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VideoHive Using Electricity Multimeter 6068434
Stock Footage \ Science
Multimeter \ Instrument \ Device \ Videohive \ Measure \ Usefull \ Memories
Stock Footage - Using Electricity Multimeter 6068434 by Christian_Fletcher @ VideoHive
Stock Footage \ Science
Person is using the digital multimeter device for electonic measurements. A multimeter or a multitester, also known as a VOM (Volt-Ohm meter), is an electronic measuring instrument that combines several measurement functions in one unit. A typical multimeter would include basic features such as the ability to measure voltage, current, and resistance. A multimeter can be a hand-held device useful for basic fault finding and field service work, or a bench instrument which can measure to a very high degree of accuracy. They can be used to troubleshoot electrical problems in a wide array of industrial and household devices such as electronic equipment, motor controls, domestic appliances, power supplies, and wiring systems.
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Alpha Channel: No; Looped Video: No; Frame Rate: 29.97; Resolution: 1920x1080; Video Encoding: H.264; File Size: 112mb; Total Clip(s) Length: 0:23.
Snowing on Cemetery; Winter Sun; Winter Traffic Sign; Gecko Lizard; Big Burmese Python; Crawling Python Muscles; Beauty Ratsnake Crawling.
Keywords: Diagnose, OHMS, Volts, current, device, electric, electrical, electricity, instrument, measurement, power, resistance, service, tool, troubleshoot.


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To examine the relationship between perceived control of diabetes and physical and mental health components of quality of life in indigent adults with diabetes.
The primary variables, perceived control of diabetes and quality of life, were evaluated among188 patients from a low income clinic located at an academic medical center. Over a 12-month period, consenting subjects completed the surveys to assess perceived control of diabetes and health-related quality of life. Sociodemographic factors (age, gender, race/ethnicity, income, education, employment, marital status and insurance status) were collected as well as clinical factors like comorbid conditions and use of insulin therapy. Multiple linear regression models were used to assess the independent association of perceived control on quality of life.
The sample largely comprised middle-aged women with diabetes, a majority being black; nearly two-thirds had at least a high school education and almost three-quarters were unemployed. Mean quality of life scores were generally below national population means. Correlation results indicated a positive relationship between perceived control and both physical and mental quality of life. Regression results supported the positive association between perceived control and quality of life, even when controlling for sociodemographics and comorbidity in the final model.
Increasing perceived control, perhaps by a combination of education and skills building (i.e., self-efficacy), will result in higher perceived quality of life among disadvantaged populations with diabetes.
As the 7th leading cause of death, diabetes is one of the most prevalent chronic diseases in the United States, with nearly 24 million people (7.8% of population) affected. Diabetes is associated with other chronic illnesses such as cardiovascular disease and obesity, and severe complications such as retinopathy, neuropathy and nephropathy; all of these having an important impact in quality of life1-2. These patients require corrective glycemic control in order to reduce the risk of complications and significant deterioration of their health and quality of life3.
An important psychosocial factor related to adequate glycemic control is the construct of perceived control. Perceived control has been studied as a multi-dimensional construct and conceptually related to a cluster of control-related items4 such as self-efficacy (confidence in the ability to execute a behavior5), locus of control (extent to which individuals believe their health is controlled by internal and/or external factors6) and outcome expectancy (expectation that a specific outcome will occur)4,7. For the purpose of this study, perceived control is defined as a "patient-centered characteristic, associated with the perception that the patient's life is manageable, and being managed. It is a function of an individual's appraisal of the balance between perceived demands and available resources"8. The relationship between glycemic control, perceived control8,9 and quality of life1,3,10 has also been investigated. However, findings are often contradictory, indicating other variables are at play11. For example, Paschalides et al.12 did not find an association between perceived control and adequate glycemic control, while Hampson et al.13 found high perceived control associated with good glycemic control. Research also shows that a significant proportion of patients report that their quality of life is diminished because of the type of treatment they have to endure, particularly when these treatments are personally objectionable or overly burdensome14.
The perception of a poorer quality of life due to significant treatment burden may lead to lack of adherence to prescribed medication regimens. Conversely, studies employing 'patient empowerment' techniques15,16, in which patients experience both increased self-efficacy and increased perceived control over treatment, show that both glycemic control and treatment satisfaction improved16. Based on these findings and that there is still no conclusive knowledge regarding the role of perceived control over quality of life in patients with type 2 diabetes4,12,13, the present study examined the relationship between perceived control and both the mental and physical health aspects of quality of life in patients with type 2 diabetes. The primary hypothesis was higher levels of perceived control would be associated with higher ratings of physical and mental quality of life in these patients.
This study was conducted as part of a larger project funded by the Agency for Health Care Research and Quality. A combined records review and random participant invitation method was used to recruit participants, followed by a self-report survey which yielded data across the dependent measures of perceived diabetes control, health, and demographics specified below.
Medical Center Billing records were used from the prior year to identify all patients with type 2 diabetes in a primary care/indigent clinic of an academic medical center in the Southeastern United States (n=3600). A 10% random sample was selected (n=360) and patients were contacted by telephone and invited to participate in the study. Over a 12-month period, consenting subjects completed surveys to assess perceived control of diabetes, and health-related quality of life. Questionnaires were administered by a research assistant. Response rate was 60% and did not differ by race/ethnicity. Data were only collected on race/ethnicity for responders and non-responders, and there was no significant difference. The Institutional Review Board approved this study protocol. All demographic characteristics collected and reported here were based on self-report.
Age was assessed as a continuous variable but then categorized into three age categories (<50, 50–64 and 65+ years old). Race/ethnicity was based on self report. None of the participants were Hispanic, so the sample was categorized as white and black. Marital status was dichotomized as married versus not married. Years of education was assessed as a continuous variable but then categorized into three categories (less than high school graduate, high school graduate and beyond high school graduate). Insurance status was categorized as private, government (Medicare or Medicaid) and no insurance. Personal income was categorized as <$5,000, <$10,000, <$15,000 and $15,000+. Employment was dichotomized as employed versus unemployed. Comorbidity status was categorized as having 0-1, 2 or 3+ medical conditions. Current comorbid conditions were identified through chart audit and included: hypertension, heart disease, stroke, heart failure, chronic kidney disease, chronic obstructive pulmonary disease, peripheral vascular disease, chronic liver disease and cancer. The use of insulin therapy in diabetes management was assessed by answering 'yes' or 'no' and was included as a measure of disease severity.
Health-related quality of life was assessed with the Medical Outcomes Short Form 12 question scale (SF-12; version 1.0)17. The SF-12 is a brief self-report instrument and includes 12 questions about physical functioning, bodily pain, physical health problems, health perceptions, vitality, role limitation due to emotional problems and questions about general mental health. The SF-12 questions can be divided into a Physical Component Summary Score (PCS) and a Mental Component Summary Score (MCS) and corresponds well to these two sub-scores on the longer SF-36 (R squares of 0.911 and 0.918 for the Physical Component Summary scores and Mental Component Summary scores, respectively). The SF-12 also has good test-retest Reliability, with PCS alpha = 0.89; MCS alpha = 0.76. Finally, construct validity ratings are high when referenced to the SF-36 (PCS construct validity = 0.95 and MCS construct validity = 0.96)17.
Perceived control of diabetes was assessed with the revised 15-item Perceived Control Questionnaire (PCQ-R15)8,18. The PCQ-R15 measures the extent to which patients feel a sense of control over diabetes. PCQ-R15 items present statements that participants score on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The scale is scored as the sum of the items and means range from 5 to 75, with higher scores indicating greater perceived control. Reliability is good, with internal consistency at 0.94.
All analyses were performed using STATA v10.0 software19. Three main types of analyses were performed. First, demographic characteristics were assessed using t test for continuous variables and χ2 statistics for categorical variables. Second, correlation analyses were conducted to determine the association of perceived control with the physical and mental health summary scores for quality of life. Finally, three separate multiple linear regression models were constructed to assess the independent association of perceived control on quality of life, while controlling for potentially related demographic and clinical factors. In the first regression model, the continuous variable for PCS-12 and MCS-12 scores were entered as dependent variables and perceived control score as the independent variable. In the second model, demographic factors were added to determine the effects of perceived control on PCS and MCS scores over and above effects of age, gender/sex, race/ethnicity, marital status, education, employment, income, and insurance status. Finally, in the third model, clinical factors were also added and controlled, and included comorbidity burden and use of insulin therapy. All variables were included in the models because they were conceptually related to the outcome of interest.
A total of 188 patients with diabetes were enrolled in the study. Demographic characteristics of the total sample population are presented in Table 1. More than half the sample (54%) was in the 50-64 years age range. Females comprised over 71% and nearly 60% were black. The majority were not married (61%), approximately 62% had at least high school education and almost 72% were unemployed. There was a nearly equal distribution across income categories (between 22 and 26% in each). Over 54% reported having a governmental source of insurance but nearly 24% were uninsured. Half of the sample (50%) reported 0-1 medical comorbidities and most did not use insulin therapy (60%).
In assessing the level of perceived control for this sample population, the mean PCQ-R15 score was 55.5±8.70. Mean quality of life scores as measured by the PCS-12 and MCS-12 were 38.28±11.83 and 45.50±11.46, respectively. Table 2 presents the correlation coefficients between PCQ-R15 and PCS-12 and between PCQ-R15 and MCS-12. The size of the observed effect between PCQ-R15 and MCS2-12 was significantly large at r=0.53, representing a strong, positive relationship between perceived control and the mental health aspect of QOL. Similarly, the observed effect size between PCQ-R15 and PCS-12 was significant and medium at r=0.34, representing a moderate, positive relationship between perceived control and the physical health aspect of quality of life.
Finally, linear regression analyses were performed to examine the relationship between perceived control and each of the quality of life component scores (Table 3). The first model demonstrates a positive association between PCQ-R15 and both PCS-12 and MCS-12 such that as the perceived control score increased by 1 unit, the beta-coefficient for MCS-12 score increases by 0.72 points (95% CI 0.56 – 0.88) and for PCS-12 score increases by 0.49 points (95% CI 0.30 – 0.67). This unadjusted model accounted for 29.1% of the variance for MCS-12 and 12.4% for PCS-12. When controlling for demographic characteristics, the strength of relationship between PCQ-R15 and each component summary score mildly diminished such that the beta-coefficient for MCS-12 increases by 0.66 points and PCS-12 increases by 0.35 points for each unit change in PCQ-R15. This second model accounted for greater variance (34.4% for MCS-12 and 24.4% for PCS-12). In the final, fully adjusted model that included clinical factors the effect size and variance were only minimally changed.
As defined in this study, perceived control refers to the perception that one's life is manageable and being managed by self-actionable behaviors8. Wallhagen8 indicates perceived control may be central to how patients with type 2 diabetes deal with their illness. The present study supports the hypothesized relationship between perceived control and health-related quality of life. Specifically, perceived control was moderately correlated (r=0.53) with the mental health aspect of quality of life, and also significantly correlated (r=0.34) with the physical health aspect of quality of life. Although causality cannot be determined in correlation analyses, and it might be the case that higher quality of life estimates could lead to more perceived control (or some third factor could affect each of these factors); nonetheless, it seems logical that increasing one's perceived control, insofar as one's diabetes is concerned, will result in improved perceived quality of life. Using this information can be more clinically relevant with a thorough assessment of both the patient's knowledge of their medical regimen as well as their level of perceived control and self-efficacy. Such assessments can be followed by a tailored approach to educate patients about managing their diabetes and focusing on not only knowledge gain, but also more broadly on increased perceived control. That is, patients need to believe they have control over their diabetes through daily self-care practices, blood glucose self-monitoring, foot care, dietary and activity adjustments and medication adherence to achieve and maintain glycemic control and higher quality of life. As Gerstorf et al.20 stated, perceived control predicts improved physical and mental health, and perhaps longer life, but the role of mediating events requires more clarification.
Prior inconsistencies in the literature relating perceived control to quality of life may result from differences in construct definition or focus on other types of control such as locus of control, which is indicative of control orientation not of feeling to be in control8. Thus, it is important to both specify and extend studies in which perceived control is compared to other, slightly different measures or constructs of "control," such as self-efficacy and locus of control. Many studies have tried to establish commonalities and differences between these constructs, with the majority focused on the relationship of increased self-efficacy to improve health outcomes4,7,21-23. Additional research is needed in this area to clarify the importance of perceived control to quality of life24 and ultimately, how perceived control is related to the impact and self-management of diabetes through glycemic control (including the interaction of other control-related constructs and psychological factors related to and affecting perceived control such as depression)20. In this way, interventions may be tailored to address perceived control according to individual patient characteristics. For example, the predictive value of perceived control on quality of life and diabetes-related outcomes likely varies with locus of control orientation and coping style. Individuals with a more external locus of control and emotion-focused (as opposed to problem-focused) coping style may not display a strong relationship between perceived control and quality of life or glycemic control. By contrast, individuals with a more internal locus of control and problem-focused coping style will demonstrate a stronger impact of their perceived control on adhering to appropriate diabetes self-management behaviors as well as a prescribed treatment regimen. In the present study, it was clear that perceived control was related to self-reported quality of life. However, future research should investigate whether perceived control is also related to outcomes such as medication adherence and glycemic control.
This study has several strengths including being adequately powered to detect a significant effect of perceived control on quality of life and showing reliability of the perceived control scale (PCQ-15R) in a low-income sample of African American patients with type 2 diabetes. However, improvements to this study that will inform future research should also be noted. The study comprised a relatively homogeneous sample that limits generalizability of these findings to other racial/ethnic groups and those of higher socioeconomic status. Thus, these findings may not be reflective of the larger diabetes population; however, it is likely more applicable to those with poorer diabetes control and more disadvantaged population. Also, health literacy was not measured but was shown to be independently associated with poor diabetes knowledge and poor self-management practices25; therefore, it is important to study when examining perceived control, glycemic control and medication adherence. The sample comprised mostly women (71.3%). Some investigators26 have posited that there might be a difference in terms of how women and men confront life-events, and samples with sufficient numbers of both genders will be necessary to answer these questions.
The study findings mesh nicely with those of Howorka et al.16, who found that 'empowered' patients, or those with both a sense of self-efficacy and perceived control over their medical situation (treatment choices and decision making), reported higher quality of life and had better glycemic control. Thus, treatment adherence outcomes may depend, in part, on the extent to which patients feel that the decision making process is under their control. Achieving control will probably require more than enhancing self-efficacy through education. Instead, such education should be complimented by efforts that focus on increasing a patient's perceived control over treatment choices and diabetes management.
This study was funded by grant 5K08HS11418 from the Agency for Health Care Research and Quality, Rockville, MD (PI – Leonard Egede MD).
Conflict of Interest: None of the authors have any financial disclosure or conflict of interest to report.
PubMed Central Canada is a service of the Canadian Institutes of Health Research (CIHR) working in partnership with the National Research Council's national science library in cooperation with the National Center for Biotechnology Information at the U.S. National Library of Medicine(NCBI/NLM). It includes content provided to the PubMed Central International archive by participating publishers.

