OBJECTIVE To elucidate the mechanisms responsible for the inhibitory effects of limonene on the proliferation of non-small cell lung cancer(NSCLC) by non-targeted metabolomics and additional approaches. METHODS The CCK-8 assay was utilized to evaluate the inhibitory effects of limonene on NSCLC A549 cell viability and to ascertain the IC50. In vitro experiments, encompassing colony formation, flow cytometry, iron content assessment, and mitochondrial staining, were conducted to assess the anti-lung cancer and iron-induced cell death effects of limonene. Metabolomic analysis was employed to identify potential pathways influenced by limonene, and Western blotting was carried out to validate pivotal proteins within these pathways. RESULTS In comparison to the control group, the limonene-treated group demonstrated a significant, dose-dependent reduction in A549 cell proliferation and colony formation. Optical microscopy revealed cellular detachment and pronounced changes in cellular morphology following exposure to limonene. Limonene induced apoptosis in A549 cells and arrested them in the G0-G1 phase of the cell cycle. Confocal microscopy unveiled diminished mitochondrial fluorescence and an augmented intracellular iron content, indicative of the classical phenomenon of ferroptosis. Metabolomic investigations unveiled divergent metabolic pathways, including glutathione(GSH) metabolism, arginine biosynthesis, D-glutamine and D-glutamate metabolism, as well as cysteine and methionine metabolism, with many of them intricately linked to intracellular GSH synthesis. Western blotting experiments underscored a marked reduction in the levels of SLC40A1, SLC7A11(xCT), and GPX4 proteins within the cells post-limonene treatment. CONCLUSION Limonene may induce ferroptosis in lung cancer cells by reducing GSH synthesis and increasing Fe2+ levels.

Objective:To analyze the prognostic factors and evaluate the accuracy of existing survival prediction models in patients with lung cancer-derived spinal metastases who have undergone open surgery.Methods:According to the inclusion criteria, the data of 76 patients with spinal metastasis of lung cancer who underwent open surgery in the department of Orthopedics in Guangdong Provincial People's Hospital were collected from January 2019 to November 2021. The relationship between the number of bone metastasis, pathological type, visceral metastasis, epidermal growth factor receptor mutation, serum alkaline phosphatase (ALP), hemoglobin (Hb), Frankel grade and postoperative survival time in 76 cases was analyzed by Cox logical regression analysis and Kaplan-Meier method to determine the potential prognostic factors. The accuracy of Tomita score, Tokuhashi revised score, Katagiri New score, New England Spinal Metastasis Score score (NESMS) and Skeletal Oncology Research Group (SORG) machine learning algorithm in predicting postoperative survival time was verified by drawing receiver operating characteristic (ROC) curve.Results:The median follow-up time of the patients was 18.0 months (2.3-36.0 months). The median survival time was 12.6 months [95% CI (10.8, 14.4)]. The survival rates at 6 and 12 months after operation were 71.6% and 52.0%, respectively. Multivariate regression analysis showed that ALP [ HR=0.23, 95% CI (0.11, 0.48), P<0.001], Hb [ HR=4.48, 95% CI (2.07, 9.70), P< 0.001] and EGFR mutation [ HR=2.22, 95% CI (1.04, 4.76), P=0.040] were independent predictors of prognosis. The accuracy of Tomita score, Tokuhashi revised score (2005), Katagiri New score and NESMS score in predicting 1-year mortality was 58.7%, 65.7%, 70.5% and 65% respectively, and the accuracy in predicting 6-month mortality was 63.7%, 62.2%, 61.2% and 56.8% respectively. The accuracy of SORG machine learning algorithm in predicting 1-year and 90 d mortality was 81.1%, 67.5%, respectively. Conclusion:No EGFR mutation, ALP>164 U/L and Hb≤125 g/L were risk factors affecting the survival of patients with spinal metastasis of lung cancer. SORG machine learning algorithm has good accuracy in predicting the postoperative survival rate of patients with lung cancer spinal metastasis.

Gluconacetobacter xylinus is a primary strain producing bacterial cellulose (BC). In G. xylinus, BcsD is a subunit of cellulose synthase and is participated in the assembly process of BC. A series of G. xylinus with different expression levels of the bcsD gene were obtained by using the CRISPR/dCas9 technique. Analysis of the structural characteristics of BC showed that the crystallinity and porosity of BC changed with the expression of bcsD. The porosity varied from 59.95%-84.05%, and the crystallinity varied from 74.26%-93.75%, while the yield of BC did not decrease significantly upon changing the expression levels of bcsD. The results showed that the porosity of bacterial cellulose significantly increased, while the crystallinity was positively correlated with the expression of bcsD, when the expression level of bcsD was below 55.34%. By altering the expression level of the bcsD gene, obtaining BC with different structures but stable yield through a one-step fermentation of G. xylinus was achieved.
Cellulose/chemistry* ; Clustered Regularly Interspaced Short Palindromic Repeats ; Fermentation ; Gluconacetobacter xylinus/metabolism*