10 ± 0 06 for apo-12′-carotenal The residual water contents in g

10 ± 0.06 for apo-12′-carotenal. The residual water contents in g/100 g of MD microcapsules were also similar: 2.30 ± 0.13 for trolox, 2.20 ± 0.07 for α-tocopherol, 2.00 ± 0.07 for β-carotene, 2.30 ± 0.11 for apo-8′-carotenal and 2.40 ± 0.04 for apo-12′-carotenal. The composition of the antioxidant compounds in the microcapsules was determined in order to verify composition changes after microencapsulation. In order to release the carotenoids, around 0.20 g of the MD microcapsules

were dispersed http://www.selleckchem.com/products/SB-203580.html in 5 ml of water, whilst 0.10 g of the GA ones were dispersed in 5 ml of water:methanol (2:3, v/v). The carotenoids were extracted exhaustively with dichloromethane from the microcapsule solution; the organic phases were recovered in a separation funnel and the residual water was removed with anhydrous Na2SO4. α-Tocopherol and trolox were extracted straight from 0.20 g of the microcapsule powder with 5 ml of ethanol by sonication (1 min), vortexing

(5 min) and centrifugation (Beckman Coulter, California, USA) at 20000 g during 5 min. Afterward, the residual water of the supernatant was removed with anhydrous Na2SO4 and filtered. The solvent was removed under vacuum in a rotary evaporator (T < 35 °C). The dry extracts were redissolved, carotenoids in methanol:methyl tert-butyl-ether (1:1, v/v), α-tocopherol in methanol and trolox in methanol:water:formic acid (70:29.5:0.5, v/v/v), and analyzed by HPLC–DAD–MS/MS. These Protease Inhibitor Library results are presented Selleckchem Rapamycin at Supplementary Figs. S2, S3 and Table S1. The experiments were conducted immediately after the preparation of fresh microcapsules aqueous solutions to avoid their slow collapse in solution since in our previous study, these microcapsules presented a half-life of 17 ± 3 h and around 60 h for the complete release of pyrene molecules (Faria et al., 2010). The assays were carried out in a microplate reader (Synergy Mx, BioTek, Vermont, USA) for fluorescence, UV/vis and luminescence measurements, equipped with a thermostat set at 37 °C and dual reagent dispenser. Two control assays were conducted in all

microplates, one of them to verify the interaction among the probe and the microcapsules, without radical generator or reactive species addition and the other one as quality analytical control (positive control), adding a compound with known capacity to scavenge the specific reactive species. No interaction between the probes and the microcapsules was observed and the maximum variation in the response of the positive controls during the assays was ⩽10%. Each ROS and RNS scavenging assay corresponds to two independent experiments, performed in duplicate. Except for peroxyl radical scavenging capacity, the results are presented as percent of inhibition, IC50 or IC20 values, calculated by non-linear regression analysis using the GraphPad Prism 5 software. The increase in scavenging capacity due to addition of antioxidant molecules was calculated by Eq. (1).

, 2012) The DGGE band signals were calculated by Quantity One so

, 2012). The DGGE band signals were calculated by Quantity One software (Bio-Rad Laboratories Inc., Tokyo, Japan). The signal intensities and band position in each lane were divided into a spectrum of 100 variables. Principal component analysis (PCA) was run using R software and performed according to a previous report (Date et al., 2012). The first objective of this study was to develop a rapid and simple method for screening candidate prebiotic foods and their components. In order to develop the screening method, we focused on the metabolic profiles from intestinal microbiota incubated in vitro with feces. In our previous study ( Date et al., 2010), metabolic dynamics and microbial

variability from the in vitro incubation with glucose were characteristically observed, and the

substrate was completely consumed within 12 h of incubation. In addition, the metabolic dynamics Everolimus from the in vitro incubation with FOS, raffinose, and stachyose (known as prebiotic foods) were characteristically varied in 1H NMR-based metabolic profiles. Therefore, we decided that 12 h after incubation was the best sampling point for evaluation and comparison of metabolic profiles generated by intestinal microbiota incubated with various substrates. The metabolic profiles Olaparib from incubation with FOS, raffinose, stachyose, pectin from apple, kelp, wheat-bran, starch from wheat, Japanese mustard spinach, chlorella, glucan, arrowroot, starch from arrowroot, agar, carrageenan, JBO, JBOVS, onion, or control (no addition of substrate) were measured by an NMR-based metabolomics approach (Fig. S1). Plots of PCA scores for these data demonstrated that the metabolic profiles clustered to two groups (Fig. 1A). One group included the metabolic profiles from the incubation with FOS, raffinose, stachyose, JBO, JBOVS, and onion. The other metabolic profiles obtained from the incubation with pectin from apple, kelp, wheat-bran, starch from wheat, Japanese however mustard spinach, chlorella, glucan, arrowroot, starch from arrowroot, agar, or carrageenan were clustered with

