Nonlinear dynamics of river runoff elucidated by horizontal visibility graphs

Horizontal Visibility Graphs (HVGs) are a recently developed method to construct networks from time series. The values of the time series are considered as the nodes of the network and are linked to each other if there is no larger value between them, such as they can "see" each other. The network properties reflect the nonlinear dynamics of the time series. For some classes of stochastic processes and for periodic time series, analytical results can be obtained for network-derived quantities such as the degree distribution, the local clustering coefficient distribution, the mean path length, and others. HVGs have the potential to discern between deterministic-chaotic and correlated-stochastic time series. Here, we investigate the sensitivity of the HVG methodology to properties and pre-processing of real-world data, i.e., time series length, the presence of ties, and deseasonalization, using a set of around 150 runoff time series from managed rivers at daily resolution from Brazil with an average length of 65 years. We show that an application of HVGs on real-world time series requires a careful consideration of data pre-processing steps and analysis methodology before robust results and interpretations can be obtained. For example, one recent analysis of the degree distribution of runoff records reported pronounced sub-exponential "long-tailed" behavior of North American rivers, whereas another study of South American rivers showed hyper-exponential "short-tailed" behavior resembling correlated noise. We demonstrate, using the dataset of Brazilian rivers, that these apparently contradictory results can be reconciled by minor differences in data-preprocessing (here: small differences in subtracting the seasonal cycle). Hence, data-preprocessing that is conventional in hydrology ("deseasonalization") changes long-term correlations and the overall runoff dynamics substantially, and we present empirical consequences and extensive simulations to investigate these issues from a HVG methodological perspective. After carefully accounting for these methodological aspects, the HVG analysis reveals that the river runoff dataset shows indeed complex behavior that appears to stem from a superposition of short-term correlated noise and "long-tailed behaviour," i.e., highly connected nodes. Moreover, the construction of a dam along a river tends to increase short-term correlations in runoff series. In summary, the present study illustrates the (often substantial) effects of methodological and data-preprocessing choices for the interpretation of river runoff dynamics in the HVG framework and its general applicability for real-world time series.

Heterogeneous local order in self-assembled nanoparticle films revealed by X-ray cross-correlations

We report on the self-assembly of gold nanoparticles coated with a soft poly(ethylene glycol) shell studied by X-ray cross-correlation analysis. Depending on the initial concentration of gold nanoparticles used, structurally heterogeneous films were formed. The films feature hot spots of dominating four- and sixfold local order with patch sizes of a few micrometres, containing 104-105 particles. The amplitude of the order parameters suggested that a minimum sample amount was necessary to form well ordered local structures. Furthermore, the increasing variation in order parameters with sample thickness demonstrated a high degree of structural heterogeneity. This wealth of information cannot be obtained by the conventional microscopy techniques that are commonly used to study nanocrystal superstructures, as illustrated by complementary scanning electron microscopy measurements.

Kinetics of Pulmonary Leukocyte Sequestration in Man during Hemodialysis with Different Membrane-Types

Although it has been suggested that pulmonary sequestration of leukocytes could account for membrane-dependent white blood cell depletion in HD, direct evidence in patients is still lacking. Therefore a study was initiated to test whether and how leukocytes distribute in the lung circulation during HD with different membranes. Thirteen patients suffering from chronic renal failure underwent lung scintigraphy during HD with cuprophane (n = 3), hemophane (n = 8) and polysulfone (n = 2) lowflux capillary dialyzers. Isolated autologous leukocytes were labelled with 99m-Technetium and reinfused before starting HD. Distribution of leukocyte related activity was registered by lung scintigraphy. In comparison to normal lung scintigraphy performed without HD, an impressive redistribution peak was demonstrated 10-20 min after the start of HD with cuprophane and also to a lesser extent with hemophane. When HD was performed with polysulfone the decrease in activity was delayed but no real redistribution was obtained.

In accordance with other phenomena, such as peripheral leukopenia and changes in granulocyte oxidative metabolism, pulmonary sequestration of leukocytes takes place in man in the initial phase of HD and appears to be strongly dependent on the type of membrane. (Int J Artif Organs 1990; 13: 729-36)

On-line Monitoring of the Intravascular Volume during Haemodialysis by Continuous Refractometry

The control of intravascular volume (IVV) by continuous on-line measurement of protein concentration would optimise the patients’ specific rate of ultrafiltration.

