The DOI matches its Crossref record; 87 of the 89 references it cites were found in a registry or an index; none of the 45 sources its claims cite is checked for support yet.
Gut-microbiota-targeted diets modulate human immune status
Open accessPublished version of a preprint
Abstract
Diet modulates the gut microbiome, which in turn can impact the immune system. Here, we determined how two microbiota-targeted dietary interventions, plant-based fiber and fermented foods, influence the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study (n = 18/arm) combined with -omics measurements of microbiome and host, including extensive immune profiling, we found diet-specific effects. The high-fiber diet increased microbiome-encoded glycan-degrading carbohydrate active enzymes (CAZymes) despite stable microbial community diversity. Although cytokine response score (primary outcome) was unchanged, three distinct immunological trajectories in high-fiber consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented-food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in industrialized society.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A significant correlation was observed between increased fiber consumption among participants and an increase in total stool carbohydrates (p-value=8e-4; LME correcting for participants across time, Figure 3E).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIn the paper
“The primary outcome of cytokine response score (Shen-Orr et al., 2016) difference from baseline to end of intervention was not significant for either arm of the study (Table S4), nor were race or gender significant covariates.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
What the sources say
- Not checked yetcites Shen-Orr et al., 2016 source
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In the paper
“Microbiota diversity was a less effective model (60%) in discerning which diet a participant followed.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, despite higher consumption of fermented vegetables and vegetable brine drinks, total sodium intake did not change in the fermented food arm compared to their baseline diet (Table S3).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“No specific taxon (ASV) exhibited altered relative abundance over time across the entire high-fiber diet arm.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, we did observe an increase in the relative abundance of microbial proteins per gram stool of the high-fiber diet arm from baseline (Week −2 and Week 0) to the end of the maintenance phase (Week 10), suggesting that the density of microbes within the microbiota may have increased with higher fiber consumption (Figure 3B).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Those in the high-fiber diet arm increased their fiber consumption from an average of 21.5±8.0 g per day at baseline to 45.1±10.7 g per day at the end of the maintenance phase (Figure 1C).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, the ratio between insoluble:soluble fiber was significantly increased from baseline to study end (ratio = 2.6+0.6 at baseline, 3.5+1.1 at week 10; p=0.002).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conversely, the high-fermented food diet participants increased their intake in animal protein due to the increased consumption of fermented dairy products.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There were no CAZymes that decreased in relative abundance, indicating that the high-fiber diet led to an overall increase in complex carbohydrate processing capacity cohort-wide and not just a reconfiguration of carbohydrate utilization functionality.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
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- It may state two separate claims as one. 65
- Probably not a substantial claim. 60
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Importantly, participants in the high-fiber diet arm did not increase their consumption of fermented foods (Figure 1C, dashed line), nor did participants consuming the high-fermented food diet increase their fiber intake (Figure 1D, dashed line) during the course of the study.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While all participants followed the requirements for the dietary intervention, each implemented the intervention differently in terms of specific subcategories of fiber-rich or fermented foods they consumed (Figure S2A, S2B).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The four next highest-performing models were all generated using measurements of the microbiota including overall 16S rRNA-based composition (80% accuracy), stool microbe proteomics (74%), stool short-chained fatty acids (67%), and metagenomic measurement of carbohydrate active enzymes (67%).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These participants also decreased their consumption of animal protein and sodium (Table S3).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“To assess participants overall health throughout the study, blood glucose, insulin, triglycerides, LDL-C, HDL-C, blood pressure, and waist circumference were measured; however, no differences were observed in this generally healthy cohort either between the two arms or longitudinally (within) (data not shown).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the fermented food diet arm reported an increase in bloating from baseline (abdominal distention score=0.06 +/− 0.06) to the end of the ramp phase (score=0.4 +/− 0.1; p=0.03; paired t-test), which was no longer significant by the end of the maintenance phase.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“participants on the high-fiber diet reported an increase in stool softness from baseline (average Bristol stool type = 3.3 +/− 0.3) to end of ramp phase (stool type=4.1 +/− 0.3; p=0.04; paired t-test) and the end of maintenance phase (stool type=4.1 +/− 0.3, p=0.004; paired t-test).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The primary outcome of cytokine response score (Shen-Orr et al., 2016) difference from baseline to end of intervention was not significant for either arm of the study (Table S4), nor were race or gender significant covariates.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
What the sources say
- Not checked yetcites Shen-Orr et al., 2016 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“High-fiber diet participants increased their intake of soluble and insoluble fiber, carbohydrates, vegetable protein, and had a modest increase in calories, along with increases in iron, magnesium, potassium, vitamin C, and calcium.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Models generated using measurements of host immune parameters including endogenous immune cell signaling (61%), inflammatory cytokines (61%), and immune cell frequency (58%) were predictive of diet arm, but less so than many of the observed changes to the microbiota listed above. Models generated using immune cell signaling capacity (49%) were no better than chance at predicting diet group.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Remarkably, over the course of the 10-week intervention, we observed a cohort-wide decrease in many inflammatory markers in individuals consuming fermented foods, coincident with an increase in microbiota diversity.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
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In the paper
“We observed that each intervention produced a distinct response and that some responses were general, i.e., cohort-wide, while others were individualized.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This model relied upon intake of animal protein, total dietary fiber, and insoluble dietary fiber for classification.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The overall microbiota composition model was characterized by an increase in the genus Lachnospira in the high-fiber diet arm and a decrease in the high-fermented food arm relative to baseline (Figure 2C).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Decreases in inflammatory markers and increases in microbiota diversity from baseline to end of intervention were significant in the fermented food arm, a specific subset of short chain fatty acids (SCFAs) was significantly decreased in the high-fiber arm from baseline to end of intervention.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Metagenomic sequencing revealed an increase in the relative abundance of 11 different carbohydrate active enzymes (CAZymes); of 10 putative non-ambiguous substrate predictions, all were predicted to degrade plant cell wall carbohydrates (Figure 3C).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Additional validated surveys were given to participants to assess perceived stress, well-being, fatigue, physical activity, and cognition; however, no significant changes were observed between the two groups or longitudinally within the groups (data not shown).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Interestingly, while fecal butyrate did not increase significantly cohort-wide during the high-fiber diet intervention, the majority of participants whose butyrate increased while B cell frequency decreased were in the high-fiber diet arm.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Systems-level microbiome and immune system longitudinal profiling as a method for revealing coordinated host-microbe relationships
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
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In the paper
“The majority of correlations between CAZymes and disease-associated proteins were negative, with proteins assigned to inflammatory response having the highest count of significant correlations (Figure 7B).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Systems-level microbiome and immune system longitudinal profiling as a method for revealing coordinated host-microbe relationships
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We additionally assessed gender, race, and BMI as covariates in the model of alpha diversity and time, but none were significantly associated (LME, p > 0.05).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
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In the paper
