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Abstract In this study, we have proposed an anisotropic microstructure in La-Fe-Si magnetocaloric composites for thermal management. This is vital to the rapid heat exchange and high working efficiency in magnetic refrigerator system. We demonstrate the anisotropic microstructure in composites can be fabricated via powder metallurgy in this work. By adjusting the particle size of the 1:13 phase, the introduced reinforcing phase with rheological property can effectively deform and anisotropic microstructure can be obviously observed. This can be attributed to the tailored stress distribution in cubic-anvil-type pressure apparatus. The element diffusion between the two phases was also discussed in this paper, taking into account the influence of particle size. Such anisotropic microstructure causes some other anisotropic physical properties in the composite, such as mechanical strength. The compressive measurements along the axial direction exhibit superior mechanical properties (~ 3.5% for strain and ~ 350 MPa for strength) compared to those along the radial direction. Attributed to the stress buffer-effect provided by the introduced ductile phase, magnetocaloric effect (magnetic entropy change ~ 7.8 J/kg K) can be maintained in the La-Fe-Si composite.

Machine learning has exhibited high efficiency in designing concrete. However, collecting the dataset for training machine learning models is challenging. To address this challenge, this paper develops an approach to collect concrete design data automatically based on information extraction techniques. The approach enables machine learning models to automatically track, extract, and learn knowledge embedded in data from relevant publications. The approach has been incorporated into AI-assisted design of low-carbon cost-effective ultra-high-performance concrete (UHPC) via integrating the capabilities of automatically collecting and processing data, predicting UHPC properties, and optimizing UHPC properties regarding the material cost, carbon footprint, and compressive strength. A self-updating mechanism is imparted to continuously learn available data. Such a mechanism enables the self-updatable automatic discovery of low-carbon cost-effective UHPC. The results showed increasing prediction accuracy and optimization performance of the proposed approach over time when more knowledge was learned from new data, therefore accelerating the design of UHPC.

High-entropy alloys (HEAs) have gained significant attentions in recent years, due to their unique properties derived from the combination of multiple elements in equimolar or near-equimolar ratios. The mechanical properties of HEAs are influenced by microstructural characteristics. In this study, MnCrFeCoNi HEA ribbons were produced using a technique called melt spinning, for which the wheel speed was adjusted to control the undercooling levels. The rapid solidification process under undercooling condition resulted in refined grain sizes to micrometers in the ribbons. One notable feature was the appearance of twin boundaries, which especially accounted for approximately 7.36 % of the microstructure for the ribbons produced at a wheel speed of 10 m/s. For the ribbons with thickness of micrometer scale, the mechanical properties (ultimate tensile strength up to 2.5 GPa and hardness up to 300 MPa) were analyzed by microstructure (grain boundaries and homogeneity) and exterior factors (e.g. thickness). Overall, this study provides a new approach for tailoring the microstructures and mechanical properties of HEAs via melt spinning technique. The HEA ribbons present a novel form that could potentially broaden the scope of applications for these materials.

Inhibition of triple-negative breast cancer metastasis has long been a challenge, mainly due to the difficulty in identifying factors that contribute to this process. In this study, freshly isolated triple-negative breast cancer biopsied cells obtained from consenting patients were subjected to flow cytometry and bioinformatic analysis to identify three endothelial cell subclusters: EC (ATP1B3), EC (HSPA1B), and EC (KRT7) in the tumor microenvironment. These endothelial cell subclusters exhibited distinguishing biological features. Based on differentially expressed genes derived from the subclusters, gene set enrichment analysis showed that EC (ATP1B3) and EC (HSPA1B) contribute to the process of metastasis, for example, in fibrosarcoma and anaplastic carcinoma. In this study, we identified the heterogeneity of endothelial cells in the human breast cancer and have provided insights into its role in metastasis.

The acoustic signal generated by mechanical motion contains the information of its motion state, but when the signal-to-noise ratio (SNR) is low, the accuracy of real-time monitoring mechanical motion state by the acoustic signal is low. This study proposes an adaptive noise reduction method based on the dislocation superposition method (DSM), which can realize the adaptive noise reduction and the extraction of fault a component from the automobile engine abnormal noise signal of low SNR. Firstly, the wavelet coefficients of engine abnormal noise signal are obtained by continuous wavelet transform (CWT), and the fault feature points of the abnormal noise signal in each period are extracted by setting hard threshold function, window function, and feature points extraction algorithm. Then, the signal segments containing fault components are obtained by using the position of feature points to extend the length of the fault component forward and backward, respectively, and Pearson’s correlation is calculated by traversal to determine the starting superposition point of each signal segment containing fault components. Finally, the signal segments of the odd group and even group are selected for superposition calculation. When the superposition stop condition is not satisfied, the number of superpositions increased until the stop condition is satisfied, and the superposition signal can be used as a fault component. The experimental results show that, compared with the improved DSM, this method has a good effect on the noise reduction and extraction of fault components of automobile engine cylinder knocking fault, and the effectiveness of this method is verified. This method is used to reduce the noise and extract the fault components of automobile engine cylinder missing fault and knock fault, and good results are obtained.

