The role of sulfur cycle in new particle formation: Cycloaddition reaction of SO3 to H2S.

The chemistry of sulfur cycle contributes significantly to the atmospheric nucleation process, which is the first step of new particle formation (NPF). In the present study, cycloaddition reaction mechanism of sulfur trioxide (SO3) to hydrogen sulfide (H2S) which is a typical air pollutant and toxic gas detrimental to the environment were comprehensively investigate through theoretical calculations and Atmospheric Cluster Dynamic Code simulations. Gas-phase stability and nucleation potential of the product thiosulfuric acid (H2S2O3, TSA) were further analyzed to evaluate its atmospheric impact. Without any catalysts, the H2S + SO3 reaction is infeasible with a barrier of 24.2 kcal/mol. Atmospheric nucleation precursors formic acid (FA), sulfuric acid (SA), and water (H2O) could effectively lower the reaction barriers as catalysts, even to a barrierless reaction with the efficiency of cis-SA > trans-FA > trans-SA > H2O. Subsequently, the gas-phase stability of TSA was investigated. A hydrolysis reaction barrier of up to 61.4 kcal/mol alone with an endothermic isomerization reaction barrier of 5.1 kcal/mol under the catalytic effect of SA demonstrates the sufficient stability of TSA. Furthermore, topological and kinetic analysis were conducted to determine the nucleation potential of TSA. Atmospheric clusters formed by TSA and atmospheric nucleation precursors (SA, ammonia NH3, and dimethylamine DMA) were thermodynamically stable. Moreover, the gradually decreasing evaporation coefficients for TSA-base clusters, particularly for TSA-DMA, suggests that TSA may participate in NPF where the concentration of base molecules are relatively higher. The present new reaction mechanism may contributes to a better understanding of atmospheric sulfur cycle and NPF.

Pore-Scale Numerical Simulation of Acid-Rock Reaction Processes in Carbonate Reservoirs.

In the process of acidizing carbonate reservoirs, dissolution is employed for reservoir modification to enhance recovery rates. This study establishes a numerical model at the pore scale for acid-rock reaction flow based on a microscopic continuum medium model, integrating phase-field theory and component transport models. Subsequently, the results of the Darcy-Brinkman-Stokes model are compared to those of the arbitrary Lagrange-Euler method to validate the accuracy of the model. Finally, the flow behavior of the acid solution at the pore scale and the complex dissolution mechanisms in carbonate reservoirs are analyzed. The research indicates that the microscopic pore-scale dissolution in carbonate reservoirs mainly manifests as five dissolution modes: uniform dissolution, compact dissolution, conical wormholes, dominant wormhole, and ramified wormholes. Different distributions of microfractures will alter the flow state of the acid solution and the rock-acid reaction process within the pores. Once the wormhole breakthrough occurs, there is an increased probability of acid flow through the wormhole to the outlet, leading to a decrease in the effectiveness of the acidizing carbonate reservoirs. A proper understanding of pore-scale acid-rock reaction laws is of great significance for the development of carbonate oil and gas reservoirs.

CT-based radiomics model using stability selection for predicting the World Health Organization/International Society of Urological Pathology grade of clear cell renal cell carcinoma.

OBJECTIVES: This study aimed to develop a model to predict World Health Organization/International Society of Urological Pathology (WHO/ISUP) low-grade or high-grade clear cell renal cell carcinoma (ccRCC) using 3D multiphase enhanced CT radiomics features (RFs). METHODS: CT data of 138 low-grade and 60 high-grade ccRCC cases were included. RFs were extracted from four CT phases: non-contrast phase (NCP), corticomedullary phase, nephrographic phase, and excretory phase (EP). Models were developed using various combinations of RFs and subjected to cross-validation. RESULTS: There were 107 RFs extracted from each phase of the CT images. The NCP-EP model had the best overall predictive value (AUC = 0.78), but did not significantly differ from that of the NCP model (AUC = 0.76). By considering the predictive ability of the model, the level of radiation exposure, and model simplicity, the overall best model was the Conventional image and clinical features (CICFs)-NCP model (AUC = 0.77; sensitivity 0.75, specificity 0.69, positive predictive value 0.85, negative predictive value 0.54, accuracy 0.73). The second-best model was the NCP model (AUC = 0.76). CONCLUSIONS: Combining clinical features with unenhanced CT images of the kidneys seems to be optimal for prediction of WHO/ISUP grade of ccRCC. This noninvasive method may assist in guiding more accurate treatment decisions for ccRCC. ADVANCES IN KNOWLEDGE: This study innovatively employed stability selection for RFs, enhancing model reliability. The CICFs-NCP model's simplicity and efficacy mark a significant advancement, offering a practical tool for clinical decision-making in ccRCC management.

