Porcine cis-acting lnc-CAST positively regulates CXCL8 expression through histone H3K27ac.

The chemokine CXCL8, also known as the neutrophil chemotactic factor, plays a crucial role in mediating inflammatory responses and managing cellular immune reactions during viral infections. Porcine reproductive and respiratory syndrome virus (PRRSV) primarily infects pulmonary alveolar macrophages (PAMs), leading to acute pulmonary infections. In this study, we explored a novel long non-coding RNA (lncRNA), termed lnc-CAST, situated within the Cxcl8 gene locus. This lncRNA was found to be highly expressed in porcine macrophages. We observed that both lnc-CAST and CXCL8 were significantly upregulated in PAMs following PRRSV infection, and after treatments with lipopolysaccharide (LPS) or lipoteichoic acid (LTA). Furthermore, we noticed a concurrent upregulation of lnc-CAST and CXCL8 expression in lungs of PRRSV-infected pigs. We then determined that lnc-CAST positively influenced CXCL8 expression in PAMs. Overexpression of lnc-CAST led to an increase in CXCL8 production, which in turn enhanced the migration of epithelial cells and the recruitment of neutrophils. Conversely, inhibiting lnc-CAST expression resulted in reduced CXCL8 production in PAMs, leading to decreased migration levels of epithelial cells and neutrophils. From a mechanistic perspective, we found that lnc-CAST, localized in the nucleus, facilitated the enrichment of histone H3K27ac in CXCL8 promoter region, thereby stimulating CXCL8 transcription in a cis-regulatory manner. In conclusion, our study underscores the pivotal critical role of lnc-CAST in regulating CXCL8 production, offering valuable insights into chemokine regulation and lung damage during PRRSV infection.

Discovery of psoralen as a quorum sensing inhibitor suppresses Pseudomonas aeruginosa virulence.

Pseudomonas aeruginosa is a common opportunistic pathogen with growing resistance and presents heightened treatment challenges. Quorum sensing (QS) is a cell-to-cell communication system that contributes to the production of a variety of virulence factors and is also related to biofilm formation of P. aeruginosa. Compared to traditional antibiotics which kill bacteria directly, the anti-virulence strategy by targeting QS is a promising strategy for combating pseudomonal infections. In this study, the QS inhibition potential of the compounds derived from the Traditional Chinese Medicines was evaluated by using in silico, in vitro, and in vivo analyses. The results showed that psoralen, a natural furocoumarin compound derived from Psoralea corylifolia L., was capable of simultaneously inhibiting the three main QS regulators, LasR, RhlR, and PqsR of P. aeruginosa. Psoralen had no bactericidal activity but could widely inhibit the production of extracellular proteases, pyocyanin, and biofilm, and the cell motilities of the model and clinical P. aeruginosa strains. RNA-sequencing and quantitative PCR analyses further demonstrated that a majority of QS-activated genes in P. aeruginosa were suppressed by psoralen. The supplementation of psoralen could protect Caenorhabditis elegans from P. aeruginosa challenge, especially for the hypervirulent strain PA14. Moreover, psoralen showed synergistic antibacterial effects with polymyxin B, levofloxacin, and kanamycin. In conclusions, this study identifies the anti-QS and antibiofilm effects of psoralen against P. aeruginosa strains and sheds light on the discovery of anti-pseudomonal drugs among Traditional Chinese Medicines. KEY POINTS: • Psoralen derived from Psoralea corylifolia L. inhibits the virulence-related phenotypes of P. aeruginosa. • Psoralen simultaneously targets the three core regulators of P. aeruginosa QS system and inhibits the expression of a large part of downstream genes. • Psoralen protects C. elegans from P. aeruginosa challenge and enhances the susceptibility of P. aeruginosa to antibiotics.

Exploring the accumulation capacity of dominant plants based on soil heavy metals forms and assessing heavy metals contamination characteristics near gold tailings ponds.

Heavy metal contamination of soil commonly accompanies problems around gold mine tailings ponds. Fully investigating the distribution characteristics of heavy metals and the survival strategies of dominant plants in contaminated soils is crucial for effective pollution management and remediation. This study aims to investigate the contamination characteristics, sources of heavy metals (As, Cd, Pb, Hg, Cu, Zn, Cr, and Ni) in soils around gold mine tailings ponds areas (JHH and WZ) and to clarify the form distribution of heavy metals (As, Cd, Pb, Hg) in contaminated plots as well as their accumulation and translocation in native dominant plants. The results of the study showed that the concentrations of As, Pb, Cd, Cu, and Zn in soil exceeded the national limits at parts of the sampling sites in both study areas. The Nemerow pollution index showed that both study areas reached extreme high pollution levels. Spatial analysis showed that the main areas of contamination were concentrated around metallurgical plants and tailings ponds, with Cd exhibiting the most extensive area of contamination. In the JHH, As (74%), Cd (66%), Pb (77%), Zn (47%) were mainly from tailings releases, and Cu (52%) and Hg (51%) were mainly from gold ore smelting. In the WZ, As (42%), Cd (41%), Pb (73%), Cu (47%), and Zn (41%) were mainly from tailings releases. As, Cd, Pb, and Hg were mostly present in the residue state, and the proportion of water-soluble, ion-exchangeable, and carbonate-bound forms of Cd (19.93%) was significantly higher than that of other heavy metals. Artemisia L. and Amaranthus L. are the primary dominating plants, which exhibited superior accumulation of Cd compared to As, Pb, and Hg, and Artemisia L. demonstrated a robust translocation capacity for As, Pb, and Hg. Compared to the concentrations of other forms of soil heavy metals, the heavy metal content in Artemisia L correlates significantly better with the total soil heavy metal concentration. These results offer additional systematic data support and a deeper theoretical foundation to bolster pollution-control and ecological remediation efforts in mining areas.

