How to catch the patch? A dendrometer study of the radial increment through successive cambia in the mangrove Avicennia

Background and Aims

Successive vascular cambia are involved in the secondary growth of at least 200 woody species from >30 plant families. In the mangrove Avicennia these successive cambia are organized in patches, creating stems with non-concentric xylem tissue surrounded by internal phloem tissue. Little is known about radial growth and tree stem dynamics in trees with this type of anatomy. This study aims to (1) clarify the process of secondary growth of Avicennia trees by studying its patchiness; and (2) study the radial increment of Avicennia stems, both temporary and permanent, in relation to local climatic and environmental conditions. A test is made of the hypothesis that patchy radial growth and stem dynamics enable Avicennia trees to better survive conditions of extreme physiological drought.

Methods

Stem variations were monitored by automatic point dendrometers at four different positions around and along the stem of two Avicennia marina trees in the mangrove forest of Gazi Bay (Kenya) during 1 year.

Key Results

Patchiness was found in the radial growth and shrinkage and swelling patterns of Avicennia stems. It was, however, potentially rather than systematically present, i.e. stems reacted either concentrically or patchily to environment triggers, and it was fresh water availability and not tidal inundation that affected radial increment.

Conclusions

It is concluded that the ability to develop successive cambia in a patchy way enables Avicennia trees to adapt to changes in the prevailing environmental conditions, enhancing its survival in the highly dynamic mangrove environment. Limited water could be used in a more directive way, investing all the attainable resources in only some locations of the tree stem so that at least at these locations there is enough water to, for example, overcome vessel embolisms or create new cells. As these locations change with time, the overall functioning of the tree can be maintained.     

Loss of P2Y2 Nucleotide Receptors Enhances Early Pathology in the TgCRND8 Mouse Model of Alzheimer's Disease

Neuroinflammation is a prominent feature in Alzheimer's disease (AD) and activation of the brain's innate immune system, particularly microglia, has been postulated to both retard and accelerate AD progression. Recent studies indicate that the G protein-coupled P2Y₂ nucleotide receptor (P2Y₂R) is an important regulator of innate immunity by assisting in the recruitment of monocytes to injured tissue, neutrophils to bacterial infections and eosinophils to allergen-infected lungs. In this study, we investigated the role of the P2Y₂R in progression of an AD-like phenotype in the TgCRND8 mouse model that expresses Swedish and Indiana mutations in amyloid precursor protein (APP). Our results indicate that P2Y ₂ R expression is upregulated in TgCRND8 mouse brain within 10 weeks of age and then decreases after 25 weeks of age, as compared to littermate controls expressing low levels of the P2Y ₂ R. TgCRND8 mice with homozygous P2Y ₂ R deletion survive less than 5 weeks, whereas mice with heterozygous P2Y ₂ R deletion survive for 12 weeks, a time point when TgCRND8 mice are fully viable. Heterozygous P2Y ₂ R deletion in TgCRND8 mice increased β-amyloid (Aβ) plaque load and soluble Aβ_1–42 levels in the cerebral cortex and hippocampus, decreased the expression of the microglial marker CD11b in these brain regions and caused neurological deficits within 10 weeks of age, as compared to age-matched TgCRND8 mice. These findings suggest that the P2Y₂R is important for the recruitment and activation of microglial cells in the TgCRND8 mouse brain and that the P2Y₂R may regulate neuroprotective mechanisms through microglia-mediated clearance of Aβ that when lost can accelerate the onset of an AD-like phenotype in the TgCRND8 mouse.     

Demonstrating the Use of High-Volume Electronic Medical Claims Data to Monitor Local and Regional Influenza Activity in the US

Introduction

Fine-grained influenza surveillance data are lacking in the US, hampering our ability to monitor disease spread at a local scale. Here we evaluate the performances of high-volume electronic medical claims data to assess local and regional influenza activity.

