LncRNA PSMB8-AS1 Instigates Vascular Inflammation to Aggravate Atherosclerosis.

BACKGROUND: Increasing evidence suggests that long noncoding RNAs play significant roles in vascular biology and disease development. One such long noncoding RNA, PSMB8-AS1, has been implicated in the development of tumors. Nevertheless, the precise role of PSMB8-AS1 in cardiovascular diseases, particularly atherosclerosis, has not been thoroughly elucidated. Thus, the primary aim of this investigation is to assess the influence of PSMB8-AS1 on vascular inflammation and the initiation of atherosclerosis. METHODS: We generated PSMB8-AS1 knockin and Apoe (Apolipoprotein E) knockout mice (Apoe-/-PSMB8-AS1KI) and global Apoe and proteasome subunit-ß type-9 (Psmb9) double knockout mice (Apoe-/-Psmb9-/-). To explore the roles of PSMB8-AS1 and Psmb9 in atherosclerosis, we fed the mice with a Western diet for 12 weeks. RESULTS: Long noncoding RNA PSMB8-AS1 is significantly elevated in human atherosclerotic plaques. Strikingly, Apoe-/-PSMB8-AS1KI mice exhibited increased atherosclerosis development, plaque vulnerability, and vascular inflammation compared with Apoe-/- mice. Moreover, the levels of VCAM1 (vascular adhesion molecule 1) and ICAM1 (intracellular adhesion molecule 1) were significantly upregulated in atherosclerotic lesions and serum of Apoe-/-PSMB8-AS1KI mice. Consistently, in vitro gain- and loss-of-function studies demonstrated that PSMB8-AS1 induced monocyte/macrophage adhesion to endothelial cells and increased VCAM1 and ICAM1 levels in a PSMB9-dependent manner. Mechanistic studies revealed that PSMB8-AS1 induced PSMB9 transcription by recruiting the transcription factor NONO (non-POU domain-containing octamer-binding protein) and binding to the PSMB9 promoter. PSMB9 (proteasome subunit-ß type-9) elevated VCAM1 and ICAM1 expression via the upregulation of ZEB1 (zinc finger E-box-binding homeobox 1). Psmb9 deficiency decreased atherosclerotic lesion size, plaque vulnerability, and vascular inflammation in Apoe-/- mice in vivo. Importantly, endothelial overexpression of PSMB8-AS1-increased atherosclerosis and vascular inflammation were attenuated by Psmb9 knockout. CONCLUSIONS: PSMB8-AS1 promotes vascular inflammation and atherosclerosis via the NONO/PSMB9/ZEB1 axis. Our findings support the development of new long noncoding RNA-based strategies to counteract atherosclerotic cardiovascular disease.

Lysine acetylation regulates the AT-rich DNA possession ability of H-NS.

H-NS, the histone-like nucleoid-structuring protein in bacteria, regulates the stability of the bacterial genome by inhibiting the transcription of horizontally transferred genes, such as the type III and type VI secretion systems (T3/T6SS). While eukaryotic histone posttranslational modifications (PTMs) have been extensively studied, little is known about prokaryotic H-NS PTMs. Here, we report that the acetylation of H-NS attenuates its ability to silence horizontally transferred genes in response to amino acid nutrition and immune metabolites. Moreover, LC-MS/MS profiling showed that the acetyllysine sites of H-NS and K120 are indispensable for its DNA-binding ability. Acetylation of K120 leads to a low binding affinity for DNA and enhances T3/T6SS expression. Furthermore, acetylation of K120 impairs the AT-rich DNA recognition ability of H-NS. In addition, lysine acetylation in H-NS modulates in vivo bacterial virulence. These findings reveal the mechanism underlying H-NS PTMs and propose a novel mechanism by which bacteria counteract the xenogeneic silencing of H-NS.

Electromagnetic Field-Assisted Frozen Tissue Planarization Enhances MALDI-MSI in Plant Spatial Omics.

