Aerobic, resistance, or combined exercise training and cardiovascular risk profile in overweight or obese adults: the CardioRACE trial.

BACKGROUND AND AIMS: To determine the comparative efficacy of resistance, aerobic, and combined resistance plus aerobic exercise on cardiovascular disease (CVD) risk profile. METHODS: This randomized controlled trial enrolled 406 adults aged 35-70 years with overweight or obesity and elevated blood pressure. Participants were randomly assigned to resistance (n = 102), aerobic (n = 101), combined resistance plus aerobic exercise (n = 101), or no-exercise control (n = 102). All exercise participants were prescribed 1 h of time-matched supervised exercise (the combination group with 30 min of each resistance and aerobic exercise) three times per week for 1 year. The primary outcome was the change from baseline to 1 year in the standardized composite Z-score of four well-established CVD risk factors: systolic blood pressure, low-density lipoprotein (LDL) cholesterol, fasting glucose, and per cent body fat. RESULTS: Among 406 participants (53% women), 381 (94%) completed 1-year follow-up. Compared with the control group, the composite Z-score decreased at 1 year, which indicates improved CVD risk profile, in the aerobic {mean difference, -0.15 [95% confidence interval (CI): -0.27 to -0.04]; P = .01} and combination [mean difference, -0.16 (95% CI: -0.27 to -0.04); P = .009] groups, but not in the resistance [mean difference, -0.02 (95% CI: -0.14 to 0.09); P = .69] group. Both aerobic and combination groups had greater reductions in the composite Z-score compared with the resistance group (both P = .03), and there was no difference between the aerobic and combination groups (P = .96). Regarding the four individual CVD risk factors, only per cent body fat decreased in all three exercise groups at 1 year, but systolic blood pressure, LDL cholesterol, and fasting glucose did not decrease in any exercise groups, compared with the control group. CONCLUSIONS: In adults with overweight or obesity, aerobic exercise alone or combined resistance plus aerobic exercise, but not resistance exercise alone, improved composite CVD risk profile compared with the control.

VLM catecholaminergic neurons control tumor growth by regulating CD8+ T cells.

It is known that tumor growth can be influenced by the nervous system. It is not known, however, if tumors communicate directly with the central nervous system (CNS) or if such interactions may impact tumor growth. Here, we report that ventrolateral medulla (VLM) catecholaminergic (CA) neurons in the mouse brain are activated in tumor-bearing mice and the activity of these neurons significantly alter tumor growth in multiple syngeneic and spontaneous mouse tumor models. Specific ablation of VLM CA neurons by a dopamine-ß-hydroxylase (DBH) promotor-activated apoptosis-promoting caspase-3 in Dbh-Cre mice as well as inhibition of these neurons by a chemogenetic method slowed tumor progression. Consistently, chemogenetic activation of VLM CA neurons promoted tumor growth. The tumor inhibition effect of VLM CA neuron ablation is mitigated in Dbh-Cre;Rag1-/- mice, indicating that this regulatory effect is mediated by the adaptive immune system. Specific depletion of CD8+ T cells using an anti-CD8+ antibody also mitigated the tumor suppression resulting from the VLM CA neuron ablation. Finally, we showed that the VLM CA neuronal ablation had an additive antitumor effect with paclitaxel treatment. Collectively, our study uncovered the role of VLM CA neurons in the mouse brain in controlling tumor growth in the mouse body.

Asynchronous and error-prone longitudinal data analysis via functional calibration.

In many longitudinal settings, time-varying covariates may not be measured at the same time as responses and are often prone to measurement error. Naive last-observation-carried-forward methods incur estimation biases, and existing kernel-based methods suffer from slow convergence rates and large variations. To address these challenges, we propose a new functional calibration approach to efficiently learn longitudinal covariate processes based on sparse functional data with measurement error. Our approach, stemming from functional principal component analysis, calibrates the unobserved synchronized covariate values from the observed asynchronous and error-prone covariate values, and is broadly applicable to asynchronous longitudinal regression with time-invariant or time-varying coefficients. For regression with time-invariant coefficients, our estimator is asymptotically unbiased, root-n consistent, and asymptotically normal; for time-varying coefficient models, our estimator has the optimal varying coefficient model convergence rate with inflated asymptotic variance from the calibration. In both cases, our estimators present asymptotic properties superior to the existing methods. The feasibility and usability of the proposed methods are verified by simulations and an application to the Study of Women's Health Across the Nation, a large-scale multisite longitudinal study on women's health during midlife.

lncRNA Helf promotes hepatic inflammation and fibrosis by interacting with PTBP1 to facilitate PIK3R5 mRNA stabilization.

