Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables.

OBJECTIVE: Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario. METHODS: In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People's Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People's Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction. RESULTS: The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively. CONCLUSION: The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Development of a detection chip for major pathogenic drug-resistant genes and drug targets in bovine respiratory system diseases.

Bovine respiratory disease (BRD) is a significant veterinary challenge, often exacerbated by pathogen resistance, hindering effective treatment. Traditional testing methods for primary pathogens - Mycoplasma bovis, Pasteurella multocida, and Mannheimia haemolytica - are notably time-consuming and lack the rapidity required for effective clinical decision-making. This study introduces a TaqMan MGB probe detection chip, utilizing fluorescent quantitative PCR, targeting key BRD pathogens and associated drug-resistant genes and sites. We developed 94 specific probes and primers, embedded into a detection chip, demonstrating notable specificity, repeatability, and sensitivity, reducing testing time to under 1 h. Additionally, we formulated probes to detect mutations in the quinolone resistance-determining region, associated with fluoroquinolone resistance in BRD pathogens. The chip exhibited robust sensitivity and specificity, enabling rapid detection of drug-resistant mutations in clinical samples. This methodology significantly expedites the diagnostic process for BRD and sensitive drug screening, presenting a practical advancement in the field.

The Long-Acting Serine Protease Inhibitor mPEG-SPA-MDSPI16 Alleviates LPS-Induced Acute Lung Injury.

Anti-inflammatory drugs have become the second-largest class of common drugs after anti-infective drugs in animal clinical care worldwide and are often combined with other drugs to treat fever and viral diseases caused by various factors. In our previous study, a novel serine protease inhibitor-encoding gene (MDSPI16) with improved anti-inflammatory activity was selected from a constructed suppressive subducted hybridization library of housefly larvae. This protein could easily induce an immune response in animals and had a short half-life, which limited its wide application in the clinic. Thus, in this study, mPEG-succinimidyl propionate (mPEG-SPA, Mw = 5 kDa) was used to molecularly modify the MDSPI16 protein, and the modified product mPEG-SPA-MDSPI16, which strongly inhibited elastase production, was purified. It had good stability and safety, low immunogenicity, and a long half-life, and the IC50 for elastase was 86 nM. mPEG-SPA-MDSPI16 effectively inhibited the expression of neutrophil elastase and decreased ROS levels. Moreover, mPEG-SPA-MDSPI16 exerted anti-inflammatory effects by inhibiting activation of the NF-κB signaling pathway and the MAPK signaling pathway in neutrophils. It also exerted therapeutic effects on a lipopolysaccharide (LPS)-induced acute lung injury (ALI) mouse model. In summary, mPEG-SPA-MDSPI16 is a novel anti-inflammatory protein modified with PEG that has the advantages of safety, nontoxicity, improved stability, and strong anti-inflammatory activity in vivo and in vitro and is expected to become an effective anti-inflammatory drug.

Weissella cibaria Relieves Gut Inflammation Caused by Escherichia coli through Inflammation Modulation and Gut Microbiota Regulation.

The emergence of multi-drug-resistant (MDR) pathogens has considerably challenged the development of new drugs. Probiotics that inhibit MDR pathogens offer advantages over chemical antibiotics and drugs due to their increased safety and fewer side effects. This study reported that Weissella cibaria P-8 isolated from pickles showed excellent antibacterial activity against intestinal pathogens, particularly the antibacterial activity against MDR Escherichia coli B2 was the highest. This study showed that the survival rates of W. cibaria P-8 at pH 2.0 and 0.3% bile salt concentration were 72% and 71.56%, respectively, and it still had antibacterial activity under pepsin, trypsin, protease K, and catalase hydrolysis. Moreover, W. cibaria P-8 inhibits the expression of inflammatory factors interleukin-1ß, tumor necrosis factor-α, and interleukin-6, upregulates the interleukin-10 level, and increases total antioxidant capacity and superoxide dismutase enzyme activity in serum. W. cibaria P-8 also efficiently repairs intestinal damage caused by E. coli infection. The gut microbiota analysis demonstrated that W. cibaria P-8 colonizes the intestine and increases the abundance of some beneficial intestinal microorganisms, particularly Prevotella. In conclusion, W. cibaria P-8 alleviated MDR E. coli-induced intestinal inflammation by regulating inflammatory cytokine and enzyme activity and rebalancing the gut microbiota, which could provide the foundation for subsequent clinical analyses and probiotic product development.

