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.

The Role of Clot Waveform Analysis and Related Parameters in the Diagnosis and Treatment of Hemophilia A.

BACKGROUND: Hemophilia A (HA) is an inherited bleeding disorder caused by a deficiency or defect in factor VIII (FVIII). METHODS: We investigated the role of clot waveform analysis (CWA) of activated partial thromboplastin time in the diagnosis and therapeutic monitoring of HA. The changes in CWA parameters the maximum clotting velocity (|Min1|), maximum clotting acceleration (|Min2|), and maximum clotting deceleration (|Max2|) were detected among mild, moderate, and severe HA groups. RESULTS: As the severity of HA subtypes increased, the levels of |Min1|, |Min2|, and |Max2| progressively decreased (p < 0.05). Receiver operating characteristic curve analysis showed that |Max2| and |Min2| were more effective than |Min1| in distinguishing different types of HA patients, with higher diagnostic efficacy. The standard curves based on Actin FSL reagent for normal and low levels of FVIII:C-|Max2| were established, with R2 values of 0.98 and 0.99, respectively. These curves can be utilized for monitoring during replacement therapies involving full-length recombinant FVIII and B-domain-deleted FVIII. Thirty cases of HA patients utilized the FVIII-|Max2| standard curve to obtain individual pharmacokinetics characteristic parameters. The clearance, half-life (t1/2), time to FVIII:C of 1% above baseline (tt1%), and predicted dosage showed no statistically significant differences compared with one-stage assay (p > 0.05). CONCLUSION: CWA is an economical and practical tool, and its related parameters are associated with the severity of HA. It has promising clinical prospects in predicting FVIII:C levels and individualized treatment when HA patients undergo replacement therapy.

Comparative proteomic analysis of rats subjected to water immersion and restraint stress as an insight into gastric ulcers.

In the present study, comparative proteomic analysis was performed in rats subjected to water immersion­restraint stress (WRS). A total of 26 proteins were differentially expressed and identified using matrix­assisted laser desorption/ionization time of flight mass spectrometry. Among the 26 differentially expressed protein spots identified, 13 proteins were significantly upregulated under WRS, including pyruvate kinase and calreticulin, which may be closely associated with energy metabolism. In addition, 12 proteins were downregulated under WRS, including hemoglobin subunit ß­2 and keratin type II cytoskeletal 8, which may be important in protein metabolism and cell death. Gene Ontology analysis revealed the cellular distribution, molecular function and biological processes of the identified proteins. The mRNA levels of certain differentially expressed proteins were analyzed using fluorescence quantitative polymerase chain reaction analysis. The results of the present study aimed to offer insights into proteins, which are differentially expressed in gastric ulcers in stress, and provide theoretical evidence of a radical cure for gastric ulcers in humans.

A systematic approach to expound the variations in taxane production under different dissolved oxygen conditions in Taxus chinensis cells.

KEY MESSAGE: Our results provide an evidence that the changes in taxane production caused by dissolved oxygen shifts could be associated with the global variations in the cell central carbon metabolism. Taxol is an important taxane synthesized by the Taxus plant. A two-stage culture of Taxus in vitro has been considered as an attractive alternative approach to produce Taxol and its precursors. To investigate the consequences of dissolved oxygen (DO) shifts for cell primary and secondary metabolism, we conducted metabolomic and transcriptomic profiling analyses under low dissolved oxygen (LDO), medium dissolved oxygen (MDO), and high dissolved oxygen (HDO) conditions in a suspension culture of Taxus chinensis cells. Under LDO, the results indicate a significant increase in the production of Taxol and its main precursors by 3.4- to 1.4-fold compared with those under MDO and HDO on 9th day. Multiple acyl taxanes (MAT) are abundant taxanes in the cells, and exhibited only a slight increase under the same conditions. Metabolomic analysis based on 209 primary metabolites indicated that several pathways in central carbon metabolism were involved, including the enhancement of the glycolysis pathway of glucose-6-phosphate to fructose-6-phosphate and pyruvate and the mevalonate pathway of terpene biosynthesis, and decline in the tricarboxylic acid pathway under LDO. These results indicate the mechanism by which related taxanes accumulate through enhancing the supplies of substrates and expression levels of hydroxylases. Excess acetyl-CoA supply induced by high oxygen stress was found to be correlated with high productivity of MAT. Our results provide an evidence that the changes in taxane production caused by DO shifts could be associated with the global variations in the cell central carbon metabolism.