The DOI matches its Crossref record; 48 of the 50 references it cites were found in a registry or an index; none of the 16 sources its claims cite is checked for support yet.
Large-Scale Cellular-Resolution Gene Profiling in Human Neocortex Reveals Species-Specific Molecular Signatures
Open accessAbstract
Summary Although there have been major advances in elucidating the functional biology of the human brain, relatively little is known of its cellular and molecular organization. Here we report a large-scale characterization of the expression of ~1,000 genes important for neural functions, by in situ hybridization with cellular resolution in visual and temporal cortices of adult human brains. These data reveal diverse gene expression patterns and remarkable conservation of each individual gene’s expression among individuals (95%), cortical areas (84%), and between human and mouse (79%). A small but substantial number of genes (21%) exhibited species-differential expression. Distinct molecular signatures, comprised of genes both common between species and unique to each, were identified for each major cortical cell type. The data suggest that gene expression profile changes may contribute to differential cortical function across species, in particular, a shift from corticosubcortical to more predominant corticocortical communications in the human brain.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
Large-scale in situ hybridization profiled ~1,000 genes at cellular resolution in adult human visual and mid temporal cortex, revealing high conservation across individuals, cortical areas, and human-mouse but also species-differential expression. The data identify distinct molecular signatures for major cortical cell types and suggest gene expression changes may contribute to differential cortical function, including a shift toward corticocortical communication in human.
Key findings
- Of 995 genes assayed, 79% were expressed above background; expression was consistent for 95% of genes among individuals, 84% across cortical areas 17, 18, and 21, and 79% between human and mouse.
- A small but substantial fraction varied: 5% of genes showed donor variation, 16% differed across the three cortical areas, and 21% (199 genes) showed moderate or marked human-mouse difference in visual cortex.
- Approximately 50% of 237 mouse cortical marker genes expressed differently in human; 59% of laminar markers and 41% of putative interneuron markers differed, while glial and vascular markers were relatively conserved. A total of 165 genes were designated human cortical markers, and 38% of these had human-mouse expression differences.
- Layer-specific shifts were prominent: 36 genes (51% of mouse layer 5 markers) had diminished or no specific human layer 5 expression, while another set was enhanced in human layer 3 large pyramidal neurons, with some genes shifting from mouse layer 5 to human layer 3. Among human lineage-specific genes present in both species, 16 showed increased and 4 decreased expression in human.
Methods
- Postmortem adult human brain tissue without known neuropathology or neuropsychiatric illness was used; visual cortex (areas 17 and 18) and mid temporal cortex (mostly area 21) were profiled. Each gene was assayed in 2–6 brains, most in 4, across 46 donor cases (27 men, 19 women), with about 92 genes per case and ~31,000 ISH images generated.
- Digoxigenin-labeled riboprobes were used for cellular-resolution in situ hybridization on a standardized platform adapted from the Allen Mouse Brain Atlas; probes were 400–1000 bp and designed for >50% overlap with mouse ortholog probes. Expression level and spatial pattern were manually scored, with tissue quality benchmarked using control genes and an Imod exclusion threshold of ±2 SD.
- Comparisons included across genes, cortical regions, individuals, and human versus mouse visual cortex (941 orthologs) and temporal cortex (611 genes with mouse coronal data). Laser capture microdissection and RT-qPCR validated donor variation for RELN.
Limitations
- The paper states that the study provides qualitative, not quantitative, assessment because of the small number of specimens per gene and difficulty quantifying a large, anatomically irregular dataset; small quantitative changes could have been missed. It also notes that only two cortical regions were analyzed, so whole-brain extrapolation may underestimate localized expression differences.
- The paper states that tissue quality variation and limited sample sizes constrained analysis, and that only particularly striking expression level differences were called out in the human-mouse comparison.
- Evident from the text: manual scoring is subjective; “putative” cell-type identities cannot be ascertained purely from scattered ISH patterns; cross-species comparisons are limited to orthologs with data in both species and, for temporal cortex, to genes with mouse coronal data.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 16 cited sources checked · 0 supported · 0 flagged
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
“Overall, 79% of the genes were expressed above background.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Differential expression across genes
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
“In this study, the most prominent boundary is between primary and secondary visual cortices.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across cortical regions
Load-bearingStrength:plain· not yet calibratedTests✓ 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
“The donor difference for RELN was validated by RT-qPCR on laser capture microdissected layer 4C tissues from the 3 donors shown in Figure 3 (ΔCp values between RELN and GAPDH control are 8.3 ± 0.3 for Donor 1, 9.2 ± 0.2 for Donor 2, and 9.1 ± 0.2 for Donor 3, means ± SD; p < 0.01 for both Donors 1–2 and 1–3 comparisons, Student’s t-test).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across individuals
Strength:plain· not yet calibratedn = 3Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Donors without known neuropathology or history of neuropsychiatric illnesses represent normal human cortex.
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 data reveal diverse gene expression patterns and remarkable conservation of each individual gene’s expression among individuals (95%), cortical areas (84%), and between human and mouse (79%).”
- Also stated in: § Comparing expression across individuals · plain
“Overall, 46 genes (5%) were determined to show donor variation in expression pattern or level (Table S2 and Supplemental Information).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Abstract > Summary
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes- Rests on an assumption: Donors without known neuropathology or history of neuropsychiatric illnesses represent normal human cortex.
- Also stated in: § Comparing expression across individuals · plain
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 no direct correlation between postmortem interval (PMI) or RNA integrity number (RIN) and the Imod score (data not shown).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
Load-bearingStrength:plain· not yet calibratedTests✓ 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
“Only 4% of genes exhibited expression pattern difference between areas 18 and 21 (Table S2), for example GRIN3A and SCN3B (Figure 2C), with a very small subset showing differential expression in all three regions, such as PENK, KCNC3 and SYT2 (Figure 2D).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across cortical regions
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
“A small but substantial number of genes (21%) exhibited species-differential expression.”
