Structure of Microbial Nanowires Reveals Stacked Hemes that Transport Electrons over Micrometers.

Long-range (>10 µm) transport of electrons along networks of Geobacter sulfurreducens protein filaments, known as microbial nanowires, has been invoked to explain a wide range of globally important redox phenomena. These nanowires were previously thought to be type IV pili composed of PilA protein. Here, we report a 3.7 Å resolution cryoelectron microscopy structure, which surprisingly reveals that, rather than PilA, G. sulfurreducens nanowires are assembled by micrometer-long polymerization of the hexaheme cytochrome OmcS, with hemes packed within ∼3.5-6 Å of each other. The inter-subunit interfaces show unique structural elements such as inter-subunit parallel-stacked hemes and axial coordination of heme by histidines from neighboring subunits. Wild-type OmcS filaments show 100-fold greater conductivity than other filaments from a ΔomcS strain, highlighting the importance of OmcS to conductivity in these nanowires. This structure explains the remarkable capacity of soil bacteria to transport electrons to remote electron acceptors for respiration and energy sharing.

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism.

MOTIVATION: Recent advances in spatial transcriptomics technologies have enabled gene expression profiles while preserving spatial context. Accurately identifying spatial domains is crucial for downstream analysis and it requires the effective integration of gene expression profiles and spatial information. While increasingly computational methods have been developed for spatial domain detection, most of them cannot adaptively learn the complex relationship between gene expression and spatial information, leading to sub-optimal performance. RESULTS: To overcome these challenges, we propose a novel deep learning method named Spatial-MGCN for identifying spatial domains, which is a Multi-view Graph Convolutional Network (GCN) with attention mechanism. We first construct two neighbor graphs using gene expression profiles and spatial information, respectively. Then, a multi-view GCN encoder is designed to extract unique embeddings from both the feature and spatial graphs, as well as their shared embeddings by combining both graphs. Finally, a zero-inflated negative binomial decoder is used to reconstruct the original expression matrix by capturing the global probability distribution of gene expression profiles. Moreover, Spatial-MGCN incorporates a spatial regularization constraint into the features learning to preserve spatial neighbor information in an end-to-end manner. The experimental results show that Spatial-MGCN outperforms state-of-the-art methods consistently in several tasks, including spatial clustering and trajectory inference.

Tbxt alleviates senescence and apoptosis of nucleus pulposus cells through Atg7 mediated autophagy activation during intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a significant cause of low back pain, characterized by excessive senescence and apoptosis of nucleus pulposus cells (NPCs). However, the precise mechanisms behind this senescence and apoptosis remains unclear. This study aimed to investigate the role of Tbxt in IDD both in vitro and in vivo, using a hydrogen peroxide (H2O2)-induced NPCs senescence and apoptosis model, as well as a rat acupuncture IDD model. Firstly, the expression of p16 and cleaved-caspase 3 significantly increased in degenerated human NPCs, accompanied by a decrease in Tbxt expression. Knockdown of Tbxt exacerbated senescence and apoptosis in the H2O2-induced NPCs degeneration model. Conversely, upregulation of Tbxt alleviated these effects induced by H2O2. Mechanistically, bioinformatic analysis revealed that the direct downstream target genes of Tbxt were highly enriched in autophagy-related pathways and overexpression of Tbxt significantly activated autophagy in NPCs. Moreover, the administration of the autophagy inhibitor, 3-methyladenine, impeded the impact of Tbxt on the processes of senescence and apoptosis in NPCs. Further investigation revealed that Tbxt enhances autophagy by facilitating the transcription of ATG7 through its interaction with a specific motif within the promoter region. In conclusion, this study suggests that Tbxt mitigates H2O2-induced senescence and apoptosis of NPCs by activating ATG7-mediated autophagy.

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.

Prediction of the axillary lymph-node metastatic burden of breast cancer by 18F-FDG PET/CT-based radiomics.

