Enhanced Runge-Kutta-driven feature selection model for early detection of gastroesophageal reflux disease.

Gastroesophageal reflux disease (GERD) profoundly compromises the quality of life, with prolonged untreated cases posing a heightened risk of severe complications such as esophageal injury and esophageal carcinoma. The imperative for early diagnosis is paramount in averting progressive pathological developments. This study introduces a wrapper-based feature selection model based on the enhanced Runge Kutta algorithm (SCCRUN) and fuzzy k-nearest neighbors (FKNN) for GERD prediction, named bSCCRUN-FKNN-FS. Runge Kutta algorithm (RUN) is a metaheuristic algorithm designed based on the Runge-Kutta method. However, RUN's effectiveness in local search capabilities is insufficient, and it exhibits insufficient convergence accuracy. To enhance the convergence accuracy of RUN, spiraling communication and collaboration (SCC) is introduced. By facilitating information exchange among population individuals, SCC expands the solution search space, thereby improving convergence accuracy. The optimization capabilities of SCCRUN are experimentally validated through comparisons with classical and state-of-the-art algorithms on the IEEE CEC 2017 benchmark. Subsequently, based on SCCRUN, the bSCCRUN-FKNN-FS model is proposed. During the period from 2019 to 2023, a dataset comprising 179 cases of GERD, including 110 GERD patients and 69 healthy individuals, was collected from Zhejiang Provincial People's Hospital. This dataset was utilized to compare our proposed model against similar algorithms in order to evaluate its performance. Concurrently, it was determined that features such as the internal diameter of the esophageal hiatus during distention, esophagogastric junction diameter during distention, and external diameter of the esophageal hiatus during non-distention play crucial roles in influencing GERD prediction. Experimental findings demonstrate the outstanding performance of the proposed model, with a predictive accuracy reaching as high as 93.824 %. These results underscore the significant advantage of the proposed model in both identifying and predicting GERD patients.

Tobramycin-mediated self-assembly of DNA nanostructures for targeted treatment of Pseudomonas aeruginosa-infected lung inflammation.

Pseudomonas aeruginosa (PA) is one of the most common multidrug-resistant pathogens found in clinics, often manifesting as biofilms. However, due to the emergence of superbugs in hospitals and the overuse of antibiotics, the prevention and treatment of PA infections have become increasingly challenging. Utilizing DNA nanostructures for packaging and delivering antibiotics presents an intervention strategy with significant potential. Nevertheless, construction of functional DNA nanostructures with multiple functionalities and enhanced stability in physiological settings remains challenging. In this study, the authors propose a magnesium-free assembly method that utilizes tobramycin (Tob) as a mediator to assemble DNA nanostructures, allowing for the functionalization of DNA nanostructures by combining DNA and antibiotics. Additionally, our study incorporates maleimide-modified DNA into the nanostructures to act as a targeting moiety specifically directed towards the pili of PA. The targeting ability of the constructed functional DNA nanostructure significantly improves the local concentration of Tob, thereby reducing the side effects of antibiotics. Our results demonstrate the successful construction of a maleimide-decorated Tob/DNA nanotube (NTTob-Mal) for the treatment of PA-infected lung inflammation. The stability and biocompatibility of NTTob-Mal are confirmed, highlighting its potential for clinical applications. Furthermore, its specificity in recognizing and adhering to PA has been validated. In vitro experiments have shown its efficacy in inhibiting PA biofilm formation, and in a murine model, NTTob-Mal has exhibited significant therapeutic effectiveness against PA-induced pneumonia. In summary, the proposed antibiotic drug-mediated DNA nanostructure assembly approach holds promise as a novel strategy for targeted treatment of PA infections.

Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment.

