bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mortality among Paris sewage workers
Authors: Wild P , Ambroise D , Benbrik E , Tiberguent A , Massin N 
Published: February 2006

Objectives:To describe the mortality of Paris sewage workers.Methods:A cohort of all Paris sewage workers since 1970 was established and followed up in mortality until 1999. The causes of death were determined by matching with a national database. The mortality rates were compared to the rates of a local reference population.Results:A large excess in mortality (standardised mortality ratio (SMR) = 1.25; 530 cases, 95% CI 1.15 to 1.36) and in particular mortality from cancer (SMR = 1.37, 235 cases) was detected which was particularly important in the subgroup of subjects who had left employment because they resigned or were laid off (SMR = 1.77; 50 cases). The excess mortality is to a large extent due to alcohol related diseases (SMR = 1.65, 122 cases) especially malignant (SMR = 1.85, 16 cases) and non-malignant (SMR =  1.68, 38 cases) liver diseases, lung cancer (SMR = 1.47, 68 cases), and infectious diseases (SMR =  1.86, 25 cases). The SMRs for some diseases (all cancers, cancers of the oesophagus and lung, all alcohol related diseases) seem to increase with duration of employment as a sewage worker. Other than lung cancer, smoking related diseases were not in excess.Conclusion:The increased mortality by both malignant and non-malignant liver diseases is probably due to excessive alcohol consumption, but could be partially the result of occupational exposure to chemical and infectious agents and interactions of these factors. The excess lung cancer is unlikely to be due to an increased smoking prevalence.
Applying a moving total mortality count to the cities in the NMMAPS database to estimate the mortality effects of particulate matter air pollution
Authors: Roberts S , Martin M A 
Published: February 2006

Objectives:To apply a new method for estimating the association between daily ambient particulate matter air pollution (PM) and daily mortality to data from over 100 United States cities contained in the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) database and to see whether the results from the 90 cities NMMAPS analysis are robust to this different modelling approach. This new method has recently been shown to provide improved estimates for the association between PM and daily mortality when every-day PM data are unavailable. It avoids the need for selecting a lag of PM at which the mortality effects of PM are to be investigated.Methods:With the aid of analytical methods and databases developed for NMMAPS, Poisson log linear models controlling for long term trends and weather effects were used to estimate the association between PM and mortality for cities in the NMMAPS database using the new method. A two stage Bayesian hierarchical model was then used to combine city specific estimates to form a national average PM mortality effect estimate.Results:A 10 μg/m3increase in PM was associated with a 0.12% increment in total mortality and a 0.17% increment in cardiovascular and respiratory mortality. These results are consistent with those found in the NMMAPS analysis.Conclusions:There is a statistically significant association between short term changes in PM and mortality on average for the cities contained in the NMMAPS database. These findings are further evidence that this widespread pollutant adversely affects public health.
A study of quality of life in Internet health chat room users
Authors: Holmes Susan 
Published: February 2006

Maintenance of quality of life (QoL) is central to healthcare and an increasingly important outcome of care provision reflecting enhanced awareness of the need to consider the effects of a disease or treatment on a patient's life. However, while its assessment has intuitive appeal it is predicated on the belief that QoL can be effectively defined, assessed and quantified. Achieving this is, however, difficult as individuals value different things and, it is claimed, often define QoL differently; there are no ‘generally agreed referents' and no ‘gold standard’ through which it can be measured. This may significantly affect the value and the uses to which such data can be put. The study described here represents the first stage of a programme of work focusing upon defining QoL as it is currently perceived in the UK; it relied upon a qualitative, descriptive survey involving a sample of Internet health chat room users. It attempts to define QoL and to identify the factors contributing to life quality in these respondents. A subsidiary aim was to evaluate the use of email as a recruitment tool in such research. A common definition was difficult to find but, in general terms, is taken to represent ‘what you think of your life’. Within this a range of factors are seen to contribute to individual perceptions and it was possible to identify those appearing to determine perceptions of QoL in this study population. Email was an effective route for recruiting subjects in this work.
Up-regulation of asparagine synthetase expression is not linked to the clinical response l-asparaginase in pediatric acute lymphoblastic leukemia
Authors: Appel Inge M. , den Boer Monique L. , Meijerink Jules P. P. , Veerman Anjo J. P. , Reniers Nathalie C. M. , Pieters Rob 
Published: February 2006

