Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC).Experimental Design: One-hundred and eighteen patients (training cohort: n ¼ 88; validation cohort: n ¼ 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms. Nomogram discrimination and calibration were evaluated. Associations between radiomics features and clinical data were investigated using heatmaps.Results: The radiomics signatures were significantly associated with PFS. A radiomics signature derived from joint CET1-w and T2-w images showed better prognostic performance than signatures derived from CET1-w or T2-w images alone. One radiomics nomogram combined a radiomics signature from joint CET1-w and T2-w images with the TNM staging system. This nomogram showed a significant improvement over the TNM staging system in terms of evaluating PFS in the training cohort (C-index, 0.761 vs. 0.514; P < 2.68 Â 10 À9 ). Another radiomics nomogram integrated the radiomics signature with all clinical data, and thereby outperformed a nomogram based on clinical data alone (C-index, 0.776 vs. 0.649; P < 1.60 Â 10 À7 ). Calibration curves showed good agreement. Findings were confirmed in the validation cohort. Heatmaps revealed associations between radiomics features and tumor stages. Conclusions: Multiparametric MRI-based radiomics nomograms provided improved prognostic ability in advanced NPC. These results provide an illustrative example of precision medicine and may affect treatment strategies.

Supporting information placeholder ABSTRACT:We measure electronic conductance through single conjugated molecules bonded to Au metal electrodes with direct Au-C covalent bonds using the scanning tunneling microscope based break-junction technique. We start with molecules terminated with trimethyltin end groups that cleave off in situ resulting in formation of a direct covalent sigma bond between the carbon backbone and the gold metal electrodes. The molecular carbon backbone used in this study consist of a conjugated system that has one terminal methylene group on each end, which bonds to the electrodes, achieving large electronic coupling of the electrodes to the system. The junctions formed with the prototypical example of 1,4-dimethylenebenzene show a conductance approaching one conductance quantum (G 0 = 2e 2 /h). Junctions formed with methylene terminated oligophenyls with two to four phenyl units show a hundred-fold increase in conductance compared with junctions formed with amine-linked oligophenyls. The conduction mechanism for these longer oligophenyls is tunneling as they exhibit an exponential dependence of conductance with oligomer length. In addition, density functional theory based calculations for the Au-xylylene-Au junction show nearresonant transmission with a cross-over to tunneling for the longer oligomers.

We report the simultaneous measurement of conductance and thermopower of highly conducting single-molecule junctions using a scanning tunneling microscope-based break-junction setup. We start with molecular backbones (alkanes and oligophenyls) terminated with trimethyltin end groups that cleave off in situ to create junctions where terminal carbons are covalently bonded to the Au electrodes. We apply a thermal gradient across these junctions and measure their conductance and thermopower. Because of the electronic properties of the highly conducting Au-C links, the thermoelectric properties and power factor are very high. Our results show that the molecular thermopower increases nonlinearly with the molecular length while conductance decreases exponentially with increasing molecular length. Density functional theory calculations show that a gateway state representing the Au-C covalent bond plays a key role in the conductance. With this as input, we analyze a series of simplified models and show that a tight-binding model that explicitly includes the gateway states and the molecular backbone states accurately captures the experimentally measured conductance and thermopower trends.

FAM134B/RETREG1 is a selective ER-phagy receptor that regulates the size and shape of the endoplasmic reticulum. The structure of its reticulon-homology domain (RHD), an element shared with other ER-shaping proteins, and the mechanism of membrane shaping remain poorly understood. Using molecular modeling and molecular dynamics (MD) simulations, we assemble a structural model for the RHD of FAM134B. Through MD simulations of FAM134B in flat and curved membranes, we relate the dynamic RHD structure with its two wedge-shaped transmembrane helical hairpins and two amphipathic helices to FAM134B functions in membrane-curvature induction and curvature-mediated protein sorting. FAM134B clustering, as expected to occur in autophagic puncta, amplifies the membrane-shaping effects. Electron microscopy of in vitro liposome remodeling experiments support the membrane remodeling functions of the different RHD structural elements. Disruption of the RHD structure affects selective autophagy flux and leads to disease states.

