Can patterns of urban biodiversity be predicted using simple measures of green infrastructure?

Urban species and habitats provide important ecosystem services such as summertime cooling, recreation, and pollination at a variety of scales. Many studies have assessed how biodiversity responds to urbanization, but little work has been done to try and create recommendations that can be easily applied to urban planning, design and management practice. Urban planning often operates at broad spatial scales, typically using relatively simplistic targets for land cover mix to influence biodiversity and ecosystem service provision. Would more complicated, but still easily created, prescriptions for urban vegetation be beneficial? Here we assess the importance of vegetation measures (percentage vegetation cover, tree canopy cover and variation in canopy height) across four taxonomic groups (bats, bees, hoverflies and birds) at multiple spatial scales (100, 250, 500, 1000 m) within a major urban area (Birmingham, the United Kingdom). We found that small-scale (100–250-m radius) measures of vegetation were important predictors for hoverflies and bees, and that bats were sensitive to vegetation at a medium spatial-scale (250–500 m). In contrast, birds responded to vegetation characteristics at both small (100 m) and large (1000 m) scales. Vegetation cover, tree cover and variation in canopy height were expected to decrease with built surface cover; however, only vegetation height showed this expected trend. The results indicate the importance of relatively small patches of vegetation cover for supporting urban biodiversity, and show that relatively simple measures of vegetation characteristics can be useful predictors of species richness (or activity density, in the case of bats). They also highlight the danger of relying upon percentage built surface cover as an indicator of urban biodiversity potential

Increased circulating ANG II and TNF-α represents important risk factors in obese Saudi adults with hypertension irrespective of diabetic status and BMI

Central adiposity is a significant determinant of obesity-related hypertension risk, which may arise due to the pathogenic inflammatory nature of the abdominal fat depot. However, the influence of pro-inflammatory adipokines on blood pressure in the obese hypertensive phenotype has not been well established in Saudi subjects. As such, our study investigated whether inflammatory factors may represent useful biomarkers to delineate hypertension risk in a Saudi cohort with and without hypertension and/or diabetes mellitus type 2 (DMT2). Subjects were subdivided into four groups: healthy lean controls (age: 47.9±5.1 yr; BMI: 22.9±2.1 Kg/m2), non-hypertensive obese (age: 46.1±5.0 yr; BMI: 33.7±4.2 Kg/m2), hypertensive obese (age: 48.6±6.1 yr; BMI: 36.5±7.7 Kg/m2) and hypertensive obese with DMT2 (age: 50.8±6.0 yr; BMI: 35.3±6.7 Kg/m2). Anthropometric data were collected from all subjects and fasting blood samples were utilized for biochemical analysis. Serum angiotensin II (ANG II) levels were elevated in hypertensive obese (p<0.05) and hypertensive obese with DMT2 (p<0.001) compared with normotensive controls. Systolic blood pressure was positively associated with BMI (p<0.001), glucose (p<0.001), insulin (p<0.05), HOMA-IR (p<0.001), leptin (p<0.01), TNF-α (p<0.001) and ANG II (p<0.05). Associations between ANG II and TNF-α with systolic blood pressure remained significant after controlling for BMI. Additionally CRP (p<0.05), leptin (p<0.001) and leptin/adiponectin ratio (p<0.001) were also significantly associated with the hypertension phenotype. In conclusion our data suggests that circulating pro-inflammatory adipokines, particularly ANG II and, TNF-α, represent important factors associated with a hypertension phenotype and may directly contribute to predicting and exacerbating hypertension risk

Modelling chemistry in the nocturnal boundary layer above tropical rainforest and a generalised effective nocturnal ozone deposition velocity for sub-ppbv NOx conditions