subset: commoncrawl


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Finding a Missing Link: Scientists show a new connection between inflammation and cancer
For more than 100 years, researchers have sought links between inflammation and cancer. Now, a team of scientists studying gastrointestinal cancer in mice presents powerful evidence of a molecular connection between those conditions.
In two experiments, researchers at the University of California, San Diego showed that deactivating a protein called I-kappa-B kinase beta (IKK-beta) inside cells stops cancer progression in its tracks.
IKK-beta normally plays a role in healing. During infection or injury, immune system molecules activate IKK-beta. Once stimulated, this protein keeps cells alive and growing, despite the insult. IKK-beta also promotes inflammation in damaged tissues.
These effects could be a double-edged sword in the presence of carcinogens, says molecular biologist Michael Karin. Before the experiments, he speculated that, by preventing programmed cell death and encouraging inflammation, IKK-beta also promotes the emergence and growth of tumors.


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Start to Finish: 90 to 100 minutesServings: 4 to 6Difficulty Level: Beginner
Roasting gives eggplant rich, delicate flavor that's delicious on its own, but is also an ideal canvas for your favorite seasonings. Maximizing flavor from this sometimes under-appreciated vegetable hinges on salting the slices and letting them sit for a while before roasting them. This mellows the sometimes bitter flavor, leaving you with a fragrant side dish that's easy enough for any night of the week -- but elegant enough to be worthy of a special occasion.
- 2 large eggplants
- 1/3 to 1/2 cup kosher salt
- 1/4 cup olive oil
Rinse the eggplants under cold water and wipe them dry with a clean paper towel.
Peel the skin, if desired. Although most varieties have skin that can be a bit on the tough side, leaving the skin on helps hold the slices together, adds texture and boosts the nutrients in your dish.
Slice the eggplants crosswise with a clean, sharp knife to make 1/2-inch-thick slices.
Arrange the slices on a baking sheet lined with paper towels and liberally sprinkle both sides with salt.
Salting the eggplant before cooking it helps minimize bitterness and prevents it from absorbing too much oil during the roasting process.
Let the salted eggplant slices sit at room temperature for approximately 1 hour before rinsing them thoroughly to remove the excess salt. Lightly press each slice to get rid of excess moisture and pat each dry.
Preheat your oven to 450 degrees Fahrenheit. Meanwhile, prepare 2 baking sheets by lining them with foil and applying a light coating of olive oil.
Divide the slices between the 2 sheets, placing them in a single layer.
Sprinkle the eggplant with salt and pepper and roast them for 20 to 30 minutes without flipping them. When the slices are cooked, they should be golden and tender.
With its light flavor, eggplant pairs well with a variety of spices and seasonings. At a minimum, finish your roasted eggplant with a sprinkle of salt and a little cracked black pepper to enhance the deep flavor achieved during the roasting process. Some other seasoning ideas include the following:
- Grab a small bundle of fresh herbs -- basil, oregano, parsley, mint and thyme all add distinctive flavor. Remove the stems and roll large leafy herbs such as mint or basil into a cigarlike shape and chiffonade it by cutting the roll crosswise into thin strips. Roughly chop smaller-leaved herbs such as parsley or thyme with a sharp knife. Sprinkle fresh herbs over the hot roasted eggplant slices.
- Drizzle the slices with a good-quality vinegar such as balsamic, red wine or champagne to add a bright, tangy acidity that contrasts with the creamy richness of the eggplant.
- Sprinkle a small amount of cheese on top of the roasted slices. Feta, ricotta salata, Parmesan or Romano all add a punch of flavor.


