Mental Well-Being during COVID-19: A Cross-Sectional Study of Fly-In Fly-Out Workers in the Mining Industry in Australia

Coronavirus disease 2019 (COVID-19) has devastated the world, and its mental health impact has been recognized in the general population. However, little is known about the mental health impact of COVID-19 on fly-in fly-out (FIFO) workers, who are flown to temporarily stay and work in remote areas, during this pandemic. This study examined the mental well-being of FIFO workers in the mining industry during COVID-19 restrictions in Western Australia. An online survey was conducted between May to November 2020 among (N = 842) FIFO workers who underwent COVID-19 screening at a large mining company in Western Australia. The mental well-being score among workers was higher than population norms. One-way ANOVA with Bonferroni post-hoc tests showed significant differences in mental well-being by age, being placed under travel quarantine, undertaking self-isolation, impact of social distance guidelines, and experience of COVID-19 related symptoms. Multiple linear regression analysis showed workers who were younger, placed under travel quarantine and experienced two or more COVID-19 related symptoms were more likely to have worse mental well-being. Acknowledging the negative emotions and distress experiences among the vulnerable groups could help in providing suitable support to help lessen these negative experiences in FIFO workers.

Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes

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Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

Genome-wide 5hmC profiles to enable cancer detection and tissue of origin classification in breast, colorectal, lung, ovarian, and pancreatic cancers

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Background: Epigenomics assays have recently become popular tools for identification of molecular biomarkers, both in tissue and in plasma. In particular 5-hydroxymethyl-cytosine (5hmC) method, has been shown to enable the epigenomic regulation of gene expression and subsequent gene activity, with different patterns, across several tumor and normal tissues types. In this study we show that 5hmC profiles enable discrete classification of tumor and normal tissue for breast, colorectal, lung ovary and pancreas. Such classification was also recapitulated in cfDNA from patient with breast, colorectal, lung, ovarian and pancreatic cancers. Methods: DNA was isolated from 176 fresh frozen tissues from breast, colorectal, lung, ovary and pancreas (44 per tumor per tissue type and up to 11 tumor tissues for each stage (I-IV)) and up to 10 normal tissues per tissue type. cfDNA was isolated from plasma from 783 non-cancer individuals and 569 cancer patients. Plasma-isolated cfDNA and tumor genomic DNA, were enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to a reference genome to construct features sets of 5hmC patterns. Results: 5hmC multinomial logistic regression analysis was employed across tumor and normal tissues and identified a set of specific and discrete tumor and normal tissue gene-based features. This indicates that we can classify samples regardless of source, with a high degree of accuracy, based on tissue of origin and also distinguish between normal and tumor status.Next, we employed a stacked ensemble machine learning algorithm combining multiple logistic regression models across diverse feature sets to the cfDNA dataset composed of 783 non cancers and 569 cancers comprising 67 breast, 118 colorectal, 210 Lung, 71 ovarian and 100 pancreatic cancers. We identified a genomic signature that enable the classification of non-cancer versus cancers with an outer fold cross validation sensitivity of 49% (CI 45%-53%) at 99% specificity. Further, individual cancer outer fold cross validation sensitivity at 99% specificity, was measured as follows: breast 30% (CI 119% -42%); colorectal 41% (CI 32%-50%); lung 49% (CI 42%-56%); ovarian 72% (CI 60-82%); pancreatic 56% (CI 46%-66%). Conclusions: This study demonstrates that 5hmC profiles can distinguish cancer and normal tissues based on their origin. Further, 5hmC changes in cfDNA enables detection of the several cancer types: breast, colorectal, lung, ovarian and pancreatic cancers. Our technology provides a non-invasive tool for cancer detection with low risk sample collection enabling improved compliance than current screening methods. Among other utilities, we believe our technology could be applied to asymptomatic high-risk individuals thus enabling enrichment for those subjects that most need a diagnostic imaging follow up.

Abstract 783: Epigenomic detection of multiple cancers in plasma derived cell free DNA

Background: Our feasibility study employed a novel genomic detection methodology that enriches 5-hydroxymethylcytosine (5hmC) loci in cell free DNA (cfDNA) from the plasma of cancer patients using click chemistry coupled with sequencing and machine learning based classification methods. These classification methods were developed to detect the presence of disease in the plasma of cancer and control subjects. Cancer and control patient cfDNA cohorts were accrued from multiple sites consisting of 48 breast, 55 lung, 32 prostate and 2 pancreatic datasets consisting of 41 and 53 cancer subjects (Set 1 and 2). In addition, a control cohort of 260 subjects (non-cancer) was employed to match cancer patient demographics (age, sex and smoking status) in a case-control study design.