Plant samples with irregular morphology are challenging for longitudinal tissue sectioning. This has restricted the ability to gain insight into some plants using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Herein, we develop a novel technique termed electromagnetic field-assisted frozen tissue planarization (EMFAFTP). This technique involves using a pair of adjustable electromagnets on both sides of a plant tissue. Under an optimized electromagnetic field strength, nondestructive planarization and regularization of the frozen tissue is induced, allowing the longitudinal tissue sectioning that favors subsequent molecular profiling by MALDI-MSI. As a proof of concept, flowers, leaves and roots with irregular morphology from six plant species are chosen to evaluate the performance of EMFAFTP for MALDI-MSI of secondary metabolites, amino acids, lipids, and proteins among others in the plant samples. The significantly enhanced MALDI-MSI capabilities of these endogenous molecules demonstrate the robustness of EMFAFTP and suggest it has the potential to become a standard technique for advancing MALDI-MSI into a new era of plant spatial omics.

2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, µm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.

Enhancement of in situ detection and imaging of phytohormones in plant tissues by MALDI-MSI using 2,4-dihydroxy-5-nitrobenzoic acid as a novel matrix.

Phytohormones possess unique chemical structures, and their physiological effects are regulated through intricate interactions or crosstalk among multiple phytohormones. MALDI-MSI enables the simultaneous detection and imaging of multiple hormones. However, its application for tracing phytohormones is currently restricted by low abundance of hormone in plant and suboptimal matrix selection. 2,4-Dihydroxy-5-nitrobenzoic acid (DHNBA) was reported as a new MALDI matrix for the enhanced detection and imaging of multiple phytohormones in plant tissues. DHNBA demonstrates remarkable sensitivity improvement when compared to the commonly used matrix, 2,5-dihydroxybenzoic acid (DHB), in the detection of isoprenoid cytokinins (trans-zeatin (tZ), dihy-drozeatin (DHZ), meta-topolin (mT), and N6-(Δ2-isopentenyl) adenine (iP)), jasmonic acid (JA), abscisic acid (ABA), and 1-aminocyclo-propane-1-carboxylic acid (ACC) standards. The distinctive properties of DHNBA (i.e. robust UV absorption, uniform matrix deposition, negligible background interference, and high ionization efficiency of phytohormones) make it as an ideal matrix for enhanced detection and imaging of phytohormones, including tZ, DHZ, ABA, indole-3-acetic acid (IAA), and ACC, by MALDI-MSI in various plant tissues, for example germinating seeds, primary/lateral roots, and nodules. Employing DHNBA significantly enhances our capability to concurrently track complex phytohormone biosynthesis pathways while providing precise differentiation of the specific roles played by individual phytohormones within the same category. This will propel forward the comprehensive exploration of phytohormonal functions in plant science.

The B. subtilis Rok protein is an atypical H-NS-like protein irresponsive to physico-chemical cues.

Nucleoid-associated proteins (NAPs) play a central role in chromosome organization and environment-responsive transcription regulation. The Bacillus subtilis-encoded NAP Rok binds preferentially AT-rich regions of the genome, which often contain genes of foreign origin that are silenced by Rok binding. Additionally, Rok plays a role in chromosome architecture by binding in genomic clusters and promoting chromosomal loop formation. Based on this, Rok was proposed to be a functional homolog of E. coli H-NS. However, it is largely unclear how Rok binds DNA, how it represses transcription and whether Rok mediates environment-responsive gene regulation. Here, we investigated Rok's DNA binding properties and the effects of physico-chemical conditions thereon. We demonstrate that Rok is a DNA bridging protein similar to prototypical H-NS-like proteins. However, unlike these proteins, the DNA bridging ability of Rok is not affected by changes in physico-chemical conditions. The DNA binding properties of the Rok interaction partner sRok are affected by salt concentration. This suggests that in a minority of Bacillus strains Rok activity can be modulated by sRok, and thus respond indirectly to environmental stimuli. Despite several functional similarities, the absence of a direct response to physico-chemical changes establishes Rok as disparate member of the H-NS family.