the controls. Because the FOS, raffinose, and stachyose are well known prebiotic foods, JBO, JBOVS, and onion were potential candidate prebiotic foods. To identify the factors contributing to these clusterings, analysis of loading plots based on the 1H NMR spectra was performed to provide information on the spectral position responsible for the position of coordinates in the corresponding scores plots (Fig. 1B). The results indicated that lactate and acetate contributed to the clustering for both the ‘candidate prebiotic food group’ and the ‘control group’ because the peaks of acetate and lactate in the ‘candidate prebiotic food group’ were shifted (Fig. S1). Furthermore, the pH levels were relatively low and the lactate production levels were relatively high in the ‘candidate prebiotic food group’ compared with the ‘control group’ (Fig. 1C).

The [M]+ at m/z 669 led to MS/MS fragments at m/z 507[M−162]+, 46

The [M]+ at m/z 669 led to MS/MS fragments at m/z 507[M−162]+, 465[M−204]+ and 303[M−162-204]+ ( Table 2). In this case, losses of 162 u and 204 u corresponded, respectively, to a unit of hexose and of an acetylated hexose (162 + 42 u) ( Cuyckens & Claeys, 2004), and the fragment at m/z 303 is characteristic of the aglycone delphinidin. Furthermore, the elution order in relation to dpn 3,5-diglucoside is consistent with what is expected from the reversed-phase elution, e.g., the acylated

anthocyanins elute after their corresponding non-acylated anthocyanins ( Wu & Prior, 2005). The major anthocyanins found in jambolão were delphinidin 3,5-diglucoside (45%), petunidin 3,5-diglucoside (32%) and malvidin PLX-4720 research buy 3,5-diglucoside (15%). These results are consistent with those reported in previous studies with jambolão fruits, where the major anthocyanins were identified as 3,5-diglucosides of delphinidin (23–33%), petunidin (32–35%) and malvidin (21–38%) (Brito et al., 2007, Li et al., 2009a and Veigas et al., 2007). In addition to these anthocyanins, Brito et al. (2007) and MK-1775 cost Li et al., 2009a and Li et al., 2009b also identified 3,5-diglucosides of cyanidin and peonidin. The phenolic

compounds shown in Table 3 (chromatogram in Fig. S3 from Supplementary data) were mainly identified by the mass spectra characteristics, since ionisation in the positive and negative modes gave complementary information, such as the case where only the protonated molecule ([M+H]+) with sodium adduct [M+Na]+ was detected in the positive mode. The presence of the deprotonated molecule ([M−H]−) allowed the confirmation of

the molecular weight of the compounds. The identification of gallic acid (peak 2) was based on the characteristics of UV–Vis and mass spectra (Table 3) compared to literature data (Cuyckens and Claeys, 2004 and Nuengchamnong and Ingkaninan, 2009) and confirmed by co-chromatography. This phenolic acid showed λmax at 271 nm, characteristic of phenolic acids derived from hydroxybenzoic acid. Moreover, the mass spectra obtained from both ESI+ (fragment at m/z 153) and ESI− ([M−H]− at m/z 169) showed the same characteristics as the ones obtained from the standard analysed under the same conditions. Flavopiridol (Alvocidib) Peak 1 was tentatively identified as galloyl-glucose ester based on the elution order on reversed phase relative to free gallic acid (peak 2), detection of [M−H]− at m/z 331, and loss of 162 u, equivalent to the elimination of an hexose unit, giving the fragment ion at m/z 169 corresponding to gallic acid. The [M+Na]+ at m/z 355 was observed in the ESI+ analysis. Furthermore, this compound also showed λmax at 278 nm, characteristic of phenolic acids. Moreover, the galloyl-glucose ester (peak 1) showed the same MS/MS fragmentation pattern as the galloyl-glucose ester found in jambolão wine ( Nuengchamnong & Ingkaninan, 2009).

