The adsorption of amino acids on silica surfaces has attracted considerable interest because it has a broad range of applications in various fields such as drug delivery, solid-phase peptide synthesis, and biocompatible materials synthesis. In this work, we systematically study lysine adsorption on fumed silica nanoparticles with thermal analysis and solid-state NMR. Thermogravimetric analysis results show that the adsorption behavior of lysine in low-concentration aqueous solutions is well-described by the Langmuir isotherm. With ultrafast magic-angle-spinning 1H NMR and multinuclear and multidimensional 13C and 15N solid-state NMR, we successfully determine the protonation state of bulk lysine and find that lysine is adsorbed on silica nanoparticle surfaces through the side-chain amine groups. Density functional theory calculations carried out on lysine and lysine–silanol complex structures further confirm that the side-chain amine groups interact with the silica surface hydroxyl groups via strong hydrogen bonding. Furthermore, we find that lysine preferentially has monolayer coverage on silica surfaces in high salt concentration solutions because of the ionic complexes formed with surface bound lysine molecules.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene output at the post-transcriptional level by targeting degenerate elements primarily in 3′untranslated regions (3′UTRs) of mRNAs. Individual miRNAs can regulate networks of hundreds of genes, yet for the majority of miRNAs few, if any, targets are known. Misexpression of miRNAs is also a major contributor to cancer progression, thus there is a critical need to validate miRNA targets in high-throughput to understand miRNAs' contribution to tumorigenesis. Here we introduce a novel high-throughput assay to detect miRNA targets in 3′UTRs, called Luminescent Identification of Functional Elements in 3′UTRs (3′LIFE). We demonstrate the feasibility of 3′LIFE using a data set of 275 human 3′UTRs and two cancer-relevant miRNAs, let-7c and miR-10b, and compare our results to alternative methods to detect miRNA targets throughout the genome. We identify a large number of novel gene targets for these miRNAs, with only 32% of hits being bioinformatically predicted and 27% directed by non-canonical interactions. Functional analysis of target genes reveals consistent roles for each miRNA as either a tumor suppressor (let-7c) or oncogenic miRNA (miR-10b), and preferentially target multiple genes within regulatory networks, suggesting 3′LIFE is a rapid and sensitive method to detect miRNA targets in high-throughput.

Background: Long-lived marine megavertebrates (e.g. sharks, turtles, mammals, and seabirds) are inherently vulnerable to anthropogenic mortality. Although some mathematical models have been applied successfully to manage these animals, more detailed treatments are often needed to assess potential drivers of population dynamics. In particular, factors such as age-structure, density-dependent feedbacks on reproduction, and demographic stochasticity are important for understanding population trends, but are often difficult to assess. Lemon sharks (Negaprion brevirostris) have a pelagic adult phase that makes them logistically difficult to study. However, juveniles use coastal nursery areas where their densities can be high.

Results: We use a stage-structured, Markov-chain stochastic model to describe lemon shark population dynamics from a 17-year longitudinal dataset at a coastal nursery area at Bimini, Bahamas. We found that the interaction between delayed breeding, density-dependence, and demographic stochasticity accounts for 33 to 49% of the variance in population size.

Conclusions: Demographic stochasticity contributed all random effects in this model, suggesting that the existence of unmodeled environmental factors may be driving the majority of interannual population fluctuations. In addition, we are able to use our model to estimate the natural mortality rate of older age classes of lemon sharks that are difficult to study. Further, we use our model to examine what effect the length of a time series plays on deciphering ecological patterns. We find that—even with a relatively long time series—our sampling still misses important rare events. Our approach can be used more broadly to infer population dynamics of other large vertebrates in which age structure and demographic stochasticity are important.

Hong Kong Observatory currently uses a series of meteorological instruments, including long-range LIDAR (light detection and ranging) systems, to provide alerting services of low-level windshear and turbulence for Hong Kong International Airport. For some events that are smaller in spatial dimensions and are rapidly changing, such as low altitude windshear and turbulence associated with buildings or man-made structures, it would be necessary to involve meteorological instruments that offer greater spatial resolution. Therefore, the Observatory has set up a short-range LIDAR on the roof of the AsiaWorld-Expo during the summers over the past several years, conducting field research on the feasibility of strengthening early alerting for windshear and turbulence over the north runway’s eastern arrival runway (Runway 25RA) and developing an automated early alerting algorithm. This paper takes the pilot reports for Runway 25RA during the 2013 field research as verification samples, using different thresholds for radial wind velocity spatial and temporal changes detected by the short-range LIDAR to calculate the relative operating characteristic (ROC) curve, and analyzes its early alerting performance.

