Wastewater Surveillance of US Coast Guard Installations and Seagoing Military Vessels to Mitigate the Risk of COVID-19 Outbreaks, March 2021-August 2022.

OBJECTIVES: Military training centers and seagoing vessels are often environments at high risk for the spread of COVID-19 and other contagious diseases, because military trainees and personnel arrive after traveling from many parts of the country and live in congregate settings. We examined whether levels of SARS-CoV-2 genetic material in wastewater correlated with SARS-CoV-2 infections among military personnel living in communal barracks and vessels at US Coast Guard training centers in the United States. METHODS: The Coast Guard developed and established 3 laboratories with wastewater testing capability at Coast Guard training centers from March 2021 through August 2022. We analyzed wastewater from barracks housing trainees and from 4 Coast Guard vessels for the presence of SARS-CoV-2 genes N and E and quantified the results relative to levels of a fecal indicator virus, pepper mild mottle virus. We compared quantified data with the timing of medically diagnosed COVID-19 infection among (1) military personnel who had presented with symptoms or had been discovered through contact tracing and had medical tests and (2) military personnel who had been discovered through routine surveillance by positive SARS-CoV-2 antigen or polymerase chain reaction test results. RESULTS: Levels of viral genes in wastewater at Coast Guard locations were best correlated with diagnosed COVID-19 cases when wastewater testing was performed twice weekly with passive samplers deployed for the entire week; such testing detected ≥1 COVID-19 case 69.8% of the time and ≥3 cases 88.3% of the time. Wastewater assessment in vessels did not continue because of logistical constraints. CONCLUSION: Wastewater testing is an effective tool for measuring the presence and patterns of SARS-CoV-2 infections among military populations. Success with wastewater testing for SARS-CoV-2 infections suggests that other diseases may be assessed with similar approaches.

Oxygenated weathering products of Deepwater Horizon oil come from surprising precursors.

Following the release of crude oil from the Macondo well in 2010, a wide range of weathering processes acted on the spilled oil. A recent study revealed that samples from this spill were oxidized into oxygenated hydrocarbons (OxHC) comprising more than 50% of the extracted hydrocarbons. The precursors of these compounds were not identified despite using a wide range of analytical tools, including gas chromatography (GC). To search for these precursors, over 40 samples were analyzed by comprehensive two-dimensional gas chromatography (GC×GC), one of the largest studies of its kind to date. Partial least squares regression was employed to elucidate the GC×GC peaks that could be the precursors of OxHC in our samples. We found that the formation of OxHC correlated with the disappearance of saturated hydrocarbons, including alkylcyclopentanes, alkyl cyclohexanes, alkylated bicyclic saturated compounds, tricyclic terpanpoids, and alkylbenzenes. These results indicate a previously under-reported chemodynamic process in oil spill weathering.

Analysis of petroleum compositional similarity using multiway principal components analysis (MPCA) with comprehensive two-dimensional gas chromatographic data.

The accurate establishment of oil similarity is a longstanding problem in petroleum geochemistry and a necessary component for resolving the architecture of an oil reservoir. Past limitations have included the excessive reliance on a relatively small number of biomarkers to characterize such complex fluids as crude oils. Here we use multiway principal components analysis (MPCA) on large numbers of specific chemical components resolved with comprehensive two-dimensional gas chromatography-flame ionization detection (GC×GC-FID) to determine the molecular relatedness of eight different maltene fractions of crude oils. MPCA works such that every compound eluting within the same first and second dimension retention time is quantitatively compared with what elutes at that same retention times within the other maltene fractions. Each maltene fraction and corresponding MPCA analysis contains upwards of 3500 quantified components. Reservoir analysis included crude oil sample pairs from around the world that were collected sequentially at depth within a single well, collected from multiple depths in the same well, and from different depths and different wells but thought to be intersected by the same permeable strata. Furthermore, three different regions of each GC×GC-FID chromatograms were analysed to evaluate the effectiveness of MPCA to resolve compositional changes related to the source of the oil generating sediments and its exposure to biological and/or physical weathering processes. Compositional and instrumental artefacts introduced during sampling and processing were also quantitatively evaluated. We demonstrate that MPCA can resolve multi-molecular differences between oil samples as well as provide insight into the overall molecular relatedness between various crude oils.

From the archives of the AFIP: breast masses in children and adolescents: radiologic-pathologic correlation.