Recent researches have noted many changes of short-term dynamic modalities in mild cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic functional brain networks of 82 MCI patients and 85 individuals in the normal control (NC) group were constructed using the sliding window method and Pearson correlation. The window size was determined using single-scale time-dependent (SSTD) method. Subsequently, k-means was applied to cluster all window samples, identifying three dynamic functional connectivity (DFC) states. Collective sparse symmetric non-negative matrix factorization (cssNMF) was then used to perform community detection on these states and quantify differences in brain regions. Finally, metrics such as within-community connectivity strength, community strength, and node diversity were calculated for further analysis. The results indicated high similarity between the two groups in state 2, with no significant differences in optimal community quantity and functional segregation (p < 0.05). However, for state 1 and state 3, the optimal community quantity was smaller in MCI patients compared to the NC group. In state 1, MCI patients had lower within-community connectivity strength and overall strength than the NC group, whereas state 3 showed results opposite to state 1. Brain regions with statistical difference included MFG.L, ORBinf.R, STG.R, IFGtriang.L, CUN.L, CUN.R, LING.R, SOG.L, and PCUN.R. This study on DFC states explores changes in the brain functional networks of patients with MCI from the perspective of alterations in the community structures of DFC states. The findings could provide new insights into the pathological changes in the brains of MCI patients.

A bacteriophage against Citrobacter braakii and its synergistic effect with antibiotics.

A bacteriophage BD49 specific for Citrobacter braakii was screened out and purified by double-layer plate method. It consists of a polyhedral head of 93.1 ± 1.2 nm long and 72.9 ± 4.2 nm wide, tail fibers, collar, sheath and baseplate. The bacteriophage was identified by morphology observed with transmission electron microscope (TEM), whole genome sequencing carried out by Illumina next generation sequencing (NGS) technique, and gene annotation based on Clusters of Orthologous Groups of proteins (COG) database. It was identified primarily as a member of Caudovirales by morphology and further determined as Caudovirales, Myoviridae, and Citrobacter bacteriophage by alignment of its whole genome sequence with the NCBI database and establishment of phylogenetic tree. The bacteriophage showed good environmental suitability with optimal multiplicity of infection (MOI) of 0.01, proliferation time of 80 min, optimum living temperature of 30-40 °C, and living pH of 5-10. In addition, it exhibited synergistic effect with ciprofloxacin against C. braakii in antibacterial tests.

A Bibliometric Analysis of the Trends and Evolution on Inhalation Injury Research.

Inhalation injury is a common complication in burn patients and is also a factor that can affect the multiple prognoses of burn patients. Attention to inhalation injury began early globally, but few articles have systematically analyzed its development. We employed bibliometric methods to analyze articles on inhalation injury published in 3 medical databases. A total of 3056 relevant articles on inhalation injury were included in our analysis and divided into 3 distinct periods based on Price's law. Notably, a slowdown in publication growth was observed in period III. The majority of these articles were authored by a small group of individuals, with a significant proportion of them being American scholars. In fact, nearly half of the articles were published by American researchers. Applying Bradford's Law, we identified 4 major output sources in the field, namely Burns, Journal of Burn Care & Research, Journal of Trauma, and Critical Care Medicine. Recent research has focused on the clinical risks and outcomes associated with inhalation injury, while basic research in this area has been relatively neglected over the last decade. In conclusion, the growth of publications on inhalation injuries has largely followed standard scientific growth patterns, with a small number of countries and established research groups contributing the majority of articles. However, the recent slowdown in scientific output is a cause for concern, and the lack of emphasis on basic research and clinical trials in this field raises questions about the foundation for widespread clinical management of inhalation injuries.

Self-Adaptive Perception of Object's Deformability with Multiple Deformation Attributes Utilizing Biomimetic Mechanoreceptors.

The perception of object's deformability in unstructured interactions relies on both kinesthetic and cutaneous cues to adapt the uncertainties of an object. However, the existing tactile sensors cannot provide adequate cutaneous cues to self-adaptively estimate the material softness, especially in non-standard contact scenarios where the interacting object deviates from the assumption of an elastic half-infinite body. This paper proposes an innovative design of a tactile sensor that integrates the capabilities of two slow-adapting mechanoreceptors within a soft medium, allowing self-decoupled sensing of local pressure and strain at specific locations within the contact interface. By leveraging these localized cutaneous cues, the sensor can accurately and self-adaptively measure the material softness of an object, accommodating variations in thicknesses and applied forces. Furthermore, when combined with a kinesthetic cue from the robot, the sensor can enhance tactile expression by the synergy of two relevant deformation attributes, including material softness and compliance. It is demonstrated that the biomimetic fusion of tactile information can fully comprehend the deformability of an object, hence facilitating robotic decision-making and dexterous manipulation.

