DataSheet_1_A nomogram based on the preoperative neutrophil-to-lymphocyte ratio to distinguish sarcomatoid renal cell carcinoma from clear cell renal cell carcinoma.docx

ObjectiveOur study aimed to assess the predictive value of the preoperative neutrophil-to-lymphocyte ratio(NLR) in distinguishing sarcomatoid renal cell carcinoma (SRCC) from clear cell renal cell carcinoma(CCRCC) and to developing a nomogram based on the preoperative NLR and other factors to distinguish SRCC from CCRCC.Materials and methodsThe database involved 280 patients, including 46 SRCC and 234 CCRCC. logistic analysis was conducted to select the variables associated with identifying SRCC preoperatively, and subgroup analysis was used to further validate the ability of NLR with preoperative identification of SRCC.In addition, The data were randomly separated into a training cohort(n=195) and a validation cohort(n=85). And an NLR-based nomogram was plotted based on the logistic analysis results. The nomogram was evaluated according to its discrimination, consistency, and clinical benefits.ResultsMultivariate analysis indicated that NLR, flank pain, tumor size, and total cholesterol(TC) were independent risk factors for identifying SRCC. The results of subgroup analysis showed that higher NLR was associated with a higher probability of SRCC in most subgroups. The area under the curve(AUC) of the training and validation cohorts were 0.801 and 0.738, respectively. The results of the calibration curve show high consistency between predicted and actual results. Decision Curve Analysis(DCA) showed clinical intervention based on the model was beneficial over most of the threshold risk range.ConclusionNLR is a potential indicator for preoperative differentiation of SRCC and CCRCC, and the predictive model constructed based on NLR has a good predictive ability. The new model could provide suggestions for the early identification of SRCC.</p

Measurements of Surfactant Adsorption on Sandstone in the Presence of Deep Eutectic Solvents

How to reduce surfactant adsorption on a rock surface is a challenging task because surfactant adsorption would negatively affect the performance of surfactants in enhanced oil recovery. This study thoroughly investigates the effects of various deep eutectic solvent (DES) samples on surfactant adsorption. The surfactant adsorption amounts are quantitatively determined by measuring the variations in the surface tensions of surfactant solutions before and after the adsorption experiments. First, the surface tensions of various pure DES solution samples at different concentrations are measured. The results suggest that the prepared DES samples cannot alter the surface tension of water. Then, the surface tensions of various pure surfactant solutions with different concentrations are measured to build the relationship between surface tension and surfactant concentrations. Afterward, the adsorption experiments are conducted by mixing the crushed Berea sandstone samples with the pure surfactant solutions and the composite DES–surfactant solutions. Next, the surface tensions of the supernatants separated from the mixtures are measured. Correspondingly, the surfactant adsorption amounts are back-calculated from the built relationship between the surface tension and surfactant concentration. The results demonstrate that the DES samples prepared in this study can inhibit the adsorption of the three surfactants on the rock surface. Among all the tested DES samples, the DES sample of choline chloride (ChCl)/urea (1:2) has the most promising performance in inhibiting the adsorption of the surfactant of petroleum sulfonate on the rock surface. Finally, two dynamic adsorption experiments further prove that surfactant adsorption on sandstone particles can be inhibited by adding DES samples

DataSheet1_Sarcomatoid-associated gene risk index for clear cell renal cell carcinoma.xlsx

Sarcomatoid renal cell carcinoma is a de-differentiated form of kidney cancer with an extremely poor prognosis. Genes associated with sarcomatoid differentiation may be closely related to the prognosis of renal cell carcinoma. The prognosis of renal cell carcinoma itself is extremely variable, and a new prognostic model is needed to stratify patients and guide treatment. Data on clear cell renal cell carcinoma with or without sarcomatoid differentiation were obtained from TCGA database, and a sarcomatoid-associated gene risk index (SAGRI) and column line graphs were constructed using sarcomatoid-associated genes. The predictive power of the SAGRI and column line graphs was validated using an internal validation set and an independent validation set (E-MTAB-1980). The SAGRI was constructed using four sarcoma-like differentiation-related genes, COL7A1, LCTL, NPR3, ZFHX4, and had a 1-year AUC value of 0.725 in the training set, 0.712 in the internal validation set, and 0.770 in the independent validation set for TCGA training cohort, with high model reliability. The molecular characteristics among the SAGRI subgroups were analyzed by multiple methods, and results suggested that the SAGRI-HIGH subgroup may benefit more from immunotherapy to improve prognosis. SAGRI satisfactorily predicted the prognosis of patients with clear cell renal cell carcinoma with or without sarcomatoid differentiation.</p