The spectrum of breast lesions in children and adolescents varies markedly from that for adults, with the former lesions being overwhelmingly benign. A breast mass in a young boy or girl may arise from normal and abnormal breast development. Other causes of masses include infection, trauma, and cyst formation. After onset of puberty, most cases of breast enlargement arise from benign fibroadenoma in girls and gynecomastia in boys. These conditions have specific imaging appearances, although juvenile (often giant) fibroadenoma cannot be distinguished from phyllodes tumor, which can be benign or malignant. In children, both conditions usually appear as well-circumscribed, hypoechoic masses at sonography and show diffuse enhancement except for nonenhancing septations at magnetic resonance imaging. A diagnosis of juvenile papillomatosis (a benign lesion) portends later development of breast cancer, and patients with this condition should be closely monitored. Malignant lesions of the breast in children are rare. The most common malignant lesions are metastases and are usually associated with widespread disease. The most common primary breast malignancy is malignant phyllodes tumor. Primary breast carcinoma is exceedingly rare in the pediatric age group, but its imaging appearance in children is the same as seen in adults and is different from that of almost all benign lesions. In girls, diagnostic interventions may injure the developing breast and cause subsequent disfigurement. Given this risk and the low prevalence of malignant disease in this population, a prudent course should be followed in the diagnosis of breast lesions. Imaging findings are very helpful for selecting patients for further diagnostic procedures. Although malignancy is rare, lesions with suspicious imaging findings or progressive growth should be subjected to cytologic or histologic examination.

Estuarine water classification using EEM spectroscopy and PARAFAC-SIMCA.

The primary method for the prevention of the introduction of nonindigenous aquatic nuisance species in the U.S. is ballast water exchange (BWE). Our recent work focused on the use of the excitation emission matrix (EEM) spectroscopy of the colored dissolved organic matter (CDOM) to "fingerprint" water as a function of its port of origin, and therefore provide a forensic tool for the enforcement of BWE regulations. In that work, we utilized N-way partial least squares with discriminant analysis (NPLS-DA), which models the data with an emphasis on differences among classes (ports of origin). In this work, EEMs of samples from three different U.S. ports were analyzed by parallel factor analysis (PARAFAC) coupled with soft independent modeling of class analogy (SIMCA) to provide an effective classification method with a low false positive rate. This coupling, which is shown for the first time in this work, can be a useful alternative to NPLS-DA in that PARAFAC-SIMCA decomposes the EEM signal into chemical components and utilizes the scores for these components in the classification scheme. This gives the user the option of removing the contributions of interfering or unidentifiable fluorescent components prior to classification.

Estuarial fingerprinting through multidimensional fluorescence and multivariate analysis.

As part of a strategy for preventing the introduction of aquatic nuisance species (ANS) to U.S. estuaries, ballast water exchange (BWE) regulations have been imposed. Enforcing these regulations requires a reliable method for determining the port of origin of water in the ballast tanks of ships entering U.S. waters. This study shows that a three-dimensional fluorescence fingerprinting technique, excitation emission matrix (EEM) spectroscopy, holds great promise as a ballast water analysis tool. In our technique, EEMs are analyzed by multivariate classification and curve resolution methods, such as N-way partial least squares Regression-discriminant analysis (NPLS-DA) and parallel factor analysis (PARAFAC). We demonstrate that classification techniques can be used to discriminate among sampling sites less than 10 miles apart, encompassing Boston Harbor and two tributaries in the Mystic River Watershed. To our knowledge, this work is the first to use multivariate analysis to classify water as to location of origin. Furthermore, it is shown that curve resolution can show seasonal features within the multidimensional fluorescence data sets, which correlate with difficulty in classification.

A laser-induced fluorescence dual-fiber optic array detector applied to the rapid HPLC separation of polycyclic aromatic hydrocarbons.

A multi-channel detection system utilizing fiber optics has been developed for the laser-induced fluorescence (LIF) analysis of chromatographic eluents. It has been applied to the detection of polycyclic aromatic hydrocarbons (PAH) in a chromatographically overlapped standard mixture and to a complex soil sample extract obtained during fieldwork. The instrument utilizes dual-fiber optic arrays, one to deliver multiple excitation wavelengths (258-342 nm) generated by a Raman shifter, and the other to collect fluorescence generated by the sample at each excitation wavelength; the collected fluorescence is dispersed and detected with a spectrograph/CCD combination. The resulting data were arranged into excitation emission matrices (EEM) for visualization and data analysis. Rapid characterization of PAH mixtures was achieved under isocratic chromatographic conditions (1.5 mL min(-1) and 80% acetonitrile in water), with mid microg L(-1) detection limits, in less than 4 minutes. The ability of the instrument to identify co-eluting compounds was demonstrated by identifying and quantifying analytes in the rapid analysis of a 17 component laboratory-prepared PAH mixture and a soil extracted sample. Identification and quantification were accomplished using rank annihilation factor analysis (RAFA) using pure component standards and the EEMs of mixtures measured during the rapid high-performance liquid chromatography (HPLC) method as the unknowns. The percentage errors of the retention times (RTs) determined using RAFA compared to the known RTs measured with a standard absorbance detector were between 0 and 11%. For the standard PAH mixture, all 17 components were identified correctly and for the soil extracted sample, all 8 analytes present were correctly identified with only one false positive. Overall, the system achieved excellent qualitative performance with semi-quantitative results in the concentration predictions of both the standard mixture and the real-world sample. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00216-001-1125-6.