P14AS upregulates gene expression in the CDKN2A/2B locus through competitive binding to PcG protein CBX7

Background: It is well known that P16INK4A, P14ARF, P15INK4B mRNAs, and ANRIL lncRNA are transcribed from the CDKN2A/2B locus. LncRNA P14AS is a lncRNA transcribed from antisense strand of P14ARF promoter to intron-1. Our previous study showed that P14AS could upregulate the expression level of ANRIL and P16INK4A and promote the proliferation of cancer cells. Because polycomb group protein CBX7 could repress P16INK4A expression and bind ANRIL, we wonder whether the P14AS-upregulated ANRIL and P16INK4A expression is mediated with CBX7.Results: In this study, we found that the upregulation of P16INK4A, P14ARF, P15INK4B and ANRIL expression was induced by P14AS overexpression only in HEK293T and HCT116 cells with active endogenous CBX7 expression, but not in MGC803 and HepG2 cells with weak CBX7 expression. Further studies showed that the stable shRNA-knockdown of CBX7 expression abolished the P14AS-induced upregulation of these P14AS target genes in HEK293T and HCT116 cells whereas enforced CBX7 overexpression enabled P14AS to upregulate expression of these target genes in MGC803 and HepG2 cells. Moreover, a significant association between the expression levels of P14AS and its target genes were observed only in human colon cancer tissue samples with high level of CBX7 expression (n = 38, p < 0.05), but not in samples (n = 37) with low level of CBX7 expression, nor in paired surgical margin tissues. In addition, the results of RNA immunoprecipitation (RIP)- and chromatin immunoprecipitation (ChIP)-PCR analyses revealed that lncRNA P14AS could competitively bind to CBX7 protein which prevented the bindings of CBX7 to both lncRNA ANRIL and the promoters of P16INK4A, P14ARF and P15INK4B genes. The amounts of repressive histone modification H3K9m3 was also significantly decreased at the promoters of these genes by P14AS in CBX7 actively expressing cells.Conclusions: CBX7 expression is essential for P14AS to upregulate the expression of P16INK4A, P14ARF, P15INK4B and ANRIL genes in the CDKN2A/2Blocus. P14AS may upregulate these genes’ expression through competitively blocking CBX7-binding to ANRIL lncRNA and target gene promoters

Citrus Canopy SPAD Prediction under Bordeaux Solution Coverage Based on Texture- and Spectral-Information Fusion

Rapid and nondestructive prediction of chlorophyll content and response to the growth of various crops using remote sensing technology is a prominent topic in agricultural remote sensing research. Bordeaux mixture has been extensively employed for managing citrus diseases, such as black star and ulcer disease. However, the presence of pesticide residues in Bordeaux mixture can significantly modify the spectral response of the citrus canopy, thereby exerting a substantial influence on the accurate prediction of agronomic indices in fruit trees. In this study, we used unmanned aerial vehicle (UAV) multispectral imaging technology to obtain remote sensing imagery of Bordeaux-covered citrus canopies during the months of July, September, and November. We integrated spectral and texture information to construct a high-dimensional feature dataset and performed data downscaling and feature optimization. Furthermore, we established four machine learning models, namely, partial least squares regression (PLS), ridge regression (RR), ridge, random forest (RF), and support vector regression (SVR). Our objectives were to identify the most effective prediction model for estimating the SPAD (soil plant analysis development) value of Bordeaux-covered citrus canopies, assess the variation in prediction accuracy between fused features and individual features, and investigate the impact of Bordeaux solution on the spectral reflectance of the citrus canopy. The results showed that (1) the impact of Bordeaux mixture on citrus canopy reflectance bands ranked from the highest to the lowest as follows: near-infrared band at 840 nm, red-edge band at 730 nm, blue band at 450 nm, green band at 560 nm, and red band at 650 nm. (2) Fused feature models had better prediction ability than single-feature modeling, with an average R2 value of 0.641 for the four model test sets, improving by 0.117 and 0.039, respectively, compared with single-TF (texture feature) and -VI (vegetation index) modeling, and the test-set root-mean-square error (RMSE) was 2.594 on average, which was 0.533 and 0.264 lower than single-TF and -VI modeling, respectively. (3) Multiperiod data fusion effectively enhanced the correlation between features and SPAD values and consequently improved model prediction accuracy. Compared with accuracy based on individual months, R improved by 0.013 and 0.011, while RMSE decreased by 0.112 and 0.305. (4) The SVR model demonstrated the best performance in predicting citrus canopy SPAD under Bordeaux solution coverage, with R2 values of 0.629 and 0.658, and RMSE values of 2.722 and 2.752 for the training and test sets, respectively

Development of a Sensitive and Fast Determination Method for Trace Carbaryl Residues in Food Samples Based on Magnetic COF (TpPa-NH₂)@Fe₃O₄ Nanoparticles and Fluorescence Detection