Precise detection of awareness in disorders of consciousness using deep learning framework.

Diagnosis of disorders of consciousness (DOC) remains a formidable challenge. Deep learning methods have been widely applied in general neurological and psychiatry disorders, while limited in DOC domain. Considering the successful use of resting-state functional MRI (rs-fMRI) for evaluating patients with DOC, this study seeks to explore the conjunction of deep learning techniques and rs-fMRI in precisely detecting awareness in DOC. We initiated our research with a benchmark dataset comprising 140 participants, including 76 unresponsive wakefulness syndrome (UWS), 25 minimally conscious state (MCS), and 39 Controls, from three independent sites. We developed a cascade 3D EfficientNet-B3-based deep learning framework tailored for discriminating MCS from UWS patients, referred to as "DeepDOC", and compared its performance against five state-of-the-art machine learning models. We also included an independent dataset consists of 11 DOC patients to test whether our model could identify patients with cognitive motor dissociation (CMD), in which DOC patients were behaviorally diagnosed unconscious but could be detected conscious by brain computer interface (BCI) method. Our results demonstrate that DeepDOC outperforms the five machine learning models, achieving an area under curve (AUC) value of 0.927 and accuracy of 0.861 for distinguishing MCS from UWS patients. More importantly, DeepDOC excels in CMD identification, achieving an AUC of 1 and accuracy of 0.909. Using gradient-weighted class activation mapping algorithm, we found that the posterior cortex, encompassing the visual cortex, posterior middle temporal gyrus, posterior cingulate cortex, precuneus, and cerebellum, as making a more substantial contribution to classification compared to other brain regions. This research offers a convenient and accurate method for detecting covert awareness in patients with MCS and CMD using rs-fMRI data.

Prognostic Value of Segmental Strain After ST-Elevation Myocardial Infarction: Insights From the EARLY Assessment of MYOcardial Tissue Characteristics by Cardiac Magnetic Resonance (EARLY-MYO-CMR) Study.

BACKGROUND: The prognostic value of left ventricular segmental strain (SS) in ST-elevation myocardial infarction (STEMI) remains unclear. HYPOTHESIS: To assess the prognostic value and application of SS. STUDY TYPE: Retrospective analysis of a prospective registry. POPULATION: Five hundred and forty-four patients after STEMI (500 in Cohort 1, 44 in Cohort 2). FIELD STRENGTH/SEQUENCE: 3 T, balanced steady-state free precession, gradient echo, and gradient echo contrast-enhanced images. ASSESSMENT: Participants underwent cardiac MR during the acute phase after STEMI. Infarct-related artery (IRA) strain was determined based on SS obtained from cine images. The primary endpoint was the composite of major adverse cardiovascular events (MACEs) after 8 years of follow-up. In Cohort 2, SS stability was assessed by MR twice within 8 days. Contrast and non-contrast risk models based on SS were established, leading to the development of an algorithm. STATISTICAL TEST: Student's t-test, Mann-Whitney U-test, Cox and logistic regression, Kaplan-Meier analysis, net reclassification index (NRI). P < 0.05 was considered significant. RESULTS: During a median follow-up of 5.2 years, 83 patients from Cohort 1 experienced a MACE. Among SS, IRA peak circumferential strain (IRA-CS) was an independent factor for MACEs (adjusted hazard ratio 1.099), providing incremental prognostic value (NRI 0.180, P = 0.10). Patients with worse IRA-CS (>-8.64%) demonstrated a heightened susceptibility to MACE. Additionally, IRA-CS was significantly associated with microvascular obstruction (MVO) (adjusted odds ratio 1.084) and infarct size (r = 0.395). IRA-CS showed comparable prognostic effectiveness to global peak circumferential strain (NRI 0.100, P = 0.39), also counterbalancing contrast and non-contrast risk models (NRI 0.205, P = 0.05). In Cohort 2, IRA-CS demonstrated stability between two time points (P = 0.10). Based on risk models incorporating IRA-CS, algorithm "HJKL" was preliminarily proposed for stratification. DATA CONCLUSIONS: IRA-CS is an important prognostic factor, and an algorithm based on it is proposed for stratification. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Drought stress reduces the photosynthetic source of subtending leaves and the transit sink function of podshells, leading to reduced seed weight in soybean plants.

