Urine proteome profile of firefighters with exposure to emergency fire-induced smoke: A pilot study to identify potential carcinogenic effects.

Firefighters are frequently exposed to a variety of chemicals formed from smoke, which pose a risk for numerous diseases, including cancer. Comparative urine proteome profiling could significantly improve our understanding of the early detection of potential cancer biomarkers. In this study, for the first time, we conducted a comparative protein profile analysis of 20 urine samples collected from ten real-life firefighters prior to and following emergency fire-induced smoke. Using a label-free quantitative proteomics platform, we identified and quantified 1325 unique protein groups, of which 45 proteins showed differential expressions in abundance in response to fire-smoke exposure (post) compared to the control (pre). Pathway analysis showed proteins associated with epithelium development (e.g., RHCG, HEG1, ADAMTSL2) and Alzheimer's disease (SORL1) were significantly increased in response to smoke exposure samples. A protein-protein-network study showed a possible link between these differentially abundant proteins and the known cancer gene (TP53). Moreover, a cross-comparison analysis revealed that seven proteins-ALDH1A1, APCS, POMC, COL2A1, RDX, DDAH2, and SDC4 overlapped with the previously published urine cancer proteome datasets, suggesting a potential cancer risk. Our findings demonstrated that the discovery proteomic platform is a promising analytical technique for identifying potential non-invasive biomarkers associated with fire-smoke exposure in firefighters that may be related to cancer.

Preliminary analyses of accumulation of carcinogenic contaminants on retired firefighter ensembles.

Personal protective equipment (PPE) is designed to protect firefighters from hazards encountered on the fire scene, including heat and products of combustion. Decontamination practices for firefighter turnout gear have been developed to remove combustion products and other contaminants from the fabric of structural firefighting ensembles (i.e., turnout or bunker gear). Chronic exposures to residual polycyclic aromatic hydrocarbons (PAH) are a contributing cause of firefighter cancers. To identify and quantify residual contamination of PAH, samples were taken from two individual decommissioned structural firefighting ensembles and analyzed by layer (outer canvas shell, moisture barrier, and the thermal protective liner) for (1) textile integrity via field emission scanning electron microscopy and (2) quantity of PAH contamination by high-pressure liquid chromatography with ultraviolet/fluorescence detection. The results of these analyses show the presence of the PAH compounds pyrene (35% of the total mass of PAH), phenanthrene (21%), benzo(a)pyrene (14%), and benzo(a)anthracene (14%) which present a risk for dermal absorption. The data also revealed that PAH penetration through the layers of the firefighting ensemble was strongly inhibited by the moisture barrier layer.

Face-to-face with scorching wildfire: potential toxicant exposure and the health risks of smoke for wildland firefighters at the wildland-urban interface.

As wildfire risks have elevated due to climate change, the health risks that toxicants from fire smoke pose to wildland firefighters have been exacerbated. Recently, the International Agency for Research on Cancer (IARC) has reclassified wildland firefighters' occupational exposure as carcinogenic to humans (Group 1). Wildfire smoke contributes to an increased risk of cancer and cardiovascular disease, yet wildland firefighters have inadequate respiratory protection. The economic cost of wildland fires has risen concurrently, as illustrated by the appropriation of $45 billion for wildfire management over FYs 2011-2020 by the U.S. Congress. Occupational epidemiological studies of wildland firefighters are crucial for minimizing health risks; however, they must account for the mixture of exposures in wildfire smoke. This review focuses on four aspects of wildland firefighters' health risks at the wildland-urban interface: 1) economic costs and health impact, 2) respiratory protection, 3) multipollutant mixtures, and 4) proactive management of wildfires.

Urinary Metabolites of Polycyclic Aromatic Hydrocarbons in Firefighters: A Systematic Review and Meta-Analysis.

