Lagged Effect of Diurnal Temperature Range on Mortality in a Subtropical Megacity of China

Background

Many studies have found extreme temperature can increase the risk of mortality. However, it is not clear whether extreme diurnal temperature range (DTR) is associated with daily disease-specific mortality, and how season might modify any association.

Objectives

To better understand the acute effect of DTR on mortality and identify whether season is a modifier of the DTR effect.

Methods

The distributed lag nonlinear model (DLNM) was applied to assess the non-linear and delayed effects of DTR on deaths (non-accidental mortality (NAD), cardiovascular disease (CVD), respiratory disease (RD) and cerebrovascular disease (CBD)) in the full year, the cold season and the warm season.

Results

A non-linear relationship was consistently found between extreme DTR and mortality. Immediate effects of extreme low DTR on all types of mortality were stronger than those of extreme high DTR in the full year. The cumulative effects of extreme DTRs increased with the increment of lag days for all types of mortality in cold season, and they were greater for extreme high DTRs than those of extreme low DTRs. In hot season, the cumulative effects for extreme low DTRs increased with the increment of lag days, but for extreme high DTR they reached maxima at a lag of 13 days for all types of mortality except for CBD(at lag6 days), and then decreased.

Conclusions

Our findings suggest that extreme DTR is an independent risk factor of daily mortality, and season is a modifier of the association of DTR with daily mortality.     

Wrangling Phosphoproteomic Data to Elucidate Cancer Signaling Pathways

The interpretation of biological data sets is essential for generating hypotheses that guide research, yet modern methods of global analysis challenge our ability to discern meaningful patterns and then convey results in a way that can be easily appreciated. Proteomic data is especially challenging because mass spectrometry detectors often miss peptides in complex samples, resulting in sparsely populated data sets. Using the R programming language and techniques from the field of pattern recognition, we have devised methods to resolve and evaluate clusters of proteins related by their pattern of expression in different samples in proteomic data sets. We examined tyrosine phosphoproteomic data from lung cancer samples. We calculated dissimilarities between the proteins based on Pearson or Spearman correlations and on Euclidean distances, whilst dealing with large amounts of missing data. The dissimilarities were then used as feature vectors in clustering and visualization algorithms. The quality of the clusterings and visualizations were evaluated internally based on the primary data and externally based on gene ontology and protein interaction networks. The results show that t-distributed stochastic neighbor embedding (t-SNE) followed by minimum spanning tree methods groups sparse proteomic data into meaningful clusters more effectively than other methods such as k-means and classical multidimensional scaling. Furthermore, our results show that using a combination of Spearman correlation and Euclidean distance as a dissimilarity representation increases the resolution of clusters. Our analyses show that many clusters contain one or more tyrosine kinases and include known effectors as well as proteins with no known interactions. Visualizing these clusters as networks elucidated previously unknown tyrosine kinase signal transduction pathways that drive cancer. Our approach can be applied to other data types, and can be easily adopted because open source software packages are employed.     

Predator population size structure alters consumption of prey from epigeic and grazing food webs

Numerous studies have found that predators can suppress prey densities and thereby impact important ecosystem processes such as plant productivity and decomposition. However, prey suppression by spiders can be highly variable. Unlike predators that feed on prey within a single energy channel, spiders often consume prey from asynchronous energy channels, such as grazing (live plant) and epigeic (soil surface) channels. Spiders undergo few life cycle changes and thus appear to be ideally suited to link energy channels, but ontogenetic diet shifts in spiders have received little attention. For example, spider use of different food channels may be highly specialized in different life stages and thus a species may be a multichannel omnivore only when we consider all life stages. Using stable isotopes, we investigated whether wolf spider (Pardosa littoralis, henceforth Pardosa) prey consumption is driven by changes in spider size. Small spiders obtained > 80% of their prey from the epigeic channel, whereas larger spiders used grazing and epigeic prey almost equally. Changes in prey consumption were not driven by changes in prey density, but by changes in prey use by different spider size classes. Thus, because the population size structure of Pardosa changes dramatically over the growing season, changes in spider size may have important implications for the strength of trophic cascades. Our research demonstrates that life history can be an important component of predator diet, which may in turn affect community- and ecosystem-level processes.     

