Long-read sequencing of 111 rice genomes reveals significantly larger pan-genomes.

The concept of pan-genome, which is the collection of all genomes from a population, has shown a great potential in genomics study, especially for crop sciences. The rice pan-genome constructed from the second-generation sequencing (SGS) data is about 270 Mb larger than Nipponbare, the rice reference genome (NipRG), but it is still disadvantaged by incompleteness and loss of genomic contexts. The third-generation sequencing (TGS) with long reads can help to construct better pan-genomes. In this paper, we report a high-quality rice pan-genome construction method by introducing a series of new steps to deal with the long-read data, including unmapped sequence block filtering, redundancy removing, and sequence block elongating. Compared to NipRG, the long-read sequencing-based pan-genome constructed from 105 rice accessions, which contains 604 Mb novel sequences, is much more comprehensive than the one constructed from ∼3000 rice genomes sequenced with short reads. The repetitive sequences are the main components of novel sequences, which partially explain the differences between the pan-genomes based on TGS and SGS. Adding six wild rice accessions, there are about 879 Mb novel sequences and 19,000 novel genes in the rice pan-genome in total. In addition, we have created high-quality reference genomes for all representative rice populations, including five gapless reference genomes. This study has made significant progress in our understanding of the rice pan-genome, and this pan-genome construction method for long-read data can be applied to accelerate a broad range of genomics studies.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome.

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

Improved structure stability and performance of a LiFeSO4F cathode material for lithium-ion batteries by magnesium substitution.

Tavorite LiFeSO4F with high Li-ion conductivity has been considered a promising alternative to LiFePO4. However, its poor cycle stability and low electronic conductivity limit the practical application of Tavorite LiFeSO4F. In the present study, we employ a solvothermal method to produce magnesium-substitution LiMgxFe1-xSO4F (x = 0, 0.02, 0.04) cathode materials in which the Mg substitutes the Fe(2) sites. The first-principles calculations demonstrate that Mg-substitution could reduce the bandgap of LiFeSO4F and increase its electronic conductivity to 2.5 × 10-11 S cm-1. Meanwhile, CI-NEB and BV calculations reveal that the diffusion energy barrier of lithium along the (100) direction after Mg substitution is lower than the pristine sample, and the electrochemical inactive Mg2+ could improve the structure stability. The results show that the Mg-substituted LiFeSO4F exhibits enhanced cycle stability and rate performance compared with the pristine LiFeSO4F, suggesting that the use of electrochemically inactive ion substitution may be critical for the development of high-performance LiFeSO4F cathode materials for lithium-ion batteries.

Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation.

Detailed chemical kinetic models offer valuable mechanistic insights into industrial applications. Automatic generation of reliable kinetic models requires fast and accurate radical thermochemistry estimation. Kineticists often prefer hydrogen bond increment (HBI) corrections from a closed-shell molecule to the corresponding radical for their interpretability, physical meaning, and facilitation of error cancellation as a relative quantity. Tree estimators, used due to limited data, currently rely on expert knowledge and manual construction, posing challenges in maintenance and improvement. In this work, we extend the subgraph isomorphic decision tree (SIDT) algorithm originally developed for rate estimation to estimate HBI corrections. We introduce a physics-aware splitting criterion, explore a bounded weighted uncertainty estimation method, and evaluate aleatoric uncertainty-based and model variance reduction-based prepruning methods. Moreover, we compile a data set of thermochemical parameters for 2210 radicals involving C, O, N, and H based on quantum chemical calculations from recently published works. We leverage the collected data set to train the SIDT model. Compared to existing empirical tree estimators, the SIDT model (1) offers an automatic approach to generating and extending the tree estimator for thermochemistry, (2) has better accuracy and R2, (3) provides significantly more realistic uncertainty estimates, and (4) has a tree structure much more advantageous in descent speed. Overall, the SIDT estimator marks a great leap in kinetic modeling, offering more precise, reliable, and scalable predictions for radical thermochemistry.

Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks.