Firefighters are intermittently exposed to complex, mixed pollutants in random settings. Of those pollutants, PAHs (polycyclic aromatic hydrocarbons) are the most commonly studied and best understood. PAH exposure can occur via multiple routes; therefore, the levels of hydroxylated metabolites of PAHs in urine have been used as a biomonitoring tool for risk assessment. We performed a systematic review and meta-analysis of the literature to estimate the levels of urinary hydroxylated PAH (OHPAH) among firefighters, determine risk attributions, and, finally, evaluate the scope of preventive efforts and their utility as diagnostic tools. The meta-regression confirmed increases in OHPAH concentrations after fire activities by up to 1.71-times (p-values: <0.0001). Samples collected at a time point of 2−4 h after a fire suppression showed a consistent, statistically significant pattern as compared with baseline samples. The National Fire Protection Association (NFPA) standard 1582 Standard on Comprehensive Occupational Medical Program for Fire Departments lists various health examinations, including a urinalysis for occupational chemical exposure if indicated and medical screening for cancers and cardiovascular diseases. Biomonitoring is a valuable screening tool for assessing occupational exposure and the results of this meta-analysis support their inclusion in regular health screenings for firefighters.

Validation of a High Flow Rate Puff Topography System Designed for Measurement of Sub-Ohm, Third Generation Electronic Nicotine Delivery Systems.

There are few known puff topography devices designed solely for gathering electronic cigarette puff topography information, and none made for high-powered sub-ohm devices. Ten replicate Bernoulli flow cells were designed and 3D printed. The relationship between square root of pressure difference and flow rate was determined across 0−70 L/min. One representative flow cell was used to estimate puff volume and flow rate under six simulated puffing regimes (0.710 L, 2.000 L and 3.000 L, at low and high flow rates) to determine the system's accuracy and utility of using dual pressure sensors for flow measurement. The relationship between flow rate and square root of pressure differential for the ten replicate cells was best fit with a quadratic model (R2 = 0.9991, p < 0.0001). The higher-pressure sensor was accurate at both low and high flow rates for 0.71 L (102% and 111% respectively), 2.00 L (96% and 103% respectively), and 3.00 L (100.1% and 107% respectively) but the lower-pressure sensor provided no utility, underpredicting volume and flow. This puff topography system generates very little resistance to flow, easily fits between user's atomizer and mouthpiece, and is calibrated to measure flows up to 70 L/min.

Assessing urinary phenol and paraben mixtures in pregnant women with and without gestational diabetes mellitus: A case-control study.

Prior studies have identified the associations between environmental phenol and paraben exposures and increased risk of gestational diabetes mellitus (GDM), but no study addressed these exposures as mixtures. As methods have emerged to better assess exposures to multiple chemicals, our study aimed to apply Bayesian kernel machine regression (BKMR) to evaluate the association between phenol and paraben mixtures and GDM. This study included 64 GDM cases and 237 obstetric patient controls from the University of Oklahoma Medical Center. Mid-pregnancy spot urine samples were collected to quantify concentrations of bisphenol A (BPA), benzophenone-3, triclosan, 2,4-dichlorophenol, 2,5-dichlorophenol, butylparaben, methylparaben, and propylparaben. Multivariable logistic regression was used to evaluate the associations between individual chemical biomarkers and GDM while controlling for confounding. We used probit implementation of BKMR with hierarchical variable selection to estimate the mean difference in GDM probability for each component of the phenol and paraben mixtures while controlling for the correlation among the chemical biomarkers. When analyzing individual chemicals using logistic regression, benzophenone-3 was positively associated with GDM [adjusted odds ratio (aOR) per interquartile range (IQR) = 1.54, 95% confidence interval (CI) 1.15, 2.08], while BPA was negatively associated with GDM (aOR 0.61, 95% CI 0.37, 0.99). In probit-BKMR analysis, an increase in z-score transformed log urinary concentrations of benzophenone-3 from the 10th to 90th percentile was associated with an increase in the estimated difference in the probability of GDM (0.67, 95% Credible Interval 0.04, 1.30), holding other chemicals fixed at their medians. No associations were identified between other chemical biomarkers and GDM in the BKMR analyses. We observed that the association of BPA and GDM was attenuated when accounting for correlated phenols and parabens, suggesting the importance of addressing chemical mixtures in perinatal environmental exposure studies. Additional prospective investigations will increase the understanding of the relationship between benzophenone-3 exposure and GDM development.

Using Collaborative Partnerships to Engage Firefighters in Rural Communities.

