What is Better: GMM of Two Gaussians or Two Clusters With One Gaussian?

In this report, we provide a theoretical discussion on temporal data cluster analysis: does the data come from one source or two sources; is it better to cluster the data into two clusters or leave it as one cluster. Here we analyse only the simplest case: when the data comes from two symmetric Gaussian probability-density-functions (pdfs), i.e., with same variance and same absolute value of the mean, with the same prior probability per Gaussian. The data consists of segments with an a-priori known segment length. It will be shown that if the data belongs to two different Gaussian models, the likelihood of two clusters is always higher or equal than the one of a GMM with two Gaussians for any mean, variance, and segment length. If the data belongs to the GMM, the likelihood of two clusters might be either higher or less than the GMM one

Self-Organizing-Maps With BIC For Speaker Clustering

A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a Self- Organizing-Map (SOM). For estimation of the number of clusters the Bayesian Information Criterion (BIC) is applied. This approach was tested on the NIST 1996 HUB-4 evaluation test in terms of speaker and cluster purities. Results indicate that the combined SOM-BIC approach can lead to better clustering results than the baseline system

The polo-like kinase 1 (PLK1) inhibitor NMS-P937 is effective in a new model of disseminated primary CD56+ acute monoblastic leukaemia

CD56 is expressed in 15–20% of acute myeloid leukaemias (AML) and is associated with extramedullary diffusion, multidrug resistance and poor prognosis. We describe the establishment and characterisation of a novel disseminated model of AML (AML-NS8), generated by injection into mice of leukaemic blasts freshly isolated from a patient with an aggressive CD56+ monoblastic AML (M5a). The model reproduced typical manifestations of this leukaemia, including presence of extramedullary masses and central nervous system involvement, and the original phenotype, karyotype and genotype of leukaemic cells were retained in vivo. Recently Polo-Like Kinase 1 (PLK1) has emerged as a new candidate drug target in AML. We therefore tested our PLK1 inhibitor NMS-P937 in this model either in the engraftment or in the established disease settings. Both schedules showed good efficacy compared to standard therapies, with a significant increase in median survival time (MST) expecially in the established disease setting (MST = 28, 36, 62 days for vehicle, cytarabine and NMS-P937, respectively). Importantly, we could also demonstrate that NMS-P937 induced specific biomarker modulation in extramedullary tissues. This new in vivo model of CD56+ AML that recapitulates the human tumour lends support for the therapeutic use of PLK1 inhibitors in AML

Alpha-particle-induced complex chromosome exchanges transmitted through extra-thymic lymphopoiesis in vitro show evidence of emerging genomic instability

Human exposure to high-linear energy transfer α-particles includes environmental (e.g. radon gas and its decay progeny), medical (e.g. radiopharmaceuticals) and occupational (nuclear industry) sources. The associated health risks of α-particle exposure for lung cancer are well documented however the risk estimates for leukaemia remain uncertain. To further our understanding of α-particle effects in target cells for leukaemogenesis and also to seek general markers of individual exposure to α-particles, this study assessed the transmission of chromosomal damage initially-induced in human haemopoietic stem and progenitor cells after exposure to high-LET α-particles. Cells surviving exposure were differentiated into mature T-cells by extra-thymic T-cell differentiation in vitro. Multiplex fluorescence in situ hybridisation (M-FISH) analysis of naïve T-cell populations showed the occurrence of stable (clonal) complex chromosome aberrations consistent with those that are characteristically induced in spherical cells by the traversal of a single α-particle track. Additionally, complex chromosome exchanges were observed in the progeny of irradiated mature T-cell populations. In addition to this, newly arising de novo chromosome aberrations were detected in cells which possessed clonal markers of α-particle exposure and also in cells which did not show any evidence of previous exposure, suggesting ongoing genomic instability in these populations. Our findings support the usefulness and reliability of employing complex chromosome exchanges as indicators of past or ongoing exposure to high-LET radiation and demonstrate the potential applicability to evaluate health risks associated with α-particle exposure.This work was supported by the Department of Health, UK. Contract RRX95 (RMA NSDTG)

Lentiviral Vector Delivery of Human Interleukin-7 (hIL-7) to Human Immune System (HIS) Mice Expands T Lymphocyte Populations

Genetically modified mice carrying engrafted human tissues provide useful models to study human cell biology in physiologically relevant contexts. However, there remain several obstacles limiting the compatibility of human cells within their mouse hosts. Among these is inadequate cross-reactvitiy between certain mouse cytokines and human cellular receptors, depriving the graft of important survival and growth signals. To circumvent this problem, we utilized a lentivirus-based delivery system to express physiologically relevant levels of human interleukin-7 (hIL-7) in Rag2-/-γc-/- mice following a single intravenous injection. hIL-7 promoted homeostatic proliferation of both adoptively transferred and endogenously generated T-cells in Rag2-/-γc-/- Human Immune System (HIS) mice. Interestingly, we found that hIL-7 increased T lymphocyte numbers in the spleens of HIV infected HIS mice without affecting viral load. Taken together, our study unveils a versatile approach to deliver human cytokines to HIS mice, to both improve engraftment and determine the impact of cytokines on human diseases

