Genomic and Phenotypic Analysis of bla KPC-2 Associated Carbapenem Resistance in Klebsiella aerogenes: Insights into Clonal Spread and Resistance Mechanisms Across Hospital Departments in Beijing.

Purpose: This study conducted an phenotypic and whole-genome sequencing analysis with Klebsiella aerogenes to elucidate its clinical epidemiological characteristics, antimicrobial resistance (AMR) phenotype, biofilm formation ability and hemolytic activity testing, AMR genes and phylogenetic relationships, so as to provide a further understanding of the intra-hospital strain transmission. Methods: Samples were collected from a hospital in Beijing between 2020 and 2022. All strains underwent bacterial identification, antimicrobial susceptibility testing (AST) using the VITEK-2 compact system. Biofilm formation ability and hemolytic activity were tested. Second-generation sequencing was applied to all strains, with those carrying the bla KPC gene were selected for third-generation sequencing. Whole-genome analysis identified resistance genes, plasmid types, MLST typing, and phylogenetic relationships. Plasmids were assembled to detect plasmid structures and AMR gene location. Results: Among the 42 K. aerogenes isolates, 21 were carbapenem-resistant K. aerogenes (CRKA). All strains exhibited strong biofilm formation and no hemolytic activity. Most were sourced from sputum (83.3%). CRKA demonstrated extensive resistance to antibiotics, particularly ß-lactamase inhibitors and Cefotetan. This resistance pattern was closely associated with the presence of an IncFII(pHN7A8) plasmid, which carried multiple resistance genes, including bla KPC-2, bla CTX-M-65, bla TEM-1, rmtB and a large number of mobile elements. The majority of CRKA strains clustered within the same branch of the phylogenetic tree, exhibiting minimal single nucleotide polymorphism (0-13 SNPs) differences, and they shared the same sequence type (ST292), resistance genes, and plasmids, originating from different departments, suggesting clonal transmission among the hospital. Conclusion: Our research reveals that the clonal transmission of CRKA occurs across various departments within the hospital. The widespread resistance observed in CRKA, attributed to the presence of bla KPC and ESBLs genes, underscores the need for heightened vigilance to prevent the further dissemination of CRKA within the hospital and, potentially, throughout the wider community.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Association of Lipoprotein(a) Levels With Myocardial Infarction in Patients With Low-Attenuation Plaque.

BACKGROUND: Lipoprotein(a) (Lp[a]) is associated with an increased risk of myocardial infarction (MI). However, the mechanism underlying this association has yet to be fully elucidated. OBJECTIVES: This multicenter study aimed to investigate whether association between Lp(a) and MI risk is reinforced by the presence of low-attenuation plaque (LAP) identified by coronary computed tomography angiography (CCTA). METHODS: In a derivation cohort, a total of 5,607 patients with stable chest pain suspected of coronary artery disease who underwent CCTA and Lp(a) measurement were prospectively enrolled. In validation cohort, 1,122 patients were retrospectively collected during the same period. High Lp(a) was defined as Lp(a) ≥50 mg/dL. The primary endpoint was a composite of time to fatal or nonfatal MI. Associations were estimated using multivariable Cox proportional hazard models. RESULTS: During a median follow-up of 8.2 years (Q1-Q3: 7.2-9.3 years), the elevated Lp(a) levels were associated with MI risk (adjusted HR [aHR]: 1.91; 95% CI: 1.46-2.49; P < 0.001). There was a significant interaction between Lp(a) and LAP (Pinteraction <0.001) in relation to MI risk. When stratified by the presence or absence of LAP, Lp(a) was associated with MI in patients with LAP (aHR: 3.03; 95% CI: 1.92-4.76; P < 0.001). Mediation analysis revealed that LAP mediated 73.3% (P < 0.001) for the relationship between Lp(a) and MI. The principal findings remained unchanged in the validation cohort. CONCLUSIONS: Elevated Lp(a) augmented the risk of MI during 8 years of follow-up, especially in patients with LAP identified by CCTA. The presence of LAP could reinforce the relationship between Lp(a) and future MI occurrence.

