A unified approach to decentralised control based on the exterior algebra and algebraic geometry methods

The aim of the thesis is to provide a unifying framework and tools for the study of a number of control theory problems arising in Decentralised control. These problems are known as frequency assignment problems and they include the decentralised problem of pole assignment by state, output feedback and zero assignment by decentralised squaring-down. It is further shown that decentralised dynamic problems where the dynamic complexity of the controller is fixed , may also be reduced to the same formulation given for the constant Determinantal Assignment Problem(DAP). The unifying mathematical problem studied here is the Decentralised - Determinantal Assignment Problem (D- DAP) which is a special form of the general DAP defined for multivariable systems. The study of D-DAP involves the use of tools from exterior algebra in an essential way and also tools from classical algebraic geometry, specifically the theory of Grassmann varieties. In this thesis the mathematical framework of D-DAP is fully developed and used for the study of pole, zero assignment problems by decentralised constant controllers and new solvability conditions are given. The mathematical framework of D-DAP also allows the study of structural properties of Decentralised controllers. In fact new invariants for decentralised control are introduced in the form of Pliicker matrices and Decentralised Indices and a new characterisation of fixed modes and fixed zeros is given based on tools from exterior algebra. The classical notion of fixed modes, fixed zeros is extended to almost fixed modes, almost fixed zeros for certain families of systems. Finally it is shown that the general framework of D-DAP is suitable for the study of dynamic problems such as pole assignment by decentralised classical controllers of the P-D, P-I, P-I-D type

Cahiers d’études médiévales, 2 : La Science de la nature : théories et pratiques, Montréal, Bellarmin et Paris, Vrin, 1974, 199 p.

Background: Sentinel Lymph Node (SLN) sampling may significantly reduce surgical morbidity by avoiding needless radical lymphadenectomy. In gynaecological cancers, the current practice in the UK is testing the accuracy of SLN detection using radioactive isotopes within the context of clinical trials. However, radioactive tracers pose significant logistic problems. We, therefore, conducted a pilot, observational study to assess the feasibility of a novel optical imaging device for SLN detection in gynaecological cancers using near infrared (NIR) fluorescence. Methods: A novel, custom-made, optical imaging system was developed to enable detection of multiple fluorescence dyes and allow simultaneous bright-field imaging during open surgery and laparoscopic procedures. We then evaluated the performance of the system in a prospective study of 49 women with early stage vulval, cervical and endometrial cancer who were scheduled to undergo complete lymphadenectomy. Clinically approved fluorescent contrast agents indocyanine green (ICG) and methylene blue (MB) were used. The main outcomes of the study included SLN mapping detection rates, false negative rates using the NIR fluorescence technique and safety of the procedures. We also examined the association between injection sites and differential lymphatic drainage in women with endometrial cancer by fluorescence imaging of ICG and MB. Results: A total of 64 SLNs were detected during both open surgery and laparoscopy. Following dose optimisation and the learning phase, SLN detection rate approached 100 % for all cancer types with no false negatives detected. Fluorescence from ICG and MB detected para-aortic SLNs in women with endometrial cancer following uterine injection. Percutaneous SLN detection was also achieved in most women with vulval cancer. No adverse reactions associated with the use of either dyes were observed. Conclusions: This study demonstrated the successful clinical application of a novel NIR fluorescence imaging system for SLN detection across different gynaecological cancers. We showcased the first in human imaging, during the same procedure, of two fluorescence dyes in women with endometrial cancer. </p

Suppression of cancer stemness p21-regulating mRNA and microRNA signatures in recurrent ovarian cancer patient samples

<p>Abstract</p> <p>Background</p> <p>Malignant ovarian disease is characterised by high rates of mortality due to high rates of recurrent chemoresistant disease. Anecdotal evidence indicates this may be due to chemoresistant properties of cancer stem cells (CSCs). However, our understanding of the role of CSCs in recurrent ovarian disease remains sparse. In this study we used gene microarrays and meta-analysis of our previously published microRNA (miRNA) data to assess the involvement of cancer stemness signatures in recurrent ovarian disease.</p> <p>Methods</p> <p>Microarray analysis was used to characterise early regulation events in an embryonal carcinoma (EC) model of cancer stemness. This was then compared to our previously published microarray data from a study of primary versus recurrent ovarian disease. In parallel, meta-analysis was used to identify cancer stemness miRNA signatures in tumor patient samples.</p> <p>Results</p> <p>Microarray analysis demonstrated a 90% difference between gene expression events involved in early regulation of differentiation in murine EC (mEC) and embryonic stem (mES) cells. This contrasts the known parallels between mEC and mES cells in the undifferentiated and well-differentiated states. Genelist comparisons identified a cancer stemness signature set of genes in primary versus recurrent data, a subset of which are known p53-p21 regulators. This signature is present in primary and recurrent or in primary alone but essentially never in recurrent tumors specifically. Meta-analysis of miRNA expression showed a much stronger cancer stemness signature within tumor samples. This miRNA signature again related to p53-p21 regulation and was expressed prominently in recurrent tumors. Our data indicate that the regulation of p53-p21 in ovarian cancer involves, at least partially, a cancer stemness component.</p> <p>Conclusion</p> <p>We present a p53-p21 cancer stemness signature model for ovarian cancer. We propose that this may, at least partially, differentially regulate the p53-p21 mechanism in ovarian disease. Targeting CSCs within ovarian cancer represents a potential therapeutic avenue.</p

