[Investigation of fibrous cultural materials by infrared spectroscopy].

Cultural fibrous material includes both important categories, i. e. textile and paper, consisting of precious cultural materials in museum, such as costume, painting, and manuscript. In recent years more and more connoisseur and conservator's concerns are, through nondestructive method, the authenticity and the ageing identification of these cultural relics especially made from fragile materials. In this research, we used attenuated total reflection infrared spectroscopy to identify five traditional textile fibers, alongside cotton, linen, wool, mulberry silk and tussah silk, and another five paper fibers alongside straw, wheat straw, long qisong, Chinese alpine rush and mulberry bar, which are commonly used for making Chinese traditional xuan paper. The research result showed that the animal fiber (wool, mulberry silk and tussah silk) and plant fiber (cotton and linen) were easier to be distinguished by comparing the peaks at 3 280 cm-1 belonging to NH stretching vibration and a serious peaks related to amide I to amide III. In the spectrum of wool, the peak at 1 076 cm-1 was assigned to the S-O stretching vibration absorption of cystine in wool structure and can be used to tell wool from silk. The spectrum of mulberry silk and tussah silk seems somewhat difficult to be identified, as well as the spectrum of cotton and linen. Five rural paper fibers all have obvious characteristic peaks at 3 330, 2 900 cm-1 which are related to OH and CH stretching vibration. In the fingerprint wavenumber range of 1 600 - 800 cm, the similar peaks also appeared at 1 370, 1 320 cm-1 and 1 162, 1 050 cm-1, both group peaks respectively are related to CH and CO vibration in the structure of cellulose and hemicellulose in paper fibers. Although there is more similarity of the infrared spectroscopy of these 5 paper fibers, some tiny difference in absorbance also can be found at 3 300 cm-1 and in the fingerprint range at 1 332, 1 203, and 1 050 cm-1 which are related to C-O-C vibration in cellulose. Moreover, in order to explore direct and simple method to identify different materials with similar spectrum,. the principal component analysis (PCA) was applied to separate cotton and linen, mulberry silk and tussah silk, as well as five paper fibers. To eliminate and reduce the spectral scattering caused by sample uneven surface roughness, the multiplicative scatter correction (MSC) has been applied based on total spectral data. The result showed that the score plot using the first two principal components can effectively categorize both group textiles of cotton and linen, as well as mulberry silk and tussah silk, and they have similar chemical structure. For five paper fibers, the PCA was applied in different spectral range (918-550, 1 280-918, 1 700-1 280 and 3 800-2 800 cm-1), and the best result appeared in the range from 3 800 to 2 800 cm-1, in which the five paper fibers can be well categorized. This research showed that infrared spectroscopy combined with principal component analysis has great potential advantage on identifying fibrous materials with similar structure.

A liposome-based aptasensor integrated with competitive reaction enabling portable and electrochemical detection of Aß oligomer.

Aggregation of ß-amyloid (Aß) were considered as a typical pathological feature of Alzheimer's disease (AD). Extensive studies have verified that soluble Aß oligomers (AßO) were more toxic to neurons than plaques. Herein, in this work, a glucose entrapped liposome-based portable aptasensor was fabricated for recognizing and interacting with AßO by specific aptamer on liposome (G-Lip-Apt). Then, a single strand DNA, designed to be partially complementary to AßO aptamer, was modified on amino-functionalized Fe3O4@SiO2 to obtain a magnetic nanocomposite (Fe3O4@SiO2/NH2-DNA). In the presence of AßO, the specific recognition between AßO and its aptamer on G-Lip-Apt made AßO bounded with G-Lip-Apt. With subsequent introduction of Fe3O4@SiO2/NH2-DNA, the unreacted G-Lip-Apt was further linked with Fe3O4@SiO2/NH2-DNA by double stranded complementary pairing interaction. Along with the addition of TritonX-100 into the formed G-Lip-Apt/Fe3O4@SiO2/NH2-DNA complex, the encapsulated glucose was released from liposome and then measured by a personal glucose meter (PGM). Good linear correlation was acquired over concentration of 5.0-1000 nM and the limit of detection (LOD) was calculated to be 2.27 nM for AßO. The developed portable electrochemical strategy integrated magnetic separation, competitive reaction and point of care test (POCT) to achieve high sensitivity, selectivity and accuracy, therefore enabled it successfully applied to the analysis of AßO in the hippocampus and cortex of APP/PS1 transgenic AD mice.

