The plexiform lesions of severe pulmonary hypertension (PH) are complex vascular structures composed primarily of endothelial cells. In this study, we use immunohistochemical markers to identify the various cell layers of pulmonary vessels and to identify different endothelial cell phenotypes in pulmonary arteries affected by severe PH. Our computerized three-dimensional reconstructions of nine vessels in five patients with severe PH demonstrate that plexiform (n = 14) and concentric-obliterative (n = 6) lesions occur distal to branch points of small pulmonary arteries. And, whereas plexiform lesions occur as solitary lesions, concentric-obliterative lesions appear to be only associated with, and proximal to, plexiform structures. The endothelial cells of plexiform lesions express intensely and uniformly the vascular endothelial growth factor (VEGF) receptor KDR and segregate phenotypically into cyclin-kinase inhibitor p27/kip1-negative cells in the central core of the plexiform lesion and p27/kip1-positive cells in peripheral areas adjacent to incipient blood vessel formation. Using immunohistochemistry and three-dimensional reconstruction techniques, we show that plexiform lesions are dynamic vascular structures characterized by at least two endothelial cell phenotypes. Plexiform arteriopathy is not merely an end stage or postthrombotic change--it may represent one stage in an ongoing, angiogenic endothelial cell growth process.

The fibroblast foci of UIP are the leading edge of a complex reticulum that is highly interconnected and extends from the pleura into the underlying parenchyma. It is a reactive, rather than a malignant, process.

biopsies, depending on the size of the prostate. Clinically threatening cancers were defined as having volumes of ≥ 0.5 mL or Gleason sum ≥ 7. RESULTSMethod A detected significantly more carcinomas than method B in both the autopsy and prostatectomy specimens (autopsy, 72 vs 51; prostatectomy, 50 vs 32, both P < 0.001). Method A also detected more clinically threatening cancers found at autopsy (38/40 vs 31/40, P = 0.008). Among autopsy patients with negative sextant biopsies whose disease was localized to one side, method A detected 72% and method B detected 29-43% ( P < 0.001). CONCLUSIONSThe results of this computer simulation show that 5-and 10-mm grid biopsies detect threequarters and a third, respectively, at autopsy, of patients with the disease localized to one side of the prostate, which may be useful when planning highly selective ablative treatments in the future.

We address the problem of modeling long-term energy policy and investment decisions while retaining the important ability to capture fine-grained variations in intermittent energy and demand, as well as storage. In addition, we wish to capture sources of uncertainty such as future energy policies, climate, and technological advances, in addition to the variability as well as uncertainty in wind energy, demands, prices and rainfall. Accurately modeling the value of all investments such as wind and solar requires handling fine-grained temporal variability and uncertainty in wind and solar, as well as the use of storage. We propose a modeling and algorithmic strategy based on the framework of approximate dynamic programming (ADP) that can model these problems at hourly time increments over a multidecade horizon, while still capturing different types of uncertainty. This paper describes initial proof of concept experiments for an ADP-based model, called SMART, by describing the modeling and algorithmic strategy, and providing comparisons against a deterministic benchmark as well as initial experiments on stochastic datasets.