Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.     

Significance of Serum Pepsinogens as a Biomarker for Gastric Cancer and Atrophic Gastritis Screening: A Systematic Review and Meta-Analysis

Background

Human pepsinogens are considered promising serological biomarkers for the screening of atrophic gastritis (AG) and gastric cancer (GC). However, there has been controversy in the literature with respect to the validity of serum pepsinogen (SPG) for the detection of GC and AG. Consequently, we conducted a systematic review and meta-analysis to assess the diagnostic accuracy of SPG in GC and AG detection.

Methods

We searched PubMed, Embase, and the Chinese National Knowledge Infrastructure (CNKI) for correlative original studies published up to September 30, 2014. The summary sensitivity, specificity, positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR-), area under the summary receiver operating characteristic curve (AUC) and diagnostic odds ratio (DOR) were used to evaluate SPG in GC and AG screening based on bivariate random effects models. The inter-study heterogeneity was evaluated by the I² statistics and publication bias was assessed using Begg and Mazumdar’s test. Meta-regression and subgroup analyses were performed to explore study heterogeneity.

Results

In total, 31 studies involving 1,520 GC patients and 2,265 AG patients were included in the meta-analysis. The summary sensitivity, specificity, DLR+, DLR-, AUC and DOR for GC screening using SPG were 0.69 (95% CI: 0.60–0.76), 0.73 (95% CI: 0.62–0.82), 2.57 (95% CI: 1.82–3.62), and 0.43 (95% CI: 0.34–0.54), 0.76 (95% CI: 0.72–0.80) and 6.01 (95% CI: 3.69–9.79), respectively. For AG screening, the summary sensitivity, specificity, DLR+, DLR-, AUC and DOR were 0.69 (95% CI: 0.55–0.80), 0.88 (95% CI: 0.77–0.94), 5.80 (95% CI: 3.06–10.99), and 0.35 (95% CI: 0.24–0.51), 0.85 (95% CI: 0.82–0.88) and 16.50 (95% CI: 8.18–33.28), respectively. In subgroup analysis, the use of combination of concentration of PGI and the ratio of PGI:PGII as measurement of SPG for GC screening yielded sensitivity of 0.70 (95% CI: 0.66–0.75), specificity of 0.79 (95% CI: 0.79–0.80), DOR of 6.92 (95% CI: 4.36–11.00), and AUC of 0.78 (95% CI: 0.72–0.81), while the use of concentration of PGI yielded sensitivity of 0.55 (95% CI: 0.51–0.60), specificity of 0.79 (95% CI: 0.76–0.82), DOR of 6.88 (95% CI: 2.30–20.60), and AUC of 0.77 (95% CI: 0.73–0.92). For AG screening, the use of ratio of PGI:PGII as measurement of SPG yielded sensitivity of 0.69 (95% CI: 0.52–0.83), specificity of 0.84 (95% CI: 0.68–0.93), DOR of 11.51 (95% CI: 6.14–21.56), and AUC of 0.83 (95% CI: 0.80–0.86), the use of combination of concentration of PGI and the ratio of PGI:PGII yield sensitivity of 0.79 (95% CI: 0.72–0.85), specificity of 0.89 (95% CI: 0.85–0.93), DOR of 24.64 (95% CI: 6.95–87.37), and AUC of 0.87 (95% CI: 0.81–0.92), concurrently, the use of concentration of PGI yield sensitivity of 0.46 (95% CI: 0.38–0.54), specificity of 0.93 (95% CI: 0.91–0.95), DOR of 19.86 (95% CI: 0.86–456.91), and AUC of 0.86 (95% CI: 0.52–1.00).

Conclusion

SPG has great potential as a noninvasive, population-based screening tool in GC and AG screening. In addition, given the potential publication bias and high heterogeneity of the included studies, further high quality studies are required in the future.     