To prove the accuracy of a refractometric device, plasma was continuously drawn by haemofiltration during 10 haemodialysis treatments of male patients. Refractometry reflects highly significant changes in the concentrations of filtrate proteins (r = 0.862, p < 0.001) and blood proteins (rtotal = 0.593, ptotal < 0.001). In vitro, the refractometric device detected a change of protein concentration of 0.041 g/L through a refraction increase of 0.1 mV. The power of discrimination was 0.067 % of IVV. However, in vivo, the accuracy of IVV refractometric monitoring is reduced by interference factors such as sodium (0.141 mV/mmol/L), glucose (0.034 mV/mg/dl) and triglycerides (–0.040 mV/mg/dl). Adjustment of the refraction data using sodium and glucose electrodes and plasma filters with a cutoff below the size of chylomicrons is recommended.

Continuous Ionography (CIG) in Haemodialysis by Ion-Selective Carrier Membrane Electrodes (ISCME) with Solid Cement Contact for Flow-Through Measurement

Ion balance is of particular interest for patients maintained on RDT because of the importance of controlling ion movement and ion removal during haemodialysis. Continuous ionography (CIG) was therefore tested for electrolyte monitoring in extracorporeal haemodialysis in vitro and in vivo. The accuracy and stability of the electrodes were examined and various concentrations of potassium in blood, ultrafiltrate and dialysate were evaluated. Ion selective carrier membrane electrodes (ISCME) appeared to be suitable for continuous and simultaneous measurement of ions in blood and dialysis fluid. CIG monitoring of ion movement and ion removal could be the basis for adjusting and computer-managing ion elimination during extracorporeal haemodialysis.

Size-Dependent Phase Transfer Functionalization of Gold Nanoparticles To Promote Well-Ordered Self-Assembly

We present a route for the functionalization of gold nanoparticles (AuNP) based on phase transfer functionalization in order to optimize the stability and the potential for self-assembly. Depending on the desired size, different ligand exchanges have to be employed: The maximum AuNP size that can be stabilized without concentration loss is 46 nm for polystyrene-based ligands with 5 and 10 kDa. Small particles <12 nm are better stabilized by smaller ligands. We are able to demonstrate that well-ordered close-packed monolayers of 28 nm AuNP covering at least 400 μm² are possible with a potential for much larger areas. Such monolayers are of great interest for various fundamental experiments in the context of plasmonics and SERS and for sensor applications.

Excitation-Dependence of Plasmon-Induced Hot Electrons in Gold Nanoparticles

The decay of a plasmon leads to a hot electron distribution in metallic nanoparticles. Depending on the processes involved in the excitation, different distributions are obtained, which thermalize differently. We experimentally investigate excitation-wavelength and size-dependences on the generation and thermalization of the hot-electrons. We can confirm the absence of size-dependences, and we clearly observe two regimes with significantly different relaxation dynamics depending on the photon energy. The hot electron generation is more efficient when exciting with light that enables interband transitions.

Impact of the Crosslinker’s Molecular Structure on the Aggregation of Gold Nanoparticles

We studied the aggregation of AuNP induced by small aromatic molecules under different conditions. In water, the aggregation was found to be difficult to control. Phase transfer of the particles into toluene by using oleylamine as a ligand allows for a more controlled and reliable synthesis. Using nonane-1,9-dithiol as a control, our experiments demonstrate that the molecular structure of the linker has a decisive influence on the aggregation. Aromatic dithiols yielded spherical aggregates in the range of 100 nm, whereas the aliphatic linker produced large aggregates in the µm range. The length of the aromatic linker (2 vs. 3 phenylene units) strongly affected aggregation kinetics and the structure of the produced aggregates. With UV/Vis and DLS based experiments it was possible to distinguish the process of ligand layer formation and aggregation. Our results will help to develop syntheses of defined spherical aggregates and possibly more complex structures.

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.

Metal-Semiconductor Nanoparticle Hybrids Formed by Self-Organization: A Platform to Address Exciton-Plasmon Coupling

Hybrid nanosystems composed of excitonic and plasmonic constituents can have different properties than the sum of of the two constituents, due to the exciton-plasmon interaction. Here, we report on a flexible model system based on colloidal nanoparticles that can form hybrid combinations by self-organization. The system allows us to tune the interparticle distance and to combine nanoparticles of different sizes and thus enables a systematic investigation of the exciton-plasmon coupling by a combination of optical spectroscopy and quantum-optical theory. We experimentally observe a strong influence of the energy difference between exciton and plasmon, as well as an interplay of nanoparticle size and distance on the coupling. We develop a full quantum theory for the luminescence dynamics and discuss the experimental results in terms of the Purcell effect. As the theory describes excitation as well as coherent and incoherent emission, we also consider possible quantum optical effects. We find a good agreement of the observed and the calculated luminescence dynamics induced by the Purcell effect. This also suggests that the self-organized hybrid system can be used as platform to address quantum optical effects.

