Investigation on mechanical and thermal properties of 3D-printed polyamide 6, graphene oxide and glass-fibre-reinforced composites under dry, wet and high temperature conditions.

This study is focused on 3D printing of polyamide 6 (PA6), PA6/graphene oxide (PA6/GO) and PA6/glass-fibre-reinforced (PA6/GF) composites. The effect of graphene oxide and glass-fibre reinforcement on 3D-printed PA6 is explored for improvement of the interfacial bond and interlaminar strength in ambient, wet and high temperature conditions relating to electric car battery box requirements. The influence of environmental conditions and process parameters on the 3D printed polymer composites quality is also examined. Commercial PA6 filament was modified with GO to investigate the thermal and mechanical properties. The modified composites were melt-compounded using a twin-feed extruder to produce an improved 3D-printing filament. The improved filaments were then used to 3D-print test samples for tensile and compression mechanical testing using universal testing machines and thermal characterisation was performed following condition treatment in high temperature and water for correlation to dry/ambient samples. The study results show the studied materials were mostly suitable in dry/ambient conditions. PA6/GF samples demonstrated the highest strength of all three samples in ambient and high-temperature conditions, but the least strength in wet conditions due to osmotic pressure at the fibre/matrix interface that led to fibre breakage. The introduction of 0.1% GO improved the tensile strength by 33%, 11% and 23% in dry/ambient, dry/high temperature and wet/ambient conditions, respectively. The wet PA6/GO samples demonstrated the least strength in comparison to the ambient and high temperature conditions. Notwithstanding this, PA6/GO exhibited the highest tensile strength in the wet condition, making it the most suitable for a high-strength, water-exposed engineering application

Human PXR Forms a Tryptophan Zipper-Mediated Homodimer †

The human nuclear receptor pregnane X receptor (PXR) responds to a wide variety of potentially harmful chemicals and coordinates the expression of genes central to xenobiotic and endobiotic metabolism. Structural studies reveal that the PXR ligand binding domain (LBD) uses a novel sequence insert to form a homodimer unique to the nuclear receptor superfamily. Terminal β-strands from each monomeric LBD interact in an ideal antiparallel fashion to bury potentially exposed surface β-strands, generating a ten-stranded intermolecular β-sheet. Conserved tryptophan and tyrosine residues lock across the dimer interface and provide the first tryptophan-zipper (Trp-Zip) interaction observed in a native protein. We show using analytical ultracentrifugation that the PXR LBD forms a homodimer in solution. We further find that removal of the interlocking aromatic residues eliminates dimer formation but does not affect PXR's ability to interact with DNA, RXRα, or ligands. Disruption of the homodimer significantly reduces receptor activity in transient transfection experiments, however, and effectively eliminates the receptor's recruitment of the transcriptional coactivator SRC-1 both in vitro and in vivo. Taken together, these results suggest that the unique Trp-Zip-mediated PXR homodimer plays a role in the function of this nuclear xenobiotic receptor

Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests

Functional responses describe how changing resource availability affects con- sumer resource use, thus providing a mechanistic approach to prediction of the invasibility and potential damage of invasive alien species (IAS). However, functional responses can be context dependent, varying with resource characteristics and availability, consumer attributes, and environmental variables. Identifying context dependencies can allow invasion and damage risk to be predicted across different ecoregions. Understanding how ecological factors shape the functional response in agro-ecosystems can improve predictions of hotspots of highest impact and inform strategies to mitigate damage across locations with varying crop types and avail- ability. We linked heterogeneous movement data across different agro-ecosystems to predict ecologically driven variability in the functional responses. We applied our approach to wild pigs (Sus scrofa), one of the most successful and detrimental IAS worldwide where agricultural resource depredation is an important driver of spread and establishment. We used continental- scale movement data within agro-ecosystems to quantify the functional response of agricul- tural resources relative to availability of crops and natural forage. We hypothesized that wild pigs would selectively use crops more often when natural forage resources were low. We also examined how individual attributes such as sex, crop type, and resource stimulus such as dis- tance to crops altered the magnitude of the functional response. There was a strong agricul- tural functional response where crop use was an accelerating function of crop availability at low density (Type III) and was highly context dependent. As hypothesized, there was a reduced response of crop use with increasing crop availability when non-agricultural resources were more available, emphasizing that crop damage levels are likely to be highly heterogeneous depending on surrounding natural resources and temporal availability of crops. We found sig- nificant effects of crop type and sex, with males spending 20% more time and visiting crops 58% more often than females, and both sexes showing different functional responses depend- ing on crop type. Our application demonstrates how commonly collected animal movement data can be used to understand context dependencies in resource use to improve our under- standing of pest foraging behavior, with implications for prioritizing spatiotemporal hotspots of potential economic loss in agro-ecosystems

