Branch Mode Selection during Early Lung Development

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modesComment: Initially published at PLoS Comput Bio

Sleep-effects on implicit and explicit memory in repeated visual search

In repeated visual search tasks, facilitation of reaction times (RTs) due to repetition of the spatial arrangement of items occurs independently of RT facilitation due to improvements in general task performance. Whereas the latter represents typical procedural learning, the former is a kind of implicit memory that depends on the medial temporal lobe (MTL) memory system and is impaired in patients with amnesia. A third type of memory that develops during visual search is the observers’ explicit knowledge of repeated displays. Here, we used a visual search task to investigate whether procedural memory, implicit contextual cueing, and explicit knowledge of repeated configurations, which all arise independently from the same set of stimuli, are influenced by sleep. Observers participated in two experimental sessions, separated by either a nap or a controlled rest period. In each of the two sessions, they performed a visual search task in combination with an explicit recognition task. We found that (1) across sessions, MTL-independent procedural learning was more pronounced for the nap than rest group. This confirms earlier findings, albeit from different motor and perceptual tasks, showing that procedural memory can benefit from sleep. (2) Likewise, the sleep group compared with the rest group showed enhanced context-dependent configural learning in the second session. This is a novel finding, indicating that the MTL-dependent, implicit memory underlying contextual cueing is also sleep-dependent. (3) By contrast, sleep and wake groups displayed equivalent improvements in explicit recognition memory in the second session. Overall, the current study shows that sleep affects MTL-dependent as well as MTL-independent memory, but it affects different, albeit simultaneously acquired, forms of MTL-dependent memory differentially

Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

Does Sleep Improve Your Grammar? : Preferential Consolidation of Arbitrary Components of New Linguistic Knowledge

We examined the role of sleep-related memory consolidation processes in learning new form-meaning mappings. Specifically, we examined a Complementary Learning Systems account, which implies that sleep-related consolidation should be more beneficial for new hippocampally dependent arbitrary mappings (e.g. new vocabulary items) relative to new systematic mappings (e.g. grammatical regularities), which can be better encoded neocortically. The hypothesis was tested using a novel language with an artificial grammatical gender system. Stem-referent mappings implemented arbitrary aspects of the new language, and determiner/suffix+natural gender mappings implemented systematic aspects (e.g. tib scoiffesh + ballerina, tib mofeem + bride; ked jorool + cowboy, ked heefaff + priest). Importantly, the determiner-gender and the suffix-gender mappings varied in complexity and salience, thus providing a range of opportunities to detect beneficial effects of sleep for this type of mapping. Participants were trained on the new language using a word-picture matching task, and were tested after a 2-hour delay which included sleep or wakefulness. Participants in the sleep group outperformed participants in the wake group on tests assessing memory for the arbitrary aspects of the new mappings (individual vocabulary items), whereas we saw no evidence of a sleep benefit in any of the tests assessing memory for the systematic aspects of the new mappings: Participants in both groups extracted the salient determiner-natural gender mapping, but not the more complex suffix-natural gender mapping. The data support the predictions of the complementary systems account and highlight the importance of the arbitrariness/systematicity dimension in the consolidation process for declarative memories

Modeling of B cell Synapse Formation by Monte Carlo Simulation Shows That Directed Transport of Receptor Molecules Is a Potential Formation Mechanism

