Detecting Chemical Vapor Diffusion through Firefighter Turnout Gear.

Firefighters are exposed to burning materials that may release toxic partial combustion and pyrolysis products into the environment, including compounds listed as priority pollutants by the United States Environmental Protection Agency (EPA). A novel passive sampling dosimeter device containing firefighter turnout gear as a diffusion membrane and an activated charcoal strip (ACS) for volatile analyte collection was designed and used to monitor potential exposures of firefighters to volatile organic compounds. Solvent extracts from the ACS and turnout gear diffusion layer were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) to determine the diffusion of compounds from burned substrates through firefighter turnout gear and compound adsorption to the turnout gear. The compounds in these samples were identified using target factor analysis (TFA). An activated carbon layer (ACL) was added to the dosimeter between the turnout gear and the ACS. The presence of combustion and pyrolysis compounds identified on the ACS in the dosimeter was reduced.

Special Situations in the Management of Diverticular Disease.

Diverticular disease affects a large percentage of the US population, affecting over 30% among those older than 45 years old. It is responsible for ∼300,000 hospitalizations per year in the United States and can lead to serious complications such as hemorrhage, obstruction, abscess, fistulae, or bowel perforation. 2 It is an extremely common reason for emergency room and outpatient visits and evaluations by general and colorectal surgeons. In the US, patients usually present with sigmoid diverticulitis in the setting of a normal immune system so surgeons will follow well-established practice guidelines for treatment. However, there may be special circumstances in which the management of diverticulitis is not as straightforward. In this article, we will address patients who present with multifocal disease, giant colonic diverticulum, right-sided diverticulitis, and diverticulitis in the setting of immunosuppression and hopefully provide guidance for treatment in these special circumstances.

A Comprehensive Study of the Alteration of Ignitable Liquids by Weathering and Microbial Degradation.

The differing effects of weathering and microbial degradation are described here in a comprehensive study that involved 50 different ignitable liquids from the Ignitable Liquids Database and Reference Collection. Examples of ignitable liquid residues from each of the main classes established by the American Society of Testing and Materials are presented. Weathering was accomplished via evaporation, whereas microbial degradation was carried out on soil at room temperature for periods of up to 21 days. Major trends included the rapid degradation of long n-alkanes and monosubstituted alkyl benzenes (e.g., toluene, ethylbenzene, and propylbenzene). Surprisingly, some longer branched alkanes (e.g., trimethyloctanes) were also susceptible to microbial attack. Although all ignitable liquids examined suffered at least to some extent from microbial degradation, gasoline, petroleum distillates, and oxygenates were the most susceptible. Isoparaffinic and naphthenic-paraffinic products were the most resistant to microbial degradation.

Assessing evidentiary value in fire debris analysis by chemometric and likelihood ratio approaches.

Results are presented from support vector machine (SVM), linear and quadratic discriminant analysis (LDA and QDA) and k-nearest neighbors (kNN) methods of binary classification of fire debris samples as positive or negative for ignitable liquid residue. Training samples were prepared by computationally mixing data from ignitable liquid and substrate pyrolysis databases. Validation was performed on an unseen set of computationally mixed (in silico) data and on fire debris from large-scale research burns. The probabilities of class membership were calculated using an uninformative (equal) prior and a likelihood ratio was calculated from the resulting class membership probabilities. The SVM method demonstrated a high discrimination, low error rate and good calibration for the in silico validation data; however, the performance decreased significantly for the fire debris validation data, as indicated by a significant increase in the error rate and decrease in the calibration. The QDA and kNN methods showed similar performance trends. The LDA method gave poorer discrimination, higher error rates and slightly poorer calibration for the in silico validation data; however the performance did not deteriorate for the fire debris validation data.

Assessing the evidentiary value of smokeless powder comparisons.

Gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) and physical characteristics data for 726 smokeless reloading powders were analyzed by pairwise comparisons of samples comprising the same product and different products. Pairwise comparisons were restricted to samples having matching kernel shape, color, presence or absence of a perforation and measurements. Discrete results were analyzed for same and different products having matching chemical composition determined from a list of 13 organic components. A continuous score-based likelihood ratio was determined for same and different product comparisons using the Fisher transform of the Pearson correlation between the total ion spectra of the compared samples. Probability distributions for same product and different product comparisons appeared bimodal and were modeled with kernel density distributions. In the discrete and continuous data comparisons, the likelihood ratios for probabilities conditioned on same shape, color, presence/absence of perforation and size were found to provide relatively limited support for either the proposition of same product or different product. Further restricting the pairwise comparisons to samples belonging to the same cluster, as determined by agglomerative hierarchical cluster analysis, provided probability distributions for same product and different product comparisons that were more normal, but did not improve the resulting likelihood ratios. These results inform the forensic analyst regarding the evidentiary value of database search results and direct comparisons of recovered and control samples of smokeless powders.

Chemical Differentiation of Osseous and Nonosseous Materials Using Scanning Electron Microscopy-Energy-Dispersive X-Ray Spectrometry and Multivariate Statistical Analysis.

Identification of osseous materials is generally established on gross anatomical features. However, highly fragmented or taphonomically altered materials may be problematic and may require chemical analysis. This research was designed to assess the use of scanning electron microscopy-energy-dispersive X-ray spectrometry (SEM/EDX), elemental analysis, and multivariate statistical analysis (principal component analysis) for discrimination of osseous and nonosseous materials of similar chemical composition. Sixty samples consisting of osseous (human and nonhuman bone and dental) and non-osseous samples were assessed. After outliers were removed a high overall correct classification of 97.97% was achieved, with 99.86% correct classification for osseous materials. In addition, a blind study was conducted using 20 samples to assess the applicability for using this method to classify unknown materials. All of the blind study samples were correctly classified resulting in 100% correct classification, further demonstrating the efficiency of SEM/EDX and statistical analysis for differentiation of osseous and nonosseous materials.

Class-conditional feature modeling for ignitable liquid classification with substantial substrate contribution in fire debris analysis.

Forensic chemical analysis of fire debris addresses the question of whether ignitable liquid residue is present in a sample and, if so, what type. Evidence evaluation regarding this question is complicated by interference from pyrolysis products of the substrate materials present in a fire. A method is developed to derive a set of class-conditional features for the evaluation of such complex samples. The use of a forensic reference collection allows characterization of the variation in complex mixtures of substrate materials and ignitable liquids even when the dominant feature is not specific to an ignitable liquid. Making use of a novel method for data imputation under complex mixing conditions, a distribution is modeled for the variation between pairs of samples containing similar ignitable liquid residues. Examining the covariance of variables within the different classes allows different weights to be placed on features more important in discerning the presence of a particular ignitable liquid residue. Performance of the method is evaluated using a database of total ion spectrum (TIS) measurements of ignitable liquid and fire debris samples. These measurements include 119 nominal masses measured by GC-MS and averaged across a chromatographic profile. Ignitable liquids are labeled using the American Society for Testing and Materials (ASTM) E1618 standard class definitions. Statistical analysis is performed in the class-conditional feature space wherein new forensic traces are represented based on their likeness to known samples contained in a forensic reference collection. The demonstrated method uses forensic reference data as the basis of probabilistic statements concerning the likelihood of the obtained analytical results given the presence of ignitable liquid residue of each of the ASTM classes (including a substrate only class). When prior probabilities of these classes can be assumed, these likelihoods can be connected to class probabilities. In order to compare the performance of this method to previous work, a uniform prior was assumed, resulting in an 81% accuracy for an independent test of 129 real burn samples.

Chemical Differentiation of Osseous, Dental, and Non-skeletal Materials in Forensic Anthropology using Elemental Analysis.

