Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.

This article adopts Professor CHEN Chaozu′s " sanjiao composed by membrane-striae" theory as its foundation to explore the relationship between irritable bowel syndrome and functional/structural abnormalities of the membrane-striae. Sanjiao encompasses both the tangible membrane and the intangible striae. These striae permeate the entire body，and their pathological changes comprehensively reflect qi，body fluids，and fasciae. Based on the physiological function of the membrane-striae in regulating qi and fluids，the pathogenesis of irritable bowel syndrome is characterized by a disharmony of membrane-striae and an imbalance of the qi-fluid interactions. In the early stage，external pathogens，emotional factors，or dietary stimuli often cause membrane-striae constriction and disordered qi-fluid circulation. In the middle stage，stagnant fluids gradually transform into phlegm retention，leading to membrane-striae obstruction. In the late stage，deficiency of vital qi becomes predominant，manifesting as laxity of membrane-striae with impaired control or weakened conduction. The treatment of irritable bowel syndrome should adopt " unblocking" as the guiding principle. In the early stage，therapy should focus on eliminating pathogenic factors and soothing membrane-striae to promptly restore qi-fluid circulation，thereby attaining unblocking through spasm relief. In the middle stage，treatment should focus on resolving tangible obstructions in membrane-striae，achieving unblocking via dredging. In the late stage，the emphasis should shift to reinforcing healthy qi，particularly by strengthening spleen-kidney yang qi，and achieving unblocking through supplementation. Concurrently，throughout the entire treatment process，the regulation of mental state and easing of emotional tension should be integrated to alleviate patient′s anxiety，achieving the goal of holistic treatment of both body and mind.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To compare the dosimetric differences, plan complexity, verification pass rate, and execution efficiency of volumetric modulated arc therapy (VMAT) plans designed for post-mastectomy radiotherapy of breast cancer using Halcyon 2.0 and VitalBeam accelerators in flattening filter-free mode. Methods A retrospective analysis was conducted on imaging data from 87 female breast cancer patients aged 29 to 75 (49.9 ± 9.9) years who underwent modified radical mastectomy followed by radiotherapy. VMAT plans were designed using both VitalBeam and Halcyon accelerators in flattening filter-free mode. The dosimetric parameters, plan complexity, verification pass rate, and execution efficiency were compared between the plans designed for both accelerators, with a significance level of P<0.05. Results In terms of target volume parameters, Halcyon 2.0 plans demonstrated superior homogeneity index and conformity index. For organs at risk, the Halcyon 2.0 plans showed lower doses for the lungs (D_20% and D_mean) and heart (D_mean) compared to the VitalBeam plans (all P<0.05). Regarding plan complexity, Halcyon 2.0 plans exhibited better median average aperture area variation (0.35 ± 0.02), smaller aperture score, and larger median plan aperture area than VitalBeam plans (all P<0.05). However, VitalBeam plans had a superior median modulation complexity score (0.28 ± 0.01) compared to Halcyon 2.0 plans (P<0.05). Patient plans were assessed using the ArcCHECK phantom, revealing higher pass rates and significantly shorter execution time for Halcyon plans compared to VitalBeam plans (P<0.05). Conclusion Both Halcyon 2.0 and VitalBeam accelerators can provide high-quality VMAT plans for postoperative radiotherapy of breast cancer, with excellent verification pass rates ensuring treatment accuracy and efficacy. However, Halcyon 2.0 offers lower plan complexity, simplifies the treatment planning process, and reduces execution time, thereby achieving higher treatment efficiency and demonstrating greater advantages in clinical applications.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

In recent years, the incidence of dry eye disease(DED)is increasing, positioning it as one of the most prevalent diseases affecting the ocular surface. Inflammatory response is the pathological basis of DED, involving various inflammatory mediators and inflammatory signaling pathways. Consequently, anti-inflammatory treatment emerges as a fundamental strategy for preventing and managing DED. This review summarizes the classic inflammatory factors involved in the development and progression of DED, including interleukins, tumor necrosis factor, matrix metalloproteinases, chemokines, and cell adhesion molecules. It also discusses the relevant inflammatory signaling pathways: the MAPKs pathway, NF-κB pathway, Wnt pathway and TLR pathway. Additionally, this review addresses the mechanisms of action and alterations in relevant biomarkers associated with current first-line recommended anti-inflammatory therapies, including corticosteroids, immunosuppressants, nonsteroidal anti-inflammatory drugs, and traditional Chinese medicine approaches to inflammation management. This comprehensive overview aims to enhance understanding of the inflammatory mechanisms underlying DED while exploring future therapeutic prospects.

In recent years, the incidence of dry eye disease(DED)is increasing, positioning it as one of the most prevalent diseases affecting the ocular surface. Inflammatory response is the pathological basis of DED, involving various inflammatory mediators and inflammatory signaling pathways. Consequently, anti-inflammatory treatment emerges as a fundamental strategy for preventing and managing DED. This review summarizes the classic inflammatory factors involved in the development and progression of DED, including interleukins, tumor necrosis factor, matrix metalloproteinases, chemokines, and cell adhesion molecules. It also discusses the relevant inflammatory signaling pathways: the MAPKs pathway, NF-κB pathway, Wnt pathway and TLR pathway. Additionally, this review addresses the mechanisms of action and alterations in relevant biomarkers associated with current first-line recommended anti-inflammatory therapies, including corticosteroids, immunosuppressants, nonsteroidal anti-inflammatory drugs, and traditional Chinese medicine approaches to inflammation management. This comprehensive overview aims to enhance understanding of the inflammatory mechanisms underlying DED while exploring future therapeutic prospects.

In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.