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Cited by 184

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Characterizing the composition of intestinal microflora as a prospective treatment target in infant allergic disease

Open access
Kirjavainen, P·2001·FEMS Immunology and Medical Microbiology

Abstract

We assessed the fecal microflora of 10 healthy infants and 27 infants with atopic eczema during breast-feeding and after weaning. The atopic infants had less frequently Gram-positive species among the most predominant aerobes and smaller total cell counts. Further differences were associated with more extensive manifestations, seen as higher bacteroides and lower bifidobacteria counts. Weaning resulted in decreased bacteroides counts in atopic and total cell counts in healthy infants and diminished predominance by bifidobacteria in both. In conclusion, the most prominent question raised by these data is whether Gram-positive bacteria may have distinctive importance in protection against atopic sensitization. Further studies aiming to answer this question are warranted.

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Crossref · 10.1016/s0928-8244(01)00272-3

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Metadata

Authors
Kirjavainen, P.
Venue
FEMS Immunology and Medical Microbiology
Publisher
Wiley
Published
2001-12
Volume
32
Issue
1
Pages
1-7
ISSN
0928-8244 (ISSN-L)
OpenAlex
W2040083365
Cited by
184
References
3
FWCI
3.37
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Characterizing the composition of intestinal microflora as a prospective treatment target in infant allergic disease. https://app.cochat.ai/papers/10.1016/s0928-8244(01)00272-3
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Kirjavainen, P. (2001). Characterizing the composition of intestinal microflora as a prospective treatment target in infant allergic disease. FEMS Immunology and Medical Microbiology. https://doi.org/10.1016/s0928-8244(01)00272-3

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.