In order to ensure the feasibility of complex liquid spectroscopy analysis, to analyze the accuracy gain of modeling by multi-wavelength, and to determine the appropriate distribution of concentration to obtain the high quality and universal quantitative analysis model, the precision of the detection of composition concentration by spectral analysis is illustrated through a error analysis which takes into account the following three contributions: spectral instrument noise, multi-wavelength modeling and the distribution of composition concentration. By concentration resolution analysis, the concentration resolution can be achieved when the spectrometer noise is available, but also the theoretical basis is provided to select a suitable spectrometer to meet the resolution requirement of quantitative analysis. Over-sampling technique indicates that the precision improvement by modeling with multi-wavelength can obtain higher concentration detection sensitivity. The sparse-dense-ratio and Euclidean distance of both measured and non-measured components provide the theoretic guidance for choosing the suitable concentration distribution which improves the model's quality and reduces the prediction error of the sample set.
Download full-text PDF |
Source |
---|
Bioanalysis
January 2025
Bioanalysis Discovery & Development Sciences, Johnson & Johnson, Spring House, PA, USA.
Background: Most oligonucleotide bioanalytical assays currently only quantify the pharmacologically-active antisense strand, though there have been recent efforts to simultaneously quantify the sense strand using hybridization ELISA or solid phase extraction LC-MS. Hybrid LC-MS, which offers both high sensitivity and specificity unlike the currently used platforms, has not been applied to quantify both siRNA strands simultaneously.
Materials & Methods: A hybrid LC-MS assay utilizing LNA capture probes was developed and applied to quantify both strands of a 21-mer lipid-conjugated siRNA (SIR-3) using tandem mass spectrometry (MS/MS).
Environ Sci Technol
January 2025
Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Large-scale water diversion projects are essential for meeting the needs of water-stressed regions, necessitating an evaluation of their impact on water quality and aquatic ecosystems. This study provides the first snapshots of organic micropollutants (OMPs) along the 1466 km Eastern Route of China's South-to-North Water Diversion Project. Using nontarget analysis with ultrahigh-performance liquid chromatography and high-resolution mass spectrometry, we identified and quantified 357 OMPs from water samples collected during the water diversion period (WDP) and the nonwater diversion period (NWDP).
View Article and Find Full Text PDFNeural Regen Res
January 2025
Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
Chemical exchange saturation transfer magnetic resonance imaging is an advanced imaging technique that enables the detection of compounds at low concentrations with high sensitivity and spatial resolution and has been extensively studied for diagnosing malignancy and stroke. In recent years, the emerging exploration of chemical exchange saturation transfer magnetic resonance imaging for detecting pathological changes in neurodegenerative diseases has opened up new possibilities for early detection and repetitive scans without ionizing radiation. This review serves as an overview of chemical exchange saturation transfer magnetic resonance imaging with detailed information on contrast mechanisms and processing methods and summarizes recent developments in both clinical and preclinical studies of chemical exchange saturation transfer magnetic resonance imaging for Alzheimer's disease, Parkinson's disease, multiple sclerosis, and Huntington's disease.
View Article and Find Full Text PDFNat Commun
January 2025
School of Safety Science, Tsinghua University, Beijing, China.
Ultrafine particles (UFPs) under 100 nm pose significant health risks inadequately addressed by traditional mass-based metrics. The WHO emphasizes particle number concentration (PNC) for assessing UFP exposure, but large-scale evaluations remain scarce. In this study, we developed a stacking-based machine learning framework integrating data-driven and physical-chemical models for a national-scale UFP exposure assessment at 1 km spatial and 1-hour temporal resolutions, leveraging long-term standardized PNC measurements in Switzerland.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
The widespread presence of antibiotics in aquatic ecosystems is a global challenge, yet the occurrence and risks associated with their transformation products (TPs) remain poorly understood. This study investigated the occurrence and potential risks of antibiotics and their TPs in water along the Chaobai River in Beijing. We used high-resolution mass spectrometry and an integrated target, suspect, and nontarget screening approach to identify 21 parent antibiotics and 78 TPs among 90 water samples, with the majority from macrolides and sulfonamides.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!