Temporal variations of IEEE 802.11b signal strengths in an in-building environment

Recent popularity of the IEEE 802.11b Wireless Local Area Networks (WLANs) in a host of current-day applications has instigated a suite of research challenges. The 802.11b WLANs are highly reliable and wide spread. In this work, we study the temporal characteristics of RSSI in the real-working environment by conducting a controlled set of experiments. Our results indicate that a significant variability in the RSSI can occur over time. Some of this variability in the RSSI may be due to systematic causes while the other component can be expressed as stochastic noise. We present an analysis of both these aspects of RSSI. We treat the moving average of the RSSI as the systematic causes and the noise as the stochastic causes. We give a reasonable estimate for the moving average to compute the noise accurately. We attribute the changes in the environment such as the movement of people and the noise associated with the NIC circuitry and the network access point as causes for this variability. We find that the results of our analysis are of primary importance to active research areas such as location determination of users in a WLAN. The techniques used in some of the RF-based WLAN location determination systems, exploit the characteristics of the RSSI presented in this work to infer the location of a wireless client in a WLAN. Thus our results form the building blocks for other users of the exact characteristics of the RSSI.

Hand-held spectroscopic device for in vivo and intraoperative tumor detection: contrast enhancement, detection sensitivity, and tissue penetration.

Surgery is one of the most effective and widely used procedures in treating human cancers, but a major problem is that the surgeon often fails to remove the entire tumor, leaving behind tumor-positive margins, metastatic lymph nodes, and/or satellite tumor nodules. Here we report the use of a hand-held spectroscopic pen device (termed SpectroPen) and near-infrared contrast agents for intraoperative detection of malignant tumors, based on wavelength-resolved measurements of fluorescence and surface-enhanced Raman scattering (SERS) signals. The SpectroPen utilizes a near-infrared diode laser (emitting at 785 nm) coupled to a compact head unit for light excitation and collection. This pen-shaped device effectively removes silica Raman peaks from the fiber optics and attenuates the reflected excitation light, allowing sensitive analysis of both fluorescence and Raman signals. Its overall performance has been evaluated by using a fluorescent contrast agent (indocyanine green, or ICG) as well as a surface-enhanced Raman scattering (SERS) contrast agent (pegylated colloidal gold). Under in vitro conditions, the detection limits are approximately 2-5 × 10(-11) M for the indocyanine dye and 0.5-1 × 10(-13) M for the SERS contrast agent. Ex vivo tissue penetration data show attenuated but resolvable fluorescence and Raman signals when the contrast agents are buried 5-10 mm deep in fresh animal tissues. In vivo studies using mice bearing bioluminescent 4T1 breast tumors further demonstrate that the tumor borders can be precisely detected preoperatively and intraoperatively, and that the contrast signals are strongly correlated with tumor bioluminescence. After surgery, the SpectroPen device permits further evaluation of both positive and negative tumor margins around the surgical cavity, raising new possibilities for real-time tumor detection and image-guided surgery.

Selective enhancement of donor hematopoietic cell engraftment by the CXCR4 antagonist AMD3100 in a mouse transplantation model.

The interaction between stromal cell-derived factor-1 (SDF-1) with CXCR4 chemokine receptors plays an important role in hematopoiesis following hematopoietic stem cell transplantation. We examined the efficacy of post transplant administration of a specific CXCR4 antagonist (AMD3100) in improving animal survival and in enhancing donor hematopoietic cell engraftment using a congeneic mouse transplantation model. AMD3100 was administered subcutaneously at 5 mg/kg body weight 3 times a week beginning at day +2 post-transplant. Post-transplant administration of AMD3100 significantly improves animal survival. AMD3100 reduces pro-inflammatory cytokine/chemokine production. Furthermore, post transplant administration of AMD3100 selectively enhances donor cell engraftment and promotes recovery of all donor cell lineages (myeloid cells, T and B lymphocytes, erythrocytes and platelets). This enhancement results from a combined effect of increased marrow niche availability and greater cell division induced by AMD3100. Our studies shed new lights into the biological roles of SDF-1/CXCR4 interaction in hematopoietic stem cell engraftment following transplantation and in transplant-related mortality. Our results indicate that AMD3100 provides a novel approach for enhancing hematological recovery following transplantation, and will likely benefit patients undergoing transplantation.

BOLD signal compartmentalization based on the apparent diffusion coefficient.

