There are many thousands of chemicals in use for a wide range of purposes, and highly efficient analytical methods are required to monitor them for protection of the environment. In order to cope with this difficult task we developed a novel, comprehensive method for 484 substances in water samples. In this method target chemicals were extracted by tandem SPE and then determined by LC-QTOF-MS-SWATH. Targets were unambiguously identified using retention times, accurate masses of a precursor and two product ions, their ion ratios, and accurate MS/MS spectrum. Quantitation was achieved by the internal standard method using a precursor ion. Results of recovery tests at two concentrations (50 and 500 ng L) showed average recoveries of 87.5% and 87.0% (RSD, 9.1% and 9.4%), respectively. Limits of detection of one-half of the targets were below 1.0 ng L. The method was applied to the influent and effluent of a sewage treatment plant, and around 100 chemicals were detected. Results of examination on matrix effects using their extracts spiked with 209 pesticides showed that the ratios of detected amounts between the extracts and the standard solution were 89.8% (influent) and 91.7% (effluent), respectively. In addition, investigation on the stability of calibration curves by injecting the same standards for 1 year showed that their quantitative results did not change; average accuracy was 103.3% (RSD, 10.0%), indicating that the calibration curves can be used for an extended period of time without calibration, and quantitative retrospective analysis can be done after creating calibration curves for new targets.
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http://dx.doi.org/10.1021/acs.analchem.9b01141 | DOI Listing |
Front Public Health
January 2025
Orcasitas Health Care Center, Madrid, Spain.
Introduction: Functional dependence on the performance of basic activities of daily living (ADLs) is associated with increased mortality. In this study, the Barthel index and its activities discriminate long-term mortality risk, and whether changes in this index are necessary to adapt it to detect mortality risk is examined.
Methods: Longitudinal study, carried out at the Orcasitas Health Center, Madrid (Spain), on the functional dependent population (Barthel ≤ 60).
World J Gastroenterol
January 2025
Department of Thoracic Surgery, Northern Jiangsu People's Hospital, Yangzhou 225000, Jiangsu Province, China.
Background: The relationship between patient nutritional, immune, and inflammatory status is linked to tumor progression and prognosis. However, there are limited studies on the prognosis of esophageal squamous cell carcinoma (ESCC) after surgery based on the comprehensive indicators of these factors.
Aim: To develop and validate a novel nomogram based on a nutritional immune-inflammatory status (NIIS) score for predicting postoperative outcomes in ESCC.
Front Immunol
January 2025
Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Aim: This study aims to create and validate a novel systematic immune-inflammation-nutrition (SIIN) score to provide a non-invasive and accurate prognostic tool for head and neck squamous cell carcinoma (HNSCC) patients.
Methods: 259 participants diagnosed with HNSCC from the First Affiliated Hospital of Xi'an Jiaotong University between 2008 and 2017 was included in this retrospective study. Patients were assigned to training (n=181) and validation (n=78) sets.
Front Surg
January 2025
Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background: To accurately identify spread through air spaces (STAS) in clinical stage IA lung adenocarcinoma, our study developed a non-invasive and interpretable biomarker combining clinical and radiomics features using preoperative CT.
Methods: The study included a cohort of 1,325 lung adenocarcinoma patients from three centers, which was divided into four groups: a training cohort ( = 930), a testing cohort ( = 238), an external validation 1 cohort ( = 93), and 2 cohort ( = 64). We collected clinical characteristics and semantic features, and extracted radiomics features.
Front Cardiovasc Med
January 2025
Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.
Background: The nomogram is a powerful and robust tool in disease risk prediction that summarizes complex variables into a visual model that is interpretable with a quantified risk probability. In the current study, a nomogram was developed to predict the occurrence of coronary artery lesions (CALs) among patients with Kawasaki disease (KD). This is especially valuable in the early identification of the risk of CALs, which will lead to proper diagnosis and treatment to reduce their associated complications.
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