Salmonella enterica exposed to sub-MIC levels of streptomycin evolved high-level resistance via novel mechanisms that are different from those observed during lethal selections. During lethal selection only rpsL mutations are found, whereas at sub-MIC selection resistance is generated by several small-effect resistance mutations that combined confer high-level resistance via three different mechanisms: (i) alteration of the ribosomal RNA target (gidB mutations), (ii) reduction in aminoglycoside uptake , and (iii) induction of the aminoglycoside-modifying enzyme AadA (znuA mutations). These results demonstrate how the strength of the selective pressure influences evolutionary trajectories and that even weak selective pressures can cause evolution of high-level resistance.It has become increasingly clear that low levels of antibiotics present in many environments can select for resistant bacteria, yet the evolutionary pathways for resistance development during exposure to low amounts of antibiotics remain poorly defined. Here we show that  Salmonella enterica exposed to sub-MIC levels of streptomycin.Mutational antibiotic resistance can emerge under either high or low antibiotic levels. Here, the authors show several small-effect resistance mutations are combined to confer high-level resistance in  Thus, there are many environments such as wastewater, sludge, soil, and river water where bacteria are exposed for long periods of time to low concentrations of polluting antibiotics that are present because of anthropogenic influences7. Furthermore, low antibiotic concentrations  might be present in certain human/animal body compartments and tissues during therapeutic or growth promotion use. Previous studies showed that low levels of antibiotics (sub-MIC) can enrich for pre-existing resistant mutants in a bacterial population, indicating that certain antibiotics, disinfectants, and heavy metals could contribute to resistance evolution at concentrations that are several hundred-fold below the MIC13.Irrespective of whether antibiotics are used to treat infections in humans or animals, for growth promotion in animals, aquaculture, or plant production, a substantial fraction of these antibiotics will ultimately end up in the environment19. When susceptible bacteria are exposed to antibiotic concentrations above the MIC they will die or stop growing, and only bacteria where resistance mutations were present prior to antibiotic exposure will be able to grow. In contrast, at sub-MIC concentrations of antibiotics the bacteria can still grow while they are under selection, generating a potentially different trajectory of evolution with progressive increase in resistance through the step-wise accumulation of resistance mutations with individually smaller effects. During selection at high concentrations of streptomycin the most common resistance mutations are target alteration mutations in the gene rpsL, encoding ribosomal protein S1221, that confer high-level resistance >1024 mg L−123. Mutations in the electron transport chain that confer a small colony variant (SCV) phenotype can also cause a moderate increase in resistance (16–96 mg L−1), which is often linked to a severe reduction in growth rate26. In this work, we investigated the evolution and genetics of antibiotic resistance selected during long-term exposure to streptomycin at sub-MIC level of the drug in Salmonella enterica, an important bacterial pathogen and model system for studies of antibiotic resistance. Results show that resistance evolution below the MIC of streptomycin occurs via different mechanisms compared to lethal selection and that high-level resistance can evolve also when bacteria are exposed to low antibiotic concentrations (sub-MIC).While many studies have examined the genetics of mutational antibiotic resistance selected at high levels (>MIC) of antibiotics, less is known about the effects of long-term exposure to low levels (<MIC) of antibioticsrpsL mutants are the major type of mutants found at selection above the MIC23. We reconfirmed these results and showed that when 10 independent cultures of susceptible Salmonella enterica serovar Typhimurium LT2 strain (designated S. typhimurium throughout the text) were selected on Mueller–Hinton (MH) agar for streptomycin resistance at 200 mg L−1 of streptomycin (50× above the MIC), 10/10 mutants had mutations in rpsL  that conferred the resistance. Whole-genome sequencing of six independent isolates confirmed that mutants selected on high streptomycin concentrations on agar plates had only rpsL mutations. Furthermore, we also performed a serial passage experiment (100 generations) in liquid MH containing 200 mg L−1 streptomycin. Whole-genome sequencing of five populations showed that the only resistance conferring mutations present in them were rpsL mutations (K42R). Thus, for 11 independent selections at high streptomycin levels only rpsL mutants were selected.Many previous studies have shown that S. typhimurium were serially passaged for 900 generations in MH medium containing 1 mg L−1 of streptomycin, corresponding to 1/4 of the MIC of the susceptible wild type. The concentration of streptomycin used causes an approximately 3% reduction in competitive growth rate of the susceptible wild type and was chosen to provide a weak sub-MIC selection. This estimation was based on previous work8, where in a serial passage competition experiment 1 mg L−1 streptomycin balances the 3% fitness cost conferred by an rpsL (K42R) mutation. Serial passage occurred every 24 h by transfer of 1 µl of overnight culture (5 × 109 cells/ml) to 1 ml of culture medium, generating a bottleneck of 5 × 106 cells during transfer. After serial passage, bacteria were plated on MH agar plates with different concentrations of streptomycin  to estimate the frequency of cells with different resistance levels. The populations were heterogeneous with regard to resistance and several of the lineages contained subpopulations (approximately 0.1−1% of the cells) with high levels of resistance (MIC of streptomycin >96 mg L−1). Clones with increased resistance were single-colony isolated from six independent lineages, and these purified clones were further analyzed. The MICs of streptomycin varied between 64 mg L−1 and >1024 mg L−1 depending on the mutant. Four clones (obtained from four different lineages) with the highest streptomycin resistances (>192 mg L−1) were investigated further. In control experiments, where bacteria were serially passaged for 1000 generations in the absence of streptomycin, no streptomycin-resistant mutants were found27.To study evolution of antibiotic resistance in a susceptible bacterial population below MIC, 20 independent lineages of the streptomycin susceptible wild-type mutSLH genes28.To identify the mutations responsible for the increased resistance to streptomycin, the four clones with the highest resistance levels were whole-genome sequenced, and their sequences were compared to that of the ancestral strain to identify potential point mutations and structural rearrangements . The results showed that all four strains had mutator phenotypes, with roughly 100 different point mutations per genome . Thus, besides the es Table  had alsoS. typhimurium strain (DA6192) used as a starting ancestral strain for the sub-MIC cycling was 4 mg L−1 and the isolated resistant mutants had MIC values ranging from 192 to >1024 mg L−1 (Table −1), we reconstructed all possible combinations of the five candidate genes: gidB, cyoB, nuoG, trkH, and znuA (identified as described above), generating 32 different mutants  (where * represents a stop codon) gave a MIC of 32 mg L−1 for streptomycin, similar to previously reported values25. In contrast, the other single mutants gave no (trkH), 1.5-fold (znuA), or 2-fold  increases in resistance  genetic background increased the resistance further, where mutations in cyoB (G283D) or nuoG (D264G) individually increased the MIC to 96 mg L−1, while the combination of both gave a MIC of 256 mg L−1 (Table znuA (S19fs) (where “fs” represents a frame shift) mutation in a genetic background of gidB (Q169*), cyoB (G283D), and nuoG (D264G) increased the MIC even further to 768 mg L−1 (Table trkH (T99A) mutation increased the resistance even further to a MIC of >1024 mg L−1. A comparison of the resistance levels of the single mutants with the higher-order mutants showed that there were strong epistatic interactions between the mutations to generate the high-level resistance  and genes encoding tRNAs. The mal mutations had no effect on resistance and are likely to be media adaptation mutations32. Similarly, mutations in genes involved in flagellar biosynthesis 27 were also seen in MH media adapted Salmonella strains, whereas the role of the tRNA mutations is unknown.Other types of mutations that were found in several of the sequenced clones were mutations in genes in the maltose operon  showed wild-type levels of aadA transcript. Thus, the znuA mutations  confer increased streptomycin resistance by causing aadA upregulation and inactivation of streptomycin via adenylylation. To test whether loss of ZnuA rather than the production of a frameshifted protein is causing the observed phenotype we constructed a deletion of the znuA reading frame in a wild-type background as well as in a quadruple mutant consisting of gidB, nuoG, cyoB, and trkH  and the triple mutant  had a significant reduction in intracellular levels of tritiated dihydrostreptomycin, supporting the notion that these mutations confer increased resistance by impairing drug uptake. While the observed decrease in intracellular streptomycin is only moderate, streptomycin uptake and resistance level does not necessarily correlate in a linear and proportional way, and a small effect on uptake could conceivably have a large effect on resistance. Additionally, the reduction in streptomycin uptake is likely to be underestimated since the background signal in all strains might partly result from extracellularly bound streptomycin.Since it is known that proton motive force is needed for streptomycin uptakehow Fig.  that ones = 0.006, such that five of them together give a 3% growth advantage in the presence of the antibiotic (during the selection the used concentration of streptomycin at ¼ MIC reduced the growth rate of the susceptible wild type by 3%). Furthermore, a mutator mutation is assumed to occur with the same rate, u, as each of the five selected resistance mutations . In addition, it is assumed  that the high-level-resistant mutants reached a frequency of 1% in the evolving population after 900 generations of growth. Results show that without mutators, 1% penetration after 900 generations can be achieved only with an unrealistically high mutation rate, u = 10−3, for each individual resistance mutation. In contrast, when mutators with mutation rate v are present, the mutant with five resistance mutations can reach 1% penetration in 900 generations within a realistic parameter range where mutation rate u varies ca. 10-fold between 5 × 10−7 and 4 × 10−6 and the ratio v/u also varies 10-fold between ca. 102 and 103 (Table s = 0.03) and only 900 generations of evolution, it is possible to step-wise accumulate five resistance mutations provided mutator clones appear early during serial passage.To examine the dynamics of the step-wise enrichment of several mutations in one clone and determine under which conditions five step-wise mutations could accumulate in 900 generations under this weak selection, we modeled the selection process . In these calculations, we applied the experimentally determined population sizes and generations of growth used during serial passage. We also assumed that all