Selective Analysis of Progesterone in Cosmetic Samples Based on Molecularly Imprinted Solid-Phase Extraction and High-Performance Liquid Chromatography.

The illegal addition of progesterone to cosmetics could cause serious adverse reactions and pose a serious threat to human health. In this work, a simple, fast and sensitive method was developed by combining molecularly imprinted solid-phase extraction and high-performance liquid chromatography (MISPE-HPLC) for the selective determination of progesterone in cosmetics. Chitosan-modified silica is used as the carrier to provide binding sites for the effective conjugation of the target. The obtained molecularly imprinted polymers exhibited excellent adsorption capacity (36.2 mg·g-1), good selectivity and fast mass transfer rate for progesterone. Meanwhile, the prepared MISPE column could eliminate the interference of co-existing substances. Combined MISPE with HPLC, a selective and effective method for detecting progesterone in different cosmetics was achieved. Under the optimum conditions, the established MISPE-HPLC method was successfully used for the detection of progesterone in real samples. The linear range of this method was 1 to 200 µg·mL-1 with a limit of detection of 0.016 µg·mL-1. Therefore, this method could be used for the selective and effective detection of progesterone in different cosmetic samples with complex substrates. We provided an alternative method for the detection of illegal additions in cosmetics.

Multi-template imprinted solid-phase microextraction coupled with UPLC-Q-TOF-MS for simultaneous monitoring of ten hepatotoxic pyrrolizidine alkaloids in scented tea.

Pyrrolizidine alkaloids (PAs) are a series of ubiquitous natural toxins in flowering plants, which are associated with serious hepatic disease in humans. However, the simultaneously fast and sensitive monitoring of different PAs are still challenge because of the diversity of PAs and huge amount of interference in complex samples, such as scented tea samples. In this study, molecularly imprinted solid phase microextraction (MIP-SPME) fibers were fabricated by using multi-template imprinting technique for selective recognition and efficient enrichment of different PAs from scented teas. MIP-SPME could be used for selective adsorption of ten types of PAs through specific recognition cavity and strong ionic interaction, including senecionine, lycopsamine, retrorsine, heliotrine, lasiocarpine, monocrotaline, echimidine, erucifoline, europine and seneciphylline. The extraction parameters were also optimized including extraction time, elution solvent and elution time. Then, ultra performance liquid chromatography- quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS) coupled with MIP-SPME method was developed for fast, simple, sensitive and accurate determination of ten PAs in scented teas. The established method was validated and presented satisfactory accuracy and high precision. It was also successfully applied for simultaneous determination of ten PAs in different scented tea samples. PAs were found in most of these scented tea samples, which suggest the cautious use of scented tea for consumers.

Highly efficient amino-functionalized aluminum-based metal organic frameworks mesoporous nanorods for selective extraction of hydrocortisone in pharmaceutical wastewater.

Hydrocortisone (HC), as a common steroid hormone drug, is also one of the key intermediates involved in the synthesis of multiple steroid hormone drugs. Residual HC in pharmaceutical wastewater frequently pollutes environmental water as steroid hormone contaminant and possesses great threat to human health as well as sustainable development of the ecosystem. Herein, in order to develop a highly efficient adsorbent system for selective enrichment and detection of HC in pharmaceutical wastewater, a novel amino-functionalized aluminum-based metal organic frameworks (Al-MOFs@NH2) mesoporous nanorod is fabricated, in which 2-aminoterephthalic acid plays a dual role as organic linker and functional modification unit. The resultant Al-MOFs@NH2 not only exhibits stable mesoporous structure but also has large specific surface area (849.76 m2 g-1) and plentiful binding sites, which significantly increases the adsorption capacity for HC. Under the promotion of hydrogen bonding and hydrophobic interaction together, Al-MOFs@NH2 possesses high adsorption capacity (218.53 mg g-1) for HC, as well as shows satisfactory selectivity for HC and other steroid hormones. Moreover, a method using Al-MOFs@NH2 as solid phase extraction adsorbents combined with high performance liquid chromatography (HPLC) has been developed to specifically enrich and detect trace amount of HC in pharmaceutical wastewater. The developed method has a low limit of detection (LOD) (0.5×10-3 µg mL-1) and shows satisfactory recoveries for HC (75.9%-102.5%) with an acceptable relative standard deviation (RSD). These results demonstrate that the facile one-step preparation and excellent adsorption capacity makes Al-MOFs@NH2 attractive to capture and remove environmental steroid hormone pollutants. More importantly, the method proposed in this work is expected to provide a prospective solution for analysis of strong bioactive contaminants in pharmaceutical wastewater.

Patch-Wise Spatial-Temporal Quality Enhancement for HEVC Compressed Video.

Recently, many deep learning based researches are conducted to explore the potential quality improvement of compressed videos. These methods mostly utilize either the spatial or temporal information to perform frame-level video enhancement. However, they fail in combining different spatial-temporal information to adaptively utilize adjacent patches to enhance the current patch and achieve limited enhancement performance especially on scene-changing and strong-motion videos. To overcome these limitations, we propose a patch-wise spatial-temporal quality enhancement network which firstly extracts spatial and temporal features, then recalibrates and fuses the obtained spatial and temporal features. Specifically, we design a temporal and spatial-wise attention-based feature distillation structure to adaptively utilize the adjacent patches for distilling patch-wise temporal features. For adaptively enhancing different patch with spatial and temporal information, a channel and spatial-wise attention fusion block is proposed to achieve patch-wise recalibration and fusion of spatial and temporal features. Experimental results demonstrate our network achieves peak signal-to-noise ratio improvement, 0.55 - 0.69 dB compared with the compressed videos at different quantization parameters, outperforming state-of-the-art approach.