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Background Inflammation may contribute to cognitive difficulties in patients with breast cancer. We tested 2 hypotheses: inflammation is elevated in patients with breast cancer vs noncancer control participants and inflammation in patients is associated with worse attention and processing speed over the course of chemotherapy. Methods Serum cytokines (interleukin [IL]–4, 6, 8, 10; tumor necrosis factor [TNF]–α) and soluble receptors [sTNFRI, II]) were measured in 519 females with breast cancer before and after chemotherapy and 338 females without cancer serving as control participants. Attention and processing speed were measured by Rapid Visual Processing (RVP), Backward Counting (BCT), and Trail Making-A (TMT-A) tests. Linear regression models examined patient vs control cytokines and receptor levels, adjusting for covariates. Linear regression models also examined relationships between patient cytokines and receptor levels and test performance, adjusting for age, body mass index, anxiety, depression, cognitive reserve, and chemotherapy duration. Statistical tests were 2-sided (α = .05). Results sTNFRI and sTNFRII increased over time in patients relative to controls, whereas IL-4, IL-6, and IL-10 decreased. Prechemotherapy, higher IL-8 associated with worse BCT (β = 0.610, SE = 0.241, P = .01); higher IL-4 (β = −1.098, SE = 0.516, P = .03) and IL-10 (β = −0.835, SE = 0.414, P = .04) associated with better TMT-A. Postchemotherapy, higher IL-8 (β = 0.841, SE = 0.260, P = .001), sTNFRI (β = 6.638, SE = 2.208, P = .003), and sTNFRII (β = 0.913, SE = 0.455, P = .045) associated with worse BCT; higher sTNFRII also associated with worse RVP (β = −1.316, SE = 0.587, P = .03). At prechemotherapy, higher IL-4 predicted RVP improvement over time (β = 0.820, SE = 0.336, P = .02); higher sTNFRI predicted worse BCT over time (β = 5.566, SE = 2.367, P = .02). Longitudinally, increases in IL-4 associated with BCT improvement (β = −0.564, SE = 0.253, P = .03). Conclusions Generally, worse attention and processing speed were associated with higher inflammatory cytokines and receptors and lower anti-inflammatory cytokines in patients; future confirmatory studies are needed.

Cancer-related cognitive impairment (CRCI) is often related to chemotherapy. Increased chronic inflammation is believed to play a key role in the development of CRCI related to chemotherapy but studies assessing this hypothesis specifically in patients receiving chemotherapy are rare.We assessed several cognitive domains using the Cambridge Neuropsychological Test Automated Battery (CANTAB) in twenty-two breast cancer patients currently receiving chemotherapy. We also measured inflammatory cytokine and receptor (MCP-1, TNF-α, sTNFRI, sTNFRII) concentrations in patient sera using Luminex assays. These concentrations were log-transformed to obtain a normal distribution. Associations between log-transformed cytokines and cognition were evaluated using Pearson correlations and linear regression, taking into account relevant covariates.Increased concentrations of sTNFRI and sTNFRII were associated with poorer performance on the CANTAB Delayed Matching to Sample (DMS, tests visual memory). Increasing sTNFRI levels were negatively correlated with DMS percent correct (r=-0.47, p=0.029) and DMS percent correct after a 12 second (s) delay (r=-0.65, p=0.001). Increasing levels of sTNFRII negatively correlated with DMS percent correct after 12s delay (r=-0.57, p=0.006). After controlling for relevant demographic (i.e. age, education) and clinical variables (i.e. disease stage, regimen type), we found that increased sTNFRI remained significantly related to decline on the DMS at the 12s delay (p=0.018).This preliminary study shows a significant association between higher sTNFRI and lower scores on the short-term visual memory delayed match to sample test in breast cancer patients receiving chemotherapy, supporting the hypothesis that sTNFRI is involved in CRCI.

