Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

BACKGROUND: Patient-based real-time quality control (PBRTQC) has gained attention because of its potential to continuously monitor the analytical quality in situations wherein internal quality control (IQC) is less effective. Therefore, we tried to investigate the application of PBRTQC method based on an artificial intelligence monitoring (AI-MA) platform in quality risk monitoring of Down syndrome (DS) serum screening. METHODS: The DS serum screening item determination data and relative IQC data from January 4 to September 7 in 2021 were collected. Then, PBRTQC exponentially weighted moving average (EWMA) and moving average (MA) procedures were built and optimized in the AI-MA platform. The efficiency of the EWMA and MA procedures with intelligent and traditional control rules were compared. Next, the optimal EWMA procedures that contributed to the quality assurance of serum screening were run and generated early warning cases were investigated. RESULTS: Optimal EWMA and MA procedures on the AI-MA platform were built. Comparison results showed the EWMA procedure with intelligent QC rules but not traditional quality rules contained the best efficiency. Based on the AI-MA platform, two early warning cases were generated by using the optimal EWMA procedure, which finally found were caused by instrument failure. Moreover, the EWMA procedure could truly reflect the detection accuracy and quality in situations wherein traditional IQC products were unstable or concentrations were inappropriate. CONCLUSIONS: The EWMA procedure built by the AI-MA platform could be a good complementary control tool for the DS serum screening by truly and timely reflecting the detection quality risks.

Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction.

Background: ST-elevation myocardial infarction (STEMI) is a myocardial infarction (MI) with ST-segment exaltation of electrocardiogram (ECG) caused by vascular occlusion of the epicardium. However, the diagnostic markers of STEMI remain little. Methods: STEMI raw microarray data are acquired from the Gene Expression Omnibus (GEO) database. Based on GSE60993 and GSE61144, differentially expressed genes (DEGs) are verified via R software, and key modules associated with pathological state of STEMI are verified by weighted correlation network analysis (WGCNA). Take the intersection gene of key module and DEGs to perform the pathway enrichment analyses by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Construct the protein-protein interaction (PPI) network by Cytoscape. Then, select and identify the diagnostic biomarkers of STEMI by least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Finally, assess the infiltration of immune cells of STEMI by CIBERSORT and analyze the correlation between diagnostic markers and infiltrating immune cells. Results: We get 710 DEGs in the STEMI group and 376 genes associated with STEMI in blue module. 92 intersection genes were concentrated in 30 GO terms and 2 KEGG pathways. 28 hub genes involved in the development of STEMI. Moreover, upregulated ALOX5AP (AUC = 1.00) and BST1 (AUC = 1.00) are confirmed as diagnostic markers of STEMI. CD8+T cells, regulatory T (Treg) cells, resting natural killer (NK) cells, M0 macrophages, resting mast cells, and neutrophils are related to the procession of STEMI. Moreover, ALOX5AP and BST1 are positively related to resting NK cells, M0 macrophages, and neutrophils, while ALOX5AP and BST1 are negatively related to CD8+ T cells, Treg cells, and resting mast cells. Conclusion: ALOX5AP and BST1 may be the diagnostic markers of STEMI. Immune cell infiltration plays a key role in the development of STEMI.

Up-regulation of BTLA expression in myeloid dendritic cells associated with the treatment outcome of neonatal sepsis.

Dentritic cells (DCs) dysfunction has been verified detrimental for sepsis and B and T lymphocyte attenuator (BTLA) is an immune-regulatory receptor shown to be associated with DCs dysfunction. However, the role of BTLA expression in myeloid DCs (mDCs) in neonatal sepsis is unknown. In the current study, we found BTLA-expressing mDCs were elevated in neonates with sepsis and the BTLA expression level in mDCs was positively correlated to the severity of sepsis. The presence of BTLA negatively regulated the phagocytosis capacity and bactericidal ability of mDCs as well as the maturation markers expression of mDCs. Our data also showed BTLA+mDCs shifted into an anti-inflammatory phenotype with decreased expression of IL-6, TNF-α and IL-12, but increased IL-10. in addition, we found BTLA expression indeedly altered the mDCs allo-stimulatory capacity. Therefore, BTLA expression in mDCs could be a useful predictive marker for neonatal sepsis and targeting BTLA expression in mDCs may be a new therapeutic strategy.

[Identification of a critical region on chromosome 4p16.3 for Wolf-Hirschhorn syndrome-associated fetal growth retardation].

OBJECTIVE: To analyze ultrasonographic finding in fetuses with Wolf-Hirschhorn syndrome (WHS) and refine the critical region on chromosome 4p16.3 for WHS-associated fetal growth retardation (FGR). METHODS: In total 2262 fetuses with abnormal ultrasonographic findings who underwent prenatal karyotyping and chromosomal microarray analysis were reviewed. WHS-associated 4p deletions detected in these fetuses were compared, and prenatal ultrasound findings in such fetuses were summarized. Meanwhile, WHS cases with prenatal ultrasound findings and isolated 4p deletions in previous studies were included for further analysis. An analysis of smallest region of overlap (SRO) among discrepant 4p deletions in these cases above was performed to define a critical region for FGR. RESULTS: 4p deletions were detected in 10 of the 2262 fetuses and 5.0% of the 202 fetuses with FGR. Combined with 80 WHS cases from previous studies, the most common prenatal ultrasound finding was FGR, which yielded a frequency of 76.7%. In addition, a SRO spanning approximately 419 kb (genomic position: 1.32-1.74 Mb) on chromosome 4p16.3 was discovered by comparing the unusual 4p deletions among the 10 fetuses. The region contained seven protein-coding genes, including TACC3, SLBP, TMEM129, FAM53A, MAEA, UVSSA and CRIPAK. CONCLUSION: For fetuses with WHS, the most common prenatal ultrasound phenotype was FGR. A region between 1.32 Mb to 1.74 Mb from the telomere on chromosome 4p16.3 is critical for WHS-associated FGR, for which TACC3 and SLBP are the candidate genes.