Evidence map›Paper›PMID 39007096›Full record

ArticlePharmaNutrition2024

Opportunities and challenges in using NIH's Dietary Supplement Label Database for research on non-nutrient ingredients: Use case for ingredients in honeybee products.

Alessandra Durazzo, Massimo Lucarini, Johanna T Dwyer, Barbara C Sorkin, Michael Heinrich, Pamela Pehrsson

Abstract read
In one paragraph

Article in PharmaNutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alessandra DurazzoCREA-Research Centre for Food and Nutrition, Via Ardeatina 546, 00178, Rome, Italy.
Massimo LucariniCREA-Research Centre for Food and Nutrition, Via Ardeatina 546, 00178, Rome, Italy.
Johanna T DwyerOffice of Dietary Supplements, National Institutes of Health, 6705 Rockledge Drive (Rockledge I) Room 730, Bethesda, MD 20817, MSC 7991, USA.
Barbara C SorkinOffice of Dietary Supplements, National Institutes of Health, 6705 Rockledge Drive (Rockledge I) Room 730, Bethesda, MD 20817, MSC 7991, USA.
Michael HeinrichUCL School of Pharmacy, Pharmacognosy and Phytotherapy, London, United Kingdom.
Pamela PehrssonBeltsville Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Bethesda, MD, United States.

Funding

Intramural NIH HHS Z99 OD999999
6 · The paper itself

Abstract

Background: Non-nutrient bioactive ingredients of foods such as bee products are often of interest in preclinical and clinical research to explore their possible beneficial effects. The National Institute of Health's Dietary Supplement Label Database (DSLD) contains over 165,000 labels of dietary supplements marketed in the United States of America (US), including declarations on labels for many of these ingredients, including those in honeybee products which have been used in foods and traditional medicines for centuries worldwide and are now also appearing in dietary supplements. Methods: This article presents a use case for honeybee products that describes and tests the utility of the DSLD and other databases available in the US as research tools for identifying and quantifying the prevalence of such ingredients.. It focuses on the limitations to the information on product composition in these databases and describes how to code the ingredients using the LanguaL Results and Conclusions: Codes for the ingredients are provided for identifying their presence in LanguaL

Indexed as

bee product ingredientscoding proceduredatabase, Dietary Supplement Label Databasedietary supplementsFoodEx2LanguaL™

Identifiers

PMID39007096
PMCPMC11243758

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.