Scale‐down simulators for mammalian cell culture as tools to access the impact of inhomogeneities occurring in large‐scale bioreactors

During the scale‐up of a bioprocess, not all characteristics of the process can be kept constant throughout the different scales. This typically results in increased mixing times with increasing reactor volumes. The poor mixing leads in turn to the formation of concentration gradients throughout the reactor and exposes cells to varying external conditions based on their location in the bioreactor. This can affect process performance and complicate process scale‐up. Scale‐down simulators, which aim at replicating the large‐scale environment, expose the cells to changing environmental conditions. This has the potential to reveal adaptation mechanisms, which cells are using to adjust to rapidly fluctuating environmental conditions and can identify possible root causes for difficulties maintaining similar process performance at different scales. This understanding is of utmost importance in process validation. Additionally, these simulators also have the potential to be used for selecting cells, which are most robust when encountering changing extracellular conditions. The aim of this review is to summarize recent work in this interesting and promising area with the focus on mammalian bioprocesses, since microbial processes have been extensively reviewed.     

Continuous Flow Routes toward Designer Metal Nanocatalysts

Mono‐ and multimetallic nanoparticles (NPs) have diverse and tunable physicochemical properties that arise from their compositions as well as crystallite size and shape. The ability to control precisely the composition and structure of NPs through synthesis is central to achieving state‐of‐the‐art designer metal NPs for use as catalysts and electrocatalysts. However, a major limitation to the use of designer metal NPs as catalysts is the ability to scale their syntheses while maintaining structural precision. To address this challenge, continuous flow routes to metal NPs involving the use of droplet microreactors are being developed, providing the synthetic versatility necessary to achieve known and completely new nanostructures. This progress report outlines how the chemistry and process parameters of droplet microreactors can be used to achieve high performing nanocatalysts through control of NP composition, size, shape, and architecture and outlines directions toward previously unimaginable nanostructures.     

Analysis of Alkylphenol ethoxylates (APEOs) from tannery sediments using LC–MS and their environmental risks

Alkyl phenol polyethoxylates (APEOs) are a major group of high production volume chemicals, extensively used as nonionic surfactants in industrial, agricultural and domestic sectors. These surfactants and its respective metabolites are found to be persistent and toxic. Mainly, they act as endocrine disruptors by mimicking the natural hormones. India being a developing country, witnesses pollution due to various industries including tannery. In the present study, sediment samples were collected from the Vellore district of Tamil Nadu, India to investigate the occurrence of APEOs. The sediments were extracted by ultrasonication and analyzed in a liquid chromatography mass spectrometer. Octyl phenol ethoxylates (OPEOs) were not observed in any of the samples. Nonyl phenol ethoxylates (NPEOs) were detected in the range of ND – 36 mg/kg with 85 % detection frequency. The occurrence of NPEOs in sediment indicates its wide usage in tannery and its partitioning behavior in environment. The levels of NPEOs in the study were found to be unsafe according to the sediment guidelines of various studies. Since NPEOs were observed in sediment samples, possibilities of occurrence of their monomers and metabolites cannot be ruled out. Therefore, further studies are warranted for understanding the levels of monomers and metabolites in order to ascertain the environmental risks more appropriately.     

Spatial synchrony in the response of a long range migratory species (Salmo salar) to climate change in the North Atlantic Ocean

A major challenge in understanding the response of populations to climate change is to separate the effects of local drivers acting independently on specific populations, from the effects of global drivers that impact multiple populations simultaneously and thereby synchronize their dynamics. We investigated the environmental drivers and the demographic mechanisms of the widespread decline in marine survival rates of Atlantic salmon (Salmo salar) over the last four decades. We developed a hierarchical Bayesian life cycle model to quantify the spatial synchrony in the marine survival of 13 large groups of populations (called stock units, SU) from two continental stock groups (CSG) in North America (NA) and Southern Europe (SE) over the period 1971–2014. We found strong coherence in the temporal variation in postsmolt marine survival among the 13 SU of NA and SE. A common North Atlantic trend explains 37% of the temporal variability of the survivals for the 13 SU and declines by a factor of 1.8 over the 1971–2014 time series. Synchrony in survival trends is stronger between SU within each CSG. The common trends at the scale of NA and SE capture 60% and 42% of the total variance of temporal variations, respectively. Temporal variations of the postsmolt survival are best explained by the temporal variations of sea surface temperature (SST, negative correlation) and net primary production indices (PP, positive correlation) encountered by salmon in common domains during their marine migration. Specifically, in the Labrador Sea/Grand Banks for populations from NA, 26% and 24% of variance is captured by SST and PP, respectively and in the Norwegian Sea for populations from SE, 21% and 12% of variance is captured by SST and PP, respectively. The findings support the hypothesis of a response of salmon populations to large climate‐induced changes in the North Atlantic simultaneously impacting populations from distant continental habitats.     