selected mutations contribute independently to resistance/fitness and that each mutation has the same selection coefficient −1) for 900 generations, and found that high-level resistance (up to >1024 mg L−1) evolved in several independent lineages. By whole-genome sequencing and genetic reconstructions, we identified five causative resistance mutations of individual clones. The mutations had individually small effects, but when combined in a wild-type background they resulted in high-level resistance due to strong positive epistasis between certain mutations  found in this study exhibit an approximately 150-fold increase in mutation rate as compared to the wild type , (ii) reduced aminoglycoside uptake , and (iii) induction of the aminoglycoside modifying enzyme AadA (due to znuA mutations)  rRNA target alteration (due to ns) Fig. . With renuoG) and cytochrome o oxidase (cyoB). Aminoglycosides are cationic molecules, and they are believed to first penetrate the outer membrane through porins, and then cross the cytoplasmic membrane in a process that is dependent on electron transport through quinones and a sufficiently high membrane potential36. The mutations we observed in the respiratory chain (cyoB and nuoG) could potentially reduce electron transport and the membrane potential, and as result reduce streptomycin uptake. Similar mutations have also previously been found in streptomycin-resistant SCVs of Salmonella25, but while the SCVs have a very slow growing phenotype, the mutants selected in this study at sub-MIC levels of streptomycin have higher growth rates  lowered resistance by 1.5-fold to 100-fold . Third, these results show that the high-level resistance can result from many different mutations of small individual effect that show positive epistasis. Thus, among the five genes examined only mutations in the gidB gene conferred measurable resistance by itself, whereas when the five mutant genes were combined resistance reached very high levels. Furthermore, a majority of these mutations were in genes that are not typical resistance genes . This finding raises the question if a substantial “dark matter” of unknown resistance mutations for other classes of antibiotics exists in clinical isolates that apart from the generally easily identified bona fide resistance genes/mutations may be involved in resistance evolution and make a significant contribution to the clinical resistance phenotype56. Thus, it is conceivable that the initial selection for common mutations of small effect could act as a stepping stone for the subsequent occurrence of a rarer large effect genetic event  and thereby act as a driver of resistance evolution. Also, considering that individually the mutations in cyoB, nuoG, trkH, and znuA conferred no/minor increases in resistance, these types of atypical resistance mutations would be difficult to identify in clinical isolates using standard genetic procedures and reconstruction. That is, transfer of DNA from a resistant strain by transformation/transduction to a susceptible strain to identify potential resistance mutations is unlikely to work since the individual mutations except for gidB had minor effects on resistance. Instead, the clinical identification of these types of mutations would first require laboratory selection and reconstitution experiments (as done here) for identification, and then a subsequent comparative analysis of susceptible and resistant clinical isolates to search for their potential presence in resistant isolates. Finally, it is worthwhile noting that the potential occurrence of atypical resistance mutations in clinical isolates would make sequence-based in silico predictions of antibiotic resistance more challenging.What are the general implications of this work? First, and most importantly, our results demonstrate that very weak and constant selective pressures of antibiotics can result in the evolution of high-level resistance. Thus, an implication from these results is that there is no necessary correlation between strength of selection and level of resistance evolved, and as a consequence it is conceivable that the low antibiotic levels present in many environments could drive the evolution of clinically relevant high-level resistance. Second, our data show that mutational spectra can differ strongly between different selective strengths. Thus, at lethal selections only Salmonella enterica serovar Typhimurium LT2 (designated S. typhimurium in the text) and are listed in Tables All strains used in this study were derived from S. typhimurium mutants with decreased susceptibility to streptomycin was performed by plating 10 independent cultures (each inoculated with 103 cfu) of the wild-type strain DA6192 on MH agar containing 200 mg L−1 streptomycin (Sigma-Aldrich). Approximately 1010 cfu from each culture were plated. The mutants (one per independent culture) were randomly picked after 24 h of incubation at 37 °C and re-isolated on plates with the same concentration of streptomycin. Cultures of isolated clones were grown over night at 37 °C in MH broth without selection and frozen in −80 °C with 10% sterile DMSO. The rpsL gene in the mutants was PCR amplified with primers binding upstream and downstream of the coding region using DreamTaq DNA polymerase (Thermo Scientific). Populations of S. typhimurium were also evolved in presence of high levels of streptomycin in liquid medium by passaging 10 lineages of the wild-type strain DA6192 in MH medium with 200 mg L−1 streptomycin. The lineages were started from overnight cultures of independent colonies grown in MH without selection. The evolution experiment was initiated with an inoculum size of approximately 1010 cells. The cultures were serially passaged by 1000-fold dilutions in 1 ml batch cultures every 24 h, and after 100 generations of cycling the cultures were frozen in −80 °C with 10% sterile DMSO. Six mutants selected on solid media and five populations evolved in liquid media were whole-genome sequenced to identify possible streptomycin resistance mutations outside of rpsL  of cycling, 105 cells were plated onto LB agar containing different concentrations of streptomycin , and 2–3 resistant clones were isolated from each lineage where they represented a fraction of the population of approximately 1% , according to the manufacturer’s instructions. Quality of gDNA were examined using NanoDrop spectrophotometer  and separated by electrophoresis on 0.8% (w/v) agarose gels for visualization. The gDNA was sent to the Beijing Genomic Institute sequencing facility  for whole-genome resequencing using the Illumina HiSeq 2000 sequencing system  with 50× coverage. Briefly, sequencing libraries per gDNA were prepared according to the Solexa sequencing protocols . Illumina analysis pipeline was used for image analysis, base calling, and quality score calibration. Subsequently, raw sequence reads were quality filtered and exported as FASTQ files resulting in 12,000,000 high-quality sequence reads per gDNA isolated. For the clones and populations selected with 200 mg L−1 of streptomycin, DNA extraction was done from 1 ml of overnight cultures using Epicentre MasterPure Complete DNA and RNA Purification Kit  following the manufacturer’s instructions. Libraries to be sequenced with Miseq (2 × 300) were made using the Illumina’s Nextera XT kit, and samples were dual-indexed and pooled. The paired-end sequence reads have been deposited to the NCBI Sequence Read Archive (SRA) with accession no. SRP133288.Genomic DNA (gDNA) was extracted from 4 ml of overnight cultures of the mutants isolated after 900 generations of growth in 1 mg LS. typhimurium DA6192 in house reference genome27 using CLC Genomics Workbench version 11  with default parameters . Subsequently, InDels and structural variants were determined following default parameters , and single-nucleotide polymorphisms were determined following default parameters  = 75.0; base quality filter = yes; neighborhood radius = 5; minimum central quality = 20; minimum neighborhood quality = 15; read direction filter = yes; direction frequency (%) = 5.0; relative read direction filter = yes; significance (%) = 1.0; read position filter = no; remove pyro-error variants = no).The reads were mapped to the previously sequenced Mutated regions were PCR amplified with primers binding upstream and downstream of the mutation using DreamTaq DNA polymerase (Thermo Scientific). PCR products were purified and sent to Eurofins MWG Operon  for sequencing.57 and P22 transduction. A cat-sacB marker (GenBank accession number KM018298) was inserted near each mutation using Lambda-Red recombineering58, generating a marker-held tandem duplication. The marker and the linked mutation were then moved using P22 transduction into the recipient strains, and the transductants were re-streaked on salt-free LB agar containing 5% sucrose. Only bacteria that lose the cat-sacB marker through recombination between the two copies of the duplicated sequence can grow since expression of sacB is lethal in the presence of sucrose59. The transduced mutations were then confirmed by PCR and sequencing. Gene deletions were constructed by replacing the gene with a cat-sacB cassette, and then removing the cassette with a single-stranded DNA oligo in a second round of recombineering. Primer sequences are listed in Supplementary Table yebB (S54G) and lon (P12syn), were co-transduced from the isolated mutants, while the rest appeared during the reconstruction process.The reconstructed strains were constructed by using Duplication-Insertion Recombineering600 measurements were taken every 4 min. The calculations were based on OD600 values between 0.02 and 0.1, where growth was observed to be exponential.Growth rates were measured at 37 °C in MH broth using a Bioscreen C Analyzer . Each well was inoculated with a 1000-fold dilution of an overnight culture and measurements were made in quadruplicates. The cultures were grown for 24 h with continuous shaking, and ODMIC values were determined by Etest according to the instructions of the manufacturer . Etests were performed on MH agar plates incubated for 16–18 h at 37 °C. All MIC values presented are the median values of 2–5 Etests from biological replicates.60. From frozen stock, the strains were streaked on MH agar plates and single colonies were used to start overnight cultures in 1 ml MH medium. These cultures were diluted 103 in sterile filtered phosphate-buffered saline and 24 independent cultures of each strain were started with an initial inoculum of approximately 1000 cfu in 1 ml MH medium. The cultures were incubated in 37 °C for 20 h to stationary phase, and rifampin-resistant mutants were detected by plating a fraction of each culture on MH agar medium supplemented with 100 mg L−1 rifampicin. The volumes plated was 50 µL for non-mutator strains and 5 µL for mutator strains. The population sizes of the cultures were estimated by plating on non-selective MH agar plates. Plates were incubated for 24 h in 37 °C before counting the number of colonies per plate. The estimated mutation rates were calculated with the empirical probability generating function using the web tool bz-rates61, with correction for the plating efficiency.The mutation rates of the different strains were estimated with fluctuation assays600 = 0.4. To test the effect of excess zinc on aadA expression some cultures were supplemented with 1 mM ZnCl2. 400 µl of bacterial culture were mixed with 800 µl RNAprotect Bacteria Reagent (Qiagen) and total RNA was extracted using the RNeasy Mini Kit (Qiagen), according to manufacturer’s recommendation. Subsequently, the extracted RNA was treated with DNase Turbo DNA-free kit (Amb ion) according to manufacturer’s recommendation and subjected to gel electrophoresis to confirm the integrity of the samples. 