Multi-omics-based characterization of the influences of Mycobacterium tuberculosis virulence factors EsxB and PPE68 on host cells.

Mycobacterium tuberculosis, the ancient master of causing tuberculosis, is one of the most successful pathogens capable of persistently colonizing host lungs. The EsxB (CFP-10) of ESX-1 system and PPE68 of the PPE family contribute to the virulence of M. tuberculosis. However, the virulence potential and pathogenetic characteristics of these two proteins during M. tuberculosis infection remain unclear. In this study, two prokaryotic expression plasmids for EsxB or PPE68 of M. tuberculosis were constructed and the recombinant proteins His-EsxB or His-PPE68 were purified. The proteome and transcriptome of MH-S cells treated with His-EsxB or His-PPE68 were explored, followed by validating the expression of the identified differentially expressed genes (DEGs) using quantitative PCR. A total of 159/439 specific proteins or 633/1117 DEGs were obtained between control and His-EsxB or His-PPE68 treated groups in the MH-S proteomes and transcriptomes. Additionally, 37/60 signal pathways were predicted in the His-EsxB or His-PPE68 treated groups and "Cytokine-cytokine receptor interaction" was the most represented pathway. Furthermore, the expression of the DEGs (IL-1ß, IL-6, and TNF-α) was significantly upregulated, suggesting that these DEGs contributed to the host response during EsxB or PPE68 treatment. These findings provide detailed information on developing an effective intervention strategy to control M. tuberculosis infection.

The differential value of radiomics based on traditional T1-weighted sequences in newborns with hyperbilirubinemia.

BACKGROUND: On the basis of visual-dependent reading method, radiological recognition and assessment of neonatal hyperbilirubinemia (NH) or acute bilirubin encephalopathy (ABE) on conventional magnetic resonance imaging (MRI) sequences are challenging. Prior studies had shown that radiomics was possible to characterize ABE-induced intensity and morphological changes on MRI sequences, and it has emerged as a desirable and promising future in quantitative and objective MRI data extraction. To investigate the utility of radiomics based on T1-weighted sequences for identifying neonatal ABE in patients with hyperbilirubinemia and differentiating between those with NH and the normal controls. METHODS: A total of 88 patients with NH were enrolled, including 50 patients with ABE and 38 ABE-negative individuals, and 70 age-matched normal neonates were included as controls. All participants were divided into training and validation cohorts in a 7:3 ratio. Radiomics features extracted from the basal ganglia of T1-weighted sequences on magnetic resonance imaging were evaluated and selected to set up the prediction model using the K-nearest neighbour-based bagging algorithm. A receiver operating characteristic curve was plotted to assess the differentiating performance of the radiomics-based model. RESULTS: Four of 744 radiomics features were selected for the diagnostic model of ABE. The radiomics model yielded an area under the curve (AUC) of 0.81 and 0.82 in the training and test cohorts, with accuracy, precision, sensitivity, and specificity of 0.82, 0.80, 0.91, and 0.69 and 0.78, 0.8, 0.8, and 0.75, respectively. Six radiomics features were selected in this model to distinguish those with NH from the normal controls. The AUC for the training cohort was 0.97, with an accuracy of 0.92, a precision of 0.92, a sensitivity of 0.93, and a specificity of 0.90. The performance of the radiomics model was confirmed by testing the test cohort, and the AUC, accuracy, precision, sensitivity, and specificity were 0.97, 0.92, 0.96, 0.89, and 0.95, respectively. CONCLUSIONS: The proposed radiomics model based on traditional TI-weighted sequences may be used effectively for identifying ABE and even differentiating patients with NH from the normal controls, which can provide microcosmic information beyond experience-dependent vision and potentially assist in clinical diagnosis and treatment.

Subinhibitory Cefotaxime and Levofloxacin Concentrations Contribute to Selection of Pseudomonas aeruginosa in Coculture with Staphylococcus aureus.