Machine learning-assisted Te-CdS@Mn3O4 nano-enzyme induced self-enhanced molecularly imprinted ratiometric electrochemiluminescence sensor with smartphone for portable and visual monitoring of 2,4-D.

Here, a novel and portable machine learning-assisted smartphone-based visual molecularly imprinted ratiometric electrochemiluminescence (MIRECL) sensing platform was constructed for highly selective sensitive detection of 2,4-Dichlorophenoxyacetic acid (2,4-D) for the first time. Te doped CdS-coated Mn3O4 (Te-CdS@Mn3O4) with catalase-like activity served as cathode-emitter, while luminol as anode luminophore accompanied H2O2 as co-reactant, and Te-CdS@Mn3O4 decorated molecularly imprinted polymers (MIPs) as recognition unit, respectively. Molecular models were constructed and MIP band and binding energies were calculated to elucidate the luminescence mechanism and select the best functional monomers. The peroxidase activity and the large specific surface area of Mn3O4 and the electrochemical effect can significantly improve the ECL intensity and analytical sensitivity of Te-CdS@Mn3O4. 2,4-D-MIPs were fabricated by in-situ electrochemical polymerization, and the rebinding of 2,4-D inhibits the binding of H2O2 to the anode emitter, and with the increase of the cathode impedance, the ECL response of Te-CdS@Mn3O4 decreases significantly. However, the blocked reaction of luminol on the anode surface also reduces the ECL response. Thus, a double-reduced MIRECL sensing system was designed and exhibited remarkable performance in sensitivity and selectivity due to the specific recognition of MIPs and the inherent ratio correction effect. Wider linear range in the range of 1 nM-100 µM with a detection limit of 0.63 nM for 2,4-D detection. Interestingly, a portable and visual smartphone-based MIRECL analysis system was established based on the capture of luminescence images by smartphones, classification and recognition by convolutional neural networks, and color analysis by self-developed software. Therefore, the developed MIRECL sensor is suitable for integration with portable devices for intelligent, convenient, and fast detection of 2,4-D in real samples.

Selective extraction and analysis of catecholamines in rat blood microdialysate by polymeric ionic liquid-diphenylboric acid-packed capillary column and fast separation in high-performance liquid chromatography-electrochemical detector.

Concentration of blood catecholamines (CAs) is linked to a host of cardiovascular diseases, including hypertension and stenocardia. The matrix interferences and low concentration require tedious sample pretreatment methods before quantitative analysis by the gold standard method of high-performance liquid chromatography-electrochemical detector (HPLC-ECD). Solid phase extraction (SPE) has been widely used as the pretreatment technique. Here, a facile polymeric ionic liquid (PIL)-diphenylboric acid (DPBA)-packed capillary column was prepared to selectively extract dopamine (DA), noradrenaline (NE) and epinephrine (E) prior to their quantitative analysis by a fast separation in HPLC-ECD method, while microdialysis sampling method was applied to get the analysis sample. Parameters that influenced desorption efficiency, such as pH, salt concentration, acetonitrile content and wash time, were examined and optimized. The proposed method, combining microdialysis sampling technique, SPE and HPLC-ECD system, was successfully applied to detect CAs in rat blood microdialysate with high sensitivity and selectivity in small sample volumes (5-40µl) and a short analysis time (8min), yielding good reproducibility (RSD 6.5-7.7%) and spiked recovery (91-104.4%).