Identification of robust cellular programs using reproducible LDA that impact sex-specific disease progression in different genotypes of a mouse model of AD

The gene expression profiles of distinct cell types reflect complex genomic interactions among multiple simultaneous biological processes within each cell that can be altered by disease progression as well as genetic background. The identification of these active cellular programs is an open challenge in the analysis of single-cell RNA-seq data. Latent Dirichlet Allocation (LDA) is a generative method used to identify recurring patterns in counts data, commonly referred to as topics that can be used to interpret the state of each cell. However, LDA's interpretability is hindered by several key factors including the hyperparameter selection of the number of topics as well as the variability in topic definitions due to random initialization. We developed Topyfic, a Reproducible LDA (rLDA) package, to accurately infer the identity and activity of cellular programs in single-cell data, providing insights into the relative contributions of each program in individual cells. We apply Topyfic to brain single-cell and single-nucleus datasets of two 5xFAD mouse models of Alzheimer's disease crossed with C57BL6/J or CAST/EiJ mice to identify distinct cell types and states in different cell types such as microglia. We find that 8-month 5xFAD/Cast F1 males show higher level of microglial activation than matching 5xFAD/BL6 F1 males, whereas female mice show similar levels of microglial activation. We show that regulatory genes such as TFs, microRNA host genes, and chromatin regulatory genes alone capture cell types and cell states. Our study highlights how topic modeling with a limited vocabulary of regulatory genes can identify gene expression programs in single-cell data in order to quantify similar and divergent cell states in distinct genotypes.

The ENCODE Uniform Analysis Pipelines

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3' end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of 200,000 full-length transcripts, 40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3' processing are deployed across human tissues, with nearly half of multi-transcript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.

The ENCODE Uniform Analysis Pipelines

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.

Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq

The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. However, its application to single-cell RNA-seq has been limited by throughput and expense. Here we develop and characterize long-read Split-seq (LR-Split-seq), which uses combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells.

Author Correction: An atlas of dynamic chromatin landscapes in mouse fetal development

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03089-4.

Spatiotemporal DNA methylome dynamics of the developing mouse fetus

Cytosine DNA methylation is essential for mammalian development but understanding of its spatiotemporal distribution in the developing embryo remains limited^1,2. Here, as part of the mouse Encyclopedia of DNA Elements (ENCODE) project, we profiled 168 methylomes from 12 mouse tissues or organs at 9 developmental stages from embryogenesis to adulthood. We identified 1,808,810 genomic regions that showed variations in CG methylation by comparing the methylomes of different tissues or organs from different developmental stages. These DNA elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. During late stages of fetal development, non-CG methylation accumulated within the bodies of key developmental transcription factor genes, coinciding with their transcriptional repression. Integration of genome-wide DNA methylation, histone modification and chromatin accessibility data enabled us to predict 461,141 putative developmental tissue-specific enhancers, the human orthologues of which were enriched for disease-associated genetic variants. These spatiotemporal epigenome maps provide a resource for studies of gene regulation during tissue or organ progression, and a starting point for investigating regulatory elements that are involved in human developmental disorders.

Analysis of 168 methylomes from 12 mouse tissues at 9 developmental stages sheds light on the epigenetic and regulatory landscape during mammalian fetal development.

An atlas of dynamic chromatin landscapes in mouse fetal development

The Encyclopedia of DNA Elements (ENCODE) project has established a genomic resource for mammalian development, profiling a diverse panel of mouse tissues at 8 developmental stages from 10.5 days after conception until birth, including transcriptomes, methylomes and chromatin states. Here we systematically examined the state and accessibility of chromatin in the developing mouse fetus. In total we performed 1,128 chromatin immunoprecipitation with sequencing (ChIP-seq) assays for histone modifications and 132 assay for transposase-accessible chromatin using sequencing (ATAC-seq) assays for chromatin accessibility across 72 distinct tissue-stages. We used integrative analysis to develop a unified set of chromatin state annotations, infer the identities of dynamic enhancers and key transcriptional regulators, and characterize the relationship between chromatin state and accessibility during developmental gene regulation. We also leveraged these data to link enhancers to putative target genes and demonstrate tissue-specific enrichments of sequence variants associated with disease in humans. The mouse ENCODE data sets provide a compendium of resources for biomedical researchers and achieve, to our knowledge, the most comprehensive view of chromatin dynamics during mammalian fetal development to date.