Material and Methods

We used electronic medical claims data compiled by IMS Health in 480 US locations to create weekly regional influenza-like-illness (ILI) time series during 2003–2010. IMS Health captured 62% of US outpatient visits in 2009. We studied the performances of IMS-ILI indicators against reference influenza surveillance datasets, including CDC-ILI outpatient and laboratory-confirmed influenza data. We estimated correlation in weekly incidences, peak timing and seasonal intensity across datasets, stratified by 10 regions and four age groups (<5, 5–29, 30–59, and 60+ years). To test IMS-Health performances at the city level, we compared IMS-ILI indicators to syndromic surveillance data for New York City. We also used control data on laboratory-confirmed Respiratory Syncytial Virus (RSV) activity to test the specificity of IMS-ILI for influenza surveillance.

Results

Regional IMS-ILI indicators were highly synchronous with CDC''s reference influenza surveillance data (Pearson correlation coefficients rho≥0.89; range across regions, 0.80–0.97, P<0.001). Seasonal intensity estimates were weakly correlated across datasets in all age data (rho≤0.52), moderately correlated among adults (rho≥0.64) and uncorrelated among school-age children. IMS-ILI indicators were more correlated with reference influenza data than control RSV indicators (rho = 0.93 with influenza v. rho = 0.33 with RSV, P<0.05). City-level IMS-ILI indicators were highly consistent with reference syndromic data (rho≥0.86).

Conclusion

Medical claims-based ILI indicators accurately capture weekly fluctuations in influenza activity in all US regions during inter-pandemic and pandemic seasons, and can be broken down by age groups and fine geographical areas. Medical claims data provide more reliable and fine-grained indicators of influenza activity than other high-volume electronic algorithms and should be used to augment existing influenza surveillance systems.     

Harbor Seals (Phoca vitulina) Can Perceive Optic Flow under Water

Optic flow, the pattern of apparent motion elicited on the retina during movement, has been demonstrated to be widely used by animals living in the aerial habitat, whereas underwater optic flow has not been intensively studied so far. However optic flow would also provide aquatic animals with valuable information about their own movement relative to the environment; even under conditions in which vision is generally thought to be drastically impaired, e. g. in turbid waters. Here, we tested underwater optic flow perception for the first time in a semi-aquatic mammal, the harbor seal, by simulating a forward movement on a straight path through a cloud of dots on an underwater projection. The translatory motion pattern expanded radially out of a singular point along the direction of heading, the focus of expansion. We assessed the seal''s accuracy in determining the simulated heading in a task, in which the seal had to judge whether a cross superimposed on the flow field was deviating from or congruent with the actual focus of expansion. The seal perceived optic flow and determined deviations from the simulated heading with a threshold of 0.6 deg of visual angle. Optic flow is thus a source of information seals, fish and most likely aquatic species in general may rely on for e. g. controlling locomotion and orientation under water. This leads to the notion that optic flow seems to be a tool universally used by any moving organism possessing eyes.     

Interaction between Water and Wind as a Driver of Passive Dispersal in Mangroves

Although knowledge on dispersal patterns is essential for predicting long-term population dynamics, critical information on the modalities of passive dispersal and potential interactions between vectors is often missing. Here, we use mangrove propagules with a wide variety of morphologies to investigate the interaction between water and wind as a driver of passive dispersal. We imposed 16 combinations of wind and hydrodynamic conditions in a flume tank, using propagules of six important mangrove species (and genera), resulting in a set of dispersal morphologies that covers most variation present in mangrove propagules worldwide. Additionally, we discussed the broader implications of the outcome of this flume study on the potential of long distance dispersal for mangrove propagules in nature, applying a conceptual model to a natural mangrove system in Gazi Bay (Kenya). Overall, the effect of wind on dispersal depended on propagule density (g l^-1). The low-density Heritiera littoralis propagules were most affected by wind, while the high-density vertically floating propagules of Ceriops tagal and Bruguiera gymnorrhiza were least affected. Avicennia marina, and horizontally floating Rhizophora mucronata and C. tagal propagules behaved similarly. Morphological propagule traits, such as the dorsal sail of H. littoralis, explained another part of the interspecific differences. Within species, differences in dispersal velocities can be explained by differences in density and for H. littoralis also by variations in the shape of the dorsal sail. Our conceptual model illustrates that different propagule types have a different likelihood of reaching the open ocean depending on prevailing water and wind currents. Results suggest that in open water, propagule traits (density, morphology, and floating orientation) appear to determine the effect of water and wind currents on dispersal dynamics. This has important implications for inter- and intraspecific variation in dispersal patterns and the likelihood of reaching suitable habitat patches within a propagule''s viable period.     