BACKGROUND: Hepatic fibrosis is a common consequence of chronic liver diseases without approved antifibrotic therapies. Long noncoding RNAs (lncRNAs) play an important role in various pathophysiological processes. However, the functions of certain lncRNAs involved in mediating the antifibrotic role remain largely unclear. METHODS: The RNA level of lnc-High Expressed in Liver Fibrosis (Helf) was detected in both mouse and human fibrotic livers. Furthermore, lnc-Helf-silenced mice were treated with carbon tetrachloride (CCl4) or bile duct ligation (BDL) to investigate the function of lnc-Helf in liver fibrosis. RESULTS: We found that lnc-Helf has significantly higher expression in human and mouse fibrotic livers as well as M1 polarized hepatic macrophages (HMs) and activated hepatic stellate cells (HSCs). In vivo studies showed that silencing lnc-Helf by AAV8 vector alleviates CCl4- and BDL-induced hepatic inflammation and fibrosis. Furthermore, in vitro experiments revealed that lnc-Helf promotes HSCs activation and proliferation, as well as HMs M1 polarization and proliferation in the absence or presence of cytokine stimulation. Mechanistically, our data illustrated that lnc-Helf interacts with RNA binding protein PTBP1 to promote its interaction with PIK3R5 mRNA, resulting in increased stability and activating the AKT pathway, thus promoting HSCs and HMs activation and proliferation, which augments hepatic inflammation and fibrosis. CONCLUSION: Our results unveil a lnc-Helf/PTBP1/PIK3R5/AKT feedforward, amplifying signaling that exacerbates the process of hepatic inflammation and fibrosis, thus providing a possible therapeutic strategy for hepatic fibrosis.

Semiparametric function-on-function quantile regression model with dynamic single-index interactions.

In this paper we propose a new semiparametric function-on-function quantile regression model with time-dynamic single-index interactions. Our model is very flexible in taking into account of the nonlinear time-dynamic interaction effects of the multivariate longitudinal/functional covariates on the longitudinal response, that most existing quantile regression models for longitudinal data are special cases of our proposed model. We propose to approximate the bivariate nonparametric coefficient functions by tensor product B-splines, and employ a check loss minimization approach to estimate the bivariate coefficient functions and the index parameter vector. Under some mild conditions, we establish the asymptotic normality of the estimated single-index coefficients using projection orthogonalization technique, and obtain the convergence rates of the estimated bivariate coefficient functions. Furthermore, we propose a score test to examine whether there exist interaction effects between the covariates. The finite sample performance of the proposed method is illustrated by Monte Carlo simulations and an empirical data analysis.

Predictive Functional Linear Models with Diverging Number of Semiparametric Single-Index Interactions.

When predicting crop yield using both functional and multivariate predictors, the prediction performances benefit from the inclusion of the interactions between the two sets of predictors. We assume the interaction depends on a nonparametric, single-index structure of the multivariate predictor and reduce each functional predictor's dimension using functional principal component analysis (FPCA). Allowing the number of FPCA scores to diverge to infinity, we consider a sequence of semiparametric working models with a diverging number of predictors, which are FPCA scores with estimation errors. We show that the parametric component of the model is root-n consistent and asymptotically normal, the overall prediction error is dominated by the estimation of the nonparametric interaction function, and justify a CV-based procedure to select the tuning parameters.

ESTIMATION FOR EXTREME CONDITIONAL QUANTILES OF FUNCTIONAL QUANTILE REGRESSION.

Quantile regression as an alternative to modeling the conditional mean function provides a comprehensive picture of the relationship between a response and covariates. It is particularly attractive in applications focused on the upper or lower conditional quantiles of the response. However, conventional quantile regression estimators are often unstable at the extreme tails, owing to data sparsity, especially for heavy-tailed distributions. Assuming that the functional predictor has a linear effect on the upper quantiles of the response, we develop a novel estimator for extreme conditional quantiles using a functional composite quantile regression based on a functional principal component analysis and an extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator under some regularity conditions, and compare it with other estimation methods using Monte Carlo simulations. Finally, we demonstrate the proposed method by empirically analyzing two real data sets.

Isorhamnetin Suppresses Human Gastric Cancer Cell Proliferation through Mitochondria-Dependent Apoptosis.

