No abstract

The successful use of electrochemiluminescence (ECL) in immunoassay for clinical diagnosis requires development of novel ECL signal probes. Herein, we report lanthanide (Ln) metal−organic frameworks (LMOFs) as ECL signal emitters in the ECL immunoassay. The LMOFs were prepared from precursors containing Eu (III) ions and 5-boronoisophthalic acid (5-bop), which could be utilized to adjust optical properties. Investigations of ECL emission mechanisms revealed that 5-bop was excited with ultraviolet photons to generate a triplet-state, which then triggered Eu (III) ions for red emission. The electron-deficient boric acid decreased the energy-transfer efficiency from the triplet-state of 5-bop to Eu (III) ions; consequently, both were excited with highefficiency at single excitation. In addition, by progressively tailoring the atomic ratios of Ni/Fe, NiFe composites (Ni/Fe 1:1) were synthesized with more available active sites, enhanced stability, and excellent conductivity. As a result, the self-luminescent europium LMOFs displayed excellent performance characteristics in an ECL immunoassay with a minimum detectable limit of 0.126 pg mL −1 , using Cytokeratins21-1 (cyfra21-1) as the target detection model. The probability of false positive/false negative was reduced dramatically by using LMOFs as signal probes. This proposed strategy provides more possibilities for the application of lanthanide metals in analytical chemistry, especially in the detection of other disease markers.

We consider the scheduling problem of minimizing the average weighted completion time of n jobs with release dates on a single machine. We first study two linear programming relaxations of the problem, one based on a time-indexed formulation, the other on a completiontime formulation. We show their equivalence by proving that a O(n log n) greedy algorithm leads to optimal solutions to both relaxations. The proof relies on the notion of mean busy times of jobs, a concept which enhances our understanding of these LP relaxations. Based on the greedy solution, we describe two simple randomized approximation algorithms, which are guaranteed to deliver feasible schedules with expected objective value within factors of 1.7451 and 1.6853, respectively, of the optimum. They are based on the concept of common and independent a-points, respectively. The analysis implies in particular that the worst-case relative error of the LP relaxations is at most 1.6853, and we provide instances showing that it is at least e/(e-1) 1.5819. Both algorithms may be derandomized, their deterministic versions running in O(n 2) time. The randomized algorithms also apply to the on-line setting, in which jobs arrive dynamically over time and one must decide which job to process without knowledge of jobs that will be released afterwards.

A DNA-programmed membrane fusion strategy for directing intracellular delivery of proteins into live cells.