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Wuhan Fine Biotech
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R&D Systems
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Fisher Scientific
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Exosome Diagnostics
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Cell Signaling Technology Inc
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Proteintech
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Proteintech
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R&D Systems
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Journal: BMC Infectious Diseases
Article Title: Elevated serum TIM4 is associated with disease severity and serves as a potential predictive biomarker in chronic hepatitis B
doi: 10.1186/s12879-026-12709-9
Figure Lengend Snippet: Scatter plots demonstrating correlation analysis between serum TIM4 and laboratory parameters. Parameters analyzed include liver function markers (ALT, AST, TBIL, and DBIL), biochemistry markers (BUN and SCr), and hematological markers (WBC, RBC, Hb, and PLT). Each panel displays the correlation coefficient (r) and its statistical significance (p-values) from bivariate analysis. Solid regression lines indicate statistically significant correlations ( p < 0.05), whereas dashed lines indicate non-significant associations. ALT ( r = 0.33, p < 0.01), AST ( r = 0.35, p < 0.01), TBIL ( r = 0.16, p = 0.04), DBIL ( r = 0.29, p < 0.01), PLT ( r = -0.36, p < 0.01), WBC ( r = -0.08, p = 0.31), RBC ( r = -0.07, p = 0.38), Hb ( r = -0.03, p = 0.73), BUN ( r = -0.04, p = 0.65), SCr ( r = 0.02, p = 0.80)
Article Snippet: Serum TIM4 concentration was quantified using a commercially available
Techniques:
Journal: BMC Infectious Diseases
Article Title: Elevated serum TIM4 is associated with disease severity and serves as a potential predictive biomarker in chronic hepatitis B
doi: 10.1186/s12879-026-12709-9
Figure Lengend Snippet: Receiver operating characteristic (ROC) curve for serum TIM4 levels in discriminating severe from non-severe CHB patients. The area under the curve (AUC) was 0.640 (95% CI: 0.527–0.754, p = 0.022), indicating a moderate ability to predict severe CHB. The optimal TIM4 cutoff value of 447.68 pg/mL was determined by maximizing Youden’s index, providing a sensitivity of 63.3% and specificity of 62.9%
Article Snippet: Serum TIM4 concentration was quantified using a commercially available
Techniques:
Journal: The Journal of Experimental Medicine
Article Title: XPR1 regulates fetal liver macrophage development, identity, and pyrenocyte clearance
doi: 10.1084/jem.20241587
Figure Lengend Snippet: FL macrophage development requires Xpr1 expression in hematopoietic cells. (A) Representative flow cytometry plots and total cell numbers (mean ± SD) of FL macrophages (Mac) extracted from E16.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl embryos (pre-gated on CD45 + Lin − [CD19 − CD3 − B220 − Ter119 − CD49b − CD90.2 − ] cells). Data show n = 4–8 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (B) Graphs showing embryo and liver weights of E18.5 Xpr1 fl/+ , Xpr1 fl/fl , Vav1 iCre Xpr1 fl/+ , and Vav1 iCre Xpr1 fl/fl embryos. Data show n = 5–9 per group and were pooled from three independent experiments. Statistical analysis was performed using one-way ANOVA with Tukey’s multiple comparison test. (C) Representative flow cytometry plots and total cell numbers (mean ± SD) of liver Ly6C hi monocytes (Mo) extracted from E16.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl embryos (pre-gated on CD45 + Lin − F4/80 − CD117 lo-int CD48 − cells). Data show n = 4–8 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (D) UMAP plots of myeloid cells extracted from livers of E16.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl embryos (pre-gated on CD45 + Lin − CD64 + F4/80 + MHCII − Ly6G − cells) and analyzed by flow cytometry. Data were generated from n = 2–4 samples per group and are representative of at least four independent experiments. (E) Graphs showing frequencies of cell clusters defined among CD45 + cells ( D ). Data show n = 2 per group and are representative of at least four independent experiments. (F) Heatmap of cell surface marker expression on cell clusters defined in D. Data were transformed and percentile normalized. (G) Immunohistochemistry of E16.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl livers. DAPI (blue), CD64 (red), and F4/80 (green). Insets: Magnifications of the outlined regions showing expression of all markers, CD64/DAPI, and F4/80/DAPI (from left to right). Images are representative of at least five embryos per group. Scale bar: 40 µm. (H) Immunohistochemistry of E15.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl livers, stained for Hoechst (blue), IBA1 (cyan), and TIM4 (white). Insets: Single stainings. Images are representative of three embryos per group. Scale bar: 100 µm in overview, 50 µm in inset. **P < 0.01, ***P < 0.001, and ****P < 0.0001. ns, not significant.
