li, q. | bioRxiv Science

bioRxiv2025

A new nitrogen biochemical process: Oxidization of ammonium into nitrogen gas using nitrate

The nitrifying bacteria oxidize ammonium into nitrite or nitrate under aerobic conditions, while the anaerobic ammonia-oxidizing bacteria utilize nitrite to oxidize ammonium into nitrogen gas under anaerobic conditions. There is no biochemical process that can directly oxidize ammonium into nitrogen gas using nitrate under anaerobic conditions. In this study, mature anaerobic ammonium oxidation (anammox) granular sludge was inoculated in an anaerobic nitrogen-removal system, while nitrate and ammonium were used as the influent substrates. The experiment was conducted for 537 days at a temperature of 30-32{degrees}C and a pH of 8.0-9.0. The transformation from nitrite-anammox to nitrate-anammox was stably achieved on the 350th day. The experimental results showed that, nitrate directly oxidized ammonium into nitrogen gas under anaerobic conditions. The produced gas consisted of 96.3% nitrogen and 3.7% carbon dioxide. The removal ratio of ammonium to nitrate was approximately 1.67:1, and the total inorganic nitrogen removal rate reached up to 290.20 mg/(L{middle dot}d). Unlike the nitrite-anammox reaction, this reaction was accompanied by an acid production process, which caused a decrease in pH. When the substrate was changed to nitrite and ammonium, the total nitrogen removal rate of only 1.1-1.3 mg/(L{middle dot}d) was achieved. This new biochemical reaction of nitrogen was defined as nitrate-anammox. The study reveals a new pathway of nitrogen transformation, providing novel insights into the global nitrogen cycle.

microbiology↗

bioRxiv2024

A Novel Computational Pre-Procedural Planning Model for Coronary Interventions Based on Coronary CT Angiography

In percutaneous coronary intervention (PCI), the ability to predict post-PCI fractional flow reserve (FFR) and stented vessel informs procedural planning. However, highly precise and effective methods to quantitatively simulate coronary intervention are lacking. This study developed a validated virtual coronary intervention (VCI) technique for non-invasive physiological and anatomical assessment of PCI. In this study, patients with substantial lesions (pre-PCI FFR of less than 0.80) were enrolled. VCI framework was used to predict vessel reshape and post-PCI FFR. The accuracy of predicted post-VCI FFR, luminal cross-sectional area (CSA) and centreline curvature was validated with post-PCI computed tomography (CT) angiography datasets. Overall, 21 patients were selected for the study, of which 9 patients (9 vessels) were included in the analysis. The average time for PCI simulation was 24.92 {+/-} 1.00 s on a single processor. The calculated post-PCI FFR was 0.92 {+/-} 0.09 and the predicted post-VCI FFR was 0.90 {+/-} 0.08 (mean difference: -0.02 {+/-} 0.05 FFR unit; limits of agreement: -0.08 to 0.05). Morphologically, the predicted CSA is 16.36 {+/-} 4.41 mm2 and post-CSA is 17.91 {+/-} 4.84 mm2 (mean difference: -1.55 {+/-} 1.89 mm2; limits of agreement: -5.22 to 2.12), the predicted centreline curvature of stented region is 0.15 {+/-} 0.04 mm{square}1 and post-PCI centreline curvature is 0.17 {+/-} 0.03 mm{square}1 (mean difference: -0.02 {+/-} 0.06 mm{square}1; limits of agreement: -0.12 to 0.09). The proposed VCI technique achieves non-invasive pre-procedural anatomical and physiological assessment of coronary intervention. The proposed model has the potential to optimize PCI pre-procedural planning and improve the safety and efficiency of PCI. HighlightsO_LIPresent a computational pre-procedural planning model for coronary interventions. C_LIO_LIDevelop a computational framework to predict post-PCI FFR. C_LIO_LIValidation of the model with post-PCI CT angiography datasets. C_LIO_LIThe proposed model has the potential to optimize PCI pre-procedural planning. C_LI

bioengineering↗