Lamellar Organization of Pigments in Chlorosomes, the Light Harvesting Complexes of Green Photosynthetic Bacteria

Chlorosomes of green photosynthetic bacteria constitute the most efficient light harvesting complexes found in nature. In addition, the chlorosome is the only known photosynthetic system where the majority of pigments (BChl) is not organized in pigment-protein complexes but instead is assembled into aggregates. Because of the unusual organization, the chlorosome structure has not been resolved and only models, in which BChl pigments were organized into large rods, were proposed on the basis of freeze-fracture electron microscopy and spectroscopic constraints. We have obtained the first high-resolution images of chlorosomes from the green sulfur bacterium Chlorobium tepidum by cryoelectron microscopy. Cryoelectron microscopy images revealed dense striations ∼20 Å apart. X-ray scattering from chlorosomes exhibited a feature with the same ∼20 Å spacing. No evidence for the rod models was obtained. The observed spacing and tilt-series cryoelectron microscopy projections are compatible with a lamellar model, in which BChl molecules aggregate into semicrystalline lateral arrays. The diffraction data further indicate that arrays are built from BChl dimers. The arrays form undulating lamellae, which, in turn, are held together by interdigitated esterifying alcohol tails, carotenoids, and lipids. The lamellar model is consistent with earlier spectroscopic data and provides insight into chlorosome self-assembly

Dynamic Modeling with Structural Equations and Stochastic Differential Equations: Applications with the German Socioeconomic Panel

Reinecke J, Schmidt P, Weick S. Dynamic Modeling with Structural Equations and Stochastic Differential Equations: Applications with the German Socioeconomic Panel. Quality and Quantity. 2005;39(4):483-506

Early detection and prevention of delirium in older patients with cancer

Delirium poses a common and multifactorial complication in older patients with cancer. Delirium independently contributes to poorer clinical outcomes and impedes communication between patients with cancer, their family and health care providers. Because of its clinical impact and potential reversibility, efforts for prevention, early recognition or prompt treatment are critical. However, nurses and other health care providers often fail to recognize delirium or misattribute its symptoms to dementia, depression or old age. Yet, failure to determine an individual's risk for delirium can initiate the cascade of negative events causing additional distress for patients, family and health care providers alike. Therefore, parameters for determining an individual's risk for delirium and guidelines for the routine and systematic assessment of cognitive functioning are provided to form a basis for the prompt and accurate diagnosis of delirium. Guidelines for the prevention and treatment of delirium are also discussed

Continuous time state space modeling of panel data by means of sem

continuous time state space modeling, exact discrete model, linear stochastic differential equations, longitudinal structural equation modeling, panel analysis,