The formation of the protein segregation structure known as the “immunological synapse” in the contact region between B cells and antigen presenting cells appears to precede antigen (Ag) uptake by B cells. The mature B cell synapse consists of a central cluster of B cell receptor/Antigen (BCR/Ag) complexes surrounded by a ring of LFA-1/ICAM-1 complexes. In this study, we used an in silico model to investigate whether cytoskeletally driven transport of molecules toward the center of the contact zone is a potential mechanism of immunological synapse formation in B cells. We modeled directed transport by the cytoskeleton in an effective manner, by biasing the diffusion of molecules toward the center of the contact zone. Our results clearly show that biased diffusion of BCR/Ag complexes on the B cell surface is sufficient to produce patterns similar to experimentally observed immunological synapses. This is true even in the presence of significant membrane deformation as a result of receptor–ligand binding, which in previous work we showed had a detrimental effect on synapse formation at high antigen affinity values. Comparison of our model’s results to those of experiments shows that our model produces synapses for realistic length, time, and affinity scales. Our results also show that strong biased diffusion of free molecules has a negative effect on synapse formation by excluding BCR/Ag complexes from the center of the contact zone. However, synapses may still form provided the bias in diffusion of free molecules is an order-of-magnitude weaker than that of BCR/Ag complexes. We also show how diffusion trajectories obtained from single-molecule tracking experiments can generate insight into the mechanism of synapse formation

A computational analysis of the dynamic roles of talin, Dok1, and PIPKI for integrin activation

Integrin signaling regulates cell migration and plays a pivotal role in developmental processes and cancer metastasis. Integrin signaling has been studied extensively and much data is available on pathway components and interactions. Yet the data is fragmented and an integrated model is missing. We use a rule-based modeling approach to integrate available data and test biological hypotheses regarding the role of talin, Dok1 and PIPKI in integrin activation. The detailed biochemical characterization of integrin signaling provides us with measured values for most of the kinetics parameters. However, measurements are not fully accurate and the cellular concentrations of signaling proteins are largely unknown and expected to vary substantially across different cellular conditions. By sampling model behaviors over the physiologically realistic parameter range we find that the model exhibits only two different qualitative behaviours and these depend mainly on the relative protein concentrations, which offers a powerful point of control to the cell. Our study highlights the necessity to characterize model behavior not for a single parameter optimum, but to identify parameter sets that characterize different signaling modes

Hostos Online Learning Assessment: A Survey of Student Perceptions

The Office of Education Technology (EdTech) at Hostos Community College and faculty members from various departments created the Hostos Online Learning Assessment (HOLA) Task Force to design a survey for gathering and assessing data about students’ perceptions of their online learning experiences. The task force wanted to utilize the survey results to identify strengths and weaknesses in online instruction and student preparedness for the online learning environment. Student perceptions of online learning are integral to building upon current best practices and also gauging the preparedness of the students for the online learning environment, particularly in an urban, Hispanic-serving community college. The survey and results will be discussed within the broader context of best practices and online learning assessments as well as the way the HOLA Task Force is utilizing the data to make meaningful changes in the survey instrument, in addition planning for continuous improvement in online learning

Monte Carlo Investigation of Diffusion of Receptors and Ligands that Bind Across Opposing Surfaces

Studies of receptor diffusion on a cell surface show a variety of behaviors, such as diffusive, sub-diffusive, or super-diffusive motion. However, most studies to date focus on receptor molecules diffusing on a single cell surface. We have previously studied receptor diffusion to probe the molecular mechanism of receptor clustering at the cell–cell junction between two opposing cell surfaces. Here, we characterize the diffusion of receptors and ligands that bind to each other across two opposing cell surfaces, as in cell–cell and cell–bilayer interactions. We use a Monte Carlo method, where receptors and ligands are simulated as independent agents that bind and diffuse probabilistically. We vary receptor–ligand binding affinity and plot the molecule-averaged mean square displacement (MSD) of ligand molecules as a function of time. Our results show that MSD plots are qualitatively different for flat and curved interfaces, as well as between the cases of presence and absence of directed transport of receptor–ligand complexes toward a specific location on the interface. Receptor–ligand binding across two opposing surfaces leads to transient sub-diffusive motion at early times provided the interface is flat. This effect is entirely absent if the interface is curved, however, in this instance we observe sub-diffusive motion. In addition, a decrease in the equilibrium value of the MSD occurs as affinity increases, something which is absent for a flat interface. In the presence of directed transport of receptor–ligand complexes, we observe super-diffusive motion at early times for a flat interface. Super-diffusive motion is absent for a curved interface, however, in this case we observe a transient decrease in MSD with time prior to equilibration for high-affinity values