Developing Algorithms for Quantifying the Super Resolution Microscopic Data: Applications to the Quantification of Protein-Reorganization in Bacteria Responding to Treatment by Silver Ions

Histone-like nucleoid structuring proteins (HNS) play significant roles in shaping the chromosomal DNA, regulation of transcriptional networks in microbes, as well as bacterial responses to environmental changes such as temperature fluctuations. In this work, the intracellular organization of HNS proteins in E. coli bacteria was investigated utilizing super-resolution fluorescence microscopy, which surpasses conventional microscopy by 10–20 fold in spatial resolution. More importantly, the changes of the spatial distribution of HNS proteins in E. coli, by addition of silver ions into the growth medium were explored. To quantify the spatial distribution of HNS in bacteria and its changes, an automatic method based on Voronoi diagram was implemented. The HNS proteins localized in super-resolution fluorescence microscopy were segmented and clustered based on several quantitative parameters, such as molecular areas, molecular densities, and mean inter-molecular distances of the k-th rank, all of which were computed from the Voronoi diagrams. These parameters, as well as the associated clustering analysis, allowed us to quantify how the spatial organization of HNS proteins responds to silver, and provided insight into understanding how microbes adapt to new environments

Light-Weight Structural Optimization Through Biomimicry, Machine Learning, and Inverse Design

In load-bearing lightweight architectures, cellular materials were frequently utilized. While octahedron, tetrahedron, and octet truss lattice truss were built for lightweight architectures with stretching and flexural dominance, it can be believed that new cells could easily be designed that might perform much better than the present ones in terms of mechanical and architectural characteristics. Machine learning-based structure scouting and design improvisation for better mechanical performance is a growing field of study. Additionally, biomimicry—the science of imitating nature’s elements—offers people a wealth of resources from which to draw motivation as they work to create a better quality of life. Here, utilizing machine learning approaches, novel lattice truss unit cellular architectures with enhanced architectural characteristics were designed. An inverse design methodology employing generative adversarial networks is suggested to investigate and improvise the lightweight lattice truss unit cellular architectures. The proposed framework was utilized to identify various lattice truss unit cellular architectures with load carrying capacities 40–120% greater than those of octet unit cells. A further 130–160% raise in buckling load bearing capacity was made possible by substituting porous biomimicry columns for the solid trusses in the light-weight lattice truss unit cellular architectures. This dissertation\u27s main goal is to investigate various improvisation strategies for creating lightweight architectures, particularly when using data analysis and machine learning methods. Lightweight cellular architectures with thin-walls and lattice truss unit cellular architectures with improved shape memory capabilities were created using the knowledge gleaned from numerous of the research projects mentioned in the preceding paragraphs load-bearing architectures and devices, lightweight architecture with shape memory and with better strength, better stretchability, and better elastic stress recovery are widely desired. As compared to the bulk shape memory polymeric cylinders, the cellular architectures with thin walls show 200% betterer elastic stress recovery that is normalized with respect to base designs. The architectural improvisation of many other additional designs and practical implementation can be accomplished using the inverse design framework

Development of novel imaging biomarkers using positron emission tomography for characterization of malignant phenotype and response evaluation