Ligand Layer Engineering To Control Stability and Interfacial Properties of Nanoparticles

The use of mixed ligand layers including poly(ethylene glycol)-based ligands for the functionalization of nanoparticles is a very popular strategy in the context of nanomedicine. However, it is challenging to control the composition of the ligand layer and maintain high colloidal and chemical stability of the conjugates. A high level of control and stability are crucial for reproducibility, upscaling, and safe application. In this study, gold nanoparticles with well-defined mixed ligand layers of α-methoxypoly(ethylene glycol)-ω-(11-mercaptoundecanoate) (PEGMUA) and 11-mercaptoundecanoic acid (MUA) were synthesized and characterized by ATR-FTIR spectroscopy and gel electrophoresis. The colloidal and chemical stability of the conjugates was tested by dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), and UV/vis spectroscopy based experiments, and their interactions with cells were analyzed by elemental analysis. We demonstrate that the alkylene spacer in PEGMUA is the key feature for the controlled synthesis of mixed layer conjugates with very high colloidal and chemical stability and that a controlled synthesis is not possible using regular PEG ligands without the alkylene spacer. With the results of our stability tests, the molecular structure of the ligands can be clearly linked to the colloidal and chemical stabilization. We expect that the underlying design principle can be generalized to improve the level of control in nanoparticle surface chemistry.

Effective PEGylation of gold nanorods

Standard procedures to coat gold nanorods (AuNR) with poly(ethylene glycol) (PEG)-based ligands are not reliable and high PEG-grafting densities are not achieved. In this work, the ligand exchange of AuNR with PEGMUA, a tailored PEG-ligand bearing a C10 alkylene spacer, is studied. PEGMUA provides AuNR with very high stability against oxidative etching with cyanide. This etching reaction is utilized to study the ligand exchange in detail. Ligand exchange is faster, less ligand consuming and more reproducible with assisting chloroform extraction. Compared to PEG ligands commonly used, PEGMUA provides much higher colloidal and chemical stability. Further analyses based on NMR-, IR- and UV/Vis-spectroscopy reveal that significantly higher PEG-grafting densities, up to ∼3 nm(-2), are obtained with PEGMUA. This demonstrates how the molecular structure of the PEG ligand can be used to dramatically improve the ligand exchange and to synthesize PEGylated AuNR with high chemical and colloidal stability and high PEG grafting densities. Such AuNR are especially interesting for applications in nanomedicine.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Clustering of CdSe/CdS Quantum Dot/Quantum Rods into Micelles Can Form Bright, Non-blinking, Stable, and Biocompatible Probes

We investigate clustered CdSe/CdS quantum dots/quantum rods, ranging from single to multiple encapsulated rods within amphiphilic diblock copolymer micelles, by time-resolved optical spectroscopy. The effect of the clustering and the cluster size on the optical properties is addressed. The clusters are bright and stable and show no blinking while retaining the fundamental optical properties of the individual quantum dots/quantum rods. Cell studies show neither unspecific uptake nor morphological changes of the cells, despite the increased sizes of the clusters.

A 1-Year Quantitative Survey of Noro-, Adeno-, Human Boca-, and Hepatitis E Viruses in Raw and Secondarily Treated Sewage from Two Plants in Norway