text: HOw many of you have checked out the Skype app? I bet you were just as disappointed as I was, and the ratings for it on the Market werent exactly applauding Skypes' (for android) 'features'. Is there any way to actually use my Evo to communicate with skype users? I have an unlimited plan, so Im assuming I automatically fall out of Skypes target demographic for this app as it does nothing more than drain my battery, and not bring any features to the table. Which idiot thought it would be wise to use Skype without implementing its only feature worth using? Im mad, very mad, as there is no way to communicate on a visual basis with the only [lets get real for a second here] really recognized Voice-Chat program.


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This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene (tumour protein p53) in a group of breast cancer patients with long-term (12 to 16 years) follow-up.
The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using temporal temperature gradient gel electrophoresis and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42 K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples.
Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. Breast cancer cases in the 'basal-like' and 'ERBB2+' gene expression subgroups had a very high mortality the first two years, while the 'highly proliferating luminal' cases developed the disease more slowly, showing highest mortality after 5 to 8 years. The TP53 mutation status showed strong association with the 'basal-like' and 'ERBB2+' subgroups, and tumors with mutation had a characteristic gene expression pattern.
TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease.
The evidence suggesting that molecular profiling can refine breast cancer prognosis are so far promising. From cDNA microarray analysis of locally advanced breast carcinomas, Perou and colleagues [1] identified five subgroups based on their distinct gene expression patterns. The subgroups were shown to differ with respect to outcome [2], and have also been identified in other datasets [3]. van't Veer and colleagues [4] analyzed node-negative breast cancer patients under the age of 55 years using DNA microarrays and identified a 'poor prognosis signature' that predicted short interval to distant metastasis. A larger set of samples was studied by van de Vijver and colleagues [5] to confirm the predictive value of this signature in women under 53 years of age. Other datasets have been analyzed with similar findings of molecular subgroups with different clinical outcomes [6-10]. However, there are few published studies with a relatively large number of patients with long-term follow-up.
Several well-established clinical, histopathological and molecular factors are today used as prognostic and predictive markers of breast cancer. These include patient age, tumor size, lymph node status, presence of distant metastasis (TNM-stage; tumor, node, metastasis), histological type, tumor grade, and estrogen receptor (ER), progesterone receptor (PR) and ERBB2/HER-2 status. Improvements of prognostic criteria have been achieved by optimally combining available markers. The National Cancer Institute [11] and St Gallen Conference [12] provide adjuvant treatment guidelines based on these markers. Currently, TNM-staging [13], the Nottingham Prognostic Index [14] and Adjuvant Online [15] are the most commonly used integrated prognostic models.
TP53 mutation status is rarely obtained for routine analysis, despite accumulating evidence of its prognostic value. Mutations in the TP53 gene have been reported to be present in more than half of all cancer cases [16]; however, the frequency shows variation between types/subtypes of cancer. In breast cancer, the frequency of TP53 gene mutations is approximately 20% to 30%. Acquiring a TP53 mutation has been suggested to be an early event in breast cancer development and it is related to poor prognosis and chemo resistance [17]. Allelic imbalance (AI) (or loss of heterozygosity (LOH)) at chromosome location 17p13, where the TP53 gene is located, has been reported in more than half of breast carcinomas [18]. Traditionally, AI is considered as an additional event eliminating the TP53 tumor suppressor function.
In this study we address the question of whether gene expression profiles offer better prognostic information in patients with long-term follow-up. We performed univariate and multivariate analysis of seven standard markers and TP53 mutation status for the total group of breast cancer patients. We then analyzed a large subset of these tumors using cDNA microarrays and assigned the samples to five previously defined molecular expression groups. The strength of gene expression-based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. This is the first report that includes both gene expression groups and TP53 mutation status in a multivariate analysis.
A series of 212 primary breast cancer cases were studied; 80 of these tumors were analyzed using cDNA microarrays, along with one normal breast tissue sample collected from breast reduction surgery. Patient samples were sequentially collected at Ullevål University Hospital from 1990 to 1994 (IRB approval 350, protocol 75026). The last update of patient information was done in 2006, providing an observation time of 12 to 16 years. Patients were followed until death or emigration, and only 12 patients were lost to follow-up. The average age of the 80 cases analyzed by cDNA microarrays was 65.0 years at time of primary surgery (range 28.2 to 87.7 years), similar to the average age of 64.4 years (range 28.2 to 91.5 years) for the total series. The 80 cases were selected from the total series based only on sufficient amount of fresh frozen tissue for microarray analysis. Consequently, a slightly higher fraction of patients with larger tumor size was observed in this subcohort. A summary of the clinical and histopathological data of the patients is shown in Table Table11 (see Additional file 1 for more detailed information). All patients were treated according to Norwegian national guidelines at the time of diagnosis [19]. Patients receiving adjuvant systemic therapy were given nine courses of CMF (cyclophosphamide, methotrexate, 5-fluorouracil) and/or Tamoxifen for two years. Dosage of radiation given as adjuvant treatment was dependent on indication; after breast conserving therapy the mammary gland was given 50 Gy (2 Gy × 25). The number of samples entered into the survival analyses is smaller than 212 (full dataset) and 80 (subset with gene expression data); excluding patients with missing information or distant metastases at the time of diagnosis and primary surgery, leaves us with a maximum number of 200 (full set) and 77 (subset) patients.
Primary breast carcinoma tissue was snap frozen and stored at -80°C. Frozen sections stained with hematoxylin/eosin were reviewed to confirm tumor content, and specimens in which at least 5% of the cells were carcinoma cells were included in this study. The majority of samples (80%) analyzed using microarrays had at least 40% tumor cell content. Sections from paraffin embedded tissue were re-evaluated by an experienced breast pathologist (JMN) to classify and grade the carcinomas according to the modified Scarff-Bloom-Richardson method [20] (Table (Table11).
DNA was isolated from both peripheral blood cells (leukocytes) and tumor tissue using chloroform/phenol extraction followed by ethanol precipitation (Nuclear Acid Extractor 340A; Applied Biosystems, Foster City, California, USA) according to standard procedures. TP53 mutation detection in tumor DNA was performed by prescreening exon 2–11 using temporal temperature gradient gel electrophoresis (TTGE) [21]. Samples with aberrant migrating bands from TTGE were sequenced (ABI PRISM™ 377 DNA Sequencer, Applied Biosystems) to determine the nature of the mutation. AI analysis was performed using the ABI 310 capillary electrophoresis on two different highly polymorphic markers in the TP53 locus, one located in intron 1 [22] and the other downstream of exon 11 [23]. AI was scored according to a threshold of 0.84 (ratio between two allele variants in tumor divided by ratio between two alleles in blood) [24]. At least one of the polymorphic markers had to show AI to score positive. The ER and PR were analyzed using both immunohistochemistry (IHC) and biochemical/ligand-binding assay (Abbott Diagnostics, Abbott Park, Illinois, USA). The results from IHC were used in our data analysis since that is the current recommended method; however, in a few cases where IHC had not been performed, results from a biochemical/ligand binding assay were used.
Total RNA was isolated from snap frozen tumor tissue using TRIzol® solution (Invitrogen™, Carlsbad, California, USA). The concentration of total RNA was determined using an HP 8453 spectrophotometer (Hewlett Packard) and the integrity of the RNA was assessed using a 2100 Bioanalyzer (Agilent, Santa Clara, California, USA). Linear amplification of total RNA was performed using an optimized protocol previously described [25]. Amplified tumor RNA was labeled by Cy5 and amplified RNA from Universal Human Reference total RNA (Stratagene®, La Jolla, California, USA) was labeled by Cy3. The labeling and hybridization of amplified RNA to cDNA microarrays, containing more than 42,000 elements, was performed as previously described [25]. Experimental protocols can be found at the referred web site [26]. Images of the arrays was acquired using a Gene Pix 4000B scanner (Axon Instruments, Sunnyvale, California, USA), and analyzed using Gene Pix Pro 3.0/4.0/4.1 software and by visual inspection. Data were entered in the Stanford Microarray Database [27], and intensity levels were normalized. Data were filtered for spot quality and included in the analysis if the pixels within a spot showed a regression correlation of at least 0.6 or if the signal intensity of both sample and reference were at least 1.5 over background. A hierarchical clustering algorithm integrated into the Stanford Microarray Database was applied to group genes and samples on the basis of their similarities in expression, and the results were visualized using TreeView [28] and Java TreeView [29] software (for analysis software links, see [30]). Prior to clustering analysis, the data were centered to median expression of each gene across the dataset. The hierarchical clustering shown in Figure Figure11 was performed using previously described 'intrinsic' genes [3] consisting of 540 clones (representing 496 genes corresponding to a single unique UniGene cluster) whose expression was measurable in at least 70% of the samples. The 'intrinsic' set of genes consisted of genes with significantly greater variation in expression between different tumors than between paired samples from the same tumor, the name reflecting that genes were selected to optimally identify intrinsic characteristics of breast tumors.
In the analysis of breast cancer death for all patients and for patients with gene expression data, we used the Kaplan-Meier estimator and univariate Cox regression to assess the marginal effect of each factor (that is, when not correcting for the effect of other factors). The joint effect of two or more factors was assessed using multivariate Cox regression. A parsimonious Cox regression model with only significant factors was obtained by backwards elimination starting with all factors, and the final model was checked for all possible two-factor interactions. The P value for the total effect of a factor was calculated from the (partial) likelihood ratio statistic, while the Wald test statistic was used to compute the P value for each level of a multilevel factor. The proportional hazards assumption of Cox regression was checked using the test of Grambsch and Therneau [31] with Kaplan-Meier weights as implemented in S-PLUS (version 6.1 for Windows. Insightful Corporation, Seattle, Washington, USA).
Pearson correlation analysis was used (Microsoft Excel 2000) to find the correlation between the gene expression profile of a single sample and five previously defined centroids [3]. The five centroids were based on a set of tumor samples from advanced breast cancer cases and represent the average expression profiles of sample subgroups defined by hierarchical clustering using genes that showed more similar expression between two samples from the same tumor than between any other tumor ('intrinsic' genes). Cross-tabulation and Pearson X2-test or Fishers Exact test (when appropriate) were performed using SPSS (version 13.0. SPSS Inc, Chicago, Illinois, USA) when studying distribution of clinical, histopathological or molecular genetic parameters. Genes with potential significant changes in expression between tumors having TP53 mutations and tumors with wild-type TP53 were identified using the significance analysis of microarray (SAM) procedure [32,33]. Data from 27,393 clones whose expression was measurable in at least 80% of the samples were included in the analysis.
The 80 breast tumor samples were assigned to five different subgroups according to their gene expression pattern; luminal A, highly proliferating luminals, normal-like, basal-like and ERBB2+. The assignment of tumors into subgroups was based on hierarchical clustering using the 540 previously identified 'intrinsic' genes. The resulting dendrogram showed two main groups of breast tumors (Figure (Figure1);1); those with high expression of the ER-related gene cluster and luminal type characteristics (left branch), and those showing a lower relative expression of the ER-related cluster (right branch). Further subdivision of the samples identified five groups similar to those previously described [2] also in this set of breast tumors. The correlation between the gene expression profile of each sample and five previously described centroids [2] were calculated and a scatter chart was made (Figure (Figure2)2) according to the order of samples in the dendrogram from hierarchical clustering (Figure (Figure1).1). The correlation of each sample to each of the centroids showed a continuous wave pattern over the sample set, and visualized how each sample carries elements from different profiles. The luminal A and basal-like breast tumors showed a pronounced opposite proportional pattern.