12070 Background: Cognitive impairment is a prevalent side effect of chemotherapy. We have previously shown that chemotherapy treatment is associated with worse performance on the Rapid Visual Processing test (RVP), an objective measure of sustained attention, over time compared to non-cancer controls. Better understanding of the biologic mechanisms underlying cognitive impairment in cancer patients is needed. The pro-inflammatory cytokine tumor necrosis factor alpha (TNFα) has been implicated in increasing blood brain barrier (BBB) permeability, which in turn is associated with cognitive impairment. This study assessed the relationships of TNFα and S100β, a biomarker of BBB permeability, to each other and to RVP performance over time. Methods: We analyzed a subset of participants (n = 89 patients, n = 52 controls, mean age = 60) from a prospective longitudinal study of women with breast cancer receiving chemotherapy and non-cancer controls. TNFα and S100β were measured in serum pre-chemotherapy (T1, ≤7 days before first treatment) and post-chemotherapy (T2, ≤1 month after last treatment) and at corresponding times for controls. Sustained attention was assessed by total correct rejections on the RVP test at T1 and T2. Separate linear regression models including all participants were used to relate 1) baseline TNFα and S100β levels to change in RVP performance over time, 2) change in TNFα and S100β to change in RVP performance over time, and 3) change in TNFα to change in S100β. Models were adjusted for age. 4) T-tests were used to compare the TNFα and S100β change scores (T1 to T2) of patients vs controls. Results: Greater increase (T1 to T2) in the pro-inflammatory cytokine TNFα was associated with worse cognition, measured by performance on RVP over time (p = 0.02). Higher baseline S100β, a biomarker of BBB permeability, was associated with worse performance on RVP over time (p = 0.09). Increase in TNFα was associated with increase in S100β (p = 0.11). S100β increased from T1 to T2 in patients relative to controls (p = 0.09). Conclusions: These results suggest that higher TNFα may be related to increases in blood brain barrier permeability and worse cognition. Future studies will further define the link between inflammation, blood brain barrier permeability and chemotherapy-related cognitive decline, with the goal of informing the development of new interventions. Funding: R01CA231014, T32CA102618, DP2CA195765, UG1CA189961.

The aryl hydrocarbon receptor (AhR) is a ligand-activated member of the basic-helix-loop-helix/PER-ARNT-SIM(PAS) transcription factor superfamily that also mediates the toxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Increasing evidence suggests that AhR influences the development of many tissues, including the central nervous system. Our previous studies suggest that sustained AhR activation by TCDD and/or AhR deletion disrupts cerebellar granule neuron precursor (GNP) development. In the current study, to determine whether endogenous AhR controls GNP development in a cell-autonomous manner, we created a GNP-specific AhR deletion mouse, AhR(fx/fx) /Math1(CRE/+) (AhR CKO). Selective AhR deletion in GNPs produced abnormalities in proliferation and differentiation. Specifically, fewer GNPs were engaged in S-phase, as demonstrated by ∼25% reductions in thymidine (in vitro) and Bromodeoxyuridine (in vivo) incorporation. Furthermore, total granule neuron numbers in the internal granule layer at PND21 and PND60 were diminished in AhR conditional knockout (CKO) mice compared with controls. Conversely, differentiation was enhanced, including ∼40% increase in neurite outgrowth and 50% increase in GABARα6 receptor expression in deletion mutants. Our results suggest that AhR activity plays a role in regulating granule neuron number and differentiation, possibly by coordinating this GNP developmental transition. These studies provide novel insights for understanding the normal roles of AhR signaling during cerebellar granule cell neurogenesis and may have important implications for the effects of environmental factors in cerebellar dysgenesis.

Background Cyclophosphamide chemotherapy is a mainstay of adjuvant breast cancer treatment. Unfortunately, this drug is associated with cognitive impairments in cancer patients that may accelerate cognitive aging. Memory is particularly affected in many patients. In order to better understand the precise cognitive impairments caused by this chemotherapy agent, we investigated a clinically relevant dose and administration paradigm on delayed spatial memory abilities in C57BL/6 mice. We utilized a delayed alternation paradigm similar to a delayed match to sample paradigm reported to be sensitive in human neurotoxicology research. Methods A dose of 200 mg/kg cyclophosphamide was administered intravenously (at weekly intervals) for 4 weeks to C57BL/6 mice starting at 6 ½ months of age. Memory was tested in mice using a reward-based delayed spatial alternation paradigm with delay values of 1.5, 3, 6.1, 12.4 and 25 s presented randomly over 80 sessions (16 reinforcers per session), and testing began at the initiation of chemotherapy through 3 months. Results At the longest delay, i.e., that requiring the greatest memory, mice treated with chemotherapy exhibited a significant decline over time in percent correct which leveled off compared to controls that continued to improve slightly. Conclusions Our clinically relevant model shows cyclophosphamide chemotherapy causes a slight decline in delayed spatial memories at the longest delay that is sustained over time as mice age.