The changing mouse embryo transcriptome at whole tissue and single-cell resolution

During mammalian embryogenesis, differential gene expression gradually builds the identity and complexity of each tissue and organ system1. Here we systematically quantified mouse polyA-RNA from day 10.5 of embryonic development to birth, sampling 17 tissues and organs. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets that were further characterized by the transcription factor motif codes of their promoters. We decomposed the tissue-level transcriptome using single-cell RNA-seq (sequencing of RNA reverse transcribed into cDNA) and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for one-third of differential gene expression and more than 40% of identified cell types. By integrating promoter sequence motifs with companion ENCODE epigenomic profiles, we identified a prominent promoter de-repression mechanism in neuronal expression clusters that was attributable to known and novel repressors. Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types that included progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell-type transcription factor networks and complementary sets of candidate enhancer elements by using single-cell RNA-seq to decompose integrative cis-element (IDEAS) models that were derived from whole-tissue epigenome chromatin data. These ENCODE reference data, computed network components and IDEAS chromatin segmentations are companion resources to the matching epigenomic developmental matrix, and are available for researchers to further mine and integrate.

Dynamics of microRNA expression during mouse prenatal development

MicroRNAs (miRNAs) play a critical role as posttranscriptional regulators of gene expression. The ENCODE Project profiled the expression of miRNAs in an extensive set of organs during a time-course of mouse embryonic development and captured the expression dynamics of 785 miRNAs. We found distinct organ-specific and developmental stage–specific miRNA expression clusters, with an overall pattern of increasing organ-specific expression as embryonic development proceeds. Comparative analysis of conserved miRNAs in mouse and human revealed stronger clustering of expression patterns by organ type rather than by species. An analysis of messenger RNA expression clusters compared with miRNA expression clusters identifies the potential role of specific miRNA expression clusters in suppressing the expression of mRNAs specific to other developmental programs in the organ in which these miRNAs are expressed during embryonic development. Our results provide the most comprehensive time-course of miRNA expression as part of an integrated ENCODE reference data set for mouse embryonic development.

A comparative encyclopedia of DNA elements in the mouse genome

The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.

Landscape of transcription in human cells

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

An encyclopedia of mouse DNA elements (Mouse ENCODE)

To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome.

Multigenome DNA sequence conservation identifies Hox cis-regulatory elements

To learn how well ungapped sequence comparisons of multiple species can predict cis-regulatory elements in Caenorhabditis elegans, we made such predictions across the large, complex ceh-13/lin-39 locus and tested them transgenically. We also examined how prediction quality varied with different genomes and parameters in our comparisons. Specifically, we sequenced approximately 0.5% of the C. brenneri and C. sp. 3 PS1010 genomes, and compared five Caenorhabditis genomes (C. elegans, C. briggsae, C. brenneri, C. remanei, and C. sp. 3 PS1010) to find regulatory elements in 22.8 kb of noncoding sequence from the ceh-13/lin-39 Hox subcluster. We developed the MUSSA program to find ungapped DNA sequences with N-way transitive conservation, applied it to the ceh-13/lin-39 locus, and transgenically assayed 21 regions with both high and low degrees of conservation. This identified 10 functional regulatory elements whose activities matched known ceh-13/lin-39 expression, with 100% specificity and a 77% recovery rate. One element was so well conserved that a similar mouse Hox cluster sequence recapitulated the native nematode expression pattern when tested in worms. Our findings suggest that ungapped sequence comparisons can predict regulatory elements genome-wide.

