Tailored Lattice Compressive Strain of Pt-Skins by the L12 -Pt3 M Intermetallic Core for Highly Efficient Oxygen Reduction.

The sluggish kinetics of oxygen reduction reaction (ORR) and unsatisfactory durability of Pt-based catalysts are severely hindering the commercialization of proton-exchange-membrane fuel cells (PEMFCs). In this work, the lattice compressive strain of Pt-skins imposed by Pt-based intermetallic cores is tailored for highly effective ORR through the confinement effect of the activated nitrogen-doped porous carbon (a-NPC). The modulated pores of a-NPC not only promote Pt-based intermetallics with ultrasmall size (average size of <4 nm), but also efficiently stabilizes intermetallic nanoparticles and sufficient exposure of active sites during the ORR process. The optimized catalyst (L12 -Pt3 Co@ML-Pt/NPC10 ) achieves excellent mass activity (1.72 A mgPt -1 ) and specific activity (3.49 mA cmPt -2 ), which are 11- and 15-fold that of commercial Pt/C, respectively. Besides, owing to the confinement effect of a-NPC and protection of Pt-skins, L12 -Pt3 Co@ML-Pt/NPC10 retains 98.1% mass activity after 30 000 cycles, and even 95% for 100 000 cycles, while Pt/C retains only 51.2% for 30 000 cycles. Rationalized by density functional theory, compared with other metals (Cr, Mn, Fe, and Zn), L12 -Pt3 Co closer to the top of "volcano" induces a more suitable compressive strain and electronic structure on Pt-skin, leading to an optimal oxygen adsorption energy and a remarkable ORR performance.

Insights into the microstructure and interconnectivity of porosity in porous starch by hyperpolarized 129Xe NMR.

For the first time, hyperpolarized (HP) 129Xe NMR measurements are utilized to explore porous structures of porous starch (PS) successfully. Some micropores resided inside the mesopore walls of PS were detected by variable temperature (VT) HP 129Xe NMR, and the pore sizes of micropores were also estimated using the empirical relationship. Furthermore, the interconnectivity of pores was investigated in detail by two-dimensional (2D) exchange spectroscopy (EXSY). The exchange process of xenon from microporosity within pore walls to the free gas space was occurred at the mixing time of ≥12 ms at 173 K, which indicated the well interconnectivity between micropores and mesopores. This study not only exhibits a new approach for investigation of pores and hollows of PS, but also provides a better understanding of porous structures for rational design in adsorbing functional compounds.

129Xe NMR: A powerful tool for studying the adsorption mechanism between mesoporous corn starch and palladium.

For the first time, 129Xe NMR measurements are utilized to explore adsorption mechanism between porous structures of mesoporous corn starch and Palladium. Dithiocarbamate modified mesoporous corn starch (donated as DTC MS) was synthesized and applied for adsorption of Pd (II) ion successfully. The structural characterization of DTC MS was carried out by FT-IR, 13C solid-state NMR and XRD, respectively. To study the adsorption mechanism, variable temperature 129Xe NMR was measured on samples of DTC MS and Pd adsorbed in DTC mesoporous starch (donated as Pd-DTC MS), respectively. It was found that Pd ions were mainly located inside pores and channels instead of the surface of mesoporous starch. The results not only demonstrate that 129Xe NMR spectroscopy is a powerful tool to assess the porous structure of MS, but also pave the way for investigating the interaction between functional molecules and porous starch.

Construction of octenyl succinic anhydride modified porous starch for improving bioaccessibility of ß-carotene in emulsions.

Modified porous starch (PS), by introducing octenyl succinic anhydride (OSA) moieties, was synthesized successfully, which was applied as an emulsion of ß-carotene for the first time. The pores and channels within porous starch provided more possibilities for OSA to modify starch. The ester linkage of OSA modified PS with different degrees of substitution (DS) were confirmed by both 13C solid-state NMR and Fourier transform-infrared spectroscopy (FT-IR). The hydrophobic octenyl succinic and hydrophilic hydroxyl groups of OSA modified PS showed the good emulsifying capability, which could be utilized to prepare ß-carotene emulsions. And the bioaccessibility of ß-carotene was also enhanced with increasing DS of OSA modified starch. This study not only paves a new way using porous starches for modification of starch, but also offers an attractive alternative for obtaining emulsion-based delivery systems for bioactive components.

Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference.

Cancer is mainly caused by somatic genome alterations (SGAs). Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. We developed a novel tumor-specific computational framework that finds the likely causative SGAs in an individual tumor and estimates their impact on oncogenic processes, which suggests the disease mechanisms that are acting in that tumor. This information can be used to guide precision oncology. We report a tumor-specific causal inference (TCI) framework, which estimates causative SGAs by modeling causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and estimated for each tumor the SGAs that causally regulate the differentially expressed genes (DEGs) in that tumor. Overall, TCI identified 634 SGAs that are predicted to cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both the well-known and the novel candidate drivers that are predicted by TCI. TCI provides a unified framework that integrates multiple types of SGAs and molecular phenotypes to estimate which genome perturbations are causally influencing one or more molecular/cellular phenotypes in an individual tumor. By identifying major candidate drivers and revealing their functional impact in an individual tumor, TCI sheds light on the disease mechanisms of that tumor, which can serve to advance our basic knowledge of cancer biology and to support precision oncology that provides tailored treatment of individual tumors.