500 ng of DNase-treated RNA were reverse transcribed using the High Capacity Reverse Transcription kit (Applied Biosystems), according to the manufacturer’s recommendation. Relative aadA and iraP transcript levels were determined using PerfeCTa SYBR Green SuperMix (Quanta Biosciences) with the Eco Real-Time PCR System (Illumina). The efficiency of each primer pair was determined in a set of six 10-fold dilutions. Expression levels of aadA and iraP were normalized to the reference genes hcaT and cysG. Primer sequences are listed in Supplementary Table Overnight cultures were diluted 1:100 in 10 ml MH broth and incubated at 37 °C to OD600 = 0.5. The cultures were supplemented with tritiated dihydrostreptomycin  to a final activity of 50 nCi ml−1. After 30 min, 2 ml were transferred to an Eppendorf tube, washed three times with PBS and finally transferred to 2 ml Optiphase HiSafe 3 (PerkinElmer) scintillation cocktail. Counts per minute were determined using a Tri-Carb 2810 TR liquid scintillation analyzer (PerkinElmer) over a duration of 1 min per sample.To determine the concentration of intracellular dihydrostreptomycin an overnight culture of the strain of interest was diluted 1:200 in MH broth and grown to ODNn(t) be the number of cells with n selected (by s each) mutations at time t, and Mn(t) be the corresponding number of mutator cells. They grow with rate (1 + ns)k. Up to five selected mutations can occur in random order each with the basic rate u. Mutators are also assumed to occur with rate u. When n selected mutations are present, the next one can occur in 5-n ways; hence with total rate u(5 − n)(1 + ns)k. The mutator cells have the basic mutation rate v.N-1 and M-1 = 0 at all times, these equations are valid for Ne is an effective population size. A non-zero initial value for N1(0) is based on the equilibrium value in a population without antibiotics where a mutation will be counter-selected by –s. The solution for the non-mutator part of the population isWe consider a deterministic growth model where back mutations and stochastic effects are neglected. Let A = 0 is for the case with N1(0) = 0 and A = 1 corresponds to the case where N1(0) = Ne5u/s. The mutators are most easily handled by numerical integration. LetThe parameter The fractions of the different variants at any time can be calculated froms = 0.006, such that five of them give a 3% growth advantage in the presence of the antibiotic. Furthermore, a mutator mutation is assumed to occur with the same rate, u, as each of the selected ones. It is straightforward to expand the calculations to include a non-zero initial presence of mutators. However, with an expected fraction on the order of 10−6, this is found to have a very small effect on the results and is not considered further. The expected initial fraction of single mutants, 5 u/s, may be on the order of 10−3, which can contribute significantly. Variants with two or more mutations are expected to be present in insignificant fractions initially. Mutators are expected to accumulate deleterious mutations over time contributing to some growth disadvantage for them. Here it is assumed that this effect is small on the time scale considered. Finally, the growth rate k = ln(2) if time, t, is considered in number of generations (doublings). Figure In the calculations, it has been assumed that all selected mutations contribute independently and that each has the same selection coefficient u = 9.5 × 10−4, or slightly lower, u = 7.4 × 10−4, if there is a fraction 5 u/s of single mutants present initially. When mutators contribute, this initial condition has little effect and has not been included in the calculations of the results shown in Fig. u ca. 10-fold between 5 × 10−7 and 4 × 10−6 and the ratio v/u also 10-fold between ca. 102 and 103. It is noteworthy that throughout these ranges, 1% penetration is reached with a mutator rate v of ca. (3.5–5) × 10−4.Without mutators, 1% penetration after 900 generations can be achieved only with a very high mutation rate, 5 = 32 genotypes, so the collection of all 32 reconstructed mutants with resistance phenotypes .We studied five different genetic loci with either the wild-type or a mutant sequence, making a total of 264. Interactions between the different mutations that are purely additive will have epistatic coefficients equal to zero, while epistatic interactions will be non-zero. The epistasis coefficients of each order are calculated so that higher-order epistasis coefficients only represent the variation that cannot be described as the sum of the lower-order effects. The mathematical theory behind the model has been thoroughly discussed by Poelwijk et al.64, so we will only give a summary of the model here.The epistatic effects were calculated in two different ways; as the global epistatic effect of each mutation , and as the epistatic effect of each mutation with the wild-type sequence as reference (corresponding to a Taylor expansion)n epistasis coefficients of all orders, y (log2(MIC)) of all the individual variants listed in binary order (Supplementary Table n × 2n matrix If we define entclass1pt{minimaε; the epistatic effects of each mutation as an average over all possible sequence variants. In this case, we can defineV is a weighting matrix to normalize for the different numbers of terms for epistasis of different orders, recursively defined asH corresponds to the Walsh–Hadamard transform64 generated by the recursive definitionWe first calculated the global, background-averaged epistasis The vector of background-averaged epistatic terms XT only includes the terms associated with the wild type, and the matrix X can be defined asTo calculate the vector of epistatic terms The calculations were performed using Python 3.6 with the NumPy library.Python scripts are available from the corresponding author upon request.SRP133288. All other relevant data are available from the corresponding author upon request.All WGS data that support the findings of this study have been deposited in the NCBI SRA and are accessible through the accession no. Supplementary InformationPeer Review File


R. Soc. open sci.4, 170633. (Published Online 23 August 2017). (doi:10.1098/rsos.170633)δ), instead of large italic delta characters (Δ). The correct text, figures and tables are presented below. The references are not included as they were presented correctly in the published paper.Throughout the abstract, §§1–4 and the figures and tables, large delta characters (Δ) were incorrectly displayed as small delta characters (δ15N and δ13C) of consumers have been used for physiological and food web studies. Previous studies have shown δ15N and δ13C values are affected by several biological and environmental factors during starvation, but the generality of the effect of starvation on δ15N and δ13C values has not yet been tested. Here, we performed a meta-analysis to evaluate the effects of starvation on δ15N and δ13C values of consumers, and the underlying factors that may explain the observed variation. The Δ15N and Δ13C values were calculated as the differences between the final δ15N and δ13C values of consumers (post-starvation) and the pre-starvation values on each experiment. Our meta-analysis showed a large variation in the Δ15N and Δ13C values of consumers . The Δ15N values of most consumers increased along the length of the starvation period and were influenced by nitrogen excretion and thermoregulation types, probably because differences in nitrogen metabolism and thermoregulation affect nitrogen processing and excretion rates. None of our predictor variables accounted for the variation in Δ13C values, which showed both increases and decreases due to fasting. Our findings suggest that starvation results in changes in consumer δ15N values which are mainly explained by the length of the fasting period and by nitrogen and energy metabolism, but the underlying mechanisms of the starvation effects on δ13C values seem to be more complex than previously thought.Nitrogen and carbon stable isotopic compositions (1.15N/14N) and carbon (13C/12C) stable isotope ratios has provided important insights into food web structure and biogeochemical processing of nitrogen (N) and carbon (C) within ecosystems [1–4]. This is because the manner in which the stable isotopic composition of N (δ15N) and C (δ13C) of a consumer reflects its diet is fairly predictable . These predictable differences in the δ15N and δ13C values between a consumer and its food resources have been called ‘trophic enrichment’ or ‘discrimination factor’ and their average values are useful to infer the trophic position of an animal and sources of energy [2]. Several meta-analyses and reviews , however, have reported a large variation in trophic enrichment across consumers. This isotope variation can impose difficulties when using average enrichment values to estimate trophic position, and hence there is still an increasing need to fully understand the underlying mechanisms affecting consumer isotope enrichment [9].Natural variation in nitrogen . These increases in δ15N values with starvation are likely due to an increased reliance on internal N resources with a large use and excretion of 14N . Similarly, increases in animal δ13C values are caused by a strong reliance on internal lipid reserves during fasting; as lipids are depleted in 13C, the bulk δ13C values of consumers become heavily enriched . Despite recent progress on the effects of starvation on consumer isotope composition, there is still little consensus about the general trends because studies have shown increases, decreases or lack of changes in both δ15N and δ13C values during fasting . Reasons for these differences are unclear, but they may be dependent on the starvation-discrimination effects of the taxonomic group or the length of starvation period considered in these studies. Therefore, the generality of starvation effects on δ15N and δ13C values of consumers is currently unknown.Starvation is a state when animals do not eat, and therefore animal physiology and behaviour change [12]. During starvation, N and C uptake is near zero, but N and C loss by excretion and respiration remains, even if at a low rate [13–15]. Further, starvation can induce shifts in protein and carbohydrate metabolism [12], increasing the δ15N and δ13C values of consumers across aquatic and terrestrial systems. We hypothesized that the effect of starvation on the isotope composition of consumers would be predictable based on the following underlying mechanisms:δ15N and δ13C values of consumers. Assuming that splanchnic organs represent up to 10% of all body protein [20], a 4% increase in whole organismal δ15N values will lead to an increase of only 0.4‰ in all body protein. Longer fasting time increases the use of body protein to obtain energy, with a preferential use of 14N, and thus the δ15N values of the remaining body protein increase. Based on this information, Martinez del Rio & Wolf [21] proposed a hypothesis that predicts that the δ15N values of consumers should increase with fasting time duration. This hypothesis has been supported by several empirical experiments ; however, to our knowledge, its generality has never been tested. In addition, animal body lipids depress bulk δ13C values because fatty acids have lower δ13C values than bulk δ13C values , and therefore, starvation may decrease the lipid reserves in the body of animals increasing 13C in consumers [25].(1) Fasting time  influences the δ15N and δ13C values of consumers.