Resensitizing tigecycline- and colistin-resistant Escherichia coli using an engineered conjugative CRISPR/Cas9 system.

Tigecycline and colistin were referred to as the "last resort" antibiotics in defending against carbapenem-resistant, Gram-negative bacterial infections, and are currently widely used in clinical treatment. However, the emergence and prevalence of plasmid-mediated tet(X4) and mcr-1 genes pose a serious threat to the therapeutic application of tigecycline and colistin, respectively. In this research, a tigecycline- and colistin-resistant bacteria resensitization system was developed based on efficient and specific DNA damage caused by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Associated Protein 9 (Cas9) nucleases. A conjugation method was used to deliver the resensitization system, which harbors two single-guide RNAs targeting tet(X4) and mcr-1 genes and constitutively expressed Cas9. The conjugation efficiency was nearly 100% after conjugation condition optimization in vitro, and the resensitivity efficiency for clinical isolates was over 90%. In addition, when performing resensitization in vivo, the resistance marker was replaced with a glutamate-based, chromosomal, plasmid-balanced lethal system to prevent the introduction of additional resistance genes in clinical settings, making this strategy a therapeutic approach to combat the in vivo spread of antibiotic resistance genes (ARGs) among bacterial pathogens. As a proof of concept, this resensitive system can significantly decrease the counts of tigecycline- and colistin-resistant bacteria to 1% in vivo. Our study demonstrates the efficacy and adaptability of CRISPR-Cas systems as powerful and programmable antimicrobials in resensitizing tet(X4)- and mcr-1-mediated, tigecycline- and colistin-resistant strains, and opens up new pathways for the development of CRISPR-based tools for selective bacterial pathogen elimination and precise microbiome composition change. IMPORTANCE: The emergence of plasmid-encoded tet(X4) and mcr-1 isolated from human and animal sources has affected the treatment of tigecycline and colistin, and has posed a significant threat to public health. Tigecycline and colistin are considered as the "last line of defense" for the treatment of multidrug-resistant (MDR) Gram-negative bacterial infections, so there is an urgent need to find a method that can resensitize tet(X4)-mediated tigecycline-resistant and mcr-1-mediated colistin-resistant bacteria. In this study, we developed a glutamate-based, chromosomal, plasmid-balanced lethal conjugative CRISPR/Cas9 system, which can simultaneously resensitize tet(X4)-mediated tigecycline-resistant and mcr-1-mediated colistin-resistant Escherichia coli. The counts of tigecycline- and colistin-resistant bacteria decreased to 1% in vivo after the resensitization system was administered. This study opens up new pathways for the development of CRISPR-based tools for selective bacterial pathogen elimination and precise microbiome composition change.

Biomimetic injectable and bilayered hydrogel scaffold based on collagen and chondroitin sulfate for the repair of osteochondral defects.