, 2001 and Wallace, 1996) Of special global concern

is t

, 2001 and Wallace, 1996). Of special global concern

is the indoor use of solid fuel. More than 3 mill deaths were attributed to this cause in 2010 (Lim et al., 2012). Particles from outdoors can be transported into the indoor environment by ventilation and infiltration (Chen and Zhao, 2011). Indoor concentrations of PM that originates from outdoor sources are affected VX-809 molecular weight by multiple factors such as location, weather conditions (including outdoor temperature and wind speed), outdoor PM concentrations, the chemical and physical properties of the pollutants (specifically deposition and resuspension rate, and chemical reactions), building characteristics, air exchange rates, window openings and personal behaviors (Morawska et al., 2013). In addition, a variety of indoor emission sources such as candle burning, cooking, heating devices, environmental tobacco smoke, office equipment, biological sources, and human activity contribute substantially to the total personal exposure (Morawska et al., 2013 and Wallace and Ott, 2011). Indoor air PM also include bioaerosols such as bacteria, fungi, endotoxin and other components found in settled dust which can have inflammatory potential and effect on e.g. respiratory health

(Tischer et al., 2011). In addition, indoor suspended PM including soot particles may act as potential allergen carriers (Ormstad, 2000). Inhalation of indoor air pollutants together with selleck inhibitor these indoor aeroallergens or endotoxin may induce airway inflammation, leading to the

exacerbation of airway mafosfamide and allergic diseases, including asthma (Leung et al., 2002). Studies on adults with asthma and rhinitis have shown that the indoor home environment was associated with lung dysfunction, poor health status, and disease severity (Blanc et al., 2005). Nevertheless, there is a lack of studies relating indoor concentrations of UFPs to respiratory and cardiovascular health outcomes, especially with parallel assessment of associations with outdoor pollutants. We conducted a cross-sectional study to investigate whether microvascular function (MVF) and lung function were inversely associated with exposure to real-life levels of air pollution in the indoor and outdoor environments in an urban population. MVF and endothelial function have been widely used for cardiovascular hazard identification of PM (Moller et al., 2011). The outdoor air pollution levels were assessed by urban background monitoring in terms of PM10, PM2.5, mean particle diameter and PNC (size range 10–280 nm), which is highly dominated by UFP. The indoor exposure assessment included measurements of PNC (size range 10–300 nm) also highly dominated by UFP from candle burning, which is an important source in the winter period in Denmark (Bekö et al.

In Experiment 1, we showed that performance dropped with 11 branc

In Experiment 1, we showed that performance dropped with 11 branches compared to 6 branches, thus providing evidence that children detect and use the information provided by the one-to-one correspondence between branches and puppets. However, owing to the small sample size, the performance of this group alone did not reveal whether subset-knowers are at

all able to reconstruct large exact numbers of objects, when one-to-one correspondence cues are not informative. We thus administered the 11-branch condition to the participants of Experiment 2 as well, in an effort to increase the sample. Here we present the data pooled for all participants in Experiments 1 and 2. The 11-branch condition was identical to Experiment 1 (no transformation), Roxadustat datasheet except that the sets of 5 or 6 puppets were now placed on a tree with 11 branches, thus making a difference of one puppet harder to detect. Children received two trials in the 11-branch condition (one with 5 puppets, one with 6 puppets), after completion of the two trials of Experiment 1 or 2. In total, 36 subset-knowers (16 female, mean age 34.08 months,

32:06–35:26) contributed data for both set sizes (5 and 6 puppets): 13 participants from Experiment 1, 13 participants from the puppet addition/subtraction condition in Experiment 2, and 10 participants from the branch addition/subtraction condition in Experiment 2. Fig. 6 presents children’s performance in this experiment. There was no difference between the subgroups ATM Kinase Inhibitor of children who had

previously participated in different experiments or conditions ( ps>.24,ηp2s<.09 for the main effect and interaction involving Subgroup) so the data were pooled across these experiments and conditions. Children’s performance 3-oxoacyl-(acyl-carrier-protein) reductase was opposite in direction to the correct pattern: they searched longer in the trial in which no puppet should have remained in the box (5-puppet trial) than in the trial in which one puppet should have remained (6-puppet trial), F  (1, 33) = 4.4, p   = .043, ηp2=.12. This seemingly counterintuitive result appears to be an effect of the feedback received on the first trial: on the second trial, children tended to align their searches with this feedback. Hence, children tended to search less after a first trial with 5 puppets, in which no further search was warranted (3072 ms searching with 5 puppets followed by 887 ms searching with 6 puppets); in contrast, the searching time increased slightly after a first trial with 6 puppets, in which the feedback had shown one puppet to be missing (1467 ms searching with 6 puppets followed by 1874 ms searching with 5 puppets). This pattern resulted in an interaction between Set Size and Trial Order, F  (1, 34) = 5.7, p   = .023, ηp2=.14.

