Humanized CD30-Targeted Chimeric Antigen Receptor T Cells Exhibit Potent Preclinical Activity Against Hodgkin’s Lymphoma Cells

CD30-directed chimeric antigen receptors (CARs) with single chain antibody fragment (scFv)-binding domains from murine HRS3 show strong cytotoxicity to Hodgkin’s Lymphoma cells and have been used in clinical trials. However, murine scFv in CAR might induce specific rejective immune responses in patients, which compromises the therapeutic effects. The use of human or humanized antibody fragments for CAR construction, rather than those derived from mouse antibodies, can reduce the immunogenicity of the CAR. Importantly, this strategy might simultaneously decrease the risk of cytokine-mediated toxicities and improve CAR T cell persistence. Murine HRS3 antibody has been successfully humanized by grafting the complementarity-determining regions (CDRs) from the mouse antibody framework onto human immunoglobulin consensus sequences, followed by an in vitro evolutionary strategy to select functional Fab fragments with the same affinity as murine sources. In this study, humanized scFvs were utilized to construct a CD30-directed CAR (hHRS3-CAR), and its effectiveness was compared with that of HRS3-CAR. The hHRS3-CAR-T cells specifically kill CD30-positive tumor cell lines in vitro and eliminate lymphoma xenografts in immunodeficient mice with comparable efficiency to HRS3-CAR. The hHRS-CAR-T could be used in clinical trials based on the previously reported advantages of humanized CARs, such as the reduction of immune rejection and better persistence of cells.

An Evolutionary Frog Leaping Algorithm for Global Optimization Problems and Applications

Shuffled frog leaping algorithm, a novel heuristic method, is inspired by the foraging behavior of the frog population, which has been designed by the shuffled process and the PSO framework. To increase the convergence speed and effectiveness, the currently improved versions are focused on the local search ability in PSO framework, which limited the development of SFLA. Therefore, we first propose a new scheme based on evolutionary strategy, which is accomplished by quantum evolution and eigenvector evolution. In this scheme, the frog leaping rule based on quantum evolution is achieved by two potential wells with the historical information for the local search, and eigenvector evolution is achieved by the eigenvector evolutionary operator for the global search. To test the performance of the proposed approach, the basic benchmark suites, CEC2013 and CEC2014, and a parameter optimization problem of SVM are used to compare 15 well-known algorithms. Experimental results demonstrate that the performance of the proposed algorithm is better than that of the other heuristic algorithms.

Heat Exchanger Network Optimization Based on the Participatory Evolution Strategy for Streams

The non-structural model of a heat exchanger network randomly selects a position of a node on hot and cold streams to generate a heat exchanger and an existing heat exchanger to participate in the evolution. Despite the model being more random and flexible, this selection method cannot easily find a good solution. In addition, the heat exchangers participating in the evolution might not be involved in all streams in each evolutionary process. A stream that does not participate in the evolution will have no significance to the current iteration. Therefore, many iterations are required to make each stream participate in the evolution, which limits the evolution efficiency of the optimization algorithm. In view of this shortcoming, this study proposes a participatory evolutionary strategy for streams based on hot streams. The proposed strategy reorders the existing heat exchangers on hot and cold streams and takes the corresponding measures to ensure that a heat exchanger is selected for each stream to participate in the evolution in every cycle. The proposed participatory evolutionary strategy for streams improves the global optimal solution for designs based on non-structural models. The effectiveness of the proposed strategy is demonstrated in two cases.

An extended artificial bee colony with local search for solving the Skyline-based web services composition under interval QoS properties

In this paper, we introduce an extended version of artificial bee colony with a local search method (EABC) for solving the QoS uncertainty-aware web service composition (IQSC) problem, where the ambiguity of the QoS properties are represented using the interval-number model. At first, we formulate the addressed problem as an interval constrained single-objective optimization model. Then, we use the skyline operator to prune the redundant and dominated web services from their sets of functionally equivalent ones. Whereas, EABC is employed to solve the IQSC problem in a reduced search space more effectively and more efficiently. For the purpose of validation of the performance and the efficiency of the proposed approach, we present the experimental comparisons to an existing skyline-based PSO, an efficient discrete gbest-guided artificial bee colony and a recently provided Harris Hawks optimization with an elite evolutionary strategy algorithms on an interval extended version of the public QWS dataset.

Application of Improved Differential Evolution Algorithm in Solving Equations

The problem of finding roots of equations has always been an important research problem in the fields of scientific and engineering calculations. For the standard differential evolution algorithm cannot balance the convergence speed and the accuracy of the solution, an improved differential evolution algorithm is proposed. First, the one-half rule is introduced in the mutation process, that is, half of the individuals perform differential evolutionary mutation, and the other half perform evolutionary strategy reorganization, which increases the diversity of the population and avoids premature convergence of the algorithm; Second, set up an adaptive mutation operator and a crossover operator to prevent the algorithm from falling into the local optimum and improve the accuracy of the solution. Finally, classical high-order algebraic equations and nonlinear equations are selected for testing, and compared with other algorithms. The results show that the improved algorithm has higher solution accuracy and robustness, and has a faster convergence speed. It has outstanding effects in finding roots of equations, and provides an effective method for engineering and scientific calculations.