In the subsequent Cox regression analysis the breast tumor samples were assigned to five subgroups based on hierarchical clustering, combined with the pattern of centroid correlation and fine-tuned by gene expression pattern of characteristic subgroup markers. It should be emphasized that the classification method is unsupervised, meaning that the samples are grouped solely based on the gene expression data.
In Table Table22 (Univariate analysis) relative risks (hazard ratios) with 95% confidence intervals (CI) of univariate Cox regressions for all factors considered are shown. P values for testing the hypothesis of no marginal effect of a factor and its levels are also given. Tumor size and TP53 status are the two most significant factors, but lymph node status also has a significant effect. Patients with TP53 mutations have a breast cancer death rate that is four to five times higher than for those without mutations. Patients with tumor size T3–T4 have a breast cancer death rate that is about four times higher than for those with tumor size T1, while patients with tumor size T2 have a breast cancer death rate that is about double that of those with size T1. Patients with four or more positive lymph nodes have a breast cancer death rate that is about three times higher than for those with negative lymph nodes. The effect of TP53 status and tumor size on breast cancer death is also shown in the Kaplan-Meier plots of Figure Figure2a.2a. The high number of patients with the heterogeneous grade 2 probably explains why grade is not as strong a prognostic marker as expected in this series of samples. In a multivariate Cox regression model obtained after elimination of all non-significant factors, the TP53 status, tumor size and lymph node status are the only significant remaining factors (Table (Table2,2, Multivariate analysis), and their effects are about the same as in the univariate analysis.
By performing univariate Cox regressions on the samples included in the array experiment for all factors considered, TP53 mutation status, gene expression group, tumor size and lymph node status were all significant factors for survival (Table (Table3,3, Univariate analysis). The effect of tumor size is somewhat larger than for the analysis of all patients, while the effect of TP53 status is somewhat smaller. The gene expression groups have a large effect on survival. The breast cancer death rates for the highly proliferating luminal, the basal-like and the ERBB2+ groups are about six times higher than for the luminal A group, while the breast cancer death rate for the normal-like group is almost three times that of the luminal A group. As the assumption of proportional hazards is violated for the highly proliferating luminals, the relative risk estimate for this group should be interpreted as an average over the time period considered. The effect of TP53 mutation status and tumor size on breast cancer death is also shown in the Kaplan-Meier plots in Figure Figure3b,3b, while Figure Figure3c3c gives the Kaplan-Meier plot for the five gene expression groups. The non-proportionality of the hazard of highly proliferating luminals is clearly seen in the latter.
In a multivariate Cox regression model obtained after elimination of all non-significant factors, TP53 mutation status and lymph node status are the significant remaining factors (Table (Table3,3, Multivariate analysis). Gene expression groups and tumor size were the last factors to be eliminated. TP53 mutation status and gene expression group are closely related; 17 of the 20 patients with TP53 mutation are in the basal-like or ERBB2+ group. This makes it difficult to separate the effect of TP53 from the effect of the gene expression groups. TP53 mutation and lymph node status are the strongest predictors of survival in the multivariate analysis, with effects of about the same size as in the univariate analyses.
Our set of samples was also classified according to three previously described gene lists [4,8,9]. By clustering the samples using the genes overlapping with our arrays, the samples were separated into two main branches in each dendrogram; predicted to be a good prognosis group and a poor prognosis group. Although the genes on our arrays did not overlap with all genes from the respective lists and the respective score procedure in each paper was not followed, it was interesting to see whether the gene lists had significance using this simple approach. In univariate Cox regression analysis two of the gene lists were significant in predicting breast cancer survival (15/21 genes: relative risk (RR) 3.70, 95%CI 1.64 to 8.34, P = 0.0007; 63/76 genes: RR 2.24, 95%CI 1.09–4.61, P = 0.028), while the third was close to being significant despite the limited number of overlapping genes (26/70 genes: RR 1.99, 95%CI 0.93 to 4.26, P = 0.067). None of the classifiers were significant when included in multivariate analysis together with the variables listed in Table Table3,3, a result where the interpretation should be made according to the previous stated limitations of our approach.
The most striking characteristic of the basal-like and ERBB2+ subclusters (Figure (Figure4)4) was that most cases carried a TP53 mutation in their tumor. In the basal-like dendrogram branch 83% (10/12) of the carcinomas harbored a TP53 mutation, and in the ERBB2+ subcluster the fraction was 70% (7/10). In the two basal-like tumors with wild-type TP53 (Figure (Figure4)4) the mutations may have been missed, or other components of the pathway may have been affected. The basal-like subcluster showed a higher correlation between the samples in the dendrogram compared to other subclusters, as well as higher correlation to the 'basal-like centroid' (Figure (Figure2),2), which may reflect the strong impact of a TP53 mutation on the global transcription program.
Most of the TP53 mutations detected among the 80 samples analyzed on the microarray (17/20, 85%) and among the total series of samples (39/48, 81%) were missense mutations, which is the type of mutation most frequently found in TP53 [34]. Only three samples outside the basal-like and ERBB2+ clusters were affected with TP53 mutations; two missense mutations outside the DNA binding domain (codon 113, codon 138) affecting the highly proliferating luminals and one frequent missense mutation in the DNA major groove interacting domain (codon 273) affecting the luminal A group. Figure Figure44 further shows that IHC detected only 50% (10/20) of the mutations detected by TTGE. Almost half of the samples analyzed had AI (LOH) of TP53 in their tumor tissue (array: 19/41, 46%; total: 47/98, 48%), and LOH was strongly associated with the presence of a TP53 mutation (p < 0.001). Among the samples analyzed using microarray analysis, the samples with the highest frequency of AI seemed to cluster in the outermost three subgroups with the poorest outcome (basal-like, ERBB2+ and highly proliferating luminal groups). Interestingly, the highly proliferating luminals showed a high frequency of AI (7/8, 88%) despite a low frequency of mutations in the TP53 gene.
Although the relative expression level of TP53 mRNA measured using microarrays showed variation between individual samples, the basal-like and ERBB2+ groups, which had the most TP53 mutants, clearly showed the highest mRNA expression, while the luminal group had intermediate expression and the normal-like group had a lower expression (the data were centered to median expression across the dataset; Figure Figure4).4). Two of the three mutated samples falling outside the basal-like and ERBB2+ groups had mutations that gave a lower relative expression of TP53 mRNA.
SAM analysis was performed to find the gene expression pattern specific for tumors containing a TP53 mutation. With an estimated median number of false negatives being zero (delta slider 1.56 and fold change 2.0), 377 significant clones were selected when analyzing a set of 27,393 cDNA clones (Additional file 3). The highly specific gene expression pattern associated with TP53 mutation status is illustrated in Figure Figure5,5, where hierarchical clustering of the 80 samples and 80 selected genes (the 40 most significantly upregulated and 40 most downregulated genes of the 377 genes) are shown. Many genes that showed higher relative expression in carcinomas with a TP53 mutation were involved in the cell cycle and cell proliferation (for example, CCNB2, CDCA5, CENPA, and UBE2C), while the genes with lower relative expression showed more diverse functions and were highly associated with ER status (for example, IRS1, ESR1, DNAL1 and NAT1). Some of the genes (for example, MYBL2, CDCA8, DNALI1 and DACH1) were also identified recently by Miller and colleagues [35] as part of a 32-gene expression signature that distinguishes TP53 mutant and wild-type tumors. Further investigation of the gene expression pattern of different TP53 mutations is needed to understand more about the different effects they have in breast cancer.
The distribution of clinicopathological markers between the gene expression subgroups is shown in Figure Figure4.4. The subgroups that showed the poorest survival had the largest difference in median age, members of the basal-like and ERBB2+ groups being the youngest (median age 56 years (28 to 75) and 60 years (47 to 87), respectively) and those of the highly proliferating luminal group the oldest (median age 75 years (59 to 82)). Dividing the patients into two equally large groups (<65 years and ≥65 years) gave a significant skewed distribution between the five gene expression groups (p = 0.019), but there was no significant difference when dividing them into pre- and post-menopausal women (<55 years and ≥55 years) (Figure (Figure4).4). Tumor size did not show a statistically significant skewed distribution between the gene expression groups, suggesting that the gene expression patterns provide new and different information compared to this established marker. Neither was node status associated with any particular gene expression group.
The histological type and grade, as well as ER and TP53 mutation status all showed a highly significant skewed distribution between the gene expression groups (p < 0.001; Figure Figure4).4). The ERBB2+ and basal-like groups showed the highest fraction of grade 3 tumors (80% and 58%, respectively). Although carcinomas of the luminal A and highly proliferating luminal subgroups were mainly grade 2, they differed by the fact that the luminal A group included 22% of cases with grade 1 and no grade 3 cases, while the highly proliferating luminal group included 27% of cases with grade 3 and no grade 1 cases. Among the luminal samples, 89% were ER positive, while none of the basal-like and only 30% of the ERBB2+-group were ER positive. The relative mRNA expression of ER (centered over the dataset) was compared to protein expression (IHC) and showed a strong correlation (Figure (Figure44).
Tissue samples with a low fraction of malignant epithelial cells were included in this study to increase our understanding of how this may affect a tumor's characteristic gene expression pattern. Samples with different percentages of malignant epithelial cells were distributed among all subclasses, although an over-representation (not statistically significant) of tumors with low tumor content were seen in the normal-like subgroups (Figure (Figure4).4). The invasive lobular carcinomas tended to have lower tumor content than invasive ductal carcinomas. Hierarchical clustering of samples with ≥40% tumor cells results in the same subgroups as when all samples were included. These results suggest that the gene expression profile of a grossly dissected tumor sample in many cases is not heavily influenced by a relatively low quantity of malignant cells, and that tumor stromal cells also may affect the gene expression profile.
Invasive ductal carcinomas were distributed among all subclusters, but entirely dominated the highly proliferating luminal, basal-like and ERBB2+ groups (Figure (Figure4).4). Invasive lobular carcinomas were divided into two groups, those clustering with the normal-like subgroup, previously referred to as 'typical-lobular' [36], and the 'ductal-like lobular' clustering with the two luminal groups (14/22 and 7/22, respectively). The only lobular samples clustering on the edge of the basal-like group were alveolar lobular with pleomorphic areas. Two tubulolobular carcinomas clustered together in the highly proliferating luminal subgroup, and three mucinous carcinomas clustered together in the luminal A subgroup, showing that the phenotypes distinguished by pathologists are also distinct on a molecular level. A fourth sample, an invasive ductal carcinoma, was part of the 'mucinous cluster,' showing a gene expression pattern similar to these tumors despite the fact that no typical mucinous elements in paraffin-embedded or frozen tissue sections from this patient were seen. The mucinous samples were all ER positive by IHC, TP53 wild type, ERBB2 negative and E-cadherin positive. A ductal carcinoma in situ with microinvasion and a metaplastic carcinoma clustered in the normal-like subgroup. The invasive ductal carcinoma sample from a man (ULL-020) clustered with the highly proliferating luminal group.