Conversely, resprouted individuals


Conversely, resprouted individuals

usually see more exhibit multiple stems growing from the stump of trees damaged during the prior slash-and-burn event. It is common to find sprouts growing among stump remains of different ages. This observation demonstrates that the BN tree can survive and resprout from successive SC cycles. We attempted to determine the minimum number of times that each resprouted individual was cut. To do so, we observed the sequence of previous growth cycles in the preserved stumps and added one more cycle in cases where the oldest visible stumps had already grown from a multiple-stem individual. Indications from the living stems and from the soil around each tree’s base also furnished information about the number of times the individuals were cut and resprouted. A single resprouted stem could be mistaken for an uncut tree that had grown directly from seed. However, even such individuals preserve evidence in the form of scars, calluses, and thickness typical of trees that suffered fire damage or clear-cutting and then resprouted. We also examined the soil under the base of the trees, where we searched for buried stumps, charcoal,

dark-hued carbonized wood tissue, and depressions resulting from root-structure decomposition. Proteases inhibitor Digging in the soil was the best way to distinguish tiny resprouts from recently emerged seedlings, which preserve their almonds for over a year (Cornejo, 2003). We calculated dispersal distance by georeferencing all BN plants found and all of the conspecific productive adults surrounding the 40 cultivation sites. Pair distances were measured with the near tool in ArcGIS v.9.1 (ESRI, 2005). To compare BN density with

the chances for each site to receive dispersed seeds from the surrounding parental trees, we used the ArcGIS spatial analyst tool to obtain the minimum Euclidean distance from the nearest productive BN trees to each 5-m2 raster cell inside the perimeter of the sites (Parrish et al., 2007). With this approach, the average cell distance calculated for the entire site not only accounted Bcl-w correctly for the distances to all surrounding parent trees but also remained proportional to the areal extent, allowing for direct comparisons among the different sites. The extractivists may choose to preserve their fallows once the sites reach a noticeable BN density, thereby excluding them from further cultivation cycles. To assess this decisive factor, we compared the BN regeneration density with the landholder’s or community’s decision to preserve (or not to preserve) the sites. Another protective practice is aimed not at the fallow site as a whole, but at stretches of it or even at individual BN plants. In this case, the secondary forest is cut and burned as usual, but some BN trees are deliberately spared and remain standing, typically on the perimeter of the future crop or pasture site.

We would like to thank Ana Regina de Oliveira Polay, Fernanda Bar

We would like to thank Ana Regina de Oliveira Polay, Fernanda Barrichello Tosello, Thais Mageste Duque, and Geovania Caldas Almeida for technical support. “
“During the cleaning and shaping of the root canal system, dentin chips are created by instrument action. These chips associated FRAX597 solubility dmso with organic materials,

microorganisms, and irrigant solutions form the so-called smear layer. This layer adheres to the dentinal surface and occludes the dentinal tubules 1 and 2. Many researchers believe that the smear layer should be removed. This layer contains bacteria and necrotic tissue (3). It forms a barrier between the filling material and sound dentin that inhibits the penetration of irrigants into dentinal tubules, increases microleakage with commonly used sealers, and decreases the bond strength of resin based materials 4, 5, 6, 7, 8, 9 and 10. Some chemical agents CH5424802 in vitro such as EDTA solutions at concentrations ranging from 15 to 17%, citric acid (5%-50%), and phosphoric acid (5%-37%), therefore, are used

to remove this layer (11). Despite the relevant literature available concerning the effect of these agents on the smear layer removal, the small number of studies with similar methodologies and comparable time intervals and concentrations limits the ability to make valid comparisons between these treatments, especially when considering the use of phosphoric acid. This chemical agent has been extensively used to remove the smear layer from coronal dentin 12, 13 and 14, and only a few studies