The purpose of this study was to utilize community-based participatory research (CBPR) methods to identify behaviors that may increase the exposure rates of firefighters to carcinogens and other occupational hazards. Key informant interviews and focus groups were conducted as part of a larger study that included exposure assessments at fire stations, in fire engines, and in personal vehicles. A purposive sample of five fire chiefs and leaders of the firefighter association was chosen, and these individuals were selected to participate in interviews. Unstructured interviews explored issues related to firefighter exposures and occupational hazards. Three focus groups were conducted over a three-month period. Following the focus groups, survey questions emphasizing the following three aspects of firefighting were developed: exposure to airborne smoke contaminants during fire suppression, accumulated exposure on turnout gear after fire suppression, and exposure to airborne contaminants at the fire departments. The use of community-based participatory research can be very beneficial, especially when conducting research with a group that may be hard to reach or have misgivings regarding researchers. By utilizing this approach in the current study, researchers were able to partner with a community that may be hard to reach and gain buy-in from community leadership.

Effects of Platelet-Rich Plasma on Clinical Outcomes After Anterior Cruciate Ligament Reconstruction: A Systematic Review and Meta-analysis.

BACKGROUND: Many studies have documented the use of platelet-rich plasma (PRP) alongside anterior cruciate ligament (ACL) reconstruction (ACLR) in the management of ACL injury, but evidence on the benefits of PRP in improving the clinical outcomes of ACLR is inconsistent. PURPOSE: To help in our understanding, we undertook a systematic review and meta-analysis of randomized controlled trials (RCTs) that evaluated the effects of PRP on patient-reported functional scores, the clinical assessments of knee function and structure, and complications. STUDY DESIGN: Systematic review; Level of evidence, 1. METHODS: We searched 9 online databases for RCTs published in English or Chinese that examined the effects of PRP on ACLR. The primary outcome measures were visual analog scale (VAS) for pain and International Knee Documentation Committee (IKDC) scores. The secondary outcomes included KT-1000 arthrometer, pivot-shift test, Lysholm and Tegner scores, tunnel widening, graft characterization, and complications. Subgroup analyses were performed according to time of assessments. Fixed- and random-effects models were selected for data analysis. RESULTS: A total of 14 studies were included. When PRP was injected to graft tunnels, the pooled VAS scores of the 2 groups were similar (P = .31), and the subgroup analysis found that VAS and IKDC only improved at 3 months postoperatively (P = .0003 and P < .00001, respectively). When PRP was used at the bone-patellar tendon-bone harvest sites, VAS was decreased in the first 6 months postoperatively (P < .00001), whereas IKDC score was not remarkably different (P = .07). After PRP injection, Lysholm scores at 3 months postoperatively was different between the 2 groups (P < .00001), but the Tegner scores (P = .86), KT-1000 measurements (P = .12), the positive rate of pivot-shift test (P = .64), the enlargement of tunnels (femoral, P = .91; tibial, P = .80), and the characterization of grafts (P = .05) were not different. No difference in complications was found in either group. CONCLUSION: PRP applied alongside ACLR could reduce postoperative pain and improve knee function in the short and medium terms but is ineffective in the long term. PRP does not improve knee stability and the enlargement of tunnels and does not accelerate the healing of grafts. Further studies would be required.

Reconstructing Historical Exposures to Respirable Dust and Respirable Silica in the Taconite Mining Industry for 1955-2010.

The goal of this study was to reconstruct the historical respirable silica (RS) and respirable dust (RD) exposures of workers in the Minnesota taconite industry from 1955 to 2010 as part of several epidemiological studies for assessing the association between exposure to components of taconite dusts and the development of respiratory diseases. A job-exposure matrix (JEM) was developed that uses 9127 RS and 19 391 RD occupational hygiene historical measurements. Historical RS and RD data were extracted from several sources and were grouped into seven mines and then into eight departments [Concentrating, Crushing, Janitor, Mining, Office/control room, Pelletizing, Shop (mobile), and Shop (stationary)]. Within each department, we applied a two-level random-intercept regression model which assumes that the natural log of Y (RD or RS concentration) changes over time at a constant rate. Among all predicted RD and RS values, we found that larger RD values were located in the following departments: Crushing, Concentrating, Pelletizing, and Shop (mobile). Larger RS values were located only in either Crushing or Shop (mobile). The annual rates of change for historical RD and RS exposures were between -3.3 and 3.2%. The silica percentage in the dust varied by mine/department with the highest value of 29.3% in Mine F (Crushing) and the lowest value of 2.1% in Mine B (Pelletizing). The predicted historical RD and RS arithmetic mean exposures ranged between <0.075 and 3.14 mg m-3, and between <0.005 and 0.36 mg m-3, respectively. The result of this study is a JEM by mine, department, and year for RD and RS for epidemiological studies.

