49 research outputs found
Both Myoblast Lineage and Innervation Determine Fiber Type and Are Required for Expression of the Slow Myosin Heavy Chain 2 Gene
AbstractSkeletal muscle fibers express members of the myosin heavy chain (MyHC) gene family in a fiber-type-specific manner. In avian skeletal muscle it is the expression of the slow MyHC isoforms that most clearly distinguishes slow- from fast-contracting fiber types. Two hypotheses have been proposed to explain fiber-type-specific expression of distinct MyHC genes during development—an intrinsic mechanism based on the formation of different myogenic lineage(s) and an extrinsic, innervation-dependent mechanism. We developed a cell culture model system in which both mechanisms were evaluated during fetal muscle development. Myoblasts isolated from prospective fast (pectoralis major) or slow (medial adductor) fetal chick muscles formed muscle fibers in cell culture, none of which expressed slow MyHC genes. By contrast, when muscle fibers formed from myoblasts derived from the slow muscle were cocultured with neural tube, the muscle fibers expressed a slow MyHC gene, while muscle fibers formed from myoblasts of fast muscle origin continued to express only fast MyHC. Motor endplates formed on the fibers derived from myoblasts of both fast and slow muscle origin in cocultures, and slow MyHC gene expression did not occur when neuromuscular transmission or depolarization was blocked. We have cloned the slow MyHC gene that is expressed in response to innervation and identified it as the slow MyHC 2 gene, the predominant adult slow isoform. cDNAs encoding portions of the three slow myosin heavy chain genes (MyHC1, slow MyHC 2, and slow MyHC 3) were isolated. Only slow MyHC 2 mRNA was demonstrated to be abundant in the cocultures of neural tube and muscle fibers derived from myoblasts of slow muscle origin. Thus, expression of the slow MyHC 2 gene in thisin vitrosystem indicates that formation of slow muscle fiber types is dependent on both myoblast lineage (intrinsic mechanisms) and innervation (extrinsic mechanisms), and suggests neither mechanism alone is sufficient to explain formation of muscle fibers of different types during fetal development
Recovery of the Historical SN1957D in X-rays with Chandra
SN1957D, located in one of the spiral arms of M83, is one of the small number
of extragalactic supernovae that has remained detectable at radio and optical
wavelengths during the decades after its explosion. Here we report the first
detection of SN1957D in X-rays, as part of a 729 ks observation of M83 with
\chandra. The X-ray luminosity (0.3 - 8 keV) is 1.7 (+2.4,-0.3) 10**37 ergs/s.
The spectrum is hard and highly self-absorbed compared to most sources in M83
and to other young supernova remnants, suggesting that the system is dominated
at X-ray wavelengths by an energetic pulsar and its pulsar wind nebula. The
high column density may be due to absorption within the SN ejecta. HST WFC3
images resolve the supernova remnant from the surrounding emission and the
local star field. Photometry of stars around SN1957D, using WFC3 images,
indicates an age of less than 10**7 years and a main sequence turnoff mass more
than 17 solar masses. New spectra obtained with Gemini-South show that the
optical spectrum continues to be dominated by broad [O III] emission lines, the
signature of fast-moving SN ejecta. The width of the broad lines has remained
about 2700 km/s (FWHM). The [O III] flux dropped precipitously between 1989 and
1991, but continued monitoring shows the flux has been almost constant since.
In contrast, radio observations over the period 1990-2011 show a decline rate
inf the flux proportional to t**-4, far steeper than the rate observed earlier,
suggesting that the primary shock has overrun the edge of a pre-SN wind.Comment: 28 pages, including 3 tables and 7 figures, accepted for publication
in Ap
Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines
BACKGROUND: To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery. METHODOLOGY/PRINCIPAL FINDINGS: We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy. CONCLUSIONS/SIGNIFICANCE: For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of 'liquid biopsies' to better model drug discovery
New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients
<p>Abstract</p> <p>Background</p> <p>Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.</p> <p>Methods</p> <p>We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.</p> <p>Results</p> <p>285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.</p> <p>Conclusion</p> <p>We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets. </p
Design and methods for a randomized clinical trial comparing three outreach efforts to improve screening mammography adherence
<p>Abstract</p> <p>Background</p> <p>Despite the demonstrated need to increase screening mammography utilization and strong evidence that mail and telephone outreach to women can increase screening, most managed care organizations have not adopted comprehensive outreach programs. The uncertainty about optimum strategies and cost effectiveness have retarded widespread acceptance. While 70% of women report getting a mammogram within the prior 2 years, repeat mammography rates are less than 50%. This 5-year study is conducted though a Central Massachusetts healthcare plan and affiliated clinic. All womenhave adequate health insurance to cover the test.</p> <p>Methods/Design</p> <p>This randomized study compares 3 arms: reminder letter alone; reminder letter plus reminder call; reminder letter plus a second reminder and booklet plus a counselor call. All calls provide women with the opportunity to schedule a mammogram in a reasonable time. The invention period will span 4 years and include repeat attempts. The counselor arm is designed to educate, motivate and counsel women in an effort to alleviate PCP burden.</p> <p>All women who have been in the healthcare plan for 24 months and who have a current primary care provider (PCP) and who are aged 51-84 are randomized to 1 of 3 arms. Interventions are limited to women who become ≥18 months from a prior mammogram. Women and their physicians may opt out of the intervention study.</p> <p>Measurement of completed mammograms will use plan billing records and clinic electronic records. The primary outcome is the proportion of women continuously enrolled for ≥24 months who have had ≥1 mammogram in the last 24 months. Secondary outcomes include the number of women who need repeat interventions. The cost effectiveness analysis will measure all costs from the provider perspective.</p> <p>Discussion</p> <p>So far, 18,509 women aged 51-84 have been enrolled into our tracking database and were randomized into one of three arms. At baseline, 5,223 women were eligible for an intervention. We anticipate that the outcome will provide firm data about the maximal effectiveness as well as the cost effectiveness of the interventions both for increasing the mammography rate and the repeat mammography rate.</p> <p>Trial registration</p> <p><url>http://clinicaltrials.gov/</url><a href="http://www.clinicaltrials.gov/ct2/show/NCT01332032">NCT01332032</a></p