Emergence and ongoing outbreak of ST80 vancomycin-resistant Enterococcus faecium in Guangdong province, China from 2021 to 2023: a multicenter, time-series and genomic epidemiological studyEpidemiology of vancomycin-resistant Enterococcus faecium.

BACKGROUND: Surveillance systems revealed that the prevalence of vancomycin-resistant Enterococcus faecium (VREfm) has increased. We aim to investigate the epidemiological and genomic characteristics of VREfm in China. METHODS: We collected 20747 non-redundant E. faecium isolates from inpatients across 19 hospitals in six provinces between Jan 2018 and June 2023. VREfm was confirmed by antimicrobial susceptibility testing. The prevalence was analyzed using changepoint package in R. Genomic characteristics were explored by whole-genome sequencing. RESULTS: 5.59% (1159/20747) of E. faecium isolates were resistant to vancomycin. The prevalence of VREfm increased in Guangdong province from 5% before 2021 to 20%-50% in 2023 (p < 0.0001), but not in the other five provinces. Two predominant clones before 2021, ST17 and ST78, were substituted by an emerging clone, ST80, from 2021 to 2023 (88.63%, 195/220). All ST80 VREfm from Guangdong formed a single lineage (SC11) and were genetically distant from the ST80 VREfm from other countries, suggesting a regional outbreak. All ST80 VREfm in SC11 carried a new type of plasmid harboring a vanA cassette, which was embedded in a Tn1546-like structure flanked by IS1678 and ISL3. However, no conjugation-related gene was detected and no transconjugant was obtained in conjugation experiment, indicating that the outbreak of ST80 VREfm could be attributed to clonal transmission. CONCLUSIONS: We revealed an ongoing outbreak of ST80 VREfm with a new vanA-harboring plasmid in Guangdong, China. This clone has also been identified in other provinces and countries, foreboding a risk of wider spreading shortly. Continuous surveillance is needed to inform public health interventions.

Determination of pulmonary vessel alteration in Chinese male smokers by quantitative computed tomography measurements: a retrospective study.

Background: The blood volume of intraparenchymal vessels is reported to be increased in smokers. However, the blood volume can be affected by many confounders besides tobacco exposure. This study aimed to investigate the association between cigarette smoking and pulmonary blood volume after adjusting the related factors in a large cohort of Chinese males. Methods: In this retrospective study, male participants admitted to the First Affiliated Hospital of Xi'an Jiaotong University for annual health assessment between February 2017 and February 2018 were enrolled. All subjects underwent non-contrast chest computed tomography (CT) scans, and 152 subjects underwent a review CT scan 2-3 years later. A three-dimensional approach was employed to segment the lung and intrapulmonary vessels and quantitative CT (QCT) measurements, including lung volume (LV), intrapulmonary vessel volume (IPVV), low-attenuation area <-950 Hounsfield unit (LAA-950 and LAA-950%), and mean lung density (MLD). Linear regression was used to estimate the association between IPVV and the smoking index (SI). A paired t-test was used to compare the QCT parameters between the initial and follow-up CT scans. Results: A total of 656 male participants were enrolled and classified into three subgroups: non-smokers (n=311), current smokers (n=267), and former smokers (n=78). The IPVV of current smokers (134.62±23.96 vs. 120.76±25.52 mL) and former smokers (130.79±25.13 vs. 120.76±25.52 mL) were significantly larger than that of non-smokers (P<0.05). A higher SI was associated with greater IPVV [non-standardized coefficient: 0.167, 95% confidence interval (CI): 0.086-0.248]. For current smokers, the IPVV of the follow-up scan significantly increased compared to its baseline scan (135.49±28.60 vs. 129.73±29.75 mL, t=-2.326, P=0.02), but for the non-smokers and former smokers, the IPVV of the follow-up scan did not increase or decrease compared to the baseline scan (P>0.05). Conclusions: Pulmonary vascular volumes detectable on non-contrast CT are associated with cigarette exposure, and smoking cessation may prevent pulmonary vasculature remodeling.

Stereoscopic artificial compound eyes for spatiotemporal perception in three-dimensional space.