Urinary Proteomics of Simulated Firefighting Tasks and Its Relation to Fitness Parameters.

Firefighting rescues are high-hazard activities accompanied by uncertainty, urgency, and complexity. Knowledge of the metabolic characteristics during firefighting rescues is of great value. The purpose of this study was to explore the firefighting-induced physiological responses in greater depth. The urine samples of ten firefighters were collected before and after the simulated firefighting, and the proteins in urine samples were identified by the liquid chromatography-mass spectroscopy. Blood lactate and heart rate were measured. There were 360 proteins up-regulated and 265 proteins downregulated after this simulated firefighting. Changes in protein expression were significantly related to acute inflammatory responses, immune responses, complement activation, and oxidative stress. Beta-2-microglobulin (r = 0.76, p < 0.05) and von Willebrand factors (r = 0.81, p < 0.01) were positively correlated with heart rate during simulated firefighting, and carbonic anhydrase 1 (r = 0.67, p < 0.05) were positively correlated with blood lactate after simulated firefighting. These results illustrated that Beta-2-microglobulin, von Willebrand, and carbonic anhydrase 1 could be regarded as important indicators to evaluate exercise intensity for firefighters.

Asbestos Detection with Fluorescence Microscopy Images and Deep Learning.

Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously developed software was not accurate for samples with low fiber concentration. Machine learning-based techniques (e.g., deep learning) for image analysis, particularly Convolutional Neural Networks (CNN), have been widely applied to many areas. The objectives of this study were to (1) create a database of a wide-range asbestos concentration (0-50 fibers/liter) fluorescence microscopy (FM) images in the laboratory; and (2) determine the applicability of the state-of-the-art object detection CNN model, YOLOv4, to accurately detect asbestos. We captured the fluorescence microscopy images containing asbestos and labeled the individual asbestos in the images. We trained the YOLOv4 model with the labeled images using one GTX 1660 Ti Graphics Processing Unit (GPU). Our results demonstrated the exceptional capacity of the YOLOv4 model to learn the fluorescent asbestos morphologies. The mean average precision at a threshold of 0.5 (mAP@0.5) was 96.1% ± 0.4%, using the National Institute for Occupational Safety and Health (NIOSH) fiber counting Method 7400 as a reference method. Compared to our previous counting software (Intec/HU), the YOLOv4 achieved higher accuracy (0.997 vs. 0.979), particularly much higher precision (0.898 vs. 0.418), recall (0.898 vs. 0.780) and F-1 score (0.898 vs. 0.544). In addition, the YOLOv4 performed much better for low fiber concentration samples (<15 fibers/liter) compared to Intec/HU. Therefore, the FM method coupled with YOLOv4 is remarkable in detecting asbestos fibers and differentiating them from other non-asbestos particles.

In Silico identification of a common mobile element insertion in exon 4 of RP1.

Mobile element insertions (MEIs) typically exceed the read lengths of short-read sequencing technologies and are therefore frequently missed. Recently, a founder Alu insertion in exon 4 of RP1 has been detected in Japanese patients with macular dystrophy by PCR and gel electrophoresis. We aimed to develop a grep search program for the detection of the Alu insertion in exon 4 of RP1 using unprocessed short reads. Among 494 unrelated Korean patients with inherited eye diseases, 273 patients with specific retinal phenotypes who were previously genotyped by targeted panel or whole exome sequencing were selected. Five probands had a single heterozygous truncating RP1 variant, and one of their unaffected parents also carry this variant. To find a hidden genetic variant, whole genome sequencing was performed in two patients, and it revealed AluY c.4052_4053ins328/p.(Tyr1352Alafs*9) insertion in RP1 exon 4. This AluY insertion was additionally identified in other 3 families, which was confirmed by PCR and gel electrophoresis. We developed simplified grep search program to detect this AluY insertion in RP1 exon 4. The simple grep search revealed a median variant allele frequency of 0.282 (interquartile range, 0.232-0.383), with no false-positive results using 120 control samples. The MEI in RP1 exon 4 was a common founder mutation in Korean, occurring in 1.8% of our cohort. The RP1-Alu grep program efficiently detected the AluY insertion, without the preprocessing of raw data or complex installation processes.