Negative density-dependent dispersal emerges from the joint evolution of density- and body condition-dependent dispersal strategies

Empirical studies have documented both positive and negative density-dependent dispersal, yet most theoretical models predict positive density dependence as a mechanism to avoid competition. Several hypotheses have been proposed to explain the occurrence of negative density-dependent dispersal, but few of these have been formally modeled. Here, we developed an individual-based model of the evolution of density-dependent dispersal. This model is novel in that it considers the effects of density on dispersal directly, and indirectly through effects on individual condition. Body condition is determined mechanistically, by having juveniles compete for resources in their natal patch. We found that the evolved dispersal strategy was a steep, increasing function of both density and condition. Interestingly, although populations evolved a positive density-dependent dispersal strategy, the simulated metapopulations exhibited negative density-dependent dispersal. This occurred because of the negative relationship between density and body condition: high density sites produced low-condition individuals that lacked the resources required for dispersal. Our model, therefore, generates the novel hypothesis that observed negative density-dependent dispersal can occur when high density limits the ability of organisms to disperse. We suggest that future studies consider how phenotype is linked to the environment when investigating the evolution of dispersal.     

The Microtubule-Associated Protein END BINDING1b, Auxin, and Root Responses to Mechanical Cues

The ability of roots to penetrate through the soil and maneuver around rocks and other impenetrable objects requires a system for modulating output from mechanosensory response networks. The microtubule-associated protein END BINDING1b (EB1b) has a role in this process; it represses root responses to mechanical cues. In this study, a possible relationship between EB1b and auxin during root responses to mechanical cues was investigated. We found that eb1b-1-mutant roots are more sensitive than wild-type roots to chemicals that disrupt auxin transport, whereas the roots of mutants with defects in auxin transport are resistant to these treatments. Using seedlings that express the auxin-sensitive DR5rev::GFP construct, we also found that wild-type and eb1b-1 roots treated with the auxin transport inhibitor naphthylphthalamic acid exhibited dose-dependent reductions in basipetal auxin transport that were indistinguishable from each other. The responses of eb1b-1 roots to mechanical cues were also enhanced over wild type in the presence of p -chlorophenoxyisobutyric acid, a chemical thought to inhibit auxin signaling. Finally, roots of eb1b-1 and wild-type plants exhibited slight increases in loop formation in response to increasing levels of exogenously applied indole-3-acetic acid or 1-naphthalene acetic acid. Taken together, these results suggest that the repression of loop formation by EB1b and auxin transport/signaling occurs by different mechanisms.     

Host mTORC1 Signaling Regulates Andes Virus Replication

Hantavirus pulmonary syndrome (HPS) is a severe respiratory disease characterized by pulmonary edema, with fatality rates of 35 to 45%. Disease occurs following infection with pathogenic New World hantaviruses, such as Andes virus (ANDV), which targets lung microvascular endothelial cells. During replication, the virus scavenges 5′-m⁷G caps from cellular mRNA to ensure efficient translation of viral proteins by the host cell cap-dependent translation machinery. In cells, the mammalian target of rapamycin (mTOR) regulates the activity of host cap-dependent translation by integrating amino acid, energy, and oxygen availability signals. Since there is no approved pharmacological treatment for HPS, we investigated whether inhibitors of the mTOR pathway could reduce hantavirus infection. Here, we demonstrate that treatment with the FDA-approved rapamycin analogue temsirolimus (CCI-779) blocks ANDV protein expression and virion release but not entry into primary human microvascular endothelial cells. This effect was specific to viral proteins, as temsirolimus treatment did not block host protein synthesis. We confirmed that temsirolimus targeted host mTOR complex 1 (mTORC1) and not a viral protein, as knockdown of mTORC1 and mTORC1 activators but not mTOR complex 2 components reduced ANDV replication. Additionally, primary fibroblasts from a patient with tuberous sclerosis exhibited increased mTORC1 activity and increased ANDV protein expression, which were blocked following temsirolimus treatment. Finally, we show that ANDV glycoprotein Gn colocalized with mTOR and lysosomes in infected cells. Together, these data demonstrate that mTORC1 signaling regulates ANDV replication and suggest that the hantavirus Gn protein may modulate mTOR and lysosomal signaling during infection, thus bypassing the cellular regulation of translation.     

