Zwitterionic surfactant as an additive for efficient electrophoretic separation of easily absorbed rhodamine dyes on plastic microchips.

Plastic microchips possess the advantages of easy fabrication and low-cost, but their surface properties are frequently incompatible with electrophoretic separation without proper surface modification. Meanwhile, the separation microchannels on typical microchips are usually only a few centimeters long, the pressurized flow may significantly affect the electrophoretic separation if their inner diameters (id) are relatively larger (approximately > 50 µm), viscous separation medium is therefore required for efficient separation. Herein, a zwitterionic surfactant, N-hexadecyl-N,N-dimethyl-3-ammonio-1-propane sulfonate (HDAPS), was used as a multifunctional additive to inhibit the analyte adsorption, improve the surface status, control Joule heating and modulate the resolution on cyclic olefin copolymer microchips with 80 µm id, 5 cm long separation microchannels, eliminating the necessity of viscous polymeric additives. The effectiveness of HDAPS was compared with an ionic polymeric additive, poly(diallydimethylammonium chloride). The streaming potential and electroosmotic flow measurements indicated an effective inhibition of the adsorption of rhodamine B and a stable negative surface charge with zwitterionic HDAPS. Using 15 mmol/L HDAPS, 40% (v/v) methanol, and 10 mmol/L boric acid (pH 3.2) as the running buffer, rapid separation of four rhodamines was achieved within 90 s under a separation electric field of 520 V/cm. The theoretical plate numbers were in a range of 5.0×105-6.9×105/m. The relative standard deviations were no more than 0.9% for retention time and 1.5% for peak area. The proposed system was verified by the determination of rhodamines in eyeshadow and wolfberry, with standard recoveries in a range of 98.2%-101.4%.

Dental Lesion Segmentation Using an Improved ICNet Network with Attention.

Precise segmentation of tooth lesions is critical to creation of an intelligent tooth lesion detection system. As a solution to the problem that tooth lesions are similar to normal tooth tissues and difficult to segment, an improved segmentation method of the image cascade network (ICNet) network is proposed to segment various lesion types, such as calculus, gingivitis, and tartar. First, the ICNet network model is used to achieve real-time segmentation of lesions. Second, the Convolutional Block Attention Module (CBAM) is integrated into the ICNet network structure, and large-size convolutions in the spatial attention module are replaced with layered dilated convolutions to enhance the relevant features while suppressing useless features and solve the problem of inaccurate lesion segmentations. Finally, part of the convolution in the network model is replaced with an asymmetric convolution to reduce the calculations added by the attention module. Experimental results show that compared with Fully Convolutional Networks (FCN), U-Net, SegNet, and other segmentation algorithms, our method has a significant improvement in the segmentation effect, and the image processing frequency is higher, which satisfies the real-time requirements of tooth lesion segmentation accuracy.

Sensitive analysis of curcuminoids via micellar electrokinetic chromatography with laser-induced native fluorescence detection and mixed micelles-induced fluorescence synergism.

Curcuminoids, the major bioactive constituents of traditional medicine known as turmeric, have exhibited extensive therapeutic benefits. Excited by violet-blue light, curcuminoids can emit native fluorescence, making them possible to be detected with high sensitivity and specificity by laser-induced native fluorescence (LINF). Here, a commercial 445 nm laser diode was used as an excitation source to construct a confocal laser-induced fluorescence (LIF) detector and then a complete capillary electrophoresis (CE) system coupled with LIF detection was established. With three major curcuminoids, curcumin, demethoxy curcumin (DMC) and bisdemethoxy curcumin (BDMC) as target analytes, a micellar electrokinetic chromatography (MEKC) method was proposed using mixed micelles consisting of Triton X-100 and SDS to sensitize the native fluorescence of curcuminoids and enhance their separation efficiency. Fluorescence spectra revealed that the mixed micelles induced fluorescence synergism could enhance the signals of three curcuminoids by 77-, 57-, and 47-fold for curcumin, DMC, and BDMC. After systematic investigation, the optimal separation buffer for curcuminoids was chosen as follows: 20 mM Triton X-100, 20 mM SDS, 30% (v/v) methanol in 10 mM borax solution at pH 10.0. Under these conditions, a baseline separation of three curcuminoids was achieved within 10 min and the detection limits were found to be 4.1, 2.6, and 0.4 ng/mL for curcumin, DMC, and BDMC, respectively. Furthermore, the developed MEKC-LINF method was validated in terms of precision, linearity, accuracy and successfully applied for the determination of three curcuminoids in turmeric, medicinal turmeric liniment, curry seasoning, and human urine samples.