Methods: Machine learning methods, applied to each cancer case cohort individually, with a balancing non-cancer cohort, were able to classify cancer and control samples. Measures of predictive performance using 5-fold cross validation coupled with out-of-fold Area Under the Receiver Operating Characteristic Curve (AUROC) measures were employed. Gene sets selected as part of biomarker discovery were further analyzed for disease relevance using pathway analysis tools (GSEA, mSigDB).

Results: 260 controls and 229 cancers from four disease types (breast, lung, pancreas and prostate) were analyzed; more than 60% of cancer patients had early stage disease (I or II). Predictive performance, employing AUROC measures, was established for breast (0.89), lung (0.84), pancreas (set 1 - 0.95 and 2 - 0.93) and prostate (0.83). The genes defining each of these predictive models were enriched for pathways relevant to disease specific etiology, notably in the control of gene regulation in these same pathways. The breast cancer cohort consisted primarily of stage I and II patients including tumors < 2 cm and these samples exhibited a higher prediction probability score. The prostate cancer cohort consisted of both indolent and aggressive disease sample and prediction performance was equally high for both (AUROC for indolent vs aggressive was 0.81 and 0.77, respectively).

Conclusions: These findings suggest that 5hmC changes in cfDNA enable non-invasive detection of early stage breast, pancreatic, prostate, and lung cancers. Furthermore, 5hmC profiling in cfDNA may enable the prediction of clinically relevant features such as tumor size in breast adenocarcinoma or indolent disease in prostate cancer. Finally, this study identified a suite of 5hmC biomarkers that may be further validated in larger, and more diverse, patient cohorts.

Citation Format: Anna Bergamaschi, Jeremy Ku, Yuhong Ning, Francois Collin, Chris Ellison, Tierney Phillips, Erin McCarthy, Wendy Wang, Michael Antoine, David Haan, Aaron Scott, Paul Lloyd, Gulfem Guler, Alan Ashworth, Stephen Quake, Samuel Levy. Epigenomic detection of multiple cancers in plasma derived cell free DNA [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 783.

Monitoring immunotherapy response in non-small cell lung cancer patients using 5-hydroxymethylcytosine signatures in circulating cell free DNA

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Background: Liquid biopsies are gaining prominence for not only cancer diagnosis but also patient monitoring. Mutational signals derived from cell-free DNA (cfDNA) show promise to assess response to cancer treatment, including immunotherapy. However, reliance of these methods on mutational data from tissue biopsies limit their applicability when a tumor biopsy is unavailable, or when mutational landscape of tumor changes under the selective pressures of cancer drug treatment. Epigenomic approaches have the potential to address these shortcomings. Methods: Blood draws were obtained from a cohort of non-small cell lung cancer (NSCLC) patients (n = 19) who went on to anti-PD1 treatment prior to therapy start and while on therapy. cfDNA was isolated from plasma and was subsequently processed to generate 5hmC genome-wide profiles. Results: We analyzed cfDNA from NSCLC patients undergoing anti-PD1 therapy to investigate whether immunotherapy response can be detected from plasma. Using a predictive model trained on lung cancer and non-cancer samples, we were able to detect changes in prediction scores in patient treated with immunotherapy that were consistent with RECIST. Patients with progressive disease (n = 3), determined by RECIST, had prediction scores that increased while they received treatment. On the other hand, majority of the patients that exhibited partial response to treatment (n = 12) had predictive scores that decreased with treatment, again consistent with RECIST. Furthermore, score changes consistent with RECIST was observed one cycle prior to the RECIST timepoint in all except one patient, where an extra blood draw after baseline was available (n = 7). Annotation of the regions that account for differential scoring identified enhancer, 5’UTR and promoter regions. Comparison of partial responders to patients with progressive disease revealed genes involved in metastasis, oncogenes and tumor suppressors that change in opposing directions between these patient groups, consistent with the underlying biology. Conclusions: Our results suggest that 5hmC profiles from cfDNA can be used to determine immunotherapy response in non-small cell lung cancer patients. Compared with mutation based liquid biopsy methods to assess response, epigenomics-based methods have the advantage of being agnostic to starting tumor mutations, and not relying on a mutational analysis from tumor biopsy. Future work will help determine applicability of this method to other kinds of therapies and cancer types.