“Interestingly, while the total number of fermented food servings consumed per day was positively correlated with alpha diversity, the number of servings of yogurt or vegetable brine drinks was most strongly correlated (Figure 5C).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, while the number of servings of fermented food consumed was correlated to an increase in diversity, this relationship was not as strong as the relationship between diversity and time (Figure 5C).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Analysis of CyTOF data to identify the frequency of a larger set of immune cell types revealed that effector memory CD4+ T cells increased, and non-classical monocytes decreased during the intervention (Figure 6C, S3).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake decreases markers of host inflammation
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While there was not a significant difference in microbiota alpha diversity between the ‘high-inflammation” and “low-inflammation i” groups (p-value=0.096), there was a trend towards increasing microbiota diversity in the “low-inflammation group i” that followed the intermediate inflammatory response observed.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
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In the paper
“Anaerostipes had a significant joint p-value in the ZIBR model (Table S7) and was previously described as a “hyper-butyrate producer” (2014).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
What the sources say
- Not checked yetcites [2014]
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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In the paper
“Thirty eight correlations were statistically significant (Pearson, adjusted p-value ≤ 0.05, Benjamini-Hochberg correction), 18 of which were positive and 20 of which were negative (Figure S6B).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake decreases markers of host inflammation
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These clusters were driven by observed changes in endogenous signaling, most notably decreasing signaling in two clusters (“low-inflammation i” and “low-inflammation ii”), as opposed to an increase in signaling in the “high-inflammation” cluster.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was a modest difference in a Lachnospiraceae taxon between the two low-inflammation clusters.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the model comparing high-inflammation and low-inflammation i, the inflammation group factor was significant (p-value = 7.2e-4), but the time variable was not (p-value = 0.69).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Importantly, high-fiber consumption did appear to increase stool microbial protein density, carbohydrate-degrading capacity, and altered SCFA production”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Fiber-rich foods contain microbiota-accessible carbohydrates that serve as a fermentable carbon source for the microbiota.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Nine ASVs increased over time, all in the Firmicutes phylum, including four in the Lachnospiraceae family, two in the Ruminococcaceae family, and one in the Streptococcaceae family (Figure 5D).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Specifically, there were decreased levels of activation in 14 of the 60 different cell type-specific signaling responses, and only one signaling increase (Figure 6B).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake decreases markers of host inflammation
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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In the paper
“There was no difference in alcohol consumption between arms at baseline, nor did alcohol consumption significantly change over the course of the study (LME, p > 0.05).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The other two models did not have significant p-values.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, in the fermented food diet arm, the relative abundance of only 8 CAZymes (3 of which were annotated as starch-degrading and 5 annotated as plant-degrading) differed and all decreased in the maintenance phase relative to baseline.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, no differences in total fiber intake were observed between inflammation clusters, nor were there significant differences in BMI (t-test, p-value > 0.05).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The magnitude of these changes were not significantly different between binned “high” and “low” fermented food consumers (t-test, adjusted p-value > 0.05, n = 19), nor did any change correlate with BMI.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake decreases markers of host inflammation
Strength:plain· not yet calibratedn = 19Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The recursive feature random forest models returned the minimum feature set needed for highest accuracy (Table S5).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Out of 92 proteins, 67 were detected in >75% of samples and used in analysis.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Significant correlations (p-value adjusted ≤ 0.05) shown in Figure S6B.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“A 2-week food exchange study in which African Americans consumed a rural African diet and rural Africans ate a typical African American diet revealed measurable changes to the microbiota and markers of cancer risk despite the brevity of the dietary intervention (O’Keefe et al., 2015).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites O’Keefe et al., 2015 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These results suggest that fermented foods may be powerful modulators of the human microbiome-immune system axis and may provide an avenue to combat NCCDs.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Non-communicable chronic diseases are largely driven by chronic inflammation and their rates are increasing with industrialization.
- Rests on an assumption: The human microbiome influences inflammatory status.
In the paper
“These findings and the shortfall between fiber consumption in the average American diet versus recommended levels suggest that boosting fiber intake could be a powerful way to modulate the human immune system via the microbiota (Deehan and Walter, 2016).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites Deehan and Walter, 2016
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“These data suggest the carbohydrate degradation by participants’ microbiota was insufficient to process the increased fiber consumption, consistent with analyses of industrialized microbiome (Smits et al., 2017; Vangay et al., 2018).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They may also provide compensatory exposure to safe environmental and foodborne microbes that have been lost over the course of sanitizing the industrialized environment.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given that fermented foods have historically been part of many diets around the world, consuming fermented foods may offer an effective way to reintroduce evolutionarily important interactions.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Fermented foods, such as kombucha, yogurt, and kimchi, have gained popularity as reports of potential health benefits in animal models and humans have emerged (Dimidi et al., 2019; Villarreal-Soto et al., 2020).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Short-term changes in diet during prospective dietary intervention studies have also been shown to rapidly change the human gut microbiota (David et al., 2014).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites David et al., 2014 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Elevated isobutyric and isovaleric acid have been associated with hypercholesterolemia (Granado-Serrano et al., 2019) and elevated valeric acid in autism spectrum disorder (Liu et al., 2019).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fiber intake shifts carbohydrate processing capacity and metabolic output of the microbiota
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Its increase could indicate increased epithelial cell turnover within the small intestine in the high-fermented food diet cohort (Benesh et al., 2010).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
What the sources say
- Not checked yetcites Benesh et al., 2010 source
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In other words, an individual’s microbiota composition became more similar to that of other participants within the same arm over the intervention, despite retaining the strong signal of individuality.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Large cohort studies as well as limited interventional studies have linked the consumption of fermented foods with weight maintenance and decreased diabetes, cancer, and cardiovascular disease risks (Mozaffarian et al., 2011; Díaz-López et al., 2016; Gille et al., 2018).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The importance of the gut microbiota, or microbiome, in human health (Lynch and Pedersen, 2016) necessitates enhanced understanding of the factors that influence the composition and function of this microbial community.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites Lynch and Pedersen, 2016 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Dietary interventions that specifically alter dietary fiber, such as increases in total carbohydrates, whole grains, and resistant starch versus wheat bran consumption, have shown impacts on the microbiota along with improvements in health markers of the study participants (Duncan et al., 2007; Martínez et al., 2013; Walker et al., 2011).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“A recent longitudinal study of a subset of American Gut Project participants found differences in microbiota composition and fecal metabolome among fermented food consumers vs. non-consumers (Taylor et al., 2020).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites Taylor et al., 2020
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Lachnospira has been positively associated with high dietary fiber consumption in a human prospective study (Lin et al., 2018).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > A high-fiber diet and a high fermented foods diet result in distinct effects on the gut microbiota and host immune system
What the sources say
- Not checked yetcites Lin et al., 2018 source
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The integration of the gut microbiota into human biology suggests that manipulation of gut microbes may be a powerful means to alter diverse aspects of human health.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
None of the sources cited for this claim have been checked yet.