Drought stress is the key factor limiting soybean yield potential. Soybean seed formation involves a coordinated "subtending leaf-podshell-seed" process, but little is known about the assimilation and transport of photoassimilates in subtending leaves, podshells and seeds or their relationships with soybean seed formation under drought stress. To address these research gaps, two-year experiments with two soybean cultivars, Wandou 37 (drought tolerant) and Zhonghuang 13 (drought sensitive), were conducted under three soil water content (SWC) conditions in 2020 and 2021 based on the responses of their yield to drought. We analyzed the photosynthetic assimilation and translocation of photoassimilates in subtending leaves, podshells and seeds by stable isotope labeling. Compared with those under 75% SWC, 60% SWC and 45% SWC significantly decreased the Wandou 37 seed weight by 19.4% and 37.5%, respectively, and that of Zhonghuang 13 by 26.9% and 48.6%, respectively. Compared with those under 75% SWC, drought stress decreased the net photosynthetic rate and the activities of sucrose phosphate synthase (SPS) and sucrose synthase (SuSy), which in turn decreased the photosynthetic capacity of the subtending leaves. The podshells ensure the input of photoassimilates by increasing the SuSy activity, but the weakened source-sink relationship between podshells and seeds under drought stress leads to a decrease in the translocation of assimilates from podshells to seeds. The lack of assimilates under drought stress is an important factor restricting the development of soybean seeds. We conclude that the decrease in seed weight was caused by the decrease in the photosynthetic capacity of the subtending leaves and the decrease in the overall availability of photoassimilates; moreover, by a decrease in the translocation of assimilates from podshells to seeds.

RecA inhibitor epicatechin prolongs the development of fluoroquinolone resistance in Pasteurella multocida.

Pasteurella multocida (P. multocida), a primary pathogen of bovine respiratory diseases, has become resistant to many antibiotics, including fluoroquinolones and aminoglycosides. A large number of studies have proved that SOS reaction plays a crucial role in the development of antibiotic resistance. We have shown that the deletion of SOS response-related genes (recA, recO) can delay the development of fluoroquinolone resistance in P. multocida, therefore, it can be used as potential targets for antibiotic resistance inhibitors. In this study, we have used molecular docking to screen RecA protein inhibitors with high throughput screening, and found that epicatechin as an inhibitor significantly inhibited the formation of fluoroquinolone resistance in P. multocida, while in vitro coadministration of epicatechin with and without ciprofloxacin improved the efficacy of the antimicrobial agent. In conclusion, our results indicate that epicatechin is an efficient RecA inhibitor, implying that combining it with ciprofloxacin is a highly promising method for treating P. multocida resistant to fluoroquinolones.

MR Uniformity Ratio Estimates to Evaluate Ventricular Mechanical Dyssynchrony and Prognosis After ST-Segment Elevation Myocardial Infarction.

BACKGROUND: The impact of left ventricular mechanical dyssynchrony (LVMD) on the long-term prognosis of ST-segment elevation myocardial infarction (STEMI) is unclear. HYPOTHESIS: MR uniformity ratio estimates (URE) can detect LVMD and assess STEMI prognosis. STUDY TYPE: Retrospective analysis of a prospective multicenter registry (EARLY-MYO trial, NCT03768453). POPULATION: Overall, 450 patients (50 females) with first-time STEMI were analyzed, as well as 40 participants without cardiovascular disease as controls. FIELD STRENGTH/SEQUENCE: 3.0-T, balanced steady-state free precession cine and late gadolinium enhancement imaging. ASSESSMENT: MRI data were acquired within 1 week of symptom onset. Major adverse cardiovascular events (MACEs), including cardiovascular death, nonfatal re-infarction, hospitalization for heart failure, and stroke, were the primary clinical outcomes. LVMD was represented by circumferential URE (CURE) and radial URE (RURE) calculated using strain measurements. The patients were grouped according to clinical outcomes or URE values. Patients' clinical characteristics and MR indicators were compared. STATISTICAL TESTS: The Student's t-test, Mann-Whitney U test, chi-square test, Fisher's exact test, receiver operating characteristic curve analysis with area under the curve, Kaplan-Meier analysis, Cox regression, logistic regression, intraclass correlation coefficient, c-index, and integrated discrimination improvement were used. P < 0.05 was considered statistically significant. RESULTS: CURE and RURE were significantly lower in patients with STEMI than in controls. The median follow-up was 60.5 months. Patients with both lower CURE and RURE values experienced a significantly higher incidence of MACEs by 3.525-fold. Both CURE and RURE were independent risk factors for MACEs. The addition of UREs improved diagnostic efficacy and risk stratification based on infarct size and left ventricular ejection fraction (LVEF). The indicators associated with LVMD included male sex, serum biomarkers (peak creatine phosphokinase and cardiac troponin I), infarct size, and LVEF. DATA CONCLUSION: CURE and RURE may be useful to evaluate long-term prognosis after STEMI. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

