Temporal compressive edge imaging enabled by a lensless diffuser camera.

Lensless imagers based on diffusers or encoding masks enable high-dimensional imaging from a single-shot measurement and have been applied in various applications. However, to further extract image information such as edge detection, conventional post-processing filtering operations are needed after the reconstruction of the original object images in the diffuser imaging systems. Here, we present the concept of a temporal compressive edge detection method based on a lensless diffuser camera, which can directly recover a time sequence of edge images of a moving object from a single-shot measurement, without further post-processing steps. Our approach provides higher image quality during edge detection, compared with the "conventional post-processing method." We demonstrate the effectiveness of this approach by both numerical simulation and experiments. The proof-of-concept approach can be further developed with other image post-processing operations or versatile computer vision assignments toward task-oriented intelligent lensless imaging systems.

Structural Flexibility and Disassembly Kinetics of Single Ferritin Molecules Using Optical Nanotweezers.

Ferritin, a spherical protein shell assembled from 24 subunits, functions as an efficient iron storage and release system through its channels. Understanding how various chemicals affect the structural behavior of ferritin is crucial for unravelling the origins of iron-related diseases in living organisms including humans. In particular, the influence of chemicals on ferritin's dynamics and iron release is barely explored at the single-protein level. Here, by employing optical nanotweezers using double-nanohole (DNH) structures, we examined the effect of ascorbic acid (reducing reagent) and pH on individual ferritin's conformational dynamics. The dynamics of ferritin increased as the concentration of ascorbic acid approached saturation. At pH 2.0, ferritin exhibited significant structural fluctuations and eventually underwent a stepwise disassembly into fragments. This work demonstrated the disassembly pathway and kinetics of a single ferritin molecule in solution. We identified four critical fragments during its disassembly pathway, which are 22-mer, 12-mer, tetramer, and dimer subunits. Moreover, we present single-molecule evidence of the cooperative disassembly of ferritin. Interrogating ferritin's structural change in response to different chemicals holds importance for understanding their roles in iron metabolism, hence facilitating further development of medical treatments for its associated diseases.

Role of deubiquitinase USP47 in cardiac function alleviation and anti-inflammatory immunity after myocardial infarction by regulating NLRP3 inflammasome-mediated pyroptotic signal pathways.

Myocardial infarction (MI) is an event of heart attack due to the formation of plaques in the interior walls of the arteries. This study is conducted to explore the role of ubiquitin-specific peptidase 47 (USP47) in cardiac function and inflammatory immunity. MI mouse models were established, followed by an appraisal of cardiac functions, infarct size, pathological changes, and USP47 and NLRP3 levels. MI cell models were established in HL-1 cells using anoxia. Levels of cardiac function-associated proteins, USP7, interferon regulatory factor 1 (IRF1), platelet factor-4 (CXCL4), pyroptotic factors, and neutrophil extracellular traps (NETs) were determined. The bindings of IRF1 to USP47 and the CXCL4 promoter and the ubiquitination of IRF1 were analyzed. USP47 was upregulated in myocardial tissues of MI mice. USP47 inhibition alleviated cardiac functions, and decreased infarct size, pro-inflammatory cytokines, NETs, NLRP3, and pyroptosis. The ubiquitination and expression levels of IRF1 were increased by silencing USP47, and IRF1 bound to the CXCL4 promoter to promote CXCL4. Overexpression of IRF1 or CXCL4 in vitro and injection of Nigericin in vivo reversed the effect of silencing USP47 on alleviating pyroptosis and cardiac functions. Collectively, USP47 stabilized IRF1 and promoted CXCL4, further promoting pyroptosis, impairing cardiac functions, and aggravating immune inflammation through NLRP3 pathways.

Connecting impaired fibrinolysis and dyslipidemia.