Positron emission tomography (PET) enables noninvasive tumour imaging, as changes in metabolic activity secondary to therapy can be measured before changes in tumour size are evident on standard anatomic imaging. Two imaging approaches representing proliferation dependent and independent technologies are evolving as potential methods for assessing growth signalling and, thus, treatment response: [18F]3’-deoxy-3’-fluorothymidine (FLT) and [11C]choline. The validity of the former in patients with pancreatic cancer is unproven and likewise, the role of the latter in response to androgen deprivation/radiotherapy in prostate cancer (PCa) remains unexplored. Using a variety of approaches, the aim of this thesis was to provide an understanding of the role of these tracers in lesion detection and response assessment in patients by PET/computed tomography (PET/CT). Given the high physiological hepatic localisation of FLT, a recently reported kinetic spatial filtering (KSF) algorithm was evaluated as a way to de-noise abdominal FLT-PET data from patients with advanced pancreatic cancer. Application of KSF led to improved lesion detection. FLT uptake (SUV60,max) significantly increased in mid-treatment (gemcitabine based) progressors (p=0.04). In this limited number of patients, reduction in FLT uptake did not predict overall survival. The role of [11C]choline PET/CT in lesion detection and response in prostate cancer (PCa) was also investigated using semi-quantitative and quantitative methods. As a prelude to the quantitative imaging studies, it was established that irreversible tracer uptake characterised tumour (breast cancer) [11C]choline kinetics. Similar irreversible uptake characterised PCa. An important finding was that tumour [11C]choline uptake (in 29 PCa patients) correlated with choline kinase (CHK) expression but not proliferation, as assessed by Ki67 labelling index. Immunohistochemistry of the above patients’ prostate cores with CHKα antibody demonstrated a spectrum of CHKα expression, ranging from expression in prostatic-intraepithelial-neoplasia to low to high expression in malignant cores. These findings were further corroborated in a larger cohort of 75 malignant cores derived from non-imaging studies. Having established [11C]choline as a proliferation independent marker of growth, its role in assessing treatment response was investigated. [11C]choline PET was sensitive to metabolic changes within prostate tumours following androgen deprivation and radical radiotherapy. While promising data were obtained with [11C]choline PET, the radiotracer is subject to metabolic degradation complicating data analysis. To this end, a novel metabolically stable analogue of choline ([18F]fluoromethyl-[1,2-2H4]-choline ([18F]D4FCH)) was transitioned into volunteers and patients to study its pharmacokinetics and preliminary diagnostic potential. This tracer embodies deuterium isotope substitution as a means to discourage systemic metabolism. The radiotracer had favourable dosimetry (effective-dose: 0.025mSv/MBq) and safety. Preliminary results in non-small cell lung cancer showed that the tracer is taken up in tumours. Further studies are warranted to characterise this new tracer in different tumour types. As a prelude to imaging cancer cell death in tumours, a caspase-3 specific radiotracer, [18F](S)-1-((1-(2-fluoroethyl)-1H-[1,2,3]-triazol-4-yl)methyl)-5-(2(2,4- difluorophenoxymethyl)-pyrrolidine-1-sulfonyl) isatin ([18F]ICMT-11) was also transitioned into volunteers. The radiotracer had favourable dosimetry (effective-dose: 0.025mSv/MBq) and safety. In summary, FLT-PET/CT combined with KSF and [11C]choline PET/CT were shown to be promising methods for imaging early treatment response in patients. Further work will be required to evaluate the clinical relevance of these data in terms of overall patient outcome. Furthermore, a new choline-based radiotracer and a caspase-3 specific radiotracer have been transitioned into humans.Open Acces

Positron emission tomography imaging of tumor cell metabolism and application to therapy response monitoring

Cancer cells do reprogram their energy metabolism to enable several functions, such as generation of biomass including membrane biosynthesis, and overcoming bioenergetic and redox stress. In this article, we review both established and evolving radioprobes developed in association with positron emission tomography (PET) to detect tumor cell metabolism and effect of treatment. Measurement of enhanced tumor cell glycolysis using 2-deoxy-2-[(18)F]fluoro-D-glucose is well established in the clinic. Analogs of choline, including [(11)C]choline and various fluorinated derivatives are being tested in several cancer types clinically with PET. In addition to these, there is an evolving array of metabolic tracers for measuring intracellular transport of glutamine and other amino acids or for measuring glycogenesis, as well as probes used as surrogates for fatty acid synthesis or precursors for fatty acid oxidation. In addition to providing us with opportunities for examining the complex regulation of reprogramed energy metabolism in living subjects, the PET methods open up opportunities for monitoring pharmacological activity of new therapies that directly or indirectly inhibit tumor cell metabolism

