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Objective: The rhizome of Atractylodes macrocephala Koidz. (Asteraceae), called Atractylodes macrocephala rhizome (AMR) and known by its traditional name Bai Zhu, is a prominent Chinese herbal medicine employed for preventing miscarriage. However, our previous study revealed that high dosages of AMR administered during pregnancy could cause embryotoxicity but the specific embryotoxic components and their underlying mechanisms remain unclear. This study aimed to screen and identify the potential embryotoxic components of AMR. Methods: The AMR extracts and sub-fractions were analyzed by thin layer chromatography and subsequently screened by in vitro mouse limb bud micromass and mouse whole embryo culture bioassays. The embryotoxic fractions from AMR were further evaluated in vivo using a pregnant mouse model. The structures of the potential embryotoxic components were analyzed using matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). Results: In vitro and in vivo bioassays revealed that AMR glycoside-enriched sub-fractions (AMR-A-IIa and AMR-A-IIb) exhibited potential embryotoxicity. These sub-fractions, when administered to pregnant animals, increased the incidence of stillbirth and congenital limb malformations. MS spectrometry analysis identified cycasin derivatives in both sub-fractions, suggesting their possible role in the observed limb malformations. However, further experiments are necessary to validate this hypothesis and to elucidate the underlying mechanisms. Conclusions: Our study provides significant scientific evidence on the pharmacotoxicity of AMR, which is important for the safe clinical application of commonly used Chinese herbal medicines during pregnancy.
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The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.
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Combating the illicit use of PDE5 inhibitor drugs is a focal point in forensic science research. In order to achieve rapid identification of such drugs, this study applies terahertz time-domain spectroscopy combined with chemometrics to establish a fast and accurate detection method for PDE5 inhibitors. The optimal detection method is determined by comparing the spectral performance of three optical parameters, namely absorption coefficient, refractive index, and dielectric constant. Linear discriminant models based on different spectral parameters, whale optimization algorithm optimized extreme learning machine models, and whale optimization algorithm optimized random forest models are established. The effectiveness and performance of principal component analysis and competitive adaptive reweighted sampling algorithm for spectral feature data selection are also investigated. The PDE5 inhibitor identification model based on the competitive adaptive reweighted sampling - whale optimization algorithm - random forest (CARS-WOA-RF) model achieves an accuracy of 98.61%, and the identification model for two concentrations of Sildenafil achieves 100% accuracy. The results demonstrate that terahertz time-domain spectroscopy combined with chemometrics can effectively detect various common types of PDE5 inhibitor drugs and different concentrations.
Assuntos
Inibidores da Fosfodiesterase 5 , Espectroscopia Terahertz , Animais , Baleias , Quimiometria , Máquina de Vetores de Suporte , AlgoritmosRESUMO
Isomerization commonly occurs in synthetic cannabinoids (SCs). Owing to the few differences in their structure and properties, it is difficult to simultaneously separate and identify them. Thus, the identification of synthetic cannabinoids is challenging, posing a threat to public security. This study aims to separate and identify four SCs, which are 2-[1-(5-fluoropentyl)-1H-indole-3-formylamino]-3,3-dimethylbutyrate methyl ester (5F-MDMB-PICA), 2-[1-(5-fluoropentyl)-1H-indole-3-formylamino]-3-methylbutyrate ethyl ester (5F-EMB-PICA), N-(1-amino-2,2-dimethyl-1-oxobutyl-2-yl)-1-butyl-1H-indazole-3-formamide (ADB-BINACA), N-(1-carbamoyl-2-methylpropyl)-1-pentyl indazole-3-formamide (AB-PINACA).Supercritical fluid chromatography-mass spectroscopy (SFC-MS) can realize the effective separation of some cannabinoid isomers. However, most laboratories are not equipped with SFC-MS systems. Ultra-high performance liquid chromatography-high resolution mass spectroscopy (UHPLC-HRMS) effectively combines the excellent efficient separation characteristics of liquid chromatography and the powerful qualitative ability of mass spectrometry. It is a commonly used technical method for the detection of amide synthetic cannabinoids and their metabolites in vivo and in vitro because of its advantages of high accuracy and efficiency. Liquid chromatography allows the separation of tested components by exploiting the difference in the partition coefficients between the mobile and stationary phases. When the two phases are in relative motion, the tested components are divided between the two phases, facilitating the separation and analysis of each component. Although the difference in the polarities of the tested amide synthetic cannabinoid isomeric substances is extremely small, liquid chromatography can induce a strong separation effect. The advantages of UHPLC-HRMS include high resolution imparted by mass spectrometry and high sensitivity, allowing its application in the qualitative analysis of various substances. Through UHPLC-HRMS, trace analytes at the nanogram scale as well as pure drugs and their metabolites in biosamples can be detected. This study proposed a method for the determination of two pairs of amide synthetic cannabinoid isomers-5F-EMB-PICA and 5F-MDMB-PICA, ADB-BINACA and AB-PINACA-through UHPLC-HRMS. A Hypersil GOLD C18 column (100 mm×2.1 mm, 1.9 µm) was selected for separation via liquid chromatography, and gradient elution was performed with methanol containing 0.1% formic acid and a 0.1% formic acid aqueous solution containing 10 mmol/L ammonium formate. Full scan/data-dependent secondary mass spectrometry (Full MS/dd-MS2) was conducted in the positive ion mode for detection. The results indicated that the four synthetic cannabinoid isomers could be accurately detected under the abovementioned conditions. The resolution between 5F-EMB-PICA and 5F-MDMB-PICA was 2.06, while that between ADB-BINACA and AB-PINACA was 1.22, indicating the effective separation and detection of both pairs. Furthermore, method validation was conducted to ensure the accuracy of the proposed method. The relationship of the four amide synthetic cannabinoid isomers exhibited excellent linearity. The correlation coefficients (R2) were >0.99. Moreover, the matrix effects of the four SCs in hair samples were between 88.67% and 111.76% and the recoveries were 96.23%-105.11%. The intra-day and inter-day precisions (RSDs) were <10%. The proposed method was used to identify the case materials. AB-PINACA was detected in a hair sample at a content of 0.73 µg/g. 5F-MDMB-PICA was detected in a tobacco sample at a content of 11.3 mg/g. The results indicate that the proposed method can be used for the examination of practical samples conducted by public security organizations. This study provides a reference method for the identification of synthetic cannabinoid isomers.