A State of the Art lecture entitled "Connecting Fibrinolysis and Dyslipidemia" was presented at the International Society on Thrombosis and Haemostasis Congress 2023. Hemostasis balances the consequences of blood clotting and bleeding. This balance relies on the proper formation of blood clots, as well as the breakdown of blood clots. The primary mechanism that breaks down blood clots is fibrinolysis, where the fibrin net becomes lysed and the blood clot dissolves. Dyslipidemia is a condition where blood lipid and lipoprotein levels are abnormal. Here, we review studies that observed connections between impaired fibrinolysis and dyslipidemia. We also summarize the different correlations between thrombosis and dyslipidemia in different racial and ethnic groups. Finally, we summarize relevant and new findings on this topic presented during the 2023 International Society on Thrombosis and Haemostasis Congress. More studies are needed to investigate the mechanistic connections between impaired fibrinolysis and dyslipidemia and whether these mechanisms differ in racially and ethnically diverse populations.

Highly Permeable and Regenerative Microhoneycomb Filters.

Allergic reactions can profoundly influence the quality of life. To address the health risks posed by allergens and overcome the permeability limitations of the current filter materials, this work introduces a novel microhoneycomb (MH) material for practical filter applications such as masks. Through a synthesis process integrating ice-templating and a gas-phase post-treatment with silane, MH achieves unprecedented levels of moisture resistance and mechanical stability while preserving the highly permeable microchannels. Notably, MH is extremely elastic, with a 92% recovery rate after being compressed to 80% deformation. The filtration efficiency surpasses 98.1% against pollutant particles that simulate airborne pollens, outperforming commercial counterparts with fifth-fold greater air permeability while ensuring unparalleled user comfort. Moreover, MH offers a sustainable solution, being easily regenerated through back-flow blowing, distinguishing it from conventional nonwoven fabrics. Finally, a prototype mask incorporating MH is presented, demonstrating its immense potential as a high-performance filtration material, effectively addressing health risks posed by allergens and other harmful particles.

Efficacy of revascularization in CTO patients based on hibernating myocardium therapy.

BACKGROUND: The effectiveness of percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) is still uncertain, especially for patients with ischemic left ventricular dysfunction. This study aimed to assess hibernating myocardium (HM), as determined by single-photon emission computed tomography (SPECT) and 18F-FDG positron emission tomography (PET), and to compare the benefits of PCI and optimal medical therapy (OMT). METHODS: A retrospective study collected data from 332 patients with CTO and ischemic left ventricular dysfunction. The study compared patients who underwent PCI or OMT via propensity score matching (PSM) analysis which was performed with a 1:2 matching protocol using the nearest neighbour matching algorithm. The primary endpoint of the study was the occurrence of major adverse cardiac events (MACE), defined as a composite of cardiac death, readmission for worsening heart failure (WHF), revascularization and myocardial infarction (MI). RESULTS: After PSM, there were a total of 246 individuals in the PCI and OMT groups. Following Cox regression, hibernating myocardium/total perfusion defect (HM/TPD) was identified as an independent risk factor (hazard ratio (HR): 1.03, 95% confidence interval (CI): 1.008-1.052, p = .007). The cut-off value of HM/TPD was 38%. The results of the subgroup analysis suggest that for patients with HM/TPD >38%, the OMT group had a greater risk of MACE (p = .035). A sensitivity analysis restricting patients with single-vessel CTO lesions, HM/TPD remained an independent predictor (HR 1.025, 95% CI 1.008-1.043, p = .005). CONCLUSION: HM/TPD is an independent predictor of MACE, and for patients with HM/TPD > 38%, CTO-PCI had a lower risk of MACE compared with OMT. However, further validation is still needed through large-scale studies.

Ag-Catalyzed Switchable Synthesis of Site-Specifically Functionalized Pyrroles via Azafulvenium Intermediates.

Here, we present a versatile, silver-catalyzed multi-auto-tandem reaction involving enamines, alkynals, and nucleophiles, utilizing the highly reactive intermediate azafulvenium. This method allows for flexible and switchable regiodivergent reactions through either intermolecular or intramolecular nucleophilic attacks, which can be controlled by adjusting the catalytic conditions. A range of site-specific functionalized or polycyclic fused pyrrole products were efficiently produced with a high level of chemocontrol.