Onion cryptochrome 1 (AcCRY1) regulates photomorphogenesis and photoperiod flowering in Arabidopsis and exploration of its functional mechanisms under blue light.

Cryptochromes (CRYs), as blue-light photoreceptors, play a crucial role in regulating flowering time and hypocotyl and cotyledon development. Their physiological functions have been extensively studied in various plant species. However, research on onions remains limited. In this study, we identified AcCRY1 and conducted preliminary investigations into its function. Our results demonstrate that AcCRY1 possesses a conserved domain typical of cryptochromes with high homology to those found in monocots. Furthermore, we examined the expression level of AcCRY1 in onion. The green tissues is significantly higher compared to non-green tissues, and it exhibits a significant response to blue-light induction. AcCRY1 demonstrates cytoplasmic localization under blue-light conditions, while it localizes in the nucleus during darkness, indicating a strong dependence on blue-light for its subcellular distribution. In comparison to cry1, overexpression of AcCRY1 leads to a significant shorten in seedling hypocotyl length, notable expansion of cotyledons, and acceleration of flowering time. The yeast two-hybrid experiment demonstrated the in vitro interaction between AcCRY1, AcCOP1, and AcSPA1. Additionally, BIFC analysis confirmed their interaction in Onion epidermis. Notably, under blue-light conditions, a significantly enhanced binding activity was observed compared to dark conditions. These findings establish a functional foundation for the regulatory role of AcCRY1 in important physiological processes of onion and provide initial insights into the underlying molecular mechanisms.

Fractal Spiking Neural Network Scheme for EEG-Based Emotion Recognition.

Electroencephalogram (EEG)-based emotion recognition is of great significance for aiding in clinical diagnosis, treatment, nursing and rehabilitation. Current research on this issue mainly focuses on utilizing various network architectures with different types of neurons to exploit the temporal, spectral, or spatial information from EEG for classification. However, most studies fail to take full advantage of the useful Temporal-Spectral-Spatial (TSS) information of EEG signals. In this paper, we propose a novel and effective Fractal Spike Neural Network (Fractal-SNN) scheme, which can exploit the multi-scale TSS information from EEG, for emotion recognition. Our designed Fractal-SNN block in the proposed scheme approximately simulates the biological neural connection structures based on spiking neurons and a new fractal rule, allowing for the extraction of discriminative multi-scale TSS features from the signals. Our designed training technique, inverted drop-path, can enhance the generalization ability of the Fractal-SNN scheme. Sufficient experiments on four public benchmark databases, DREAMER, DEAP, SEED-IV and MPED, under the subject-dependent protocols demonstrate the superiority of the proposed scheme over the related advanced methods. In summary, the proposed scheme provides a promising solution for EEG-based emotion recognition.

Extraction of brain function pattern with visual-capture-task fMRI using dynamic time-window method in ADHD children.

Attention deficit/Hyperactivity disorder (ADHD) has a great impact on children's development. This paper uses a novel adaptive brain state extraction algorithm to construct a dynamic time-window brain network, which captures the brain function pattern characteristics of ADHD children with higher temporal resolution. The test data were acquired by functional magnetic resonance imaging (fMRI) obtained from 23 children with ADHD during the visual-capture-task [age: (8.27 ± 2.77)]. A spatial standard deviation method is used after the initial data processing, to extract the brain activity pattern state; An improved clustering algorithm is constructed to verify the changes made to the dynamic time-window brain network model. There can be seen clear differences between each state within 0.05 s after the test. The results show that our improved new framework can effectively obtain the characteristics of dynamic brain functional connection strength changes during the task. In addition, the new algorithm is able to capture the dynamic changes of the brain network, with an 80 % improvement compared to traditional methods for the average modularity value Q. This work demonstrates a novel approach to find out the pattern changes between dynamic brain function connections, which can be of great significance for the adjuvant treatment of children with ADHD.

Enteropathogenic Escherichia coli is a predominant pathotype in healthy pigs in Hubei Province of China.

