The use of segmented regression in analysing interrupted time series studies : an example in pre-hospital ambulance care

Peer reviewedPublisher PD

Synthesis and structural characterization of a mimetic membrane-anchored prion protein

During pathogenesis of transmissible spongiform encephalopathies (TSEs) an abnormal form (PrPSc) of the host encoded prion protein (PrPC) accumulates in insoluble fibrils and plaques. The two forms of PrP appear to have identical covalent structures, but differ in secondary and tertiary structure. Both PrPC and PrPSc have glycosylphospatidylinositol (GPI) anchors through which the protein is tethered to cell membranes. Membrane attachment has been suggested to play a role in the conversion of PrPC to PrPSc, but the majority of in vitro studies of the function, structure, folding and stability of PrP use recombinant protein lacking the GPI anchor. In order to study the effects of membranes on the structure of PrP, we synthesized a GPI anchor mimetic (GPIm), which we have covalently coupled to a genetically engineered cysteine residue at the C-terminus of recombinant PrP. The lipid anchor places the protein at the same distance from the membrane as does the naturally occurring GPI anchor. We demonstrate that PrP coupled to GPIm (PrP-GPIm) inserts into model lipid membranes and that structural information can be obtained from this membrane-anchored PrP. We show that the structure of PrP-GPIm reconstituted in phosphatidylcholine and raft membranes resembles that of PrP, without a GPI anchor, in solution. The results provide experimental evidence in support of previous suggestions that NMR structures of soluble, anchor-free forms of PrP represent the structure of cellular, membrane-anchored PrP. The availability of a lipid-anchored construct of PrP provides a unique model to investigate the effects of different lipid environments on the structure and conversion mechanisms of PrP

Development of sentinel node localization and ROLL in breast cancer in Europe

The concept of a precise region in which to find the lymph nodes that drain the lymph directly from the primary tumor site can be traced back to a century ago to the observations of Jamieson and Dobson who described how cancer cells spread from cancer of the stomach in a single lymph node, which they called the â\u80\u9cprimary glandâ\u80\u9d. However, Cabanas was the first in 1977 to realize the importance of this concept in clinical studies following lymphography performed in patients with penile cancer. Thanks to Mortonâ\u80\u99s studies on melanoma in 1992, we began to understand the potential impact of the sentinel lymph node (SN) on the surgical treatment of this type of cancer. The use of a vital dye (blue dye) administered subdermally in the region surrounding the melanoma lesion led to the identification of the sentinel node, and the vital dye technique was subsequently applied to other types of solid tumors, e.g. breast, vulva. However, difficulties in using this technique in anatomical regions with deep lymphatic vessels, e.g. axilla, led to the development of lymphoscintigraphy, started by Alex and Krag in 1993 on melanoma and breast cancer and optimized by our group at European Institute of Oncology (IEO) in Milan in 1996. Today, lymphoscintigraphy is still considered as the most reliable method for the detection of the SN. In 1996, a new method for the localization of non-palpable breast lesion called radioguided occult lesion localization (ROLL) was also developed at IEO. Retrospective and prospective studies have since shown that the ROLL procedure permits the easy and accurate surgical removal of non-palpable breast lesions, overcoming the limitations of previous techniques such as the wire-guided localization. The purpose of this paper is to describe the evolution of SN biopsy and radioguided surgery in the management of breast cancer. We also include a review of the literature on the clinical scenarios in which SN biopsy in breast cancer is currently used, with particular reference to controversies and future prospects

Regulation of immunity during visceral Leishmania infection

Unicellular eukaryotes of the genus Leishmania are collectively responsible for a heterogeneous group of diseases known as leishmaniasis. The visceral form of leishmaniasis, caused by L. donovani or L. infantum, is a devastating condition, claiming 20,000 to 40,000 lives annually, with particular incidence in some of the poorest regions of the world. Immunity to Leishmania depends on the development of protective type I immune responses capable of activating infected phagocytes to kill intracellular amastigotes. However, despite the induction of protective responses, disease progresses due to a multitude of factors that impede an optimal response. These include the action of suppressive cytokines, exhaustion of specific T cells, loss of lymphoid tissue architecture and a defective humoral response. We will review how these responses are orchestrated during the course of infection, including both early and chronic stages, focusing on the spleen and the liver, which are the main target organs of visceral Leishmania in the host. A comprehensive understanding of the immune events that occur during visceral Leishmania infection is crucial for the implementation of immunotherapeutic approaches that complement the current anti-Leishmania chemotherapy and the development of effective vaccines to prevent disease.The research leading to these results has received funding from the European Community’s Seventh Framework Programme under grant agreement No.602773 (Project KINDRED). VR is supported by a post-doctoral fellowship granted by the KINDReD consortium. RS thanks the Foundation for Science and Technology (FCT) for an Investigator Grant (IF/00021/2014). This work was supported by grants to JE from ANR (LEISH-APO, France), Partenariat Hubert Curien (PHC) (program Volubilis, MA/11/262). JE acknowledges the support of the Canada Research Chair Program