Development and validation of a predicting nomogram for in-hospital mortality of COVID-19 Omicron variant: A cohort study of 1324 cases in Beijing Anzhen Hospital.

Coronavirus disease 2019 (COVID-19) is continuously posing high global public health concerns due to its high morbidity and mortality. This study aimed to construct a convenient risk model for predicting in-hospital mortality of COVID-19 Omicron variant. A total of 1324 hospitalized patients with Omicron variant were enrolled from Beijing Anzhen Hospital. During hospitalization, the Omicron variant mortality rate was found to be 24.4%. Using the datasets of clinical demographics and laboratory tests, three machine learning algorithms, including best subset selection, stepwise selection, and least absolute shrinkage and selection operator regression analyses were employed to identify the potential predictors of in-hospital mortality. The results found that a panel of twenty-four clinical variables (including age, hyperlipemia, stroke, tumor, and several cardiovascular markers) identified by stepwise selection model exhibited significant performances in predicting the in-hospital mortality of COVID-19. The resultant nomogram showed good discrimination, highlighted by the areas under the curve values of 0.88 for 10 days, 0.81 for 20 days, and 0.82 for 30 days, respectively. Furthermore, decision curve analysis showed a significant reliability and precision for the established stepwise selection model. Collectively, this study developed an accurate and convenience risk model for predicting the in-hospital mortality of COVID-19 Omicron.

Association Between Red Blood Cell Distribution Width and Coronary Calcification in Patients Referred for Invasive Coronary Angiography.

This study aimed to determine whether red cell distribution width (RDW) is associated with coronary calcification. A total of 4796 patients who underwent coronary computed tomography angiography and subsequent invasive coronary angiography were consecutively enrolled. Coronary artery calcium score (CACS), demographic, clinical, and laboratory data were collected from electronic medical records. RDW were expressed in two forms, as a coefficient of variation (CV) or as a standard deviation (SD). Multivariable ordinal logistic regression was used to investigate the association of RDW with CACS grades (CACS 0-99, 100-399, 400-999, and >1000). A significant association was found between elevated RDW-SD and higher CACS grades after full adjustment (adjusted OR per 1-SD increase: 1.11, 95% CI: 1.05-1.18; P < .001), while no significant association was found between RDW-CV and CACS grades. When RDW-SD was analyzed as a categorical variable, it was primarily the 4th quartile of RDW-SD that was associated with elevated CACS grades compared with the 1st quartile (adjusted OR: 1.25, 95% CI: 1.07-1.46; P = .006), while the 2nd and 3rd quartiles showed no significantly higher risk. RDW-SD is a more robust biomarker for coronary calcification compared with RDW-CV.

Facile Fabrication of Hollow Nanoporous Carbon Architectures by Controlling MOF Crystalline Inhomogeneity for Ultra-Stable Na-Ion Storage.

Hollow nanoporous carbon architectures (HNCs) present significant utilitarian value for a wide variety of applications. Facile and efficient preparation of HNCs has long been pursued but still remains challenging. Herein, we for the first time demonstrate that single-component metal-organic frameworks (MOFs) crystals, rather than the widely reported hybrid ones which necessitate tedious operations for preparation, could enable the facile and versatile syntheses of functional HNCs. By controlling the growth kinetics, the MOFs crystals (STU-1) are readily engineered into different shapes with designated styles of crystalline inhomogeneity. A subsequent one-step pyrolysis of these MOFs with intraparticle difference can induce a simultaneous self-hollowing and carbonization process, thereby producing various functional HNCs including yolk-shell polyhedrons, hollow microspheres, mesoporous architectures, and superstructures. Superior to the existing methods, this synthetic strategy relies only on the complex nature of single-component MOFs crystals without involving tedious operations like coating, etching, or ligand exchange, making it convenient, efficient, and easy to scale up. An ultra-stable Na-ion battery anode is demonstrated by the HNCs with extraordinary cyclability (93 % capacity retention over 8000 cycles), highlighting a high level of functionality of the HNCs.