Measurements of atmospheric composition have been made over a remote rainforest landscape. A box model has previously been demonstrated to model the observed daytime chemistry well. However the box model is unable to explain the nocturnal measurements of relatively high [NO] and [O3], but relatively low observed [NO2]. It is shown that a one-dimensional (1-D) column model with simple O3 -NOx chemistry and a simple representation of vertical transport is able to explain the observed nocturnal concentrations and predict the likely vertical profiles of these species in the nocturnal boundary layer (NBL). Concentrations of tracers carried over from the end of the night can affect the atmospheric chemistry of the following day. To ascertain the anomaly introduced by using the box model to represent the NBL, vertically-averaged NBL concentrations at the end of the night are compared between the 1-D model and the box model. It is found that, under low to medium [NOx] conditions (NOx <1 ppbv), a simple parametrisation can be used to modify the box model deposition velocity of ozone, in order to achieve good agreement between the box and 1-D models for these end-of-night concentrations of NOx and O3. This parametrisation would could also be used in global climate-chemistry models with limited vertical resolution near the surface. Box-model results for the following day differ significantly if this effective nocturnal deposition velocity for ozone is implemented; for instance, there is a 9% increase in the following day’s peak ozone concentration. However under medium to high [NOx] conditions (NOx > 1 ppbv), the effect on the chemistry due to the vertical distribution of the species means no box model can adequately represent chemistry in the NBL without modifying reaction rate constants

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine

Definitive hypofractionated radiotherapy for early glottic carcinoma: experience of 55Gy in 20 fractions

Introduction: A wide variety of fractionation schedules have been employed for the treatment of early glottic cancer. The aim is to report our 10-year experience of using hypofractionated radiotherapy with 55Gy in 20 fractions at 2.75Gy per fraction. Methods: Patients treated between 2004 and 2013 with definitive radiotherapy to a dose of 55Gy in 20 fractions over 4 weeks for T1/2 N0 squamous cell carcinoma of the glottis were retrospectively identified. Patients with prior therapeutic minor surgery (eg. laser stripping, cordotomy) were included. The probabilities of local control, ultimate local control (including salvage surgery), regional control, cause specific survival (CSS) and overall survival (OS) were calculated. Results: One hundred thirty-two patients were identified. Median age was 65 years (range 33–89). Median follow up was 72 months (range 7–124). 50 (38 %), 18 (14 %) and 64 (48 %) of patients had T1a, T1b and T2 disease respectively. Five year local control and ultimate local control rates were: overall - 85.6 % and 97.3 % respectively, T1a - 91.8 % and 100 %, T1b - 81.6 and 93.8 %, and T2 - 80.9 % and 95.8 %. Five year regional control, CSS and OS rates were 95.4 %, 95.7 % and 78.8 % respectively. There were no significant associations of covariates (e.g. T-stage, extent of laryngeal extension, histological grade) with local control on univariate analysis. Only increasing age and transglottic extension in T2 disease were significantly associated with overall survival (both p <0.01). Second primary cancers developed in 17 % of patients. 13 (9.8 %) of patients required enteral tube feeding support during radiotherapy; no patients required long term enteral nutrition. One patient required a tracheostomy due to a non-functioning larynx on long term follow up. Conclusions: Hypofractionated radiation therapy with a dose of 55Gy in 20 fractions for early stage glottic cancer provides high rates of local control with acceptable toxicity

Infectious Disease Modeling of Social Contagion in Networks

Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.National Institutes of Health (U.S.) (grant R01GM078986)National Science Foundation (U.S.)Bill & Melinda Gates FoundationTempleton FoundationNational Institute on Aging (grant P01 AG031093)Framingham Heart Study (contract number N01-HC-25195

The genome sequence of <i>Trypanosoma brucei gambiense</i>, causative agent of chronic Human African Trypanosomiasis

&lt;p&gt;&lt;b&gt;Background:&lt;/b&gt; &lt;i&gt;Trypanosoma brucei gambiense&lt;/i&gt; is the causative agent of chronic Human African Trypanosomiasis or sleeping sickness, a disease endemic across often poor and rural areas of Western and Central Africa. We have previously published the genome sequence of a &lt;i&gt;T. b. brucei&lt;/i&gt; isolate, and have now employed a comparative genomics approach to understand the scale of genomic variation between &lt;i&gt;T. b. gambiense&lt;/i&gt; and the reference genome. We sought to identify features that were uniquely associated with &lt;i&gt;T. b. gambiense&lt;/i&gt; and its ability to infect humans.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods and findings:&lt;/b&gt; An improved high-quality draft genome sequence for the group 1 &lt;i&gt;T. b. gambiense&lt;/i&gt; DAL 972 isolate was produced using a whole-genome shotgun strategy. Comparison with &lt;i&gt;T. b. brucei&lt;/i&gt; showed that sequence identity averages 99.2% in coding regions, and gene order is largely collinear. However, variation associated with segmental duplications and tandem gene arrays suggests some reduction of functional repertoire in &lt;i&gt;T. b. gambiense&lt;/i&gt; DAL 972. A comparison of the variant surface glycoproteins (VSG) in &lt;i&gt;T. b. brucei&lt;/i&gt; with all &lt;i&gt;T. b. gambiense&lt;/i&gt; sequence reads showed that the essential structural repertoire of VSG domains is conserved across &lt;i&gt;T. brucei&lt;/i&gt;.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; This study provides the first estimate of intraspecific genomic variation within &lt;i&gt;T. brucei&lt;/i&gt;, and so has important consequences for future population genomics studies. We have shown that the &lt;i&gt;T. b. gambiense&lt;/i&gt; genome corresponds closely with the reference, which should therefore be an effective scaffold for any &lt;i&gt;T. brucei&lt;/i&gt; genome sequence data. As VSG repertoire is also well conserved, it may be feasible to describe the total diversity of variant antigens. While we describe several as yet uncharacterized gene families with predicted cell surface roles that were expanded in number in &lt;i&gt;T. b. brucei&lt;/i&gt;, no &lt;i&gt;T. b. gambiense&lt;/i&gt;-specific gene was identified outside of the subtelomeres that could explain the ability to infect humans.&lt;/p&gt

