Study on esophageal cancer radiotherapy dosimetry and position verification for volumetric modulated arc therapy.

BACKGROUND: This study analyzed the respective advantages and disadvantages by comparing volumetric modulated arc therapy (VMAT) and intensity modulated radiotherapy (IMRT) on the dose distribution and position verification distribution characteristics in esophageal cancer radiotherapy, in order to provide the reference for the clinical radiotherapy technology optimization of esophageal cancer. METHODS: A total of 56 cases of patients with esophageal cancer were selected and applied to the Pinnacle three-dimensional radiation treatment planning system (TPS), in order to design a VMAT plan and IMRT plan under the guidance of image-guided radiotherapy (IGRT). The dosimetry and position verification difference were compared between the two groups. RESULTS: Revealed that the target dose distribution of the VMAT plan and IMRT plan meets the requirements in clinical dosimetry for all 56 patients in this study. Under the premise of similar target coverage, the conformal index (CI) of the VMAT plan, homogeneity index (HI), target volume, BODY-PTV radiated volume and spinal cord Dmax, bilateral lung V5, V20 and mean lung dose (MLD), monitor unit (MU) and treatment time (TT), as well as position verification and others, were obviously superior to those in the IMRT plan; and the difference was statistically significant. CONCLUSION: CBCT guided VMAT is a potential effective treatment for esophageal cancer and may be more effective and safer than IMRT.

Edge-Cloud Co-Evolutionary Algorithms for Distributed Data-Driven Optimization Problems.

Surrogate-assisted evolutionary algorithms (EAs) have been proposed in recent years to solve data-driven optimization problems. Most existing surrogate-assisted EAs are for centralized optimization and do not take into account the challenges brought by the distribution of data at the edge of networks in the era of the Internet of Things. To this end, we propose edge-cloud co-EAs (ECCoEAs) to solve distributed data-driven optimization problems, where data are collected by edge servers. Specifically, we first propose a distributed framework of ECCoEAs, which consists of a communication mechanism, edge model management, and cloud model management. This communication mechanism is to avoid deadlock during the collaboration of edge servers and the cloud server. In edge model management, the edge models are trained based on local historical data and data composed of new solutions generated by co-evolutionary and their real evaluation values. In cloud model management, the black-box prediction functions received from edge models are used to find promising solutions to guide the edge model management. Moreover, two ECCoEAs are implemented, which proves the generality of the framework. To verify the performance of algorithms for distributed data-driven optimization problems, we design a novel benchmark test suite. The performance on the benchmarks and practical distributed clustering problems shows the effectiveness of ECCoEAs.

Theaflavin promoted apoptosis in nasopharyngeal carcinoma unexpectedly via inducing autophagy in vitro.

Objectives: This study aimed to investigate the mechanism of the anticancer effect of theaflavin (TF) in nasopharyngeal carcinoma. Materials and Methods: CNE2 cells were used to study the anticancer effect of TF. This study used Cell Counting Kit-8 (CCK8) assay on proliferation and used flow cytometry to detect apoptosis. The protein expression of Bcl-2, Bax, caspase 3, and caspase 9 was detected by Western blot, and autophagy-related proteins were also detected. Results: TF inhibited proliferation of CNE2 cells, promoted apoptosis, and up-regulated the expression of caspase 3, caspase 9, and Bax, and decreased the level of Bcl-2. Unexpectedly, TF induced autophagy rather than inhibiting autophagy through up-regulating the levels of the autophagy marker light chain 3 (LC3) and Lysosomal-associated membrane protein 1 (LAMP1) and reducing levels of the autophagosome cargo protein p62, and the effect was via the mTOR pathway. Besides, autophagy inhibitor Chloroquine (CQ) suppressed the effect of TF on Bax, Bcl-2 and activation of caspase 3 and caspase 9. Conclusion: TF promoted apoptosis of nasopharyngeal carcinoma cells, the mechanism was unexpectedly involved in inducing autophagy.

The expression and clinical significance of metastasis suppressor gene and matrix metalloproteinase-2 in esophageal squamous cell of carcinoma.

To investigate the expression and clinical significance of metastasis suppressor gene and matrix metalloproteinase-2 in esophageal squamous cell of carcinoma. choose 30 cases of specimens of esophageal squamous cell carcinoma which are removed in surgery and confirmed by pathology and 30 cases of specimens of normal esophageal mucosa. Use immunohistochemistry SP method to detect the expression of nm23-H1, MMP-2 protein in esophageal squamous cell carcinoma and normal esophageal mucosal. The positive rate of nm23-H1 protein in esophageal squamous cell carcinoma was 43.3% (13/30), while that in normal esophageal mucosa was 100% (30/30), which has a significant difference between them (χ2=22. 083, P<0.05). The positive rate of MMP-2 protein in esophageal squamous cell carcinoma was 90.0% (27/30), while that in normal esophageal mucosa was 33.3% (10/30), and there is a significant difference between them (χ2=28. 370, P<0.05); For the expression of nm23-H1 and MMP-2 in esophageal squamous cell carcinoma, there was nothing to do with sex, age and tumor size (P>0.05), but it was related to the degree of tumor differentiation, depth of invasion and lymph node metastasis (P<0.05); The expression of nm23-H1 is related to the cut end of residual cancer (P<0.05), while the expression of MMP-2 has nothing to do with the cut end of residual cancer (P>0.05); The expression of nm23-H1 and MMP-2 in esophageal squamous cell carcinoma was negatively correlated. nm23-H1 and MMP-2 have played a role in the development of esophageal cancer, which can promote the occurence of distant metastasis; The loss of expression of nm23-H1 may be related to cut end residual cancer; nm23-H1 and MMP-2 may be as an indicator for esophageal cancer metastasis and prognosis.