Arg-Gly-Asp (RGD) sequence conjugated in a synthetic copolymer bearing a sugar moiety for improved culture of parenchymal cells (hepatocytes)

A copolymer, including a Gly-Arg-Gly-Asp-Ser (GRGDS) sequence and sugar moieties, was synthesized for the culturing of parenchymal cells (hepatocytes). Hepatocyte cells attached to poly[N-p-vinylbenzyl-d-maltonamide-co-6-(p-vinylbenzamido)-hexanoic acid-GRGDS] [poly(VMA-co-VBRGD)]-coated dishes grew approximately 60% better than on other polymer-coated surface for 12 h. Also, about 80% greater albumin secretion (0.38 pg ml^–1) and about 70% greater urea synthesis (0.495 pg ml^–1) from hepatocytes were produced in this matrix as compared with unstimulated cells. The behaviour of hepatocytes on poly(VMA-co-VBGRGDS)-coated dishes was not distinct from those attached to a collagen. The conjugation of the adhesion molecules of the RGD peptide in the poly(VMA-co-VBGRGDS) copolymer therefore specifically interacts with integrin families on the hepatocyte cell membrane.     

Mechano- and pH-sensing convergence on Ca2+-mobilising proteins – A recipe for cancer?

Alterations in the (bio)chemical and physical microenvironment of cells accompany and often promote disease formation and progression. This is particularly well established for solid cancers, which are typically stiffer than the healthy tissue in which they arise, and often display profound acidification of their interstitial fluid. Cell surface receptors can sense changes in the mechanical and (bio)chemical properties of the surrounding extracellular matrix and fluid, and signalling through these receptors is thought to play a key role in disease development and advancement. This review will look at ion channels and G protein coupled receptors that are activated by mechanical cues and extracellular acidosis, and stimulation of which results in increases in intracellular Ca²⁺ concentrations. Cellular Ca²⁺ levels are dysregulated in cancer as well as cancer-associated cells, and mechano- and proton-sensing proteins likely contribute to these aberrant intracellular Ca²⁺ signals, making them attractive targets for therapeutic intervention.     

Monitoring an invasive perennial at the landscape scale with remote sensing

Summary   Worldwide, invasive weeds threaten agricultural, natural and urban ecosystems. In Australia's agricultural and grazing regions, invasive species often establish across extensive areas where weed management is hampered by an inability to detect the location and timing of an outbreak. In these vast landscapes, an effective detection and monitoring system is required to delineate the extent of the invasion and identify spatial and temporal factors associated with weed establishment and thickening. In this study, we utilize a time series of remote sensing imagery to detect the spatial and temporal patterns of Prickly Acacia ( Acacia nilotica ) invasion in the Mitchell grass plains of North Queensland. We develop a spectral index from Landsat images which is applied to images from 1989 to 2004, in combination with a classification mask, to identify locations and monitor changes in Prickly Acacia density across 29 000 km² of Mitchell grass plains. The approach identified spectral and temporal signatures consistent with Prickly Acacia infestation on 1.9% of this landscape. Field checking of results confirmed presence of the weed in previously unrecorded locations. The approach may be used to evaluate future spread, or outcomes of management strategies for Prickly Acacia in this landscape and could be employed to detect and monitor invasions in other extensive landscapes.     

Sugar‐feeding status alters biting midge photoattraction

The biting midge Culicoides sonorensis Wirth and Jones (Diptera: Ceratopogonidae) transmits pathogens to both livestock and wildlife. Biting midge surveillance relies heavily on light traps for collection; however, little is known about the light spectra preferences of C. sonorensis midges. A light assay arena was constructed and light‐emitting diodes (LEDs) of various light spectra were used as light sources to evaluate midge photoattraction. A comparison of responses to light spectra indicated the highest proportions of C. sonorensis were attracted to ultraviolet (UV) light and that midges differentiated 10‐nm differences in wavelength. Stronger intensities of UV light resulted in greater attraction. Midges exhibited both sugar‐seeking and escape behaviours under different conditions of sugar supplementation before and during the experiment. These behaviours occurred with lights of 355 nm and 365 nm in wavelength. Based on the results of this study, the attraction of C. sonorensis to light traps can be improved through the use of bright LEDs at 355 nm or 365 nm.     

Significant impact of divalent metal ions on the fidelity,sugar selectivity,and drug incorporation efficiency of human PrimPol

Human PrimPol is a recently discovered bifunctional enzyme that displays DNA template-directed primase and polymerase activities. PrimPol has been implicated in nuclear and mitochondrial DNA replication fork progression and restart as well as DNA lesion bypass. Published evidence suggests that PrimPol is a Mn²⁺-dependent enzyme as it shows significantly improved primase and polymerase activities when binding Mn²⁺, rather than Mg²⁺, as a divalent metal ion cofactor. Consistently, our fluorescence anisotropy assays determined that PrimPol binds to a primer/template DNA substrate with affinities of 29 and 979 nM in the presence of Mn²⁺ and Mg²⁺, respectively. Our pre-steady-state kinetic analysis revealed that PrimPol incorporates correct dNTPs with 100-fold higher efficiency with Mn²⁺ than with Mg²⁺. Notably, the substitution fidelity of PrimPol in the presence of Mn²⁺ was determined to be in the range of 3.4 × 10⁻² to 3.8 × 10⁻¹, indicating that PrimPol is an error-prone polymerase. Furthermore, we kinetically determined the sugar selectivity of PrimPol to be 57–1800 with Mn²⁺ and 150–4500 with Mg²⁺, and found that PrimPol was able to incorporate the triphosphates of two anticancer drugs (cytarabine and gemcitabine), but not two antiviral drugs (emtricitabine and lamivudine).     

