Combining frequency and time domain approaches to systems with multiple spike train input and output

A frequency domain approach and a time domain approach have been combined in an investigation of the behaviour of the primary and secondary endings of an isolated muscle spindle in response to the activity of two static fusimotor axons when the parent muscle is held at a fixed length and when it is subjected to random length changes. The frequency domain analysis has an associated error process which provides a measure of how well the input processes can be used to predict the output processes and is also used to specify how the interactions between the recorded processes contribute to this error. Without assuming stationarity of the input, the time domain approach uses a sequence of probability models of increasing complexity in which the number of input processes to the model is progressively increased. This feature of the time domain approach was used to identify a preferred direction of interaction between the processes underlying the generation of the activity of the primary and secondary endings. In the presence of fusimotor activity and dynamic length changes imposed on the muscle, it was shown that the activity of the primary and secondary endings carried different information about the effects of the inputs imposed on the muscle spindle. The results presented in this work emphasise that the analysis of the behaviour of complex systems benefits from a combination of frequency and time domain methods

Applying Unique Molecular Identifiers in Next Generation Sequencing Reveals a Constrained Viral Quasispecies Evolution under Cross-Reactive Antibody Pressure Targeting Long Alpha Helix of Hemagglutinin.

To overcome yearly efforts and costs for the production of seasonal influenza vaccines, new approaches for the induction of broadly protective and long-lasting immune responses have been developed in the past decade. To warrant safety and efficacy of the emerging crossreactive vaccine candidates, it is critical to understand the evolution of influenza viruses in response to these new immune pressures. Here we applied unique molecular identifiers in next generation sequencing to analyze the evolution of influenza quasispecies under in vivo antibody pressure targeting the hemagglutinin (HA) long alpha helix (LAH). Our vaccine targeting LAH of hemagglutinin elicited significant seroconversion and protection against homologous and heterologous influenza virus strains in mice. The vaccine not only significantly reduced lung viral titers, but also induced a well-known bottleneck effect by decreasing virus diversity. In contrast to the classical bottleneck effect, here we showed a significant increase in the frequency of viruses with amino acid sequences identical to that of vaccine targeting LAH domain. No escape mutant emerged after vaccination. These results not only support the potential of a universal influenza vaccine targeting the conserved LAH domains, but also clearly demonstrate that the well-established bottleneck effect on viral quasispecies evolution does not necessarily generate escape mutants

Simplifying transformations for nonlinear systems: Part I, an optimisation-based variant of normal form analysis

This paper introduces the idea of a ‘simplifying transformation’ for nonlinear structural dynamic systems. The idea simply stated; is to bring under one heading, those transformations which ‘simplify’ structural dynamic systems or responses in some sense. The equations of motion may be cast in a simpler form or decoupled (and in this sense, nonlinear modal analysis is encompassed) or the responses may be modified in order to isolate and remove certain components. It is the latter sense of simplification which is considered in this paper. One can regard normal form analysis in a way as the removal of superharmonic content from nonlinear system response. In the current paper, this problem is cast in an optimisation form and the differential evolution algorithm is used

Phenotypic and functional analysis of lymphocytes infiltrating osteolytic tumors: use as a possible therapeutic approach of osteosarcoma