2,5-Dihydroxyterephthalic Acid: A Matrix for Improved Detection and Imaging of Amino Acids.

Amino acids (AAs), which are low-molecular-weight (low-MW) metabolites, serve as essential building blocks not only for protein synthesis but also for maintaining the nitrogen balance in living systems. In situ detection and imaging of AAs are crucial for understanding more complex biological processes. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a label-free mass spectrometric imaging technique that enables the simultaneous detection and imaging of the spatial distribution and relative abundance of different endogenous/exogenous compounds in biological samples. The excellent efficiency of MALDI-MSI is attributed to the choice of the MALDI matrix. However, to the best of our knowledge, no matrix has been specifically developed for AAs. Herein, we report a MALDI matrix, 2,5-dihydroxyterephthalic acid (DHT), which can improve the detection and imaging of AAs in biological samples by MALDI-MS. Our results indicated that DHT exhibited strong ultraviolet-visible (UV-vis) absorption, uniform matrix deposition, and high vacuum stability. Moreover, the matrix-related ion signals produced from DHT were reduced by 50 and 71.8% at m/z < 500 compared to the commonly used matrices of 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA), respectively, in their respective organic solvents. In terms of quantitative performance, arginine, glutamic acid, glutamine, and proline can be detected with limits of detection of 6, 4, 6, and 4 ng/mL, respectively, using the DHT as the matrix. Using DHT as the matrix, all 20 protein AAs were successfully detected in human serum by MALDI-MS, whereas only 7 and 10 AAs were detected when DHB and CHCA matrices were used, respectively. Furthermore, 20 protein AAs and taurine were successfully detected and imaged in a section of edible Crassostrea gigas (oyster) tissue for the first time. Our study demonstrates that using DHT as a matrix can improve the detection and imaging of AAs in biological samples by MALDI-MS.

High-throughput MALDI-MSI metabolite analysis of plant tissue microarrays.

A novel metabolomics analysis technique, termed matrix-assisted laser desorption/ionization mass spectrometry imaging-based plant tissue microarray (MALDI-MSI-PTMA), was successfully developed for high-throughput metabolite detection and imaging from plant tissues. This technique completely overcomes the disadvantage that metabolites cannot be accessible on an intact plant tissue due to the limitations of the special structures of plant cells (e.g. epicuticular wax, cuticle and cell wall) through homogenization of plant tissues, preparation of PTMA moulds and matrix spraying of PTMA sections. Our study shows several properties of MALDI-MSI-PTMA, including no need of sample separation and enrichment, high-throughput metabolite detection and imaging (>1000 samples per day), high-stability mass spectrometry data acquisition and imaging reconstruction and high reproducibility of data. This novel technique was successfully used to quickly evaluate the effects of two plant growth regulator treatments (i.e. 6-benzylaminopurine and N-phenyl-N'-1,2,3-thiadiazol-5-ylurea) on endogenous metabolite expression in plant tissue culture specimens of Dracocephalum rupestre Hance (D. rupestre). Intra-day and inter-day evaluations indicated that the metabolite data detected on PTMA sections had good reproducibility and stability. A total of 312 metabolite ion signals in leaves tissues of D. rupestre were detected, of which 228 metabolite ion signals were identified, they were composed of 122 primary metabolites, 90 secondary metabolites and 16 identified metabolites of unknown classification. The results demonstrated the advantages of MALDI-MSI-PTMA technique for enhancing the overall detection ability of metabolites in plant tissues, indicating that MALDI-MSI-PTMA has the potential to become a powerful routine practice for high-throughput metabolite study in plant science.