(2) Turnover rates of N and C are influenced by the metabolism of consumers. Metabolic theory of ecology (MTE) has provided the mechanistic basis to understand the fundamental role of metabolism in the ecology of organisms to ecosystems [26–28]. MTE can help predict the whole metabolic rate of an organism from its body mass and temperature [26]. Since metabolic rate relates to all biological processes [26], changes in metabolic rate would affect the isotope values of consumers, including isotopic incorporation and turnover rates potentially through the changes in the rates of excretion and use of body energy reserves. Increases in metabolic rate should be translated into decreases in δ15N and δ13C values of consumers. For example, nitrogen excretion (e.g. type of nitrogenous waste or N waste), ontogenetic stage and thermoregulation could all affect isotope trophic enrichment. Types of nitrogenous waste include three chemical compounds: ammonia, urea and uric acid. The nature of N wastes as part of N metabolism affects the δ15N values of excretion [7], thus differences in types of nitrogenous waste of animals would affect bulk δ15N values during starvation. Ontogenetic stage can affect the δ15N and δ13C values of animals; juveniles allocate energy and materials to their growth beside maintenance and storage, and this has shown to increase δ15N values and decrease δ13C values of consumers . Several lines of evidence have shown that tissue turnover rates in mammals, birds and fishes correlate with field metabolic rates, consequently affecting the δ15N and δ13C values of animals . Thermoregulation affects metabolic processes [26], and can play a large role in the turnover of N and C in the tissue of endotherms and ectotherms, thus such differences in metabolism due to thermoregulation may influence the δ15N and δ13C values of animals during starvation.(3) Other biological/ecological traits of organisms would affect the Here, we present the results of a meta-analysis testing the generality of starvation effects on the 2.2.1.δ15N and/or δ13C values of consumers under starvation and control (pre-starvation) conditions in laboratory experiments . To make sure that we included all available papers, we also reviewed the references from all relevant studies and reviews published on the starvation–stable isotopes effects to identify additional studies.We performed a systematic and broad-range search for all publications in ISI Web of Science and Google Scholar using the search terms ‘isotope AND starv* OR fasting’, ‘isotope AND experiment*’, ‘isotope AND hung*’. The search initially returned 428 and 5580 hits from ISI Web of Science and Google Scholar, respectively. From these references, 123 papers were focused on the effects of starvation on stable isotopes, but we only kept those studies providing http://www.surf.nuqe.nagoya-u.ac.jp/~nakahara/Software/PlotDigitizerX/). In total, we obtained 47 starvation experiments from our total of 19 papers . If several studies involved the same species, the result for each species was considered one estimate; therefore, some species were represented by multiple data points .Data from the papers were collected from the texts, figures and tables of the papers. To gather data from figures, we used PlotDigitizer X v. 2.0.1 software , and initial and final body mass of the consumers from each study. We collected additional information of each species in the dataset (i.e. species traits), including taxonomic group , tissue type (whole body and some body parts as multiple samples), inhabiting ecosystem types , nitrogen excretion , ontogenetic stage (juvenile or adult) and species longevity. This additional information was collected from each paper or via Internet data sources. Few studies contained the isotopic values from the different body parts; but we only considered data from the whole body as the isotope data from the species. We obtained species mean body mass to calculate metabolic rate (see below) and thermoregulation types (ectotherm or endotherm) to evaluate the effects of metabolic rates and thermoregulation on the 2.2.Δ15N or Δ13C values) of each consumer due to starvation was calculated as the differences between the final δ15N or δ13C values (post-starvation) and the initial δ15N or δ13C values (pre-starvation), respectively, as ΔX = δXpost-starvation − δXpre-starvation, where X is 15N or 13C. To account for the effects of experiment length  on species lifespan, we calculated the standardized experiment length as (experiment length (day)/species longevity (day)).The N and C isotopic discrimination  can be predicted by the following equation [26]: B = b0M0.75eE/kT–, where b0 is the normalization constant independent of body size and temperature, and M, E, k and T are body mass (grams), the activation energy, Boltzmann's constant (8.62 × 10−5 eV K−1) and absolute body temperature in kelvin, respectively. Mean body temperature of endotherms was collected from the literature and online data sources. For ectotherms, ambient air or water temperatures on the laboratory setting were used to estimate the body temperature of the individuals. We estimated the magnitude of body mass loss by the difference between the final body mass after the experiment and the initial body mass before the experiment.The metabolic rate  were independently tested by analysis of covariance (ANCOVA) using taxa group as a fixed factor, and experiment length, standardized experiment length, metabolic rate and mass loss as covariates.Differences in the Δ15N or Δ13C values of consumers, we performed generalized linear mixed models (GLMMs) [32], with a Gaussian distribution as the error distribution. In the models, we included metabolic rate, experiment length (days), standardized experiment length (days), magnitude of body mass loss from initial condition, inhabiting ecosystem types, nitrogen excretion, ontogenetic stages and thermoregulation types as fixed factors, and ‘species’ and ‘study’ were treated as random factors to account for variations among species and studies. For Δ13C values of consumers, we included lipid extraction (extracted or not) as a fixed effect for the GLMM. We ran a Shapiro–Wilk normality test on the effects of experiment length, standardized experiment length and metabolic rate after log10-transforming data. Before the GLMMs, we calculated the variance inflation factor (VIF) to check for colinearity of the factors. The maximum VIF was 2.37 for all models, indicating that colinearity among the factors would not significantly influence the results of GLMMs. For the GLMMs, we also performed the model selection of the explanatory variables through backward stepwise procedure using Akaike information criteria (AIC) and obtained the best model. All statistics and graphics were performed using R v. 3.3.1 [33], and for GLMMs, t-tests and graphics we used ‘lme4’, ‘lmerTest’ and ‘lattice’ packages for R, respectively. For all statistical tests, a value of 0.05 was used for determining statistical significance.To evaluate the effect of starvation on the 3.3.1.Δ15N and Δ13C values of consumers across all experiments ranged from –0.82 to 4.30‰ and from –1.92 to 2.62‰, respectively . More than 100 of 139 Δ15N data of consumers (79%) were positive values, indicating that the Δ15N values of consumers increased along the starvation period in most of consumers. The range of variation of Δ13C values of consumers was larger than that of Δ15N values, and the Δ13C values distributed evenly from positive to negative values. The mean Δ15N and Δ13C values of consumers pooled across all starvation experiments were 0.47 ± 0.72‰ and 0.01 ± 0.78‰ (mean ± 1 s.d.), respectively.The ectively a,b. More3.2.Δ15N values of consumers showed significant starvation time-dependent changes in all taxonomic groups, with increases in Δ15N values with increasing experiment length and standardized experiment length , but not different among taxa groups . There were no significant effects of metabolic rate on the responses of Δ15N values to starvation for any of the taxonomic groups analysed . Similarly, we did not find any significant effect of metabolic rate on the effects of fasting on the Δ13C values of consumers . Further, there were no significant differences in the slopes of Δ15N and Δ13C values and the magnitude of body mass loss .The  changes a,b. Simiarvation a,b. FurtΔ15N values of consumers were marginally different between thermoregulation types (ectotherm or endotherm) of the consumers ; these factors were selected in the best model. We did not detect any significant effect of the ontogenetic stage and ecosystem type on the Δ15N values of consumers in the full and best models , nitrogen excretion and thermoregulation influencing the Δ15N values of consumers. However, contrary to our predictions, consumer Δ15N values were not affected by metabolic rate, mass loss, ecosystem type or ontogenetic stage. Similarly, none of our predictor variables accounted for the large variation in the Δ13C values of consumers.Our meta-analysis showed large variations in the 4.1.Δ15N values by increasing δ15N values of consumers. During starvation, there is a strong dependency on an internal recycling of N, and the N reserves in the body (i.e. protein) are used to get energy [22]. During this process, 14N is primarily used and excreted [22]. Thus, the bulk δ15N values in the body of consumers become enriched in 15N . Also, fasting animals conserve protein when they fast, especially if they have adequate reserves [34–37]. Such differences in conversion rate of protein to energy may induce the variation in the Δ15N values of consumers. Our results are consistent with the hypothesis proposed by Martinez del Rio & Wolf [21], who theoretically predicted that the δ15N values of consumers should increase with the length of fasting.We found that fasting time affected the Δ15N values of consumers may indicate that the turnover rate of the N isotopes is not an important factor during starvation . This is probably because the effect of turnover rates on N isotopic discrimination was relatively smaller than that of the starvation length. In addition, several lines of evidence suggest that although the relationship between metabolic rate and isotope discrimination is mediated through protein metabolism, a decoupling between these processes is possible because protein catabolism is not the only source of energy during fasting [38].The lack of significant effects of metabolism and magnitude of body mass loss on the Δ15N values of consumers during starvation. The role of N excretion on isotopic discrimination may be due to the differences in N metabolism [7]. Different N waste products go through a series of steps from ammonia to urea or uric acid; these steps likely fractionate 14N and 15N at different rates [7]. According to Vanderklift & Ponsard [7], animals excreting urea and uric acid would show larger consumer-diet 15N enrichment than those excreting ammonia. Our results showed that ammonia-excreting animals have enriched 15N (compared with urea and uric acid) under starvation conditions. The additional series of steps after ammonia formation for the conversion and excretion of nitrogenous wastes as urea and uric acid likely explain this pattern.Nitrogen excretion and thermoregulation were important factors affecting the Δ15N values of consumers during starvation. Food limitation typically slows down metabolic rates and affects the costs of thermoregulation. During starvation, the thermoregulation costs, which are higher in endotherms than ectotherms, could deplete energy stores and may affect δ15N values due to changes in protein metabolism affecting isotope incorporation .We also found that thermoregulation type was a major factor affecting Δ13C values of consumers; however, lipid