Background Current treatment recommendations for patients with polycythemia vera call for maintaining a hematocrit of less than 45%, but this therapeutic strategy has not been tested in a randomized clinical trial. Methods We randomly assigned 365 adults with JAK2-positive polycythemia vera who were being treated with phlebotomy, hydroxyurea, or both to receive either more intensive treatment (target hematocrit, <45%) (low-hematocrit group) or less intensive treatment (target hematocrit, 45 to 50%) (high-hematocrit group). The primary composite end point was the time until death from cardiovascular causes or major thrombotic events. The secondary end points were cardiovascular events, cardiovascular hospitalizations, incidence of cancer, progression to myelofibrosis, myelodysplasia or leukemic transformation, and hemorrhage. An intention-to-treat analysis was performed. Results After a median follow-up of 31 months, the primary end point was recorded in 5 of 182 patients in the low-hematocrit group (2.7%) and 18 of 183 patients in the high-hematocrit group (9.8%) (hazard ratio in the high-hematocrit group, 3.91; 95% confidence interval [CI], 1.45 to 10.53; P=0.007). The primary end point plus superficial-vein thrombosis occurred in 4.4% of patients in the low-hematocrit group, as compared with 10.9% in the high-hematocrit group (hazard ratio, 2.69; 95% CI, 1.19 to 6.12; P=0.02). Progression to myelofibrosis, myelodysplasia or leukemic transformation, and bleeding were observed in 6, 2, and 2 patients, respectively, in the low-hematocrit group, as compared with 2, 1, and 5 patients, respectively, in the high-hematocrit group. There was no significant between-group difference in the rate of adverse events. Conclusions In patients with polycythemia vera, those with a hematocrit target of less than 45% had a significantly lower rate of cardiovascular death and major thrombosis than did those with a hematocrit target of 45 to 50%. (Funded by the Italian Medicines Agency and others; ClinicalTrials.gov number, NCT01645124 , and EudraCT number, 2007-006694-91 .).
In the present study, we investigated the relation between cognitive performance and heart rate variability as a function of fitness level. We measured the effect of three cognitive tasks (the psychomotor vigilance task, a temporal orienting task, and a duration discrimination task) on the heart rate variability of two groups of participants: a high-fit group and a low-fit group. Two major novel findings emerged from this study. First, the lowest values of heart rate variability were found during performance of the duration discrimination task, compared to the other two tasks. Second, the results showed a decrement in heart rate variability as a function of the time on task, although only in the low-fit group. Moreover, the high-fit group showed overall faster reaction times than the low-fit group in the psychomotor vigilance task, while there were not significant differences in performance between the two groups of participants in the other two cognitive tasks. In sum, our results highlighted the influence of cognitive processing on heart rate variability. Importantly, both behavioral and physiological results suggested that the main benefit obtained as a result of fitness level appeared to be associated with processes involving sustained attention.
Predicting rates of cell state change caused by stochastic fluctuations using a data-driven landscape model.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 5 years ago
We develop a potential landscape approach to quantitatively describe experimental data from a fibroblast cell line that exhibits a wide range of GFP expression levels under the control of the promoter for tenascin-C. Time-lapse live-cell microscopy provides data about short-term fluctuations in promoter activity, and flow cytometry measurements provide data about the long-term kinetics, because isolated subpopulations of cells relax from a relatively narrow distribution of GFP expression back to the original broad distribution of responses. The landscape is obtained from the steady state distribution of GFP expression and connected to a potential-like function using a stochastic differential equation description (Langevin/Fokker-Planck). The range of cell states is constrained by a force that is proportional to the gradient of the potential, and biochemical noise causes movement of cells within the landscape. Analyzing the mean square displacement of GFP intensity changes in live cells indicates that these fluctuations are described by a single diffusion constant in log GFP space. This finding allows application of the Kramers' model to calculate rates of switching between two attractor states and enables an accurate simulation of the dynamics of relaxation back to the steady state with no adjustable parameters. With this approach, it is possible to use the steady state distribution of phenotypes and a quantitative description of the short-term fluctuations in individual cells to accurately predict the rates at which different phenotypes will arise from an isolated subpopulation of cells.
The actin-based molecular motor myosin VI functions in the endocytic uptake pathway, both during the early stages of clathrin-mediated uptake and in later transport to/from early endosomes. This study uses fluorescence recovery after photobleaching (FRAP) to examine the turnover rate of myosin VI during endocytosis. The results demonstrate that myosin VI turns over dynamically on endocytic structures with a characteristic half-life common to both the large insert isoform of myosin VI on clathrin-coated structures and the no-insert isoform on early endosomes. This half-life is shared by the myosin VI-binding partner Dab2 and is identical for full-length myosin VI and the cargo-binding tail region. The 4-fold slower half-life of an artificially dimerized construct of myosin VI on clathrin-coated structures suggests that wild type myosin VI does not function as a stable dimer, but either as a monomer or in a monomer/dimer equilibrium. Taken together, these FRAP results offer insight into both the basic turnover dynamics and the monomer/dimer nature of myosin VI.
There is increasing recognition of the therapeutic function pets can play in relation to mental health. However, there has been no systematic review of the evidence related to the comprehensive role of companion animals and how pets might contribute to the work associated with managing a long-term mental health condition. The aim of this study was to explore the extent, nature and quality of the evidence implicating the role and utility of pet ownership for people living with a mental health condition.