In the paper
“Rapid “westernization” of the microbiota has been observed in U.S. immigrants, with loss of microbial functions and taxa accompanied by deteriorating markers of host health, increased BMI, and rising inflammatory markers typical in industrialized populations (Vangay et al., 2018; Sonnenburg and Sonnenburg, 2019).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Although, we and others have reported a general resilience of the human microbiota over short time periods (days to months) coupled with retention of highly individualized microbiome identities (Wu et al., 2011; Fragiadakis et al., 2020).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Introduction
What the sources say
- Not checked yetcites Wu et al., 2011
- Not checked yetcites Fragiadakis et al., 2020 source
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“One participant dropped out of the study due to personal reasons and two participants were prescribed antibiotics during the course of the study and were excluded from analysis. The final count for participants was identical in each arm, n=18.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Participants successfully increased their assigned dietary fiber or fermented food consumption over the course of the study.
Strength:plain· not yet calibratedn = 18Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“P-values for all ASVs in association with time were adjusted for multiple hypothesis testing using a Benjamini-Hochberg correction.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“p-values were corrected using Benjamini-Hochberg hypothesis correction.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In analyses comparing different data types to each other, parameters were centered and scaled (across columns) to eliminate experimental bias.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Trial was registered at ClinicalTrials.gov, identifier: NCT03275662.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > EXPERIMENTAL MODEL AND SUBJECT DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The dietary intervention phase was performed over a 4 week ramp period and a 6 week maintenance period; we do not know the durability of many of the changes we observed or if further changes would arise during a longer intervention.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion > Limitations of the Study
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“It is important to note that our findings for these foods may not directly reflect the composition of the exact foods (e.g., due to batch variation) eaten by the participants, who purchased their own fermented food.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A simple randomization was done for the two groups using a random number generator (Excel), performed by a statistician not involved in the intervention or data collection.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“indicating that microbiome remodeling was occurring within the study time frame, just not through an increase in total species.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Fiber-rich foods contain microbiota-accessible carbohydrates that serve as a fermentable carbon source for the microbiota.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Taken together, these data suggest divergent immune system responses to the high-fiber intervention, with “high-inflammation” participants exhibiting broad increases in steady-state immune activation versus “low-inflammation” participants exhibiting decreases in steady-state immune activation.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The study was performed among healthy individuals; future work should examine the effects of these diets in the context of disease or inflammatory conditions”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion > Limitations of the Study
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The slow and steadily increasing diversity suggests a time element for remodeling of the microbiome composition through diet, consistent with the relative recalcitrance of the human microbiota to rapid diet-induced remodeling (Wu et al., 2011).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion
What the sources say
- Not checked yetcites Wu et al., 2011
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These data support that fermented food consumption has an indirect effect on microbiota diversity, rendering the microbiota receptive to the incorporation or increased representation of previously undetected strains within the gut.”
- Also stated in: § Discussion · hedged
“Notably, the new taxa contributing to the increased diversity were largely not from the fermented foods themselves, indicating an indirect effect of their consumption on remodeling the microbiota.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Fermented food intake increases microbiota diversity
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The gut microbiota modulates chronic inflammation or immune status.
- Also stated in: § Discussion · hedged
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Only participants that were randomized were included in calculation of primary outcome (two participants in the high-fiber diet excluded).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedn = 2Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The following validated health surveys were used by participants: PROMIS v1.1 global health, PROMIS v1.0 - fatigue, WHO well-being index, PROMIS applied cognition short form, Perceived Stress Scale (Cohen et al., 1983), and the International Physical Activity Questionnaire (Craig et al., 2003).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
What the sources say
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Because samples from the same participant are not independent from one another and introduces autocorrelation, we used the participant term as a random variable in the lme function using the nLME package in R.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Two participants requested to be placed on the high-fiber diet and were non-randomized.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedn = 2Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Finally, while current data demonstrates a profound effect of these diets on both the microbiome and immune status, further work must examine causality of these interrelated aspects of human biology with an emphasis on the mechanistic underpinnings using additional experimental models.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion > Limitations of the Study
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Taxa with significant baseline coefficients were filtered out to focus on the significant differences induced by the dietary intervention (Table S7).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The study included a modest number of participants (n = 18/arm) which limits statistical power and presents challenges with regard to generalizability of results.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion > Limitations of the Study
Strength:plain· not yet calibratedn = 18Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The study was approved annually by the Stanford University Human Subjects Committee.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > EXPERIMENTAL MODEL AND SUBJECT DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These associations suggest that CAZymes and host proteins may respond to dietary interventions in coordinated yet opposing directions (i.e., increased CAZyme abundance correlates with decreased levels of inflammation-associated proteins) and may serve as a direct link between diet, the microbiome and host physiology.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Systems-level microbiome and immune system longitudinal profiling as a method for revealing coordinated host-microbe relationships
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To determine if the high-fiber and high-fermented food diet arms were significantly different at baseline, the samples were filtered to week −2, β-diversity was calculated, and the analysis of variance using distance matrices was calculated with the adonis function (method = “euclidean”) in the vegan package in R (version 2.5.6).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In other words, as participants’ microbiome CAZymes increase in relative abundance they may exhibit a decrease in basal inflammatory status combined with being less responsive after cytokine stimulation.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > Systems-level microbiome and immune system longitudinal profiling as a method for revealing coordinated host-microbe relationships
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The study had no control arm, and instead relied upon comparisons between the two dietary arms, and within-participant comparisons over time.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion > Limitations of the Study