Quantitative estimates of reaction barriers and solvent effects are essential for developing kinetic mechanisms and predicting reaction outcomes. Here, we create a new data set of 5,600 unique elementary radical reactions calculated using the M06-2X/def2-QZVP//B3LYP-D3(BJ)/def2-TZVP level of theory. A conformer search is done for each species using TPSS/def2-TZVP. Gibbs free energies of activation and of reaction for these radical reactions in 40 common solvents are obtained using COSMO-RS for solvation effects. These balanced reactions involve the elements H, C, N, O, and S, contain up to 19 heavy atoms, and have atom-mapped SMILES. All transition states are verified by an intrinsic reaction coordinate calculation. We next train a deep graph network to directly estimate the Gibbs free energy of activation and of reaction in both gas and solution phases using only the atom-mapped SMILES of the reactant and product and the SMILES of the solvent. This simple input representation avoids computationally expensive optimizations for the reactant, transition state, and product structures during inference, making our model well-suited for high-throughput predictive chemistry and quickly providing information for (retro-)synthesis planning tools. To properly measure model performance, we report results on both interpolative and extrapolative data splits and also compare to several baseline models. During training and testing, the data set is augmented by including the reverse direction of each reaction and variants with different resonance structures. After data augmentation, we have around 2 million entries to train the model, which achieves a testing set mean absolute error of 1.16 kcal mol-1 for the Gibbs free energy of activation in solution. We anticipate this model will accelerate predictions for high-throughput screening to quickly identify relevant reactions in solution, and our data set will serve as a benchmark for future studies.

Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions.

Obtaining accurate enthalpies of formation of chemical species, ΔHf, often requires empirical corrections that connect the results of quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state. One approach is to use atomization energy corrections followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) as shown by Buerger et al. We implement both approaches in Arkane, an open-source software that can calculate species thermochemistry using results from various QM software packages. In this work, we collect 421 reference species from the literature to derive ΔHf corrections and fit atomization energy corrections and BACs for 15 commonly used model chemistries. We find that both types of BACs yield similar accuracy, although Anantharaman- and Melius-type BACs appear to generalize better. Furthermore, BACs tend to achieve better accuracy than IDRs for commonly used model chemistries, and IDRs can be less robust because of the sensitivity to the chosen reference species and reactions. Overall, Anantharaman- and Melius-type BACs are our recommended approach for achieving accurate QM corrections for enthalpies.

Genomic typing and virulence gene profile analysis of Salmonella Derby from different sources.

Salmonella enterica serovar Derby (S. Derby) is one of the most common Salmonella serovars which can infect poultry, swine, and humans. With the reduction of the sequencing cost and the improvement of sequencing technology, whole genome sequencing (WGS) has become an important method for bacterial determination, molecular investigation, and pathogenic tracing analysis. In this study, we investigated S. Derby isolates from different sources in China using in-silico multilocus sequence typing (MLST), core genome MLST (cgMLST) and whole genome MLST (wgMLST) analysis based on WGS. The results showed that 21 S. Derby strains were divided into 3 STs using MLST analysis, including ST40 (n = 19, accounting for 90.48%), ST71 (n = 1, accounting for 4.76%) and ST8016 (n = 1, accounting for 4.76%). cgMLST and wgMLST analysis categorized the tested strains into 13 cgSTs and 21 wgSTs, respectively. The minimum spanning trees of cgMLST and wgMLST both divided these strains into 3 clusters and 4 singletons. In addition, virulence gene profiles of S. Derby isolates were also analyzed, and a total of 174 virulence genes belonged to 8 categories were identified. In summary, we studied genomic typing, phylogenetic relationship and virulence gene profiles of S. Derby strains from different sources in China. These findings were beneficial for the epidemiology and pathogenesis of Salmonella.

Biofilm-forming ability of Salmonella enterica strains of different serotypes isolated from multiple sources in China.

Salmonella is an important zoonotic and foodborne pathogen that can infect humans and animals, causing severe concerns about food safety and a heavy financial burden worldwide. The pathogen can adhere to living and abiotic surfaces by forming biofilms, which increases the risk of transmission and infection. In this study, we investigated the biofilm-forming ability of 243 Salmonella strains of 36 serotypes from different sources in China using microplate crystal violet staining method. The results showed that 99.6% tested strains, with the exception of one strain of S. Thompson, were capable of forming biofilms. The strains with the biofilm-forming ability of strong, medium and weak accounted for 2.88%, 24.28% and 72.43%, respectively. The strains of S. Havana and S. Hvittingfoss had the strongest biofilm-forming ability, with the OD570 of 0.81 ± 0.02 and 0.81 ± 0.38, respectively, while the strains of S. Agona and S. Bovismorbificans had the weakest biofilm-forming ability, with the OD570 of 0.16 ± 0.02 and 0.15 ± 0.00, respectively. Furthermore, statistical analysis results demonstrated that isolation of source had no effect on the biofilm formation ability, while the detection rates of pefABCD and ddhC were positively correlated with the biofilm formation ability of Salmonella. In particular, the detection rate of ddhC gene was more than 60% in the biofilm forming strains. These findings have important guiding significance for the investigation of pathogenesis, as well as the prevention and control of salmonellosis.