extraction had the strongest effect on the Δ13C values of consumers. Lipids in animals have lower δ13C values than bulk δ13C values and individual fatty acids have different δ13C values . Multiple studies have shown that starvation results in an enrichment in 13C due to an increase in the amount of carbon from 13C-depleted lipids metabolized to meet energetic demands , others have shown no effects of fasting on Δ13C . Our study revealed that the average bulk δ13C values treated with lipid extraction decreased after starvation rather than increasing, and thus, it may not simply result from removal of the lipids with relatively low δ13C values. These results are consistent with the later studies; however, most of the studies showing no effect of starvation over isotopic composition evaluated bulk responses in δ13C values. For example, McCue et al. [46] showed that cockroach did not change significantly in response to starvation lasting up to 168 days, although the isotopic values of the excreta became significantly depleted in 13C. Similarly, Gaye-Siessegger et al. [17] found enriched δ13C values in the lipid-free material of fishes after starvation. Different Δ13C values of consumers in response to starvation due to lipid extraction treatments may be driven by differences in species compositions between extracted and non-extracted treatments, suggesting species-specific variations in lipid content. However, further studies are needed to test the hypothesis of the different Δ13C values of consumers treated for lipid extraction and no lipid extraction.None of the hypothesized factors, including experiment length (5–243 days), significantly affected δ15N and δ13C values of animals were not tested in these experiments. We propose that further experiments need to account for the effect of these stressors on the isotope values of consumers during the starvation experiments.In this meta-analysis, we tested several factors including environmental conditions and biological traits that could explain variation in stable isotope composition of consumers under starvation. Nevertheless, some other factors not tested in this study, such as water and nutrient stresses, could also contribute to the variation of the starvation effects over stable isotopes . During starvation experiments testing for isotope changes, the animals may have been exposed to water, nutrient and other stresses imposed by the experimental conditions [47]. However, the effects of such experimental conditions on the 4.2.Δ15N and Δ13C values of consumers, which resulted from several of our predictors, including experiment length and consumer traits, we did not find straightforward mechanisms explaining the large variations in the Δ13C values of consumers. This lack of conclusive results may be due to the complex mechanisms underlying the starvation effects on the isotope values. In addition, the sample sizes in our meta-analysis were also limited, especially for invertebrates (nine taxa), which could have precluded us from finding conclusive trends. Thus, we encourage more studies to test the starvation-effect hypothesis, especially for invertebrate species.Although our study showed variations in


Sub-stoichiometric TiO2−x deposits are formed through in-situ reaction of the TiO1.9 within the high temperature plasma flame and manipulated through introduction of varying amounts of hydrogen in the plasma. Although the TiO2−x particles experience reduction within plasma, it can also re-oxidize through interaction with the surrounding ambient atmosphere, resulting in a complex interplay between process conditions and stoichiometry. The deposits predominantly contain rutile phase with presence of Magneli phases especially under significantly reducing plasma conditions. The resultant deposits show sensitivity to thermoelectric properties and under certain optimal conditions repeatedly show Seebeck coefficients reaching values of −230 μV K−1 at temperatures of 750 K while providing an electrical conductivity of 5.48 × 103 S m−1, relatively low thermal conductivity in the range of 1.5 to 2 W m−1 K−1 resulting in power factor of 2.9 μW cm−1 K−2. The resultant maximum thermoelectric figure of merit value reached 0.132 under these optimal conditions. The results point to a potential pathway for a large-scale fabrication of low-cost oxide based thermoelectric with potential applicability at moderate to high temperatures.The thermoelectric properties of sub-stoichiometric TiO ZT), where ZT = (S2σκ−1)T, where S, σ, κ, and T are the Seebeck Coefficient, electrical conductivity, thermal conductivity, and absolute temperature, respectivelyZT of conventional systems cannot be substantially increased because the three parameters are constrained due to fundamental effects. A large Seebeck coefficient needs low carrier concentration, which invariably results in low electrical conductivity while low Seebeck coefficient materials offer a high electrical conductivity. To date, the leading materials are Bi2Te3-based alloys2X 2Te3 and PbTe, suffer from thermal and chemical instabilities, high toxicity, relatively low availability and high cost. The use of rare or toxic elements in these compounds further limits their large-scale commercial application. An additional aspect that has limited the use of thermoelectric is the difficulty associated with their manufacture and ease of conversion from materials to engineering devices.Thermoelectric materials can generate electrical voltage directly from a temperature gradient and therefore, have attracted much attention as a means to harvest electrical energy from waste heatre ZT = Sσκ−1T, whxCoO2 and Ca3Co4O9 exhibit the best p-type thermoelectric performancen-type oxides demonstrating high TE performance comparable to p-type oxides have not yet been developed. Potential candidates for n-type oxide thermoelectric materials include perovskite-type SrTiO3 and CaMnO3 where Nb-doped SrTiO3 has the highest ZTn-type oxide materials by engineering their morphology, doping and stoichiometryTransition metal oxide materials have received attention as possible thermoelectric materials as they offer reasonable electrical conductivity and Seebeck coefficient, while being cost-effective, environmentally friendly, and available over a range of compositions. Oxides of cobalt, copper, manganese, molybdenum, rhodium, titanium, tungsten, vanadium and zinc offer wide range of electronic properties ranging from insulating to semiconducting and conducting2 naturally occurs in three polymorphic forms which are anatase, rutile and brookite. Anatase and rutile are both tetragonal while brookite exhibits orthorhombic structureS of bulk TiO2 is reported to be approximately −440 μV K−1, with σ on the order of 103 S m−1, while the κ is ~5.75 W m−1 K−1 κ, the ZT in pure TiO2 is low (<0.03). For titanium oxides, a relatively wide range of oxygen content is viable, ranging from TiO to TiO22−x has been explored as a potential thermoelectric materialet al. have demonstrated that TiO1.95 prepared by oxidizing and reducing from the Ti metal reveals S of −800 μV K−1 and σ of 55 S m−1 at 460 Ket al. have reported that TiO1.94 with an orthorhombic crystal structure prepared by reducing the anatase in H2, exhibits a peak S of −518 μV K−1 and σ of 1.9 × 103 S m−1 at 343 KS and σ increased with temperature resulting in power factors (PF) of ~510 μW m−1 K−2 at 343 K and ~35 μW m−1 K−2 at 460 K, respectively. Furthermore, a single crystal of rutile TiO2 reduced to TiO2−x via annealing in H2 elevated temperature at 1053 K shows exceptionally high S of up to 60000 μV K−1 at cryogenic temperatures of 10 K2 crystal lead to increase in carrier concentration resulting in the enhancement of σ. However, an excessive oxidation of TiO2 at elevated temperature lowered σ and S, resulting in low PF and ZT. Thus, obtaining a fabrication process for TiO2−x should be chosen to maximize the high PF while maintaining the low thermal conductivity.TiOet al.2 deposits behave as n-type semiconductor with reasonable conductivities (1.76 × 103 S cm−1) up to about 823 K, after which rapid re-oxidation occurs with concomitant increases in resistance. This was attributed to oxygen loss occurring during the spray process and subsequent trapping of the vacancy state through rapid solidification. Subsequently, Colmenares-Angulo et al.2 deposits allowing tunability in electrical conductivity. There have been significant efforts to use thermal spray processes to obtain high anatase content TiO2 for potential applications such as for large area photo catalysts for decomposition of hydrocarbons and nitrogen oxides2 is extensively used for variety of industrial applications particularly in the form of films and coatings including optical, electrical, photocatalytic and tribological applicationsSharma 2−x are examined through variations in-situ reduction within the process. Plasma spray offers a range of conditions through not only the melt state of the material is affected, but also its stoichiometry associated with complex reactions between the high temperatures and its surrounding environments comprising initially of an active (reducing in presence of H2 and increase Seebeck coefficient) plasma and subsequently oxygen at the location of deposition271.9) and highly reduced (TiO1.7). For brevity only cascaded plasma spray results with the TiO1.9 powder is reported as only these conditions showed promising results. Of importance is the uniform thermal fields of cascaded plasmas that reduces variabilities in both particle temperature and plasma-particle interactions3031In this study, the thermoelectric properties of plasma sprayed TiO2 industrially produced feedstock powder (measured to be TiO1.90) was used to produce plasma spray deposits. This powder is a plasma spray grade with particle sizes ranging from 8.6 to 28.9 μm. As noted in the introduction, as part of initial screening study, over 18 different iterations of spray conditions were attempted considering both conventional and cascaded plasma spray torches as well as high velocity combustion thermal spray systems. The cascaded plasma spray torches with its uniform thermal field yielded more homogeneous deposits with significant results and as such only data from this study is reported in the paper. In this case, the H2 content of the plasma was systematically varied to control the oxygen loss and thus stoichiometry and phase of the deposit. Three significant process conditions  comprising of differences in plasma spray state and H2 content of the plasma gas are discussed in detail to and were analyzed for their phase, stoichiometry, microstructure and thermoelectric properties. This integrated strategy not only allows highlighting the significant finding but also establish the process-property relationships and to identify the contributing aspects that enhance the thermoelectric properties.As noted in the methods section (end of paper), a nominally stoichiometric TiOnO2n−1 where n = 5, 6, 7, 8, 9, 10). The sprayed deposits retained the majority of the rutile phase along some of the Magneli phases  and trace amounts of anatase. Among the deposits, deposits A and B (with 0 and 3 L min−1 of H2) show Magneli phases with n = 5, 6 while deposit C (sprayed with 9 L min−1 of H2) shows Magneli phases with n = 4, 5 and 6. The increase in Magneli phases especially Ti4O7 is resultant from both the high enthalpy of the plasma at this condition and more reducing environment of the plasma.2 content in the plasma increases, not only the phase structure and crystallinity are affected, but there is deviation from stoichiometry due to the oxygen loss. Deposit A produced without any H2 in the plasma indicated a small gain in