Multiscale Feature Analysis of Salivary Gland Branching Morphogenesis

Pattern formation in developing tissues involves dynamic spatio-temporal changes in cellular organization and subsequent evolution of functional adult structures. Branching morphogenesis is a developmental mechanism by which patterns are generated in many developing organs, which is controlled by underlying molecular pathways. Understanding the relationship between molecular signaling, cellular behavior and resulting morphological change requires quantification and categorization of the cellular behavior. In this study, tissue-level and cellular changes in developing salivary gland in response to disruption of ROCK-mediated signaling by are modeled by building cell-graphs to compute mathematical features capturing structural properties at multiple scales. These features were used to generate multiscale cell-graph signatures of untreated and ROCK signaling disrupted salivary gland organ explants. From confocal images of mouse submandibular salivary gland organ explants in which epithelial and mesenchymal nuclei were marked, a multiscale feature set capturing global structural properties, local structural properties, spectral, and morphological properties of the tissues was derived. Six feature selection algorithms and multiway modeling of the data was performed to identify distinct subsets of cell graph features that can uniquely classify and differentiate between different cell populations. Multiscale cell-graph analysis was most effective in classification of the tissue state. Cellular and tissue organization, as defined by a multiscale subset of cell-graph features, are both quantitatively distinct in epithelial and mesenchymal cell types both in the presence and absence of ROCK inhibitors. Whereas tensor analysis demonstrate that epithelial tissue was affected the most by inhibition of ROCK signaling, significant multiscale changes in mesenchymal tissue organization were identified with this analysis that were not identified in previous biological studies. We here show how to define and calculate a multiscale feature set as an effective computational approach to identify and quantify changes at multiple biological scales and to distinguish between different states in developing tissues

Quantitative metric profiles capture three-dimensional temporospatial architecture to discriminate cellular functional states

<p>Abstract</p> <p>Background</p> <p>Computational analysis of tissue structure reveals sub-visual differences in tissue functional states by extracting quantitative signature features that establish a diagnostic profile. Incomplete and/or inaccurate profiles contribute to misdiagnosis.</p> <p>Methods</p> <p>In order to create more complete tissue structure profiles, we adapted our cell-graph method for extracting quantitative features from histopathology images to now capture temporospatial traits of three-dimensional collagen hydrogel cell cultures. Cell-graphs were proposed to characterize the spatial organization between the cells in tissues by exploiting graph theory wherein the nuclei of the cells constitute the <it>nodes </it>and the approximate adjacency of cells are represented with <it>edges</it>. We chose 11 different cell types representing non-tumorigenic, pre-cancerous, and malignant states from multiple tissue origins.</p> <p>Results</p> <p>We built cell-graphs from the cellular hydrogel images and computed a large set of features describing the structural characteristics captured by the graphs over time. Using three-mode tensor analysis, we identified the five most significant features (metrics) that capture the compactness, clustering, and spatial uniformity of the 3D architectural changes for each cell type throughout the time course. Importantly, four of these metrics are also the discriminative features for our histopathology data from our previous studies.</p> <p>Conclusions</p> <p>Together, these descriptive metrics provide rigorous quantitative representations of image information that other image analysis methods do not. Examining the changes in these five metrics allowed us to easily discriminate between all 11 cell types, whereas differences from visual examination of the images are not as apparent. These results demonstrate that application of the cell-graph technique to 3D image data yields discriminative metrics that have the potential to improve the accuracy of image-based tissue profiles, and thus improve the detection and diagnosis of disease.</p

Procjena prijelazne stabilnosti dvopodručnog energetskog sustava s CSC-STATCOM-om zasnovanom na LQR-u

