[Histopathological particle algorithm. Particle identification in the synovia and the SLIM]. / Histopathologischer Partikelalgorithmus. Partikelidentifikation in der Synovialis und in der SLIM.

BACKGROUND: In the histopathological diagnostics of synovitis and the synovium-like interface membrane (SLIM) the identification of crystals and crystal-like deposits and the associated inflammatory reactions play an important role. The multitude of endogenous crystals, the range of implant materials and material combinations, and the variability in the formation process of different particles explain the high morphological particle heterogeneity which complicates the diagnostic identification of diagnostic particles. STUDY DESIGN AND METHODS: A simple histopathological particle algorithm has been designed which allows methodological particle identification based on (1) conventional transmitted light microscopy with a guide to particle size, shape and color, (2) optical polarization criteria and (3) enzyme histochemical properties (oil red staining and Prussian blue reaction). These methods, the importance for particle identification and the differential diagnostics from non-prosthetic materials are summarized in the so-called histopathological particle algorithm. RESULTS: A total of 35 cases of synovitis and SLIM were analyzed and validated according to these criteria. Based on these criteria and a dichotomous differentiation the complete spectrum of particles in the SLIM and synovia can be defined histopathologically. CONCLUSION: For histopathological diagnosis a particle score for synovitis and SLIM is recommended to evaluate (1) the predominant type of prothetic wear debris with differentiation between microparticles, and macroparticles, (2) the presence of non-prosthesis material particles and (3) the quantification of particle-association necrosis and lymphocytosis. An open, continuously updated web-based particle algorithm would be helpful to address the issue of particle heterogeneity and include all new particle materials generated in a rapidly changing field.

Does noise stress modulate effects of smoking/nicotine? Mood, vigilance, and EEG responses.

Effects of smoking multiple cigarettes on EEG, vigilance, and subjective state were assessed in a repeated measures design where noise level (high versus minimal) was crossed with nicotine dose (quasi-ad lib own versus 1.0 mg FTC nicotine machine-delivered dose versus 0.05 mg FTC nicotine machine-delivered dose). Vigilance was increased by nicotine, but not by noise and there was no noise by dose interaction. Effects of nicotine on EEG varied as a function of dose, noise, hemisphere, time, and eyes-open versus eyes-closed condition. Smoking normal nicotine delivery (0.9-1.1 mg FTC-estimated) cigarettes resulted in decreases in percentages of delta and theta EEG magnitude and increased percentage beta-1 EEG magnitude across conditions and time. Changes in alpha and theta magnitude were dependent on eyes being open versus closed. Hemispheric asymmetries varied as a function of noise and time. Consistent with inverted "U" models, effects of nicotine on EEG were clearly stimulant during the quiet conditions while there were minimal to no differences between nicotine doses during the high-noise conditions. The failure of nicotine to modify mood is interpreted in terms of bioinformational models of nicotine's subjective effects.