Engineering and public health at CDC

Engineering is the application of scientific and technical knowledge to solve human problems. Using imagination, judgment, and reasoning to apply science, technology, mathematics, and practical experience, engineers develop the design, production, and operation of useful objects or processes. During the 1940s, engineers dominated the ranks of CDC scientists. In fact, the first CDC director, Assistant Surgeon General Mark Hollis, was an engineer. CDC engineers were involved in malaria control through the elimination of standing water. Eventually the CDC mission expanded to include prevention and control of dengue, typhus, and other communicable diseases. The development of chlorination, water filtration, and sewage treatment were crucial to preventing waterborne illness. Beginning in the 1950s, CDC engineers began their work to improve public health while developing the fields of environmental health, industrial hygiene, and control of air pollution. Engineering disciplines represented at CDC today include biomedical, civil, chemical, electrical, industrial, mechanical, mining, and safety engineering. Most CDC engineers are located in the National Institute for Occupational Safety and Health (NIOSH) and the Agency for Toxic Substances and Disease Registry (ATSDR). Engineering research at CDC has a broad stakeholder base. With the cooperation of industry, labor, trade associations, and other stakeholders and partners, current work includes studies of air contaminants, mining, safety, physical agents, ergonomics, and environmental hazards. Engineering solutions remain a cornerstone of the traditional "hierarchy of controls" approach to reducing public health hazards.

Mining gene expression data by interpreting principal components

Background

There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis.

Results

We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset). We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.). Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation.

Conclusion

We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It has proven especially valuable in instances where there are many diverse conditions (10's to hundreds of different tissues or cell types), a situation in which many clustering and ordering algorithms become problematic. This approach also shows promise in other topic domains such as multi-spectral imaging datasets.

A mathematical and computational framework for quantitative comparison and integration of large-scale gene expression data

Analysis of large-scale gene expression studies usually begins with gene clustering. A ubiquitous problem is that different algorithms applied to the same data inevitably give different results, and the differences are often substantial, involving a quarter or more of the genes analyzed. This raises a series of important but nettlesome questions: How are different clustering results related to each other and to the underlying data structure? Is one clustering objectively superior to another? Which differences, if any, are likely candidates to be biologically important? A systematic and quantitative way to address these questions is needed, together with an effective way to integrate and leverage expression results with other kinds of large-scale data and annotations. We developed a mathematical and computational framework to help quantify, compare, visualize and interactively mine clusterings. We show that by coupling confusion matrices with appropriate metrics (linear assignment and normalized mutual information scores), one can quantify and map differences between clusterings. A version of receiver operator characteristic analysis proved effective for quantifying and visualizing cluster quality and overlap. These methods, plus a flexible library of clustering algorithms, can be called from a new expandable set of software tools called CompClust 1.0 (http://woldlab.caltech.edu/compClust/). CompClust also makes it possible to relate expression clustering patterns to DNA sequence motif occurrences, protein-DNA interaction measurements and various kinds of functional annotations. Test analyses used yeast cell cycle data and revealed data structure not obvious under all algorithms. These results were then integrated with transcription motif and global protein-DNA interaction data to identify G1 regulatory modules.

Effect of alpha-difluoromethyl-ornithine on the expression and function of the epidermal growth factor receptor in human breast epithelial cells in culture

We have previously shown that ornithine decarboxylase (ODC) overexpression enhances the transforming effects of HER-2neu and epidermal growth factor (EGF) in normal MCF-10A human breast epithelial cells. Our data suggest that such potentiation may be mediated by activation of the mitogen-activated protein kinase (MAPK) pathway and, possibly, STAT signalling. To further explore the interaction between the polyamine pathway and EGF/HER-2neu signalling in this system, we inhibited endogenous ODC activity with alpha-difluoromethylornithine (DFMO) and assessed the effects of this blockade on the expression of EGF receptors (EGFR) and HER-2neu as well as activation of downstream EGF target genes. We found that DFMO administration to MCF-10A cells increased EGF-R mRNA and protein levels in a dose-response fashion, while HER-2neu expression was not affected. The effect of DFMO was mediated through polyamine depletion since it could be reversed by exogenous putrescine administration. Our results also indicated that the increase in EGFR induced by DFMO was not a non-specific consequence of inhibition of cell proliferation. The upregulated EGFRs were functional since they could be phosphorylated by EGF and they were able to promote phosphorylation of downstream signalling molecules including ERK, STAT-3, and STAT-5. We propose that physiologic levels of ODC activity may be critical for regulation of a yet undefined signalling pathway, whose blockade by DFMO leads to a compensatory increase in functional EGFR.