Article Snippet: Primary antibodies used were F4/80 (clone BM8, 123101; BioLegend; clone CI:A3-1, MCA497A488; Bio-Rad), CD64 (clone AT152-9, MCA5997; Bio-Rad), IBA1 (ABIN2857032; Antibodies Online),
Techniques: Expressing, Flow Cytometry, Comparison, Generated, Marker, Transformation Assay, Immunohistochemistry, Staining
Journal: The Journal of Experimental Medicine
Article Title: XPR1 regulates fetal liver macrophage development, identity, and pyrenocyte clearance
doi: 10.1084/jem.20241587
Figure Lengend Snippet: Phenotypic and functional changes in Mrc1 Cre Xpr1 fl/fl animals. (A) Violin plots showing the expression of Mrc1 in the indicated clusters of E15.5 FL cells. Data refer to scRNA-seq data in . (B) Immunohistochemistry of E15.5 Xpr1 fl/fl control liver stained for IBA1 (cyan), CD206 (magenta), and CD31 (white). Insets: Single stainings shown of the outlined region in the overview image. Scale bar: 100 µm, inset 50 µm. Filled arrowheads show CD206 + macrophages, open arrowheads show CD206 + endothelial cells. (C) Representative flow cytometry plot of CD206 expression in liver macrophages extracted from E15.5 Xpr1 fl/fl embryos (pre-gated on CD45 + CD31 − Ly6G − F4/80 + CD11b + TER119 − cells). (D) Representative flow cytometry plots of Tim4 expression in liver macrophages extracted from E15.5 Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl embryos (pre-gated on CD45 + Ly6G − F4/80 + cells). Data are representative of at least n = 5 per group. (E) Representative flow cytometry plots and graph showing the percentage (normalized to control) of pHrodo Red + FL macrophages (gated on CD45 + F4/80 + CD11b int cells) from Mrc1 Cre Xpr1 fl/fl and Xpr1 fl/fl FLs at E15.5, exposed in vitro to pHrodo Red Zymosan bioparticles for 90 min. Data shown are n = 3–6 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (F) Heatmap of all 6,208 DEGs in the RNA-seq data of Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl FL macrophages from . Genes indicated are the core KC-genes and KC-associated transcription factors identified in . (G) Gene ontology analysis for biological processes of the DEGs in the RNA-seq data of Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl FL macrophages from . (H) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of Tim4 expression on KCs of adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice (pre-gated on CD45 + Ly6G − F4/80 + cells). Data shown are n = 3–5 per group and are pooled from two independent experiments. Statistical analyses were performed using the Student’s t test. (I) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of KCs of adult Xpr1 fl/fl and Siglec1 Cre Xpr1 fl/fl mice (pre-gated on CD45 + Ly6G − F4/80 + cells). Data shown are n = 3 per group. Statistical analyses were performed using the Student’s t test. ( J–M ) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of (J) heart macrophages (Heart Macs) (pre-gated on CD45 + Ly6G − cells), (K) Langerhans cells (LCs) (pre-gated on CD45 + Ly6G − TCRβ − SiglecF − Langerin + cells), (L) kidney macrophages (Kidney Macs) (pre-gated on CD45 + Ly6G − CD3 − CD19 − B220 − CD49b − CD90 − cells), and (M) alveolar macrophages (AMs) (pre-gated on CD45 + Ly6G − CD3 − CD19 − B220 − CD49b − CD90 − cells) of adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice. Data shown are n = 5 per group and are pooled from two independent experiments. Statistical analyses were performed using the Student’s t test. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001. ns, not significant.
