Cell sorting in a Petri dish controlled by computer vision.

Fluorescence-activated cell sorting (FACS) applying flow cytometry to separate cells on a molecular basis is a widespread method. We demonstrate that both fluorescent and unlabeled live cells in a Petri dish observed with a microscope can be automatically recognized by computer vision and picked up by a computer-controlled micropipette. This method can be routinely applied as a FACS down to the single cell level with a very high selectivity. Sorting resolution, i.e., the minimum distance between two cells from which one could be selectively removed was 50-70 micrometers. Survival rate with a low number of 3T3 mouse fibroblasts and NE-4C neuroectodermal mouse stem cells was 66 +/- 12% and 88 +/- 16%, respectively. Purity of sorted cultures and rate of survival using NE-4C/NE-GFP-4C co-cultures were 95 +/- 2% and 62 +/- 7%, respectively. Hydrodynamic simulations confirmed the experimental sorting efficiency and a cell damage risk similar to that of normal FACS

A scale-down mimic for mapping the process performance of centrifugation, depth and sterile filtration

In the production of biopharmaceuticals disk-stack centrifugation is widely used as a harvest step for the removal of cells and cellular debris. Depth filters followed by sterile filters are often then employed to remove residual solids remaining in the centrate. Process development of centrifugation is usually conducted at pilot-scale so as to mimic the commercial scale equipment but this method requires large quantities of cell culture and significant levels of effort for successful characterization. A scale-down approach based upon the use of a shear device and a bench-top centrifuge has been extended in this work towards a preparative methodology that successfully predicts the performance of the continuous centrifuge and polishing filters. The use of this methodology allows the effects of cell culture conditions and large-scale centrifugal process parameters on subsequent filtration performance to be assessed at an early stage of process development where material availability is limited

Correlations and Fluctuations in High-Energy Nuclear Collisions

Nucleon correlations in the target and projectile nuclei are shown to reduce significantly the fluctuations in multiple nucleon-nucleon collisions, total multiplicity and transverse energy in relativistic heavy-ion collisions, in particular for heavy projectile and target. The interplay between cross-section fluctuations, from color transparency and opacity, and nuclear correlations is calculated and found to be able to account for large fluctuations in transverse energy spectra. Numerical implementation of correlations and cross-section fluctuations in Monte-Carlo codes is discussed.Comment: 30 pages, in Revtex, plus 4 figures. Figures and preprint can be obtained by mailing address to: [email protected]

Evidence for Color Fluctuations in Hadrons from Coherent Nuclear Diffraction}

A QCD-based treatment of projectile size fluctuations is used to compute inelastic diffractive cross sections $\sigma_{diff}$ for coherent hadron-nuclear processes. We find that fluctuations near the average size give the major contribution to the cross section with $\le few \%$ contribution from small size configurations. The computed values of $\sigma_{diff}$ are consistent with the limited available data. The importance of coherent diffraction studies for a wide range of projectiles for high energy Fermilab fixed target experiments is emphasized. The implications of these significant color fluctuations for relativistic heavy ion collisions are discussed.Comment: Report number DOE/ER 40427-13-N93 11 pages, 3 figures available from author Mille

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). while the number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently in fisheries-induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life-history traits, behavior, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause fisheries-induced evolution with effects accumulating over time. Consequently, FIE may alter then utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons, An important reason this is not happening is the lack of an appropriate assessment framework. We therefor describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary outcomes of alternative management options. EvoIA can contribute to the ecosystem approach to fisheries management by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries

Computed tomography segmental calcium score (SCS) to predict stenosis severity of calcified coronary lesions

To estimate the probability of ≥50 % coronary stenoses based on computed tomography (CT) segmental calcium score (SCS) and clinical factors. The Institutional Review Board approved the study. A training sample of 201 patients underwent CT calcium scoring and conventional coronary angiography (CCA). All patients consented to undergo CT before CCA after being informed of the additional radiation dose. SCS and calcification morphology were assessed in individual coronary segments. We explored the predictive value of patient’s symptoms, clinical history, SCS and calcification morphology. We developed a prediction model in the training sample based on these variables then tested it in an independent test sample. The odds ratio (OR) for ≥50 % coronary stenosis was 1.8-fold greater (p = 0.006) in patients with typical chest pain, twofold (p = 0.014) greater in patients with acute coronary syndromes, twofold greater (p < 0.001) in patients with prior myocardial infarction. Spotty calcifications had an OR for ≥50 % stenosis 2.3-fold (p < 0.001) greater than the absence of calcifications, wide calcifications 2.7-fold (p < 0.001) greater, diffuse calcifications 4.6-fold (p < 0.001) greater. In middle segments, each unit of SCS had an OR 1.2-fold (p < 0.001) greater than in distal segments; in proximal segments the OR was 1.1-fold greater (p = 0.021). The ROC curve area of the prediction model was 0.795 (0.95 confidence interval 0.602–0.843). Validation in a test sample of 201 independent patients showed consistent diagnostic performance. In conjunction with calcification morphology, anatomical location, patient’s symptoms and clinical history, SCS can be helpful to estimate the probability of ≥50 % coronary stenosis