Derivates of natural products have been wildly utilized in the treatment of malignant tumors. Isorhamnetin (ISO), a most important active ingredient derived from flavonoids, shows great potential in tumor therapy. However, the therapeutic effects of ISO on gastric cancer (GC) remain unclear. Here, we demonstrate that ISO treatment dramatically inhibited the proliferation of two types of GC cells (AGS-1 and HGC-27) both in vitro and in vivo in time- and dose-dependent manners. These results are consistent with the transcriptomic analysis of ISO-treated GC cells, which yielded hundreds of differentially expressed genes that were enriched with cell growth and apoptosis. Mechanically, ISO treatment initiated the activation of caspase-3 cascade and elevated the expression of mitochondria-associated Bax/Bcl-2, cytosolic cytochrome c, followed by the activation of the cleavage of caspase-3 as well as poly ADP-ribose polymerase (PARP), resulting in the severe reduction of the mitochondrial potential and the accumulation of reactive oxygen species (ROS), while pre-treatment of the caspase-3 inhibitor could block the anti-tumor effect. Therefore, these results indicate that ISO treatment induces the apoptosis of GC cells through the mitochondria-dependent apoptotic pathway, providing a potential strategy for clinical GC therapy.

Extreme quantile estimation for partial functional linear regression models with heavy-tailed distributions.

In this article, we propose a novel estimator of extreme conditional quantiles in partial functional linear regression models with heavy-tailed distributions. The conventional quantile regression estimators are often unstable at the extreme tails due to data sparsity, especially for heavy-tailed distributions. We first estimate the slope function and the partially linear coefficient using a functional quantile regression based on functional principal component analysis, which is a robust alternative to the ordinary least squares regression. The extreme conditional quantiles are then estimated by using a new extrapolation technique from extreme value theory. We establish the asymptotic normality of the proposed estimator and illustrate its finite sample performance by simulation studies and an empirical analysis of diffusion tensor imaging data from a cognitive disorder study.

Dans cet article, un nouvel estimateur de quantiles conditionnels extrêmes est élaboré dans le cadre de modèles de régression linéaire fonctionnelle partielle avec des distributions à queues lourdes. Il est bien connu que la rareté des observations dans les ailes extrêmes de distributions à queues lourdes rend souvent les estimateurs de régression quantile usuels instables. Pour parer à la non robustesse des moindres carrés classiques, les auteurs ont commencé par estimer la fonction de pente et le coefficient partiellement linéaire d'une régression quantile en ayant recours à une approche basée sur l'analyse en composantes principales fonctionnelles. Ensuite, ils ont estimé les quantiles conditionnels extrêmes à l'aide d'une nouvelle technique d'extrapolation issue de la théorie des valeurs extrêmes. En plus d'établir la normalité asymptotique de l'estimateur proposé, les auteurs illustrent ses bonnes performances à distance finie par le biais d'une étude de simulation et une mise en oeuvre pratique sur les données d'imagerie de diffusion par tenseurs provenant d'une étude portant sur des troubles cognitifs.

Tankyrases maintain homeostasis of intestinal epithelium by preventing cell death.

Lgr5+ intestinal stem cells are crucial for fast homeostatic renewal of intestinal epithelium and Wnt/ß-catenin signaling plays an essential role in this process by sustaining stem cell self-renewal. The poly(ADP-ribose) polymerases tankyrases (TNKSs) mediate protein poly-ADP-ribosylation and are involved in multiple cellular processes such as Wnt signaling regulation, mitotic progression and telomere maintenance. However, little is known about the physiological function of TNKSs in epithelium homeostasis regulation. Here, using Villin-creERT2;Tnks1-/-;Tnks2fl/fl (DKO) mice, we observed that loss of TNKSs causes a rapid decrease of Lgr5+ intestinal stem cells and magnified apoptosis in small intestinal crypts, leading to intestine degeneration and increased mouse mortality. Consistently, deletion of Tnks or blockage of TNKS activity with the inhibitor XAV939 significantly inhibits the growth of intestinal organoids. We further showed that the Wnt signaling agonist CHIR99021 sustains the growth of DKO organoids, and XAV939 does not cause growth retardation of Apc-/- organoids. Consistent with the promoting function of TNKSs in Wnt signaling, Wnt/ß-catenin signaling is significantly decreased with stabilized Axin in DKO crypts. Together, our findings unravel the essential role of TNKSs-mediated protein parsylation in small intestinal homeostasis by modulating Wnt/ß-catenin signaling.