Forensic anthropologists are generally able to identify skeletal materials (bone and tooth) using gross anatomical features; however, highly fragmented or taphonomically altered materials may be problematic to identify. Several chemical analysis techniques have been shown to be reliable laboratory methods that can be used to determine if questionable fragments are osseous, dental, or non-skeletal in nature. The purpose of this review is to provide a detailed background of chemical analysis techniques focusing on elemental compositions that have been assessed for use in differentiating osseous, dental, and non-skeletal materials. More recently, chemical analysis studies have also focused on using the elemental composition of osseous/dental materials to evaluate species and provide individual discrimination, but have generally been successful only in small, closed groups, limiting their use forensically. Despite significant advances incorporating a variety of instruments, including handheld devices, further research is necessary to address issues in standardization, error rates, and sample size/diversity.

Preliminary validation of handheld X-ray fluorescence spectrometry: distinguishing osseous and dental tissue from nonbone material of similar chemical composition.

One of the tasks of a forensic anthropologist is to sort human bone fragments from other materials, which can be difficult when dealing with highly fragmented and taphonomically modified material. The purpose of this research is to develop a method using handheld X-ray fluorescence (HHXRF) spectrometry to distinguish human and nonhuman bone/teeth from nonbone materials of similar chemical composition using multivariate statistical analyses. The sample materials were derived primarily from previous studies: human bone and teeth, nonhuman bone, nonbiological materials, nonbone biological materials, and taphonomically modified materials. The testing included two phases, testing both the reliability of the instrument and the accuracy of the technique. The results indicate that osseous and dental tissue can be distinguished from nonbone material of similar chemical composition with a high degree of accuracy (94%). While it was not possible to discriminate rock apatite and synthetic hydroxyapatite from bone/teeth, this technique successfully discriminated ivory and octocoral.

Aortic morphologic findings after thoracic endovascular aortic repair for type B aortic dissection.

IMPORTANCE: Thoracic endovascular aortic repair (TEVAR) is used in the treatment of type B aortic dissections. Information related to aortic morphologic findings and the condition of the abdominal aorta after TEVAR is limited. OBJECTIVE: To analyze aortic morphologic findings after TEVAR for type B aortic dissections. DESIGN, SETTING, AND PARTICIPANTS: After a retrospective database review, the data for 30 patients who underwent TEVAR from January 1, 2007, through December 31, 2013, for type B aortic dissection were analyzed. Imaging software was used to calculate aortic diameters and volumes of the aorta on computed tomography (CT) or magnetic resonance imaging (MRI). Mean follow-up was 14.4 months. INTERVENTIONS: We performed TEVAR to cover proximal thoracic aorta tears in patients who underwent acute or chronic type B aortic dissections. MAIN OUTCOMES AND MEASURES: Aortic morphologic findings of pre-TEVAR CT or MRI were compared with the most recent findings of post-TEVAR CT or MRI. Frequency of thoracic false lumen thrombosis (FLT) and false lumen patency (FLP) was determined and the effect on post-TEVAR aortic morphologic findings analyzed. RESULTS: Mean (SD) TEVAR increased true lumen diameter (19.50 [6.92] mm to 31.19 [5.36] mm, P < .001) and volume (77.92 [41.70] mL to 166.95 [69.69] mL, P < .001) and decreased false lumen diameter (29.77 [12.55] mm to 21.92 [12.05] mm, P = .001) on post-TEVAR CT or MRI when compared with pre-TEVAR scans. Seventy percent of patients experienced thoracic FLT; 30% had FLP. True lumen volume expansion and false lumen volume regression occurred in patients with FLT (82.07 [46.95] mm to 180.55 [77.99] mm, P < .001 and 161.84 [106.36] mm to 115.76 [140.77] mm, P = .002, respectively) and FLP (68.23 [21.43] mm to 128.22 [21.46] mm, P < .001 and 238.64 [174.00] mm to 198.93 [120.46] mm, P = .04, respectively). Patients with FLT had increased true lumen diameter (15.67 [6.43] mm to 26.13 [7.62] mm, P < .001) and volume (54.86 [30.52] mL to 88.08 [41.07] mL, P = .001) in the abdominal aorta after TEVAR, with no change in total abdominal aortic volume (161.94 [70.12] mL vs 160.36 [82.11] mL, P = .90). Total abdominal aortic volume significantly increased in patients with thoracic FLP (187.24 [89.88] mL to 221.41 [82.64] mL, P = .02). CONCLUSIONS AND RELEVANCE: Favorable aortic remodeling of the thoracic aorta occurs after TEVAR for type B aortic dissections in patients with thoracic FLT and FLP. However, failure to achieve thrombosis of the thoracic false lumen negatively influences aortic morphologic findings of the contiguous abdominal aorta.

