An ultra scale-down analysis of the recovery by dead-end centrifugation of human cells for therapy.

An ultra scale-down method is described to determine the response of cells to recovery by dead-end (batch) centrifugation under commercially defined manufacturing conditions. The key variables studied are the cell suspension hold time prior to centrifugation, the relative centrifugal force (RCF), time of centrifugation, cell pellet resuspension velocities, and number of resuspension passes. The cell critical quality attributes studied are the cell membrane integrity and the presence of selected surface markers. Greater hold times and higher RCF values for longer spin times all led to the increased loss of cell membrane integrity. However, this loss was found to occur during intense cell resuspension rather than the preceding centrifugation stage. Controlled resuspension at low stress conditions below a possible critical stress point led to essentially complete cell recovery even at conditions of extreme centrifugation (e.g., RCF of 10000 g for 30 mins) and long (~2 h) holding times before centrifugation. The susceptibility to cell loss during resuspension under conditions of high stress depended on cell type and the age of cells before centrifugation and the level of matrix crosslinking within the cell pellet as determined by the presence of detachment enzymes or possibly the nature of the resuspension medium. Changes in cell surface markers were significant in some cases but to a lower extent than loss of cell membrane integrity. Biotechnol. Bioeng. 2015;112: 997-1011. © 2014 Wiley Periodicals, Inc

Future impacts of fresh water resource management: sensitivity of coastal deltas

We present an assessment of contemporary and future effective sealevel rise (ESLR) using a sample of 40 deltas distributed worldwide. For any delta, ESLR is a net rate defined by eustatic sea-level rise, natural gross rates of fluvial sediment deposition and subsidence, and accelerated subsidence due to groundwater and hydrocarbon extraction. Present-day ESLR, estimated from geospatial data and a simple model of deltaic dynamics, ranges from 0.5 to 12.5 mm year-1. Reduced accretion of fluvial sediment from upstream siltation of reservoirs and freshwater consumptive irrigation losses are primary determinants of ESLR in nearly 70% of the deltas, while for only 12% eustatic sea-level rise predominates. Future scenarios indicate a much larger impact on deltas than previously estimated. Serious challenges to human occupancy of deltas worldwide are conveyed by upland watershed factors, which have been studied less comprehensively than the climate change and sea-level rise question

W49A North - Global or Local or No Collapse?

We attempt to fit observations with 5" resolution of the J=2-1 transition of CS in the directions of H II regions A, B, and G of W49A North as well as observations with 20" resolution of the J=2-1, 3-2, 5-4, and 7-6 transitions in the directions of H II regions A and G by using radiative transfer calculations. These calculations predict the intensity profiles resulting from several spherical clouds along the line of sight. We consider three models: global collapse of a very large (5 pc radius) cloud, localized collapse from smaller (1 pc) clouds around individual H II regions, and multiple, static clouds. For all three models we can find combinations of parameters that reproduce the CS profiles reasonably well provided that the component clouds have a core-envelope structure with a temperature gradient. Cores with high temperature and high molecular hydrogen density are needed to match the higher transitions (e.g. J=7-6) observed towards A and G. The lower temperature, low density gas needed to create the inverse P-Cygni profile seen in the CS J=2-1 line (with 5" beam) towards H II region G arises from different components in the 3 models. The infalling envelope of cloud G plus cloud B creates the absorption in global collapse, cloud B is responsible in local collapse, and a separate cloud, G', is needed in the case of many static clouds. The exact nature of the velocity field in the envelopes for the case of local collapse is not important as long as it is in the range of 1 to 5 km/s for a turbulent velocity of about 6 km/s. High resolution observations of the J=1-0 and 5-4 transitions of CS and C34S may distinguish between these three models. Modeling existing observations of HCO+ and C18O does not allow one to distinguish between the three models but does indicate the existence of a bipolar outflow.Comment: 42 pages, 27 figures, accepted for publication in the ApJS August 2004, v153 issu

Differential Synchronization in Default and Task-Specific Networks of the Human Brain

On a regional scale the brain is organized into dynamic functional networks. The activity within one of these, the default network, can be dissociated from that in other task-specific networks. All brain networks are connected structurally but evidently are only transiently connected functionally. One hypothesis as to how such transient functional coupling occurs is that network formation and dissolution is mediated by increases and decreases in oscillatory synchronization between constituent brain regions. If so, then we should be able to find transient differences in intra-network synchronization between the default network and a task-specific network. In order to investigate this hypothesis we conducted two experiments in which subjects engaged in a Sustained Attention to Response Task while having brain activity recorded via high-density electroencephalography (EEG). We found that during periods when attention was focused internally (mind wandering) there was significantly more neural phase synchronization between brain regions associated with the default network, whereas during periods when subjects were focused on performing the visual task there was significantly more neural phase synchrony within a task-specific brain network that shared some of the same brain regions. These differences in network synchrony occurred in each of theta, alpha, and gamma frequency bands. A similar pattern of differential oscillatory power changes, indicating modulation of local synchronization by attention state, was also found. These results provide further evidence that the human brain is intrinsically organized into default and task-specific brain networks, and confirm that oscillatory synchronization is a potential mechanism for functional coupling within these networks

Towards a unified understanding of event-related changes in the EEG:the Firefly model of synchronization through cross-frequency phase modulation

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing