Nickel(II)-Mediated Reversible Thiolate/Disulfide Conversion as a Mimic for a Key Step of the Catalytic Cycle of Methyl-Coenzyme M Reductase

According to the well-accepted mechanism, methyl-coenzyme M reductase (MCR) involves Ni-mediated thiolate-to-disulfide conversion that sustains its catalytic cycle of methane formation in the energy saving pathways of methanotrophic microbes. Model complexes that illustrate Ni-ion mediated reversible thiolate/disulfide transformation are unknown. In this paper we report the synthesis, crystal structure, spectroscopic properties and redox interconversions of a set of Ni^II complexes comprising a tridentate N₂S donor thiol and its analogous N₄S₂ donor disulfide ligands. These complexes demonstrate reversible Ni^II-thiolate/Ni^II-disulfide (both bound and unbound disulfide-S to Ni^II) transformations via thiyl and disulfide monoradical anions that resemble a primary step of MCR's catalytic cycle.     

A Memristive Element Based on an Electrically Controlled Single-Molecule Reaction

The exponential proliferation of data during the information age has required the continuous exploration of novel storage paradigms, materials, and devices with increasing data density. As a step toward the ultimate limits in data density, the development of an electrically controllable single-molecule memristive element is reported. In this device, digital information is encoded through switching between two isomer states by applying a voltage signal to the molecular junction, and the information is read out by monitoring the electrical conductance of each isomer. The two states are cycled using an electrically controllable local-heating mechanism for the forward reaction and catalyzed by a single charge-transfer process for the reverse switching. This single-molecule device can be modulated in situ, is fully reversible, and does not display stochastic switching. The I–V curves of this single-molecule system also exhibit memristive character. These features suggest a new approach for the development of molecular switching systems and storage-class memories.     

Exploiting the Potential of Meroterpenoid Cyclases to Expand the Chemical Space of Fungal Meroterpenoids

Fungal meroterpenoids are a diverse group of hybrid natural products with impressive structural complexity and high potential as drug candidates. In this work, we evaluate the promiscuity of the early structure diversity-generating step in fungal meroterpenoid biosynthetic pathways: the multibond-forming polyene cyclizations catalyzed by the yet poorly understood family of fungal meroterpenoid cyclases. In total, 12 unnatural meroterpenoids were accessed chemoenzymatically using synthetic substrates. Their complex structures were determined by 2D NMR studies as well as crystalline-sponge-based X-ray diffraction analyses. The results obtained revealed a high degree of enzyme promiscuity and experimental results which together with quantum chemical calculations provided a deeper insight into the catalytic activity of this new family of non-canonical, terpene cyclases. The knowledge obtained paves the way to design and engineer artificial pathways towards second generation meroterpenoids with valuable bioactivities based on combinatorial biosynthetic strategies.     

Rapid assessment of drug response in cancer cells using microwell array and molecular imaging

Selection of personalized chemotherapy regimen for individual patients has significant potential to improve chemotherapy efficacy and to reduce the deleterious effects of ineffective chemotherapy drugs. In this study, a rapid and high-throughput in vitro drug response assay was developed using a combination of microwell array and molecular imaging. The microwell array provided high-throughput analysis of drug response, which was quantified based on the reduction in intracellular uptake (2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-d-glucose) (2-NBDG). Using this synergistic approach, the drug response measurement was completed within 4 h, and only a couple thousand cells were needed for quantification. The broader application of this microwell molecular imaging approach was demonstrated by evaluating the drug response of two cancer cell lines, cervical (HeLa) and bladder (5637) cancer cells, to two distinct classes of chemotherapy drugs (cisplatin and paclitaxel). This approach did not require an extended cell culturing period, and the quantification of cellular drug response was 4–16 times faster compared with other cell-microarray drug response studies. Moreover, this molecular imaging approach had comparable sensitivity to traditional cell viability assays, i.e., the MTT assay and propidium iodide labeling of cellular nuclei;and similar throughput results as flow cytometry using only 1,000–2,000 cells. Given the simplicity and robustness of this microwell molecular imaging approach, it is anticipated that the assay can be adapted to quantify drug responses in a wide range of cancer cells and drugs and translated to clinical settings for a rapid in vitro drug response using clinically isolated samples.      