In the patient series analyzed here both uni- and multivariate analysis show that TP53 mutation status was a very pronounced prognostic factor. Although some studies have reported similar findings, others have found a weaker prognostic power for TP53 mutation status [37], which may be due to the mutation screening approach used (as well as population differences). The most frequently used method for mutation screening of the TP53 gene has been IHC, which detects only mutations that induce protein accumulation, missing frameshift, nonsense and splice mutations. In this study, several of the missense mutations with high levels of mRNA expression were also missed by IHC (Figure (Figure4),4), showing the insufficiency of this technique for mutation screening. The TTGE/sequencing analysis detected 15% of the TP53 mutations outside exons 5 to 8, supporting the importance of analyzing the whole gene and not only exons 5 to 8 as many previous studies have done.
A key issue is whether TP53 mutation status is a prognostic marker or instead a marker of therapy response only (predictive marker). The results in Table Table22 (Multivariate analysis) show the total effects of tumor size and TP53 status on survival, effects that may be direct and/or indirect via adjuvant treatment. When including adjuvant therapy in the multivariate analysis, RR values similar to those in Table Table22 were found (TP53, RR 5.1), indicating that the total effects are mainly a result of the direct effects, not indirect effects via treatment. Analysis of patients receiving surgery only (no adjuvant treatment) also gave similar result (TP53, RR 4.3). Although several studies have suggested that TP53 mutation status is a predictive factor [38,39], randomized large-scale studies are needed to make certain of this. TP53 mutation status may be both a predictive marker of some treatment regimes as well as a strong prognostic factor.
The strong correlation of TP53 mutations with the basal-like subtype is a biologically important finding, and whether it is the nature of ER-negative basal-like tumors that allows mutational events in the TP53 gene or that the basal-like gene expression profile is a consequence only of a TP53 mutation is unresolved and should stimulate further investigation on the origin of breast tumor cells. A related question to address in larger studies is whether the specific gene expression pattern we found associated with TP53 mutation status was a result of cellular events directly initiated by mutant TP53 or rather a result of the dominant cell type (basal-like progenitor or cancer stem cell) in these tumors. Similar questions apply to the ERBB2+ subtype, which also shows a strong correlation with TP53 mutations; in addition, the sequence and impact of the ERBB2 amplification versus the TP53 mutational event needs investigation. Sørlie and colleagues [2] reported in their patient cohort of locally advanced breast cancer a high frequency of TP53 mutations also within the luminal B samples (highly proliferating luminal cases). A relatively low frequency of TP53 mutations was found within the highly proliferating luminals (2/15) in our set of patients with earlier stage tumors. We propose that TP53 mutations may be an early and causal event in basal-like tumors whereas in luminal B (highly proliferating luminals) tumors it may be a consequence of genomic instability. The strong association found between AI and point mutations in the TP53 gene in the basal-like and ERBB2+ samples support the concept of TP53 acting as a tumor suppressor gene in these tumors [40], while the high frequency of AI despite a low frequency of TP53 mutations in the highly proliferating luminal group suggests a different mechanism for TP53 in these tumors.
There is a massive interest in defining gene expression profiles of breast tumors to understand the development and progression of the disease and to create a novel clinically useful diagnostic tool. Many reports are very promising, although the clinical and genetic heterogeneity of the disease does not make it straightforward to predict recurrence and outcome in individuals based on a snapshot of the biological processes in the individual tumor. Our study aimed to investigate the potential of gene expression profiling as a prognostic marker in patients with long term follow-up, and not to create yet another gene list associated with patient outcome. The extreme amount of variables (genes) and the relatively low number of cases and events increases the probability of accidental but apparently significant findings [41] in microarray analysis. In this study we have chosen an unsupervised approach for the classification of samples. The results certainly support the huge potential of information found in expression patterns, and the classification is shown to be a statistically highly significant predictor of survival.
The Kaplan-Meier plot (Figure (Figure3c)3c) illustrates a significant difference in survival between the different expression groups, as seen in previous studies [3]. Notice that the two groups with very poor prognosis had a diverse progression of disease. Breast cancer cases in both the basal-like and ERBB2+ groups had a very high mortality rate during the first two years, while the highly proliferating luminal cases developed the disease more slowly, showing highest mortality after five to eight years. We were not able to pinpoint any specific heterogeneity (clinical, histopathological or molecular markers) of the patients within the highly proliferating luminal cluster, the group showing non-proportional hazard, and suggest the curve reflects biological characteristics. Many patients with highly proliferating luminal cancer received Tamoxifen treatment for two years, and the poor outcome in this group compared to luminal A patients could be explained by the lack of a Tamoxifen effect. Alternatively, this anti-estrogen treatment may temporarily prolong patient survival in this group for the first years they receive the drug. The different progression observed in basal-like versus highly proliferating luminal patients may be consistent with the bimodal mortality rate reported by Demicheli and colleagues [42].
Different approaches have been used in an attempt to define clinically relevant groups based on gene expression patterns, but a consensus on how to do this has not yet been reached. In our study a classification similar to the one identified by Sørlie and colleagues [2] was obtained, supporting the existence of such subgroups in a broader spectrum of breast tumor stages. A few samples were, for various reasons, difficult to categorize. The lack of proliferation genes in the intrinsic gene list causes a less clear correlation with the luminal B centroid, but when proliferation genes from the total cluster (Figure (Figure1h)1h) were included the characteristics of the highly proliferating luminals (luminal B-like) compared to the luminal A group were clearly shown. Although the majority of luminal samples were most highly correlated with the luminal A-centroid, the group we named highly proliferating luminals is clearly different from the luminal A group in the scatter chart, having the second highest correlation with the luminal B-centroid (Figure (Figure2).2). We suggest that earlier stages of luminal B (here named highly proliferating luminals) may have less pronounced expression profiles than the advanced tumors where the centroids were defined (our data set versus Sørlie and colleagues [2]). The small cluster between the normal-like and the basal-like group shows highest correlation with the ERBB2-centroid, although this group demonstrates extremely low expression of both the ERBB2 gene (Figure (Figure1g)1g) and basal-like genes (Figure (Figure1f).1f). The samples seem more normal-like based on the fact that a normal breast tissue sample clustered within this group, as well as showing expression of genes previously identified to characterize normal-like samples. This small cluster illustrates the difficulties in assigning individual samples to subgroups based on correlation with centroids alone. The correlation of each sample with each of the centroids showed a continuous pattern over the sample set, and visualizes how each sample carries elements from different profiles (Figure (Figure2).2). In Figure Figure1g,1g, the ERBB2+ group on the far right side shows high expression of an ERBB2-related gene cluster and is, therefore, included in this group, despite the fact that its members also show correlation with the luminal B centroid. It is a matter of choice which group to assign these samples to. The ERBB2+ group is defined by a molecular event (overexpression of ERBB2), whereas the luminal B group is recognized by highly proliferating ER-positive tumors. Three samples do not show increased ERBB2 expression, but they are included in the ERBB2+ group based on their clustering. Although these samples express a low level of ERBB2 on the RNA level, it has been observed that the protein level (fluorescence in situ hybridization analysis) does not always correspond and thus may be high.
The combination of gene expression groups and clinical/histopathological parameters in this study has added more details and levels of understanding to our current picture of breast carcinomas. The long follow-up of patients revealed that the highly proliferating luminal group had an even worse prognosis than the basal-like and the ERBB2+ groups. The relatively good outcome for the first five years for the highly proliferating luminal group may be explained by the natural history of these tumors or by use of Tamoxifen. The strong association found between the basal-like group and TP53 mutations suggests that such mutations may be causal in these tumors, while TP53 mutations may be a later event in the highly proliferating luminal carcinomas. The high frequency of TP53 AI in the highly proliferating luminal group supports a mechanism other than TP53 mutations causing genomic instability in these tumors, and should be further explored. The characteristic gene expression pattern found in tumors carrying a TP53 mutation also needs further investigation in larger sets of samples with various mutations included.
Both TP53 mutation status and gene expression subgroups demonstrated strong prognostic impact, and may add valuable new information that complements the established prognostic markers. TP53 may help distinguish high risk tumors in need of treatment from among small, node negative tumors, which do not currently receive adjuvant treatment (that is, they are undertreated); on the other hand, it may help avoid treatment of individuals in patient groups that today may be overtreated. The choice of treatment may, for example, be influenced by avoiding drugs dependent on TP53-mediated apoptosis or, in the future, by using drugs that target and reactivate TP53. Although gene expression-based subgroups showed massive prognostic strength, a more robust classification method is needed for future application in clinical practice. Development of a new integrated prognostic model that includes TP53 and gene expression groups could be useful in the choosing of treatment.
AI = allelic imbalance; CMF = cyclophosphamide, methotrexate, 5-fluorouracil; ER = estrogen receptor; IHC = immunohistochemistry; LOH = loss of heterozygosity; PR = progesterone receptor; RR = relative risk; SAM = significance analysis of microarray; TTGE = temporal temperature gradient gel electrophoresis.
The authors declare that they have no competing interests.
AL collected updated clinical data, participated in revising the histology, carried out the gene expression analysis, organized the TP53 mutation analysis, participated in the design of the study, performed some statistical analysis and drafted the manuscript. HZ carried out parts of the gene expression analysis. ØB participated in the design of the study and carried out the statistical survival analysis. JMN carried out the histology analysis. IRKB and TI collected clinical and molecular data. RK collected the patient material. ALBD conceived of the study, participated in its design and coordination and helped draft the manuscript. SSJ participated in the design of the study, coordinated the gene expression analysis and helped draft the manuscript. All authors read and approved the final manuscript.
A table listing clinical information (array).
A table listing TP53 associated genes.
A table listing TP53 mutations.
A figure showing the hierarchical clustering using the total set of genes.
This work was supported by Public Health Service grant U01CA85129 from the National Cancer Institute, National Institutes of Health, the California Breast Cancer Resesarch Program of the University of California, Grant Number 10EB-1086, the European Union's 6th framework program on Mutant TP53, SalusAnsvar Medical Prize, the Norwegian Cancer Society grant D99061 and The Research Council of Norway grant 155218/300. AL has during this work been a research fellow of the Norwegian Cancer Society and is currently post doc in the European Union's 6th framework program on Mutant TP53.
PubMed Central Canada is a service of the Canadian Institutes of Health Research (CIHR) working in partnership with the National Research Council's national science library in cooperation with the National Center for Biotechnology Information at the U.S. National Library of Medicine(NCBI/NLM). It includes content provided to the PubMed Central International archive by participating publishers.


