Estimates of crowding in long-term care: Comparing two approaches

Objective: Because studies of crowding in long-term care settings are lacking, the authors sought to: (1) generate initial estimates of crowding in nursing homes and assisted living facilities; and (2) evaluate two operational approaches to its measurement. ----- ----- Background: Reactions to density and proximity are complex. Greater density intensifies people's reaction to a situation in the direction (positive or negative) that they would react if the situation were to occur under less dense conditions. People with dementia are especially reactive to the environment. ----- ----- Methods: Using a cross-sectional correlational design in nursing homes and assisted living facilities involving 185 participants, multiple observations (N = 6,455) of crowding and other environmental variables were made. Crowding, location, and sound were measured three times per observation; ambiance was measured once. Data analyses consisted of descriptive statistics, t-tests, and one-way analysis of variance. ----- ----- Results: Crowding estimates were higher for nursing homes and in dining and activity rooms. Crowding also varied across settings and locations by time of day. Overall, the interaction of location and time affected crowding significantly (N = 5,559, df [47, 511], F = 105.69, p < .0001); effects were greater within location-by-hour than between location-by-hour, but the effect explained slightly less variance in Long-Term Care Crowding Index (LTC-CI) estimates (47.41%) than location alone. Crowding had small, direct, and highly significant correlations with sound and with the engaging subscale for ambiance; a similar, though inverse, correlation was seen with the soothing subscale for ambiance. ----- ----- Conclusions: Crowding fluctuates consistent with routine activities such as meals in long-term care settings. Furthermore, a relationship between crowding and other physical characteristics of the environment was found. The LTC-CI is likely to be more sensitive than simple people counts when seeking to evaluate the effects of crowding on the behavior of elders-particularly those with dementia-in long-term care settings. aging in place.

Velocity-jump models with crowding effects

Velocity jump processes are discrete random walk models that have many applications including the study of biological and ecological collective motion. In particular, velocity jump models are often used to represent a type of persistent motion, known as a “run and tumble”, which is exhibited by some isolated bacteria cells. All previous velocity jump processes are non-interacting, which means that crowding effects and agent-to-agent interactions are neglected. By neglecting these agent-to-agent interactions, traditional velocity jump models are only applicable to very dilute systems. Our work is motivated by the fact that many applications in cell biology, such as wound healing, cancer invasion and development, often involve tissues that are densely packed with cells where cell-to-cell contact and crowding effects can be important. To describe these kinds of high cell density problems using a velocity jump process we introduce three different classes of crowding interactions into a one-dimensional model. Simulation data and averaging arguments lead to a suite of continuum descriptions of the interacting velocity jump processes. We show that the resulting systems of hyperbolic partial differential equations predict the mean behavior of the stochastic simulations very well.

Models of collective cell behaviour with crowding effects : comparing lattice-based and lattice-free approaches

Individual-based models describing the migration and proliferation of a population of cells frequently restrict the cells to a predefined lattice. An implicit assumption of this type of lattice based model is that a proliferative population will always eventually fill the lattice. Here we develop a new lattice-free individual-based model that incorporates cell-to-cell crowding effects. We also derive approximate mean-field descriptions for the lattice-free model in two special cases motivated by commonly used experimental setups. Lattice-free simulation results are compared to these mean-field descriptions and to a corresponding lattice-based model. Data from a proliferation experiment is used to estimate the parameters for the new model, including the cell proliferation rate, showing that the model fits the data well. An important aspect of the lattice-free model is that the confluent cell density is not predefined, as with lattice-based models, but an emergent model property. As a consequence of the more realistic, irregular configuration of cells in the lattice-free model, the population growth rate is much slower at high cell densities and the population cannot reach the same confluent density as an equivalent lattice-based model.

Lattice-free descriptions of collective motion with crowding and adhesion

Cell-to-cell adhesion is an important aspect of malignant spreading that is often observed in images from the experimental cell biology literature. Since cell-to-cell adhesion plays an important role in controlling the movement of individual malignant cells, it is likely that cell-to-cell adhesion also influences the spatial spreading of populations of such cells. Therefore, it is important for us to develop biologically realistic simulation tools that can mimic the key features of such collective spreading processes to improve our understanding of how cell-to-cell adhesion influences the spreading of cell populations. Previous models of collective cell spreading with adhesion have used lattice-based random walk frameworks which may lead to unrealistic results, since the agents in the random walk simulations always move across an artificial underlying lattice structure. This is particularly problematic in high-density regions where it is clear that agents in the random walk align along the underlying lattice, whereas no such regular alignment is ever observed experimentally. To address these limitations, we present a lattice-free model of collective cell migration that explicitly incorporates crowding and adhesion. We derive a partial differential equation description of the discrete process and show that averaged simulation results compare very well with numerical solutions of the partial differential equation.