AIM: This study aims to investigate the prevalence of intestinal pathogenic Escherichia coli (InPEC) in healthy pig-related samples and evaluate the potential virulence of the InPEC strains. METHODS AND RESULTS: A multiplex PCR method was established to identify different pathotypes of InPEC. A total of 800 rectal swab samples and 296 pork samples were collected from pig farms and slaughterhouses in Hubei province, China. From these samples, a total of 21 InPEC strains were isolated, including 19 enteropathogenic E. coli (EPEC) and 2 shiga toxin-producing E. coli (STEC) strains. By whole-genome sequencing and in silico typing, it was shown that the sequence types and serotypes were diverse among the strains. Antimicrobial susceptibility assays showed that 90.48% of the strains were multi-drug resistant. The virulence of the strains was first evaluated using the Galleria mellonella larvae model, which showed that most of the strains possessed medium to high pathogenicity. A moderately virulent EPEC isolate was further selected to characterize its pathogenicity using a mouse model, which suggested that it could cause significant diarrhea. Bioluminescence imaging (BLI) was then used to investigate the colonization dynamics of this EPEC isolate, which showed that the EPEC strain could colonize the mouse cecum for up to 5 days.

Heterogeneity and transmission of food safety-related enterotoxigenic Staphylococcus aureus in pig abattoirs in Hubei, China.

The dissemination of Staphylococcus aureus in the pork production chain is a major food safety concern. Abattoirs can serve both as disruptor and transmitter for S. aureus. In this study, we conducted a systematic genomic epidemiology research on the prevalence, heterogeneity, and transmission of S. aureus in 3,638 samples collected from four pig abattoirs in Hubei province, China. Our findings revealed substantial heterogeneity between S. aureus recovered from samples collected at upstream (from stunning step to head-removal step) and downstream (from splitting step to chilling step) locations within the slaughter process. Overall, 966 (26.6%) samples were positive for S. aureus, with significantly higher overall prevalence for upstream samples (29.0%, 488/1,681) compared to downstream samples (24.4%, 478/1,957). Antimicrobial susceptibility testing demonstrated that the isolates from the upstream exhibited significantly higher resistance proportions to different antimicrobials than those from the downstream. Whole-genome sequencing of 126 isolates revealed that ST398 (32.9%, 23/70) and ST9 (22.9%, 16/70) were more common among upstream isolates, while ST7 (35.7%, 20/56) and ST97 (28.6%, 16/56) were most frequently observed among downstream isolates. Additionally, molecular characterization analysis demonstrated that upstream isolates possessed significantly higher enterotoxigenic potential, more antimicrobial resistance genes, and S. aureus pathogenicity islands than downstream isolates. Notably, we discovered that enterotoxigenic S. aureus could be transmitted across different slaughter stages, with knives, water, and air serving as vectors. Although slaughtering processes had a substantial effect on reducing the food safety risk posed by enterotoxigenic S. aureus, the possibility of its widespread transmission should not be disregarded. IMPORTANCE Staphylococcus aureus (S. aureus) is one of the most important foodborne pathogens, and can cause foodborne poisoning by producing enterotoxins. Pork is a preferable reservoir and its contamination often occurs during the slaughter process. Our findings revealed significant differences in the prevalence, antimicrobial resistance, and enterotoxigenic potential between the upstream and downstream isolates within the slaughter process. Also, it is imperative not to overlook enterotoxigenic S. aureus transmitted across all stages of the slaughter process, with notable vectors being knives, water, and air. These findings hold significant implications for policy-makers to reassess their surveillance projects, and underscore the importance of implementing effective control measures to minimize the risk of S. aureus contamination in pork production. Moreover, we provide a more compelling method of characterizing pathogen transmission based on core-SNPs of bacterial genomes.

Road Narrow-Inspired Strain Concentration to Wide-Range-Tunable Gauge Factor of Ionic Hydrogel Strain Sensor.