Continuous Hands-off Control by CLOT Norm Minimization

In this paper, we consider hands-off control via minimization of the C LOT (Combined L -One and Two) norm. The maximum hands-off control is the L 0 -optimal (or the sparsest) control among all feasible controls that are bounded b y a specified value and transfer the state from a given initial state to the origin within a fixed time dura tion. In general, the maximum hands-off control is a bang-off-bang control taking value s of ± 1 and 0. For many real applications, such discontinuity in the control is not desirable. To ob tain a continuous but still relatively sparse control, we propose to use the CLOT norm, a conv ex combination of L 1 and L 2 norms. We show by numerical simulation that the CLOT control is con tinuous and much sparser (i.e. has longer time duration on which the control takes 0) than the conventional EN (elastic net) control, which is a convex combination of L 1 and squared L 2 norms

Uloga moderne anti-androgene terapije u liječenju lokaliziranog raka prostate

Anti-androgen therapy continues to be a basic pilar of treatment for both localized and metastatic prostate cancer. The advent of new generation of androgen receptor targeted agents (ARTA) transformed the care of patients with advanced disease. After such a success, the steps were taken to incorporate a new generation of ARTAs into the treatment landscape of localized prostate cancer. High-risk prostate cancer represents the most aggressive form of localized disease with significant metastatic potential and poor outcome. Here, the impact of novel therapies will likely be profound and transforming. This clinical space has already been a showcase for multidisciplinary treatment where the combination of local therapies with systemic treatment gradually improved patient outcomes and the chances of cure. The most recent step in redefining the treatment of localized disease is the adoption of novel ARTAs moving forward the multidisciplinary platform. In this narrative review, we discuss current clinical evidence supporting the use of novel ARTAs in patients with localized high-risk prostate cancer and cover recent developments in biomarker-driven strategies for treatment individualization in this clinical context.Anti-androgena terapija je temelj liječenja lokaliziranog i uznapredovalog raka prostate. Dolazak nove generacije lijekova koji inhibiraju androgenu osovinu preobrazila je liječenje bolesnika sa uznapredovalim rakom prostate. Temeljem uspjeha u uznapredovaloj bolesti, u tijeku su napori da se nova generacija anti-androgenih lijekova inkorporira u liječenje lokalizirane bolesti. Visokorizičan rak prostate predstavlja najagresivniji oblik lokalizirane bolesti sa značajnim metastatskim potencijalom. Za očekivati je da će u ovom stadiju utjecaj novih terapija biti preobražavajući. Lokalizirani visokorizični rak prostate se liječi multidisciplinarno. Tu su kombinacije lokalnog liječenja i sustavne terapije postepeno popravljale ishode liječenja i omogućavale priliku za izliječenje. Zadnji napor predstavlja usvajanje novih anti-androgenih terapija. U ovom preglednom članku razmatramo kliničke dokaze za upotrebu nove generacije anti-adrogene terapije u bolesnika sa lokaliziranim visokorizičnim rakom prostate i dajemo pregled zadnjih strategija za personalizaciju liječenja

Building Formal Thinking with Pupils on Magnetic Phenomena in Conceptual Laboratories

Developing formal thinking and building conceptual knowledge as a background for formal interpretation of phenomena is one of the main challenges in teaching and learning physics. In the context of the experimental exploration of the electromagnetic phenomena, pupils\u2019 conceptual referents and representations of the phenomena and their identification and exploration of conditions to produce electro-magnetic interactions are investigated through semi-structured interview in the framework of Conceptual Laboratories of Operative Exploration. The pupils construct global interpretations of phenomena starting from local interpretations of the single experiments and synthetizing them by means of building the formal abstract entities

Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy

We report a robust nonparametric descriptor,&nbsp;J&prime;(r), for quantifying the density of clustering molecules in single-molecule localization microscopy.&nbsp;J&prime;(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that&nbsp;J&prime;(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. Most importantly, the position of the&nbsp;J&prime;(r) valley () depends exclusively on the density of clustering molecules (&rho;c). Therefore, it is ideal for direct estimation of the clustering density of molecules in single-molecule localization microscopy. As an example, this descriptor was applied to estimate the clustering density of&nbsp;ptsG&nbsp;mRNA in&nbsp;E. coli&nbsp;bacteria.</p