Cerebral autoregulation: A reliable predictor of prognosis in patients receiving intravenous thrombolysis.

AIMS: To investigate the characteristics of dynamic cerebral autoregulation (dCA) after intravenous thrombolysis (IVT) and assess the relationship between dCA and prognosis. METHODS: Patients with unilateral acute ischemic stroke receiving IVT were prospectively enrolled; those who did not were selected as controls. All patients underwent dCA measurements, by quantifying the phase difference (PD) and gain, at 1-3 and 7-10 days after stroke onset. Simultaneously, two dCA-based nomogram models were established to verify the predictive value of dCA for patients with mild-to-moderate stroke. RESULTS: Finally, 202 patients who received IVT and 238 who did not were included. IVT was positively correlated with higher PD on days 1-3 and 7-10 after stroke onset. PD values in both sides at 1-3 days after stroke onset and in the affected side at 7-10 days after onset were independent predictors of unfavorable outcomes in patients who received IVT. Additionally, in patients with mild-to-moderate stroke who received IVT, the dCA-based nomogram models significantly improved the risk predictive ability for 3-month unfavorable outcomes. CONCLUSION: IVT has a positive effect on dCA in patients with acute stroke; furthermore, dCA may be useful to predict the prognosis of patients with IVT.

A novel framework for three-dimensional electrical impedance tomography reconstruction of maize ear via feature reconfiguration and residual networks.

Electrical impedance tomography (EIT) provides an indirect measure of the physiological state and growth of the maize ear by reconstructing the distribution of electrical impedance. However, the two-dimensional (2D) EIT within the electrode plane finds it challenging to comprehensively represent the spatial distribution of conductivity of the intact maize ear, including the husk, kernels, and cob. Therefore, an effective method for 3D conductivity reconstruction is necessary. In practical applications, fluctuations in the contact impedance of the maize ear occur, particularly with the increase in the number of grids and computational workload during the reconstruction of 3D spatial conductivity. These fluctuations may accentuate the ill-conditioning and nonlinearity of the EIT. To address these challenges, we introduce RFNetEIT, a novel computational framework specifically tailored for the absolute imaging of the three-dimensional electrical impedance of maize ear. This strategy transforms the reconstruction of 3D electrical conductivity into a regression process. Initially, a feature map is extracted from measured boundary voltage via a data reconstruction module, thereby enhancing the correlation among different dimensions. Subsequently, a nonlinear mapping model of the 3D spatial distribution of the boundary voltage and conductivity is established, utilizing the residual network. The performance of the proposed framework is assessed through numerical simulation experiments, acrylic model experiments, and maize ear experiments. Our experimental results indicate that our method yields superior reconstruction performance in terms of root-mean-square error (RMSE), correlation coefficient (CC), structural similarity index (SSIM), and inverse problem-solving time (IPST). Furthermore, the reconstruction experiments on maize ears demonstrate that the method can effectively reconstruct the 3D conductivity distribution.

Baseline Uric Acid Levels and Intravenous Thrombolysis Outcomes in Patients With Acute Ischemic Stroke: A Prospective Cohort Study.

BACKGROUND: The study aimed to investigate the relationship between uric acid (UA) levels and functional outcomes at 3 months in patients with acute ischemic stroke (AIS) who underwent intravenous thrombolysis (IVT). METHODS AND RESULTS: This prospective cohort study included 1001 consecutive patients with AIS who underwent IVT. The correlation between UA levels and post-IVT AIS outcomes was examined. Any nonlinear relationship was assessed using a restricted cubic spline function. The nonlinear P value for the association of UA levels with favorable (modified Rankin Scale [mRS] score ≤2) and excellent (mRS score ≤1) outcomes at 3 months post-IVT were <0.001 and 0.001, respectively. However, for patients with and without hyperuricemia, no evident nonlinear relationship was observed between UA levels and favorable 3-month post-IVT outcomes, with nonlinear P values of 0.299 and 0.207, respectively. The corresponding interaction analysis yielded a P value of 0.001, indicating significant heterogeneity. Similar results were obtained for excellent outcomes at 3 months post-IVT. In the hyperuricemia group, increased UA levels by 50 µmol/L reduced the odds of a favorable 3-month post-AIS outcome (odds ratio [OR], 0.75 [95% CI, 0.57-0.97]). Conversely, in the nonhyperuricemia group, a similar UA increase was linked to higher favorable outcome odds (OR, 1.31 [95% CI, 1.15-1.50]). CONCLUSIONS: An inverted U-shaped nonlinear relationship was observed between UA levels and favorable and excellent outcomes at 3 months in patients with AIS who underwent IVT. Higher UA levels predict favorable outcomes in patients without hyperuricemia but unfavorable outcomes in those with hyperuricemia.

