Integrated Hfq-interacting RNAome and transcriptomic analysis reveals complex regulatory networks of nitrogen fixation in root-associated Pseudomonas stutzeri A1501.

The RNA chaperone Hfq acts as a global regulator of numerous biological processes, such as carbon/nitrogen metabolism and environmental adaptation in plant-associated diazotrophs; however, its target RNAs and the mechanisms underlying nitrogen fixation remain largely unknown. Here, we used enhanced UV cross-linking immunoprecipitation coupled with high-throughput sequencing to identify hundreds of Hfq-binding RNAs probably involved in nitrogen fixation, carbon substrate utilization, biofilm formation, and other functions. Collectively, these processes endow strain A1501 with the requisite capabilities to thrive in the highly competitive rhizosphere. Our findings revealed a previously uncharted landscape of Hfq target genes. Notable among these is nifM, encoding an isomerase necessary for nitrogenase reductase solubility; amtB, encoding an ammonium transporter; oprB, encoding a carbohydrate porin; and cheZ, encoding a chemotaxis protein. Furthermore, we identified more than 100 genes of unknown function, which expands the potential direct regulatory targets of Hfq in diazotrophs. Our data showed that Hfq directly interacts with the mRNA of regulatory proteins (RsmA, AlgU, and NifA), regulatory ncRNA RsmY, and other potential targets, thus revealing the mechanistic links in nitrogen fixation and other metabolic pathways. IMPORTANCE: Numerous experimental approaches often face challenges in distinguishing between direct and indirect effects of Hfq-mediated regulation. New technologies based on high-throughput sequencing are increasingly providing insight into the global regulation of Hfq in gene expression. Here, enhanced UV cross-linking immunoprecipitation coupled with high-throughput sequencing was employed to identify the Hfq-binding sites and potential targets in the root-associated Pseudomonas stutzeri A1501 and identify hundreds of novel Hfq-binding RNAs that are predicted to be involved in metabolism, environmental adaptation, and nitrogen fixation. In particular, we have shown Hfq interactions with various regulatory proteins' mRNA and their potential targets at the posttranscriptional level. This study not only enhances our understanding of Hfq regulation but, importantly, also provides a framework for addressing integrated regulatory network underlying root-associated nitrogen fixation.

Epigallocatechin-3-gallate derived polymer coated Prussian blue for synergistic ROS elimination and antibacterial therapy.

Reactive oxygen species (ROS) play a vital role in wound healing process by fighting against invaded bacteria. However, excess ROS at the wound sites lead to oxidative stress that can trigger deleterious effects, causing cell death, tissue damage and chronic inflammation. Therefore, we fabricated a core-shell structured nanomedicine with antibacterial and antioxidant properties via a facile and green strategy. Specifically, Prussian blue (PB) nanozyme was fabricated and followed by coating a layer of epigallocatechin-3-gallate (EGCG)-derived polymer via polyphenolic condensation reaction and self-assembly process, resulting in PB@EGCG. The introduction of PB core endowed EGCG-based polyphenol nanoparticles with excellent NIR-triggered photothermal properties. Besides, owing to multiple enzyme-mimic activity of PB and potent antioxidant capacity of EGCG-derived polymer, PB@EGCG exhibited a remarkable ROS-scavenging ability, mitigated intracellular ROS level and protected cells from oxidative damage. Under NIR irradiation (808 nm, 1.5 W/cm2), PB@EGCG (50 µg/mL) exerted synergistic EGCG-derived polymer-photothermal antibacterial activity against Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus). In vivo therapeutic effect was evaluated using a S. aureus-infected rat model indicated PB@EGCG with a prominent bactericidal ability could modulate the inflammatory microenvironment and accelerate wound healing. Overall, this dual-functional nanomedicine provides a promising strategy for efficient antibacterial therapy.

Research on an Adaptive Method for the Angle Calibration of Roadside LiDAR Point Clouds.

Light Detection and Ranging (LiDAR), a laser-based technology for environmental perception, finds extensive applications in intelligent transportation. Deployed on roadsides, it provides real-time global traffic data, supporting road safety and research. To overcome accuracy issues arising from sensor misalignment and to facilitate multi-sensor fusion, this paper proposes an adaptive calibration method. The method defines an ideal coordinate system with the road's forward direction as the X-axis and the intersection line between the vertical plane of the X-axis and the road surface plane as the Y-axis. This method utilizes the Kalman filter (KF) for trajectory smoothing and employs the random sample consensus (RANSAC) algorithm for ground fitting, obtaining the projection of the ideal coordinate system within the LiDAR system coordinate system. By comparing the two coordinate systems and calculating Euler angles, the point cloud is angle-calibrated using rotation matrices. Based on measured data from roadside LiDAR, this paper validates the calibration method. The experimental results demonstrate that the proposed method achieves high precision, with calculated Euler angle errors consistently below 1.7%.

A Model Transfer Method among Spectrometers Based on Improved Deep Autoencoder for Concentration Determination of Heavy Metal Ions by UV-Vis Spectra.

