Trace Analysis of 61 Emerging Br-, Cl-, and I-DBPs: New Methods to Achieve Part-Per-Trillion Quantification in Drinking Water.

Disinfection byproducts (DBPs) are a ubiquitous source of chemical exposure in drinking water and have been associated with serious health impacts in human epidemiologic studies. While toxicology studies have pinpointed DBPs with the greatest toxic potency, analytical methods have been lacking for quantifying complete classes of most toxic DBPs at sufficiently low quantification limits (ng/L). This new method reports the parts-per-trillion quantification for 61 toxicologically significant DBPs from 7 different chemical classes, including unregulated iodinated haloacetic acids (HAAs) and trihalomethanes (THMs), haloacetaldehydes, haloketones, haloacetonitriles, halonitromethanes, and haloacetamides, in addition to regulated HAAs and THMs. The final optimized method uses salt-assisted liquid-liquid extraction in a single extraction method for a wide range of DBPs, producing the lowest method detection limits to-date for many compounds, including highly toxic iodinated, brominated, and nitrogen-containing DBPs. Extracts were divided for the analysis of the HAAs (including iodinated HAAs) by diazomethane derivatization and analysis using a GC-triple quadrupole mass spectrometer with multiple reaction monitoring, resulting in higher signal-to-noise ratios, greater selectivity, and improved detection of these compounds. The remaining DBPs were analyzed using a GC-single quadrupole mass spectrometer with selected ion monitoring, utilizing a multimode inlet allowed for lower injection temperatures to allow the analysis of thermally labile DBPs. Finally, the use of a specialty-phase GC column (Restek Rtx-200) significantly improved peak shapes, which improved separations and lowered detection limits. Method detection limits for most DBPs were between 15 and 100 ng/L, and relative standard deviations in tap water samples were mostly between 0.2 and 30%. DBP concentrations in real samples ranged from 40 to 17 760 ng/L for this study.

Distinguishing Non-Small Cell Lung Cancer Subtypes in Fine Needle Aspiration Biopsies by Desorption Electrospray Ionization Mass Spectrometry Imaging.

BACKGROUND: Distinguishing adenocarcinoma and squamous cell carcinoma subtypes of non-small cell lung cancers is critical to patient care. Preoperative minimally-invasive biopsy techniques, such as fine needle aspiration (FNA), are increasingly used for lung cancer diagnosis and subtyping. Yet, histologic distinction of lung cancer subtypes in FNA material can be challenging. Here, we evaluated the usefulness of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to diagnose and differentiate lung cancer subtypes in tissues and FNA samples. METHODS: DESI-MSI was used to analyze 22 normal, 26 adenocarcinoma, and 25 squamous cell carcinoma lung tissues. Mass spectra obtained from the tissue sections were used to generate and validate statistical classifiers for lung cancer diagnosis and subtyping. Classifiers were then tested on DESI-MSI data collected from 16 clinical FNA samples prospectively collected from 8 patients undergoing interventional radiology guided FNA. RESULTS: Various metabolites and lipid species were detected in the mass spectra obtained from lung tissues. The classifiers generated from tissue sections yielded 100% accuracy, 100% sensitivity, and 100% specificity for lung cancer diagnosis, and 73.5% accuracy for lung cancer subtyping for the training set of tissues, per-patient. On the validation set of tissues, 100% accuracy for lung cancer diagnosis and 94.1% accuracy for lung cancer subtyping were achieved. When tested on the FNA samples, 100% diagnostic accuracy and 87.5% accuracy on subtyping were achieved per-slide. CONCLUSIONS: DESI-MSI can be useful as an ancillary technique to conventional cytopathology for diagnosis and subtyping of non-small cell lung cancers.

Intraoperative Evaluation of Breast Tissues During Breast Cancer Operations Using the MasSpec Pen.

Importance: Surgery with complete tumor resection remains the main treatment option for patients with breast cancer. Yet, current technologies are limited in providing accurate assessment of breast tissue in vivo, warranting development of new technologies for surgical guidance. Objective: To evaluate the performance of the MasSpec Pen for accurate intraoperative assessment of breast tissues and surgical margins based on metabolic and lipid information. Design, Setting, and Participants: In this diagnostic study conducted between February 23, 2017, and August 19, 2021, the mass spectrometry-based device was used to analyze healthy breast and invasive ductal carcinoma (IDC) banked tissue samples from adult patients undergoing breast surgery for ductal carcinomas or nonmalignant conditions. Fresh-frozen tissue samples and touch imprints were analyzed in a laboratory. Intraoperative in vivo and ex vivo breast tissue analyses were performed by surgical staff in operating rooms (ORs) within 2 different hospitals at the Texas Medical Center. Molecular data were used to build statistical classifiers. Main Outcomes and Measures: Prediction results of tissue analyses from classification models were compared with gross assessment, frozen section analysis, and/or final postoperative pathology to assess accuracy. Results: All data acquired from the 143 banked tissue samples, including 79 healthy breast and 64 IDC tissues, were included in the statistical analysis. Data presented rich molecular profiles of healthy and IDC banked tissue samples, with significant changes in relative abundances observed for several metabolic species. Statistical classifiers yielded accuracies of 95.6%, 95.5%, and 90.6% for training, validation, and independent test sets, respectively. A total of 25 participants enrolled in the clinical, intraoperative study; all were female, and the median age was 58 years (IQR, 44-66 years). Intraoperative testing of the technology was successfully performed by surgical staff during 25 breast operations. Of 273 intraoperative analyses performed during 25 surgical cases, 147 analyses from 22 cases were subjected to statistical classification. Testing of the classifiers on 147 intraoperative mass spectra yielded 95.9% agreement with postoperative pathology results. Conclusions and Relevance: The findings of this diagnostic study suggest that the mass spectrometry-based system could be clinically valuable to surgeons and patients by enabling fast molecular-based intraoperative assessment of in vivo and ex vivo breast tissue samples and surgical margins.