The simultaneous regeneration of articular cartilage and subchondral bone is a major challenge. Bioinspired scaffolds with distinct regions resembling stratified anatomical architecture provide a potential strategy for osteochondral defect repair. Here, we report the development of an injectable and bilayered hydrogel scaffold with a strong interface binding force. In this bilayer hydrogel, composed of carbonyl hydrazide grafted collagen (COL-CDH) and oxidized chondroitin sulfate (OCS), which are derivatives of osteochondral tissue components, in combination with poly (ethylene glycol) diacrylate (PEGDA), functions as a cartilage layer; while zinc-doped hydroxyapatite acts as a subchondral bone layer that is based on the cartilage layer. The strong interface between the two layers involves dynamic amide bonds formed between COL-CDH and OCS, and permanent CC bonds formed by PEGDA radical reactions. This bilayer hydrogel can be used to inoculate adipose mesenchymal stem cells which can then differentiate into chondrocytes and osteoblasts, secreting glycosaminoglycan, and promoting calcium deposition. This accelerates the regeneration of cartilage and subchondral bone. Micro-CT and tissue staining revealed an increase in the amount of bone present in new subchondral bone, and new tissues with a structure similar to normal cartilage. This study therefore demonstrates that injectable bilayer hydrogels are a promising scaffold for repairing osteochondral defects.

Nonlinear effect of NOx concentration decrease on secondary aerosol formation in the Beijing-Tianjin-Hebei region: Evidence from smog chamber experiments and field observations.

During the COVID-19 lockdown in the Beijing-Tianjin-Hebei (BTH) region in China, large decrease in nitrogen oxides (NOx) emissions, especially in the transportation sector, could not avoid the occurrence of heavy PM2.5 pollution where nitrate dominated the PM2.5 mass increase. To experimentally reveal the effect of NOx control on the formation of PM2.5 secondary components (nitrate in particular), photochemical simulation experiments of mixed volatile organic compounds (VOCs) under various NOx concentrations with smog chamber were performed. The proportions of gaseous precursors in the control experiment were comparable to ambient conditions typically observed in the BTH region. Under relatively constant VOCs concentrations, when the initial NOx concentration was reduced to 40% of that in the control experiment (labelled as NOx,0), the particle mass concentration was not significantly reduced, but when the initial NOx concentration decreased to 20 % of NOx,0, the mass concentration of particles as well as nitrate and organics showed a sudden decrease. A "critical point" where the mass concentration of secondary aerosol started to decline as the initial NOx concentration decreased, located at 0.2-0.4 NOx,0 (or 0.18-0.44 NO2,0) in smog chamber experiments. The oxidation capacity and solar radiation intensity played key roles in the mass concentration and compositions of the formed particles. In field observations in the BTH region in the autumn and winter seasons, the "critical point" exist at 0.15-0.34 NO2,0, which coincided mostly with the laboratory simulation results. Our results suggest that a reduction of NOx emission by >60% could lead to significant reductions of secondary aerosol formation, which can be an effective way to further alleviate PM2.5 pollution in the BTH region.

Adsorption Behavior of Organoarsenicals over MnFe2O4-Graphene Hybrid Nanocomposite: The Role of Organoarsenic Chemical Structures.

As a kind of emerging contaminant, organoarsenic compounds have drawn wide concern because of their considerable solubilities in water, and the highly toxic inorganic arsenic species formed during their biotic and abiotic degradation in the natural environment. Thus, the effective removal and studying of the adsorption mechanism of organoarsenic compounds are of significant urgency. In this work, MnFe2O4 and MnFe2O4/graphene were prepared through a facile solvothermal method. From the results of the Transmission Electron Microscope (TEM) characterization, it can be found that MnFe2O4 nanoparticles were uniformly distributed on the surface of the graphene. And the specific surface area of the MnFe2O4/graphene was about 146.39 m2 g-1, much higher than that of the MnFe2O4 (86.15 m2 g-1). The interactions between organoarsenic compounds and adsorbents were conducted to study their adsorption behavior and mechanism. The maximum adsorption capacities of MnFe2O4/graphene towards p-arsanilic acid (p-ASA) and roxarsone (ROX) were calculated to be 22.75 and 30.59 mg g-1. Additionally, the ionic strength, negative ions, and humus were introduced to investigate the adsorption performance of organoarsenic compounds. Electrostatic adsorption and surface complexation are the primary adsorption mechanisms on account of X-ray photoelectron spectroscopy (XPS) and the Fourier-transform infrared spectroscopy (FT-IR) analysis. This research extends the knowledge into studying the interaction between organoarsenic species and hybrid nanomaterials in the natural environment.