Simultaneous modeling of detection rate and exposure concentration using semi-continuous models to identify exposure determinants when left-censored data may be a true zero.

BACKGROUND: Most methods for treating left-censored data assume the analyte is present but not quantified. Biased estimates may result if the analyte is absent such that the unobserved data represents a mixed exposure distribution with an unknown proportion clustered at zero. OBJECTIVE: We used semi-continuous models to identify time and industry trends in 52,457 OSHA inspection lead sample results. METHOD: The first component of the semi-continuous model predicted the probability of detecting concentrations ≥ 0.007 mg/m3 (highest estimated detection limit, 62% of measurements). The second component predicted the median concentration of measurements ≥ 0.007 mg/m3. Both components included a random-effect for industry and fixed-effects for year, industry group, analytical method, and other variables. We used the two components together to predict median industry- and time-specific lead concentrations. RESULTS: The probabilities of detectable concentrations and the median detected concentrations decreased with year; both were also lower for measurements analyzed for multiple (vs. one) metals and for those analyzed by inductively-coupled plasma (vs. atomic absorption spectroscopy). The covariance was 0.30 (standard error = 0.06), confirming the two components were correlated. SIGNIFICANCE: We identified determinants of exposure in data with over 60% left-censored, while accounting for correlated relationships and without assuming a distribution for the censored data.

Health Risks of Structural Firefighters from Exposure to Polycyclic Aromatic Hydrocarbons: A Systematic Review and Meta-Analysis.

Firefighters have an elevated risk of cancer, which is suspected to be caused by occupational and environmental exposure to fire smoke. Among many substances from fire smoke contaminants, one potential source of toxic exposure is polycyclic aromatic hydrocarbons (PAH). The goal of this paper is to identify the association between PAH exposure levels and contributing risk factors to derive best estimates of the effects of exposure on structural firefighters' working environment in fire. We surveyed four databases (Embase, Medline, Scopus, and Web of Science) for this systematic literature review. Generic inverse variance method for random effects meta-analysis was applied for two exposure routes-dermal and inhalation. In dermal, the neck showed the highest dermal exposure increased after the fire activity. In inhalation, the meta-regression confirmed statistically significant increases in PAH concentrations for longer durations. We also summarized the scientific knowledge on occupational exposures to PAH in fire suppression activities. More research into uncontrolled emergency fires is needed with regard to newer chemical classes of fire smoke retardant and occupational exposure pathways. Evidence-based PAH exposure assessments are critical for determining exposure-dose relationships in large epidemiological studies of occupational risk factors.

Urinary total arsenic and arsenic methylation capacity in pregnancy and gestational diabetes mellitus: A case-control study.

Previous studies suggest arsenic exposure may increase the risk of gestational diabetes mellitus (GDM). However, prior assessments of total arsenic concentrations have not distinguished between toxic and nontoxic species. Our study aimed to investigate the relationships between inorganic arsenic exposure, arsenic methylation capacity, and GDM. Sixty-four cases of GDM and 237 controls were analyzed for urinary concentrations of inorganic arsenic species and their metabolites (arsenite (As3), arsenate (As5), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA)), and organic forms of arsenic. Inorganic arsenic exposure was defined as the sum of inorganic and methylated arsenic species (iSumAs). Methylation capacity indices were calculated as the percentage of inorganic arsenic species [iAs% = (As3 + As5)/iSumAs, MMA% = MMA/iSumAs, and DMA% = DMA/iSumAs]. Multivariable logistic regression was performed to evaluate the association between inorganic arsenic exposure, methylation capacity indices, and GDM. We did not observe evidence of a positive association between iSumAs and GDM. However, women with GDM had an increased odds of inefficient methylation capacity when comparing the highest and lowest tertiles of iAs% (adjusted odds ratio (aOR) = 1.48, 95% CI 0.58-3.77) and MMA% (aOR = 1.95 (95% CI 0.81-4.70) and a reduced odds of efficient methylation capacity as indicated by DMA% (aOR = 0.62 (95% CI 0.25-1.52), though the confidence intervals included the null value. While the observed associations with arsenic methylation indices were imprecise and warrant cautious interpretation, the direction and magnitude of the relative measures reflected a pattern of lower detoxification of inorganic arsenic exposures among women with GDM.

