Single-cell atlas of human liver and blood immune cells across fatty liver disease stages reveals distinct signatures linked to liver dysfunction and fibrogenesis

May combine two claims.

Differential gene expression revealed two TCL1A+CD27− naive B cell populations, including a PLCG2+ naive B cell subset expressing PLCG2, and both naive subsets expressed ICOSLG.

“Differential gene expression analyses revealed two TCL1A+CD27− naive B cell populations37, including a transitioning subset (PLCG2+ naive B cells) expressing PLCG2, which facilitates the development of mature B cells upon B cell receptor (BCR) activation38, where both naive B cell subsets expressed ICOSLG (Fig. 6c–e).”

• cites [37] Stewart, A. et al. Single-cell transcriptomic analyses define distinct peripheral B cell subsets and discrete development pathways. Front. Immunol. 12, 602539 (2021). sourceDisputed

  The Results (B Cell Subsets; page unavailable) distinguish transitional and naive cells and report TCL1A expression in both, rather than identifying two naive populations. The Discussion (page unavailable) describes the transitional and naive populations as transcriptionally homogeneous. The cited paper therefore does not support the claim that differential expression revealed two TCL1A+CD27− naive populations. (LLM, conf=0.86)

  Checked by a reasoning model — may be wrong.

  Experimental — accuracy not yet measured
• cites [38] Hikida, M., Johmura, S., Hashimoto, A., Takezaki, M. & Kurosaki, T. Coupling between B cell receptor and phospholipase C-gamma2 is essential for mature B cell development. J. Exp. Med. 198, 581–589 (2003). sourceSupported
  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

cDC1s expressed XCR1, the receptor for lymphotactins XCL1 or XCL2, an interaction important for DC-mediated CD8+ T cell cytotoxic immune response.

“Furthermore, cDC1s expressed XCR1 (Fig. 4c,d), encoding the receptor for lymphotactins XCL1 or XCL2, the interaction of which plays an important role in DC-mediated, CD8+ T cell, cytotoxic immune response28.”

• cites [28] Heger, L. et al. XCR1 expression distinguishes human conventional dendritic cell type 1 with full effector functions from their immediate precursors. Proc. Natl Acad. Sci. USA 120, e2300343120 (2023). sourcePartly supported

  The Results section (‘Human cDC1 Contain XCR1+ and XCR1− Cells’; page unavailable) confirms that human cDC1 include an XCR1-expressing subset. The Discussion (page unavailable) describes an important role for the XCR1–XCL1 interaction in cytotoxic CD8+ T-cell responses, drawing on murine findings. Our copy does not identify XCL2 as an XCR1 ligand, and its human in-vitro results found comparable CD8+ T-cell cross-priming by XCR1+ and XCR1− cDC1. (LLM, conf=0.86)

  Experimental — accuracy not yet measured

May combine two claims.

Human single-cell data in MASLD/MASH are mostly derived from mouse models, and analogous human data come from available datasets or less well-stratified cohorts, often from liver tissue or biopsies requiring digestion and flow-based immune enrichment.

“Analogous human data are either compiled from available datasets or less well-stratified cohorts, most of which are derived from liver tissue or biopsies that require digestion and flow cytometry-based enrichment of immune cells5.”

• cites [5] Guilliams, M. et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell 185, 379–396.e38 (2022). sourcePartly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured

• AssumptionRests on an assumption: Most single-cell data in the MASLD/MASH field are derived from mouse models.

May combine two claims.

pDCs were enriched in proinflammatory genes MZB1, SPIB, and UGCG, enabling high IFNα secretion, and expressed TLR7 and GZMB.

“Differential gene analyses showed that pDCs were enriched in proinflammatory genes (MZB1, SPIB and UGCG), enabling them to secrete high amounts of IFNα and genes such as TLR7 and GZMB27, reported to mediate inflammation resolution and suppression of T cell expansion, respectively (Fig. 4c,d).”

• cites [27] Jahrsdörfer, B. et al. Granzyme B produced by human plasmacytoid dendritic cells suppresses T-cell expansion. Blood 115, 1156–1165 (2010). sourceSupported

May combine two claims.

CCL5+HOPX+ TH1 cells show similar positive trends with fibrosis in both compartments, and RTKN2+CCR7lo memory Treg cells show similar trends in the liver.

“with similar trends in CCL5+HOPX+ TH1 cells in both compartments and RTKN2+CCR7lo memory Treg cells in the liver (Fig. 5g)”

• cites [32] Rau, M. et al. Progression from nonalcoholic fatty liver to nonalcoholic steatohepatitis is marked by a higher frequency of Th17 cells in the liver and an increased Th17/resting regulatory T cell ratio in peripheral blood and in the liver. J. Immunol. 196, 97–105 (2016). sourceNot checked — no full text of the source
• cites [33] Woestemeier, A. et al. Multicytokine-producing CD4+ T cells characterize the livers of patients with NASH. JCI Insight 8, e15381 (2023). sourceCould not verify

  The Results section on fibrotic NASH livers reports an association between fibrosis and Th17-polarized CD4+ T cells, not the specified TH1 or memory Treg subsets. Searches for HOPX, RTKN2, and the named subset markers found no passage establishing the claimed trends in either compartment. Page numbers are unavailable in our copy. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

HLAhiS100lo cDC2s were enriched in antigen-presenting genes, whereas S100hiHLAlo cDC2s enriched for regulatory genes including TGFBR1 and S100A9, reported to suppress DC cytokine production.

“Although the HLAhiS100lo cDC2 cluster was enriched in antigen-presenting genes, S100hiHLAlo cDC2s enriched for regulatory genes, including TGFBR1 and S100A9, were reported to suppress DC cytokine production29 (Fig. 4c,d).”

• cites [29] Averill, M. M. et al. S100A9 differentially modifies phenotypic states of neutrophils, macrophages, and dendritic cells. Circulation 123, 1216–1226 (2011). sourceSupported

May combine two claims.

