechanisms of inflammation-cancer transformation in CAG from five aspects： inflammatory microenvironment， autophagy， glycolysis， bile acids， and ferroptosis. In conjunction with TCM theory and a deeper understanding of the distinct mechanisms involved in the inflammation-cancer transformation of CAG， this review further discussed the specific mechanisms through which TCM intervened in treating CAG and PLGC， with the aim of providing theoretical support and therapeutic insights for future clinical applications.

“Inflammation-cancer” transformation of chronic atrophic gastritis （CAG） refers to the process in which the gastric mucosa， in the context of CAG， progresses through stages of precancerous lesions of gastric cancer （PLGC）， such as intestinal metaplasia and dysplasia， and eventually develops into gastric cancer （GC）. In China， the incidence and mortality rates of GC rank among the highest in the world， and the proportion of GC cases caused by gastric mucosal infection and inflammation has been increasing. Modern medical treatments for CAG and PLGC mainly rely on drug therapy， endoscopic resection， and regular surveillance. Although these disease management strategies are relatively mature， they present limitations in early lesion prevention and recurrence risk control. Therefore， it is imperative to identify therapeutic approaches for CAG and PLGC that offer preventive， reversible， and recurrence-reducing benefits. With advances in research on the mechanisms underlying inflammation-cancer transformation and the integration of traditional Chinese and Western medicine， the advantages of TCM in preventing and even reversing early-stage CAG and PLGC have gradually become apparent. This review explored the mechanisms of inflammation-cancer transformation in CAG from five aspects： inflammatory microenvironment， autophagy， glycolysis， bile acids， and ferroptosis. In conjunction with TCM theory and a deeper understanding of the distinct mechanisms involved in the inflammation-cancer transformation of CAG， this review further discussed the specific mechanisms through which TCM intervened in treating CAG and PLGC， with the aim of providing theoretical support and therapeutic insights for future clinical applications.

Objective:To investigate the prognostic value of Onodera's prognostic nutrition index (PNI) before treatment in patients with cervical and upper thoracic esophageal squamous cell carcinoma (CUTESCC) undergoing definitive chemoradiotherapy (dCRT) and its predictive value in the occurrence of ≥ grade 2 radiation esophagitis (RE).Methods:The data of 163 CUTESCC patients eligible for inclusion criteria admitted to the Fourth Hospital of Hebei Medical University from January 2012 to December 2017 were retrospectively analyzed. The receiver operating characteristic (ROC) curve was used to calculate the best cut-off value of PNI for predicting the prognosis of patients. The prognosis of patients was analyzed by univariate and Cox multivariate analyses. Logistics binary regression model was adopted to analyze the risk factors of ≥ grade 2 RE in univariate and multivariate analyses. The significant factors in logistic multivariate analysis were used to construct nomogram for predicting ≥ grade 2 RE.Results:The optimal cut-off value of PNI was 48.57 [area under the curve (AUC): 0.653, P<0.001]. The median overall survival (OS) and progression-free survival (PFS) were 26.1 and 19.4 months, respectively. The OS ( χ2=6.900, P=0.009) and PFS ( χ2=9.902, P=0.003) of patients in the PNI ≥ 48.57 group ( n=47) were significantly better than those in the PNI < 48.57 group ( n=116). Cox multivariate analysis showed that cTNM stage and PNI were the independent predictors of OS ( HR=1.513, 95% CI: 1.193-1.920, P=0.001; HR=1.807, 95% CI: 1.164-2.807, P=0.008) and PFS ( HR=1.595, 95% CI: 1.247-2.039, P<0.001; HR=2.260, 95% CI: 1.439-3.550, P<0.001). Short-term efficacy was another independent index affecting PFS ( HR=2.072, 95% CI: 1.072-4.003, P=0.030). Logistic multivariate analysis showed that the maximum transverse diameter of the lesion ( OR=3.026, 95% CI: 1.266-7.229, P=0.013), gross tumor volume (GTV) ( OR=3.456, 95% CI: 1.373-8.699, P=0.008), prescription dose ( OR=3.124, 95% CI: 1.346-7.246, P=0.009) and PNI ( OR=2.072, 95% CI: 1.072-4.003, P=0.030) were the independent factors affecting the occurrence of ≥ grade 2 RE. These four indicators were included in the nomogram model, and ROC curve analysis showed that the model could properly predict the occurrence of ≥ grade 2 RE (AUC=0.686, 95% CI: 0.585-0.787). The calibration curve indicated that the actually observed values were in good agreement with the predicted RE. Decision curve analysis (DCA) demonstrated satisfactory nomogram positive net returns in most threshold probabilities. Conclusions:PNI before treatment is an independent prognostic factor for patients with CUTESCC who received definitive chemoradiotherapy. The maximum transverse diameter of the lesion, GTV, prescription dose and PNI are the risk factors for ≥ grade 2 RE in this cohort. Establishing a prediction model including these factors has greater predictive value.