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Participants and dieticians could not be blinded to randomization assignments in order to perform and counsel the dietary changes, nor was the study team blinded.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A Statistical Analysis Plan was not pre-published”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Terms for gender, race, and BMI were included in the model as covariates in the analysis of diversity over time.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“Akkermansia has been positively associated with metabolic health (Derrien et al., 2017), but has also been associated with low-fiber diets and is rare in populations consuming traditional diets (Earle et al., 2015; Desai et al., 2016; Smits et al., 2017).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Coprococcus has been associated with higher quality of life indicators and both Ruminococcus and Oscillospira have been associated with improved markers of health including leanness and improved lipid profile (Valles-Colomer et al., 2019; Klimenko et al., 2018; Chen et al., 2020).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Results > High-dimensional immune system profiling reveals sub-types of host responses to fiber intake
What the sources say
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“however multiple hypothesis testing correction was applied as described throughout.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This result is especially striking given that participants in this arm changed little else in their diet and consumed a variety of fermented foods (i.e., some ate mostly fermented dairy products while others ate mostly fermented vegetable products).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > Discussion
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“p-values were adjusted using Benjamini-Hochberg correction.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Significance was assessed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“features were restricted to those in four major cell types (CD4+ T cells, CD8+ T cells, B cells, classical monocytes)”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Samples were excluded if the number of singlets was less than 10,000 cells.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“analysis was performed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For analysis we restricted our feature set to features with an average fold change greater than two.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“filtered to only ASVs present in at least 25% of samples.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Host proteins were filtered to top 75% (230 proteins total) and microbe proteins were filtered to top 50% proteins (2,157 proteins total) with the highest variance across participants.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“16S data were filtered to only ASVs present in at least 25% of samples and rank-normalized within each sample according to the methods described by (Callahan et al., 2017).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
What the sources say
- Not checked yetcites Callahan et al., 2017
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Significance was assessed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✗ Asserted: fails✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Correlations were filtered to only host-microbe comparisons before Benjamini-Hochberg hypothesis correction.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“If a participant did not have both the baseline and end of intervention time point for a given experimental platform they were removed from analysis.”
- Also stated in: § QUANTIFICATION AND STATISTICAL ANALYSIS · plain
“If a participant did not have both the baseline and end of intervention time point for a given experimental platform they were removed from analysis.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § QUANTIFICATION AND STATISTICAL ANALYSIS · plain
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“a recursive feature random forest (caret, rfeControl, number=100, leave one out cross validation) was used.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Since ZIBR cannot handle missing data, missing samples were filled with the average ASV abundance for each group at each timepoint.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Correlations between host proteins and microbe proteins are not shown here as they were derived from the same sample and experimental platform and had inflated internal bias compared to the other cross-omic comparisons.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > QUANTIFICATION AND STATISTICAL ANALYSIS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For significance analysis, participants with missing data were excluded.”
§ Gut Microbiota-Targeted Diets Modulate Human Immune Status > STAR Methods > METHOD DETAILS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
Non-communicable chronic diseases are largely driven by chronic inflammation and their rates are increasing with industrialization.
“Non-communicable chronic diseases (NCCDs) are largely driven by chronic inflammation and rates are increasing rapidly with industrialization.”
The paper relies on this without support.
The human microbiome influences inflammatory status.
“Given that the human microbiome is known to influence inflammatory status, a key question is whether diets that target the gut microbiome can attenuate systemic inflammation in healthy individuals.”
The paper relies on this without support.
Findings in the studied healthy adult cohort can be generalized to industrialized society for the purpose of countering decreased microbiome diversity and increased inflammation.
“Fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in industrialized society.”
The paper relies on this without support.
The gut microbiota modulates chronic inflammation or immune status.
“many NCCDs are driven by chronic inflammation, an immunological state that is modulated by the gut microbiota.”
The paper relies on this without support.
Diet is a major driver of the species and functions in the gut microbiome.
“Extensive data across the field of gut microbiome science has established diet as a major driver of the species and functions that reside within an individual’s gut.”
The paper relies on this without support.
Fiber-rich foods contain microbiota-accessible carbohydrates that serve as a fermentable carbon source for the microbiota.
“Fiber-rich foods contain an abundance of microbiota accessible carbohydrates (MACs), which provide a fermentable carbon source for the microbiota.”
The paper relies on this without support.
Serum cytokine levels and signaling markers reflect host inflammation status.
“Elevated cytokine levels at steady state have been linked to chronic, low-grade inflammation.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Greater microbiota diversity is associated with lower levels of systemic inflammation [74,77] and improvements in conditions such as depression and anxiety [65]”
From Psychobiotic effects on anxiety are modulated by lifestyle behaviors: a randomized placebo-controlled trial on healthy adults (2023) · cites this paper as [74]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Serum baseline is dated to a week without a blood collection
MinorThe metabolomics results place a serum sample at week −2, but the specimen schedule lists the pre-intervention blood collection at week −3 and no collection at week −2.
“Untargeted metabolomics on serum samples at baseline (week −2) and end of maintenance (week 10) was conducted using untargeted, high-throughput liquid chromatography-mass spectrometry (LC-MS).”
“Blood samples were collected at 7 time points: −3 weeks, start of intervention, week 4 (end of ramp-up), week 6, week 8, week 10 (3 time points during maximum intake), and week 14 (end of observation).”
Inflammation-panel analyte counts disagree
MinorThe results describe a panel of 93 measured proteins, while the serum-cytokine methods specify 92 analytes.
“we identified 19 of 93 cytokines, chemokines, and other inflammatory serum proteins that decreased over the fermented food intervention”
“Cytokine data were generated from serum samples submitted to Olink Proteomics for analysis using their provided inflammation panel assay of 92 analytes”
Stool carbohydrate measurement method changes between sections
MinorThe results say stool monosaccharides were measured by HPLC, but the corresponding methods describe GC-MS measurement.
“Carbohydrates were extracted from stool samples, acid-hydrolyzed to release monosaccharides, and then measured using HPLC.”
“Methods for measurement of monosaccharides present in stool samples using GC-MS are described in (DeJongh et al., 1969).”
