Characterization of Artifact Influence on the Classification of Glucose Time Series Using Sample Entropy Statistics

[EN] This paper analyses the performance of SampEn and one of its derivatives, Fuzzy Entropy (FuzzyEn), in the context of artifacted blood glucose time series classification. This is a difficult and practically unexplored framework, where the availability of more sensitive and reliable measures could be of great clinical impact. Although the advent of new blood glucose monitoring technologies may reduce the incidence of the problems stated above, incorrect device or sensor manipulation, patient adherence, sensor detachment, time constraints, adoption barriers or affordability can still result in relatively short and artifacted records, as the ones analyzed in this paper or in other similar works. This study is aimed at characterizing the changes induced by such artifacts, enabling the arrangement of countermeasures in advance when possible. Despite the presence of these disturbances, results demonstrate that SampEn and FuzzyEn are sufficiently robust to achieve a significant classification performance, using records obtained from patients with duodenal-jejunal exclusion. The classification results, in terms of area under the ROC of up to 0.9, with several tests yielding AUC values also greater than 0.8, and in terms of a leave-one-out average classification accuracy of 80%, confirm the potential of these measures in this context despite the presence of artifacts, with SampEn having slightly better performance than FuzzyEn.The Czech partners were supported by DROIKEM000023001 and RVOVFN64165. No funding was received to support this research work by the Spanish partners.Cuesta Frau, D.; Novák, D.; Burda, V.; Molina Picó, A.; Vargas-Rojo, B.; Mraz, M.; Kavalkova, P.... (2018). Characterization of Artifact Influence on the Classification of Glucose Time Series Using Sample Entropy Statistics. Entropy. 20(11):1-18. https://doi.org/10.3390/e20110871S118201

Influence of Duodenal-Jejunal Implantation on Glucose Dynamics: A Pilot Study Using Different Nonlinear Methods

[EN] Diabetes is a disease of great and rising prevalence, with the obesity epidemic being a significant contributing risk factor. Duodenal¿jejunal bypass liner (DJBL) is a reversible implant that mimics the effects of more aggressive surgical procedures, such as gastric bypass, to induce weight loss. We hypothesized that DJBL also influences the glucose dynamics in type II diabetes, based on the induced changes already demonstrated in other physiological characteristics and parameters. In order to assess the validity of this assumption, we conducted a quantitative analysis based on several nonlinear algorithms (Lempel¿Ziv Complexity, Sample Entropy, Permutation Entropy, and modified Permutation Entropy), well suited to the characterization of biomedical time series. We applied them to glucose records drawn from two extreme cases available of DJBL implantation: before and after 10 months. The results confirmed the hypothesis and an accuracy of 86.4% was achieved with modified Permutation Entropy. Other metrics also yielded significant classification accuracy results, all above 70%, provided a suitable parameter configuration was chosen. With the Leave¿One¿Out method, the results were very similar, between 72% and 82% classification accuracy. There was also a decrease in entropy of glycaemia records during the time interval studied. These findings provide a solid foundation to assess how glucose metabolism may be influenced by DJBL implantation and opens a new line of research in this field.The Czech clinical partners were supported by DRO IKEM 000023001 and RVO VFN 64165. The Czech technical partners were supported by Research Centre for Informatics grant numbers CZ.02.1.01/0.0/16 - 019/0000765 and SGS16/231/OHK3/3T/13-Support of interactive approaches to biomedical data acquisition and processing. No funding was received to support this research work by the Spanish and British partnersCuesta Frau, D.; Novák, D.; Burda, V.; Abasolo, D.; Adjei, T.; Varela, M.; Vargas, B.... (2019). Influence of Duodenal-Jejunal Implantation on Glucose Dynamics: A Pilot Study Using Different Nonlinear Methods. Complexity. 2019. https://doi.org/10.1155/2019/6070518S2019Kassirer, J. P., & Angell, M. (1998). Losing Weight — An Ill-Fated New Year’s Resolution. New England Journal of Medicine, 338(1), 52-54. doi:10.1056/nejm199801013380109Van Gaal, L., & Dirinck, E. (2016). Pharmacological Approaches in the Treatment and Maintenance of Weight Loss. Diabetes Care, 39(Supplement 2), S260-S267. doi:10.2337/dcs15-3016De Jonge, C., Rensen, S. S., Verdam, F. J., Vincent, R. P., Bloom, S. R., Buurman, W. A., … Greve, J. W. M. (2015). Impact of Duodenal-Jejunal Exclusion on Satiety Hormones. 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Novel CHK1 inhibitor MU380 exhibits significant single-agent activity in TP53-mutated chronic lymphocytic leukemia cells