Harmful behaviour through plasmid transfer: a successful evolutionary strategy of bacteria harbouring conjugative plasmids

Conjugative plasmids are extrachromosomal mobile genetic elements pervasive among bacteria. Plasmids' acquisition often lowers cells' growth rate, so their ubiquity has been a matter of debate. Chromosomes occasionally mutate, rendering plasmids cost-free. However, these compensatory mutations typically take hundreds of generations to appear after plasmid arrival. By then, it could be too late to compete with fast-growing plasmid-free cells successfully. Moreover, arriving plasmids would have to wait hundreds of generations for compensatory mutations to appear in the chromosome of their new host. We hypothesize that plasmid-donor cells may use the plasmid as a ‘weapon’ to compete with plasmid-free cells, particularly in structured environments. Cells already adapted to plasmids may increase their inclusive fitness through plasmid transfer to impose a cost to nearby plasmid-free cells and increase the replication opportunities of nearby relatives. A mathematical model suggests conditions under which the proposed hypothesis works, and computer simulations tested the long-term plasmid maintenance. Our hypothesis explains the maintenance of conjugative plasmids not coding for beneficial genes. This article is part of the theme issue ‘The secret lives of microbial mobile genetic elements’.

A Bayesian Neural Network-Based Method to Calibrate Microscopic Traffic Simulators

Calibrating the microsimulation model is essential to enhance its ability to capture reality. The paper proposes a Bayesian neural network (BNN)-based method to calibrate parameters of microscopic traffic simulators, which reduces repeated running of simulations in the calibration and thus significantly improves the calibration efficiency. We use BNN with probability distributions on the weights to quickly predict the simulation results according to the inputs of the parameters to be calibrated. Based on the BNN model with the best performance, heuristic algorithms (HAs) are performed to seek the optimal values of the parameters to be calibrated with the minimum difference between the predicted results of BNN and the field-measured values. Three HAs are considered, including genetic algorithm (GA), evolutionary strategy (ES), and bat algorithm (BA). A TransModeler case of highway links in Shanghai, China, indicates the validity of the proposed calibration method in terms of error and efficiency. The results demonstrate that the BNN model is able to accurately predict the simulation and adequately capture the uncertainty of the simulation. We also find that the BNN-BA model produces the best calibration efficiency, while the BNN-ES model offers the best performance in calibration accuracy.

A Study of the Coevolution of Digital Organisms with an Evolutionary Cellular Automaton

This paper presents an Evolutionary Cellular Automaton (ECA) that simulates the evolutionary dynamics of biological interactions by manipulating strategies of dispersion and associations between digital organisms. The parameterization of the different types of interaction and distribution strategies using configuration files generates easily interpretable results. In that respect, ECA is an effective instrument for measuring the effects of relative adaptive advantages and a good resource for studying natural selection. Although ECA works effectively in obtaining the expected results from most well-known biological interactions, some unexpected effects were observed. For example, organisms uniformly distributed in fragmented habitats do not favor eusociality, and mutualism evolved from parasitism simply by varying phenotypic flexibility. Finally, we have verified that natural selection represents a cost for the emergence of sex by destabilizing the stable evolutionary strategy of the 1:1 sex ratio after generating randomly different distributions in each generation.

Exceptionally simple, rapidly replaced teeth in sauropod dinosaurs demonstrate a novel evolutionary strategy for herbivory in Late Jurassic ecosystems

Background Dinosaurs dominated terrestrial environments for over 100 million years due in part to innovative feeding strategies. Although a range of dental adaptations was present in Late Jurassic dinosaurs, it is unclear whether dinosaur ecosystems exhibited patterns of tooth disparity and dietary correlation similar to those of modern amniotes, in which carnivores possess simple teeth and herbivores exhibit complex dentitions. To investigate these patterns, we quantified dental shape in Late Jurassic dinosaurs to test relationships between diet and dental complexity. Results Here, we show that Late Jurassic dinosaurs exhibited a disparity of dental complexities on par with those of modern saurians. Theropods possess relatively simple teeth, in spite of the range of morphologies tested, and is consistent with their inferred carnivorous habits. Ornithischians, in contrast, have complex dentitions, corresponding to herbivorous habits. The dentitions of macronarian sauropods are similar to some ornithischians and living herbivorous squamates but slightly more complex than other sauropods. In particular, all diplodocoid sauropods investigated possess remarkably simple teeth. The existence of simple teeth in diplodocoids, however, contrasts with the pattern observed in nearly all known herbivores (living or extinct). Conclusions Sauropod dinosaurs exhibit a novel approach to herbivory not yet observed in other amniotes. We demonstrate that sauropod tooth complexity is related to tooth replacement rate rather than diet, which contrasts with the results from mammals and saurians. This relationship is unique to the sauropod clade, with ornithischians and theropods displaying the patterns observed in other groups. The decoupling of herbivory and tooth complexity paired with a correlation between complexity and replacement rate demonstrates a novel evolutionary strategy for plant consumption in sauropod dinosaurs.