Food-log frequency during ramp-up is inconsistent
MinorOne methods section says food logs were kept every other week throughout the study; another says they were kept every week during the ramp phase.
“They were asked to keep detailed food logs 3 days per week (2 weekdays and 1 weekend) every other week through the duration of the study.”
“Participants logged all their food and drink intake for 3 days (2 weekdays and 1 weekend) each week during the ramp phase and every other week for the rest of the study using the HealthWatch360 app.”
Citations
Cites
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
A Global Measure of Perceived Stress
Cohen, S., Kamarck, T., & Mermelstein, R. (1983) · Journal of Health and Social Behavior · doi:10.2307/2136404 · Cited by 32,807
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., et al. (2019) · Journal of Open Source Software · doi:10.21105/joss.01686 · Cited by 22,138
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,942
International physical activity questionnaire: 12-country reliability and validity
CRAIG, C. L., MARSHALL, A. L., SJ??STR??M, M., BAUMAN, A. E., BOOTH, M. L., AINSWORTH, B. E., PRATT, M., EKELUND, U., YNGVE, A., SALLIS, J. F., et al. (2003) · Medicine & Science in Sports & Exercise · doi:10.1249/01.mss.0000078924.61453.fb · Cited by 21,619
ggplot2: Elegant Graphics for Data Analysis
Ginestet, C. E. (2011) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/j.1467-985x.2010.00676_9.x · Cited by 14,511
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
Fast and sensitive protein alignment using DIAMOND
Buchfink, B., Xie, C., & Huson, D. H. (2015) · Nature Methods · doi:10.1038/nmeth.3176 · Cited by 14,201
Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., Abraham, J., Adair, T., Aggarwal, R., Ahn, S. Y., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61728-0 · Cited by 14,070
Flagged first, then by citations
2 of the 89 references couldn’t be matched to a known paper.
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Sorted by citations
Short-chain fatty acids: Linking diet, the microbiome and immunity
Mann, E. R., Lam, Y. K., & Uhlig, H. H. (2024) · Nature reviews. Immunology · doi:10.1038/s41577-024-01014-8 · Cited by 1,595
Fermented Foods, Health and the Gut Microbiome
Leeuwendaal, N. K., Stanton, C., O’Toole, P. W., & Beresford, T. P. (2022) · Nutrients · doi:10.3390/nu14071527 · Cited by 496
Microbiome diversity protects against pathogens by nutrient blocking
Spragge, F., Bakkeren, E., Jahn, M. T., Araujo, E. B. N., Pearson, C. F., Wang, X., Pankhurst, L. J., Cunrath, O., & Foster, K. R. (2023) · Science · doi:10.1126/science.adj3502 · Cited by 466
Influence of Foods and Nutrition on the Gut Microbiome and Implications for Intestinal Health
Zhang, P. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23179588 · Cited by 475
Kim, C. H. (2023) · Cellular & Molecular Immunology · doi:10.1038/s41423-023-00987-1 · Cited by 420
The Role of the Gut Microbiota in the Relationship Between Diet and Human Health
Perler, B. K., Friedman, E. S., & Wu, G. D. (2022) · Annual Review of Physiology · doi:10.1146/annurev-physiol-031522-092054 · Cited by 402
Targeting the gut microbiota for cancer therapy
Fernandes, M. R., Aggarwal, P., Costa, R. G. F., Cole, A. M., & Trinchieri, G. (2022) · Nature Reviews Cancer · doi:10.1038/s41568-022-00513-x · Cited by 290
Feeding gut microbes to nourish the brain: unravelling the diet–microbiota–gut–brain axis
Schneider, E., O’Riordan, K. J., Clarke, G. A., & Cryan, J. F. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01108-6 · Cited by 317
Gaur, G., & Gänzle, M. G. (2023) · Current Research in Food Science · doi:10.1016/j.crfs.2023.100448 · Cited by 267
A critical review on interplay between dietary fibers and gut microbiota
Ye, S., Shah, B. R., Li, J., Liang, H., Zhan, F., Geng, F., & Li, B. (2022) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2022.04.010 · Cited by 271
Graham, A. E., & Ledesma‐Amaro, R. (2023) · Nature Communications · doi:10.1038/s41467-023-37891-1 · Cited by 290
Rethinking healthy eating in light of the gut microbiome
Armet, A. M., Deehan, E. C., O’Sullivan, A. F., Mota, J. F., Field, C. J., Prado, C. M., Lucey, A. J., & Walter, J. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2022.04.016 · Cited by 252
Stein-Thoeringer, C. K., Saini, N. Y., Zamir, E., Blumenberg, V., Schubert, M.-L., Mor, U., Fante, M. A., Schmidt, S., Hayase, E., Hayase, T., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02234-6 · Cited by 255
Microbiome-based interventions to modulate gut ecology and the immune system
Hitch, T. C. A., Hall, L. J., Walsh, S. K., Leventhal, G. E., Slack, E. M. C., de Wouters, T., Walter, J., & Clavel, T. (2022) · Mucosal Immunology · doi:10.1038/s41385-022-00564-1 · Cited by 268
Microbiota in inflammatory bowel disease: mechanisms of disease and therapeutic opportunities
Iliev, I. D., Ananthakrishnan, A. N., & Guo, C.-J. (2025) · Nature Reviews Microbiology · doi:10.1038/s41579-025-01163-0 · Cited by 249
Fermented foods and gastrointestinal health: underlying mechanisms
Mukherjee, A., Breselge, S., Dimidi, E., Marco, M. L., & Cotter, P. D. (2023) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-023-00869-x · Cited by 275
Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes
Carter, M. M., Olm, M. R., Merrill, B. D., Dahan, D., Tripathi, S. M., Spencer, S. P., Yu, F. B., Jain, S., Neff, N. F., Jha, A. R., et al. (2023) · Cell · doi:10.1016/j.cell.2023.05.046 · Cited by 233
Self-citationEffect of Dietary Protein and Processing on Gut Microbiota—A Systematic Review
Wu, S., Bhat, Z., Gounder, R., Ahmed, I. A. M., Juhaimi, F. A., Ding, Y., & Bekhit, A. E. A. (2022) · Nutrients · doi:10.3390/nu14030453 · Cited by 244
