The dissociable effects of reward on sequential motor behavior

Reward has consistently been shown to enhance motor behavior; however, its beneficial effects appear to be largely unspecific. For example, reward is associated with both rapid and training-dependent improvements in performance, with a mechanistic account of these effects currently lacking. Here we tested the hypothesis that these distinct reward-based improvements are driven by dissociable reward types: monetary incentive and performance feedback. Whereas performance feedback provides information on how well a motor task has been completed (knowledge of performance), monetary incentive increases the motivation to perform optimally without providing a performance-based learning signal. Experiment 1 showed that groups who received monetary incentive rapidly improved movement times (MTs), using a novel sequential reaching task. In contrast, only groups with correct performance-based feedback showed learning-related improvements. Importantly, pairing both maximized MT performance gains and accelerated movement fusion. Fusion describes an optimization process during which neighboring sequential movements blend together to form singular actions. Results from experiment 2 served as a replication and showed that fusion led to enhanced performance speed while also improving movement efficiency through increased smoothness. Finally, experiment 3 showed that these improvements in performance persist for 24 h even without reward availability. This highlights the dissociable impact of monetary incentive and performance feedback, with their combination maximizing performance gains and leading to stable improvements in the speed and efficiency of sequential actions. NEW & NOTEWORTHY Our work provides a mechanistic framework for how reward influences motor behavior. Specifically, we show that rapid improvements in speed and accuracy are driven by reward presented in the form of money, whereas knowledge of performance through performance feedback leads to training-based improvements. Importantly, combining both maximized performance gains and led to improvements in movement quality through fusion, which describes an optimization process during which sequential movements blend into a single action

Quantitative electron energy-loss spectroscopy (EELS) analyses of lead zirconate titanate

Electron energy-loss spectroscopy (EELS) analyses have been performed on a sol–gel deposited lead zirconate titanate film, showing that EELS can be used for heavy as well as light element analysis. The elemental distributions within the sol–gel layers are profiled using the Pb N<sub>6,7</sub>-edges, Zr M-edges, Ti L-edges and O K-edge. A multiple linear least squares fitting procedure was used to extract the Zr signal which overlaps with the Pb signal. Excellent qualitative information has been obtained on the distribution of the four elements. The non-uniform and complementary distributions of Ti and Zr within each sol–gel deposited layer are observed. The metal:oxygen elemental ratios are quantified using experimental standards of PbTiO<sub>3</sub>, PbZrO<sub>3</sub>, ZrO<sub>2</sub> and TiO<sub>2</sub> to provide relevant cross-section ratios. The quantitative results obtained for Ti/O and Pb/O are very good but the Zr/O results are less accurate. Methods of further improving the results are discussed

Class Attendance and Students’ Evaluations of Teaching: Do No-Shows Bias Course Ratings and Rankings?

Background: Many university departments use students’ evaluations of teaching (SET) to compare and rank courses. However, absenteeism from class is often nonrandom and, therefore, SET for different courses might not be comparable. Objective: The present study aims to answer two questions. Are SET positively biased due to absenteeism? Do procedures, which adjust for absenteeism, change course rankings? Research Design: The author discusses the problem from a missing data perspective and present empirical results from regression models to determine which factors are simultaneously associated with students’ class attendance and course ratings. In order to determine the extent of these biases, the author then corrects average ratings for students’ absenteeism and inspect changes in course rankings resulting from this adjustment. Subjects: The author analyzes SET data on the individual level. One or more course ratings are available for each student. Measures: Individual course ratings and absenteeism served as the key outcomes. Results: Absenteeism decreases with rising teaching quality. Furthermore, both factors are systematically related to student and course attributes. Weighting students’ ratings by actual absenteeism leads to mostly small changes in ranks, which follow a power law. Only a few, average courses are disproportionally influenced by the adjustment. Weighting by predicted absenteeism leads to very small changes in ranks. Again, average courses are more strongly affected than courses of very high or low in quality. Conclusions: No-shows bias course ratings and rankings. SET are more appropriate to identify high- and low-quality courses than to determine the exact ranks of average courses

A nuclear factor 1 binding site mediates the transcriptional activation of a type I collagen promoter by transforming growth factor-beta

Transforming growth factor-beta (TGF-beta) increases the steady-state RNA levels of several fibroblast extracellular matrix proteins. Using DNA transfection, we show that TGF-beta stimulates the activity of the mouse alpha 2(l) collagen promoter 5- to 10-fold in mouse NIH 3T3 and rat osteosarcoma cells. Deletion analysis indicates that a segment of this promoter between -350 and -300, overlapping a nuclear factor 1 (NF1) binding site, is needed for TGF-beta stimulation. A 3 bp substitution mutation abolishing NF1 binding to this site inhibits TGF-beta activation. Insertion of this NF1 binding site 5' to the SV40 early promoter makes the promoter TGF-beta inducible, but the 3 bp substitution does not. Similarly, when the NF1 binding site at the replication origin of adenovirus 2 and 5 is inserted 5' to the SV40 promoter, the promoter responds to TGF-beta. Therefore an NF1 binding site mediates the transcriptional activation of the mouse alpha 2(l) collagen promoter by TGF-beta

NRF2-driven miR-125B1 and miR-29B1 transcriptional regulation controls a novel anti-apoptotic miRNA regulatory network for AML survival

Transcription factor NRF2 is an important regulator of oxidative stress. It is involved in cancer progression, and has abnormal constitutive expression in acute myeloid leukaemia (AML). Posttranscriptional regulation by microRNAs (miRNAs) can affect the malignant phenotype of AML cells. In this study, we identified and characterised NRF2-regulated miRNAs in AML. An miRNA array identified miRNA expression level changes in response to NRF2 knockdown in AML cells. Further analysis of miRNAs concomitantly regulated by knockdown of the NRF2 inhibitor KEAP1 revealed the major candidate NRF2-mediated miRNAs in AML. We identified miR-125B to be upregulated and miR-29B to be downregulated by NRF2 in AML. Subsequent bioinformatic analysis identified putative NRF2 binding sites upstream of the miR-125B1 coding region and downstream of the mir-29B1 coding region. Chromatin immunoprecipitation analyses showed that NRF2 binds to these antioxidant response elements (AREs) located in the 5′ untranslated regions of miR-125B and miR-29B. Finally, primary AML samples transfected with anti-miR-125B antagomiR or miR-29B mimic showed increased cell death responsiveness either alone or co-treated with standard AML chemotherapy. In summary, we find that NRF2 regulation of miR-125B and miR-29B acts to promote leukaemic cell survival, and their manipulation enhances AML responsiveness towards cytotoxic chemotherapeutics