Arthropods' eyes are effective biological vision systems for object tracking and wide field of view because of their structural uniqueness; however, unlike mammalian eyes, they can hardly acquire the depth information of a static object because of their monocular cues. Therefore, most arthropods rely on motion parallax to track the object in three-dimensional (3D) space. Uniquely, the praying mantis (Mantodea) uses both compound structured eyes and a form of stereopsis and is capable of achieving object recognition in 3D space. Here, by mimicking the vision system of the praying mantis using stereoscopically coupled artificial compound eyes, we demonstrated spatiotemporal object sensing and tracking in 3D space with a wide field of view. Furthermore, to achieve a fast response with minimal latency, data storage/transportation, and power consumption, we processed the visual information at the edge of the system using a synaptic device and a federated split learning algorithm. The designed and fabricated stereoscopic artificial compound eye provides energy-efficient and accurate spatiotemporal object sensing and optical flow tracking. It exhibits a root mean square error of 0.3 centimeter, consuming only approximately 4 millijoules for sensing and tracking. These results are more than 400 times lower than conventional complementary metal-oxide semiconductor-based imaging systems. Our biomimetic imager shows the potential of integrating nature's unique design using hardware and software codesigned technology toward capabilities of edge computing and sensing.

Bidirectional regulation of levodopa-induced dyskinesia by a specific neural ensemble in globus pallidus external segment.

Levodopa-induced dyskinesia (LID) is an intractable motor complication arising in Parkinson's disease with the progression of disease and chronic treatment of levodopa. However, the specific cell assemblies mediating dyskinesia have not been fully elucidated. Here, we utilize the activity-dependent tool to identify three brain regions (globus pallidus external segment [GPe], parafascicular thalamic nucleus, and subthalamic nucleus) that specifically contain dyskinesia-activated ensembles. An intensity-dependent hyperactivity in the dyskinesia-activated subpopulation in GPe (GPeTRAPed in LID) is observed during dyskinesia. Optogenetic inhibition of GPeTRAPed in LID significantly ameliorates LID, whereas reactivation of GPeTRAPed in LID evokes dyskinetic behavior in the levodopa-off state. Simultaneous chemogenetic reactivation of GPeTRAPed in LID and another previously reported ensemble in striatum fully reproduces the dyskinesia induced by high-dose levodopa. Finally, we characterize GPeTRAPed in LID as a subset of prototypic neurons in GPe. These findings provide theoretical foundations for precision medication and modulation of LID in the future.

Brachyury promotes extracellular matrix synthesis through transcriptional regulation of Smad3 in nucleus pulposus.

Metabolic dysfunction of the extracellular matrix (ECM) is one of the primary causes of intervertebral disc degeneration (IVDD). Previous studies have demonstrated that the transcription factor Brachyury (Bry) has the potential to promote the synthesis of collagen II and aggrecan, while the specific mechanism is still unknown. In this study, we used a lipopolysaccharide (LPS)-induced model of nucleus pulposus cell (NPC) degeneration and a rat acupuncture IVDD model to elucidate the precise mechanism through which Bry affects collagen II and aggrecan synthesis in vitro and in vivo. First, we confirmed Bry expression decreased in degenerated human nucleus pulposus (NP) cells (NPCs). Knockdown of Bry exacerbated the decrease in collagen II and aggrecan expression in the lipopolysaccharide (LPS)-induced NPCs degeneration in vitro model. Bioinformatic analysis indicated that Smad3 may participate in the regulatory pathway of ECM synthesis regulated by Bry. Chromatin immunoprecipitation followed by quantitative polymerase chain reaction (ChIP-qPCR) and luciferase reporter gene assays demonstrated that Bry enhances the transcription of Smad3 by interacting with a specific motif on the promoter region. In addition, Western blot and reverse transcription-qPCR assays demonstrated that Smad3 positively regulates the expression of aggrecan and collagen II in NPCs. The following rescue experiments revealed that Bry-mediated regulation of ECM synthesis is partially dependent on Smad3 phosphorylation. Finally, the findings from the in vivo rat acupuncture-induced IVDD model were consistent with those obtained from in vitro assays. In conclusion, this study reveals that Bry positively regulates the synthesis of collagen II and aggrecan in NP through transcriptional activation of Smad3.NEW & NOTEWORTHY Mechanically, in the nucleus, Bry enhances the transcription of Smad3, leading to increased expression of Smad3 protein levels; in the cytoplasm, elevated substrate levels further lead to an increase in the phosphorylation of Smad3, thereby regulating collagen II and aggrecan expression. Further in vivo experiments provide additional evidence that Bry can alleviate IVDD through this mechanism.

