Abstract: A collision reaction pool ion acceleration apparatus which has extremely low crosstalk. The apparatus comprises an apparatus body, a vacuum chamber, a first tube bundle channel and a second tube bundle channel. The vacuum chamber is fixedly connected to the interior of the apparatus body; the other end of the interior of the apparatus body is fixedly connected to a first insulation seat. A collision chamber is embeddedly connected to the inside the first insulation seat, and a high-frequency electrode quadrupole lens is fixedly connected to two sides of the collision chamber. When charged ions enter the collision chamber, the high-frequency electrode quadrupole lens focuses on the charged ions, so that the incoming charged ions form a new motion trajectory in the collision chamber, and the charged ions are easily separated from the collision chamber, thereby increasing the working efficiency.

Abstract: A collision reaction pool ion acceleration apparatus which has extremely low crosstalk. The apparatus comprises an apparatus body, a vacuum chamber, a first tube bundle channel and a second tube bundle channel. The vacuum chamber is fixedly connected to the interior of the apparatus body; the other end of the interior of the apparatus body is fixedly connected to a first insulation seat. A collision chamber is embeddedly connected to the inside the first insulation seat, and a high-frequency electrode quadrupole lens is fixedly connected to two sides of the collision chamber. When charged ions enter the collision chamber, the high-frequency electrode quadrupole lens focuses on the charged ions, so that the incoming charged ions form a new motion trajectory in the collision chamber, and the charged ions are easily separated from the collision chamber, thereby increasing the working efficiency.

Abstract: The invention discloses a pretreatment method, a preservation method, an automatic treatment system and a detection method for a urine sample, and directs to the technical field of biological detection. The pretreatment method comprises subjecting a urine sample after protein lysis to a reductive alkylation treatment, followed by protein enrichment and enzymolysis. The protein enrichment is performed on the sample after the reductive alkylation treatment using a PVDF filter plate for protein enrichment; The invention also provides an automatic treatment system and an automatic sample treatment method. The treatment system greatly reduces the labor intensity of people, is beneficial to facilitate the treatment efficiency of urine sample treatment, meets the requirements of high-flux and automated pretreatment of the proteomics, and accommodates the reproducibility and flux of current clinical needs.

Abstract: The present disclosure provides a marker and use thereof in predicting a possibility of a subject with diabetes. The marker described may include at least one of ?-hydroxybutyric acid (?-HB), 1,5-anhydroglucitol (1,5-AG), asymmetric dimethylarginine (ADMA), cystine, ethanolamine, taurine, L-leucine, L-tryptophan, hydroxylysine, and L-aspartate. The possibility of the subject with diabetes may be predicted using a prediction model (e.g., prediction models 2-5) related to the marker based on a concentration of the marker. The prediction model 2 is related to ?-HB. The prediction model 3 is related to 1,5-AG and ADMA. The prediction model 4 is related to cystine, ethanolamine, taurine, L-leucine, L-tryptophan and hydroxylysine. The prediction model 5 is related to ?-HB, 1,5-AG, cystine, ethanolamine, taurine and L-aspartate.

Abstract: The embodiments of the present disclosure provide a method for analyzing a body fluid proteome. The method comprises: obtaining a sample to be tested I enriched with low-abundance proteins by removing high-abundance proteins in an initial sample A using an affinity technique; obtaining a sample to be tested II enriched with low-abundance proteins by removing high-abundance proteins in an initial sample B using chemical precipitation, wherein the initial sample A and the initial sample B are obtained from a same body fluid sample of a same subject; obtaining a proteome data set I by performing proteomic analysis on the sample to be tested I; obtaining a proteome data set II by performing proteomic analysis on the sample to be tested II; and determining a final quantified proteome data set of the body fluid sample based on the proteome data set I and the proteome data set II.

Abstract: The present disclosure provides a marker and use thereof in predicting a possibility of a subject with diabetes. The marker described may include at least one of ?-hydroxybutyric acid (?-HB), 1,5-anhydroglucitol (1,5-AG), asymmetric dimethylarginine (ADMA), cystine, ethanolamine, taurine, L-leucine, L-tryptophan, hydroxylysine, and L-aspartate. The possibility of the subject with diabetes may be predicted using a prediction model (e.g., prediction models 2-5) related to the marker based on a concentration of the marker. The prediction model 2 is related to ?-HB. The prediction model 3 is related to 1,5-AG and ADMA. The prediction model 4 is related to cystine, ethanolamine, taurine, L-leucine, L-tryptophan and hydroxylysine. The prediction model 5 is related to ?-HB, 1,5-AG, cystine, ethanolamine, taurine and L-aspartate.