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Spatial heterodyne spectroscopy (SHS) is used for quantitative analysis and classification of liquid samples. SHS is a version of a Michelson interferometer with no moving parts and with diffraction gratings in place of mirrors. The instrument converts frequency-resolved information into a spatially resolved one and records it in the form of interferograms. The back-extraction of spectral information is done by the fast Fourier transform. A SHS instrument is constructed with the resolving power 5000 and spectral range 522-593 nm. Two original technical solutions are used as compared to previous SHS instruments: the use of a high-frequency diode-pumped solid-state laser for excitation of Raman spectra and a microscope-based collection system. Raman spectra are excited at 532 nm at the repetition rate 80 kHz. Raman shifts between 330 cm and 1600 cm are measured. A new application of SHS is demonstrated: for the first time, it is used for quantitative Raman analysis to determine concentrations of cyclohexane in isopropanol and glycerol in water. Two calibration strategies are employed: univariate based on the construction of a calibration plot and multivariate based on partial least squares regression. The detection limits for both cyclohexane in isopropanol and glycerol in water are at a 0.5 mass% level. In addition to the Raman-SHS chemical analysis, classification of industrial oils (biodiesel, poly(1-decene), gasoline, heavy oil IFO380, polybutenes, and lubricant) is performed using the Raman-fluorescence spectra of the oils and principal component analysis. The oils are easily discriminated showing distinct non-overlapping patterns in the principal component space.
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http://dx.doi.org/10.1177/0003702819863847 | DOI Listing |
Microb Genom
September 2025
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, PR China.
African swine fever virus (ASFV) is highly transmissible and can cause up to 100% mortality in pigs. The virus has spread across most regions of Asia and Europe, resulting in the deaths of millions of pigs. A deep understanding of the genetic diversity and evolutionary dynamics of ASFV is necessary to effectively manage outbreaks.
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September 2025
International Centre of Excellence for Aquatic Animal Health, The Centre for Environment, Fisheries and Aquaculture Science, Weymouth, DT4 8UB, UK.
High rates of mortality of the common cockle, , have occurred in the Wash Estuary, UK, since 2008. A previous study linked the mortalities to a novel genotype of , with a strong correlation between cockle moribundity and the presence of . Here, we characterize a novel iridovirus, identified by chance during metagenomic sequencing of a gradient purification of cells, with the presence also correlated to cockle moribundity.
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September 2025
National Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Taiwan, ROC.
remains a leading respiratory pathogen for children and the elderly. In Taiwan, a national PCV13 catch-up vaccination programme for children began in March 2013. This study investigates the population structure and antimicrobial profiles of pneumococcal isolates in Taiwan from 2006 to 2022.
View Article and Find Full Text PDFCrit Care Explor
September 2025
Division of Tropical Medicine and Infectious Diseases, Department of Internal Medicine, Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia.
Importance: Sepsis remains a leading cause of death in infectious cases. The heterogeneity of immune responses is a major challenge in the management and prognostication of patients with sepsis. Identifying distinct immune response subphenotypes using parsimonious classifiers may improve outcome prediction, particularly in resource-limited settings.
View Article and Find Full Text PDFClin Transl Gastroenterol
September 2025
Department of Internal Medicine, School of Medicine, University of Medicine and Pharmacy at Ho Cho Minh City, Vietnam.
Background: Severe acute pancreatitis (SAP) is a life-threatening condition requiring early risk stratification. While the Bedside Index for Severity in Acute Pancreatitis (BISAP) is widely used, its reliance on complex parameters limits its applicability in resource-constrained settings. This study introduces a decision tree model based on Classification and Regression Tree (CART) analysis, utilizing Neutrophil-to-Lymphocyte Ratio (NLR) and C-reactive Protein (CRP), as a simpler alternative for early SAP prediction.
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