BACKGROUND: The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT)-based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer. METHODS: A retrospective analysis was conducted and involved 124 patients with pathologically confirmed early-stage breast cancer who had undergone 18F-FDG PET/CT examination. The ultrasound, PET/CT, and clinical pathological features of all patients were analysed, and radiomic features from PET images were extracted to establish a multi-parameter predictive model. RESULTS: The ultrasound lymph-node positivity rate and PET lymph-node positivity rate in the high nodal burden group were significantly higher than those in the low nodal burden group (χ2 = 19.867, p < 0.001; χ2 = 33.025, p < 0.001). There was a statistically significant difference in the PET-based radiomics score (RS) for predicting axillary lymph-node burden between the high and low lymph-node burden groups. (-1.04 ± 0.41 vs. -1.47 ± 0.41, t = -4.775, p < 0.001). The ultrasound lymph-node positivity (US_LNM) (odds ratio [OR] = 3.264, 95% confidence interval [CI] = 1.022-10.423), PET lymph-node positivity (PET_LNM) (OR = 14.242, 95% CI = 2.960-68.524), and RS (OR = 5.244, 95% CI = 3.16-20.896) are all independent factors associated with high lymph-node burden (p < 0.05). The area under the curve (AUC) of the multi-parameter (MultiP) model was 0.895, which was superior to those of US_LNM, PET_LNM, and RS models (AUC = 0.703, 0.814, 0.773, respectively), with statistically significant differences (Z = 2.888, 3.208, 3.804, respectively; p = 0.004, 0.002, < 0.001, respectively). Decision curve analysis indicated that the MultiP model provided a higher net benefit for all patients. CONCLUSION: A MultiP model based on PET-based radiomics was able to effectively predict axillary lymph-node metastatic burden in breast cancer. TRIAL REGISTRATION: This study was registered with ClinicalTrials.gov (registration number: NCT05826197) on May 7, 2023.

E3 ubiquitin ligase RNF187 promotes growth of spermatogonia via lysine 48-linked polyubiquitination-mediated degradation of KRT36/KRT84.

Ubiquitination is the most common post-translational modification and is essential for various cellular regulatory processes. RNF187, which is known as RING domain AP1 coactivator-1, is a member of the RING finger family. RNF187 can promote the proliferation and migration of various tumor cells. However, whether it has a similar role in regulating spermatogonia is not clear. This study explored the role and molecular mechanism of RNF187 in a mouse spermatogonia cell line (GC-1). We found that RNF187 knockdown reduced the proliferation and migration of GC-1 cells and promoted their apoptosis. RNF187 overexpression significantly increased the proliferation and migration of GC-1 cells. In addition, we identified Keratin36/Keratin84 (KRT36/KRT84) as interactors with RNF187 by co-immunoprecipitation and mass spectrometry analyses. RNF187 promoted GC-1 cell growth by degrading KRT36/KRT84 via lysine 48-linked polyubiquitination. Subsequently, we found that KRT36 or KRT84 overexpression significantly attenuated proliferation and migration of RNF187-overexpressing GC-1 cells. In summary, our study explored the involvement of RNF187 in regulating the growth of spermatogonia via lysine 48-linked polyubiquitination-mediated degradation of KRT36/KRT84. This may provide a promising new strategy for treating infertility caused by abnormal spermatogonia development.

Brachyury positively regulates extracellular matrix synthesis via directly promoting aggrecan transcription in nucleus pulposus.

Nucleus pulposus (NP) degeneration is characterized by the decreased cellularity of nucleus pulposus cells (NPCs) and diminished content of hydrophilic extracellular matrix (ECM). Overexpression of brachyury has been reported to reverse the degenerated NPCs into healthy phenotypes. However, the direct correlation between brachyury and ECM has not been fully elucidated. This study revealed that brachyury expression decreased in human degenerated NP tissues and Lipopolysaccharide (LPS)-induced degenerated rat NPCs model. In vitro and in vivo experiments further showed that brachyury deficiency suppressed the synthesis of aggrecan and collagen II in NP. Mechanistically, ChIP-qPCR assays demonstrated that brachyury bound to the promoter region of aggrecan in NPCs. Furthermore, luciferase reporter assays revealed that brachyury transcriptionally activated aggrecan expression through binding with a novel specific motif. In rat in vivo model, brachyury overexpression partially reversed the degenerative phenotype. In conclusion, brachyury positively regulated ECM synthesis via directly promoting aggrecan transcription in NPCs. Accordingly, it may be helpful to be developed into a promising therapeutic target for NP degeneration.