Leveraging diet to engineer the gut microbiome
Wolter, M., Grant, E. T., Boudaud, M., Steimle, A., Pereira, G. V., Martens, E. C., & Desai, M. S. (2021) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-021-00512-7 · Cited by 211
The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
Kase, B. E., Liese, A. D., Zhang, J., Murphy, E. A., Zhao, L., & Steck, S. E. (2024) · Nutrients · doi:10.3390/nu16071045 · Cited by 221
Ni, Y., Qian, L., Siliceo, S. L., Long, X., Nychas, E., Liu, Y., Ismaiah, M. J., Leung, H., Zhang, L., Gao, Q., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.08.002 · Cited by 237
Diet and Anxiety: A Scoping Review
Aucoin, M., LaChance, L., Naidoo, U., Remy, D., Shekdar, T., Sayar, N., Cardozo, V., Rawana, T., Chan, I., & Cooley, K. (2021) · Nutrients · doi:10.3390/nu13124418 · Cited by 248
Dietary regulation in health and disease
Wu, Q., Gao, Z., Yu, X., & Wang, P. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01104-w · Cited by 190
Western diets and chronic diseases
Adolph, T. E., & Tilg, H. (2024) · Nature Medicine · doi:10.1038/s41591-024-03165-6 · Cited by 224
The maternal gut microbiome in pregnancy: implications for the developing immune system
Koren, O., Konnikova, L., Brodin, P., Mysorekar, I. U., & Collado, M. C. (2023) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-023-00864-2 · Cited by 204
Human immune diversity: from evolution to modernity
Liston, A., Humblet-Baron, S., Duffy, D., & Goris, A. (2021) · Nature Immunology · doi:10.1038/s41590-021-01058-1 · Cited by 187
Global Regulatory Frameworks for Fermented Foods: A Review
Mukherjee, A., Gómez‐Sala, B., O’Connor, E. M., Kenny, J. G., & Cotter, P. D. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.902642 · Cited by 190
Enzymes-Assisted Extraction of Plants for Sustainable and Functional Applications
Štreimikytė, P., Viškelis, P., & Viškelis, J. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23042359 · Cited by 183
Oliver, A., Chase, A. B., Weihe, C., Orchanian, S. B., Riedel, S. F., Hendrickson, C. L., Lay, M., Sewall, J. M., Martiny, J. B. H., & Whiteson, K. (2021) · mSystems · doi:10.1128/msystems.00115-21 · Cited by 171
Luo, A., Xie, Z., Wang, Y., Wang, X., Li, S., Yan, J., Zhan, G., Zhou, Z., Zhao, Y., & Li, S. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104642 · Cited by 169
A high-fiber diet synergizes with Prevotella copri and exacerbates rheumatoid arthritis
Jiang, L., Shang, M., Yu, S., Liu, Y., Zhang, H., Zhou, Y., Wang, M., Wang, T., Li, H., Liu, Z., et al. (2022) · Cellular and Molecular Immunology · doi:10.1038/s41423-022-00934-6 · Cited by 158
Berding, K., Bastiaanssen, T. F. S., Moloney, G. M., Boscaini, S., Strain, C. R., Anesi, A., Long-Smith, C., Mattivi, F., Stanton, C., Clarke, G., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-022-01817-y · Cited by 153
Nutritional regulation of microbiota-derived metabolites: Implications for immunity and inflammation
Arifuzzaman, M., Collins, N., Guo, C., & Artis, D. (2024) · Immunity · doi:10.1016/j.immuni.2023.12.009 · Cited by 159
Gut microbiota shapes cancer immunotherapy responses
Lei, W., Zhou, K., Lei, Y., Li, Q., & Zhu, H. (2025) · npj Biofilms and Microbiomes · doi:10.1038/s41522-025-00786-8 · Cited by 182
Zhang, Y., Wu, Y. Q., Liu, X.-F., Chen, X., & Su, J. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102196 · Cited by 157
The Role of Diet and Gut Microbiota in Regulating Gastrointestinal and Inflammatory Disease
Gill, P. A., Inniss, S., Kumagai, T., Rahman, F. Z., & Smith, A. M. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.866059 · Cited by 164
Role of the microbiota in response to and recovery from cancer therapy
Blake, S. J., Wolf, Y., Boursi, B., & Lynn, D. J. (2023) · Nature reviews. Immunology · doi:10.1038/s41577-023-00951-0 · Cited by 151
Role of dietary fiber in promoting immune health—An EAACI position paper
Venter, C., Meyer, R. W., Greenhawt, M., Pali‐Schöll, I., Nwaru, B. I., Roduit, C., Untersmayr, E., Adel‐Patient, K., Agache, I. O., Agostoni, C. V., et al. (2022) · Allergy · doi:10.1111/all.15430 · Cited by 166
Fermented foods, their microbiome and its potential in boosting human health
Valentino, V., Magliulo, R., Farsi, D. N., Cotter, P. D., O’Sullivan, Ó., Ercolini, D., & Filippis, F. D. (2024) · Microbial Biotechnology · doi:10.1111/1751-7915.14428 · Cited by 170
Control of immunity via nutritional interventions
Collins, N., & Belkaid, Y. (2022) · Immunity · doi:10.1016/j.immuni.2022.01.004 · Cited by 131
Human organoids-on-chips for biomedical research and applications
Wang, H., Ning, X., Zhao, F. H., Zhao, H., & Li, D. (2024) · Theranostics · doi:10.7150/thno.90492 · Cited by 148
Microbiome Assembly in Fermented Foods
Louw, N. L., Lele, K., Ye, R., Edwards, C. B., & Wolfe, B. E. (2023) · Annual Review of Microbiology · doi:10.1146/annurev-micro-032521-041956 · Cited by 138
Duan, Y., Huang, J., Sun, M., Jiang, Y., Wang, S., Wang, L., Yu, N., Peng, D., Wang, Y., Chen, W., et al. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.125953 · Cited by 143
Marco, M. L., Hutkins, R. W., Hill, C., Fulgoni, V. L. I., Cifelli, C. J., Gahche, J. J., Slavin, J. L., Merenstein, D. J., Tancredi, D. J., & Sanders, M. E. (2022) · Journal of Nutrition · doi:10.1093/jn/nxac074 · Cited by 130
Li, Z., Zheng, M., Zheng, J., & Gänzle, M. G. (2023) · Current Opinion in Food Science · doi:10.1016/j.cofs.2023.101007 · Cited by 128
Zhou, X., Shen, X., Johnson, J. S., Spakowicz, D. J., Agnello, M., Zhou, W., Avina, M., Honkala, A. T., Chleilat, F., Chen, S. J., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.02.012 · Cited by 181
The neurovascular unit and systemic biology in stroke — implications for translation and treatment
