Mass spectrometry in viral proteomics

Mass spectrometry is a valuable tool in structural and functional viral proteomics, where it has been used to identify viral capsid proteins, viral mutants, and posttranslational modifications. Further, mass-based approaches combined with time-resolved proteolysis (mass mapping) have revealed the dynamic nature of viral particles in solution; this method is contributing to an understanding of the dynamic domains of the viral capsid which may have significant value in developing new approaches for viral inactivation. As a result of these experiments, and by comparison with complementary data from X-ray crystallography, a new dimension to viral protein structure and function is emerging.     

Mass spectrometry of lipid molecules

The mechanisms of mass spectrometric fragmentation and their applications to the elucidation of structure of lipids related to fatty acids are reviewed. The mechanism of fragmentation of saturated fatty acids and the mass spectrometric determination of the position of the double bond in unsaturated esters are emphasized. The use of pyrolysis-mass spectrometry for locating double bonds is introduced. Patterns of fragmentation of wax esters and glycerides are also given. Presented at the AOCS-AACC Joint Meeting, Washington, D.C., April, 1968.     

Application of robotics In the clinical laboratory

The basic types of robot are explained, and the performances and costs of some commercial examples are given. The potential advantages and problems of introducing robots into clinical laboratories are identified and the specifcation of a suitable robot is developed. None of the commercially available robots meets all aspects of the specificalion, and currently the purchase of a robot is considered premature for most clinical laboratories.     

Mass spectrometry/mass spectrometry: capabilities and applications to fuel-related materials

The expanding capabilities of mass spectrometry/mass spectrometry (m.s.-m.s.) in mixture analysis and its applications to fuel-related materials are illustrated. High and low collision energy m.s.-m.s. data obtained on reverse geometry and triple quadrupole spectrometers are given for coal-derived liquid (SRC II) and diesel particulate samples. The direct analysis capability of the m.s.-m.s. methodology and its limitations are illustrated for the identification of an aliphatic carboxylic acid in diesel paniculate. The selective ionization techniques of ammonia chemical ionization and negative chemical ionization are shown to be particularly useful in enhancing the specificity of m.s.-m.s. characterizations. Negative chemical ionization is used to confirm the presence of hydroxybenzoic acid in a diesel particulate sample. Combined laser desorption-chemical ionization is also demonstrated to be an effective ionization technique in m.s.-m.s. analysis. A variant of m.s.-m.s., in which selected anions fragment with charge inversion to give fragment cations, is also employed in the analysis of SRC II and used to identify thioaryl moieties. Functional group screening by an alternative m.s.—m.s. scan procedure, neutral loss scanning, is demonstrated for phenols in SRC II. A scan for all parent ions of a selected daughter ion provides a screening procedure for rapidly identifying all compounds of a given structural type in a complex mixture. The dependence of m.s.-m.s. spectra on collision energy and pressure is shown to add further detail to m.s.—m.s. analysis. The development of a library of m.s.—m.s. spectra of reference compounds to be used for the identification of individual constituents in fuel-related materials is described.     

Comment: Applications of robotics in the clinical laboratory

The implementation of a robotic workstation in the clinical laboratory involves considerations and compromises common to any instrument design and development activity. The trade-off between speed and flexibility not only affects the way the instrument interacts with human operators and other devices (the ‘real-world interface’), but also places limitations on the adaptation of chemistries to the given instrument. Mechanical optimization for speed and reproducibility places restrictions on the imprecision of consumables. Attempts to adapt a robot to a constrained system may entail compromises that either degrades the theoretically-attainable quality of results, or requires human interaction to compensate for physical or mechanical limitations. The general considerations of function and workflow, programming and support, and reliability place practical limits on the implementation of robotic workstations in the clinical laboratory.     

原子荧光法应用于实验室废水中砷的测定

研究了原子荧光法在光谱仪设定条件为:总电流70 mA,负高压270 V,原子化器温度300℃,载气Ar_2流量600 mL/min,辅助气Ar_1流量200 mL/min,载流2%HCl,读数时间25 s,延时时间3 s, KBH_4浓度1%～1.5%的条件下,应用于实验室废水中砷的检测。结果表明,该方法操作简单,检测结果精度高,对于判断实验室废水是否符合环境排放限值要求,避免盲目排放对环境造成污染具有重要意义。     

Mass spectrometry of triglycerides: I. Structural effects

Mass spectra of several triglycerides of specific structure or with specific deuterium labeling have been measured with a low resolution mass spectrometer. With saturated triglycerides the abundances of ions characteristic of the component acids, [M-RCO₂]⁺, increase with increasing chain length, and [M-RCO₂CH₂]⁺ decrease with increasing chain length. Unsaturation in the acyl moiety causes the abundant formation of [RCO-1]⁺. Structures have been suggested for a number of the main peaks obtained from saturated triglycerides, and high resolution spectra of one triglyceride agree with the postulated structures. The peaks, [RCO+74]⁺, [RCO+115]⁺ and [RCO+128+14n]⁺, represent structures which contain the glyceryl portion of the triglyceride, since in case of the replacement of its hydrogens with deuteriums, these peaks are shifted accordingly. Evidence which indicates the possibility of determining the location of unsaturation by the interruption of homology of the [RCO+128+14n]⁺ series, brought about by the addition of deuterium to the unsaturated linkages, is introduced. Further evidence is also presented, which indicates that the [M-RCO₂CH₂]⁺ ions arise from the positions 1 and 3 and, in agreement with earlier studies from other laboratories, it is thus possible to identify the acyl groups attached to the 1 and 2 positions of the glyceryl moiety. Presented in part at the AOCS Meeting, New Orleans, April 1970. Part V of a series on Mass Spectrometry of Lipids. For IV see Lipids 4:421–427 (1969).     

Increasing the biosafety of analytical systems in the clinical laboratory

Biosafety is an important part of the know-how of all clinical laboratory professionals. Biosafely must have high priority in the design and use of analytical systems. Attention should be focused on reducing the handling of biological specimens, reducing biohazards to laboratory personnel, and on improving the labelling and containment of biohazardous materials. In this paper, biosafety issues are discussed in relation to the design of analytical systems, their use and maintenance.     

Use of artificial intelligence in analytical systems for the clinical laboratory

The incorporation of information-processing technology into analytical systems in the form of standard computing software has recently been advanced by the introduction of artificial intelligence (AI), both as expert systems and as neural networks.This paper considers the role of software in system operation, control and automation, and attempts to define intelligence. AI is characterized by its ability to deal with incomplete and imprecise information and to accumulate knowledge. Expert systems, building on standard computing techniques, depend heavily on the domain experts and knowledge engineers that have programmed them to represent the real world. Neural networks are intended to emulate the pattern-recognition and parallel processing capabilities of the human brain and are taught rather than programmed. The future may lie in a combination of the recognition ability of the neural network and the rationalization capability of the expert system.In the second part of the paper, examples are given of applications of AI in stand-alone systems for knowledge engineering and medical diagnosis and in embedded systems for failure detection, image analysis, user interfacing, natural language processing, robotics and machine learning, as related to clinical laboratories.It is concluded that AI constitutes a collective form of intellectual propery, and that there is a need for better documentation, evaluation and regulation of the systems already being used in clinical laboratories.