Materials, Design, Analysis, and Reporting (MDAR) is a multidisciplinary research framework aimed at helping authors, editors, and other interested parties increase reporting transparency within life science manuscripts. The MDAR checklist aims to serve as a generic, minimum reporting standard for life science studies, a complement to journal and community specific guidelines and initiatives. The checklist is organized into three different sections: Materials, Design, and Analysis. For more information on MDAR, please check out their research.
With every submission to our systems, SciScore returns an MDAR checklist (in addition to our other reports), which is partially completed automatically using information detected in your research. You will most likely need to fill in additional information depending on your research topic as SciScore is currently only trained to detect a limited number of criteria, shown below. In the checklist, we note missing information with a "Not detected" and information not currently checked with a "Not currently checked by SciScore". If SciScore makes substantial mistakes with your manuscript, please contact us to help us learn from our mistakes.
The materials section contains expandable tables comprising information related to biological reagents and unique specimens (including some information regarding human participants if applicable). For key resources (e.g. antibodies, cell lines, and organisms), if no RRID is available, please submit your resource to its respective authority.
The items detected in this section of the MDAR report include the following:
Antibodies:
Please provide supplier name, catalogue number and RRID.
Immunohistochemical staining for BrdU was then performed using an anti-BrdU antibody (RRID:AB_10763546).
Cell Materials:
Cell lines - Please provide enough information to uniquely identify each strain, including accession number, supplier name, catalog number, clone number, and RRID.
The EPLC-65 cell line (RRID:CVCL_8194) was maintained in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% FBS at 37°C in a 5% CO2 atmosphere.
Primary cultures - Not currently checked by SciScore
Experimental Animals:
Laboratory animals - Please provide enough information to uniquely identify each organism, including species, strain, genetic modification status, accession or catalog number, supplier name, clone number, and RRID.
C57Bl6/JN (MGI, Cat# 2160357) or TH-Cre [B6.Cg-Tg(Th-cre)1Tmd/J; Jackson Laboratory] mice were used for all experiments.
Animal observed in or captured from the field - Not currently checked by SciScore
Model organisms - Please provide enough information to uniquely identify each organism, including species, strain, genetic modification status, accession or catalog number, supplier name, clone number, and RRID.
Currently, SciScore sorts both model organisms and laboratory animals into the same section of the MDAR report: laboratory animals (shown above).
Plants and microbes:
Plants - Not currently checked by SciScore
Microbes - Not currently checked by SciScore
Human research participants:
Institutional Review Board statement - Please identify the authority that granted ethical approval of your human research.
This study was approved by the Institutional Review Board Committee, and was carried out in accordance with the principles expressed in the Declaration of Helsinki.
Informed consent - Please provide a statement confirming that informed consent was obtained from research subjects.
Patients gave the written informed consent, and their records were de-identified prior to the analysis.
Age and sex of all study participants - Please report on both the age and the sex of all study participants.
Male mice at 6–8 weeks of age were purchased from Japan Clea (Tokyo, Japan).
Design:
The design section contains expandable tables comprising information related to the experimental design of the study, including methodologies and statistics.
The items detected in this section of the MDAR report include the following:
Study protocol:
Please provide the trial registration number (or DOI) for clinical trials research.
The authors confirm that all on going and related trials for this intervention are registered in the ClinicalTrials.gov platform–accession number NCT03025815.
Laboratory protocol:
Please provide a DOI (or a database accession number or URL) for detailed experimental procedures if available.
The study protocol can be accessed at dx.doi.org/10.17504/protocols.io.bcp6ivre.
Experimental study design: Please state if and how the below criteria were fulfilled, including instances where they were not completed.
Sample size determination
Sample size was based on estimations by power analysis with a level of significance of 0.05 and a power of 0.9.
Randomization
Enrolled subjects on continuous suppressive ART were randomized to receive mesalamine or matching placebo for 12 weeks, followed by a 12 week crossover period on the alternative arm.
Blinding
Subjects, coordinators, clinicians, and laboratory personnel were blinded to treatment assignment.
Inclusion & Exclusion Criteria
Subjects were elgible for the cross-sectional study if they were fluent in English and had a sexual partner (SP) in the previous 18 months and ineligible if they were postmenopausal or had undergone a sex change.
Sample definition and in-laboratory replication:
Number of times that replication occurred
Bioassays were replicated three times.
Type of replication - technical or biological
Each real-time PCR experiment included technical replicates, in a final volume of 15 µL.