Non-specific uptake of 18F-FAPI-04 in the pancreas and its related factors: a post-hoc analysis of an ongoing prospective clinical trial.

This study aimed to analyze the characteristics of the non-specific uptake (NSU) of 18F-labeled fibroblast activation protein inhibitor (18F-FAPI) of the pancreas and investigate the related factors. Totally, 78 patients who underwent both 18F-fluorodeoxyglucose (FDG) and 18F-FAPI PET/CT examinations were divided into normal (n = 53) and NSU (n = 25) groups. The differences in general information, medical history, laboratory indexes and uptake were compared. Receiver operating characteristic (ROC) curves were used to analyze the optimal cut-off values. The correlations between 18F-FAPI-SUVmax and blood cell analysis, liver function indexes, tumor markers, and inflammatory indices were analyzed. The logistic regression model was used to estimate the independent factors. Both 18F-FAPI (4.48 ± 0.98 vs. 2.01 ± 0.53, t = 11.718, P < 0.05) and 18F-FDG (2.23 ± 0.42 vs. 2.02 ± 0.44, t = 2.036, P = 0.045) showed significantly higher in NSU group. Patients in the NSU group tended to be complicated with a history of drinking (P = 0.034), chronic liver diseases (P = 0.006), and surgery of gastrectomy (P = 0.004). ROC analysis showed cutoff values of 3.25 and 2.05 for 18F-FAPI and 18F-FDG in identifying the NSU. Patients in the NSU group showed less platelet count, higher platelet volume, higher total bilirubin, direct or indirect bilirubin (P < 0.05). Platelet count, platelet crit, large platelet ratio, aspartate aminotransferase (AST), α-L-fucosidase, and total, direct or indirect bilirubin were correlated with 18F-FAPI-SUVmax (P < 0.05). AST [1.099 (1.014, 1.192), P = 0.021] and total bilirubin [1.137 (1.035, 1.249), P = 0.007] were two independent factors in the step forward logistic regression, and platelet/% [1.079 (1.004, 1.160), P = 0.039] and total bilirubin [1.459 (1.016, 2.095), P = 0.041] were two independent factors in the step backward logistic regression for the prediction of pancreatic uptake of 18F-FAPI. 18F-FAPI-PET/CT was better than 18F-FDG in predicting the pancreatic NSU, and NSU is related to a history of drinking, chronic liver diseases, gastrectomy, heteromorphic platelet, and impaired liver function.

Room-Temperature Growth of Square-Millimeter Single-Crystalline Two-Dimensional Metal Halides on Silicon.

Silicon is the cornerstone of electronics and photonics. In this context, almost all integrated devices derived from two-dimensional (2D) materials stay rooted in silicon technology. However, as the growth substrate, silicon has long been thought to be a hindrance for growing 2D materials through bottom-up methods that require high growth temperatures, and thus, indirect routes are usually considered instead. Although promising growth of large-area 2D materials on silicon has been demonstrated, the direct growth of single-crystalline materials using low-thermal-budget synthesis methods remains challenging. Here, we report the room-temperature growth of millimeter-scale single-crystal 2D metal halides on silicon substrates with a hydroxyl-terminated surface. Theoretical calculations reveal that the activation energy for surface diffusion can be reduced by an order of magnitude by terminating the surface with hydroxyl groups, from which on-silicon growth is greatly facilitated at room temperature and enables a 4-order-of-magnitude increase in area. The high quality and uniformity of the resulting single crystals are further evidenced. The optoelectronic devices employing the as-grown materials show an ultralow dark current of 10-13 A and a high detectivity of 1013 Jones, thereby corroborating a weak-light detection ability. These results would point to a rich space of surface modulation that can be used to surmount current limitations and demonstrate a promising strategy for growing 2D materials directly on silicon at room temperature to produce large single crystals.