Endocrine disruptors and obesity

The purpose of this review is to summarise current evidence that some environmental chemicals may be able to interfere in endocrine regulation of energy metabolism and adipose tissue structure. Recent findings demonstrate that such endocrine disrupting chemicals, termed “obesogens”, can promote adipogenesis and cause weight gain. This includes compounds to which the human population is exposed in daily life through their use in pesticides/herbicides, industrial and household products, plastics, detergents, flame retardants and ingredients in personal care products. Animal models and epidemiological studies have shown that an especially sensitive time for exposure is in utero or the neonatal period. In summarising the actions of obesogens, it is noteworthy that as their structures are mainly lipophilic, their ability to increase fat deposition has the added consequence of increasing the capacity for their own retention. This has the potential for a vicious spiral not only of increasing obesity but also increasing retention of other lipophilic pollutant chemicals with an even broader range of adverse actions. This might offer an explanation as to why obesity is an underlying risk factor for so many diseases including cancer

Is the meiofauna a good indicator for climate change and anthropogenic impacts?

Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research

Rhabdomyoblastic Differentiation in Head and Neck Malignancies Other Than Rhabdomyosarcoma

Rhabdomyosarcoma is a relatively common soft tissue sarcoma that frequently affects children and adolescents and may involve the head and neck. Rhabdomyosarcoma is defined by skeletal muscle differentiation which can be suggested by routine histology and confirmed by immunohistochemistry for the skeletal muscle-specific markers myogenin or myoD1. At the same time, it must be remembered that when it comes to head and neck malignancies, skeletal muscle differentiation is not limited to rhabdomyosarcoma. A lack of awareness of this phenomenon could lead to misdiagnosis and, subsequently, inappropriate therapeutic interventions. This review focuses on malignant neoplasms of the head and neck other than rhabdomyosarcoma that may exhibit rhabdomyoblastic differentiation, with an emphasis on strategies to resolve the diagnostic dilemmas these tumors may present. Axiomatically, no primary central nervous system tumors will be discussed.info:eu-repo/semantics/publishedVersio

Corporate reputation past and future: a review and integration of existing literature and a framework for future research

The concept of corporate reputation is steadily growing in interest among management researchers and practitioners. In this article, we trace key milestones in the development of reputation literature over the past six decades to suggest important research gaps as well as to provide contextual background for a subsequent integration of approaches and future outlook. In particular we explore the need for better categorised outcomes; a wider range of causes; and a deeper understanding of contingencies and moderators to advance the field beyond its current state while also taking account of developments in the macro business environment. The article concludes by presenting a novel reputation framework that integrates insights from reputation theory and studies, outlines gaps in knowledge and offers directions for future research

A Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s Parameters: Current Trends and Future Directions

Water quality has a significant influence on human health. As a result, water quality parameter modelling is one of the most challenging problems in the water sector. Therefore, the major factor in choosing an appropriate prediction model is accuracy. This research aims to analyse hybrid techniques and pre-processing data methods in freshwater quality modelling and forecasting. Hybrid approaches have generally been seen as a potential way of improving the accuracy of water quality modelling and forecasting compared with individual models. Consequently, recent studies have focused on using hybrid models to enhance forecasting accuracy. The modelling of dissolved oxygen is receiving more attention. From a review of relevant articles, it is clear that hybrid techniques are viable and precise methods for water quality prediction. Additionally, this paper presents future research directions to help researchers predict freshwater quality variables

Application of hybrid machine learning models and data pre-processing to predict water level of watersheds: Recent trends and future perspective

The community’s well-being and economic livelihoods are heavily influenced by the water level of watersheds. The changes in water levels directly affect the circulation processes of lakes and rivers that control water mixing and bottom sediment resuspension, further affecting water quality and aquatic ecosystems. Thus, these considerations have made the water level monitoring process essential to save the environment. Machine learning hybrid models are emerging robust tools that are successfully applied for water level monitoring. Various models have been developed, and selecting the optimal model would be a lengthy procedure. A timely, detailed, and instructive overview of the models’ concepts and historical uses would be beneficial in preventing researchers from overlooking models’ potential selection and saving significant time on the problem. Thus, recent research on water level prediction using hybrid machines is reviewed in this article to present the “state of the art” on the subject and provide some suggestions on research methodologies and models. This comprehensive study classifies hybrid models into four types algorithm parameter optimisation-based hybrid models (OBH), pre-processing-based hybrid models (PBH), the components combination-based hybrid models (CBH), and hybridisation of parameter optimisation-based with preprocessing-based hybrid models (HOPH); furthermore, it explains the pre-processing of data in detail. Finally, the most popular optimisation methods and future perspectives and conclusions have been discussed