Applying a Novel Combination of Techniques to Develop a Predictive Model for Diabetes Complications

Among the many related issues of diabetes management, its complications constitute the main part of the heavy burden of this disease. The aim of this paper is to develop a risk advisor model to predict the chances of diabetes complications according to the changes in risk factors. As the starting point, an inclusive list of (k) diabetes complications and (n) their correlated predisposing factors are derived from the existing endocrinology text books. A type of data meta-analysis has been done to extract and combine the numeric value of the relationships between these two. The whole n (risk factors) - k (complications) model was broken down into k different (n-1) relationships and these (n-1) dependencies were broken into n (1-1) models. Applying regression analysis (seven patterns) and artificial neural networks (ANN), we created models to show the (1-1) correspondence between factors and complications. Then all 1-1 models related to an individual complication were integrated using the naïve Bayes theorem. Finally, a Bayesian belief network was developed to show the influence of all risk factors and complications on each other. We assessed the predictive power of the 1-1 models by R², F-ratio and adjusted R² equations; sensitivity, specificity and positive predictive value were calculated to evaluate the final model using real patient data. The results suggest that the best fitted regression models outperform the predictive ability of an ANN model, as well as six other regression patterns for all 1-1 models.     

Bacterial Species-Specific Activity of a Fluoroquinolone against Two Closely Related Pasteurellaceae with Similar MICs: Differential In Vitro Inoculum Effects and In Vivo Efficacies

We investigated the antimicrobial activity of a fluoroquinolone against two genetically close bacterial species belonging to the Pasteurellaceae family. Time-kill experiments were used to measure the in vitro activity of marbofloxacin against two strains of Mannheimia haemolytica and Pasteurella multocida with similar MICs. We observed that marbofloxacin was equally potent against 10⁵ CFU/mL inocula M. haemolytica and P. multocida. However, an inoculum effect was observed with P. multocida, meaning that marbofloxacin activity was decreased against a 10⁸ CFU/mL inoculum, whereas no inoculum effect was observed with M. haemolytica. Marbofloxacin activity was also tested in a lung infection model with immunocompromised mice intratracheally infected with 10⁹ CFU of each bacteria. At the same dose, the clinical and bacteriological outcomes were much better for mice infected with M. haemolytica than for those infected with P. multocida. Moreover, bacteriological eradication was obtained with a lower marbofloxacin dose for mice infected with M. haemolytica. Our results suggest that the differential in vivo marbofloxacin efficacy observed with the two bacterial species of similar MIC could be explained by a differential inoculum effect. Consequently, MICs determined on 10⁵ CFU inocula were not predictive of the differences in antibiotic efficacies against high bacterial inocula of closely related bacterial strains. These results could stimulate further investigations on bacterial species-specific antibiotic doses in a clinical setting.     

Process economics evaluation of cell-free synthesis for the commercial manufacture of antibody drug conjugates

Continuous improvements of cell-free synthesis (CFS) systems have generated interest in adopting the technology for the manufacture of biologics. This paper provides an evaluation of the manufacturing cost-effectiveness of CFS for the commercial production of antibody-drug conjugates (ADCs). The evaluation was performed using an advanced techno-economic engine (TEE) built in Python. The TEE is programmed in an object-oriented environment capable of simulating a plethora of process flowsheets and predicting size and cost metrics for the process and the facility. A case study was formulated to compare the economics of whole bioprocesses based on either a CFS system or a mammalian cell system (CHO) for the manufacture of an ADC at a range of product demands. The analysis demonstrated the potential of CFS for the commercial manufacture of biologics and identified key cost drivers related to the system. The CFS system showed an approximately 80% increase in the cost of goods compared to CHO with a significant cost attributed to the in-house manufacture of the bacterial cell extract, necessary for the CFS reaction step in the process. A sensitivity and target analysis highlighted the need for further process improvements especially in the titer for the CFS process to become more competitive against well-established systems.