Bacterial species in the polymicrobial community evolve interspecific interaction relationships to adapt to the survival stresses imposed by neighbors or environmental cues. Pseudomonas aeruginosa and Staphylococcus aureus are two common bacterial pathogens frequently coisolated from patients with burns and respiratory disease. Whether the application of commonly used antibiotics influences the interaction dynamics of the two species still remains largely unexplored. By performing a series of on-plate competition assays and RNA sequencing-based transcriptional profiling, we showed that the presence of the cephalosporin antibiotic cefotaxime or the quinolone antibiotic levofloxacin at subinhibitory concentration contributes to selecting P. aeruginosa from the coculture with S. aureus by modulating the quorum-sensing (QS) system of P. aeruginosa. Specifically, a subinhibitory concentration of cefotaxime promotes the growth suppression of S. aureus by P. aeruginosa in coculture. This process may be related to the increased production of the antistaphylococcal molecule pyocyanin and the expression of lasR, which is the central regulatory gene of the P. aeruginosa QS hierarchy. On the other hand, subinhibitory concentrations of levofloxacin decrease the competitive advantage of P. aeruginosa over S. aureus by inhibiting the growth and the las QS system of P. aeruginosa. However, pqs signaling of P. aeruginosa can be activated instead to overcome S. aureus. Therefore, this study contributes to understanding the interaction dynamics of P. aeruginosa and S. aureus during antibiotic treatment and provides an important basis for studying the pathogenesis of polymicrobial infections. IMPORTANCE Increasing evidence has demonstrated the polymicrobial characteristics of most chronic infections, and the frequent communications among bacterial pathogens result in many difficulties for clinical therapy. Exploring bacterial interspecific interaction during antibiotic treatment is an emerging endeavor that may facilitate the understanding of polymicrobial infections and the optimization of clinical therapies. Here, we investigated the interaction of cocultured P. aeruginosa and S. aureus with the intervention of commonly used antibiotics in clinic. We found that the application of subinhibitory concentrations of cefotaxime and levofloxacin can select P. aeruginosa in coculture with S. aureus by modulating P. aeruginosa QS regulation to enhance the production of antistaphylococcal metabolites in different ways. This study emphasizes the role of the QS system in the interaction of P. aeruginosa with other bacterial species and provides an explanation for the persistence and enrichment of P. aeruginosa in patients after antibiotic treatment and a reference for further clinical therapy.

Acrocarpospora catenulata sp. nov., a novel actinobacterium isolated from lake sediment.

A novel actinobacterium, designated strain H8750T, was isolated from sediment sampled at Lugu Lake, southwest PR China and its polyphasic taxonomy was studied. Strain H8750T produced well-developed substrate mycelium, and formed club-shaped and hooked structures borne on the tip of the aerial mycelia. It contained meso-diaminopimelic, glucose, ribose and madurose in whole-cell hydrolysates. The predominant menaquinones were MK-9(H4), MK-9(H2) and MK-9(H6). The phospholipid profile contained diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, hydroxy-phosphatidylethanolamine, unidentified phospholipids and unidentified aminophospholipids. The major fatty acid (>10 %) were cis 9 C17 : 1, iso-C16 : 0 and C15 : 0. The DNA G+C content was 69.7 mol% based on the whole genome sequence. Phylogenetic analysis based on 16S rRNA gene and whole-genome sequences indicated that strain H8750T was closely related to Acrocarpospora macrocephala JCM 10982T (98.0 %), Acrocarpospora pleiomorpha JCM 10983T (97.9 %) and Acrocarpospora phusangensis DSM 45867 T (97.8 %) and formed a monophyletic clade within the genus Acrocarpospora in the phylogenetic trees. The average nucleotide identity and digital DNA-DNA hybridization values between strain H8750T and its closely related Acrocarpospora species were 79.8~87.2 % and 25.9~28.0 %, respectively, which showed that it belonged to a distinct species. Furthermore, the morphological and phenotypic characteristics allowed the isolate to be differentiated from its closely related species. Therefore, it is concluded that strain H8750T can be classified as representing a novel species of the genus Acrocarpospora, for which the name Acrocarpospora catenulata sp. nov. is proposed. The type strain is H8750T (=JCM 34849T=CICC 25116T). Moreover, based on the gene prediction results, strain H8750T may have the genetic potential to synthesize many new secondary metabolites, which further increases its bioactive value.

A novel antibiotic combination of linezolid and polymyxin B octapeptide PBOP against clinical Pseudomonas aeruginosa strains.