- Also stated in: § Comparing expression between species · plain
“Overall, gene expression showed a high degree of concordance between mouse and human visual cortices, with only 21% of the genes (199 genes) showing moderate or marked difference in either expression patterns or levels (Table S2).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Abstract > Summary
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
- Also stated in: § Comparing expression between species · plain
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
“Variation in expression levels of CTNND2 often correlated with Imod of the tissue block, indicating that as a moderate to low expressing gene CTNND2 may be more sensitive to tissue quality variation.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
Strength:hedged· not yet calibratedCausal:correlational· 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
“Approximately 50% of the 237 genes identified as cortical markers in the Allen Mouse Brain Atlas expressed differently in human.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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 wide range of pattern differences was observed, often restricted to particular anatomical domains or cell populations (Figure 4A).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
- It may state two separate claims as one. 32
- Probably not a substantial claim. 15
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 include secreted protein (48%), extracellular matrix (50%), cell adhesion (36%), and peptide ligand (31%) genes, which are interestingly all involved in intercellular communication.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
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.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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
“Many genes exhibit differential expression across cortical layers and thus can delineate anatomical boundaries and fine cytoarchitectural differences.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across cortical regions
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Expression of CARTPT appeared to be independent of tissue quality variation.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
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
“Gene expression patterns were similar between areas 18 and 21 for the vast majority of the genes, with only subtle cytoarchitectural difference.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across cortical regions
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
“Among these, 59% of the laminar markers and 41% of the putative interneuron markers from mouse showed expression difference in human, while glial and vascular marker expression was relatively conserved.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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 Kv1-type genes included those showing interneuron preference (e.g. KCNA2), laminar enrichment in excitatory neurons (e.g. KCNA1 and KCNA6), as well as low or no expression.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Differential expression across genes
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
“For example, the disease genes (354) and comparative genomics genes (95) showed similarly low cross-species variability, with only 13% and 23% exhibiting expression difference, respectively.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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
“GAP43 and PCP4 showed a higher degree of consistency in expression pattern and level, with deviations in only 7% and 21% of tissue samples, respectively.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
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
“CTNND2 and CARTPT showed less consistency, with deviations in 31% and 41% of samples, respectively.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
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
“With additional genes dropping out due to weak expression in mouse and undetectable in human (although not scored as “different”) as well as 25 newly identified human marker genes, consequently a total of 165 genes were designated as human cortical markers (Table S2), and among these 38% had human-mouse difference in expression pattern or level.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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 include 56 laminar markers, 61 putative interneuron markers, 12 putative astrocyte markers, 10 oligodendrocyte markers, and 3 vascular markers (Table S2).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
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
“Nearly all of these genes, including those only present in human, were found to be expressed in human cortex, mostly in widespread pattern with variable expression levels (Figure S2 and Table S2).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
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
“Among the 611 genes, expression difference was seen in 159 genes (26%) between human and mouse visual cortices and in 149 genes (24%) between human and mouse temporal cortices.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
- Rests on an assumption: Mouse TEa is the closest homolog of human area 21.
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
“Nearly all of these genes (except CCK) were found to have interneuron-specific expressions which were well-conserved between mouse and human (with the exception of CALB1, CORT, CRH, NPY, PDYN).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
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
“The majority (126) of these genes showed expression difference in both types of comparison, with only a small number of genes showing unique difference in one cortical area (5% visual area only, 4% temporal area only) (Figure 4D).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
- Rests on an assumption: Mouse TEa is the closest homolog of human area 21.
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
“On the other hand, we also found very significant expression of the glutamatergic neuronal marker SLC17A7 as well as the layer 6B marker CTGF in WM (Figure S4).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
Strength:boosted· 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
“In addition, similar to the above cortical region comparison in human, a small degree of expression difference was observed between mouse TEa and primary visual cortex (V1) (6%), as well as between TEa and the adjacent mouse auditory cortex A1/A2 (3%).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: Mouse TEa is the closest homolog of human area 21.
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
“Layer 6B is present in both human and mouse cortex and was found to be labeled by a common set of genes (i.e., ADRA2A, CTGF, NR4A2, Figure 5A and Figure 6).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
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
“In addition to these well-known interneuron markers, a number of new putative interneuron marker genes as well as genes with enriched expression in interneurons were identified, again some are common between human and mouse and others are differentially expressed (Table S2).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
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
“Here we show that the WM neurons are composed of glutamatergic, GABAergic and peptidergic neurons and express a diversity of genes.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
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
“In conclusion, a large number of genes related to neural functions were profiled in an unprecedented scale with cellular resolution in two cortical regions of human brains, revealing a wide range of distinct expression patterns in different cell types or populations.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“- Diverse expression patterns delineate regional boundaries and distinct cell types”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Experimental Procedures > Laser capture microdissection and RT-qPCR
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
“A small percentage of genes did show substantial expression difference among human individuals (5%) or between human and mouse (21%).”
- Also stated in: § Laser capture microdissection and RT-qPCR · plain
“- While 5% genes vary among human individuals, 21% differ between human and mouse”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § Laser capture microdissection and RT-qPCR · plain
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 large dataset also enabled a detailed comparison of gene expression between human and mouse cerebral cortex, revealing cross-species conservation and divergence of gene expression at anatomical and cell type levels.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
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 assess whether an expression level difference reflected tissue integrity or a donor difference, a Pearson rank correlation was performed on genes showing significant difference in intensity level (Supplemental Information).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across individuals
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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 Kv3-type genes showed predominantly scattered patterns, consistent with preferential expression in interneurons.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Differential expression across genes
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.