Butyl Acetate Pyrolysis and Combustion Chemistry: Mechanism Generation and Shock Tube Experiments.

The combustion and pyrolysis behaviors of light esters and fatty acid methyl esters have been widely studied due to their relevance as biofuel and fuel additives. However, a knowledge gap exists for midsize alkyl acetates, especially ones with long alkoxyl groups. Butyl acetate, in particular, is a promising biofuel with its economic and robust production possibilities and ability to enhance blendstock performance and reduce soot formation. However, it is little studied from both experimental and modeling aspects. This work created detailed oxidation mechanisms for the four butyl acetate isomers (normal-, sec-, tert-, and iso-butyl acetate) at temperatures varying from 650 to 2000 K and pressures up to 100 atm using the Reaction Mechanism Generator. About 60% of species in each model have thermochemical parameters from published data or in-house quantum calculations, including fuel molecules and intermediate combustion products. Kinetics of essential primary reactions, retro-ene and hydrogen atom abstraction by OH or HO2, governing the fuel oxidation pathways, were also calculated quantum-mechanically. Simulation of the developed mechanisms indicates that the majority of the fuel will decompose into acetic acid and relevant butenes at elevated temperatures, making their ignition behaviors similar to butenes. The adaptability of the developed models to high-temperature pyrolysis systems was tested against newly collected high-pressure shock experiments; the simulated CO mole fraction time histories have a reasonable agreement with the laser measurement in the shock tube. This work reveals the high-temperature oxidation chemistry of butyl acetates and demonstrates the validity of predictive models for biofuel chemistry established on accurate thermochemical and kinetic parameters.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of >130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

ivTerm-An R package for interactive visualization of functional analysis results of meta-omics data.

Interpreting functional analysis results derived from environmental samples using direct sequencing meta-omics data, including metagenomics and meta-transcriptomics data, is challenging due to their complexity. Visualization of functional analysis results can help researchers discover relevant biological insights. Despite the availability of many R packages, there lacks interactive and comprehensive graphic systems for displaying functional terms and corresponding genes in meta-omics analysis results. Here, we present ivTerm, an R-shiny package with a user-friendly graphical interface that enables users to inspect functional annotations, compare results across multiple experiments, create customized charts, and download these charts. It provides various basic and innovative chart types to visualize functional terms and involved genes. Users can also browse the description of terms obtained from the database web servers automatically. Two examples, including a metagenome analysis data for human gut and a meta-transcriptome data for coral symbiomes, are given to show the usage of ivTerm. In the end, we compared ivTerm with existing tools with similar functions, such as GOplot, ViSEAGO, and Chordomics. The tool ivTerm is convenient and efficient for biologists to gain an integrated view and develop deep insights by interactive analysis of meta-omics data. It can accelerate the procedure to develop insights from complex meta-omics data. The code for ivTerm is freely available at https://github.com/SJTU-CGM/ivTerm.

Long noncoding RNA LINC00511 regulates the proliferation, apoptosis, invasion and autophagy of trophoblast cells to mediate pre-eclampsia progression through modulating the miR-31-5p/homeobox protein A7 axis.

AIM: Pre-eclampsia (PE) is the usual complication during pregnancy. Long noncoding RNAs are essential regulatory factors in many diseases. Nevertheless, the role of LINC00511 in the development of PE has not been fully elucidated. METHODS: The expression of LINC00511, homeobox protein A7 (HOXA7) and miR-31-5p was determined by quantitative real-time polymerase chain reaction. The levels of HOXA7 protein and autophagy-related proteins were measured by western blot analysis. Besides, cell proliferation was evaluated using cell counting kit 8 and colony formation assays. The apoptosis and invasion of cells were detected via flow cytometry and transwell assay, respectively. Further, the interaction between miR-31-5p and LINC00511 or HOXA7 was confirmed by dual-luciferase reporter assay. RESULTS: The LINC00511 and HOXA7 expression levels were decreased in placental tissues of PE patients, and the expression levels of both were positively correlated. LINC00511 knockdown suppressed proliferation, invasion and autophagy, while enhanced apoptosis in trophoblast cells. Meanwhile, the elevated HOXA7 expression promoted proliferation, invasion, autophagy, and inhibited the apoptosis of trophoblast cells. Besides, overexpression of HOXA7 also could reverse the effect of LINC00511 knockdown on the biological function of trophoblast cells. Further experiments confirmed that miR-31-5p could be sponged by LINC00511 and could target HOXA7. Also, miR-31-5p mimic could invert the promoting effect of LINC00511 overexpression on the biological function of trophoblast cells. CONCLUSION: LINC00511 expression was crucial for maintaining the normal function of trophoblast cells, and the decreased its expression might promote the progress of PE, which might provide some theoretical strategies for reducing the development of PE.