Controlling the electrical conductance and in particular the occurrence of quantum interference in single-molecule junctions through gating effects, has potential for the realization of highperformance functional molecular devices. In this work, we used an electrochemically-gated, mechanically-controllable break junction technique to tune the electronic behaviour of thiophene-based molecular junctions that show destructive quantum interference (DQI) features. By varying the voltage applied to the electrochemical gate at room temperature, we

We have measured the conductance of single-molecule junctions created with three different molecular wires using the scanning tunneling microscope-based break-junction technique. Each wire contains one of three different cyclic five-membered rings: cyclopentadiene, furan, or thiophene. We find that the single-molecule conductance of these three wires correlates negatively with the resonance energy of the five-membered ring; the nonaromatic cyclopentadiene derivative has the highest conductance, while the most aromatic of this series, thiophene, has the lowest. Furthermore, we show for another wire structure that the conductance of furan-based wires is consistently higher than for analogous thiophene systems, indicating that the negative correlation between conductance and aromaticity is robust. The best conductance would be for a quinoid structure that diminishes aromaticity. The energy penalty for partly adopting the quinoid structure is less with compounds having lower initial aromatic stabilization. An additional effect may reflect the lower HOMOs of aromatic compounds.

Gastric cancer is one of the leading causes of cancer mortality in the world, and finding novel agents and strategies for the treatment of advanced gastric cancer is of urgent need. Curcumin is a well-known natural product with anti-cancer ability, but is limited by its poor chemical stability. In this study, an analog of curcumin with high chemical stability, WZ35, was designed and evaluated for its anti-cancer effects and underlying mechanisms against human gastric cancer. WZ35 showed much stronger anti-proliferative effects than curcumin, accompanied by dose-dependent induction of cell cycle arrest and apoptosis in gastric cancer cells. Mechanistically, our data showed that WZ35 induced reactive oxygen species (ROS) production, resulting in the activation of both JNK-mitochondrial and ER stress apoptotic pathways and eventually cell apoptosis in SGC-7901 cells. Blockage of ROS production totally reversed WZ35-induced JNK and ER stress activation as well as cancer cell apoptosis. In vivo, WZ35 showed a significant reduction in SGC-7901 xenograft tumor size in a dose-dependent manner. Taken together, this work provides a novel anticancer candidate for the treatment of gastric cancer, and importantly, reveals that increased ROS generation might be an effective strategy in human gastric cancer treatment.

The development of mechanism-based, multiscale pharmacokinetic–pharmacodynamic (PK-PD) models for chimeric antigen receptor (CAR)-T cells is needed to enable investigation of in vitro and in vivo correlation of CAR-T cell responses and to facilitate preclinical-to-clinical translation. Toward this goal, we first developed a cell-level in vitro PD model that quantitatively characterized CAR-T cell-induced target cell depletion, CAR-T cell expansion and cytokine release. The model accounted for key drug-specific (CAR-affinity, CAR-densities) and system-specific (antigen densities, E:T ratios) variables and was able to characterize comprehensive in vitro datasets from multiple affinity variants of anti-EGFR and anti-HER2 CAR-T cells. Next, a physiologically based PK (PBPK) model was developed to simultaneously characterize the biodistribution of untransduced T-cells, anti-EGFR CAR-T and anti-CD19 CAR-T cells in xenograft -mouse models. The proposed model accounted for the engagement of CAR-T cells with tumor cells at the site of action. Finally, an integrated PBPK-PD relationship was established to simultaneously characterize expansion of CAR-T cells and tumor growth inhibition (TGI) in xenograft mouse model, using datasets from anti-BCMA, anti-HER2, anti-CD19 and anti-EGFR CAR-T cells. Model simulations provided potential mechanistic insights toward the commonly observed multiphasic PK profile (i.e., rapid distribution, expansion, contraction and persistence) of CAR-T cells in the clinic. Model simulations suggested that CAR-T cells may have a steep dose-exposure relationship, and the apparent Cmax upon CAR-T cell expansion in blood may be more sensitive to patient tumor-burden than CAR-T dose levels. Global sensitivity analysis described the effect of other drug-specific parameters toward CAR-T cell expansion and TGI. The proposed modeling framework will be further examined with the clinical PK and PD data, and the learnings can be used to inform design and development of future CAR-T therapies.