Functional MRI (fMRI) can detect blood oxygenation level dependent (BOLD) hemodynamic responses secondary to neuronal activity. The most commonly used method for detecting fMRI signals is the gradient-echo echo-planar imaging (EPI) technique because of its sensitivity and speed. However, it is generally believed that a significant portion of these signals arises from large veins, with additional contribution from the capillaries and parenchyma. Early experiments using diffusion-weighted gradient-echo EPI have suggested that intra-voxel incoherent motion (IVIM) weighting inherent in the sequence can selectively attenuate contributions from different vessels based on the differences in the mobility of the blood within them. In the present study, we used similar approach to characterize the apparent diffusion coefficient (ADC) distribution within the activated areas of BOLD contrast. It is shown that the voxel values of the ADCs obtained from this technique can infer various vascular contributions to the BOLD signal.

Probing the ultimate limits of plasmonic enhancement.

Metals support surface plasmons at optical wavelengths and have the ability to localize light to subwavelength regions. The field enhancements that occur in these regions set the ultimate limitations on a wide range of nonlinear and quantum optical phenomena. We found that the dominant limiting factor is not the resistive loss of the metal, but rather the intrinsic nonlocality of its dielectric response. A semiclassical model of the electronic response of a metal places strict bounds on the ultimate field enhancement. To demonstrate the accuracy of this model, we studied optical scattering from gold nanoparticles spaced a few angstroms from a gold film. The bounds derived from the models and experiments impose limitations on all nanophotonic systems.

Smoothened signal transduction is promoted by G protein-coupled receptor kinase 2.

Deregulation of the Sonic hedgehog pathway has been implicated in an increasing number of human cancers. In this pathway, the seven-transmembrane (7TM) signaling protein Smoothened regulates cellular proliferation and differentiation through activation of the transcription factor Gli. The activity of mammalian Smoothened is controlled by three different hedgehog proteins, Indian, Desert, and Sonic hedgehog, through their interaction with the Smoothened inhibitor Patched. However, the mechanisms of signal transduction from Smoothened are poorly understood. We show that a kinase which regulates signaling by many "conventional" 7TM G-protein-coupled receptors, G protein-coupled receptor kinase 2 (GRK2), participates in Smoothened signaling. Expression of GRK2, but not catalytically inactive GRK2, synergizes with active Smoothened to mediate Gli-dependent transcription. Moreover, knockdown of endogenous GRK2 by short hairpin RNA (shRNA) significantly reduces signaling in response to the Smoothened agonist SAG and also inhibits signaling induced by an oncogenic Smoothened mutant, Smo M2. We find that GRK2 promotes the association between active Smoothened and beta-arrestin 2. Indeed, Gli-dependent signaling, mediated by coexpression of Smoothened and GRK2, is diminished by beta-arrestin 2 knockdown with shRNA. Together, these data suggest that GRK2 plays a positive role in Smoothened signaling, at least in part, through the promotion of an association between beta-arrestin 2 and Smoothened.

Independent beta-arrestin 2 and G protein-mediated pathways for angiotensin II activation of extracellular signal-regulated kinases 1 and 2.

Stimulation of a mutant angiotensin type 1A receptor (DRY/AAY) with angiotensin II (Ang II) or of a wild-type receptor with an Ang II analog ([sarcosine1,Ile4,Ile8]Ang II) fails to activate classical heterotrimeric G protein signaling but does lead to recruitment of beta-arrestin 2-GFP and activation of extracellular signal-regulated kinases 1 and 2 (ERK1/2) (maximum stimulation approximately 50% of wild type). This G protein-independent activation of mitogen-activated protein kinase is abolished by depletion of cellular beta-arrestin 2 but is unaffected by the PKC inhibitor Ro-31-8425. In parallel, stimulation of the wild-type angiotensin type 1A receptor with Ang II robustly stimulates ERK1/2 activation with approximately 60% of the response blocked by the PKC inhibitor (G protein dependent) and the rest of the response blocked by depletion of cellular beta-arrestin 2 by small interfering RNA (beta-arrestin dependent). These findings imply the existence of independent G protein- and beta-arrestin 2-mediated pathways leading to ERK1/2 activation and the existence of distinct "active" conformations of a seven-membrane-spanning receptor coupled to each.

Activation and targeting of extracellular signal-regulated kinases by beta-arrestin scaffolds.

