Ecological Associations of Littoraria irrorata with Spartina cynosuroides and Spartina alterniflora

It is well-documented that marsh periwinkles (Littoraria irrorata) consume and inhabit smooth cordgrass (Spartina alterniflora), but their interactions with big cordgrass (Spartina cynosuroides) remain unknown. Plant communities in mesohaline marshes will change as sea-level rise shifts species from salt-intolerant (e.g., S. cynosuroides) plants to salt-tolerant (e.g., S. alterniflora) ones. Therefore, understanding how L. irrorata interacts with different habitats provides insight into this species’ generalist nature and allows us to predict the potential impacts of changing plant communities on L. irrorata. We show, for the first time, that L. irrorata inhabits, climbs, and grazes S. cynosuroides. We compared both habitats and found snails were larger, plant tissue was tougher, and sediment surface temperatures were higher in S. alterniflora than S. cynosuroides. Snails had greater survivorship from predators in S. cynosuroides than in S. alterniflora. Further, snails grazed S. cynosuroides more than S. alterniflora, evidenced by a greater number of radulation scars. Despite these differences, snail densities were equal between habitats suggesting functional redundancy between S. cynosuroides and S. alterniflora for L. irrorata. Our results indicate L. irrorata is a habitat generalist that uses both S. alterniflora and S. cynosuroides, which may allow it to gain an ecological foothold as sea-level rises

Multi-objective optimisation of machine tool error mapping using automated planning

Error mapping of machine tools is a multi-measurement task that is planned based on expert knowledge. There are no intelligent tools aiding the production of optimal measurement plans. In previous work, a method of intelligently constructing measurement plans demonstrated that it is feasible to optimise the plans either to reduce machine tool downtime or the estimated uncertainty of measurement due to the plan schedule. However, production scheduling and a continuously changing environment can impose conflicting constraints on downtime and the uncertainty of measurement. In this paper, the use of the produced measurement model to minimise machine tool downtime, the uncertainty of measurement and the arithmetic mean of both is investigated and discussed through the use of twelve different error mapping instances. The multi-objective search plans on average have a 3% reduction in the time metric when compared to the downtime of the uncertainty optimised plan and a 23% improvement in estimated uncertainty of measurement metric when compared to the uncertainty of the temporally optimised plan. Further experiments on a High Performance Computing (HPC) architecture demonstrated that there is on average a 3% improvement in optimality when compared with the experiments performed on the PC architecture. This demonstrates that even though a 4% improvement is beneficial, in most applications a standard PC architecture will result in valid error mapping plan

The formation of gullies on Mars today

A decade of high-resolution monitoring has revealed extensive activity in fresh Martian gullies. Flows within the gullies are diverse: they can be relatively light, neutral or dark, colourful or bland, and range from superficial deposits to 10 m-scale topographic changes. We observed erosion and transport of material within gullies, new terraces, freshly eroded channel segments, migrating sinuous curves, channel abandonment, and lobate deposits. We also observed early stages of gully initiation, demonstrating that these processes are not merely modifying pre-existing land-forms. The timing of activity closely correlates with the presence of seasonal CO2 frost, so the current changes must be part of ongoing gully formation that is driven largely by its presence. We suggest that the cumulative effect of many flows erodes alcoves and channels, and builds lobate aprons, with no involvement of liquid water. Instead, flows may be fluidized by sublimation of entrained CO2 ice or other mechanisms. The frequent activity is likely to have erased any features dating from high-obliquity periods, so fresh gully geomorphology at middle and high latitudes is not evidence for past liquid water. CO2 ice-driven processes may have been important throughout Martian geological history and their deposits could exist in the rock record, perhaps resembling debris-flow sediments.Mars Data Analysis Program [NNH13AV85I]; Mars Reconnaissance Orbiter HiRISE project12 month embargo; published 27 November 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Repurposing Itraconazole as a Treatment for Advanced Prostate Cancer: A Noncomparative Randomized Phase II Trial in Men With Metastatic Castration‐Resistant Prostate Cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139926/1/onco0163-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139926/2/onco0163.pd

