A Shift Towards Coexistence: Humane Treatment of Mice (Mus musculus), Norway Rats (Rattus norvegicus), and Black Rats (Rattus rattus)

Despite the lasting aversion many hold towards rats and mice owing to historical associations with diseases such as the plague, there exists a growing consensus among researchers advocating for a reappraisal of these creatures. A noticeable trend is emerging in Western Europe, wherein rodents are increasingly viewed as urban neighbors, challenging the prevailing negative perceptions. To explain the ongoing shift, we use examples from medicine, popular culture, science, and exhibitions. The recognition of rats and mice as sentient and intelligent beings necessitates human stewardship in the context of urban coexistence. We conclude that understanding the ecology and behavior of rats and mice in urban environments, as well as human behavior change, is a prerequisite for achieving harmonious urban coexistence

High practice variation in risk stratification, baseline oncological staging, and follow-up strategies for T1 colorectal cancers in the Netherlands

Background and study aims Based on pathology, locally resected T1 colorectal cancer (T1-CRC) can be classified as having low- or high-risk for irradicality and/or lymph node metastasis, the latter requiring adjuvant surgery. Reporting and application of pathological high-risk criteria is likely variable, with inherited variation regarding baseline oncological staging, treatment and surveillance. Methods We assessed practice variation using an online survey among gastroenterologists and surgeons participating in the Dutch T1-CRC Working Group. Results Of the 130 invited physicians, 53 % participated. Regardi

Effects of Detergent on α-Synuclein Structure: A Native MS-Ion Mobility Study

The intrinsically disordered protein α-synuclein plays a major role in Parkinson’s disease. The protein can oligomerize resulting in the formation of various aggregated species in neuronal cells, leading to neurodegeneration. The interaction of α-synuclein with biological cell membranes plays an important role for specific functions of α-synuclein monomers, e.g., in neurotransmitter release. Using different types of detergents to mimic lipid molecules present in biological membranes, including the presence of Ca2+ ions as an important structural factor, we aimed to gain an understanding of how α-synuclein interacts with membrane models and how this affects the protein conformation and potential oligomerization. We investigated detergent binding stoichiometry, affinity and conformational changes of α-synuclein taking detergent concentration, different detergent structures and charges into account. With native nano-electrospray ionization ion mobility-mass spectrometry, we were able to detect unique conformational patterns resulting from binding of specific detergents to α-synuclein. Our data demonstrate that α-synuclein monomers can interact with detergent molecules irrespective of their charge, that protein-micelle interactions occur and that micelle properties are an important factor

Survey among FELASA members about rehoming of animals used for scientific and educational purposes

Rehoming is an important fate, which should be considered for animals used for scientific and educational purposes, and which is highlighted in the European Directive 2010/63 EU. In 2018, the Federation of European Laboratory Animal Science Associations (FELASA) convened a working group to review current literature and identify existing practices with the aim of issuing general recommendations on the rehoming of research animals. In order to understand the number and species of animals being rehomed and which species and information to include in the recommendations, the working group launched a survey that was distributed among FELASA members, yielding 97 valid records for analysis. Most respondents of the survey considered the rehoming of cats, dogs, mice, rats, rabbits, pigs and minipigs. The most important issues reported by the respondents were related to availability/suitability of animals, availability of adopters and legal issues. Based on the data and information collected in this survey, the working group decided on the format and content of the future recommendations: a first section containing a general protocol for rehoming, addressing the issues raised by the respondents, and a second section containing species-specific information and advice about cats, dogs, small prey mammals, equines, primates, camelids and minipigs

FELASA recommendations for the rehoming of animals used for scientific and educational purposes

Directive 2010/63/EU of the European Parliament and the Council of 22 September 2010 states that at the end of a procedure, the most appropriate decision on the future of an animal previously used or intended for use in scientific procedures should be taken on the basis of animal welfare and potential risks to the environment. Member States may allow animals to be rehomed provided the health of the animal allows it, there is no danger to public health, animal health or the environment and if appropriate measures have been taken to safeguard the wellbeing of the animal. In countries where rehoming is permitted, it is the responsibility of the Animal Welfare Body to advise on a rehoming scheme which must include appropriate socialization in order to help facilitate successful rehoming, avoid unnecessary distress to the animals and guarantee public safety. This paper reviews the EU legislation, existing guidance, current literature and best practice to define rehoming, sets out general considerations for rehoming laboratory animals including socialization and provides practical advice on the steps required in a rehoming scheme. For those species most frequently rehomed, more detailed species-specific sections are included

Native Ion Mobility-Mass Spectrometry Reveals the Formation of β-Barrel Shaped Amyloid-β Hexamers in a Membrane-Mimicking Environment.