A concentration-descending washing strategy with methanol for the enhancement of protein imaging in biological tissues by MALDI-MS.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a powerful approach that has been widely used for in situ detection of various endogenous compounds in tissues. However, there are still challenges with in situ analysis of proteins using MALDI-MSI due to the ion suppression effects of small molecules in tissue sections. Therefore, tissue-washing steps are crucial for protein MALDI tissue imaging to remove these interfering molecules. Here, we successfully developed a new method named the concentration-descending washing strategy (CDWS) with methanol (MeOH), i.e., washing of biological tissue with 100%, 95%, and 70% MeOH solutions, for the enhancement of endogenous in situ protein detection and imaging in tissues using MALDI-MS. The method of MeOH-based CDWS (MeOH-CDWS) led to the successful in situ detection of 272 ± 3, 185 ± 4, and 134 ± 2 protein ion signals from rat liver, rat brain, and germinating Chinese-yew seed tissue sections, respectively. By comparison, 161 ± 2, 121 ± 1, and 114 ± 2 protein ions were detected by three commonly used methods, i.e., Carnoy's wash, ethanol (EtOH)-based CAWS (i.e., concentration-ascending washing strategy, 70% EtOH followed by 90% EtOH/9% AcOH), and isopropanol (iPrOH)-based CAWS (70% iPrOH followed by 95% iPrOH), respectively, in rat liver tissue sections, indicating that 68.9 ± 3.1%, 124.8 ± 3.3%, and 138.6 ± 4.4% more protein ion signals could be detected by the use of MeOH-CDWS than the three abovementioned washing strategies. Our results show that the use of MeOH-CDWS improves the performance of MALDI-MSI for in situ protein detection such as the number and intensity of proteins. The use of MeOH-CDWS improves the fixation of proteins and thus reduces the loss of proteins, which significantly reduces protein delocalization in tissue and enhances the performance of MALDI tissue imaging of protein. Thus, the use of MeOH-CDWS improves the quality of protein images in tissue sections through MALDI-MSI and has the potential to be used as standard practice for MALDI tissue imaging of proteins.

Novel anti-repression mechanism of H-NS proteins by a phage protein.

H-NS family proteins, bacterial xenogeneic silencers, play central roles in genome organization and in the regulation of foreign genes. It is thought that gene repression is directly dependent on the DNA binding modes of H-NS family proteins. These proteins form lateral protofilaments along DNA. Under specific environmental conditions they switch to bridging two DNA duplexes. This switching is a direct effect of environmental conditions on electrostatic interactions between the oppositely charged DNA binding and N-terminal domains of H-NS proteins. The Pseudomonas lytic phage LUZ24 encodes the protein gp4, which modulates the DNA binding and function of the H-NS family protein MvaT of Pseudomonas aeruginosa. However, the mechanism by which gp4 affects MvaT activity remains elusive. In this study, we show that gp4 specifically interferes with the formation and stability of the bridged MvaT-DNA complex. Structural investigations suggest that gp4 acts as an 'electrostatic zipper' between the oppositely charged domains of MvaT protomers, and stabilizes a structure resembling their 'half-open' conformation, resulting in relief of gene silencing and adverse effects on P. aeruginosa growth. The ability to control H-NS conformation and thereby its impact on global gene regulation and growth might open new avenues to fight Pseudomonas multidrug resistance.

Coordinate Fault Ride-Through Strategy for Connection of Offshore Wind Farms Using Voltage Source-Converter-Based High-Voltage Direct-Current Transmission under Single Polar Fault.

In a system where wind farms are connected to the grid via a bipolar flexible DC transmission, the occurrence of a short-time fault at one of the poles results in the active power emitted by the wind farm being transmitted through the non-faulty pole. This condition leads to an overcurrent in the DC system, thereby causing the wind turbine to disconnect from the grid. Addressing this issue, this paper presents a novel coordinated fault ride-through strategy for flexible DC transmission systems and wind farms, which eliminates the need for additional communication equipment. The proposed strategy leverages the power characteristics of the doubly fed induction generator (DFIG) under different terminal voltage conditions. By considering the safety constraints of both the wind turbine and the DC system, as well as optimizing the active power output during wind farm faults, the strategy establishes guidelines for the wind farm bus voltage and the crowbar switch signal. Moreover, it harnesses the power regulation capability of the DFIG rotor-side crowbar circuit to enable fault ride-through in the presence of single-pole short-time faults in the DC system. Simulation results demonstrate that the proposed coordinated control strategy effectively mitigates overcurrent in the non-faulty pole of flexible DC transmission during fault conditions.