A cardiologist-like computer-aided interpretation framework to improve arrhythmia diagnosis from imbalanced training datasets.

Arrhythmias can pose a significant threat to cardiac health, potentially leading to serious consequences such as stroke, heart failure, cardiac arrest, shock, and sudden death. In computer-aided electrocardiogram interpretation systems, the inclusion of certain classes of arrhythmias, which we term "aggressive" or "bullying," can lead to the underdiagnosis of other "vulnerable" classes. To address this issue, a method for arrhythmia diagnosis is proposed in this study. This method combines morphological-characteristic-based waveform clustering with Bayesian theory, drawing inspiration from the diagnostic reasoning of experienced cardiologists. The proposed method achieved optimal performance in macro-recall and macro-precision through hyperparameter optimization, including spliced heartbeats and clusters. In addition, with increasing bullying by aggressive arrhythmias, our model obtained the highest average recall and the lowest average drop in recall on the nine vulnerable arrhythmias. Furthermore, the maximum cluster characteristics were found to be consistent with established arrhythmia diagnostic criteria, lending interpretability to the proposed method.

Peak early diastolic strain rate improves prediction of adverse cardiovascular outcomes in patients with ST-elevation myocardial infarction.

BACKGROUND: The prognostic role of diastolic dysfunction measured by the circumferential peak early diastolic strain rate (PEDSR) on ST-elevation myocardial infarction (STEMI) is not completely established. OBJECTIVES: We aimed to investigate the prognostic value of diastolic function by measuring PEDSR within 1 week after STEMI. METHODS: The cardiac magnetic resonance (CMR) pictures of 420 subjects from a clinical registry study (NCT03768453) were analyzed and the composite major adverse cardiac events (MACEs) were followed up. RESULTS: The PEDSR of patients was significantly lower compared with that of control subjects (P < 0.001). Within the median follow-up period of 52 months, PEDSR of patients who experienced MACEs deceased more significantly than that of patients without MACEs (P < 0.001). After adjusting with clinical or CMR indexes, per 0.1/s reduction of PEDSR increased the risks of MACEs to 1.402 or 1.376 fold and the risk of left ventricular (LV) remodeling to 1.503 or 1.369 fold. When PEDSR divided by best cutoff point, significantly higher risk of MACEs (P < 0.001) and more remarkable LV remodeling (P < 0.001) occurred in patients with PEDSR ≤ 0.485/s. Moreover, when adding the PEDSR to the conventional prognostic factors such as LV ejection fraction and infarction size, better prognostic risk classification models were created. Finally, aging, tobacco use, remarkable LV remodeling, and a low LV ejection fraction were factors related with the reduction of PEDSR. CONCLUSIONS: Diastolic dysfunction has an important prognostic effect on patients with STEMI. Measurement of the PEDSR in the acute phase could serve as an effective index to predict the long-term risk of MACEs and cardiac remodeling.

MRI-based brain age prediction model for children under 3 years old using deep residual network.

Early identification and intervention of abnormal brain development individual subjects are of great significance, especially during the earliest and most active stage of brain development in children aged under 3. Neuroimage-based brain's biological age has been associated with health, ability, and remaining life. However, the existing brain age prediction models based on neuroimage are predominantly adult-oriented. Here, we collected 658 T1-weighted MRI scans from 0 to 3 years old healthy controls and developed an accurate brain age prediction model for young children using deep learning techniques with high accuracy in capturing age-related changes. The performance of the deep learning-based model is comparable to that of the SVR-based model, showcasing remarkable precision and yielding a noteworthy correlation of 91% between the predicted brain age and the chronological age. Our results demonstrate the accuracy of convolutional neural network (CNN) brain-predicted age using raw T1-weighted MRI data with minimum preprocessing necessary. We also applied our model to children with low birth weight, premature delivery history, autism, and ADHD, and discovered that the brain age was delayed in children with extremely low birth weight (less than 1000 g) while ADHD may cause accelerated aging of the brain. Our child-specific brain age prediction model can be a valuable quantitative tool to detect abnormal brain development and can be helpful in the early identification and intervention of age-related brain disorders.