GY-SLAM: A Dense Semantic SLAM System for Plant Factory Transport Robots.

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network, GY, based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and the SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While mAP@0.5 increased by 0.514% to 95.364, the model simultaneously reduced the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system localization accuracy and robustness. It shows a remarkable 92.59% improvement in RMSE for Absolute Trajectory Error (ATE), along with a 93.11% improvement in RMSE for the translational drift of Relative Pose Error (RPE) and a 92.89% improvement in RMSE for the rotational drift of RPE. Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.

Genomic insights and antimicrobial resistance profiles of CRKP and non-CRKP isolates in a Beijing geriatric medical center: emphasizing the blaKPC-2 carrying high-risk clones and their spread.

Background: The escalating resistance of Klebsiella pneumoniae, a prevalent pathogen in healthcare settings, especially its carbapenem-resistant K. pneumoniae (CRKP), to a wide array of antibiotics, notably ß-lactams, constitutes a formidable challenge for healthcare and global public health management. Methods: This research compared the resistance phenotypes and genomic profiles of CRKP and Non-CRKP isolates in a Beijing hospital, focusing on high-risk blaKPC-2 gene-bearing CRKP clones and the structure of mobile genetic elements facilitating their spread across hospital departments. Forty K. pneumoniae isolates were collected from various departments of the hospital and subjected to antimicrobial susceptibility testing and whole-genome sequencing to analyze their resistance phenotypes and genomic features. Results: The study revealed that among the 31 CRKP isolates, ST11 is the most common sequence type, with K47 and OL101 being the dominant capsule types, primarily observed in the respiratory department. In terms of antimicrobial susceptibility: 87.5% of the isolates exhibited multidrug resistance (MDR), with a high resistance rate of 30% against tigecycline. All CRKP isolates demonstrated resistance to multiple drug classes (≥5 CLSI classes). Non-CRKP isolates also showed high resistance rates to minocycline and doxycycline (77.8%). the ST11-KL47-OL101 type emerged as the predominant clone among the CRKP isolates carrying the blaKPC-2 gene. This dominance appears to be mediated by the pKpnR03_2 plasmid, which harbors not only blaKPC-2 and rmtb but also gene clusters pertinent to iron transport and arsenic resistance. These isolates, clustering in the C3 clade of the phylogenetic tree, exhibited minor genetic variations and close evolutionary relationships, suggesting a plasmid-driven spread across various hospital departments. Conclusion: In summary, our study highlights the extensive spread of antibiotic-resistant K. pneumoniae across various departments in our hospital, with a particular emphasis on the dominant clonal proliferation of the ST11-KL47-OL101 CRKP strain. This finding underscores the significant role of plasmid-mediated gene transfer in the evolution and dissemination of resistant strains within hospital environments. The study emphasizes the necessity for ongoing surveillance of antibiotic resistance and genomic analysis in hospital settings to effectively monitor and manage these challenges.

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease.

OBJECTIVES: To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis. METHODS: Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. RESULTS: The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01). CONCLUSION: ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis. CLINICAL RELEVANCE STATEMENT: ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other. KEY POINTS: • Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

3D Aligned Nanofiber Scaffold Fabrication with Trench-Guided Electrospinning for Cardiac Tissue Engineering.

