Response of Laser-Induced Thermal Lens Effect at Solid Surface

Recently Kuo et al. [1,2] and Satio et al.[3] presented the surface-thermal lens (STL) technique, this novel photothermal deformation technique has attracted great attention because it is a highly sensitive, noncontact and nondestructive measurement[4–6]. In this technique, a modulated pump beam is focused on the sample surface to produce the surface deformation and a cw probe beam is incident at the deformation region. Differing from the conventional photothermal deformation techniques, the spot size of the probe beam at the sample surface is much larger than the pump beam one. Then the probe beam reflected from the surface produces a diffraction pattern at the detection plane. More recently, STL technique has been successfully applied to study the temperature dependence of the thermal conductivity of semiconductor materials[5], weak absorption of optical thin films[6] and characterization of the solid materials[7,8]. However, the mechanism of STL phenomena has not been completely understood. Most theoretical models took no account of the influence of the air-thermal lens (ATL), although some experiment showed that the air significantly affected the detected diffraction pattern[2]. In addition, it is necessary to characterize frequency responses of signals because the response is used to determine the thermal property of the solid materials[5]

Photothermal Length Measurement of Vickers Cracks in SI3N4

Ceramic materials are gaining ever increasing popularity in different high—technology applications, especially in those where high temperatures are used. However, the mechanical strength of ceramics has thus far set limitations on their utilizing. The critical size of cracks in ceramic material depends on the force applied, but in typical applications it is less than 100 µm. This small size in addition to the fact that critical cracks are often closed makes the use of conventional NDT methods in crack detection very difficult or even impossible. More nuisance comes from the porosity of the material which takes methods needing immersing in liquids out of consideration

Reduced suppressive effect of beta(2)-adrenoceptor agonist on fibrocyte function in severe asthma

Background Patients with severe asthma have increased airway remodelling and elevated numbers of circulating fibrocytes with enhanced myofibroblastic differentiation capacity, despite being treated with high doses of corticosteroids, and long acting β2-adrenergic receptor (AR) agonists (LABAs). We determined the effect of β2-AR agonists, alone or in combination with corticosteroids, on fibrocyte function. Methods Non-adherent non-T cells from peripheral blood mononuclear cells isolated from healthy subjects and patients with non-severe or severe asthma were treated with the β2-AR agonist, salmeterol, in the presence or absence of the corticosteroid dexamethasone. The number of fibrocytes (collagen I+/CD45+ cells) and differentiating fibrocytes (α-smooth muscle actin+ cells), and the expression of CC chemokine receptor 7 and of β2-AR were determined using flow cytometry. The role of cyclic adenosine monophosphate (cAMP) was elucidated using the cAMP analogue 8-bromoadenosine 3′,5′-cyclic monophosphate (8-Br-cAMP) and the phosphodiesterase type IV (PDE4) inhibitor, rolipram. Results Salmeterol reduced the proliferation, myofibroblastic differentiation and CCR7 expression of fibrocytes from healthy subjects and non-severe asthma patients. Fibrocytes from severe asthma patients had a lower baseline surface β2-AR expression and were relatively insensitive to salmeterol but not to 8-Br-cAMP or rolipram. Dexamethasone increased β2-AR expression and enhanced the inhibitory effect of salmeterol on severe asthma fibrocyte differentiation. Conclusions Fibrocytes from patients with severe asthma are relatively insensitive to the inhibitory effects of salmeterol, an effect which is reversed by combination with corticosteroids

Laser Thermomechanical Evaluation of Bonding Integrity

Thermal imaging for the nondestructive evaluation (NDE) of materials appears to be of ever increasing importance for industrial applications. The development of new materials. both metallic and ceramic. as thermal and oxide barrier coatings present new challenges to inspection techniques. Thermal imaging methods seem ideally suited for such applications. being particularly sensitive to surface and near surface material thermal inhomogeneities that may be defect-related. However, these same sophisticated materials can pose rather sever requirements upon the efficacy of any particular type of thermal imaging. Typical problems encountered include rough. optically scattering surfaces. surfaces ranging from highly reflective to absorptive, complex surface geometry and microscopic to very macroscopic (practical components) imaging requirements.</p

Common-path interferometric label-free protein sensing with resonant dielectric nanostructures

Research toward photonic biosensors for point-of-care applications and personalized medicine is driven by the need for high-sensitivity, low-cost, and reliable technology. Among the most sensitive modalities, interferometry offers particularly high performance, but typically lacks the required operational simplicity and robustness. Here, we introduce a common-path interferometric sensor based on guided-mode resonances to combine high performance with inherent stability. The sensor exploits the simultaneous excitation of two orthogonally polarized modes, and detects the relative phase change caused by biomolecular binding on the sensor surface. The wide dynamic range of the sensor, which is essential for fabrication and angle tolerance, as well as versatility, is controlled by integrating multiple, tuned structures in the field of view. This approach circumvents the trade-off between sensitivity and dynamic range, typical of other phase-sensitive modalities, without increasing complexity. Our sensor enables the challenging label-free detection of procalcitonin, a small protein (13 kDa) and biomarker for infection, at the clinically relevant concentration of 1 pg mL−1, with a signal-to-noise ratio of 35. This result indicates the utility for an exemplary application in antibiotic guidance, and opens possibilities for detecting further clinically or environmentally relevant small molecules with an intrinsically simple and robust sensing modality