Genetic characterization of MDR genomic elements carrying two aac(6')-aph(2″) genes in feline-derived clinical Enterococcus faecalis isolate.

Multidrug-resistant Enterococcus faecalis (E. faecalis) often cause intestinal infections in cats. The aim of this study was to investigate a multidrug-resistant E. faecalis isolate for plasmidic and chromosomal antimicrobial resistance and their genetic environment. E. faecalis strain ESC1 was obtained from the feces of a cat. Antimicrobial susceptibility testing was carried out using the broth microdilution method. Conjugation experiments were performed using Escherichia coli and Staphylococcus aureus as receptors. Complete sequences of chromosomal DNA and plasmids were generated by whole genome sequencing (WGS) and bioinformatics analysis for the presence of drug resistance genes and mobile elements. Multidrug-resistant E. faecalis ESC1 contained a chromosome and three plasmids. The amino acid at position 80 of the parC gene on the chromosome was mutated from serine to isoleucine, and hence the amino acid mutation at this site led to the resistance of ESC1 strain to fluoroquinolones. Eleven antibiotic resistance genes were located on two plasmids. We identified a novel composite transposon carrying two aminoglycoside resistance genes aac(6')-aph(2″). This study reported the coexistence of a novel 5.4 kb composite transposon and a resistance plasmid with multiple homologous recombination in an isolate of E. faecalis ESC1. This data provides a basis for understanding the genomic signature and antimicrobial resistance mechanisms of this pathogen.

Famotidine Enhances Rifampicin Activity against Acinetobacter baumannii by Affecting OmpA.

The development of novel antibiotic adjuvants is imminent because of the frequent emergence of resistance in Gram-negative bacteria, which severely restricts the efficiency and longevity of commonly used clinical antibiotics. It is reported that famotidine, a clinical inhibitor of gastric acid secretion, enhances the antibacterial activity of rifamycin antibiotics, especially rifampicin, against Gram-negative bacteria and reverses drug resistance. Studies have shown that famotidine disrupts the cell membrane of Acinetobacter baumannii and inhibits the expression of the outer membrane protein ompA gene, while causing a dissipation of the plasma membrane potential, compensatively upregulating the pH gradient and ultimately increasing the accumulation of reactive oxygen species by leading to increased bacterial mortality. In addition, famotidine also inhibited the efflux pump activity and the biofilm formation of A. baumannii. In the Galleria mellonella and mouse infection models, the combination of famotidine and rifampicin increased the survival rate of infected animals and decreased the bacterial load in mouse organs. In conclusion, famotidine has the potential to be a novel rifampicin adjuvant, providing a new option for the treatment of clinical Gram-negative bacterial infections. IMPORTANCE In this study, famotidine was discovered for the first time to have potential as an antibiotic adjuvant, enhancing the antibacterial activity of rifamycin antibiotics against A. baumannii and overcoming the limitations of drug therapy. With the discovery of novel applications for the guanidine-containing medication famotidine, the viability of screening prospective antibiotic adjuvants from guanidine-based molecules was further explored. In addition, famotidine exerts activity by affecting the OmpA protein of the cell membrane, indicating that this protein might be used as a therapeutic drug target to treat A. baumannii infections.

Citric Acid Confers Broad Antibiotic Tolerance through Alteration of Bacterial Metabolism and Oxidative Stress.

