Deposition of silver nanoparticles in geochemically heterogeneous porous media: predicting affinity from surface composition analysis.

The transport of uncoated silver nanoparticles (AgNPs) in a porous medium composed of silica glass beads modified with a partial coverage of iron oxide (hematite) was studied and compared to that in a porous medium composed of unmodified glass beads (GB). At a pH lower than the point of zero charge (PZC) of hematite, the affinity of AgNPs for a hematite-coated glass bead (FeO-GB) surface was significantly higher than that for an uncoated surface. There was a linear correlation between the average nanoparticle affinity for media composed of mixtures of FeO-GB and GB collectors and the relative composition of those media as quantified by the attachment efficiency over a range of mixing mass ratios of the two types of collectors, so that the average AgNPs affinity for these media is readily predicted from the mass (or surface) weighted average of affinities for each of the surface types. X-ray photoelectron spectroscopy (XPS) was used to quantify the composition of the collector surface as a basis for predicting the affinity between the nanoparticles for a heterogeneous collector surface. A correlation was also observed between the local abundances of AgNPs and FeO on the collector surface.

Morphing low-affinity ligands into high-avidity nanoparticles by thermally triggered self-assembly of a genetically encoded polymer.

Multivalency is the increase in avidity resulting from the simultaneous interaction of multiple ligands with multiple receptors. This phenomenon, seen in antibody-antigen and virus-cell membrane interactions, is useful in designing bioinspired materials for targeted delivery of drugs or imaging agents. While increased avidity offered by multivalent targeting is attractive, it can also promote nonspecific receptor interaction in nontarget tissues, reducing the effectiveness of multivalent targeting. Here, we present a thermal targeting strategy--dynamic affinity modulation (DAM)--using elastin-like polypeptide diblock copolymers (ELP(BC)s) that self-assemble from a low-affinity to high-avidity state by a tunable thermal "switch", thereby restricting activity to the desired site of action. We used an in vitro cell binding assay to investigate the effect of the thermally triggered self-assembly of these ELP(BC)s on their receptor-mediated binding and cellular uptake. The data presented herein show that (1) ligand presentation does not disrupt ELP(BC) self-assembly; (2) both multivalent ligand presentation and upregulated receptor expression are needed for receptor-mediated interaction; (3) increased size of the hydrophobic segment of the block copolymer promotes multivalent interaction with membrane receptors, potentially due to changes in the nanoscale architecture of the micelle; and (4) nanoscale presentation of the ligand is important, as presentation of the ligand by micrometer-sized aggregates of an ELP showed a low level of binding/uptake by receptor-positive cells compared to its presentation on the corona of a micelle. These data validate the concept of thermally triggered DAM and provide rational design parameters for future applications of this technology for targeted drug delivery.

Innovation in business groups

Using novel data on European firms, this paper investigates the relationship between business groups and innovation. Controlling for various firm characteristics, we find that group affiliates are more innovative than standalones. We examine several hypotheses to explain this finding, focusing on group internal capital markets and knowledge spillovers. We find that group affiliation is particularly important for innovation in industries that rely more on external funding and in groups with more diversified capital sources, consistent with the internal capital markets hypothesis. Our results suggest that knowledge spillovers are not the main driver of innovation in business groups because firms affiliated with the same group do not have a common research focus and are unlikely to cite each other's patents. © 2010 INFORMS.

Reference groups and product line decisions: An experimental investigation of limited editions and product proliferation

Some luxury goods manufacturers offer limited editions of their products, whereas some others market multiple product lines. Researchers have found that reference groups shape consumer evaluations of these product categories. Yet little empirical research has examined how reference groups affect the product line decisions of firms. Indeed, in a field setting it is quite a challenge to isolate reference group effects from contextual effects and correlated effects. In this paper, we propose a parsimonious model that allows us to study how reference groups influence firm behavior and that lends itself to experimental analysis. With the aid of the model we investigate the behavior of consumers in a laboratory setting where we can focus on the reference group effects after controlling for the contextual and correlated effects. The experimental results show that in the presence of strong reference group effects, limited editions and multiple products can help improve firms' profits. Furthermore, the trends in the purchase decisions of our participants point to the possibility that they are capable of introspecting close to two steps of thinking at the outset of the game and then learning through reinforcement mechanisms. © 2010 INFORMS.

The impact of structured support groups for pregnant South African women recently diagnosed HIV positive.