The shared circulating diagnostic biomarkers and molecular mechanisms of systemic lupus erythematosus and inflammatory bowel disease.

Background: Systemic lupus erythematosus (SLE) is a multi-organ chronic autoimmune disease. Inflammatory bowel disease (IBD) is a common chronic inflammatory disease of the gastrointestinal tract. Previous studies have shown that SLE and IBD share common pathogenic pathways and genetic susceptibility, but the specific pathogenic mechanisms remain unclear. Methods: The datasets of SLE and IBD were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified using the Limma package. Weighted gene coexpression network analysis (WGCNA) was used to determine co-expression modules related to SLE and IBD. Pathway enrichment was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis for co-driver genes. Using the Least AbsoluteShrinkage and Selection Operator (Lasso) regressionand Support Vector Machine-Recursive Feature Elimination (SVM-RFE), common diagnostic markers for both diseases were further evaluated. Then, we utilizedthe CIBERSORT method to assess the abundance of immune cell infiltration. Finally,we used the single-cell analysis to obtain the location of common diagnostic markers. Results: 71 common driver genes were identified in the SLE and IBD cohorts based on the DEGs and module genes. KEGG and GO enrichment results showed that these genes were closely associated with positive regulation of programmed cell death and inflammatory responses. By using LASSO regression and SVM, five hub genes (KLRF1, GZMK, KLRB1, CD40LG, and IL-7R) were ultimately determined as common diagnostic markers for SLE and IBD. ROC curve analysis also showed good diagnostic performance. The outcomes of immune cell infiltration demonstrated that SLE and IBD shared almost identical immune infiltration patterns. Furthermore, the majority of the hub genes were commonly expressed in NK cells by single-cell analysis. Conclusion: This study demonstrates that SLE and IBD share common diagnostic markers and pathogenic pathways. In addition, SLE and IBD show similar immune cellinfiltration microenvironments which provides newperspectives for future treatment.

Ex vivo liver resection and auto-transplantation as an alternative for the treatment of liver malignancies: Progress and challenges.

Hepatectomy is still the major curative treatment for patients with liver malignancies. However, it is still a big challenge to remove the tumors in the central posterior area, especially if their location involves the retrohepatic inferior vena cava and hepatic veins. Ex vivo liver resection and auto-transplantation (ELRA), a hybrid technique of the traditional liver resection and transplantation, has brought new hope to these patients and therefore becomes a valid alternative to liver transplantation. Due to its technical difficulty, ELRA is still concentrated in a few hepatobiliary centers that have experienced surgeons in both liver resection and liver transplantation. The efficacy and safety of this technique has already been demonstrated in the treatment of benign liver diseases, especially in the advanced alveolar echinococcosis. Recently, the application of ELRA for liver malignances has gained more attention. However, standardization of clinical practice norms and international consensus are still lacking. The prognostic impact in these oncologic patients also needs further evaluation. In this review, we summarized the principles and recent progresses on ELRA.

Widespread extracellular electron transfer pathways for charging microbial cytochrome OmcS nanowires via periplasmic cytochromes PpcABCDE.

Extracellular electron transfer (EET) via microbial nanowires drives globally-important environmental processes and biotechnological applications for bioenergy, bioremediation, and bioelectronics. Due to highly-redundant and complex EET pathways, it is unclear how microbes wire electrons rapidly (>106 s-1) from the inner-membrane through outer-surface nanowires directly to an external environment despite a crowded periplasm and slow (<105 s-1) electron diffusion among periplasmic cytochromes. Here, we show that Geobacter sulfurreducens periplasmic cytochromes PpcABCDE inject electrons directly into OmcS nanowires by binding transiently with differing efficiencies, with the least-abundant cytochrome (PpcC) showing the highest efficiency. Remarkably, this defined nanowire-charging pathway is evolutionarily conserved in phylogenetically-diverse bacteria capable of EET. OmcS heme reduction potentials are within 200 mV of each other, with a midpoint 82 mV-higher than reported previously. This could explain efficient EET over micrometres at ultrafast (<200 fs) rates with negligible energy loss. Engineering this minimal nanowire-charging pathway may yield microbial chassis with improved performance.

Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Improved HOG Features.

The lack of discernible vehicle contour features in low-light conditions poses a formidable challenge for nighttime vehicle detection under hardware cost constraints. Addressing this issue, an enhanced histogram of oriented gradients (HOGs) approach is introduced to extract relevant vehicle features. Initially, vehicle lights are extracted using a combination of background illumination removal and a saliency model. Subsequently, these lights are integrated with a template-based approach to delineate regions containing potential vehicles. In the next step, the fusion of superpixel and HOG (S-HOG) features within these regions is performed, and the support vector machine (SVM) is employed for classification. A non-maximum suppression (NMS) method is applied to eliminate overlapping areas, incorporating the fusion of vertical histograms of symmetrical features of oriented gradients (V-HOGs). Finally, the Kalman filter is utilized for tracking candidate vehicles over time. Experimental results demonstrate a significant improvement in the accuracy of vehicle recognition in nighttime scenarios with the proposed method.

All-Inorganic Perovskite Solar Cells: Defect Regulation and Emerging Applications in Extreme Environments.

All-inorganic perovskite solar cells (PSCs), such as CsPbX3 , have garnered considerable attention recently, as they exhibit superior thermodynamic and optoelectronic stabilities compared to the organic-inorganic hybrid PSCs. However, the power conversion efficiency (PCE) of CsPbX3 PSCs is generally lower than that of organic-inorganic hybrid PSCs, as they contain higher defect densities at the interface and within the perovskite light-absorbing layers, resulting in higher non-radiative recombination and voltage loss. Consequently, defect regulation has been adopted as an important strategy to improve device performance and stability. This review aims to comprehensively summarize recent progresses on the defect regulation in CsPbX3 PSCs, as well as their cutting-edge applications in extreme scenarios. The underlying fundamental mechanisms leading to the defect formation in the crystal structure of CsPbX3 PSCs are firstly discussed, and an overview of literature-adopted defect regulation strategies in the context of interface, internal, and surface engineering is provided. Cutting-edge applications of CsPbX3 PSCs in extreme environments such as outer space and underwater situations are highlighted. Finally, a summary and outlook are presented on future directions for achieving higher efficiencies and superior stability in CsPbX3 PSCs.

Curvature-enhanced graph convolutional network for biomolecular interaction prediction.

Geometric deep learning has demonstrated a great potential in non-Euclidean data analysis. The incorporation of geometric insights into learning architecture is vital to its success. Here we propose a curvature-enhanced graph convolutional network (CGCN) for biomolecular interaction prediction. Our CGCN employs Ollivier-Ricci curvature (ORC) to characterize network local geometric properties and enhance the learning capability of GCNs. More specifically, ORCs are evaluated based on the local topology from node neighborhoods, and further incorporated into the weight function for the feature aggregation in message-passing procedure. Our CGCN model is extensively validated on fourteen real-world bimolecular interaction networks and analyzed in details using a series of well-designed simulated data. It has been found that our CGCN can achieve the state-of-the-art results. It outperforms all existing models, as far as we know, in thirteen out of the fourteen real-world datasets and ranks as the second in the rest one. The results from the simulated data show that our CGCN model is superior to the traditional GCN models regardless of the positive-to-negative-curvature ratios, network densities, and network sizes (when larger than 500).

Application of a novel polymer cross-linked with magnetite for efficient norfloxacin adsorption at a wide pH range.