Unfolded Von Willebrand Factor Binds Protein S and Reduces Anticoagulant Activity.

Protein S (PS), the critical plasma cofactor for the anticoagulants tissue factor (TF) pathway inhibitor (TFPI) and activated protein C (APC), circulates in two functionally distinct pools: free (anticoagulant) or bound to complement component 4b-binding protein (C4BP) (anti-inflammatory). Acquired free PS deficiency is detected in several viral infections, but its cause is unclear. Here, we identified a shear-dependent interaction between PS and von Willebrand Factor (VWF) by mass spectrometry. Consistently, plasma PS and VWF comigrated in both native and agarose gel electrophoresis. The PS/VWF interaction was blocked by TFPI but not APC, suggesting an interaction with the C-terminal sex hormone binding globulin (SHBG) region of PS. Microfluidic systems, mimicking arterial laminar flow or disrupted turbulent flow, demonstrated that PS stably binds VWF as VWF unfolds under turbulent flow. PS/VWF complexes also localized to platelet thrombi under laminar arterial flow. In thrombin generation-based assays, shearing plasma decreased PS activity, an effect not seen in the absence of VWF. Finally, free PS deficiency in COVID-19 patients, measured using an antibody that binds near the C4BP binding site in SHBG, correlated with changes in VWF, but not C4BP, and with thrombin generation. Our data suggest that PS binds to a shear-exposed site on VWF, thus sequestering free PS and decreasing its anticoagulant activity, which would account for the increased thrombin generation potential. As many viral infections present with free PS deficiency, elevated circulating VWF, and increased vascular shear, we propose that the PS/VWF interaction reported here is a likely contributor to virus-associated thrombotic risk.

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography.

OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance. METHODS: This retrospective study enrolled patients who underwent coronary CT angiography and subsequent invasive coronary angiography. Multiple ML algorithms were used to train the models for predicting severe coronary calcification (cardiac CT-measured coronary artery calcium [CT-CAC] score ≥ 400). The ML-based CAC (ML-CAC) score derived from the ML predictive probability was stratified into quartiles for prognostic analysis. The primary endpoint was a composite of all-cause death, nonfatal myocardial infarction, or nonfatal stroke. RESULTS: Overall, 5785 patients were divided into training (80%) and test sets (20%). For clinical practicability, we selected the nine-feature support vector machine model with good and satisfactory performance regarding both discrimination and calibration based on five repetitions of the 10-fold cross-validation in the training set (mean AUC = 0.715, Brier score = 0.202), and based on the test in the test set (AUC = 0.753, Brier score = 0.191). In the test set cohort (n = 1137), the primary endpoint was observed in 50 (4.4%) patients during a median 2.8 years' follow-up. The ML-CAC system was significantly associated with an increased risk of the primary endpoint (adjusted hazard ratio for trend 2.26, 95% CI 1.35-3.79, p = 0.002). There was no significant difference in the prognostic value between the ML-CAC and CT-CAC systems (C-index, 0.67 vs. 0.69; p = 0.618). CONCLUSION: ML-CAC score predicted from clinical variables can serve as a novel prognostic indicator in patients referred for invasive coronary angiography. CLINICAL RELEVANCE STATEMENT: In patients referred for invasive coronary angiography who have not undergone preoperative CT-measured coronary artery calcium scoring, machine learning-based coronary artery calcium score assessment can serve as an alternative for predicting the prognosis. KEY POINTS: • The coronary artery calcium (CAC) score, a solid prognostic indicator, can be predicted using non-CT methods. • We developed a machine learning (ML)-CAC model utilising nine clinical variables to predict severe coronary calcification. • The ML-CAC system offers significant prognostic value in patients referred for invasive coronary angiography.

Clot or Not? Reviewing the Reciprocal Regulation Between Lipids and Blood Clotting.

