Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

Full Sequence and Comparative Analysis of the Plasmid pAPEC-1 of Avian Pathogenic E. coli χ7122 (O78∶K80∶H9)

(APEC), are very diverse. They cause a complex of diseases in Human, animals, and birds. Even though large plasmids are often associated with the virulence of ExPEC, their characterization is still in its infancy., are also present in the sequence of pAPEC-1. The comparison of the pAPEC-1 sequence with the two available plasmid sequences reveals more gene loss and reorganization than previously appreciated. The presence of pAPEC-1-associated genes is assessed in human ExPEC by PCR. Many patterns of association between genes are found.The pathotype typical of pAPEC-1 was present in some human strains, which indicates a horizontal transfer between strains and the zoonotic risk of APEC strains. ColV plasmids could have common virulence genes that could be acquired by transposition, without sharing genes of plasmid function

From theoretical concepts to policies and applied programmes: the landscape of integration of oral health in primary care

Background: Despite its importance, the integration of oral health into primary care is still an emerging practice in the field of health care services. This scoping review aims to map the literature and provide a summary on the conceptual frameworks, policies and programs related to this concept. Methods: Using the Levac et al. six-stage framework, we performed a systematic search of electronic databases, organizational websites and grey literature from 1978 to April 2016. All relevant original publications with a focus on the integration of oral health into primary care were retrieved. Content analyses were performed to synthesize the results. Results: From a total of 1619 citations, 67 publications were included in the review. Two conceptual frameworks were identified. Policies regarding oral heath integration into primary care were mostly oriented toward common risk factors approach and care coordination processes. In general, oral health integrated care programs were designed in the public health sector and based on partnerships with various private and public health organizations, governmental bodies and academic institutions. These programmes used various strategies to empower oral health integrated care, including building interdisciplinary networks, training nondental care providers, oral health champion modelling, enabling care linkages and care coordinated process, as well as the use of e-health technologies. The majority of studies on the programs outcomes were descriptive in nature without reporting long-term outcomes. Conclusions: This scoping review provided a comprehensive overview on the concept of integration of oral health in primary care. The findings identified major gaps in reported programs outcomes mainly because of the lack of related research. However, the results could be considered as a first step in the development of health care policies that support collaborative practices and patient-centred care in the field of primary care sector

Matrix metalloproteinases in human melanoma cell lines and xenografts: increased expression of activated matrix metalloproteinase-2 (MMP-2) correlates with melanoma progression

Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) are involved in tumour progression and metastasis. In this study, we investigated the in vitro and in vivo expression patterns of MMP-1, MMP-2, MMP-3, MMP-9, TIMP-1 and TIMP-2 mRNA and protein in a previously described human melanoma xenograft model. This model consists of eight human melanoma cell lines with different metastatic behaviour after subcutaneous (s.c.) injection into nude mice. MMP-1 mRNA was detectable in all cell lines by reverse transcription polymerase chain reaction (RT-PCR), but the expression was too low to be detected by Northern blot analysis. No MMP-1 protein could be found using Western blotting. MMP-2 mRNA and protein were present in all cell lines, with the highest expression of both latent and active MMP-2 in the highest metastatic cell lines MV3 and BLM. MMP-3 mRNA was expressed in MV3 and BLM, and in the non-metastatic cell line 530, whereas MMP-3 protein was detectable only in MV3 and BLM. None of the melanoma cell lines expressed MMP-9. TIMP-1 and TIMP-2 mRNA and protein, finally, were present in all cell lines. A correlation between TIMP expression level and metastatic capacity of cell lines, however, was lacking. MMP and TIMP mRNA and protein expression levels were also studied in s.c. xenograft lesions derived from a selection of these cell lines. RT-PCR analysis revealed that MMP-1 mRNA was present in MV3 and BLM xenografts, and to a lesser extent in 530. Positive staining for MMP-1 protein was found in xenograft lesions derived from both low and high metastatic cell lines, indicating an in vivo up-regulation of MMP-1. MMP-2 mRNA was detectable only in xenografts derived from the highly metastatic cell lines 1F6m, MV3 and BLM. In agreement with the in vitro results, the highest levels of both latent and activated MMP-2 protein were observed in MV3 and BLM xenografts. With the exception of MMP-9 mRNA expression in 530 xenografts, MMP-3, MMP-9, and TIMP-1 mRNA and protein were not detectable in any xenograft, indicating a down-regulated expression of MMP-3 and TIMP-1 in vivo. TIMP-2 mRNA and protein were present in all xenografts; interestingly, the strongest immunoreactivity of tumour cells was found at the border of necrotic areas. Our study demonstrates that of all tested components of the matrix metalloproteinase system, only expression of activated MMP-2 correlates with increased malignancy in our melanoma xenograft model, corroborating an important role of MMP-2 in human melanoma invasion and metastasis. © 1999 Cancer Research Campaig