stoichiometry (TiO1.93) perhaps associated with interaction of the hot particle with oxygen in the environment at the deposition location37−1 of H2 showed significant loss of oxygen resulting in a stoichiometry of TiO1.83. Deposit B sprayed with 3 L min−1 of H2 in the plasma maintains the stoichiometry, but this again may be associated with competition of oxygen loss in the active portion of the plasma and regaining the oxygen at the deposition location due to comingling with atmospheric oxygen dampening the next changing in stoichiometry. Deposit B* sprayed with 6 L min−1 of H2  consequently leading to greater propensity of micro and macro-crack formation. Deposit B had relatively lower particle and substrate temperature resulting in reduced propensity for micro-cracking. This micro-cracking is attributed to the large quenching stresses associated with the rapid solidification of the depositing molten particles. The particles are exposed to the high thermal energy resulting in melting followed by rapid solidification which induces volume change and temperature change resulting in build-up of large tensile stress and which are relieved through cracking39−1 of H2) shows the lowest density (3.925 g cm−1) compared to those sprayed at higher temperature, and exhibits a somewhat porous microstructure. Deposit B and C show increase in density from 4.138 to 4.218 g cm−1, but also greater content of micro-cracks.In situ beam curvature measurements were conducted to further quantify these microstructural observations via extracting the deposition stress and elastic modulus of the sprayed deposits following principles described in the literature4142432 imparts higher enthalpy to the plasma and thus higher particle temperature and this should generally produce higher density deposits. The lower evolving stress and lower modulus in deposition C confirm the microstructural observations in terms of observation of substantial micro- and macro-cracking at the higher H2 conditions. These cracks also lower the deposit integrity captured by the lower modulus of deposit C.σ, Seebeck coefficient, S, and power factor, PF, for the deposits are summarized in 2−x deposits respond similar to a semiconductor following same temperature-dependent trend as reported in the literature202 in the plume with a resultant stoichiometry of TiO1.93 can observe an increase in slope at 620 to 730 K following which there is a small decrease. The first change in slope above 620 K is attributed to the thermal excitation of carriers, while the second is related to the phase transition from space group I41/amd to the P42/mnmσ is significantly lower than that of the deposit A because of the micro-cracks within its microstructure. Deposit C shows electrical conductivity similar to that of deposit A despite presence of macro-cracks in the deposit, due to the significant presence of Ti4O7 phase. This confirms the greater conductivities of the deposits associated oxygen loss with larger deviation from microstructure and phase.The electrical conductivity, −1 to −246 μV K−1, and were measured −230, −139, −100 μV K−1 at 750 K, respectively, suggesting that the deposits are n-type conductors. Deposit A comprising of larger fraction of the rutile phase exhibited the largest Seebeck coefficient. As He et al.2 resulted in an increase in the Seebeck coefficient where bulk rutile had Seebeck coefficient of −440 μV K−1. The power factor increased with increasing measurement temperature for all of the deposits and the highest power factor of 2.91 μW cm−1 K−2 at 750 K was achieved with deposit A.The Seebeck coefficients for the deposit A, B, and C were all negative, ranging from −73.5 μV K4O7) with associated increase in electrical conductivity and reduction in Seebeck coefficient as well. However, microstructural integrity can also contribute to the measure of electrical conductivity. Although the deposit A has a lower oxygen deficiency, the deposit does not have significant micro and macro-cracking. The deposit C has a relatively high conductivity due to presence of Ti4O7 phase46The difference in the Seebeck coefficient is attributed to the presence of oxygen defects which is inversely proportional to the carrier density whereas electrical conductivity depends upon combination of oxygen vacancy, microstructure and crystallinity2−x deposits ranged from 1.36 W m−1 K−1 to 2.17 W m−1 K−1 depending on the stoichiometry of the deposits and the temperature at which it was measured as shown in 17−1 K−1 at 650 K was measured from deposit A and the thermal conductivity value increased to 1.65 W m−1 K−1 at 750 K, which is relatively low compared to the literature1720244548492−x deposits. The κl was calculated by subtracting the κe from the total thermal conductivity. The electronic contribution was estimated by using the Wiedemann-Franz law−1 K−1 at 750 K in deposit A among the two other deposits and the ratio of κl to κtot are shown in 27The total thermal conductivity for the TiOet al.In this study we have only been able to report the thermal conductivity in the through-thickness direction as it is extremely difficult to reliably measure the conductivity in the in-plane direction for these thin deposits. It would be expected that the in-plane conductivity would be somewhat higher due to the lamellar nature of the sprayed material. However, the microstructure of sprayed layers is rather chaotic with successive assemblage of thousands of particles which eliminates some of the microstructural anisotropy. Chi ZT with reference from the literature is shown in 2−x454849ZT value reached maximum at 0.132 at 750 K. Lastly, condition for deposit A was repeated in six separate processing trials to ensure repeatability with separate fabrication and measurements resulting in a highly repeatable ZT ranging from 0.123 to 0.133. In addition, complete multilayer devices incorporating multiple junction incorporating both series and parallel connections with Ni as a nominal p-type material showed scalable increase in voltage and current.The calculated dimensionless figure of merit, 2−x as alternative thermoelectric materials prepared through and industrial scale, layered manufacturing process. In The results presented in this paper are significant from several points of view. First confirmation on the potential of sub-stoichiometric oxides such as TiOZT can be identified:2−x system. Both XRD and TGA results  confirms this to be case. The median temperature through this alternative measurement for deposit A is 2100 K compared to 2200 K for deposit B and 2340 K for deposit C. The absence of H2 in the plasma not only reduces the particle temperature but also suppresses the propensity for any inflight reduction, and potentially encourages interaction of the hot particle with the oxygen in ambient environment resulting in a small stoichiometry gain in the deposit A compared to deposit B and C.Consistent with contemporary knowledge, significant retention of the original rutile phase and reduced decomposition are beneficial to retain the high Seebeck coefficient in the TiO results  confirm 2 rich conditions, loss of stoichiometry and presence of Ti4O7 Magneli phase are favored which suppress the Seebeck coefficient, but concomitantly offer higher electrical conductivity.Under higher particle temperature and HZT. To understand this unusual result, one needs to look at the microstructure more critically. As shown in 4O7 Magneli phase there are sufficient charge carriers and reduces impedances to provide reasonable electrical conductivity. The nanoscale separations and interfaces that are still present likely contribute to the reduced thermal conductivity.Condition for deposit A is unusual in that it not only retains the Seebeck but also has high electrical conductivity with no significant deviation in thermal conductivity resulting in high 2 flow changed from 0 to 9 L min−1. This shift in the 2θ angle can potentially be attributed to differences in residual stresses between the coating observed earlier in the curvature based stress measurement.Higher resolution XRD data collected on deposits A and C  not onlyLastly, curvature based evolving stress and modulus data reported are consistent with the microstructural observations indicating that deposit A shows excellent integrity and bonding leading to high electrical conductivity.As noted, earlier although many iterations of process parameters and initial stoichiometry were examined as part of the larger study and among them, only condition for deposit A showed this relatively high thermoelectric figure of merit. By comparing condition for deposit A with B and C presented in this paper, key attributes that allow for high p-n junctions, sequencing the layers and junctions to provide series and parallel connections to add voltage while retaining current carrying capability enabling useful energy harvesting systems. As more promising materials are identified, the fabrication concepts can be concurrently contemplated for device engineering.In summary, the results and integrated analysis presented in this paper suggest potential for considering plasma spray as both a synthesis and manufacturing tool for thermoelectric oxides. Ongoing activities are focused on building thermoelectric waste heat harvesting devices that integrate 2−x having oxygen defects and a combination of rutile and Magneli phases were investigated. It was observed that use of H2 in the plasma forming gas allowed tunability in TiO2−x stoichiometry and phase content. Deposits produced under high H2 conditions tended to comprise of rutile phase and reduced Magneli phases with significant oxygen deficiency, while deposits produced without any H2 in the plasma flame resulted in predominantly rutile phase with stoichiometry closer to TiO2. The introduction of oxygen deficiencies with resultant formation of Ti4O7 increases electrical conductivity σ, but diminishes S. The deposits have significantly reduced through-thickness thermal conductivities due to the presence of large number of pores and interfaces within the defected microstructure of the plasma sprayed deposits. The combined attributes of optimized phase, stoichiometry and microstructure resulted in a TiO2−x material with reasonable ZT value reaching 0.132 at 750 K for this class of transition metal oxides.The thermoelectric properties of cascaded plasma spray synthesized TiOA key benefit of the plasma spray approach is the ability to directly apply these functional oxide deposits onto thermostructural components in either blanket or patterned (either through masking or via direct writing) with the ability to integrate insulator and conductors to produce complete devices. An added embodiment is the ability to accomplish this at relatively low processing temperatures (<473 K) allowing for multilayer assembly to enable direct fabrication of thermoelectric systems on both planar and conformal waste heat systems. The results point to a pathway for further exploration of transition metal oxide based thermoelectric materials through a flexible and scalable manufacturing process.2−x deposits were fabricated by atmospheric plasma spray process with torch hardware , varying the hydrogen gas ratio. As noted in the paper, although a much larger range of plasma spray operating conditions including use of both conventional and cascaded plasma sprays were contemplated significant results were only observed for the cascaded plasma attributed to its more uniform plasma flow field. The details of spray conditions are provided in 1.9 . These materials are used for wear applications and as such stoichiometry is not carefully monitored. The deposits for Seebeck and electrical conductivity measurements were deposited