Background Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are assumed to be prognostic factors in many diseases such as inflammatory diseases, cardiovascular diseases and cancer. However, NLR and PLR are race specific, it is important to determine the reference values of NLR and PLR in different races. The study aimed to investigate the reference range of NLR and PLR in Chinese Han population from Chaoshan region in South China. Methods A retrospective study was conducted in the First Affiliated Hospital of Shantou University Medical College in South China. Five thousand healthy adults aged 20–69 years were included. NLR and PLR were determined. Results Of 5000 healthy adults, 2500 men and 2500 women were included. The mean NLR and PLR across all ages for men and women were 1.59 ± 0.59, 92.88 ± 28.70, 1.62 ± 0.64 and 108.02 ± 32.99, respectively. The 95% reference range of NLR in normal male and female are 0.43~2.75 and 0.37~2.87, PLR are 36.63~149.13 and 43.36~172.68, respectively. The female had a higher NLR at age 30~49 than the male while the NLR at age 60~69 was higher in male than in female. The PLR was higher in female than in male. Conclusion The study provides reference data on NLR and PLR from different age and sex groups in South China. NLR and PLR varied with age and sex.
Abstract-Graph model is emerging as a very effective tool for learning the complex structures and relationships hidden in data. Generally, the critical purpose of graph-oriented learning algorithms is to construct an informative graph for image clustering and classification tasks. In addition to the classical K-nearestneighbor and r-neighborhood methods for graph construction, l1-graph and its variants are emerging methods for finding the neighboring samples of a center datum, where the corresponding ingoing edge weights are simultaneously derived by the sparse reconstruction coefficients of the remaining samples. However, the pair-wise links of l1-graph are not capable of capturing the high order relationships between the center datum and its prominent data in sparse reconstruction. Meanwhile, from the perspective of variable selection, the l1 norm sparse constraint, regarded as a LASSO model, tends to select only one datum from a group of data that are highly correlated and ignore the others. To simultaneously cope with these drawbacks, we propose a new elastic net hypergraph learning model, which consists of two steps. In the first step, the Robust Matrix Elastic Net model is constructed to find the canonically related samples in a somewhat greedy way, achieving the grouping effect by adding the l2 penalty to the l1 constraint. In the second step, hypergraph is used to represent the high order relationships between each datum and its prominent samples by regarding them as a hyperedge. Subsequently, hypergraph Laplacian matrix is constructed for further analysis. New hypergraph learning algorithms, including unsupervised clustering and multi-class semisupervised classification, are then derived. Extensive experiments on face and handwriting databases demonstrate the effectiveness of the proposed method.
It has been previously demonstrated that lipopolysaccharides (LPS) inhibit the viability, migration, adhesion and in vitro angiogenesis of late endothelial progenitor cells (EPCs). However, the mechanisms underlying this LPS‑induced impairment of late EPC functional activity are unknown. The aim of the present study was to investigate whether Toll‑like receptor 4 (TLR4) is expressed and functional on late EPCs, using late EPCs of 3‑5 passages. Cells were deprived of serum for 24 h prior to experiments and incubated with 10 µg/ml LPS for 24 h with or without pretreatment with 2 µg/ml TLR4 signaling inhibitor CLI‑095 for 30 min. The viability, migration, adhesion and in vitro angiogenesis, as well as the expression of silent information regulator 1 (SIRT1), in late EPCs were evaluated. Treatment with 10 µg/ml LPS decreased the viability, migration and adhesion abilities, and in vitro angiogenesis of late EPCs. Pretreatment with the TLR4 signaling inhibitor reversed this LPS‑induced dysfunction of late EPCs. LPS downregulated the expression of SIRT1 protein, however, blocking TLR4 attenuated the effect of LPS on SIRT1 expression. Therefore, the results of the present study indicate that LPS impaired the functional activity of late EPCs via TLR4, which may be associated with decreased SIRT1 expression.
Objectives:To demonstrate the prevalence of ABO blood groups with deep venous thromboembolism in Chinese Han population.Methods:A retrospective study was conducted between January 2010 and March 2015 in The First Affiliated Hospital of Shantou University Medical College in Chaoshan District of Guangdong Province in South China. Eighty nine patients with confirmed diagnosis of deep venous thromboembolism were included. Frequency of blood groups was determined.Results:Of 89 patients with deep venous thromboembolism, 28 patients had blood group A (31.5%), 28 patients had blood group B (31.5%), 13 patients had blood group AB (14.6%), and 20 patients had blood group O (22.5%). Compared with O blood type, the odds ratios of deep venous thromboembolism for A, B and AB were 2.23 (95% CI, 1.27-3.91), 2.34 (95% CI, 1.34-4.09) and 4.43 (95% CI, 2.24-8.76).Conclusion:There is a higher risk of venous thromboembolism in non-O blood groups than O group.
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