Passive smoking and risk of gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Pregestational smoking increases the risk of gestational diabetes mellitus (GDM) and is a common health problem during pregnancy, with its incidence on the rise worldwide, especially in China. This study is a meta-analysis of passive smoking as a risk factor associated with GDM. METHODS: Two independent reviewers searched passive smoking and the risk of GDM in PubMed, Medline, Web of Knowledge, Science Direct, China National Knowledge Internet (CNKI) and Wanfang databases (up to May 2023). The authors extracted the study data independently and used the Newcastle-Ottawa scale (NOS) to evaluate the quality of the included articles. A meta-analysis was conducted using a random effects model depending on the size of the heterogeneity. Begg's and Egger's tests were performed to assess publication bias. RESULTS: The overall relative risk for GDM caused by passive smoking was 1.47 (95% CI: 1.31-1.64), with moderate heterogeneity between studies (I2=41.7%, p=0.079). Subgroup and sensitivity analyses were stable, and no evidence of publication bias was found. CONCLUSIONS: Passive smoking is a risk factor for GDM, even in those who are not active smokers. To eliminate the effects of other confounding factors, larger prospective cohort studies are required to clarify the relationship between passive smoking and the occurrence of GDM.

Carbon Quantum Dots Accelerating Surface Charge Transfer of 3D PbBiO2I Microspheres with Enhanced Broad Spectrum Photocatalytic Activity-Development and Mechanism Insight.

The development of a highly efficient, visible-light responsive catalyst for environment purification has been a long-standing exploit, with obstacles to overcome, including inefficient capture of near-infrared photons, undesirable recombination of photo-generated carriers, and insufficient accessible reaction sites. Hence, novel carbon quantum dots (CQDs) modified PbBiO2I photocatalyst were synthesized for the first time through an in-situ ionic liquid-induced method. The bridging function of 1-butyl-3-methylimidazolium iodide ([Bmim]I) guarantees the even dispersion of CQDs around PbBiO2I surface, for synchronically overcoming the above drawbacks and markedly promoting the degradation efficiency of organic contaminants: (i) CQDs decoration harness solar photons in the near-infrared region; (ii) particular delocalized conjugated construction of CQDs strength via the utilization of photo-induced carriers; (iii) π-π interactions increase the contact between catalyst and organic molecules. Benefiting from these distinguished features, the optimized CQDs/PbBiO2I nanocomposite displays significantly enhanced photocatalytic performance towards the elimination of rhodamine B and ciprofloxacin under visible/near-infrared light irradiation. The spin-trapping ESR analysis demonstrates that CQDs modification can boost the concentration of reactive oxygen species (O2•-). Combined with radicals trapping tests, valence-band spectra, and Mott-Schottky results, a possible photocatalytic mechanism is proposed. This work establishes a significant milestone in constructing CQDs-modified, bismuth-based catalysts for solar energy conversion applications.

Formation mechanism of typical aromatic sulfuric anhydrides and their potential role in atmospheric nucleation process.

Sulfuric anhydrides, generated from the cycloaddition reaction of SO3 with carboxylic acids, have been revealed to be potential participants in the nucleation process of new particle formation (NPF). Hence the reaction mechanisms of typical aromatic acids (benzoic acid (BA), phenylacetic acid (PAA), phthalic acid (PA), isophthalic acid (mPA), and terephthalic acid (PTA)) with SO3 to generate the corresponding aromatic sulfuric anhydrides were investigated by density functional theory calculations at the level of M06-2X/6-311++G(3df,3pd). As a result, these reactions were found to be feasible in the gas phase with barriers of 0.34, 0.30, 0.18, 0.08 and 0.12 kcal/mol to generate corresponding aromatic sulfuric anhydrides, respectively. The thermodynamic stabilities of clusters containing aromatic sulfuric anhydrides and atmospheric nucleation precursors (sulfuric acid, ammonia and dimethylamine) were further analyzed to identify the potential role of aromatic sulfuric anhydrides in NPF. As the thermodynamic stability of a cluster depends on both the number and strength of hydrogen bonds, the greater stability of the interactions between atmospheric nucleation precursors and aromatic sulfuric anhydrides than with aromatic acids make aromatic sulfuric anhydrides potential participators in the nucleation process of NPF. Moreover, compared with BA, the addition of a -CH2- functional group in PAA has little influence on the reaction barrier with SO3 but an inhibitive effect on the thermodynamic stability of clusters. The position of the two -COOH functional groups in PA, mPA and PTA does not have a consistent impact on the reaction barrier with SO3 or the thermodynamic stability.

