Background: Information technology plays an important role in the developmental process. Activities of the Vietnam health sector mainly provide social services so that the investment in application and development of information technology has met various difficulties and constraints. Objectives: This study aims to discover the real status and resolutions in state management on health information technology. Subjects and method: Research performed on 144 state organizations involved in the health sector in Vietnam, with 403 surveys between 2006 and 2007. The data were collected and analyzed by SPSS 10.0 software. Results: The state management capacity on information technology in the health sector remained weak and contains shortcomings. The health sector had no overall plan for applying and developing information technology; 43.8% of surveyed organizations have no special division for IT; 34.7% have no IT specialist. The investment effect was not high enough yet, up to 62.5% of surveyed organizations have LAN but only 42.4% have specialist management of software. There are no procedures for monitoring, surveying and assessing the effect of IT activities in the health sector. Conclusion: Real state of management on IT in the health sector still face many difficulties and ineffectiveness due to the orientation for application of IT development in the health sectors is still unclear.
State management ; information technology

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.