None of the sources cited for this claim have been checked yet.
In the paper
“Microarray studies have also revealed distinct gene expression profiles and coexpression networks associated with different human brain regions, major cell types, and cellular processes (Johnson et al., 2009; Miller et al., 2010; Oldham et al., 2006; Oldham et al., 2008).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > 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.
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
“Due to the inevitable tissue quality difference between the two species, and the demonstrated impact of tissue quality on expression intensity, only particularly striking expression level differences (e.g., + versus +++ or more) were called out.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression between species
Strength:boosted· 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
“To establish a metric for evaluating tissue quality for ISH analysis, a modified intensity score (Imod) was calculated for each control gene and each tissue sample (Supplemental Information).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
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
“Only genes with level variations showing no significant correlation with tissue integrity were considered as having donor difference.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Comparing expression across individuals
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
“To control for the inherent tissue quality variation across donors and specimens, several control genes were assayed in every tissue block to benchmark tissue and ISH quality (Figure S1A).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
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
“Genes within each group exhibited differential expression, suggesting that different cell types have different compositions of potassium channels which could result in different excitability properties.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Differential expression across genes
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“However, comparative microarray studies have shown a high degree of conservation across species in overall gene expression, although there is considerable upregulation of brain gene expression in humans compared to non-human primates (Khaitovich et al., 2006; Preuss et al., 2004; Vallender et al., 2008).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > 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
“Gene expression change has been considered a major driver of species differentiation and evolution (King and Wilson, 1975).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Introduction
What the sources say
- Not checked yetcites King and Wilson, 1975 source
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
“Therefore, tissue blocks for which Imod was 2.0 standard deviations (SD) beyond the median Imod value [Imod < 2 (i.e., below -2 SD) or Imod > 4 (i.e., above +2 SD)] were excluded from the study (Figure S1B).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Tissue quality validation and cross-sample variation
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“Layer 2 and 3 neurons mainly mediate intracortical connections both locally and distantly.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
What the sources say
- Not checked yetcites Douglas and Martin, 2004 source
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.
None of the sources cited for this claim have been checked yet.
In the paper
“This finding is consistent with previous microarray gene expression profiling studies (Caceres et al., 2003; Gu and Gu, 2003; Johnson et al., 2009; Miller et al., 2010; Oldham et al., 2008), extending the conclusion further by providing cellular level details.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
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
“Layers 2 and 3 in human and other primates are greatly expanded compared to mouse, suggesting the occurrence of a substantially increased intracortical connectivity in human (Marin-Padilla, 1992).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
What the sources say
- Not checked yetcites Marin-Padilla, 1992 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. It may state two separate claims as one.
In the paper
“Layer 5 and 6 neurons mainly send output projections to various subcortical and contralateral regions.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
What the sources say
- Not checked yetcites Douglas and Martin, 2004 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.
In the paper
“Layer 4 neurons are the main targets of thalamocortical inputs.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
What the sources say
- Not checked yetcites Douglas and Martin, 2004 source
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
“Cortical excitatory neurons in different layers are believed to have differential input/output connections and play distinct roles in the cortical circuits (Douglas and Martin, 2004).”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Results > Distinct molecular signatures of cortical cell types
What the sources say
- Not checked yetcites Douglas and Martin, 2004 source
Strength:hedged· 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, it should be noted that this study provides qualitative, not quantitative, assessment, due to the small number of specimens used for each gene and the difficulty in quantifying anatomical data in such a large, anatomically irregular dataset.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
Load-bearingStrength:plain· not yet calibratedTests✓ 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
“supporting the notion that despite substantial structural and functional variability among individuals, the basic cellular composition and gene expression profiles of the human brain are fundamentally similar, variations being likely reflected in more subtle ways.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The two cortical regions analyzed are representative of the human neocortex.
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 support the use of mouse as a good model system for the understanding of human brain function, while pointing out important differences in the cellular organization between mouse and human brains and the differential functions individual genes may play in each species.”
§ Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures > Discussion
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
Existing gene expression profiling studies have typically been performed on homogenized tissues and cannot discern cellular heterogeneity or spatial localization within the brain.
“To date, such gene expression profiling studies have typically been performed on homogenized tissues, unable to discern cellular heterogeneity as well as spatial localization within the brain.”
The paper relies on this without support.
Human visual cortex areas 17/18 and mouse visual cortex are homologous enough to compare gene expression.
“A substantially higher degree of gene expression variation was observed when comparing putatively homologous human and mouse cortical areas.”
The paper relies on this without support.
Mouse TEa is the closest homolog of human area 21.
“we compared human area 21 with the caudal part of mouse temporal association cortex (TEa), likely to be the closest homolog of area 21.”
The paper relies on this without support.
Postmortem human brain tissue gene expression reflects in vivo gene expression.
“Expression analysis of 995 genes was done by ISH in multiple postmortem adult brain specimens from two functionally distinct cortical regions: visual cortex (containing Brodmann’s areas 17 and 18), and mid temporal cortex (containing mostly Brodmann’s area 21, with parts of area 22 and sometimes 20), from individuals without any known neuropathology or history of neuropsychiatric illnesses.”
The paper relies on this without support.
Donors without known neuropathology or history of neuropsychiatric illnesses represent normal human cortex.
“from individuals without any known neuropathology or history of neuropsychiatric illnesses.”
The paper relies on this without support.
The two cortical regions analyzed are representative of the human neocortex.
