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Many vision-based bolt looseness detection methods that directly observe the bolts have been developed. However, these methods have many limitations in terms of the conditions and processes of their implementation. To address these problems, this paper proposed a fully automated vision-based bolt looseness detection method for a rigid multi-bolt connection. The proposed method combines digital shearing speckle pattern interferometry (DSSPI) and recurrent neural network (RNN) and involves capturing speckle fringe patterns under various looseness cases using the DSSPI system and classifying these patterns with an RNN model to detect the loose bolts. The proposed method can detect all the bolts within the measured surface at one time, which is efficient. On the other hand, it eliminates the need for prior information such as the initial angle and position of each bolt. It can even detect unseen bolts in multi-bolt connections, making it applicable for connections in complex structures in which occlusion often occurs. Additionally, the method eliminates the complex process of distortion rectification. These features make the method achieve a single-judgment time (four bolts at one detection) of only 4.70 millisecond with a detection accuracy over 99%, which has potential for the real-time detection of loose bolts in multi-bolt connections. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the rheological properties, particle size distribution, color change, and stability of lily juice under different ultrasonic treatment conditions (152 W, 304 W, 456 W, 608 W, and 760 W). The results showed that the lily juice exhibited non-Newtonian shear thinning behavior, and the viscosity decreased with the increase in ultrasonic power. Under ultrasonic treatment conditions, there was no significant change in the pH value and zeta potential value of the samples. The content of cloudy value and total soluble solids (TSS) increased gradually. However, both the sedimentation components and centrifugal sedimentation rate showed a downward trend and an asymptotic behavior. In addition, high-power ultrasound changed the color index (L* value decreased, a* value increased), tissue structure, and particle distribution of the sample, and small particles increased significantly. To sum up, ultrasonic treatment has great potential in improving the physical properties and suspension stability of lily juice. [ABSTRACT FROM AUTHOR]

Regulator of ribosome synthesis 1 (RRS1), a crucial regulatory factor in ribosome biogenesis, exerts a remarkable impact on the progression of breast cancer (BC). However, the exact mechanisms and pathways have not yet been fully elucidated. To investigate the impact of RRS1 on BC growth and metastasis, along with its underlying mechanisms. We discovered that RRS1 is overexpressed in BC tissues and cell lines. This study aims to regulate the level of RRS1 through lentiviral transfection technology to explore its potential function in BC cells. Knockdown of RRS1 resulted in the inhibition of cell proliferation, invasion, and migration, whereas overexpression had the opposite effects. We firstly identified the interaction between RRS1 and Glucose-Regulated Protein 78 (GRP78) using Co-immunoprecipitation (Co-IP) combined with mass spectrometry analysis, providing evidences of co-localization and positive regulation between RRS1 and GRP78. We observed that RRS1 inhibited the degradation of GRP78 through the ubiquitin–proteasome pathway, resulting in the stabilization of GRP78. In addition, our findings suggested that RRS1 promoted BC progression by activating the GRP78-mediated phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway. In conclusion, this newly discovered RRS1/GRP78 signaling axis provides a molecular and theoretical basis for further exploring the mechanisms of breast cancer invasion and metastasis. [ABSTRACT FROM AUTHOR]

Distributed optical fiber acoustic sensing (DAS) is promising for long-distance intrusion-anomaly detection tasks. However, realistic settings suffer from high-intensity interference noise, compromising the detection performance of DAS systems. To address this issue, we propose STNet, an intrusion detection network based on the Stockwell transform (S-transform), for DAS systems, considering the advantages of the S-transform in terms of noise resistance and ability to detect disturbances. Specifically, the signal detected by a DAS system is divided into space–time data matrices using a sliding window. Subsequently, the S-transform extracts the time-frequency features channel by channel. The extracted features are combined into a multi-channel time-frequency feature matrix and presented to STNet. Finally, a non-maximum suppression algorithm (NMS), suitable for locating intrusions, is used for the post-processing of the detection results. To evaluate the effectiveness of the proposed method, experiments were conducted using a realistic high-speed railway environment with high-intensity noise. The experimental results validated the satisfactory performance of the proposed method. Thus, the proposed method offers an effective solution for achieving high intrusion detection rates and low false alarm rates in complex environments. [ABSTRACT FROM AUTHOR]

Hepatitis C virus (HCV) is a positive-sense, single-stranded RNA virus that causes chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. The release of infectious HCV particles from infected hepatocytes is a crucial step in viral dissemination and disease progression. While the exact mechanisms of HCV particle release remain poorly understood, emerging evidence suggests that HCV utilizes intracellular membrane trafficking and secretory pathways. These pathways include the Golgi secretory pathway and the endosomal trafficking pathways, such as the recycling endosome pathway and the endosomal sorting complex required for transport (ESCRT)-dependent multivesicular bodies (MVBs) pathway. This review provides an overview of recent advances in understanding the release of infectious HCV particles, with a particular focus on the involvement of the host cell factors that participate in HCV particle release. By summarizing the current knowledge in this area, this review aims to contribute to a better understanding of endosomal pathways involved in the extracellular release of HCV particles and the development of novel antiviral strategies. [ABSTRACT FROM AUTHOR]