How bats adapt their sonar behavior to accommodate the noisiness of a crowded day roost is a mystery. Some bats change their pulse acoustics to enhance the distinction between theirs and another bat’s echoes, but additional mechanisms are needed to explain the bat sonar system’s exceptional resilience to jamming by conspecifics. Variable pulse repetition rate strategies offer one potential solution to this dynamic problem, but precisely how changes in pulse rate could improve sonar performance in social settings is unclear. Here we show that bats decrease their emission rates as population density increases, following a pattern that reflects a cumulative mutual suppression of each other’s pulse emissions. Playback of artificially-generated echolocation pulses similarly slowed emission rates, demonstrating that suppression was mediated by hearing the pulses of other bats. Slower emission rates did not support an antiphonal emission strategy but did reduce the relative proportion of emitted pulses that overlapped with another bat’s emissions, reducing the relative rate of mutual interference. The prevalence of acoustic interferences occurring amongst bats was empirically determined to be a linear function of population density and mean emission rates. Consequently as group size increased, small reductions in emission rates spread across the group partially mitigated the increase in interference rate. Drawing on lessons learned from communications networking theory we show how modest decreases in pulse emission rates can significantly increase the net information throughput of the shared acoustic space, thereby improving sonar efficiency for all individuals in a group. We propose that an automated acoustic suppression of pulse emissions triggered by bats hearing each other’s emissions dynamically optimizes sonar efficiency for the entire group.
Variability in motor performance results from the interplay of error correction and neuromotor noise. This study examined whether visual amplification of error, previously shown to improve performance, affects not only error correction, but also neuromotor noise, typically regarded as inaccessible to intervention. Seven groups of healthy individuals, with six participants in each group, practiced a virtual throwing task for three days until reaching a performance plateau. Over three more days of practice, six of the groups received different magnitudes of visual error amplification; three of these groups also had noise added. An additional control group was not subjected to any manipulations for all six practice days. The results showed that the control group did not improve further after the first three practice days, but the error amplification groups continued to decrease their error under the manipulations. Analysis of the temporal structure of participants' corrective actions based on stochastic learning models revealed that these performance gains were attained by reducing neuromotor noise and, to a considerably lesser degree, by increasing the size of corrective actions. Based on these results, error amplification presents a promising intervention to improve motor function by decreasing neuromotor noise after performance has reached an asymptote. These results are relevant for patients with neurological disorders and the elderly. More fundamentally, these results suggest that neuromotor noise may be accessible to practice interventions.
Components of the chromatin remodelling SWI/SNF complex are recurrently mutated in tumours, suggesting that altering the activity of the complex plays a role in oncogenesis. However, the role that the individual subunits play in this process is not clear. We set out to develop an inhibitor compound targeting the bromodomain of BRD9 in order to evaluate its function within the SWI/SNF complex. Here, we present the discovery and development of a potent and selective BRD9 bromodomain inhibitor series based on a new pyridinone-like scaffold. Crystallographic information of the inhibitors bound to BRD9 guided their development with respect to potency for BRD9 and selectivity against BRD4. These compounds modulate BRD9 bromodomain cellular function and display anti-tumour activity in an AML xenograft model. Two chemical probes, BI-7273 (1) and BI-9564 (2), were identified that should prove useful in further exploring BRD9 bromodomain biology in both in vitro and in vivo settings.
Most imaging studies in the biological sciences rely on analyses that are relatively simple. However, manual repetition of analysis tasks across multiple regions in many images can complicate even the simplest analysis, making record keeping difficult, increasing the potential for error, and limiting reproducibility. While fully automated solutions are necessary for very large data sets, they are sometimes impractical for the small- and medium-sized data sets common in biology. Here we present the Slide Set plugin for ImageJ, which provides a framework for reproducible image analysis and batch processing. Slide Set organizes data into tables, associating image files with regions of interest and other relevant information. Analysis commands are automatically repeated over each image in the data set, and multiple commands can be chained together for more complex analysis tasks. All analysis parameters are saved, ensuring transparency and reproducibility. Slide Set includes a variety of built-in analysis commands and can be easily extended to automate other ImageJ plugins, reducing the manual repetition of image analysis without the set-up effort or programming expertise required for a fully automated solution.
With many benefits and applications, immunochromatographic (ICG) assay detection systems have been reported on a great deal. However, the existing research mainly focuses on increasing the dynamic detection range or application fields. Calibration of the detection system, which has a great influence on the detection accuracy, has not been addressed properly. In this context, this work develops a calibration strip for ICG assay photoelectric detection systems. An image of the test strip is captured by an image acquisition device, followed by performing a fuzzy c-means (FCM) clustering algorithm and maximin-distance algorithm for image segmentation. Additionally, experiments are conducted to find the best characteristic quantity. By analyzing the linear coefficient, an average value of hue (H) at 14 min is chosen as the characteristic quantity and the empirical formula between H and optical density (OD) value is established. Therefore, H, saturation (S), and value (V) are calculated by a number of selected OD values. Then, H, S, and V values are transferred to the RGB color space and a high-resolution printer is used to print the strip images on cellulose nitrate membranes. Finally, verification of the printed calibration strips is conducted by analyzing the linear correlation between OD and the spectral reflectance, which shows a good linear correlation (R² = 98.78%).