Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis

The application of laser‑induced fluorescence in oil spill detection

Over the past two decades, oil spills have been one of the most serious ecological disasters, causing massive damage to the aquatic and terrestrial ecosystems as well as the socio-economy. In view of this situation, several methods have been developed and utilized to analyze oil samples. Among these methods, laser-induced fluorescence (LIF) technology has been widely used in oil spill detection due to its classification method, which is based on the fluorescence characteristics of chemical material in oil. This review systematically summarized the LIF technology from the perspective of excitation wavelength selection and the application of traditional and novel machine learning algorithms to fluorescence spectrum processing, both of which are critical for qualitative and quantitative analysis of oil spills. It can be seen that an appropriate excitation wavelength is indispensable for spectral discrimination due to different kinds of polycyclic aromatic hydrocarbons' (PAHs) compounds in petroleum products. By summarizing some articles related to LIF technology, we discuss the influence of the excitation wavelength on the accuracy of the oil spill detection model and proposed several suggestions on the selection of excitation wavelength. In addition, we introduced some traditional and novel machine learning (ML) algorithms and discussed the strengths and weaknesses of these algorithms and their applicable scenarios. With an appropriate excitation wavelength and data processing algorithm, it is believed that laser-induced fluorescence technology will become an efficient technique for real-time detection and analysis of oil spills.

Measurement of trace bisphenol A in drinking water with combination of immunochromatographic detection technology and SERS method

Sensitive and selective detection of target analyte is very important in many fields such as commodity inspection and quality monitoring. In this work, based on the principle of competitive immunoassay, surface-enhanced Raman spectroscopy (SERS) was used to establish a rapid and highly sensitive method for the detection of trace amounts of bisphenol A in water. Here, Raman molecule 5,5-dithiobis-2-nitrobenzoic acid and anti-BPA antibody were conjugated with Au (core)@Ag (shell) nanoparticle to serve as SERS nanoprobe. After the SERS nanoprobe is combined with the substance to be tested, it uses the siphon effect to pass through the test line and the charging line on the test strip. And the Raman test was performed on the T line with a Raman spectrometer. The detection limitation was 0.1 pg/mL. Compared with the reported gas chromatography, liquid chromatography, fluorescence analysis, and other detection methods, SERS ICA does not demand complicated sample preparation procedures, and has the advantages of simple detection methods, quick results, High sensitivity, good specificity, and low technical demands for laboratory environment and testers. In addition, Raman spectrometers have gradually developed to be portable, making it easier to meet the needs of on-site rapid and highly sensitive detection, and will show broad prospects for applications in the fields of biomedical diagnosis and food safety monitoring.

Recognition of polycyclic aromatic hydrocarbons using fluorescence spectrometry combined with bird swarm algorithm optimization support vector machine

Polycyclic aromatic hydrocarbons (PAHs), known as a widespread toxic pollutants in aquatic environments, have caused enormous harm to human society and even the earth's ecology. Therefore, it is necessary to identify PAHs pollutants accurately and efficiently. In this work, the binary mixed solvents Acenaphthylene and Fluorene (ANP-FLU), Acenaphthylene and Naphthalene (ANP-NAP), FLU-NAP representing typical PAHs mixtures in aqueous solution were identified by using three-dimensional fluorescence spectroscopy and machine learning intelligent algorithm. The fluorescence spectroscopy was used to analyze the similarity and difference of ANP, FLU, NAP and the mixtures of two above compounds. What's more, bird swarm algorithm optimization support vector machine (BSA-SVM), introduced as a new method, was proposed to identify PAHs. In order to verify the accuracy of the BSA-SVM algorithm, the BSA-SVM, particle swarm optimization support vector machine (PSO-SVM), genetic optimization support vector machine (GA-SVM) and SVM algorithms were test by processing the same spectral data. The test set classification accuracy of BSA-SVM can reach 100%, which was higher than that of PSO-SVM, GA-SVM and SVM. Moreover, with the exception of the original SVM model, the training speed of BSA-SVM was the fastest among the three optimization algorithms. The satisfying results demonstrated that the BSA-SVM was more suitable for qualitative analysis of PAHs.

Effects of polycyclic aromatic hydrocarbons on the UV-induced fluorescence spectra of crude oil films on the sea surface

As the main fluorescent substances in oils, polycyclic aromatic hydrocarbons (PAHs) are the basis of ultraviolet (UV)-induced fluorescence spectroscopy methods to detect oil films on the sea surface. The relative contents of PAHs in six crude oil samples and their effects on ultraviolet fluorescence spectra were studied. The PAHs were divided into four categories according to their fluorescence characteristics. Naphthalene series dominated the fluorescence spectra, which led to a main peak at 320-350 nm, but this showed no relationship with PAH content. The six oil samples could not be distinguished by differences in the fluorescence spectra in this range, but could be distinguished by the fluorescence spectra in the 350-380 nm band. The relative contents of dibenzothiophene and phenanthrene series showed significant positive correlations (R² = 0.96) with fluorescence intensity. Fluorescence spectroscopy combined with GC-MS can be used to distinguish and identify crude oils.

Detection of Organochlorine Pesticides in Contaminated Marine Environments via Cyclodextrin-Promoted Fluorescence Modulation

The development of practical and robust detection methods for pesticides is an important research objective owing to the known toxicity, carcinogenicity, and environmental persistence of these compounds. Pesticides have been found in bodies of water that are located near areas where pesticides are commonly used and easily spread to beaches, lakes, and rivers; affect the species living in those waterways; and harm humans who come into contact with or eat fish from such water. Reported herein is the rapid, sensitive, and selective detection of four organochlorine pesticides in a variety of water sources across the state of Rhode Island using cyclodextrin-promoted fluorescence detection. This method relies on the ability of cyclodextrin to promote analyte-specific fluorescence modulation of a high quantum yield fluorophore when a pesticide is in close proximity, combined with subsequent array-based statistical analyses of the measurable changes in the emission signals. This system operates with high sensitivity (low micromolar detection limits), selectivity (100% differentiation between structurally similar analytes), and general applicability (for different water samples with varying salinity and pH as well as for different water temperatures).

Myoinositol: The Bridge (PONTI) to Reach a Healthy Pregnancy

The use of folic acid in the periconceptional period can prevent about 70% of neural tube defects (NTDs). In the remaining cases, no medical prevention is available, and those conditions should be defined as folate-resistant NTDs. Rodent models suggest that some folate-resistant NTDs can be prevented by inositol (myoinositol and chiroinositol) supplementation prior to pregnancy. Should folic acid be combined with myoinositol periconceptional supplementation to reduce the overall risk of NTDs even in humans? Hereafter, we discuss the results from the PONTI study that strongly support both the effectiveness and safety of myoinositol periconceptional supplementation in preventing human NTDs. We further report on the largest case series of pregnancies treated with myoinositol and folic acid. At our institution, a sequential study during 12 years involved mothers at risk of fetal NTDs, and 29 babies from 27 pregnancies were born after periconceptional combined myoinositol and folic acid supplementation. No case of NTDs was observed, despite the high recurrence risk in the mothers. Taken together, those data suggest that periconceptional folic acid plus myoinositol can reduce both the occurrence and recurrence risks of NTDs in a greater number of cases than folic acid alone.