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Macrophage migration inhibitory factor (MIF), a multifunctional cytokine, is secreted by various cells and participates in inflammatory reactions, including innate and adaptive immunity. There are some evidences that MIF is involved in many vitreoretinal diseases. For example, MIF can exacerbate many types of uveitis; measurements of MIF levels can be used to monitor the effectiveness of uveitis treatment. MIF also alleviates trauma-induced and glaucoma-induced optic nerve damage. Furthermore, MIF is critical for retinal/choroidal neovascularization, especially complex neovascularization. MIF exacerbates retinal degeneration; thus, anti-MIF therapy may help to mitigate retinal degeneration. MIF protects uveal melanoma from attacks by natural killer cells. The mechanism underlying the effects of MIF in these diseases has been demonstrated: it binds to cluster of differentiation 74, inhibits the c-Jun N-terminal kinase pathway, and triggers mitogen-activated protein kinases, extracellular signal-regulated kinase-1/2, and the phosphoinositide-3-kinase/Akt pathway. MIF also upregulates Toll-like receptor 4 and activates the nuclear factor kappa-B signaling pathway. This review focuses on the structure and function of MIF and its receptors, including the effects of MIF on uveal inflammation, retinal degeneration, optic neuropathy, retinal/choroidal neovascularization, and uveal melanoma.

Weight information plays a pivotal role in sturgeon breeding and production management. However, manual measurement is time consuming and labor intensive due to the immense size of the sturgeon. Due to the unique body shape of the sturgeon, traditional image segmentation algorithms struggle to extract the necessary features from sturgeon images, which makes them unsuitable for this particular species. Moreover, accurately measuring weight in an occlusion environment is difficult. To address these challenges, an improved YOLOv5s model with a context augmentation module, focal-efficient intersection over union, and soft non-maximum suppression was proposed in this paper. To validate the model’s feasibility, the improved YOLOv5s model was first pre-trained using the sturgeon dataset, followed by further training on the occlusion dataset for segmentation tasks. Based on the phenotypic data obtained from the improved model, a multilayer perceptron method was used to estimate the sturgeon’s weight accurately. Experimental results demonstrated that the average precision of the improved YOLOv5s model reached 89.80% under occlusion conditions, and the correlation coefficient of noncontact weight measurement results reached 89.80%. The experimental results showed that the improved algorithm effectively performs segmentation of sturgeon in occlusion conditions and can accurately estimate the mass.

The sturgeon is an important commercial aquaculture species in China. The measurement of sturgeon mass plays a remarkable role in aquaculture management. Furthermore, the measurement of sturgeon mass serves as a key phenotype, offering crucial information for enhancing growth traits through genetic improvement. Until now, the measurement of sturgeon mass is usually conducted by manual sampling, which is work intensive and time consuming for farmers and invasive and stressful for the fish. Therefore, a noninvasive volume reconstruction model for estimating the mass of swimming sturgeon based on RGB-D sensor was proposed in this paper. The volume of individual sturgeon was reconstructed by integrating the thickness of the upper surface of the sturgeon, where the difference in depth between the surface and the bottom was used as the thickness measurement. To verify feasibility, three experimental groups were conducted, achieving prediction accuracies of 0.897, 0.861, and 0.883, which indicated that the method can obtain the reliable, accurate mass of the sturgeon. The strategy requires no special hardware or intensive calculation, and it provides a key to uncovering noncontact, high-throughput, and highly sensitive mass evaluation of sturgeon while holding potential for evaluating the mass of other cultured fishes.

Abstract Background Percutaneous coronary intervention (PCI) is a safe and effective therapy for patients with obstructive coronary artery disease (CAD). We aimed to assess the correlation between the success rate of angiography and the maximum insertion length and resistance of a soft-tipped guidewire. Methods Five hundred twenty-one patients were treated by successful radial artery puncture. According to whether the guidewire resistance, the patients were divided to three groups. 17 patients were maximum insertion length of guidewire ≤ 30 cm when resistance was encountered (group 1). 17 patients were maximum insertion length of guidewire between 30 and 45 cm when resistance was encountered (group 2). 487 patients were no resistance encountered (group 3). Results The coronary angiography success rates of group 1, 2, and 3 were 52.94%, 47.05%, 98.97%, respectively. Typically, angiography can be completed in patients with Ω-shaped, S-shape or Z-shaped tortuosity. Conclusions The maximum insertion length of straight guidewire and resistance can be used to determine radial artery status. The radial artery tortuosity or spasm significantly affects the success rate of coronary angiography.

