Using machine learning algorithms based on patient admission laboratory parameters to predict adverse outcomes in COVID-19 patients.

Amidst the global COVID-19 pandemic, the urgent need for timely and precise patient prognosis assessment underscores the significance of leveraging machine learning techniques. In this study, we present a novel predictive model centered on routine clinical laboratory test data to swiftly forecast patient survival outcomes upon admission. Our model integrates feature selection algorithms and binary classification algorithms, optimizing algorithmic selection through meticulous parameter control. Notably, we developed an algorithm coupling Lasso and SVM methodologies, achieving a remarkable area under the ROC curve of 0.9277 with the use of merely 8 clinical laboratory parameters collected upon admission. Our primary contribution lies in the utilization of straightforward laboratory parameters for prognostication, circumventing data processing intricacies, and furnishing clinicians with an expeditious and precise prognostic assessment tool.

Initial Oxidation Behavior of AlCoCrFeNi High-Entropy Coating Produced by Atmospheric Plasma Spraying in the Range of 650 °C to 1000 °C.

As protective coatings for the thermal parts of aero-engines, AlCoCrFeNi coatings have good application prospects. In this study, atmospheric plasma spraying (APS) was used to prepare AlCoCrFeNi high-entropy coatings (HECs), which were oxidized from 650 °C to 1000 °C. The mechanism of the oxide layer formation and the internal phase transition were systematically investigated. The results show that a mixed oxide scale with a laminated structure was formed at the initial stage of oxidation. The redistribution of elements and phase transition occurred in the HECs' matrix; the BCC/B2 structure transformed to Al-Ni ordered B2 phase and Fe-Cr disordered A2 phase.

Adenosine Deaminase as a Potential Diagnostic and Prognostic Biomarker for Severe Fever with Thrombocytopenia Syndrome.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease caused by the Dabie bandavirus, with a high mortality rate. Currently, there are no effective vaccines or specific treatments for SFTS. Early diagnosis and accurate severity assessment are crucial. METHODS: This study included 171 cases of SFTS, COVID-19, and hepatitis B virus (HBV) patients and healthy controls. We compared the serum adenosine deaminase (ADA) activity across these groups. The diagnostic and prognostic efficiency of serum ADA for SFTS was evaluated by using receiver operating characteristic (ROC) curve analysis. We also examined the correlation between serum ADA in SFTS patients and clinical lab parameters as well as serum cytokines. RESULTS: SFTS patients had significantly higher serum ADA activity than those of COVID-19, HBV patients, and healthy controls. Nonsurvivor SFTS patients had notably higher ADA than survivors. ROC analysis indicated ADA as an effective SFTS diagnostic and prognostic biomarker. ADA correlated with prognosis, viral load, APTT, PT, AST, ferritin, negatively with HDL-c and LDL-c, and positively with cytokines like IL-6, TNF-α, and IL-1ß. Multiorgan failure patients showed significant ADA increase. CONCLUSION: Elevated serum ADA activity in SFTS patients is linked with disease severity and prognosis, showing potential as a diagnostic and prognostic biomarker for SFTS.