Constructing three-dimensional (3D) aligned nanofiber scaffolds is significant for the development of cardiac tissue engineering, which is promising in the field of drug discovery and disease mechanism study. However, the current nanofiber scaffold preparation strategy, which mainly includes manual assembly and hybrid 3D printing, faces the challenge of integrated fabrication of morphology-controllable nanofibers due to its cross-scale structural feature. In this research, a trench-guided electrospinning (ES) strategy was proposed to directly fabricate 3D aligned nanofiber scaffolds with alternative ES and a direct ink writing (DIW) process. The electric field effect of DIW poly(dimethylsiloxane) (PDMS) side walls on guiding whipping ES nanofibers was investigated to construct trench design rules. It was found that the width/height ratio of trenches greatly affected the nanofiber alignment, and the trench width/height ratio of 1.5 provided the nanofiber alignment degree over 60%. As a proof of principle, 3D nanofiber scaffolds with controllable porosity (60-80%) and alignment (30-60%) were fabricated. The effect of the scaffolds was verified by culturing human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), which resulted in the uniform 3D distribution of aligned hiPSC-CMs with ∼1000 µm thickness. Therefore, this printing strategy shows great potential for the efficient engineered tissue construction.

Impaired kidney function and the risk of all-cause mortality and cardiovascular disease among Chinese hypertensive adults: Using three different equations to estimate the glomerular filtration rate.

OBJECTIVES: We aimed to seek accurate assessments of the glomerular filtration rate (GFR) in a Chinese hypertensive population to identify individuals at high risk for chronic kidney disease (CKD) progression. Then, the risk of cardiovascular disease (CVD) and all-cause death due to kidney injury were further investigated under appropriate GFR-estimation equations. METHODS: In this prospective follow-up cohort study of 10,171 hypertensive patients, we compared the discrimination power of a trio of GFR-estimation equations using Harrell's C-index, measuring the model fit by calculating the Akaike information criterion. Univariate and multivariable logistic regression analyses were respectively used to calculate the hazard ratio (HR) and 95% confidence interval [CI] values for CKD progression. In addition, we also assessed the risk of CVD and all-cause death with impaired renal function using multivariable-adjusted Cox regression models. RESULTS: The Modification of Diet in Renal Disease (MDRD) equation showed the highest C-index range for the predicted probability of CKD progression in the fully adjusted model. During MDRD analysis, a low eGFR (60-89 mL/min/1.73m2 or < 60 mL/min/1.73m2) was an independent risk factor for CVD, especially stroke (1.28 [95% CI, 1.05-1.55] and 1.89 [95% CI, 1.08-3.31]), as well as all-cause mortality (1.28 [95% CI, 1.09-1.50] and 1.68 [95% CI, 1.01-2.78]). CONCLUSIONS: The MDRD equation seems to be more suitable for screening CKD progression in Chinese hypertensive populations, targeting potential risk factors for effective prevention to reduce renal impairment so as to further limit CVD morbidity and mortality.

The silk gland proteome of Stenopsyche angustata provides insights into the underwater silk secretion.

Caddisworms (Trichoptera) spin adhesive silks to construct a variety of underwater composite structures. Many studies have focused on the fibroin heavy chain of caddisworm silk and found that it contains heavy phosphorylation to maintain a stable secondary structure. Besides fibroins, recent studies have also identified some new silk proteins within caddisworm silk. To better understand the silk composition and its secretion process, this study reports the silk gland proteome of a retreat-building caddisworm, Stenopsyche angustata Martynov (Trichoptera, Stenopsychidae). Using liquid chromatography tandem mass spectrometry (LC-MS/MS), 2389 proteins were identified in the silk gland of S. angustata, among which 192 were predicted as secreted silk proteins. Twenty-nine proteins were found to be enriched in the front silk gland, whereas 109 proteins were enriched in the caudal silk gland. The fibroin heavy chain and nine uncharacterized silk proteins were identified as phosphorylated proteins. By analysing the sequence of the fibroin heavy chain, we found that it contains 13 Gly/Thr/Pro-rich regions, 12 Val/Ser/Arg-rich regions and a Gly/Arg/Thr-rich region. Three uncharacterized proteins were identified as sericin-like proteins due to their larger molecular weights, signal peptides and repetitive motifs rich in serine. This study provides valuable information for further clarifying the secretion and adhesion of underwater caddisworm silk.