Developing a simple and effective method for measuring carbaryl residues in food is urgent due to its widespread use and the associated health risks in agriculture, as well as various defects in existing detection techniques. The COF (TpPa-NH2)@Fe3O4 nanocomposite (amino modification) was synthesized via a two-step method and used as an adsorbent for the extraction of carbaryl from food samples in this study. The results indicated that COF (TpPa-NH2)@Fe3O4 can rapidly and successfully capture carbaryl directly from samples via π–π stacking and hydrophobic interactions, achieving maximum adsorption within 5 min under a small adsorbent quantity using a fluorescence spectrophotometer. Under the optimized conditions, carbaryl exhibited good linearity in the range of 0.2–120 µg·kg−1, and the limit of detection was 0.012 µg·kg−1. The recoveries of the samples were 96.0–107.4%. This method has broad application prospects for the monitoring of carbaryl in food

Reproducible and fast preparation of superhydrophobic surfaces via an ultrasound-accelerated one-pot approach for oil collection

The currently available superhydrophobic coating techniques that utilize mussel-inspired polydopamine coating to construct hierarchical superhydrophobic structures require multiply procedures and are time-consuming processes. Here, we propose an ultrasound-accelerated strategy to various commercial sponges with hierarchically structured superhydrophobic surfaces by briefly submerging sponges into a slightly alkaline aqueous mixture comprising dopamine hydrochloride (DA) and dodecyltrimethoxysilane (DTMS) under ultrasound. The ultrasound is found significantly accelerate the hierarchical surface structures from PDA, while only minorly influences the hydrolysis of DTMS that hydrophobically modifies the surface of PDA. As a result, the hierarchical superhydrophobic surfaces are formed within 25 min. In addition, the superhydrophobicity of the surface can be recovered by repeating this ultrasound-assisted process, provided that the superhydrophobic feature is vanished or lost during their use in a harsh environment. These superhydrophobic sponges are superior materials for oil collection from water, in a durably robust, efficient and recyclable manner with multi-life span. This strategy presents a rather high efficient and time-saving process for constructing/recovering hierarchical superhydrophobic surfaces, which may be useful for the rapid engineering commercial materials with restorable superhydrophobic surfaces.Peer reviewe

Optimizing the YOLOv7-Tiny Model with Multiple Strategies for Citrus Fruit Yield Estimation in Complex Scenarios

The accurate identification of citrus fruits is important for fruit yield estimation in complex citrus orchards. In this study, the YOLOv7-tiny-BVP network is constructed based on the YOLOv7-tiny network, with citrus fruits as the research object. This network introduces a BiFormer bilevel routing attention mechanism, which replaces regular convolution with GSConv, adds the VoVGSCSP module to the neck network, and replaces the simplified efficient layer aggregation network (ELAN) with partial convolution (PConv) in the backbone network. The improved model significantly reduces the number of model parameters and the model inference time, while maintaining the network’s high recognition rate for citrus fruits. The results showed that the fruit recognition accuracy of the modified model was 97.9% on the test dataset. Compared with the YOLOv7-tiny, the number of parameters and the size of the improved network were reduced by 38.47% and 4.6 MB, respectively. Moreover, the recognition accuracy, frames per second (FPS), and F1 score improved by 0.9, 2.02, and 1%, respectively. The network model proposed in this paper has an accuracy of 97.9% even after the parameters are reduced by 38.47%, and the model size is only 7.7 MB, which provides a new idea for the development of a lightweight target detection model

Analysis of microbial diversity and its degradation function in wooden piles at Shahe ancient bridge site in Xi’an and protection measures

Abstract Microorganisms possess the capability to impact virtually any form of cultural heritage, leading to contamination, degradation, and even combined degradation, where diverse microorganism communities facilitate the decay of wooden materials. This study aims to analyze the microbial diversity of the wooden structure bridge at the Shahe Ancient bridge site in Xi'an. The objective is to investigate the correlation between microbial species and the state of wood degradation, as well as explore the relationship between wood microbial species and the potential influence of the wood preservation environment on its long-term preservation. Simultaneously, the conventional laboratory separation technique was employed to isolate the microorganisms that were contaminated by experimental ancient wood. This was done to assess the inhibitory effect of two fungicides on the dominant microorganisms found in ancient wood, identify the most effective inhibitor, and subsequently establish an experimental foundation for safeguarding ancient bridge wood structures. The primary objective of this research was to establish microbial control criteria for the enduring conservation of historical sites, while also equipping conservators with scientifically-guided data to inform future research and restoration endeavors. Graphical Abstrac

Multi-Analytical Research on the Caisson Painting of Dayu Temple in Hancheng, Shaanxi, China

In this research, the caisson painting of Dayu Temple in Hancheng, Shaanxi, China, was analyzed via a multi-analytical methodology, using a pH meter, an ultra-depth-of-field optical microscope, a scanning electron microscope-energy dispersive spectrometer (SEM-EDS), a high-resolution X-ray diffractometer (XRD), a micro-confocal laser Raman spectrometer, a gas chromatography mass spectrometer (GC-MS), and X-ray fluorescence spectroscopy (XRF). With the corroborative evidence derived from the above analyses, it could be determined that the caisson painting of Dayu Temple was painted on bamboo paper and attached to hemlock wood substrate of the Pinaceae Tsuga genus using starch paste, with common colorants such as carbon black, cinnabar mixed with a small amount of red lead, ultramarine, and ultramarine mixed with Paris green, with animal glue having been adopted as a sizing agent. These results provide important scientific data for the production craft of precious caisson paintings, contributing to the revelation of their historic, artistic, and scientific value, and should enable conservators to make informed decisions in restoration