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.

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.

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.

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.

BMI-1 promotes breast cancer proliferation and metastasis through different mechanisms in different subtypes.

Breast cancer is among the most common malignant cancers in women. B-cell-specific Moloney murine leukemia virus integration site 1 (BMI-1) is a transcriptional repressor that has been shown to be involved in tumorigenesis, the cell cycle, and stem cell maintenance. In our study, increased expression of BMI-1 was found in both human triple negative breast cancer and luminal A-type breast cancer tissues compared with adjacent tissues. We also found that knockdown of BMI-1 significantly suppressed cell proliferation and migration in vitro and in vivo. Further mechanistic research demonstrated that BMI-1 directly bound to the promoter region of CDKN2D/BRCA1 and inhibited its transcription in MCF-7/MDA-MB-231. More importantly, we discovered that knockdown of CDKN2D/BRCA1 could promote cell proliferation and migration after repression by PTC-209. Our results reveal that BMI-1 transcriptionally suppressed BRCA1 in TNBC cell lines whereas, in luminal A cell lines, CDKN2D was the target gene. This provides a reference for the precise treatment of different types of breast cancer in clinical practice.

Autoantibodies against laminin-521 are pathogenic in anti-glomerular basement membrane disease.

Anti-glomerular basement membrane (anti-GBM) disease is an organ-specific autoimmune disorder characterized by autoantibodies against GBM components. Evidence from human inherited kidney diseases and animal models suggests that the α, ß, and γ chains of laminin-521 are all essential for maintaining the glomerular filtration barrier. We previously demonstrated that laminin-521 is a novel autoantigen within the GBM and that autoantibodies to laminin-521 are present in about one-third of patients. In the present study, we investigated the pathogenicity of autoantibodies against laminin-521 with clinical and animal studies. Herein, a rare case of anti-GBM disease was reported with circulating autoantibodies binding to laminin-521 but not to the NC1 domains of α1-α5(IV) collagen. Immunoblot identified circulating IgG from this patient bound laminin α5 and γ1 chains. A decrease in antibody levels was associated with improved clinical presentation after plasmapheresis and immunosuppressive treatments. Furthermore, immunization with laminin-521 in female Wistar-Kyoto rats induced crescentic glomerulonephritis with linear IgG deposits along the GBM, complement activation along with infiltration of T cells and macrophages. Lung hemorrhage occurred in 75.0% of the rats and was identified by the presence of erythrocyte infiltrates and hemosiderin-laden macrophages in the lung tissue. Sera and kidney-eluted antibodies from rats immunized with laminin-521 demonstrated specific IgG binding to laminin-521 but not to human α3(IV)NC1, while the opposite was observed in human α3(IV)NC1-immunized rats. Thus, our patient data and animal studies imply a possible independent pathogenic role of autoantibodies against laminin-521 in the development of anti-GBM disease.

Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction.

MOTIVATION: In recent years, a growing number of studies have proved that microRNAs (miRNAs) play significant roles in the development of human complex diseases. Discovering the associations between miRNAs and diseases has become an important part of the discovery and treatment of disease. Since uncovering associations via traditional experimental methods is complicated and time-consuming, many computational methods have been proposed to identify the potential associations. However, there are still challenges in accurately determining potential associations between miRNA and disease by using multisource data. RESULTS: In this study, we develop a Multi-view Multichannel Attention Graph Convolutional Network (MMGCN) to predict potential miRNA-disease associations. Different from simple multisource information integration, MMGCN employs GCN encoder to obtain the features of miRNA and disease in different similarity views, respectively. Moreover, our MMGCN can enhance the learned latent representations for association prediction by utilizing multichannel attention, which adaptively learns the importance of different features. Empirical results on two datasets demonstrate that MMGCN model can achieve superior performance compared with nine state-of-the-art methods on most of the metrics. Furthermore, we prove the effectiveness of multichannel attention mechanism and the validity of multisource data in miRNA and disease association prediction. Case studies also indicate the ability of the method for discovering new associations.