An exploratory study of CT radiomics using differential network feature selection for WHO/ISUP grading and progression-free survival prediction of clear cell renal cell carcinoma.

Objectives: To explore the feasibility of predicting the World Health Organization/International Society of Urological Pathology (WHO/ISUP) grade and progression-free survival (PFS) of clear cell renal cell cancer (ccRCC) using the radiomics features (RFs) based on the differential network feature selection (FS) method using the maximum-entropy probability model (MEPM). Methods: 175 ccRCC patients were divided into a training set (125) and a test set (50). The non-contrast phase (NCP), cortico-medullary phase, nephrographic phase, excretory phase phases, and all-phase WHO/ISUP grade prediction models were constructed based on a new differential network FS method using the MEPM. The diagnostic performance of the best phase model was compared with the other state-of-the-art machine learning models and the clinical models. The RFs of the best phase model were used for survival analysis and visualized using risk scores and nomograms. The performance of the above models was tested in both cross-validated and independent validation and checked by the Hosmer-Lemeshow test. Results: The NCP RFs model was the best phase model, with an AUC of 0.89 in the test set, and performed superior to other machine learning models and the clinical models (all p <0.05). Kaplan-Meier survival analysis, univariate and multivariate cox regression results, and risk score analyses showed the NCP RFs could predict PFS well (almost all p < 0.05). The nomogram model incorporated the best two RFs and showed good discrimination, a C-index of 0.71 and 0.69 in the training and test set, and good calibration. Conclusion: The NCP CT-based RFs selected by differential network FS could predict the WHO/ISUP grade and PFS of RCC.

Rapid Detection of MCR-Mediated Colistin Resistance in Escherichia coli.

Colistin is one of the last-resort antibiotics for infections caused by multidrug-resistant Gram-negative bacteria. However, the wide spread of novel plasmid-carrying colistin resistance genes mcr-1 and its variants substantially compromise colistin's therapeutic effectiveness and pose a severe danger to public health. To detect colistin-resistant microorganisms induced by mcr genes, rapid and reliable antibiotic susceptibility testing (AST) is imminently needed. In this study, we identified an RNA-based AST (RBAST) to discriminate between colistin-susceptible and mcr-1-mediated colistin-resistant bacteria. After short-time colistin treatment, RBAST can detect differentially expressed RNA biomarkers in bacteria. Those candidate mRNA biomarkers were successfully verified within colistin exposure temporal shifts, concentration shifts, and other mcr-1 variants. Furthermore, a group of clinical strains were effectively distinguished by using the RBAST approach during the 3-h test duration with over 93% accuracy. Taken together, our findings imply that certain mRNA transcripts produced in response to colistin treatment might be useful indicators for the development of fast AST for mcr-positive bacteria. IMPORTANCE The emergence and prevalence of mcr-1 and its variants in humans, animals, and the environment pose a global public health threat. There is a pressing urgency to develop rapid and accurate methods to identify MCR-positive colistin-resistant bacteria in the clinical samples, providing a basis for subsequent effective antibiotic treatment. Using the specific mRNA signatures, we develop an RNA-based antibiotic susceptibility testing (RBAST) for effectively distinguishing colistin-susceptible and mcr-1-mediated colistin-resistant strains. Meanwhile, the detection efficiency of these RNA biomarkers was evidenced in other mcr variants-carrying strains. By comparing with the traditional AST method, the RBAST method was verified to successfully characterize a set of clinical isolates during 3 h assay time with over 93% accuracy. Our study provides a feasible method for the rapid detection of colistin-resistant strains in clinical practice.

