| 1. |
- El-Seedi, Hesham, et al.
(författare)
-
Gelatin nanofibers : Recent insights in synthesis, bio-medical applications and limitations
- 2023
-
Ingår i: Heliyon. - : Elsevier. - 2405-8440. ; 9:5
-
Forskningsöversikt (refereegranskat)abstract
- The use of gelatin and gelatin-blend polymers as environmentally safe polymers to synthesis electrospun nanofibers, has caused a revolution in the biomedical field. The development of efficient nanofibers has played a significant role in drug delivery, and for use in advanced scaffolds in regenerative medicine. Gelatin is an exceptional biopolymer, which is highly versatile, despite variations in the processing technology. The electrospinning process is an efficient technique for the manufacture of gelatin electrospun nanofibers (GNFs), as it is simple, efficient, and cost-effective. GNFs have higher porosity with large surface area and biocompatibility, despite that there are some drawbacks. These drawbacks include rapid degradation, poor mechanical strength, and complete dissolution, which limits the use of gelatin electrospun nanofibers in this form for biomedicine. Thus, these fibers need to be cross-linked, in order to control its solubility. This modification caused an improvement in the biological properties of GNFs, which made them suitable candidates for various biomedical applications, such as wound healing, drug delivery, bone regeneration, tubular scaffolding, skin, nerve, kidney, and cardiac tissue engineering. In this review an outline of electrospinning is shown with critical summary of literature evaluated with respect to the various applications of nanofibers-derived gelatin.
|
|
| 2. |
- Guo, Zhiming, et al.
(författare)
-
Detection model transfer of apple soluble solids content based on NIR spectroscopy and deep learning
- 2023
-
Ingår i: Computers and Electronics in Agriculture. - : Elsevier. - 0168-1699 .- 1872-7107. ; 212
-
Tidskriftsartikel (refereegranskat)abstract
- Transfer and updating of near infrared (NIR) spectroscopy model of fruit internal quality has become the focus of the industrial application. Internet of Things (IoT) and deep learning (DL) were proposed to perform soluble solids content (SSC) model transfer of apple by NIR. A model transfer platform including low-power handheld internal quality terminal and interacting cloud data system had been constructed. An autoencoder (AE) neural network model was developed for the spectral correction and model transfer. The average time for transmitting detection results to the detection terminal was 1.5 to 2.0 s, with a 100% effective transmission rate. After 5000 iterations of training, the correlation coefficient of different detection terminals improved by 55%, and the root mean square error was reduced by 94%. Selected samples from the second batch of apples detected by the No. 1 detection terminal were added to the original neural network for training. After adding 30 samples, the correlation coefficient increased by 13% and the root mean square error decreased by 90%. The results demonstrated that the AE neural network for spectral correction was effective in eliminating differences between devices and significantly reducing the impact of different detection terminals on the accuracy of NIR detection of SSC in apples. Therefore, the NIR detection model transfer technique could be practically exploited for fruit quality control assessment using different detection terminals.
|
|
| 3. |
- Guo, Zhiming, et al.
(författare)
-
Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy
- 2023
-
Ingår i: Food reviews international (Print). - : Taylor & Francis Group. - 8755-9129 .- 1525-6103. ; 39:3, s. 1440-1461
-
Forskningsöversikt (refereegranskat)abstract
- Heavy metals accumulating in the human body produce physiological toxicity by interfering with the transport of human proteins and enzymes. Heavy metals detection is significant for food safety assurance. This review focuses on recent advances of heavy metals detection of food and agricultural products by surface-enhanced Raman spectroscopy (SERS). The article covers the SERS basic principles and advances in heavy metals detection, including mercury, arsenic, cadmium, lead, chromium among others. Insights in the potential of combining chemometrics and multivariate analysis with SERS and the exploration of novel SERS substrate platforms from both macro and micro scale are discussed. Finally, future application of SERS in heavy metal detection are prospected. SERS is a powerful and promising technique offering the advantages of simple sampling, rapid data collection and non-invasiveness. The findings of this study can allow better understanding of the heavy metals' occurrence and the possibility of its detection using SERS.
|
|
| 4. |
- Guo, Zhiming, et al.