have analyzed its performance in root dentin 15, 16 and 17. Therefore, the aim of this study was to compare the effectiveness of 37% phosphoric acid with that of 17% EDTA and 10% citric acid in removing the smear layer by means of scanning electron microscopy (SEM). This study was approved by the Ethics Committee of the Federal University of Rio de Janeiro. Fifty-two single-rooted maxillary human canines, extracted because of periodontal or prosthetic reasons, were used. The teeth were Nitroxoline randomly selected from known patients. All patients signed an informed consent document to take part of this research. Their age ranged from 45 to 73 years old. The teeth with straight roots, mature root apex, and similar anatomic characteristics were selected for this study. The teeth were accessed by using #1558 carbide burs (Kg Sorensen, São Paulo, SP, Brazil). The teeth were shaped by using a K3 NiTi rotary system (SybronEndo, Orange, CA). The sequence used was the following: 25/.06, followed by a sequence of Gates-Glidden burs (Dentsply Maillefer, Ballaigues, Switzerland) from 1 to 5 to prepare the middle-cervical third. The K3 sequence used in the apical third was 15/.04, 20/.02, 20/.04, 25/.04, 20/.06 and 25/.06. All files achieved both working length in the apex. Between files, the canals were irrigated with 1 mL of sodium hypochlorite. After instrumentation, the teeth were irrigated with 5 mL of distilled water.

, 2011) Thus, in view of the growing numbers of immunosuppressed

, 2011). Thus, in view of the growing numbers of immunosuppressed patients, the development of alternative anti-adenovirus treatment options is required Lapatinib price to decrease adenovirus-mediated mortality among immunocompromised patients, and also to decrease economic losses caused by milder forms of adenovirus-related disease. RNA interference (RNAi) is a post-transcriptional mechanism of gene silencing conserved among

eukaryotic cells (Carthew and Sontheimer, 2009, Ghildiyal and Zamore, 2009, Huntzinger and Izaurralde, 2011, Hutvagner and Simard, 2008 and Kawamata and Tomari, 2010). It is mediated through small double-stranded RNAs (dsRNAs), of ∼21–25 nt in length, which guide the RNA-induced silencing complex (RISC) to the respective target mRNAs (Fire et al., 1998). Depending on the degree of complementarity between the so-called antisense (or guide) strand of the dsRNA and target mRNA, RNAi can bring about the cleavage of the mRNA (in the case of full or nearly full complementarity), accelerated degradation (as a consequence of deadenylation), or translational repression. Following the discovery

that the introduction of synthetic small interfering RNAs (siRNAs) into cells can trigger RNAi (Elbashir et al., 2001), this mechanism was rapidly harnessed as a tool to silence disease-associated human, and also viral genes (Davidson and McCray, 2011). Since then, siRNA-mediated silencing of viral genes has been employed this website to inhibit the replication of a variety of DNA and RNA viruses, in vitro and also in vivo ( Arbuthnot, 2010, Haasnoot et al., 2007 and Zhou and Rossi, 2011).

Adenoviruses contain a linear dsDNA genome, ∼36 kb long. The first gene to be expressed during the infection cycle is E1A. This gene has a central role, because it reprograms the cell in a way that promotes efficient virus replication (Berk, 2005, Pelka et al., 2008 and Zhao et al., 2003). Deletion of E1A renders adenoviruses replication deficient. E1A expression ultimately leads to the activation of other early and late promoters and triggers the onset of viral DNA replication. Viral DNA replication is dependent on three viral proteins: the viral DNA polymerase; the preterminal protein (pTP); and the DNA-binding protein (DBP) (de Jong et al., 2003). Besides creating Adenosine triphosphate dsDNAs for packaging into capsids (accomplished with the help of the IVa2 protein) (Zhang and Imperiale, 2003), replication of the adenoviral genome activates the expression of other viral genes, e.g., IVa2 ( Flint, 1986 and Iftode and Flint, 2004) and genes transcribed from the major late promoter (MLP) ( Shaw and Ziff, 1980). Upregulation of major late (ML) gene expression also involves the IVa2 protein ( Tribouley et al., 1994), and results in the synthesis of gene products that primarily constitute structural components of the virion or are involved in its assembly. The major component of the capsid is the hexon protein ( Russell, 2009).