Potent neutralizing anti-CD1d antibody reduces lung cytokine release in primate asthma model

CD1d is a receptor on antigen-presenting cells involved in triggering cell populations, particularly natural killer T (NKT) cells, to release high levels of cytokines. NKT cells are implicated in asthma pathology and blockade of the CD1d/NKT cell pathway may have therapeutic potential. We developed a potent anti-human CD1d antibody (NIB.2) that possesses high affinity for human and cynomolgus macaque CD1d (K_D ∼100 pM) and strong neutralizing activity in human primary cell-based assays (IC₅₀ typically <100 pM). By epitope mapping experiments, we showed that NIB.2 binds to CD1d in close proximity to the interface of CD1d and the Type 1 NKT cell receptor β-chain. Together with data showing that NIB.2 inhibited stimulation via CD1d loaded with different glycolipids, this supports a mechanism whereby NIB.2 inhibits NKT cell activation by inhibiting Type 1 NKT cell receptor β-chain interactions with CD1d, independent of the lipid antigen in the CD1d antigen-binding cleft. The strong in vitro potency of NIB.2 was reflected in vivo in an Ascaris suum cynomolgus macaque asthma model. Compared with vehicle control, NIB.2 treatment significantly reduced bronchoalveolar lavage (BAL) levels of Ascaris-induced cytokines IL-5, IL-8 and IL-1 receptor antagonist, and significantly reduced baseline levels of GM-CSF, IL-6, IL-15, IL-12/23p40, MIP-1α, MIP-1β, and VEGF. At a cellular population level NIB.2 also reduced numbers of BAL lymphocytes and macrophages, and blood eosinophils and basophils. We demonstrate that anti-CD1d antibody blockade of the CD1d/NKT pathway modulates inflammatory parameters in vivo in a primate inflammation model, with therapeutic potential for diseases where the local cytokine milieu is critical.     

Comparison of dwarf bamboos (Indocalamus sp.) leaf parameters to determine relationship between spatial density of plants and total leaf area per plant

The relationship between spatial density and size of plants is an important topic in plant ecology. The self‐thinning rule suggests a ?3/2 power between average biomass and density or a ?1/2 power between stand yield and density. However, the self‐thinning rule based on total leaf area per plant and density of plants has been neglected presumably because of the lack of a method that can accurately estimate the total leaf area per plant. We aimed to find the relationship between spatial density of plants and total leaf area per plant. We also attempted to provide a novel model for accurately describing the leaf shape of bamboos. We proposed a simplified Gielis equation with only two parameters to describe the leaf shape of bamboos one model parameter represented the overall ratio of leaf width to leaf length. Using this method, we compared some leaf parameters (leaf shape, number of leaves per plant, ratio of total leaf weight to aboveground weight per plant, and total leaf area per plant) of four bamboo species of genus Indocalamus Nakai (I. pedalis (Keng) P.C. Keng, I. pumilus Q.H. Dai and C.F. Keng, I. barbatus McClure, and I. victorialis P.C. Keng). We also explored the possible correlation between spatial density and total leaf area per plant using log‐linear regression. We found that the simplified Gielis equation fit the leaf shape of four bamboo species very well. Although all these four species belonged to the same genus, there were still significant differences in leaf shape. Significant differences also existed in leaf area per plant, ratio of leaf weight to aboveground weight per plant, and leaf length. In addition, we found that the total leaf area per plant decreased with increased spatial density. Therefore, we directly demonstrated the self‐thinning rule to improve light interception.     

不同产地丁香挥发性成分分析

采用顶空固相微萃取-气相色谱-质谱联用技术对产自国内外4个地区的丁香(Eugenia caryophyllata Thunb.)挥发性成分进行了检测,并以峰面积归一化法计算了各组分的相对含量。结果显示,从4个产地13批次丁香中共鉴定出挥发性成分72种(匹配度均高于75),其中,主要成分含量排名前两位的均为丁香酚、(-)-α-芹子烯,排名第三位的挥发性成分分别为:顺式-α-没药烯(马达加斯加塔马塔夫,平均为3.75%)、罗勒烯(中国广东,平均为4.21%)、亚麻三烯(中国广西,平均为3.74%)、丁香烯(印度尼西亚爪哇岛,平均为3.60%)。表明同一产地的丁香挥发性成分具有一定的相似性,不同产地丁香挥发性成分也有一定的差异,这对丁香产地的鉴别具有重要意义。主成分分析和聚类分析的结果既可以将4个产地的丁香很好地区分开来,又能反映出它们之间的亲缘关系。本研究采用HS-SPME-GC-MS方法检测不同产地丁香挥发性成分并结合主成分分析(PCA)及聚类分析法,能有效区分4个产地的丁香,该方法可作为丁香产地的鉴别方法,也为进一步比较不同产地丁香挥发性成分的差异及质量控制提供了新思路。     