Platelet adhesion and degranulation induce pro-survival and pro-angiogenic signalling in ovarian cancer cells

Thrombosis is common in ovarian cancer. However, the interaction of platelets with ovarian cancer cells has not been critically examined. To address this, we investigated platelet interactions in a range of ovarian cancer cell lines with different metastatic potentials [HIO-80, 59M, SK-OV-3, A2780, A2780cis]. Platelets adhered to ovarian cancer cells with the most significant adhesion to the 59M cell line. Ovarian cancer cells induced platelet activation [P-selectin expression] in a dose dependent manner, with the most significant activation seen in response to the 59M cell line. The platelet antagonists [cangrelor, MRS2179, and apyrase] inhibited 59M cell induced activation suggesting a P2Y12 and P2Y1 receptor mediated mechanism of platelet activation dependent on the release of ADP by 59M cells. A2780 and 59M cells potentiated PAR-1, PAR-4, and TxA2 receptor mediated platelet activation, but had no effect on ADP, epinephrine, or collagen induced activation. Analysis of gene expression changes in ovarian cancer cells following treatment with washed platelets or platelet releasate showed a subtle but valid upregulation of anti-apoptotic, anti-autophagy pro-angiogenic, pro-cell cycle and metabolic genes. Thus, ovarian cancer cells with different metastatic potential adhere and activate platelets differentially while both platelets and platelet releasate mediate pro-survival and pro-angiogenic signals in ovarian cancer cells

Platelet adhesion and degranulation induce pro-survival and pro-angiogenic signalling in ovarian cancer cells

Thrombosis is common in ovarian cancer. However, the interaction of platelets with ovarian cancer cells has not been critically examined. To address this, we investigated platelet interactions in a range of ovarian cancer cell lines with different metastatic potentials [HIO-80, 59M, SK-OV-3, A2780, A2780cis]. Platelets adhered to ovarian cancer cells with the most significant adhesion to the 59M cell line. Ovarian cancer cells induced platelet activation [P-selectin expression] in a dose dependent manner, with the most significant activation seen in response to the 59M cell line. The platelet antagonists [cangrelor, MRS2179, and apyrase] inhibited 59M cell induced activation suggesting a P2Y12 and P2Y1 receptor mediated mechanism of platelet activation dependent on the release of ADP by 59M cells. A2780 and 59M cells potentiated PAR-1, PAR-4, and TxA2 receptor mediated platelet activation, but had no effect on ADP, epinephrine, or collagen induced activation. Analysis of gene expression changes in ovarian cancer cells following treatment with washed platelets or platelet releasate showed a subtle but valid upregulation of anti-apoptotic, anti-autophagy pro-angiogenic, pro-cell cycle and metabolic genes. Thus, ovarian cancer cells with different metastatic potential adhere and activate platelets differentially while both platelets and platelet releasate mediate pro-survival and pro-angiogenic signals in ovarian cancer cells

Immune Checkpoint Inhibitors Targeting the PD-1/PD-L1 Pathway in Advanced, Recurrent Endometrial Cancer: A Scoping Review with SWOT Analysis

Results of recent clinical trials using the immune check point inhibitors (ICI) pembrolizumab or dostarlimab with/without lenvatinib has led to their approval for specific molecular subgroups of advanced recurrent endometrial cancer (EC). Herein, we summarise the clinical data leading to this first tissue-agnostic approval. As this novel therapy is not yet available in the United Kingdom standard care setting, we explore the strengths, weaknesses, opportunities, and threats (SWOT) of ICI treatment in EC. Major databases were searched focusing on clinical trials using programmed cell death protein 1 (PD-1) and its ligand (PD-L1) ICI which ultimately contributed to anti-PD-1 approval in EC. We performed a data quality assessment, reviewing survival and safety analysis. We included 15 studies involving 1609 EC patients: 458 with mismatch repair deficiency (MMRd)/microsatellite instability-high (MSI-H) status and 1084 with mismatch repair proficiency/microsatellite stable (MMRp/MSS) status. Pembrolizumab/dostarlimab have been approved for MMRd ECs, with the addition of lenvatinib for MMRp cases in the recurrent setting. Future efforts will focus on the pathological assessment of biomarkers to determine molecular phenotypes that correlate with response or resistance to ICI in order to identify patients most likely to benefit from this treatment

Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning

Introduction Accurate prediction of patient prognosis can be especially useful for the selection of best treatment protocols. Machine Learning can serve this purpose by making predictions based upon generalizable clinical patterns embedded within learning datasets. We designed a study to support the feature selection for the 2-year prognostic period and compared the performance of several Machine Learning prediction algorithms for accurate 2-year prognosis estimation in advanced-stage high grade serous ovarian cancer (HGSOC) patients. Methods The prognosis estimation was formulated as a binary classification problem. Dataset was split into training and test cohorts with repeated random sampling until there was no significant difference (p = 0.20) between the two cohorts. A ten-fold cross-validation was applied. Various state-of-the-art supervised classifiers were used. For feature selection, in addition to the exhaustive search for the best combination of features, we used the-chi square test of independence and the MRMR method. Results Two hundred nine patients were identified. The model's mean prediction accuracy reached 73%. We demonstrated that Support-Vector-Machine and Ensemble Subspace Discriminant algorithms outperformed Logistic Regression in accuracy indices. The probability of achieving a cancer-free state was maximised with a combination of primary cytoreduction, good performance status and maximal surgical effort (AUC 0.63). Standard chemotherapy, performance status, tumour load and residual disease were consistently predictive of the mid-term overall survival (AUC 0.63–0.66). The model recall and precision were greater than 80%. Conclusion Machine Learning appears to be promising for accurate prognosis estimation. Appropriate feature selection is required when building an HGSOC model for 2-year prognosis prediction. We provide evidence as to what combination of prognosticators leads to the largest impact on the HGSOC 2-year prognosis

Regulation of microRNA biosynthesis and expression in 2102Ep embryonal carcinoma stem cells is mirrored in ovarian serous adenocarcinoma patients

<p>Abstract</p> <p>Background</p> <p>Tumours with high proportions of differentiated cells are considered to be of a lower grade to those containing high proportions of undifferentiated cells. This property may be linked to the differentiation properties of stem cell-like populations within malignancies. We aim to identify molecular mechanism associated with the generation of tumours with differing grades from malignant stem cell populations with different differentiation potentials. In this study we assessed microRNA (miRNA) regulation in two populations of malignant Embryonal Carcinoma (EC) stem cell, which differentiate (NTera2) or remain undifferentiated (2102Ep) during tumourigenesis, and compared this to miRNA regulation in ovarian serous carcinoma (OSC) patient samples.</p> <p>Methods</p> <p>miRNA expression was assessed in NTera2 and 2102Ep cells in the undifferentiated and differentiated states and compared to that of OSC samples using miRNA qPCR.</p> <p>Results</p> <p>Our analysis reveals a substantial overlap between miRNA regulation in 2102Ep cells and OSC samples in terms of miRNA biosynthesis and expression of mature miRNAs, particularly those of the miR-17/92 family and clustering to chromosomes 14 and 19. In the undifferentiated state 2102Ep cells expressed mature miRNAs at up to 15,000 fold increased levels despite decreased expression of miRNA biosynthesis genes Drosha and Dicer. 2102Ep cells avoid differentiation, which we show is associated with consistent levels of expression of miRNA biosynthesis genes and mature miRNAs while expression of miRNAs clustering to chromosomes 14 and 19 is deemphasised. OSC patient samples displayed decreased expression of miRNA biosynthesis genes, decreased expression of mature miRNAs and prominent clustering to chromosome 14 but not 19. This indicates that miRNA biosynthesis and levels of miRNA expression, particularly from chromosome 14, are tightly regulated both in progenitor cells and in tumour samples.</p> <p>Conclusion</p> <p>miRNA biosynthesis and expression of mature miRNAs, particularly the miR-17/92 family and those clustering to chromosomes 14 and 19, are highly regulated in both progenitor cells and tumour samples. Strikingly, 2102Ep cells are not simply malfunctioning but respond to differentiation specifically, a mechanism that is highly relevant to OSC samples. Our identification and future manipulation of these miRNAs may facilitate generation of lower grade malignancies from these high-grade cells.</p