The ciliary GTPase Arl13b regulates cell migration and cell cycle progression

Funding This work was supported by grants from British Council China (Sino-UK higher Education for PhD studies) to YD and CM, The Carnegie Trust for the Universities of Scotland (70190) and The NHS Grampian Endowment Funds (14/09) to BL, and National Natural Science Foundation of China (31528011) to BL and YD.

Single-cell functional analysis of parathyroid adenomas reveals distinct classes of calcium sensing behaviour in primary hyperparathyroidism.

Primary hyperparathyroidism (PHPT) is a common endocrine neoplastic disorder caused by a failure of calcium sensing secondary to tumour development in one or more of the parathyroid glands. Parathyroid adenomas are comprised of distinct cellular subpopulations of variable clonal status that exhibit differing degrees of calcium responsiveness. To gain a clearer understanding of the relationship among cellular identity, tumour composition and clinical biochemistry in PHPT, we developed a novel single cell platform for quantitative evaluation of calcium sensing behaviour in freshly resected human parathyroid tumour cells. Live-cell intracellular calcium flux was visualized through Fluo-4-AM epifluorescence, followed by in situ immunofluorescence detection of the calcium sensing receptor (CASR), a central component in the extracellular calcium signalling pathway. The reactivity of individual parathyroid tumour cells to extracellular calcium stimulus was highly variable, with discrete kinetic response patterns observed both between and among parathyroid tumour samples. CASR abundance was not an obligate determinant of calcium responsiveness. Calcium EC50 values from a series of parathyroid adenomas revealed that the tumours segregated into two distinct categories. One group manifested a mean EC50 of 2.40 mM (95% CI: 2.37-2.41), closely aligned to the established normal range. The second group was less responsive to calcium stimulus, with a mean EC50 of 3.61 mM (95% CI: 3.45-3.95). This binary distribution indicates the existence of a previously unappreciated biochemical sub-classification of PHPT tumours, possibly reflecting distinct etiological mechanisms. Recognition of quantitative differences in calcium sensing could have important implications for the clinical management of PHPT.

X-linked inhibitor of apoptosis protein mediates tumor cell resistance to antibody-dependent cellular cytotoxicity.

Inflammatory breast cancer (IBC) is the deadliest, distinct subtype of breast cancer. High expression of epidermal growth factor receptors [EGFR or human epidermal growth factor receptor 2 (HER2)] in IBC tumors has prompted trials of anti-EGFR/HER2 monoclonal antibodies to inhibit oncogenic signaling; however, de novo and acquired therapeutic resistance is common. Another critical function of these antibodies is to mediate antibody-dependent cellular cytotoxicity (ADCC), which enables immune effector cells to engage tumors and deliver granzymes, activating executioner caspases. We hypothesized that high expression of anti-apoptotic molecules in tumors would render them resistant to ADCC. Herein, we demonstrate that the most potent caspase inhibitor, X-linked inhibitor of apoptosis protein (XIAP), overexpressed in IBC, drives resistance to ADCC mediated by cetuximab (anti-EGFR) and trastuzumab (anti-HER2). Overexpression of XIAP in parental IBC cell lines enhances resistance to ADCC; conversely, targeted downregulation of XIAP in ADCC-resistant IBC cells renders them sensitive. As hypothesized, this ADCC resistance is in part a result of the ability of XIAP to inhibit caspase activity; however, we also unexpectedly found that resistance was dependent on XIAP-mediated, caspase-independent suppression of reactive oxygen species (ROS) accumulation, which otherwise occurs during ADCC. Transcriptome analysis supported these observations by revealing modulation of genes involved in immunosuppression and oxidative stress response in XIAP-overexpressing, ADCC-resistant cells. We conclude that XIAP is a critical modulator of ADCC responsiveness, operating through both caspase-dependent and -independent mechanisms. These results suggest that strategies targeting the effects of XIAP on caspase activation and ROS suppression have the potential to enhance the activity of monoclonal antibody-based immunotherapy.