Chemotherapeutic agents produce persistent difficulties in memory through an unknown mechanism. We tested the hypothesis that chemotherapeutic agents readily able to cross the blood–brain barrier (cyclophosphamide and fluorouracil), as opposed to those not known to readily cross the barrier (paclitaxel and doxorubicin), reduce neural cell proliferation following chemotherapy. We found that 5-bromo-2-deoxyuridine labeling following chemotherapy given to C57BL/6 mice revealed a similar reduction in neural cell proliferation in the dentate gyrus for all four agents. Insulin-like growth factor 1, a molecule implicated in promoting neurogenesis, counteracted the effects of high doses of chemotherapy on neural cell proliferation.

The widespread environmental contaminant 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) has been linked to developmental neurotoxicity associated with abnormal cerebellar maturation in both humans and rodents. TCDD mediates toxicity via binding to the aryl hydrocarbon receptor (AhR), a transcription factor that regulates the expression of xenobiotic metabolizing enzymes and growth regulatory molecules. Our previous studies demonstrated that cerebellar granule neuron precursor cells (GNPs) express transcriptionally active AhR during critical developmental periods. TCDD exposure also impaired GNP proliferation and survival in vitro. Therefore, this study tested the hypothesis that TCDD exposure disrupts cerebellar development by interfering with GNP differentiation. In vivo experiments indicated that TCDD exposure on postnatal day (PND) 6 resulted in increased expression of a mitotic marker and increased thickness of the external granule layer (EGL) on PND10. Expression of the early differentiation marker TAG-1 was also more pronounced in postmitotic, premigratory granule neurons of the EGL, and increased apoptosis of GNPs was observed. On PND21, expression of the late GNP differentiation marker GABA(A alpha 6) receptor (GABAR(A alpha 6)) and total estimated cell numbers were both reduced following exposure on PND6. Studies in unexposed adult AhR(-/-) mice revealed lower GABAR(A alpha 6) levels and DNA content. In vitro studies showed elevated expression of the early differentiation marker p27/Kip1 and the GABAR(A alpha 6) in GNPs following TCDD exposure, and the expression patterns of proteins related to granule cell neurite outgrowth, beta III-tubulin and polysialic acid neural cell adhesion molecule, were consistent with enhanced neuroblast differentiation. Together, our data suggest that TCDD disrupts a normal physiological role of AhR, resulting in compromised GNP maturation and neuroblast survival, which impacts final cell number in the cerebellum.

We have compared video and photographic methods for calculating the number of ultraviolet radiation (uv)-induced pyrimidine dimers in DNA from the bacteriophage T7 exposed to uv (0 to 800 J/m2) from an FS40 sunlamp. DNA was incubated with a pyrimidine dimer-specific Micrococcus luteus uv endonuclease, subjected to alkaline agarose gel electrophoresis, neutralized, and stained with ethidium bromide, and the DNA fluorescence was recorded either with a video camera or on photographic film. The slopes of the dose-response curves for the number of uv-endonuclease-sensitive sites per 10(3) bases (pyrimidine dimers) was 1.2 (+/- 0.1) X 10(-4) uv-endonuclease-sensitive sites per J/m2 for the video analysis and 1.3 (+/- 0.04) X 10(-4) uv-endonuclease-sensitive sites per J/m2 for the photographic analysis. Results for pyrimidine dimer determination by either method were statistically comparable.

An iterative learning algorithm for multi-channel coherence analysis (MCA) is developed in this paper. MCA is an extension of the well known canonical correlation analysis (CCA) that allows for more than two data channels to be analyzed. The many applications of CCA have motivated this extension to exploit the linear relationship between many data channels. This paper discusses fundamental differences between the two analysis techniques while reviewing the standard method for performing MCA. Discussion on why MCA correlations are not deemed "canonical" as they are in the two-channel case of CCA is also provided. The developed iterative learning for MCA is then demonstrated and its performance evaluated on a synthesized data set.