Both hyperlipidemia and thrombosis contribute to the risks of atherosclerotic cardiovascular diseases, which are the leading cause of death and reduced quality of life in survivors worldwide. The accumulation of lipid-rich plaques on arterial walls eventually leads to the rupture or erosion of vulnerable lesions, triggering excessive blood clotting and leading to adverse thrombotic events. Lipoproteins are highly dynamic particles that circulate in blood, carry insoluble lipids, and are associated with proteins, many of which are involved in blood clotting. A growing body of evidence suggests a reciprocal regulatory relationship between blood clotting and lipid metabolism. In this review article, we summarize the observations that lipoproteins and lipids impact the hemostatic system, and the clotting-related proteins influence lipid metabolism. We also highlight the gaps that need to be filled in this area of research.

Appropriate time for ejection fraction reassessment after revascularization in patients with left ventricular dysfunction for risk stratification of sudden cardiac death.

BACKGROUND: Appropriate time for ejection fraction (EF) reassessment after revascularization in patients with left ventricular dysfunction has not been investigated comprehensively, although 3 months after revascularization is recommended to stratify the risk of sudden cardiac death (SCD). HYPOTHESIS: EF reassessed within different timeframe after revascularization may have incosistent contribution for risk stratification of SCD. METHODS: Patients who had EF ≤ 40% before revascularization and had EF reassessment at least once during follow-up were included. The role of early (<3 months) versus late (3-12 months) EF measurements in prediction of all-cause mortality and SCD were compared. RESULTS: A total of 1589 patients were identified. EF reassessed <3 months was lower than EF reassessed within 3-12 months (42.1 ± 9.7% vs. 45.8 ± 10.8%; p < .01). Among 1069 patients who had EF reassessed <3 months, EF ≤ 35% was associated with a higher risk of all-cause mortality (hazard ratio [HR], 1.67; 95% confidence interval [CI], 1.22-2.29; p < .01), but had no association with the risk of SCD (HR, 1.44; 95% CI, 0.84-2.48; p = .18). By contrast, among 595 patients who had EF reassessed within 3-12 months, EF ≤ 35% was associated with higher risks of both all-cause death (HR, 1.81; 95% CI, 1.06-3.10; p = .03) and SCD (HR, 2.71; 95% CI, 1.31-5.61; p < .01). The relative contribution of SCD to all-cause death was higher in patients with EF ≤ 35% than patients with EF > 35% when EF was reassessed within 3-12 months (p = .04). However, when EF was reassessed <3 months, the mode of death was similar in patients with EF ≤ 35% versus >35% (p = .85). CONCLUSIONS: 3 to 12 months after revascularization may be appropriate for cardiac function reassessment and SCD risk stratification.

Interaction between top-down decision-driven congruency effect and bottom-up input-driven congruency effect is correlated with conscious awareness.

In a conventional (Stroop) priming paradigm, it was well documented that objective prime-target incongruency delays response time (RT) to target compared to prime-target congruent condition. Recent evidence suggests that incongruency between the target and subjectively reported prime identity also delays RT over and above the classic congruency effect. When the prime is rendered invisible, the former effect is fundamentally a bottom-up (BU) stimulus-driven congruency effect and the latter a top-down (TD) guess-driven congruency effect. An influential theory of consciousness, global neuronal workspace theory, postulates that the long-lasting simultaneous and reciprocal interaction between TD decision network and BU input network is preserved during conscious processing and disabled during unconscious processing. Current study is focused on testing this theoretical postulation using two behavioral experiments. Our results showed that indeed TD-congruency and BU-congruency produced additive RT effects on prime-invisible trials, which implies that TD and BU prime representations are activated in independent neuronal populations. Meanwhile, an underadditive interaction effect was observed as prime visibility rose, which is a signature that TD and BU prime representations recruited overlapping neuronal populations during conscious perception. In addition, we suggest that current behavioral paradigm might be a financially friendly alternative to detect the presence of representational overlap in the brain between a wide range of mental representations, such as expectation, prediction, conscious/unconscious perception, and conscious/unconscious working memory. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Loss of Nrf1 rather than Nrf2 leads to inflammatory accumulation of lipids and reactive oxygen species in human hepatoma cells, which is alleviated by 2-bromopalmitate.