Targeting the actin cytoskeleton in HER2+ metastatic cancer cells using a macrolide toxin

Breast and ovarian cancers are among the leading causes of cancer related deaths in women worldwide. In a subset of these cancers, dysregulation of the human epidermal growth factor receptor 2 (HER2) leads to overexpression of the receptor on the cell surface. Previous studies have found that these HER2+ cancers show high rates of progression to metastatic disease. Metastasis is driven by cytoskeletal rearrangements that produce filamentous actin (F-actin) based structures that penetrate and degrade extracellular matrix to facilitate tumour invasion. Advancements in targeted therapy have made F-actin an attractive target for the development of new cancer therapies. In this thesis, we tested the actin-depolymerizing macrolide toxin, Mycalolide B (MycB), as a potential warhead for a novel antibody drug conjugate (ADC) to target highly metastatic HER2+ breast and ovarian cancers. We found that MycB treatment of HER2+ breast (SKBR3, MDA-MB-453) and ovarian (SKOV3) cancer cells led to loss of viability (IC50 values ≤ 64 nM). Sub-lethal doses of MycB treatment caused potent suppression of leading edge protrusions, migration and invasion potential of HER2+ cancer cells (IC50 ≤ 32 nM). In contrast, other F-actin based processes such as receptor endocytosis were less sensitive to MycB treatment. MycB treatment skewed the size of endocytic vesicles, which may reflect defects in F-actin based vesicle motility or maturation. Given that HER2+ cancers have been effectively targeted by Trastuzumab and Trastuzumab-based ADCs, we tested the effects of a combination of Trastuzumab and MycB on cell migration and invasion. We found that MycB/ Trastuzumab combination treatments inhibited motility of SKOV3 cells to a greater degree than either treatment alone. Altogether, our results provide proof-of-principle that actin toxins such as MycB can be used as a novel class of warheads for ADCs to target and combat highly metastatic cancers.

Incidence and clinicobiologic characteristics of leukemic B-cell chronic lymphoproliferative disorders with more than one B-cell clone.

Leukemic B-chronic lymphoproliferative disorders (B-CLPDs) are generally believed to derive from a monoclonal B cell; biclonality has only occasionally been reported. In this study, we have explored the incidence of B-CLPD cases with 2 or more B-cell clones and established both the phenotypic differences between the coexisting clones and the clinicobiologic features of these patients. In total, 53 B-CLPD cases with 2 or more B-cell clones were studied. Presence of 2 or more B-cell clones was suspected by immunophenotype and confirmed by molecular/genetic techniques in leukemic samples (n = 42) and purified B-cell subpopulations (n = 10). Overall, 4.8% of 477 consecutive B-CLPDs had 2 or more B-cell clones, their incidence being especially higher among hairy cell leukemia (3 of 13), large cell lymphoma (2 of 10), and atypical chronic lymphocytic leukemia (CLL) (4 of 29). In most cases the 2 B-cell subsets displayed either different surface immunoglobulin (sIg) light chain (n = 37 of 53) or different levels of the same sIg (n = 9 of 53), usually associated with other phenotypic differences. Compared with monoclonal cases, B-CLL patients with 2 or more clones had lower white blood cell (WBC) and lymphocyte counts, more frequently displayed splenomegaly, and required early treatment. Among these, the cases in which a CLL clone coexisted with a non-CLL clone were older and more often displayed B symptoms, a monoclonal component, and diffuse infiltration of bone marrow and required early treatment more frequently than cases with monoclonal CLL or 2 CLL clones.

Campagna MEDITS 2009 Sub-area Geografica (GSA16) (GSA 16, Stretto di Sicilia): Rapporto Finale campagna Medits 2009