(författare)
-
Novel mesoporous silica surface loaded gold nanocomposites SERS aptasensor for sensitive detection of zearalenone
- 2023
-
Ingår i: Food Chemistry. - : Elsevier. - 0308-8146 .- 1873-7072. ; 403
-
Tidskriftsartikel (refereegranskat)abstract
- Mycotoxin contamination is a severe threat to global food security, thus fast and effective detection of myco-toxins is of great significance. Herein, mesoporous silica surface loaded gold nanocomposites (MSN-Rh6G-AuNPs) were prepared as surface-enhanced Raman scattering (SERS) substrate, and the SERS aptasensor (MSN-Rh6G-AuNPs@apt) was further obtained by aptamer functionalization which can realize the quantitative and sensitive detection of zearalenone (ZEN). The small nanogaps between AuNPs made MSN-Rh6G-AuNPs present strong SERS performance under excitation light irradiation, while the aptamer performed the functions of ZEN recognition and Raman signal masking. The acquired results revealed that the SERS intensity at 1508 cm-1 had a good linear relationship with ZEN concentration of 3-200 ng/mL and the limit of detection (LOD) was calculated to be 0.0064 ng/mL. In addition, the designed SERS aptasensor was successfully applied to the detection of ZEN in corn, indicating great potential in practical implications.
|
|
| 5. |
- Guo, Zhiming, et al.
(författare)
-
Sensitive determination of Patulin by aptamer functionalized magnetic surface enhanced Raman spectroscopy (SERS) sensor
- 2023
-
Ingår i: Journal of Food Composition and Analysis. - : Elsevier BV. - 0889-1575 .- 1096-0481. ; 115
-
Tidskriftsartikel (refereegranskat)abstract
- Food pollution caused by Patulin (PAT) seriously threatens the safety of human diets and has attracted extensive attention. Early and accurate detections of PAT are essential to prevent further toxin spreading and contamination. A surface enhanced Raman scattering (SERS) aptasensor was fabricated by combining a gold-silver core shell structure containing signal molecule (ADANRs) and chitosan modified magnetic nanoparticles (CS-Fe3O4). The modified ADANRs with the complementary chain of the aptamer (SH-cDNA-ADANRs) which were served as the signal probes and the aptamer modified CS-Fe3O4 (NH2-apt-CS-Fe3O4) were served as the capture probes. In addition to the ability to recognize the target PAT, the capture probe also showed a strong enrichment ability under the action of external magnetic force. The intraparticle plasma coupling between the inner gold core and the outer silver shell can greatly improve the SERS activity of the signal molecules. SERS aptasensor was used to collect the spectra of actual apple samples spiked with different PAT content. The minimum detection limit of SERS aptasensor for detecting PAT in actual samples was 0.0384 ng/mL and the recovery rate range was from 96.3% to 108%. In conclusion, the sensitive and specific SERS aptasensor detection of PAT based on aptamer functionalized nanoparticles exhibited great potential for practical application in mycotoxin detection and analysis.
|
|
| 6. |
- Ke, Qian, et al.
(författare)
-
Determination of Dicofol in Tea Using Surface-Enhanced Raman Spectroscopy Coupled Chemometrics
- 2023
-
Ingår i: Molecules. - : MDPI AG. - 1431-5157 .- 1420-3049. ; 28:14
-
Tidskriftsartikel (refereegranskat)abstract
- Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core-shell Au@AgNPs. Then, the core-shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 x 10(-11) mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky-Golay combined with competitive adaptive reweighted sampling-partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.
|
|
| 7. |
- Khalifa, Shaden A. M., et al.