Growth dynamics and heritability for plant high-throughput phenotyping studies using hierarchical functional data analysis.

In modern high-throughput plant phenotyping, images of plants of different genotypes are repeatedly taken throughout the growing season, and phenotypic traits of plants (e.g., plant height) are extracted through image processing. It is of interest to recover whole trait trajectories and their derivatives at both genotype and plant levels based on observations made at irregular discrete time points. We propose to model trait trajectories using hierarchical functional principal component analysis (HFPCA) and show that the problem of recovering derivatives of the trajectories is reduced to estimating derivatives of eigenfunctions, which is solved by differentiating eigenequations. Based on HFPCA, we also propose a new measure for the broad-sense heritability by allowing it to vary over time during plant growth. Simulation studies show that the proposed procedure performs better than its competitors in terms of recovering both trait trajectories and their derivatives. Interesting characteristics of plant growth and heritability dynamics are revealed in the application to a modern plant phenotyping study.

TRAF3-interacting JNK-activating modulator promotes inflammation by stimulating translocation of Toll-like receptor 4 to lipid rafts.

Toll-like receptors (TLRs) are key players of the innate immune system and contribute to inflammation and pathogen clearance. Although TLRs have been extensively studied, it remains unclear how exactly bacterial lipopolysaccharide (LPS)-induced conformational changes of the extracellular domain of the TLRs trigger the dimerization of their intracellular domain across the plasma membrane and thereby stimulate downstream signaling. Here, using LPS-stimulated THP-1-derived macrophages and murine macrophages along with immunoblotting and immunofluorescence and quantitative analyses, we report that in response to inflammatory stimuli, the coiled-coil protein TRAF3-interacting JNK-activating modulator (T3JAM) associates with TLR4, promotes its translocation to lipid rafts, and thereby enhances macrophage-mediated inflammation. T3JAM overexpression increased and T3JAM depletion decreased TLR4 signaling through both the MyD88-dependent pathway and TLR4 endocytosis. Importantly, deletion or mutation of T3JAM to disrupt its coiled-coil-mediated homoassociation abrogated TLR4 recruitment to lipid rafts. Consistently, T3JAM depletion in mice dampened TLR4 signaling and alleviated LPS-induced inflammatory damage. Collectively, our findings reveal an additional molecular mechanism by which TLR4 activity is regulated and suggest that T3JAM may function as a molecular clamp to "tighten up" TLR4 and facilitate its translocation to lipid rafts.

The MST4-MOB4 complex disrupts the MST1-MOB1 complex in the Hippo-YAP pathway and plays a pro-oncogenic role in pancreatic cancer.

The mammalian STE20-like protein kinase 1 (MST1)-MOB kinase activator 1 (MOB1) complex has been shown to suppress the oncogenic activity of Yes-associated protein (YAP) in the mammalian Hippo pathway, which is involved in the development of multiple tumors, including pancreatic cancer (PC). However, it remains unclear whether other MST-MOB complexes are also involved in regulating Hippo-YAP signaling and have potential roles in PC. Here, we report that mammalian STE20-like kinase 4 (MST4), a distantly related ortholog of the MST1 kinase, forms a complex with MOB4 in a phosphorylation-dependent manner. We found that the overall structure of the MST4-MOB4 complex resembles that of the MST1-MOB1 complex, even though the two complexes exhibited opposite biological functions in PC. In contrast to the tumor-suppressor effect of the MST1-MOB1 complex, the MST4-MOB4 complex promoted growth and migration of PANC-1 cells. Moreover, expression levels of MST4 and MOB4 were elevated in PC and were positively correlated with each other, whereas MST1 expression was down-regulated. Because of divergent evolution of key interface residues, MST4 and MOB4 could disrupt assembly of the MST1-MOB1 complex through alternative pairing and thereby increased YAP activity. Collectively, these findings identify the MST4-MOB4 complex as a noncanonical regulator of the Hippo-YAP pathway with an oncogenic role in PC. Our findings highlight that although MST-MOB complexes display some structural conservation, they functionally diverged during their evolution.

Comparison of the Cardiovascular Benefits of Resistance, Aerobic, and Combined Exercise (CardioRACE): Rationale, design, and methods.