The small RNA PrrH of Pseudomonas aeruginosa regulates hemolysis and oxidative resistance in bloodstream infection.

Small regulatory RNAs (sRNAs) regulate multiple physiological functions in bacteria, and sRNA PrrH can regulate iron homeostasis and virulence. However, the function of PrrH in Pseudomonas aeruginosa (P. aeruginosa) bloodstream infection (BSI) is largely unknown. The aim of this study was to investigate the role of PrrH in P. aeruginosa BSI model. First, P. aeruginosa PAO1 was co-cultured with peripheral blood cells for 6 h. qRT-PCR results showed a transient up-regulation of PrrH expression at 1 h. Simultaneously, the expression of iron uptake genes fpvA, pvdS and phuR were upregulated. In addition, the use of iron chelator 2,2'-dipyridyl to create low-iron conditions caused up-regulation of PrrH expression, a result similar to the BSI model. Furthermore, the addition of FeCl3 was found to decrease PrrH expression. These results support the hypothesis that the expression of PrrH is regulated by iron in BSI model. Then, to clarify the effect of PrrH on major cells in the blood, we used PrrH mutant, overexpressing and wild-type strains to act separately on erythrocytes and neutrophils. On one hand, the hemolysis assay revealed that PrrH contributes to the hemolytic activity of PAO1, and its effect was dependent on the T3SS system master regulator gene exsA, yet had no association with the hemolytic phospholipase C (plcH), pldA, and lasB elastase genes. On the other hand, PrrH mutant enhanced the oxidative resistance of PAO1 in the neutrophils co-culture assay, H2O2-treated growth curve and conventional plate spotting assays. Furthermore, the katA was predicted to be a target gene of PrrH by bioinformatics software, and then verified by qRT-PCR and GFP reporter system. In summary, dynamic changes in the expression of prrH are iron-regulated during PAO1 bloodstream infection. In addition, PrrH promotes the hemolytic activity of P. aeruginosa in an exsA-dependent manner and negatively regulates katA to reduce the oxidative tolerance of P. aeruginosa.

Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study.

PURPOSE: The accurate assessment of axillary lymph node metastasis (LNM) in early-stage breast cancer (BC) is of great importance. This study aimed to construct an integrated model based on clinicopathology, ultrasound, PET/CT, and PET radiomics for predicting axillary LNM in early stage of BC. MATERIALS AND METHODS: 124 BC patients who underwent 18 F-fluorodeoxyglucose (18 F-FDG) PET/CT and whose diagnosis were confirmed by surgical pathology were retrospectively analyzed and included in this study. Ultrasound, PET and clinicopathological features of all patients were analyzed, and PET radiomics features were extracted to establish an ultrasound model (clinicopathology and ultrasound; model 1), a PET model (clinicopathology, ultrasound, and PET; model 2), and a comprehensive model (clinicopathology, ultrasound, PET, and radiomics; model 3), and the diagnostic efficacy of each model was evaluated and compared. RESULTS: The T stage, US_BIRADS, US_LNM, and PET_LNM in the positive axillary LNM group was significantly higher than that of in the negative LNM group (P = 0.013, P = 0.049, P < 0.001, P < 0.001, respectively). Radiomics score for predicting LNM (RS_LNM) for the negative LNM and positive LNM were statistically significant difference (-1.090 ± 0.448 vs. -0.693 ± 0.344, t = -4.720, P < 0.001), and the AUC was 0.767 (95% CI: 0.674-0.861). The ROC curves showed that model 3 outperformed model 1 for the sensitivity (model 3 vs. model 1, 82.86% vs. 48.57%), and outperformed model 2 for the specificity (model 3 vs. model 2, 82.02% vs. 68.54%) in the prediction of LNM. The AUC of mode 1, model 2 and model 3 was 0.687, 0.826 and 0.874, and the Delong test showed the AUC of model 3 was significantly higher than that of model 1 and model 2 (P < 0.05). Decision curve analysis showed that model 3 resulted in a higher degree of net benefit for all the patients than model 1 and model 2. CONCLUSION: The use of a comprehensive model based on clinicopathology, ultrasound, PET/CT, and PET radiomics can effectively improve the diagnostic efficacy of axillary LNM in BC. TRIAL REGISTRATION: This study was registered at ClinicalTrials Gov (number NCT05826197) on 7th, May 2023.

Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery.

Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this paper, we propose a fingerprint-enhanced graph attention network (FinGAT) model by the combination of sequence-based 2D fingerprints and structure-based graph representation. In our feature learning process, sequence information is transformed into a fingerprint vector, and structural information is encoded through a GAT module into another vector. These two vectors are concatenated and input into a multilayer perceptron (MLP) for antibiotic activity classification. Our model is extensively tested and compared with existing models. It has been found that our FinGAT can outperform various state-of-the-art GNN models in antibiotic discovery.

Effects of farmland abandonment on anthropogenic-alluvial soil microbiota and contaminant residues in Lycium barbarum fields.

AIMS: There has been an increasing tendency to abandon crop cultivation and farming in old Lycium barbarum (wolfberry) stands to allow for natural restoration. However, little research has been dedicated to deciphering how soil quality changes in L. barbarum fields following abandonment from a physicochemical and microbiological perspective. Here we assessed the effects of farmland abandonment on anthropogenic-alluvial soil microbiota and contaminant residues in L. barbarum fields in Ningxia, China. METHODS AND RESULTS: Soil microbiota, heavy metal, and neonicotinoid pesticide profiles in L. barbarum fields abandoned for one to four years were characterized. Microbial community analysis was performed by high-throughput sequencing of the bacterial 16S ribosomal RNA genes and the fungal nuclear ribosomal internal transcribed spacer region. Soil bacterial diversity increased from before abandonment to year three after abandonment, and fungal diversity peaked in year one after abandonment. Enrichment of potentially beneficial taxa (e.g. Limnobacter, Cavicella) as well as pathogenic taxa (e.g. Ilyonectria) was observed in the abandoned field soils, along with depletion of other taxa (e.g. Planococcus, Bipolaris). Soil copper, zinc, cadmium, imidacloprid, and acetamiprid concentrations all decreased with increasing time since abandonment and had varied correlations with soil quality, microbial diversity, and the relative abundances of major phyla. Soil available phosphorus, nitrate-nitrogen, and pH were the key factors shaping bacterial communities. The structuring of fungal communities was strongly influenced by soil pH, available phosphorus, and available nitrogen contents. CONCLUSIONS: There were positive consequences of farmland abandonment in L. barbarum fields, such as optimized microbial community structure, reduced heavy metal accumulation, and enhanced pesticide degradation.

Diagnostic value of 3D volume measurement of central pulmonary artery based on CTPA images in the pulmonary hypertension.