Changes in serum inflammatory factors in group B streptococcal infection and their predictive value for premature rupture of membranes complicated by chorioamnionitis.

Objective: The aim of this study as to unveil changes in serum inflammatory factors in pregnant women with genital tract group B Streptococcus (GBS) infection and their predictive value for premature rupture of membranes (PROM) complicated by chorioamnionitis (CS) and adverse pregnancy outcomes. Methods: The value of serum inflammatory factor levels in predicting PROM complicating CS and adverse pregnancy outcomes in GBS-infected pregnant women was evaluated by ELISA. Results: Serum IL-6, TNF-α, PCT and hs-CRP levels were higher in pregnant women with GBS infection. The combined diagnosis of these factors had excellent diagnostic value in PROM complicating CS and adverse pregnancy outcomes. Conclusion: Joint prediction of IL-6, TNF-α, PCT and hs-CRP has the best predictive value for PROM complicating CS and adverse pregnancy outcomes.

[Box: see text].

SIRT4 Has an Anti-Cancer Role in Cervical Cancer by Inhibiting Glutamine Metabolism via the MEK/ERK/C-Myc Axis.

BACKGROUND/AIM: Glutamine metabolism is crucial in cell proliferation, aging, and apoptosis across various cancer types. Existing research indicates that Sirtuin 4 (SIRT4), primarily located in mitochondria, modulates this process. This study aimed to clarify the regulatory relationship between SIRT4 and glutamine metabolism in cervical cancer. MATERIALS AND METHODS: SIRT4 mRNA levels and their clinical correlation to cervical cancer were analyzed using the UALCAN database. Immunohistochemistry (IHC) was performed to assess SIRT4 protein expression in tissue samples from cervical cancer patients. Transient transfection was employed to create Hela and Siha cell lines with overexpressed SIRT4, mitogen-activated extracellular signal-regulated kinase (MEK), and glutaminase 1 (GLS1). The impact on cellular functions was studied using MTT, soft agar, transwell, and western blotting assays. Glutamate and ATP levels were also measured to evaluate metabolic changes. RESULTS: Low levels of SIRT4 mRNA in cervical cancer tissues correlated with tumor metastasis and poor survival rates. Overexpression of SIRT4 led to suppressed cell proliferation, colony growth, and motility, along with significant down-regulation of GLS expression, a key contributor to glutamine metabolism. Additionally, SIRT4 overexpression resulted in the inactivation of the MEK/ERK/c-myc signaling pathway, while overexpression of MEK reversed these effects. Notably, the inhibitory effects of SIRT4 on cell proliferation, colony formation, migration, and invasion in Hela and Siha cells were significantly attenuated following GLS1 overexpression. CONCLUSION: SIRT4 acts as an anti-cancer agent in cervical cancer by inhibiting glutamine metabolism through the MEK/ERK/c-myc signaling pathway, providing a novel sight for cervical cancer therapy.

Chitosan-initiated gold nanoparticles with enhanced fluorescence for unique Fe3+/PPi sensing and photothermal therapy.

The design of surface ligands is crucial for ligand-protected gold nanoparticles (AuNPs). Herein, following the principle of green synthesis, environmentally friendly gold nanoparticles (AuNPs@His@CC, AuHC) were fabricated based on dual ligands of histidine and carboxylated chitosan. AuHC showed the advantages of low toxicity, good photoluminescent stability and ideal biocompatibility. Compared with single histidine-coated gold nanoclusters (AuNCs@His, AuH), AuHC presented enhanced fluorescence attributed to the addition of chitosan. The blue-emitting AuHC has a unique response to Fe3+ with detection limits as low as 9.51 nM. Interestingly, the quenched fluorescence of AuHC-Fe3+ system could be restored through the introduction of PPi with a detection limit of 10.6 µM. So an "on-off-on" fluorescence sensing platform was achieved. Apart from good optical properties and sensing, the designed AuHC demonstrated outstanding photothermal conversion efficiency (27.8 %), which made it ideal material for thermal ablation of tumor. To be specific, after laser irradiation (660 nm, 0.78 W cm-2, 10 min) of AuHC, the survival rate of HeLa cells as a tumor cell model decreased to 12.7 %, indicating that AuHC has a significant tumor inhibition effect in vitro. Besides, AuHC also could be a befitting candidate for overcoming drug-resistant tumor cells such as MCF-7/ADR cells. Notably, AuHC can markedly ablate solid tumors in 4T1 tumor-bearing mice after laser irradiation (660 nm, 0.78 W cm-2, 10 min). Hence this work provides insight into the design of multifunctional AuNPs platform for simultaneously integrating the ion sensing and photothermal therapy of cancer.