Aim. Pirfenidone (PFD), an antifibrotic drug, has various beneficial functions such as antioxidant, antifibrotic, and anti-inflammatory effects. This study aimed to explore the molecular mechanisms underlying how PFD modulates retinal pigment epithelial (RPE) cells involved in neovascularization and subretinal fibrosis. Methods. ARPE-19 cell lines were treated with transforming growth factor-beta 2 (TGF-β2) alone or in combination with PFD. RPE cell viability, as a consequence of PFD use, was determined by the CCK-8 assay. Cell migration was assessed by the wound closure assay and quantified by the Image J software. Protein expression of the following markers was measured by the western blot analysis: an epithelial cell marker and E-cadherin; mesenchymal cell markers, fibronectin, matrix metalloprotein-9 (MMP-9), and alpha-smooth muscle actin (α-SMA); a fibrotic marker and connective tissue growth factor (CTGF); an angiogenesis marker and vascular endothelial growth factor (VEGF); NF-κB/Snail. The mRNA levels of fibronectin and α-SMA were determined by quantitative real-time PCR. VEGF was quantitatively measured by the enzyme-linked immunosorbent assay. Results. The cell viability assay revealed that PFD had no significant cytotoxic effect on RPE cells at concentrations of less than 1 mg/mL. The cell scratch assay showed that TGF-β2 stimulation significantly improved the migration of RPE cells and that PFD attenuated this effect. PFD significantly inhibited the TGF-β2-induced protein expression of E-cadherin and increased the TGF-β2-induced protein expression of fibronectin, MMP-9, α-SMA, CTGF, and VEGF in ARPE-19 cells. The mRNA expression of fibronectin and α-SMA was inhibited by PFD in TGF-β2-inducedARPE-19 cells. Additionally, the increased intracellular and supernatant expression of VEGF protein was suppressed by PFD. Mechanistically, RPE cells treated with PFD + TGF-β2 exhibited a decrease in phosphorylation of the NF-κB P65 subunit and activation of Snail, compared with the RPE cells treated with TGF-β2 alone. Conclusion. PFD ameliorated TGF-β2-induced neovascularization and fibrosis by suppressing the NF-κB/Snail signaling pathway. Therefore, PFD may be a potential drug in the treatment of age-related macular degeneration.

In order to improve the control performance of the micro gas turbine in the full range of operating conditions, this paper proposes a new control technique based on the hybridization of improved particle swarm optimization algorithm and cuckoo search algorithm (HIPSO_CS) to tune the fuzzy PID controller parameters. Firstly, the traditional particle swarm optimization algorithm is improved by linearly decreasing the number of particles and the value of the inertia weight. Secondly, the cuckoo algorithm’s local random walk strategy is introduced into the particle swarm optimization algorithm to enhance particles’ diversity. Through comparing with traditional optimization algorithms, the proposed HIPSO_CS algorithm is verified to have high convergence accuracy and fast iteration speed. To improve the dynamic response performance of the micro gas turbine, controllers with different structures are designed, and a comparative study of HIPSO_CS optimized Fuzzy PID/PID/PI is presented. The simulation results show that the micro gas turbine controlled by the fuzzy PID controller has a rapid response to fuel flow, minor speed overshoot, and shorter stabilization time during load increase or decrease. In addition, the designed control method can also achieve significant control effects under load disturbance, model parameter changes, and extreme operating condition.

Previously we showed the generation of a protein trap library made with the gene-break transposon (GBT) in zebrafish (Danio rerio) that could be used to facilitate novel functional genome annotation towards understanding molecular underpinnings of human diseases (Ichino et al, 2020). Here, we report a significant application of this library for discovering essential genes for heart rhythm disorders such as sick sinus syndrome (SSS). SSS is a group of heart rhythm disorders caused by malfunction of the sinus node, the heart’s primary pacemaker. Partially owing to its aging-associated phenotypic manifestation and low expressivity, molecular mechanisms of SSS remain difficult to decipher. From 609 GBT lines screened, we generated a collection of 35 zebrafish insertional cardiac (ZIC) mutants in which each mutant traps a gene with cardiac expression. We further employed electrocardiographic measurements to screen these 35 ZIC lines and identified three GBT mutants with SSS-like phenotypes. More detailed functional studies on one of the arrhythmogenic mutants, GBT411, in both zebrafish and mouse models unveiled Dnajb6 as a novel SSS causative gene with a unique expression pattern within the subpopulation of sinus node pacemaker cells that partially overlaps with the expression of hyperpolarization activated cyclic nucleotide gated channel 4 (HCN4), supporting heterogeneity of the cardiac pacemaker cells.

The colorimetric conversion of wide-color-gamut cameras plays an important role in the field of wide-color-gamut displays. However, it is rather difficult for us to establish the conversion models with desired approximation accuracy in the case of wide color gamut. In this paper, we propose using an optimal method to establish the color conversion models that change the RGB space of cameras to the XYZ space of a CIEXYZ system. The method makes use of the Pearson correlation coefficient to evaluate the linear correlation between the RGB values and the XYZ values in a training group so that a training group with optimal linear correlation can be obtained. By using the training group with optimal linear correlation, the color conversion models can be established, and the desired color conversion accuracy can be obtained in the whole color space. In the experiments, the wide-color-gamut sample groups were designed and then divided into different groups according to their hue angles and chromas in the CIE1976L*a*b* space, with the Pearson correlation coefficient being used to evaluate the linearity between RGB and XYZ space. Particularly, two kinds of color conversion models employing polynomial formulas with different terms and a BP artificial neural network (BP-ANN) were trained and tested with the same sample groups. The experimental results show that the color conversion errors (CIE1976L*a*b* color difference) of the polynomial transforms with the training groups divided by hue angles can be decreased efficiently.