Antibiotic tolerance has become an increasingly serious crisis that has seriously threatened global public health. However, little is known about the exogenous factors that can trigger the development of antibiotic tolerance, both in vivo and in vitro. Herein, we found that the addition of citric acid, which is used in many fields, obviously weakened the bactericidal activity of antibiotics against various bacterial pathogens. This mechanistic study shows that citric acid activated the glyoxylate cycle by inhibiting ATP production in bacteria, reduced cell respiration levels, and inhibited the bacterial tricarboxylic acid cycle (TCA cycle). In addition, citric acid reduced the oxidative stress ability of bacteria, which led to an imbalance in the bacterial oxidation-antioxidant system. These effects together induced the bacteria to produce antibiotic tolerance. Surprisingly, the addition of succinic acid and xanthine could reverse the antibiotic tolerance induced by citric acid in vitro and in animal infection models. In conclusion, these findings provide new insights into the potential risks of citric acid usage and the relationship between antibiotic tolerance and bacterial metabolism.

Analysis of an IncR plasmid carried by carbapenem-resistant Klebsiella pneumoniae: A survey of swine Klebsiella pneumoniae in Jilin Province.

OBJECTIVES: This study was conducted in Jilin Province to investigate the mechanism involved in the antibiotic resistance and pathogenicity of Klebsiella pneumoniae. METHODS: Lung samples were collected from large-scale pig farms in Jilin Province. Antimicrobial susceptibility and mouse lethality assays were carried out. K. pneumoniae isolate JP20, with high virulence and antibiotic resistance, was chosen for whole-genome sequencing. The complete sequence of its genome was annotated, and the virulence and antibiotic resistance mechanism were analysed. RESULTS: A total of 32 K. pneumoniae strains were isolated and tested for antibiotic resistance and pathogenicity. Among them, the JP20 strain showed high levels of resistance to all tested antimicrobial agents and strong pathogenicity in mice (lethal dose of 1.35 × 1011 CFU/mL). Sequencing of the multidrug-resistant and highly virulent K. pneumoniae JP20 strain revealed that the antibiotic resistance genes were mainly carried by an IncR plasmid. We speculate that extended-spectrum ß-lactamases and loss of outer membrane porin OmpK36 play an important role in carbapenem antibiotic resistance. This plasmid contains a mosaic structure consisting of a large number of mobile elements. CONCLUSION: Through genome-wide analysis, we found that an lncR plasmid carried by the JP20 strain may have evolved in pig farms, possibly leading to multidrug resistance in the JP20 strain. It is speculated that the antibiotic resistance of K. pneumoniae in pig farms is mainly mediated by mobile elements (insertion sequences, transposons, and plasmids). These data provide a basis for monitoring the antibiotic resistance of K. pneumoniae and lay a foundation for an improved understanding of the genomic characteristics and antibiotic resistance mechanism of K. pneumoniae.

Nomograms referenced by cardiac magnetic resonance in the prediction of cardiac injuries in patients with ST-elevation myocardial infarction.

BACKGROUND: Evaluation of cardiac injuries is essential in patients with ST-elevation myocardial infarction (STEMI). Cardiac magnetic resonance (CMR) has become the gold standard for quantifying cardiac injuries; however, its routine application is limited. A nomogram is a useful tool for prognostic prediction based on the comprehensive utilization of clinical data. We presumed that the nomogram models established using CMR as a reference could precisely predict cardiac injuries. METHODS: This analysis included 584 patients with acute STEMI from a CMR registry study for STEMI (NCT03768453). The patients were divided into training (n = 408) and testing (n = 176) datasets. The least absolute shrinkage and selection operator method and multivariate logistic regression were used to construct nomograms for predicting left ventricular ejection fraction (LVEF) ≤40%, infarction size (IS) ≥ 20% on the LV mass, and microvascular dysfunction. RESULTS: The nomogram for predicting LVEF≤40%, IS≥20%, and microvascular dysfunction comprised 14, 10, and 15 predictors, respectively. With the nomograms, the individual risk probability of developing specific outcomes could be calculated, and the weight of each risk factor was demonstrated. The C-index of the nomograms in the training dataset were 0.901, 0.831, and 0.814, respectively, and were comparable in the testing set, showing good nomogram discrimination and calibration. The decision curve analysis demonstrated good clinical effectiveness. Online calculators were also constructed. CONCLUSIONS: With the CMR results as the reference standard, the established nomograms demonstrated good effectiveness in predicting cardiac injuries after STEMI and could provide physicians with a new option for individual risk stratification.

Antibiotic synergist OM19r reverses aminoglycoside resistance in multidrug-resistant Escherichia coli.