Article Snippet: Primary antibodies used were F4/80 (clone BM8, 123101; BioLegend; clone CI:A3-1, MCA497A488; Bio-Rad), CD64 (clone AT152-9, MCA5997; Bio-Rad), IBA1 (ABIN2857032; Antibodies Online),
Techniques: Functional Assay, Expressing, Immunohistochemistry, Control, Staining, Flow Cytometry, In Vitro, RNA Sequencing
Journal: The Journal of Experimental Medicine
Article Title: XPR1 regulates fetal liver macrophage development, identity, and pyrenocyte clearance
doi: 10.1084/jem.20241587
Figure Lengend Snippet: XPR1 regulates iron-recycling macrophages in the spleen and BM. (A) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of splenic macrophages from E18.5 control ( Xpr1 fl/fl and Xpr1 fl/+ ) and Vav1 iCre Xpr1 fl/fl embryos (pre-gated on CD45 + Lin − Ly6C − Ly6G − SiglecF − CD64 + cells). n = 3–10 per group, pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (B) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of splenic Ly6C hi monocytes from E18.5 Xpr1 fl/fl and Vav1 iCre Xpr1 fl/fl embryos (pre-gated on CD45 + Lin − Mac − SiglecF − cells). Data show n = 3–10 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (C) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of splenic red pulp macrophages (RPMs) from adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice (pre-gated on CD45 + Lin − Ly6G − SiglecF − CD90 − MHCII − cells). Data show n = 3–5 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (D) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of splenic Ly6C hi monocytes from adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice (pre-gated on CD45 + Lin − Ly6G − SiglecF − CD90 − B220 − CX3CR1 + CD64 + cells). Data show n = 3–5 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (E) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of F4/80 + MerTK + BM macrophages (top) (pre-gated on CD45 + Lin − Ly6C − Ly6G − ) and among these, CD163 + TIM4 + macrophages (bottom) from adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice. Data show n = 4–6 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. (F) Representative flow cytometry plots, frequencies, and numbers (mean ± SD) of BM monocytes (CD115 + CX3CR1 + ) from adult Xpr1 fl/fl and Mrc1 Cre Xpr1 fl/fl mice (pre-gated on CD45 + Lin − Ly6G − Ly6C + SiglecF − ). Data show n = 4–6 per group and are pooled from two independent experiments. Statistical analysis was performed using the Student’s t test. ***P < 0.001 and ****P < 0.0001. ns, not significant.
Article Snippet: Primary antibodies used were F4/80 (clone BM8, 123101; BioLegend; clone CI:A3-1, MCA497A488; Bio-Rad), CD64 (clone AT152-9, MCA5997; Bio-Rad), IBA1 (ABIN2857032; Antibodies Online),
Techniques: Flow Cytometry, Control
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: Schematic representation of the experimental design and analysis workflow. The figure outlines the sequential steps involved in sample collection, exosome isolation using three distinct methods (SEC, Lectin Binding, TIM4 Binding), proteomic and transcriptomic analysis, including differential expression profiling and enrichment analysis
Article Snippet:
Techniques: Isolation, Binding Assay, Quantitative Proteomics
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: Differential expression patterns of detected proteins across the three exosome isolation methods: SEC, Lectin Binding, and TIM4 Binding. Heatmaps display the protein expression profiles for each method, highlighting method-specific expression patterns
Article Snippet:
Techniques: Quantitative Proteomics, Isolation, Binding Assay, Expressing
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: Differential expression patterns of detected miRNAs across the three exosome isolation methods: SEC, Lectin Binding, and TIM4 Binding. Heatmaps illustrate miRNA expression profiles, emphasizing the method-specific miRNA expression across the different isolation techniques
Article Snippet:
Techniques: Quantitative Proteomics, Isolation, Binding Assay, Expressing
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: Unique proteins and miRNAs across the three exosome isolation methods. The Venn diagrams highlight the method-dependent variations in the number of unique proteins and miRNAs detected by SEC, Lectin Binding, and TIM4 Binding methods. ( A ) proteins, ( B ) miRNAs
Article Snippet:
Techniques: Isolation, Binding Assay
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: Gene Ontology (GO) enrichment analysis of unique proteins identified in SEC, Lectin Binding, and TIM4 Binding exosome isolation methods. The analysis highlights significantly enriched exsomal proteins or target proteins by enriched miRNAs through each isolation method: ( A ) protein ( B ) miRNA
Article Snippet:
Techniques: Binding Assay, Isolation
Journal: BMC Cancer
Article Title: Different plasma exosome isolation methods generated distinct microRNA and protein profiles in healthy controls and patients with advanced prostate and lung cancer
doi: 10.1186/s12885-025-15492-z
Figure Lengend Snippet: KEGG-pathway enrichment analysis of uniquely detected miRNAs. ‘microRNAs in cancer’ as the top-ranked pathway in SEC ( A ), Lectin binding ( B ) and TIM4 binding ( C )
Article Snippet:
Techniques: Binding Assay