MiR-338-3p Is a Biomarker in Neonatal Acute Respiratory Distress Syndrome (ARDS) and Has Roles in the Inflammatory Response of ARDS Cell Models

To investigate the association between serum miR-338-3p levels and neonatal acute respiratory distress syndrome (ARDS) and its mechanism. The relative miR-338-3p expression in serum was detected by quantitative real-time RT-PCR. Interleukin-1beta (IL-1β), IL-6, and tumor necrosis factor-alpha (TNF-α) levels were detected by ELISAs. A receiver operating characteristic (ROC) curve analysis of serum miR-338-3p evaluated the diagnosis of miR-338-3p in neonatal ARDS. Pearson’s correlation analysis evaluated the correlation between serum miR-338-3p and neonatal ARDS clinical factors. Flow cytometry evaluated apoptosis, and a CCK-8 assay assessed cell viability. A luciferase assay evaluated the miR-338-3p/AKT3 relationship. The miR- 338-3p expression was decreased in neonatal ARDS patients and in lipopolysaccharide (LPS)-treated cells. The ROC curve showed the accuracy of miR-338-3p for evaluating neonatal ARDS patients. The correlation analysis demonstrated that miR-338-3p was related to PRISM-III, PaO2/FiO2, oxygenation index, IL-1β, IL-6, and TNF-α in neonatal ARDS patients. MiR-338-3p overexpression inhibited the secretion of inflammatory components, stifled cell apoptosis, and LPS-induced advanced cell viability. The double-luciferase reporter gene experiment confirmed that miR-338-3p negatively regulates AKT3 mRNA expression. Serum miR-338-3p levels were related to the diagnosis and severity of neonatal ARDS, which may be attributed to its regulatory effect on inflammatory response in ARDS

MicroRNA-33b inhibits liver cancer cell proliferation, migration and invasion via down-regulation of Fli-1 and MMP-2 protein expressions

Purpose: To study the influence of microRNA-33b (miR-33b) on liver cancer cell proliferation, migration and invasiveness, and the mechanism involved. Methods: MicroRNA-33b or Fli-1 overexpression plasmid was transfected into liver cancer (SMMC7721) cells. Cell proliferation, migration, and invasiveness were determined using cell counting kit 8 (CCK-8), scratch test, and Transwell invasion assay, respectively. The amounts of miR-33b and Fli-1 in liver cancer tissues,  paracancerous normal tissues, and miR-33b overexpression and control groups were measured using qRT-PCR, while protein concentration of matrix metalloproteinase 2 (MMP-2) was assayed using Western blotting. Results: Fli-1 protein was markedly upregulated in liver cancerous cells, relative to paracancerous normal tissues (p < 0.05). MicroRNA-33b protein expression was also significantly upregulated in miR33b overexpression group, but the corresponding Fli-1 expression was downregulated in miR-33b overexpression group, relative to control (p < 0.05). MicroRNA-33b overexpression significantly and time-dependently inhibited SMMC7721 cell proliferation and migration, but it reduced the degree of apoptosis (p < 0.05). Liver cancer (SMMC7721) cells in miR-33b overexpression group were less invasive than the control group (p < 0.05). Similarly, miR-33b overexpression significantly downregulated MMP-2 protein expression in SMMC7721cells (p < 0.05). Conclusion: Overexpression of miR-33b suppresses the proliferation, migratory and invasive potential of hepatic cancer cells via down-regulation of Fli-1 and MMP-2 protein expression. This finding may be useful in the identification of new liver cancer drugs

Artificial trans-encoded small non-coding RNAs specifically silence the selected gene expression in bacteria

Recently, many small non-coding RNAs (sRNAs) with important regulatory roles have been identified in bacteria. As their eukaryotic counterparts, a major class of bacterial trans-encoded sRNAs acts by basepairing with target mRNAs, resulting in changes in translation and stability of the mRNA. RNA interference (RNAi) has become a powerful gene silencing tool in eukaryotes. However, such an effective RNA silencing tool remains to be developed for prokaryotes. In this study, we described first the use of artificial trans-encoded sRNAs (atsRNAs) for specific gene silencing in bacteria. Based on the common structural characteristics of natural sRNAs in Gram-negative bacteria, we developed the designing principle of atsRNA. Most of the atsRNAs effectively suppressed the expression of exogenous EGFP gene and endogenous uidA gene in Escherichia coli. Further studies demonstrated that the mRNA base pairing region and AU rich Hfq binding site were crucial for the activity of atsRNA. The atsRNA-mediated gene silencing was Hfq dependent. The atsRNAs led to gene silencing and RNase E dependent degradation of target mRNA. We also designed a series of atsRNAs which targeted the toxic genes in Staphyloccocus aureus, but found no significant interfering effect. We established an effective method for specific gene silencing in Gram-negative bacteria

Research on Fractal Characterization of Data Transmission Performance of Hard Disk

The data transfer rate is the traditional criterion for evaluating the overall performance of a hard disk. In this paper, the data transmission performance of hard disk was characterized based on fractal theory. The traditional mechanical hard disks and solid state disks with different capacities and specifications were tested and the corresponding signal graph of data transfer was analysed for the calculation of fractal dimension D. The results indicate that the process of hard disk data transfer has fractal characteristics; the fractal dimension D increases with the increase of the average transfer rate and the rotating speed of mechanical hard disk. However, there seems no direct correspondence between the fractal dimension D and the capacity of the hard disk; the larger the floating range of data transmission, the greater value of fractal dimension D

Research on Fractal Characterization of Data Transmission Performance of Hard Disk