An Emergency Coordinated Control Strategy to Improve the Transient Stability of a Single-Ended Distribution Network with Flexible Interconnection Channel Blocking.

Based on the scenario of high-penetration distributed photovoltaic connected to an AC/DC distribution network, this paper analyzes the dynamic characteristics of frequency and voltage in a distribution network after the blocking failure of the flexible interconnection channel. In order to enhance the transient stability of the system after the fault, this paper comprehensively considers the active regulation ability of photovoltaic units, and puts forward an emergency coordinated control strategy for a single-ended distribution network with flexible interconnection channel blocking. Firstly, the non-fault channel is overloaded for a short time, then the comprehensive influence of factors such as electrical distance, response time and adjustment cost on the frequency modulation effect of the system is quantitatively evaluated; according to the evaluation results, the photovoltaic and synchronous units are controlled by "control instead of tripping", and finally, the high-frequency tripping is carried out, based on the principle of "photovoltaics first". After the frequency control is completed, the reactive power optimization model of the system is established, and the improved tabu-particle swarm optimization algorithm is used to solve it, so as to optimize the voltage of the distribution network nodes. Finally, an equivalent simulation model is established to verify the coordinated control strategy.

A Collaborative Governance Strategy for Power Quality in AC/DC Distribution Networks Considering the Coupling Characteristics of Both Sides.

The interactions between power quality in the AC-DC distribution network segments contribute to the distributed propagation of power quality anomalies throughout the entire network. Focusing on the photovoltaic multifunctional grid-connected inverter (PVMFGCI), this study deeply explores a collaborative governance strategy for optimizing regional power quality. Initially, the analysis dissects the DC ripple generation mechanism corresponding to harmonics and asymmetry in AC subnetwork voltages. Subsequently, a strategy is proposed for partitioning comprehensive control regions for AC-side power quality, taking into account photovoltaic governance resources based on insights from photovoltaic control realms and power quality classifications. Further, a collaborative allocation model for governance resources incorporating active optimization potentials of grid-connected converters is established based on the governance capabilities and residual capacities of PVMFGCI. Finally, the effectiveness of the proposed approach is validated through a MATLAB-based example analysis.

A Lightweight Algorithm for Insulator Target Detection and Defect Identification.

The accuracy of insulators and their defect identification by UAVs (unmanned aerial vehicles) in transmission-line inspection needs to be further improved, and the model size of the detection algorithm is significantly reduced to make it more suitable for edge-end deployment. In this paper, the algorithm uses a lightweight GhostNet module to reconstruct the backbone feature extraction network of the YOLOv4 model and employs depthwise separable convolution in the feature fusion layer. The model is lighter on the premise of ensuring the effect of image information extraction. Meanwhile, the ECA-Net channel attention mechanism is embedded into the feature extraction layer and PANet (Path Aggregation Network) to improve the recognition accuracy of the model for small targets. The experimental results show that the size of the improved model is reduced from 244 MB to 42 MB, which is only 17.3% of the original model. At the same time, the mAp of the improved model is 0.77% higher than that of the original model, reaching 95.4%. Moreover, the mAP compared with YOLOv5-s and YOLOX-s, respectively, is improved by 1.98% and 1.29%. Finally, the improved model is deployed into Jetson Xavier NX and run at a speed of 8.8 FPS, which is 4.3 FPS faster than the original model.

A Novel Ensemble Fault Diagnosis Model for Main Circulation Pumps of Converter Valves in VSC-HVDC Transmission Systems.

