scholarly journals Teratogenic potential of Urtica massaica (Mildbr.) and Croton megalocarpus (Hutch) in mice

2018 ◽  
Vol 7 (6) ◽  
pp. 460-463
Author(s):  
Wabai W. Yvonne ◽  
◽  
Mwonjoria J.K. Maina ◽  
Njagi E. Mwaniki ◽  
◽  
...  
Keyword(s):  
Animal Model ◽  
Analysis Of Variance ◽  
Plant Extracts ◽  
Food Additives ◽  
Scientific Data ◽  
Gravid Uterus ◽  
Teratogenic Effects ◽  
Data Set ◽  
Teratogenic Potential ◽  
Partial Resorption

Urtica massaica (Urticaceae) and Croton megalocarpus are used either as vegetables or as food additives and as medicine in traditional African societies. However, in spite of the widespread consumption of these plants as folklore remedies and for diet, there is a scarcity of scientific data on their teratogenicity. Hence this study sought to assess the teratogenic effects of these plant extracts in an animal model. The study was conducted using Swiss albino mice. The extracts of these plants were administered orally in mice which were then euthanized. The weights of the gravid uterus and pups, as well as the number of pups, were determined. The pups were examined for gross malformations. The data set was analysed using one-way analysis of variance and Tukey as the post-Anova test. P < 0.05 was the limit of significance. U. massaica and C. megalocarpus caused 40% and 20% fetal partial resorption respectively. The latter also caused microcephaly and polyhydramnios. Hence, U. massaica leaves and C. megalocarpus stem extracts exhibited teratogenic activity and should be used with care during pregnancy

Evaluation of a structured expert elicitation estimating the proportion of illness acquired by foodborne transmission for nine enteric pathogens in Australia

2015 ◽  
Vol 144 (5) ◽  
pp. 897-906 ◽  
Author(s):  
H. VALLY ◽  
K. GLASS ◽  
L. FORD ◽  
G. HALL ◽  
M. D. KIRK ◽  
...  
Keyword(s):  
Analysis Of Variance ◽  
Expert Opinion ◽  
Systematic Reviews ◽  
Burden Of Disease ◽  
Scientific Data ◽  
Expert Elicitation ◽  
Enteric Pathogens ◽  
Formal Synthesis ◽  
Robust Estimates ◽  
Elicitation Process

SUMMARYEstimates of the proportion of illness transmitted by food for different enteric pathogens are essential for foodborne burden-of-disease studies. Owing to insufficient scientific data, a formal synthesis of expert opinion, an expert elicitation, is commonly used to produce such estimates. Eleven experts participated in an elicitation to estimate the proportion of illnesses due to food in Australia for nine pathogens over three rounds: first, based on their own knowledge alone; second, after being provided with systematic reviews of the literature and Australian data; and finally, at a workshop where experts reflected on the evidence. Estimates changed significantly across the three rounds (P= 0·002) as measured by analysis of variance. Following the workshop in round 3, estimates showed smoother distributions with significantly less variation for several pathogens. When estimates were combined to provide combined distributions for each pathogen, the width of these combined distributions reflected experts’ perceptions of the availability of evidence, with narrower intervals for pathogens for which evidence was judged to be strongest. Our findings show that the choice of expert elicitation process can significantly influence final estimates. Our structured process – and the workshop in particular – produced robust estimates and distributions appropriate for inclusion in burden-of-disease studies.

Replication of Data Analyses

2017 ◽  
Author(s):  
Emery R. Boose ◽  
Barbara S. Lerner
Keyword(s):  
Original Work ◽  
Statistical Tests ◽  
Scientific Paper ◽  
Scientific Data ◽  
Data Sources ◽  
Narrative Form ◽  
Data Provenance ◽  
General Description ◽  
Data Set ◽  
Data Analyses

The metadata that describe how scientific data are created and analyzed are typically limited to a general description of data sources, software used, and statistical tests applied and are presented in narrative form in the methods section of a scientific paper or a data set description. Recognizing that such narratives are usually inadequate to support reproduction of the analysis of the original work, a growing number of journals now require that authors also publish their data. However, finer-scale metadata that describe exactly how individual items of data were created and transformed and the processes by which this was done are rarely provided, even though such metadata have great potential to improve data set reliability. This chapter focuses on the detailed process metadata, called “data provenance,” required to ensure reproducibility of analyses and reliable re-use of the data.