“in two cortical regions of human brains”
“the basic cellular composition and gene expression profiles of the human brain are fundamentally similar”
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
“To complement and validate the microarray data, several targeted, large-scale in situ hybridization (ISH) data sets were generated using a high-throughput ISH platform1, 8.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [8]
In the citing paper
“a study of ~700 genes in human versus mouse cortex by in situ hybridization found approximately 25% of genes having at least subtle differences in areal or cellular patterning39”
From Canonical genetic signatures of the adult human brain (2015) · cites this paper as [39]
Citations
Cites
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Self-citationGlobal variation in copy number in the human genome
Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., et al. (2006) · Nature · doi:10.1038/nature05329 · Cited by 4,377
Cahoy, J. D., Emery, B., Kaushal, A., Foo, L. C., Zamanian, J. L., Christopherson, K. S., Xing, Y., Lubischer, J. L., Krieg, P. A., Krupenko, S. A., et al. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4178-07.2008 · Cited by 3,129
Interneurons of the neocortical inhibitory system
Markram, H., Toledo-Rodriguez, M., Wang, Y., Gupta, A., Silberberg, G., & Wu, C. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1519 · Cited by 2,954
King, M.-C., & Wilson, A. C. (1975) · Science · doi:10.1126/science.1090005 · Cited by 2,815
NEURONAL CIRCUITS OF THE NEOCORTEX
Douglas, R. J., & Martin, K. A. C. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144152 · Cited by 1,886
The human brain in numbers: a linearly scaled-up primate brain
Herculano-Houzel, S. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.031.2009 · Cited by 1,778
Neuronal subtype specification in the cerebral cortex
Molyneaux, B. J., Arlotta, P., Menezes, J. R. L., & Macklis, J. D. (2007) · Nature reviews. Neuroscience · doi:10.1038/nrn2151 · Cited by 1,704
Flagged first, then by citations
2 of the 50 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
An anatomically comprehensive atlas of the adult human brain transcriptome
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., van de Lagemaat, L. N., Smith, K. A., Ebbert, A., Riley, Z. L., et al. (2012) · Nature · doi:10.1038/nature11405 · Cited by 3,083
Self-citationShared and distinct transcriptomic cell types across neocortical areas
Tasic, B., Yao, Z., Graybuck, L. T., Smith, K. A., Nguyen, T. N., Bertagnolli, D., Goldy, J., Garren, E., Economo, M. N., Viswanathan, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0654-5 · Cited by 1,746
Self-citationConserved cell types with divergent features in human versus mouse cortex
Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775
Self-citationAdult mouse cortical cell taxonomy revealed by single cell transcriptomics
Tasic, B., Menon, V., Nguyen, T. N., Kim, T. K., Jarsky, T., Yao, Z., Levi, B., Gray, L. T., Sorensen, S. A., Dolbeare, T., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4216 · Cited by 1,714
Self-citationFunctional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture
Paşca, A. M., Sloan, S. A., Clarke, L. E., Tian, Y., Makinson, C. D., Huber, N., Kim, C. H., Park, J.-Y., O'Rourke, N. A., Nguyen, K. D., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3415 · Cited by 1,609
A survey of human brain transcriptome diversity at the single cell level
Darmanis, S., Sloan, S. A., Zhang, Y., Enge, M., Caneda, C., Shuer, L. M., Hayden Gephart, M. G., Barres, B. A., & Quake, S. R. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1507125112 · Cited by 1,401
Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex
Maynard, K. R., Collado-Torres, L., Weber, L. M., Uytingco, C., Barry, B. K., Williams, S. R., Catallini, J. L., Tran, M. N., Besich, Z., Tippani, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00787-0 · Cited by 1,222
Self-citationIntegrative functional genomic analyses implicate specific molecular pathways and circuits in autism
Parikshak, N. N., Luo, R., Zhang, A., Won, H., Lowe, J. K., Chandran, V., Horvath, S., & Geschwind, D. H. (2013) · Cell · doi:10.1016/j.cell.2013.10.031 · Cited by 1,039
Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex
Nowakowski, T. J., Bhaduri, A., Pollen, A. A., Alvarado, B., Mostajo-Radji, M. A., Di Lullo, E., Haeussler, M., Sandoval-Espinosa, C., Liu, S. J., Velmeshev, D., et al. (2017) · Science · doi:10.1126/science.aap8809 · Cited by 964
Highly Multiplexed Subcellular RNA Sequencing in Situ
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Yang, J. L., Ferrante, T. C., Terry, R., Jeanty, S. S. F., Li, C., Amamoto, R., et al. (2014) · Science · doi:10.1126/science.1250212 · Cited by 973
Self-citationIntegrative single-cell analysis of transcriptional and epigenetic states in the human adult brain
Lake, B. B., Chen, S., Sos, B. C., Fan, J., Kaeser, G. E., Yung, Y. C., Duong, T. E., Gao, D., Chun, J., Kharchenko, P. V., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4038 · Cited by 983
Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain
Lake, B. B., Ai, R., Kaeser, G. E., Salathia, N. S., Yung, Y. C., Liu, R., Wildberg, A., Gao, D., Fung, H.-L., Chen, S., et al. (2016) · Science · doi:10.1126/science.aaf1204 · Cited by 957
The evolution of distributed association networks in the human brain
Buckner, R. L., & Krienen, F. M. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.017 · Cited by 836
Dong, K., & Zhang, S. (2022) · Nature Communications · doi:10.1038/s41467-022-29439-6 · Cited by 761
Patches of Disorganization in the Neocortex of Children with Autism
Stoner, R., Chow, M. L., Boyle, M. P., Sunkin, S. M., Mouton, P. R., Roy, S., Wynshaw-Boris, A., Colamarino, S. A., Lein, E. S., & Courchesne, E. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1307491 · Cited by 722
Self-citationBrain organoids: advances, applications and challenges
Qian, X., Song, H., & Ming, G.-L. (2019) · Development · doi:10.1242/dev.166074 · Cited by 724
Burt, J. B., Demirtaş, M., Eckner, W. J., Navejar, N. M., Ji, J. L., Martin, W. J., Bernacchia, A., Anticevic, A., & Murray, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0195-0 · Cited by 657
Canonical genetic signatures of the adult human brain
Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., Jegga, A. G., Aronow, B. J., Lee, C.-K., Bernard, A., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4171 · Cited by 663
Self-citationGenetic identification of brain cell types underlying schizophrenia
Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Skene, N. G., Bryois, J., Bakken, T. E., Breen, G., Crowley, J. J., Gaspar, H. A., Giusti-Rodriguez, P., Hodge, R. D., Miller, J. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0129-5 · Cited by 651
Self-citationNeural Stem Cells: Generating and Regenerating the Brain
Gage, F. H., & Temple, S. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.037 · Cited by 595
Cortical Evolution: Judge the Brain by Its Cover
Geschwind, D. H., & Rakic, P. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.045 · Cited by 519
Lee, J. H., Daugharthy, E. R., Scheiman, J., Kalhor, R., Ferrante, T. C., Terry, R., Turczyk, B. M., Yang, J. L., Lee, H. S., Aach, J., et al. (2015) · Nature Protocols · doi:10.1038/nprot.2014.191 · Cited by 529
Seidlitz, J., Váša, F., Shinn, M., Romero-García, R., Whitaker, K. J., Vértes, P. E., Wagstyl, K., Reardon, P. K., CLASEN, L. S., Liu, S., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.11.039 · Cited by 496
Development and arealization of the cerebral cortex
Cadwell, C. R., Bhaduri, A., Mostajo-Radji, M. A., Keefe, M. G., & Nowakowski, T. J. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.009 · Cited by 408
Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems
Alon, S., Goodwin, D., Sinha, A., Wassie, A. T., Chen, F., Daugharthy, E. R., Bando, Y., Kajita, A., Xue, A. G., Marrett, K., et al. (2021) · Science · doi:10.1126/science.aax2656 · Cited by 421
Self-citationBridging the Gap between Connectome and Transcriptome
Fornito, A., Arnatkevičiūtė, A., & Fulcher, B. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.10.005 · Cited by 381
A comprehensive transcriptional map of primate brain development
Bakken, T. E., Miller, J. A., Ding, S., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., Dalley, R. A., Royall, J. J., Lemon, T. A., et al. (2016) · Nature · doi:10.1038/nature18637 · Cited by 387
Self-citationDeepST: identifying spatial domains in spatial transcriptomics by deep learning
Xu, C., Jin, X., Wei, S., Wang, P., Luo, M., Xu, Z., Yang, W., Cai, Y., Xiao, L., Lin, X., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac901 · Cited by 374
Brain organoids for the study of human neurobiology at the interface of in vitro and in vivo
Chiaradia, I., & Lancaster, M. A. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-00730-3 · Cited by 360
Subcortical origins of human and monkey neocortical interneurons
Ma, T., Wang, C., Wang, L., Zhou, X., Tian, M., Zhang, Q., Zhang, Y., Li, J., Liu, Z., Cai, Y., et al. (2013) · Nature Neuroscience · doi:10.1038/nn.3536 · Cited by 322
Shen, E., Overly, C. C., & Jones, A. R. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2012.09.005 · Cited by 333
Self-citationTranscriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type
Boldog, E., Bakken, T. E., Hodge, R. D., Novotny, M., Aevermann, B. D., Baka, J., Bordé, S., Close, J. L., Diez-Fuertes, F., Ding, S.-L., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0205-2 · Cited by 291
Self-citationMohan, H., Verhoog, M. B., Doreswamy, K. K., Eyal, G., Aardse, R., Lodder, B. N., Goriounova, N. A., Asamoah, B., B. Brakspear, A. B. C., Groot, C., et al. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv188 · Cited by 280
Lake, B. B., Codeluppi, S., Yung, Y. C., Gao, D., Chun, J., Kharchenko, P. V., Linnarsson, S., & Zhang, K. (2017) · Scientific Reports · doi:10.1038/s41598-017-04426-w · Cited by 271
Li, J., Seidlitz, J., Suckling, J., Fan, F., Ji, G., Meng, Y., Yang, S., Wang, K., Qiu, J., Chen, H., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21943-5 · Cited by 319
Enhanced Dendritic Compartmentalization in Human Cortical Neurons
Beaulieu-Laroche, L., Toloza, E. H. S., van der Goes, M.-S., Lafourcade, M., Barnagian, D., Williams, Z. M., Eskandar, E. N., Frosch, M. P., Cash, S. S., & Harnett, M. T. (2018) · Cell · doi:10.1016/j.cell.2018.08.045 · Cited by 296
