Numerous studies have demonstrated that plant species diversity enhances ecosystem functioning in terrestrial ecosystems, including diversity effects on insect arthropods (herbivores, predators and parasitoids) and plants. Yet, the effects of increased plant diversity across trophic levels in different ecosystems and biomes have not yet been explored on a global scale. Through a global meta-analysis of 2914 observations from 351 studies, we found that increased plant species richness reduced herbivore abundance and damage but increased predator and parasitoid abundance, predation, parasitism, and overall plant performance. Moreover, increased predator/parasitoid performance was correlated with reduced herbivore abundance and enhanced plant performance. We

The generalized leverage of an estimator is de®ned in regression models as a measure of the importance of individual observations. We derive a simple but powerful result, developing an explicit expression for leverage in a general M-estimation problem, of which the maximum likelihood problems are special cases. A variety of applications are considered, most notably to the exponential family non-linear models. The relationship between leverage and local in¯uence is also discussed. Numerical examples are given to illustrate our results.

Numerous researchers have investigated the associations among methylenetetrahydrofolate reductase gene (MTHFR) C677T polymorphism, homocysteine (Hcy) concentration, and hypertension. However, the results are controversial. Thus, a meta‐analysis implementing Mendelian randomization approach was conducted to examine the hypothesis that elevated Hcy concentration plausibly contributes to increased risk of hypertension. Based on several inclusion and exclusion criteria, eligible studies were selected to explore the correlation between MTHFR C677T and hypertension risk, MTHFR C677T and Hcy concentration in hypertension, and Hcy concentration and hypertension, and they were evaluated by odds ratios (ORs), effect size (ES), and standard mean difference with their corresponding 95% confidence intervals (95% CIs), respectively. Moreover, Mendelian randomization was implemented to evaluate the relationship between Hcy and hypertension. Consequently, 14 378 cases and 25 795 controls were involved in this study and the results showed that MTHFR C677T led to an elevated risk of hypertension (for T vs C: OR = 1.27, 95% CI = 1.17‐1.37; for TT vs CC: OR = 1.53, 95% CI = 1.30‐1.79). Additionally, in hypertensive subjects, the pooled Hcy concentration in individuals of TT genotype was 7.74 μmol/L (95% CI: 5.25‐10.23) greater than that in individuals of CC genotype. Moreover, the pooled Hcy concentration in hypertensive was 0.69 μmol/L (95% CI: 0.50‐0.87) greater than that in controls. The estimated causal OR associated with hypertension was 1.32 for 5 μmol/L Hcy increment. Via MTHFR C677T polymorphism, the findings in the present study demonstrated that there exists evidence on causal link between Hcy concentration and the risk of hypertension.

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Ovarian cancer (OV) is one of the leading causes of cancer deaths in women worldwide. Late diagnosis and heterogeneous treatment result to poor survival outcomes for patients with OV. Therefore, we aimed to develop novel biomarkers for prognosis prediction from the potential molecular mechanism of tumorigenesis. Eight eligible data sets related to OV in GEO database were integrated to identify differential expression genes (DEGs) between tumour tissues and normal. Enrichment analyses discovered DEGs were most significantly enriched in G2/M checkpoint signalling pathway. Subsequently, we constructed a multi‐gene signature based on the LASSO Cox regression model in the TCGA database and time‐dependent ROC curves showed good predictive accuracy for 1‐, 3‐ and 5‐year overall survival. Utility in various types of OV was validated through subgroup survival analysis. Risk scores formulated by the multi‐gene signature stratified patients into high‐risk and low‐risk, and the former inclined worse overall survival than the latter. By incorporating this signature with age and pathological tumour stage, a visual predictive nomogram was established, which was useful for clinicians to predict survival outcome of patients. Furthermore, SNRPD1 and EFNA5 were selected from the multi‐gene signature as simplified prognostic indicators. Higher EFNA5 expression or lower SNRPD1 indicated poorer outcome. The correlation between signature gene expression and clinical characteristics was observed through WGCNA. Drug‐gene interaction was used to identify 16 potentially targeted drugs for OV treatment. In conclusion, we established novel gene signatures as independent prognostic factors to stratify the risk of OV patients and facilitate the implementation of personalized therapies.

