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A simple, reliable and rapid isocratic liquid chromatography (LC)-mass spectrometric detection (MS) coupled with electrospray ionization (ESI) method for simultaneous separation and determination of calycosin-7-O-β-D-glucoside, ononin, calycosin and formonometin in Astragali Radix was developed. After the samples were extracted with ethanol, the optimum separation conditions for these analytes were achieved using water and acetonitrile (70:30, v/v) containing 0.2% (v/v) acetic acid as a mobile phase and a 2.0 mm×150 mm Hypersil-Keystone C18 column. Selective ion monitoring (SIM) mode and [M+H]+ ions at m/z 447, 431, 285 and 269 were used for quantitative analysis of four main active components above mentioned. The calibration curves were linear in the range of 0.4−175.0 μg/mL for calycosin-7-O-β-D-glucoside, 0.2−146.0 μg/mL for ononin, 0.4−210.0 μg/mL for calycosin and 0.5−217.0 μg/mL for formonetion, respectively. The limits of quantification (LOQ) and detection (LOD) were 0.4 μg/mL and 0.08 μg/mL for calycosin-7-O-β-D-glucoside, 0.2 μg/mL and 0.06 μg/mL for ononin, 0.4 μg/mL and 0.1 μg/mL for calycosin, 0.5 μg/mL and 0.1 μg/mL formonetion, respectively. The standard recoveries were in the range of 96.5%−104.7%. The developed method has successfully been used for the determination of four main flavonoids in Astragali Radix from various sources and can be used for identification, differentiation and quality evaluation of Astragali Radix.

The networked measurements arrive at information processing center with different time delays. As a result, the filter is required for different filtration scenes. The existing filtering algorithms are mostly proposed for specific filtration scenes. This situation motivates our present research. A linear time-varying system with unknown noise statistical properties is considered in this paper, and a unified finite horizon H ∞ performance criterion function is built for different filtration scenes, firstly. Secondly, the performance criterion function is expressed as an indefinite quadratic inequality. And, the projection in Krein space corresponding to the indefinite quadratic form is analyzed in different filtration scenes. Thirdly, two unified finite horizon H ∞ filtering methods are deduced, according to the idea of re-filtering and updating directly. Finally, a numerical simulation with different measurement arrival scenes, illustrates the effectiveness and otherness of the proposed unified finite horizon H ∞ filtering methods.

To quantitatively summarize the association of NFKBIA gene polymorphisms with autoimmune and inflammatory diseases. We surveyed studies on the association of NFKBIA gene polymorphisms with autoimmune and inflammatory diseases in PubMed. Meta-analysis was performed in a fixed/random effect model. We identified 14 studies using a PubMed search. Meta-analysis was performed for NFKBIA gene polymorphisms at positions 2758 (A/G, 5 studies), −881 (A/G, 3 studies), −826 (C/T, 3 studies), and −297 (C/T, 3 studies). We did not detect associations of NFKBIA gene polymorphisms at positions 2758, −881, −297 with autoimmune and inflammatory diseases. An association of NFKBIA gene −826C/T polymorphism with autoimmune and inflammatory diseases was found (C vs. T: OR = 1.81, 95% CI = 0.97–3.36, P = 0.06; CT + TT vs. CC: OR = 2.11, 95% CI = 1.07–4.19, P = 0.03; TT vs. CC + CT: OR = 2.20, 95% CI = 0.78–6.21, P = 0.06; TT vs. CC: OR = 2.87, 95% CI = 0.78–10.62, P = 0.11; CT vs. CC: OR = 2.02, 95% CI = 1.22–3.36, P = 0.006). This meta-analysis demonstrates that autoimmune and inflammatory diseases are associated with NFKBIA gene −826C/T polymorphism, but not with 2758A/G, −881A/G, and −279C/T.

The aim of this study was to summarize results on the association of tumor necrosis factor-α (TNF-α) promoter -308A/G polymorphism with systemic lupus erythematosus (SLE) susceptibility in Asian populations by using the meta-analysis. We searched all the publications about the association between TNF-α promoter -308A/G polymorphism and SLE in Asian populations from PubMed, Elsevier Science Direct, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI), and Wanfang (Chinese). Meta-analysis was performed for genotypes AA versus GG, GA versus GG, AA versus GG + GA, GA + AA versus GG, and A allele versus G allele in a fixed/random effect model. A total of 12 studies (1017 cases and 1086 controls) were included in the current meta-analysis (Chinese, Japanese, and Thai). When all groups were pooled, a significant association of A allele and increased SLE risk was found (OR = 1.44, 95%CI = 1.04-2.01, P = 0.03). When analyses were restricted to more ethnically homogeneous populations, similar result was found in Chinese population (OR = 1.59, 95%CI = 1.12-2.26, P = 0.009). But the association between TNF-α promoter -308 polymorphism and SLE was not observed when examining the contrast of G/A + A/A versus G/G, A/A versus A/G + G/G, A/A versus G/G, and G/A versus G/G. This meta-analysis demonstrates the association between TNF-α promoter -308A/G polymorphism and SLE in Asian populations, especially in Chinese population.