A theoretical study on the formation mechanism of carboxylic sulfuric anhydride and its potential role in new particle formation.

New particle formation (NPF) is the major source of atmospheric aerosol particles. However, the chemical species involved and the exact mechanism are still unclear. Cycloaddition reaction of SO3 to carboxylic acids bas been identified as a possible formation mechanism of carboxylic sulfuric anhydrides which may be involved in NPF. Herein, energy profiles for forming diaterpenylic acetate sulfuric anhydride (DTASA) through cycloaddition of SO3 to diaterpenylic acid acetate (DTAA) and the potential role of DTASA in NPF were studied through computational methods combined with atmospheric cluster dynamics code (ACDC). Gas phase reaction barriers for the two carboxyl groups of DTAA are 0.4 and 0.6 kcal mol-1, respectively, illustrating a feasible formation mechanism for DTASA. According to thermodynamical analysis and dynamical simulations, atmospheric clusters containing DTASA and atmospheric nucleation precursors sulfuric acid (SA), ammonia (NH3) and dimethylamine (DMA) possess both thermodynamically and dynamically higher stabilities than those of DTAA-contained clusters. Furthermore, DTASA-NH3 and DTASA-DMA are more stable than SA-NH3 and SA-DMA, enabling DTASA, even carboxylic sulfuric anhydrides, to become potential participants in the atmospheric NPF process which may hence promote a better understanding of NPF.

Promoting Chinese urban residents' participation in source separation and recycling.

Source separation and recycling (SSR) for municipal solid waste is an important strategy for the transition to a circular economy and requires broader resident participation. How can residents' participation in SSR be promoted? Here, we consider 13 cities in Jiangsu as microcosms of China. We quantify residents' intentions to participate in SSR by distributing a validated questionnaire to 2,963 urban residents, analyze the results through structural equation modeling, and propose localized policy recommendations. We find that residents have positive attitudes toward SSR, although 92.6% of residents in southern Jiangsu were more willing to participate than those in northern Jiangsu (84.6%). Additionally, the influencing factors and their degree of influence on resident SSR participation intentions exhibit disparities across cities. "Accessibility of SSR facilities" simultaneously affects the 13 studied cities and is a key factor. "Environmental knowledge" and "environmental attitudes" are important impact factors, with occurrence frequencies of 84.6% and 69.2%, respectively. However, laws and regulations have no significant effect on residents' SSR participation intentions. We recommend that the government create favorable external conditions related to facilities and services, promote extensive publicity and educational activities through various channels, and improve the effectiveness of SSR laws and regulations. Future SSR management strategies should be localized, flexible and comprehensive. This research could help decision makers in China and other countries design policy guides to promote SSR and help link current research areas to social development.

A Reliable Prediction Model for Renal Cell Carcinoma Subtype Based on Radiomic Features from 3D Multiphase Enhanced CT Images.

BACKGROUND: This study aimed to develop a prediction model to distinguish renal cell carcinoma (RCC) subtypes. METHODS: The radiomic features (RFs) from 5 different computed tomography (CT) phases were used in the prediction models: noncontrast phase (NCP), corticomedullary phase (CMP), nephrographic phase (NP), excretory phase (EP), and all-phase (ALL-P). RESULTS: For the ALL-P model, all of the RFs obtained from the 4 single-phase images were combined to 420 RFs. The ALL-P model performed the best of all models, with an accuracy of 0.80; the sensitivity and specificity for clear cell RCC (ccRCC) were 0.85 and 0.83; those for papillary RCC (pRCC) were 0.60 and 0.91; those for chromophobe RCC (cRCC) were 0.66 and 0.91, respectively. Binary classification experiments showed for distinguishing ccRCC vs. not-ccRCC that the area under the receiver operating characteristic curve (AUC) of the ALL-P and CMP models was 0.89, but the overall sensitivity/specificity/accuracy of the ALL-P model was better. For cRCC vs. non-cRCC, the ALL-P model had the best performance. CONCLUSIONS: A reliable prediction model for RCC subtypes was constructed. The performance of the ALL-P prediction model was the best as compared to individual single-phase models and the traditional prediction model.