Trajectory analyses placed immature monocytes upstream of S100hi, ISGhi, inflammatory, and intermediate states, with S100hi and inflammatory cells linking most strongly to the differentiating cluster.

“Cluster similarity (partition-based graph abstraction (PAGA)) and pseudotime (slingshot.R)18 analyses indicate that immature monocytes differentiate into S100hi, ISGhi or inflammatory or intermediate monocytes, with S100hi and inflammatory clusters most strongly connecting to the differentiating monocyte cluster (Fig. 2h,i)”

• cites [18] Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genom. 19, 477 (2018). sourceSupported
  Experimental — accuracy not yet measured

May combine two claims.

S100hi monocytes expressed high levels of S100A8/A9/A12 and TLR4 signaling pathways, low MHC-II genes, and had a higher M-MDSC gene signature than other monocyte subtypes.

“S100hi monocytes (CD14 +S100hiHLAlo), which showed high expression of alarmins S100A8/A9/A12, TLR4 signaling pathways and low expression of MHC-II genes, characteristic of an M-MDSC signature14, and showed higher expression of the M-MDSC gene signature15 compared with other monocyte subtypes (Fig. 2e and Extended Data Table 2).”

• cites [14] Ray, A., Chakraborty, K. & Ray, P. Immunosuppressive MDSCs induced by TLR signaling during infection and role in resolution of inflammation. Front. Cell. Infect. Microbiol. 3, 52 (2013). sourcePartly supported

  Table 1 (MDSCs in cancer and infection; page unavailable) identifies human monocytic MDSCs as CD14+ and HLA-DR-low/negative, supporting the phenotype cited as characteristic of M-MDSCs. The same section links S100A and TLR4 to MDSC accumulation, but does not identify S100A8/A9/A12 expression or a TLR4-pathway gene signature as features of these monocytes. The comparison with other monocyte subtypes is attached to a different citation, not this source. (LLM, conf=0.84)

  Experimental — accuracy not yet measured
• cites [15] Mastio, J. et al. Identification of monocyte-like precursors of granulocytes in cancer as a mechanism for accumulation of PMN-MDSCs. J. Exp. Med. 216, 2150–2169 (2019). sourcePartly supported

  In Results, ‘Human monocytic cells contain MLPGs’ (page unavailable), the paper identifies CD14+HLA-DR−/low cells as M-MDSCs, supporting the low-HLA-DR aspect of the cited characterization. It does not establish that S100hi monocytes express S100A8/A9/A12 or TLR4 pathways, or that they have low MHC-II gene expression. The comparison of M-MDSC gene signatures with other monocyte subtypes is attached to citation 15, not this source. (LLM, conf=0.83)

  Experimental — accuracy not yet measured

May combine two claims.

Few MASH patients show fibrosis regression, and the exact drivers of fibrosis progression remain unclear.

“Although several drugs are currently in the pipeline, with resmetirom recently approved for MASH3, most patients do not have evidence of fibrosis improvement and the precise mechanisms driving its progression are incompletely understood.”

• cites [3] Lazarus, J. V. et al. Opportunities and challenges following approval of resmetirom for MASH liver disease. Nat. Med. 30, 3402–3405 (2024). sourceSupported

May combine two claims.

The study found a marked increase in proinflammatory TH1 cell and TH17 cell frequency and function with MASH in the liver and peripheral blood, alongside an increase in RTKN2+CCR7lo memory Treg cells.

“We found a marked increase in proinflammatory TH1 cell and TH17 cell frequency and function with MASH in the liver and peripheral blood, consistent with previous reports32,33, alongside an increase in RTKN2+CCR7lo memory Treg cells”

• cites [32] Rau, M. et al. Progression from nonalcoholic fatty liver to nonalcoholic steatohepatitis is marked by a higher frequency of Th17 cells in the liver and an increased Th17/resting regulatory T cell ratio in peripheral blood and in the liver. J. Immunol. 196, 97–105 (2016). sourceNot checked — no full text of the source
• cites [33] Woestemeier, A. et al. Multicytokine-producing CD4+ T cells characterize the livers of patients with NASH. JCI Insight 8, e15381 (2023). sourcePartly supported

  The Results section reports a more pathogenic Th17 signature in NASH liver cells and an apparent increase in multicytokine-producing CD4+ T cells, but says the sample was too small for a statistical test of that increase. It also reports Th17-cell enrichment in fibrotic NASH livers. The paper does not establish a marked increase in both Th1 and Th17 frequency and function in both liver and peripheral blood. The cited reports support the proinflammatory-cell comparison, not the citing authors’ separate Treg finding. (LLM, conf=0.88)

  Experimental — accuracy not yet measured

May combine two claims.

CD16− NK cells consist of CD16−IL7R+ NK cells with high expression of IL7R, IL18R1, KLRC1, TCF7, CD44, GPR183, SELL, and COTL1, and CD16−IL7R− NK cells containing CD160hiCXCR6hi tissue-resident NK cells that upregulate CMC1, GZMK, and XCL1 and are enriched in liver FNA.

“CD16− (CD56bright) NK cells consisted of a cluster (CD16−IL7R+ NK cells) with high expression of cytokine receptors (IL7R and IL18R1), immunocheckpoint membrane receptor NKG2A (KLRC1), transcription factor (TCF7) and cell migration or tissue-homing genes (CD44, GPR183, SELL and COTL1) and a cluster (CD16−IL7R− NK cells) that contained CD160hiCXCR6hi tissue-resident NK cells that upregulated”

• cites [44] Chen, Y. et al. The potential role of CMC1 as an immunometabolic checkpoint in T cell immunity. Oncoimmunology 13, 2344905 (2024). sourceCould not verify

  Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured
• cites [28] Heger, L. et al. XCR1 expression distinguishes human conventional dendritic cell type 1 with full effector functions from their immediate precursors. Proc. Natl Acad. Sci. USA 120, e2300343120 (2023). sourceCould not verify

  Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

CD160hiCXCR6hi tissue-resident NK cells positively correlate with fibrosis in the liver, whereas other CD16− NK cells correlate positively in the periphery and negatively in the liver.