BACKGROUND: The benefits of aerobic exercise (AE) for cardiovascular disease (CVD) have been well documented. Resistance exercise (RE) has been traditionally examined for its effects on bone density, physical function, or metabolic health, yet few data exist regarding the benefits of RE, independent of and combined with AE, for CVD prevention. This randomized controlled trial, "Comparison of the Cardiovascular Benefits of Resistance, Aerobic, and Combined Exercise (CardioRACE)," is designed to determine the relative benefits of RE, AE, or combined RE plus AE training on CVD risk factors. METHODS: Participants are 406 inactive men and women (35-70 years) with a body mass index of 25-40 kg/m2 and blood pressure (BP) of 120-139/80-89 mm Hg without taking antihypertensive medications. Participants are randomly assigned to RE only, AE only, combined RE and AE (CE), or a no exercise control group. Participants perform supervised exercise at 50%-80% of their relative maximum intensity for both AE and RE, 3 times a week for 60 minutes per session, for 1 year (all 3 groups are time matched). RESULTS: The primary outcome is a composite z score including resting BP, low-density lipoprotein cholesterol (LDL-C), fasting glucose, and percent body fat, which is assessed at baseline, 6 months, and 12 months. Diet and outside physical activity are measured throughout the intervention for 1 year. CONCLUSION: CardioRACE (ClinicalTrials.govNCT03069092) will fill an important knowledge gap regarding the effects of RE, alone or in addition to the well-documented effects of AE. CardioRACE will help generate more comprehensive and synergistic clinical and public health strategies to prevent CVD.

Does Aphid Infestation Interfere with Indirect Plant Defense against Lepidopteran Caterpillars in Wild Cabbage?

Attraction of parasitoids to plant volatiles induced by multiple herbivory depends on the specific combinations of attacking herbivore species, especially when their feeding modes activate different defense signalling pathways as has been reported for phloem feeding aphids and tissue feeding caterpillars. We studied the effects of pre-infestation with non-host aphids (Brevicoryne brassicae) for two different time periods on the ability of two parasitoid species to discriminate between volatiles emitted by plants infested by host caterpillars alone and those emitted by plants infested with host caterpillars plus aphids. Using plants originating from three chemically distinct wild cabbage (Brassica oleracea) populations, Diadegma semiclausum switched preference for dually infested plants to preference for plants infested with Plutella xylostella hosts alone when the duration of pre-aphid infestation doubled from 7 to 14 days. Microplitis mediator, a parasitoid of Mamestra brassicae caterpillars, preferred dually-infested plants irrespective of aphid-infestation duration. Separation of the volatile blends emitted by plants infested with hosts plus aphids or with hosts only was poor, based on multivariate statistics. However, emission rates of individual compounds were often reduced in plants infested with aphids plus hosts compared to those emitted by plants infested with hosts alone. This effect depended on host caterpillar species and plant population and was little affected by aphid infestation duration. Thus, the interactive effect of aphids and hosts on plant volatile production and parasitoid attraction can be dynamic and parasitoid specific. The characteristics of the multi-component volatile blends that determine parasitoid attraction are too complex to be deduced from simple correlative statistical analyses.

Finding common task-related regions in fMRI data from multiple subjects by periodogram clustering and clustering ensemble.

We propose an innovative and practically relevant clustering method to find common task-related brain regions among different subjects who respond to the same set of stimuli. Using functional magnetic resonance imaging (fMRI) time series data, we first cluster the voxels within each subject on a voxel by voxel basis. To extract signals out of noisy data, we estimate a new periodogram at each voxel using multi-tapering and low-rank spline smoothing and then use the periodogram as the main feature for clustering. We apply a divisive hierarchical clustering algorithm to the estimated periodograms within a single subject and identify the task-related region as the cluster of voxels that have periodograms with a peak frequency matching that of the stimulus sequence. Finally, we apply a machine learning technique called clustering ensemble to find common task-related regions across different subjects. The efficacy of the proposed approach is illustrated via a simulation study and a real fMRI data set. Copyright © 2016 John Wiley & Sons, Ltd.

Interactive Effects of Cabbage Aphid and Caterpillar Herbivory on Transcription of Plant Genes Associated with Phytohormonal Signalling in Wild Cabbage.