Abstractl-asparaginase (l-Asp) is an effective drug for treatment of children with acute lymphoblastic leukemia (ALL). The effectiveness is generally thought to result from a rapid depletion of asparagine in serum and cells. Asparagine synthetase (AS) opposes the action of l-Asp by resynthesis of asparagine. In vitro, resistance to l-Asp has been associated with up-regulation of AS mRNA expression. We monitored AS mRNA levels in leukemic cells before and during 5 days after intravenous administration of 1000 IU/m2 pegylated l-asparaginase (PEG-Asp) in a therapeutic window in children with ALL at initial diagnosis. Within 24 hours, AS mRNA levels increased by 3.5-fold and remained stable in the following 4 days. Baseline and l-Asp–induced expression levels of AS did not differ between clinically good, intermediate, and poor responders to PEG-Asp. No significant difference of AS mRNA up-regulation was found between precursor B- and T-ALL or between hyperdiploids, TEL/AML1 rearranged ALL or absence of genetic abnormalities. In 3 of 12 patients with T-ALL even a slight down-regulation of AS mRNA expression upon l-Asp exposure was found. In conclusion, although l-Asp exposure induces the expression of AS mRNA, the up-regulated gene expression does not correlate with an early clinical poor response to this drug in children with ALL.
Constitutive NF-κB and NFAT activation leads to stimulation of the BLyS survival pathway in aggressive B-cell lymphomas
Authors: Fu Lingchen , Lin-Lee Yen-Chiu , Pham Lan V. , Tamayo Archito , Yoshimura Linda , Ford Richard J. 
Published: February 2006

AbstractB-lymphocyte stimulator (BLyS), a relatively recently recognized member of the tumor necrosis factor ligand family (TNF), is a potent cell-survival factor expressed in many hematopoietic cells. BLyS binds to 3 TNF-R receptors, TACI, BCMA, BAFF-R, to regulate B-cell survival, differentiation, and proliferation. The mechanisms involved in BLYS gene expression and regulation are still incompletely understood. In this study, we examined BLYS gene expression, function, and regulation in B-cell non-Hodgkin lymphoma (NHL-B) cells. Our studies indicate that BLyS is constitutively expressed in aggressive NHL-B cells, including large B-cell lymphoma (LBCL) and mantle cell lymphoma (MCL), playing an important role in the survival and proliferation of malignant B cells. We found that 2 important transcription factors, NF-κB and NFAT, are involved in regulating BLyS expression through at least one NF-κB and 2 NFAT binding sites in the BLYS promoter. We also provide evidence suggesting that the constitutive activation of NF-κB and BLyS in NHL-B cells forms a positive feedback loop associated with lymphoma cell survival and proliferation. Our findings indicate that constitutive NF-κB and NFAT activations are crucial transcriptional regulators of the BLyS survival pathway in malignant B cells that could be therapeutic targets in aggressive NHL-B.
Antimicrobial proteins and polypeptides in pulmonary innate defence
Authors: Rogan Mark P , Geraghty Patrick , Greene Catherine M , O'Neill Shane J , Taggart Clifford C , McElvaney Noel G 
Published: February 2006

AbstractInspired air contains a myriad of potential pathogens, pollutants and inflammatory stimuli. In the normal lung, these pathogens are rarely problematic. This is because the epithelial lining fluid in the lung is rich in many innate immunity proteins and peptides that provide a powerful anti-microbial screen. These defensive proteins have anti-bacterial, anti- viral and in some cases, even anti-fungal properties. Their antimicrobial effects are as diverse as inhibition of biofilm formation and prevention of viral replication. The innate immunity proteins and peptides also play key immunomodulatory roles. They are involved in many key processes such as opsonisation facilitating phagocytosis of bacteria and viruses by macrophages and monocytes. They act as important mediators in inflammatory pathways and are capable of binding bacterial endotoxins and CPG motifs. They can also influence expression of adhesion molecules as well as acting as powerful anti-oxidants and anti-proteases. Exciting new antimicrobial and immunomodulatory functions are being elucidated for existing proteins that were previously thought to be of lesser importance. The potential therapeutic applications of these proteins and peptides in combating infection and preventing inflammation are the subject of ongoing research that holds much promise for the future.
Quantitative comparison of EST libraries requires compensation for systematic biases in cDNA generation
Authors: Liu Donglin , Graber Joel H 
Published: February 2006

Abstract

Background
Publicly accessible EST libraries contain valuable information that can be utilized for studies of tissue-specific gene expression and processing of individual genes. This information is, however, confounded by multiple systematic effects arising from the procedures used to generate these libraries.