Nowadays, NOR-containing wastewater has placed huge pressure on global ecology. In this study, a chemically-modified chitosan-based polymer was cross-linked with magnetite to prepare a novel magnetic composite adsorbent named Fe3O4/CS-P(AM-SSS) for norfloxacin (NOR) removal. The preparation conditions were optimized by single factor experiments and response surface methodology. A series of characterization analyses were carried out on the morphology, structure, and properties of Fe3O4/CS-P(AM-SSS), verifying that Fe3O4/CS-P(AM-SSS) was successfully prepared. Batch adsorption experiments showed that NOR was efficiently removed by Fe3O4/CS-P(AM-SSS), with a broad pH applicability of 3-10, short adsorption equilibrium time of 60 min, maximum adsorption capacity of 268.79 mg/g, and high regeneration rate of 86% after eight adsorption-desorption cycles. Due to the three-dimensional network structure and abundant functional groups provided by modified chitosan polymer, the superior adsorption capability of Fe3O4/CS-P(AM-SSS) was achieved through electrostatic interaction, π-π stacking, hydrophobic interaction, and hydrogen bonding. Adsorption process was exothermic and well fitted by the pseudo-second-order kinetic model and the Langmuir isothermal model. The presence of cations had a slight inhibitory effect on NOR adsorption, while humic acid nearly had no effect. In model swine wastewater, 90.3% NOR was removed by Fe3O4/CS-P(AM-SSS). Therefore, with these superior characteristics, Fe3O4/CS-P(AM-SSS) was expected to be an ideal material for treating NOR-containing wastewater in the future.

Detection of peach soluble solids based on near-infrared spectroscopy with High Order Spatial Interaction network.

BACKGROUND: Due to the scalability of deep learning technology, researchers have applied it to the non-destructive testing of peach internal quality. In addition, the soluble solids content (SSC) is an important internal quality indicator that determines the quality of peaches. Peaches with high SSC have a sweeter taste and better texture, making them popular in the market. Therefore, SSC is an important indicator for measuring peach internal quality and making harvesting decisions. RESULTS: This article presents the High Order Spatial Interaction Network (HOSINet), which combines the Position Attention Module (PAM) and Channel Attention Module (CAM). Additionally, a feature wavelength selection algorithm similar to the Group-based Clustering Subspace Representation (GCSR-C) is used to establish the Position and Channel Attention Module-High Order Spatial Interaction (PC-HOSI) model for peach SSC prediction. The accuracy of this model is compared with traditional machine learning and traditional deep learning models. Finally, the permutation algorithm is combined with deep learning models to visually evaluate the importance of feature wavelengths. Increasing the order of the PC-HOSI model enhances its ability to learn spatial correlations in the dataset, thus improving its predictive performance. CONCLUSION: The optimal model, PC-HOSI model, performed well with an order of 3 (PC-HOSI-3), with a root mean square error of 0.421 °Brix and a coefficient of determination of 0.864. Compared with traditional machine learning and deep learning algorithms, the coefficient of determination for the prediction set was improved by 0.07 and 0.39, respectively. The permutation algorithm also provided interpretability analysis for the predictions of the deep learning model, offering insights into the importance of spectral bands. These results contribute to the accurate prediction of SSC in peaches and support research on interpretability of neural network models for prediction. © 2024 Society of Chemical Industry.

The small RNA PrrH aggravates Pseudomonas aeruginosa-induced acute lung injury by regulating the type III secretion system activator ExsA.