Effect of detection of epigenomic changes in plasma-derived cell-free DNA on multicancer classification

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Background: Epigenomic changes in DNA methylation patterns are more precisely delineated by active demethylation events as marked by 5-hydroxymethylation (5hmC) of cytosine residues. 5hmC appears to be dynamically modulated in tumor tissues and can be employed as a cancer biomarker. Strategies which interrogate 5hmC genome-wide patterns in a liquid biopsy context may provide efficient and precise technology for early cancer screening and detection. In this study we identified genome-wide 5hmC changes in plasma based circulating free DNA (cfDNA) from breast, colorectal, lung, pancreatic and prostate cancer patients versus non-cancer individuals. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using novel click-chemistry protocol for labelling followed by sequencing and alignment to a reference genome to construct features sets of 5hmC patterns. Regularized classification models were constructed to classify cancer samples apart from non-cancer. Results: > 500 non-cancer individuals and > 500 cancer patients across five cancer types (breast, colorectal, lung, pancreas and prostate) were included in this study. About 60% of the cancer samples were early stage disease (I or II). The ability to classify non-cancer versus cancer patients was evaluated by 5-fold cross validation of our trained prediction models. Our models were able to classify all breast cancer with a test auROC of 0.86 while prediction model classification for ER negative samples had an auROC of 0.92. Colorectal performance auROC was 0.9; lung auROC = 0.92, pancreatic auROC = 0.97 and prostate auROC = 0.91. Overall sensitivity range, when allowing 2% false positive, was between 85% and 52%. Further using 5hmC signal in blood we were able to identify several signaling pathways specifically relevant to the biology of the cancers investigated. Conclusions: These findings further demonstrate that 5hmC changes in cfDNA enable non-invasive detection of breast, colorectal, lung pancreatic, and prostate cancers. Further, 5hmC signals enabled the identification of a suite of cancer signaling pathways differentially enriched in cancers versus non-cancers. These data suggest that dynamic changes in tumor cell methylation, detectable through 5-hydroxymethylation, are contained in the circulating blood and signal active disease biology.

Republished: What Is the Return on Investment for Implementation of a Crew Resource Management Program at an Academic Medical Center?

Crew Resource Management (CRM) training has been used successfully within hospital units to improve quality and safety. This article presents a description of a health system-wide implementation of CRM focusing on the return on investment (ROI). The costs included training, programmatic fixed costs, time away from work, and leadership time. Cost savings were calculated based on the reduction in avoidable adverse events and cost estimates from the literature. Between July 2010 and July 2013, roughly 3000 health system employees across 12 areas were trained, costing $3.6 million. The total number of adverse events avoided was 735—a 25.7% reduction in observed relative to expected events. Savings ranged from a conservative estimate of $12.6 million to as much as $28.0 million. Therefore, the overall ROI for CRM training was in the range of $9.1 to $24.4 million. CRM presents a financially viable way to systematically organize for quality improvement.

Abstract 1372: Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylated cytosines (5hmC) in circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). 5hmC profiles from PDAC and non-cancer samples were generated using a previously published modified hMe-Seal protocol that utilizes chemical labeling of 5hmC by β-glucosyltransferase and allows detection of cell free 5hmC from small amounts of cfDNA (1). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3’UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3 associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in a comprehensive set of genes with the most variable 5hmC counts and performed with an AUC = 0.94 - 0.96 on training data. We tested the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on three independent pancreatic cancer 5hmC data sets (n = 26, 23 and 7) compared with corresponding independent non-cancer cohorts (n =103, 53 and 10), and found validation performance to be AUC = 0.74 - 0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples. Reference: 1. Song, C. - X. et al. 5 - Hydroxymethylcytosine signatures in cell-free DNA provide information about tumor types and stages. Cell Res 27, 1231 (2017).

Citation Format: Francois Collin, Yuhong Ning, Gulfem D. Guler, Tierney Phillips, Erin McCarthy, Aaron Scott, Chris Ellison, Chin-Jen Ku, Kim Chau, Alan Ashworth, Stephen R. Quake, Samuel Levy. Detection of early stage pancreatic cancer using 5–hydroxymethylcytosine signatures in circulating cell free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1372.