Results
We used alignment of ESTs against a reference set of transcripts to estimate the size distributions of the cDNA inserts and sampled mRNA transcripts in individual EST libraries and show how these measurements can be used to inform quantitative comparisons of libraries. While significant attention has been paid to the effects of normalization and substraction, we also find significant biases in transcript sampling introduced by the combined procedures of reverse transcription and selection of cDNA clones for sequencing. Using examples drawn from studies of mRNA 3'-processing (cleavage and polyadenylation), we demonstrate effects of the transcript sampling bias, and provide a method for identifying libraries that can be safely compared without bias. All data sets, supplemental data, and software are available at our supplemental web site [1].

Conclusion
The biases we characterize in the transcript sampling of EST libraries represent a significant and heretofore under-appreciated source of false positive candidates for tissue-, cell type-, or developmental stage-specific activity or processing of genes. Uncorrected, quantitative comparison of dissimilar EST libraries will likely result in the identification of statistically significant, but biologically meaningless changes.
Transcriptomic response to differentiation induction
Authors: Patton GW , Stephens R , Sidorov IA , Xiao X , Lempicki RA , Dimitrov DS , Shoemaker RH , Tudor G 
Published: February 2006

Abstract

Background
Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A common terminal data analysis step is to map pathways of potentially interrelated genes.

Methods
We applied a transcriptomics analysis tool to elucidate the underlying pathways of leukocyte maturation at the genomic level in an established cellular model of leukemia by examining time-course data in two subclones of U-937 cells. Leukemias such as Acute Promyelocytic Leukemia (APL) are characterized by a block in the hematopoietic stem cell maturation program at a point when expansion of clones which should be destined to mature into terminally-differentiated effector cells get locked into endless proliferation with few cells reaching maturation. Treatment with retinoic acid, depending on the precise genomic abnormality, often releases the responsible promyelocytes from this blockade but clinically can yield adverse sequellae in terms of potentially lethal side effects, referred to as retinoic acid syndrome.

Results
Briefly, the list of genes for temporal patterns of expression was pasted into the ABCC GRID Promoter TFSite Comparison Page website tool and the outputs for each pattern were examined for possible coordinated regulation by shared regelems (regulatory elements). We found it informative to use this novel web tool for identifying, on a genomic scale, genes regulated by drug treatment.

Conclusion
Improvement is needed in understanding the nature of the mutations responsible for controlling the maturation process and how these genes regulate downstream effects if there is to be better targeting of chemical interventions. Expanded implementation of the techniques and results reported here may better direct future efforts to improve treatment for diseases not restricted to APL.
The PowerAtlas: a power and sample size atlas for microarray experimental design and research
Authors: Page Grier P , Edwards Jode W , Gadbury Gary L , Yelisetti Prashanth , Wang Jelai , Trivedi Prinal , Allison David B 
Published: February 2006

Abstract

Background
Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies.

Results
To address this challenge, we have developed a Microrarray PowerAtlas [1]. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO). The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC).

Conclusion
This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes.
Phase analysis of circadian-related genes in two tissues
Authors: Liu Delong , Peddada Shyamal D , Li Leping , Weinberg Clarice R 
Published: February 2006

Abstract

Background
Recent circadian clock studies using gene expression microarray in two different tissues of mouse have revealed not all circadian-related genes are synchronized in phase or peak expression times across tissues in vivo. Instead, some circadian-related genes may be delayed by 4–8 hrs in peak expression in one tissue relative to the other. These interesting biological observations prompt a statistical question regarding how to distinguish the synchronized genes from genes that are systematically lagged in phase/peak expression time across two tissues.

Results
We propose a set of techniques from circular statistics to analyze phase angles of circadian-related genes in two tissues. We first estimate the phases of a cycling gene separately in each tissue, which are then used to estimate the paired angular difference of the phase angles of the gene in the two tissues. These differences are modeled as a mixture of two von Mises distributions which enables us to cluster genes into two groups; one group having synchronized transcripts with the same phase in the two tissues, the other containing transcripts with a discrepancy in phase between the two tissues. For each cluster of genes we assess the association of phases across the tissue types using circular-circular regression. We also develop a bootstrap methodology based on a circular-circular regression model to evaluate the improvement in fit provided by allowing two components versus a one-component von-Mises model.