scholarly journals Animal Model Versus Polynomial Legendre Test-Day In Dairy Cattle

2020 ◽  
Vol 23 (1) ◽  
pp. 5-12
Author(s):  
Mircea Cătălin Rotar ◽  
Horia Grosu ◽  
Mihail Alexandru Gras ◽  
Rodica Ştefania Pelmuş ◽  
Cristina Lazăr ◽  
...  
Keyword(s):  
Animal Model ◽  
Dairy Cattle ◽  
Fixed Effects ◽  
Rank Correlation ◽  
Pedigree Information ◽  
Lactation Period ◽  
Data Set ◽  
Breeding Values ◽  
Normal Limits ◽  
Model Versus

AbstractThe aim of the study was to compare the classical animal model (based on total milk for 305 days) with the Test-Day model (using monthly records of milk yield from Official Records of Performances). The data set derived from a total 175 animals (cows with records, parents of these animals and the descendants) from two Romanian breeds (Romanian Black Spotted and Montbeliarde), the phenotypic and the pedigree information arisen from National Research Development Institute for Animal Biology and Nutrition (IBNA-Balotesti). The selection criteria to be included in the analysis for each cow was to have at least 3 test-days and the days in milk between 200 and 330 for the Test-Day model and the total amount of the 305- day lactation yield for classical Animal Model respectively. Both models use B.L.U.P methodology and for that reason all the estimates were adjusted for fixed effects and all the breeding values and the solution for fixed effects were estimated simultaneous. For the animal model the fixed effects used was the breed and the year of performing and for the Test-Day model was an extra one, the test day effect. The correlation calculated between test days was very high (over 90%) for consecutive tests, and was getting lower when the days between tests was higher (under 40%). Also, in terms of heritability the values were in normal limits throughout lactation, except at the beginning and end of lactation period where these values were a little bit higher. The comparison of the ranking of breeding values with Spearman rank correlation shows that in 80% of the cases the ranking was similar for both models. As the ranking correlations shows, it is certain that the two models are very similar when they are used for genetic evaluation. But, in conclusion, we can say that for a better lactation curve estimation it is recommending to use test-day model for dairy cattle.

scholarly journals Rethinking animal models of sepsis – working towards improved clinical translation whilst integrating the 3Rs

2020 ◽  
Vol 134 (13) ◽  
pp. 1715-1734 ◽  
Author(s):  
Manasi Nandi ◽  
Simon K. Jackson ◽  
Duncan Macrae ◽  
Manu Shankar-Hari ◽  
Jordi L. Tremoleda ◽  
...  
Keyword(s):  
Animal Model ◽  
Construct Validity ◽  
Experimental System ◽  
Scientific Data ◽  
Clinical Translation ◽  
Face Validity ◽  
Research Findings ◽  
Experimental Approaches ◽  
Per Se ◽  
Unrealistic Expectations

Abstract Sepsis is a major worldwide healthcare issue with unmet clinical need. Despite extensive animal research in this area, successful clinical translation has been largely unsuccessful. We propose one reason for this is that, sometimes, the experimental question is misdirected or unrealistic expectations are being made of the animal model. As sepsis models can lead to a rapid and substantial suffering – it is essential that we continually review experimental approaches and undertake a full harm:benefit impact assessment for each study. In some instances, this may require refinement of existing sepsis models. In other cases, it may be replacement to a different experimental system altogether, answering a mechanistic question whilst aligning with the principles of reduction, refinement and replacement (3Rs). We discuss making better use of patient data to identify potentially useful therapeutic targets which can subsequently be validated in preclinical systems. This may be achieved through greater use of construct validity models, from which mechanistic conclusions are drawn. We argue that such models could provide equally useful scientific data as face validity models, but with an improved 3Rs impact. Indeed, construct validity models may not require sepsis to be modelled, per se. We propose that approaches that could support and refine clinical translation of research findings, whilst reducing the overall welfare burden on research animals.