Errors in the specification or utilization of fossil fuel CO₂ emissions within carbon budget or atmospheric CO₂ inverse studies can alias the estimation of biospheric and oceanic carbon exchange. A key component in the simulation of CO₂ concentrations arising from fossil fuel emissions is the spatial distribution of the emission near coastlines. Regridding of fossil fuel CO₂ emissions (FFCO₂) from fine to coarse grids to enable atmospheric transport simulations can give rise to mismatches between the emissions and simulated atmospheric dynamics which differ over land or water. For example, emissions originally emanating from the land are emitted from a grid cell for which the vertical mixing reflects the roughness and/or surface energy exchange of an ocean surface. We test this potential "dynamical inconsistency" by examining simulated global atmospheric CO₂ concentration driven by two different approaches to regridding fossil fuel CO₂ emissions. The two approaches are as follows: (1) a commonly used method that allocates emissions to grid cells with no attempt to ensure dynamical consistency with atmospheric transport and (2) an improved method that reallocates emissions to grid cells to ensure dynamically consistent results. Results show large spatial and temporal differences in the simulated CO₂ concentration when comparing these two approaches. The emissions difference ranges from −30.3 TgC grid cell^-1 yr^-1 (−3.39 kgC m^-2 yr^-1) to +30.0 TgC grid cell^-1 yr^-1 (+2.6 kgC m^-2 yr^-1) along coastal margins. Maximum simulated annual mean CO₂ concentration differences at the surface exceed ±6 ppm at various locations and times. Examination of the current CO₂ monitoring locations during the local afternoon, consistent with inversion modeling system sampling and measurement protocols, finds maximum hourly differences at 38 stations exceed ±0.10 ppm with individual station differences exceeding −32 ppm. The differences implied by not accounting for this dynamical consistency problem are largest at monitoring sites proximal to large coastal urban areas and point sources. These results suggest that studies comparing simulated to observed atmospheric CO₂ concentration, such as atmospheric CO₂ inversions, must take measures to correct for this potential problem and ensure flux and dynamical consistency.

Lizards, which are amniote vertebrates like humans, are able to lose and regenerate a functional tail. Understanding the molecular basis of this process would advance regenerative approaches in amniotes, including humans. We have carried out the first transcriptomic analysis of tail regeneration in a lizard, the green anole Anolis carolinensis, which revealed 326 differentially expressed genes activating multiple developmental and repair mechanisms. Specifically, genes involved in wound response, hormonal regulation, musculoskeletal development, and the Wnt and MAPK/FGF pathways were differentially expressed along the regenerating tail axis. Furthermore, we identified 2 microRNA precursor families, 22 unclassified non-coding RNAs, and 3 novel protein-coding genes significantly enriched in the regenerating tail. However, high levels of progenitor/stem cell markers were not observed in any region of the regenerating tail. Furthermore, we observed multiple tissue-type specific clusters of proliferating cells along the regenerating tail, not localized to the tail tip. These findings predict a different mechanism of regeneration in the lizard than the blastema model described in the salamander and the zebrafish, which are anamniote vertebrates. Thus, lizard tail regrowth involves the activation of conserved developmental and wound response pathways, which are potential targets for regenerative medical therapies.

The reinforcers that maintain target instrumental responses also reinforce other responses that compete with them for expression. This competition, and its imbalance at points of transition between different schedules of reinforcement, causes behavioral contrast. The imbalance is caused by differences in the rates at which different responses come under the control of component stimuli. A model for this theory of behavioral contrast is constructed by expanding the coupling coefficient of MPR (Killeen, 1994). The coupling coefficient gives the degree of association of a reinforcer with the target response (as opposed to other competing responses). Competing responses, often identified as interim or adjunctive or superstitious behavior, are intrinsic to reinforcement schedules, especially interval schedules. In addition to that base-rate of competition, additional competing responses may spill over from the prior component, causing initial contrast; and they may be modulated by conditioned reinforcement or punishment from stimuli associated with subsequent component change, causing terminal contrast. A formalization of these hypotheses employed (a) a hysteresis model of off-target responses giving rise to initial contrast, and (b) a competing traces model of the suppression or enhancement of ongoing competitive responses by signals of following-schedule transition. The theory was applied to transient contrast, the following schedule effect, and the component duration effect.

Sensory systems encode both the static quality of a stimulus (e.g., color or shape) and its kinetics (e.g., speed and direction). The limits with which stimulus kinetics can be resolved are well understood in vision, audition, and somatosensation. However, the maximum temporal resolution of olfactory systems has not been accurately determined. Here, we probe the limits of temporal resolution in insect olfaction by delivering high frequency odor pulses and measuring sensory responses in the antennae. We show that transduction times and pulse tracking capabilities of olfactory receptor neurons are faster than previously reported. Once an odorant arrives at the boundary layer of the antenna, odor transduction can occur within less than 2 ms and fluctuating odor stimuli can be resolved at frequencies more than 100 Hz. Thus, insect olfactory receptor neurons can track stimuli of very short duration, as occur when their antennae encounter narrow filaments in an odor plume. These results provide a new upper bound to the kinetics of odor tracking in insect olfactory receptor neurons and to the latency of initial transduction events in olfaction.

Summer extreme heat events in the arid Phoenix, Arizona (USA) metropolitan region for the period 2041-2070 are projected based on the ensemble of ten climate models from the North American Regional Climate Change Assessment Program for the SRES A2 greenhouse gas emissions scenario by the Intergovernmental Panel on Climate Change. Extreme heat events are identified by measures related to two thresholds of the maximum daily air temperature distribution for the historical reference period 1971-2000. Comparing this reference period to the model ensemble-mean, the frequency of extreme heat events is projected to increase by a factor of six to 1.9 events per summer and the average number of event days per year is projected to increase by a factor of 14. The inter-model range for the average number of EHE days per summer is larger for the projected climate, 10.6 to 42.2 days, than for simulations of the past climate simulations (1.5 to 2.4 days).