Conclusion
We applied our proposed methodologies to the circadian-related genes common to heart and liver tissues in Storch et al. [2], and found that an estimated 80% of circadian-related transcripts common to heart and liver tissues were synchronized in phase, and the other 20% of transcripts were lagged about 8 hours in liver relative to heart. The bootstrap p-value for being one cluster is 0.063, which suggests the possibility of two clusters. Our methodologies can be extended to analyze peak expression times of circadian-related genes across more than two tissues, for example, kidney, heart, liver, and the suprachiasmatic nuclei (SCN) of the hypothalamus.
A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images
Authors: Chen Shann-Ching , Murphy Robert F 
Published: February 2006

Abstract

Background
Knowledge of the subcellular location of a protein is critical to understanding how that protein works in a cell. This location is frequently determined by the interpretation of fluorescence microscope images. In recent years, automated systems have been developed for consistent and objective interpretation of such images so that the protein pattern in a single cell can be assigned to a known location category. While these systems perform with nearly perfect accuracy for single cell images of all major subcellular structures, their ability to distinguish subpatterns of an organelle (such as two Golgi proteins) is not perfect. Our goal in the work described here was to improve the ability of an automated system to decide which of two similar patterns is present in a field of cells by considering more than one cell at a time. Since cells displaying the same location pattern are often clustered together, considering multiple cells may be expected to improve discrimination between similar patterns.

Results
We describe how to take advantage of information on experimental conditions to construct a graphical representation for multiple cells in a field. Assuming that a field is composed of a small number of classes, the classification accuracy can be improved by allowing the computed probability of each pattern for each cell to be influenced by the probabilities of its neighboring cells in the model. We describe a novel way to allow this influence to occur, in which we adjust the prior probabilities of each class to reflect the patterns that are present. When this graphical model approach is used on synthetic multi-cell images in which the true class of each cell is known, we observe that the ability to distinguish similar classes is improved without suffering any degradation in ability to distinguish dissimilar classes. The computational complexity of the method is sufficiently low that improved assignments of classes can be obtained for fields of twelve cells in under 0.04 second on a 1600 megahertz processor.

Conclusion
We demonstrate that graphical models can be used to improve the accuracy of classification of subcellular patterns in multi-cell fluorescence microscope images. We also describe a novel algorithm for inferring classes from a graphical model. The performance and speed suggest that the method will be particularly valuable for analysis of images from high-throughput microscopy. We also anticipate that it will be useful for analyzing the mixtures of cell types typically present in images of tissues. Lastly, we anticipate that the method can be generalized to other problems.
Various criteria in the evaluation of biomedical named entity recognition
Authors: Tsai Richard Tzong-Han , Wu Shih-Hung , Chou Wen-Chi , Lin Yu-Chun , He Ding , Hsiang Jieh , Sung Ting-Yi , Hsu Wen-Lian 
Published: February 2006

Abstract

Background
Text mining in the biomedical domain is receiving increasing attention. A key component of this process is named entity recognition (NER). Generally speaking, two annotated corpora, GENIA and GENETAG, are most frequently used for training and testing biomedical named entity recognition (Bio-NER) systems. JNLPBA and BioCreAtIvE are two major Bio-NER tasks using these corpora. Both tasks take different approaches to corpus annotation and use different matching criteria to evaluate system performance. This paper details these differences and describes alternative criteria. We then examine the impact of different criteria and annotation schemes on system performance by retesting systems participated in the above two tasks.

Results
To analyze the difference between JNLPBA's and BioCreAtIvE's evaluation, we conduct Experiment 1 to evaluate the top four JNLPBA systems using BioCreAtIvE's classification scheme. We then compare them with the top four BioCreAtIvE systems. Among them, three systems participated in both tasks, and each has an F-score lower on JNLPBA than on BioCreAtIvE. In Experiment 2, we apply hypothesis testing and correlation coefficient to find alternatives to BioCreAtIvE's evaluation scheme. It shows that right-match and left-match criteria have no significant difference with BioCreAtIvE. In Experiment 3, we propose a customized relaxed-match criterion that uses right match and merges JNLPBA's five NE classes into two, which achieves an F-score of 81.5%. In Experiment 4, we evaluate a range of five matching criteria from loose to strict on the top JNLPBA system and examine the percentage of false negatives. Our experiment gives the relative change in precision, recall and F-score as matching criteria are relaxed.

Conclusion
In many applications, biomedical NEs could have several acceptable tags, which might just differ in their left or right boundaries. However, most corpora annotate only one of them. In our experiment, we found that right match and left match can be appropriate alternatives to JNLPBA and BioCreAtIvE's matching criteria. In addition, our relaxed-match criterion demonstrates that users can define their own relaxed criteria that correspond more realistically to their application requirements.