Disruption of a GATA4/Ankrd1 Signaling Axis in Cardiomyocytes Leads to Sarcomere Disarray: Implications for Anthracycline Cardiomyopathy

Doxorubicin (Adriamycin) is an effective anti-cancer drug, but its clinical usage is limited by a dose-dependent cardiotoxicity characterized by widespread sarcomere disarray and loss of myofilaments. Cardiac ankyrin repeat protein (CARP, ANKRD1) is a transcriptional regulatory protein that is extremely susceptible to doxorubicin; however, the mechanism(s) of doxorubicin-induced CARP depletion and its specific role in cardiomyocytes have not been completely defined. We report that doxorubicin treatment in cardiomyocytes resulted in inhibition of CARP transcription, depletion of CARP protein levels, inhibition of myofilament gene transcription, and marked sarcomere disarray. Knockdown of CARP with small interfering RNA (siRNA) similarly inhibited myofilament gene transcription and disrupted cardiomyocyte sarcomere structure. Adenoviral overexpression of CARP, however, was unable to rescue the doxorubicin-induced sarcomere disarray phenotype. Doxorubicin also induced depletion of the cardiac transcription factor GATA4 in cardiomyocytes. CARP expression is regulated in part by GATA4, prompting us to examine the relationship between GATA4 and CARP in cardiomyocytes. We show in co-transfection experiments that GATA4 operates upstream of CARP by activating the proximal CARP promoter. GATA4-siRNA knockdown in cardiomyocytes inhibited CARP expression and myofilament gene transcription, and induced extensive sarcomere disarray. Adenoviral overexpression of GATA4 (AdV-GATA4) in cardiomyocytes prior to doxorubicin exposure maintained GATA4 levels, modestly restored CARP levels, and attenuated sarcomere disarray. Interestingly, siRNA-mediated depletion of CARP completely abolished the Adv-GATA4 rescue of the doxorubicin-induced sarcomere phenotype. These data demonstrate co-dependent roles for GATA4 and CARP in regulating sarcomere gene expression and maintaining sarcomeric organization in cardiomyocytes in culture. The data further suggests that concurrent depletion of GATA4 and CARP in cardiomyocytes by doxorubicin contributes in large part to myofibrillar disarray and the overall pathophysiology of anthracycline cardiomyopathy

Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets

Comparison of two dependent within subject coefficients of variation to evaluate the reproducibility of measurement devices

<p>Abstract</p> <p>Background</p> <p>The within-subject coefficient of variation and intra-class correlation coefficient are commonly used to assess the reliability or reproducibility of interval-scale measurements. Comparison of reproducibility or reliability of measurement devices or methods on the same set of subjects comes down to comparison of dependent reliability or reproducibility parameters.</p> <p>Methods</p> <p>In this paper, we develop several procedures for testing the equality of two dependent within-subject coefficients of variation computed from the same sample of subjects, which is, to the best of our knowledge, has not yet been dealt with in the statistical literature. The Wald test, the likelihood ratio, and the score tests are developed. A simple regression procedure based on results due to Pitman and Morgan is constructed. Furthermore we evaluate the statistical properties of these methods via extensive Monte Carlo simulations. The methodologies are illustrated on two data sets; the first are the microarray gene expressions measured by two plat- forms; the Affymetrix and the Amersham. Because microarray experiments produce expressions for a large number of genes, one would expect that the statistical tests to be asymptotically equivalent. To explore the behaviour of the tests in small or moderate sample sizes, we illustrated the methodologies on data from computer-aided tomographic scans of 50 patients.</p> <p>Results</p> <p>It is shown that the relatively simple Wald's test (WT) is as powerful as the likelihood ratio test (LRT) and that both have consistently greater power than the score test. The regression test holds its empirical levels, and in some occasions is as powerful as the WT and the LRT.</p> <p>Conclusion</p> <p>A comparison between the reproducibility of two measuring instruments using the same set of subjects leads naturally to a comparison of two correlated indices. The presented methodology overcomes the difficulty noted by data analysts that dependence between datasets would confound any inferences one could make about the differences in measures of reliability and reproducibility. The statistical tests presented in this paper have good properties in terms of statistical power.</p

Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimization

<p>Abstract</p> <p>Background</p> <p>Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization.</p> <p>Methods</p> <p>Gene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied.</p> <p>Results</p> <p>We identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was consistent with a unique subset of luminal A intrinsic type. When molecular subtypes were correlated with recurrence risk predicted by genes of Oncotype and MammaPrint predictors, a significant degree of heterogeneity within the same risk group was noted. This heterogeneity was distributed over several subtypes, suggesting that patients in the same risk groups require different treatment approaches.</p> <p>Conclusions</p> <p>Our results indicate that the molecular subtypes established in this study can be utilized for customization of breast cancer treatment.</p