Xu, X., Wells, A., O’Brien, D. R., Nehorai, A., & Dougherty, J. D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4488-13.2014 · Cited by 276
Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH
Fang, R., Xia, C., Close, J. L., Zhang, M., He, J., Huang, Z., Halpern, A. R., Long, B., Miller, J. A., Lein, E. S., et al. (2022) · Science · doi:10.1126/science.abm1741 · Cited by 277
Self-citationMolecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease
Otero-Garcia, M., Mahajani, S. U., Wakhloo, D., Tang, W., Xue, Y.-Q., Morabito, S., Pan, J., Oberhauser, J., Madira, A. E., Shakouri, T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.06.021 · Cited by 262
A High-Resolution Enhancer Atlas of the Developing Telencephalon
Visel, A., Taher, L., Girgis, H., May, D., Golonzhka, O., Hoch, R. V., McKinsey, G. L., Pattabiraman, K., Silberberg, S. N., Blow, M. J., et al. (2013) · Cell · doi:10.1016/j.cell.2012.12.041 · Cited by 257
Spatially aware dimension reduction for spatial transcriptomics
Shang, L., & Zhou, X. (2022) · Nature Communications · doi:10.1038/s41467-022-34879-1 · Cited by 256
Chromatin accessibility dynamics in a model of human forebrain development
Trevino, A. E., Sinnott-Armstrong, N., Andersen, J., Yoon, S.-J., Huber, N., Pritchard, J. K., Chang, H. Y., Greenleaf, W. J., & Pașca, S. P. (2020) · Science · doi:10.1126/science.aay1645 · Cited by 251
Human brain evolution: transcripts, metabolites and their regulators
Somel, M., Liu, X., & Khaitovich, P. (2013) · Nature reviews. Neuroscience · doi:10.1038/nrn3372 · Cited by 246
Kalmbach, B. E., Buchin, A., Long, B., Close, J., Nandi, A., Miller, J. A., Bakken, T. E., Hodge, R. D., Chong, P., de Frates, R., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.012 · Cited by 203
Self-citationSpatial transcriptomic survey of human embryonic cerebral cortex by single-cell RNA-seq analysis
Fan, X., Dong, J., Zhong, S., Wei, Y., Wu, Q., Yan, L., Yong, J., Sun, L., Wang, X., Zhao, Y., et al. (2018) · Cell Research · doi:10.1038/s41422-018-0053-3 · Cited by 221
Pfisterer, U., Petukhov, V., Demharter, S., Meichsner, J., Thompson, J. J., Batiuk, M. Y., Asenjo-Martínez, A., Vasistha, N. A., Thakur, A., Mikkelsen, J. D., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18752-7 · Cited by 238
Shaping Our Minds: Stem and Progenitor Cell Diversity in the Mammalian Neocortex
Franco, S. J., & Müller, U. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.022 · Cited by 240
van de Leemput, J., Boles, N. C., Kiehl, T. R., Corneo, B., Lederman, P. L., Menon, V., Lee, C., Martinez, R. A., Levi, B. P., Thompson, C. L., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.05.013 · Cited by 210
Autism spectrum disorder causes, mechanisms, and treatments: focus on neuronal synapses
Won, H., Mah, W., & Kim, E. (2013) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2013.00019 · Cited by 217
Romero-García, R., Whitaker, K. J., Váša, F., Seidlitz, J., Shinn, M., Fonagy, P., Dolan, R. J., Jones, P. B., Goodyer, I. M., Bullmore, E. T., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.060 · Cited by 191
Organization of the connections between claustrum and cortex in the mouse
Wang, Q., Ng, L., Harris, J. A., Feng, D. H., Li, Y., Royall, J. J., Oh, S. W., Bernard, A., Sunkin, S. M., Koch, C., et al. (2016) · The Journal of Comparative Neurology · doi:10.1002/cne.24047 · Cited by 199
Self-citationGenetic mapping of etiologic brain cell types for obesity
Timshel, P. N., Thompson, J. J., & Pers, T. H. (2020) · eLife · doi:10.7554/elife.55851 · Cited by 202
Baker, A. L., Kalmbach, B. E., Morishima, M., Kim, J., Juavinett, A., Li, N., & Dembrow, N. C. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.0150-18.2018 · Cited by 205
Mouse and human share conserved transcriptional programs for interneuron development
Shi, Y., Wang, M., Mi, D., Lu, T., Wang, B., Dong, H., Zhong, S., Chen, Y., Sun, L., Zhou, X., et al. (2021) · Science · doi:10.1126/science.abj6641 · Cited by 196
Krienen, F. M., Yeo, B. T. T., Ge, T., Buckner, R. L., & Sherwood, C. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510903113 · Cited by 190
Human Models Are Needed for Studying Human Neurodevelopmental Disorders
Zhao, X., & Bhattacharyya, A. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.10.009 · Cited by 192
From Mouse to Human: Evolutionary Genomics Analysis of Human Orthologs of Essential Genes
Georgi, B., Voight, B. F., & Bućan, M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003484 · Cited by 183
Selective Neuronal Vulnerability in Alzheimer’s Disease: A Network-Based Analysis
Roussarie, J.-P., Yao, V., Rodriguez-Rodriguez, P., Oughtred, R., Rust, J., Plautz, Z., Kasturia, S., Albornoz, C., Wang, W., Schmidt, E. F., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.06.010 · Cited by 180
Self-citationBrain Imaging Genomics: Integrated Analysis and Machine Learning
Shen, L., & Thompson, P. M. (2019) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2947272 · Cited by 178
LRP8-Reelin-regulated neuronal enhancer signature underlying learning and memory formation
