Evaluation of Platelet Count by Different Methods in Hyperlipidemia Specimens.

BACKGROUND: Changes in platelet count are associated with a variety of diseases and treatments. Measuring it gives better insight into the expected outcome. Our aim was to evaluate the accuracy of three methods for platelet count in hyperlipidemia samples. METHODS: Sixty non-lipid whole bloods from 60 individuals were included: 20 in low platelet count group, 20 in medium platelet count group, and 20 in high platelet count group. Then, 400 µL plasma was exchanged with 400 µL fat emulsion. Platelet count was measured after replacement by three methods, impedance method (Plt-I), optical method (Plt-O), and fluorescence method (Plt-F). RESULTS: In the low platelet count group with fat emulsion plasma exchange, except for Plt-O, other methods showed the predefined acceptance criterion (± 10%) covered the mean bias and 95% CI of proportional bias (slope) which were obtained from Bland-Altman plot and Passing-Bablok algorithm, respectively. In medium and high platelet count group with fat emulsion plasma exchange, the predefined acceptance mean bias and criterion of 95% CI of proportional bias (slope) and intercept were met only in Plt-F. In the medium platelet count group, the mean bias was -1.600% and the 95%CI of slope and intercept were 1.000 (0.815 to 1.071) and -0.500 (-12.831 to 23.907), respectively. In the high platelet count group, the mean bias was -2.250% and the 95%CI of slope and intercept were 1.071 (0.974 to 1.225) and -33.8142 (-113.703 to 8.339), respectively. CONCLUSIONS: Our results show that the Plt-F can more accurately reflect the true platelet count of lipemia specimens compared with Plt-I or Plt-O.

Four Low Expression LncRNAs are Associated with Prognosis of Human Lung Adenocarcinoma.

BACKGROUND: Lung cancer is the most prevalent and deadliest cancer worldwide. The present study aims to determine the prognosis value of low expression long non-coding RNAs (lncRNAs) in LUAD. METHODS: RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) data-base. Dysregulated genes between LUAD and paracancerous tissue were screened by GeneSpringGX. Prognostic lncRNAs which were low expressed in LUAD were filtrated by Ualcan, then further verified through the TCGA database. The association between clinicopathological features and the expression level of these lncRNAs was tested by chi-square test. Cox regression analysis was performed to test independent prognosis risk factors. Diagnostic efficiency was predicted by receiver operating characteristic (ROC) analysis. Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to explore potential functions of these prognostic signatures. RESULTS: Nine prognostic lncRNAs (LINC00092, LINC00908, WWC2-AS2, RPL13AP17, CHIAP2, SFTA1P, SIGLEC17P, CYP2B7P1, CYP4Z2P) were screened out through Ualcan and further verified by TCGA. Among them, six lncRNAs (RPL13AP17, CHIAP2, SFTA1P, SIGLEC17P, CYP2B7P1, CYP4Z2P) were pseudogene transcripts. Multivariate Cox regression analysis showed that three lnRNAs (LINC00908, WWC2-AS2 CYP2B7P) were independent prognostic risk factors for OS and two lncRNAs (WWC2-AS2, SIGLEC17P) were independent prognostic risk factors for RFS in LUAD patients. Meanwhile, they showed powerful diagnostic value by ROC curve analysis. GO analysis revealed correlation genes of prognostic signatures were mainly enriched in plasma membrane, plasma membrane part, purine nucleotide binding, cytoskeleton and ribonucleotide binding and KEGG pathway analysis showed mainly enriched in cell adhesion molecules. CONCLUSIONS: The results illuminated that four lncRNAs (LINC00908, WWC2-AS2, CYP2B7P, SIGLEC17P) may be a powerful diagnostic and prognostic assessment tool for human LUAD.

[Analysis of Gene Mutation Types of Thalassemia in Fuzhou Area of China].

OBJECTIVE: To investigate the gene mutation types and spectrum of α, ß-thalassemia in Fuzhou area of China. METHODS: Thalassemia gene screening was performed in the women receiving physical, prenatal, and pre-pregnancy examination, and the patients with suspected thalassemia in our hospital from July 2013 to March 2018.Genotypes of thalassem were detected by Gap-PCR and RDB-PCR. RESULTS: 1042 were positive among 2074 suspected cases with a positive rate of 50.24%; 618 cases were confirmed to be α-thalassemia and with a positive rate of 29.8%; 409 cases were confirmed to be ß-thalassemia with a positive rate of 19.72%. 15 cases were confirmed to be α-ß complex thalassemia with a positive rate of 0.72%. the --SEA/αα(76.54%) was the most common genotype among α-thalassemia, -α3.7/αα(10.03%) and -α4.2/αα(2.91%) in hot pursuit. In addition, IVS-II-55 (T->G) and IVS-II-119 (-G, +CTCGGCCC) were newly found alpha mutations; the IVS-2-654 (C→T) (40.83%) was the most common genotype among ß-thalassemia, CD41-42 (-TCTT) (35.94%) and CD17 (A→T) (9.78%) in hot pursuit. CONCLUSION: The genotype of thalassemia in Fuzhou area is highly heterogenic, --SEA/αα is the most common genotype among α-thalassemia, IVS-2-654 (C→T) is the most common genotype among ß-thalassemia, Meanwhile, two α-mutation sites are found in this study which were not reported in the Database of Human Hemoglobin Variants and Thalassemias.