“CD160hiCXCR6hi tissue-resident NK cells positively correlated with fibrosis in the liver, whereas other CD16− NK cells correlated positively in the periphery and negatively in the liver (Fig. 7g)”

• cites [45] Castriconi, R. et al. Molecular mechanisms directing migration and retention of natural killer cells in human tissues. Front. Immunol. 9, 2324 (2018). sourcePartly supported

  In “Defining dynamics of NK cells in healthy tissues” (page unavailable), the paper describes CXCR6-expressing tissue-resident NK cells in the liver. It does not identify them as CD160hi or report the claimed correlations with fibrosis in the liver or periphery; searches for CD160 and fibrosis returned no such passage. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims. The quote only partly states this claim.

Most identified ligand-receptor interactions were reciprocal and included signaling by chemotaxis, proinflammatory, growth, differentiation, activation, and/or antigen presentation factors, with specific interactions in early MASH versus SS (IL-13-IL-13RA2, BMP2/4-BMPR1/2 or ACVR2A/B, CNTF-CNTFR or LIFR, GAS6-AXL, GH1-GHR, HLA signaling) and in advanced MASH versus early MASH (GDF5/2-BMPR1/2 or AC

“Most identified ligand–receptor interactions were reciprocal (from HSCs to immune cells and from immune cells to HSCs) and included signaling by chemotaxis, proinflammatory, growth, differentiation, activation and/or antigen presentation factors”

• cites [47] Jiang, Y. & Lu, L. New insight into the agonism of protease-activated receptors as an immunotherapeutic strategy. J. Biol. Chem. 300, 105614 (2024). sourceCould not verify

  Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

The study delineated a fibrosis-related enrichment of CD8+ TEM cells harboring an exhausted signature in the liver, whereas CD8+ TEMRA cell frequency increased in peripheral blood with liver steatosis as assessed by CAP.

“We delineated a fibrosis-related enrichment of CD8+ TEM cells harboring a previously reported exhausted signature31,34,35 in the liver, whereas the frequency of CD8+ TEMRA cells increased in the peripheral blood with liver steatosis as assessed by CAP”

• cites [31] Haas, J. T. et al. Transcriptional network analysis implicates altered hepatic immune function in NASH development and resolution. Nat. Metab. 1, 604–614 (2019). sourcePartly supported

  The Results section, “Hepatic CD8 T cells correlate with NASH in human liver” (page unavailable), reports increased hepatic CD8 T cells in NASH and links their numbers to lobular inflammation and ballooning. It does not identify those cells as CD8+ TEM cells with an exhausted signature or report a fibrosis-related enrichment. The paper also does not report an increase in peripheral-blood CD8+ TEMRA frequency with CAP-assessed steatosis. (LLM, conf=0.84)

  Experimental — accuracy not yet measured
• cites [34] Dudek, M. et al. Auto-aggressive CXCR6+ CD8 T cells cause liver immune pathology in NASH. Nature 592, 444–449 (2021). sourcePartly supported

  The Abstract (page unavailable) reports hepatic CD8 T cells with exhaustion (PD1) characteristics, supporting the citation’s reference to a previously reported exhausted phenotype. It does not identify those cells as CD8+ TEM cells or establish a specific exhausted signature in that subset. The fibrosis and CAP findings are framed as the citing authors’ own results, not findings attributed to this source. (LLM, conf=0.82)

  Experimental — accuracy not yet measured
• cites [35] Pfister, D. et al. NASH limits anti-tumour surveillance in immunotherapy-treated HCC. Nature 592, 450–456 (2021). sourceSupported

May combine two claims.

Differential gene expression revealed three CD27+TCL1A− memory B cell populations expressing AIM2, including FCRL5+ memory B cells upregulating FCRL5 and ITGB1+ memory B cells highly expressing S100A4/6/10 and ITGB1.

“It also revealed three CD27+TCL1A− memory B cell populations that expressed the immune sensor AIM2 (ref. 39), including a subset (FCRL5+ memory B cells) that upregulated FCRL5, which encodes a BCR-signaling regulatory protein described to enrich in atypical memory B cells40, and a subset (ITGB1+ memory B cells) that highly expressed proinflammatory genes (S100A4/6/10) and ITGB1, which are involved”

• cites [39] Svensson, A., Patzi Churqui, M., Schlüter, K., Lind, L. & Eriksson, K. Maturation-dependent expression of AIM2 in human B-cells. PLoS ONE 12, e0183268 (2017). sourcePartly supported

  The Results section ('AIM2 is preferentially expressed in adult B-cells'; page unavailable) reports that adult CD27+ memory B cells express AIM2, supporting the point attached to ref. 39. It does not identify three CD27+TCL1A− populations or show AIM2 expression separately in those populations. The FCRL5 and ITGB1 subset descriptions occur after that citation and are not attributed to this source. (LLM, conf=0.86)

  Experimental — accuracy not yet measured
• cites [40] Li, H., Borrego, F., Nagata, S. & Tolnay, M. Fc receptor-like 5 expression distinguishes two distinct subsets of human circulating tissue-like memory B cells. J. Immunol. 196, 4064–4074 (2016). sourceNot checked — no full text of the source
• cites [41] Andreani, V., Ramamoorthy, S., Fässler, R. & Grosschedl, R. Integrin β1 regulates marginal zone B cell differentiation and PI3K signaling. J. Exp. Med. 220, e20220342 (2023). sourceCould not verify

  The Results section on altered transcriptional profiles describes RNA-seq of mouse transitional, follicular and marginal-zone B cells, not the claimed CD27+TCL1A− memory B-cell populations. Searches for AIM2, FCRL5, S100A4/6/10 and ITGB1 did not find a passage in our copy supporting the claimed subsets or their expression profiles. (LLM, conf=0.77)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

TREM2+ LAMs represent an immunosuppressive state and mainly originated from S100A8+ monocytes.