Multi-scale patterns of tick occupancy and abundance across an agricultural landscape in southern Africa.

Land use influences the prevalence and distribution of ticks due to the intimate relationship of ticks with their environment. This relationship occurs because land use alters two essential tick requirements: vertebrate hosts for blood meals and a suitable microclimate when off-host. Given the risks to human and animal health associated with pathogens transmitted by ticks, there is an ongoing need to understand the impact of environmental drivers on tick distributions. Here, we assessed how landscape features, neighborhood effects, and edges influenced tick occupancy and abundance across an agricultural landscape in southern Africa. We found that Rhipicephalus appendiculatus and Rhipicephalus simus increased in abundance closer to protected savanna, while Haemaphysalis elliptica increased in abundance closer to human habitation. The composition of the landscape surrounding savanna patches also differentially influenced the occupancy of each tick species; H. elliptica was more likely to be found in savanna patches surrounded by subsistence agriculture while R. appendiculatus and R. simus were more likely to be found in savanna surrounded by sugarcane monocultures. At the local scale we found that R. appendiculatus and R. simus avoided savanna edges. The availability of hosts and variation in vegetation structure between commercial agriculture, subsistence agriculture, and savanna likely drove the distribution of ticks at the landscape scale. Understanding how anthropogenic land use influences where ticks occur is useful for land use planning and for assessing public and animal health risks associated with ticks and tick-borne diseases

Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests

Functional responses describe how changing resource availability affects con- sumer resource use, thus providing a mechanistic approach to prediction of the invasibility and potential damage of invasive alien species (IAS). However, functional responses can be context dependent, varying with resource characteristics and availability, consumer attributes, and environmental variables. Identifying context dependencies can allow invasion and damage risk to be predicted across different ecoregions. Understanding how ecological factors shape the functional response in agro-ecosystems can improve predictions of hotspots of highest impact and inform strategies to mitigate damage across locations with varying crop types and avail- ability. We linked heterogeneous movement data across different agro-ecosystems to predict ecologically driven variability in the functional responses. We applied our approach to wild pigs (Sus scrofa), one of the most successful and detrimental IAS worldwide where agricultural resource depredation is an important driver of spread and establishment. We used continental- scale movement data within agro-ecosystems to quantify the functional response of agricul- tural resources relative to availability of crops and natural forage. We hypothesized that wild pigs would selectively use crops more often when natural forage resources were low. We also examined how individual attributes such as sex, crop type, and resource stimulus such as dis- tance to crops altered the magnitude of the functional response. There was a strong agricul- tural functional response where crop use was an accelerating function of crop availability at low density (Type III) and was highly context dependent. As hypothesized, there was a reduced response of crop use with increasing crop availability when non-agricultural resources were more available, emphasizing that crop damage levels are likely to be highly heterogeneous depending on surrounding natural resources and temporal availability of crops. We found sig- nificant effects of crop type and sex, with males spending 20% more time and visiting crops 58% more often than females, and both sexes showing different functional responses depend- ing on crop type. Our application demonstrates how commonly collected animal movement data can be used to understand context dependencies in resource use to improve our under- standing of pest foraging behavior, with implications for prioritizing spatiotemporal hotspots of potential economic loss in agro-ecosystems