A stereospecific enzyme of the putative biosynthetic pathway of cardenolides Characterization of a progesterone 5β-reductase from leaves of Digitalis purpurea L

AbstractLeaves of Digitalispurpurea contain an enzyme activity which catalyzes the conversion of progesterone to 5β-pregnane-3,20-dione. Since cardenolides without exception possess a 5β-configuration, 5β-pregnane-3,20-dione can serve as a precursor for this class of secondary metabolites. It is assumed that the enzyme is part of the putative biosynthetic pathway of cardenolides. This enzyme activity was spotted in the soluble fraction of a crude homogenate. Product formation was detected by gas chromatography and by gas chromatography/mass spectroscopy (g.c./m.s.). The enzyme had a pH optimum at 8.0 and an apparent Km value of 6 μM for progesterone. It required NADPH as a co-substrate with an apparent Km value of 22 μM. The optimum temperature in vitro was 30°C. The activity was not dependent on monovalent and bivalent cations

Complementary Keratoconus Indices Based on Topographical Interpretation of Biomechanical Waveform Parameters: A Supplement to Established Keratoconus Indices

Purpose:To build new models with the Ocular Response Analyzer (ORA) waveform parameters to create new indices analogous to established topographic keratoconus indices.Method:Biomechanical, tomographic, and topographic measurements of 505 eyes from the Homburger Keratoconus Centre were included. Thirty seven waveform parameters (WF) were derived from the biomechanical measurement with the ORA. Area under curve (ROC, receiver operating characteristic) was used to quantify the screening performance. A logistic regression analysis was used to create two new keratoconus prediction models based on these waveform parameters to resample the clinically established keratoconus indices from Pentacam and TMS-5.Results:ROC curves show the best results for the waveform parameters P1area, P2area, h1, h2, dive1, mslew1, aspect1, aplhf, dslope1. The new keratoconus prediction model to resample the Pentacam topographic keratoconus index (TKC) was: WFTKC = –4.068 + 0.002×P2area – 0.005×dive1 – 0.01×h1 – 2.501×aplhf, which achieves a sensitivity of 90.3% and specificity of 89.4%; to resample the TMS-5 keratoconus classification index (KCI) it was: WFKCI = –3.606 + 0.002×P2area which achieves a sensitivity of 75.4% and a specificity of 81.8%.Conclusion:Additional to the biomechanically provided Keratoconus Index two new indices which were based on the topographic gold standards (either Pentacam or TMS-5) were created. Of course, these do not replace the original topographic measurement

Unicorn, hare, or tortoise? Using machine learning to predict working memory training performance

People differ considerably in the extent to which they benefit from working memory (WM) training. Although there is increasing research focusing on individual differences associated with WM training outcomes, we still lack an understanding of which specific individual differences, and in what combination, contribute to inter-individual variations in training trajectories. In the current study, 568 undergraduates completed one of several N-back intervention variants over the course of two weeks. Participants\u27 training trajectories were clustered into three distinct training patterns (high performers, intermediate performers, and low performers). We applied machine-learning algorithms to train a binary tree model to predict individuals\u27 training patterns relying on several individual difference variables that have been identified as relevant in previous literature. These individual difference variables included pre-existing cognitive abilities, personality characteristics, motivational factors, video game experience, health status, bilingualism, and socioeconomic status. We found that our classification model showed good predictive power in distinguishing between high performers and relatively lower performers. Furthermore, we found that openness and pre-existing WM capacity to be the two most important factors in distinguishing between high and low performers. However, among low performers, openness and video game background were the most significant predictors of their learning persistence. In conclusion, it is possible to predict individual training performance using participant characteristics before training, which could inform the development of personalized interventions

Chemical genetic screen identifies Gapex-5/GAPVD1 and STBD1 as novel AMPK substrates

