Global mangrove root production,its controls and roles in the blue carbon budget of mangroves

Mangroves are among the most carbon-dense ecosystems worldwide. Most of the carbon in mangroves is found belowground, and root production might be an important control of carbon accumulation, but has been rarely quantified and understood at the global scale. Here, we determined the global mangrove root production rate and its controls using a systematic review and a recently formalised, spatially explicit mangrove typology framework based on geomorphological settings. We found that global mangrove root production averaged ~770 ± 202 g of dry biomass m⁻² year⁻¹ globally, which is much higher than previously reported and close to the root production of the most productive tropical forests. Geomorphological settings exerted marked control over root production together with air temperature and precipitation (r² ≈ 30%, p < .001). Our review shows that individual global changes (e.g. warming, eutrophication, drought) have antagonist effects on root production, but they have rarely been studied in combination. Based on this newly established root production rate, root-derived carbon might account for most of the total carbon buried in mangroves, and 19 Tg C lost in mangroves each year (e.g. as CO₂). Inclusion of root production measurements in understudied geomorphological settings (i.e. deltas), regions (Indonesia, South America and Africa) and soil depth (>40 cm), as well as the creation of a mangrove root trait database will push forward our understanding of the global mangrove carbon cycle for now and the future. Overall, this review presents a comprehensive analysis of root production in mangroves, and highlights the central role of root production in the global mangrove carbon budget.     

Risk factors of peripheral arterial disease: a case control study in Sri Lanka

Background

Peripheral artery disease (PAD) is an important global health problem and contributes to notable proportion of morbidity and mortality. This particular manifestation of systemic atherosclerosis is largely under diagnosed and undertreated. For sustainable preventive strategies in a country, it is mandatory to identify country-specific risk factors. We intended to assess the risk factors of PAD among adults aged 40–74 years.

Methods

This case control study was conducted in 2012–2013 in Sri Lanka. Seventy-nine cases and 158 controls in the age group of 40–74 years were selected for the study in order to have case to control ratio 1:2. The criterion for selecting cases and control was based on Ankle brachial pressure index (ABPI). Cases were selected from those who had ABPI 0.85 or less (ABPI ≤0.85) in either lower limb. Controls were selected from those ABPI score between 1.18 and 1.28 in both lower limbs. Only newly identified individuals with PAD were selected as cases. Controls were selected from the same geographical location and within the 5 year age group as cases.

Results

The history of diabetes mellitus more than 10 years (OR 5.8, 95% CI 2.2–14.2), history of dyslipidemia for more than 10 years (OR 4.9, 95% CI 2.1–16.2), history of hypertension for more than 10 years (OR 3.8, 95% CI 1.8–12.7) and smoking (OR 2.9, 95% CI 1.2–6.9), elevated HsCRP (OR 3.7, 95% CI 1.2–12.0) and hyperhomocysteinemia (OR 3.0, 95% CI 1.1–8.1) were revealed as country specific significant risk factor of PAD.

Conclusions

Diabetes mellitus, hypertension, dyslipidemia, smoking as well as elevated homocysteine and HsCRP found as risk factors of PAD. Longer the duration or higher level exposure to these risk factors has increased the risk of PAD. These findings emphasis the need for routine screening of PAD among patients with the identified risk factors.

     

Turing learning: a metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for ‘tricking’ the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product—the classifiers—that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.     

The role of fish-poultry integration on fish growth performance,yields and economic benefits among smallholder farmers in sub-Saharan Africa,Tanzania

Aquaculture practices from sub-Saharan Africa are characterised by low production, owing to improper technology. Production can be increased through integrating fish farming with other existing on-farm activities, particularly livestock husbandry. We assessed the role of fish-poultry integration on all male Nile tilapia, Oreochromis niloticus growth performance, yields and economic benefits among smallholder farmers in sub-Saharan Africa, Tanzania. The study also compared phytoplankton species composition, abundance and biomass between the fish-poultry integration and non-integrated system. After 180 days of the experiment, all male O. niloticus cultured under fish-poultry integration exhibited significantly higher growth rates than those in the non-integrated system (p < 0.05). Gross fish yield (GFY), net fish yield (NFY) and net annual yields (NAY) obtained from fish-poultry integration were significantly higher than those from non-integrated system (p < 0.05). Partial enterprise budget analysis revealed that fish-poultry integration was more profitable than the non-integrated system. Moreover, fish-poultry integrated system produced significantly higher phytoplankton abundance and biomass than those from the non-integrated system. Results demonstrate that rural smallholder farmers can achieve higher growth rate, farm net yields and income by integrating all male O. niloticus with other on-farm activities than practising a stand-alone fish culture system.     

Vaccination against cysticercosis and hydatid disease

Infections with the larval stages of taeniid cestode parasites cause substantial human morbidity as well as economic losses in domestic livestock species. Despite ongoing efforts around the world, few countries have been able substantially to reduce or eradicate these infections through the use of anthelmintics and lifestyle changes. Vaccines offer an additional potential tool to assist with the control of parasite transmission. Here, Marshall Lightowlers and colleagues review the substantial progress that has been made towards developing practical vaccines against hydatid disease in sheep and cysticercosis in sheep and cattle. Recombinant antigens have been used to induce more than 90% protection against challenge infections. Such success in animals encourages investigation of the potential use of vaccines in humans to prevent hydatid disease arising from infection with Echinococcus granulosus and cysticercosis from infection with Taenia solium.     