Changes in DNA hydroxymethylation for the detection of multiple cancers in plasma cell-free DNA

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Background: Methylation and hydroxymethylation of cytosines enable the epigenomic regulation of gene suppression and activation. 5-hydroxymethyl-cytosine (5hmC) is globally decreased in tumor tissue. However, genome-wide analysis using precise 5hmC labelling techniques reveals more nuanced changes upon tumorigenesis and raises the possibility that this loss could be exploited for developing a cancer biomarker. This suggests that 5hmC profiles might enable discrete classification of not only tumor tissue but also of tumor cell-free DNA (cfDNA). We sought to identify genome-wide 5hmC changes in plasma based cfDNA from cancer patients representing multiple disease types, stages and clinical characteristics in comparison with non-cancer patients. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to the genome to determine 5hmC counts per genomic feature. Regularized regression models were constructed to classify cancer samples (age matched or corrected for smoking status) on non-overlapping training (80% of all samples) and test sample sets (20% of all samples). Results: 226 non-cancer patients and 278 cancers across four cancer types (breast, colorectal, lung-squamous and pancreas) were included in this study, where more than 60% of cancer samples were early stage disease (I or II). Upon comparison with non-cancer samples, 5hmC peaks have reduced enrichment in exons in breast, colorectal and lung cancer but not in pancreatic cancer. Further, 5hmC peaks in pancreas show different patterns of enrichment in 3’UTR, translational termination sites, promoters and LTR. Overall 5hmC signal density was reduced in late stage cancers across all four diseases. The ability to classify non-cancer versus cancer patients was evaluated via cross-validation of out of fold prediction in the training set with AUC > 0.84 for all four cancer types. Further, test set sensitivity across all four cancer types was found to be > 66% with 98% specificity. Conclusions: These findings suggest that 5hmC changes in plasma cfDNA enable classification of early stages of breast, colorectal, lung-squamous and pancreas cancer and are promising biomarkers for disease detection.

Comparison of the metabolism of 10 chemicals in human and pig skin explants

Skin metabolism is important to consider when assessing local toxicity and/or penetration of chemicals and their metabolites. If human skin supply is limited, pig skin can be used as an alternative. To identify any species differences, we have investigated the metabolism of 10 chemicals in a pig and human skin explant model. Phase I metabolic pathways in skin from both species included those known to occur via cytochrome P450s, esterases, alcohol dehydrogenases and aldehyde dehydrogenases. Common Phase II pathways were glucuronidation and sulfation but other conjugation pathways were also identified. Chemicals not metabolized by pig skin (caffeine, IQ and 4‐chloroaniline) were also not metabolized by human skin. Six chemicals metabolized by pig skin were metabolized to a similar extent (percentage parent remaining) by human skin. Human skin metabolites were also detected in pig skin incubations, except for one unidentified minor vanillin metabolite. Three cinnamyl alcohol metabolites were unique to pig skin but represented minor metabolites. There were notable species differences in the relative amounts of common metabolites. The difference in the abundance of the sulfate conjugates of resorcinol and 4‐amino‐3‐nitrophenol was in accordance with the known lack of aryl sulfotransferase activity in pigs. In conclusion, while qualitative comparisons of metabolic profiles were consistent between pig and human skin, there were some quantitative differences in the percentage of metabolites formed. This preliminary assessment suggests that pig skin is metabolically competent and could be a useful tool for evaluating potential first‐pass metabolism before testing in human‐derived tissues.

We have investigated the metabolism of 10 chemicals in viable pig and human skin. Phase I and II metabolic pathways were present in skin from both species. Chemicals not metabolized by pig skin were also not metabolized by human skin. Six chemicals metabolized by pig skin were also metabolized to a similar extent by human skin. Pig and human skin produced common metabolites, although some species differences were observed and as their relative amounts differed.

What Is the Return on Investment for Implementation of a Crew Resource Management Program at an Academic Medical Center?

Crew Resource Management (CRM) training has been used successfully within hospital units to improve quality and safety. This article presents a description of a health system-wide implementation of CRM focusing on the return on investment (ROI). The costs included training, programmatic fixed costs, time away from work, and leadership time. Cost savings were calculated based on the reduction in avoidable adverse events and cost estimates from the literature. Between July 2010 and July 2013, roughly 3000 health system employees across 12 areas were trained, costing $3.6 million. The total number of adverse events avoided was 735—a 25.7% reduction in observed relative to expected events. Savings ranged from a conservative estimate of $12.6 million to as much as $28.0 million. Therefore, the overall ROI for CRM training was in the range of $9.1 to $24.4 million. CRM presents a financially viable way to systematically organize for quality improvement.