Tree of life metabarcoding can serve as a biotic benchmark for shifting baselines in urbanized estuaries.

Urbanization of estuaries drastically changed existing shorelines and bathymetric contours, in turn modifying habitat for marine foundational species that host critical biodiversity. And yet we lack approaches to characterize a significant fraction of the biota that inhabit these ecosystems on time scales that align with rates of urbanization. Environmental DNA (or eDNA) metabarcoding that combines multiple assays targeting a broad range of taxonomic groups can provide a solution, but we need to determine whether the biological communities it detects ally with different habitats in these changing aquatic environments. In this study, we tested whether tree of life metabarcoding (ToL-metabarcoding) data extracted from filtered seawater samples correlated with four known geomorphic habitat zones across a heavily urbanized estuary (Sydney Harbour, Australia). Using this method, we substantially expanded our knowledge on the composition and spatial distribution of marine biodiversity across the tree of life in Sydney Harbour, particularly for organisms where existing records are sparse. Excluding terrestrial DNA inputs, we identified significant effects of both distance from the mouth of Sydney Harbour and geomorphic zone on biological community structure in the ToL-metabarcoding dataset (entire community), as well as in each of the taxonomic subgroups that we considered (fish, macroinvertebrates, algae and aquatic plants, bacteria). This effect appeared to be driven by taxa as a collective versus a few individual taxa, with each taxon explaining no more than 0.62% of the variation between geomorphic zones. Similarly, taxonomic richness was significantly higher within geomorphic zones with large sample sizes, but also decreased by 1% with each additional kilometer from the estuary mouth, a result consistent with a reduction in tidal inputs and available habitat in upper catchments. Based on these results, we suggest that ToL-metabarcoding can be used to benchmark biological monitoring in other urbanized estuaries globally, and in Sydney Harbour at future time points based on detection of bioindicators across the tree of life. We also suggest that robust biotic snapshots can be archived following extensive curation of taxonomic assignments that incorporates ecological affinities, supported by records from relevant and regional biodiversity repositories

Faster growth with shorter antigens can explain a VSG hierarchy during African trypanosome infections:a feint attack by parasites

The parasitic African trypanosome, Trypanosoma brucei, evades the adaptive host immune response by a process of antigenic variation that involves the clonal switching of variant surface glycoproteins (VSGs). The VSGs that come to dominate in vivo during an infection are not entirely random, but display a hierarchical order. How this arises is not fully understood. Combining available genetic data with mathematical modelling, we report a VSG-length-dependent hierarchical timing of clonal VSG dominance in a mouse model, consistent with an inverse correlation between VSG length and trypanosome growth-rate. Our analyses indicate that, among parasites switching to new VSGs, those expressing shorter VSGs preferentially accumulate to a detectable level that is sufficient to trigger a targeted immune response. This may be due to the increased metabolic cost of producing longer VSGs. Subsequent elimination of faster-growing parasites then allows slower-growing parasites with longer VSGs to accumulate. This interaction between the host and parasite is able to explain the temporal distribution of VSGs observed in vivo. Thus, our findings reveal a length-dependent hierarchy that operates during T. brucei infection. This represents a ‘feint attack’ diversion tactic utilised by these persistent parasites to out-maneuver the host adaptive immune system