Natural cyclohexapeptide AFN A₁ fromStreptomyces alboflavus 313 has moderate antibacterial and antitumor activities. An artificial designed AFN A₁ homodimer, di-AFN A₁, is an antibiotic exhibiting 10 to 150 fold higher biological activities, compared with the monomer. Unfortunately, the yield of di-AFN A₁ is very low (0.09 ± 0.03 mg·L^-1) in the engineered strain Streptomyces alboflavus 313_hmtS (S. albo/313_hmtS), which is not friendly to be genetically engineered for titer improvement of di-AFN A₁ production. In this study, we constructed a biosynthetic gene cluster for di-AFN A₁ and increased its production through heterologous expression. During the collection of di-AFN A₁ biosynthetic genes, the afn genes were located at three sites of S. alboflavus 313 genome. The di-AFN A₁ biosynthetic gene cluster (BGC) was first assembled on one plasmid and introduced into the model strain Streptomyces lividans TK24, which produced di-AFN A₁ at a titer of 0.43 ± 0.01 mg·L^-1. To further increase the yield of di-AFN A₁, the di-AFN A₁ BGC was multiplied and split to mimic the natural afn biosynthetic genes, and the production of di-AFN A₁ increased to 0.62 ± 0.11 mg·L^-1 in S. lividans TK24 by the later strategy. Finally, different Streptomyces hosts were tested and the titer of di-AFN A₁ increased to 0.81 ± 0.17 mg·L^-1, about 8.0-fold higher than that in S. albo/313_hmtS. Successful heterologous expression of di-AFN A₁ with a remarkable increased titer will greatly facilitate the following synthetic biological study and drug development of this dimeric cyclohexapeptide.
Cloning, Molecular ; Streptomyces/metabolism* ; Multigene Family ; Anti-Bacterial Agents/metabolism* ; Plasmids/genetics*

BACKGROUND: Perioperative treatment has become an increasingly important aspect of the management of patients with non-small cell lung cancer (NSCLC). Small-scale clinical studies performed in recent years have shown improvements in the major pathological remission rate after neoadjuvant therapy, suggesting that it will soon become an important part of NSCLC treatment. Nevertheless, neoadjuvant immunotherapy may be accompanied by serious adverse reactions that lead to delay or cancelation of surgery, additional illness, and even death, and have therefore attracted much attention. The purpose of the clinical recommendations is to form a diagnosis and treatment plan suitable for the current domestic medical situation for the immune-related adverse event (irAE). METHODS: This recommendation is composed of experts in thoracic surgery, oncologists, thoracic medicine and irAE related departments (gastroenterology, respirology, cardiology, infectious medicine, hematology, endocrinology, rheumatology, neurology, dermatology, emergency section) to jointly complete the formulation. Experts make full reference to the irAE guidelines, large-scale clinical research data published by thoracic surgery, and the clinical experience of domestic doctors and publicly published cases, and repeated discussions in multiple disciplines to form this recommendation for perioperative irAE. RESULTS: This clinical recommendation covers the whole process of prevention, evaluation, examination, treatment and monitoring related to irAE, so as to guide the clinical work comprehensively and effectively. CONCLUSIONS Perioperative irAE management is an important part of immune perioperative treatment of lung cancer. With the continuous development of immune perioperative treatment, more research is needed in the future to optimize the diagnosis and treatment of perioperative irAE.

Adverse childhood experience (ACE) is potentially negative experience that occurs between 0 and 18 years old. The ACE adolescents have prominent mental health problems such as emotional regulation disorder, unstable interpersonal relationship, poor coping ability, and cognitive dysfunction. Until now, the factors affecting the mental health of ACE adolescents are not clear, but it is certain that the ecosystem in which ACE adolescents life affects their mental health. Specifically, the parent-child relationship, the school environment, the peer relationship in the micro-system, and the interaction between the parent-child relationship and other interpersonal relationship in the meso-system have been confirmed to be significantly related to the mental health of ACE adolescents. In the appearance system, the neighborhood cohesion, the level of family income, the educational level of parents and the different social and cultural background in the macro-system all have different degrees of impact on the development of ACE adolescents' psychological behaviors. In the diachronic system, the time and frequency of suffering from ACE have different effects on the mental health regarding the ACE adolescents.
Adolescent ; Adverse Childhood Experiences ; Child ; Child, Preschool ; Ecosystem ; Health Status ; Humans ; Infant ; Infant, Newborn ; Mental Health ; Parents

The problem of Poisson denoising is common in various photon-limited imaging applications, especialy in low-light imaging, astronomy and nuclear medical applications. Due to the smal sample problem and the related insufficient self-similarity between patches of whole image, many denoising algorithms cannot obtain the favorable denoising performance. We propose patch-order resampling PCA algorithm for Poisson noise reduction. Firstly, we use the patch-ordered operations to sort the extracted image patches and exploit the bootstrap resampling method to resample the different blocks of spectral images to obtain more data matrix of image samples. Then, we select the patches with largest weights corresponding to the vectors of image samples data matrix as the most similar patches. Finaly, we use principal component analysis algorithm for processing the image to obtain the final denoised image. Experiments results show that the proposed method achieves excelent Poisson noise removal performance in the photon-limited images with smal sample problems.