on YSZ  coated stainless steel substrate (as a dielectric) through bar-shaped masks . Thermal conductivity deposits were fabricated simultaneously on 12.7 mm dia. graphite rods, which allowed for deposit-substrate delamination post-deposition. Average thickness of deposits was 250 μm for Seebeck and electrical conductivity measurements, and 0.932, 1.400, and 0.854 mm for thermal conductivity measurement, respectively. All the deposits were prepared on preheated substrates with raster speed and stand-off distance of the plasma torch set to 1000 mm s−1 and 100 mm, respectively. In-flight particles’ temperature and velocity were monitored by using particle diagnostic sensor (See In-situ coating property (ICP) sensor, which allows simultaneous measurement of substrate curvature and substrate temperatureSub-stoichiometric TiOLte.)See . Depositα radiation (Ni β filter in secondary path). Since linear 1D detector was used, beam knife was placed above the samples in order to minimize the detection of air scattering. Additional measurement using High resolution XRD  was performed, with a Cu-Kα radiation source at 40 kV and 44 mA between 2 θ values of 10° and 80°. Thermogravimetric analysis was performed in order to measure stoichiometry of powder, and the deposits using a thermal balance  while heating TiO2−x deposits up to 1073 K at 10 K min−1, holding it for 30 minutes in air to fully oxidize. The weight of the TiO2−x deposits was approximately 30 mg.Cross-section microstructure of as-sprayed deposits and surface microstructure of splats and fractured deposits were investigated by field-emission scanning electron microscopy . X-ray diffraction of the feedstock, and deposits was carried out on X-ray diffractometer  in vertical Bragg-Brentano geometry (2.5° Soller slits in both primary and secondary beam and 0.5° divergence slit in primary path) with filtered CuK2−x deposits were measured using digital multimeter (Keithley 2700). Seebeck Coefficient was calculated using the measured voltage generated from temperature gradient through each end of TiO2−x deposits, heating one end of the substrate with propane gas torch while cooling the other end with cold air gun (Vortex). Pt/chromel wire was measured as a reference for Seebeck coefficient measurement shown in et al.TM SYSTEM X-PLATFORMTM, Anter Corporation) from room temperature to 750 K. Of those measurements, density was measured using the Archimedes method. Electrical conductivity and Seebeck coefficient were measured in-plane direction and thermal conductivity was measured in through-thickness direction. This is because it is very difficult to accurately measure in-plane thermal conductivity of sprayed materials as they have a very small dimension in the thickness axis. Our past workVoltage and electrical resistivity of the TiOHow to cite this article: Lee, H. et al. Thermoelectric properties of in-situ plasma spray synthesized sub-stoichiometry TiO2−x. Sci. Rep.6, 36581; doi: 10.1038/srep36581 (2016).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Mice bearing either subcutaneous or orthotopic PC3 LN3 prostate tumors were imaged at 7 T, using a multi-gradient echo sequence to quantify R2∗, before and during carbogen (95% O2/5% CO2) breathing, and subsequently following intravenous administration of USPIO particles. Carbogen and USPIO-induced changes in R2∗ were used to inform on hemodynamic vasculature and fractional blood volume (%), respectively. The CUSPIO imaging data were also segmented to identify and assess five categories of R2∗ response. Small and large subcutaneous and orthotopic tumor cohorts all exhibited significantly (P < 0.05) different median baseline R2∗, ΔR2∗carbogen, and fractional blood volume. CUSPIO imaging showed that small subcutaneous tumors predominantly exhibited a negative ΔR2∗carbogen followed by a positive ΔR2∗USPIO, consistent with a well perfused tumor vasculature. Large subcutaneous tumors exhibited a small positive ΔR2∗carbogen and relatively low fractional blood volume, suggesting less functional vasculature. Orthotopic tumors revealed a large, positive ΔR2∗carbogen, consistent with vascular steal, and which may indicate that vascular function is more dependent on site of implantation than tumor size. Regions exhibiting significant ΔR2∗carbogen, but no significant ΔR2∗USPIO, suggesting transient vascular shutdown over the experimental timecourse, were apparent in all 3 cohorts. CUSPIO imaging can inform on efficient drug delivery via functional vasculature in vivo, and on appropriate tumor model selection for pre-clinical therapy trialsThe aim of this study was to use the combined carbogen-ultrasmall superparamagnetic iron oxide (CUSPIO) magnetic resonance imaging (MRI) method, which uses spatial correlations in independent susceptibility imaging biomarkers, to investigate and compare the impact of tumor size and anatomical site on vascular structure and function  The resulting change in R2∗, ΔR2∗carbogen, reflects changes in oxygenation and the hemodynamic response in functional vasculature. Intravenous injection of USPIO particles increases R2∗ in tissue surrounding blood vessels that are perfused with blood plasma at the time of injection. With a known blood concentration of USPIO particles, ΔR2∗USPIO can be used to calculate fractional blood volume. Given the difference in size of erythrocytes and USPIO particles, ,1 the volume of distribution influenced by hyperoxia and USPIO is likely to differ, with small vessels offering preferential access to USPIO particles. By combining, into a single imaging session, sequential measurements of ΔR2∗ induced by carbogen breathing and USPIO particles, greater information about vascular function and structure can be deduced than could be achieved using each technique individually.2 The CUSPIO protocol achieves this by implementing a novel segmentation scheme, in which ΔR2∗ estimates are compared and assigned to 1 of 5 response categories. Our previous work has shown that these categories provide distinct information about vascular function, the spatial distribution of plasma perfusion and transient hypoxia, and that these biomarkers can inform on tumor response to anti-angiogenic therapy.3The combined carbogen ultrasmall superparamagnetic iron oxide (USPIO) imaging protocol (CUSPIO) combines two magnetic resonance imaging (MRI) techniques, intrinsic susceptibility contrast MRI and contrast-enhanced susceptibility MRI with USPIO particles. The transverse relaxation rate  models, in which tumors are driven by the expression of the target of interest and arise spontaneously within the native tissue of origin, are being increasingly exploited.8 These models more faithfully emulate human tumor growth, tumor-host stromal interactions and vasculature, metastatic potential, and therapeutic response in vivo. The systematic use of orthotopic and GEM models in pre-clinical cancer research demands noninvasive anatomical and functional imaging methods for the longitudinal monitoring of tumor progression and response, which can also accurately inform on key hallmarks of cancer, such as angiogenesis. We have previously demonstrated the use of several MRI strategies with which to assess, and reveal differences, in the vascular phenotype and response of ectopic, orthotopic, and GEM models.15The clinical relevance of rodent models in both fundamental cancer research and drug development has been an ongoing debate for many years. The inadequacies and limitations of ectopic (subcutaneous) models are frequently highlighted, but there has also been a historical reluctance to adopt more complex models in cancer research.The purpose of this study was to exploit CUSPIO imaging to investigate vascular function and structure in small and large subcutaneous, and orthotopically propagated PC3 LN3 prostate xenografts, and compare the differences in these characteristics between the different models.16 were cultured in T75 cm3 flasks  in Dubbecco's Modified Eagles Medium  supplemented with 10% (v/v) fetal bovine serum, 5 mM L-glutamine,100 IU/mL penicillin, and 100 μg/mL streptomycin . Cells were maintained at 37°C in a humidified 5% CO2 atmosphere.Human PC3 LN3 prostate tumor cells, originally generated in-house from lymph node metastases arising in nude mice bearing orthotopic PC3 tumors,17 and the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines.18 Male NCr nude mice under isoflurane anesthesia were injected with 1 × 106 PC3 LN3 cells subcutaneously on the right flank, or 1 × 105 cells into the ventral prostate gland.9 The subcutaneously inoculated animals were randomized into 2 groups of 6 mice, to be imaged as small and large tumors. Animals from group 1 were imaged 1 week later, and animals from group 2 were imaged 3 weeks later. Orthotopically inoculated animals were monitored by palpation and imaged after 3 weeks (n = 5). No adverse effects were observed in any of the mice, and none excluded from the study.All experiments were performed in accordance with the local ethical review panel, the UK Home Office Animals (Scientific Procedures) Act 1986, the United Kingdom National Cancer Research Institute guidelines for animal welfare in cancer research,2/5% CO2) at a flow rate of 1 L/min. During MRI, all mice were restrained using dental paste in order to limit respiratory motion artefacts.19 A warm air blower was used to maintain the animal's core temperature at 37°C within the magnet bore.Tumor-bearing mice were anesthetised by an intraperitoneal injection of 10 mL/kg of fentanyl citrate (0.315 mg/mL) along with fluanisone (10 mg/ml) , midazolam (5 mg/mL) , and sterile water (1 : 1 : 2). A lateral tail vein was cannulated with a 27G butterfly catheter  for remote administration of USPIO particles. A nosepiece was positioned for delivery of air or carbogen  were first acquired from contiguous 1 mm thick axial slices for tumor localization and volume determination. Next, 2 sets of multigradient echo (MGE) images  were acquired from 3 axial 1 mm slices through the tumor center while the mouse breathed air. The gas supply was then switched to carbogen, and following a 10-minute transition period, a further identical MGE image set was acquired. The gas supply was then reverted back to air and, after another 10-minute transition period, another MGE image set was acquired. A final MGE image set was then acquired 1 minute after intravenous injection of 150 μmol/kg USPIO particles .MRI was performed on a 7-T horizontal bore microimaging system  using a 3 cm birdcage coil. T2-weighted images for each tumor-containing slice, using in-house software . MGE data were analyzed using a Bayesian maximum a posteriori approach.20 This modeled the MGE signal magnitude as a single exponential decay and took into account its Rician distribution. Furthermore, it enabled estimates of ΔR2∗ uncertainty to be defined and the probability that a given ΔR2∗ estimate was significantly greater than or less than zero. Thus, the number of voxels within the tumor ROI with an uncertainty of less than 0.05 ms−1 and with a significant (P < 0.05) change in R2∗ induced by carbogen (ΔR2∗carbogen) and/or USPIO particles (ΔR2∗USPIO) were calculated. Fractional blood volume  was quantified from the ΔR2∗USPIO data as previously described.21 The increase in blood susceptibility caused by the USPIO particles was extrapolated from a previously published value for a dose of 200 μmol/kg.22Tumor volumes were determined using segmentation from regions of interest (ROIs) drawn on T2∗carbogen, the blue channel to voxels with negative ΔR2∗carbogen, and the green channel to positive ΔR2∗USPIO. It was assumed that ΔR2∗USPIO could only be positive, and negative values were assumed to be a result of