Different Human Copper-Zinc Superoxide Dismutase Mutants, SOD1G93A and SOD1H46R, Exert Distinct Harmful Effects on Gross Phenotype in Mice

Amyotrophic lateral sclerosis (ALS) is a heterogeneous group of fatal neurodegenerative diseases characterized by a selective loss of motor neurons in the brain and spinal cord. Creation of transgenic mice expressing mutant Cu/Zn superoxide dismutase (SOD1), as ALS models, has made an enormous impact on progress of the ALS studies. Recently, it has been recognized that genetic background and gender affect many physiological and pathological phenotypes. However, no systematic studies focusing on such effects using ALS models other than SOD1G93A mice have been conducted. To clarify the effects of genetic background and gender on gross phenotypes among different ALS models, we here conducted a comparative analysis of growth curves and lifespans using congenic lines of SOD1G93A and SOD1H46R mice on two different genetic backgrounds; C57BL/6N (B6) and FVB/N (FVB). Copy number of the transgene and their expression between SOD1G93A and SOD1H46R lines were comparable. B6 congenic mutant SOD1 transgenic lines irrespective of their mutation and gender differences lived longer than corresponding FVB lines. Notably, the G93A mutation caused severer disease phenotypes than did the H46R mutation, where SOD1G93A mice, particularly on a FVB background, showed more extensive body weight loss and earlier death. Gender effect on survival also solely emerged in FVB congenic SOD1G93A mice. Conversely, consistent with our previous study using B6 lines, lack of Als2, a murine homolog for the recessive juvenile ALS causative gene, in FVB congenic SOD1H46R, but not SOD1G93A, mice resulted in an earlier death, implying a genetic background-independent but mutation-dependent phenotypic modification. These results indicate that SOD1G93A- and SOD1H46R-mediated toxicity and their associated pathogenic pathways are not identical. Further, distinctive injurious effects resulted from different SOD1 mutations, which are associated with genetic background and/or gender, suggests the presence of several genetic modifiers of disease expression in the mouse genome

Meta-omics approaches to understand and improve wastewater treatment systems

Biological treatment of wastewaters depends on microbial processes, usually carried out by mixed microbial communities. Environmental and operational factors can affect microorganisms and/or impact microbial community function, and this has repercussion in bioreactor performance. Novel high-throughput molecular methods (metagenomics, metatranscriptomics, metaproteomics, metabolomics) are providing detailed knowledge on the microorganisms governing wastewater treatment systems and on their metabolic capabilities. The genomes of uncultured microbes with key roles in wastewater treatment plants (WWTP), such as the polyphosphate-accumulating microorganism Candidatus Accumulibacter phosphatis, the nitrite oxidizer Candidatus Nitrospira defluvii or the anammox bacterium Candidatus Kuenenia stuttgartiensis are now available through metagenomic studies. Metagenomics allows to genetically characterize full-scale WWTP and provides information on the lifestyles and physiology of key microorganisms for wastewater treatment. Integrating metagenomic data of microorganisms with metatranscriptomic, metaproteomic and metabolomic information provides a better understanding of the microbial responses to perturbations or environmental variations. Data integration may allow the creation of predictive behavior models of wastewater ecosystems, which could help in an improved exploitation of microbial processes. This review discusses the impact of meta-omic approaches on the understanding of wastewater treatment processes, and the implications of these methods for the optimization and design of wastewater treatment bioreactors.Research was supported by the Spanish Ministry of Education and Science (Contract Project CTQ2007-64324 and CONSOLIDER-CSD 2007-00055) and the Regional Government of Castilla y Leon (Ref. VA038A07). Research of AJMS is supported by the European Research Council (Grant 323009

