Objective To observe the impact of collagen patches using 1-ethyl-3- （3-dimethylaminopropyl) carbod-iimide hydrochloride chemistry （EDC） to conjugate vascular endothelial growth factor （VEGF） ＋ basic fibroblast growth factor （bFGF） or VEGF alone on the survival rate of transplanted human bone morrow mesenchymal stem cells （hBM-MSCs）in vitro and in vivo. Methods Collagen patches which were activated by EDC were used as the control group，and EDC activated collagen patches that were conjugated with VEGF or VEGF ＋ bFGF were used as the experiment groups（VEGF group and VEGF ＋ bFGF group）. hBM-MSCs （0.5×106/patch） were used as seeding cells to construct engineered heart tissue （EHT）. MTT assay was performed to assess in vitro proliferation of hBM-MSCs on 3 different collagen patches. Ventricular aneurysm model after myocardial infarction was created by left anterior descending artery （LAD） ligation in male SD rats，and EHT which were constructed with 3 different patches were used for ventricular plasty. Four weeks later，immunofluorescence staining was used to examine arteriole density （anti-α-SMA staining） and transplanted cell survival （anti-h-mitochondria staining）. Results （1） hMSCs proliferation in VEGF group and VEGF ＋ bFGF group was significantly better than that in the control group on the 2nd and 4th day after cell transplantation （P＜0.05）； （2） Four weeks afterEHT implantation，immunofluorescence staining for α-SMA revealed that arteriole density of VEGF group and VEGF ＋ bFGF group was significantly higher than that of the control group （P＜0.05）； （3） Immunofluorescence staining forh-mitochondria showed that survival rates of transplanted hBM-MSCs of VEGF group and VEGF ＋ bFGF group were significantly higher than that of the control group （P＜0.05）； （4） There was a significantly positive correlation between survival rate of hBM-MSCs and arteriole density （r 2=0.99，P=0.02）. Conclusion VEGF or VEGF ＋ bFGF conjugated collagen patch can significantly improve hBM-MSCs proliferation in vitro and enhance survival rate of transplanted hBM-MSCs by accelerating revascularization of EHT in vivo.
With the development of artificial intelligence, machine learning has been widely used in diagnosis of diseases. It is crucial to conduct diagnostic test accuracy studies and evaluate the performance of models reasonably to improve the accuracy of diagnosis. For machine learning-based diagnostic test accuracy studies, this paper introduces the principles of study design in the aspects of target conditions, selection of participants, diagnostic tests, reference standards and ethics.