International Business Machines Corporation

Zhejiang Sukean Pharmaceutical Co., Ltd.

Yan Su

Ming Zhao

Wei Tang

Yi Zhou

Michael Paul Groover

Robin Han

Chao Zhang

Pintong Huang

Yajing Liu

Edward Lin

A set of serum metabolic biomarkers and detection kit for detecting drug-resistant tuberculosis are provided. The set of the serum metabolic biomarkers includes 17 serum metabolic biomarkers. The 17 serum metabolic biomarkers are verified to be associated with tuberculosis based on the level changes of these biomarkers. The 17 metabolites includes taurine, homocysteine, uric acid, ascorbic acid, suberylglycine, uridine, dopamine 4-sulfate, inosinic acid, glyceraldehyde phosphate, [3-methoxy-4-(phosphoryl)phenyl]carbonyl sulfonic acid, nuclomedone, n4-cyclopropyl-6-(2,3-dichlorophenyl)-1,2,3,4-tetrahydropyrimidine-2,4-diimine, 1-[2-chlorine-2-(2,4-dichlorophenyl)ethenyl]-1,2,4-triazole, tetrachloro-phthalic anhydride, malotilate, fulvic acid, and L-neopterin. The serum metabolic biomarkers and detection kit for detecting drug-resistant tuberculosis can assist doctors in accurately diagnosing the disease, which is of great significance for the diagnosis and mass screening for drug-resistant tuberculosis.

Serum metabolic biomarkers and kit for detecting drug-resistant tuberculosis

A set of serum metabolic biomarkers and detection kit for detecting tuberculosis are provided. The set of the serum metabolic biomarkers includes 17 serum metabolic biomarkers. The 17 serum metabolic biomarkers comprising D-Leucic acid, Leucinic acid, L-Cystine, MG(0:0/14:0/0:0), S-Lactoylglutathione, Octacosanoic acid, Cer(d18:1/12:0), Raffinose, LysoPC(20:1(11Z)/0:0), LysoPC(22:4(7Z,10Z,13Z,16Z)/0:0), PC(18:1(9Z)e/2:0), Torvoside G(TG(15:0/15:0/15:0)), CE(16:1(9Z)), all-trans-Heptaprenyl diphosphate, PC(15:0/16:0), NADP, TG(20:0/20:0/20:1(11Z)). The 17 serum metabolic biomarkers are verified to be associated with tuberculosis based on the level changes of these biomarkers. The tuberculosis detection model based on the levels of the 17 metabolic biomarkers can achieve an area under the ROC curve of 99.5%, sensitivity of 98.2%, and specificity of 95.8% in detecting tuberculosis. The serum metabolic biomarkers and detection kit for detecting tuberculosis can assist doctors in accurately diagnosing the disease, which is of great significance for the diagnosis and mass screening for tuberculosis.

Serum metabolic biomarkers for detecting tuberculosis and tuberculosis detection kit

A tuberculosis detection kit includes diagnostic reagents for 17 serum metabolites of patients with tuberculosis, the detecting reagent being used for quantitative detection of the 17 serum metabolites of the patients with tuberculosis, the 17 serum metabolites comprising D-Leucic acid, Leucinic acid, L-Cystine, MG(0:0/14:0/0:0), S-Lactoylglutathione, Octacosanoic acid, Cer(d18:1/12:0), Raffinose, LysoPC(20:1(11Z)/0:0), LysoPC(22:4(7Z,10Z,13Z,16Z)/0:0), PC(18:1(9Z)e/2:0), Torvoside G(TG(15:0/15:0/15:0)), CE(16:1(9Z)), all-trans-Heptaprenyl diphosphate, PC(15:0/16:0), NADP, TG(20:0/20:0/20:1(11Z)).

Tuberculosis detection kit

A kit for detecting drug-resistant tuberculosis, includes: detection reagents, configured to perform quantitative detection on 17 serum metabolites of patients with tuberculosis, the 17 serum metabolites comprising: taurine, homocysteine, uric acid, ascorbic acid, suberylglycine, uridine, dopamine 4-sulfate, inosinic acid, glyceraldehyde phosphate, [3-methoxy-4-(phosphoryl)phenyl]carbonyl sulfonic acid, nuclomedone, n4-cyclopropyl-6-(2,3-dichlorophenyl)-1,2,3,4-tetrahydropyrimidine-tetrachlorophthalic anhydride, malotilate, fulvic acid, and L-neopterin.

Kit for detecting drug-resistant tuberculosis

Provided are techniques for code load processing. While performing code load processing of a set of modules of a same module type, it is determined that a first module in the set of modules is not in an operational state. It is determined that a second module is a redundant module for the first module. In response to determining that the second module is in an operational state and has already completed code update, the code load processing is continued. In response to determining that the second module is in an operational state and has not already completed code update, it is determined whether there is a third redundant module that is in an operational state. In response to determining that there is a third redundant module that is in an operational state, the code load processing is continued.

Cloud infrastructure for reducing storage facility code load suspend rate by redundancy check

A system for managing a code load for a storage system is disclosed. The system can include instantiating a code load. The code load can include a first update for a first component and a second update for a second component. The system can include monitoring the operational state of the first and second components in response to instantiating the code load. The system can also include determining to perform the first update in response to a triggering event. The system can also include performing the first update in response to determining to perform the first update.

Managing a code load

Provided are a computer program product, system, and method for applying a platform code level update to update a source partition in a computing system. Computational resources in the computing system are allocated to a destination partition. A code load is applied to the destination partition to implement an updated platform code level comprising an update to the platform code level on the source partition while the source partition is operational and processing computing requests. Submission of new transactions to the source partition is blocked in response to applying the code load to the destination partition. An operational environment and system state at the source partition are migrated to the destination partition in response to blocking submission of new transactions to the source partition. Transactions are directed to the destination partition intended for the source partition in response to migrating the operational environment and system state to the destination partition.

Applying a platform code level update to an operational node

A method and system for managing a code load for a storage system is disclosed. The method and system can include instantiating a code load. The code load can include a first update for a first component and a second update for a second component. The method and system can include monitoring the operational state of the first and second components in response to instantiating the code load. The method and system can also include determining to perform the first update in response to a triggering event. The method and system can also include performing the first update in response to determining to perform the first update.

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Zhejiang, China

Yan Su