155,698 research outputs found

    Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data

    Get PDF
    A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015‚Äď2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared

    Closing the Organofluorine Mass Balance in Marine Mammals Using Suspect Screening and Machine Learning-Based Quantification

    No full text
    High-resolution mass spectrometry (HRMS)-based suspect and nontarget screening has identified a growing number of novel per- and polyfluoroalkyl substances (PFASs) in the environment. However, without analytical standards, the fraction of overall PFAS exposure accounted for by these suspects remains ambiguous. Fortunately, recent developments in ionization efficiency (IE) prediction using machine learning offer the possibility to quantify suspects lacking analytical standards. In the present work, a gradient boosted tree-based model for predicting log IE in negative mode was trained and then validated using 33 PFAS standards. The root-mean-square errors were 0.79 (for the entire test set) and 0.29 (for the 7 PFASs in the test set) log IE units. Thereafter, the model was applied to samples of liver from pilot whales (n = 5; East Greenland) and white beaked dolphins (n = 5, West Greenland; n = 3, Sweden) which contained a significant fraction (up to 70%) of unidentified organofluorine and 35 unquantified suspect PFASs (confidence level 2‚Äď4). IE-based quantification reduced the fraction of unidentified extractable organofluorine to 0‚Äď27%, demonstrating the utility of the method for closing the fluorine mass balance in the absence of analytical standards

    Antibody-Conjugated Polymersomes with Encapsulated Indocyanine Green J‚ÄĎAggregates and High Near-Infrared Absorption for Molecular Photoacoustic Cancer Imaging

    No full text
    Imaging plays a critical role in all stages of cancer care from early detection to diagnosis, prognosis, and therapy monitoring. Recently, photoacoustic imaging (PAI) has started to emerge into the clinical realm due to its high sensitivity and ability to penetrate tissues up to several centimeters deep. Herein, we encapsulated indocyanine green J (ICGJ) aggregate, one of the only FDA-approved organic exogenous contrast agents that absorbs in the near-infrared range, at high loadings up to ‚ąľ40% w/w within biodegradable polymersomes (ICGJ-Ps) composed of poly(lactide-co-glycolide-b-polyethylene glycol) (PLGA-b-PEG). The small Ps hydrodynamic diameter of 80 nm is advantageous for in vivo applications, while directional conjugation with epidermal growth factor receptor (EGFR) targeting cetuximab antibodies renders molecular specificity. Even when exposed to serum, the ‚ąľ11 nm-thick membrane of the Ps prevents dissociation of the encapsulated ICGJ for at least 48 h with a high ratio of ICGJ to monomeric ICG absorbances (i.e., I895/I780 ratio) of approximately 5.0 that enables generation of a strong NIR photoacoustic (PA) signal. The PA signal of polymersome-labeled breast cancer cells is proportional to the level of cellular EGFR expression, indicating the feasibility of molecular PAI with antibody-conjugated ICGJ-Ps. Furthermore, the labeled cells were successfully detected with PAI in highly turbid tissue-mimicking phantoms up to a depth of 5 mm with the PA signal proportional to the amount of cells. These data show the potential of molecular PAI with ICGJ-Ps for clinical applications such as tumor margin detection, evaluation of lymph nodes for the presence of micrometastasis, and laparoscopic imaging procedures