Legislative Documents

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Additional file 3 of Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups

Comparison of revealed subtypes to subtypes revealed for histologically classified oligoastrocytomas and astrocytomas. (PDF 2365 kb

A new scoring system for primary central nervous system lymphoma - a retrospective multi-center analysis in Taiwan

[[abstract]]Background: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin’s lymphoma. Two independent prognostic scoring systems have been developed at the Memorial Sloan-Kettering Cancer Center (MSKCC) and the International Extranodal Lymphoma Study Group (IELSG). The former considers age and Karnofski’s performance status (PS) as prognostic parameters(JCO. 2006;24:5711). The latter includes age, Eastern Cooperative Oncology Group (ECOG) PS, the presence of deep lesions, serum lactate dehydrogenase (LDH) and total protein levels in the cerebrospinal fluid (CSF)(JCO 2003;21:266). Neither of the two systems has been verified in the Asian population, leading to concerns regarding applicability in this region. Aims: This study was conducted to test the prognostic power of the 2 systems in PCNSL patients in Taiwan. In addition, we analyzed the parameters of the IELSG system to figure out the most powerful prognostic factors and then established a new scoring system. Methods: The medical records of patients with tissue-proven PCNSL were retrieved from 15 academic hospitals in Taiwan through January 2002 to December 2011. They were stratified into different groups according to the MSKCC or the IELSG system and the overall survivals (OS) were evaluated. All parameters in the IELSG system were checked by multi-variable analysis to establish a new scoring system. Results: When the IELSG scoring system was applied, the 2-year OS in low, intermediate and high-risk groups were 78.3%, 43.9% and 37.5% respectively with a crossover in the latter 2 groups（Figure 1）. When the patients were stratified by the MSKCC scoring system, the 2-year OS of class I, II and III were 65%, 68% and 20% （Figure 2）, respectively. We conducted single-variable analysis of the 5 parameters included in the IELSG scoring system and only age and ECOG PS were statistically significant. In the multi-variable analysis, these 2 factors were almost equally weighted. Based on these findings, we re-stratified the patients into 3 groups. Group 1 comprised patients with both age < 60 and ECOG PS < 2 and Group 3 with both age ≧ 60 and ECOG PS ≧ 2. The patients not fulfilling criteria of either Group1 or Group 3 were categorized as Group 2. According to this new scoring system, the median OS of Groups 1, 2 and 3 were 1,573, 548 and 304 days（Figure 3）, respectively, and their OS curves could be nicely distinguished

Additional file 5 of Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

Table S4. Genes located on 1p/19q with strong impact on signaling pathways. (XLS 115 kb

Additional file 4 of Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

Table S3. Differentially expressed genes between oligodendrogliomas with 1p/19q co-deletion and normal brain tissue. (XLS 2240 kb

Additional file 6 of Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups

1006 transcription factors of the gene signature. (XLSX 92.4 kb

Additional file 8 of Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

Table S7. Genes located on rarely mutated chromosomal arms with strong impact on metabolic pathways. (XLS 187 kb

Additional file 7 of Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups

Consensus gene regulatory network. Rows of the matrix represent 5113 response variables (signature genes); columns represent 1007 predictors (transcription factors + gene-specific copy number). A cell’s value shows how many times the link from the respective predictor gene to the respective response gene was present across the 100 cross-validation iterations. Negative values indicate repressing links and positive values indicate activating links. (TXT 10209 kb

Taylor coefficients and coefficient multipliers of Hardy and Bergman-type spaces

This book provides a systematic overview of the theory of Taylor coefficients of functions in some classical spaces of analytic functions and especially of the coefficient multipliers between spaces of Hardy type. Offering a comprehensive reference guide to the subject, it is the first of its kind in this area. After several introductory chapters covering the basic material, a large variety of results obtained over the past 80 years, including the most recent ones, are treated in detail. Several chapters end with discussions of practical applications and related topics that graduate students and experts in other subjects may find useful for their own purposes. Thus, a further aim of the book is to communicate to non-specialists some concrete facts that may be of value in their own work. The book can also be used as a textbook or a supplementary reference for an advanced graduate course. It is primarily intended for specialists in complex and functional analysis, graduate students, and experts in other related fields

Model-Based Evaluation of Spontaneous Tumor Regression in Pilocytic Astrocytoma

<div><p>Pilocytic astrocytoma (PA) is the most common brain tumor in children. This tumor is usually benign and has a good prognosis. Total resection is the treatment of choice and will cure the majority of patients. However, often only partial resection is possible due to the location of the tumor. In that case, spontaneous regression, regrowth, or progression to a more aggressive form have been observed. The dependency between the residual tumor size and spontaneous regression is not understood yet. Therefore, the prognosis is largely unpredictable and there is controversy regarding the management of patients for whom complete resection cannot be achieved. Strategies span from pure observation (wait and see) to combinations of surgery, adjuvant chemotherapy, and radiotherapy. Here, we introduce a mathematical model to investigate the growth and progression behavior of PA. In particular, we propose a Markov chain model incorporating cell proliferation and death as well as mutations. Our model analysis shows that the tumor behavior after partial resection is essentially determined by a risk coefficient <i>γ</i>, which can be deduced from epidemiological data about PA. Our results quantitatively predict the regression probability of a partially resected benign PA given the residual tumor size and lead to the hypothesis that this dependency is linear, implying that removing any amount of tumor mass will improve prognosis. This finding stands in contrast to diffuse malignant glioma where an extent of resection threshold has been experimentally shown, below which no benefit for survival is expected. These results have important implications for future therapeutic studies in PA that should include residual tumor volume as a prognostic factor.</p></div