The application of stretchable strain sensors in human movement recognition, health monitoring, and soft robotics has attracted wide attention. Compared with traditional electronic conductors, stretchable ionic hydrogels are more attractive to organization-like soft electronic devices yet suffer poor sensitivity due to limited ion conduction modulation caused by their intrinsic soft chain network. This paper proposes a strategy to modulate ion transport behavior by geometry-induced strain concentration to adjust and improve the sensitivity of ionic hydrogel-based strain sensors (IHSS). Inspired by the phenomenon of vehicles slowing down and changing lanes when the road narrows, the strain redistribution of ionic hydrogel is optimized by structural and mechanical parameters to produce a strain-induced resistance boost. As a result, the gauge factor of the IHSS is continuously tunable from 1.31 to 9.21 in the strain range of 0-100%, which breaks through the theoretical limit of homogeneous strain-distributed ionic hydrogels and ensures a linear electromechanical response simultaneously. Overall, this study offers a universal route to modulate the ion transport behavior of ionic hydrogels mechanically, resulting in a tunable sensitivity for IHSS to better serve different application scenarios, such as health monitoring and human-machine interface.

Gut Microbiota and Respiratory Infections: Insights from Mendelian Randomization.

The role of the gut microbiota in modulating the risk of respiratory infections has garnered increasing attention. However, conventional clinical trials have faced challenges in establishing the precise relationship between the two. In this study, we conducted a Mendelian randomization analysis with single nucleotide polymorphisms employed as instrumental variables to assess the causal links between the gut microbiota and respiratory infections. Two categories of bacteria, family Lactobacillaceae and genus Family XIII AD3011, were causally associated with the occurrence of upper respiratory tract infections (URTIs). Four categories of gut microbiota existed that were causally associated with lower respiratory tract infections (LRTIs), with order Bacillales and genus Paraprevotella showing a positive association and genus Alistipes and genus Ruminococcaceae UCG009 showing a negative association. The metabolites and metabolic pathways only played a role in the development of LRTIs, with the metabolite deoxycholine acting negatively and menaquinol 8 biosynthesis acting positively. The identification of specific bacterial populations, metabolites, and pathways may provide new clues for mechanism research concerning therapeutic interventions for respiratory infections. Future research should focus on elucidating the potential mechanisms regulating the gut microbiota and developing effective strategies to reduce the incidence of respiratory infections. These findings have the potential to significantly improve global respiratory health.

Multifunctional high-simulation 3D-printed hydrogel model manufacturing engineering for surgical training.

Advanced bionic organ models with vivid biological structures and wetness and softness are essential for medical-surgical training. Still, there are many challenges in the preparation process, such as matching mechanical properties, good feedback on surgical instruments, reproducibility of specific surgical scenarios, and distinguishability between structural levels. In this paper, we achieved tissuemimicking dual-network (DN) hydrogels with customizable stiffness by adjusting the composition of the hydrogel matrix and the immersion time of the ionic solution to match different biological soft tissues precisely. Combined with advanced threedimensional (3D) printing fabrication techniques, various performance-tunable bionic hydrogel organ models with structural complexity and fidelity, including kidney, liver, pancreas, and vascular tissues, were perfectly fabricated. The simulation and applicability of the model were also simulated for the forced change of the suture needle in the puncture and suture of a single tissue and between different tissues, the cutting of substantive organs by ultrasonic scalpel, the coagulation and hemostasis of blood vessels, the visualization of the internal structure under ultrasound, and the microwave ablation of liver tumors. By constructing advanced biomimetic organ models based on hydrogel with specific and tunable properties, the development of surgical training, medical device testing, and medical education reform will be significantly promoted.

A solvent-responsive terbium-organic framework for photocatalytic CO2 reduction.

A Tb-MOF with a 5,5,6-c 3-nodal net, {[Tb(DTDA)1.5·2H2O]·DMF·8H2O}n (AQNU-4), has been synthesized (DTDA = 2',5'-diethoxy-[1,1':4',1''-terphenyl]-4,4''-dicarboxylic acid). AQNU-4 contains a 1-periodic secondary building unit (rod SBU) and has an unusual topological type with the point symbol {32·44·62·7·8}{32·46·5·6}{32·46·52·65}. Efficient light harvesting and electron-hole separation make AQNU-4 an effective photocatalyst for use in the CO2 reduction reaction (CO2RR). Interestingly, as a photocatalyst, AQNU-4 shows an obvious solvent dependence during the catalytic process. In cyclohexanone in particular, it shows the highest CO2 to CO conversion, reaching 138.65 µmol g-1 h-1, making AQNU-4 a good solvent-responsive MOF material.