Since Nrf1 and Nrf2 are essential for regulating the lipid metabolism pathways, their dysregulation has thus been shown to be critically involved in the non-controllable inflammatory transformation into cancer. Herein, we have explored the molecular mechanisms underlying their distinct regulation of lipid metabolism, by comparatively analyzing the changes in those lipid metabolism-related genes in Nrf1α-/- and/or Nrf2-/- cell lines relative to wild-type controls. The results revealed that loss of Nrf1α leads to lipid metabolism disorders. That is, its lipid synthesis pathway was up-regulated by the JNK-Nrf2-AP1 signaling, while its lipid decomposition pathway was down-regulated by the nuclear receptor PPAR-PGC1 signaling, thereby resulting in severe accumulation of lipids as deposited in lipid droplets. By contrast, knockout of Nrf2 gave rise to decreases in lipid synthesis and uptake capacity. These demonstrate that Nrf1 and Nrf2 contribute to significant differences in the cellular lipid metabolism profiles and relevant pathological responses. Further experimental evidence unraveled that lipid deposition in Nrf1α-/- cells resulted from CD36 up-regulation by activating the PI3K-AKT-mTOR pathway, leading to abnormal activation of the inflammatory response. This was also accompanied by a series of adverse consequences, e.g., accumulation of reactive oxygen species (ROS) in Nrf1α-/- cells. Interestingly, treatment of Nrf1α-/- cells with 2-bromopalmitate (2BP) enabled the yield of lipid droplets to be strikingly alleviated, as accompanied by substantial abolishment of CD36 and critical inflammatory cytokines. Such Nrf1α-/- -led inflammatory accumulation of lipids, as well as ROS, was significantly ameliorated by 2BP. Overall, this study provides a potential strategy for cancer prevention and treatment by precision targeting of Nrf1, Nrf2 alone or both.

Silicon Radical-Induced CH4 Dissociation for Uniform Graphene Coating on Silica Surface.

Due to the manufacturability of highly well-defined structures and wide-range versatility in its microstructure, SiO2 is an attractive template for synthesizing graphene frameworks with the desired pore structure. However, its intrinsic inertness constrains the graphene formation via methane chemical vapor deposition. This work overcomes this challenge by successfully achieving uniform graphene coating on a trimethylsilyl-modified SiO2 (denote TMS-MPS). Remarkably, the onset temperature for graphene growth dropped to 720 °C for the TMS-MPS, as compared to the 885 °C of the pristine SiO2. This is found to be mainly from the Si radicals formed from the decomposition of the surface TMS groups. Both experimental and computational results suggest a strong catalytic effect of the Si radicals on the CH4 dissociation. The surface engineering of SiO2 templates facilitates the synthesis of high-quality graphene sheets. As a result, the graphene-coated SiO2 composite exhibits a high electrical conductivity of 0.25 S cm-1. Moreover, the removal of the TMP-MPS template has released a graphene framework that replicates the parental TMS-MPS template on both micro- and nano- scales. This study provides tremendous insights into graphene growth chemistries as well as establishes a promising methodology for synthesizing graphene-based materials with pre-designed microstructures and porosity.

Prominent Structural Dependence of Quantum Capacitance Unraveled by Nitrogen-Doped Graphene Mesosponge.

Porous carbons are important electrode materials for supercapacitors. One of the challenges associated with supercapacitors is improving their energy density without relying on pseudocapacitance, which is based on fast redox reactions that often shorten device lifetimes. A possible solution involves achieving high total capacitance (Ctot ), which comprises Helmholtz capacitance (CH ) and possibly quantum capacitance (CQ ), in high-surface carbon materials comprising minimally stacked graphene walls. In this work, a templating method is used to synthesize 3D mesoporous graphenes with largely identical pore structures (≈2100 m2 g-1 with an average pore size of ≈7 nm) but different concentrations of oxygen-containing functional groups (0.3-6.7 wt.%) and nitrogen dopants (0.1-4.5 wt.%). Thus, the impact of the heteroatom functionalities on Ctot is systematically investigated in an organic electrolyte excluding the effect of pore structures. It is found that heteroatom functionalities determine Ctot , resulting in the cyclic voltammetry curves being rectangular or butterfly-shaped. The nitrogen functionalities are found to significantly enhance Ctot owing to increased CQ .