Hierarchical cluster analysis of ignitable liquids based on the total ion spectrum.

Gas chromatography-mass spectrometry (GC-MS) data of ignitable liquids in the Ignitable Liquids Reference Collection (ILRC) database were processed to obtain 445 total ion spectra (TIS), that is, average mass spectra across the chromatographic profile. Hierarchical cluster analysis, an unsupervised learning technique, was applied to find features useful for classification of ignitable liquids. A combination of the correlation distance and average linkage was utilized for grouping ignitable liquids with similar chemical composition. This study evaluated whether hierarchical cluster analysis of the TIS would cluster together ignitable liquids of the same ASTM class assignment, as designated in the ILRC database. The ignitable liquids clustered based on their chemical composition, and the ignitable liquids within each cluster were predominantly from one ASTM E1618-11 class. These results reinforce use of the TIS as a tool to aid in forensic fire debris analysis.

Outcomes after abdominal aortic aneurysm repair requiring a suprarenal cross-clamp.

OBJECTIVE: The objective of this study was to analyze the early and late outcomes of patients who require a suprarenal aortic cross-clamp during elective open repair of an abdominal aortic aneurysm (AAA). METHODS: Patients from 1998 to 2012 who required a suprarenal aortic cross-clamp during elective open AAA repair were reviewed. Data abstracted included demographics and comorbidities; preoperative, perioperative, and late renal function; late interventions related to AAA repair; and late mortality. A decrease in renal function was defined as a >30% decline in estimated glomerular filtration rate (eGFR) compared with the preoperative value. Primary outcomes included renal function, intervention-free survival, and overall survival. RESULTS: During the study period, 211 patients underwent open elective or urgent AAA repair; 69 required a suprarenal cross-clamp. The mean age was 71 years, and 80% were men. The mean preoperative creatinine concentration was 1.2 mg/dL, and the mean preoperative eGFR was 66 mL/min/1.73 m2. Location of the aortic cross-clamp was suprarenal (37), supramesenteric (21), and supraceliac (11). Perioperatively, 21 patients (30%) experienced a significant decrease in eGFR; four patients required hemodialysis. Six patients had full recovery of renal function by discharge. Perioperative morbidity and mortality were 35% and 4%, respectively. At a mean follow-up of 3 years, seven patients had an eGFR significantly less than the preoperative value. Late interventions related to the AAA repair were required in eight patients. Indications included wound complication (3), anastomotic aneurysm (2), incisional hernia (1), anastomotic graft stenosis (1), and proximal aortic dilation (1). Overall 5-year intervention-free survival was 62% and overall survival 77%. Intervention-free survival was enhanced by antiplatelet use (P = .04), whereas overall survival was decreased by chronic obstructive pulmonary disease (P = .003) and perioperative pneumonia (P = .001). CONCLUSIONS: More than a quarter of patients requiring a suprarenal cross-clamp during open AAA repair experience renal dysfunction. Late graft-related complications are few, with preoperative and perioperative pulmonary function negatively affecting overall patient survival.