Telese, F., Ma, Q., Perez, P. M., Notani, D., Oh, S., Li, W., Comoletti, D., Ohgi, K. A., Taylor, H., & Rosenfeld, M. G. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.033 · Cited by 166
Self-citationCobolt: integrative analysis of multimodal single-cell sequencing data
Gong, B., Zhou, Y., & Purdom, E. (2021) · Genome Biology · doi:10.1186/s13059-021-02556-z · Cited by 168
Stevanović, M. J., Drakulić, D., Lazic, A., Ninković, D. S., Schwirtlich, M., & Mojsin, M. M. (2021) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.654031 · Cited by 168
Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains
Khrameeva, E., Kurochkin, I., Han, D., Guijarro, P., Kanton, S., Santel, M., Qian, Z., Rong, S., Mazin, P., Sabirov, M., et al. (2020) · Genome Research · doi:10.1101/gr.256958.119 · Cited by 162
The basis of cellular and regional vulnerability in Alzheimer’s disease
Mrdjen, D., Fox, E. J., Bukhari, S. A., Montine, K. S., Bendall, S. C., & Montine, T. J. (2019) · Acta Neuropathologica · doi:10.1007/s00401-019-02054-4 · Cited by 162
Single-cell dissection of the human motor and prefrontal cortices in ALS and FTLD
Pineda, S. S., Lee, H., Fitzwalter, B. E., Mohammadi, S., Pregent, L., Gardashli, M., Mantero, J. C., Engelberg-Cook, E., DeJesus‐Hernandez, M., van Blitterswijk, M., et al. (2024) · Cell · doi:10.1016/j.cell.2024.02.031 · Cited by 158
Song, Y.-H., Yoon, J., & Lee, S. (2021) · Experimental & Molecular Medicine · doi:10.1038/s12276-021-00580-4 · Cited by 154
Genetic Changes Shaping the Human Brain
Bae, B.-I., Jayaraman, D., & Walsh, C. A. (2015) · Developmental Cell · doi:10.1016/j.devcel.2015.01.035 · Cited by 135
Comprehensive transcriptome analysis of neocortical layers in humans, chimpanzees and macaques
He, Z., Han, D., Efimova, O., Guijarro, P., Yu, Q., Oleksiak, A., Jiang, S., Anokhin, K. V., Velichkovsky, B. M., Grünewald, S., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4548 · Cited by 137
Chen, S., Chang, Y., Li, L., Acosta, D., Li, Y., Guo, Q., Wang, C., Turkes, E., Morrison, C., Julian, D., et al. (2022) · Acta Neuropathologica Communications · doi:10.1186/s40478-022-01494-6 · Cited by 144
Genes, Cells and Brain Areas of Intelligence
Goriounova, N. A., & Mansvelder, H. D. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00044 · Cited by 148
THItoGene: a deep learning method for predicting spatial transcriptomics from histological images
Jia, Y., Liu, J., Chen, L., Zhao, T., & Wang, Y. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad464 · Cited by 130
Vezoli, J., Magrou, L., Goebel, R., Wang, X., Knoblauch, K., Vinck, M. A., & Kennedy, H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117479 · Cited by 132
Cortical Gradients and Laminar Projections in Mammals
Goulas, A., Zilles, K., & Hilgetag, C. C. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.06.003 · Cited by 128
Aiding and Abetting Anhedonia: Impact of Inflammation on the Brain and Pharmacological Implications
Lucido, M. J., Bekhbat, M., Goldsmith, D. R., Treadway, M. T., Haroon, E., Felger, J. C., & Miller, A. H. (2021) · Pharmacological Reviews · doi:10.1124/pharmrev.120.000043 · Cited by 133
Signature morphoelectric properties of diverse GABAergic interneurons in the human neocortex
Lee, B. R., Dalley, R., Miller, J. A., Chartrand, T., Close, J., Mann, R., Mukora, A., Ng, L., Alfiler, L., Baker, K., et al. (2023) · Science · doi:10.1126/science.adf6484 · Cited by 125
Self-citationMiyoshi, E., Morabito, S., Henningfield, C. M., Das, S., Rahimzadeh, N., Shabestari, S. K., Michael, N., Emerson, N., Reese, F., Shi, Z., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01961-x · Cited by 115
Altered gene expression in the dorsolateral prefrontal cortex of individuals with schizophrenia
Guillozet-Bongaarts, A. L., Hyde, T. M., Dalley, R. A., Hawrylycz, M., Henry, A. M., Hof, P. R., Hohmann, J. G., Jones, A. R., Kuan, C. L., Royall, J. J., et al. (2013) · Molecular Psychiatry · doi:10.1038/mp.2013.30 · Cited by 113
Self-citationHandel, A. E., Chintawar, S., Lalic, T., Whiteley, E. S., Vowles, J., Giustacchini, A., Argoud, K., Sopp, P., Nakanishi, M., Bowden, R. J., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddv637 · Cited by 108
Kalmbach, B. E., Hodge, R. D., Jorstad, N. L., Owen, S. F., de Frates, R. A., Yanny, A. M., Dalley, R. A., Mallory, M., Graybuck, L. T., Radaelli, C., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.08.030 · Cited by 106
Self-citationXue, K., Guo, L., Zhu, W., Liang, S., Xu, Q., Ma, L., Liu, M., Zhang, Y., & Liu, F. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-022-01474-3 · Cited by 98
Hodge, R. D., Miller, J. A., Novotny, M. A., Kalmbach, B. E., Ting, J. T., Bakken, T. E., Aevermann, B. D., Barkan, E. R., Berkowitz-Cerasano, M. L., Cobbs, C., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14952-3 · Cited by 95
Self-citationEvolution and development of the mammalian cerebral cortex
Molnár, Z., Kaas, J. H., de Carlos, J. A., Hevner, R. F., Lein, E., & Němec, P. (2014) · Brain Behavior and Evolution · doi:10.1159/000357753 · Cited by 93
Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease
Lein, E. S., Belgard, T. G., Hawrylycz, M., & Molnár, Z. (2017) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013858 · Cited by 92