The authors of this study evaluated a structured 10-session psychosocial support group intervention for newly HIV-diagnosed pregnant South African women. Participants were expected to display increases in HIV disclosure, self-esteem, active coping and positive social support, and decreases in depression, avoidant coping, and negative social support. Three hundred sixty-one pregnant HIV-infected women were recruited from four antenatal clinics in Tshwane townships from April 2005 to September 2006. Using a quasi-experimental design, assessments were conducted at baseline and two and eight months post-intervention. A series of random effects regression analyses were conducted, with the three assessment points treated as a random effect of time. At both follow-ups, the rate of disclosure in the intervention group was significantly higher than that of the comparison group (p<0.001). Compared to the comparison group at the first follow-up, the intervention group displayed higher levels of active coping (t=2.68, p<0.05) and lower levels of avoidant coping (t=-2.02, p<0.05), and those who attended at least half of the intervention sessions exhibited improved self-esteem (t=2.11, p<0.05). Group interventions tailored for newly HIV positive pregnant women, implemented in resource-limited settings, may accelerate the process of adjusting to one's HIV status, but may not have sustainable benefits over time.

Life-narrative and word-cued autobiographical memories in centenarians: comparisons with 80-year-old control, depressed, and dementia groups.

Centenarians provided autobiographical memories to either a request for a life narrative or a request to produce autobiographical memories to cue words. Both methods produced distributions with childhood-amnesia, reminiscence-bump, and recency components. The life-narrative method produced relatively more bump memories at the expense of recent memories. The life-narrative distributions were similar to those obtained from 80-year-old adults without clinical symptoms and from 80-year-old Alzheimer's dementia and depression patients, except that the centenarians had an additional 20-year period of relatively low recall between the bump and recency components. The centenarians produced more emotionally neutral memories than the other three groups and produced fewer and less detailed memories than the non-clinical 80-year-old sample.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

D-Amino acid peptide residualizing agents bearing N-hydroxysuccinimido- and maleimido-functional groups and their application for trastuzumab radioiodination.

INTRODUCTION: Proteins that undergo receptor-mediated endocytosis are subject to lysosomal degradation, requiring radioiodination methods that minimize loss of radioactivity from tumor cells after this process occurs. To accomplish this, we developed the residualizing radioiodination agent N(ϵ)-(3-[(*)I]iodobenzoyl)-Lys(5)-N(α)-maleimido-Gly(1)-D-GEEEK (Mal-D-GEEEK-[(*)I]IB), which enhanced tumor uptake but also increased kidney activity and necessitates generation of sulfhydryl moieties on the protein. The purpose of the current study was to synthesize and evaluate a new D-amino acid based agent that might avoid these potential problems. METHODS: N(α)-(3-iodobenzoyl)-(5-succinimidyloxycarbonyl)-D-EEEG (NHS-IB-D-EEEG), which contains 3 D-glutamates to provide negative charge and a N-hydroxysuccinimide function to permit conjugation to unmodified proteins, and the corresponding tin precursor were produced by solid phase peptide synthesis and subsequent conjugation with appropriate reagents. Radioiodination of the anti-HER2 antibody trastuzumab using NHS-IB-D-EEEG and Mal-D-GEEEK-IB was compared. Paired-label internalization assays on BT474 breast carcinoma cells and biodistribution studies in athymic mice bearing BT474M1 xenografts were performed to evaluate the two radioiodinated D-peptide trastuzumab conjugates. RESULTS: NHS-[(131)I]IB-D-EEEG was produced in 53.8%±13.4% and conjugated to trastuzumab in 39.5%±7.6% yield. Paired-label internalization assays with trastuzumab-NHS-[(131)I]IB-D-EEEG and trastuzumab-Mal-D-GEEEK-[(125)I]IB demonstrated similar intracellular trapping for both conjugates at 1h ((131)I, 84.4%±6.1%; (125)I, 88.6%±5.2%) through 24h ((131)I, 60.7%±6.8%; (125)I, 64.9%±6.9%). In the biodistribution experiment, tumor uptake peaked at 48 h (trastuzumab-NHS-[(131)I]IB-D-EEEG, 29.8%±3.6%ID/g; trastuzumab-Mal-D-GEEEK-[(125)I]IB, 45.3%±5.3%ID/g) and was significantly higher for (125)I at all time points. In general, normal tissue levels were lower for trastuzumab-NHS-[(131)I]IB-D-EEEG, with the differences being greatest in kidneys ((131)I, 2.2%±0.4%ID/g; (125)I, 16.9%±2.8%ID/g at 144 h). CONCLUSION: NHS-[(131)I]IB-D-EEEG warrants further evaluation as a residualizing radioiodination agent for labeling internalizing antibodies/fragments, particularly for applications where excessive renal accumulation could be problematic.