BACKGROUND: Osteosarcoma is the most common type of primary bone tumor. The use of aggressive chemotherapy has drastically improved the prognosis of the patients with non-metastatic osteosarcomas, however the prognosis of the patients with metastasis is still very poor. Then, new and more effective treatments for curing osteosarcoma, such as immunotherapy are needed. Tumor-infiltrating lymphocytes (TIL) have been involved in the control of tumor development and already assessed with success for the treatment of several cancers including melanoma. While TIL represent a fascinating therapeutic approach in numerous malignant pathologies, there is few report concerning adult bone-associated tumors including osteosarcoma. METHODS: Human TIL were isolated and characterized (phenotype, lytic activity) from twenty-seven patients with bone-associated tumors (osteosarcoma, Ewing's sarcoma, giant cell tumor, chondrosarcoma, plasmocytoma and bone metastases). Similar experiments were performed using rat osteosarcoma model. RESULTS: While TIL with a main CD4(+ )profile were easily isolated from most of the tumor samples, only TIL extracted from osteosarcoma were cytotoxic against allogeneic tumor cells. In all cases, TIL lytic activity was significantly higher compared to autologous peripheral blood leukocytes. Similar data were observed in rat osteosarcoma model where TIL were characterized by a main CD4(+ )profile and high lytic activity against allogeneic and autologous tumor cells. Moreover, rat TIL expansion was not accompanied by refractoriness to further activation stimulus mainly by tumor antigens. CONCLUSION: These results demonstrated that TIL therapy could be a very efficient strategy for the treatment of adult osteosarcoma

Stigma of living as an autism carer: a brief psycho-social support intervention (SOLACE). Study protocol for a randomised controlled feasibility study.

Stigma is prominent in the lives of autistic individuals and their families and contributes significantly to the challenges faced by families raising an autistic child. Parents and carers can feel blamed for their child's behaviour, feel socially excluded and isolated and suffer from low self-esteem and poor psychological well-being. This increases the risk of experiencing self-stigma which further exacerbates these and other negative consequences. Therefore, there is a need for interventions that help parents/family carers cope with autism-related stigma as well as prevent the internalisation of stigma. The primary objective of this study is to assess the feasibility and acceptability of a stigma support intervention for parents and carers of autistic children titled 'Stigma of Living as an Autism Carer (SOLACE)'. The secondary objective is to explore the preliminary impact of the intervention on the mental health of the parents and carers. tests for differences within the group. Other outcomes of interest are stigma, self-stigma, self-esteem, self-blame, social isolation, self-compassion and perceived responsibility and control. Results from the feasibility randomised controlled trial will be used to refine the study protocol and inform the design of an intervention for future use in a larger, powered trial. SOLACE could potentially improve the psychological well-being of parents/family carers of autistic children through increased resistance to stigma. ISRCTN Registry number ISRCTN61093625 (October 13, 2017)

Properties of healthcare teaming networks as a function of network construction algorithms

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: The Center for Medicare Services Outpatient Claims DE-SynPUF (DE-SynPUF)\cite{RN120} test set is publicly available from the CMS web site. The full 2013 Medicare Part B Limited Data Set for Medicare claims can be obtained from the Center for Medicare Services. This data is bound by a privacy and limited distribution agreement, as well as HIPAA regulations, and thus cannot be made public with this manuscript. However, the files can be requested from the Center for Medicare Services by individual investigators and used to reproduce our findings. Release of the derived networks is also limited by Medicare requirements to remove nodes and edges where the total number of shared patients 11 shared patients, and these are available on figshare.com as referenced in the Supplemental Data section of the manuscript.Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106±108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: Binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.National Institute of HealthPhilip Templeton FoundationUniversity of Rochester Center for Health Informatic

Update on HER-2 as a target for cancer therapy: HER2/neu peptides as tumour vaccines for T cell recognition

During the past decade there has been renewed interest in the use of vaccine immunotherapy for the treatment of cancer. This review focuses on HER2/neu, a tumour-associated antigen that is overexpressed in 10–40% of breast cancers and other carcinomata. Several immunogenic HER2/neu peptides recognized by T lymphocytes have been identified to be included in cancer vaccines. Some of these peptides have been assessed in clinical trials of patients with breast and ovarian cancer. Although it has been possible to detect immunological responses against the peptides in the immunized patients, no clinical responses have so far been described. Immunological tolerance to self-antigens like HER2/neu may limit the functional immune responses against them. It will be of interest to determine whether immune responses against HER2/neu epitopes can be of relevance to cancer treatment