In order to explore the structural changes and products of histamine degradation by multicopper oxidase (MCO) in Lactiplantibacillus plantarum LPZN19, a 1500 bp MCO gene in L. plantarum LPZN19 was cloned, and the recombinant MCO was expressed in E. coli BL21 (DE3). After purification by Ni2+-NTA affinity chromatography, the obtained MCO has a molecular weight of 58 kDa, and it also has the highest enzyme activity at 50 °C and pH 3.5, with a relative enzyme activity of 100%, and it maintains 57.71% of the relative enzyme activity at 5% salt concentration. The secondary structure of MCO was determined by circular dichroism, in which the proportions of the α-helix, β-sheet, β-turn and random coil were 2.9%, 39.7%, 21.2% and 36.1%, respectively. The 6xj0.1.A with a credibility of 68.21% was selected as the template to predict the tertiary structure of MCO in L. plantarum LPZN19, and the results indicated that the main components of the tertiary structure of MCO were formed by the further coiling and folding of a random coil and β-sheet. Histamine could change the spatial structure of MCO by increasing the content of the α-helix and β-sheet. Finally, the LC-MS/MS identification results suggest that the histamine was degraded into imidazole acetaldehyde, hydrogen peroxide and ammonia. [ABSTRACT FROM AUTHOR]

To address the complexity of small or unique reconstruction distances in digital holography, we propose an inverse cross-correlation-based algorithm for the digital holographic imaging of multiplanar objects with a large depth of field. In this method, a planar output mapping is closely around the objects, and it is established by calculating the image inverse cross-correlation matrix of the reconstructed image at similar reconstruction distances, whereby the object edges serve as the result guide. Combining the search for edge planes with the depth estimation operator, the depth of field of digital holography is improved, thus allowing for a digital holography that is capable of meeting the requirements of the holographic imaging of multiplanar objects. Compared with the traditional depth estimation operator method, the proposed method solves the reconstruction ambiguity problem in multiple planes with a simple optical path, and no additional optical or mechanical devices need to be added, thus greatly improving the reconstruction quality. The numerical calculation results and the experimental results with multiplanar samples validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Sweet potatoes (Ipomoea batatas (L.) Lam.) are a widely cultivated member of the Convolvulaceae family. Despite intensive agricultural interest, the metabolic determinants of sweet potato quality remain poorly understood owing to a lack of reliable or systematic sweet potato metabolite analyses. This study aimed to reveal the mechanism of flavonoid biosynthesis using widely targeted metabolomics and qRT-PCR analysis of white (S19) and yellow (BS) sweet potatoes. We found that the PAL, C4H, 4CL, CHS, CHI, IFS, F3H, F3'H, DFR, ANS, and ANR genes were differentially expressed in BS. Upregulation of PAL, C4H, 4CL, and CHS led to the accumulation of large amounts of chalcone, which is highly expressed in yellow flesh, resulting in the yellow color of BS. In S19, the high expression of FLS and the low expression of DFR inhibited pigment accumulation, while the low expression of CHS also inhibited flavonoid synthesis, ultimately leading to the white color. In conclusion, this study identified the main differentially expressed genes and their metabolites in the flavonoid biosynthesis pathway, and preliminarily elucidated the mechanism underlying the different flesh colors in sweet potato, thus providing new insights into the composition and abundance of metabolites in sweet potatoes with different-colored flesh. [ABSTRACT FROM AUTHOR]

Unhealthy diets rich in fats and/or sugar are considered as the major external cause of the obesity epidemic, which is often accompanied by a significant decrease in gut hormone glucagon-like peptide-1 (GLP1) levels. Numerous studies have demonstrated notable contributions of the gut microbiota in this process. Nevertheless, the underlying mechanism still needs further investigation. The role of epigenetic modifications in gene expression and metabolism has been well demonstrated, with m6A methylation on RNAs being the most prevalent modification throughout their metabolism. In the present study, we found that the expressions of small intestinal Gcg and Pc3, two key genes regulating GLP1 expression, were significantly downregulated in obese mice, associated with reduced GLP1 level. Immunohistochemistry analysis indicated that a high-fat diet slightly increased the density of enteroendocrine L cells in the small intestine, implying that decreased GLP1 levels were not caused by the changes in L cell intensity. Instead, the small intestinal m6A level as well as the expression of known "writers", mettl3/14 and wtap, were found to be positively correlated with the expression of Gcg and Pc3. Fecal microbiota transplantation with feces from normal and obese mice daily to antibiotic-treated mice revealed that dysbiosis in diet-induced obesity was sufficient to reduce serum GLP1, small intestinal m6A level, and intestinal expressions of Gcg, Pc3, and writer genes (mettl3/14, wtap). However, as the most direct and universal methyl donor, the production of fecal S-adenosylmethionine was neither affected by the different dietary patterns nor their shaped microbiota. These results suggested that microbial modulation of the epitranscriptome may be involved in regulating GLP1 expression, and highlighted epitranscriptomic modifications as an additional level of interaction between diet and individual health. [ABSTRACT FROM AUTHOR]

