Liver Fibrosis-4 index indicates atrial fibrillation in acute ischemic stroke

BACKGROUND: Non-alcoholic fatty liver disease and particularly liver fibrosis is related to cardiovascular disease and may indicate an increased risk for atrial fibrillation (AF), but this association has not yet been systematically investigated in a cohort of ischemic stroke patients. METHODS: We analyzed data from a prospective single-center study enrolling all consecutive ischemic stroke patients admitted to our stroke unit over a one-year-period. All patients received a thorough etiological work-up. For evaluation of liver fibrosis, we determined the FIB-4 index, a well-established noninvasive liver fibrosis test. Laboratory results were analyzed from a uniform blood sample taken at stroke unit admission. RESULTS: Of 414 included patients (mean age 70.2 years, 57.7% male), FIB-4 indicated advanced liver fibrosis in 92 (22.2%). AF as the underlying stroke mechanism was present in 28.0% (large vessel disease: 25.6%, small vessel disease: 11.4%, cryptogenic: 29.2%). Patients with FIB-4 ≥2.67 had higher rates of AF (53.3% vs. 20.8%, p<0.001), this association remained significant after correction for established AF risk factors (Odds Ratio 2.53, 95% confidence interval 1.44-4.46, p=0.001). FIB-4 was further associated with worse functional outcome three months (p<0.001) and higher mortality four years post-stroke (p<0.02), but these relationships were no longer present after correction for age and initial stroke severity. Moreover, FIB-4 did not associate with long-term recurrent vascular events. CONCLUSIONS: Liver fibrosis assessed by the FIB-4 index is independently associated with AF in acute ischemic stroke patients. Further studies should evaluate whether adding the FIB-4 index to AF risk scores increases their precision

ASXL1 mutations predict inferior molecular response to nilotinib treatment in chronic myeloid leukemia

Gene mutations independent of BCR::ABL1 have been identified in newly diagnosed patients with chronic myeloid leukemia (CML) in chronic phase, whereby mutations in epigenetic modifier genes were most common. These findings prompted the systematic analysis of prevalence, dynamics, and prognostic significance of such mutations, in a clinically well-characterized patient population of 222 CML patients from the TIGER study (CML-V) by targeted next-generation sequencing covering 54 myeloid leukemia-associated genes. In total, 53/222 CML patients (24%) carried 60 mutations at diagnosis with ASXL1 being most commonly affected (n = 20). To study mutation dynamics, longitudinal deep sequencing analysis of serial samples was performed in 100 patients after 12, 24, and 36 months of therapy. Typical patterns of clonal evolution included eradication, persistence, and emergence of mutated clones. Patients carrying an ASXL1 mutation at diagnosis showed a less favorable molecular response to nilotinib treatment, as a major molecular response (MMR) was achieved less frequently at month 12, 18, and 24 compared to all other patients. Patients with ASXL1 mutations were also younger and more frequently found in the high risk category, suggesting a central role of clonal evolution associated with ASXL1 mutations in CML pathogenesis

Personality matters: how adaptive selling skills mediate the effect of personality traits on salespeople’s exploited cross-selling potential

This article examines how salespeople’s personality traits influence their adaptive selling skills and exploited cross-selling potential. We collect both a cross-industry and cross-country dataset of 430 salespeople who engage in cross-selling activities. In contrast with prior research on the relationship between personality traits and general sales performance, we find none of the big-five personality traits to have a significant direct effect on the exploited cross-selling potential. However, drawing on the theory of self-monitoring, we find that the big-five traits have dimensionally varying, significant effects on adaptive selling skills. In turn, adaptive selling skills have a significant direct effect on exploited cross-selling potential. Moreover, our analyses reveal that the personality traits conscientiousness and extraversion have indirect positive effects on exploited cross-selling potential. These findings provide beneficial insights for human resources as well as human development practice in both recruiting and training initiatives. In particular, we provide guidance on how to hire and train the best personnel for intensive cross-selling sales positions in firms. In addition, we introduce new perspectives for research on the relationship between personality traits and performance measures by identifying the importance of possible mediators

When does sales system agility lead to organizational performance?

Although academics and practitioners express strong interest in agility, prior research has not investigated sales system agility (SSA). Rapid developments in customer preferences, technology, and the competitive landscape conflict with rigid sales systems. This study introduces SSA and examines its performance consequences using a cross-industry, multisource data set. The authors find that SSA does not always affect performance, but managers need to overcome execution challenges. Drawing on the dynamic capabilities view and contemporary extensions of agency theory, the authors identify sales system design and sales system management as focal contingency factors. Multichannel usage (as the major design component of sales systems) diminishes the positive returns of SSA. By contrast, both formal and informal governance mechanisms enhance the positive performance effects of SSA. These sales system management components decrease agency conflicts in the manufacturer–sales partner dyad and thus curtail reactance and/or increase decision-making speed. The focal managerial implication of the study is that SSA is not a one-size-fits-all approach. Instead, the findings suggest that managers need to align their agility approaches with effective governance mechanisms

PTPRG and PTPRC modulate nilotinib response in chronic myeloid leukemia cells

The introduction of second-generation tyrosine kinase inhibitors (TKIs) targeting the protein-tyrosine kinase (PTK) BCR-ABL1 has improved treatment response in chronic myeloid leukemia (CML). However, in some patients response still remains suboptimal. Protein-tyrosine phosphatases (PTPs) are natural counter-actors of PTK activity and can affect TKI sensitivity, but the impact of PTPs on treatment response to second-generation TKIs is unknown. We assessed the mRNA expression level of 38 PTPs in 66 newly diagnosed CML patients and analyzed the potential relation with treatment outcome after 9 months of nilotinib medication. A significantly positive association with response was observed for higher PTPN13, PTPRA, PTPRC (also known as CD45), PTPRG, and PTPRM expression. Selected PTPs were then subjected to a functional analysis in CML cell line models using PTP gene knockout by CRISPR/ Cas9 technology or PTP overexpression. These analyses revealed PTPRG positively and PTPRC negatively modulating nilotinib response. Consistently, PTPRG negatively and PTPRC positively affected BCR-ABL1 dependent transformation. We identified BCR-ABL1 signaling events, which were affected by modulating PTP levels or nilotinib treatment in the same direction. In conclusion, the PTP status of CML cells is important for the response to second generation TKIs and may help in optimizing therapeutic strategie

InFuse: A Comprehensive Framework for Data Fusion in Space Robotics

International audienceFused sensory data provides decision-making processes with exploitable information about the external environment and a describes some preliminary work on the InFuse project to create a modular and portable data fusion system funded Research Cluster on Space Robotics Technologies. In space robotics, a wide range of data fusion techniques are required to accomplish challenging objectives for exploration, science and commercial purposes. This includes navigation for planetary and orbital robotics, scientific data gathering, and on-orbit spacecraft servicing applications. InFuse aims to develop a comprehensive open-source data fusion toolset to combine and interpret sensory data from multiple robotic sensors, referred as a Common Data Fusion Framework (CDFF)