text:
Bad Company in Concert: Merchants of Cool Trailer (2002)
"17 tracks recorded live at the Paramount Theatre in Denver" 21 May 2002 84 mins
Merchants of Cool, a live album selected from gigs in Denver and Anaheim in 2002, sees them at their strongest in years. With Rodgers and drummer Simon Kirke from the original outfit and guitarist David "Bucket" Colwell, now a member of more than 10 years' standing, they're supremely tight, running through a succession of hits like "Can't Get Enough," "Feel Like Makin' Love," "Burnin' Sky," "Rock and Roll Fantasy," and Free's immortal "All Right Now." Mostly, the songs are well-honed and urgent, free from indulgent solos, but Rodgers--whose voice has always been Bad Company's main attraction--leaves too many choruses to the crowd.
Watch the official Bad Company in Concert: Merchants of Cool 2002 trailer in HD below or find more Bad Company in Concert: Merchants of Cool videos on Vidimovie.


text:
We're very happy to announce the arrival of new kittens
Jupiter male (grey and white) and Junon female arrived this morning.
Junon was born with her front left leg missing.
In France animals are named using the letter of the year, this year it's J. It's not an obligation, but many people follow the rule and it certainly helps when estimating/remembering what year your pet was born.
They were born in May, and I estimate they're between 12-14 weeks old. They're currently confined to the middle bedroom and I can hear then pattering around. They've decided the safest place, is the most inaccessible for us, inside the box base of the "click clack", a fold down sofa bed.