Bioaerosol lung damage in a worker with repeated exposure to fungi in a water-damaged building

There has been increased concern over health effects related to potential exposure of building occupants to bioaerosols. We report the case of a worker with a respiratory illness related to bioaerosol exposure in a water-damaged building with extensive fungal contamination. We performed environmental tests to evaluate potential exposure to fungi, and we used mycotoxin-specific IgG antibody in serologic studies in the attempt to evaluate exposure to mycotoxins. Extensive fungal contamination was documented in many areas of the building. Penicillium, Aspergillus, and Stachybotrys species were the most predominant fungi found in air sampling. Our serologic test was not useful in differentiating workers who were probably occupationally exposed to mycotoxins from those who were not; however, it did yield evidence that individuals may make specific IgG antibodies to macrocyclic tricothecene mycotoxins. Further research is needed concerning health effects related to bioaerosol exposures, particularly regarding markers of exposure to specific fungi that may produce mycotoxins. In the absence of clinical tools specific for evaluation of mycotoxin-related illness, a systematic clinical approach for evaluating persons with suspected building-related respiratory illness is warranted.

Evaluation of occupational transmission of hepatitis A virus among wastewater workers

To provide information concerning potential occupational transmission of hepatitis A virus (HAV) among wastewater workers in a large city in the United States, a cross-sectional survey was performed using a saliva test to detect antibodies to HAV (anti-HAV). Fifty-nine (20%) of 302 participants tested positive for anti-HAV. After controlling for the confounding effects of age and race, wastewater work was not significantly associated with an increase in the prevalence of anti-HAV (prevalence ratio = 1.3; 95% confidence interval 0.7 to 2.4). Additionally, when examining only the wastewater workers, no statistically significant occupational risk factors for anti-HAV were identified. The results of this survey are consistent with the position of the Centers for Disease Control and Prevention regarding groups at risk for HAV infection.

Prediction of glycemic index among high-sugar, low-starch foods

A weighted mean of the glycemic index (GI) values of the constituent sugars of a non-starchy fruit is known to give a rough estimate of the GI of that fruit. Previously observed GI values (GIob) were, on average, lower than the calculated GI of the sugar mixture (GIsm) for nine acidic fruits (pH of 3.24-4.17) and tended to exceed the GIsm for six near-neutral non-starchy foods (pH < 5.33). A formula for predicting GI from GIsm and food pH was developed, and it accounted for 69% of the sum of squares for the 15 GIob values. A model that proposed that organic acids and their acidic anions slow gastric emptying and thereby lower GI was developed, and it was found to account for 57% of the GIob sum of squares. The substances responsible for lowering GI in acid fruits and the mechanisms of their action remain to be identified.

Hypersensitivity pneumonitis in a machinist

Hypersensitivity pneumonitis (HP), or extrinsic allergic alveolitis, is a patchy, interstitial lung disease that involves an immunologic reaction of the lung to repeated inhalation of foreign antigens. In this report, we describe a machinist with exposure to metalworking fluids (MWFs) and biopsy-confirmed HP. Return to work, which could be equated with a retrospective workplace-specific bronchoprovocation test, proved that working within an environment in which MWFs were used was associated with clinical deterioration in the patient's pulmonary status and with clinical improvement after removal from exposure.