uncertainty in R2∗ estimates. Regions with both negative ΔR2∗carbogen and positive ΔR2∗USPIO therefore appeared cyan (blue + green), and regions with both positive ΔR2∗carbogen and positive ΔR2∗USPIO appeared yellow (red + green).RGB maps were then generated, with the red channel designated to voxels with a positive ΔR23 Mice were killed 1 minute after injection of Hoechst 33342 and tumors rapidly excised and snap frozen over liquid nitrogen. Contiguous 10 μm frozen sections at three levels through each tumor were cut on a cryotome in approximately the same plane as was imaged with MRI. Sections were fixed in ice-cold acetone for 10 minutes before being mounted in phosphate-buffered saline. Hoechst 33342 fluorescence signals from whole tumor sections were then recorded at 365 nm using a motorized scanning stage  attached to a BX51 microscope  driven by CellP . The area of Hoechst 33342 fluorescence as a percentage of the total tumor area mean Hoechst perfused area (mHPA)] was then calculated using CellP.Following MRI, Hoechst 33342  was administered intravenously via a lateral tail vein. Hoechst 33342 is a nuclear dye that stains the cells lining blood vessels that are perfused at the time of injection, affording a measure of functional tumor vasculature.t test assuming 2 samples of the population with equal variance. A P value of < 0.05 was considered significant.All data are reported as mean of median values ± 1 standard error of the mean unless otherwise stated. Statistical significance was determined using Student's 2-tailed unpaired 3, which was significantly smaller than the large subcutaneous tumor cohort . The orthotopically propagated PC3 LN3 xenografts had a mean volume of 377 ± 134 mm3.The small tumor cohort of subcutaneous PC3 LN3 xenografts had a mean volume of 44 ± 9 mm2∗, and ΔR2∗carbogen , and regions where there was no significant ΔR2∗carbogen followed by a significant ΔR2∗USPIO (green voxels). The CUSPIO response categories in PC3 LN3 prostate tumors were separated spatially into regions that were larger than a single voxel (0.23 × 0.23 mm2), but small compared with the entire tumor ROI.2The predicted predominant response of tumor tissue to carbogen breathing and USPIO particles is a negative ΔR2∗ response category was calculated, and is summarized in Table To quantify the spatial information displayed in the CUSPIO RGB maps, the percentage of tumor ROI voxels that exhibited each RComposite fluorescence images of Hoechst 33342 uptake from small and large subcutaneous tumors and an orthotopic PC3 LN3 xenograft are shown in Fig. in vivo. PC3 LN3 prostate tumors were propagated subcutaneously and orthotopically, and the subcutaneous tumors were separated into small and large tumor cohorts. All tumors were then imaged using the CUSPIO imaging protocol. It was hypothesized that tumor size and site of implantation would affect the resulting vascular phenotype.In this study, the CUSPIO imaging protocol was used to investigate how tumor size and site of implantation affect the vascular characteristics and function of PC3 LN3 prostate tumors aO2, and therefore in equilibrium with tissue pO2, measurements of baseline R2∗ have been exploited as a sensitive biomarker of hypoxia.24 The significantly faster baseline R2∗ determined in the small subcutaneous PC3 LN3 xenografts suggests that tumors from this cohort were the most hypoxic. In order to progress, such small tumors are likely to initiate a strong hypoxia-driven vasculogenic drive, with associated increase expression of vascular endothelial growth factor (VEGF), resulting in immature, unstable vasculature transporting predominantly deoxygenated blood, resulting in a relatively faster R2∗. Magnetic field inhomogeneties arising from susceptibility artifacts caused by air-tissue interfaces, which may be more prevalent when imaging such small tumors, would also impact on the R2∗ measurement, though the use of dental paste to immobilize the tumors should limit this.19As the oxygenation of hemoglobin is proportional to the arterial blood p2∗carbogen was significantly different across all three tumor cohorts, suggesting that both the size and site of implantation of the PC3 LN3 tumors had an effect on their incipient hemodynamic vasculature.25 Differences in functional vasculature between subcutaneous and orthotopic tumors reflect a difference in the interaction of tumor vessels with the host vasculature, or differential pericyte/endothelial cell recruitment by different host tissues.27 Tumor-stromal interactions are powerful determinants of vascular growth factor expression, and therefore the resulting vasculature.28 Furthermore, growth factor receptor expression differs in endothelial cells from different tissues, which may be reflected in these differences in MRI vascular biomarkers.29 Differences between small and large subcutaneous xenografts is likely a consequence of more mature vasculature, higher interstitial pressure, and increasing lack of vascular hierarchy associated with larger tumours.30 The small subcutaneous tumor cohort exhibited a negative ΔR2∗carbogen, indicative of a functional, erythrocyte perfused vascular network.11 Combined with their significantly faster baseline R2∗, these data suggest that the small PC3 LN3 tumors were hypoxic at baseline, and become less hypoxic during carbogen breathing.31 The positive ΔR2∗carbogen measured in the large subcutaneous and orthotopic tumors can be explained by the vascular steal effect, that is, the distribution of blood away from the tumor vascular bed by the systemic vasculature.33 From this, it can be inferred that both these cohorts have less hemodynamic vasculature than the small subcutaneous tumors.Tumor ΔR30 Vasculogenesis in small tumors provides a nutritive blood supply, but which may not meet the evolving metabolic adaptation/demands of the cancer cells, hence their markedly elevated hypoxia. As tumors progress, their rapid growth outpaces angiogenesis, resulting in a more poorly organized vascular hierarchy that, in conjunction with raised interstitial fluid pressure, causes plasma perfusion as a percentage of tumor volume to decrease.27 Hoechst 33342 uptake showed close agreement with the MRI-derived fractional blood volume results from the same subcutaneous tumors, providing further validation of this imaging biomarker.35 Orthotopic PC3 LN3 tumors exhibited a significantly larger blood volume than the large subcutaneous tumors, reflecting differences in vascular phenotype associated with the different tumor microenvironments, as there was no significant difference in the mean volumes of these tumor cohorts. This is consistent with the elevated vascular volume, measured by MRI, in orthotopic, compared with subcutaneous, PC3 tumors.36 These differences may arise from tumor cell interactions with stromal cells from the prostate compared with dermal site, or because of differential angiogenic growth factor receptor expression in the different tissues.The significantly greater fractional blood volume in the small subcutaneous PC3 LN3 tumors is consistent with previous work showing that small tumors are often better perfused.2∗ changed significantly (+ or -) during carbogen breathing, but did not change after administration of USPIO particles (blue and red voxels), as previously observed in other tumor models.2 This suggests that these regions have experienced vascular shutdown in the 15-minute period between carbogen inhalation and injection of USPIO particles. RGB maps from all tumors also showed a heterogeneous spatial distribution of ΔR2∗USPIO (green) voxels, which is indicative of heterogeneous plasma perfusion. Green CUSPIO voxels have been previously shown to have a close spatial association with Hoechst 33342 uptake.2 RGB maps from the orthotopic PC3 LN3 tumors showed localized regions of green and cyan voxels, compared with more heterogeneous distribution seen in the subcutaneous tumors. This may reflect a difference in vascular supply to the tumors, resulting from the different microenvironments.9The CUSPIO RGB maps from all 3 PC3 LN3 tumor cohorts revealed regions wherein R2∗ response categories between the small and large subcutaneous tumors, suggesting a similar incidence of transient hypoxia and levels of plasma perfusion in these 2 cohorts. Tumor size may therefore only weakly influence the incidence of intermittent blood flow and plasma perfusion, compared with tumor-stroma interactions and the effect of site of implantation. The similarity in the yellow and cyan CUSPIO response categories in the small and large tumors suggests that these two models had similarly patent, functional vasculature.There was no significant difference in any of the CUSPIO ΔR2∗carbogen measured in the orthotopic tumors, compared with the negative mean ΔR2∗carbogen measured in the small subcutaneous cohort. Numerous factors are important determinants of the vascular phenotype that develops in tumors, including VEGF expression, endothelial cell VEGF receptor expression, and platelet-derived growth factor receptor (PDGFR-β) expression, and are all influenced by tumor-stroma interactions. The differences in CUSPIO response categories measured between small subcutaneous and orthotopic PC3 LN3 tumors may therefore reflect differences in pericyte coverage and vascular density in these two models, and which may also be influenced by the vascular bed at each anatomical site.38Quantitation of the CUSPIO categories revealed that orthotopic PC3 LN3 tumors exhibited a significantly greater percentage of red and yellow voxels, and a significantly smaller number of blue voxels, than the small subcutaneous cohort. The lower number of blue voxels suggests a lower incidence of transient hypoxia in the orthotopic tumors. The greater number of yellow voxels also suggests that the orthotopic tumors experienced a lower incidence of intermittent blood flow, as more of the tumor remained perfused throughout the whole CUSPIO imaging session than the small subcutaneous tumors. The greater percentage of red voxels, combined with the higher incidence of yellow voxels, in the orthotopic tumors, may indicate a greater incidence of vascular steal. This inference aligns with the positive mean ΔRin vivo provided by techniques such as CUSPIO imaging is imperative for appropriate tumor model selection when designing pre-clinical therapy trials. Carbogen inhalation has been used both clinically and pre-clinically to increase drug uptake in solid tumors through hypercapnia-induced vasodilation.43 The potential to use CUSPIO imaging to noninvasively assess the degree and heterogeneity of vascular functionality, tumor oxygenation, and vascular shutdown will impact on both chemotherapy and radiotherapy, which generally exhibit higher efficacy in well oxygenated tumor tissue.44 Differences in vascular architecture and function arising in subcutaneous and orthotopic models also has implications for the sensitivity of a model in which to evaluate novel anti-angiogenic drugs, and targeted agents whose mode of action is predicted to elicit an anti-angiogenic effect.3Efficient tumor plasma perfusion is a key determinant of drug delivery, so a clear understanding on the extent, patency, and spatial distribution of functional tumor vasculature 2∗carbogen, fractional blood volume, and CUSPIO response categories were determined between small and large subcutaneous, and orthotopically propagated PC3 LN3 prostate cancer xenografts.In conclusion, the vascular structure and function of tumor xenografts, derived from a PC3 LN3 human prostate cell line, was shown to be dependent on both the site of implantation and relative tumor size using the CUSPIO imaging protocol. Significant differences in ΔR