ArticleNutrients2023
Uncovering Predictive Factors and Interventions for Restoring Microecological Diversity after Antibiotic Disturbance.
Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed.
- Gut Microbiota Resilience and Environmental Stressors: A Hidden Key to Lifespan Optimization?Probiotics and antimicrobial proteins · 2026Review
- Cleaning reshapes bacterial communities in public toilets through disturbance and random reassembly.Scientific reports · 2026Article
- Absence of gut microbiota restoration following meropenem treatment in a systemic infection model.npj antimicrobials and resistance · 2025Article
- Understanding dysbiosis and resilience in the human gut microbiome: biomarkers, interventions, and challenges.Frontiers in microbiology · 2025Review
- Food colorant brilliant blue causes persistent functional and structural changes in an in vitro simplified microbiota model system.ISME communications · 2025Article
- Gut microbes of a high-value marine fish, Snubnose Pompano (Trachinotus blochii) are resilient to therapeutic dosing of oxytetracycline.Scientific reports · 2024Article
- Artificial Intelligence Technology for Food Nutrition.Nutrients · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Antibiotic treatment can lead to a loss of diversity of gut microbiota and may adversely affect gut microbiota composition and host health. Previous studies have indicated that the recovery of gut microbes from antibiotic-induced disruption may be guided by specific microbial species. We expect to predict recovery or non-recovery using these crucial species or other indices after antibiotic treatment only when the gut microbiota changes. This study focused on this prediction problem using a novel ensemble learning framework to identify a set of common and reasonably predictive recovery-associated bacterial species (p-RABs), enabling us to predict the host microbiome recovery status under broad-spectrum antibiotic treatment. Our findings also propose other predictive indicators, suggesting that higher taxonomic and functional diversity may correlate with an increased likelihood of successful recovery. Furthermore, to explore the validity of p-RABs, we performed a metabolic support analysis and identified
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Registered trials
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.