The intelligent fault diagnosis of main circulation pumps is crucial for ensuring their safe and stable operation. However, limited research has been conducted on this topic, and applying existing fault diagnosis methods designed for other equipment may not yield optimal results when directly used for main circulation pump fault diagnosis. To address this issue, we propose a novel ensemble fault diagnosis model for the main circulation pumps of converter valves in voltage source converter-based high voltage direct current transmission (VSG-HVDC) systems. The proposed model employs a set of base learners already able to achieve satisfying fault diagnosis performance and a weighting model based on deep reinforcement learning that synthesizes the outputs of these base learners and assigns different weights to obtain the final fault diagnosis results. The experimental results demonstrate that the proposed model outperforms alternative approaches, achieving an accuracy of 95.00% and an F1 score of 90.48%. Compared to the widely used long and short-term memory artificial neural network (LSTM), the proposed model exhibits improvements of 4.06% in accuracy and 7.85% in F1 score. Furthermore, it surpasses the latest existing ensemble model based on the improved sparrow algorithm, with enhancements of 1.56% in accuracy and 2.91% in F1 score. This work presents a data-driven tool with high accuracy for the fault diagnosis of main circulation pumps, which plays a critical role in maintaining the operational stability of VSG-HVDC systems and satisfying the unmanned requirements of offshore flexible platform cooling systems.

TransFNN: A Novel Overtemperature Prediction Method for HVDC Converter Valves Based on an Improved Transformer and the F-NN Algorithm.

Appropriate cooling of the converter valve in a high-voltage direct current (HVDC) transmission system is highly significant for the safety, stability, and economical operation of a power grid. The proper adjustment of cooling measures is based on the accurate perception of the valve's future overtemperature state, which is characterized by the valve's cooling water temperature. However, very few previous studies have focused on this need, and the existing Transformer model, which excels in time-series predictions, cannot be directly applied to forecast the valve overtemperature state. In this study, we modified the Transformer and present a hybrid Transformer-FCM-NN (TransFNN) model to predict the future overtemperature state of the converter valve. The TransFNN model decouples the forecast process into two stages: (i) The modified Transformer is used to obtain the future values of the independent parameters; (ii) the relation between the valve cooling water temperature and the six independent operating parameters is fit, and the output of the Transformer is used to calculate the future values of the cooling water temperature. The results of the quantitative experiments showed that the proposed TransFNN model outperformed other models with which it was compared; with TransFNN being applied to predict the overtemperature state of the converter valves, the forecast accuracy was 91.81%, which was improved by 6.85% compared with that of the original Transformer model. Our work provides a novel approach to predicting the valve overtemperature state and acts as a data-driven tool for operation and maintenance personnel to use to adjust valve cooling measures punctually, effectively, and economically.

Synthesis and bioactivity evaluation of novel nuciferine derivatives with antihyperuricemia and nephroprotective effects.

Hyperuricemia is a common metabolic disease with a series of complications. Nuciferine, a typical aporphine alkaloid natural compound extracted from the leaves of Nelumbo nucifera Gaertn., was confirmed to have an antihyperuricemia effect. In the present study, 30 novel nuciferine derivatives were designed and synthesized. The effects of all derivatives on the regulation of URAT1 were studied in a uric acid-induced HK-2 cell model with benzbromarone as a positive control. The results indicated that Compound 1j showed the optimal URAT1 inhibitory activity through repressing PI3K/Akt pathway in HK-2 cells and the inhibitory effect was similar to that of benzbromarone. In addition, in vivo experiments demonstrated that Compound 1j could reduce uric acid levels and ameliorate kidney damage in hyperuricemic mice. On the one hand, Compound 1j could inhibit the expression of URAT1 and GLUT9 to increase the uric acid excretion index. On the other hand, Compound 1j could regulate the TLR4/IκBα/NF-κB signaling pathway to reduce the levels of inflammatory cytokines, thereby alleviating kidney damage. Meanwhile, a molecular docking assay revealed the potential molecular binding power (-9.79 kcal/mol) between Compound 1j and URAT1, which was more tightly bound than the lead compound nuciferine (-7.44 kcal/mol). Based on these results, Compound 1j may be a future drug for the development of new potential antihyperuricemia and nephroprotective drug candidates.