Using both confocal immunofluorescence microscopy and biochemical approaches, we have examined the role of beta-arrestins in the activation and targeting of extracellular signal-regulated kinase 2 (ERK2) following stimulation of angiotensin II type 1a receptors (AT1aR). In HEK-293 cells expressing hemagglutinin-tagged AT1aR, angiotensin stimulation triggered beta-arrestin-2 binding to the receptor and internalization of AT1aR-beta-arrestin complexes. Using red fluorescent protein-tagged ERK2 to track the subcellular distribution of ERK2, we found that angiotensin treatment caused the redistribution of activated ERK2 into endosomal vesicles that also contained AT1aR-beta-arrestin complexes. This targeting of ERK2 reflects the formation of multiprotein complexes containing AT1aR, beta-arrestin-2, and the component kinases of the ERK cascade, cRaf-1, MEK1, and ERK2. Myc-tagged cRaf-1, MEK1, and green fluorescent protein-tagged ERK2 coprecipitated with Flag-tagged beta-arrestin-2 from transfected COS-7 cells. Coprecipitation of cRaf-1 with beta-arrestin-2 was independent of MEK1 and ERK2, whereas the coprecipitation of MEK1 and ERK2 with beta-arrestin-2 was significantly enhanced in the presence of overexpressed cRaf-1, suggesting that binding of cRaf-1 to beta-arrestin facilitates the assembly of a cRaf-1, MEK1, ERK2 complex. The phosphorylation of ERK2 in beta-arrestin complexes was markedly enhanced by coexpression of cRaf-1, and this effect is blocked by expression of a catalytically inactive dominant inhibitory mutant of MEK1. Stimulation with angiotensin increased the binding of both cRaf-1 and ERK2 to beta-arrestin-2, and the association of beta-arrestin-2, cRaf-1, and ERK2 with AT1aR. These data suggest that beta-arrestins function both as scaffolds to enhance cRaf-1 and MEK-dependent activation of ERK2, and as targeting proteins that direct activated ERK to specific subcellular locations.

A beta-adrenergic receptor kinase-like enzyme is involved in olfactory signal termination.

We have previously shown that second-messenger-dependent kinases (cAMP-dependent kinase, protein kinase C) in the olfactory system are essential in terminating second-messenger signaling in response to odorants. We now document that subtype 2 of the beta-adrenergic receptor kinase (beta ARK) is also involved in this process. By using subtype-specific antibodies to beta ARK-1 and beta ARK-2, we show that beta ARK-2 is preferentially expressed in the olfactory epithelium in contrast to findings in most other tissues. Heparin, an inhibitor of beta ARK, as well as anti-beta ARK-2 antibodies, (i) completely prevents the rapid decline of second-messenger signals (desensitization) that follows odorant stimulation and (ii) strongly inhibits odorant-induced phosphorylation of olfactory ciliary proteins. In contrast, beta ARK-1 antibodies are without effect. Inhibitors of protein kinase A and protein kinase C also block odorant-induced desensitization and phosphorylation. These data suggest that a sequential interplay of second-messenger-dependent and receptor-specific kinases is functionally involved in olfactory desensitization.

Adrenergic receptors. Models for regulation of signal transduction processes.

Adrenergic receptors are prototypic models for the study of the relations between structure and function of G protein-coupled receptors. Each receptor is encoded by a distinct gene. These receptors are integral membrane proteins with several striking structural features. They consist of a single subunit containing seven stretches of 20-28 hydrophobic amino acids that represent potential membrane-spanning alpha-helixes. Many of these receptors share considerable amino acid sequence homology, particularly in the transmembrane domains. All of these macromolecules share other similarities that include one or more potential sites of extracellular N-linked glycosylation near the amino terminus and several potential sites of regulatory phosphorylation that are located intracellularly. By using a variety of techniques, it has been demonstrated that various regions of the receptor molecules are critical for different receptor functions. The seven transmembrane regions of the receptors appear to form a ligand-binding pocket. Cysteine residues in the extracellular domains may stabilize the ligand-binding pocket by participating in disulfide bonds. The cytoplasmic domains contain regions capable of interacting with G proteins and various kinases and are therefore important in such processes as signal transduction, receptor-G protein coupling, receptor sequestration, and down-regulation. Finally, regions of these macromolecules may undergo posttranslational modifications important in the regulation of receptor function. Our understanding of these complex relations is constantly evolving and much work remains to be done. Greater understanding of the basic mechanisms involved in G protein-coupled, receptor-mediated signal transduction may provide leads into the nature of certain pathophysiological states.

Autophagy enhances NFκB activity in specific tissue macrophages by sequestering A20 to boost antifungal immunity.

Immune responses must be well restrained in a steady state to avoid excessive inflammation. However, such restraints are quickly removed to exert antimicrobial responses. Here we report a role of autophagy in an early host antifungal response by enhancing NFκB activity through A20 sequestration. Enhancement of NFκB activation is achieved by autophagic depletion of A20, an NFκB inhibitor, in F4/80(hi) macrophages in the spleen, peritoneum and kidney. We show that p62, an autophagic adaptor protein, captures A20 to sequester it in the autophagosome. This allows the macrophages to release chemokines to recruit neutrophils. Indeed, mice lacking autophagy in myeloid cells show higher susceptibility to Candida albicans infection due to impairment in neutrophil recruitment. Thus, at least in the specific aforementioned tissues, autophagy appears to break A20-dependent suppression in F4/80(hi) macrophages, which express abundant A20 and contribute to the initiation of efficient innate immune responses.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

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.