Background/Aims: Transforming growth factor beta 1 (TGF-β1) plays a critical role in the pathogenesis of glomerulosclerosis. The purpose of this study was to examine the effects of inhibition of miR-155 on podocyte injury induced by TGF-β1 and to determine further molecular mediators involved in the effects of miR-155. Methods: Conditionally immortalized podocytes were cultured in vitro and they were divided into four groups: control; TGF-β1 treatment; TGF-β1 with miR-155 knockdown [using antisense oligonucleotides against miR-155 (ASO-miR-155)] and TGF-β1 with negative control antisense oligonucleotides (ASO-NC). Real time RT-PCR and Western blot analysis were employed to determine the mRNA and protein expression of nephrin, desmin and caspase-9, respectively. Flow cytometry was used to examine the apoptotic rate of podocytes and DAPI fluorescent staining was used to determine apoptotic morphology. In addition, we examined the levels of miR-155, TGF-β1, nephrin, desmin and caspase-9 in glomerular tissues of nephropathy induced by intravenous injections of adriamycin in rats. Results: mRNA and protein expression of desmin and caspase-9 was increased in cultured TGF-β1-treated podocytes, whereas nephrin was decreased as compared with the control group. Importantly, miR-155 knockdown significantly attenuated upregulation of desmin and caspase-9, and alleviated impairment of nephrin induced by TGF-β1. Moreover, the number of apoptotic podocytes was increased after exposure to TGF-β1 and this was alleviated after miR-155 knockdown. Knocking down miR-155 also decreased an apoptosis rate of TGF-β1-treated podocytes. Note that negative control antisense oligonucleotides failed to alter an increase of the apoptosis rate in TGF-β1-treated podocytes. Consistent with in vitro results, expression of miR-155, TGF-β1, desmin and caspase-9 was increased and nephrin was decreased in glomerular tissues with nephropathy in vivo experiments. Conclusions: TGF-β1 impairs the protein expression of nephrin and amplifies the protein expression of desmin and caspase -9 via miR-155 signal pathway. Inhibition of miR-155 alleviates these changes in podocytes-treated with TGF-β1 and attenuated apoptosis of podocytes. Our data suggest that miR-155 plays a role in mediating TGF-β1-induced podocyte injury via nephrin, desmin and caspase-9. Results of the current study also indicate that blocking miR-155 signal has a protective effect on podocyte injury. Targeting one or more of these signaling molecules may present new opportunities for treatment and management of podocyte injury observed in glomerulosclerosis.

Objectives: This study aims to investigate the positive detection rate and predictive value of autoantibodies, including anti-double stranded deoxyribonucleic acid (anti-dsDNA) antibodies, anti-histone antibodies (AHAs), anti-ribosomal (anti-Rib) P antibodies, anti-Smith (anti-Sm) antibodies, anti-UI ribonucleoprotein (anti-U1RNP) antibodies, anti-Sjogren's syndrome type A antibodies and anti-Sjogren's syndrome type B antibodies, on organ damage in patients with systemic lupus erythematous (SLE). Patients and methods: A total of 225 patients with SLE (37 males, 188 females; mean age 37.4±15.9 years; range, 7 to 80 years) were evaluated retrospectively. Statistical analysis was performed to obtain the positive detection rate of autoantibodies and to investigate the predictive value. Results: There were statistically significant differences of positive anti-dsDNA antibodies in renal damage, photosensitization, hematological abnormalities and serositis (p<0.05) and a statistically significant difference of positive AHAs in photosensitization (p<0.05). There was statistically significant difference of positive anti-UIRNP antibodies in renal damage (p<0.05). There were also statistically significant differences of positive anti-Smith antibodies in renal damage, arthritis, photosensitization, oral ulcers, hematological abnormalities and serositis (p<0.05) and of positive anti-Rib antibodies in renal damage, arthritis, photosensitization, malar rash, hematological abnormalities and serositis (p<0.05). However, there were no statistically significant differences of positive anti-Sjogren's syndrome type B antibodies and anti-Sjogren's syndrome type A antibodies in renal damage, arthritis, malar rash, neuropsychiatric disorders, hematological abnormalities and serositis (p>0.05). Conclusion: Autoantibody spectrum is an important serological basis for SLE diagnosis. There are differences in the autoantibodies distribution of SLE patients with different organ damage, suggesting a certain clinical value for prediction of organ damage in SLE. [ABSTRACT FROM AUTHOR]