Application of self-organizing feature maps to analyze the relationships between ignitable liquids and selected mass spectral ions.

The unsupervised artificial neural networks method of self-organizing feature maps (SOFMs) is applied to spectral data of ignitable liquids to visualize the grouping of similar ignitable liquids with respect to their American Society for Testing and Materials (ASTM) class designations and to determine the ions associated with each group. The spectral data consists of extracted ion spectra (EIS), defined as the time-averaged mass spectrum across the chromatographic profile for select ions, where the selected ions are a subset of ions from Table 2 of the ASTM standard E1618-11. Utilization of the EIS allows for inter-laboratory comparisons without the concern of retention time shifts. The trained SOFM demonstrates clustering of the ignitable liquid samples according to designated ASTM classes. The EIS of select samples designated as miscellaneous or oxygenated as well as ignitable liquid residues from fire debris samples are projected onto the SOFM. The results indicate the similarities and differences between the variables of the newly projected data compared to those of the data used to train the SOFM.

Progress toward the determination of correct classification rates in fire debris analysis II: utilizing soft independent modeling of class analogy (SIMCA).

A multistep classification scheme was used to detect and classify ignitable liquid residues in fire debris into the classes defined by the ASTM E1618-10 standard method. The total ion spectra (TIS) of the samples were classified by soft independent modeling of class analogy (SIMCA) with cross-validation and tested on fire debris. For detection of ignitable liquid residue, the true-positive rate was 94.2% for cross-validation and 79.1% for fire debris, with false-positive rates of 5.1% and 8.9%, respectively. Evaluation of SIMCA classifications for fire debris relative to a reviewer's examination led to an increase in the true-positive rate to 95.1%; however, the false-positive rate also increased to 15.0%. The correct classification rates for assigning ignitable liquid residues into ASTM E1618-10 classes were generally in the range of 80-90%, with the exception of gasoline samples, which were incorrectly classified as aromatic solvents following evaporative weathering in fire debris.

Basic data related to thrombolytic therapy for acute venous thrombosis.

BACKGROUND: Treatment guidelines for thrombolysis in iliofemoral deep venous thrombosis (DVT) are based on a limited number of observational and prospective studies. The acute venous thrombosis: thrombus removal with adjunctive catheter-directed thrombolysis (ATTRACT) trial will be the first large, multicenter randomized control trial to evaluate the relative advantages of several current treatment strategies. The objective of this study was to summarize the existing data that inform the use of catheter-directed thrombolysis (CDT) or pharmacomechanical thrombectomy in the management of acute iliofemoral DVT. METHODS: A search of the current literature was done using PubMed, Ovid, and Cochrane databases for all available articles published up to December 2013. RESULTS: Of those studies, which included at least 25 patients, 19 case series were identified from 1996 to 2012. Treatment groups included anticoagulation, surgical thrombectomy, pharmacomechanical thrombectomy, and CDT. Cases observed in each ranged from 26 to 101. Three studies were identified which derived data from national multicenter registries. Only 2 randomized control trials were identified from 2002 to 2012. Both support the use of CDT over anticoagulation alone for treatment of iliofemoral DVT. CONCLUSIONS: Present treatment guidelines for acute iliofemoral DVT have been in flux and are derived from a relatively small amount of clinical data. They are summarized here in anticipation of results from the ongoing ATTRACT trial.

Progress toward the determination of correct classification rates in fire debris analysis.

Principal components analysis (PCA), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) were used to develop a multistep classification procedure for determining the presence of ignitable liquid residue in fire debris and assigning any ignitable liquid residue present into the classes defined under the American Society for Testing and Materials (ASTM) E 1618-10 standard method. A multistep classification procedure was tested by cross-validation based on model data sets comprised of the time-averaged mass spectra (also referred to as total ion spectra) of commercial ignitable liquids and pyrolysis products from common building materials and household furnishings (referred to simply as substrates). Fire debris samples from laboratory-scale and field test burns were also used to test the model. The optimal model's true-positive rate was 81.3% for cross-validation samples and 70.9% for fire debris samples. The false-positive rate was 9.9% for cross-validation samples and 8.9% for fire debris samples.