BACKGROUND: Antibiotic-resistant Gram-negative bacteria are becoming a major public health threat such as the important opportunistic pathogen Pseudomonas aeruginosa (P. aeruginosa). The present study investigated enhancement of the linezolid spectrum, which is normally used to treat Gram-positive bacteria, at inhibiting P. aeruginosa growth. METHODS: The checkerboard test or time-kill assay were carried out to determine the antibacterial effects of linezolid in cooperation with polymyxin B octapeptide PBOP (LP) against P. aeruginosa based on in vitro model. The protective effect of LP against P. aeruginosa infection was assessed based on a Caenorhabditis elegans (C. elegans) model. RESULTS: The synergistic activity and antibacterial effects were significantly increased against P. aeruginosa by LP treatment, while linezolid and PBOP as monotherapies exhibited no remarkably bactericidal activity against the clinical strains. Additionally, LP treatment modified biofilm production, morphology, swimming motility of P. aeruginosa, and protected C. elegans from P. aeruginosa infection. CONCLUSIONS: This research demonstrates that LP combination has significant synergistic activity against P. aeruginosa, and PBOP is potential to be an activity enhancer. Notably, this strategy improved the antibacterial activity spectrum of linezolid and other anti-Gram-positive agents and represents an effective choice to surmount the antibiotic resistance of bacteria in the long term.

In Vitro Inhibitory Effects of Maqian Essential Oil against Ectopic Endometrial Stromal Cells and LPS-Induced Endometrial Epithelial Cells.

Previous studies revealed that MQEO (Maqian fruits essential oil), which is extracted from the fruit of Maqian (Zanthoxylum myriacanthum var. Pubescens), had a good anti-inflammatory effect, but the effect on endometriosis in vitro remains unknown. In the present study, the inhibitory effects of MQEO against the EESCs (ectopic endometrial stromal cells) were investigated. Cells were treated with a concentration gradient (from 0.025 % to 0.15 %) of MQEO for 24 h and cell viability was detected by CCK-8. In addition, apoptotic rates were investigated using flow cytometry. The effect of MQEO on cell migration was determined by wound-healing and transwell assay. The expression of apoptosis-associated and cell adhesion-related proteins was assessed by western blotting. The transcriptional levels of IL-1, IL-6 and TNF-α were determined by Real-time qPCR. RNA-seq was used to identify the DEGs (differentially expressed genes) in MQEO-pretreated EESCs. We found that the MQEO condition dosage-dependently reduced the cell viability of EESCs. Based on flow cytometry results, the number of apoptotic cells increased significantly with dosage. The wound-healing and transwell results showed that MQEO group exhibited a significantly decreased cell motility and migration ability in comparison with the normal group. Western blotting results showed that MQEO down-regulated the expression of Bcl-2, ICAM-1 (intercellular adhesion molecule 1) and CD44, but up-regulated the cleaved caspase-3 expression in EESCs. What's more, MQEO also inhibited the LPS-induced inflammation in human EECs (endometrial epithelial cells). RNA-seq revealed that 221 DEGs were up-regulated genes and 284 DEGs were down-regulated in MQEO-pretreated EESCs. Our data uncovered the beneficial effects of MQEO in endometriosis and provided new insights into the mechanism of the effect of MQEO on EESCs, suggesting MQEO could be a promising new therapeutic agent for endometriosis.

First Report of Twig Anthracnose of Acacia melanoxylon Caused by Colletotrichum siamense in China.

Acacia melanoxylon R. Br. native to Australia, is a high-quality timber tree with wide genetic and phenotypic diversity. In recent years, A. melanoxylon has been extensively cultivated in some provinces in southern China. In December 2019, anthracnose-like symptoms were observed on twigs of A. melanoxylon in China. In certain valleys in south China, the disease incidence on plants and shoots was 60-75% and 80-90%, respectively. The wither rate of disease branches was 30-40% in dry seasons from September to November. The appearance of symptoms occurred in a humid and warm valley. Symptoms were initially observed on the young branches as brown spindle shaped sunken spots. At later stages, the disease spots girdled the whole branch, which became wilted and its leaves turned reddish-brown. For pathogen isolation, diseased branches were sampled and 55 pieces (5× 5 mm) of these branches section were surface-sterilized in 75% ethanol for 30 seconds, followed by 0.5% NaClO for 5 min and then were rinsed three times in distilled water. After drying with sterilized filter paper, the surface-sterilized sections were transferred to potato dextrose agar medium (PDA) and incubated at 25 °C for 7 days in the dark. Three isolates were obtained as representatives for morphological characterization and were labeled as 1A912, 1B912, and 1C912. These specimens were deposited in the Guangdong Province Key Laboratory of Microbial Signals and Disease Control at the South China Agricultural University (China). Purified isolates were initially white, cottony and with dense aerial mycelium on PDA at 25 ℃, ten days later their colonies turned grayish white with orange conidial masses. Conidia were one-celled, hyaline, straight, cylindrical, with round obtuse ends, and measured 11.0 to16.3× 4.0 to 6.0 µm (n= 100), appressoria were 5.86 to 9.07 × 3.55 to 6.96 µm (n= 100). Morphological characteristics of selected isolates matched the Colletotrichum gloeosporioides species complex (Weir et al. 2012). For further identification, the internal transcribed spacer (ITS) region, and partial sequences of the actin (ACT), beta-tubulin (TUB2), and glycerol dehyde-3-phosphate dehydrogenase (GAPDH) genes were amplified by PCR, and sequenced, using primer pairs ITS1/ ITS4 (White et al. 1990), Bt2a/ Bt2b (Donaldson and Glass 1995), ACT512F/ ACT783R, GDF1/ GDR1(Weir et al. 2012). The sequences were deposited in GenBank (ITS: MW228101-MW228103; TUB2: MW250346, MW320707, MW320708; ACT: MW250347, MW320703, MW320704; GAPDH: MW250348, MW320705, MW320706). The multilocus phylogenetic analysis distinguished the isolates 1A912, 1B912, and 1C912 as C. siamense. Pathogenicity of those three isolates of C. siamense was tested on healthy twigs of the one clone of A. melanoxylon. 27 young twigs of nine 1-year-old plants were inoculated with the mycelium of the 7 days-old isolates 1A912, 1B912, and 1C912(Each isolate infected three plants and each infected three young twigs) through an artificial wound. The same nine plants were inoculated with PDA medium alone (each infected three young twigs) as a negative control. Five days after inoculation, brown spindle spots similar to the field disease symptoms were observed on the twigs. No symptoms were observed on the control plants. The experiment was repeated twice. The fungus was successfully reisolated from the symptomatic plants, and had identical morphological and molecular characteristics to the initial isolates, fulfilling Koch´s postulates. To our knowledge, this is the first report of anthracnose caused by C. siamense on A. melanoxylon in China. Twig anthracnose can reduce the growth of A. melanoxylon. Further research on management options for this disease is required.