A current source converter (CSC) based static synchronous compensator (STATCOM) is a shunt flexible AC transmission system (FACTS) device, which has a vital role as a stability support for small and large transient instability in an interconnected power network. A robust linear quadratic regulator (LQR) based controller for CSC-STATCOM is proposed. In this paper, LQR based CSC-STATCOM is designed to enhance the transient stability of two-area two-machine power system. First of all, modeling &amp; LQR based controller design for CSC-STATCOM are described. After that, the impact of the proposed scheme on the test system with different disturbances is demonstrated. The feasibility of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results show an improvement in the transient stability of power system with CSC-STATCOM. Also, the robustness and effectiveness of CSC-STATCOM are better rather than other shunt FACTS devices (SVC &amp; VSC-STATCOM) in this paper.Statički sinkroni kompenzator (STATCOM) zasnovan na pretvaraču strujnog izvora (CSC) je uređaj za izmjenični prijenos s fleksibilnim "shuntom" (FACTS), koji značajno doprinosi stabilnosti malih i srednjih prijelaznih nestabilnosti u međusobno povezanoj energetskoj mreži. Ovdje je predložen robusni sustav upravljanja zasnovan na linearnom kvadratičnom regulatoru (LQR) za CSC-STATCOM. U ovom radu, CSC-STATCOM zasnovan na LQR-u dizajniran je za povećanje stabilnosti dvopodručnog energetskog sustava s dva motora. Prvo su opisani postupak modeliranja te upravljački sustav zasnovan na LQR-u za CSC-STATCOM. Nakon toga, prikazan je utjecaj predstavljene sheme na ispitni sustav uz prisutnost različitih poremećaja. Provedivost predstavljenog pristupa je prikazana kroz MATLAB simulacije čiji rezultati prikazuju poboljšanje u prijelaznoj stabilnosti energetskog sustava s CSC-STATCOM-om. Također, u ovom radu je prikazana veća robusnost i efikasnost CSC-STATCOM "shunt" FACTS uređaja u odnosu na SVC i VSC-STATCOM

Automatic Tumor-Stroma Separation in Fluorescence TMAs Enables the Quantitative High-Throughput Analysis of Multiple Cancer Biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry

The First Thorough Side-Channel Hardware Trojan

Hardware Trojans have gained high attention in academia, industry and by government agencies. The effective detection mechanisms and countermeasures against such malicious designs are only possible when there is a deep understanding of how hardware Trojans can be built in practice. In this work, we present a mechanism which shows how easily a stealthy hardware Trojan can be inserted in a provably-secure side-channel analysis protected implementation. Once the Trojan is triggered, the malicious design exhibits exploitable side-channel leakage leading to successful key recovery attacks. Such a Trojan does not add or remove any logic (even a single gate) to the design which makes it very hard to detect. In ASIC platforms, it is indeed inserted by subtle manipulations at the sub-transistor level to modify the parameters of a few transistors. The same is applicable on FPGA applications by changing the routing of particular signals, leading to null resource utilization overhead. The underlying concept is based on a secure masked hardware implementation which does not exhibit any detectable leakage. However, by running the device at a particular clock frequency one of the requirements of the underlying masking scheme is not fulfilled anymore, i.e., the Trojan is triggered, and the device\u27s side-channel leakage can be exploited. Although as a case study we show an application of our designed Trojan on an FPGA-based threshold implementation of the PRESENT cipher, our methodology is a general approach and can be applied on any similar circuit

Reconciling d+1 Masking in Hardware and Software

The continually growing number of security-related autonomous devices require efficient mechanisms to counteract low-cost side-channel analysis (SCA) attacks like differential power analysis. Masking provides a high resistance against SCA at an adjustable level of security. A high level of security, however, goes hand in hand with an increasing demand for fresh randomness which also affects other implementation costs. Since software based masking has other security requirements than masked hardware implementations, the research in these fields have been quite separated from each other over the last ten years. One important practical difference is that recently published software based masking schemes show a lower randomness footprint than hardware masking schemes. In this work we combine existing software and hardware based masking schemes into a unified masking approach (UMA). We demonstrate how UMA can be used to protect software and hardware implementations likewise, and for lower randomness costs especially for hardware implementations. Theoretical considerations as well as practical implementation results are then used to compare this unified masking approach to other schemes from different perspectives and at different levels of security

Treatment-specific risk of subsequent malignant neoplasms in five-year survivors of diffuse large B-cell lymphoma