(författare)
-
Frankincense of Boswellia sacra: Traditional and modern applied uses, pharmacological activities, and clinical trials
- 2023
-
Ingår i: Industrial crops and products (Print). - : Elsevier. - 0926-6690 .- 1872-633X. ; 203
-
Tidskriftsartikel (refereegranskat)abstract
- Since Boswellia sacra (Burseraceae) was studied in the 19th century, it has been known for its economic and cultural values. It is cultivated mainly in the southwest regions of Oman and some regions of Yemen, and is a natural source of frankincense, "Luban" in Arabic, around the world. Frankincense, the aromatic resin of B. sacra, is used widely both for traditional purposes and for the treatment of various ailments; e.g., dental infections, tumors, dysentery, vomiting, and fevers. Recently, many reports provided evidence for the potential biological activities of B. sacra, its synonym Boswellia carteri, and their constituent chemical compounds. These activities include cytotoxic, anti-inflammatory, antimicrobial, anti-diabetes, immunomodulatory, and anticoagulant effects. B. sacra was also tested for effects against gastric, hepatic, neurological, and skin disorders in vitro and in vivo. Clinical trials revealed good effects against carcinomas and gliomas, as well as against bladder and brain tumors. Its uses as a plant-based agent in nanotechnology displayed promising results. More efforts should be directed to further investigate these safe, plant-based bio-preservatives, and best practices should be outlined to protect these trees from extinction.
|
|
| 8. |
- Tahir, Haroon Elrasheid, et al.
(författare)
-
HPLC-DAD, GC-MS, UHPLC-Q-TOF/MS2, ICP-MS and FT-NIR combined with the chemometrics explain seasonal variation in Cassia senna L. leaves from the coast of Red Sea in Sudan
- 2023
-
Ingår i: South African Journal of Botany. - : Elsevier. - 0254-6299 .- 1727-9321. ; 163, s. 20-29
-
Tidskriftsartikel (refereegranskat)abstract
- Crops reveal considerable capability to regulate their phytochemicals and trace element contents to seasonal changes in temperature and rainfalls. In this study, we have measured the secondary metabolites, volatiles, and trace elements of Cassia senna L leaves collected from the Red Sea State, Sudan during winter 2018, summer 2019, and autumn 2020. Chemical profiles were evaluated by High-performance liquid chromatography with diode-array detection (HPLC-DAD), Ultra-high performance liquid chromatography (UHPLC); Inductively coupled plasma mass spectrometry(ICP-MS), Gas chromatography-mass spectrometry (GC-MS), Fourier-transform near-infrared spectroscopy (FT-NIR). 46 metabolites, 33 volatile compounds, and 13 elements were reported. The findings suggested significant seasonal variations in sennoside (A-B) compounds, which were reported to have positive health effects. In this study, aloesin was identified for the first time in senna leaves. Analysis of seasonal variations was obtained by principal component analysis and orthogonal partial least squares discriminant model. Additionally, chemical markers for each harvest season were reported. Overall, the number of metabolites and volatiles identified as a function of the season was autumn > summer> winter. Our results have enhanced the knowledge of the selection of harvesting time, with the best characteristics for the intended therapeutic application.(c) 2023 SAAB. Published by Elsevier B.V. All rights reserved.
|
|
| 9. |
- Yang, Xiaoxue, et al.
(författare)
-
Improved deep reinforcement learning for car-following decision-making
- 2023
-
Ingår i: Physica A. - : Elsevier B.V.. - 0378-4371 .- 1873-2119. ; 624
-
Tidskriftsartikel (refereegranskat)abstract
- Accuracy improvement of Car-following (CF) model has attracted much attention in recent years. Although a few studies incorporate deep reinforcement learning (DRL) to describe CF behaviors, proper design of reward function is still an intractable problem. This study improves the deep deterministic policy gradient (DDPG) car-following model with stacked denoising autoencoders (SDAE), and proposes a data-driven reward representation function, which quantifies the implicit interaction between ego vehicle and preceding vehicle in car-following process. The experimental results demonstrate that DDPG-SDAE model has superior ability of imitating driving behavior: (1) validating effectiveness of the reward representation method with low deviation of trajectory; (2) demonstrating generalization ability on two different trajectory datasets (HighD and SPMD); (3) adapting to three traffic scenarios clustered by a dynamic time warping distance based k-medoids method. Compared with Recurrent Neural Networks (RNN) and intelligent driver model (IDM), DDPG-SDAE model shows better performance on the deviation of speed and relative distance. This study demonstrates superiority of a novel reward extraction method fusing SDAE into DDPG algorithm and provides inspiration for developing driving decision-making model. © 2023 Elsevier B.V.