Antibiotic intervention redisposes bacterial interspecific interacting dynamics in competitive environments.

Interspecific interaction happens frequently among bacterial species and can promote the colonization of polymicrobial community in various environments. However, it is not clear whether the intervention of antibiotics, which is a common therapeutic method for infectious disease, will influence the interacting dynamics of different pathogenic bacteria. By using the frequently co-isolated bacteria Pseudomonas aeruginosa and Staphylococcus aureus as models, here we identify an antibiotic-determined mutual invasion relationship between bacterial pathogens. We show that although P. aeruginosa has a significant intrinsic competitive advantage over S. aureus by producing the quorum-sensing (QS)-controlled anti-staphylococcal molecules, methicillin-resistant S. aureus (MRSA) can inhibit neighbouring P. aeruginosa in the presence of subinhibitory aminoglycoside antibiotics (e.g. streptomycin) to P. aeruginosa. Importantly, subinhibitory streptomycin decreases the expression of QS-regulated genes in P. aeruginosa and thus relieves the survival stress of MRSA brought by P. aeruginosa. On the other side, the iron-uptake systems and pathogenicity of MRSA can be enhanced by the extracellular products of streptomycin-treated P. aeruginosa. Therefore, this study provides an explanation for the substitution of dominant species and persistent coexistence of bacterial pathogens in the host with repeated antibiotic therapies and contributes to further understanding the pathogenesis of chronic polymicrobial infections.

CT Radiomics for the Prediction of Synchronous Distant Metastasis in Clear Cell Renal Cell Carcinoma.

PURPOSE: The aim of this study was to construct and verify a computed tomography (CT) radiomics model for preoperative prediction of synchronous distant metastasis (SDM) in clear cell renal cell carcinoma (ccRCC) patients. METHODS: Overall, 172 patients with ccRCC were enrolled in the present research. Contrast-enhanced CT images were manually sketched, and 2994 quantitative radiomic features were extracted. The radiomic features were then normalized and subjected to hypothesis testing. Least absolute shrinkage and selection operator (LASSO) was applied to dimension reduction, feature selection, and model construction. The performance of the predictive model was validated through analysis of the receiver operating characteristic curve. Multivariate and subgroup analyses were performed to verify the radiomic score as an independent predictor of SDM. RESULTS: The patients randomized into a training (n = 104) and a validation (n = 68) cohort in a 6:4 ratio. Through dimension reduction using LASSO regression, 9 radiomic features were used for the construction of the SDM prediction model. The model yielded moderate performance in both the training (area under the curve, 0.89; 95% confidence interval, 0.81-0.97) and the validation cohort (area under the curve, 0.83; 95% confidence interval, 0.69-0.95). Multivariate analysis showed that the CT radiomic signature was an independent risk factor for clinical parameters of ccRCC. Subgroup analysis revealed a significant connection between the SDM and radiomic signature, except for the lower pole of the kidney subgroup. CONCLUSIONS: The CT-based radiomics model could be used as a noninvasive, personalized approach for SDM prediction in patients with ccRCC.

NRF2 Exerts Anti-Inflammatory Effects in LPS-Induced gEECs by Inhibiting the Activation of the NF-κB.