Tiedt, S., Buchan, A. M., Dichgans, M., Lizasoaín, I., Moro, M. Á., & Lo, E. H. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00703-z · Cited by 135
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Takeuchi, T., Nakanishi, Y., & Ohno, H. (2024) · Annual Review of Immunology · doi:10.1146/annurev-immunol-090222-102035 · Cited by 143
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Jahn, L. J., Rekdal, V. M., & Sommer, M. O. A. (2023) · Cell · doi:10.1016/j.cell.2022.12.002 · Cited by 119
Buhaș, M. C., Gavrilaș, L. I., CANDREA, A. R., Cătinean, A., Mocan, A., Miere, D., & Tataru, A. D. (2022) · Nutrients · doi:10.3390/nu14142970 · Cited by 134
Hill, C., Tancredi, D. J., Cifelli, C. J., Slavin, J. L., Gahche, J. J., Marco, M. L., Hutkins, R. W., Fulgoni, V. L. I., Merenstein, D. J., & Sanders, M. E. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.02.019 · Cited by 117
Wang, X., Cai, Z., Wang, Q., Wu, C., Sun, Y., Wang, Z., Xu, X., Xue, W., Cao, Z., Zhang, M., et al. (2023) · Cell Host & Microbe · doi:10.1016/j.chom.2023.11.005 · Cited by 128
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Chakaroun, R., Olsson, L. M., & Bäckhed, F. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-022-00771-0 · Cited by 131
Xue, H., Liang, B., Wang, Y., Gao, H., Fang, S., Xie, K., & Tan, J. (2024) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.132170 · Cited by 121
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Cox, T. O., Lundgren, P., Nath, K., & Thaiss, C. A. (2022) · Genome Medicine · doi:10.1186/s13073-022-01092-0 · Cited by 119
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Gänzle, M. G., Monnin, L., Zheng, J., Zhang, L., Coton, M., Sicard, D., & Walter, J. (2023) · Annual Review of Food Science and Technology · doi:10.1146/annurev-food-072023-034207 · Cited by 121
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Quinn-Bohmann, N., Wilmanski, T. M., Sarmiento, K. R., Levy, L., Lampe, J. W., Gurry, T., Rappaport, N., Loss, E. O., Venturelli, O. S., Diener, C., et al. (2024) · Nature Microbiology · doi:10.1038/s41564-024-01728-4 · Cited by 125
Bonilla, H. F., Peluso, M. J., Rodgers, K. E., Aberg, J. A., Patterson, T. F., Tamburro, R. F., Baizer, L., Goldman, J. D., Rouphael, N., Deitchman, A. N., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1129459 · Cited by 107
Schnabl, B., Damman, C. J., & Carr, R. M. (2025) · Journal of Clinical Investigation · doi:10.1172/jci186423 · Cited by 133
Sun, J., Chen, F., & Wu, G. (2023) · The ISME Journal · doi:10.1038/s41396-023-01483-0 · Cited by 118
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Gänzle, M. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-11909-y · Cited by 100
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López-Armada, M. J., Fernández-Rodríguez, J. A., & Blanco, F. J. (2022) · Antioxidants · doi:10.3390/antiox11061151 · Cited by 118
Dilmore, A. H., Martino, C., Neth, B. J., West, K., Zemlin, J., Rahman, G., Panitchpakdi, M. W., Meehan, M. J., Weldon, K. C., Blach, C., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13007 · Cited by 108
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Dicks, L. M. T. (2024) · Gut Microbes · doi:10.1080/19490976.2024.2420765 · Cited by 99
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Guan, Z., Xuanqi, Z., Zhu, J., Yuan, W., Jia, J., Zhang, C., Sun, T., Leng, H., Jiang, C., Xu, Y., et al. (2023) · Pharmacological Research · doi:10.1016/j.phrs.2023.106930 · Cited by 106
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Sharma, R., Diwan, B., Singh, B. P., & Kulshrestha, S. (2022) · Food Production Processing and Nutrition · doi:10.1186/s43014-022-00101-4 · Cited by 112
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Dhiman, S., Kaur, S., Thakur, B., Singh, P., & Tripathi, M. (2025) · Fermentation · doi:10.3390/fermentation11060346 · Cited by 108
Zhang, X., Yang, Q., Huang, J., Lin, H., Luo, N., & Tang, H. (2024) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-024-01912-x · Cited by 100
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Wang, X., Yuan, W., Yang, C., Wang, Z., Zhang, J., Xu, D., Sun, X., & Sun, W. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1365554 · Cited by 104
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Routy, B., Jackson, T., Mählmann, L., Baumgartner, C. K., Blaser, M., Byrd, A., Corvaia, N., Couts, K., Davar, D., Derosa, L., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2023.12.003 · Cited by 89
Trouwborst, I., Gijbels, A., Jardon, K. M. C., Siebelink, E., Hul, G. B. J., Wanders, L., Erdõs, B., Péter, S., Singh‐Povel, C. M., den Bosch, J. D. V., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2022.12.002 · Cited by 90
Jiang, Y., Jarr, K. J., Layton, C., Gardner, C. D., Ashouri, J. F., Abreu, M. T., & Sinha, S. R. (2021) · Nutrients · doi:10.3390/nu13030890 · Cited by 97
Self-citationdbCAN-seq update: CAZyme gene clusters and substrates in microbiomes
Zheng, J., Hu, B., Zhang, X., Ge, Q., Yan, Y., Akresi, J. E., Piyush, V., Huang, L., & Yin, Y. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1068 · Cited by 88
Kalkan, A. E., BinMowyna, M. N., Raposo, A., Ahmad, M. F., Ahmed, F., Otayf, A. Y., Carrascosa, C., Saraiva, A., & Karav, S. (2025) · Nutrients · doi:10.3390/nu17081305 · Cited by 116
Park, I., & Mannaa, M. (2025) · Foods · doi:10.3390/foods14132292 · Cited by 104
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Gilbert, J. A., Azad, M. B., Bäckhed, F., Blaser, M. J., Byndloss, M. X., Chiu, C. Y., Chu, H., Dugas, L. R., Elinav, E., Gibbons, S. M., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03615-9 · Cited by 113
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Mousa, W. K., Chehadeh, F., & Husband, S. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.825338 · Cited by 91