|
|
| 10. |
- Yin, Limei, et al.
(författare)
-
Development of a Sensitive SERS Method for Label-Free Detection of Hexavalent Chromium in Tea Using Carbimazole Redox Reaction
- 2023
-
Ingår i: Foods. - : MDPI AG. - 2304-8158. ; 12:14
-
Tidskriftsartikel (refereegranskat)abstract
- Tea plants absorb chromium-contaminated soil and water and accumulate in tea leaves. Hexavalent chromium (Cr6+) is a very toxic heavy metal; excessive intake of tea containing Cr6+ can cause serious harm to human health. A reliable and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed using Au@Ag nanoparticles as an enhanced substrate for the determination of Cr6+ in tea. The Au@AgNPs coated with carbimazole showed a highly selective reaction to Cr6+ in tea samples through a redox reaction between Cr6+ and carbimazole. The Cr6+ in the contaminated tea sample reacted with methimazole-the hydrolysate of carbimazole-to form disulfide, which led to the decrease in the Raman intensity of the peak at 595 cm(-1). The logarithm of the concentration of Cr6+ has a linear relationship with the Raman intensity at the characteristic peak and showed a limit of detection of 0.945 mg/kg for the tea sample. The carbimazole functionalized Au@AgNPs showed high selectivity in analyzing Cr6+ in tea samples, even in the presence of other metal ions. The SERS detection technique established in this study also showed comparable results with the standard ICP-MS method, indicating the applicability of the established technique in practical applications.
|
|
| 11. |
- Yin, Limei, et al.
(författare)
-
Dual-layers Raman reporter-tagged Au@Ag combined with core-satellite assemblies for SERS detection of Zearalenone
- 2023
-
Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 429
-
Tidskriftsartikel (refereegranskat)abstract
- Zearalenone (ZEN) is a prevalent mycotoxin identified in corn. A SERS-based immunosensor by constructing core-satellite assemblies was developed for ZEN detection. ZEN monoclonal antibody modified gold nanostars (AuNSs) were fabricated as the capture probe (core). The Raman signal probes (satellites) utilized ZEN antigen linked to the core-shell structures loaded with two layers of Raman reporter molecules (AuMBA@AgMBANPs). The coupling between AuNSs and AuMBA@AgMBANPs can produce a poweful electromagnetic field, thus considerably amplifying the Raman signal. The detection range of ZEN for corn samples under the optimal conditions was 5 -400 & mu;g/kg with a LOD of 3 & mu;g/kg, which completely satisfying the requirement of maximum residual level (60 & mu;g/kg). Moreover, the proposed SERS method was consistent with the HPLC-FLD method for the detection of ZEN in naturally contaminated corn samples (90.58% -105.29%). Conclusively, fabricated immunosensor with exceptional sensitivity and specificity broaden the application of SERS in mycotoxin detection.
|
|
| 12. |
- Yin, Limei, et al.
(författare)
-
Spoilage Monitoring and Early Warning for Apples in Storage Using Gas Sensors and Chemometrics
- 2023
-
Ingår i: Foods. - : MDPI AG. - 2304-8158. ; 12:15
-
Tidskriftsartikel (refereegranskat)abstract
- In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O-2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing-partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (R-p) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse's sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.
|
|