Anti-biofilm and anti-adherence properties of novel cyclic dipeptides against oral pathogens

Microorganisms embedded in a biofilm are significantly more resistant to antimicrobial agents and the defences of the human immune system, than their planktonic counterpart. Consequently, compounds that can inhibit biofilm formation are of great interest for novel therapeutics. In this study, a screening approach was used to identify novel cyclic dipeptides that have anti-biofilm activity against oral pathogens. Five new active compounds were identified that prevent biofilm formation by the cariogenic bacterium Streptococcus mutans and the pathogenic fungus Candida albicans. These compounds also inhibit the adherence of microorganisms to a hydroxylapatite surface. Further investigations were conducted on these compounds to establish the structure–activity relationship, and it was deduced that the common cleft pattern is required for these molecules to act effectively against biofilms.     

Relationship between the concentration of sugars in the roots and VA mycorrhizal infection

Summary The VA-infected wheat varieties showed an increase of total (Lozano var.) and reducing (Lozano and Pane vars.) sugars in their root extracts. However, no clear relationship between sugar concentration in the root and VA mycorrhizal infection level could be established.In addition, the VA mycorrhizal hosts sorghum, alfalfa, sunflower and maize, and non-host radish and cabbage plants were tested for sugar content in their root extracts after fifteen days of growth. Sugars present in the root extracts of these plants did not seem to be a decisive factor in plant susceptibility to VA infection.     

Zoning eco-environmental vulnerability for environmental management and protection

Eco-environmental vulnerability assessment is crucial for environmental and resource management. However, evaluation of eco-environmental vulnerability over large areas is a difficult and complex process because it is affected by many variables including hydro-meteorology, topography, land resources, and human activities. The Thua Thien – Hue Province and its largest river system, the Perfume River, are vital to the social-economic development of the north central coastal region of Vietnam, but there is no zoning system for environmental protection in this region. An assessment framework is proposed to evaluate the vulnerable eco-environment in association with 16 variables with 6 of them constructed from Landsat 8 satellite image products. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands where social-economic activities have been developing rapidly. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. The proposed integrated method of remote sensing (RS), GIS, and AHP to evaluate the eco-environmental vulnerability is useful for environmental protection and proper planning for land use and construction in the future.     

Modelling biomass of mountainous grasslands by including a species composition map

High mountain grasslands offer multiple goods and services to society but are severely threatened by improper land use practices such as abandonment or rapid intensification. In order to reduce abandonment and strengthen the common extensive agricultural practice a sustainable land use management of high mountain grasslands is needed. A spatially detailed yield assessment helps to identify possible meadows or, on the contrary, areas with a low carrying capacity in a region, making it easier to manage these sites. Such assessments are rarely available for remote and inaccessible areas. Remotely sensed vegetation indices are able to provide valuable information on grassland properties. These indices tend, however, to saturate for high biomass. This affects their applicability to assessments of high-yield grasslands.The main aim of this study was to model a spatially explicit grassland yield map and to test whether saturation issues can be tackled by consideration of plant species composition in the modelling process. The high mountain grassland of the subalpine belt (1800 – 2500 m a.s.l.) in the Kazbegi region, Greater Caucasus, Georgia, was chosen as test site for its strong species composition and yield gradients.We first modelled the species composition of the grassland described as metrically scaled gradients in the form of ordination axes by random forest regression. We then derived vegetation indices from Rapid Eye imagery, and topographic variables from a digital elevation model, which we used together with the multispectral bands as predictive variables. For comparison, we performed two yield models, one excluding the species composition maps and one including the species composition map as predictors. Moreover, we performed a third individual model, with species composition as predictors and a split dataset, to produce the final yield map.Three main grassland types were found in the vegetation analysis: Hordeum violaceum-meadows, Gentianella caucasea-grassland and Astragalus captiosus-grassland. The three random forest regression models for the ordination axes explained 64%, 33% and 46% of the variance in species composition. Independent validation of modelled ordination scores against a validation data set resulted in an R² of 0.64, 0.32 and 0.46 for the first, second and third axes, respectively. The model based on species composition resulted in a R² = 0.55, whereas the benchmark model showed weaker relationships between yield and the multispectral reflectance, vegetation indices, and topographical parameters (R² = 0.42). The final random forest yield model used to derive the yield map resulted in 62% variance explained and an R² = 0.64 between predicted and observed biomass. The results further indicate that high yields are generally difficult to predict with both models.The benefit of including a species composition map as a predictor variable for grassland yield lies in the preservation of ecologically meaningful features, especially the occurrence of high yielding vegetation type of Hordeum violaceum meadows is depicted accurately in the map. Even though we used a gradient based design, sharp boundaries or immediate changes in productivity were visible, especially in small structures such as arable fields or roads (Fig. 6b), making it a valuable tool for sustainable land use management. The saturation effect however, was mitigated by using species composition as predictor variables but is still present at high yields.