Effect of Crowding Agents, Signal Peptide, and Chaperone SecB on the Folding and Aggregation of E. coli Maltose Binding Protein

SecB, a soluble cytosolic chaperone component of the Secexport pathway, binds to newly synthesized precursor proteins and prevents their premature aggregation and folding and subsequently targets them to the translocation machinery on the membrane. PreMBP, the precursor form of maltose binding protein, has a 26-residue signal sequence attached to the N-terminus of MBP and is a physiological substrate of SecB. We examine the effect of macromolecular crowding and SecB on the stability and refolding of denatured preMBP and MBP. PreMBP was less stable than MBP (ΔTm =7( 0.5 K) in both crowded and uncrowded solutions. Crowding did not cause any substantial changes in the thermal stability ofMBP(ΔTm=1(0.4 K) or preMBP (ΔTm=0(0.6 K), as observed in spectroscopically monitored thermal unfolding experiments. However, both MBP and preMBP were prone to aggregation while refolding under crowded conditions. In contrast to MBP aggregates, which were amorphous, preMBP aggregates form amyloid fibrils.Under uncrowded conditions, a molar excess of SecB was able to completely prevent aggregation and promote disaggregation of preformed aggregates of MBP. When a complex of the denatured protein and SecB was preformed, SecB could completely prevent aggregation and promote folding of MBP and preMBP even in crowded solution. Thus, in addition to maintaining substrates in an unfolded, export-competent conformation, SecB also suppresses the aggregation of its substrates in the crowded intracellular environment. SecB is also able to promote passive disaggregation of macroscopic aggregates of MBP in the absence of an energy source such as ATP or additional cofactors. These experiments also demonstrate that signal peptide can reatly influence protein stability and aggregation propensity.

Crowding, molecular volume and plasticity: An assessment involving crystallography, NMR and simulations

The discrepancy between the X-ray and NMR structures of Mycobacterium tuberculosis peptidyl-tRNA hydrolase in relation to the functionally important plasticity of the molecule led to molecular dynamics simulations. The X-ray and the NMR studies along with the simulations indicated an inverse correlation between crowding and molecular volume. A detailed comparison of proteins for which X-ray and the NMR structures appears to confirm this correlation. In consonance with the reported results of the investigations in cellular compartments and aqueous solution, the comparison indicates that the crowding results in compaction of the molecule as well as change in its shape, which could specifically involve regions of the molecule important in function. Crowding could thus influence the action of proteins through modulation of the functionally important plasticity of the molecule. Selvaraj M, Ahmad R, Varshney U and Vijayan M 2012 Crowding, molecular volume and plasticity: An assessment involving crystallography, NMR and simulations. J. Biosci. 37 953-963] DOI 10.1007/s12038-012-9276-5

Periodically Grafted Amphiphilic Copolymers: Effects of Steric Crowding and Reversal of Amphiphilicity

Two series of periodically clickable polyesters were prepared; one of them carries alkylene segments along its backbone, whereas the other carries poly(ethylene glycol) (PEG) segments. These polyesters were clicked with either MPEG-350 azide or docosyl (C22) azide to yield periodically grafted amphiphilic copolymers (PGACs) carrying either flexible hydrophilic or crystallizable hydrophobic backbone segments. The immiscibility between hydrocarbon and PEG segments causes both of these systems to fold in either a zigzag or hairpin-like conformation; the hairpin-like conformation appears to be preferred when flexible PEG segments are present in the backbone. The folded chains further reorganize in the solid state to develop a lamellar morphology that permits the collocation of the PEG and hydrocarbon (HC) segments within alternate domains; evidence for the self-segregation was gained from DSC, SAXS, and AFM studies. SAXS studies revealed the formation of an extended lamellar structure, whereas AFM images showed uniform layered morphology with layer heights that matched reasonably well with the interlamellar spacing obtained from the SAXS study. Labeling One representative PGAC, carrying crystallizable long alkylene segments in the backbone and pendant PEG-350 side chains, with a small mole fraction of pyrene fluorophore permitted the examination of the conformational transition that occurs upon going from a good to a poor solvent; this single-chain folded conformation, we postulate, is the intermediate that organizes into the lamellar morphology.

Targeting human telomeric G-quadruplex DNA with curcumin and its synthesized analogues under molecular crowding conditions

The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.