“a report that TREM2+ LAMs represent an immunosuppressive state and mainly originated from S100A8+ monocytes50”

• cites [50] Zhou, L. et al. Integrated analysis highlights the immunosuppressive role of TREM2+ macrophages in hepatocellular carcinoma. Front. Immunol. 13, 848367 (2022). sourceSupported

May combine two claims.

The results suggest the emergence of potentially pathogenic B cell populations with MASLD/MASH progression, including enrichment of naive B cell populations expressing ICOSLG in the liver that possibly drive increased T cell activation via ICOS-ICOSLG interaction, and enrichment of memory B cells and plasma cells in peripheral blood.

“These results suggested the emergence of potentially pathogenic B cell populations with MASLD/MASH progression, including enrichment of naive B cell populations that expressed ICOSLG in the liver and possibly drove increased T cell activation via ICOS–ICOSLG interaction, and enrichment of memory B cells and plasma cells in the peripheral blood”

• cites [42] Maleki, I. et al. Serum immunoglobulin A concentration is a reliable biomarker for liver fibrosis in non-alcoholic fatty liver disease. World J. Gastroenterol. 20, 12566–12573 (2014). sourceCould not verify

  Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured
• cites [43] De Roza, M. A. et al. Immunoglobulin G in non-alcoholic steatohepatitis predicts clinical outcome: A prospective multi-centre cohort study. World J. Gastroenterol. 27, 7563–7571 (2021). sourceCould not verify

  Split into 2 atoms — 0 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 2 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured

Classified as probably not a substantial claim. May combine two claims.

M-MDSCs are known to increase during inflammation and suppress T cell functions.

“M-MDSCs (‘S100hi’ monocytes), which are known to increase during inflammation and suppress T cell functions14.”

• cites [14] Ray, A., Chakraborty, K. & Ray, P. Immunosuppressive MDSCs induced by TLR signaling during infection and role in resolution of inflammation. Front. Cell. Infect. Microbiol. 3, 52 (2013). sourcePartly supported

  The section on MDSC induction by pathogens says inflammation promotes MDSC accumulation, and the section on LPS-induced lung MDSCs says MDSCs inhibit T-cell proliferation and responses. The paper identifies a monocytic MDSC subset, but these passages do not establish that this subset specifically increases during inflammation or identify it as ‘S100hi’ monocytes. No page numbers are available in our copy. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Sample sizes were not predetermined statistically, though they matched those in earlier studies.

“No statistical methods were used to predetermine sample sizes but our sample sizes were similar to those reported in previous publications8.”

• cites [8] Cui, A. et al. Single-cell atlas of the liver myeloid compartment before and after cure of chronic viral hepatitis. J. Hepatol. 80, 251–267 (2024). sourceCould not verify

  The Results section (‘A landscape of intrahepatic myeloid cells defined by scRNA-seq’; page unavailable) gives this paper’s sample counts, but does not say whether the citing study’s sample sizes were statistically predetermined or comparable to its own. I searched the indexed copy for sample-size planning and comparisons with previous publications; the Materials and methods passage points to supplementary information without addressing either point. (LLM, conf=0.72)

  Experimental — accuracy not yet measured

Classified as probably not a substantial claim.

De-differentiation of human macrophages into monocyte-like cells has been shown to be induced by bacterial toxins that elevate cAMP.

“The de-differentiation of human macrophages into monocyte-like cells has been shown to be induced by bacterial toxins that elevate cAMP”

• cites [51] Ahmad, J. N. et al. Bordetella adenylate cyclase toxin inhibits monocyte-to-macrophage transition and dedifferentiates human alveolar macrophages into monocyte-like cells. mBio 10, e01743-19 (2019). sourceSupported
• cites [52] Wahlang, B., McClain, C., Barve, S. & Gobejishvili, L. Role of cAMP and phosphodiesterase signaling in liver health and disease. Cell. Signal. 49, 105–115 (2018). sourceCould not verify

  The section on cAMP in alcoholic liver disease discusses cAMP levels and inflammatory responses in monocytes and macrophages, but not macrophage de-differentiation. Searches for macrophages becoming monocyte-like cells and for cAMP-elevating bacterial toxins found no passage addressing the claimed transformation. (LLM, conf=0.72)

  Experimental — accuracy not yet measured

May combine two claims.

These T cell functional changes were mirrored by decreased frequencies of XCR1+ cDC1s and increased frequencies of cDC2s.

“These T cell functional changes were mirrored by decreased frequencies of XCR1+ cDC1s (which prime CD8+ T cells) and increased frequencies of cDC2s (which prime CD4+ T cells)”

• cites [31] Haas, J. T. et al. Transcriptional network analysis implicates altered hepatic immune function in NASH development and resolution. Nat. Metab. 1, 604–614 (2019). sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Persistent expression of S100A9 in M-MDSC-derived macrophages regulates their suppressive activity via CEBPB.

“Persistent expression of S100A9 in M-MDSC-derived macrophages was reported to regulate their suppressive activity via the transcription factor CEBPB15”

• cites [15] Mastio, J. et al. Identification of monocyte-like precursors of granulocytes in cancer as a mechanism for accumulation of PMN-MDSCs. J. Exp. Med. 216, 2150–2169 (2019). sourceCould not verify

  The Results sections on MLPG identification and human monocytic cells report that M-MDSCs can differentiate into macrophages, but do not address persistent S100A9 expression or regulation of macrophage suppressive activity through CEBPB. Further searches for S100A9 and CEBPB returned no passage establishing that mechanism; the available copy therefore does not verify the attributed claim. Page numbers were not provided. (LLM, conf=0.76)

  Experimental — accuracy not yet measured

May combine two claims.

Genes upstream of IFNα and IFNβ were most highly expressed in pDCs, indicating pDCs were a predominant source of IFNα and IFNβ.

“Expression of genes upstream of IFNα and IFNβ (Extended Data Table 2) were highest in pDCs (Extended Data Fig. 4c), indicating that pDCs were a predominant source of IFNα and IFNβ”

May combine two claims.

Serum sCD163 was higher in MASH than NS-SS and showed positive associations with liver enzymes, stiffness, APRI, and NAS.

