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Shikonin (SHK) has been proven to have a good anti-tumor effect. However, poor water solubility and low bioavailability limit its wide application in clinical practice. In this study, to overcome these drawbacks, RGD-modified shikonin-loaded liposomes (RGD-SSLs-SHK) were successfully prepared. It exhibited excellent physicochemical characteristics including particle size, zeta potential, encapsulation efficiency, and delayed release time. Meanwhile, the targeting activity of the RGD-modified liposomes was demonstrated by flow cytometry and confocal microscopy in the αvβ3-positive MDA-MB-231 cells. Besides exhibiting greater cytotoxicity in vitro, compared with non-targeted shikonin-loaded liposomes (SSLs-SHK), RGD-SSLs-SHK could also evidently induce apoptosis by decreasing the expression of Bcl-2 and increasing the expression of Bax. It could also inhibit cell proliferation, migration, invasion, and adhesion by reducing the expression of MMP-9 and the level of NF-κB p65, but did not affect the expression of MMP-2 in the MDA-MB-231 cells. Therefore, these findings indicated that the strategy to use RGD-modified liposomes as carriers for targeted delivery of shikonin is a very promising approach to achieve breast cancer targeted therapy. [ABSTRACT FROM AUTHOR]

Simple Summary: The size of antlers varies among species; antlers of the wapiti (Cervus canadensis xanthopygus) grow much faster than those of its close relative the sika deer (Cervus nippon hortulorum) in the same growing period. This contrast provides a potential model for comparative studies for the identification of potent growth factors and unique regulatory systems. In the present study, the reference transcriptomes of the antler reserve mesenchyme (RM) tissue of wapiti and sika deer were constructed using single molecule real time sequencing data. The expression profiling, positive selection, and alternative splicing of the antler transcripts were compared, and interactive relationships and expression patterns of hub genes were identified and analysed. We identified that RNA Binding Motif Protein X-Linked (RBMX) gene was under strongly positive selection. One gene found to interact with RBMX was methyltransferase-like 3 (METTL3), an oncogene that could promote translation of cancer cell proteins. There was a contrasting relationship in expression level between RBMX and METTL3 genes in the RM tissue. We believe our study can provide a better understanding of rapid antler growth at the molecular level in particular and endochondral ossification in general. The molecular mechanism underlying rapid antler growth has not been elucidated. The contrast of the wapiti and sika deer antler provides a potential model for comparative studies for the identification of potent growth factors and unique regulatory systems. In the present study, reference transcriptomes of antler RM tissue of wapiti and sika deer were constructed using single molecule real time sequencing data. The expression profiling, positive selection, and alternative splicing of the antler transcripts were compared. The results showed that: a total of 44,485 reference full-length transcripts of antlers were obtained; 254 highly expressed transcripts (HETs) and 1936 differentially expressed genes (DEGs) were enriched and correlated principally with translation, endochondral ossification and ribosome; 228 genes were found to be under strong positive selection and would thus be important for the evolution of wapiti and sika deer; among the alternative splicing variants, 381 genes were annotated; and 4 genes with node degree values greater than 50 were identified through interaction network analysis. We identified a negative and a positive regulator for rapid antler growth, namely RNA Binding Motif Protein X-Linked (RBMX) and methyltransferase-like 3 (METTL3), respectively. Overall, we took advantage of this significant difference in growth rate and performed the comparative analyses of the antlers to identify key specific factors that might be candidates for the positive or negative regulation of phenomenal antler growth rate. [ABSTRACT FROM AUTHOR]

Simple Summary: Previous studies on the growth rate of antlers are inconsistent, and few genes significantly related to growth traits have been obtained, which may be caused by the low-quality genome of sika deer or by the traditional genome-wide association analysis method being singly used. In this study, we conducted an integrated analysis of genome-wide association analysis and weighted gene co-expression network analysis using resequencing data identified in our previous analysis, which used antler weight and transcriptome sequencing data of faster- vs. slower-growing antlers of sika deer. The results show that a total of 49 genes related to antler growth rate were identified, and most of those genes were enriched in the IGF1R (insulin-like growth factor 1 receptor) and LOX (lysyl oxidase) modules. A gene regulation network of antler growth rate through the IGF1R pathway was constructed. We believe that our findings in the present study can provide further insight into revealing the molecular mechanism underlying the regulation of the tissue that can grow quickly without transforming into a tumor. Furthermore, the results of this study may be applied for increasing antler output for the deer industry. Deer antlers are organs of bone and have an extremely rapid growth rate. Thus far, the molecular mechanism underlying rapid antler growth has not been properly elucidated, and key genes driving this growth rate have not been fully identified. In this study, based on the newly assembled high-quality sika deer genome, we conducted an integrated analysis of genome-wide association analysis (GWAS) and weighted gene co-expression network analysis (WGCNA) using genome resequencing data from our previous GWAS, with weight and transcriptome sequencing data of faster- vs. slower-growing antlers of sika deer. The expressions of key genes were verified using Fragments Per Kilobase of transcript per Million fragments mapped (FPKM) in different tissue zones of the antler growth center, different types of sika deer tissues and antler tissues collected from faster and slower growth rates. The results show that a total of 49 genes related to antler growth rate were identified, and most of those genes were enriched in the IGF1R and LOX modules. The gene regulation network of antler growth rate through the IGF1R pathway was constructed. In conclusion, the integration of GWAS and WGCNA analyses had great advantages in identifying regulatory genes of complex antler growth traits over using singular methods individually, and we believe that our findings in the present study can provide further insight into unveiling the mechanism underlying extraordinary fast antler growth rate in particular, as well as the regulatory mechanism of rapid tissue proliferation in general. [ABSTRACT FROM AUTHOR]

