Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network

Past and present distribution, densities and movements of blue whales <i>Balaenoptera musculus</i> in the Southern Hemisphere and northern Indian Ocean

1Blue whale locations in the Southern Hemisphere and northern Indian Ocean were obtained from catches (303 239), sightings (4383 records of =8058 whales), strandings (103), Discovery marks (2191) and recoveries (95), and acoustic recordings.2Sighting surveys included 7 480 450 km of effort plus 14 676 days with unmeasured effort. Groups usually consisted of solitary whales (65.2%) or pairs (24.6%); larger feeding aggregations of unassociated individuals were only rarely observed. Sighting rates (groups per 1000 km from many platform types) varied by four orders of magnitude and were lowest in the waters of Brazil, South Africa, the eastern tropical Pacific, Antarctica and South Georgia; higher in the Subantarctic and Peru; and highest around Indonesia, Sri Lanka, Chile, southern Australia and south of Madagascar.3Blue whales avoid the oligotrophic central gyres of the Indian, Pacific and Atlantic Oceans, but are more common where phytoplankton densities are high, and where there are dynamic oceanographic processes like upwelling and frontal meandering.4Compared with historical catches, the Antarctic (‘true’) subspecies is exceedingly rare and usually concentrated closer to the summer pack ice. In summer they are found throughout the Antarctic; in winter they migrate to southern Africa (although recent sightings there are rare) and to other northerly locations (based on acoustics), although some overwinter in the Antarctic.5Pygmy blue whales are found around the Indian Ocean and from southern Australia to New Zealand. At least four groupings are evident: northern Indian Ocean, from Madagascar to the Subantarctic, Indonesia to western and southern Australia, and from New Zealand northwards to the equator. Sighting rates are typically much higher than for Antarctic blue whales.6South-east Pacific blue whales have a discrete distribution and high sighting rates compared with the Antarctic. Further work is needed to clarify their subspecific status given their distinctive genetics, acoustics and length frequencies.7Antarctic blue whales numbered 1700 (95% Bayesian interval 860–2900) in 1996 (less than 1% of original levels), but are increasing at 7.3% per annum (95% Bayesian interval 1.4–11.6%). The status of other populations in the Southern Hemisphere and northern Indian Ocean is unknown because few abundance estimates are available, but higher recent sighting rates suggest that they are less depleted than Antarctic blue whales.</li

Elevated levels of active Transforming Growth Factor beta1 in the subchondral bone relate spatially to cartilage loss and impaired bone quality in human knee osteoarthritis

Abstract not availableD. Muratovic, D.M. Findlay, R.D. Quarrington, X. Cao, L.B. Solomon, G.J. Atkins, J.S. Kuliwab

Image Analysis of Bone Density Following Anterior Cruciate Ligament Injury

Background Following an anterior cruciate ligament (ACL) injury, the affected knee is known to experience bone loss and is at significant risk of becoming osteoporotic. Surgical reconstruction is performed to attempt to restore the function of the knee and theoretically restore this bone density loss. Cross-sectional analysis of the proximal tibia using peripheral quantitative computed tomography (pQCT) enables localised analysis of bone mineral density (BMD) changes. The aim of this study was to establish the pattern of bone density changes in the tibia pre- and post- ACL reconstruction using pQCT image analysis. Methods Eight patients who underwent ACL reconstruction were included. A cross sectional analysis of the proximal tibia was performed using a pQCT scanner pre-operatively and one to two years post-operatively on both the injured and contralateral (control) knee. The proximal two and three percent slices [S2 and S3] along the tibia were acquired. These were exported to Matlab(tm) and automated segmentation was performed to remove the tibia from its surrounding structures. Cross correlation was applied to co-register pairs of images and patterns of change in BMD were mapped using a t-test (p&lt;0.05). Connected components of pixels with significant change in BMD were created and used to assess the impact of ACL injury &amp; reconstruction on the proximal tibial BMD. Results Prior to surgical ACL reconstruction, the BMD in the injured leg was significantly reduced relative to the control leg [S2: p=0.002, S3: p=0.002]. Post surgery, the proximal tibial BMD did not change in either leg [Control S2: p=0.102, S3: p=0.181; Injured S2: p=0.093, S3: p=0.439]. The post surgical images demonstrated patterns of increasing BMD surrounding the tunnel in the form of compact bone. Discussion A significant reduction in proximal tibial BMD was observed in the ACL injured legs relative to control legs. The pattern of pre-operative bone loss was generally observed to be global across the entire slice. No change in BMD was observed following ACL reconstruction, in either injured or control leg. These results indicate that proximal tibial BMD is reduced and does not change after ACL reconstruction

Negative relationships between species richness and temporal variability are common but weak in natural systems

Effects of species diversity on population and community stability (or more precisely, the effects of species richness on temporal variability) have been studied for several decades, but there have been no large-scale tests in natural communities of predictions from theory. We used 91 data sets including plants, fish, small mammals, zooplankton, birds, and insects, to examine the relationship between species richness and temporal variability in populations and communities. Seventy-eight of 91 data sets showed a negative relationship between species richness and population variability; 46 of these relationships were statistically significant. Only five of the 13 positive richness-population variability relationships were statistically significant. Similarly, 51 of 91 data sets showed a negative relationship between species richness and community variability; of these, 26 were statistically significant. Seven of the 40 positive richness–community-variability relationships were statistically significant. We were able to test transferability (i.e., the predictive ability of models for sites that are spatially distinct from sites that were used to build the models) for 69 of 91 data sets; 35 and 31 data sets were transferable at the population and community levels, respectively. Only four were positive at the population level, and two at the community level. We conclude that there is compelling evidence of a negative relationship between species richness and temporal variability for about one-half of the ecological communities we examined. However, species richness explained relatively little of the variability in population or community abundances and resulted in small improvements in predictive ability

Tectonic model for development of the Byrd Glacier discontinuity and surrounding regions of the Transantarctic Mountains during Neoproterozoic-Early Paleozoic

The Byrd Glacier discontinuity us a major boundary crossing the Ross Orogen, with crystalline rocks to the north and primarily sedimentary rocks to the south. Most models for the tectonic development of the Ross Orogen in the central Transantarctic Mountains consits of two-dimensional transects across the belt, but do not adress the major longitudinal contrast at Byrd Glacier. This paper presents a tectonic model centering on the Byrd Glacier discontinuity. Rifting in the Neoproterozoic producede a crustal promontory in the craton margin to the north of Byrd Glacier. Oblique convergence of the terrane (Beardmore microcontinent) during the latest Neroproterozoic and Early Cambrian was accompanied by subduction along the craton margin of East Antarctica. New data presented herein in the support of this hypothesis are U-Pb dates of 545.7 ± 6.8 Ma and 531.0 ± 7.5 Ma on plutonic rocks from the Britannia Range, subduction stepped out, and Byrd Glacier. After docking of the terrane, subduction stepped out, and Byrd Group was deposited during the Atdabanian-Botomian across the inner margin of the terrane. Beginning in the upper Botomian, reactivation of the sutured boundaries of the terrane resulted in an outpouring of clastic sediment and folding and faulting of the Byrd Group