“We assessed patient serum levels of the macrophage activation marker sCD163 and found that they positively correlated with liver enzymes, liver stiffness, APRI and NAS, and were higher in patients with MASH compared with those with NS–SS (Extended Data Fig. 1)”

May combine two claims.

Macrophages in advanced versus early MASH showed higher S100A9 and LAM/SAM genes and lower expression of genes for antigen presentation, pattern sensing, phagocytosis control, and removal of damaged proteins.

“Differential gene analysis comparing advanced MASH with early MASH macrophages (MP_0–3) revealed the upregulation of S100A9 and LAM- or SAM-associated genes, as well as downregulation of genes involved in antigen presentation (MHC-I or MHC-II), pattern recognition (C1Qs), phagocytosis regulation (selenoprotein or SELENOP) and damaged protein removal (UBC) (Fig. 3g)”

May combine two claims.

S100A9+CD68+ macrophage fractions were absent in NS and SS, appeared at MASH F1, and rose further at MASH F2.

“the fraction of S100A9+CD68+ macrophages (as a percentage of CD68+ macrophages) was undetectable in NS and SS, emerged in MASH F1 and further increased in MASH F2 (Fig. 3h).”

May combine two claims.

The scRNA-seq dataset contained 168,634 high-quality cells: 52,961 from liver aspirates and 115,673 from blood mononuclear cells.

“We surveyed single-cell transcriptomic (single-cell RNA sequencing (scRNA-seq)) data of 168,634 high-quality cells sequenced immediately after isolation from paired liver FNAs (52,961 cells) and PBMCs (115,673 cells).”

May combine two claims.

The cohort included 25 patients spanning the MASLD/MASH spectrum, with paired liver FNA and PBMC samples.

“We studied immune cells from liver FNAs and the corresponding peripheral blood mononuclear cells (PBMCs) of 25 patients spanning the MASLD/MASH spectrum.”

May combine two claims.

Liver aspirates had more CD16− NK, MAIT, and CD8+ T cells and fewer B cells than blood mononuclear cells.

“Compared with PBMCs, liver FNAs contained higher proportions of CD16− NK cells, MAIT cells and CD8+ T cells and lower proportions of B cells9 (Extended Data Fig. 3a).”

• cites [9] Racanelli, V. & Rehermann, B. The liver as an immunological organ. Hepatology 43, S54–S62 (2006). sourceNot checked — no full text of the source

May combine two claims.

CD8+ TEMRA populations (CD45RA+SELLloGNLYhi TEMRA 1 and CD45RA+SELLloGNLYlo TEMRA 2) decrease in the liver with steatosis grading and increase in the blood with CAP.

“the CD8+ TEMRA populations (CD45RA+SELLloGNLYhi CD8+ TEMRA 1 cells and CD45RA+SELLloGNLYlo CD8+ TEMRA 2 cells) decreased in the liver with steatosis grading and increased in the blood with CAP (Fig. 5g)”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

PreMP_2 cells were more abundant in liver aspirates and had high FOS and FOSB expression, while PreMP_1 and PreMP_3 were more abundant in blood.

“Within the transitioning monocytes (PreMP_1–3), PreMP_2 monocytes (ATP2B1-AS1+S100A12hi) were enriched in liver FNAs and highly expressed proinflammatory genes (FOS and FOSB), whereas PreMP_1 and PreMP_3 were enriched in the periphery (Fig. 3a,b)”

May combine two claims. The quote only partly states this claim.

Participants with MASH had higher liver enzymes ALT and AST, greater FIB-4 and APRI scores, increased liver stiffness by Fibroscan, and higher NAS compared with NS-SS.

“Liver function blood tests for participants with MASH compared with those with NS–SS showed higher liver enzymes (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)), reflecting liver injury, and greater calculated noninvasive fibrosis scores FIB-4 (fibrosis 4 index) and APRI (AST to platelet ratio index)”

• Also stated in: § FNAs are amenable to the study of liver immune cells · plain

  “alongside increased liver stiffness assessed by transient elastography (Fibroscan) and histological nonalcoholic fatty liver disease activity score (NAS) (Extended Data Table 1).”

May combine two claims. The quote only partly states this claim.

Unsupervised clustering and differential gene analysis of T cells identified 14 subsets, including CD4+ naive, central memory, TH1, TH17, cytotoxic T lymphocyte, naive and memory Treg, CD8+ naive, central memory, effector memory, two TEMRA subsets, MAIT, and γδ T cells.

“Unsupervised clustering and differential gene analysis delineated 14 T cell subsets: CD4+ naive T (TN) cells (CCR7hiCD45RA+), CD4+ central memory T (TCM) cells (CD45RO+SELLhi), helper type 1 T (TH1) cells (CCL5+HOPX+) and type 17 T (TH17) cells (KLRB1+RORC+)”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

CD45RO+SELLlo CD8+ TEM cells and KLRB1+SLC4A10+ MAIT cells are enriched in liver FNAs compared with PBMCs.

“Differential abundance analysis between compartments showed that CD45RO+SELLlo CD8+ TEM cells and KLRB1+SLC4A10+ MAIT cells were enriched in liver FNAs compared with PBMCs (Fig. 5f).”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

Liver FNA macrophage clustering identified seven clusters separated into transitioning monocytes (PreMP_1-3) and macrophages (MP_0-3).

“Liver FNAs captured a small number of macrophages (1,434 cells) in which unsupervised clustering and differential gene analyses resulted in seven clusters separated into two distinct groups:”

May combine two claims.

In liver aspirates, immature, S100hi, ISGhi, and differentiating monocyte fractions were higher in MASH than in NS-SS.

“Liver FNA proportions of immature monocytes, S100hi monocytes (M-MDSCs), ISGhi monocytes and differentiating monocytes increased in MASH compared with NS–SS (Fig. 2g)”

May combine two claims.

S100hiHLAlo cDC2s showed enrichment for lipid-metabolism transcription factors, cholesterol-uptake genes, mevalonate/cholesterol pathway genes, and the TCA catalyst IDH1.