Nanoplastics have gradually become a concern due to the wide use of plastics. Nanoplastics in aqueous phase can be exposed to users through water supply networks and cannot be efficiently removed by conventional water treatment processes. This work studied the degradation of polystyrene nanoplastics (PS-NP) by two commonly used advanced oxidation systems: UV/NaClO and UV/peroxymonosulfate (PMS). Results showed that almost no turbidity was detected in the PS-NP solution (5.00 mg/L) after treated by both UV/NaClO and UV/PMS for 360 min, suggesting the excellent turbidity removal ability. Yet, scanning electron microscope (SEM) and total organic carbon (TOC) removal tests demonstrated that PS-NP could not be completely degraded by UV/NaClO. The mineralization rate using UV/NaClO was only 7.00% even when the NaClO concentration increased to 5.00 mM, and many PS-NP particles could still be observed in SEM images. By contrast, the mineralization rate reached 63.90% in the UV/PMS system under the identical experimental conditions, and no spherical particles appeared in the SEM results. Density functional theory (DFT) calculations revealed that the different reaction sites and energy barriers of SO4•− and •Cl on PS-NP resulted in the differences in mineralization rates and degradation intermediates. The degradation pathway of PS-NP by UV/NaClO and UV/PMS was proposed accordingly. Additionally, the intermediates toxicity evaluation by a luminescent bacteria test showed that the inhibition rate in the UV/NaClO system (2.97%) was not markedly different from that in the control group without any treatment (1.98%); while that in UV/PMS system increased sharply to 98.19%. This work demonstrated that UV/PMS was more effective in PS-NP degradation than UV/NaClO, and the chemical risks of degradation intermediates were non-negligible. [ABSTRACT FROM AUTHOR]

Deep learning anomaly detection is important in distributed optical fiber acoustic sensing (DAS). However, anomaly detection is more challenging than traditional learning tasks, due to the scarcity of true-positive data and the vast imbalance and irregularity within datasets. Furthermore, it is impossible to catalog all types of anomalies, therefore, the direct application of supervised learning is deficient. To overcome these problems, an unsupervised deep learning method that only learns the normal data features from ordinary events is proposed. First, a convolutional autoencoder is used to extract DAS signal features. A clustering algorithm then locates the feature center of the normal data, and the distance to the new signal is used to determine whether it is an anomaly. The efficacy of the proposed method was evaluated in a real high-speed rail intrusion scenario, and considered all behaviors that may threaten the normal operation of high-speed trains as abnormal. The results show that the threat detection rate of this method reaches 91.5%, which is 5.9% higher than that of the state-of-the-art supervised network and, at 7.2%, the false alarm rate is 0.8% lower than the supervised network. Moreover, using a shallow autoencoder reduces the parameters to 1.34 K, which is significantly lower than the 79.55 K of the state-of-the-art supervised network. [ABSTRACT FROM AUTHOR]

Many ribosomal proteins are highly expressed in tumors and are closely related to their diagnosis, prognosis and pathological characteristics. However, few studies are available on the correlation between ribosomal proteins and chemoresistance. RRS1 (human regulator of ribosome synthesis 1), a critical nuclear protein involved in ribosome biogenesis, also plays a key role in the genesis and development of breast cancer by protecting cancer cells from apoptosis. Given that apoptosis resistance is one of the causes of the cisplatin resistance of tumor cells, our aim was to determine the relationship between RRS1 and cisplatin resistance in breast cancer cells. Here, we report that RRS1 is associated with cisplatin resistance in breast cancer cells. RRS1 silencing increased the sensitivity of MCF-7/DDP cells to cisplatin and inhibited cancer cell proliferation by blocking cell cycle distribution and enhancing apoptosis. AEG-1 (astrocyte elevated gene-1) promotes drug resistance by interfering with the ubiquitination and proteasomal degradation of MDR1 (multidrug resistance gene 1), thereby enhancing drug efflux. We found that RRS1 binds to and stabilizes AEG-1 by inhibiting ubiquitination and subsequent proteasomal degradation, which then promotes drug efflux by upregulating MDR1. Furthermore, RRS1 also induces apoptosis resistance in breast cancer cells through the ERK/Bcl-2/BAX signaling pathway. Our study is the first to show that RRS1 sensitizes breast cancer cells to cisplatin by binding to AEG-1, and it provides a theoretical basis to improve the efficacy of cisplatin-based chemotherapy. [ABSTRACT FROM AUTHOR]

Piezoelectric wearable electronics, which can sense external pressure, have attracted widespread attention. However, the enhancement of electromechanical coupling performance remains a great challenge. Here, a new solid solution of Ba1−xSrxSn0.09Ti0.91O3 (x = 0.00~0.08) is prepared to explore potential high-performance, lead-free piezoelectric ceramics. The coexistence of the rhombohedral phase, orthorhombic phase and tetragonal phase is determined in a ceramic with x = 0.06, showing enhanced electrical performance with a piezoelectric coefficient of d33~650 pC/N. Furthermore, Ba0.94Sr0.06Sn0.09Ti0.91O3 (BSST) is co-blended with PDMS to prepare flexible piezoelectric nanogenerators (PENGs) and their performance is explored. The effects of inorganic particle concentration and distribution on the piezoelectric output of the composite are systematically analyzed by experimental tests and computational simulations. As a result, the optimal VOC and ISC of the PENG (40 wt%) can reach 3.05 V and 44.5 nA, respectively, at 138.89 kPa, and the optimal sensitivity of the device is up to 21.09 mV/kPa. Due to the flexibility of the device, the prepared PENG can be attached to the surface of human skin as a sensor to monitor vital movements of the neck, fingers, elbows, spine, knees and feet of people, thus warning of dangerous behavior or incorrect posture and providing support for sports rehabilitation. [ABSTRACT FROM AUTHOR]