Recently, we read with interest the article by Yu et al. [1]. They performed a meta-analysis to make an estimation of the association between two single-nucleotide polymorphisms (SNPs) in the interleukin-10 (IL-10) gene promoter, -1082A [ G (rs1800896) and -592C [ A (rs1800872), and breast cancer, and the results suggest that there was lack of association between the two SNPs and breast cancer. However, I have several concerns. First, they concluded that there was lack of association between the two SNPs and breast cancer. Only 3 of the 10 studies were conducted in non-Caucasians included in the meta-analysis. Especially, the study by Guzowski et al. [2] only included 50 cases and 25 controls, and the study by Gonullu et al. [3] only included 38 cases and 24 controls. Therefore, the results of the meta-analysis indicate that there was lack of association between the two SNPs and breast cancer, mainly in Caucasians. Further studies with larger sample size are needed to clarify the role of IL-10 in breast carcinogenesis in non-Caucasians. Secondly, in the discussion, they stated that ‘‘the total subject number of rs1800896 studies seemed to be insufficient (*1,600 cases and 1,600 controls) to reach a reliable conclusion.’’ However, we estimated the expected power of rs1800896 studies at the 0.05 level of significance, assuming that odds ratio (OR) was 1.5 for difference in allele frequency, as well as the minor (a) allele frequency was 0.2, and we found the expected power was 0.999. Thus, the total subject number of rs1800896 studies was sufficient to reach a reliable conclusion. Thirdly, in the article, though the genotype contrasts (Aa genotype vs. AA genotype, aa genotype vs. AA genotype, aa?Aa genotypes vs. AA genotype, and aa genotype vs. Aa?AA genotypes) were included, the allele (a allele vs. A allele) contrast was not included. It is needed to perform the allele contrast. In conclusion, the meta-analysis suggests that there was lack of association between the two SNPs in IL-10 gene promoter and breast cancer, mainly in Caucasians. Further studies with larger sample size are needed in non-Caucasians. Meanwhile, further gene–gene and gene–environment interactions studies stratified by ethnicity are still needed. We look forward to seeing the results from these interesting studies.

To the Editor, Recently, we read with great interest the article by Wang et al. [1]. They performed a meta-analysis of 10 case– control studies (4,443 cases and 5,447 controls) to examine the association between thymidylate synthase (TYMS) gene polymorphisms and breast cancer (BC). Their metaanalysis suggests that the TSER polymorphism may increase susceptibility to BC in the Caucasian population, and the TS30-UTR polymorphism may be a genetic determinant for developing BC in the Asian population. However, the authors have several concerns related to the article. First, the results of the meta-analysis should be interpreted with caution. In the conclusion, they stated that ‘‘ethnic background should be carefully considered in further studies.’’ For the TSER polymorphism, the overall odds ratios (ORs) and the corresponding 95% confidence interval (CI) showed a statistical association between this polymorphism and BC risk under homozygote comparison, allele comparison and the recessive model. In the subgroup analysis by ethnicity, the association was detected in the Caucasian population, but not in the Asian population. While, only two studies were conducted in the Asian population, and null findings may be due to a lack of statistical power in the Asian population. Similarly, for the TS30-UTR polymorphism, the overall ORs and the corresponding 95%CI showed a statistical association between this polymorphism and BC risk under homozygote comparison. Subgroup analysis revealed that there was only a marginal association in the Asian population for homozygote comparison (P = 0.05). Nevertheless, the meta-analysis showed a modest association in the overall population (All in HWE) when the Caucasian study by Justenhoven et al. [2] was included in the analysis (P = 0.03). Furthermore, for the TS30-UTR polymorphism, only two studies were conducted in the Caucasian population under homozygote comparison, and, of the two studies, the genotype distributions of controls in one study were not in agreement with Hardy–Weinberg equilibrium (HWE) [3]. There may be no enough power to detect a significant association of the TS30-UTR polymorphism with BC in the Caucasian population. Therefore, the data included in the meta-analysis are insufficient to support the conclusion that ethnic background should be carefully considered in further studies. Second, there are some issues in the methods. In the results, they stated that ‘‘A total of 10 studies (4,443 cases and 5,447 controls) met the inclusion criteria.’’ However, in the methods, they stated that ‘‘The following criteria were used to select the eligible studies... (d) a genotype distribution among the control populations consistent with Hardy–Weinberg Equilibrium (HWE).’’ Of the ten studies, the genotype distributions among the control populations in two studies were not in agreement with HWE [3, 4]. Thus, the two studies did not meet the inclusion criteria and should be excluded. Poor reporting of meta-analysis diminishes their value to clinicians, policy makers, and other users. An international group that included experienced authors and methodologists developed PRISMA (preferred reporting items for systematic reviews and metaanalyses) as a guideline for systematic reviews and metaanalyses. The PRISMA statement consists of a 27-item Y.-F. Zou X.-L. Feng Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China

Dear editor, Complex diseases are caused by a combination of genetic, environmental, and lifestyle factors, most of which have not yet been identiWed. The vast majority of diseases, including several congenital defects and a number of adult-onset diseases, fall into complex diseases. Complex diseases do not obey the standard Mendelian patterns of inheritance [1]. In the past few decades, many studies have been performed to relate genetic polymorphisms to complex diseases. In these studies, researchers examined the association between the allele, genotype and complex diseases. They usually select a dominant genetic eVect and a recessive genetic eVect of the minor allele. However, the two genetic inheritance patterns may not be comprehensive for complex diseases, and there may be another genetic eVect of the minor allele. Recently, we investigated the association between the tumor necrosis factor- (TNF-) promoter i238A/G polymorphism (TNF- i238G>A, rs361525) and systemic lupus erythematosus (SLE) using a meta-analysis [2]. We