The nefgenes of the human immunodeficiency viruses type 1 and 2 (HIV-1 and HIV-2) and the related simian immunodeficiency viruses (SIVs) encode a protein (Nef) whose role in virus replication and cytopathicity remains uncertain. As an attempt to elucidate the function of nef, we characterized the nucleotide and corresponding protein sequences of naturally occurring nef genes obtained from several HIV-1-infected individuals. A consensus Nef sequence was derived and used to identify several features that were highly conserved among the Nef sequences. These features included a nearly invariant myristylation signal, regions of sequence polymorphism and variable duplication, a region with an acidic charge, a (PXX)4 repeat sequence, and a potential protein kinase C phosphorylation site. Clustering of premature stop codons at position 124 was noted in 6 of the 54 Nef sequences. Further analysis revealed four stretches of residues that were highly conserved not only among the patient-derived HIV-1 Nef sequences, but also among the Nef sequences of HIV-2 and the SIVs, suggesting that Nef proteins expressed by these retroviruses are functionally equivalent. The "Nef-defining" sequences were used to evaluate the sequence alignments of known proteins reported to share sequence similarity with Nef sequences and to conduct additional computer-based searches for similar protein sequences. A gene encoding the consensus Nef sequence was also generated. This gene encodes a full-length Nef protein that should be a valuable tool in further studies of Nef function.

The purpose of this study was to determine whether intensity windowing (IW) improves detection of simulated masses in dense mammograms. Simulated masses were embedded in dense mammograms digitized at 50 microns/pixel, 12 bits deep. Images were printed with no windowing applied and with nine window width and level combinations applied. A simulated mass was embedded in a realistic background of dense breast tissue, with the position of the mass (against the background) varied. The key variables involved in each trial included the position of the mass, the contrast levels and the IW setting applied to the image. Combining the 10 image processing conditions, 4 contrast levels, and 4 quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty observers were asked to detect the quadrant of the image into which the mass was located. There was a statistically significant improvement in detection performance for masses when the window width was set at 1024 with a level of 3328. IW should be tested in the clinic to determine whether mass detection performance in real mammograms is improved.

This study attempts to determine whether intensity windowing (IW) improves detection of simulated calcifications in dense mammograms. Clusters of five simulated calcifications were embedded in dense mammograms digitized at 50-1~m pixels, 12 bits deep. Film images with no windowing applied were compared with film images with nine different window widths and levels applied. A simulated cluster was embedded in a realistic background of dense breast tissue, with the position of the cluster varied. The key variables involved in each trial included the position of the cluster, contrast level of the cluster, and the IW settings applied to the image. Combining the ten IW conditions, four contrast levels and four quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty student observers were asked to detect the quadrant of the image in which the mass was Iocated. There was a statistically significant improvement in detection performance for clusters of calcifications when the window width was set at 1024 with a level of 3328, and when the window width was set at 1024 with a level cf 3456. The selected IW settings should be tested in the clinic with digital mammograms to determine whether calcification detection performance can be improved. Copyright 9 1997 by W.B. Saunders CompanyKEY WORDS: mammography, image processing, intensity windowing, observer studies, calcifications, computers, radiology.M AMMOGRAPHY, especially in women with dense breasts, is not perfectly sensitive to all cancers. Approximately 10% to 15% of palpable malignancies are not visible mammographically. ~ Tbere is some reason to believe that digital mammography rnight allow for greater contrast and improved detection of small and early tumors over standard film screen technology, especially ir image processing is used to improve image contrast. 2,3There are many potentially useful image processing algorithms, and each algorithm has a number of parameters that can be systematically varied to improve or worsen lesion detectability. Radiologists cannot and should not evaluate these algorithms in the clinic with real patients. Such a task would be overwhelming and potentially could cause much unnecessary patient anxiety. Ideally, a test set of image phantorns with simulated lesions in known locations should be used to test each potentially useful algorithm and its attendant parameters in the laboratory setting before any patient's images ate interpreted using these algorithms. We have developed such a laboratory method for evaluation of image processing algorithms. 4 In previous work, we have shown that detection performance with the application of contrast limited adaptive equalization (CLAHE) to digitized mammograms is parallel for radiologists and student observers. 4 Using the same experimental paradigm, we report here on whether intensity windowing (IW) can improve the detection of calcifications in dense mammograms in...