Introduction: The continued emergence and spread of multidrug-resistant (MDR) bacterial pathogens require a new strategy to improve the efficacy of existing antibiotics. Proline-rich antimicrobial peptides (PrAMPs) could also be used as antibacterial synergists due to their unique mechanism of action. Methods: Utilizing a series of experiments on membrane permeability, In vitro protein synthesis, In vitro transcription and mRNA translation, to further elucidate the synergistic mechanism of OM19r combined with gentamicin. Results: A proline-rich antimicrobial peptide OM19r was identified in this study and its efficacy against Escherichia coli B2 (E. coli B2) was evaluated on multiple aspects. OM19r increased antibacterial activity of gentamicin against multidrug-resistance E. coli B2 by 64 folds, when used in combination with aminoglycoside antibiotics. Mechanistically, OM19r induced change of inner membrane permeability and inhibited translational elongation of protein synthesis by entering to E. coli B2 via intimal transporter SbmA. OM19r also facilitated the accumulation of intracellular reactive oxygen species (ROS). In animal models, OM19r significantly improved the efficacy of gentamicin against E. coli B2. Discussion: Our study reveals that OM19r combined with GEN had a strong synergistic inhibitory effect against multi-drug resistant E. coli B2. OM19r and GEN inhibited translation elongation and initiation, respectively, and ultimately affected the normal protein synthesis of bacteria. These findings provide a potential therapeutic option against multidrug-resistant E. coli.

EBD: an eye biomarker database.

MOTIVATION: Many ophthalmic disease biomarkers have been identified through comprehensive multiomics profiling, and hold significant potential in advancing the diagnosis, prognosis, and management of diseases. Meanwhile, the eye itself serves as a natural biomarker for several systemic diseases including neurological, renal, and cardiovascular systems. We aimed to collect and standardize this eye biomarkers information and construct the eye biomarker database (EBD) to provide ophthalmologists with a platform to search, analyze, and download these eye biomarker data. RESULTS: In this study, we present the EBD , a world-first online compilation comprising 889 biomarkers for 26 ocular diseases and 939 eye biomarkers for 181 systemic diseases. The EBD also includes the information of 78 "nonbiomarkers"-the objects that have been proven cannot be biomarkers. Biological function and network analysis were conducted for these ocular disease biomarkers, and several hub pathways and common network topology characteristics were newly identified, which may promote future ocular disease biomarker discovery and characterizes the landscape of biomarkers for eye diseases at the pathway and network level. The EBD is expected to yield broader utility among developmental biologists and clinical scientists in and outside of the eye field by assisting in the identification of biomarkers linked to eye disorders and related systemic diseases. AVAILABILITY AND IMPLEMENTATION: EBD is available at http://www.eyeseeworld.com/ebd/index.html.

Transcriptomic Changes and satP Gene Function Analysis in Pasteurella multocida with Different Levels of Resistance to Enrofloxacin.

Pasteurella multocida (Pm) is one of the major pathogens of bovine respiratory disease (BRD), which can develop drug resistance to many of the commonly used antibiotics. Our earlier research group found that with clinical use of enrofloxacin, Pm was more likely to develop drug resistance to enrofloxacin. In order to better understand the resistance mechanism of Pm to enrofloxacin, we isolated PmS and PmR strains with the same PFGE typing in vitro, and artificially induced PmR to obtain the highly resistant phenotype, PmHR. Then transcriptome sequencing of clinically isolated sensitive strains, resistant and highly drug-resistant strains, treated with enrofloxacin at sub-inhibitory concentrations, were performed. The satP gene, of which the expression changed significantly with the increase in drug resistance, was screened. In order to further confirm the function of this gene, we constructed a satP deletion (ΔPm) strain using suicide vector plasmid pRE112, and constructed the C-Pm strain using pBBR1-MCS, and further analyzed the function of the satP gene. Through a continuously induced resistance test, it was found that the resistance rate of ΔPm was obviously lower than that of Pm in vitro. MDK99, agar diffusion and mutation frequency experiments showed significantly lower tolerance of ΔPm than the wild-type strains. The pathogenicity of ΔPm and Pm was measured by an acute pathogenicity test in mice, and it was found that the pathogenicity of ΔPm was reduced by about 400 times. Therefore, this study found that the satP gene was related to the tolerance and pathogenicity of Pm, and may be used as a target of enrofloxacin synergistic effect.