Computed Tomography Image under Three-Dimensional Reconstruction Algorithm Based in Diagnosis of Renal Tumors and Retroperitoneal Laparoscopic Partial Nephrectomy.

This study was to explore the clinical application value of computed tomography (CT) images based on a three-dimensional (3D) reconstruction algorithm for laparoscopic partial nephrectomy (LPN) in patients with renal tumors. 30 cases of renal cell carcinoma (RCC) patients admitted to the hospital were selected as the research objects and were rolled into two groups using a random table method. The patients who received PLN under the three-dimensional reconstruction and laparoscopic technique were included in the experimental group (group A), and the patients who received LPN using CT images only were included in the control group (group B). In addition, the treatment results of the two groups of patients were compared and analyzed. Results. The effective rate of the established model was 93.3%; the total renal arteriovenous variability of group A (13.3%) was higher than that of group B (6.7%), and the operation time (131.5 ± 32.1 minutes) was much lower than that of group B (158.7 ± 36.2 minutes), showing statistical significance (P < 0.05). Conclusion. CT images based on 3D reconstruction algorithms had high clinical application value for LPN in patients with renal tumors, which could improve the efficiency and safety of LPN.

Rapid and Accurate Antibiotic Susceptibility Determination of tet(X)-Positive E. coli Using RNA Biomarkers.

The emergence and prevalence of novel plasmid-mediated tigecycline resistance genes, namely, tet(X) and their variants, pose a serious threat to public health worldwide. Rapid and accurate antibiotic susceptibility testing (AST) that can simultaneously detect the genotype and phenotype of tet(X)-positive bacteria may contribute to the deployment of an effective antibiotic arsenal, mortality reduction, and a decrease in the use of broad-spectrum antimicrobial agents. However, current bacterial growth-based AST methods, such as broth microdilution, are time consuming and delay the prompt treatment of infectious diseases. Here, we developed a rapid RNA-based AST (RBAST) assay to effectively distinguish tet(X)-positive and -negative strains. RBAST works by detecting specific mRNA expression signatures in bacteria after short-term tigecycline exposure. As a proof of concept, a panel of clinical isolates was characterized successfully by using the RBAST method, with a 3-h assay time and 87.9% accuracy (95% confidence interval [CI], 71.8% to 96.6%). Altogether, our findings suggest that RNA signatures upon antibiotic exposure are promising biomarkers for the development of rapid AST, which could inform early antibiotic choices. IMPORTANCE Infections caused by multidrug-resistant (MDR) Gram-negative pathogens are an increasing threat to global health. Tigecycline is one of the last-resort antibiotics for the treatment of these complicated infections; however, the emergence of plasmid-encoded tigecycline resistance genes, namely, tet(X), severely diminishes its clinical efficacy. Currently, there is a lack of rapid and accurate antibiotic susceptibility testing (AST) for the detection of tet(X)-positive bacteria. In this study, we developed a rapid and robust RNA-based antibiotic susceptibility determination (RBAST) assay to effectively distinguish tet(X)-negative and -positive strains using specific RNA biomarkers in bacteria after tigecycline exposure. Using this RBAST method, we successfully characterized a set of clinical strains in 3 h. Our data indicate that the RBAST assay is useful for identifying tet(X)-positive Escherichia coli.

Machine-Learning-Based m5C Score for the Prognosis Diagnosis of Osteosarcoma.