A study of enteric viruses in raw and treated sewage from two secondary treatment plants, which received sewage from Oslo city (plant A) and small municipalities in Hedmark county in Norway (plant B), showed high levels of noro-, adeno-, and bocavirus throughout the year. A seasonal variation was observed for adeno- and GII norovirus with higher levels during winter and bocavirus that had more positive samples during winter. The virus concentrations in raw sewage were comparable in the two plants, with medians (log10 genome copies per liter) of 6.1, 6.3, 6.0, and 4.5 for noro GI, noro GII, adeno-, and bocavirus, respectively. The level of hepatitis E virus was not determined as it was below the limit of quantification. The mean log10 virus reduction was 0.55 (plant A) and 1.44 (plant B) with the highest reduction found in the plant with longer hydraulic retention time. The adenoviruses were dominantly serotype 41, while serotype 12 appeared sporadically. Of the 102 raw and treated sewage samples that were tested, eight were positive for hepatitis E virus of which four were from treated sewage. Two of the four obtained gene sequences from hepatitis E virus originated from the rural sewage samples and showed high similarity with a genotype 3 strain of hepatitis E virus detected in local piglets. Two other hepatitis E virus sequences obtained from urban sewage samples showed high similarities with genotype 3 strains isolated from urban sewage in Spain and a human genotype 1 isolate from India. The study gives information on the levels of noroviruses in raw and treated sewage, which is valuable to risk assessment, information indicating that some infections with hepatitis E viruses in Norway have a regional origin and that human bocavirus 2 and 3 are prevalent in the Norwegian population.

Abstract 2358: Quantifying PD-L1 spatial distribution signatures for patient selection approaches

Inhibitors of inflammatory checkpoints, such as PD-L1 inhibitors, have demonstrated great promise in preclinical and clinical studies. This therapeutic paradigm focuses on controlling natural inflammatory checkpoints to stimulate an elevated inflammatory response against the tumor to increase anti-tumor inflammatory cell infiltrates in the tumor microenvironment or decrease inflammatory suppressor infiltrates. The proteins which control these processes can be found in the tumor cells, cells in the tumor micro-environment (TME), or in both locales. Positive cells are often assessed in a qualitative or semi-quantitative manner using immunohistochemistry and evaluation of a limited number of representative microscopy fields across a particular tissue compartment (tumor vs stroma) or the whole tissue area. However, the locale of the inflammatory suppressors such as PD-L1 may be more revealing than estimating the tumor-wide dispersion of an inflammatory cell type. Unfortunately, the intricate spatial relationships and the often complex distribution of inflammatory cells in tissues pose significant challenges for a meaningful evaluation.

We have developed an approach which can quantify these spatial relationships in a contextual, biologically meaningful score. Immunohistochemistry staining for PD-L1 in whole lung cancer tissue sections was performed, and our CellMap software was used to assess inflammatory cell distribution in the whole tissue sections. PD-L1 positive cells were quantified relative to: 1) the total number of cells in the tumor and stromal tissue compartments, and 2) the number of cells within a distance from the tumor/stroma interface. Interestingly, several unique PD-L1 distribution patterns relative to the tumor/stroma interface were observed in the sample cohort analyzed. Quantifying the distribution of PD-L1 positive cells as a function of distance from the tumor/stroma interface revealed distribution signatures, which could be used to differentiate between samples. In contrast, this differentiation of the same samples was not possible when PD-L1 cells were assessed relative to the total number of cells.

This study provided a novel method for assessing inflammatory cell type spatial distribution relative to a tissue feature, the tumor/stroma interface. The data suggested that unique spatial patterns of inflammatory cell type distribution could be used to uniquely stratify patients compared to existing quantitative methods. Taken together, this proof-of-concept study demonstrates a unique quantitative assessment of inflammatory cell infiltrates in tumors that could be used to gain new insights into inflammatory cell type distributions and interactions in tumors, inflammatory cell spatial responses to oncology therapies, and novel patient selection criteria for traditional and immuno-oncology therapeutics.

Citation Format: Joseph S. Krueger, Nathan Martin, Anthony Milici, Holger Lange. Quantifying PD-L1 spatial distribution signatures for patient selection approaches. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2358. doi:10.1158/1538-7445.AM2015-2358

Abstract 3391: Companion diagnostic strategies specific to antibody therapies

One premise of antibody-drug conjugates (ADC) is that the bound mAb-antigen complex on the cell surface will internalize and be metabolized by lysosomal proteases to release the free drug. Thus, the efficacy of an ADC is dependent not only on the presence of cell surface antigens, but also an active system of receptor turnover and receptor-mediated endocytosis. Thus, a predictive assay for patient response would ideally account for both the degree of cell surface expression of the target, as well as cytoplasmic presence of the target to quantify a surrogate for receptor turnover and internalization. Immunohistochemistry based assays (IHC) are best suited to address these questions, as it is the only method which provides the ability to measure both membrane and cytoplasm expression of the target simultaneously within archival FFPE biopsies. However, the biological mechanisms behind receptor internalization and turnover have not been elucidated for novel therapeutic targets. In most cases, an IHC assay is utilized to evaluate these measures, without prior advance knowledge of how these measures are suitable for patient selection. Unanticipated difficulties in tissue interpretation, such as low apparent expression of the target, occlusion of membrane staining by cytoplasmic staining, or heterogeneity in staining often lead to failure in determining a correct patient stratification approach.

