Heterogeneity of cancer stem cell-related marker expression is associated with three-dimensional structures in malignant pleural effusion produced by lung adenocarcinoma.

INTRODUCTION: Cancer stem cells have been described in lung adenocarcinoma-associated malignant pleural effusion. They show clinically important features, including the ability to initiate new tumours and resistance to treatments. However, their correlation with the three-dimensional tumour structures in the effusion is not well understood. METHODS: Cell blocks produced from lung adenocarcinoma patients' pleural effusion were examined for cancer stem cell-related markers Nanog and CD133 using immunocytochemistry. The three-dimensional cancer cell structures and CD133 expression patterns were visualized with tissue-clearing technology. The expression patterns were correlated with tumour cell structures, genetic variants and clinical outcomes. RESULTS: Thirty-nine patients were analysed. Moderate-to-strong Nanog expression was detected in 27 cases (69%), while CD133 was expressed by more than 1% of cancer cells in 11 cases (28%). Nanog expression was more homogenous within individual specimens, while CD133 expression was detected in single tumour cells or cells within small clusters instead of larger structures in 8 of the 11 positive cases (73%). Although no statistically significant correlation between the markers and tumour genetic variants or patient survival was observed, we recorded seven cases with follow-up specimens after cancer treatment, and four (57%) showed a change in stem cell-related marker expression corresponding to treatment response. CONCLUSIONS: Lung adenocarcinoma cells in the pleural effusion show variable expression of cancer stem cell-related markers, some showing a correlation with the size of cell clusters. Their expression level is potentially correlated with cancer treatment effects.

Radon concentration in seawater as a geochemical indicator of submarine fault activity in the Yatsushiro Sea, Japan.

This study examined the relationship between radon (222Rn) concentrations in seawater and crustal activity in the Yatsushiro Sea by investigating the submarine fault zone situated at the southern end of the Futagawa-Hinagu fault zone, activated by the 2016 Kumamoto earthquake (M7.3). We conducted an analysis of 222Rn concentration in samples of bottom water just above the seafloor and pore water in sediments, utilizing multiple and piston cores from the Hakuho Maru Expedition KH18-3. The findings revealed significantly elevated 222Rn concentrations in the central sites of the Yatsushiro Sea, coinciding with a high-stress field exhibiting dense active faults. Seismicity analysis revealed heightened moment release and a low b-value post the 2016 Kumamoto earthquake, indicative of increased seismic activity and the potential for substantial earthquakes in the Yatsushiro Sea vicinity. Our results indicate that heightened concentrations of 222Rn in seawater can serve as an effective tracer for identifying and estimating submarine fault activities. Moreover, our research highlights the utility of 222Rn concentrations in detecting active submarine faults and assessing their activity. It contributes to a comprehensive understanding of the potential for significant earthquakes in the Yatsushiro Sea in the future.

Structural and surface characterizations of 2D ß-In2Se3/3D ß-Ga2O3 heterostructures grown on c-Sapphire substrates by molecular beam epitaxy.

Integrating two-dimensional (2D) layered materials with wide bandgap ß-Ga2O3 has unveiled impressive opportunities for exploring novel physics and device concepts. This study presents the epitaxial growth of 2D ß-In2Se3/3D ß-Ga2O3 heterostructures on c-Sapphire substrates by plasma-assisted molecular beam epitaxy. Firstly, we employed a temperature-dependent two-step growth process to deposit Ga2O3 and obtained a phase-pure ( 2 ¯ 01 ) ß-Ga2O3 film on c-Sapphire. Interestingly, the in-situ reflective high-energy electron diffraction (RHEED) patterns observed from this heterostructure revealed the in-plane 'b' lattice constant of ß-Ga2O3 ~ 3.038Å. In the next stage, for the first time, 2D In2Se3 layers were epitaxially realized on 3D ß-Ga2O3 under varying substrate temperatures (Tsub) and Se/In flux ratios (RVI/III). The deposited layers exhibited (00l) oriented ß-In2Se3 on ( 2 ¯ 01 ) ß-Ga2O3/c-Sapphire with the epitaxial relationship of [ 11 2 ¯ 0 ] ß-In2Se3 || [010] ß-Ga2O3 and [ 10 1 ¯ 0 ] ß-In2Se3 || [102] ß-Ga2O3 as observed from the RHEED patterns. Also, the in-plane 'a' lattice constant of ß-In2Se3 was determined to be ~ 4.027Å. The single-phase ß-In2Se3 layers with improved structural and surface quality were achieved at a Tsub ~ 280 °C and RVI/III ~ 18. The microstructural and detailed elemental analysis further confirmed the epitaxy of 2D layered ß-In2Se3 on 3D ß-Ga2O3, a consequence of the quasi-van der Waals epitaxy. Furthermore, the ß-Ga2O3 with an optical bandgap (Eg) of ~ 5.04 eV (deep ultraviolet) when integrated with 2D ß-In2Se3, Eg ~ 1.43eV (near infra-red) can reveal potential applications in the optoelectronic field.

Development and Validation of a 3D Resnet Model for Prediction of Lymph Node Metastasis in Head and Neck Cancer Patients.

The accurate diagnosis and staging of lymph node metastasis (LNM) are crucial for determining the optimal treatment strategy for head and neck cancer patients. We aimed to develop a 3D Resnet model and investigate its prediction value in detecting LNM. This study enrolled 156 head and neck cancer patients and analyzed 342 lymph nodes segmented from surgical pathologic reports. The patients' clinical and pathological data related to the primary tumor site and clinical and pathology T and N stages were collected. To predict LNM, we developed a dual-pathway 3D Resnet model incorporating two Resnet models with different depths to extract features from the input data. To assess the model's performance, we compared its predictions with those of radiologists in a test dataset comprising 38 patients. The study found that the dimensions and volume of LNM + were significantly larger than those of LNM-. Specifically, the Y and Z dimensions showed the highest sensitivity of 84.6% and specificity of 72.2%, respectively, in predicting LNM + . The analysis of various variations of the proposed 3D Resnet model demonstrated that Dual-3D-Resnet models with a depth of 34 achieved the highest AUC values of 0.9294. In the validation test of 38 patients and 86 lymph nodes dataset, the 3D Resnet model outperformed both physical examination and radiologists in terms of sensitivity (80.8% compared to 50.0% and 91.7%, respectively), specificity(90.0% compared to 88.5% and 65.4%, respectively), and positive predictive value (77.8% compared to 66.7% and 55.0%, respectively) in detecting individual LNM + . These results suggest that the 3D Resnet model can be valuable for accurately identifying LNM + in head and neck cancer patients. A prospective trial is needed to evaluate further the role of the 3D Resnet model in determining LNM + in head and neck cancer patients and its impact on treatment strategies and patient outcomes.