Two Chinese herb-derived small molecule telomerase activators, astragaloside IV (AG-IV) and cycloastragenol (CAG), have recently been shown to improve the proliferative response of CD8+ T lymphocytes from HIV-infected patients by upregulating telomerase activity. Here, we examined the signaling mechanism of AG-IV and CAG. Telomerase activity in human embryonic kidney HEK293 fibroblasts was increased upon treatment with increasing concentrations of AG-IV or CAG. Both compounds induced the phosphorylation of extracellular signal-regulated protein kinase (ERK) in a time- and dose-dependent manner in HEK293 cells and HEK-neo keratinocytes. AG-IV and CAG also stimulated ERK phosphorylation in other cell lines of lung, brain, mammary, endothelial, and hematopoietic origins. Use of selective inhibitors and dominant negative mutants revealed the involvement of c-Src, MEK (ERK kinase), and epidermal growth factor receptor in CAG-induced ERK phosphorylation. Our data indicate that AG-IV and CAG may exert their cellular effects through the activation of the Src/MEK/ERK pathway.

Objective Numerous studies have explored the role of methylenetetrahydrofolate reductase gene ( MTHFR ) C677T polymorphism and homocysteine (Hcy) concentration in obesity, but the results are inconsistent. Hence, we performed a meta-analysis implementing Mendelian randomization approach to test the assumption that the increased Hcy concentration is plausibly related to the elevated risk of obesity. Methods Eligible studies were selected based on several inclusion and exclusion criteria. Correlations between MTHFR C677T and obesity risk, MTHFR C677T and Hcy concentration in obesity, Hcy concentration, and obesity were estimated by ORs, effect size and standard mean difference with their corresponding 95% CIs, respectively. Furthermore, Mendelian randomization analysis was performed to estimate the relationship between Hcy level and obesity. Results Consequently, this meta-analysis implemented with Mendelian randomization approach was conducted among 8,622 cases and 29,695 controls. The results indicated that MTHFR C677T is associated with an increased risk of obesity (for T vs C: OR=1.06, 95% CI=1.02–1.10; for TT vs CC: OR=1.13, 95% CI=1.03–1.24). Moreover, in obese subjects, the pooled Hcy concentration in individuals of TT genotype was 2.91 mmol/L (95% CI: 0.27–5.55) higher than that in individuals of CC genotype. Furthermore, the pooled Hcy concentration in subjects with obesity was 0.74 mmol/L (95% CI: 0.36–1.12) higher than that in controls. The evaluated plausible OR associated with obesity was 1.23 for 5 μmol/L Hcy level increase. Conclusions Through this meta-analysis, we emphasize a strong relationship between Hcy level and obesity by virtue of MTHFR C677T polymorphism.

Intronic polyadenylation (IpA) usually leads to changes in coding region of an mRNA, and its implication in diseases has been recognized, though at its very beginning status. Conveniently and accurately identifying IpA is of great importance for further evaluating its biological significance. Here, we developed IPAFinder, a bioinformatic method for the de novo identification of intronic poly(A) sites and their dynamic changes from standard RNA-seq data. Applying IPAFinder to 256 pan-cancer tumor/normal pairs across six tumor types, we discovered 490 recurrent dynamically changed IpA events, some of which are novel and derived from cancer-associated genes such as TSC1, SPERD2, and CCND2. Furthermore, IPAFinder revealed that IpA could be regulated by factors related to splicing and m6A modification. In summary, IPAFinder enables the global discovery and characterization of biologically regulated IpA with standard RNA-seq data and should reveal the biological significance of IpA in various processes.