BACKGROUND: Osteosarcoma is a common and highly metastatic malignant tumor, and m5C RNA methylation regulates various biological processes. The purpose of this study was to explore the prognostic role of m5C in osteosarcoma using machine learning. METHODS: Osteosarcoma gene data and the corresponding clinical information were downloaded from the GEO database. Machine learning methods were used to screen m5C-related genes and construct m5C scores. In addition, the clusterProfiler package was used to predict the m5C-related functional pathways. xCell and CIBERSORT were used to calculate the immune microenvironment cells. GSVA was applied to analyze different categories of m5C genes, and the correlation between the GSVA and m5C scores was evaluated. RESULTS: Twenty m5C genes were identified, and 54 related genes were screened. The m5C score was constructed based on the PCA score. With an increase in the m5C score, the expression of m5C genes and their related genes changed. Functional analysis indicated that the focal adhesion, cell-substrate adherens junction, cell adhesion molecule binding, and E2F targets might change with the m5C score. The naive B cells and CD4+ memory T cell also changed with the m5C score. The results of the correlation analysis showed that the m5C score was significantly correlated with the reader and eraser genes. CONCLUSION: The m5C score might be a prognostic index for osteosarcoma.

Clinical significance and mechanism of LncRNA GAS-5 in osteoarthritis.

OBJECTIVE: To investigate the clinical significance and mechanism of LncRNA GAS-5 in osteoarthritis. METHODS: 67 patients with knee osteoarthritis (the case group) and 60 patients who underwent physical examination (the healthy group) were selected to evaluate the expression level of lncRNA GAS-5 in peripheral blood mononuclear cells. Cell experiments were conducted that took THP-1 cells carrying NC-shRNA (negative lentivirus) as the control group, and THP1 cells carrying GAS5-shRNA (lentivirus infection) as the study group; we evaluated the expression of lncRNA GAS-5 gene, and the expression of immune-related cytokines. RESULTS: (1) The expression of lncRNA GAS-5 in the case group was lower than in the healthy group (P<0.05). (2) The expression level of lncRNA GAS-5 in the case group versus control group, had an inhibition rate of 65.49% (P<0.05). The expression levels of 18 cytokines such as IL-1, IL-2, IL-6, IL-7, IL-17, G-CSF, M-CSF, and TGF-ß1, in the study group were higher than in the control group (P<0.05), but the expression of IL-10 and IL-13 were significantly lower than in the control group (P<0.05). CONCLUSION: The expression of lncRNA GAS-5 is low in osteoarthritis patients. While the expression of lncRNA GAS-5 is inhibited, related immune and inflammatory factors are also affected, so lncRNA GAS-5 may affect the occurrence and progression of osteoarthritis through immune regulation. A low level of lncRNA GAS-5 may be a marker for the occurrence and progression of osteoarthritis.

CT-based multi-phase Radiomic models for differentiating clear cell renal cell carcinoma.

BACKGROUND: The aim of the study is to compare the diagnostic value of models that based on a set of CT texture and non-texture features for differentiating clear cell renal cell carcinomas(ccRCCs) from non-clear cell renal cell carcinomas(non-ccRCCs). METHODS: A total of 197 pathologically proven renal tumors were divided into ccRCC(n = 143) and non-ccRCC (n = 54) groups. The 43 non-texture features and 296 texture features that extracted from the 3D volume tumor tissue were assessed for each tumor at both Non-contrast Phase, NCP; Corticomedullary Phase, CMP; Nephrographic Phase, NP and Excretory Phase, EP. Texture-score were calculated by the Least Absolute Shrinkage and Selection Operator (LASSO) to screen the most valuable texture features. Model 1 contains the three most distinctive non-texture features with p < 0.001, Model 2 contains texture scores, and Model 3 contains the above two types of features. RESULTS: The three models shown good discrimination of the ccRCC from non-ccRCC in NCP, CMP, NP, and EP. The area under receiver operating characteristic curve (AUC)values of the Model 1, Model 2, and Model 3 in differentiating the two groups were 0.748-0.823, 0.776-0.887 and 0.864-0.900, respectively. The difference in AUC between every two of the three Models was statistically significant (p < 0.001). CONCLUSIONS: The predictive efficacy of ccRCC was significantly improved by combining non-texture features and texture features to construct a combined diagnostic model, which could provide a reliable basis for clinical treatment options.