Ultraviolet Visible (UV-Vis) spectroscopy detection technology has been widely used in quantitative analysis for its advantages of rapid and non-destructive determination. However, the difference of optical hardware severely restricts the development of spectral technology. Model transfer is one of the effective methods to establish models on different instruments. Due to the high dimension and nonlinearity of spectral data, the existing methods cannot effectively extract the hidden differences in spectra of different spectrometers. Thus, based on the necessity of spectral calibration model transfer between the traditional large spectrometer and the micro-spectrometer, a novel model transfer method based on improved deep autoencoder is proposed to realize spectral reconstruction between different spectrometers. Firstly, two autoencoders are used to train the spectral data of the master and slave instrument, respectively. Then, the hidden variable constraint is added to enhance the feature representation of the autoencoder, which makes the two hidden variables equal. Combined with a Bayesian optimization algorithm for the objective function, the transfer accuracy coefficient is proposed to characterize the model transfer performance. The experimental results show that after model transfer, the spectrum of the slave spectrometer is basically coincident with the master spectrometer and the wavelength shift is eliminated. Compared with the two commonly used direct standardization (DS) and piecewise direct standardization (PDS) algorithms, the average transfer accuracy coefficient of the proposed method is improved by 45.11% and 22.38%, respectively, when there are nonlinear differences between different spectrometers.

Dynamic Calibration Method of Sensor Drift Fault in HVAC System Based on Bayesian Inference.

Sensor drift fault calibration is essential to maintain the operation of heating, ventilation and air conditioning systems (HVAC) in buildings. Bayesian inference (BI) is becoming more and more popular as a commonly used sensor fault calibration method. However, this method focused mainly on sensor bias fault, and it could be difficult to calibrate drift fault that changes with time. Therefore, a dynamic calibration method for sensor drift fault of HVAC systems based on BI is developed. Taking the drift fault calibration of the chilled water supply temperature sensor of the chiller as an example, the performance of the proposed dynamic calibration method is evaluated. Results show that the combination of the Exponentially Weighted Moving-Average (EWMA) method with high detection accuracy and the proposed BI dynamic calibration method can effectively improve the calibration accuracy of drift fault, and the Mean Absolute Percentage Error (MAPE) value between the calibrated and normal data is less than 5%.

Analysis of Drought and Flood Variations on a 200-Year Scale Based on Historical Environmental Information in Western China.

Historical environmental evidence has been characterized by time accuracy, high spatial resolution and rich information, which may be widely used in the reconstruction of historical data series. Taking the upper reaches of the Weihe River as an example in Western China, the grades and index sequences of the drought and flood disasters from 1800 to 2016 were reconstructed based on various historical environmental information and standardized precipitation indicator (SPI). Moreover, the characteristics of droughts and floods were analyzed using statistical diagnostic methods, and the mechanisms affecting centennial-scale droughts and floods were discussed. The validity of reconstruction sequence of droughts/floods was verified, which showed that the reconstruction sequence may reasonably indicate the status of drought and flood. The reconstruction indicated the following periods of drought/flood: a period of extreme and big droughts in 1835s-1893s, 1924s-1943s and 1984s-2008s, a period of extreme and big floods in 1903s-1923s, and a period of extreme and big droughts/floods in 1944s-1983s. Moreover, the droughts were more serious in the western part of this region and the floods were relatively severe in the east of this region, while the droughts and floods have long-term period of about 100 years and mutation. The influence mechanism of external environmental forcing factors driving floods/droughts were revealed. The results showed that the cycle of El Niño Southern Oscillation (ENSO) and sunspot activities were closely related to the variations of drought/flood, meanwhile, ENSO has a significant lag time scale cumulative influence on droughts and floods, especially the 15-year sliding effect was the most obvious. In the peak year of sunspots, the probability of heavy drought/extreme floods was large, and the 102-year sunspot cycle has a more significant effect on drought and flood disasters. The mutation of droughts and floods occurred in the context of the drastic changes in the ground environment, and transformation of precipitation and land use structure. These results will enhance the understandings of historical environmental climate characteristics and mechanisms over the hundred years, and be useful for the future regional water resources and assessment, and ecological environment management.

Trends and Frontiers of Research on Cancer Gene Therapy From 2016 to 2020: A Bibliometric Analysis.

Background: With rapid development in molecular biology techniques and a greater understanding of cancer pathogenesis, the growing attention has been concentrated on cancer gene therapy, with numerous articles on this topic published in recent 5 years. However, there is lacking a bibliometric analysis of research on cancer gene therapy. Therefore, the aim of the present study was to conduct a bibliometric analysis to provide the trends and frontiers of research on cancer gene therapy during 2016-2020. Methods: We utilized CiteSpace 5.7.R5 software to conduct a bibliometric analysis of publications on cancer gene therapy published during 2016-2020. The bibliometric records were obtained from the Web of Science Core Collection. Results: A total of 4,392 papers were included in the bibliometric analysis. Materials Science and Nanoscience and Nanotechnology took an increasing part in the field of cancer gene therapy. Additionally, WANG W was the most productive author, while ZHANG Y ranked top in terms of citations. Harvard Medical School and Sichuan University ranked top in the active institutions. P NATL ACAD SCI USA was identified as the core journal in the field of cancer gene therapy. "Ovarian cancer" was found to be the latest keyword with the strongest burst. The keyword analysis suggested that the top three latest clusters were labeled "gene delivery," "drug delivery," and "gene therapy." In the reference analysis, cluster#2 labeled "gene delivery" held a dominant place considering both the node volume and mean year. Conclusion: The academic attention on cancer gene therapy was growing at a dramatically high speed. Materials Science and Nanoscience and Nanotechnology might become promising impetus for the development of this field. "Gene delivery" was thought to best reflect the research frontier on cancer gene therapy. The top-cited articles on gene delivery were focused on several novel non-viral vectors due to their specialty compared with viral vectors. "Ovarian cancer" was likely to be the potential research direction. These findings would help medical workers conduct further investigations on cancer gene therapy.