Dichotomy Between Clustering Performance and Minimum Distortion in Piecewise-Dependent-Data (PDD) Clustering

In many signal such speech, bio-signals, protein chains, etc. there is a dependency between consecutive vectors. As the dependency is limited in duration such data can be called as Piecewise-Dependent- Data (PDD). In clustering it is frequently needed to minimize a given distance function. In this paper we will show that in PDD clustering there is a contradiction between the desire for high resolution (short segments and low distance) and high accuracy (long segments and high distortion), i.e. meaningful clustering

Extended BIC Criterion for Model Selection

Model selection is commonly based on some variation of the BIC or minimum message length criteria, such as MML and MDL. In either case the criterion is split into two terms: one for the model (data code length/model complexity) and one for the data given the model (message length/data likelihood). For problems such as change detection, unsupervised segmentation or data clustering it is common practice for the model term to comprise only a sum of sub-model terms. In this paper it is shown that the full model complexity must also take into account the number of sub models and the labels which assign data to each sub model. From this analysis we derive an extended BIC approach (EBIC) for this class of problem. Results with artificial data are given to illustrate the properties of this procedure

Eradication of chronic myeloid leukemia stem cells: a novel mathematical model predicts no therapeutic benefit of adding G-CSF to imatinib

Imatinib mesylate induces complete cytogenetic responses in patients with chronic myeloid leukemia (CML), yet many patients have detectable BCR-ABL transcripts in peripheral blood even after prolonged therapy. Bone marrow studies have shown that this residual disease resides within the stem cell compartment. Quiescence of leukemic stem cells has been suggested as a mechanism conferring insensitivity to imatinib, and exposure to the Granulocyte-Colony Stimulating Factor (G-CSF), together with imatinib, has led to a significant reduction in leukemic stem cells in vitro. In this paper, we design a novel mathematical model of stem cell quiescence to investigate the treatment response to imatinib and G-CSF. We find that the addition of G-CSF to an imatinib treatment protocol leads to observable effects only if the majority of leukemic stem cells are quiescent; otherwise it does not modulate the leukemic cell burden. The latter scenario is in agreement with clinical findings in a pilot study administering imatinib continuously or intermittently, with or without G-CSF (GIMI trial). Furthermore, our model predicts that the addition of G-CSF leads to a higher risk of resistance since it increases the production of cycling leukemic stem cells. Although the pilot study did not include enough patients to draw any conclusion with statistical significance, there were more cases of progression in the experimental arms as compared to continuous imatinib. Our results suggest that the additional use of G-CSF may be detrimental to patients in the clinic

Online/Offline OR Composition of Sigma Protocols

Proofs of partial knowledge allow a prover to prove knowledge of witnesses for k out of n instances of NP languages. Cramer, Schoenmakers and Damgård [10] provided an efficient construction of a 3-round public-coin witness-indistinguishable (k, n)-proof of partial knowledge for any NP language, by cleverly combining n executions of Σ-protocols for that language. This transform assumes that all n instances are fully specified before the proof starts, and thus directly rules out the possibility of choosing some of the instances after the first round. Very recently, Ciampi et al. [6] provided an improved transform where one of the instances can be specified in the last round. They focus on (1, 2)-proofs of partial knowledge with the additional feature that one instance is defined in the last round, and could be adaptively chosen by the verifier. They left as an open question the existence of an efficient (1, 2)-proof of partial knowledge where no instance is known in the first round. More in general, they left open the question of constructing an efficient (k, n)-proof of partial knowledge where knowledge of all n instances can be postponed. Indeed, this property is achieved only by inefficient constructions requiring NP reductions [19]. In this paper we focus on the question of achieving adaptive-input proofs of partial knowledge. We provide through a transform the first efficient construction of a 3-round public-coin witness-indistinguishable (k, n)-proof of partial knowledge where all instances can be decided in the third round. Our construction enjoys adaptive-input witness indistinguishability. Additionally, the proof of knowledge property remains also if the adversarial prover selects instances adaptively at last round as long as our transform is applied to a proof of knowledge belonging to the widely used class of proofs of knowledge described in [9,21]. Since knowledge of instances and witnesses is not needed before the last round, we have that the first round can be precomputed and in the online/offline setting our performance is similar to the one of [10]. Our new transform relies on the DDH assumption (in contrast to the transforms of [6,10] that are unconditional)