Pseudomonas aeruginosa is an opportunistic pathogen that causes acute and chronic infections in immunocompromised individuals. Small regulatory RNAs (sRNAs) regulate multiple bacterial adaptations to environmental changes, especially virulence. Our previous study showed that sRNA PrrH negatively regulates the expression of a number of virulence factors, such as pyocyanin, rhamnolipid, biofilm, and elastase in the P. aeruginosa strain PAO1. However, previous studies have shown that the prrH-deficient mutant attenuates virulence in an acute murine lung infection model. All ΔprrH-infected mice survived the entire 28-day course of the experiment, whereas all mice inoculated with the wild-type or the complemented mutant succumbed to lung infection within 4 days of injection, but the specific mechanism is unclear. Herein, we explored how PrrH mediates severe lung injury by regulating the expression of virulence factors. In vivo mouse and in vitro cellular assays demonstrated that PrrH enhanced the pathogenicity of PAO1, causing severe lung injury. Mechanistically, PrrH binds to the coding sequence region of the mRNA of exsA, which encodes the type III secretion system master regulatory protein. We further demonstrated that PrrH mediates a severe inflammatory response and exacerbates the apoptosis of A549 cells. Overall, our results revealed that PrrH positively regulates ExsA, enhances the pathogenicity of P. aeruginosa, and causes severe lung injury. IMPORTANCE: Pseudomonas aeruginosa is a Gram-negative bacterium and the leading cause of nosocomial pneumonia. The pathogenicity of P. aeruginosa is due to the secretion of many virulence factors. Small regulatory RNAs (sRNAs) regulate various bacterial adaptations, especially virulence. Therefore, understanding the mechanism by which sRNAs regulate virulence is necessary for understanding the pathogenicity of P. aeruginosa and the treatment of the related disease. In this study, we demonstrated that PrrH enhances the pathogenicity of P. aeruginosa by binding to the coding sequence regions of the ExsA, the master regulatory protein of type III secretion system, causing severe lung injury and exacerbating the inflammatory response and apoptosis. These findings revealed that PrrH is a crucial molecule that positively regulates ExsA. Type III-positive strains are often associated with a high mortality rate in P. aeruginosa infections in clinical practice. Therefore, this discovery may provide a new target for treating P. aeruginosa infections, especially type III-positive strains.

Degradation and mechanism of PFOA by peroxymonosulfate activated by nitrogen-doped carbon foam-anchored nZVI in aqueous solutions.

Perfluorooctanoic acid (PFOA) is an emerging pollutant that is non-biodegradable and presents severe environmental and human health risks. In this study, we present an effective and mild approach for PFOA degradation that involves the use of nitrogen-doped carbon foam anchored with nanoscale zero-valent iron (nZVI@NCF) to activate low concentration peroxymonosulfate (PMS) for the treatment. The nZVI@NCF/PMS system efficiently removed 84.4% of PFOA (2.4 µM). The active sites of nZVI@NCF including Fe0 (110) and graphitic nitrogen played crucial roles in the degradation. Electrochemical analyses and density functional theory calculations revealed that nZVI@NCF acted as an electronic donor, transferring electrons to both PMS and PFOA during the reaction. By further analyzing the electron paramagnetic resonance and byproducts, it was determined that electron transfer and singlet oxygen were responsible for PFOA degradation. Three degradation pathways involving decarboxylation and surface reduction of PFOA in the nZVI@NCF/PMS system were determined. Finding from this study indicate that nZVI@NCF/PMS systems are effective in degrading PFOA and thus present a promising persulfate-advanced oxidation process technology for PFAS treatment.

Prediction of LncRNA-Protein Interactions Based on Kernel Combinations and Graph Convolutional Networks.

The complexes of long non-coding RNAs bound to proteins can be involved in regulating life activities at various stages of organisms. However, in the face of the growing number of lncRNAs and proteins, verifying LncRNA-Protein Interactions (LPI) based on traditional biological experiments is time-consuming and laborious. Therefore, with the improvement of computing power, predicting LPI has met new development opportunity. In virtue of the state-of-the-art works, a framework called LncRNA-Protein Interactions based on Kernel Combinations and Graph Convolutional Networks (LPI-KCGCN) has been proposed in this article. We first construct kernel matrices by taking advantage of extracting both the lncRNAs and protein concerning the sequence features, sequence similarity features, expression features, and gene ontology. Then reconstruct the existent kernel matrices as the input of the next step. Combined with known LPI interactions, the reconstructed similarity matrices, which can be used as features of the topology map of the LPI network, are exploited in extracting potential representations in the lncRNA and protein space using a two-layer Graph Convolutional Network. The predicted matrix can be finally obtained by training the network to produce scoring matrices w.r.t. lncRNAs and proteins. Different LPI-KCGCN variants are ensemble to derive the final prediction results and testify on balanced and unbalanced datasets. The 5-fold cross-validation shows that the optimal feature information combination on a dataset with 15.5% positive samples has an AUC value of 0.9714 and an AUPR value of 0.9216. On another highly unbalanced dataset with only 5% positive samples, LPI-KCGCN also has outperformed the state-of-the-art works, which achieved an AUC value of 0.9907 and an AUPR value of 0.9267.