Analysis of cardiovascular function in diabetic patients using EEMD-ICA fusion multi-scale percussion entropy.

BACKGROUND: Diabetes is a chronic disease that can lead to a variety of complications and even cause death. The signal characteristics of the photoplethysmography signals (PPG) and electrocardiogram signals (ECG) can reflect the autonomic and vascular aspects of the effects of diabetes on the body. OBJECTIVE: Based on the complex mechanism of interaction between PPG and ECG, a set of ensemble empirical mode decomposition-independent component analysis (EEMD-ICA) fusion multi-scale percussion entropy index (MSPEI) method was proposed to analyze cardiovascular function in diabetic patients. METHODS: Firstly, the original signal was decomposed into multiple Intrinsic Mode Function (IMFs) by ensemble empirical mode decomposition EEMD, principal components of IMF were extracted by independent component analysis (ICA), then the extracted principal components were reconstructed to eliminate the complex high and low frequency noise of physiological signals. In addition, the MSPEI was calculated for the ECG R-R interval and PPG amplitude sequence.(RRI and Amp) The results showed that, compared with EEMD method, the SNR of EEMD-ICA method increases from 2.1551 to 11.3642, and the root mean square error (RMSE) decreases from 0.0556 to 0.0067. This algorithm can improve the performance of denoising and retain more feature information. The large and small scale entropy of MSPEI (RRI,Amp) was significantly different between healthy and diabetic patients (p< 0.01). RESULTS: Compared with arteriosclerosis index (AI) and multi-scale cross-approximate entropy (MCAE): MSPEISS (RRI,Amp) indicated that diabetes can affect the activity of human autonomic nervous system, while MSPEILS (RRI,Amp) indicated that diabetes can cause or worsen arteriosclerosis. CONCLUSION: Multi-scale Percussion Entropy algorithm has more advantages in analyzing the influence of diabetes on human cardiovascular and autonomic nervous function.

Diagnostic performance of 3.0 T unenhanced Dixon water-fat separation coronary MR angiography in patients with low-to-intermediate risk of coronary artery disease.

PURPOSE: To evaluate the diagnostic performance of 3.0 T unenhanced compressed-sensing sensitivity encoding (CS-SENSE) Dixon water-fat separation coronary MR angiography (CMRA) in patients with low-to-intermediate risk of coronary artery disease (CAD) and its ability to grade the severity of CAD based on Coronary Artery Disease Reporting and Data System (CAD-RADS). METHODS: A total of 55 patients who was clinically evaluated as low-to-intermediate risk of CAD were finally included to undergo both 3.0 T CS-SENSE water-fat separation CMRA and coronary computed tomography angiography (CCTA), and 11 of them also underwent X-ray coronary angiography (CAG). The severity of coronary artery disease was graded in patients who had completed both CCTA and CMRA examinations by the use of CAD-RADS reports for the patients with stable chest pain, and the diagnostic consistency between the two approaches was evaluated. Diagnostic performance of CMRA was assessed using the combination of CCTA and CAG as the reference standard for excluding or confirming CAD respectively. RESULTS: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of 3.0 T unenhanced water-fat separation coronary MRA were 90.0%, 95.0%, 81.8%, 97.4% and 94.0% for a patient-based analysis respectively. In comparison with CCTA, 3.0 T Dixon water-fat separation CMRA demonstrated excellent consistency in grading the severity of coronary heart disease according to CAD-RADS (0.77 for kappa value). CONCLUSION: In the group of low-to-intermediate probability for CAD, 3.0 T unenhanced CS-SENSE Dixon water-fat separation CMRA can present satisfactory diagnostic performance for the exclusion of CAD with high sensitivity and negative predictive value as well as the evaluation of grading the severity of coronary artery disease.

Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids.

BACKGROUND: Biliary atresia (BA) is a rare fatal liver disease in children, and the aim of this study was to develop a method to diagnose BA early. METHODS: We determined serum levels of matrix metalloproteinase-7 (MMP-7), the results of 13 liver tests, and the levels of 20 bile acids, and integrated computational models were constructed to diagnose BA. RESULTS: Our findings demonstrated that MMP-7 expression levels, as well as the results of four liver tests and levels of ten bile acids, were significantly different between 86 BA and 59 non-BA patients (P < 0.05). The computational prediction model revealed that MMP-7 levels alone had a higher predictive accuracy [area under the receiver operating characteristic curve (AUC) = 0.966, 95% confidence interval (CI): 0.942, 0.989] than liver test results and bile acid levels. The AUC was 0.890 (95% CI 0.837, 0.943) for liver test results and 0.825 (95% CI 0.758, 0.892) for bile acid levels. Furthermore, bile levels had a higher contribution to enhancing the predictive accuracy of MMP-7 levels (AUC = 0.976, 95% CI 0.953, 1.000) than liver test results. The AUC was 0.983 (95% CI 0.962, 1.000) for MMP-7 levels combined with liver test results and bile acid levels. In addition, we found that MMP-7 levels were highly correlated with gamma-glutamyl transferase levels and the liver fibrosis score. CONCLUSION: The innovative integrated models based on a large number of indicators provide a noninvasive and cost-effective approach for accurately diagnosing BA in children. Video Abstract (MP4 142103 KB).

Construction of Single-Atom Catalysts for N, O Synergistic Coordination and Application to Electrocatalytic O2 Reduction.

Replacing expensive platinum oxygen reduction reaction (ORR) catalysts with atomically dispersed single-atom catalysts is an effective way to improve the energy conversion efficiency of fuel cells. Herein, a series of single-atom catalysts, TM-N2O2Cx (TM=Sc-Zn) with TM-N2O2 active units, were designed, and their catalytic performance for electrocatalytic O2 reduction was investigated based on density functional theory. The results show that TM-N2O2Cx exhibits excellent catalytic activity and stability in acidic media. The eight catalysts (TM=Sc, Ti, V, Cr, Mn, Fe, Co, and Ni) are all 4e- reaction paths, among which Sc-N2O2Cx, Ti-N2O2Cx, and V-N2O2Cx follow dissociative mechanisms and the rest are consistent with associative mechanisms. In particular, Co-N2O2Cx and Ni-N2O2Cx enable a smooth reduction in O2 at small overpotentials (0.44 V and 0.49 V, respectively). Furthermore, a linear relationship between the adsorption free energies of the ORR oxygen-containing intermediates was evident, leading to the development of a volcano plot for the purpose of screening exceptional catalysts for ORR. This research will offer a novel strategy for the design and fabrication of exceptionally efficient non-precious metal catalysts on an atomic scale.

A clinical strategy to improve the diagnostic performance of 3T non-contrast coronary MRA and noninvasively evaluate coronary distensibility: combination of diastole and systole imaging.

BACKGROUND: The clinical application of coronary MR angiography (MRA) combining diastole and systole imaging has never been described comprehensively in coronary artery disease (CAD) patients. We aimed to design an optimal non-contrast coronary MRA scan protocol combining diastolic and systolic imaging and to (1) evaluate its diagnostic performance for detecting significant coronary stenosis; (2) evaluate the feasibility of this protocol to noninvasively measure the coronary distensibility index (CDI). METHODS: From June 2021 to May 2022, 33 healthy volunteers and 91 suspected CAD patients scheduled for X-ray coronary angiography (CAG) were prospectively enrolled. 3T non-contrast water-fat coronary MRA was carried out twice at diastole and systole. Significant coronary stenosis was defined as a luminal diameter reduction of ≥ 50% using CAG as the reference and was evaluated as follows: (1) by coronary MRA in diastole alone; (2) by coronary MRA in systole alone; (3) by combined coronary MRA in diastole and systole. According to CAG, the patients were divided into significant CAD patients and non-significant CAD patients. The difference in CDI among participants was evaluated. RESULTS: Combined coronary MRA was completed in 31 volunteers and 76 patients. The per-patient sensitivity, specificity, and accuracy of combined coronary MRA were 97.5%, 83.3%, and 90.8%, respectively. Compared with single diastolic mode, combined coronary MRA showed equally high sensitivity but improved specificity on a per-patient basis (83.3% vs. 63.9%, adjusted P = 0.013). The CDI tested by coronary MRA decreased incrementally from healthy volunteers to non-significant and significant CAD patients. CONCLUSION: Compared with single-phase mode, 3 T non-contrast combined coronary MRA significantly improved specificity and may have potential to be a simple noninvasive method to measure CDI.