Ethics: Please state details regarding the ethical approval of your research if applicable.
Institutional Review Board approval - for studies involving human subjects
The study was approved by the Institutional Review Board at the University of California, San Diego.
Institutional Animal Care and Use Committee approval - for studies involving experimental vertebrate organisms
Brigham Young University’s Institutional Animal Care and Use Committee (IACUC) has approved the animal use protocol for this study.
Field Sample Permit approval - for studies involving field samples and specimens
Permission to conduct field surveys on each location was given by the individual landowners concerned, and by the regulatory authority (Natural England) in those situations where the field site was afforded protected status (i.e. Site of Special Scientific Interest).
Dual Use Research of Concern (DURC):
Granting authority information - Not currently checked by SciScore
Analysis:
The analysis section contains expandable tables comprising information related to the statistical analysis, code, and data of your research.
The items detected in this section of the MDAR report include the following:
Attrition:
Please report if any data was excluded from the analysis.
Of these, 21 ticks could not be removed from the birds and 162 ticks were lost due to technical problems during nucleic acid extraction, resulting in 1,150 ticks available for analysis.
Statistics:
Please describe every statistical test used in your analysis.
For tissue culture experiments, statistical differences were calculated using a paired Student’s t-test.
Data availability:
Data availability statement
All genetic sequence data is available upon request to the authors.
Publicly available data identifiers - Please add DOIs and URLs.
Reused, publicly available data identifiers - Please add DOIs and URLs.
Currently, SciScore has trouble differentitating between new and reused publicly available data. As a result, we sort both into the publicly available section above.
Code Availability:
Code availability statement
Image analysis was performed with ImageJ software macro (code available upon request).
Please state which guidelines and checklists have been followed and provided - Not currently checked by SciScore
How to use this report:
Ensure that each criterion that you expect is addressed in your manuscript; please check what is relevant in the criteria above. In general though, adding more criteria is better as it provides greater transparency, allowing outside stakeholders (other researchers, journal editors, and funders) to make better, more informed decisions on the reproducibility of your research.
Pro Tip: If a journal expects that a criterion should be filled, but you do not believe that it is relevant, address it using a negative statement. Examples:
No subjects were excluded from our study.
We did not assess whether subjects were male or female because embryos were not genotyped.
Experimental subjects were not randomized into groups because this was deemed irrelevant to this study.
Experimenters were not blinded to the subject's genotype because knockout mice were visibly different from controls.
We did not check for sample sizes using a power analysis because our study does not report statistics between groups or within group variables.
No technical replication was completed because the Sasquatch was visible only once.
Possible Problems: SciScore does not recognize my sentence as fulfilling a criterion. In some cases, this is because researchers use complex sentences with uncommon syntactic patterns. Please try to simplify your sentences where possible, but if this issue persists, please contact us.
General notes on interpretation of text mining results:
SciScore is a machine learning, text analysis tool and is therefore susceptible to making two types of errors: false positives and false negatives.
False negatives: The most common error occurs when our models fail to detect a sentence that contains a rigor criterion or a resource, such as an antibody. False negatives generally occur either because the sentence is complex or in a less common syntactic pattern. Generally, simple sentences in clear standard English are simpler to process and result in fewer false negatives. If a truly complex sentence structure is required to describe reagents, a table may help not only SciScore but also human readers. If an RRID is detected in a sentence, SciScore will be triggered to take a look at the sentence, which may have been skipped otherwise.
False positives: This type of error occurs when our models falsely detect criteria that is not present. We try to minimize these false positives using several strategies, however, they still occur in roughly 3-5% of cases. If this impacts your SciScore experience, please contact our team and include the sentence where SciScore made the error. SciScore is always trying to learn from its mistakes for improved performance next time around.
Known Issues:
As mentioned before, SciScore is not perfect. Below we have provided a list of problems we are working to fix. If you notice any other persistent problems, please contact us.
Equations and figures, go figure. If you have been unable to get your SciScore report back or are noticing a significant number of errors, equations and figures can sometimes be the culprit. Try submitting without them.
We are still trying to iron out all of the kinks in our new identifers sections (for protocols, code IDs and data IDs). Sometimes identifiers will still be shown in red even though they resolve (and therefore should be blue). By clicking on the links provided in your SciScore report, you can check this out for yourself to double check SciScore. If you are redirected to a specific data record, then the identifier resolves! If not, then there could be an issue with the identifer (typo, etc.), the network (i.e. we reach out to a database and it does not respond), or the identifer is so new that our records haven't been updated to match.