Targeting human telomeric G-quadruplex DNA with curcumin and its synthesized analogues under molecular crowding conditions

The formation of telomeric G-quadruplexes has been shown to inhibit telomerase activity. Indeed, a number of small molecules capable of p-stacking with G-tetrads have shown the ability to inhibit telomerase activity through the stabilization of G-quadruplexes. Curcumin displays a wide spectrum of medicinal properties ranging from anti-bacterial, anti-viral, anti-protozoal, anti-fungal and anti-inflammatory to anti-cancer activity. We have investigated the interactions of curcumin and its structural analogues with the human telomeric sequence AG(3)(T(2)AG(3))(3) under molecular crowding conditions. Experimental studies indicated the existence of a AG(3)(T(2)AG(3))(3)/curcumin complex with binding affinity of 0.72 x 10(6) M-1 under molecular crowding conditions. The results from UV-visible absorption spectroscopy, a fluorescent TO displacement assay, circular dichroism and molecular docking studies, imply that curcumin and their analogues interact with G-quadruplex DNA via groove binding. While other analogs of curcumin studied here bind to G-quadruplexes in a qualitatively similar manner their affinities are relatively lower in comparison to curcumin. The Knoevenagel condensate, a methoxy-benzylidene derivative of curcumin, also exhibited significant binding to G-quadruplex DNA, although with two times decreased affinity. Our study establishes the potential of curcumin as a promising natural product for G-quadruplex specific ligands.

Emergency department crowding: prioritising quantified crowding measures using a Delphi study.

AimsEmergency department (ED) crowding has been associated with a number of negative health outcomes, including unnecessary deaths, increased waiting times and a decrease in care quality. Despite the seriousness of this issue, there is little agreement on appropriate crowding measures to assess crowding effects on ED operations. The objective of this study was to prioritise a list of quantified crowding measures that would assess the current state of a department.MethodsA three round Delphi study was conducted via email and an Internet based survey tool. The panel consisted of 40 professionals who had exposure to and expertise in crowding. Participants submitted quantified crowding measures which, through three rounds, were evaluated and ranked to assess participant agreement for inclusion.ResultsThe panel identified 27 measures of which eight (29.6%) reached consensus at the end of the study. These measures comprised: (1) ability of ambulances to offload; (2) patients who leave without being seen or treated; (3) time until triage; (4) ED occupancy rate; (5) patients' total length of stay in the ED; (6) time to see a physician; (7) ED boarding time; and (8) number of patients boarding in the ED.ConclusionsThis study resulted in the identification of eight quantified crowding measures, which present a comprehensive view of how crowding is affecting ED operations, and highlighted areas of concern. These quantified measures have the potential to make a considerable contribution to decision making by ED management and to provide a basis for learning across different departments.

Comparing crowding in human and ideal observers.

A visual target is more difficult to recognize when it is surrounded by other, similar objects. This breakdown in object recognition is known as crowding. Despite a long history of experimental work, computational models of crowding are still sparse. Specifically, few studies have examined crowding using an ideal-observer approach. Here, we compare crowding in ideal observers with crowding in humans. We derived an ideal-observer model for target identification under conditions of position and identity uncertainty. Simulations showed that this model reproduces the hallmark of crowding, namely a critical spacing that scales with viewing eccentricity. To examine how well the model fits quantitatively to human data, we performed three experiments. In Experiments 1 and 2, we measured observers' perceptual uncertainty about stimulus positions and identities, respectively, for a target in isolation. In Experiment 3, observers identified a target that was flanked by two distractors. We found that about half of the errors in Experiment 3 could be accounted for by the perceptual uncertainty measured in Experiments 1 and 2. The remainder of the errors could be accounted for by assuming that uncertainty (i.e., the width of internal noise distribution) about stimulus positions and identities depends on flanker proximity. Our results provide a mathematical restatement of the crowding problem and support the hypothesis that crowding behavior is a sign of optimality rather than a perceptual defect.

A neurophysiologically plausible population code model for feature integration explains visual crowding.

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

A crowding model of visual clutter.

Visual information is difficult to search and interpret when the density of the displayed information is high or the layout is chaotic. Visual information that exhibits such properties is generally referred to as being "cluttered." Clutter should be avoided in information visualizations and interface design in general because it can severely degrade task performance. Although previous studies have identified computable correlates of clutter (such as local feature variance and edge density), understanding of why humans perceive some scenes as being more cluttered than others remains limited. Here, we explore an account of clutter that is inspired by findings from visual perception studies. Specifically, we test the hypothesis that the so-called "crowding" phenomenon is an important constituent of clutter. We constructed an algorithm to predict visual clutter in arbitrary images by estimating the perceptual impairment due to crowding. After verifying that this model can reproduce crowding data we tested whether it can also predict clutter. We found that its predictions correlate well with both subjective clutter assessments and search performance in cluttered scenes. These results suggest that crowding and clutter may indeed be closely related concepts and suggest avenues for further research.