Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

© 2017 The Author(s). This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis

Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer

© 2020, Springer Nature Switzerland AG. The aim of this paper is to build a computer based clinical decision support tool using a semi-supervised framework, the Fisher Information Network (FIN), for visualization of a set of mammographic images. The FIN organizes the images into a similarity network from which, for any new image, reference images that are closely related can be identified. This enables clinicians to review not just the reference images but also ancillary information e.g. about response to therapy. The Fisher information metric defines a Riemannian space where distances reflect similarity with respect to a given probability distribution. This metric is informed about generative properties of data, and hence assesses the importance of directions in space of parameters. It automatically performs feature relevance detection. This approach focusses on the interpretability of the model from the standpoint of the clinical user. Model predictions were validated using the prevalence of classes in each of the clusters identified by the FIN

Transport properties of copper phthalocyanine based organic electronic devices

Ambipolar charge carrier transport in Copper phthalocyanine (CuPc) is studied experimentally in field-effect transistors and metal-insulator-semiconductor diodes at various temperatures. The electronic structure and the transport properties of CuPc attached to leads are calculated using density functional theory and scattering theory at the non-equilibrium Green's function level. We discuss, in particular, the electronic structure of CuPc molecules attached to gold chains in different geometries to mimic the different experimental setups. The combined experimental and theoretical analysis explains the dependence of the mobilityand the transmission coefficient on the charge carrier type (electrons or holes) and on the contact geometry. We demonstrate the correspondence between our experimental results on thick films and our theoretical studies of single molecule contacts. Preliminary results for fluorinated CuPc are discussed.Comment: 18 pages, 16 figures; to be published in Eur. Phys. J. Special Topic

Recent Updates on the Melanin-Concentrating Hormone (MCH) and Its Receptor System: Lessons from MCH1R Antagonists

Melanin-concentrating hormone (MCH) is a 19-amino-acid cyclic peptide which was originally found to lighten skin color in fish that is highly conserved among many species. MCH interacts with two G-protein-coupled receptors, MCH1R and MCH2R, but only MCH1R is expressed in rodents. MCH is mainly synthesized in the lateral hypothalamus and zona incerta, while MCH1R is widely expressed throughout the brain. Thus, MCH signaling is implicated in the regulation of many physiological functions. The identification of MCH1R has led to the development of small-molecule MCH1R antagonists that can block MCH signaling. MCH1R antagonists are useful not only for their potential therapeutic value, but also for understanding the physiological functions of the endogenous MCH system. Here, we review the physiological functions of the MCH system which have been investigated using MCH1R antagonists such as food intake, anxiety, depression, reward, and sleep. This will help us understand the physiological functions of the MCH system and suggest some of the potential applications of MCH1R antagonists in human disorders

Optimization of insect cell based protein production processes - online monitoring, expression systems, scale-up

Due to the increasing use of insect cell based expression systems in research and industrial recombinant protein production, the development of efficient and reproducible production processes remains a challenging task. In this context, the application of online monitoring techniques is intended to ensure high and reproducible product qualities already during the early phases of process development. In the following chapter, the most common transient and stable insect cell based expression systems are briefly introduced. Novel applications of insect cell based expression systems for the production of insect derived antimicrobial peptides/proteins (AMPs) are discussed using the example of G. mellonella derived gloverin. Suitable in situ sensor techniques for insect cell culture monitoring in disposable and common bioreactor systems are outlined with respect to optical and capacitive sensor concepts. Since scale-up of production processes is one of the most critical steps in process development, a conclusive overview is given about scale up aspects for industrial insect cell culture processes

Effect of Nitrogen, Potassium, Magnesium and Zinc Sulfates on Yield and Some Characteristics of Biodiesel Produced from Safflower

In order to evaluate the effect of different amounts of nitrogen fertilizer, potassium sulfate, magnesium sulfate and zinc sulfate on biodiesel produced from safflower, a field experiment was carried out as completely randomized blocks design with three replications, at Research Farm of Shahrekord University in 2010. Treatments included nitrogen fertilizer at three levels (150, 200 and 300 kg/ha), potassium, magnesium and zinc sulfates at 150, 100 and 50 kg/ha, respectively, and control (no fertilizer application). By nourishing the safflower plants, the seed yield and biodiesel traits such as density, iodine value and saponification value were measured. The results showed that the seed yield under treatment of 300 kg/ha nitrogen (913 kg/ha) was greater than other treatments. Magnesium sulfate and potassium sulfate produced the highest oil percentage (32.84 and 32.5, respectively). The biodiesel production under utilization of potassium sulfate had greater density, iodine value and saponification value (867.25 kg/m3, 139.7 mg iodine per 100 g oil, and 190.6 mg sodium hydroxide per g oil, respectively) compared to other treatments. In general, it was concluded that application of micronutrient fertilizers (especially potassium sulfate) improves seed-oil and biodiesel characteristics of safflower

Heritability and Relationship among Durum Wheat Quality Traits Using a Recombinant Inbred Lines Population

Traits related to seed quality have an important role in production of durum wheat. To estimate the heritability of protein content, semolina content, Zeleny number, seed hardness, SDS, dry and fresh gluten content, gluten index, and also to investigate the relationship of these traits in durum wheat, a recombinant inbred lines (RILs) population including 94 recombinant inbred lines (F10), two parents (Ac. Navigator and G9580B-FE1C) and four controls (Diper, Preion and PI10235 varieties and a local variety “Ajr”) were evaluated. This experiment was carried out in the Research Farm of Shahrekord University, Shahrekord, Iran, using a triple lattice design.. Results showed that frequency distribution for gluten index was bimodal and for the rest of the traits was normal. This indicated the two-genes control and quantitative inheritance of these traits in the population,respectively. Transgressive segregation was observed for all the traits. The calculated heritability for protein content, seed hardness, SDS and semolina content was in the low range of 11.4-24.7%. For fresh and dry gluten and Zeleny number, it was 45, 36.2 and 37.1%, respectively. For gluten index, it was high (76.6%). The genetic correlation coefficient between protein content and Zeleny number was positive and high (r= 0.98), which indicates the suitability of this trait as a criterion for protein content. The results of path analysis for semolina, as the main feature in pasta production, based on genetic correlation coefficients, showed that the highest negative direct effect was related to Zeleny number the highest positive effect was related to protein content, which indicated the importance of these traits in explaining the semolina yield