Numerical study on flow and heat transfer characteristics of rectangular mini-channel of interpolated double S turbulators.

In this study, we propose a new type of small-channel plug-in, the double S turbulators, for passive heat transfer enhancement to improve the flow and heat transfer performance of the fluid in the channel. In the range of Reynolds number 254.51~2545.09, under constant wall temperature heating conditions, the effects of interpolated double S turbulators with different long axial radii (1mm, 1.5mm, 2mm) on the average Nusselt number, pressure drop, total thermal resistance and field synergy number in the rectangular mini-channel were studied. The simulation results show that compared with the smooth rectangular mini-channel, after interpolating double S turbulators with different long axial radii (1mm, 1.5mm, 2mm), the average Nusselt number increased by 81.74%~101.74%, 71.29%~94.06%, 67.16%~88.48%, the total thermal resistance decreased by 45.1%~50.72%, 41.72%~48.74%, 40.28%~47.2%, and the number of field synergies increased by 85.58%~111.65%, 74.1%~102.6%, 69.64%~96.12%. At present, there are few studies on the boundary condition of constant wall temperature, and this paper supplements the research on this aspect. At the same time, the heat transfer performance of the rectangular mini-channel of the interpolated double S turbulators is stronger than that of the ordinary smooth rectangular mini-channel, which not only provides a new idea for the manufacture of micro heat dissipation equipment, but also improves the heat transfer performance of micro heat dissipation equipment and improves its work efficiency. According to the simulation data, the prediction formula of average Nusselt number and pressure drop was established by nonlinear regression method, which can be used to predict the flow and heat transfer characteristics of the rectangular mini-channel of the interpolated double S turbulators.

Recognition and combination of multiple cell-death features showed good predictive value in lung adenocarcinoma.

Background: Cell death is a key regulatory process in organisms and its study has become increasingly important in the field of cancer. While prior research has primarily centered on the individual pathways of cell death in cancer, there has been a lack of comprehensive investigation into the synergistic effects of multiple cell death pathways. Methods: Genes related to autophagy, apoptosis, necroptosis, pyroptosis, and cuproptosis was selected, and patients' data was collected from The Cancer Genome Atlas (TCGA)project. Cell death features were identified using principal component analysis and combined to create a composite score. A scalable prediction model was then created using LASSO regression after a thorough assessment of the composite scores. The model was subsequently validated across multiple external datasets to establish its robustness and reliability. Results: The cell death features effectively represented the gene expression patterns in the samples. The composite score well predicted prognosis, clinical stage, mutation, tumor microenvironment, and immunotherapy effectiveness. The model built on composite scores accurately predicted prognosis and immunotherapy effectiveness across multiple datasets. GJB2 was identified as a potential biomarker. Conclusion: Models based on multiple cell death pathways have significant predictive power for prognosis and immunotherapy effectiveness in lung adenocarcinoma. This highlights the synergistic role of multiple cell death pathways in cancer development and offers a new perspective for cancer research.