Perspectives and experiences of Chinese nurses on quality improvement initiatives: A mixed-methods study.

AIM: To investigate Chinese nurses' views and experiences in relation to quality improvement implementation, as well as to determine the impact of contextual factors on nursing quality improvement initiatives. BACKGROUND: Nurses play a major role in carrying out quality improvement initiatives. Contextual factors influence the implementation and success of quality improvement initiatives. Studies that investigated the impact of contextual factors on Chinese nurses' practice in quality improvement remain limited. METHODS: A sequential explanatory mixed-methods design was used for this study. A quantitative cross-sectional survey was used to assess the context of quality improvement initiatives. Simple random sampling was used to recruit quality improvement teams. The sample included 356 nurses from tertiary teaching hospitals; 291 (81.7%) of them completed questionnaires. Nursing managers and nurses (n = 18) were purposively selected to participate in semi-structured interviews; their experiences and perceptions regarding the contextual factors of quality improvement initiatives were obtained. RESULTS: In the quantitative phase, the "microsystem" (mean=5.24) and "QI team" (mean = 4.97) contexts were reported as supportive contexts. The organizational context was weak, with a mean score of 3.92. In the qualitative phase, three themes related to the contextual challenges emerged: (1) nurses' attitudes and satisfaction, (2) team efficacy, and (3) organizational infrastructure and culture. CONCLUSIONS: Efforts to elevate organizational culture and reward systems are needed in Chinese hospitals. Further education aimed at increasing skills and knowledge should be provided, to ensure effective quality improvement implementation. IMPLICATIONS FOR NURSING MANAGEMENT: During quality improvement initiatives, management tasks should focus on increasing nurses' satisfaction, solving skill and knowledge deficits, and clarifying nurses' roles in relation to quality improvement.

Mechanism of lignin inhibition of enzymatic biomass deconstruction.

BACKGROUND: The conversion of plant biomass to ethanol via enzymatic cellulose hydrolysis offers a potentially sustainable route to biofuel production. However, the inhibition of enzymatic activity in pretreated biomass by lignin severely limits the efficiency of this process. RESULTS: By performing atomic-detail molecular dynamics simulation of a biomass model containing cellulose, lignin, and cellulases (TrCel7A), we elucidate detailed lignin inhibition mechanisms. We find that lignin binds preferentially both to the elements of cellulose to which the cellulases also preferentially bind (the hydrophobic faces) and also to the specific residues on the cellulose-binding module of the cellulase that are critical for cellulose binding of TrCel7A (Y466, Y492, and Y493). CONCLUSIONS: Lignin thus binds exactly where for industrial purposes it is least desired, providing a simple explanation of why hydrolysis yields increase with lignin removal.

Nucleation dynamics of active particles.

We present a model of a collection of active and adhesive Brownian particles that are capable of aggregation. Besides the mechanical interaction between particles, a simple active dynamics term (motility) is included to provide an active movement. At a given instant, each particle is either in an active (swim) or unanimated (stop) state, which is controlled by a random process. The model includes important features that are inspired by the phenomenon of biological cell-cell association. One feature is the mean motility that is related to the percentage of the particle being active and the maximum swimming speed. Another feature is the stochastic nature of switching between the swim and stop state. We explored how these key features affect the nucleation dynamics and the stability of the aggregates using simulations. Interestingly, particles can change their collective behavior by solely altering the frequency of switching between the swim and stop state while keeping the mean motility unchanged. These results provide insight into how motor-driven forces can be utilized by active biological systems to modulate the single-to-cluster transition efficiently. A dimensionless parameter is also proposed to measure the overall strength of the nonequilibrium effect on active particles.

Swimming motility plays a key role in the stochastic dynamics of cell clumping.