Recombining without Hotspots: A Comprehensive Evolutionary Portrait of Recombination in Two Closely Related Species of Drosophila

Meiotic recombination rate varies across the genome within and between individuals, populations, and species in virtually all taxa studied. In almost every species, this variation takes the form of discrete recombination hotspots, determined in some mammals by a protein called PRDM9. Hotspots and their determinants have a profound effect on the genomic landscape, and share certain features that extend across the tree of life. Drosophila, in contrast, are anomalous in their absence of hotspots, PRDM9, and other species-specific differences in the determination of recombination. To better understand the evolution of meiosis and general patterns of recombination across diverse taxa, we present a truly comprehensive portrait of recombination across time, combining recently published cross-based contemporary recombination estimates from each of two sister species with newly obtained linkage-disequilibrium-based historic estimates of recombination from both of these species. Using Drosophila pseudoobscura and Drosophila miranda as a model system, we compare recombination rate between species at multiple scales, and we suggest that Drosophila replicate the pattern seen in human-chimpanzee in which recombination rate is conserved at broad scales. We also find evidence of a species-wide recombination modifier(s), resulting in both a present and historic genome-wide elevation of recombination rates in D. miranda, and identify broad scale effects on recombination from the presence of an inversion. Finally, we reveal an unprecedented view of the distribution of recombination in D. pseudoobscura, illustrating patterns of linked selection and where recombination is taking place. Overall, by combining these estimation approaches, we highlight key similarities and differences in recombination between Drosophila and other organisms.

Nuclear and genome dynamics in multinucleate ascomycete fungi

Genetic variation between individuals is essential to evolution and adaptation. However, intra-organismic genetic variation also shapes the life histories of many organisms, including filamentous fungi. A single fungal syncytium can harbor thousands or millions of mobile and potentially genotypically different nuclei, each having the capacity to regenerate a new organism. Because the dispersal of asexual or sexual spores propagates individual nuclei in many of these species, selection acting at the level of nuclei creates the potential for competitive and cooperative genome dynamics. Recent work in Neurospora crassa and Sclerotinia sclerotiorum has illuminated how nuclear populations are coordinated for fungal growth and other behaviors and has revealed both molecular and physical mechanisms for preventing and policing inter-genomic conflict. Recent results from population-level genomic studies in a variety of filamentous fungi suggest that nuclear exchange between mycelia and recombination between heterospecific nuclei may be of more importance to fungal evolution, diversity and the emergence of newly virulent strains than has previously been recognized.

Impact of a worker notification program: assessment of attitudinal and behavioral outcomes

BACKGROUND

Hundreds of worker notification programs are conducted each year to communicate occupational risks to workers. However, few attempts have been made to evaluate their effectiveness and few have described how communication theories are applied in developing notification messages. We developed and assessed the effectiveness of a worker notification program at a beryllium machining plant.

METHODS

We compared self-protective attitudinal and behavioral responses among workers in two plants: (1) an intervention plant that received beryllium risk notification and (2) a matched control plant that did not receive notification.

RESULTS

Workers receiving notification reported significantly stronger perceptions of threat and efficacy, more positive attitudes toward safety practices, and engaged in more protective behaviors than the workers at the control plant.

CONCLUSIONS

This study demonstrates the utility of applying communication theories in the development of notification messages and the results suggest that mass presentations may be just as effective, if not more so, than one-on-one notifications. Am. J. Ind. Med. 37:205-213, 2000. Published 2000 Wiley-Liss, Inc.

Acute, lethal graft-versus-host disease in an F1-hybrid model using grafts from parental-strain, T-cell receptor-delta gene knockout donors

Gammadelta T cells have been implicated in the pathogenesis of acute graft-versus-host disease (GVHD). We therefore performed experiments to determine whether mortality from GVHD is reduced in C57BL/6 x DBA/2 F1-hybrid (BDF1-hybrid) mice when parental strain, T-cell receptor-delta (TCRdelta) knockout (KO) donors are used. We compared mortality, weight loss, interferon-gamma (IFN-gamma) production and cytotoxic activity in recipients of either wild-type or TCRdelta KO grafts. In both groups there was significant weight loss and an identical level of mortality. Elevated IFN-gamma levels were present in both groups, but recipients of TCRdelta KO grafts produced twice as much as recipients of wild-type grafts. Elevated natural killer (NK) and NK-like activity was also seen in both. These results demonstrate that TCRdelta KO grafts can induce GVHD as severe as that seen in recipients of wild-type grafts, a finding that is at odds with studies demonstrating reduced mortality when gammadelta T cells are purged from donor mice. We suggest that the inconsistency may lie in the higher levels of IFN-gamma seen with TCRdelta KO grafts and that the protection afforded by the absence of gammadelta T cells in the graft is overwhelmed by the higher levels of IFN-gamma.