Exposure of casino employees to environmental tobacco smoke

Environmental and medical evaluations were performed to evaluate occupational exposure to environmental tobacco smoke (ETS) among casino employees. Air concentrations of both nicotine and respirable dust were similar to those published in the literature for other non-industrial indoor environments. The geometric mean serum cotinine level of the 27 participants who provided serum samples was 1.34 nanograms per milliliter (ng/mL) (pre-shift) and 1.85 ng/mL (post-shift). Both measurements greatly exceeded the geometric mean value of 0.65 ng/mL for participants in the Third National Health and Nutrition Examination Survey (NHANES III) who reported exposure to ETS at work. This evaluation demonstrates that a sample of employees working in a casino gaming area were exposed to ETS at levels greater than those observed in a representative sample of the US population, and that the serum and urine cotinine of these employees increased during the workshift.

Exposures and health effects: an evaluation of workers at a sodium azide production plant

Sodium azide is the principal gas-generating agent used to inflate automobile supplemental restraint systems, more commonly called airbags. Although sodium azide is known to affect the cardiovascular system by causing peripheral vasodilation, there is no published literature describing occupational exposures to sodium azide in the rapidly growing automobile airbag industry. In 1994-1995, the National Institute for Occupational Safety and Health (NIOSH) conducted a cross-sectional study of health complaints reported by sodium azide production workers at the only continuous sodium azide production facility in the United States. The NIOSH evaluation consisted of a plant industrial hygiene survey, a symptom questionnaire, ambulatory blood pressure monitoring, and blood azide analysis. Personal breathing zone air monitoring revealed exposures to sodium azide and hydrazoic acid (a reactant product) at levels greater than the NIOSH Recommended Exposure Limits (RELs). In some cases, exposures exceeded the REL despite the use of air-supplied respirators. The questionnaire revealed that most workers reported headache (10 of 11 [91%]), episodes of low blood pressure (9 of 11 [82%]), and palpitations (8 of 11 [73%]) occurring in the production areas within the 6 months preceding the study. Mild headache (4 of 11 [36%]) was the only symptom reported during our 24-hr medical survey. Ambulatory blood pressure monitoring revealed one asymptomatic employee with a drop in blood pressure (defined as a drop in systolic [at least 20 mm Hg] and diastolic [at least 10 mm Hg] blood pressure) during a period of exposure to sodium azide at a level five times the NIOSH REL. Improvements in plant engineering controls, increased attention to employee hygiene practices, and a more comprehensive respiratory protection program were recommendations made by NIOSH to reduce exposures at the plant. All facilities handling sodium azide should be aware of the potential toxicity of sodium azide and hydrazoic acid.

Outbreak of brucellosis at a United States pork packing plant

In 1992, the North Carolina Department of Environment, Health, and Natural Resources received 18 case reports of brucellosis from a county health department. All patients had potential exposure to the kill floor of one pork processing plant. A subsequent National Institute for Occupational Safety and Health health hazard evaluation surveyed 154 (99%) of 156 kill floor workers of this plant and found that 30 (19%) had evidence of recent (or persistent) brucellosis. These data show that significant exposure to Brucella is occurring among packing plant workers in North Carolina and suggest that some of the approximately 38,000 production workers in pork processing plants in the United States are at risk of contracting swine brucellosis. Additional measures may need to be taken to prevent occupational exposure to Brucella.

Ablation of a congenital neck mass in a foal

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Determination of organic vapor respirator cartridge variability in terms of degree of activation of the carbon and cartridge packing density

The protection provided by carbon-containing organic vapor respirator cartridges depends in part on the packing density of the carbon in the cartridges and its degree of activation. Large variations in these parameters could have significant effects on the service-life of respirator cartridges. Variability among commercially available organic vapor respirator cartridges was examined with regard to the following characteristics: the particle size distribution, amount of carbon and packing density of the carbon in the cartridges and the degree of activation of the carbon. The degree of activation was determined by measuring the maximum adsorption space and the structural constant of the carbon. These two parameters--Wo (cm3/g) and k (cal/M)-2--are constants in the Dubinin/Radushkevich (D/R) model from which physical absorption onto microporous adsorbents, such as activated carbon, are described. Respirator cartridges from three different suppliers were examined. Significant variability (11-40%) in the amount and the degree of activation of the carbon occurred between cartridges of different manufacturers, as well as among cartridges of an individual manufacturer.