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"Xu, Weimin"
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Effect of myoglobin, hemin, and ferric iron on quality of chicken breast meat
Objective: The objective was to evaluate the impact of different forms of iron including myoglobin, hemin, and ferric chloride on the quality of chicken breast meat. Methods: Chicken breast muscles were subjected to 1, 2, 3 mg/mL of FeCl3, myoglobin and hemin treatment respectively, and the production of reactive oxygen species (ROS) and malondialdehyde, meat color, tenderness, water holding capacity and morphology of meat was evaluated. Results: Hemin was found to produce more ROS and induce greater extent of lipid oxidation than myoglobin and ferric chloride. However, it showed that hemin could significantly increase the redness and decrease the lightness of the muscle. Hemin was also shown to be prominent in improving water holding capacity of meat, maintaining a relatively higher level of the immobilized water from low-field nuclear magnetic resonance measurements. Morphology observation by hematoxylin-eosin staining further confirmed the results that hemin preserved the integrity of the muscle. Conclusion: The results indicated that hemin may have economic benefit for the industry based on its advantage in improving water holding capacity and quality of meat.
Journal Article
Evaluation of antioxidant property of heat shock protein 90 from duck muscle
Objective: The objectives of this study were to investigate the direct antioxidative effect of 90 Kda heat shock protein (Hsp90) obtained from duck muscle.Methods: The interaction of Hsp90 with phospholipids and oxidized phospholipids was studied with surface plasmon resonance (SPR), and their further oxidation in the presence of Hsp90 was evaluated with thiobarbituric acid reactive substances (TBARS) assay. The scavenging effect on the 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2’-azinobis (3-ethylbenzthiazoline-6-sulfonic acid (ABTS) was measured, and the electron paramagnetic resonance (EPR) spectroscopy in combination with 5-tert-Butoxycarbonyl-5-methyl-1-pyrroline-N-oxide and 2-phenyl-4,4,5,5,-tetramethylimidazoline-1-oxyl-3-oxide (PTIO) was utilized to determine the abilities of Hsp90 in scavenging hydroxyl and PTIO radicals.Results: SPR showed Hsp90 could bind with both phospholipids and oxidized phospholipids, and prevent their further oxidation by the TBARS assay. The DPPH and ABTS scavenging activity increased with Hsp90 concentration, and could reach 27% and 20% respectively at the protein concentration of 50 μM. The EPR spectra demonstrated Hsp90 could directly scavenge ·OH and PTIO· radicals.Conclusion: This suggests that Hsp90, a natural antioxidant in meat, may play an important role in cellular defense against oxidative stress, and may have potential use in meat products.
Journal Article
The value of mesenteric closure after laparoscopic right hemicolectomy: a scoping review
Objective
To evaluate the prognostic impact and describe suturing tools of mesenteric closure after laparoscopic right hemicolectomy (LRH).
Methods
PubMed, Embase, Cochrane library, Web of Science, and Scopus databases, were searched and publications relating to mesenteric closure data and tools were extracted. Search terms: “Mesenteric Defects” and “Mesenteric Closure” were used, and manual searches of eligible articles from literature reference lists performed.
Result
A total of 7 publications were identified. 5 focused on prognostic impact and 4 referred to tools for mesenteric closure, two of which concerned both prognostic data and tools. All studies related to prognostic impact were single center with “low” modified GRADE quality. A high degree of heterogeneous was found.
Conclusion
The evidence from current research does not support routine closure of mesenteric defects. Use of a polymer ligation clip has produced favorable results in a small sample size trial and further investigation is merited. A large randomized controlled trial is still warranted.
Journal Article
Bi-Josephson effect in a driven-dissipative supersolid
The Josephson effect is a macroscopic quantum tunneling phenomenon in a system with superfluid property, when it is split into two parts by a barrier. Here, we examine the Josephson effect in a driven-dissipative supersolid realized by coupling Bose–Einstein condensates to an optical ring cavity. We show that the spontaneous breaking of spatial translation symmetry in supersolid makes the location of the splitting barrier have a significant influence on the Josephson effect. Remarkably, for the same splitting barrier, depending on its location, two different types of DC Josephson currents are found in the supersolid phase (compared to only one type found in the superfluid phase). Thus, we term it a bi-Josephson effect. We examine the Josephson relationships and critical Josephson currents in detail, revealing that the emergence of supersolid order affects these two types of DC Josephson currents differently—one is enhanced, while the other is suppressed. The findings of this work unveil unique Josephson physics in the supersolid phase, and show new opportunities to build novel Josephson devices with supersolids.