“Marker gene analysis showed that S100hiHLAlo cDC2s also enriched for transcription factors of lipid metabolism (SREBF1/2), cholesterol uptake (LDLR), mevalonate or cholesterol pathway genes (HMGCSR, HMGCR, MVD and FDFT1), tricarboxylic acid (TCA) rate-limiting catalyst (IDH1)”

May combine two claims.

NMF11, a T cell activation program expressed across all T cells, positively correlates with steatosis and NAS in the liver.

“Correlation analysis showed NMF11, which represented a T cell activation program expressed across all T cells, positively correlated with steatosis and NAS in the liver (Fig. 5k)”

May combine two claims.

CD45RO+SELLlo CD8+ TEM cells significantly increase in the liver with liver stiffness but decrease in the blood with steatosis grading.

“CD45RO+SELLlo CD8+ TEM cells, which harbored an exhausted phenotype, significantly increased in the liver with liver stiffness but decreased in the blood with steatosis grading”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

Liver FNA samples were cell suspensions that did not require digestion, captured few embedded cells such as hepatocytes, and were naturally enriched for immune cells.

“Liver FNAs consisted of cell suspensions, did not require digestion, captured few embedded cells (for example, hepatocytes) and were, therefore, naturally enriched for immune cells.”

May combine two claims.

Seventeen major cell types were identified and represented in every patient.

“Major cell types, 17 represented in every patient, were identified (Fig. 1b–d):”

May combine two claims.

IFIT3+ and MX1+ macrophage fractions rose from SS to MASH F1 and MASH F2, respectively.

“We found that the proportion of IFIT3+ and MX1+ macrophages, as a fraction of CD68+ cells, increased from SS to MASH F1 and MASH F2, respectively (Extended Data Fig. 4f)”

May combine two claims.

Unsupervised clustering of DCs delineated pDCs, cDC1s, cDC2s, and cDC2s were further divided into HLAhiS100lo and S100hiHLAlo populations.

“Unsupervised clustering delineated three major subsets: pDCs (CLEC4C+), which are potent producers of type 1 IFNs, cDC1s (CLEC9A+), which are specialized in presenting antigens to CD8+ T cells, and cDC2s (CLEC10A+), which present antigens to CD4+ T cells and were further divided into HLAhiS100lo cDC2 and S100hiHLAlo cDC2 populations (Fig. 4a,b).”

May combine two claims.

Hepatic cytotoxic T cell functions increase with inflammation but decrease with fibrosis, and these cells acquire an exhausted signature.

“Hepatic cytotoxic T cell functions increased with inflammation, but decreased with fibrosis, while acquiring an exhausted signature, whereas natural killer cell-driven toxicity intensified.”

May combine two claims.

The study observed marked enrichment of monocyte subsets, monocyte-dominated cell crosstalk (with lymphocytes, DCs, and HSCs) that increased as early as SS, and intensified overall T cell activation with MASH progression in the liver.

“We observed a marked enrichment of monocyte subsets, monocyte-dominated cell crosstalk (with lymphocytes, DCs and HSCs) that increased as early as SS, and intensified overall T cell activation with MASH progression in the liver.”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims. The quote only partly states this claim.

Unilateral ligand-receptor interactions in early MASH versus SS included increased CCL14-CCR1 recruitment signaling from HSCs to immune cells, profibrotic TGFβ signaling from pDCs, MAIT, and CD4+ T cell subsets to HSCs, proinflammatory RETN-TLR4 from monocytes, and apoptotic TRAIL/TNFSF10-TNFRSF10 signaling from CD16−IL7R+ NK cells.

“Unilateral ligand–receptor interactions (from HSCs to immune cells or from immune cells to HSCs) in early MASH versus SS included increased CCL14–CCR1 recruitment signaling from HSCs to immune cells”

• cites [48] Radaeva, S. et al. Natural killer cells ameliorate liver fibrosis by killing activated stellate cells in NKG2D-dependent and tumor necrosis factor-related apoptosis-inducing ligand-dependent manners. Gastroenterology 130, 435–452 (2006). sourceNot checked — no full text of the source

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

Individual ligand-receptor interactions between HSCs and immune cells changed across disease stages, confirming intensified HSC crosstalk with immune cells in early MASH versus SS.

“Individual ligand–receptor interactions between HSCs and immune cells changed across disease stages (Fig. 8c and Extended Data Fig. 8a,b), confirming intensified HSC crosstalk with immune cells in early MASH versus SS.”

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

Liver cytotoxic T cells acquired an exhausted phenotype, whereas NK cell-driven toxicity intensified with fibrosis progression.

“Liver cytotoxic T cells acquired an exhausted phenotype, whereas NK cell-driven toxicity intensified with fibrosis progression.”

May combine two claims.

Inflammatory NMF5, most highly expressed by CD16+CCL4hi NK cells, positively correlates with MASLD/MASH progression measurements in the periphery, whereas immunomodulatory NMF6, most highly expressed by CD16−IL7R+ NK cells, positively correlates with MASLD/MASH progression measurements in the liver.

“inflammatory NMF5 (most highly expressed by CD16+CCL4hi NK cells) positively correlated with MASLD/MASH progression measurements in the periphery, whereas immunomodulatory NMF6 (most highly expressed by CD16−IL7R+ NK cells) positively correlated with MASLD/MASH progression measurements in the liver (Fig. 7k).”

May combine two claims.

In advanced MASH versus early MASH, HSC-to-macrophage signaling involved proinflammatory MIF-(CXCR2 + CD74) to promote macrophage recruitment, whereas TGFβ signaling to HSCs increased from CD45RO+SELLlo CD8 TEM cells.

“In advanced MASH versus early MASH, HSC-to-macrophage signaling involved proinflammatory macrophage migration inhibitory factor (MIF)–(CXCR2 + CD74) to promote macrophage recruitment, whereas TGFβ signaling to HSCs increased from CD45RO+SELLlo CD8 TEM cells (which harbored an exhausted phenotype) (Fig. 8c).”

