Regulatory Mechanisms of the Ihh/PTHrP Signaling Pathway in Fibrochondrocytes in Entheses of Pig Achilles Tendon

This study is aimed at exploring the effect of stress stimulation on the proliferation and differentiation of fibrochondrocytes in entheses mediated via the Indian hedgehog (Ihh)/parathyroid hormone-related protein (PTHrP) signaling pathway. Differential stress stimulation on fibrochondrocytes in entheses was imposed. Gene expression and protein levels of signaling molecules including collagen type I (Col I), Col II, Col X, Ihh, and PTHrP in the cytoplasm of fibrochondrocytes were detected. Ihh signal blocking group was set up using Ihh signaling pathway-specific blocking agent cyclopamine. PTHrP enhancement group was set up using PTHrP reagent. Ihh/PTHrP double intervention group, as well as control group, was included to study the regulatory mechanisms of the Ihh/PTHrP signaling pathway in fibrochondrocytes. Under low cyclic stress tensile (CTS), PTHrP, Col I, and Col II gene expression and protein synthesis increased. Under high CTS, Ihh and Col X gene expression and protein synthesis increased. Blocking Ihh signaling with cyclopamine resulted in reduced PTHrP gene expression and protein synthesis and increased Col X gene expression and protein synthesis. Ihh and PTHrP coregulate fibrochondrocyte proliferation and differentiation in entheses through negative feedback regulation. Fibrochondrocyte is affected by the CTS. This phenomenon is regulated by stress stimulation through the Ihh/PTHrP signaling pathway

Effect of Salt Tracer Dosages on the Mixing Process in the Water Model of a Single Snorkel Refining Furnace

The improvement in mixing conditions in a vacuum refining unit plays an important role in enhancing the purity and decarburization of molten steel. Mixing time is an important index to evaluate the operation efficiency of a metallurgical reactor. However, in water models, the effect of salt tracer dosages on the measured mixing time in a vacuum reactor is not clear. In this study, a water model of a Single Snorkel Refining Furnace (SSRF) was established to study the effect of salt solution tracer dosages on the mixing time of monitor points. The experimental results show that, in some areas at the top of the ladle, the mixing time decreases first and then increases when increasing the tracer dosage. Numerical simulation results show that, when the tracer dosage increases, the tracer flows downwards at a higher pace from the vacuum chamber to the bottom of the ladle. This may compensate for the injection time interval of large dosage cases. However, the mass fraction of the KCl tracer at the right side of the bottom is the highest, which indicates that there may be a dead zone. For the dimensionless concentration time curves and a 99% mixing time, at the top of the vacuum chamber, the curve shifts to the right side and the mixing time decreases gradually with the increase in tracer dosage. At the bottom of the ladle, with the increase in tracer dosage, the peak value of the dimensionless concentration time curve is increased slightly. The mixing time of the bottom of the ladle decreases significantly with the increase in tracer dosage. However, in the dead zone, the mixing time will increase when the tracer dosage is large. At the top of the ladle, the effect of the tracer dosage is not obvious. The mixing time of the top of the ladle decreases first and then increases when increasing the tracer dosage. In addition, the mixing time of the top of the ladle is the shortest, which means that sampling at the top of the ladle in industrial production cannot represent the entire mixing state in the ladle

Effect of Uniform and Non-Uniform Increasing Casting Flow Rate on Dispersion and Outflow Percentage of Tracers in Four Strand Tundishes under Strand Blockage Conditions

The flow field, tracer dispersion and uniformity of strands in two designs of four-strand tun-dishes under normal conditions and single-strand blockage conditions are studied by numerical simulation. The casting speed (flow rate) of strands are increasing uniformly or non-uniformly to improve the strand blockage condition. The uniformity of strands of the cases are evaluated by a novel outflow percentage analysis method. The results show that the flow field in the tundish does not change significantly when the single-strand is blocked or the casting flow rate is increased. After blockage of one strand, the consistency of each strand of u-shaped weir tundish is better than that of double-weir tundish. With the uniform increasing of the casting flow rate, the response time of each strand decreases and the outflow percentage increases. However, the uniformity of strands improved slightly in double-weir tundish but decreased in u-shaped tundish. For the double-weir tundish, significantly increasing the casting flow rate of the strand located in the blocked part by a factor of 1.5 and slightly increasing the casting flow rate of the other strands by a factor of 1.25, the consistency of each strand is the best. For the u-shaped weir tundish, the consistency of each strand is improved by non-uniform increasing of the casting flow rate of the strands. The flow rate of the strand located in the blocked part and the other strands is increased by a factor of 1.25, and 1.375 or 1.2 and 1.4 are the optimized cases