This article presents an energy-efficient BJT-based temperature sensor. The output of sensing front-ends is modulated by employing an incremental Δ - Σ ADC as a readout interface. The cascoded floating-inverter-based dynamic amplifier (FIA) is used as the integrator instead of the conventional operational transconductance amplifier (OTA) to achieve a low power consumption. To enhance the accuracy, chopping and dynamic element matching (DEM) are applied to eliminate the component mismatch error while β -compensation resistor and optimized bias current are used to minimize the effect of β variation. Fabricated in a standard 180-nm CMOS process, this sensor has an active area of 0.13 mm 2 . While dissipating only 45.7 μ W in total, the sensor achieves an inaccuracy of ±0.8 °C (3 σ) from −50 °C to 150 °C after one-point calibration. [ABSTRACT FROM AUTHOR]

Satellite synthetic aperture radar (SAR) interferometry (InSAR) is a powerful technology to monitor slow ground surface movements. However, the extraction and interpretation of information from big sets of InSAR measurements is a complex and demanding task. In this paper, a new method is presented for automatically detecting potential instability risks affecting buildings and infrastructures, by searching for anomalies in the persistent scatterer (PS) deformations, either in the spatial or in the temporal dimensions. In the spatial dimension, in order to reduce the dataset size and improve data reliability, we utilize a hierarchical clustering method to obtain convergence points that are more trustworthy. Then, we detect deformations characterized by large values and spatial inhomogeneity. In the temporal dimension, we use a signal processing method to decompose the input into two main components: regular periodic deformations and piecewise linear deformations. After removing the periodic component, the velocity variation in each identified temporal partition is analyzed to detect anomalous velocity trends and accelerations. The method has been tested on different sites in China, based on InSAR measurements from COSMO-SkyMed data. The results, verified with in-field surveys, confirm the potential of the method for the automatic detection of deformation anomalies that could cause building or infrastructure stability problems. [ABSTRACT FROM AUTHOR]

Land degradation and desertification in arid and semi-arid areas is of great concern. Accurately mapping percentage vegetation cover (PVC) of the areas is critical but challenging because the areas are often remote, sparsely vegetated, and rarely populated, and it is difficult to collect field observations of PVC. Traditional methods such as regression modeling cannot provide accurate predictions of PVC in the areas. Nonparametric constant k-nearest neighbors (Cons_kNN) has been widely used in estimation of forest parameters and is a good alternative because of its flexibility. However, using a globally constant k value in Cons_kNN limits its ability of increasing prediction accuracy because the spatial variability of PVC in the areas leads to spatially variable k values. In this study, a novel method that spatially optimizes determining the spatially variable k values of Cons_kNN, denoted with Opt_kNN, was proposed to map the PVC in both Duolun and Kangbao County located in Inner Mongolia and Hebei Province of China, respectively, using Landsat 8 images and sample plot data. The Opt_kNN was compared with Cons_kNN, a linear stepwise regression (LSR), a geographically weighted regression (GWR), and random forests (RF) to improve the mapping for the study areas. The results showed that (1) most of the red and near infrared band relevant vegetation indices derived from the Landsat 8 images had significant contributions to improving the mapping accuracy; (2) compared with LSR, GWR, RF and Cons_kNN, Opt_kNN resulted in consistently higher prediction accuracies of PVC and decreased relative root mean square errors by 5%, 11%, 5%, and 3%, respectively, for Duolun, and 12%, 1%, 23%, and 9%, respectively, for Kangbao. The Opt_kNN also led to spatially variable and locally optimal k values, which made it possible to automatically and locally optimize k values; and (3) the RF that has become very popular in recent years did not perform the predictions better than the Opt_kNN for the both areas. Thus, the proposed method is very promising to improve mapping the PVC in the arid and semi-arid areas. [ABSTRACT FROM AUTHOR]