220 research outputs found

    Discussions on the relationships between meteorology and oceanography

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    G. E. R. DEACON: There must be some of you who, like me, did most of their seagoing 20 to 30 years ago and find it difficult to keep pace with the present urgency of introducing more precise reasoning into oceanography. This afternoon\u27s session dealing mainly with such precise arguments has not been easy to follow, and it is clear that there is much serious hard work ahead...

    Integrated analysis of RNA and DNA from the phase III trial CALGB 40601 identifies predictors of response to trastuzumab-based neoadjuvant chemotherapy in HER2-positive breast cancer

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    Purpose: Response to a complex trastuzumab-based regimen is affected by multiple features of the tumor and its microenvironment. Developing a predictive algorithm is key to optimizing HER2-targeting therapy. Experimental Design: We analyzed 137 pretreatment tumors with mRNA-seq and DNA exome sequencing from CALGB 40601, a neoadjuvant phase III trial of paclitaxel plus trastuzumab with or without lapatinib in stage II to III HER2-positive breast cancer. We adopted an Elastic Net regularized regression approach that controls for covarying features within high-dimensional data. First, we applied 517 known gene expression signatures to develop an Elastic Net model to predict pCR, which we validated on 143 samples from four independent trials. Next, we performed integrative analyses incorporating clinicopathologic information with somatic mutation status, DNA copy number alterations (CNA), and gene signatures. Results: The Elastic Net model using only gene signatures predicted pCR in the validation sets (AUC ¼ 0.76). Integrative analyses showed that models containing gene signatures, clinical features, and DNA information were better pCR predictors than models containing a single data type. Frequently selected variables from the multiplatform models included amplifications of chromosome 6p, TP53 mutation, HER2-enriched subtype, and immune signatures. Variables predicting resistance included Luminal/ERþ features. Conclusions: Models using RNA only, as well as integrated RNA and DNA models, can predict pCR with improved accuracy over clinical variables. Somatic DNA alterations (mutation, CNAs), tumor molecular subtype (HER2E, Luminal), and the microenvironment (immune cells) were independent predictors of response to trastuzumab and paclitaxel-based regimens. This highlights the complexity of predicting response in HER2-positive breast cancer

    Transfusion-Dependent Thalassemia in Northern Sarawak: A Molecular Study to Identify Different Genotypes in the Multi-Ethnic Groups and the Importance of Genomic Sequencing in Unstudied Populations

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    Background: Although thalassemia is a genetic hemoglobinopathy in Malaysia, there is limited data on thalassemia mutations in the indigenous groups. This study aims to identify the types of globin gene mutations in transfusion-dependent patients in Northern Sarawak. Methods: Blood was collected from 32 patients from the Malay, Chinese, Kedayan, Bisayah, Kadazandusun, Tagal, and Bugis populations. The α- and β-globin gene mutations were characterized using DNA amplification and genomic sequencing. Results: Ten β- and 2 previously reported α-globin defects were identified. The Fil-ipino β-deletion represented the majority of the β-thalassemia alleles in the indigenous patients. Homozygosity for the deletion was observed in all Bisayah, Kadazandusun and Tagal patients. The β-globin gene mutations in the Chinese patients were similar to the Chinese in West Malaysia. Hb Adana (HBA2:c.179G>A) and the –α 3.7 /αα deletion were detected in 5 patients. A novel 24-bp deletion in the α2-globin gene (HBA2:c.95 + 5_95 + 28delGGCTCCCTCCCCTGCTCCGACCCG) was identified by sequencing. Co-inheritance of α-thalassemia with β-thalassemia did not ameliorate the severity of thalassemia major in the patients. Conclusion: The Filipino β-deletion was the most common gene defect observed. Homozygosity for the Filipino β-deletion appears to be unique to the Malays in Sarawak. Genomic sequencing is an essential tool to detect rare genetic variants in the study of new populations

    Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

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    PURPOSE: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database. METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared. RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups. CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research

    Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

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    Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets
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