The contribution of trees to ecosystem methane emissions in a temperate forested wetland

Wetland‐adapted trees are known to transport soil‐produced methane (CH₄), an important greenhouse gas to the atmosphere, yet seasonal variations and controls on the magnitude of tree‐mediated CH₄ emissions remain unknown for mature forests. We examined the spatial and temporal variability in stem CH₄ emissions in situ and their controls in two wetland‐adapted tree species (Alnus glutinosa and Betula pubescens) located in a temperate forested wetland. Soil and herbaceous plant‐mediated CH₄ emissions from hollows and hummocks also were measured, thus enabling an estimate of contributions from each pathway to total ecosystem flux. Stem CH₄ emissions varied significantly between the two tree species, with Alnus glutinosa displaying minimal seasonal variations, while substantial seasonal variations were observed in Betula pubescens. Trees from each species emitted similar quantities of CH₄ from their stems regardless of whether they were situated in hollows or hummocks. Soil temperature and pore‐water CH₄ concentrations best explained annual variability in stem emissions, while wood‐specific density and pore‐water CH₄ concentrations best accounted for between‐species variations in stem CH₄ emission. Our study demonstrates that tree‐mediated CH₄ emissions contribute up to 27% of seasonal ecosystem CH₄ flux in temperate forested wetland, with the largest relative contributions occurring in spring and winter. Tree‐mediated CH₄ emissions currently are not included in trace gas budgets of forested wetland. Further work is required to quantify and integrate this transport pathway into CH₄ inventories and process‐based models.     

Ligand-dependent differences in estrogen receptor beta-interacting proteins identified in lung adenocarcinoma cells corresponds to estrogenic responses

Background

A recent epidemiological study demonstrated a reduced risk of lung cancer mortality in breast cancer patients using antiestrogens. These and other data implicate a role for estrogens in lung cancer, particularly nonsmall cell lung cancer (NSCLC). Approximately 61% of human NSCLC tumors express nuclear estrogen receptor β (ERβ); however, the role of ERβ and estrogens in NSCLC is likely to be multifactorial. Here we tested the hypothesis that proteins interacting with ERβ in human lung adenocarcinoma cells that respond proliferatively to estradiol (E₂) are distinct from those in non-E₂-responsive cells.

Methods

FLAG affinity purification of FLAG-ERβ-interacting proteins was used to isolate ERβ-interacting proteins in whole cell extracts from E₂ proliferative H1793 and non-E₂-proliferative A549 lung adenocarcinoma cell lines. Following trypsin digestion, proteins were identified using liquid chromatography electrospray ionization tandem mass spectrometry (LC-MS/MS). Proteomic data were analyzed using Ingenuity Pathway Analysis. Select results were confirmed by coimmunoprecipitation.

Results

LC-MS/MS identified 27 non-redundant ERβ-interacting proteins. ERβ-interacting proteins included hsp70, hsp60, vimentin, histones and calmodulin. Ingenuity Pathway Analysis of the ERβ-interacting proteins revealed differences in molecular and functional networks between H1793 and A549 lung adenocarcinoma cells. Coimmunoprecipitation experiments in these and other lung adenocarcinoma cells confirmed that ERβ and EGFR interact in a gender-dependent manner and in response to E₂ or EGF. BRCA1 interacted with ERβ in A549 cell lines and in human lung adenocarcinoma tumors, but not normal lung tissue.

Conclusion

Our results identify specific differences in ERβ-interacting proteins in lung adenocarcinoma cells corresponding to ligand-dependent differences in estrogenic responses.

     

Level of daily physical activity in individuals with COPD compared with healthy controls

Background

Persons with Chronic Obstructive Pulmonary Disease (COPD), performing some level of regular physical activity, have a lower risk of both COPD-related hospital admissions and mortality. COPD patients of all stages seem to benefit from exercise training programs, thereby improving with respect to both exercise tolerance and symptoms of dyspnea and fatigue. Physical inactivity, which becomes more severe with increasing age, is a point of concern in healthy older adults. COPD might worsen this scenario, but it is unclear to what degree. This literature review aims to present the extent of the impact of COPD on objectively-measured daily physical activity (DPA). The focus is on the extent of the impact that COPD has on duration, intensity, and counts of DPA, as well as whether the severity of the disease has an additional influence on DPA.

Results

A literature review was performed in the databases PubMed [MEDLINE], Picarta, PEDRO, ISI Web of Knowledge and Google scholar. After screening, 11 studies were identified as being relevant for comparison between COPD patients and healthy controls with respect to duration, intensity, and counts of DPA. Four more studies were found to be relevant to address the subject of the influence the severity of the disease may have on DPA. The average percentage of DPA of COPD patients vs. healthy control subjects for duration was 57%, for intensity 75%, and for activity counts 56%. Correlations of DPA and severity of the disease were low and/or not significant.

Conclusions

From the results of this review, it appears that patients with COPD have a significantly reduced duration, intensity, and counts of DPA when compared to healthy control subjects. The intensity of DPA seems to be less affected by COPD than duration and counts. Judging from the results, it seems that severity of COPD is not strongly correlated with level of DPA. Future research should focus in more detail on the relation between COPD and duration, intensity, and counts of DPA, as well as the effect of disease severity on DPA, so that these relations become more understandable.     

GObar: A Gene Ontology based analysis and visualization tool for gene sets

Background  

Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such sets of genes is, usually, not readily apparent.