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

CD16+ NK cell subsets include CD16+CCL4hi NK cells with high expression of CCL3, CCL4, and CCL4L2, CD16+S100B+ NK cells with high GZMH, and CD16+PTGDS+ NK cells with distinct PTGDS expression.

“Their subsets included a cluster (CD16+CCL4hi NK cells) with high expression of proinflammatory chemokines or ligands (CCL3, CCL4 and CCL4L2), a cluster (CD16+S100B+ NK cells) with high expression of GZMH and a cluster (CD16+PTGDS+ NK cells) with distinct expression of a gene involved in prostaglandin metabolism (PTGDS) (Fig. 7d,e).”

May combine two claims.

CD16+ NK cells in liver and blood show increased cytotoxic and inflammatory functions that correlate with histological and noninvasive fibrosis markers.

“This was accompanied by an enrichment in cytotoxic and inflammatory functions in CD16+ NK cells in the liver and blood with histological and noninvasive markers of fibrosis”

May combine two claims.

CellChat analysis predicted that monocytes are the main drivers of cell-to-cell communication, increasing from NS as early as SS and through advanced MASH, whereas lymphocyte interactions peaked in early MASH but decreased in advanced MASH.

“The predicted total number of significant ligand–receptor interactions for each pair of cell types indicated that monocytes were the main drivers of cell-to-cell communication, increasing from NS as early as in SS and through advanced MASH, whereas lymphocyte interactions peaked in early MASH but decreased in advanced MASH (Fig. 8a).”

• cites [46] Jin, S., Plikus, M. V. & Nie, Q. CellChat for systematic analysis of cell-cell communication from single-cell transcriptomics. Nat. Protoc. 20, 180–219 (2025). sourceNot checked — no full text of the source

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

JCHAIN+IGHhi plasma cells express TNFRSF17 and FKBP11, positively correlate with MASLD/MASH progression measurements in peripheral blood, and are enriched in the liver compared to blood.

“JCHAIN+IGHhi plasma cells expressed genes essential for their maturation and proper assembly or secretion of antibodies (TNFRSF17 and FKBP11), were positively correlated with MASLD/MASH progression measurements in peripheral blood (Fig. 6f), and enriched in the liver compared to the blood (Fig. 6g).”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

HSC crosstalk with monocytes, macrophages, and cDC2s increases with disease progression, whereas interactions with other immune cells peak in early MASH compared with SS and advanced MASH.

“Comparison across disease stages showed that HSC crosstalk with monocytes, macrophages and cDC2s increased with disease progression, whereas interactions with other immune cells peaked in early MASH compared with SS and advanced MASH (Fig. 8b).”

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

CD8+ T cell subsets in the liver FNA dataset showed cytotoxic activity that positively correlated with patient liver inflammation scores but negatively correlated with histological and noninvasive markers of fibrosis.

“The CD8+ T cell subsets in our liver FNA dataset showed cytotoxic activity that positively correlated with patient liver inflammation scores, but negatively correlated with histological and noninvasive markers of fibrosis”

• AssumptionRests on an assumption: The single-cell transcriptomic profiles from liver fine-needle aspirates are representative of the whole liver immune microenvironment.

May combine two claims.

Cytotoxic programs NMF1, NMF2, and NMF4 are enriched in CD16+ NK cell subsets and positively correlate with MASLD/MASH progression measurements in the liver (NMF4) and periphery (NMF2).

“Cytotoxic programs (NMF1, NMF2 and NMF4) were enriched in CD16+ NK cell subsets and positively correlated with MASLD/MASH progression measurements in the liver (NMF4) and the periphery (NMF2) (Fig. 7k).”

May combine two claims.

CD16+ NK cells have low expression of NCAM1 (CD56dim) and high expression of CX3CR1 and cytotoxic factors PRF1, GZMA, GZMB, GZMH, and FGFBP2.

“Differential gene expression analyses revealed that CD16+ NK cells had low expression of NCAM1 (CD56dim) and high expression of chemotaxis (CX3CR1) and cytotoxic (PRF1, GZMA, GZMB, GZMH and FGFBP2) factors (Fig. 7d,e).”

May combine two claims.

MP_0 macrophages had higher MHC-II expression yet resembled transitioning monocytes, suggesting they were differentiating macrophages.

“MP_0 macrophages (TUBA1BhiHLAhi) upregulated MHC-II but shared features with transitioning monocytes, likely representing differentiating macrophages (Fig. 3b)”

May combine two claims.

The authors concluded that monocyte recruitment to the liver rises with MASLD/MASH progression and that S100hi monocytes contribute to fibrogenesis.

“increased recruitment of monocytes to the liver with MASLD/MASH progression and pinpointed S100hi monocytes (M-MDSCs) as contributors to liver fibrogenesis.”

May combine two claims.

The cohort groups did not differ significantly in age, race, or sex, and had comparable body mass indices.

“Analysis of demographic data between these groups showed no significant differences in age, race and sex, and the groups had comparable body mass indices (Extended Data Table 1).”

May combine two claims.

The authors inferred that ongoing inflammation enriches immunosuppressive S100A9+ macrophages, which may then drive fibrosis in advanced MASH.

“Together, our results indicated the enrichment of immunosuppressive S100A9+ macrophages in response to continuous inflammation, which could further promote fibrosis in advanced MASH.”

May combine two claims.

The authors concluded that the cohort's biochemical profile matched MASLD/MASH and that it represented the affected population.

“These characteristics demonstrated typical biochemical features of MASLD/MASH, indicating that our cohort was representative of the MASLD-affected population.”

May combine two claims.

The results indicate enrichment of proinflammatory CD4+ T cell subsets (TH17 and TH1) with parallel enrichment of immunoregulatory memory Treg cells and exhausted CD8+ TEM cells with MASLD/MASH progression, and overall loss of cytotoxic T cell functions as liver fibrosis progresses.