Liquidambar formosana Hance is a pinene-rich deciduous plant species in the Altingiaceae family that is used as a medicinal plant in China. However, the regulatory mechanisms underlying α-pinene and β-pinene biosynthesis in L. formosana leaves remain unknown. Here, a joint analysis of the volatile compounds and transcriptomes of L. formosana leaves was performed to comprehensively explore the terpene synthase (TPS) that may participate in α-pinene and β-pinene biosynthesis. Headspace solid-phase microextraction (HS-SPME) and gas chromatography–mass spectrometry (GC–MS) jointly detected volatile L. formosana leaves. Trees with high and low levels of both α-pinene and β-pinene were defined as the H group and L group, respectively. RNA sequencing data revealed that DXR (1-deoxy-D-xylulose-5-phosphate reductoisomerase), HDS [(E)-4-hydroxy-3-methylbut-2-eny-l-diphosphate synthase], and TPS may be the major regulators of monoterpenoid biosynthesis. We identified three TPSs (LfTPS1, LfTPS2, and LfTPS3), which are highly homologous to α-pinene and β-pinene synthases of other species in phylogenetic analysis. Four TPS genes (LfTPS1, LfTPS2, LfTPS4, LfTPS5) may be critically involved in the biosynthesis and regulation of α-pinene and β-pinene in L. formosana. Bioinformatic and transcriptomic results were verified using quantitative real-time PCR. We identified LfTPS1, LfTPS2 as candidate genes for α-pinene and β-pinene biosynthesis that significantly improve the yield of beneficial terpenoids. [ABSTRACT FROM AUTHOR]

Unlike traditional small molecule drugs, fullerene is an all-carbon nanomolecule with a spherical cage structure. Fullerene exhibits high levels of antiviral activity, inhibiting virus replication in vitro and in vivo. In this review, we systematically summarize the latest research regarding the different types of fullerenes investigated in antiviral studies. We discuss the unique structural advantage of fullerenes, present diverse modification strategies based on the addition of various functional groups, assess the effect of structural differences on antiviral activity, and describe the possible antiviral mechanism. Finally, we discuss the prospective development of fullerenes as antiviral drugs. [ABSTRACT FROM AUTHOR]

(1) Background: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Enhancer RNA (eRNA) has potential utility in the diagnosis, prognosis and treatment of cancer, but the role of eRNAs in NSCLC metastasis is not clear; (2) Methods: Differentially expressed transcription factors (DETFs), enhancer RNAs (DEEs), and target genes (DETGs) between primary NSCLC and metastatic NSCLC were identified. Prognostic DEEs (PDEEs) were screened by Cox regression analyses and a predicting model for metastatic NSCLC was constructed. We identified DEE interactions with DETFs, DETGs, reverse phase protein arrays (RPPA) protein chips, immunocytes, and pathways to construct a regulation network using Pearson correlation. Finally, the mechanisms and clinical significance were explained using multi-dimensional validation unambiguously; (3) Results: A total of 255 DEEs were identified, and 24 PDEEs were selected into the multivariate Cox regression model (AUC = 0.699). Additionally, the NSCLC metastasis-specific regulation network was constructed, and six key PDEEs were defined (ANXA8L1, CASTOR2, CYP4B1, GTF2H2C, PSMF1 and TNS4); (4) Conclusions: This study focused on the exploration of the prognostic value of eRNAs in the metastasis of NSCLC. Finally, six eRNAs were identified as potential markers for the prediction of metastasis of NSCLC. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a worldwide public health concern without major therapeutic breakthroughs over the past decades. Developing effective treatment options and improving the prognosis of TBI depends on a better understanding of the mechanisms underlying TBI. This study performed a comprehensive analysis of 15 RNA expression datasets of rat TBIs from the GEO database. By integrating the results from the various analyses, this study investigated the biological processes, pathways, and cell types associated with TBI and explored the activity of these cells during various TBI phases. The results showed the response to cytokine, inflammatory response, bacteria-associated response, metabolic and biosynthetic processes, and pathways of neurodegeneration to be involved in the pathogenesis of TBI. The cellular abundance of microglia, perivascular macrophages (PM), and neurons were found to differ after TBI and at different times postinjury. In conclusion, immune- and inflammation-related pathways, as well as pathways of neurodegeneration, are closely related to TBI. Microglia, PM, and neurons are thought to play roles in TBI with different activities that vary by phase of TBI. [ABSTRACT FROM AUTHOR]

