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This study was conducted to investigate the effect of the Ficus sycomorus extract on Eimeria intestinalis in experimentally infected rabbits. For this purpose, forty male 30-day-old rabbits (Blanc de Bouscat) were divided into four groups (n = 10 in each group). Rabbits kept in the first group served as negative control (non-treated-non-infected). Rabbits kept in the second, third, and fourth groups were challenged at 10 weeks old with 3 x 10(4) E. intestinalis sporulated oocysts. The third and fourth groups were treated orally with diclazuril 10% (0.05 mg/kg body weight) and F. sycomorus (100 mg/Kg) for three consecutive days, respectively. The efficacy was assessed based on the growth performance parameters, clinical symptoms, oocyst shedding, histopathological findings, and hematological parameters for 16 days post challenge. The study revealed that rabbits treated with F. sycomorus methanolic extract and diclazuril showed mild clinical symptoms with a significant decrease in oocyst shedding compared with the positive control. Moreover, the diclazuril-treated group showed the highest leukocytic count and the lowest monocytes percentage compared with other groups. Furthermore, the lowest lymphocytes percentage was recorded in the control positive group. Histopathologically, moderate coccidia infestation in the intestinal mucosa and moderate hydropic degeneration of hepatocytes were observed in the diclazuril treated group compared with the negative control. However, mild coccidia infestation in the intestinal mucosa and slight coagulative necrosis of hepatocytes was found in the F. sycomorus treated group. In conclusion, F. sycomorus methanolic extract had promising effects on the live performance, oocyst count, and blood variables, while it possesses adverse consequences on the hepatic tissues. Further studies are required to optimize the dose and extraction method to mitigate its side effects.

In the present study, a phytochemical of Ficus sycomorus (Moraceae family) was screened, and the effect of this extract on rabbit performance indices, immunity, and carcass quality measures was determined. Ficus sycomorus samples were collected, air-dried, and extracted with 70% methanol to prepare a solution of 100 mg/mL concentration. The extract was subjected to high-resolution mass spectrometric measurements via ultra-high performance liquid chromatography-quadrupole time-of-flight-nanospray mass spectrometry (UPLC-QToF-MS) and 1H NMR analysis. Forty-eight male rabbits, one-month-old, belonging to the Blanc de Bouscat and New Zealand White breeds were selected and distributed equally in a 2 x 3 factorial trial. The rabbits within each breed received F. sycomorus extract at the dose of 0, 100, and 200 mg/kg for 60 days. Blood samples were collected and serum obtained for the detection of liver enzymes, serum lipids, and proteins. The results of UPLC-QToF-MS and molecular networking analysis revealed the presence of procyanidin B2, procyanidin A1, genistein, eriodyctiol, catechin, luteolin, biochanin A, and chlorogenic acid that might exhibit various pharmaceutical activities. However, the F. sycomorus extract reduced rabbit performance indices and carcass quality measures. In addition, this extract significantly depressed the low-density lipoprotein and triglycerides, which may indicate the antidyslipidemia effect of this extract on rabbits.

Improvements in web technologies and artificial intelligence enable novel, more data-driven research practices for scientists. However, scientific knowledge generated from data-intensive research practices is disseminated with unstructured formats, thus hindering the scholarly communication in various respects. The traditional document-based representation of scholarly information hampers the reusability of research contributions. To address this concern, we developed the Physics Ontology (PhySci) to represent physics-related scholarly data in a machine-interpretable format. PhySci facilitates knowledge exploration, comparison, and organization of such data by representing it as knowledge graphs. It establishes a unique conceptualization to increase the visibility and accessibility to the digital content of physics publications. We present the iterative design principles by outlining a methodology for its development and applying three different evaluation approaches: data-driven and criteria-based evaluation, as well as ontology testing.

Systematic assessment of scientific events has become increasingly important for research communities. A range of metrics (e.g., citations, h-index) have been developed by different research communities to make such assessments effectual. However, most of the metrics for assessing the quality of less formal publication venues and events have not yet deeply investigated. It is also rather challenging to develop respective metrics because each research community has its own formal and informal rules of communication and quality standards. In this article, we develop a comprehensive framework of assessment metrics for evaluating scientific events and involved stakeholders. The resulting quality metrics are determined with respect to three general categories—events, persons, and bibliometrics. Our assessment methodology is empirically applied to several series of computer science events, such as conferences and workshops, using publicly available data for determining quality metrics. We show that the metrics’ values coincide with the intuitive agreement of the community on its “top conferences”. Our results demonstrate that highly-ranked events share similar profiles, including the provision of outstanding reviews, visiting diverse locations, having reputed people involved, and renowned sponsors. © 2020, The Author(s).

The way how research is communicated using text publications has not changed much over the past decades. We have the vision that ultimately researchers will work on a common structured knowledge base comprising comprehensive semantic and machine-comprehensible descriptions of their research, thus making research contributions more transparent and comparable. We present the SemSur ontology for semantically capturing the information commonly found in survey and review articles. SemSur is able to represent scientific results and to publish them in a comprehensive knowledge graph, which provides an efficient overview of a research field, and to compare research findings with related works in a structured way, thus saving researchers a significant amount of time and effort. The new release of SemSur covers more domains, defines better alignment with external ontologies and rules for eliciting implicit knowledge. We discuss possible applications and present an evaluation of our approach with the retrospective, exemplary semantification of a survey. We demonstrate the utility of the SemSur ontology to answer queries about the different research contributions covered by the survey. SemSur is currently used and maintained at OpenResearch.org.