text:
AskMe - Renting in Highland
Albyn housing - part ownership
Asked on Aug 23 2016, Renting in Highland
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text:
New Orleans Hornets reserve Chris Andersen will miss at least five games after undergoing minor surgery on his infected right elbow.
Andersen split open his elbow during a Feb. 28 loss at the Dallas Mavericks
and required two stitches, but had been playing through the injury
until he missed Monday night's loss to the San Antonio Spurs.
"For two weeks we've tried to keep it clean, and he was on oral antibiotics, but he kept opening it up," trainer Terry Kofler said
"He opened it up real good the other night (against
Milwaukee) and came in Sunday and it was swollen."
Andersen had the elbow cleaned out on Sunday and remained in the hospital Tuesday afternoon, team spokesman Harold Kaufman said.
Andersen has averaged 10.1 points and nine rebounds during his
last eight games. His absence left the Hornets with nine players
against the Spurs. George Lynch missed his second straight game
following his mother-in-law's death.


text:
These cabinets resist acid, corrosion and rust. Ideal for food service, wash-down and clean room environments. Durable 18-Gauge, type 304 stainless steel construction. 4-Adjustable shelves on 2 in. increments plus bottom shelf.
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- Tray design shelves with side/back and front lips
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text: A friend of mine is coming into town on Saturday to take me to dinner! He wants to go some where fancy, and told me to choose. I'd like to go to a nicer restaurant (any location in Manhattan, any style of food) that's not terribly expensive (a la Per Se or Masa.) I've recently been to Eleven Madison, which I love, and to Tabla, so they're out. Any suggestions? Thank you in advance for any help you can provide.


text: Judiciary NRL casualty ward: Finals Week 3 The latest injury and suspension news for all 16 clubs in the 2017 NRL Telstra Premiership. Thu 21 Sep 2017, 9:00AMStaff writers, NRL.comBlair fined for Friend trip Brisbane prop Adam Blair has pleaded guilty to trippingand received a $1,100 fine. Mon 11 Sep 2017, 3:15PMLussick free to play, Tetevano cops one Roosters forward Zane Tetevano will miss one match for a high tackle while Manly's Darcy Lussick has been found not guilty of tripping and is free to play. Tue 05 Sep 2017, 9:00PMWallace cops three-match ban Gold Coast Titans forward Jarrod Wallace has been suspended for three matches for a shoulder charge on Bulldog Moses Mbye. Tue 29 Aug 2017, 10:00AMPapali'i charged with dangerous contact Warriors forward Isaiah Papali'i can avoid suspension despite being hit with a dangerous contact charge from Sunday's golden point loss to Manly. Mon 28 Aug 2017, 11:57AMWests Tigers duo, King charged Michael Chee-Kam and Matt McIlwrick are facing a week out after the pair were charged for incidents in Wests Tigers' loss to the Cowboys. Sat 26 Aug 2017, 4:58PMMatagi charged with tripping Parramatta forward Suaia Matagi has been charged with tripping Kodi Nikorima in Thursday's win over the Broncos. Fri 25 Aug 2017, 11:31AMSuspended Ma'u to miss Broncos clash Parramatta forward Manu Ma'u will miss the Eels' NRL clash with Brisbane due to a suspension for a shoulder charge. Mon 21 Aug 2017, 1:35PMMorris charged with lifting tackle Bulldogs winger Brett Morris has been charged with a grade one dangerous throw on Sea Eagles centre Brian Kelly. Mon 21 Aug 2017, 11:53AMHargreaves and Nofoaluma can escape ban David Nofoaluma and Jared Waerea-Hargreaves can both escape one-match bans with early guilty pleas after both were cited by the NRL match review committee. Sun 20 Aug 2017, 5:04PMMore


text:
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8 Dixon Ave #1, Amityville, New York 11701 - For Office Use Only. Great For Attorney, Accountant, Financial Consultant, Etc. For Office Use Only. Up & Coming And Very Convenient Location Right Off Of Route 110. Tenant Pays Gas, Electric And Cable/Internet. Inviting And Clean 2nd Floor Offices. Common Area Use Of Waiting Area. Ample Parking. Cable Ready.
Listing Courtesy of MR Imperial Real Estate


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Little "C" had her 1st day with us today. I spent some time sitting back and watching what she enjoyed and making some observations.
She seems really keen on the happyland toys and was focused for a good 15 minutes on this crane and conveyor belt.
She started buy looking at all the moving parts and turning handles, rotating the crane and opening the little hatch door. She tried to drop the bucket through the hole but worked out that it wouldn't fit. After exploring this for herself for a good amount of time, she asked me to help her and show her how it worked.
I showed her how to place the blocks in the bucket and then drop them on to the hatch. I drove a dump truck under it and then opened the hatch for the blocks to drop down. She loved that the dump truck was filled up and repeated the process herself several time.
I then showed her how to work the conveyor belt. Adding blocks at the bottom and turning the handle to make them go up and then they fell on to the hatch so they could fill the truck again. She was very keen to try it out for herself and, with some guidance, soon worked which way to turn the handle to get the desired movement.
Before long she was filling dumper truck after dumper truck with blocks using the 2 methods she had practiced and even drove the truck back around to the bottom of the conveyor belt so that she could reload it.
- Child selected play leading to self initiated learning.
- operating simple mechanical toys
- Showing an interest in technological toys with knobs and pulleys.
- Offer more toys with buttons, flaps and leavers.
- Offer a latches board to explore.
- Look at different mechanisms in our everyday life and see how they work.
Little "C" showed interest and determination for a prolonged period of time, showing fascination and wanting to understand how the toy worked. She showed and interest and curiosity in items in her environment and thought critically to try and work them. She was actively learning as she moved the different parts of the toy and tried to link each one. She sort help from others when she felt she could not work it out and watched carefully to what she was shown. Eager to give it a go for herself and showing a real "can do" attitude.
Today's play, meets the following EYFS Prime and specific areas:
- Communication and language
- Understanding the world.
- Physical Development


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... Title: JD Fertilizer Box Topper (all models) ... JD Fertilizer Box Topper (all models) Kinze Fertilizer Box Topper -all models ...
NON-AFFILITATION WITH COMPANIES MENTIONED. maywes.com is owned and operated by Pride Solutions LLC. Some of our products are compatible with brands listed as an aftermarket vendor. Pride Solutions LLC is not endorsed, sponsored by or affiliated with any other companies mentioned. All brands, copyrights, logos, likenesses, specific model numbers, and registered trademarks are property of their respective companies or organizations.


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Show off your love of football in comfortable style with the Antigua Men's Minnesota Vikings Icon Short Sleeve Polo Shirt, which is made of 100% polyester piqué with moisture-wicking Desert Dry™ fabric technology. Designed with a textured, tonal stripe pattern, this polo shirt features a team logo on the left chest to display your Vikings fandom and contrast coverstitch details at the cuffs, armholes and shoulders. 3-button placket. For additional NFL apparel, check out Academy.com.


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Superdry Womens Blue Vintage Logo Sequin T Shirt
Sorry, this item is unavailable to buy.
Superdry Vintage Logo Sequin T-Shirt in 'princeton blue marl' displays a cracked white Superdry print to the front and pretty sequin embellishment. The casual Superdry tee also displays '23' to the sleeve and finished with Superdry branding.
- Women's Blue Superdry T-Shirt
- Sequin Embellishment
- Cracked Front Print
Info & Care
- 55% Polyester
- 45% Cotton
- Wash at 30°C on Gentle Cycle
- Do Not Tumble Dry
- Hang to Dry
- Iron on Low Heat
- Do Not Dry Clean
Masdings aim to dispatch all orders placed before 15:30 on the same day, Monday – Friday excluding weekends and bank holidays. Please see the Delivery page for further information.
Masdings offer 7 delivery options across the UK, Europe and Rest of the world, for more details check the delivery page.
Please return the item(s) to us in their original condition complete with labels* within 14 days of receipt in a protective postage bag/box.
For more information please see the Shipping & Returns page.