scholarly journals EKSTRAKSI KOLAGEN TULANG IKAN CAKALANG (Katsuwonus pelamis) MENJADI GELATIN DENGAN ASAM KLORIDA

2017 ◽  
Vol 5 (3) ◽  
pp. 69
Author(s):  
Febri Triani Singkuku ◽  
Hens Onibala ◽  
Agnes Triasih Agustin
Keyword(s):  
Analysis Of Variance ◽  
Food Additives ◽  
Skipjack Tuna ◽  
Anova Analysis ◽  
Katsuwonus Pelamis ◽  
Fish Waste ◽  
Randomized Design ◽  
Animal Bones ◽  
Sarcoplasmic Protein ◽  
Skeletal Bone

Protein of fish can be divided into 3 main groups i.e. myofibril protein which exist mostly in meat, sarcoplasmic protein present in the blood and stroma protein which can be found in the skin and fish bones. Fish waste can be processed into highly value product such as gelatin. Gelatin is the final product after collagen from the skin or animal bones were hydrolysis. The main resources for making gelatin was the skin or bones of cattle and pigs. The objective of this study was to obtain the gelatin from the skeletal bone of skipjack tuna which were extracted using varied concentration of hydrochloric acid (1, 3, and 5%) . This study used a complete randomized design. The data were analyzed by ANOVA (analysis of variance) using JMP software. The gelatin has a rendemen value varying between 2.5–16,25%, water content 7,75–9,75%, protein level 17,6–48,2% and fat content 0,6–3%. The results showed that the gelatin from the skeletal bone of skipjack tuna can be used as food additives (BTP) due to its high protein value, and can assist the reduction of organic waste from fishery industry due to its economical value. Protein ikan dapat dibagi menjadi 3 golongan yaitu protein myofibril yang terdapat pada daging, protein sarkoplasma yang ada pada darah dan protein stroma yang terdapat pada kulit dan tulang ikan (limbah ikan). Limbah ikan dapat diolah menjadi bahan yang memiliki daya jual seperti gelatin. Gelatin merupakan hasil hidrolisis kolagen dari kulit atau tulang hewan. Pada umumnya gelatin diolah dari kulit atau tulang sapi dan babi. Penelitian ini bertujuan untuk mendapatkan gelatin dari tulang ikan cakalang yang diekstrak menggunakan larutan asam klorida(HCI) yang bervariasi (1, 3, dan 5%). Penelitian ini menggunakan rancangan acak lengkap. Data yang didapatkan dianalisis dengan uji ANOVA (analysis of variance) dengan bantuan software JMP. . Gelatin yang dihasilkan memiliki nilai rendemen bervariasi antara 2,5–16,25%, kadar air 7,75–9,75%, kadar protein 17,6–48,2% dan kadar lemak 0,6–3%. Hasil penelitian menunjukkan potensi tulang ikan cakalang yang diekstraksi menjadi gelatin memiliki nilai protein yang baik sehingga dapat dijadikan bahan tambahan pangan (BTP), dan memiliki nilai ekonomis tinggi sehingga dapat membantu proses pengurangan limbah organik industri perikanan

Making more research count: a blockchain enabled one-stop shop for immutable behavioral research

foresight ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christian Hugo Hoffmann
Keyword(s):  
Institutional Economics ◽  
New Technologies ◽  
Behavioral Science ◽  
Data Integrity ◽  
Original Data ◽  
Scientific Data ◽  
Data Set ◽  
Content Type ◽  
Blockchain Technology ◽  
The Right

Purpose The purpose of this paper is to offer a panoramic view at the credibility issues that exist within social sciences research. Design/methodology/approach The central argument of this paper is that a joint effort between blockchain and other technologies such as artificial intelligence (AI) and deep learning and how they can prevent scientific data manipulation or data forgery as a way to make science more decentralized and anti-fragile, without losing data integrity or reputation as a trade-off. The authors address it by proposing an online research platform for use in social and behavioral science that guarantees data integrity through a combination of modern institutional economics and blockchain technology. Findings The benefits are mainly twofold: On the one hand, social science scholars get paired with the right target audience for their studies. On the other hand, a snapshot of the gathered data at the time of creation is taken so that researchers can prove that they used the original data set to peers in the future while maintaining full control of their data. Originality/value The proposed combination of behavioral economics with new technologies such as blockchain and AI is novel and translated into a cutting-edge tool to be implemented.