“These results indicated enrichment of proinflammatory CD4+ T cell subsets (TH17 cells and TH1 cells) with parallel enrichment of immunoregulatory memory Treg cells and exhausted CD8+ TEM cells with MASLD/MASH progression and overall loss of cytotoxic T cell functions as liver fibrosis progressed”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The design was cross-sectional and treatment-free.

“This was a cross-sectional study (involving all 25 patients in each transcriptomic analysis), which did not involve treatment”

May combine two claims.

These phenomena indicate recruitment and activation of the mononuclear phagocytic system in the liver, possibly initiated by chemotactic hepatocyte stress responses, where enriched monocytes prime or suppress T cell responses.

“These phenomena indicate recruitment and activation of the mononuclear phagocytic system in the liver, possibly initiated by chemotactic hepatocyte stress responses, where enriched monocytes prime or suppress T cell responses.”

May combine two claims.

During MASH, T cells shift away from antigen-specific cytotoxic functions, which may increase susceptibility to infections or liver cancer.

“These observations indicate a shift from the antigen-specific, cytotoxic functions of T cells during MASH that could contribute to increased vulnerability during infections or toward developing liver cancer.”

May combine two claims. The quote only partly states this claim.

This NK cell interaction is beneficial and antifibrotic.

“A beneficial, antifibrotic NK cell interaction”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

The peripheral blood frequency of XCR1+ cDC1s has been reported to be greater in patients with MASLD/MASH.

“the peripheral blood frequency of XCR1+ cDC1s has been reported to be greater in patients with MASLD/MASH”

Probably not a substantial claim: may not pass S3 (load-bearing).

Peripheral blood XCR1+ cDC1 frequency is greater in MASLD/MASH patients than healthy controls.

“Of note, the peripheral blood frequency of XCR1+ cDC1s has been reported to be greater in patients with MASLD/MASH compared with healthy controls53”

• cites [53] Deczkowska, A. et al. XCR1+ type 1 conventional dendritic cells drive liver pathology in non-alcoholic steatohepatitis. Nat. Med. 27, 1043–1054 (2021). sourceNot checked — no full text of the source

May combine two claims.

The analysis suggests that reciprocal interactions, in which HSCs activated immune cells and influenced their recruitment and phenotype and immune cells modulated HSC activation and fibroblast proliferation, changed across MASLD/MASH stages.

“our analysis suggested that reciprocal interactions, in which HSCs activated immune cells and influenced their recruitment and phenotype and, in turn, immune cells modulated HSC activation and fibroblast proliferation, changed across MASLD/MASH stages.”

• AssumptionRests on an assumption: Predicted ligand–receptor interactions from CellChat reflect actual cell–cell communication in vivo.

May combine two claims.

XCL1/2 attracts XCR1+ cDC1s, possibly as a mechanism to restore CD8+ T cell priming.

“which recruits XCR1+ cDC1s and could represent an attempt to rescue CD8+ T cell priming.”

Probably not a substantial claim: may not pass S3 (load-bearing).

High B2M expression across all samples supported data quality.

“Cells across all samples highly expressed the housekeeping gene, B2M, confirming the quality of our data”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Pathway enrichment used clusterProfiler and Gene Ontology Biological Processes, with significance at Benjamini-Hochberg-corrected P < 0.05.

“We used the R package clusterProfiler to visualize pathway enrichment assessed by the enrichGO function and the Gene Ontology Biological Processes database. All pathways shown are significant, according to the Benjamini–Hochberg-corrected P < 0.05.”

Classified as probably not a substantial claim. May combine two claims.

Clusters were annotated using DEGs and validated by transferring labels from the Azimuth PBMC reference.

“These clusters were annotated according to differentially expressed genes (DEGs) and verified by annotation transfer of established expert annotations of human single-cell data in the Azimuth PBMC reference dataset.”

Classified as probably not a substantial claim. May combine two claims.

Eligible patients were at least 18 years old, had fatty liver on imaging, and could give informed consent.

“Inclusion criteria comprised age ≥18 years, fatty liver infiltration on ultrasound, computed tomography scan or magnetic resonance imaging and the ability to provide informed consent.”

Classified as probably not a substantial claim. May combine two claims.

Two single-blinded pathologists reviewed each biopsy (requiring >15 mm or >10 portal tracts), and discordant staging was resolved by taking the higher score.

“Each liver biopsy (with >15 mm length or >10 portal tracts) was reviewed by 2 single-blinded liver pathologists at Massachusetts General Hospital. When staging differed, the more advanced scoring was considered.”

Classified as probably not a substantial claim. May combine two claims.

Patients were excluded for hepatitis B, C, or HIV, other chronic liver diseases, steatogenic drugs, or heavy alcohol use.

“Exclusion criteria included infection with hepatitis B virus, HCV or HIV, or other causes of chronic liver disease, including steatogenic medications and significant alcohol consumption”

Probably not a substantial claim: may not pass S3 (load-bearing).

Every patient provided written informed consent prior to enrollment.

“All patients gave written consent before participation.”

Classified as probably not a substantial claim. May combine two claims.

Filtering removed cells with low library size, genes in fewer than three cells, mitochondrial content above 35%, and doublets.

“cells with a library size <25%, genes detected in <3 cells, cells with mitochondrial content >35% and doublets were excluded.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The Mass General Brigham Institutional Review Board and the sponsor approved the study.

“approved by the Mass General Brigham Institutional Review Board and the sponsor.”

Probably not a substantial claim: may not pass S3 (load-bearing).

AUCell computed gene set enrichment scores using Reactome-derived signatures.

“We utilized the AUCell R package to calculate gene set enrichment scores8. Gene sets used for these analyses were derived from the Reactome database”

Classified as probably not a substantial claim.

Batch effects were corrected using Harmony.

“The Harmony algorithm was applied to correct for batch effects”

Classified as probably not a substantial claim.

CellChat inferred ligand-receptor interactions from expression of known pairs.

“Ligand–receptor interactions between hepatic cell populations were inferred using the CellChat R package based on the expression of known ligand–receptor pairs”

• AssumptionRests on an assumption: Inferred ligand–receptor interactions from expression data reflect actual intercellular signaling.