Self-citationWang, B., Luo, J., Liu, Y., Shi, W., Xiong, Z., Shen, C., & Long, Y. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad262 · Cited by 91
HCN channels are a novel therapeutic target for cognitive dysfunction in Neurofibromatosis type 1
Omrani, A., van der Vaart, T., Mientjes, E., van Woerden, G. M., Hojjati, M. R., Li, K. W., Gutmann, D. H., Levelt, C. N., Smit, A. B., Silva, A. J., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.48 · Cited by 90
Ptchd1 deficiency induces excitatory synaptic and cognitive dysfunctions in mouse
Ung, D. C., Iacono, G., Méziane, H., Blanchard, E., Papon, M.-A., Selten, M. M., van Rhijn, J. R., Montjean, R., Rucci, J., Lorenzo, S. M., et al. (2017) · Molecular Psychiatry · doi:10.1038/mp.2017.39 · Cited by 91
Cross-species neuroscience: closing the explanatory gap
Barron, H. C., Mars, R. B., Dupret, D., Lerch, J. P., & Sampaio‐Baptista, C. (2020) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0633 · Cited by 89
Spatial transcriptomics reveals human cortical layer and area specification
Qian, X., Coleman, K., Jiang, S., Kriz, A. J., Marciano, J. H., Luo, C., Cai, C., Manam, M. D., Caglayan, E., Lai, A., et al. (2025) · Nature · doi:10.1038/s41586-025-09010-1 · Cited by 109
A human-specific modifier of cortical connectivity and circuit function
Schmidt, E. R. E., Zhao, H. T., Park, J. M., Dipoppa, M., Monsalve-Mercado, M. M., Dahan, J. B., Rodgers, C. C., Lejeune, A., Hillman, E. M. C., Miller, K. D., et al. (2021) · Nature · doi:10.1038/s41586-021-04039-4 · Cited by 82
Spatial transcriptomics reveals molecular dysfunction associated with cortical Lewy pathology
Goralski, T. M., Meyerdirk, L. K., Breton, L., Brasseur, L., Kurgat, K., DeWeerd, D., Turner, L., Becker, K., Adams, M., Newhouse, D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47027-8 · Cited by 79
Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer’s disease
Morabito, S., Miyoshi, E., Michael, N., & Swarup, V. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa182 · Cited by 74
Brain Transcriptome Databases: A User's Guide
Keil, J. M., Qalieh, A., & Kwan, K. Y. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1930-17.2018 · Cited by 79
New pathogenic insights from large animal models of neurodegenerative diseases
Yin, P., Li, S., Li, X., & Yang, W. (2022) · Protein & Cell · doi:10.1007/s13238-022-00912-8 · Cited by 79
A Connectomic Hypothesis for the Hominization of the Brain
Changeux, J., Goulas, A., & Hilgetag, C. C. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa365 · Cited by 80
Common cell type nomenclature for the mammalian brain
Miller, J. A., Gouwens, N. W., Tasic, B., Collman, F., van Velthoven, C. T. J., Bakken, T. E., Hawrylycz, M., Zeng, H., Lein, E. S., & Bernard, A. (2020) · eLife · doi:10.7554/elife.59928 · Cited by 75
Self-citationGore, B. B., Soden, M. E., & Zweifel, L. S. (2013) · Current Protocols in Neuroscience · doi:10.1002/0471142301.ns0435s65 · Cited by 72
High-resolution gene expression atlases for adult and developing mouse brain and spinal cord
Henry, A. M., & Hohmann, J. G. (2012) · Mammalian Genome · doi:10.1007/s00335-012-9406-2 · Cited by 73
Self-citationYan, J., Du, L., Kim, S., Risacher, S. L., Huang, H., Moore, J. H., Saykin, A. J., Shen, L., & Initiative, A. D. N. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu465 · Cited by 71
Cioli, C., Abdi, H., Beaton, D., Burnod, Y., & Mesmoudi, S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0115913 · Cited by 69
Wu, J., Li, Y., Huang, Y., Liu, L., Zhang, H., Nagy, C., Tan, X., Cheng, K., Liu, Y., Pu, J., et al. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01379-4 · Cited by 72
Metadata
- Authors
- Zeng, H., Shen, E. H., Hohmann, J. G., Oh, S. W., Bernard, A., Royall, J. J., Glattfelder, K. J., Sunkin, S. M., Morris, J. A., Guillozet-Bongaarts, A. L., Smith, K. A., Ebbert, A. J., Swanson, B., Kuan, L., Page, D. T., Overly, C. C., Lein, E. S., Hawrylycz, M. J., Hof, P. R., Hyde, T. M., Kleinman, J. E., & Jones, A. R.
- Affiliations
- Allen Institute for Brain Science (US)
- Icahn School of Medicine at Mount Sinai (US)
- National Institutes of Health (US)
- Corresponding author
- Zeng, Hongkui
- Jones, Allan R.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2012-04
- Volume
- 149
- Issue
- 2
- Pages
- 483-496
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3328777
- OpenAlex
- W2031215175
- Semantic Scholar
- fd5272f4a6f3a8eb67e25740b40534b4348bff74
- Cited by
- 426
- References
- 50
- Citations by year
- 2026: 25 · 2025: 49 · 2024: 41 · 2023: 40 · 2022: 34 · 2021: 33 · 2020: 45 · 2019: 22 · 2018: 25 · 2017: 19 · 2016: 21 · 2015: 27 · 2014: 18 · 2013: 16 · 2012: 11
- FWCI
- 9.26
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (Z99 MH999999)
- National Institute of Mental Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- human neocortex, gene expression profiling, visual cortex, temporal cortex, cortical cell types, species-specific gene expression, in situ hybridization, corticocortical connectivity
- MeSH terms
- Adult, Animals, Gene Expression Regulation, Humans, Neurons, Species Specificity, Temporal Lobe, Visual Cortex, Neocortex, Gene Expression Profiling, Mice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review