Feature-Based Uncertainty Visualization

Big Data ◽  
2016 ◽  
pp. 261-287
Author(s):  
Keqin Wu ◽  
Song Zhang
Keyword(s):  
Scientific Data ◽  
Data Sets ◽  
Data Set ◽  
Uncertainty Visualization ◽  
Scalar Data ◽  
Critical Issues ◽  
Contour Level ◽  
Feature Based ◽  
2D Data ◽  
The Impact

While uncertainty in scientific data attracts an increasing research interest in the visualization community, two critical issues remain insufficiently studied: (1) visualizing the impact of the uncertainty of a data set on its features and (2) interactively exploring 3D or large 2D data sets with uncertainties. In this chapter, a suite of feature-based techniques is developed to address these issues. First, an interactive visualization tool for exploring scalar data with data-level, contour-level, and topology-level uncertainties is developed. Second, a framework of visualizing feature-level uncertainty is proposed to study the uncertain feature deviations in both scalar and vector data sets. With quantified representation and interactive capability, the proposed feature-based visualizations provide new insights into the uncertainties of both data and their features which otherwise would remain unknown with the visualization of only data uncertainties.

Using Research Evidence to Inform Public Policy Decisions

2013 ◽  
Vol 51 (5) ◽  
pp. 412-422 ◽  
Author(s):  
Charles Moseley ◽  
Harold Kleinert ◽  
Kathleen Sheppard-Jones ◽  
Stephen Hall
Keyword(s):  
Public Policy ◽  
Large Scale ◽  
Research Evidence ◽  
State Level ◽  
Scientific Data ◽  
Policy Decisions ◽  
Data Set ◽  
Large Scale Data ◽  
Drive State ◽  
Public Policy Decisions

Abstract The application of scientific data in the development and implementation of sound public policy is a well-established practice, but there appears to be less consensus on the nature of the strategies that can and should be used to incorporate research data into policy decisions. This paper describes the promise and the challenges of using research evidence to inform public policy. Most specifically, we demonstrate how the application of a large-scale data set, the National Core Indicators (NCI), can be systematically used to drive state-level policy decisions, and we describe a case example of one state's application of NCI data to make significant changes to its Intellectual and Developmental Disabilities waiver. The need for continued research in this area is highlighted.

Developmental exposure to fenproporex: reproductive and morphological evaluation

2005 ◽  
Vol 24 (8) ◽  
pp. 397-402 ◽  
Author(s):  
C Q Moreira ◽  
M JSS Faria ◽  
J E Baroneza ◽  
R J Oliveira ◽  
E G Moreira
Keyword(s):  
Gravid Uterus ◽  
Maternal Weight ◽  
Developmental Exposure ◽  
Morphological Evaluation ◽  
Anorectic Drugs ◽  
Significant Difference ◽  
Uterine Growth ◽  
Teratogenic Potential ◽  
C 30 ◽  
Cervical Ribs

This study was designed to evaluate the maternal toxicity and teratogenicity of fenproporex, one of the most widelyused anorectic drugs in many countries, including Brazil. Three periods of exposure were evaluated: (a) 30 days before mating; (b) from gestational day (GD) 0 to 14; and (c) 30 days before mating and during pregnancy, until GD 14. Female mice from experimental groups received, by gavage, 15 mg/kg of fenproporex. Treatment with fenproporex increased ambulation of dams in the open field test and did not influence the mobility in the forcedswimming test. There was no significant difference in maternal weight gain between the controls and fenproporex-treated groups, although fenproporex treatment reduced the gravid uterus weight. No significant difference was observed in postimplantation loss, fetal viability and sex ratio. In addition, this compound did not impair intra-uterine growth. The reduction in the number of implantations in the groups receiving fenproporex indicates that this drug may have an adverse effect on implantation. Fenproporex treatment also increased the number of fetuses presenting small kidneys and cervical ribs. The present results indicate that fenproporex, in the dose and exposure periods tested, appears to exhibit a low maternal toxicity and teratogenic potential in mice.

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