La campagna scientifica Medits, nell’ambito del Programma nazionale Italiano per la raccolta dei dati alieutici (Reg. CE n°199/2008 e n°665/2008), ha l’obiettivo generale di valutare la distribuzione, l’abbondanza e la composizione per taglia delle specie oggetto di pesca presenti nei mari Italiani. L’Istituto di ricerche per l’Ambiente Marino Costiero (IAMC), sede di Mazara del Vallo, del Consiglio nazionale delle Ricerche (CNR), effettua campagne di ricerca in mare nella GSA 16 (FAO, 2001) dello Stretto di Sicilia, tramite rete a strascico (trawl survey), sin dalla primavera del 1985, con l’obiettivo generale di studiare l’abbondanza ed i cicli vitali delle risorse demersali e di stimarne lo stato di sfruttamento. Sono di seguito riportate le informazioni relative alla campagna Medits 2009 (di seguito indicata come MedSp09) nei fondi ricadenti nella GSA 16 (Stretto di Sicilia) che comprendono buona parte dei fondali antistanti il litorale meridionale della Sicilia. La campagna si è svolta tra il 21 maggio ed il 16 giugno 2009 per un totale di 120 cale valide allocate nella GSA 16 (Stretto di Sicilia). Nel presente rapporto sono riportati i risultati sulle percentuali di presenza, sugli indici di abbondanza e sulle strutture di lunghezza degli stock demersali ottenuti nel corso della campagna MEDITS 2009 per le 39 specie bersaglio.

Analysis and modelling of immune cell behaviour in lymph nodes based on multi-photon imaging

This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

Articulation and Clarification of the Dendric Cell Algorithm

The Dendritic Cell algorithm (DCA) is inspired by recent work in innate immunity. In this paper a formal description of the DCA is given. The DCA is described in detail, and its use as an anomaly detector is illustrated within the context of computer security. A port scan detection task is performed to substantiate the influence of signal selection on the behaviour of the algorithm. Experimental results provide a comparison of differing input signal mappings.

Dendritic Cells for SYN Scan Detection

Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and key to the activation of the human immune system, behaviour which has been abstracted to form the Dendritic Cell Algorithm (DCA). In algorithmic terms, individual DCs perform multi-sensor data fusion, asynchronously correlating the fused data signals with a secondary data stream. Aggregate output of a population of cells is analysed and forms the basis of an anomaly detection system. In this paper the DCA is applied to the detection of outgoing port scans using TCP SYN packets. Results show that detection can be achieved with the DCA, yet some false positives can be encountered when simultaneously scanning and using other network services. Suggestions are made for using adaptive signals to alleviate this uncovered problem.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

10 th semester pre-service teacher beliefs and cognitive dissonances : a narrative reflection on efl practice at la Salle University

Tesis (Licenciado en Lenguas Castellana, Inglés y Francés).--Universidad de La Salle. Facultad de Ciencias de La Educación. Licenciatura en Lengua Castellana, Inglés y Francés, 2014

Linfoma primário da vagina – revisão da literatura a propósito de um caso clínico

Os tumores primários malignos da vagina são raros, contribuindo apenas para cerca de 1%-2% dos cancros ginecológicos. O linfoma não-Hodgkin (LNH) primário da vagina é raríssimo (existindo aproximadamente 100 casos descritos na literatura). A sua associação com infecção pelo vírus Epstein Barr (VEB) foi descrita em escassos casos. Os autores pretendem fazer uma revisão da literatura de linfoma primário da vagina, com base num caso clínico de LNH-B de grandes células numa mulher nulípara de 25 anos de idade.

DCA for bot detection

Ensuring the security of computers is a non-trivial task, with many techniques used by malicious users to compromise these systems. In recent years a new threat has emerged in the form of networks of hijacked zombie machines used to perform complex distributed attacks such as denial of service and to obtain sensitive data such as password information. These zombie machines are said to be infected with a dasiahotpsila - a malicious piece of software which is installed on a host machine and is controlled by a remote attacker, termed the dasiabotmaster of a botnetpsila. In this work, we use the biologically inspired dendritic cell algorithm (DCA) to detect the existence of a single hot on a compromised host machine. The DCA is an immune-inspired algorithm based on an abstract model of the behaviour of the dendritic cells of the human body. The basis of anomaly detection performed by the DCA is facilitated using the correlation of behavioural attributes such as keylogging and packet flooding behaviour. The results of the application of the DCA to the detection of a single hot show that the algorithm is a successful technique for the detection of such malicious software without responding to normally running programs.