Characterization of mixed lymphocyte reaction blocking antibodies (MLR-Bf) in human pregnancy

BACKGROUND: It is known that during normal pregnancy and after immunotherapy blocking antibodies are developed, these antibodies inhibit mixed lymphocyte reaction and are also anti-mitogenic in nature. Mixed lymphocyte reaction blocking antibodies are specific to the husband's lymphocytes. In the present study an attempt has been made to characterize the mixed lymphocyte reaction blocking antibodies in normal pregnancy and in women with recurrent spontaneous abortion after immunotherapy. METHODS: Serum was obtained from women of different gestational windows of pregnancy (Ist, IInd, IIIrd trimesters and post delivery period of normal pregnancy), recurrent spontaneous aborters from pre and post immunization. Healthy (male and females) controls were screened for the presence of mixed lymphocyte reaction blocking antibodies. The standard mixed lymphocyte reaction technique was used to evaluate the inhibitory effect of serum in the mixed lymphocyte reaction. Each serum was tested for cytotoxic antibodies. Immunoglobulin G and its isotypes were isolated according to the standard protocol. RESULTS: In the present study we have observed that there was significant inhibition of proliferation response when immunoglobulin G from different trimesters of pregnancy were added to one way mixed lymphocyte reaction or to phytohemagglutinin activated lymphocyte proliferation assay. Similar pattern was seen when immunoglobulin G isolated from adequately immunized women with recurrent spontaneous abortion was used. It was further confirmed that amongst all the isotypes of immunoglobulin G, only immunoglobulin G-3 was found to be positive for the inhibitory effect. CONCLUSIONS: Present study indicates that mixed lymphocyte reaction blocking antibodies are immunoglobulin G-3 in nature. It is developed during pregnancy and also after immunotherapy in women with recurrent spontaneous abortion who subsequently have the successful pregnancy

Genome variations: Effects on the robustness of neuroevolved control for swarm robotics systems

Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and bene t swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.info:eu-repo/semantics/acceptedVersio

Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults

Rolling bearings are the core components of rotating machinery, and their normal operation is crucial to entire industrial applications. Most existing condition monitoring methods have been devoted to extracting discriminative features from vibration signals that reflect bearing health status. However, the complex working conditions of rolling bearings often make the fault-related information easily buried in noise and other interference. Therefore, it is challenging for existing approaches to extract sufficient critical features in these scenarios. To address this issue, this paper proposes a novel CNN-Transformer network, referred to as Dconformer, capable of extracting both local and global discriminative features from noisy vibration signals. The main contributions of this research include: (1) Developing a novel joint-learning strategy that simultaneously enhances the performance of signal denoising and fault diagnosis, leading to robust and accurate diagnostic results; (2) Constructing a novel CNN-transformer network with a multi-branch cross-cascaded architecture, which inherits the strengths of CNNs and transformers and demonstrates superior anti-interference capability. Extensive experimental results reveal that the proposed Dconformer outperforms five state-of-the-art approaches, particularly in strong noisy scenarios

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: [email protected] 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented

Type Ia Supernova Explosion Models

Because calibrated light curves of Type Ia supernovae have become a major tool to determine the local expansion rate of the Universe and also its geometrical structure, considerable attention has been given to models of these events over the past couple of years. There are good reasons to believe that perhaps most Type Ia supernovae are the explosions of white dwarfs that have approached the Chandrasekhar mass, M_ch ~ 1.39 M_sun, and are disrupted by thermonuclear fusion of carbon and oxygen. However, the mechanism whereby such accreting carbon-oxygen white dwarfs explode continues to be uncertain. Recent progress in modeling Type Ia supernovae as well as several of the still open questions are addressed in this review. Although the main emphasis will be on studies of the explosion mechanism itself and on the related physical processes, including the physics of turbulent nuclear combustion in degenerate stars, we also discuss observational constraints.Comment: 38 pages, 4 figures, Annual Review of Astronomy and Astrophysics, in pres

Sequence-based prediction for vaccine strain selection and identification of antigenic variability in foot-and-mouth disease virus

Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence - by controlling for phylogenetic structure - for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization uses pre-existing datasets, this approach quickly and cheaply increases both our understanding of antigenic relationships and our power to control disease

Adjuvant and neoadjuvant therapy for gastric cancer using epirubicin/cisplatin/5-fluorouracil (ECF) and alternative regimens before and after chemoradiation

Chemoradiation is now used more commonly for gastric cancer following publication of the US Intergroup trial results that demonstrate an advantage to adjuvant postoperative chemoradiotherapy. However, there remain concerns regarding the toxicity of this treatment, the optimal chemotherapy regimen and the optimal method of radiotherapy delivery. In this prospective study, we evaluated the toxicity and feasibility of an alternative chemoradiation regimen to that used in the Intergroup trial. A total of 26 patients with adenocarcinoma of the stomach were treated with 3D-conformal radiation therapy to a dose of 45 Gy in 25 fractions with concurrent continuous infusional 5-fluorouracil (5-FU). The majority of patients received epirubicin, cisplatin and 5-FU (ECF) as the systemic component given before and after concurrent chemoradiation. The overall rates of observed grade 3 and 4 toxicities were 38 and 15%, respectively. GIT grade 3 toxicity was observed in 19% of patients, while haematologic grade 3 and 4 toxicities were observed in 23%. Our results suggest that this adjuvant regimen can be delivered safely and with acceptable toxicity. This regimen forms the basis of several new studies being developed for postoperative adjuvant therapy of gastric cancer

Hydraulic & Design Parameters in Full-Scale Constructed Wetland & Treatment Units: Six Case Studies

The efficiency of pond and constructed wetland (CW) treatment systems, is influenced by the internal hydrodynamics and mixing interactions between water and aquatic vegetation. In order to contribute to current knowledge of how emergent real vegetation affects solute mixing, and on what the shape and size effects are on the mixing characteristics, an understanding and quantification of those physical processes and interactions was evaluated. This paper presents results from tracer tests conducted during 2015-2016 in six full-scale systems in the UK under different flow regimes, operational depths, shapes and sizes, and in-/outlet configurations. The aim is to quantify the hydraulic performance and mixing characteristics of the treatment units, and to investigate the effect of size and shape on the mixing processes. Relative comparison of outlet configuration, inflow conditions, and internal features between the six different treatment units showed variations in residence times of up to a factor of 3. A key outcome of this study, demonstrated that the width is a more important dimension for the efficiency of the unit compared to the depth. Results underlined the importance of investigating hydrodynamics and physics of flow in full-size units to enhance treatment efficiency and predictions of water quality models