Haloarcula marismortui (Volcani) sp. nov., nom. rev., an extremely halophilic bacterium from the Dead Sea

An extremely halophilic red archaebacterium isolated from the Dead Sea (Ginzburg et al., J. Gen. Physiol. 55: 187-207, 1970) belongs to the genus Haloarcula and differs sufficiently from the previously described species of the genus to be designated a new species; we propose the name Haloarcula marismortui (Volcani) sp. nov., nom. rev. because of the close resemblance of this organism to "Halobacterium marismortui," which was first described by Volcani in 1940. The type strain is strain ATCC 43049.     

Regulation of the cellular p53 tumor antigen in teratocarcinoma cells and their differentiated progeny.

F9 embryonal carcinoma cells express high levels of a 53,000-molecular-weight cellular tumor antigen called p53. When F9 cell cultures are treated with retinoic acid and dibutyryl adenosine 3',5'-phosphate, they differentiate, predominantly into endoderm-like cells. This differentiation is accompanied by a marked decrease in the levels of p53. The mechanism(s) responsible for this decline in the level of p53 in differentiated cells was investigated. The results demonstrate that the high levels of p53 in F9 cells relative to their differentiated progeny were not due to alterations in the stability or turnover of this protein. Rather, the regulation during differentiation involved a marked decrease in the amount of in vitro translatable p53 mRNA detected in the differentiated cell cultures. This mechanism is unlike the one operating during the simian virus 40 infection or transformation, where the increased levels of p53 are largely due to the increased stability of the p53 protein.     

Sulfide inhibition of photosystem II in cyanobacteria (blue-green algae) and tobacco chloroplasts.

The present study shows that in the presence of 600 nm light, sulfide acts as a specific inhibitor of photosynthetic electron transport between water and Photosystem II in the cyanobacteria Aphanothece halophytica and Synechococcus 6311 as well as in tobacco chloroplasts. In the presence of 600 nm light sulfied affects the fast fluorescence transients as does a low concentration (10 mM) of hydroxylamine; the fluorescence yield decreases in the presence of either chemical and can be restored by the addition of 3-(3,4-dichlorophenyl)-1,1-dimethylurea. In chloroplasts, however, NH2OH, an electron donor at high concentrations (40 mM), relieves the sulfide effect. In the dark, sulfide affects the cyanobacterial fluorescence transients through decrease of oxygen tension. The fluorescence yield increases in a similar pattern to that observed under nitrogen flushing. Upon omission of sulfide in A. halophytica, the characteristic aerobic fluorescence transients return, consistent with the ease of alternation between oxygenic and sulfide-dependent anoxygenic photosynthesis in many cyanobacteria.     

Demyelination and cytopathic effects in cultures of mammalian dorsal root ganglia infected with encephalomyocarditis virus.

Replication of encephalomyocarditis virus and its cytopathic effects were studied in myelinated cultures of dorsal root ganglia obtained from newborn mice. Six hours after infection virus progeny was detected in the culture. At 24 h the virus titer reached 2 times 10(6) PFU per culture and remained at this level until 48 h. The first cytopathic alterations began at 24 h and consisted of rounding of Schwann and satellites cells and their detachment from neurons. Later, bead-like swellings of the myelin appeared along the axons followed by splitting and degeneration of lamellae. The cytopathic effect in the neurons started 29 h after infection, reaching complete neuronolysis at 48 h. Virus particles, scattered or arranged in crystal-like aggregates, were first seen in the cytoplasm of glial cells and then in neurons and axons.     

The geometry of the Pareto front in biological phenotype space

When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade‐off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption, the best‐fitness solutions (termed the Pareto front) lie on simple low‐dimensional shapes in trait space: line segments, triangles and other polygons. The vertices of these polygons are specialists at a single task. Here, we generalize this finding, by considering performance functions of general form, not necessarily functions that decay monotonically with distance from their peak. We find that, except for performance functions with highly eccentric contours, simple shapes in phenotype space are still found, but with mildly curving edges instead of straight ones. In a wide range of systems, complex data on multiple quantitative traits, which might be expected to fill a high‐dimensional phenotype space, is predicted instead to collapse onto low‐dimensional shapes; phenotypes near the vertices of these shapes are predicted to be specialists, and can thus suggest which tasks may be at play.     

Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network

Recurrent connections play an important role in cortical function, yet their exact contribution to the network computation remains unknown. The principles guiding the long-term evolution of these connections are poorly understood as well. Therefore, gaining insight into their computational role and into the mechanism shaping their pattern would be of great importance. To that end, we studied the learning dynamics and emergent recurrent connectivity in a sensory network model based on a first-principle information theoretic approach. As a test case, we applied this framework to a model of a hypercolumn in the visual cortex and found that the evolved connections between orientation columns have a "Mexican hat" profile, consistent with empirical data and previous modeling work. Furthermore, we found that optimal information representation is achieved when the network operates near a critical point in its dynamics. Neuronal networks working near such a phase transition are most sensitive to their inputs and are thus optimal in terms of information representation. Nevertheless, a mild change in the pattern of interactions may cause such networks to undergo a transition into a different regime of behavior in which the network activity is dominated by its internal recurrent dynamics and does not reflect the objective input. We discuss several mechanisms by which the pattern of interactions can be driven into this supercritical regime and relate them to various neurological and neuropsychiatric phenomena.     

The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity

Synaesthesia is an unusual perceptual experience in which an inducer stimulus triggers a percept in a different domain in addition to its own. To explore the conditions under which synaesthesia evolves, we studied a neuronal network model that represents two recurrently connected neural systems. The interactions in the network evolve according to learning rules that optimize sensory sensitivity. We demonstrate several scenarios, such as sensory deprivation or heightened plasticity, under which synaesthesia can evolve even though the inputs to the two systems are statistically independent and the initial cross-talk interactions are zero. Sensory deprivation is the known causal mechanism for acquired synaesthesia and increased plasticity is implicated in developmental synaesthesia. The model unifies different causes of synaesthesia within a single theoretical framework and repositions synaesthesia not as some quirk of aberrant connectivity, but rather as a functional brain state that can emerge as a consequence of optimising sensory information processing.