Comparison of CT-derived Plaque Characteristic Index With CMR Perfusion for Ischemia Diagnosis in Stable CAD.

BACKGROUND: Coronary computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR) have been used to diagnose lesion-specific ischemia in patients with coronary artery disease. The aim of this study was to investigate the diagnostic performance of CCTA-derived plaque characteristic index compared with myocardial blood flow (MBF) and myocardial perfusion reserve (MPR) derived from CMR perfusion in the assessment of lesion-specific ischemia. METHODS: Between October 2020 and March 2022, consecutive patients with suspected or known coronary artery disease, who were clinically referred for invasive coronary angiography were prospectively enrolled. All participants sequentially underwent CCTA and CMR and invasive fractional flow reserve within 2 weeks. The diagnostic performance of CCTA-derived plaque characteristics, CMR perfusion-derived stress MBF, and MPR were compared. Lesions with fractional flow reserve ≤0.80 were considered to be hemodynamically significant stenosis. RESULTS: Nighty-two patients with 141 vessels were included in this study. Plaque length, minimum luminal area, plaque area, percent area stenosis, total atheroma volume, vessel volume, lipid-rich volume, spotty calcium, napkin-ring signs, stress MBF, and MPR in flow-limiting stenosis group were significantly different from nonflow-limiting group. The overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of lesion-specific ischemia diagnosis were 61.0%, 55.3%, 63.1%, 35.6%, and 79.3% for stress MBF, and 89.4%, 89.5%, 89.3%, 75.6%, 95.8% for MPR; meanwhile, 82.3%, 79.0%, 84.5%, 65.2%, and 91.6% for CCTA-derived plaque characteristic index. CONCLUSIONS: In our prospective study, CCTA-derived plaque characteristics and MPR derived from CMR performed well in diagnosing lesion-specific myocardial ischemia and were significantly better than stress MBF in stable coronary artery disease.

Layer-specific strain in patients with cardiac amyloidosis using tissue tracking MR.

Background: Cardiac infiltration is the major predictor of poor prognosis in patients with systemic amyloidosis, thus it becomes of great importance to evaluate cardiac involvement. Purpose: We aimed to evaluate left ventricular myocardial deformation alteration in patients with cardiac amyloidosis (CA) using layer-specific tissue tracking MR. Material and Methods: Thirty-nine patients with CA were enrolled. Thirty-nine normal controls were also recruited. Layer-specific tissue tracking analysis was done based on cine MR images. Results: Compared with the control group, a significant reduction in LV whole layer strain values (GLS, GCS, and GRS) and layer-specific strain values was found in patients with CA (all P < 0.01). In addition, GRS and GLS, as well as subendocardial and subepicardial GLS, GRS, and GCS, were all diminished in patients with CA and reduced LVEF, when compared to those with preserved or mid-range LVEF (all P < 0.05). GCS showed the largest AUC (0.9952, P = 0.0001) with a sensitivity of 93.1% and specificity of 90% to predict reduced LVEF (<40%). Moreover, GCS was the only independent predictor of LV systolic dysfunction (Odds Ratio: 3.30, 95% CI:1.341-8.12, and P = 0.009). Conclusion: Layer-specific tissue tracking MR could be a useful method to assess left ventricular myocardial deformation in patients with CA.