Preparation of heterojunction C3N4/WO3 photocatalyst for degradation of microplastics in water.

In this study, a WO3/g-C3N4 composite photocatalyst was synthesized via a hydrothermal method and characterized for its potential application in photocatalytic H2 generation from PET degradation. XRD analysis revealed that the hexagonal WO3 crystal structure was achieved after 10 h of hydrothermal time, with particles of suitable size for uniform loading on the g-C3N4 surface. SEM images showed the successful loading of WO3 nanorods onto the g-C3N4 surface, significantly increasing the specific surface area. FTIR and UV-vis diffuse reflectance spectroscopy confirmed the formation of a Z-type heterojunction between WO3 and g-C3N4. Photoluminescence measurements indicated a reduced rate of electron-hole pair recombination in the composite. The 30% WO3/g-C3N4 composite demonstrated a high H2 evolution rate of 14.21 mM and excellent stability in PET solution under visible light irradiation. 1H NMR and EPR spectroscopy analyses revealed the degradation of PET into small molecular compounds and the generation of active radicals, including ·O2-, during the reaction. Overall, the WO3/g-C3N4 composite exhibited promising potential for photocatalytic H2 production and PET degradation.

Influence-Driven Data Poisoning for Robust Recommender Systems.

Recent studies have shown that recommender systems are vulnerable, and it is easy for attackers to inject well-designed malicious profiles into the system, resulting in biased recommendations. We cannot deprive these data's injection right and deny their existence's rationality, making it imperative to study recommendation robustness. Despite impressive emerging work, threat assessment of the bi-level poisoning problem and the imperceptibility of poisoning users remain key challenges to be solved. To this end, we propose Infmix, an efficient poisoning attack strategy. Specifically, Infmix consists of an influence-based threat estimator and a user generator, Usermix. First, the influence-based estimator can efficiently evaluate the user's harm to the recommender system without retraining, which is challenging for existing attacks. Second, Usermix, a distribution-agnostic generator, can generate unnoticeable fake data even with a few known users. Under the guidance of the threat estimator, Infmix can select the users with large attacking impacts from the quasi-real candidates generated by Usermix. Extensive experiments demonstrate Infmix's superiority by attacking six recommendation systems with four real datasets. Additionally, we propose a novel defense strategy, adversarial poisoning training (APT). It mimics the poisoning process by injecting fake users (ERM users) committed to minimizing empirical risk to build a robust system. Similar to Infmix, we also utilize the influence function to solve the bi-level optimization challenge of generating ERM users. Although the idea of "fighting fire with fire" in APT seems counterintuitive, we prove its effectiveness in improving recommendation robustness through theoretical analysis and empirical experiments.

Screening quality markers (Q-markers) of Xiaoer Chaige Tuire Oral Liquid by in vitro sequential metabolism and in vivo biopharmaceutical analysis.

