A nomogram risk prediction model for no-reflow after primary percutaneous coronary intervention based on rapidly accessible patient data among patients with ST-segment elevation myocardial infarction and its relationship with prognosis

BackgroundNo-reflow occurring after primary percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) can increase the incidence of major adverse cardiovascular events (MACE). The present study aimed to construct a nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients, and to further explore its prognostic utility in this patient population.MethodsResearch subjects included 443 STEMI patients who underwent primary PCI between February 2018 and February 2021. Rapidly available clinical data obtained from emergency admissions were collected. Independent risk factors for no-reflow were analyzed using a multivariate logistic regression model. Subsequently, a nomogram for no-reflow was constructed and verified using bootstrap resampling. A receiver operating characteristic (ROC) curve was plotted to evaluate the discrimination ability of the nomogram model and a calibration curve was used to assess the concentricity between the model probability curve and ideal curve. Finally, the clinical utility of the model was evaluated using decision curve analysis.ResultsThe incidence of no-reflow was 18% among patients with STEMI. Killip class ≥2 on admission, pre-operative D-dimer and fibrinogen levels, and systemic immune–inflammation index (SII) were independent risk factors for no-reflow. A simple and quickly accessible prediction nomogram for no-reflow after PCI was developed. This nomogram demonstrated good discrimination, with an area under the ROC curve of 0.716. This nomogram was further validated using bootstrapping with 1,000 repetitions; the C-index of the bootstrap model was 0.706. Decision curve analysis revealed that this model demonstrated good fit and calibration and positive net benefits. Kaplan–Meier survival curve analysis revealed that patients with higher model scores were at a higher risk of MACE. Multivariate Cox regression analysis revealed that higher model score(s) was an independent predictor of MACE (hazard ratio 2.062; P = 0.004).ConclusionsA nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients was constructed. This novel nomogram may be useful in identifying STEMI patients at higher risk for no-reflow and may predict prognosis in this patient population

Quantification of airway thickness changes in smoke-inhalation injury using in-vivo 3-D endoscopic frequency-domain optical coherence tomography

Smoke inhalation injury is frequently accompanied by cyanide poisoning that may result in substantial morbidity and mortality, and methods are needed to quantitatively determine extent of airway injury. We utilized a 3-D endoscopic frequency-domain optical coherence tomography (FD-OCT) constructed with a swept-source laser to investigate morphological airway changes following smoke and cyanide exposure in rabbits. The thickness of the mucosal area between the epithelium and cartilage in the airway was measured and quantified. 3-D endoscopic FD-OCT was able to detect significant increases in the thickness of the tracheal walls of the rabbit beginning almost immediately after smoke inhalation injuries which were similar to those with combined smoke and cyanide poisoning

QTL Mapping Combined With Bulked Segregant Analysis Identify SNP Markers Linked to Leaf Shape Traits in Pisum sativum Using SLAF Sequencing

Leaf shape is an important trait that influences the utilization rate of light, and affects quality and yield of pea (Pisum sativum). In the present study, a joint method of high-density genetic mapping using specific locus amplified fragment sequencing (SLAF-seq) and bulked segregant analysis (BSA) was applied to rapidly detect loci with leaf shape traits. A total of 7,146 polymorphic SLAFs containing 12,213 SNP markers were employed to construct a high-density genetic map for pea. We conducted quantitative trait locus (QTL) mapping on an F2 population to identify QTLs associated with leaf shape traits. Moreover, SLAF-BSA was conducted on the same F2 population to identify the single nucleotide polymorphism (SNP) markers linked to leaf shape in pea. Two QTLs (qLeaf_or-1, qLeaf_or-2) were mapped on linkage group 7 (LG7) for pea leaf shape. Through alignment of SLAF markers with Cicer arietinum, Medicago truncatula, and Glycine max, the pea LGs were assigned to their corresponding homologous chromosomal groups. The comparative genetic analysis showed that pea is more closely related to M. truncatula. Based on the sequencing results of two pools with different leaf shape, 179 associated markers were obtained after association analysis. The joint analysis of SLAF-seq and BSA showed that the QTLs obtained from mapping on a high-density genetic map are convincing due to the closely associated map region with the BSA results, which provided more potential markers related to leaf shape. Thus, the identified QTLs could be used in marker-assisted selection for pea breeding in the future. Our study revealed that joint analysis of QTL mapping on a high-density genetic map and BSA-seq is a cost-effective and accurate method to reveal genetic architecture of target traits in plant species without a reference genome

Optical imaging in an Alzheimer’s mouse model reveals amyloid-β-dependent vascular impairment

Alzheimer's disease (AD) and cerebrovascular disease are often comorbid conditions, but the relationship between amyloid-β and in vivo vascular pathophysiology is poorly understood. We utilized a multimodal, multiscale optical imaging approach, including spatial frequency domain imaging, Doppler optical coherence tomography, and confocal microscopy, to quantify AD-dependent changes in a triple transgenic mouse model (3xTg-AD) and age-matched controls. From three months of age (naïve) to 20 months (severe AD), the brain tissue concentration of total and oxy-hemoglobin (Total Hb, ctO2Hb) decreased 50 and 70%, respectively, in 3xTg-AD mice. Compared to age-matched controls, significant differences in brain hemoglobin concentrations occurred as early as eight months (Total Hb: 126 ± 5 μM versus 108 ± 4 μM; ctO2Hb: 86 ± 5 μM versus 70 ± 3 μM; for control and AD, respectively). These changes were linked to a 29% vascular volume fraction decrease and 35% vessel density reduction in the 20-month-old 3xTg-AD versus age-matched controls. Vascular reduction coincided with increased brain concentration of amyloid-β protein, vascular endothelial growth factor (VEGF), and endothelial nitric oxide synthase (eNOS) at eight and 20 months compared to the three-month baseline. Our results suggest that amyloid-β blocks the normally reparative effects of upregulated VEGF and eNOS, and may accelerate in vivo vascular pathophysiology in AD