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NEWARK -- They didn't start well and they certainly didn't finish well. For a team that professes to be in a playoff chase, the Islanders' desperation level rose for only about a 15-minute stretch of the second period in their 5-1 loss to the Devils Thursday night.
And that was long enough only to cut a 2-0 deficit to 2-1. Once the third period got under way, the Devils were dumping pucks, cycling around the Islanders and creating offense.
The final indicated a rout, which it wasn't, considering the Devils scored five times on only 20 shots, with three of the goals from Ilya Kovalchuk, who was by far the best player on the ice.
But it did reveal the Islanders' inability to be aggressive from the outset and stay that way until the end. And that hurts far more than a four-goal loss.
"Our chances are dwindling here, and every game we lose, we're that much closer to being out of it," said Andrew MacDonald, who banked a shot off Martin Brodeur at 16:21 of the second for the Isles' lone goal. "We can't afford to be losing games like this."
Jack Capuano was a bit stupefied, seeing as how his team gave up only 11 shots through 40 minutes but still began to dictate the tempo and hunt down on the forecheck only after Kovalchuk's second goal, a one-timed rocket past Evgeni Nabokov on the power play at 3:33 of the second.
"It's mind-boggling the way we didn't execute," Capuano said. "You give up 11 shots to that team, you're doing something right . . . We had some guys, quite frankly, that were invisible."
The only Islander benched was Matt Martin, who barely played in the third period. Marty Reasoner went just 2-for-8 on faceoffs and took a penalty. Jay Pandolfo missed a golden scoring chance early and was going to be whistled for a minor in the third when Patrik Elias scored on his third whack at a loose puck.
Kovalchuk completed his hat trick 64 seconds after Elias' goal, and the game was out of reach.
John Tavares was held without a point and still doesn't have one against the Devils in four games this season. There were several shifts in which Tavares' line simply didn't have the puck, as the Elias-Dainius Zubrus-Petr Sykora line played keepaway.
"You look at the whole game, and it's not enough," P.A. Parenteau said. "We had some moments, Brodeur made some good saves, but we still have to make more happen."
The odd scheduling that has these two teams playing three times in six days wraps up Saturday night at the Coliseum, with the Islanders then facing the Rangers at the Garden on Sunday night.
With 15 games remaining, the Islanders are closer to 15th than eighth in the Eastern Conference.
If anything more needs to be said, then it's already too late.
"It seems like we just didn't have enough jump at the start," MacDonald said. "We have to come out stronger."


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Student Lifecycle Management is the collection, storage and processing of student data that is associated with the student lifecycle.
Academic Enrichment: Lynn Hiler
Academic Scholarships: Sandy Copher
Admissions and Registrar: Ellie Goodman
Agriculture: Jamie Dunn
Agriculture - Human Environmental Sciences: Louise Gladstone
Arts and Sciences: Michelle Combs
Assessment: Deborah Sparkman
Athletics: Mike Haley
Business and Economics: Robert Martin-Curry
Communication and Information: Suanne Early
Dean of Students: Nicholas Kehrwald, Cindy Wright
Dentistry: Melissa Lockard
Design: Azhar Swanson
Distance Learning: Jackie Briscoe
Donovan Scholars Program, Council on Aging: Kevin Horn
Education: Cynthia Jennings
Engineering: B.J. Brandenburg
Financial Aid: Nimmi Wiggins
Fine Arts: Misty Howard
Graduate Family Housing: Paula Dunn
Graduate School: Linda Davis
Health Sciences: Sharon Goins
Information Technology Services: Diana Gold
Institutional Diversity: Terry Allen
Institutional Equity and Equal Opportunity: Heather Roop
International Affairs: Shan "Sandee" Huang
James W Stuckert Career Center: Ray Clere
Law: Alison Begor
Lewis Honors College: Donna Hancock
Libraries: Melissa Barlow
Medicine: Brendan McCarthy
Nursing: Joanne Davis
Parking and Transportation: David Cowan
Pharmacy: Rene Maldonado
Planning and Institutional Effectiveness: Ann D. Weber
Public Health: Amber Moreland, Nicholas Morgan
Residence Life: Tony Ralph
Senate Council Office: Sheila Brothers
Social Work: Lyn LeMieux, Gary Trumble
Student Account Services: Linda Smitha
Student and Academic Life: Terri Runyon
Student and Academic Services (UK 101): Debbie Calvert
Student Center: Phillip Latiff
Student Support Services: Lynda Wilson Bush
Teaching and Academic Support Center: Cynthia Buster
Transformative Learning: Molly Reynolds
UK Alumni Association: John Hoagland
UK Police Department: Robert McKinley
Undergraduate Housing: Brooke Daniel
University Health Services: Carol Redden


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The Visitor Trailer (2014)
10 October 2014 74 mins
"The Visitor", a silent figure incorporated by the filmmaker, roams through three Mega-cities, creating encounters with random people, following a dramaturgy of chance both with the choice of the protagonist as with the outcome of each story. First simply attendant, she becomes a friend, intruder and even beloved one who shares the whole daily life of her protagonists, their sleeping places and worries. Through this new presence in their life, not only the loneliness of the different people becomes apparent, but, as the relation intensifies, the border between "I" and "the other" starts to blur.
Watch the official The Visitor 2014 trailer in HD below or find more The Visitor videos on Vidimovie.


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References in periodicals archive ?
Site Engineer, Stenographer, Office Assistants, Record Keeper, Peons, Chowkidars And Safaiwala In National Highways Of India, Regional Office-Gujarat At Gandhinagar.
Regarding the working of these committees, the official told that woman leader was elected amongst the local group of BISP beneficiaries, as well as a record keeper, who were responsible for communicating problems of the group to the Tehsil offices or other representatives of BISP.
In September, FINAL FANTASY: Record Keeper players will be transported to the realm of Eorzea, where the story of FFXIV unfolds, and will get a chance to play as two characters from the underground organization, The Scions of the Seventh Dawn.
Link Group is a leading global third party financial record keeper, comprising four core businesses: Pension and Superannuation Administration, Corporate Markets, Information & Data Services, and Property Services.
Under the new plan, the record keeper reports to PERA on an investment option level, the custodian bank reports to PERA on an underlying portfolio level, and the investment options, by way of the underlying options, hold assets for three separate plan trusts.
The fire chief was the primary record keeper for the drugs and, in most instances, his name was signed to dispensing sheets at the hospital.
The third American president was a meticulous record keeper.
With regard to recordkeeping, Dickstein says, the regulations say that when there's no stated charge, the record keeper has to come up with a good-faith estimate of the cost.
While plan administrators will continue to rely on third-party vendors for recordkeeping and investments accounting, final responsibility for monitoring the record keeper and selecting the current menu of investments rests with the sponsor.
The AG's branch, which is the official record keeper in the service, has maintained Gen Singh's date of birth as May 10, 1951, although the Military Secretary's branch records it as May 10, 1950.
Northern Trust offers a range of services to CIF clients, including acting as master record keeper and, if needed, performing accounting for assets held externally to the CIF, and supporting the individual needs of the underlying participants.
Insurance companies cannot just increase the prices any time they want," Shaima Al Balushi, a record keeper at the Ministry of Agriculture and Fisheries, said.
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An app for Apple iPhone
users wanting to buy or find personalized registration plates has been
Developed by www.iBuildApps,
the free application aims to tap into the UK's obsession with personalized
license plates. Figures from the Office of National Statistics reveal one in
twenty UK
drivers already own a personalized number plate, with an average spend of £500
per plate.
Users can choose from
millions of available licence plates, either by selecting by category or by
searching directly for a word or name of their choosing. Users can then view
their selected plate on a brand new Porsche and make an enquiry about its
Bryn Firkins, who developed
the app, said: 'Brits love their motors. According to Apple, five of the ten
most downloaded iPhone apps in the UK in 2009 were car related. This
app helps drivers secure the perfect plate for their new car whilst still
sitting in the dealer's showroom'.
is hoping the app will be used by iPhone users to buy personalized plates for
friends and family as Christmas presents.
Mobile Industry Awards 2017 - B2B & Distribution Finalists
Mobile Industry Awards 2017 – Retail Finalists announced
Mobile Industry Awards 2017 - Best Ruggedised Device
Nazish Dossa Joins Brighstar as UK Managing Director.
Get your FREE copy of Mobile's e-zine and stay up to speed on your PC, laptop or
Get your FREE e-zine
Huawei - 'Our 2017 focus is premium products'
Retail Special
S6 to re-ignite the market
Brightstar 20:20 and HTC join forces
Meeting the challenge of in-building coverage


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Affordable, fee-based independent financial advice for UK residents
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Sevan Hotels
Hotel bookings and reviews
Hotels in Sevan
Hotel Ratings and Locations
BEST WESTERN Bohemian Resort is a high quality service hotel, located on the most beautiful beach of...
This 3 star hotel is located on the coastline of Sevan. The Hotel has an outdoor swimming pool. All ...
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