Mucosal Immunization of Lactating Female Rhesus Monkeys with a Transmitted/Founder HIV-1 Envelope Induces Strong Env-Specific IgA Antibody Responses in Breast Milk

We previously demonstrated that vaccination of lactating rhesus monkeys with a DNA prime/vector boost strategy induces strong T-cell responses but limited envelope (Env)-specific humoral responses in breast milk. To improve vaccine-elicited antibody responses in milk, hormone-induced lactating rhesus monkeys were vaccinated with a transmitted/founder (T/F) HIV Env immunogen in a prime-boost strategy modeled after the moderately protective RV144 HIV vaccine. Lactating rhesus monkeys were intramuscularly primed with either recombinant DNA (n = 4) or modified vaccinia virus Ankara (MVA) poxvirus vector (n = 4) expressing the T/F HIV Env C.1086 and then boosted twice intramuscularly with C.1086 gp120 and the adjuvant MF59. The vaccines induced Env-binding IgG and IgA as well as neutralizing and antibody-dependent cellular cytotoxicity (ADCC) responses in plasma and milk of most vaccinated animals. Importantly, plasma neutralization titers against clade C HIV variants MW965 (P = 0.03) and CAP45 (P = 0.04) were significantly higher in MVA-primed than in DNA-primed animals. The superior systemic prime-boost regimen was then compared to a mucosal-boost regimen, in which animals were boosted twice intranasally with C.1086 gp120 and the TLR 7/8 agonist R848 following the same systemic prime. While the systemic and mucosal vaccine regimens elicited comparable levels of Env-binding IgG antibodies, mucosal immunization induced significantly stronger Env-binding IgA responses in milk (P = 0.03). However, the mucosal regimen was not as potent at inducing functional IgG responses. This study shows that systemic MVA prime followed by either intranasal or systemic protein boosts can elicit strong humoral responses in breast milk and may be a useful strategy to interrupt postnatal HIV-1 transmission.     

The Src Homology 3 Domain-containing Guanine Nucleotide Exchange Factor Is Overexpressed in High-grade Gliomas and Promotes Tumor Necrosis Factor-like Weak Inducer of Apoptosis-Fibroblast Growth Factor-inducible 14-induced Cell Migration and Invasion via Tumor Necrosis Factor Receptor-associated Factor 2

Glioblastoma (GB) is the highest grade of primary adult brain tumors, characterized by a poorly defined and highly invasive cell population. Importantly, these invading cells are attributed with having a decreased sensitivity to radiation and chemotherapy. TNF-like weak inducer of apoptosis (TWEAK)-Fn14 ligand-receptor signaling is one mechanism in GB that promotes cell invasiveness and survival and is dependent upon the activity of multiple Rho GTPases, including Rac1. Here we report that Src homology 3 domain-containing guanine nucleotide exchange factor (SGEF), a RhoG-specific guanine nucleotide exchange factor, is overexpressed in GB tumors and promotes TWEAK-Fn14-mediated glioma invasion. Importantly, levels of SGEF expression in GB tumors inversely correlate with patient survival. SGEF mRNA expression is increased in GB cells at the invasive rim relative to those in the tumor core, and knockdown of SGEF expression by shRNA decreases glioma cell migration in vitro and invasion ex vivo. Furthermore, we showed that, upon TWEAK stimulation, SGEF is recruited to the Fn14 cytoplasmic tail via TRAF2. Mutation of the Fn14-TRAF domain site or depletion of TNF receptor-associated factor 2 (TRAF2) expression by siRNA oligonucleotides blocked SGEF recruitment to Fn14 and inhibited SGEF activity and subsequent GB cell migration. We also showed that knockdown of either SGEF or RhoG diminished TWEAK activation of Rac1 and subsequent lamellipodia formation. Together, these results indicate that SGEF-RhoG is an important downstream regulator of TWEAK-Fn14-driven GB cell migration and invasion.