Nuclear factor E2-related factor 2 (NRF2) plays an anti-inflammatory role in several pathological processes, but its function in lipopolysaccharide- (LPS-) induced goat endometrial epithelial cells (gEECs) is still unknown. We designed a study to investigate the function of NRF2 in LPS-induced gEECs. LPS was found to increase the NRF2 expression and the nuclear abundance of NRF2 in gEECs in a dose-dependent manner. NRF2 knockout (KO) not only increased the expression of LPS-induced proinflammatory cytokines (TNF-α, IL-1ß, IL-6 and IL-8) but also increased the expression of TLR4, p-IκBα/IκBα, and p-p65/p65 proteins. Immunoprecipitation experiments showed that NRF2 directly binds to p65 in the nucleus and inhibits the binding of p65 to downstream target genes (TNF-α, IL-1ß, IL-6, and IL-8). Even though a NF-κB/p65 inhibitor (PDTC) reduced the LPS-induced NRF2 expression and nuclear abundance of NRF2, overexpressing TNF-α reversed the inhibitory effects of PDTC on the NRF2 expression and on its abundance in the nucleus. Similarly, knockdown of the proinflammatory cytokines (TNF-α, IL-1ß, IL-6, or IL-8) significantly decreased the LPS-induced NRF2 expression and NRF2 in the nucleus. In conclusion, our data suggest that proinflammatory cytokines induced by LPS through the TLR4/NF-κB pathway promote the NRF2 expression and its translocation into the nucleus. Our work also suggests that NRF2 inhibits the expression of proinflammatory cytokines by directly binding to p65.

Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer.

OBJECTIVES: To identify the clinical value of ultrasound radiomic features in the preoperative prediction of tumor stage and pathological grade of bladder cancer (BLCA) patients. METHODS: We retrospectively collected patients who had been diagnosed with BLCA by pathology. Ultrasound-based radiomic features were extracted from manually segmented regions of interest. Participants were randomly assigned to a training cohort and a validation cohort at a ratio of 7:3. Radiomic features were Z-score normalized and submitted to dimensional reduction analysis (including Spearman's correlation coefficient analysis, the random forest algorithm, and statistical testing) for core feature selection. Classifiers for tumor stage and pathological grade prediction were then constructed. Prediction performance was estimated by the area under the curve (AUC) of the receiver operating characteristic curve and was verified by the validation cohort. RESULTS: A total of 5936 radiomic features were extracted from each of the ultrasound images obtained from 157 patients. The BLCA tumor stage and pathological grade prediction models were developed based on 30 and 35 features, respectively. Both models showed good predictive ability. For the tumor stage prediction model, the AUC was 0.94 in the training cohort and 0.84 in the validation cohort. For the pathological grade model, the AUCs obtained were 0.84 in the training cohort and 0.75 in the validation cohort. CONCLUSIONS: The ultrasound-based radiomics models performed well in the preoperative tumor staging and pathological grading of BLCA. These findings should be applied clinically to optimize treatment and to assess prognoses for BLCA.

Ultrasound Image-Based Radiomics: An Innovative Method to Identify Primary Tumorous Sources of Liver Metastases.

OBJECTIVES: To develop radiomic models of B-mode ultrasound (US) signatures for determining the origin of primary tumors in metastatic liver disease. METHODS: A total of 254 patients with a diagnosis of metastatic liver disease were included in this retrospective study. The patients were divided into 3 groups depending on the origin of the primary tumor: group 1 (digestive tract versus non-digestive tract tumors), group 2 (breast cancer versus non-breast cancer), and group 3 (lung cancer versus other malignancies). The patients in each group were allocated to a training or testing set (a ratio of 8:2). The region of interest of liver metastasis was determined through manual differentiation of the tumors, and radiomic signatures were acquired from B-mode US images. Optimal features were selected to develop 3 radiomic models using multiple-dimensionality reduction and classifier screening. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess each model's performance. RESULTS: A total of 5936 features were extracted, and 40, 6, and 14 optimal features were sequentially identified for the development of radiomic models for groups 1, 2, and 3, respectively, with training set AUC values of 0.938, 0.974, and 0.768 and testing set AUC values of 0.767, 0.768, and 0.750. The differences in age, sex, and number of liver metastatic lesions varied greatly between the 4 primary tumors (P < .050). CONCLUSIONS: B-mode US radiomic models could be effective supplemental means to identify the origin of hepatic metastatic lesions (ie, unknown primary sites).

Magnetic resonance imaging (MRI) radiomics of papillary thyroid cancer (PTC): a comparison of predictive performance of multiple classifiers modeling to identify cervical lymph node metastases before surgery.

