Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified...

Lipid coverage is crucial in comprehensive lipidomics studies challenged by high diversity in lipid structures and wide dynamic range in lipid levels. Current state-of-the-art lipidomics technologies are mostly based on mass spectrometry (MS), including direct-infusion MS, chromatography-MS, and matrix-assisted laser desorption ionization (MALDI) imaging MS, each with its pros and cons. Due to the need or favorability for measurement of isomers and isobars, chromatography-MS is preferable for lipid profiling. The ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based nontargeted lipidomics approach and UHPLC-tandem MS (UHPLC-MS/MS)-based targeted approach are two representative methodological platforms for chromatography-MS. In the present study, we developed a high coverage pseudotargeted lipidomics method combining the advantages of nontargeted and targeted lipidomics approaches. The high coverage of lipids was achieved by integration of the detected lipids derived from nontargeted UHPLC-HRMS lipidomics analysis of multiple matrices (e.g., plasma, cell, and tissue) and the predicted lipids speculated on the basis of the structure and chromatographic retention behavior of the known lipids. A total of 3377 targeted lipid ion pairs with over 7000 lipid molecular structures were defined. The pseudotargeted lipidomics method was well validated with satisfactory analytical characteristics in terms of linearity, precision, reproducibility, and recovery for lipidomics profiling. Importantly, it showed better repeatability and higher coverage of lipids than the nontargeted lipidomics method. The applicability of the developed pseudotargeted lipidomics method was testified in defining differential lipids related to diabetes. We believe that comprehensive lipidomics studies will benefit from the developed high coverage pseudotargeted lipidomics approach.

A series of mesoporous WO3 catalysts were facilely synthesized by a hydrothermal method using mesoporous silica KIT-6 as a hard template and silicotungstic acid as a precursor.

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Transition metal oxides (TMOs) are promising electrochromic (EC) materials for applications such as smart windows and displays, yet the challenge still exists to achieve good flexibility, high coloration efficiency and fast response simultaneously. MXenes (e.g. Ti3C2Tx) and their derived TMOs (e.g. 2D TiO2) are good candidates for high-performance and flexible EC devices because of their 2D nature and the possibility of assembling them into loosely networked structures. Here we demonstrate flexible, fast, and high-coloration-efficiency EC devices based on self-assembled 2D TiO2/Ti3C2Tx heterostructures, with the Ti3C2Tx layer as the transparent electrode, and the 2D TiO2 layer as the EC layer. Benefiting from the well-balanced porosity and connectivity of these assembled nanometer-thick heterostructures, they present fast and efficient ion and electron transport, as well as superior mechanical and electrochemical stability. We further demonstrate large-area flexible devices which could potentially be integrated onto curved and flexible surfaces for future ubiquitous electronics.

Inosine monophosphate dehydrogenase (IMPDH) of human is an attractive target for immunosuppressive agents. Currently, smallmolecule inhibitors do not show good selectivity for different IMPDH isoforms (IMPDH1 and IMPDH2), resulting in some adverse effects, which limit their use. Herein, we used a small-molecule probe specifically targeting IMPDH2 and identified Cysteine residue 140 (Cys140) as a selective druggable site. On covalently binding to Cys140, the probe exerts an allosteric regulation to block the catalytic pocket of IMPDH2 and further induces IMPDH2 inactivation, leading to an effective suppression of neuroinflammatory responses. However, the probe does not covalently bind to IMPDH1. Taken together, our study shows Cys140 as a druggable site for selectively inhibiting IMPDH2, which provides great potential for development of therapy agents for autoimmune and neuroinflammatory diseases with less unfavorable tolerability profile.nosine monophosphate dehydrogenase (IMPDH) is a major rate-limiting enzyme involved in guanosine and deoxyguanosine biosynthesis and widely expressed in immunocytes (1). There exist two IMPDH isoforms (IMPDH1 and IMPDH2), which are encoded by distinct genes (2, 3). Many inflammation-relevant diseases have been specially characterized by the high expression of isoform II of IMPDH (IMPDH2) in rapidly proliferating immunocytes, rather than the "housekeeping" type I isoform (IMPDH1) in normal human leukocytes and lymphocytes (4, 5). Therefore, selective targeting of IMPDH2 with small molecules is an attractive topic for development of antiinflammation agents with low side effects.Both IMPDH isoforms contain two major domains: the catalytic domain for substrate interaction and the Bateman domain, which is not required for catalytic activity but exerts an important allosteric regulation effect on IMPDH activity by communicating with the catalytic domain (6, 7). By influencing catalytic domain activity, the Bateman domain can regulate IMPDH function and further blocks the downstream-of-inflammation signaling pathways (8, 9). Currently, IMPDH inhibitors are divided into two major categories. One kind of inhibitor, including 6-chloropurine riboside ribavirin and mizoribine, targets the binding pocket of the natural substrate, inosine monophosphate (IMP). Another kind of inhibitor (e.g., mycophenolic acid and thiazole-4-carboxamide adenine dinucleotide) targets the site of the cofactor, NAD + / NADH, which usually leads to low selectivity or even side effects in clinical trials, such as diarrhea and leukopenia (10, 11). Moreover, a third ligand has been speculated to bind to a possible site far from the IMP and NAD + pockets as an allosteric inhibitor. However, an allosteric site for designing selective IMPDH2 inhibitors has been largely unexplored.Natural small molecules remain promising drug sources (12, 13). In the present study, we report that a natural small-molecule probe, sappanone A (SA, Fig.1A), demonstrated significant inhibitory effects on neuroinflammation by directly targetin...

LSCF and 3DOM-LSCF catalysts can significantly improve the catalytic performance and 100% selectivity for the reduction of CO2 with H2O vapor to CH4 under thermal and photo-thermal reaction conditions.