The transcriptome of pulmonary hypertension (PH) is complex and highly genetically heterogeneous, with noncoding RNA transcripts playing crucial roles. The majority of RNAs in the noncoding transcriptome are long noncoding RNAs (lncRNAs) with less circular RNAs (circRNAs), which are two characteristics gaining increasing attention in the forefront of RNA research field. These noncoding transcripts (especially lncRNAs and circRNAs) exert important regulatory functions in PH and emerge as potential disease biomarkers and therapeutic targets. Recent technological advancements have established great momentum for discovery and functional characterization of ncRNAs, which include broad transcriptome sequencing such as bulk RNA-sequence, single-cell and spatial transcriptomics, and RNA-protein/RNA interactions. In this review, we summarize the current research on the classification, biogenesis, and the biological functions and molecular mechanisms of these noncoding RNAs (ncRNAs) involved in the pulmonary vascular remodeling in PH. Furthermore, we highlight the utility and challenges of using these ncRNAs as biomarkers and therapeutics in PH. [ABSTRACT FROM AUTHOR]

In this study, the adsorption mechanisms of dodecylamine hydrochloride(DDAHC), sodium dodecyl sulfate (SDS), sodium dodecyl benzene sulfonate(SDBS), and their mixed anionic/cationic collectors at ten different molar ratios on a muscovite (Mcv) surface in neutral aqueous solution were assessed by molecular dynamics simulations (MDS). According to the snapshot, interaction energy, radial distribution function (RDF), and density profile between the Mcv surface and collector molecules, the individual DDAHC collector was an effective collector for the flotation of Mcv. The molar ratio of anionic/cationic collectors was determined to be an essential factor in the flotation recovery of Mcv. The DDAHC collector was involved in the adsorption of the mixed anionic/cationic collectors on the Mcv (001) surface, whereas SDS and SDBS collectors were co-adsorbed with DDAHC. The mixed cationic/anionic collector showed the best adsorption on the Mcv surface in a molar ratio of 2. Additionally, SDBS, which has one more benzene ring than SDS, was more likely to form spherical micelles with DDAHC, thus resulting in better adsorption on the Mcv surface. The results of micro-flotation experiments indicated that the DDAHC collector could improve the flotation recovery of Mcv in neutral aqueous solution, which was in agreement with MDS-derived findings. In conclusion, DDAHC alone is the optimum collector for Mcv flotation under the neutral aqueous conditions, while the mixture of DDAHC and SDBS collectors (molar ratio = 2:1) exhibits the similar flotation performance. [ABSTRACT FROM AUTHOR]

Due to the partially reduced π-conjugation of the fullerene cage, multi-functionalized fullerene derivatives exhibit remarkable fluorescent properties compared to pristine fullerenes, which have high potential for application in organic light-emitting diodes (OLEDs). In this study two multi-functionalized C70 derivatives, C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2, with excellent fluorescence properties, were designed and synthesized. Compared with C70(OCH3)10 containing a single kind of functional group, both the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 exhibited enhanced fluorescence properties with blue fluorescence emission. The fluorescence quantum yields of the C70(OCH3)10[C(COOEt)2] and C70(OCH3)10[C(COOEt)2]2 were 1.94% and 2.30%, respectively, which were about ten times higher than that of C70(OCH3)10. The theoretical calculations revealed that the multi-functionalization of the C70 increased the S1–T1 energy gap, reducing the intersystem crossing efficiency, resulting in the higher fluorescence quantum yield of the C70 derivatives. The results indicate that multi-functionalization is a viable strategy to improve the fluorescence of fullerene derivatives. [ABSTRACT FROM AUTHOR]

Phosphorus (Pi) is a macronutrient essential for plant growth, development, and reproduction. However, there is not an efficient available amount of Pi that can be absorbed by plants in the soil. Previously, an elite line, MSDZ 109, selected from Malus mandshurica, was justified for its excellent tolerance to low phosphorus (low−Pi) stress. To date, however, the genes involved in low−Pi stress tolerance have not yet been unraveled in this species. Currently, the physiological responses of this line for different days to low−Pi stress were characterized, and their roots as well as leaves were used to carry out transcriptome analysis, so as to illuminate the potential molecular pathways and identify the genes involved in low−Pi stress−response. After exposure to low−Pi treatment (32 µmol/L KH2PO4) for 20 day after treatment (DAF) the biomass of shoots was significantly reduced in comparison with that of the stress−free (control), and root architecture diversely changed. For example, the root growth parameters e.g., length, surface area, and total volume somewhat increase in comparison with those of the control. The activity of acid phosphatase (ACP) increased with the low−Pi treatment, whereas the photosynthetic rate and biomass were declining. The activity of antioxidant enzymes, e.g., superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), were substantially elevated in response to low−Pi treatment. Many enzyme−related candidate genes e.g., MmCAT1, MmSOD1 and MmPOD21 were up−regulated to low−Pi treatment. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the processes of photosynthesis, plant hormone signal transduction, and MAPK signaling pathway were affected in the low−Pi response. In combination with the physiological characterization, several low−Pi−responsive genes, e.g., PHT, PHO, were identified, and the genes implicated in Pi uptake and transport, such as MmPHT1;5, MmPHO1, MmPAP1, etc., were also obtained since their expression status varied among the exposure times, which probably notifies the candidates involved in low−Pi−responsive tolerance in this line. Interestingly, low−Pi treatment activated the expression of transcription factors including the WRKY family, MYB family, etc. The available evidences will facilitate a better understanding of the roles of this line underlying the high tolerance to low−Pi stress. Additionally, the accessible data are helpful for the use of the apple rootstock M. mandshurica under low−Pi stress. [ABSTRACT FROM AUTHOR]