PURPOSE: To compare predictive efficiency of multiple classifiers modeling and establish a combined magnetic resonance imaging (MRI) radiomics model for identifying lymph node (LN) metastases of papillary thyroid cancer (PTC) preoperatively. MATERIALS AND METHODS: A retrospective analysis based on the preoperative MRI scans of 109 PTC patients including 77 patients with LN metastases and 32 patients without metastases was conducted, and we divided enroll cases into trained group and validation group. Radiomics signatures were selected from fat-suppressed T2-weighted MRI images, and the optimal characteristics were confirmed by spearman correlation test, hypothesis testing and random forest methods, and then, eight predictive models were constructed by eight classifiers. The receiver operating characteristic (ROC) curves analysis were performed to demonstrate the effectiveness of the models. RESULTS: The area under the curve (AUC) of ROC based on MRI texture diagnosed LN status by naked eye was 0.739 (sensitivity = 0.571, specificity = 0.906). Based on the 5 optimal signatures, the best AUC of MRI radiomics model by logistics regression classifier had a considerable prediction performance with AUCs 0.805 in trained group and 0.760 in validation group, respectively, and a combination of best radiomics model with visual diagnosis of MRI texture had a high AUC as 0.969 (sensitivity = 0.938, specificity = 1.000), suggesting combined model had a preferable diagnostic efficiency in evaluating LN metastases of PTC. CONCLUSION: Our combined radiomics model with visual diagnosis could be a potentially effective strategy to preoperatively predict LN metastases in PTC patients before clinical intervention.

[Application of MRI-based Radiomics Models in the Assessment of Hepatic Metastasis of Rectal Cancer].

OBEJECTIVE: To explore the clinical value of using radiomics models based on different MRI sequences in the assessment of hepatic metastasis of rectal cancer. METHODS: 140 patients with pathologically confirm edrectal cancer were included in the study. They underwent baseline magnetic resonance imaging (MRI) between April 2015 and May 2018 before receiving any treatment. According to the results of liver biopsy, surgical pathology, and imaging, patients were put into two groups, the patients with hepatic metastasis and those without. T2 weighted images (T2WI), diffusion weighted images (DWI) and apparent diffusion coefficient (ADC) images were used to draw the region of interest (ROI) of primary lesions on consecutive slices on ITK-SNAP. 3-D ROIs were generated and loaded into Artificial Intelligent Kit for extraction of radiomics features and 396 features were extracted for each sequence. The feature data were preprocessed on Python and the samples were oversampled, using Support Vector Machine-Synthetic Minority Over-Sampling Technique (SVM-SMOTE) to balance the number of samples in the group with liver metastasis and the group with no liver metastasis at the end of the follow-up. Then, the samples were divided into the training cohort and the test cohort at a ratio of 2∶1. The logistic regression models were developed with selected radionomic features on R software. The receiver operating characteristics (ROC) curves and calibration curves were used to evaluate the performance of the models. RESULTS: In total, 52 patients with liver metastasis and 88 patients without liver metastasis at the end of follow-up were enrolled. Carcinoembryonic antigen (CEA) and T stage and N stage evaluated on the MRI images showed statistically significant difference between the two groups ( P<0.05). After data preprocessing and selecting, except for 17 non-radiomic features, the model combining T2WI, DWI and ADC features, the model of T2WI features alone, the model of DWI features alone and the model of ADC features alone were developed with 32 features, 10 features, 30 features and 15 features, respectively. The combined model (T2WI+DWI+ADC), the T2WI model, and the ADC model can assess hepatic metastasis accurately, with the area under curve ( AUC) on the train set reaching 93.5%, 89.2%, 90.6% and that of the test set reaching 80.8%, 80.5%, 81.4%, respectively. The combined model did not show a higher AUC than those of the T2WI and ADC alone models. Model based on DWI features has a slightly insufficient AUC of 90.3% in the train set and 75.1% in the test set. The calibration curve showed the smallest fluctuation in the combined model, which is closest fit to the diagonal reference line. The fluctuation in the three independent data set models were similar. The calibration curves of all the four models showed that as the risk increased, the prediction of the models turned from an underestimation to an overestimating the risk. In brief, the combined model showed the best performance, with the best fit to the diagonal reference line in calibration curve and high AUC comparable to the AUC of the T2WI model and ADC model. The performance of T2WI and ADC alone models were second to that of the combined model, while the DWI alone model showed relatively poor performance. CONCLUSION: Radiomics models based on MRI could be effectively used in assessing liver metastasis in rectal cancer, which may help determine clinical staging and treatment.

[Application of Automated Machine Learning Based on Radiomics Features of T2WI and RS-EPI DWI to Predict Preoperative T Staging of Rectal Cancer].

