Objective:To retrieve relevant evidence on exercise assessment and exercise training for children with congenital heart disease at home and abroad, and to summarize the best evidence to provide reference for clinical medical staff.Methods:UpToDate, National Guidelines Clearinghouse (NGC), Registered Nurses Association of Ontario (RNAO), Scottish Intercollegiate Guidelines Network (SIGN), National Institute for Health and Care Excellence (NICE), BMJ Best Practice, American Heart Association (AHA), Cochrane Library, Joanna Briggs Institute(JBI) Evidence-Based Health Care Center Database, PubMed, CINAHL, China Biomedical Literature Database, Yimaitong, Wangfang Database, CNKI were searched, related evidence on exercise assessment and exercise training for children with congenital heart disease. The search period was from the establishment of the database to March 2021. Clinical decision-making and recommended practice used retrospective evaluation methods for quality evaluation; guidelines used the 2012 version of the clinical guideline research and evaluation system (AGREE Ⅱ) for evaluation; systematic reviews used the systematic evaluation tool (AMSTAR) for evaluation; expert consensus used JBI (2016 version) evaluate the authenticity evaluation tools of opinions and consensus articles. Two researchers independently evaluated the literature, combined with the judgment of professionals, and extracted the literature data that met the standards.Results:A total of 15 documents were included, including 2 clinical decisions, 4 guidelines, 1 recommended practice, 5 systematic reviews, 3 expert consensus, and 22 best evidences. Including related personnel, exercise evaluation, exercise monitoring, exercise classification, exercise training, and exercise follow-up.Conclusions:This study summarizes the best evidence of exercise assessment and exercise training for children with congenital heart disease, and provides evidence-based evidence for clinical practice. It is recommended that children with congenital heart disease undergo exercise assessment and formulate a personalized exercise training program to promote the transformation of the best evidence into clinical practice.

【Objective】 To investigate the effect of HLA-G expressed in platelets on Tax protein of human T cell leukemia type 1 virus (HTLV-1). 【Methods】 Platelets were isolated from anticoagulant whole blood, and HLA-G molecule on platelet membrane was detected by flow cytometry. The content of secretory HLA-G before and after platelet lysis was detected by ELISA, HTLV-1 human lymphoma cells MT2 were cultured with platelet lysate (PL). The effect of HLA-G in platelets on the expression of HTLV-1 protein Tax was evaluated by Western blot (WB). 【Results】 Membrane type mHLA-G was highly expressed on the surface of platelet membrane. The expression of secretory sHLA-G (ng/mL) increased after platelet lysis (15.73±1.01) vs (6.65±0.47), the expression of sHLA-G increased with the increase of platelet concentration in a dose-dependent manner. Compared with fetal bovine serum, PL significantly promoted the high expression of HLA-G protein and HTLV-1 virus tax protein in MT2 cells, and the addition of anti-HLA-G antibody to PL could effectively inhibit the expression of Tax and HLA-G protein. 【Conclusion】 High expression of immune tolerance molecule HLA-G on platelets can induce high expression of HTLV-1 protein Tax in human lymphoma cell MT2, which contributes to viral infection.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is an underdiagnosed genetic heart disease worldwide. The management and prognosis of obstructive HCM (HOCM) and non-obstructive HCM (HNCM) are quite different, but it also remains challenging to discriminate these two subtypes. HCM is characterized by dysmetabolism, and myocardial amino acid (AA) metabolism is robustly changed. The present study aimed to delineate plasma AA and derivatives profiles, and identify potential biomarkers for HCM. METHODS: Plasma samples from 166 participants, including 57 cases of HOCM, 52 cases of HNCM, and 57 normal controls (NCs), who first visited the International Cooperation Center for HCM, Xijing Hospital between December 2019 and September 2020, were collected and analyzed by high-performance liquid chromatography-mass spectrometry based on targeted AA metabolomics. Three separate classification algorithms, including random forest, support vector machine, and logistic regression, were applied for the identification of specific AA and derivatives compositions for HCM and the development of screening models to discriminate HCM from NC as well as HOCM from HNCM. RESULTS: The univariate analysis showed that the serine, glycine, proline, citrulline, glutamine, cystine, creatinine, cysteine, choline, and aminoadipic acid levels in the HCM group were significantly different from those in the NC group. Four AAs and derivatives (Panel A; proline, glycine, cysteine, and choline) were screened out by multiple feature selection algorithms for discriminating HCM patients from NCs. The receiver operating characteristic (ROC) analysis in Panel A yielded an area under the ROC curve (AUC) of 0.83 (0.75-0.91) in the training set and 0.79 (0.65-0.94) in the validation set. Moreover, among 10 AAs and derivatives (arginine, phenylalanine, tyrosine, proline, alanine, asparagine, creatine, tryptophan, ornithine, and choline) with statistical significance between HOCM and HNCM, 3 AAs (Panel B; arginine, proline, and ornithine) were selected to differentiate the two subgroups. The AUC values in the training and validation sets for Panel B were 0.83 (0.74-0.93) and 0.82 (0.66-0.98), respectively. CONCLUSIONS The plasma AA and derivatives profiles were distinct between the HCM and NC groups. Based on the differential profiles, the two established screening models have potential value in assisting HCM screening and identifying whether it is obstructive.
Humans ; Amino Acids ; Cysteine ; Cardiomyopathy, Hypertrophic/diagnosis* ; Biomarkers ; Proline ; Arginine ; Ornithine ; Glycine ; Choline