Stromatolite-dominated microbialites at the Permian–Triassic boundary of the Xikou section on South Qinling Block,China

Permian–Triassic boundary microbialites (PTBMs) are organosedimentary carbonates formed immediately after the end-Permian mass extinction. All those reported PTBMs constrained by convincing conodont biozones are present stratigraphycally not higher than the Hindeodus parvus zone and most of them are dominated by thrombolites. This paper provides the first record of a brief, but spectacular development of stromatolite-dominated PTBMs within the basal Isarcicella isarcica conodont zone of the earliest Triassic from the Xikou section of South Qinling Block that was at the margin of the North China Block during the Permian–Triassic transition and was geographically separated from the major occurrence of post-extinction microbialites in the South China Block. This stromatolite cap overlies a 3.7-m-thick oolitic limestone and is composed of a lower 0.2-m-thick bed and an upper 0.5-m-thick bed, separated by a 0.2-m-thick greyish green siliciclastic mudstone. These two stromatolite beds mainly consist of columnar stromatolites with subordinate domal stromatolites. The intercolumn and interstitial spaces within the stromatolites are filled with oolitic grainstones. At the microscopic scale, laminoid structures in stromatolites comprise wavy, millimetric-domical and tangled laminae. The increased grain and fossil contents and/or bioturbation in the domical and tangled laminae indicate that the formation of these laminae is likely related to an increase in the populations and the disruptions by benthic metazoans, as well as an influx of sediment grains. The δ¹³C_carb values fluctuate between 2‰ and 3‰ in the uppermost Permian strata; a distinct negative shift of 1.9‰ occurs at the topmost oolitic grainstone, just below the lower stromatolite bed, and the lowest value of −0.1‰ is located at the base of the upper stromatolite bed. The stratigraphic succession from stromatolites to thrombolites of the PTBMs may represent a transgressive succession and/or a transient ecosystem recovery immediately after the end-Permian mass extinction. The thrombolites-dominated PTBMs mainly developed in near-equator shallow marine geographic locations, and stromatolite-dominated PTBMs mainly developed at higher latitude settings, which probably indicates that a relatively lower diversity and abundance of marine benthic metazoans existed at higher latitudes after the end-Permian mass extinction.     

Using density surface models to estimate spatio-temporal changes in population densities and trend

Precise measures of population abundance and trend are needed for species conservation; these are most difficult to obtain for rare and rapidly changing populations. We compare uncertainty in densities estimated from spatio–temporal models with that from standard design-based methods. Spatio–temporal models allow us to target priority areas where, and at times when, a population may most benefit. Generalised additive models were fitted to a 31-year time series of point-transect surveys of an endangered Hawaiian forest bird, the Hawai‘i ‘ākepa Loxops coccineus. This allowed us to estimate bird densities over space and time. We used two methods to quantify uncertainty in density estimates from the spatio–temporal model: the delta method (which assumes independence between detection and distribution parameters) and a variance propagation method. With the delta method we observed a 52% decrease in the width of the design-based 95% confidence interval (CI), while we observed a 37% decrease in CI width when propagating the variance. We mapped bird densities as they changed across space and time, allowing managers to evaluate management actions. Integrating detection function modelling with spatio–temporal modelling exploits survey data more efficiently by producing finer-grained abundance estimates than are possible with design-based methods as well as producing more precise abundance estimates. Model-based approaches require switching from making assumptions about the survey design to assumptions about bird distribution. Such a switch warrants consideration. In this case the model-based approach benefits conservation planning through improved management efficiency and reduced costs by taking into account both spatial shifts and temporal changes in population abundance and distribution.     

Mechanistic insights into the role of large carnivores for ecosystem structure and functioning

Large carnivores can exert top–down effects in ecosystems, but the size of these effects are largely unknown. Empirical investigation on the importance of large carnivores for ecosystem structure and functioning presents a number of challenges due to the large spatio-temporal scale and the complexity of such dynamics. Here, we applied a mechanistic global ecosystem model to investigate the influence of large-carnivore removal from undisturbed ecosystems. First, we simulated large-carnivore removal on the global scale to inspect the geographic pattern of top–down control and to disentangle the functional role of large carnivores in top–down control in different environmental contexts. Second, we conducted four small-scale ecosystem simulation experiments to understand direct and indirect changes in food-web structure under different environmental conditions. We found that the removal of top–down control exerted by large carnivores (> 21 kg) can trigger large trophic cascades, leading to an overall decrease in autotroph biomass globally. Furthermore, the loss of large carnivores resulted in an increase of mesopredators. The magnitude of these changes was positively related to primary productivity (NPP), in line with the ‘exploitation ecosystem hypothesis’. In addition, we found that seasonality in NPP dampened the magnitude of change following the removal of large carnivores. Our results reinforce the idea that large carnivores play a fundamental role in shaping ecosystems, and further declines and extinctions can trigger substantial ecosystem responses. Our findings also support previous studies suggesting that natural ecosystem dynamics have been severely modified and are still changing as a result of the widespread decline and extinction of large carnivores.     

2′-Functional group of adenosine in 10–23 DNAzyme promotes catalytic activity

10–23 DNAzyme is an artificially selected catalytic DNA molecule. Its great potential as genetic therapeutics promoted chemical modifications for more efficient DNAzymes. Here, 10–23 DNAzyme was modified on its six deoxyadenosine residues (A5, A9, A11, A12, A15 in the catalytic domain and A0 of the recognition arm next to the cleavage site) with compound 1, an adenosine analogue with 2′-O-[N-(aminoethyl)carbamoyl]methyl group. A positive effect of compound 1 at A15 was observed (HJDS-05, k_obs = 0.0111 min⁻¹). Compared to the effect of 2′-H and 2′-OMe at A15, this result provided an approach for more efficient DNAzyme by combining 2′-substituted amino group of adenosine with A15 as the lead structure.