Association of low HDL-c levels with severe symptoms and poor clinical prognosis in patients with severe fever and thrombocytopenia syndrome.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by a novel bunyavirus, characterized by high fever, thrombocytopenia, and multiple organ damage. Disturbances in lipid metabolism often occur during viral infections, but the changes and clinical significance of lipid profiles in SFTS patients remain unclear. This study aimed to investigate the alterations in lipid profiles and their clinical significance in SFTS patients. Methods: A total of 157 SFTS patients and 157 healthy controls were enrolled in this study. Serum lipid levels were collected and analyzed among different groups and prognosis categories. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of lipid levels in distinguishing between severe and mild cases, as well as surviving and non-surviving patients. Pearson correlation analysis was used to examine the associations between lipid levels and clinical laboratory parameters. Results: SFTS patients exhibited significantly lower levels of HDL-c, LDL-c, cholesterol, APoAI, and ApoB compared to healthy controls, while triglyceride levels were significantly higher. Serum HDL-c and ApoAI demonstrated good performance as indicators for distinguishing between survivors and non-survivors (AUC of 0.87 and 0.85, respectively). Multivariate regression analysis indicated that HDL-c independently acts as a protective factor in patients with SFTS. HDL-c levels showed decline in non-survivors but recovered in survivors. Moreover, HDL-c exhibited significant correlations with various clinical laboratory parameters (IL-6, CRP, AST, TT, APTT, PLT, ALB, and CD4). Conclusion: This study identified abnormalities in serum lipid metabolism among SFTS patients. HDL-c and ApoAI levels hold potential as biomarkers for distinguishing survivors from non-survivors. Additionally, HDL-c and ApoAI may serve as therapeutic targets for the management of SFTS patients.

Investigations on Oxidation Behavior of Free-Standing CoNiCrAlYHf Coating with Different Surface Roughness at 1050 °C.

MCrAlYHf bond coats are employed in jet and aircraft engines, stationary gas turbines, and power plants, which require strong resistance to oxidation at high temperatures. This study investigated the oxidation behavior of a free-standing CoNiCrAlYHf coating with varying surface roughness. The surface roughness was analyzed using a contact profilometer and SEM. Oxidation tests were conducted in an air furnace at 1050 °C to examine the oxidation kinetics. X-ray diffraction, focused ion beam, scanning electron microscopy, and scanning transmission electron microscopy were employed to characterize the surface oxides. The results show that the sample with Ra = 0.130 µm demonstrates better oxidation resistance compared to Ra = 7.572 µm and other surfaces with higher roughness in this study. Reducing surface roughness led to a decrease in the thickness of oxide scales, while the smoothest surface exhibited increased growth of internal HfO2. The ß-phase on the surface with Ra = 130 µm demonstrated faster growth of Al2O3 compared to the γ-phase. An empirical model was suggested to explain the impact of surface roughness on oxidation behavior based on the correlation between the surface roughness level and oxidation rates.

Effects of Stepped Heating on the Initial Growth of Oxide Scales on NiCrAlHf Bond Coat Alloy under Air and Water Vapor Atmospheres.

Temperature and atmosphere have a significant effect on the oxidation of MCrAlY (M = Ni, Co) bond coating. The initial growth behavior of the NiCrAlHf bond coat alloy was investigated at 1100 °C under different atmospheric conditions and using heating methods. A thick Al2O3 oxide layer and large HfO2 particles were observed, perhaps due to metastable oxide growth at low temperatures when using stepped heating. However, in air and water vapor atmospheres, the oxide scale was thinner and the HfO2 precipitates were smaller in stepped heating than in constant heating. The size and distribution of the HfO2 particles might have induced different microstructures, particularly voids within the oxide scale.

Correlative Atom Probe Tomography and Transmission Electron Microscopy Analysis of Grain Boundaries in Thermally Grown Alumina Scale.

We employed correlative atom probe tomography (APT) and transmission electron microscopy (TEM) to analyze the alumina scale thermally grown on the oxide dispersion-strengthened alloy MA956. Segregation of Ti and Y and associated variation in metal/oxygen stoichiometry at the grain boundaries and triple junctions of alumina were quantified and discussed with respect to the oxidation behavior of the alloy, in particular, to the formation of cation vacancies. Correlative TEM analysis was helpful to avoid building pragmatically well-looking but substantially incorrect APT reconstructions, which can result in erroneous quantification of segregating species, and highlights the need to consider ionic volumes and detection efficiency in the reconstruction routine. We also demonstrate a cost-efficient, robust, and easy-handling setup for correlative analysis based solely on commercially available components, which can be used with all conventional TEM tools without the need to modify the specimen holder assembly.