Dual-emission carbon dots-based biosensor for polarity/targeting bimodal recognition and mild photothermal therapy of tumor.

It is essential to develop a multifunctional nanoplatform for biosensing, tumor diagnosis and treatment simultaneously. Herein, dual-emission fluorescent carbon dots (HA-CDs) were fabricated via a one-pot solvothermal method using spinach powder as carbon source and hyaluronic acid (HA) as targeting agent. The obtained HA-CDs exhibited outstanding optical properties, good targeted tumor and excellent photothermal conversion performance. Interestingly, HA-CDs can sensitively perceive the changes in polar environments attributed to the inherent ratiometric fluorescence characteristics, and combined with the intrinsic targeting tumor ability achieved tumor cell recognition. More importantly, the HA-CDs possess good photothermal conversion efficiency of 21.2 % to be beneficial for photothermal therapy of tumors. The survival rate of HeLa cells incubated with HA-CDs dramatically decreased to 14 % after 660 nm laser irradiation, revealing the significant tumor inhibition of HA-CDs in vitro. Notably, through individual intraperitoneal and intratumoral injection, it was found that HA-CDs demonstrated a similar tumor suppressed effect on 4T1 tumor-bearing mice exposed to laser irradiation, fully uncovering that HA-CDs can efficiently accumulate at tumor site by intraperitoneal injection. Besides, the histopathological analysis of major organs ex vivo revealed a good biosafety profile. Collectively, this strategy of designed HA-CDs provides a new multifunctional nanoplatform for potential clinical application.

Complete genome sequence of the 4-hydroxybenzoate-degrading bacterium Gymnodinialimonas sp. 57CJ19, a potential novel species from intertidal sediments.

A bacterium Gymnodinialimonas sp. 57CJ19, was isolated from the intertidal sediments of Aoshan Bay, and further assays showed that it has the ability to degrade the antibacterial preservative 4-hydroxybenzoate. The complete genome sequence was sequenced, and phylogenomic analyses indicated that strain 57CJ19 represents a potential novel species in the genus Gymnodinialimonas (family Rhodobacteraceae). Its genome contains a 3,861,607-bp circular chromosome with 61.25% G + C content. Gene prediction revealed 3716 protein-encoding genes, 41 tRNA genes, 3 rrn operons, and 3 non-coding RNA genes. Functional annotation revealed a complete metabolic pathway for 4-hydroxybenzoate. The genome sequence of strain 57CJ19 provides new insights into the potential and underlying genomic basis of aromatic compound pollutant degradation by marine bacteria.

Synthesis, photoluminescence and electroluminescence properties of a new blue emitter with aggregation-induced emission and thermally activated delayed fluorescence characteristics.

The emitters with aggregation-induced emission (AIE) and thermally activated delayed fluorescence (TADF) characteristics are in high demand in organic light-emitting diodes (OLEDs) owing to their strong fluorescence and high exciton utilization under electrical excitation. Herein, a blue emitter, 10-(3-((3,5-di(9H-carbazol-9-yl)phenyl)sulfonyl)phenyl)-9,9-dimethyl-9,10-dihydroacridine (m-CZ-DPS-DMAC), was synthesized by incorporating carbazole as skeleton, acridine as electron donor, and diphenyl sulfone as electron acceptor. m-CZ-DPS-DMAC emits weak fluorescence in good solvent, while it is obviously enhanced in the aggregate state, which is typical of AIE molecules. Meanwhile, the energy levels of the singlet and triplet states (ΔEST) of the molecule is relatively small, and it also exhibits obvious temperature dependence and oxygen sensitivity, which directly proves its TADF properties. In view of the above properties, a series of non-doped and doped OLEDs were prepared using m-CZ-DPS-DMAC as light-emitting layers. Among them, non-doped OLED (device A) displays blue emission (488 nm) with the turn-on voltage (Von), the maximum luminance (Lmax), the maximum current efficiency (CEmax), the maximum power efficiency (PEmax) and the maximum external quantum efficiency (EQEmax) of 2.6 V, 3460 cd m-2, 26.09 cd A-1, 29.26 lm W-1 and 10.05%, respectively. Doped OLED (device C) constructed based on m-CZ-DPS-DMAC doped 30% in DPEPO shows the satisfactory performance with the maximum emission peak of 486 nm, the Von of 2.8 V, the Lmax of 4571 cd m-2, the CEmax of 21.37 cd A-1, the PEmax of 22.37 lm W-1, and the EQEmax of 9.44%, respectively. The outstanding performance of m-CZ-DPS-DMAC proves that it is a potential material for designing blue OLEDs with AIE-TADF properties.