A micro-device vibration measurement method based on microscopic speckle interferometry combined with orthogonal phase is presented. This method utilizes the approximate linear distribution characteristics of orthogonal points (points satisfying the condition that the initial phase difference equal to π/2) to quickly obtain the vibration information of the measured object. Compared with common optical measurement methods, this method does not require scanning imaging and can realize real-time full-field measurement. Moreover, the measurement principle and equipment is simple, so there is no need to introduce a stroboscopic light source or heterodyne device. [ABSTRACT FROM AUTHOR]

Modeling and simulation of the morphology evolution of immiscible polymer blends during injection molding is crucial for predicting and tailoring the products' performance. This paper reviews the state-of-the-art progress in the multiscale modeling and simulation of injection molding of polymer blends. Technological development of the injection molding simulation on a macroscale was surveyed in detail. The aspects of various models for morphology evolution on a mesoscale during injection molding were discussed. The current scale-bridging strategies between macroscopic mold-filling flow and mesoscopic morphology evolution, as well as the pros and cons of the solutions, were analyzed and compared. Finally, a comprehensive summary of the above models is presented, along with the outlook for future research in this field. [ABSTRACT FROM AUTHOR]

The traditional microscopic speckle interferometer has limited applications in engineering due to its small field of view. In this paper, we propose a large-field microscopic speckle interferometer which embeds two doublet lens groups in the improved Mach–Zehnder optical path structure to expand its field of view. At the same time, the new system can reduce the coherent noise of reflected light in the optical path. We use this new system to measure the dynamic displacement process of the entire surface of the microchips. The experimental results show that our improved measurement system can achieve large-field, real-time and high-precision dynamic measurement of micro-electromechanical systems (MEMS). [ABSTRACT FROM AUTHOR]

The diurnal variation of the diffuse attenuation coefficient for downwelling irradiance at 490 nm (K d (490)) has complex characteristics in the coastal regions. However, owing to the scarcity of in situ data, our knowledge on the diurnal variation is inadequate. In this study, an optical-buoy dataset was used to investigate the diurnal variation of K d (490) in the coastal East China Sea, and to evaluate the K d (490) L2 products of geostationary ocean color imager (GOCI), as well as the performance of six empirical algorithms for K d (490) estimation in the Case-2 water. The results of validation show that there was high uncertainty in GOCI L2 K d (490) , with mean absolute percentage errors (MAPEs) of 69.57% and 68.86% and root mean square errors (RMSEs) of 0.70 and 0.71 m−1 compared to buoy-measured K d 12 (490) and K d 13 (490) , respectively. Meanwhile, with the coefficient of determination (R2) of 0.71, as well as the lowest MAPE of 27.31% and RMSE of 0.29 m−1, the new dual ratio algorithm (NDRA) performed the best in estimating K d (490) in the target area, among the six algorithms. Further, four main types of K d (490) diurnal variation were found from buoy data, showing different variabilities compared to the area closer to the shore. One typical diurnal variation pattern showed that K d (490) decreased at flood tide and increased at ebb tide, which was confirmed by GOCI images through the use of NDRA. Hydrometeorological factors influencing the diurnal variations of K d (490) were also studied. In addition to verifying the predominant impact of tide, we found that the dominant effect of tide and wind on the water column is intensifying sediment resuspension, and the change of sediment transport produced by them are secondary to it. [ABSTRACT FROM AUTHOR]

The standing stock of phytoplankton carbon is a basic and essential property for understanding oceanic ecosystems, biogeochemical cycles, and regional climates. However, current related algorithms mainly focus on remote-sensed application, which cannot describe the vertical profile of phytoplankton carbon throughout the whole euphotic zone. In this study, we modified a previous absorption-based bio-optical algorithm to acquire vertical variabilities of the total and size-partitioned phytoplankton carbon based on field data from the South China Sea (SCS). The mean absolute errors and the biases between estimated and field picophytoplankton carbon were <2.14 and 0.6–2.0, respectively. The results showed that the vertical profile of total phytoplankton carbon displayed a Gaussian distribution in the stratified SCS basin. The picophytoplankton carbon was always the fundamental component of the total phytoplankton carbon within the whole euphotic zone. The dominant picophytoplankton species changed from Synechococcus-like cyanobacteria at the sea surface to pico-sized haptophytes at the phytoplankton carbon maximum layer. The strong covariation between total phytoplankton carbon and chlorophyll-a concentration suggested that they can be converted into each other through an accurate carbon-to-chlorophyll ratio in the open SCS. These results provide essential information that can be used to decipher the three-dimensional structure of total and size-partitioned phytoplankton carbon in the open SCS. [ABSTRACT FROM AUTHOR]