Structural basis for osmotic regulation of the DNA binding properties of H-NS proteins.

H-NS proteins act as osmotic sensors translating changes in osmolarity into altered DNA binding properties, thus, regulating enterobacterial genome organization and genes transcription. The molecular mechanism underlying the switching process and its conservation among H-NS family members remains elusive. Here, we focus on the H-NS family protein MvaT from Pseudomonas aeruginosa and demonstrate experimentally that its protomer exists in two different conformations, corresponding to two different functional states. In the half-opened state (dominant at low salt) the protein forms filaments along DNA, in the fully opened state (dominant at high salt) the protein bridges DNA. This switching is a direct effect of ionic strength on electrostatic interactions between the oppositely charged DNA binding and N-terminal domains of MvaT. The asymmetric charge distribution and intramolecular interactions are conserved among the H-NS family of proteins. Therefore, our study establishes a general paradigm for the molecular mechanistic basis of the osmosensitivity of H-NS proteins.

Superior results of return to sport after double-bundle versus single-bundle anterior cruciate ligament reconstruction in young active patients.

PURPOSE: To compare return to sport and clinical results in young active patients who underwent anatomic single-bundle (SB) versus double-bundle (DB) anterior cruciate ligament reconstruction (ACLR). METHODS: Young active patients undergoing SB or DB ACLR from 2017 to 2019 at our institution were retrospectively reviewed. The primary outcome measures were the rate and time to return to sports, with secondary measures including the Lachman test, pivot shift test, Lysholm scores, International Knee Documentation Committee (IKDC) scores and graft rupture. RESULTS: The study included a total of 90 patients (DB group, 42; SB group, 48), with a mean follow-up of 27.1 ± 6.1 months. Young active patients who underwent DB ACLR had a higher rate of return to pivoting sports than those who underwent SB ACLR (HR = 2.4; 95% confidence interval [CI]: 1.4, 4.1; p = 0.013). The DB group returned to pivoting sports at a mean ± SD of 11.0 ± 2.9 months compared with 12.7 ± 2.7 months in the SB group (p = 0.01). There was one traumatic failure in the SB group and one contralateral ACL rupture in the DB group. There was no significant difference in the rate and time to return to running, Lachman test, pivot-shift test, Lysholm or IKDC scores in either group. CONCLUSION: Both anatomical SB and DB techniques achieved satisfactory clinical outcomes. DB techniques led to superior performance of return to pivoting sports but nonsignificant differences in time and rate of return to running, passive stability measurement, subjective knee function outcome and graft rupture rate in both groups at the 2-year follow-up. The DB ACLR should be considered a viable option to treat young patients with high activity demands. LEVEL OF EVIDENCE: III.

Improved Algorithm for Insulator and Its Defect Detection Based on YOLOX.

Aerial insulator defect images have some features. For instance, the complex background and small target of defects would make it difficult to detect insulator defects quickly and accurately. To solve the problem of low accuracy of insulator defect detection, this paper concerns the shortcomings of IoU and the sensitivity of small targets to the model regression accuracy. An improved SIoU loss function was proposed based on the regular influence of regression direction on the accuracy. This loss function can accelerate the convergence of the model and make it achieve better results in regressions. For complex backgrounds, ECA (Efficient Channel Attention Module) is embedded between the backbone and the feature fusion layer of the model to reduce the influence of redundant features on the detection accuracy and make progress in the aspect. As a result, these experiments show that the improved model achieved 97.18% mAP which is 2.74% higher than before, and the detection speed could reach 71 fps. To some extent, it can detect insulator and its defects accurately and in real-time.