Automated Author ProfileLiao, Hua
Southern Medical University
Liao, Hua
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 1: Myofiber directs macrophages IL-10-Vav1-Rac1 efferocytosis pathway in inflamed muscle following CTX myoinjury by arousing intrinsic TGF-β signaling. Fig.S1. Construction and identification of SM TGF-βr2−/−mice. Genomic PCR identification of SM TGF-βr2−/− mice was showed. MCK-Cre+/TGF-βr2flox/wt: the lanes 1, 4, 7, 8, 10; MCK-Cre+/TGF-βr2flox/flox : the lanes 3, 5, 9; MCK-Cre+/TGF-βr2wt/wt: the lanes 2, 6; Western blots analysis of TGF-βr2 protein expression in myocardium, gastrocnemius, tibialis anterior muscle and immunofluorescence staining resultsof TGF-βr2 protein expression in tibialis anterior muscle between controlandSM TGF-βr2−/− mice. Statistical data were expressed as the mean± SD. Multiple comparisons were analyzed by One-way ANOVA. Bar = 50 μm. Fig.S2. Immunofluorescence double-staining results of eMHC and Dystrophin in inflamed TA muscle from SM TGF-βr2-/- and control mice. The mean fluorescence intensity of eMHC was quantified. Statistical data were expressed as the mean±SD. Multiple comparisons were analyzed by One-way ANOVA. Bar = 50 μm. Fig.S3. Myofiber specific TGF-β signaling has no effect on the recognition signaling of apoptotic cells. FACS analysis of the expression of eat-me signal in apoptotic cellsand no-eat-me signal in living cellsin inflamed muscle from control and SM TGF-βr2-/- mice. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD. Fig.S4. Myofiber TGF-β signaling shows no effect on the nuclear engulfment receptor associated-efferocytosis signaling in macrophage. FACS analysis of the expression of PPARγ and CD36 in macrophage sorted from inflamed muscle, between SM TGF-βr2-/- and control mice. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD. Fig.S5. Immunofluorescence staining demonstrates the effects of myofiber TGF-β-IL-10 signaling on M2 phenotypeand efferocytosis molecules expressionin macrophages co-cultured with TGF-βr2−/−- or control-MPC-Myotubes, exposed to pro-inflammatory milieu, treated with or without SRI, rmIL-10 or AS101, respectively. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD.. Bar = 50 μm. Fig.S6. A proposed model depicting the mechanism by which myofibers modulating IL-10-Vav1-Rac1 macrophages efferocytosis signaling pathway in inflamed muscle through activating the intrinsic TGF-β signaling.
Authors
- Liao, Zhaohong ;
- Lan, Haiqiang ;
- Jian, Xiaoting ;
- Huang, Jingwen ;
- Wang, Han ;
- Hu, Jijie ;
- Liao, Hua
Additional file 1: Myofiber directs macrophages IL-10-Vav1-Rac1 efferocytosis pathway in inflamed muscle following CTX myoinjury by arousing intrinsic TGF-β signaling. Fig.S1. Construction and identification of SM TGF-βr2−/−mice. Genomic PCR identification of SM TGF-βr2−/− mice was showed. MCK-Cre+/TGF-βr2flox/wt: the lanes 1, 4, 7, 8, 10; MCK-Cre+/TGF-βr2flox/flox : the lanes 3, 5, 9; MCK-Cre+/TGF-βr2wt/wt: the lanes 2, 6; Western blots analysis of TGF-βr2 protein expression in myocardium, gastrocnemius, tibialis anterior muscle and immunofluorescence staining resultsof TGF-βr2 protein expression in tibialis anterior muscle between controlandSM TGF-βr2−/− mice. Statistical data were expressed as the mean± SD. Multiple comparisons were analyzed by One-way ANOVA. Bar = 50 μm. Fig.S2. Immunofluorescence double-staining results of eMHC and Dystrophin in inflamed TA muscle from SM TGF-βr2-/- and control mice. The mean fluorescence intensity of eMHC was quantified. Statistical data were expressed as the mean±SD. Multiple comparisons were analyzed by One-way ANOVA. Bar = 50 μm. Fig.S3. Myofiber specific TGF-β signaling has no effect on the recognition signaling of apoptotic cells. FACS analysis of the expression of eat-me signal in apoptotic cellsand no-eat-me signal in living cellsin inflamed muscle from control and SM TGF-βr2-/- mice. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD. Fig.S4. Myofiber TGF-β signaling shows no effect on the nuclear engulfment receptor associated-efferocytosis signaling in macrophage. FACS analysis of the expression of PPARγ and CD36 in macrophage sorted from inflamed muscle, between SM TGF-βr2-/- and control mice. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD. Fig.S5. Immunofluorescence staining demonstrates the effects of myofiber TGF-β-IL-10 signaling on M2 phenotypeand efferocytosis molecules expressionin macrophages co-cultured with TGF-βr2−/−- or control-MPC-Myotubes, exposed to pro-inflammatory milieu, treated with or without SRI, rmIL-10 or AS101, respectively. Multiple comparisons were analyzed by One-way ANOVA. Statistical data were expressed as mean±SD.. Bar = 50 μm. Fig.S6. A proposed model depicting the mechanism by which myofibers modulating IL-10-Vav1-Rac1 macrophages efferocytosis signaling pathway in inflamed muscle through activating the intrinsic TGF-β signaling.
Authors
- Liao, Zhaohong ;
- Lan, Haiqiang ;
- Jian, Xiaoting ;
- Huang, Jingwen ;
- Wang, Han ;
- Hu, Jijie ;
- Liao, Hua