The morphology of polymer blends plays a critical role in determining the properties of the blends and performance of resulting injection-molded parts. However, it is currently impossible to predict the morphology evolution during injection molding and the final micro-structure of the molded parts, as the existing models for the morphology evolution of polymer blends are still limited to a few simple flow fields. To fill this gap, this paper proposed a novel model for droplet morphology evolution during the mold filling process of polymer blends by coupling the models on macro- and meso-scales. The proposed model was verified by the injection molding experiment of PP/POE blends. The predicted curve of mold cavity pressure during filling process agreed precisely with the data of the corresponding pressure sensors. On the other hand, the model successfully tracked the moving trajectory and simulated morphology evolution of the droplets during the mold-filling process. After mold-filling ended, the simulation results of the final morphology of the droplets were consistent with the observations of the scanning electron microscope (SEM) experiment. Moreover, this study revealed the underlying mechanism of the droplet morphology evolution through the force analysis on the droplet. It is validated that the present model is a qualified tool for simulating the morphology evolution of polymer blends during injection molding and predicting the final microstructure of the products. [ABSTRACT FROM AUTHOR]

Using the Weather Research and Forecasting model with chemistry module (WRF-Chem), Typhoon Nida (2016) was simulated to investigate the effects of anthropogenic gaseous emissions on the vortex system. Based on the Multi-resolution Emission Inventory for China (MEIC), three certain experiments were conducted: one with base-level emission intensity (CTRL), one with one-tenth the emission of SO 2 (SO2_C), and one with one-tenth the emission of NH 3 (NH3_C). Results show that the simulations reasonably reproduced the typhoon's track and intensity, which were slightly sensitive to the anthropogenic gaseous emissions. When the typhoon was located over the ocean, a prolonged duration of raindrop growth and more precipitation occurred in CTRL run. The strongest updraft in CTRL is attributed to the maximum latent heating through water vapor condensation. During the landfalling period, larger (smaller) differential reflectivities in the main-core of the vortex were produced in NH3_C (SO2_C) run. Such opposite changes of raindrop size distributions may lead to stronger (weaker) rainfall intensity, and the ice-related microphysical processes and the relative humidity in low troposphere were two possible influential factors. Moreover, additional ten-member ensemble results in which white noise perturbations were added to the potential temperature field, indicated that the uncertainty of thermodynamic field in the current numerical model should not be ignored when exploring the impacts of aerosol on the microphysics and TC precipitation. [ABSTRACT FROM AUTHOR]

Regarding urban flooding issues, applying Artificial Intelligence (AI) methodologies can provide a timely prediction of imminent incidences of flash floods. The study aims to develop and deploy an effective real-time pluvial flood forecasting AI platform. The platform integrates rainfall hyetographs embedded with uncertainty analyses as well as hydrological and hydraulic modeling. It establishes a large number synthetic of torrential rainfall events and their simulated flooding datasets. The obtained data contain 6000 sets of color-classified rainfall hyetograph maps and 300,000 simulated flooding maps (water depth) in an urban district. The generated datasets are utilized for AI image processing. Through the AI deep learning classifications, the rainfall hyetograph map feature parameters are detected and extracted. The trained features are applied to predict potential rainfall events, recognize their potential inundated water depths as well as display flooding maps in real-time. The performance assessments of the platform are evaluated by Root Means Square Error (RMSE), Nash Sutcliffe Efficiency Coefficient (NSCE) and Mean Absolute Percentage Error (MAPE). The results of RMSE and NSCE indicators illustrate that the methodologies and approaches of the AI platform are reliable and acceptable. However, the values of MAPE show inconsistency. Ultimately, the platform can perform and be utilized promptly in real-time and ensure sufficient lead time in order to prevent possible flooding hazards. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) is one of predisposing factors for hepatocellular carcinoma (HCC). The role of HBV x protein (HBx) in mediating the induction and maintenance of cancer stemness during HBV-related HCC attracts considerable attention, but the exact mechanism has not been clearly elucidated. Here, ABCG2-dependent stem-like side population (SP) cells, which are thought to be liver cancer stem cells (LCSCs), were present in HCC cells, and the fraction of this subset was increased in HBx-expressing HCC cells. In addition, glycolysis was upregulated in LCSCs and HBx-expressing HCC cells, and intervention of glycolysis attenuated cancer stem-like phenotypes. Mitochondria play an important role in the maintenance of energy homeostasis, BNIP3L-dependent mitophagy was also activated in LCSCs and HBx-expressing HCC cells, which triggered a metabolic shift toward glycolysis. In summary, we proposed a positive feedback loop, in which HBx induced BNIP3L-dependent mitophagy which upregulated glycolytic metabolism, increasing cancer stemness of HCC cells in vivo and in vitro. BNIP3L might be a potential therapeutic target for intervention of LCSCs-associated HCC. Anti-HBx, a monoclonal antibody targeting intracellular HBx, had the potential to delay the progression of HBV infection related-HCC. [ABSTRACT FROM AUTHOR]

The phytoplankton size class (PSC) plays an important role in biogeochemical processes in the ocean. In this study, a regional model of PSCs is proposed to retrieve vertical PSCs from the total minus water absorption coefficient (at-w(λ)) and Chlorophyll a concentration (Chla). The PSC model is developed by first reconstructing phytoplankton absorption and Chla from at-w(λ), and then extracting PSC from them using the support vector machine (SVM). In situ bio-optical data collected in the South China Sea from 2006 to 2013 were used to train the SVM. The proposed PSC model was subsequently validated using an independent PSC dataset from the Northeast South China Sea Cruise in 2015. The results indicate that the PSC model performed better than the three components model, with a value of r2 between 0.35 and 0.66, and the absolute percentage difference between 56% and 181%. On the whole, our PSC model shows a remarkable utility in terms of inferring vertical PSCs from the South China Sea. [ABSTRACT FROM AUTHOR]