Optimised and Rapid Pre-clinical Screening in the SOD1G93A Transgenic Mouse Model of Amyotrophic Lateral Sclerosis (ALS)

The human SOD1G93A transgenic mouse has been used extensively since its development in 1994 as a model for amyotrophic lateral sclerosis (ALS). In that time, a great many insights into the toxicity of mutant SOD1 have been gained using this and other mutant SOD transgenic mouse models. They all demonstrate a selective toxicity towards motor neurons and in some cases features of the pathology seen in the human disease. These models have two major drawbacks. Firstly the generation of robust preclinical data in these models has been highlighted as an area for concern. Secondly, the amount of time required for a single preclinical experiment in these models (3–4 months) is a hurdle to the development of new therapies. We have developed an inbred C57BL/6 mouse line from the original mixed background (SJLxC57BL/6) SOD1G93A transgenic line and show here that the disease course is remarkably consistent and much less prone to background noise, enabling reduced numbers of mice for testing of therapeutics. Secondly we have identified very early readouts showing a large decline in motor function compared to normal mice. This loss of motor function has allowed us to develop an early, sensitive and rapid screening protocol for the initial phases of denervation of muscle fibers, observed in this model. We describe multiple, quantitative readouts of motor function that can be used to interrogate this early mechanism. Such an approach will increase throughput for reduced costs, whilst reducing the severity of the experimental procedures involved

Dihydrotestosterone Ameliorates Degeneration in Muscle, Axons and Motoneurons and Improves Motor Function in Amyotrophic Lateral Sclerosis Model Mice

Amyotrophic lateral sclerosis (ALS) is a lethal disease characterized by a progressive loss of motoneurons. The clinical symptoms include skeletal muscle weakness and atrophy, which impairs motor performance and eventually leads to respiratory failure. We tested whether dihydrotestosterone (DHT), which has both anabolic effects on muscle and neuroprotective effects on axons and motoneurons, can ameliorate clinical symptoms in ALS. A silastic tube containing DHT crystals was implanted subcutaneously in SOD1-G93A mice at early symptomatic age when decreases in body weight and grip-strength were observed as compared to wild-type mice. DHT-treated SOD1-G93A mice demonstrated ameliorated muscle atrophy and increased body weight, which was associated with stronger grip-strength. DHT treatment increased the expression of insulin-like growth factor-1 in muscle, which can exert myotrophic as well as neurotrophic effects through retrograde transport. DHT treatment attenuated neuromuscular junction denervation, and axonal and motoneuron loss. DHT-treated SOD1-G93A mice demonstrated improvement in motor behavior as assessed by rota-rod and gait analyses, and an increased lifespan. Application of DHT is a relatively simple and non-invasive procedure, which may be translated into therapy to improve the quality of life for ALS patients

In quest of a systematic framework for unifying and defining nanoscience

This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience

Search for Standard Model Higgs Boson Production in Association with a W Boson using a Neural Network

Submitted to Phys. Rev. DWe present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 inverse fb. We select events consistent with a signature of a single charged lepton, missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to $150 GeV/c^2, respectively.We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions (pp̅ →W±H→ℓνbb̅ ) at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9  fb-1. We select events consistent with a signature of a single charged lepton (e±/μ±), missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to 150  GeV/c2, respectively.Peer reviewe