Noninvasive measurement of intestinal inflammation after burn injury.

Intestinal inflammation has been linked with multiorgan failure in patients with burn and other traumatic injuries. We hypothesized that markers of intestinal inflammation are detectible noninvasively. Fecal samples were collected from seven severely burned patients and 15 control patients for the measurement of inflammatory cytokines using a multiplex assay kit. In addition, fecal levels of myeloperoxidase (MPO) and elastase were measured using standard procedures. Compared with a control group, levels of inflammatory cytokines were significantly increased in the burn group. Interleukin (IL)-6 increased to a mean (± SEM) of 2.16 ± 0.61 to 3.81 ± 0.49 pg/mg (P < .05), as did IL-8 (3.32 ± 0.76 to 20.51 ± 6.65 pg/mg; P < .05), IL-12 (6.23±0.98 to 8.11±0.95pg/mg; P=0.01), IL-13 (3.86 ± 0.32 to 11.83 ± 1.47 pg/mg; P < .05), monocyte chemoattractant protein-1 (2.78 ± 2.61 to 6.5 ± 3.97 pg/mg; P < .05), MPO (13.41 ± 1.40 to 24.52 ± 4.31 units/mg protein; P < .05), and elastase (2.46 ± 0.38 to 5.08 ± 0.72 pg/mL; P < .05). Our results suggest that markers of intestinal inflammation are measurable by noninvasive means and are increased after burn injury compared with controls. Of note, increased IL-8 correlated with increased MPO and elastase activity, suggesting a role for neutrophil activation in burn-mediated intestinal inflammation. Thus, these inflammatory cytokine profiles may be valuable biomarkers of intestinal inflammation after burn injury.

Discriminant analysis in the presence of interferences: combined application of target factor analysis and a Bayesian soft-classifier.

A method is described for performing discriminant analysis in the presence of interfering background signal. The method is based on performing target factor analysis on a data set comprised of contributions from analyte(s) and interfering components. A library of data from representative analyte classes is tested for possible contributing factors by performing oblique rotations of the principal factors to obtain the best match, in a least-squares sense, between test and predicted vectors. The degree of match between the test and predicted vectors is measured by the Pearson correlation coefficient, r, and the distribution of r for each class is determined. A Bayesian soft classifier is used to calculate the posterior probability based on the distributions of r for each class, which assist the analyst in assessing the presence of one or more analytes. The method is demonstrated by analyses performed on spectra obtained by laser induced breakdown spectroscopy (LIBS). Single and multiple bullet jacketing transfers to steel and porcelain substrates were analyzed to identify the jacketing materials. Additionally, the metal surrounding bullet holes was analyzed to identify the class of bullet jacketing that passed through a stainless steel plate. Of 36 single sample transfers, the copper jacketed (CJ) and non-jacketed (NJ) class on porcelain had an average posterior probability of the metal deposited on the substrate of 1.0. Metal jacketed (MJ) bullet transfers to steel and porcelain were not detected as successfully. Multiple transfers of CJ/NJ and CJ/MJ on the two substrates resulted in posterior probabilities that reflected the presence of both jacketing materials. The MJ/NJ transfers gave posterior probabilities that reflected the presence of the NJ material, but the MJ component was mistaken for CJ on steel, while non-zero probabilities were obtained for both CJ and MJ on porcelain. Jacketing transfer from a bullet to steel as the projectile passed through the steel also proved difficult to analyze. Over 50% of the samples left insufficient transfer to be identified. Transfer from NJ and CJ jacketing was successfully identified by posterior probabilities greater than 0.8.