A Bayesian Approach for Determining the Relationship Between Various Elongate Mineral Particles (EMPs) Definitions.

A variety of dimensions (lengths and widths) of elongate mineral particles (EMPs) have been proposed as being related to health effects. In this paper, we develop a mathematical approach for deriving numerical conversion factors (CFs) between these EMP exposure metrics and applied it to the Minnesota Taconite Health Worker study which contains 196 different job exposure groups (28 similar exposure groups times 7 taconite mines). This approach comprises four steps: for each group (i) obtain EMP dimension information using ISO-TEM 10312/13794 analysis; (ii) use bivariate lognormal distribution to characterize overall EMP size distribution; (iii) use a Bayesian approach to facilitate the formation of the bivariate lognormal distribution; (iv) derive conversion factors between any pair of EMP definitions. The final CFs allow the creation of job exposure matrices (JEMs) for alternative EMP metrics using existing EMP exposures already characterized according to the National Institute of Occupational Safety and Health (NIOSH)-defined EMP exposure metric (length >5 µm with an aspect ratio ≥3.0). The relationships between the NIOSH EMP and other EMP definitions provide the basis of classification of workers into JEMs based on alternate definitions of EMP for epidemiological studies of mesothelioma, lung cancer, and non-malignant respiratory disease.

Inhalable and Respirable Particulate and Endotoxin Exposures in Kentucky Equine Farms.

Adverse respiratory health effects in the agricultural industry have been linked to particulate endotoxin exposure. However, whether the endotoxin concentration is significantly correlated to the size of the particle remains an open question. To date, limited research has been conducted to assess particulate endotoxin exposures in the agricultural industry in general or the equine industry in particular. A task-based exposure assessment was conducted to characterize the endotoxin levels of inhalable and respirable particles on four Kentucky farms during the summer season. We conducted personal sampling of respirable and inhalable particles (n = 75) across all four farms and particulate endotoxin (n = 58) on two of them. Simultaneously, we collected real-time area samples across all four farms by task - horse care, filing hooves, cleaning stalls, cleaning barns, cleaning dry lots, and cleaning trucks. The endotoxin concentration of inhalable particles (geometric mean: 50.2-1,024 EU/m3) was ~50 times higher than that of respirable particles (geometric mean: 1.72-19.0 EU/m3). Horse care generated the lowest endotoxin concentrations for both particle sizes, while cleaning tasks tended to produce higher concentrations. There was no significant correlation between the endotoxin and particle concentrations for each size fraction based on tasks by farm (R2 = 0.069 for inhalable; 0.214 for respirable). The equine workers in this study were exposed to higher endotoxin concentrations than workers in other industries, such as the swine industry. Providing exposure control guidelines and recommendations to the equine industry is necessary to reduce long-term endotoxin exposure and to prevent adverse respiratory symptoms.

Examining Behaviors Related to Retirement, Cleaning, and Storage of Turnout Gear Among Rural Firefighters.

Background: Although the increased occupational exposures among career firefighters are well documented, there are gaps in research related to exposures among volunteer firefighters. This study was completed in a state where the majority of firefighters are volunteers. We aimed to examine if differences existed in career versus volunteer firefighters' behaviors related to the retirement, cleaning, and storage of turnout gear which may increase occupational exposures. Methods: A cross-sectional survey was administered to a convenience sample of 300 firefighters during a training event for both volunteer and career firefighters from one fire district in Kentucky. We measured factors that may affect behaviors related to retirement, cleaning, and storage of turnout gear, such as age of turnout gear at retirement, frequency of cleaning, and location of storage. Results: Two hundred and seventy-five firefighters out of 300 invited participants completed the survey, for a response rate of 92%. The majority of the participants were compliant with National Fire Protection Association Standards with most reporting cleaning their gear as needed, storing gear at the fire station, and retiring gear within 10 years of the manufactured date. Most of the participants (88%) were concerned about job-related exposures and felt susceptible to diseases like cancer and respiratory illness. The structural issues of cost and accessibility were identified as the primary barriers to the proper retirement and cleaning of turnout gear, especially among volunteer firefighters. Conclusions/Application to Practice: Most participants retired, cleaned, and stored turnout as recommended. The majority of participants were concerned with job-related exposures. The structural issues of cost and accessibility were identified as the primary barriers to the proper retirement and cleaning of turnout gear, especially among volunteer firefighters. By identifying differences, tailored trainings could be aimed at volunteer firefighters to help reduce their exposures.