BACKGROUND: This retrospective study aims to evaluate the diagnostic value of volume measurement of central pulmonary arteries using computer tomography pulmonary angiography (CTPA) for predicting pulmonary hypertension (PH). METHODS: A total of 59 patients in our hospital from November 2013 to April 2021 who underwent both right cardiac catheterization (RHC) and CTPA examination were included. Systolic pulmonary artery pressure (SPAP), mean PAP (mPAP), and diastolic PAP (DPAP) were acquired from RHC testing. Patients were divided into the non-PH group (18 cases) and the PH group (41 cases). The diameters of the main pulmonary artery (DMPA), right pulmonary artery (DRPA), and left pulmonary artery (DLPA) were measured manually. A 3D model software was used for the segmentation of central pulmonary arteries. The cross-sectional areas (AMPA, ARPA, ALPA) and the volumes (VMPA, VRPA, VLPA) were calculated. Measurements of the pulmonary arteries derived from CTPA images were compared between the two groups, and correlated with the parameters of RHC testing. ROC curves and decision curve analysis (DCA) were used to evaluate the benefit of the three-dimensional CTPA parameters for predicting PH. A multiple linear regression model with a forward-step approach was adopted to integrate all statistically significant CTPA parameters for PH prediction. RESULTS: All parameters (DMPA, DRPA, DLPA, AMPA, ARPA, ALPA, VMPA, VRPA, and VLPA) of CTPA images exhibited significantly elevated in the PH group in contrast to the non-PH group (P < 0.05), and showed positive correlations with the parameters of RHC testing (mPAP, DPAP, SPAP) (r ranged 0.586~0.752 for MPA, 0.527~0.640 for RPA, and 0.302~0.495 for LPA, all with P < 0.05). For the MPA and RPA, 3D parameters showed higher correlation coefficients compared to their one-dimensional and two-dimensional counterparts. The ROC analysis indicated that the VMPA showed higher area under the curves (AUC) than the DMPA and AMPA without significance, and the VRPA showed higher AUC than the DRPA and ARPA significantly (DRPA vs. VRPA, Z = 2.029, P = 0.042; ARPA vs. VRPA, Z = 2.119, P = 0.034). The DCA demonstrated that the three-dimensional parameters could provide great net benefit for MPA and RPA. The predictive equations for mPAP, DPAP, and SPAP were formulated as [8.178 + 0.0006 * VMPA], [1.418 + 0.0005 * VMPA], and [-11.137 + 0.0006*VRPA + 1.259 * DMPA], respectively. CONCLUSION: The 3D volume measurement of the MPA and RPA based on CTPA images maybe more informative than the traditional diameter and cross-sectional area in predicting PH.

Effects of the coexistence of antibiotics and heavy metals on the fate of antibiotic resistance genes in chicken manure and surrounding soils.

Both heavy metals and antibiotics exert selection pressure on bacterial resistance, and as they are commonly co-contaminated in the environment, they may play a larger role in bacterial resistance. This study examined how breeding cycles affect antibiotic resistance genes (ARGs) in chicken manure and the surrounding topsoils at 20, 50, 100, 200, and 300 m from twelve typical laying hen farms in the Ningxia Hui Autonomous Region of northwest China. Six antibiotics, seven heavy metals, ten mobile genetic elements (MGEs), and microbial community affected the ARGs profile in chicken dung and soil samples. Tetracycline antibiotic residues were prevalent in chicken manure, as were relatively high content of aureomycin during each culture period. Zinc (Zn) content was highest among the seven heavy metals in chicken feces. Chicken dung also enriched aminoglycosides, MLSB, and tetracycline ARGs, notably during brooding and high production. The farm had a minimal influence on antibiotics in the surrounding soil, but its effect on ARGs and MGEs closer to the farm (50 m) was stronger, and several ARGs and MGEs increased with distance. Manure microbial composition differed dramatically throughout breeding cycles and sampling distances. ARGs were more strongly related with antibiotics and heavy metals in manure than soil, whereas MGEs were the reverse. Antibiotics, heavy metals, MGEs, and bacteria in manure accounted 12.28%, 22.25%, 0.74%, and 0.19% of ARGs composition variance, respectively, according to RDA and VPA. Bacteria (2.89%) and MGEs (2.82%) only affected soil ARGs composition. These findings showed that heavy metals and antibiotics are the main factors affecting faecal ARGs and bacteria and MGEs soil ARGs. This paper includes antibiotic resistance data for large-scale laying hen husbandry in northwest China and a theoretical framework for decreasing antibiotic resistance.