| 1. |
- Liu, Xiaotong, et al.
(författare)
-
Hydroxy Fatty Acids as Novel Markers for Authenticity Identification of the Honey Entomological Origin Based on the GC-MS Method
- 2023
-
Ingår i: Journal of Agricultural and Food Chemistry. - : American Chemical Society (ACS). - 0021-8561 .- 1520-5118. ; 71:18, s. 7163-7173
-
Tidskriftsartikel (refereegranskat)abstract
- The authenticity of honey is generally a worldwide concern, and there is a pressing need to establish a suitable entomological method to identify the authenticity of Apis cerana cerana (A. cerana) and Apis mellifera ligustica (A. mellifera) honey. Hydroxy fatty acids as bee-derived components are known to widely exist in honey and other biosamples. Herein, we present an identification strategy for hydroxy fatty acids based on the relative quantification with reference to royal jelly and targeted quantification combined with multivariate statistical analysis to identify the honey entomological origin. Multivariate statistical analysis was used to further determine differential hydroxy fatty acids between A. cerana honey and A. mellifera honey. Results showed that 8-hydroxyoctanoic acid (96.20-253.34 versus 0-32.46 mg kg-1) and 3,10-dihydroxydecanoic acid (1.96-6.56 versus 0-0.35 mg kg-1) could be used as markers for accurate identification of the honey entomological origin, while the three fraud honey samples were recognized using this method. This study provides the novel marker hydroxy fatty acids to identify A. cerana honey and A. mellifera honey from the perspective of bee-derived component differences.
|
|
| 2. |
- Song, Chenchen, et al.
(författare)
-
Activity fingerprinting of AMR β-lactamase towards a fast and accurate diagnosis
- 2023
-
Ingår i: Frontiers in cellular and infection microbiology. - 2235-2988. ; 13
-
Tidskriftsartikel (refereegranskat)abstract
- Antibiotic resistance has become a serious threat to global public health and economic development. Rapid and accurate identification of a patient status for antimicrobial resistance (AMR) are urgently needed in clinical diagnosis. Here we describe the development of an assay method for activity fingerprinting of AMR β-lactamases using panels of 7 β-lactam antibiotics in 35 min. New Deli Metallo β-lactamase-1 (NDM-1) and penicillinase were demonstrated as two different classes of β-lactamases. The panel consisted of three classes of antibiotics, including: penicillins (penicillin G, piperacillin), cephalosporins (cefepime, ceftriaxone, cefazolin) and carbapenems (meropenem and imipenem). The assay employed a scheme combines the catalytic reaction of AMR β-lactamases on antibiotic substrates with a flow-injected thermometric biosensor that allows the direct detection of the heat generated from the enzymatic catalysis, and eliminates the need for custom substrates and multiple detection schemes. In order to differentiate classes of β-lactamases, characterization of the enzyme activity under different catalytic condition, such as, buffer composition, ion strength and pH were investigated. This assay could provide a tool for fast diagnosis of patient AMR status which makes possible for the future accurate treatment with selected antibiotics.
|
|
| 3. |
- Zhang, Bingke, et al.
(författare)
-
Facile Synthesis of Organic–Inorganic Hybrid Heterojunctions of Glycolated Conjugated Polymer-TiO 2−X for Efficient Photocatalytic Hydrogen Evolution
- 2024
-
Ingår i: Small. - 1613-6810 .- 1613-6829. ; In Press
-
Tidskriftsartikel (refereegranskat)abstract
- The utilization of the organic–inorganic hybrid photocatalysts for water splitting has gained significant attention due to their ability to combine the advantages of both materials and generate synergistic effects. However, they are still far from practical application due to the limited understanding of the interactions between these two components and the complexity of their preparation process. Herein, a facial approach by combining a glycolated conjugated polymer with a TiO2−X mesoporous sphere to prepare high-efficiency hybrid photocatalysts is presented. The functionalization of conjugated polymers with hydrophilic oligo (ethylene glycol) side chains can not only facilitate the dispersion of conjugated polymers in water but also promote the interaction with TiO2−X forming stable heterojunction nanoparticles. An apparent quantum yield of 53.3% at 365 nm and a hydrogen evolution rate of 35.7 mmol h−1 g−1 is achieved by the photocatalyst in the presence of Pt co-catalyst. Advanced photophysical studies based on femtosecond transient absorption spectroscopy and in situ, XPS analyses reveal the charge transfer mechanism at type II heterojunction interfaces. This work shows the promising prospect of glycolated polymers in the construction of hybrid heterojunctions for photocatalytic hydrogen production and offers a deep understanding of high photocatalytic performance by such heterojunction photocatalysts.
|
|
| 4. |
- Zhuang, Xiahai, et al.
(författare)
-
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation : An open-access grand challenge.
- 2019
-
Ingår i: Medical Image Analysis. - : Elsevier BV. - 1361-8415 .- 1361-8423. ; 58
-
Tidskriftsartikel (refereegranskat)abstract
- Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, an initial set of training data is generally needed for constructing priors or for training. Furthermore, it is difficult to perform comparisons between different methods, largely due to differences in the datasets and evaluation metrics used. This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017. The challenge provided 120 three-dimensional cardiac images covering the whole heart, including 60 CT and 60 MRI volumes, all acquired in clinical environments with manual delineation. Ten algorithms for CT data and eleven algorithms for MRI data, submitted from twelve groups, have been evaluated. The results showed that the performance of CT WHS was generally better than that of MRI WHS. The segmentation of the substructures for different categories of patients could present different levels of challenge due to the difference in imaging and variations of heart shapes. The deep learning (DL)-based methods demonstrated great potential, though several of them reported poor results in the blinded evaluation. Their performance could vary greatly across different network structures and training strategies. The conventional algorithms, mainly based on multi-atlas segmentation, demonstrated good performance, though the accuracy and computational efficiency could be limited. The challenge, including provision of the annotated training data and the blinded evaluation for submitted algorithms on the test data, continues as an ongoing benchmarking resource via its homepage (www.sdspeople.fudan.edu.cn/zhuangxiahai/0/mmwhs/).
|
|