Plants are commonly attacked by a variety of insect herbivores and have developed specific defenses against different types of attackers. At the molecular level, herbivore-specific signalling pathways are activated by plants in response to attackers with different feeding strategies. Feeding by leaf-chewing herbivores predominantly activates jasmonic acid (JA)-regulated defenses, whereas feeding by phloem-sucking herbivores generally activates salicylic acid (SA)-regulated defenses. When challenged sequentially by both phloem-sucking and leaf-chewing herbivores, SA-JA antagonism may constrain the plant's ability to timely and adequately divert defense to the second herbivore that requires activation of a different defensive pathway. We investigated the effect of the temporal sequence of infestation by the aphid Brevicoryne brassicae and three caterpillar species, Plutella xylostella, Pieris brassicae, and Mamestra brassicae, on the interaction between JA and SA signal-transduction pathways in three wild cabbage populations. We found no support for SA-JA antagonism, irrespective of the temporal sequence of herbivore introduction or the identity of the caterpillar species based on the transcript levels of the JA- and SA-regulated marker genes LOX and PR-1, respectively, at the examined time points, 6, 24, and 48 h. In general, infestation with aphids alone had little effect on the transcript levels of the two marker genes, whereas the three caterpillar species upregulated not only LOX but also PR-1. Transcriptional changes were different for plants from the three different natural cabbage populations.

Acetylation of Smc3 by Eco1 is required for S phase sister chromatid cohesion in both human and yeast.

Sister chromatid cohesion is normally established in S phase in a process that depends on the cohesion establishment factor Eco1, a conserved acetyltransferase. However, due to the lack of known in vivo substrates, how Eco1 regulates cohesion is not understood. Here we report that yeast Eco1 and its human ortholog, ESCO1, both acetylate Smc3, a component of the cohesin complex that physically holds the sister chromatid together, at two conserved lysine residues. Mutating these lysine residues to a nonacetylatable form leads to increased loss of sister chromatid cohesion and genome instability in both yeast and human. In addition, we clarified that the acetyltransferase activity of Eco1 is essential for its function. Our study thus identified a molecular target for the acetyltransferase Eco1 and revealed that Smc3 acetylation is a conserved mechanism in regulating sister chromatid cohesion.

Frailty models for pneumonia to death with a left-censored covariate.

Frailty models are multiplicative hazard models for studying association between survival time and important clinical covariates. When some values of a clinical covariate are unobserved but known to be below a threshold called the limit of detection (LOD), naive approaches ignoring this problem, such as replacing the undetected value by the LOD or half of the LOD, often produce biased parameter estimate with larger mean squared error of the estimate. To address the LOD problem in a frailty model, we propose a flexible smooth nonparametric density estimator along with Simpson's numerical integration technique. This is an extension of an existing method in the likelihood framework for the estimation and inference of the model parameters. The proposed new method shows the estimators are asymptotically unbiased and gives smaller mean squared error of the estimates. Compared with the existing method, the proposed new method does not require distributional assumptions for the underlying covariates. Simulation studies were conducted to evaluate the performance of the new method in realistic scenarios. We illustrate the use of the proposed method with a data set from Genetic and Inflammatory Markers of Sepsis study in which interlekuin-10 was subject to LOD.

Intra-specific variation in wild Brassica oleracea for aphid-induced plant responses and consequences for caterpillar-parasitoid interactions.

Herbivore-induced plant responses not only influence the initiating attackers, but also other herbivores feeding on the same host plant simultaneously or at a different time. Insects belonging to different feeding guilds are known to induce different responses in the host plant. Changes in a plant's phenotype not only affect its interactions with herbivores but also with organisms higher in the food chain. Previous work has shown that feeding by a phloem-feeding aphid on a cabbage cultivar facilitates the interaction with a chewing herbivore and its endoparasitoid. Here we study genetic variation in a plant's response to aphid feeding using plants originating from three wild Brassica oleracea populations that are known to differ in constitutive and inducible secondary chemistry. We compared the performance of two different chewing herbivore species, Plutella xylostella and M. brassicae, and their larval endoparasitoids Diadegma semiclausum and M. mediator, respectively, on plants that had been infested with aphids (Brevicoryne brassicae) for 1 week. Remarkably, early infestation with B. brassicae enhanced the performance of the specialist P. xylostella and its parasitoid D. semiclausum, but did not affect that of the generalist M. brassicae, nor its parasitoid M. mediator. Performance of the two herbivore-parasitoid interactions also varied among the cabbage populations and the effect of aphid infestation marginally differed among the three populations. Thus, the effect of aphid infestation on the performance of subsequent attackers is species specific, which may have concomitant consequences for the assembly of insect communities that are naturally associated with these plants.