BACKGROUND: Xiaoer Chaige Tuire Oral Liquid (XCT) is a preparation composed of 7 traditional Chinese medicines including Bupleuri Radix, Puerariae Lobatae Radix, Scutellariae Radix, Gypsum Fibrosum, Artemisiae Annuae Herba, Paeoniae Radix Alba and Glycyrrhizae Radix Et Rhizoma Praeparata Cum Melle in proportion. According to traditional Chinese medicine theory, it has the function of dispelling wind evil and relieving exterior syndrome, clearing summer heat and dampness, and reducing internal heat. So, it is indicated for pediatric upper respiratory tract infection caused by exogenous wind-heat. Modern pharmacological studies have indicated that XCT has a variety of activities such as anti-inflammation and antivirus. PURPOSE: To screen potential quality markers (Q-markers) of XCT by tracking in vivo bioactive compounds concomitantly using in vitro sequential metabolism and in vivo biopharmaceutical analysis. METHODS: In vitro metabolic models including artificial gastric juice, intestinal juice, intestinal microbiota, Caco-2 cell monolayer and liver S9 were employed to simulate metabolism of main compounds of XCT in the body. High performance liquid chromatography with diode-array detection (HPLC-DAD) was used to quantitatively determine main components of XCT preparation and its sequential metabolism samples. Ultra performance liquid chromatography with QExactive Orbitrap tandem mass spectrometry (UPLC-QExactive-HF-x-Orbitrap-MS) was used to qualitatively determine in vivo components of XCT preparation in rat plasma and metabolites obtained with liver S9 fraction of rats. RESULTS: Twenty-five compounds were identified from the preparation of XCT. Sequential in vitro metabolism studies indicated that most of these compounds except baicalin and baicalein were stable in artificial gastric juice, albiflorin, glycyrrhizic acid, gallic acid and baicalein were unstable in artificial intestinal juice, daidzin, liquiritin and genistin were hydrolyzed into their aglycones daidzein, liquiritigenin and genistein by intestinal microbiota, and 7 compounds thereout including benzoic acid, puerarin, 3'-methoxypuerarin, paeoniflorin, scopoletin, daidzein and liquiritigenin were shown to be well absorbed with Caco-2 cell monolayer model. These 7 compounds were demonstrated to be metabolized via hydroxylation and glycosylation by liver S9 system. Ten components of XCT preparation including puerarin, baicalin, wogonoside, benzoic acid, daidzein, baicalein, wogonin, oroxylin A, isoscopoletin and isoliquiritigenin were identified from rat plasma by in vivo biopharmaceutical analysis. Most of the compounds screened with both in vitro and in vivo metabolic studies were shown to be active against inflammation and influenza virus. CONCLUSIONS: A screening strategy for potential quality markers (Q-markers) of XCT preparation based on tracking in vivo bioactive compounds using the combination of in vitro sequential metabolism and in vivo biopharmaceutical analysis was established. With this strategy, a total of 12 compounds including puerarin, daidzein, benzoic acid, baicalin, baicalein, wogonoside, wogonin, oroxylin A, 3'-methoxypuerarin, paeoniflorin, scopoletin and liquiritigenin were screened to be potential Q-markers of XCT, which provides a material basis for quality control and development of XCT.

Percutaneous Structural Interventions in Adult Congenital Heart Disease: State-of-the-Art Review.

Structural interventions play a crucial role in the management of adult congenital heart disease (ACHD). In recent years, this field has seen significant advancements in catheter-based procedures despite limited investment from industry and lack of device development specific to this population. Because each patient is unique in their anatomy, pathophysiology, and surgical repair, many devices are used off-label with a "best fit" strategy. Therefore, continuous innovation is needed to adapt what is available to ACHD and to increase collaboration with industry and regulatory bodies to develop dedicated equipment. These innovations will further advance the field and offer this growing population less invasive options with fewer complications and faster recovery times. In this article, we summarize some of the contemporary structural interventions performed in adults with congenital defects and present cases performed at Houston Methodist to better illustrate them. We aim to offer a greater understanding of the field and stimulate interest in this rapidly growing specialty.

Cotransfer of resistance to cephalosporins, colistin, and fosfomycin mediated by an IncHI2/pSH16G4928-like plasmid in ESBL-producing monophasic Salmonella Typhimurium strains of pig origin.

AIMS: To assess the co-transmission risk of phenotypic and genetic resistance to cephalosporins, colistin, and fosfomycin in Salmonella strains collected along the whole pork production chain. METHODS AND RESULTS: From a total of 107 Salmonella isolates from samples collected in pig slaughterhouses and markets, 15 ESBL-producing Salmonella strains resistant to cefotaxime were identified by broth microdilution method and clavulanic acid inhibition test, including 14 monophasic Salmonella Typhimurium strains and one Salmonella Derby strain. Whole genome sequence analysis showed that nine monophasic S. Typhimurium strains coresistant to colistin and fosfomycin carried the resistance genes blaCTX-M-14, mcr-1, and fosA3. Conjugational transfer tests demonstrated that the phenotypic and genetic resistance to cephalosporins, colistin, and fosfomycin could cotransfer back and forth between Salmonella and Escherichia coli via an IncHI2/pSH16G4928-like plasmid. CONCLUSIONS: This study reports the cotransmission of phenotypic and genetic resistance to cephalosporins, colistin, and fosfomycin via an IncHI2/pSH16G4928-like plasmid in Salmonella strains of animal origin, giving an alarm for the prevention of the development and spread of bacterial multidrug resistance.