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Background: Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT. Methods: Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro. Results: 485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin. Conclusions: NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it. [ABSTRACT FROM AUTHOR]

A theoretical model for predicting the temperature-dependent thermal conductivity of pure molten salts, both simple and complex, is presented. The model is based on kinetic theory and incorporates Einstein's concept of minimum thermal conductivity. The proposed formulation can consider the magnitude of thermal conductivity for separate salts, including complex and polymerizing salts. The model's thermal conductivity predictions were compared to reliable experimental data in the literature and a previously recommended thermal conductivity model using the Bland–Altman method. The comparison showed accurate thermal conductivity predictions relative to the reliable experimental data, with an average deviation of 10% or less. The model's predictions were also compared to the experimental data on an individual basis for halide, divalent halide, carbonate, nitrate, nitrite, sulfate, and hydroxide molten salts, demonstrating reliable predictions for the molten salts studied and improved accuracy over the previous model. Lastly, a database of simple and complex molten salts, with the necessary parameters for modeling their thermal conductivity, is recommended. • A database for the thermal conductivity of more than 60 molten salts is presented. • The model is developed based on the kinetic theory. • Few key thermophysical properties are required for the model parameterization. • The predictive capability of the model is found to be very good. • The model is valid from the melting temperature up to 75% of the boiling temperature. [ABSTRACT FROM AUTHOR]