Numerous conceptual models incorporate some or all of these basic

Numerous conceptual models incorporate some or all of these basic concepts (e.g., Bull, 1991, Simon and Rinaldi, 2006, Wohl, 2010 and Chin et al.,

in press): in this section, I focus on the basic concepts. Connectivity is used to describe multiple aspects of fluxes of matter, energy and organisms (Fig. 1). Hydrologic connectivity refers to the movement of water, such as down a hillslope in the surface and/or subsurface, from hillslopes into channels, or along a river network (Pringle, 2001 and Bracken and Croke, 2007). Sediment connectivity describes the movement or storage of sediment down hillslopes, into channels, along river networks, and Selleckchem CCI 779 so forth (Fryirs et al., 2007). River connectivity refers to water-mediated selleck compound fluxes within a river network (Ward, 1997). Biological connectivity describes the ability of organisms or plant propagules to disperse between suitable habitats or between isolated populations for breeding (Merriam, 1984). Landscape connectivity refers to the movement of water, sediment, or other materials between individual landforms (Brierley et al., 2006). Structural connectivity characterizes the extent

to which landscape units, which can range in scale from <1 m for bunchgrasses dispersed across exposed soil to the configuration of hillslopes and valley bottoms across thousands of meters, are physically linked to one another (Wainwright et al., 2011). Functional connectivity describes Carnitine dehydrogenase process-specific interactions between multiple structural characteristics, such as runoff and sediment moving downslope between the bunchgrasses and exposed soil patches (Wainwright et al., 2011). Any of these forms of connectivity can be described in terms of spatial extent, which partly depends on temporal variability. River connectivity, for example, fluctuates through time as discharge fluctuates, just as functional

connectivity along a hillslope fluctuates through time in response to precipitation (Wainwright et al., 2011). Connectivity can also be used to describe social components. The terms multidisciplinary, interdisciplinary, holistic, and integrative, as applied to research or management, all refer to disciplinary connectivity, or the ability to convey information originating in different scholarly disciplines, the incorporation of different disciplinary perspectives, and the recognition that critical zone processes transcend any particular scholarly discipline. Beyond the fact that the characteristics of connectivity critically influence process and form in the critical zone, the specifics of connectivity can be used to understand how past human manipulations have altered a particular landscape or ecosystem, and how future manipulations might be used to restore desired system traits. This approach is exemplified by the connectivity diagrams for rivers in Kondolf et al. (2006) (Fig. 2).

More recent work in North America has reinforced this view by sho

More recent work in North America has reinforced this view by showing how valleys can contain ‘legacy sediments’ related to particular phases and forms of agricultural change (Walter and Selleckchem Duvelisib Merritts, 2008). Similar work in North West Europe has shown that the relative reflection of climatic and human activity

depends upon several factors including geological inheritance, principally the hydrology and erodibility of bedrock, the size of the basin and the spatially varied nature of human activity (Houben, 2007). The geological impact of humans has also been proposed as a driver of societal failure (Montgomery, 2007a); however, the closer the inspection of such cases of erosion-induced collapse the more other, societal, factors are seen to have been

important if not critical (Butzer, 2012). Soil erosion has also been perceived as a problem from earliest times (Dotterweich, 2013). In this paper we review the interaction of humans and alluviation both from first principals, and spatially, present two contrasting Old World case studies and finally and discuss the implications for the identification of the Anthropocene and its status. The relationship between the natural and semi-natural (or pre-Anthropocene) climatic drivers of Earth surface erosion, and subsequent transport and human activity, selleck chemicals llc is fundamentally multiplicative as conceptualised in Eq. (1) and (2). So in the absence of humans we can, at least theoretically, determine a climatic erosion or denudation rate. equation(1) Climate⋅geology⋅vegetation(land use)=erosionClimate⋅geology⋅vegetation(land use)=erosion This implies that the erosional potential of the climate (erosivity) is multiplied by the susceptibility of the geology including

soils to erosion (erobibility). Re-writing this equation it becomes equation(2) www.selleck.co.jp/products/erlotinib.html Erosivity(R)⋅erodibility(K)⋅vegetation(landuse) (L)=erosion (E)Erosivity(R)⋅erodibility(K)⋅vegetation(landuse) (L)=erosion (E) Re-arranging this becomes equation(3) R L=EK And assuming that K is a constant we can see that the erosion rate is a result of the product of climate and vegetation cover. This relationship is contained not only in both statistical soil erosion measures such as the Revised Universal Soil Loss Equation (RUSLE), but also in more realistic models which are driven by topography, soil characteristics (such as infiltration rate) and biomass, and that can be used to estimate the effective storage capacity or runoff threshold (h) from Kirkby et al.