Immune regulation of the gut-brain axis and lung-brain axis involved in ischemic stroke
Xie, X., Wang, L., Dong, S., Ge, S., & Zhu, T. (2023) · Neural Regeneration Research · doi:10.4103/1673-5374.380869 · Cited by 87
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Zhang, Y., Thomas, J. P., Korcsmáros, T., & Gul, L. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101738 · Cited by 88
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Olendzki, B. C., Bucci, V., Cawley, C., Maserati, R., McManus, M. M., Olednzki, E., Madziar, C., Chiang, D., Ward, D. V., Pellish, R. S., et al. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2046244 · Cited by 83
Changes of gut microbiota reflect the severity of major depressive disorder: a cross sectional study
Hu, X., Li, Y., Wu, J., Zhang, H., Huang, Y., Tan, X., Wen, L., Zhou, X., Xie, P., Olasunkanmi, O. I., et al. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02436-z · Cited by 93
Rastogi, Y. R., Thakur, R., Thakur, P., Mittal, A., Chakrabarti, S., Siwal, S. S., Thakur, V. K., Saini, R. V., & Saini, A. K. (2022) · International Journal of Food Microbiology · doi:10.1016/j.ijfoodmicro.2022.109666 · Cited by 84
Our extended microbiome: The human-relevant metabolites and biology of fermented foods
Caffrey, E. B., Sonnenburg, J. L., & Devkota, S. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.03.007 · Cited by 87
Self-citationReview of microbiota gut brain axis and innate immunity in inflammatory and infective diseases
Yuan, C., He, Y., Xie, K., Feng, L., Gao, S., & Cai, L. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1282431 · Cited by 87
Shi, Y., Zhong, L., Zhong, H., Zhang, J., Liu, X., Peng, M., Fu, G., & Hu, Y. (2022) · Aquaculture · doi:10.1016/j.aquaculture.2022.738150 · Cited by 75
Distribution and roles of Ligilactobacillus murinus in hosts
Chuandong, Z., Hu, J., Li, J., Wu, Y., Wu, C., Lai, G., Shen, H., Wu, F., Tao, C., Liu, S., et al. (2024) · Microbiological Research · doi:10.1016/j.micres.2024.127648 · Cited by 81
Microbiota-immune-brain interactions: A lifespan perspective
Ratsika, A., Cruz-Pereira, J. S., Lynch, C. M. K., Clarke, G. A., & Cryan, J. F. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.102652 · Cited by 83
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Juarez, V. M., Montalbine, A. N., & Singh, A. K. (2022) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2022.114400 · Cited by 77
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Zsálig, D., Berta, A., Tóth, V., Szabó, Z., Klara, S. M., Figler, M., Pusztafalvi, H., & Polyák, É. (2023) · Applied Sciences · doi:10.3390/app13010610 · Cited by 79
Albrich, W. C., Ghosh, T. S., Ahearn-Ford, S., Mikaeloff, F., Lunjani, N., Forde, B. M., Suh, N., Kleger, G., Pietsch, U., Frischknecht, M., et al. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2073131 · Cited by 72
The Role of Gut Microbiome in Sleep Quality and Health: Dietary Strategies for Microbiota Support
Sejbuk, M., Siebieszuk, A., & Witkowska, A. M. (2024) · Nutrients · doi:10.3390/nu16142259 · Cited by 83
Inflammation and gut dysbiosis as drivers of CKD–MBD
Evenepoel, P., Stenvinkel, P., Shanahan, C. M., & Pacifici, R. (2023) · Nature Reviews Nephrology · doi:10.1038/s41581-023-00736-7 · Cited by 82
Causality of gut microbiome and hypertension: A bidirectional mendelian randomization study
Li, Y., Fu, R., Li, R., Zeng, J., Liu, T., Li, X., & Jiang, W. (2023) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2023.1167346 · Cited by 61
Wang, B., Chen, X., Chen, Z., Xiao, H., Dong, J., Li, Y., Zeng, X., Liu, J., Wan, G., Fan, S., et al. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-022-00911-z · Cited by 70
Soldán, M., Argalášová, Ľ., Hadvinová, L., Galileo, B., & Babjaková, J. (2024) · Nutrients · doi:10.3390/nu16183134 · Cited by 89
Pensinger, D. A., Fisher, A. T., Dobrila, H. A., Treuren, W. V., Gardner, J. O., Higginbottom, S. K., Carter, M. M., Schumann, B., Bertozzi, C. R., Anikst, V. E., et al. (2023) · Infection and Immunity · doi:10.1128/iai.00570-22 · Cited by 68
Self-citation
Metadata
- Authors
- Wastyk, H. C., Fragiadakis, G. K., Perelman, D., Dahan, D., Merrill, B. D., Yu, F. B., Topf, M., Gonzalez, C. G., Van Treuren, W., Han, S., Robinson, J. L., Elias, J. E., Sonnenburg, E. D., Gardner, C. D., & Sonnenburg, J. L.
- Affiliations
- Stanford Medicine (US)
- Chan Zuckerberg Biohub San Francisco (US)
- Corresponding author
- Sonnenburg, Erica D.
- Gardner, Christopher D.
- Sonnenburg, Justin L.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-08
- Volume
- 184
- Issue
- 16
- Pages
- 4137-4153.e14
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC9020749
- OpenAlex
- W3179557623
- Cited by
- 1,385
- References
- 89
- Citations by year
- 2026: 300 · 2025: 349 · 2024: 280 · 2023: 249 · 2022: 175 · 2021: 32
- FWCI
- 58.71
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 369 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Sean N. Parker Center for Allergy and Asthma Research, Stanford University
- National Institutes of Health (T32 AI 7328-29)
- National Science Foundation
- Israel National Road Safety Authority (F32AG062119)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Life Sciences › Agricultural and Biological Sciences › Food Science › Probiotics and Fermented Foods
- Keywords
- gut microbiota, diet, plant fibers, high-fiber diet, fermented foods, immune system, microbiome diversity, carbohydrate-active enzymes, glycan degradation, cytokine response, inflammation, immune profiling, microbiota-immune interactions
- MeSH terms
- Gastrointestinal Microbiome, Fermented Foods, Diet, Dietary Fiber, Feeding Behavior, Female, Humans, Immunity, Inflammation, Male, Middle Aged, Signal Transduction, Biodiversity
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