Effect of Uniform and Non-Uniform Increasing Casting Flow Rate on Dispersion and Outflow Percentage of Tracers in Four Strand Tundishes under Strand Blockage Conditions

The flow field, tracer dispersion and uniformity of strands in two designs of four-strand tun-dishes under normal conditions and single-strand blockage conditions are studied by numerical simulation. The casting speed (flow rate) of strands are increasing uniformly or non-uniformly to improve the strand blockage condition. The uniformity of strands of the cases are evaluated by a novel outflow percentage analysis method. The results show that the flow field in the tundish does not change significantly when the single-strand is blocked or the casting flow rate is increased. After blockage of one strand, the consistency of each strand of u-shaped weir tundish is better than that of double-weir tundish. With the uniform increasing of the casting flow rate, the response time of each strand decreases and the outflow percentage increases. However, the uniformity of strands improved slightly in double-weir tundish but decreased in u-shaped tundish. For the double-weir tundish, significantly increasing the casting flow rate of the strand located in the blocked part by a factor of 1.5 and slightly increasing the casting flow rate of the other strands by a factor of 1.25, the consistency of each strand is the best. For the u-shaped weir tundish, the consistency of each strand is improved by non-uniform increasing of the casting flow rate of the strands. The flow rate of the strand located in the blocked part and the other strands is increased by a factor of 1.25, and 1.375 or 1.2 and 1.4 are the optimized cases

Wireless Powered Intelligent Radio Environment with Non-Linear Energy Harvesting

—This paper investigates a wireless powered intelligent radio environment, where a fractional non-linear energy harvesting (NLEH) is proposed to enable an intelligent reflecting surface (IRS) assisted wireless powered Internet of Things (WP IoT) network. The IRS engages in downlink wireless energy transfer (WET) and uplink wireless information transfer (WIT). We aim to improve the overall performance of the considered network, and the approach is to maximize its sum throughput subject to constraints of two different types of IRS beam patterns and time durations. To solve the formulated problem, we first consider the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions to optimally design the time durations in closed-form. Then, a quadratic transformation (QT) is proposed to iteratively transform the fractional NLEH model into the subtractive form, where the IRS phase shifts are optimally derived by the Complex Circle Manifold (CCM) method in each iteration. Finally, numerical results are demonstrated to promote the proposed scheme in comparison to the benchmark schemes, where the benefits are induced by the IRS compared with the benchmark schemes

Predictive value of ultrasonic artificial intelligence in placental characteristics of early pregnancy for gestational diabetes mellitus

BackgroundTo explore the predictive value of placental features in early pregnancy for gestational diabetes mellitus (GDM) using deep and radiomics-based machine learning (ML) applied to ultrasound imaging (USI), and to develop a nomogram in conjunction with clinical features.MethodsThis retrospective multicenter study included 415 pregnant women at 11-13 weeks of gestation from two institutions: the discovery group from center 1 (n=305, control group n=166, GDM group n=139), and the independent validation cohort (n=110, control group n=57, GDM group n=53) from center 2. The 2D USI underwent pre-processed involving normalization and resampling. Subsequently, the study performed screening of radiomics features with Person correlation and mutual information methods. An RBF-SVM model based on radiomics features was constructed using the five-fold cross-validation method. Resnet-50 as the backbone network was employed to learn the region of interest and constructed a deep convolutional neural network (DLCNN) from scratch learning. Clinical variables were screened using one-way logistic regression, with P<0.05 being the threshold for statistical significance, and included in the construction of the clinical model. Nomogram was built based on ML model, DLCNN and clinical models. The performance of nomogram was assessed by calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).ResultsThe AUCs for the ML model in the discovery cohort and independent validation cohort were 0.91 (0.88-0.94) and 0.86 (0.79-0.93), respectively. And 0.65 (0.59-0.71), 0.69 (0.59-0.79) for the DLCNN, 0.66 (0.59-0.72), 0.66 (0.55-0.76) for the clinical model, respectively. The nomogram exhibited the highest performance with AUCs of 0.93 (0.90-0.95) and 0.88 (0.81-0.94) The receiver operating characteristic curve (ROC) proved the superiority of the nomogram of clinical utility, and calibration curve showed the goodness of fit of the model. The DCA curve indicated that the nomogram outperformed other models in terms of net patient benefit.ConclusionsThe study emphasized the intrinsic relationship between early pregnancy placental USI and the development of GDM. The use of nomogram holds potential for clinical applications in predicting the development of GDM