Effect of pyruvate on lens myo-inositol transport and polyol formation in diabetic cataract

In diabetic cataract, sorbitol pathway flux perturbs intracellular metabolism by two putative mechanisms. The osmolyte hypothesis implicates the aldose reductase enzyme, increased rate of reduction of glucose of sorbitol and reciprocal osmoregulatory depletion of organic osmolytes (myo-inositol). Redox hypothesis favors alterations in the ratios (NADP+/NADPH and/or NADH/NAD+ as the primary cause of glucose-induced aldose reductase related defects. Increase in NADH/NAD+ promotes increased oxidation of sorbitol to fructose by polyol dehydrogenase; potential normalization of this ratio by coadministration of pyruvate (which reoxidizes NADH to NAD+ via lactate dehydrogenases reaction) was investigated. Effects of exogenous pyruvate on lens polyol formation and sodium-dependent myo-inositol (MI) cotransporter using two in vitro models of sugar cataract were determined. Rat lenses were incubated for 16 h in either normal (5.5 mM) or high sugar medium, 35.5 mM glucose or 30 mM galactose. Then lens MI influx was compared to polyol, MI and fructose content. Pyruvate did not affect MI influx or sorbitol content in lenses incubated in control medium. In 35.5 mM glucose, coadministration of pyruvate maintained lens MI influx at 76% of control values vs. 43% for lenses without pyruvate. Furthermore, pyruvate treatment diminished lens sorbitol content by 50% and increased lens sugar content (myo-inositol, fructose, lactate) and media lactate levels. Lenses incubated in high galactose medium formed galactitol with a corresponding decreased MI content. Coadministration of pyruvate had no effect on either lens sugar content (galactitol, myo-inositol, fructose) or MI influx, consistent with the fact that galactitol was not metabolized to fructose. In conclusion, pyruvate did not exert a direct effect on the MI co-transporter or prevent galactitol inhibition of MI influx. Coadministration of pyruvate with high glucose altered lens metabolism and promoted reduction of pyruvate to lactate, increased fructose, decreased sorbitol, enhanced MI influx, maintained lens MI content, implicating both osmotic and redox systems.

In vivo direction of CD4 T cells to Th1 and Th2-like patterns of cytokine synthesis

Factors that influence the initial development, and continued maintenance, of Th1 or Th2-like responses in vivo play a pivotal role in determining immune effector mechanisms and clinical outcome. Here, we review recent developments in this area with particular emphasis on (i) the ability of chemically modified exogenous antigens to preferentially activate Th1-dominated responses in vivo and (ii) the role played by NK cells in initial commitment of naive exogenous antigen-specific T cells to Th1 or Th2-like cytokine synthesis. We find that NK cell depletion of naive mice prior to immunization with OVA (which induces balanced Th0 like responses), or a high Mr polymer (that preferentially elicits OVA-specific Th1-dominated responses), fails to influence the development of cytokine or specific antibody responses. The results argue that NK cells do not play an essential role in shaping induction of immune responses to exogenous antigens, the most common class of inhalant allergen.

Bacterial meningitis in Arizona American Indian children

Bacterial meningitis is a major cause of morbidity and mortality in Arizona infants and children. A retrospective review of 102 cases of meningitis occurring in the American Indian population documents the prevalence of the Haemophilus influenzae organism with a peak incidence in the first year of life. The rate of H influenzae resistance to ampicillin was 16%. Overall morbidity and mortality rates are comparable with reviews of diverse populations, but there is an exceptional mortality and prolonged hospitalization in patients less than 1 year of age. The development of an efficacious vaccine against H influenzae may substantially reduce and prevent this cause of meningitis.

Sputum cytology among frequent users of pressurized spray cans

Sputum samples were collected from a group of private patients who had no respiratory symptoms but who frequently used aerosols generated by pressurized cans, and from two groups of controls. Atypical metaplastic changes in exfoliated cells were compared between the groups. An excess of moderate and marked atypical metaplastic cells was found among the frequent aerosol users. This association, which suggests that some aerosol preparations either alter the flora of the bronchial tree or contain carcinogenic agents, strongly suggests that additional studies be done on aerosol can ingredients, and that these sprays be used in a manner to minimize inhalation of the resultant aerosol, except for medical preparations where proper control is exercised.