Ingredient amounts are crucial for food-oriented health systems, but this information is seldom used in food-oriented health systems due to the difficulty of fetching it from online recipes. This study proposes a predictive model named DeepRecipes to extract ingredient amounts from online textual recipes. The model predicts ingredient amounts according to a given recipe’s name and listed ingredients. We train the model on a small set of recipes containing all ingredients and their corresponding amounts. As we can extract the recipe names and ingredients from almost all online recipes, the proposed model can potentially recover ingredient amounts for massive online recipes. We first trained the model on a small set of recipes containing all ingredients and their corresponding amounts. Then, we compared ten models as references for their performances. The performance of DeepRecipes exceeds those of all the comparison models. The model’s mean absolute error (MAE) and mean absolute percentage error (MAPE) are $3.96\times {10}^{-1}$ and 18.57%, respectively, and its APEs are lower than 50% in more than 95% of the total predictions. This accuracy is sufficient for providing rough ingredient amount estimations for food-oriented health systems.

The failure of many aircraft structures and materials is caused by the accumulation of fatigue damage under variable-amplitude cyclic loading wherein the damage evolution of materials is complicated. Therefore, to study the cumulative fatigue damage of materials under variable-amplitude cyclic loading, a new nonlinear fatigue damage accumulation model is proposed based on the ecological quality dissipation of materials by considering the effects of load interaction and sequence. The proposed new model is validated by the test data obtained for three kinds of material under multilevel fatigue loading. Compared with the Miner model and Kwofie model, the proposed model can more effectively analyse the accumulative damage and predict fatigue life of different materials under variable-amplitude cyclic loading than others. The study provides a basis for predicting fatigue life accurately and determining reasonable maintenance periods of aircraft structures.

In order to improve the prediction accuracy of foundation pit deformation, an improved optimization algorithm of supply and demand-exponential power product foundation pit deformation prediction model (ISDO-EPP model) is proposed. Through six standard test functions and three application examples, the optimization ability of the ISDO algorithm is verified, and the optimization results are compared with those of basic supply demand optimization algorithm (SDO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), moth swarm algorithm (MSA), and particle swarm optimization algorithm (PSO). Taking the settlement prediction of three foundation pits as an example, the delay time and embedding dimension of each case are determined by autocorrelation function method and false nearest neighbor method, and input and output vectors are constructed to train and predict each model. The results show that the search ability of the ISDO algorithm is better than that of SDO and other five algorithms, and the ISDO algorithm has better search accuracy, global search ability, and robustness. The absolute values of average relative errors of the ISDO-EPP model for three cases are 0.73%, 3.36%, and 1.33%, respectively, which are better than ISDO-SVM and ISDO-BP models. It shows that the ISDO algorithm can effectively optimize the parameters of the EPP model, and the ISDO-EPP model is feasible and effective for deformation prediction.

Because of its powerful genetics, the adult zebrafish has been increasingly used for studying cardiovascular diseases. Considering its heart rate of ~100 beats per minute at ambient temperature, which is very close to human, we assessed the use of this vertebrate animal for modeling heart rhythm disorders such as sinus arrest (SA) and sick sinus syndrome (SSS). We firstly optimized a protocol to measure electrocardiogram in adult zebrafish. We determined the location of the probes, implemented an open-chest microsurgery procedure, measured the effects of temperature, and determined appropriate anesthesia dose and time. We then proposed an PP interval of more than 1.5 seconds as an arbitrary criterion to define an SA episode in an adult fish at ambient temperature, based on comparison between the current definition of an SA episode in humans and our studies of candidate SA episodes in aged wild-type fish and Tg(SCN5A-D1275N) fish (a fish model for inherited SSS). With this criterion, a subpopulation of about 5% wild-type fish can be considered to have SA episodes, and this percentage significantly increases to about 25% in 3-year-old fish. In response to atropine, this subpopulation has both common SSS phenotypic traits that are shared with the Tg(SCN5A-D1275N) model, such as bradycardia; and unique SSS phenotypic traits, such as increased QRS/P ratio and chronotropic incompetence. In summary, this study defined baseline SA and SSS in adult zebrafish and underscored use of the zebrafish as an alternative model to study aging-associated SSS.

The platelet aggregation and 5-HT release by washed platelet from coronary heart disease patients following platelet activating factor (PAF) treatment were detected by turbidimetry and O-phthalaldehyde assay. The free calcium concentration in the platelets was measured with the fura-2/AM probe fluorescent technique. Results showed safflower yellow could inhibit the PAF induced washed platelet aggregation and 5-HT release, which were in a safflor-yellow-dose dependent manner. When the PAF was 2.0×10-9 mol/L, the inhibition rate of platelet aggregation was 26.2%, 41.3%, 58.1%, 81.2%, and the inhibition rate of 5-HT release was 3.7%, 11.9%, 29.9% and 54.4% after treatment with safflower yellow at 0.21, 0.42, 0.85 and 1.69 g/L, respectively. The study concludes safflower yellow can inhibit the PAF induced platelet aggregation, 5-HT release by platelets and elevation of free calcium in platelets.