The data transfer rate is the traditional criterion for evaluating the overall performance of a hard disk. In this paper, the data transmission performance of hard disk was characterized based on fractal theory. The traditional mechanical hard disks and solid state disks with different capacities and specifications were tested and the corresponding signal graph of data transfer was analysed for the calculation of fractal dimension D. The results indicate that the process of hard disk data transfer has fractal characteristics; the fractal dimension D increases with the increase of the average transfer rate and the rotating speed of mechanical hard disk. However, there seems no direct correspondence between the fractal dimension D and the capacity of the hard disk; the larger the floating range of data transmission, the greater value of fractal dimension D

Tribocorrosion of Fe-Based Amorphous Coating in Simulated Body Fluids

An arc-sprayed Fe-based amorphous coating with high hardness and low porosity was prepared. A tribo-electrochemical approach was used to study the tribocorrosion behaviour of the amorphous coating. The volume wear losses of the amorphous coating with different sliding paths in dry, 0.9% NaCl, and PBS solutions were measured, as well as the friction coefficient and the polarization curves in static and dynamic situations. The volume wear loss with the linear sliding path is higher than those with circular and triangle paths. Since the ions in the solution accelerate the wear, the volume loss of the amorphous coating in 0.9% NaCl solution is higher than dry and in PBS solution. The wear loss of 316L stainless steel (SS) is about 1.7 times more than the amorphous coating in PBS solution under a load of 10 N. Although 316L SS possesses better corrosion resistance than the amorphous coating in the static situation, the corrosion resistance of the amorphous coating is much better than that of 316L SS during tribocorrosion. The wear mechanism of the amorphous coating includes abrasive wear accompanying with corrosive wear. For the intrinsic superior corrosion resistance, amorphous coating shows the prospective tribology application in the corrosion environment

CMM-Based Volumetric Assessment Methodology for Polyethylene Tibial Knee Inserts in Total Knee Replacement

Total knee replacement is a common surgical procedure in orthopaedics. Accurate volumetric wear assessment of the polyethylene knee inserts has been an essential subject for improving the longevity. A new CMM-based methodology was presented to determine volumetric material loss based on curve surface fitting without prewear data, CAD model, or original design of drawings. Both computational and experimental simulated volume removal tests were run to validate the methodology by comparing with the gravimetric measurements. The volume and linear wear of the tibial inserts were calculated using the presented method based on the coordinates acquired by the CMM. The results indicate that the methodology is adequate for clinically retrieved tibial inserts where no prewear data are provided. This technique can also be used for biotribological study of other polyethylene components, since wear and damage can be assessed visually and volumetrically

Comparison of Different Multispectral Sensors for Photosynthetic and Non-Photosynthetic Vegetation-Fraction Retrieval

It is very difficult and complex to acquire photosynthetic vegetation (PV) and non-PV (NPV) fractions (fPV and fNPV) using multispectral satellite sensors because estimations of fPV and fNPV are influenced by many factors, such as background-noise interference of pixel-, spatial-, and spectral-scale effects. In this study, comparisons between Sentinel-2A Multispectral Instrument (S2 MSI), Landsat-8 Operational Land Imager (L8 OLI), and GF1 Wide Field View (GF1 WFV) sensors for retrieving sparse photosynthetic and non-photosynthetic vegetation coverage are presented. The analysis employed a linear spectral-mixture model (LSMM) and nonlinear spectral-mixture model (NSMM) to unmix pixels with different spectral and spatial resolution images based on field endmembers; the estimated endmember fractions were later validated with reference to fraction measurements. The results demonstrated that: (1) with higher spatial and spectral resolution, the S2 MSI sensor had a clear advantage for retrieving PV and NPV fractions compared to L8 OLI and GF1 WFV sensors; (2) through incorporating more red edge (RE) and near-infrared (NIR) bands, the accuracy of NPV fraction estimation could be greatly improved; (3) nonlinear spectral mixing effects were not obvious on the 10–30 m spatial scale for desert vegetation; (4) in arid regions, a shadow endmember is a significant factor for sparse vegetation coverage estimated with remote-sensing data. The estimated NPV fractions were especially affected by the shadow effects and could increase root mean square by 50%. The utilized approaches in the study could effectively assess the performance of major multispectral sensors to extract fPV and fNPV through the novel method of spectral-mixture analysis

Using Relative Projection Density for Classification of Terrestrial Laser Scanning Data with Unknown Angular Resolution

Point cloud classification is a key step for three-dimensional (3D) scene analysis in terrestrial laser scanning but is commonly affected by density variation. Many density-adaptive methods are used to weaken the impact of density variation and angular resolution, which denotes the angle between two horizontally or vertically adjacent laser beams and are commonly used as known parameters in those methods. However, it is difficult to avoid the case of unknown angular resolution, which limits the generality of such methods. Focusing on these problems, we propose a density-adaptive feature extraction method, considering the case when the angular resolution is unknown. Firstly, we present a method for angular resolution estimation called neighborhood analysis of randomly picked points (NARP). In NARP, n points are randomly picked from the original data and the k nearest points of each point are searched to form the neighborhood. The angles between the beams of each picked point and its corresponding neighboring points are used to construct a histogram, and the angular resolution is calculated by finding the adjacent beams of each picked point under this histogram. Then, a grid feature called relative projection density is proposed to weaken the effect of density variation based on the estimated angular resolution. Finally, a 12-dimensional feature vector is constructed by combining relative projection density and other commonly used geometric features, and the semantic label is generated utilizing a Random Forest classifier. Five datasets with a known angular resolution are used to validate the NARP method and an urban scene with a scanning distance of up to 1 km is used to compare the relative projection density with traditional projection density. The results demonstrate that our method achieves an estimation error of less than 0.001° in most cases and is stable with respect to different types of targets and parameter settings. Compared with traditional projection density, the proposed relative projection density can improve the performance of classification, particularly for small-size objects, such as cars, poles, and scanning artifacts