AMP-activated protein kinase (AMPK) is a key regulator of cellular energy homeostasis, acting as a sensor of energy and nutrient status. As such, AMPK is considered a promising drug target for treatment of medical conditions particularly associated with metabolic dysfunctions. To better understand the downstream effectors and physiological consequences of AMPK activation, we have employed a chemical genetic screen in mouse primary hepatocytes in an attempt to identify novel AMPK targets. Treatment of hepatocytes with a potent and specific AMPK activator 991 resulted in identification of 65 proteins phosphorylated upon AMPK activation, which are involved in a variety of cellular processes such as lipid/glycogen metabolism, vesicle trafficking, and cytoskeleton organisation. Further characterisation and validation using mass spectrometry followed by immunoblotting analysis with phosphorylation site-specific antibodies identified AMPK-dependent phosphorylation of Gapex-5 (also known as GTPase-activating protein and VPS9 domain-containing protein 1 (GAPVD1)) on Ser902 in hepatocytes and starch-binding domain 1 (STBD1) on Ser175 in multiple cells/tissues. As new promising roles of AMPK as a key metabolic regulator continue to emerge, the substrates we identified could provide new mechanistic and therapeutic insights into AMPK-activating drugs in the liver

Investigating the Role of Individual Differences in Adherence to Cognitive Training

Consistent with research across several domains, intervention adherence is associated with desired outcomes. Our study investigates adherence, defined by participants’ commitment to, persistence with, and compliance with an intervention’s regimen, as a key mechanism underlying cognitive training effectiveness. We examine this relationship in a large and diverse sample comprising 4,775 adults between the ages of 18 and 93. We test the predictive validity of individual difference factors, such as age, gender, cognitive capability (i.e., fluid reasoning and working memory), grit, ambition, personality, self-perceived cognitive failures, socioeconomic status, exercise, and education on commitment to and persistence with a 20-session cognitive training regimen, as measured by the number of sessions completed. Additionally, we test the relationship between compliance measures: (i) spacing between training sessions, as measured by the average time between training sessions, and (ii) consistency in the training schedule, as measured by the variance in time between training sessions, with performance trajectories on the training task. Our data suggest that none of these factors reliably predict commitment to, persistence with, or compliance with cognitive training. Nevertheless, the lack of evidence from the large and representative sample extends the knowledge from previous research exploring limited, heterogenous samples, characterized by older adult populations. The absence of reliable predictors for commitment, persistence, and compliance in cognitive training suggests that nomothetic factors may affect program adherence. Future research will be well served to examine diverse approaches to increasing motivation in cognitive training to improve program evaluation and reconcile the inconsistency in findings across the field

A Latent Factor Analysis of Working Memory Measures Using Large-Scale Data

Working memory (WM) is a key cognitive system that is strongly related to other cognitive domains and relevant for everyday life. However, the structure of WM is yet to be determined. A number of WM models have been put forth especially by factor analytical studies. In broad terms, these models vary by their emphasis on WM contents (e.g., visuospatial, verbal) vs. WM processes (e.g., maintenance, updating) as critical, dissociable elements. Here we conducted confirmatory and exploratory factor analyses on a broad set of WM tasks, half of them numerical-verbal and half of them visuospatial, representing four commonly used task paradigms: simple span, complex span, running memory, and n-back. The tasks were selected to allow the detection of both content-based (visuospatial, numerical-verbal) and process-based (maintenance, updating) divisions. The data were collected online which allowed the recruitment of a large and demographically diverse sample of adults (n = 711). Both factor analytical methods pointed to a clear division according to task content for all paradigms except n-back, while there was no indication for a process-based division. Besides the content-based division, confirmatory factor analyses supported a model that also included a general WM factor. The n-back tasks had the highest loadings on the general factor, suggesting that this factor reflected high-level cognitive resources such as executive functioning and fluid intelligence that are engaged with all WM tasks, and possibly even more so with the n-back. Together with earlier findings that indicate high variability of process-based WM divisions, we conclude that the most robust division of WM is along its contents (visuospatial vs. numerical-verbal), rather than along its hypothetical subprocesses

Functional Connectivity in Tactile Object Discrimination—A Principal Component Analysis of an Event Related fMRI-Study

