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.

Interactions of sulfuric acid with common atmospheric bases and organic acids: Thermodynamics and implications to new particle formation.

Interactions of the three common atmospheric bases, dimethylamine ((CH3)2NH), methylamine (CH3NH2), ammonia (NH3), all considered to be efficient stabilizers of binary clusters in the Earth's atmosphere, with H2SO4, the key atmospheric precursor, and 14 common atmospheric organic acids (COAs) (formic, acetic, oxalic, malonic, succinic, glutaric acid, adipic, benzoic, phenylacetic, pyruvic, maleic acid, malic, tartaric and pinonic acids) have been studied using the density functional theory (DFT) and composite high-accuracy G3MP2 method. The thermodynamic stability of mixed (COA)(H2SO4), (COA)(B1), (COA)(B2) and (COA)(B3) dimers and (COA)(H2SO4)(B1), (COA)(H2SO4)(B2) and (COA)(H2SO4)(B3) trimers, where B1, B2 and B3 refer to (CH3)2NH, CH3NH2 and NH3, respectively, have been investigated and their impacts on the thermodynamic stability of clusters containing H2SO4 have been studied. Our investigation shows that interactions of H2SO4 with COA, (CH3)2NH, CH3NH2 and NH3 lead to the formation of more stable mixed dimers and trimers than (H2SO4)2 and (H2SO4)2(base), respectively, and emphasize the importance of common organic species for early stages of atmospheric nucleation. We also show that although amines are generally confirmed to be more active than NH3 as stabilizers of binary clusters, in some cases mixed trimers containing NH3 are more stable thermodynamically than those containing CH3NH2. This study indicates an important role of COA, which coexist and interact with that H2SO4 and common atmospheric bases in the Earth atmosphere, in formation of stable pre-nucleation clusters and suggests that the impacts of COA on new particle formation (NPF) should be studied in further details.

Molecular and pharmacological characterization of poultry (Gallus gallus, Anas platyrhynchos, Anser cygnoides domesticus) and pig (Sus scrofa domestica) melanocortin-5 receptors and their mutants.

The melanocortin-5 receptor (MC5R) is a member of the G protein-coupled receptor superfamily that plays a critical role in lipid production, skeletal muscle fatty acid oxidation, and adipocyte lipolysis. Although multiple functions and important value of MC5R in human beings have been fully demonstrated, however, the potential molecular cloning, pharmacological characteristics and key amino acids in poultry and pig were still not fully understood. Herein, we successfully cloned MC5R genes from chicken (Gallus gallus, cMC5R), duck (Anas platyrhynchos, dMC5R), goose (Anser cygnoides domesticus, gMC5R) and pig (Sus scrofa domestica, pMC5R), and compared their genetic and protein difference with hMC5R through phylogenetic analysis and homology models. Besides, we constructed three alanine-substitution mutants for each of MC5Rs through homologous reorganization, including c/d/gMC5R-D119A/F254A/H257A and pMC5R-D204A/F339A/H342A. Subsequently, we focused our investigation on the pharmacological characterization of four wide-type MC5Rs and their mutants in HEK293T cells, including the intracellular cAMP generation and phosphorylation level of ERK1/2. The results showed that these mutants had decreased cAMP levels under the stimulation of ligands, in spite of enhanced basal activity for c/d/gF254A and pH342A, indicating their important roles in the location and activation of receptors. Notably, these MC5Rs and mutants displayed significant species-specific phenotypes in the activation of pERK1/2 with ligands, which was not completely consistent with hMC5R. These findings demonstrated that presence of interspecies differences for MC5Rs, particularly for the pERK1/2 pathway. Taken together, our study expands current knowledge about the molecular and pharmacological characterization of c/d/g/pMC5Rs, providing preliminary data for MC5R-targeted drug screening or genetic breeding of economic animals in the future.

Pharmacology of the giant panda (Ailuropoda melanoleuca) melanocortin-3 receptor.