Reconstructing historical exposures to elongate mineral particles (EMPs) in the taconite mining industry for 1955-2010.

As part of ongoing epidemiological studies for assessing the association between exposure to dust from taconite operations and the development of respiratory diseases, the goal of this study was to reconstruct the exposures of workers to elongate mineral particle (EMP) in the Minnesota taconite mining industry from 1955-2010. Historical NIOSH-7400 and equivalent EMP personal exposure data were extracted from two sources: (1) the Mine Safety and Health Administration (MSHA) online database recorded for all inspection results since 1978 with 655 EMP monitoring records from 1978-2010 for 13 MSHA Mine IDs associated with this study; and (2) the mining companies' internal monitoring reports contained 96 personal EMP exposure records. NIOSH-7400 EMP personal exposures were measured for workers in different jobs in all active mines in 2010 by obtaining 1,285 personal samples. After data treatment, all data were grouped into seven mines and eight departments. Within each mine-department, the yearly EMP mean concentration in f/cc for each year of operation was predicted using two approaches. The performance of two approaches varied by situation. The assumptions underlying each approach described in this article have limitations. A linear regression based on limited historical measurements and those made in 2010-2011 (Approach 1) does not yield reasonable and plausible values of the slope. Approach 2 assumes that the EMP and the respirable dust in the same department share the same historical time trend. This approach allowed us to avail of the more reasonable slope estimates from the historical respirable dust data set and yielded more plausible historical exposure estimates for most locations. This work with two different job exposure matrix (JEMs) provides a unique research opportunity to study the potential impact of exposure assessment to epidemiological results. Both JEMs are being used to assess associations between EMP and respiratory disease in epidemiological studies.

The Korean undiagnosed diseases program: lessons from a one-year pilot project.

BACKGROUND: The Korean Undiagnosed Diseases Program (KUDP) was launched in January 2017 as a one-year pilot project to address the increasing global interest in patients with undiagnosed rare diseases. The purpose of this paper is to summarize the project results and emphasize the unmet research needs among patients with undiagnosed rare diseases in Korea. RESULTS: Patient enrollment, assessment, and diagnostic processes were determined by the KUDP clinical expert consortium. Patients followed a diagnostic workflow after being categorized into one of four groups: I) insufficient clinical information or lack of standard diagnostic processes; II) undiagnosed due to low disease awareness; III) clinically diagnosed but unconfirmed genetically due to genetic heterogeneities; or IV) unknown disease due to complex, atypical clinical presentations. After excluding two patients from group I, 97 patients were enrolled, including 10 in group II, 67 in group III, and 20 in group IV. Most of them (92 of 97, 94.8%) were pediatric patients (< 18 years old) and 59 (60.8%) were male. The primary symptoms for 80 patients (82.5%) were neurologic. During the one-year pilot study, 72 patients completed a diagnostic assessment including clinical and molecular genetic analyses; some patients also underwent pathological or biochemical analysis. Twenty-eight of these patients (28/72, 38.9%) achieved molecular genetic diagnosis. Thirteen patients were diagnosed based on traditional tests, including biochemical assay, single or targeted genetic analysis, and chromosomal microarray. We performed whole exome sequencing on 52 patients, among whom 15 (28.8%, 15/52) reached a final diagnosis. One new disorder was identified via international collaboration. CONCLUSIONS: Using an efficient clinical diagnostic workflow, this KUDP pilot study resulted in a fair diagnostic success rate, improving the potential for additional diagnoses and new scientific discovery of complex and rare diseases. KUDP also satisfied unmet needs for rare diseases with multisystem involvement, highlighting the value of emerging genomic technologies for further research into rare and still-undiagnosed conditions.