Introduction of small-molecule inhibitors of B-cell receptor signaling and BCL2 protein significantly improves therapeutic options in chronic lymphocytic leukemia. However, some patients suffer from adverse effects mandating treatment discontinuation, and cases with TP53 defects more frequently experience early progression of the disease. Development of alternative therapeutic approaches is, therefore, of critical importance. Here we report details of the anti-chronic lymphocytic leukemia single-agent activity of MU380, our recently identified potent, selective, and metabolically robust inhibitor of checkpoint kinase 1. We also describe a newly developed enantioselective synthesis of MU380, which allows preparation of gram quantities of the substance. Checkpoint kinase 1 is a master regulator of replication operating primarily in intra-S and G2/M cell cycle checkpoints. Initially tested in leukemia and lymphoma cell lines, MU380 significantly potentiated efficacy of gemcitabine, a clinically used inducer of replication stress. Moreover, MU380 manifested substantial single-agent activity in both TP53-wild type and TP53-mutated leukemia and lymphoma cell lines. In chronic lymphocytic leukemia-derived cell lines MEC-1, MEC-2 (both TP53-mut), and OSU-CLL (TP53-wt) the inhibitor impaired cell cycle progression and induced apoptosis. In primary clinical samples, MU380 used as a single-agent noticeably reduced the viability of unstimulated chronic lymphocytic leukemia cells as well as those induced to proliferate by anti-CD40/IL-4 stimuli. In both cases, effects were comparable in samples harboring p53 pathway dysfunction (TP53 mutations or ATM mutations) and TP53-wt/ATM-wt cells. Lastly, MU380 also exhibited significant in vivo activity in a xenotransplant mouse model (immunodeficient strain NOD-scid IL2Rγnull) where it efficiently suppressed growth of subcutaneous tumors generated from MEC-1 cells

STAT3 and TP53 mutations associate with poor prognosis in anaplastic large cell lymphoma

Funder: European Union’s Horizon 2020 Marie Skłodowska – Curie Innovative Training Networks (ITN - ETN) under grant agreement No.: 675712European Union’s Horizon 2020 Marie Skłodowska – Curie Innovative Training Networks (ITN - ETN) under grant agreement No.: 675712 Czech Science Foundation (GA CR), junior project no. 19-23424Y MEYS CZ project CEITEC 2020 (LQ1601)Funder: MEYS CZ project CEITEC 2020 (LQ1601) NCMG research infrastructure (LM22018132 funded by MEYS CR)Funder: European Union’s Horizon 2020 Marie Skłodowska – Curie Innovative Training Networks (ITN - ETN) under grant agreement No.: 675712.Funder: MH CZ-RVO 6526970

In Vitro and In Vivo Models of CLL–T Cell Interactions: Implications for Drug Testing

T cells are key components in environments that support chronic lymphocytic leukemia (CLL), activating CLL-cell proliferation and survival. Here, we review in vitro and in vivo model systems that mimic CLL–T-cell interactions, since these are critical for CLL-cell division and resistance to some types of therapy (such as DNA-damaging drugs or BH3-mimetic venetoclax). We discuss approaches for direct CLL-cell co-culture with autologous T cells, models utilizing supportive cell lines engineered to express T-cell factors (such as CD40L) or stimulating CLL cells with combinations of recombinant factors (CD40L, interleukins IL4 or IL21, INFγ) and additional B-cell receptor (BCR) activation with anti-IgM antibody. We also summarize strategies for CLL co-transplantation with autologous T cells into immunodeficient mice (NOD/SCID, NSG, NOG) to generate patient-derived xenografts (PDX) and the role of T cells in transgenic CLL mouse models based on TCL1 overexpression (Eµ-TCL1). We further discuss how these in vitro and in vivo models could be used to test drugs to uncover the effects of targeted therapies (such as inhibitors of BTK, PI3K, SYK, AKT, MEK, CDKs, BCL2, and proteasome) or chemotherapy (fludarabine and bendamustine) on CLL–T-cell interactions and CLL proliferation