A general method for the selection of high-level scFv and IgG antibody expression by stably transfected mammalian cells

The isolation of mammalian cell lines capable of high-yield expression of recombinant antibodies is typically performed by screening multiple individual clones by limiting dilution techniques. A number of experimental strategies have recently been devised to identify high-expressing clones, but protocols are often difficult to implement, time consuming, costly and limited in terms of number of clones which can be screened. In this article, we describe new vectors for the expression of recombinant antibodies in IgG format and in other formats, based on the single-chain Fv module, as well as a high-throughput screening procedure, based on the direct staining of antibodies transiting the membrane of a stably transfected cell, followed by preparative sorting using a high-speed cell sorter. This procedure allows, in one step, to deposit single cells into individual wells of a 96-well microtiter plate (thus facilitating cloning) and to preferentially recover those rare cell populations which express dramatically higher levels of recombinant antibody. Using cell cultures followed by affinity purification techniques, we could confirm that the new vectors and the new screening procedure reliably yield high-expression clones and homogenous protein preparations. We expect that these techniques should find broad applicability for both academic and industrial antibody engineering researc

Development of a mechatronic sorting system for removing contaminants from wool

Automated visual inspection (AVI) systems have been extended to many fields, such as agriculture and the food, plastic and textile industries. Generally, most visual systems only inspect product defects, and then analyze and grade them due to the lack of any sorting function. This main reason rests with the difficulty of using the image data in real time. However, it is increasingly important to either sort good products from bad or grade products into separate groups usingAVI systems. This article describes the development of a mechatronic sorting system and its integration with a vision system for automatically removing contaminants from wool in real time. The integration is implemented by a personal computer, which continuously processes live images under the Windows 2000 operating system. The developed real-time sorting approach is also applicable to many other AVI systems

Improved neighbor list algorithm in molecular simulations using cell decomposition and data sorting method

An improved neighbor list algorithm is proposed to reduce unnecessary interatomic distance calculations in molecular simulations. It combines the advantages of Verlet table and cell linked list algorithms by using cell decomposition approach to accelerate the neighbor list construction speed, and data sorting method to lower the CPU data cache miss rate, as well as partial updating method to minimize the unnecessary reconstruction of the neighbor list. Both serial and parallel performance of molecular dynamics simulation are evaluated using the proposed algorithm and compared with those using conventional Verlet table and cell linked list algorithms. Results show that the new algorithm outperforms the conventional algorithms by a factor of 2~3 in cases of both small and large number of atoms.Comment: 14 pages, 7 figures. Submitted to Computer Physics Communication

Fine-sorting One-dimensional Particle-In-Cell Algorithm with Monte-Carlo Collisions on a Graphics Processing Unit

Particle-in-cell (PIC) simulations with Monte-Carlo collisions are used in plasma science to explore a variety of kinetic effects. One major problem is the long run-time of such simulations. Even on modern computer systems, PIC codes take a considerable amount of time for convergence. Most of the computations can be massively parallelized, since particles behave independently of each other within one time step. Current graphics processing units (GPUs) offer an attractive means for execution of the parallelized code. In this contribution we show a one-dimensional PIC code running on Nvidia GPUs using the CUDA environment. A distinctive feature of the code is that size of the cells that the code uses to sort the particles with respect to their coordinates is comparable to size of the grid cells used for discretization of the electric field. Hence, we call the corresponding algorithm "fine-sorting". Implementation details and optimization of the code are discussed and the speed-up compared to classical CPU approaches is computed

Even faster sorting of (not only) integers

In this paper we introduce RADULS2, the fastest parallel sorter based on radix algorithm. It is optimized to process huge amounts of data making use of modern multicore CPUs. The main novelties include: extremely optimized algorithm for handling tiny arrays (up to about a hundred of records) that could appear even billions times as subproblems to handle and improved processing of larger subarrays with better use of non-temporal memory stores

Whole-blood sorting, enrichment and in situ immunolabeling of cellular subsets using acoustic microstreaming

Analyzing undiluted whole human blood is a challenge due to its complex composition of hematopoietic cellular populations, nucleic acids, metabolites, and proteins. We present a novel multi-functional microfluidic acoustic streaming platform that enables sorting, enrichment and in situ identification of cellular subsets from whole blood. This single device platform, based on lateral cavity acoustic transducers (LCAT), enables (1) the sorting of undiluted donor whole blood into its cellular subsets (platelets, RBCs, and WBCs), (2) the enrichment and retrieval of breast cancer cells (MCF-7) spiked in donor whole blood at rare cell relevant concentrations (10 mL− 1), and (3) on-chip immunofluorescent labeling for the detection of specific target cellular populations by their known marker expression patterns. Our approach thus demonstrates a compact system that integrates upstream sample processing with downstream separation/enrichment, to carry out multi-parametric cell analysis for blood-based diagnosis and liquid biopsy blood sampling

A fast GPU Monte Carlo Radiative Heat Transfer Implementation for Coupling with Direct Numerical Simulation

We implemented a fast Reciprocal Monte Carlo algorithm, to accurately solve radiative heat transfer in turbulent flows of non-grey participating media that can be coupled to fully resolved turbulent flows, namely to Direct Numerical Simulation (DNS). The spectrally varying absorption coefficient is treated in a narrow-band fashion with a correlated-k distribution. The implementation is verified with analytical solutions and validated with results from literature and line-by-line Monte Carlo computations. The method is implemented on GPU with a thorough attention to memory transfer and computational efficiency. The bottlenecks that dominate the computational expenses are addressed and several techniques are proposed to optimize the GPU execution. By implementing the proposed algorithmic accelerations, a speed-up of up to 3 orders of magnitude can be achieved, while maintaining the same accuracy