Use of random forest in FTIR analysis of LDL cholesterol and tri‐glycerides for hyperlipidemia

A quantitative determination method for the diagnosis of hyperlipidemia was developed using Fourier transform infrared (FTIR) spectroscopy. Random forest (RF) was demonstrated as a potential multivariate algorithm for the FTIR analysis of low‐density lipoprotein cholesterol (LDL‐C) and tri‐glycerides (TG) in human serum samples. The informative wavebands for LDL‐C and TG were selected based on the Gini importance. The selected wavebands were mainly within the fingerprint region. The RF modeling results were better than those derived using PLS in validation process, because the chance for over‐fitting was possibly eliminated in RF algorithm. ARF also demonstrated favorable results in the test process. The prospective model exhibited a higher than 90% true prediction in negative/positive properties for male and female samples. These clinical statistical results indicated the optimization of RF algorithm performed accurately in the FTIR determination of LDL‐C and TG. RF is evaluated as a promising tool for diagnosing and controlling hyperlipidemia in populations. The parameter optimization methodology is useful in the improving model accuracy using FTIR spectroscopic technology. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1693–1702, 2015     

植物转录因子家族在耐盐抗旱调控网络中的作用

植物对干旱和高盐环境的适应是一个复杂的生物学过程,涉及多条信号通路的交叉调控。其中,通过转录因子发挥的调控作用对增强植物的耐盐抗旱特性具有重要意义。结合最近的相关研究,重点综述了植物中的MYB、b ZIP、WRKY、NAC、AP2/ERF等各类转录因子在响应高盐干旱胁迫的信号通路中与ABA信号通路、ROS信号通路、Sn RK2信号通路及H2O2信号通路等存在的交叉整合作用,以期为利用基因工程手段增强植物的耐盐抗旱性提供更有效的改良途径。     

Downregulation of TNIP1 Expression Leads to Increased Proliferation of Human Keratinocytes and Severer Psoriasis-Like Conditions in an Imiquimod-Induced Mouse Model of Dermatitis

Psoriasis is a chronic, inflammatory skin disease involving both environmental and genetic factors. According to genome-wide association studies (GWAS), the TNIP1 gene, which encodes the TNF-α–induced protein 3-interacting protein 1 (TNIP1), is strongly linked to the susceptibility of psoriasis. TNIP1 is a widely expressed ubiquitin sensor that binds to the ubiquitin-editing protein A20 and restricts TNF- and TLR-induced signals. In our study, TNIP1 expression decreased in specimens of epidermis affected by psoriasis. Based on previous studies suggesting a role for TNIP1 in modulating cancer cell growth, we investigated its role in keratinocyte proliferation, which is clearly abnormal in psoriasis. To mimic the downregulation or upregulation of TNIP1 in HaCaT cells and primary human keratinocytes (PHKs), we used a TNIP1 specific small interfering hairpin RNA (TNIP1 shRNA) lentiviral vector or a recombinant TNIP1 (rTNIP1) lentiviral vector, respectively. Blocking TNIP1 expression increased keratinocyte proliferation, while overexpression of TNIP1 decreased keratinocyte proliferation. Furthermore, we showed that TNIP1 signaling might involve extracellular signal-regulated kinase1/2 (Erk1/2) and CCAAT/enhancer-binding protein β (C/EBPβ) activity. Intradermal injection of TNIP1 shRNA in BALB/c mice led to exaggerated psoriatic conditions in imiquimod (IMQ)-induced psoriasis-like dermatitis. These findings indicate that TNIP1 has a protective role in psoriasis and therefore could be a promising therapeutic target.