Microscopic Imaging Technology Assisted Dynamic Monitoring and Restoration of Micron-Level Cracks in the Painted Layer of Terracotta Warriors and Horses of the Western Han Dynasty

Cracks are one of the most common issues affecting colored pottery relics; these can be divided into macroscopic cracks, recognizable by the human eye, and micron cracks, which cannot be observed by the naked eye. The gradual development of micron cracks eventually leads to large-scale cracks and the shedding of the coating layer. The repair of such micron cracks poses a key technical difficulty in restoring painted pottery remnants from the Western Han Dynasty. We attempt to solve this problem by reporting on a method that entails the use of a water-borne fluoropolymer material as the adhesive agent, as well as ultra-depth-of-field, digital microscopic imaging technology to build an operating platform for an optical imaging monitoring system. By making simulated ceramic samples, we systematically investigated the influences of water-borne fluoropolymer on chromaticity, adhesion, contact angle, surface morphology, and thermal stability of the paint layer. The results indicate that the color of the painted layer, when treated with the water-borne fluoropolymer, did not change, and the adhesion and contact angle of the painted layer were improved. Additionally, the outcomes of the SEM analysis show that the adhesion and hydrophobicity of the painted layer were improved because the water-borne fluoropolymer filled up the porous structure of the painted layer and covered the pigment particles. These findings demonstrate that aqueous, water-borne fluoropolymer can be used as an adhesive agent for micron cracks. Meanwhile, via the operating platform of the optical imaging monitoring system, the micron cracks of the painted terracotta warriors and horses from the Western Han Dynasty were successfully repaired using the water-borne fluoropolymer. The results imply that the microstructure, size, and geometric spaces of the cracks can be obtained directly utilizing microscopic imaging technology. The dynamic monitoring and imaging system described above can be employed to assist prosthetists in visualizing micro-repair operations in real time, assist with fine visual operations during the repair process, and realize dynamic video recording of the entire repair process. Our work provides a simple visualization method to repair micron-scale cracks in painted pottery relics by applying modern fluoropolymer and ultra-depth-of-field digital microscopic imaging technology

Analysis of Iron Anchor Diseases Unearthed from Gudu Ruins in Xianyang City, Shaanxi Province, China

Iron cultural relics are easily affected by environmental factors and can completely rust away. As early as the Qin Dynasty in ancient China, Xianyang Gudu was part of the most important transportation route to the West from ancient Chang’an; research into Xianyang Gudu has provided important information for understanding the historical changes in ancient China, East–West trade, and ancient boating technology. In this research, we use the iron anchors unearthed from the Gudu ruins in Xianyang City, Shaanxi Province, China as the research object; then, we used a scanning electron microscope–energy dispersive spectrometer (SEM-EDS), a high-resolution X-ray diffractometer (XRD), ion chromatography, and other methods to detect the corroded products of the iron anchors, and analyzed the iron anchor diseases in different preservation environments to explore the relationship between iron anchor disease and the preservation environment. This research found that the corroded products of the iron anchors contained the harmful tetragonal lepidocrocite (β-FeOOH) and that a high concentration of salt ions in the river channel accelerated the corrosion of the anchors; this analysis, based on the disease results, can provide a basis for the subsequent scientific restoration of iron anchors

Spatiotemporal variation of net primary productivity influenced by climatic variables in the karst area of China

Karst area is one of the most ecologically fragile regions. Monitoring spatial and temporal variation of net primary productivity (NPP) and its response to climate change are essential for vegetation restoration. In this study, we used the CASA (Carnegie-Ames-Stanford Approach) model to estimate the NPP in the karst area of China during 2001 to 2019. We analyzed the response of multi-scale NPP to climate change by using Theil-Sen Median trend analysis, partial correlation analysis and time lag analysis. The results showed that the average NPP was 399.06 gC·m−2, decreased from southeast to northwest, with an annual increase rate of 1.93 gC·m−2 from 2001 to 2019. The broadleaf forest had the highest NPP, and summer NPP accounted for 48.12% of annual NPP. Climate change significantly promotes the increase of NPP in the early growing season. Partial correlation analysis showed that NPP was more correlated with precipitation (0.20) than temperature (0.12), this phenomenon was more pronounced in some arid regions. Where precipitation caused a decrease in NPP during the rainy season. The time lag of NPP to temperature change was shorter than precipitation, indicating that NPP is more sensitive to temperature in most regions. The time lag of NPP to temperature changes was very short in spring. Whereas, even in arid regions, the time lag of NPP to precipitation changes was still long. This study can deepen our knowledge of the response of NPP to climate change in karst ecosystems.</p