MétaCan
Menu
← Back to cohort
Record W6920714847 · doi:10.6084/m9.figshare.14314649

Additional file 1 of The CD33 short isoform is a gain-of-function variant that enhances Aβ1–42 phagocytosis in microglia

2021· article· en· W6920714847 on OpenAlexaff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrogliaPhagocytosisFlow cytometryGenetically modified mouseImmunofluorescenceGreen fluorescent proteinTransgene

Abstract

fetched live from OpenAlex

Additional file 1: Fig. 1. Quantifying microglia in the brain of human CD33 transgenic mice by immunofluorescence staining. The density of microglia was assessed by the number of IBA1 + cells per mm2 of tissue from the average of a minimum of five sections from each genotype. The microglia density was evaluated in (a) whole brain, and in three selected regions: (b) cortex, (c) hippocampus, and (d) midbrain. No significant difference was detected amongst the four cohorts that were analyzed (N = 5 mice per genotype). Fig. 2. Quantifying GFP expression in the brain of human CD33 transgenic mice by immunofluorescence staining. (a) The percentage of GFP positive cells in the IBA1+ or NeuN+populations were assessed in a minimum of five individual sections from five mice per genotype. Representative images are shown for each genotype. (b,c) Quantifying the percentage of GFP + cells in the (b) IBA1+ and (c) NeuN+ reveals minimal leakiness outside of the microglial cell lineage. Fig. 3. hCD33m transgenic microglia have an enhanced ability to phagocytose fluorescent beads. A competitive flow cytometry-based phagocytosis assay between primary hCD33m+ (blue) and WT (black) microglia, showing the (a) representative flow cytometry data for uptake of fluorescent polystyrene beads and (b) quantification of uptake. % Phagocytosis represents the cytochalasin-D subtracted values referenced to the average of the WT microglia set to 100%. (N=6). Fig. 4. Cell annotation for BAMs, monocytes and microglia. (a) BAM specific gene markers, Ms4a7, H2-Eb1 and Mrc1 exclusively expressed in cluster 9. (b) Ly6c2, Plac8 and Ace, genes representative of monocytes expressed in cluster 11. (c) Validation for the microglia specific genes, Sall1, Tmem119 and P2ry12 for clusters 0–8. Fig. 5. Differential gene expression of the microglia clusters from Experiment 1. (a) UMAP projection of the 12 identified clusters from Experiment 1. (b) Heatmap showing the top 50 differentially expressed genes in each cluster. Fig. 6. The top 30 DEGs in Cluster 0 from Experiment 1. Fig. 7. Single cell analysis of control, hCD33M and hCD33m in Experiment 2 reveals differences in isoform gene expression. (a) UMAP projections of the 13,982 cells in the merged Experiment 2 datasets showing 13 individual clusters. (b) Bar graphs showing the absolute number of cells from each isoform present in each cluster (top) and their respective proportions (bottom). (c) UMAP projection of the individual Control, hCD33M and hCD33m datasets. (d) Heatmap of representative genes. (e) Violin plots of hCD33m specific cluster 0 genes. Fig. 8. Feature plots showing the differentially expressed genes for each of the 11 lusters. Cluster were defined by the unsupervised SCCAF clustering and the expression of two representative genes were chosen for each cluster. Cluster 0–8, and 10 expressed microglial genes, whereas cluster 9 expressed border associated macrophage genes and cluster 11 expressed monocyte genes. Fig. 9. Anti-CD33 clone HIM3–4 does not recognize hCD33m. U937 cells overexpressing either hCD33M or hCD33m tested with anti-CD33 antibody clone HIM3–4 before and after pre-treatment with neuraminidase. Fig. 10. Optimizing and quantifying intracellular staining with S503 on U937 and THP1 cells. (a) CD33−/− U937 cells overexpressing CD33m were used to optimize a procedure with trypsin to remove cell surface antigens. Cells were treated with or without trypsin prior to staining with S503 (blue) or isotype control (grey). Cells were not fixed or permeabilized in this experiment. (b) Quantification of the mean fluorescence intensity (MFI) values for S503 staining of U937 cells with the indicated genotypes, taken from Fig. 5e of the main manuscript. MFI values are isotype control-subtracted. (c) An independent experiment showing that intracellular staining of hCD33m can be detected within hCD33m-overexpressing CD33−/− U937 cells. (d) Extracellular (left panel) and intracellular (right panel) staining with S503 and isotype control (grey) on WT and CD33−/− THP1 cells. Fig. 11. Cell surface staining of hCD33m + and hCD33M+ transgenic primary mouse microglia with antibody S503. (a) Flow cytometry histograms of WT (black), hCD33M+ (red), and hCD33m + (blue) primary microglia stanine with either isotype or S503. (b) Quantification of the mean fluorescence intensity (MFI) values for n = 3 samples for each condition. N.S. = no statistical significance (P > 0.05). Fig. 12. hCD33M+ mouse microglia express hCD33M at levels modestly lower than human peripheral blood monocytes. (a) Peripheral blood mononuclear cells were assessed for CD33M expression (red) on CD14+ peripheral blood monocytes relative to an isotype control (grey). (b) hCD33M+ primary mouse microglia were assessed for CD33M expression (red) relative to an isotype control (grey). (c) Mean fluorescence intensity (MFI) values from the flow cytometry graphs of CD33M signal. Data represents three different healthy human subjects and three different CD33M+ mice. Fig. 13. CD33 transcript levels in transgenic mouse microglia. (a) mCd33 transcript levels in primary microglia from hCD33 transgenic mice demonstrate that expression of neither hCD33 isoform alters the mCd33 transcript levels. (b) hCD33 transcript levels in primary microglia from hCD33 transgenic mice. Both datasets are derived from aligning our scRNAseq datasets with the inclusion of hCD33. Note that this method does not differentiate hCD33M and hCD33m transcripts due to extensive overlap between the two isoforms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8840.177

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.248
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueFigshare→Same topicNeuroinflammation and Neurodegeneration Mechanisms→French-language works237,207→