The mechanisms behind the Amyloid-β (Aβ) peptide neurotoxicity in Alzheimer's disease are intensely studied and under debate. One suggested mechanism is that the peptides assemble in biological membranes to form β-barrel shaped oligomeric pores that induce cell leakage. Direct detection of such putative assemblies and their exact oligomeric states is however complicated by a high level of heterogeneity. The theory consequently remains controversial, and the actual formation of pore structures is disputed. We herein overcome the heterogeneity problem by employing a native mass spectrometry approach and demonstrate that Aβ(1-42) peptides form coclusters with membrane mimetic detergent micelles. The coclusters are gently ionized using nanoelectrospray and transferred into the mass spectrometer where the detergent molecules are stripped away using collisional activation. We show that Aβ(1-42) indeed oligomerizes over time in the micellar environment, forming hexamers with collision cross sections in agreement with a general β-barrel structure. We also show that such oligomers are maintained and even stabilized by addition of lipids. Aβ(1-40) on the other hand form significantly lower amounts of oligomers, which are also of lower oligomeric state compared to Aβ(1-42) oligomers. Our results thus support the oligomeric pore hypothesis as one important cell toxicity mechanism in Alzheimer's disease. The presented native mass spectrometry approach is a promising way to study such potentially very neurotoxic species and how they could be stabilized or destabilized by molecules of cellular or therapeutic relevance

Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: statistical recommendations for conduct and planning

Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant‐level covariate (eg, age, gender, biomarker). Single trials do not usually have sufficient power to detect genuine treatment‐covariate interactions, which motivate the sharing of individual participant data (IPD) from multiple trials for meta‐analysis. Here, we provide statistical recommendations for conducting and planning an IPD meta‐analysis of randomized trials to examine treatment‐covariate interactions. For conduct, two‐stage and one‐stage statistical models are described, and we recommend: (i) interactions should be estimated directly, and not by calculating differences in meta‐analysis results for subgroups; (ii) interaction estimates should be based solely on within‐study information; (iii) continuous covariates and outcomes should be analyzed on their continuous scale; (iv) nonlinear relationships should be examined for continuous covariates, using a multivariate meta‐analysis of the trend (eg, using restricted cubic spline functions); and (v) translation of interactions into clinical practice is nontrivial, requiring individualized treatment effect prediction. For planning, we describe first why the decision to initiate an IPD meta‐analysis project should not be based on between‐study heterogeneity in the overall treatment effect; and second, how to calculate the power of a potential IPD meta‐analysis project in advance of IPD collection, conditional on characteristics (eg, number of participants, standard deviation of covariates) of the trials (potentially) promising their IPD. Real IPD meta‐analysis projects are used for illustration throughout

Search Filters for Finding Prognostic and Diagnostic Prediction Studies in Medline to Enhance Systematic Reviews

Background: The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter. Methodology/Principal Findings: Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next -using word frequency methods - we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85. Conclusions/Significance: Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studie

CD73 (ecto‐5′‐nucleotidase) hepatocyte levels differ across mouse strains and contribute to mallory‐denk body formation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100334/1/hep26525.pd

Management of superficial venous thrombosis based on individual risk profiles: protocol for the development and validation of three prognostic prediction models in large primary care cohorts

BACKGROUND: Superficial venous thrombosis (SVT) is considered a benign thrombotic condition in most patients. However, it also can cause serious complications, such as clot progression to deep venous thrombosis (DVT) and pulmonary embolism (PE). Although most SVT patients are encountered in primary healthcare, studies on SVT nearly all were focused on patients seen in the hospital setting. This paper describes the protocol of the development and external validation of three prognostic prediction models for relevant clinical outcomes in SVT patients seen in primary care: (i) prolonged (painful) symptoms within 14 days since SVT diagnosis, (ii) for clot progression to DVT or PE within 45 days and (iii) for clot recurrence within 12 months. METHODS: Data will be used from four primary care routine healthcare registries from both the Netherlands and the UK; one UK registry will be used for the development of the prediction models and the remaining three will be used as external validation cohorts. The study population will consist of patients ≥18 years with a diagnosis of SVT. Selection of SVT cases will be based on a combination of ICPC/READ/Snowmed coding and free text clinical symptoms. Predictors considered are sex, age, body mass index, clinical SVT characteristics, and co-morbidities including (history of any) cardiovascular disease, diabetes, autoimmune disease, malignancy, thrombophilia, pregnancy or puerperium and presence of varicose veins. The prediction models will be developed using multivariable logistic regression analysis techniques for models i and ii, and for model iii, a Cox proportional hazards model will be used. They will be validated by internal-external cross-validation as well as external validation. DISCUSSION: There are currently no prediction models available for predicting the risk of serious complications for SVT patients presenting in primary care settings. We aim to develop and validate new prediction models that should help identify patients at highest risk for complications and to support clinical decision making for this understudied thrombo-embolic disorder. Challenges that we anticipate to encounter are mostly related to performing research in large, routine healthcare databases, such as patient selection, endpoint classification, data harmonisation, missing data and avoiding (predictor) measurement heterogeneity