The melanocortin-3 receptor (MC3R) is a member of the G protein-coupled receptor superfamily that plays a critical role in controlling energy balance and metabolism. Although pharmacological characterization of MC3R has been reported previously in several other species, there is no report on the MC3R from giant panda (Ailuropoda melanoleuca). This ancient species is known as a 'living fossil' and is among the most endangered animals in the world. Giant panda survive on a specialized diet of bamboo despite possessing a typical carnivorous digestive system. We report herein the molecular cloning and pharmacological characterization of amMC3R. Homology and phylogenetic analysis showed that amMC3R was highly homologous (>85%) to several other mammalian MC3Rs. Using human MC3R (hMC3R) as a control, the binding of five agonists, [Nle4, D-Phe7]-α-melanocyte stimulating hormone (NDP-MSH), α-, ß-, γ-, and D-Trp8-γ-MSH, was investigated, as well as Gs-cAMP and pERK1/2 signaling. The results showed that amMC3R bound NDP- and D-Trp8-γ-MSH with the highest affinity, followed by α-, ß-, and γ-MSH, with the same rank order as hMC3R. When stimulated with agonists, amMC3R displayed increased intracellular cAMP and activation of pERK1/2. These data suggest that the cloned amMC3R was a functional receptor. The availability of amMC3R and knowledge of its pharmacological functions will assist further investigation of its role in controlling energy balance and metabolism.

The role of nitric acid in atmospheric new particle formation.

Nitric acid, an air pollutant with strong acidity and oxidizability, can be found in considerable quantities in the gas and aerosol phase. Understanding the role of nitric acid in atmospheric new particle formation is essential to study the complicated nucleation mechanism. Using density functional theory combined with the Atmospheric Clusters Dynamic Code (ACDC), the role of nitric acid in the formation of new particles has been investigated under different atmospheric conditions (different precursor concentrations and temperatures). The results show that nitric acid can form clusters with sulfuric acid and ammonia by hydrogen bond or even proton-transfer interactions. The concentrations of clusters involving nitric acid can be comparable with those of sulfuric acid-ammonia-based clusters, considering the thermodynamic stability combined with the realistic atmospheric concentrations of precursors. Within the atmospheric concentration range, nitric acid can enhance the formation rates of sulfuric acid-ammonia clusters, especially at low temperature, low sulfuric acid concentration and high ammonia concentration. In addition, the new particle formation mechanism indicates that nitric acid can contribute to the cluster formation and the role of nitric acid in the cluster formation pathway is as a "bridge" connecting the smaller and larger clusters.

Clustering mechanism of oxocarboxylic acids involving hydration reaction: Implications for the atmospheric models.

The formation of atmospheric aerosol particles from condensable gases is a dominant source of particulate matter in the boundary layer, but the mechanism is still ambiguous. During the clustering process, precursors with different reactivities can induce various chemical reactions in addition to the formation of hydrogen bonds. However, the clustering mechanism involving chemical reactions is rarely considered in most of the nucleation process models. Oxocarboxylic acids are common compositions of secondary organic aerosol, but the role of oxocarboxylic acids in secondary organic aerosol formation is still not fully understood. In this paper, glyoxylic acid, the simplest and the most abundant atmospheric oxocarboxylic acid, has been selected as a representative example of oxocarboxylic acids in order to study the clustering mechanism involving hydration reactions using density functional theory combined with the Atmospheric Clusters Dynamic Code. The hydration reaction of glyoxylic acid can occur either in the gas phase or during the clustering process. Under atmospheric conditions, the total conversion ratio of glyoxylic acid to its hydration reaction product (2,2-dihydroxyacetic acid) in both gas phase and clusters can be up to 85%, and the product can further participate in the clustering process. The differences in cluster structures and properties induced by the hydration reaction lead to significant differences in cluster formation rates and pathways at relatively low temperatures.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.