Insights into the Regulatory Characteristics of the Mycobacterial Dephosphocoenzyme A Kinase: Implications for the Universal CoA Biosynthesis Pathway

Being vastly different from the human counterpart, we suggest that the last enzyme of the Mycobacterium tuberculosis Coenzyme A biosynthetic pathway, dephosphocoenzyme A kinase (CoaE) could be a good anti-tubercular target. Here we describe detailed investigations into the regulatory features of the enzyme, affected via two mechanisms. Enzymatic activity is regulated by CTP which strongly binds the enzyme at a site overlapping that of the leading substrate, dephosphocoenzyme A (DCoA), thereby obscuring the binding site and limiting catalysis. The organism has evolved a second layer of regulation by employing a dynamic equilibrium between the trimeric and monomeric forms of CoaE as a means of regulating the effective concentration of active enzyme. We show that the monomer is the active form of the enzyme and the interplay between the regulator, CTP and the substrate, DCoA, affects enzymatic activity. Detailed kinetic data have been corroborated by size exclusion chromatography, dynamic light scattering, glutaraldehyde crosslinking, limited proteolysis and fluorescence investigations on the enzyme all of which corroborate the effects of the ligands on the enzyme oligomeric status and activity. Cysteine mutagenesis and the effects of reducing agents on mycobacterial CoaE oligomerization further validate that the latter is not cysteine-mediated or reduction-sensitive. These studies thus shed light on the novel regulatory features employed to regulate metabolite flow through the last step of a critical biosynthetic pathway by keeping the latter catalytically dormant till the need arises, the transition to the active form affected by a delicate crosstalk between an essential cellular metabolite (CTP) and the precursor to the pathway end-product (DCoA)

Estimating Level of Engagement from Ocular Landmarks

E-learning offers many advantages like being economical, flexible and customizable, but also has challenging aspects such as lack of – social-interaction, which results in contemplation and sense of remoteness. To overcome these and sustain learners’ motivation, various stimuli can be incorporated. Nevertheless, such adjustments initially require an assessment of engagement level. In this respect, we propose estimating engagement level from facial landmarks exploiting the facts that (i) perceptual decoupling is promoted by blinking during mentally demanding tasks; (ii) eye strain increases blinking rate, which also scales with task disengagement; (iii) eye aspect ratio is in close connection with attentional state and (iv) users’ head position is correlated with their level of involvement. Building empirical models of these actions, we devise a probabilistic estimation framework. Our results indicate that high and low levels of engagement are identified with considerable accuracy, whereas medium levels are inherently more challenging, which is also confirmed by inter-rater agreement of expert coders

Phenotypic engineering by reprogramming gene transcription using novel artificial transcription factors in Escherichia coli

Now that many genomes have been sequenced and the products of newly identified genes have been annotated, the next goal is to engineer the desired phenotypes in organisms of interest. For the phenotypic engineering of microorganisms, we have developed novel artificial transcription factors (ATFs) capable of reprogramming innate gene expression circuits in Escherichia coli. These ATFs are composed of zinc finger (ZF) DNA-binding proteins, with distinct specificities, fused to an E. coli cyclic AMP receptor protein (CRP). By randomly assembling 40 different types of ZFs, we have constructed more than 6.4 × 104 ATFs that consist of 3 ZF DNA-binding domains and a CRP effector domain. Using these ATFs, we induced various phenotypic changes in E. coli and selected for industrially important traits, such as resistance to heat shock, osmotic pressure and cold shock. Genes associated with the heat-shock resistance phenotype were then characterized. These results and the general applicability of this platform clearly indicate that novel ATFs are powerful tools for the phenotypic engineering of microorganisms and can facilitate microbial functional genomic studies

Using verbal autopsy to measure causes of death: the comparative performance of existing methods

Background: Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. Methods: We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. Results: Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. Conclusions: Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices. © 2014 Murray et al.; licensee BioMed Central Ltd