Background: The introduction of rituximab significantly improved the prognosis of diffuse large B-cell lymphoma (DLBCL), emphasizing the importance of evaluating the long-term consequences of exposure to radiotherapy, alkylating agents and anthracycline-containing (immuno)chemotherapy among DLBCL survivors. Methods: Long-term risk of subsequent malignant neoplasms (SMNs) was examined in a multicenter cohort comprising 2373 5-year DLBCL survivors treated at ages 15-61 years in 1989-2012. Observed SMN numbers were compared with expected cancer incidence to estimate standardized incidence ratios (SIRs) and absolute excess risks (AERs/10 000 person-years). Treatment-specific risks were assessed using multivariable Cox regression. Results: After a median follow-up of 13.8 years, 321 survivors developed one or more SMNs (SIR 1.5, 95% CI 1.3-1.8, AER 51.8). SIRs remained increased for at least 20 years after first-line treatment (SIR ≥20-year follow-up 1.5, 95% CI 1.0-2.2, AER 81.8) and were highest among patients ≤40 years at first DLBCL treatment (SIR 2.7, 95% CI 2.0-3.5). Lung (SIR 2.0, 95% CI 1.5-2.7, AER 13.4) and gastrointestinal cancers (SIR 1.5, 95% CI 1.2-2.0, AER 11.8) accounted for the largest excess risks. Treatment with &gt;4500 mg/m2 cyclophosphamide/&gt;300 mg/m2 doxorubicin versus ≤2250 mg/m2/≤150 mg/m2, respectively, was associated with increased solid SMN risk (hazard ratio 1.5, 95% CI 1.0-2.2). Survivors who received rituximab had a lower risk of subdiaphragmatic solid SMNs (hazard ratio 0.5, 95% CI 0.3-1.0) compared with survivors who did not receive rituximab. Conclusion: Five-year DLBCL survivors have an increased risk of SMNs. Risks were higher for survivors ≤40 years at first treatment and survivors treated with &gt;4500 mg/m2 cyclophosphamide/&gt;300 mg/m2 doxorubicin, and may be lower for survivors treated in the rituximab era, emphasizing the need for studies with longer follow-up for rituximab-treated patients.</p

Treatment-specific risk of subsequent malignant neoplasms in five-year survivors of diffuse large B-cell lymphoma

Background: The introduction of rituximab significantly improved the prognosis of diffuse large B-cell lymphoma (DLBCL), emphasizing the importance of evaluating the long-term consequences of exposure to radiotherapy, alkylating agents and anthracycline-containing (immuno)chemotherapy among DLBCL survivors. Methods: Long-term risk of subsequent malignant neoplasms (SMNs) was examined in a multicenter cohort comprising 2373 5-year DLBCL survivors treated at ages 15-61 years in 1989-2012. Observed SMN numbers were compared with expected cancer incidence to estimate standardized incidence ratios (SIRs) and absolute excess risks (AERs/10 000 person-years). Treatment-specific risks were assessed using multivariable Cox regression. Results: After a median follow-up of 13.8 years, 321 survivors developed one or more SMNs (SIR 1.5, 95% CI 1.3-1.8, AER 51.8). SIRs remained increased for at least 20 years after first-line treatment (SIR ≥20-year follow-up 1.5, 95% CI 1.0-2.2, AER 81.8) and were highest among patients ≤40 years at first DLBCL treatment (SIR 2.7, 95% CI 2.0-3.5). Lung (SIR 2.0, 95% CI 1.5-2.7, AER 13.4) and gastrointestinal cancers (SIR 1.5, 95% CI 1.2-2.0, AER 11.8) accounted for the largest excess risks. Treatment with &gt;4500 mg/m2 cyclophosphamide/&gt;300 mg/m2 doxorubicin versus ≤2250 mg/m2/≤150 mg/m2, respectively, was associated with increased solid SMN risk (hazard ratio 1.5, 95% CI 1.0-2.2). Survivors who received rituximab had a lower risk of subdiaphragmatic solid SMNs (hazard ratio 0.5, 95% CI 0.3-1.0) compared with survivors who did not receive rituximab. Conclusion: Five-year DLBCL survivors have an increased risk of SMNs. Risks were higher for survivors ≤40 years at first treatment and survivors treated with &gt;4500 mg/m2 cyclophosphamide/&gt;300 mg/m2 doxorubicin, and may be lower for survivors treated in the rituximab era, emphasizing the need for studies with longer follow-up for rituximab-treated patients.</p