Journal Article
Predefined-Time Adaptive Virtual Synchronous Generator Secondary Control for Microgrids
The traditional secondary control method for virtual synchronous generators suffers from limitations such as slow dynamic response and poor adaptability under varying operating conditions, which significantly affect the reliability and stability of microgrids. To address these issues, this paper proposes an adaptive virtual synchronous generator secondary control method for microgrids based on predefined-time convergence. First, a predefined-time controller is designed, whose convergence time can be preset by the user, thereby resolving the problem of excessively long convergence times for frequency regulation and power sharing. Second, an adaptive inertia damping control method incorporating Gaussian functions is introduced to mitigate frequency fluctuations during disturbances in the microgrid system, effectively suppressing frequency deviations and enhancing microgrid stability. Finally, based on Lyapunov stability theory, the convergence of the proposed control method is rigorously proved, and its feasibility is validated through MATLAB/Simulink simulations. The results demonstrate that the proposed secondary control method reduces the frequency and active power convergence times by 0.98 s and 0.49 s, respectively, compared to traditional virtual synchronous generator secondary control methods. Additionally, it exhibits smaller frequency fluctuation magnitude during disturbances, enabling fast and smooth frequency recovery.
Journal Article
Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study
Background
This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, particularly in cases with discordant US and MG Breast Imaging Reporting and Data System (BI-RADS) classifications.
Methods
We retrospectively collected image data from 1283 women with breast lesions who underwent both US and MG within one month at two medical centres and categorised them into concordant and discordant BI-RADS classification subgroups. We developed a DL-UM network via integrating US and MG images, and DL networks using US (DL-U) or MG (DL-M) alone, respectively. The performance of DL-UM network for breast lesion diagnosis was evaluated using ROC curves and compared to DL-U and DL-M networks in the external testing dataset. The diagnostic performance of radiologists with different levels of experience under the assistance of DL-UM network was also evaluated.
Results
In the external testing dataset, DL-UM outperformed DL-M in sensitivity (0.962 vs. 0.833,
P
= 0.016) and DL-U in specificity (0.667 vs. 0.526,
P
= 0.030), respectively. In the discordant BI-RADS classification subgroup, DL-UM achieved an AUC of 0.910. The diagnostic performance of four radiologists improved when collaborating with the DL-UM network, with AUCs increased from 0.674–0.772 to 0.889–0.910, specificities from 52.1%–75.0% to 81.3%–87.5% and reducing unnecessary biopsies by 16.1%–24.6%, particularly for junior radiologists. Meanwhile, DL-UM outputs and heatmaps enhanced radiologists’ trust and improved interobserver agreement between US and MG, with weighted kappa increased from 0.048 to 0.713 (
P
< 0.05).
Conclusions
The DL-UM network, integrating complementary US and MG features, assisted radiologists in improving breast lesion diagnosis and management, potentially reducing unnecessary biopsies.
Journal Article
Adaptive Hybrid Control for Bridge Cranes Under Model Mismatch and Wind Disturbance
Addressing the challenge of balancing high-precision positioning with strict safety constraints for underactuated bridge cranes subject to model parameter mismatch and stochastic wind disturbances, an adaptive hybrid control framework is presented integrating a Safety-Aware Dynamic Gain Sliding Mode Controller (DG-SMC) with a TD3-based residual deep reinforcement learning network. By designing a gain scheduling mechanism based on swing angle amplitude, the proposed method physically limits trolley acceleration to strictly constrain the payload swing angle within a safe range (±7°). Simultaneously, a TD3 agent is introduced as a residual compensator to adaptively learn system dynamics through environmental interaction, generating real-time compensatory control forces to counteract unmodeled dynamics arising from system parameter deviations and continuous wind resistance. Numerical simulations demonstrate that, under conditions involving payload mass deviations of up to 25% and stochastic wind disturbances, the proposed control method effectively reduces steady-state positioning errors, suppresses payload swing during operation, and significantly enhances the system’s energy dissipation efficiency and global robustness in uncertain environments.
Journal Article
Bayesian approach for network adjustment for gravity survey campaign: methodology and model test
The drift rate of relative gravimeters differs from time to time and from meter to meter. Furthermore, it is inefficient to estimate the drift rate by returning them frequently to the base station or stations with known gravity values during gravity survey campaigns for a large region. Unlike the conventional gravity adjustment procedure, which employs a linear drift model, we assumed that the variation of drift rate is a smooth function of lapsed time. Using this assumption, we proposed a new gravity data adjustment method by means of objective Bayesian statistical inference. Some hyper-parameters were used as trade-offs to balance the fitted residuals of gravity differences between station pairs and the smoothness of the temporal variation of the drift rate. We employed Akaike’s Bayesian information criterion (ABIC) to estimate these hyper-parameters. A comparison between results from applying the classical and the Bayesian adjustment methods to some simulated datasets showed that the new method is more robust and adaptive for solving problems caused by irregular nonlinear meter drift. The new adjustment method is capable of determining the time-varying drift rate function of any specific gravimeter and optimizing the weight constraints for every gravimeter used in a gravity survey. We also carried out an error analysis for the inverted gravity value at each station based on the marginal distribution. Finally, we used this approach to process actual gravity survey campaign data from an observation network in North China.
Journal Article