Plasma tissue-type plasminogen activator is associated with lipoprotein(a) and clinical outcomes in hospitalized patients with COVID-19.

Background: Patients with COVID-19 have a higher risk of thrombosis and thromboembolism, but the underlying mechanism(s) remain to be fully elucidated. In patients with COVID-19, high lipoprotein(a) (Lp(a)) is positively associated with the risk of ischemic heart disease. Lp(a), composed of an apoB-containing particle and apolipoprotein(a) (apo(a)), inhibits the key fibrinolytic enzyme, tissue-type plasminogen activator (tPA). However, whether the higher Lp(a) associates with lower tPA activity, the longitudinal changes of these parameters in hospitalized patients with COVID-19, and their correlation with clinical outcomes are unknown. Objectives: To assess if Lp(a) associates with lower tPA activity in COVID-19 patients, and how in COVID-19 populations Lp(a) and tPA change post infection. Methods: Endogenous tPA enzymatic activity, tPA or Lp(a) concentration were measured in plasma from hospitalized patients with and without COVID-19. The association between plasma tPA and adverse clinical outcomes was assessed. Results: In hospitalized patients with COVID-19, we found lower tPA enzymatic activity and higher plasma Lp(a) than that in non-COVID-19 controls. During hospitalization, Lp(a) increased and tPA activity decreased, which associates with mortality. Among those who survived, Lp(a) decreased and tPA enzymatic activity increased during recovery. In patients with COVID-19, tPA activity is inversely correlated with tPA concentrations, thus, in another larger COVID-19 cohort, we utilized plasma tPA concentration as a surrogate to inversely reflect tPA activity. The tPA concentration was positively associated with death, disease severity, plasma inflammatory, and prothrombotic markers, and with length of hospitalization among those who were discharged. Conclusion: High Lp(a) concentration provides a possible explanation for low endogenous tPA enzymatic activity, and poor clinical outcomes in patients with COVID-19.

Development and validation of a predicted nomogram for mortality of COVID-19: a multicenter retrospective cohort study of 4,711 cases in multiethnic.

Background: Coronavirus disease 2019 (COVID-19) is an infectious disease spreading rapidly worldwide. As it quickly spreads and can cause severe disease, early detection and treatment may reduce mortality. Therefore, the study aims to construct a risk model and a nomogram for predicting the mortality of COVID-19. Methods: The original data of this study were from the article "Neurologic Syndromes Predict Higher In-Hospital Mortality in COVID-19." The database contained 4,711 multiethnic patients. In this secondary analysis, a statistical difference test was conducted for clinical demographics, clinical characteristics, and laboratory indexes. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were applied to determine the independent predictors for the mortality of COVID-19. A nomogram was conducted and validated according to the independent predictors. The area under the curve (AUC), the calibration curve, and the decision curve analysis (DCA) were carried out to evaluate the nomogram. Results: The mortality of COVID-19 is 24.4%. LASSO and multivariate logistic regression analysis suggested that risk factors for age, PCT, glucose, D-dimer, CRP, troponin, BUN, LOS, MAP, AST, temperature, O2Sats, platelets, Asian, and stroke were independent predictors of CTO. Using these independent predictors, a nomogram was constructed with good discrimination (0.860 in the C index) and internal validation (0.8479 in the C index), respectively. The calibration curves and the DCA showed a high degree of reliability and precision for this clinical prediction model. Conclusion: An early warning model based on accessible variates from routine clinical tests to predict the mortality of COVID-19 were conducted. This nomogram can be conveniently used to facilitate identifying patients who might develop severe disease at an early stage of COVID-19. Further studies are warranted to validate the prognostic ability of the nomogram.