Assessment of Inclusion Removal Ability in Refining Slags Containing Ce₂O₃

The elimination of inclusions in steelmaking processes has been widely studied. The removal of inclusions by slags containing the rare earth oxide Ce2O3 are studied using an integrated numerical model. The integrated model involves the inclusion motion model, interfacial tension calculation model, surface tension calculation model of slag, and the mass action concentration model, based on ion and molecule coexistence theory. The motion behaviors of both solid Al2O3 inclusions and 50%wtAl2O3–50%wtCaO liquid inclusions of varied sizes at CaO-Ce2O3-SiO2-Al2O3(-MgO) slag systems are evaluated. The results show that it is more difficult to remove the inclusions with smaller sizes and in slag with a higher viscosity. Liquid inclusions are more difficult to remove than solid inclusions. It is found that the CaO-Ce2O3-SiO2-Al2O3-MgO refining slag shows a better ability to remove Al2O3 inclusions than that of the CaO-SiO2-Al2O3-MgO slag. The reason for this is that the addition of the rare earth oxide Ce2O3 can decrease the viscosity of slags, as well as improving the wetting effects of slags on Al2O3 inclusions. For two slags systems, the CaO-Ce2O3-SiO2-Al2O3-MgO slag system shows a better ability to remove Al2O3 inclusions than the CaO-Ce2O3-SiO2-Al2O3 slag system. The addition of 5% to 8% Ce2O3 in a CaO-SiO2-Al2O3-MgO slag is an optimized case for industrial applications

The lncRNA MACC1-AS1 promotes gastric cancer cell metabolic plasticity via AMPK/Lin28 mediated mRNA stability of MACC1

Abstract Background Metabolic plasticity has been increasingly thought to be a determinant of tumor growth and metastasis. MACC1, a transcriptional regulator of MET, was recognized as an oncogene in gastric cancer (GC); however, its transcriptional or post-translational regulation was not clear. We previously reported the metabolic role of MACC1 in glycolysis to promote GC progression. MACC1-AS1 is the antisense lncRNA of MACC1, yet its function was previously unknown. Methods We profiled and analyzed the expression of MACC1-AS1 utilizing the TCGA database as well as in situ hybridization using 123 pairs of GC tissues and matched adjacent normal gastric mucosa tissues (ANTs). The biological role of MACC1-AS1 in cell growth and metastasis was determined by performing in vitro and in vivo functional experiments. Glycolysis and antioxidant capabilities were assayed to examine its metabolic function. Further, the specific regulatory effect of MACC1-AS1 on MACC1 was explored transcriptionally and post-transcriptionally. Results MACC1-AS1 was shown to be expressed significantly higher in GC tissues than in ANTs, which predicted poor prognosis in GC patients. MACC1-AS1 promoted GC cell proliferation and inhibited cell apoptosis under metabolic stress. Mechanistically, MACC1-AS1 stabilized MACC1 mRNA and post-transcriptionally augmented MACC1 expression. Further, MACC1-AS1 was shown to mediate metabolic plasticity through MACC1 upregulation and subsequent enhanced glycolysis and anti-oxidative capabilities, and this was suggested to be coordinated by the AMPK/Lin28 pathway. Conclusions Elevated expression of MACC1-AS1 in gastric cancer tissues is linked to poor prognosis and promotes malignant phenotype upon cancer cells. MACC1-AS1 is elevated under metabolic stress and facilitates metabolic plasticity by promoting MACC1 expression through mRNA stabilization. Our study implicates lncRNA MACC1-AS1 as a valuable biomarker for GC diagnosis and prognosis