BACKGROUND: Tactile object discrimination is an essential human skill that relies on functional connectivity between the neural substrates of motor, somatosensory and supramodal areas. From a theoretical point of view, such distributed networks elude categorical analysis because subtraction methods are univariate. Thus, the aim of this study was to identify the neural networks involved in somatosensory object discrimination using a voxel-based principal component analysis (PCA) of event-related functional magnetic resonance images. METHODOLOGY/PRINCIPAL FINDINGS: Seven healthy, right-handed subjects aged between 22 and 44 years were required to discriminate with their dominant hand the length differences between otherwise identical parallelepipeds in a two-alternative forced-choice paradigm. Of the 34 principal components retained for analysis according to the 'bootstrapped' Kaiser-Guttman criterion, t-tests applied to the subject-condition expression coefficients showed significant mean differences between the object presentation and inter-stimulus phases in PC 1, 3, 26 and 32. Specifically, PC 1 reflected object exploration or manipulation, PC 3 somatosensory and short-term memory processes. PC 26 evinced the perception that certain parallelepipeds could not be distinguished, while PC 32 emerged in those choices when they could be. Among the cerebral regions evident in the PCs are the left posterior parietal lobe and premotor cortex in PC 1, the left superior parietal lobule (SPL) and the right cuneus in PC 3, the medial frontal and orbitofrontal cortex bilaterally in PC 26, and the right intraparietal sulcus, anterior SPL and dorsolateral prefrontal cortex in PC 32. CONCLUSIONS/SIGNIFICANCE: The analysis provides evidence for the concerted action of large-scale cortico-subcortical networks mediating tactile object discrimination. Parallel to activity in nodes processing object-related impulses we found activity in key cerebral regions responsible for subjective assessment and validation

The expression of mismatched repair genes and their correlation with clinicopathological parameters and response to neo-adjuvant chemotherapy in breast cancer

BACKGROUND: The DNA mismatch repair (MMR) pathway is an important post-replicative repair process. It is involved in the maintenance of genomic stability and MMR genes have therefore been named the proofreaders of replicating DNA. These genes repair the replicative errors of DNA and are thus imperative for genomic stability. The MMR genes have been found to be involved in promoting cytotoxicity, apoptosis, p53 phosphorylation and cell cycle arrest following exposure to exogenous DNA damaging agents. Loss of MMR function prevents the correction of replicative errors leading to instability of the genome, and can be detected by polymorphisms in micro satellites (1–6 nucleotide repeat sequences scattered in whole of the genome). This phenomenon, known as micro satellite instability (MSI), is a hallmark of MMR dysfunction and can be used as a marker of MMR dysfunction in colorectal and other malignancies. An alternative method for detection of MMR dysfunction is to test the expression of protein products of the MMR genes by immunohistochemistry (IHC), as mutations in these genes lead to reduced or absent expression of their gene products. Correlation between loss of MMR function and clinical, histopathological, behavioral parameters of the tumor and its response to chemotherapy in breast cancers may be of value in predicting tumor behavior and response to neoadjuvant chemotherapy (NACT). Neoadjuvant chemotherapy is an integral part of multimodal therapy for locally advanced breast cancer and predicting response may help in tailoring regimens in patients for optimum response. MATERIALS: After approval by the IRB(Institutional Review Board) and ethical committee of the hospital, 31 cases of locally advanced breast carcinoma (LABC) were studied to assess the correlation between MMR dysfunction, clinicopathological parameters and objective clinical response to neoadjuvant chemotherapy using immunohistochemistry. The immunohistochemical analysis for four MMR protein products -MLH1, MSH2, MSH6 and PMS2 was done in the pre NACT trucut biopsy specimen and after three cycles of NACT with C AF (cyclophosphamide, adriamycin, 5-fluorouracil) regimen, in the modified radical mastectomy specimen. RESULTS AND CONCLUSION: There was no significant correlation observed between expression of MMR proteins and age, family history, tumor size or histological type. However there was a statistically significant negative correlation between MLH1, MSH2 expression and histological grade. There was also a negative correlation observed between PMS2 expression after neo-adjuvant chemotherapy and clinical response. Cases with high post NACT expression of PMS2 were poor responders to chemotherapy. MSH6 was the most frequently altered MMR gene, with a negativity rate of 48% and the patients with high expression responded poorly to NACT. The study highlights the possible role of MMR expression in predicting aggressive tumor behavior (histological grade) and response to neoadjuvant chemotherapy in patients with LABC