Free Space Makes the Polymer “Dead Layer” Alive

The effect of free space on molecular motion inside the polymer “dead layer” or adsorbed nanolayers on solid surfaces is investigated. Free space is introduced into the nanolayer by choosing a polymer with a relatively big side group, poly n-butyl methacrylate (PnBMA), and polarization-resolved single-molecule fluorescence microscopy is adopted as the method. The rotational motion of the doped fluorescent probes is found to be considerably excited at moderate temperatures, attributed to the free space brought by the side group of the PnBMA. The development of the adsorbed nanolayer by the prolonged annealing of the parent film is carefully monitored, together with the evolution of the molecular motion and the glass transition temperature (Tg). The Tg values of the exposed nanolayers are considerably lower than that of the bulk system, while they become higher than those in the bulk situation when the nanolayer is covered with a polymer top layer. The experimental evidence has demonstrated that the free space made available by the side group and the air–polymer interface has considerably promoted the molecular motion inside the adsorbed nanolayers, even under the situation of overwhelming surface attraction

Policy Learning with Asymmetric Counterfactual Utilities*

Data-driven decision making plays an important role even in high stakes settings like medicine and public policy. Learning optimal policies from observed data requires a careful formulation of the utility function whose expected value is maximized across a population. Although researchers typically use utilities that depend on observed outcomes alone, in many settings the decision maker’s utility function is more properly characterized by the joint set of potential outcomes under all actions. For example, the Hippocratic principle to “do no harm” implies that the cost of causing death to a patient who would otherwise survive without treatment is greater than the cost of forgoing life-saving treatment. We consider optimal policy learning with asymmetric counterfactual utility functions of this form that consider the joint set of potential outcomes. We show that asymmetric counterfactual utilities lead to an unidentifiable expected utility function, and so we first partially identify it. Drawing on statistical decision theory, we then derive minimax decision rules by minimizing the maximum expected utility loss relative to different alternative policies. We show that one can learn minimax loss decision rules from observed data by solving intermediate classification problems, and establish that the finite sample excess expected utility loss of this procedure is bounded by the regret of these intermediate classifiers. We apply this conceptual framework and methodology to the decision about whether or not to use right heart catheterization for patients with possible pulmonary hypertension.</p

DataSheet_1_Quantitative Dynamic-Enhanced MRI and Intravoxel Incoherent Motion Diffusion−Weighted Imaging for Prediction of the Pathological Response to Neoadjuvant Chemotherapy and the Prognosis in Locally Advanced Gastric Cancer.docx

BackgroundThis study aimed to explore the predictive value of quantitative dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters for the response to neoadjuvant chemotherapy (NCT) in locally advanced gastric cancer (LAGC) patients, and the relationship between the prediction results and patients’ prognosis, so as to provide a basis for clinical individualized precision treatment.MethodsOne hundred twenty-nine newly diagnosed LAGC patients who underwent IVIM-DWI and DCE-MRI pretreatment were enrolled in this study. Pathological tumor regression grade (TRG) served as the reference standard of NCT response evaluation. The differences in DCE-MRI and IVIM-DWI parameters between pathological responders (pR) and pathological non-responders (pNR) groups were analyzed. Univariate and multivariate logistic regressions were used to identify independent predictive parameters for NCT response. Prediction models were built with statistically significant quantitative parameters and their combinations. The performance of these quantitative parameters and models was evaluated using receiver operating characteristic (ROC) analysis. Clinicopathological variables, DCE-MRI and IVIM-DWI derived parameters, as well as the prediction model were analyzed in relation to 2-year recurrence-free survival (RFS) by using Cox proportional hazards model. RFS was compared using the Kaplan–Meier method and the log-rank test.ResultsSixty-nine patients were classified as pR and 60 were pNR. Ktrans, kep, and ve values in the pR group were significantly higher, while ADCstandard and D values were significantly lower than those in the pNR group. Multivariate logistic regression analysis demonstrated that Ktrans, kep, ve, and D values were independent predictors for NCT response. The combined predictive model, which consisted of DCE-MRI and IVIM-DWI, showed the best prediction performance with an area under the curve (AUC) of 0.922. Multivariate Cox regression analysis showed that ypStage III and NCT response predicted by the IVIM-DWI model were independent predictors of poor RFS. The IVIM-DWI model could significantly stratify median RFS (52 vs. 15 months) and 2-year RFS rate (72.3% vs. 21.8%) of LAGC.ConclusionPretreatment DCE-MRI quantitative parameters Ktrans, kep, ve, and IVIM-DWI parameter D value were independent predictors of NCT response for LAGC patients. The regression model based on baseline DCE-MRI, IVIM-DWI, and their combination could help RFS stratification of LAGC patients.</p

Additional file 1 of Neoadjuvant chemotherapy with modified FOLFOXIRI for locally advanced rectal cancer to transform effectively EMVI and MRF from positive to negative: results of a long-term single center phase 2 clinical trial

Additional file 1: Table S1. Summary of adverse events of adjuvant chemotherapy(N = 42*)

DataSheet_1_Combined CT and serum CA19-9 for stratifying risk for progression in patients with locally advanced pancreatic cancer receiving intraoperative radiotherapy.pdf

Background and purposeThe aim of this study was to evaluate the significance of baseline computed tomography (CT) imaging features and carbohydrate antigen 19-9 (CA19-9) in predicting prognosis of locally advanced pancreatic cancer (LAPC) receiving intraoperative radiotherapy (IORT) and to establish a progression risk nomogram that helps to identify the potential beneficiary of IORT.MethodsA total of 88 LAPC patients with IORT as their initial treatment were enrolled retrospectively. Clinical data and CT imaging features were analyzed. Cox regression analyses were performed to identify the independent risk factors for progression-free survival (PFS) and to establish a nomogram. A risk-score was calculated by the coefficients of the regression model to stratify the risk of progression.ResultsMultivariate analyses revealed that relative enhanced value in portal-venous phase (REV-PVP), peripancreatic fat infiltration, necrosis, and CA19-9 were significantly associated with PFS (all p ConclusionThe integrated nomogram would help clinicians to identify appropriate patients who might benefit from IORT before treatment and to adapt an individualized treatment strategy.</p

Reporting of tumor lysis syndrome with targeted therapy for hepatic cancer in the FDA adverse events reporting system

Hepatic cancer is a common cancer in clinical practice. Current drug therapies for this condition include targeted therapy, chemotherapy, and immunotherapy. Tumor lysis syndrome (TLS) is the most serious complication of oncology treatment. According to the literature, several cases reported TLS occurred with targeted therapies for hepatic cancer. Reporting odds ratio and information component were used to measure the disproportionate signals for TLS associated with targeted therapies, using data from the FDA’s Adverse Event Reporting System (FAERS). A stepwise sensitivity analysis was conducted to test the robustness of signals. Time-to-onset analysis was used to describe the latency of TLS events associated with targeted therapies. The Bradford Hill criteria were used to perform a global assessment of the evidence. Sorafenib, lenvatinib, cabozantinib, and bevacizumab showed higher disproportionate signals for TLS than chemotherapy. The median number of days to TLS occurrence after drug therapy was 5.5, 6.5, and 6.5 days for sorafenib, lenvatinib, and bevacizumab, respectively. There is a significant association between tumor lysis syndrome and targeted therapies for hepatic carcinoma, with particularly strong signals for sorafenib and lenvatinib. Clinicians should be aware of the potential for tumor lysis syndrome in targeted therapies for hepatic carcinoma.</p