Developing an effective detection and classification system for use with buried underwater objects is a challenging problem. In this paper, multichannel canonical correlation analysis (MCCA) is used for feature extraction from multiple sonar returns of buried underwater objects using data collected by the new generation Buried Object Scanning Sonar (BOSS) system. Comparisons are made between the classification results of features extracted by the proposed algorithm and those extracted by the two-channel canonical correlation analysis (CCA) algorithm on the SAX '04 data set. Extracted features are subsequently used in the development of classification systems able to differentiate between mine-like and non-mine-like objects. This study compares different feature extraction algorithms and classification schemes, and the results are presented in terms of classification rates and overall detection/classification performance. The results show that, for the SAX '04 data set, the features extracted via MCCA yield higher correct classification rates than feature extracted using CCA while simultaneously reducing structural complexity.

Multichannel canonical correlation analysis (MCCA) is used in this paper for feature extraction from multiple sonar returns off of buried underwater objects using data collected by the new generation buried object scanning sonar (BOSS) system. Comparisons are made between the classification results of features extracted by the proposed algorithm and those extracted by the two-channel canonical correlation analysis (CCA) algorithm. This study compares different feature extraction and classification algorithms, and the results are presented in terms of confusion matrices. The results show that MCCA yields higher correct classification rates than CCA while reducing the classifier's structural complexity.

The separation of DNA by gel electrophoresis provides a rapid method for determining size distributions of DNA in solution. Densitometric scanning of photographs of gels has been the standard method of analysis of agarose gels. However, analysis of photographs is complicated by the non-linear response of photographic film. Charged-coupled device video cameras have become popular for quantitative densitometry and we have used a charge-coupled device camera to image agarose gels to quantitate DNA damage. We compare video and photographic densitometry for quantitation of ultraviolet radiation (UV)-induced DNA damage and find that the two methods give equivalent results.

A method of analyzing DNA agarose gels using interactive computer graphics is described. After electrophoresis in an alkaline agarose gel, DNA is neutralized, stained with ethidium bromide and excited with ultraviolet radiation. The resulting fluorescent distribution on the gel is photographed, and the negative scanned by a digitizing densitometer. The data is subsequently analyzed using a computer program developed to facilitate manipulation and selection of data from the densitometer trace. The method has been applied to determine pyrimidine dimer yields in DNA from human lymphocytes exposed to UV radiation. The technique significantly reduces the time required to analyze such data, while also providing greater accuracy. The method could be easily adapted to assist in similar analyses of other macromolecules such as RNA or proteins.

When modeling thermal imaging systems to predict their performance, there are three functional areas that must be specifically characterized: the object being imaged; the intervening atmosphere; and the sensor itself. This paper will discuss two computer simulations presently being used by the U.S. Army Missile Command (MICOM) which integrate models of these three functional areas to calculate the performance of a variety of thermal imaging systems for a range of atmospheres, scenarios, targets, and sensors. Common to both approaches is: use of the Johnson bar criteria for detection, recognition and identification; the use (direct or indirect) of the AFGL LOWTRAN code to model the atmosphere; and, finally, some methodologies for modeling staring focal plane arrays (FPAs) as the sensor detection element. The three functional areas will be discussed first, followed by discussions of the two approaches; the Fire Control Sensor Simulator (FCSS), an engagement model; and, the MICOM Infrared Imaging System Performance Model (MIISPM), a more detailed model emphasizing the sensor itself. The MIISPM is based upon the Night Vision Laboratory Static Performance Model (NVLSPM), but has been enhanced in several important ways, discussed in the paper. While both approaches provide as output the same performance criteria (probability of detection, recognition and identification, as a function of range), each model has its own strengths for different aspects of the sensor performance problem: for the FCSS, targets and scenarios; for the MIISPM, details of the sensor. Both approaches will be presented and compared in terms of the results, run time efficiency, and required hardware. Both models presently run on IBM or IBM compatible personal computers.