In order to investigate patient selection strategies for ADCs, we have invented several proprietary approaches for measuring critical properties of the therapeutic target on the cell surface or inside the cell which can be used to understand and predict efficacy to an ADC using FFPE biopsies. These quantitative pathology approaches are based on image analysis approaches which been designed specifically for ADC CDx programs to develop a pathology based scoring system which can be predictive of ADC response: 1) Accurately quantifying low levels of cell surface target expression; 2) Defining cell surface target expression independent of cytoplasmic expression; 3) Overcoming staining heterogeneity; and 4) Determining the correct staining thresholds for quantification. These image analysis based approaches can be used to define and evaluate a scoring approach, train pathologists, assess objective performance, and best determine a cutpoint approach using statistical approaches. These image analysis based tools can be used to create a manual scoring paradigm for an IHC assay or can be incorporated into a medical device directly to support the PMA effort. Incorporation of these novel tools will enable ADC developers to create efficacy and patient stratification paradigms which incorporate the critical biological endpoints unique to ADCs.

Citation Format: Joseph S. Krueger, David Young, Holger Lange, Steve Potts. Companion diagnostic strategies specific to antibody therapies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3391. doi:10.1158/1538-7445.AM2015-3391

Abstract 2360: Quantitative analysis of multiple subtypes of immune system cells in cancer tissues

Current cancer biology acknowledges the key role of the immune system in tumor biology, and promise for the modulation of immune system in cancer treatment. The composition of the inflammatory cell populations in tissues is reflective of the overall state of the Tumor Micro-Environment (TME), and the identification of distinct inflammatory cell types may hold prognostic or predictive value. Immunohistochemistry allows for reliable identification of the cell constituents to facilitate analysis of the TME while remaining in the tissue context.

Establishing a quantitative paradigm for inflammatory cell types and subtype profiling requires unbiased and automated whole-tissue based quantitation methods, which are capable of spatial integration of multiple inflammatory cell markers across the whole tissue. While single slide fluorescent multiplex approaches can address this need, the use of difficult-to-implement wet assay strategies involving multiplexing 6-8 fluorescent markers on the same tissue section are difficult to implement in a global clinical diagnostic lab setting. To answer this need, we combined novel advents in Tissue Image Analysis (TIA) to integrate spatial expression of serial-section stained whole tissue clinical lung cancer specimens.

In this proof-of-principle study,we were able to superimpose specific locations of individual cell types onto 6 serial sections and evaluate different inflammatory cell types. We used serial sections of clinical lung specimens stained for six immune phenotypic markers (CD68, CD4, CD8, CD33, FoxP3, and CD11b) to illustrate a repertoire of inflammatory cell types. Our proprietary CellMap algorithm was utilized to identify, enumerate, and determine the precise location of individual inflammatory cells in tissues on cell-by-cell basis in the tumor microenvironment (TME). Our proprietary FACTS (Feature Analysis on Consecutive Tissue Sections) approach was used to integrate the spatial expression of individual markers onto a reference H&E slide, and/or adjacent slides. Using the aligned FACTS data and our proprietary MultivariateMap approach, we integrated the patterns of each marker based on immune cell type function and their location relative to each other and the tumor epithelial cells.

In this study, we demonstrated how spatial integration of immune cell markers in the context of whole tissues can be applied to the diagnostic setting. By creating a comprehensive landscape of the immune system state in the tissue biopsies, we were able to identify crucial patterns which represent function and role in immune system biology. These approaches provide a robust platform for immuno-oncology applications by providing information on the state of the immune system in cancer using approaches implementable in the clinic. The use of these approaches will benefit further understanding of cancer pathology, and can directly lead to the development of diagnostic tests with clinical utility.

Citation Format: Mirza Peltjo, Carsten Schnatwinkel, Nathan Martin, Holger Lange, Joseph S. Krueger. Quantitative analysis of multiple subtypes of immune system cells in cancer tissues. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2360. doi:10.1158/1538-7445.AM2015-2360