Efficient bacterial drug susceptibility test can help precise guidance on using antimicrobial and improve the efficiency of development of antibiotics.Traditional antimicrobial susceptibility testing(AST)methods are simple,reliable and specific,but suffer from drawbacks of time-consuming.The CCK8 reagent can be reduced by the dehydrogenase in the bacterial cells to form a water-soluble orange-yellow formazan,and the concentration of viable bacteria is proportional to the absorbance of formazan at 450 nm(OD450 nm).In this work,based on the principle of CCK8 colorimetry,the antibiotic loaded composite fiber membrane was used as the culture matrix for AST.Simple,rapid and high-throughput AST was realized by the difference in OD450 nm,which reflected the differences in viable bacteria quantity during bacterial growth.The total detection time was less than 8 h.The potential application of the method was evaluated using S.aureus,P.aeruginosa in wound simulation fluid and E.coli in artificial urine as simulated actual samples.The results of this method were in consistent with the disk diffusion test.This method provided a new idea for AST,which was helpful for the guidance of clinical medication and the development of antibiotics.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.