Detection of Antibiotic Resistance and Analysis of Resistance Genes and Virulence Genes of Salmonella Isolated from Human.

Salmonella is a food-borne pathogen that can cause zoonoses. The emergence of drug-resistant strains of Salmonella is of great concern. It is necessary to understand the prevalence of antibiotic resistance, antibiotic resistance genes and virulence genes in human Salmonella. In this study, drug susceptibility test was used to detect and analyze the drug resistance of 24 Salmonella strains collected from human. A multi-drug resistant strain QLUF123 was selected for whole genome sequencing, and its drug resistance genes and virulence genes were analyzed. The results showed that 24 Salmonella strains were resistant to the tested antibiotics, 87.50% of the strains had multi-drug resistance, the resistance rate to ceftazidime, sulfamethoxazole and tilmicosin reached more than 80%. The alignment results based on the whole genome sequence showed that there were multiple types of drug-resistant genes in QLUF123, among which efflux pump system genes were the most abundant, including sdiA, mdtK, baeR and other multidrug-resistant efflux pump system genes. QLUF123 carried 46 kinds of virulence factors and 249 related virulence genes, among which the three functions of secretory system, adhesion and motility accounted for the most virulence genes, accounting for 93.57%. In this study, antibiotic resistance of human Salmonella was detected by drug sensitivity test, and drug resistance and virulence genes in Salmonella were analyzed by whole genome sequencing technology, which is of great significance for scientific treatment and rational drug use of related diseases caused by Salmonella infection.

Effect of polyene phosphatidylcholine/ursodeoxycholic acid/ademetionine on pregnancy outcomes in intrahepatic cholestasis.

BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) is a liver disorder that occurs in pregnant women and can lead to a range of adverse pregnancy outcomes. The condition is typically marked by pruritus (itching) and elevated levels of liver enzymes and bile acids. The standard treatment for ICP has generally been ursodeoxycholic acid and ademetionine 1,4-butanedisulfonate, but the efficacy of this approach remains less than optimal. Recently, polyene phosphatidylcholine has emerged as a promising new therapeutic agent for ICP due to its potential hepatoprotective effects. AIM: To evaluate the effect of polyene phosphatidylcholine/ursodeoxycholic acid/ ademetionine 1,4-butanedisulfonate on bile acid levels, liver enzyme indices, and pregnancy outcomes in patients with ICP. METHODS: From June 2020 to June 2021, 600 patients with ICP who were diagnosed and treated at our hospital were recruited and assigned at a ratio of 1:1 via random-number table method to receive either ursodeoxycholic acid/ademetionine 1,4-butanedisulfonate (control group, n = 300) or polyene phosphatidylcholine/ursodeoxycholic acid/ademetionine 1,4-butanedisulfonate (combined group, n = 300). Outcome measures included bile acids levels, liver enzyme indices, and pregnancy outcomes. RESULTS: Prior to treatment, no significant differences were observed between the two groups (P > 0.05). Post-treatment, patients in both groups had significantly lower pruritus scores, but the triple-drug combination group had lower scores than the dual-drug combination group (P < 0.05). The bile acid levels decreased significantly in both groups, but the decrease was more significant in the triple-drug group (P < 0.05). The triple-drug group also exhibited a greater reduction in the levels of certain liver enzymes and a lower incidence of adverse pregnancy outcomes compared to the dual-drug group (P < 0.05). CONCLUSION: Polyene phosphatidylcholine/ursodeoxycholic acid/ademetionine 1,4-butanedisulfonate effectively relieves pruritus and reduces bile acid levels and liver enzyme indices in patients with ICP, providing a positive impact on pregnancy outcome and a high safety profile. Further clinical trials are required prior to clinical application.