Phosphorus (Pi) is a macronutrient essential for plant growth, development, and reproduction. However, there is not an efficient available amount of Pi that can be absorbed by plants in the soil. Previously, an elite line, MSDZ 109, selected from Malus mandshurica , was justified for its excellent tolerance to low phosphorus (low-Pi) stress. To date, however, the genes involved in low-Pi stress tolerance have not yet been unraveled in this species. Currently, the physiological responses of this line for different days to low-Pi stress were characterized, and their roots as well as leaves were used to carry out transcriptome analysis, so as to illuminate the potential molecular pathways and identify the genes involved in low-Pi stress-response. After exposure to low-Pi treatment (32 µmol/L KH 2 PO 4 ) for 20 day after treatment (DAF) the biomass of shoots was significantly reduced in comparison with that of the stress-free (control), and root architecture diversely changed. For example, the root growth parameters e.g., length, surface area, and total volume somewhat increase in comparison with those of the control. The activity of acid phosphatase (ACP) increased with the low-Pi treatment, whereas the photosynthetic rate and biomass were declining. The activity of antioxidant enzymes, e.g., superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), were substantially elevated in response to low-Pi treatment. Many enzyme-related candidate genes e.g., MmCAT1 , MmSOD1 and MmPOD21 were up-regulated to low-Pi treatment. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the processes of photosynthesis, plant hormone signal transduction, and MAPK signaling pathway were affected in the low-Pi response. In combination with the physiological characterization, several low-Pi-responsive genes, e.g., PHT, PHO, were identified, and the genes implicated in Pi uptake and transport, such as MmPHT1;5 , MmPHO1 , MmPAP1 , etc., were also obtained since their expression status varied among the exposure times, which probably notifies the candidates involved in low-Pi-responsive tolerance in this line. Interestingly, low-Pi treatment activated the expression of transcription factors including the WRKY family, MYB family, etc. The available evidences will facilitate a better understanding of the roles of this line underlying the high tolerance to low-Pi stress. Additionally, the accessible data are helpful for the use of the apple rootstock M. mandshurica under low-Pi stress.

It is increasingly appreciated that transcripts derived from non-coding parts of the human genome, such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), are key regulators of biological processes both in normal physiology and disease. Their dysregulation during tumourigenesis has attracted significant interest in their exploitation as novel cancer therapeutics. Prostate cancer (PCa), as one of the most diagnosed malignancies and a leading cause of cancer-related death in men, continues to pose a major public health problem. In particular, survival of men with metastatic disease is very poor. Defects in DNA damage response (DDR) pathways culminate in genomic instability in PCa, which is associated with aggressive disease and poor patient outcome. Treatment options for metastatic PCa remain limited. Thus, researchers are increasingly targeting ncRNAs and DDR pathways to develop new biomarkers and therapeutics for PCa. Increasing evidence points to a widespread and biologically-relevant regulatory network of interactions between lncRNAs and miRNAs, with implications for major biological and pathological processes. This review summarises the current state of knowledge surrounding the roles of the lncRNA:miRNA interactions in PCa DDR, and their emerging potential as predictive and diagnostic biomarkers. We also discuss their therapeutic promise for the clinical management of PCa.

The morphology of polymer blends plays a critical role in determining the properties of the blends and performance of resulting injection-molded parts. However, it is currently impossible to predict the morphology evolution during injection molding and the final micro-structure of the molded parts, as the existing models for the morphology evolution of polymer blends are still limited to a few simple flow fields. To fill this gap, this paper proposed a novel model for droplet morphology evolution during the mold filling process of polymer blends by coupling the models on macro- and meso-scales. The proposed model was verified by the injection molding experiment of PP/POE blends. The predicted curve of mold cavity pressure during filling process agreed precisely with the data of the corresponding pressure sensors. On the other hand, the model successfully tracked the moving trajectory and simulated morphology evolution of the droplets during the mold-filling process. After mold-filling ended, the simulation results of the final morphology of the droplets were consistent with the observations of the scanning electron microscope (SEM) experiment. Moreover, this study revealed the underlying mechanism of the droplet morphology evolution through the force analysis on the droplet. It is validated that the present model is a qualified tool for simulating the morphology evolution of polymer blends during injection molding and predicting the final microstructure of the products.

Polydopamine-coated FeCo nanocubes (PDFCs) were successfully synthesized and tested under microwave irradiation of 2.45 GHz frequency and 0.86 W/cm(2) power. These particles were found to be non-toxic in the absence of irradiation, but gained significant toxicity upon irradiation. Interestingly, no increase in relative heating rate was observed when the PDFCs were irradiated in solution, eliminating nanoparticle (NP)-induced thermal ablation as the source of toxicity. Based on these studies, we propose that microwave-induced redox processes generate the observed toxicity.