Thickness and refractive index of DPPC and DPPE monolayers by multiple-beam interferometry

The thickness and refractive index of 1,2-dipalmitoyl-sn-glycero-3-phosphatidyl choline (DPPC) and 1,2-dipalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE) monolayers Langmuir--Blodgett (LB) deposited on mica were measured in dry air and bulk water using multiple-beam interferometry (MBI). Measurements of thickness using atomic force microscopy (AFM) of identical monolayers, and X-ray reflectivity (XRR) of the monolayers on quartz were taken for comparison. The measurement of the properties of solid-supported monolayers in dry air allows lipid optical properties to be determined free from solvent effects. The thickness and refractive index measured by MBI were 25.5?±?0.6 Å and 1.485?±?0.007 for DPPE monolayers, and 23.9?±?0.5 Å and 1.478?±?0.006 for DPPC monolayers in dry air. These thicknesses are consistent with the other techniques used in this work as well as other measurements in the literature. The refractive indices of solid-supported lipid monolayers have not been previously measured. The values are higher than previous measurements on black lipid films done by reflectometry, which is attributed to increased lipid packing density and the absence of hydrocarbon solvents. Applying water to the monolayers had no measurable effect on their properties, indicating that any change in hydration was below detection.

Screening,Growth Medium Optimisation and Heterotrophic Cultivation of Microalgae for Biodiesel Production

This article presents a study on screening of microalgal strains from the Peking University Algae Collection and heterotrophic cultivation for biodiesel production of a selected microalgal strain. Among 89 strains, only five were capable of growing under heterotrophic conditions in liquid cultures and Chlorella sp. PKUAC 102 was found the best for the production of heterotrophic algal biodiesel. Composition of the growth medium was optimised using response surface methodology and optimised growth conditions were successfully used for cultivation of the strain in a fermentor. Conversion of algal lipids to fatty acid methyl esters (FAMEs) showed that the lipid profile of the heterotrophically cultivated Chlorella sp. PKUAC 102 contains fatty acids suitable for biodiesel production.     

Formulas and Asymptotics for the Asymmetric Simple Exclusion Process

This is an expanded version of a series of lectures delivered by the second author in June, 2009. It describes the results of three of the authors’ papers on the asymmetric simple exclusion process, from the derivation of exact formulas for configuration probabilities, through Fredholm determinant representation, to asymptotics with step initial condition establishing KPZ universality. Although complete proofs are in general not given, at least the main elements of them are.     

Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems

Numerous planning problems can be formulated as multi-stage stochastic programs and many possess key discrete (integer) decision variables in one or more of the stages. Progressive hedging (PH) is a scenario-based decomposition technique that can be leveraged to solve such problems. Originally devised for problems possessing only continuous variables, PH has been successfully applied as a heuristic to solve multi-stage stochastic programs with integer variables. However, a variety of critical issues arise in practice when implementing PH for the discrete case, especially in the context of very difficult or large-scale mixed-integer problems. Failure to address these issues properly results in either non-convergence of the heuristic or unacceptably long run-times. We investigate these issues and describe algorithmic innovations in the context of a broad class of scenario-based resource allocation problem in which decision variables represent resources available at a cost and constraints enforce the need for sufficient combinations of resources. The necessity and efficacy of our techniques is empirically assessed on a two-stage stochastic network flow problem with integer variables in both stages.     

A graph-based multi-sample test for identifying pathways associated with cancer progression

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway being studied, followed by a graph-based multivariate test, which is very easy to implement in practice. The new test is applied to the rich Cancer Genome Atlas data to study the (epi)genetic alterations of 186 KEGG pathways in the development of serous ovarian cancer. To make use of the comprehensive data, we incorporate three data types in the analysis representing gene expression level, copy number and DNA methylation level. Our analysis suggests a list of nine pathways that are closely associated with serous ovarian cancer progression, including cell cycle, ERBB, JAK-STAT signaling and p53 signaling pathways. By pairwise tests, we found that most of the identified pathways contribute only to a particular transition step. For instance, the cell cycle and ERBB pathways play key roles in the early-stage transition, while the ECM receptor and apoptosis pathways contribute to the progression from stage III to stage IV. The proposed computational pipeline is powerful in detecting important pathways and gene sets that drive cancers at certain stage(s). It offers new insights into the understanding of molecular mechanism of cancer initiation and progression.