OBJECTIVE: To explore the radiomics features of T2 weighted image (T2WI) and readout-segmented echo-planar imaging (RS-EPI) plus difusion-weighted imaging (DWI), to develop an automated mahchine-learning model based on the said radiomics features, and to test the value of this model in predicting preoperative T staging of rectal cancer. METHODS: The study retrospectively reviewed 131 patients who were diagnosed with rectal cancer confirmed by the pathology results of their surgical specimens at West China Hospital of Sichuan University between October, 2017 and December, 2018. In addition, these patients had preoperative rectal MRI. Tumor regions from preoperative MRI were manually segmented by radiologists with the ITK-SNAP software from T2WI and RS-EPI DWI images. PyRadiomics was used to extract 200 features-100 from T2WI and 100 from the apparent diffusion coefficient (ADC) calculated from the RS-EPI DWI. MWMOTE and NEATER were used to resample and balance the dataset, and 13 cases of T 1-2 stage simulation cases were added. The overall dataset was divided into a training set (111 cases) and a test set (37 cases) by a ratio of 3∶1. Tree-based Pipeline Optimization Tool (TPOT) was applied on the training set to optimize model parameters and to select the most important radiomics features for modeling. Five independent T stage models were developed accordingly. Accuracy and the area under the curve ( AUC) of receiver operating characteristic (ROC) were used to pick out the optimal model, which was then applied on the training set and the original dataset to predict the T stage of rectal cancer. RESULTS: The performance of the the five T staging models recommended by automated machine learning were as follows: The accuracy for the training set ranged from 0.802 to 0.838, sensitivity, from 0.762 to 0.825, specificity, from 0.833 to 0.896, AUC, from 0.841 to 0.893, and average precision (AP) from 0.870 to 0.901. After comparison, an optimal model was picked out, with sensitivity, specificity and AUC for the training set reaching 0.810, 0.875, and 0.893, respectively. The sensitivity, specificity and AUC for the test set were 0.810, 0.813, and 0.810, respectively. The sensitivity, specificity and AUC for the original dataset were 0.810, 0.830, and 0.860, respectively. CONCLUSION: Based on the radiomics data of T2WI and RS-EPI DWI, the model established by automated machine learning showed a fairly high accuracy in predicting rectal cancer T stage.

Effect of hypertension on outcomes of adult inpatients with COVID-19 in Wuhan, China: a propensity score-matching analysis.

BACKGROUND: Previous studies have shown that Coronavirus Disease 2019 (COVID-19) patients with underlying comorbidities can have worse outcomes. However, the effect of hypertension on outcomes of COVID-19 patients remains unclear. RESEARCH QUESTION: The aim of this study was to explore the effect of hypertension on the outcomes of patients with COVID-19 by using propensity score-matching (PSM) analysis. STUDY DESIGN AND METHODS: Participants enrolled in this study were patients with COVID-19 who had been hospitalized at the Central Hospital of Wuhan, China. Chronic comorbidities and laboratory and radiological data were reviewed; patient outcomes and lengths of stay were obtained from discharge records. We used the Cox proportional-hazard model (CPHM) to analyze the effect of hypertension on these patients' outcomes and PSM analysis to further validate the abovementioned effect. RESULTS: A total of 226 patients with COVID-19 were enrolled in this study, of whom 176 survived and 50 died. The proportion of patients with hypertension among non-survivors was higher than that among survivors (26.70% vs. 74.00%; P < 0.001). Results obtained via CPHM showed that hypertension could increase risk of mortality in COVID-19 patients (hazard ratio 3.317; 95% CI [1.709-6.440]; P < 0.001). Increased D-dimer levels and higher ratio of neutrophils to lymphocytes (N/L) were also found to increase these patients' mortality risk. After matching on propensity score, we still came to similar conclusions. After we applied the same method in critically ill patients, we found that hypertension also increased risk of death in patients with severe COVID-19. CONCLUSION: Hypertension, increased D-dimer and the ratio of neutrophil to lymphocyte increased mortality in patients with COVID-19, with hypertension in particular.

Nutrient factor-dependent performance of bacterial quorum sensing system during population evolution.

Bacterial quorum sensing (QS) system regulates the production of most costly but sharable extracellular products (public goods) in a growth-phase-dependent manner, and the development of this energy-intensive process is susceptible to environmental changes. However, the role of nutrient factors in dominating the QS-mediated cooperative interaction and intracellular metabolism still remains less understood. Here we studied the performance of QS system by growing Pseudomonas aeruginosa under different nutrient and culture conditions. The results of comparative-transcriptomic analyses revealed that carbon source-limitation was the main factor suppressing the activation of QS system, and a substantial number of public-good-encoding genes were induced when phosphorus is limiting in short-term culture. By contrast, although the QS regulation of P. aeruginosa in all the cultures was generally decreased along with the enrichment of QS-deficient individuals during evolution, limitation of different nutrient factors had discrepant effects in directing the formation of population structure by coordinating the production of public goods and primary metabolism, especially the starch and sucrose metabolism. These findings demonstrate the pleiotropy of QS regulation in balancing the development of cooperative behavior and metabolism, and provide a reference for further understanding the role of QS system in causing persistent infections.