Dynamic cell-to-cell interactions are a prerequisite to many biological processes, including development and biofilm formation. Flagellum induced motility has been shown to modulate the initial cell-cell or cell-surface interaction and to contribute to the emergence of macroscopic patterns. While the role of swimming motility in surface colonization has been analyzed in some detail, a quantitative physical analysis of transient interactions between motile cells is lacking. We examined the Brownian dynamics of swimming cells in a crowded environment using a model of motorized adhesive tandem particles. Focusing on the motility and geometry of an exemplary motile bacterium Azospirillum brasilense, which is capable of transient cell-cell association (clumping), we constructed a physical model with proper parameters for the computer simulation of the clumping dynamics. By modulating mechanical interaction ('stickiness') between cells and swimming speed, we investigated how equilibrium and active features affect the clumping dynamics. We found that the modulation of active motion is required for the initial aggregation of cells to occur at a realistic time scale. Slowing down the rotation of flagellar motors (and thus swimming speeds) is correlated to the degree of clumping, which is consistent with the experimental results obtained for A. brasilense.

A variational model for oligomer-formation process of GNNQQNY peptide from yeast prion protein Sup35.

Many human neurodegenerative diseases are associated with the aggregation of insoluble amyloid-like fibrous proteins. However, the processes by which the randomly diffused monomer peptides aggregate into the highly regulated amyloid fibril structures are largely unknown. We proposed a residue-level coarse-grained variational model for the investigation of the aggregation pathway for a small assembly of amyloid proteins, the peptide GNNQQNY from yeast prion protein Sup35. By examining the free energy surface, we identified the residue-level sequential pathways for double parallel and antiparallel ß-peptides, which show that the central dry polar zipper structure is the major folding core in both cases. The critical nucleus size is determined to be three peptides for the homogeneous nucleation process, whereas the zig-zag growth pattern appears most favorably for heterogeneous nucleation. Consistent with the dock-and-lock mechanism, the aggregation process of free peptides to the fibril core was found to be highly cooperative. The quantitative validation with the computational simulations and experimental data demonstrated the usefulness of the proposed model in understanding the general mechanism of the amyloid fibril system.

Dissecting the kinetic process of amyloid fiber formation through asymptotic analysis.

Amyloids are insoluble fibrous protein aggregates which, when abnormally accumulated in the body, can result in amyloidosis and various neurodegenerative diseases. In this work, we describe a new approach to the asymptotic solution of the master equation of amyloid fiber aggregations. It is found that four distinct and successive stages (lag phase, exponential growth phase, breaking phase, and static phase) dominate the fiber formation process. On the basis of the distinctive power-law dependence of the half-time and apparent growth rate of the fiber formation on the initial protein concentration, we propose a novel classification for amyloid proteins theoretically.

A lattice-gas model for amyloid fibril aggregation.

A simple lattice-gas model, with two fundamental energy terms -elongation and nucleation effects, is proposed for understanding the mechanisms of amyloid fibril formation. Based on the analytical solution and Monte Carlo simulation of 1D system, we have thoroughly explored the dependence of mass concentration, number concentration of amyloid filaments and the lag-time on the initial protein concentration, the critical nucleus size, the strengths of nucleation and elongation effects, respectively. We also found that thickening process (self-association of filaments into multi-strand fibrils) is not essential for the modeling of amyloid filaments through simulations on 2D lattice. Compared with the kinetic model recently proposed by Knowles et al., highly quantitative consistency of two models in the calculation of mass fraction of filaments is found. Moreover our model can generate a better prediction on the number fraction, which is closer to experimental values when the elongation strength gets stronger.

Capillarity-like growth of protein folding nuclei.

A full structural description of transition state ensembles in protein folding includes the specificity of the ordered residues composing the folding nucleus as well as spatial density. To our knowledge, the spatial properties of the folding nucleus and interface of specific nuclei have yet to receive significant attention. We analyze folding routes predicted by a variational model in terms of a generalized formalism of the capillarity scaling theory that assumes the volume of the folded core of the nucleus grows with chain length as V(f) approximately N(3nu). For 27 two-state proteins studied, the scaling exponent nu ranges from 0.2 to 0.45 with an average of 0.33. This average value corresponds to packing of rigid objects, although generally the effective monomer size in the folded core is larger than the corresponding volume per particle in the native-state ensemble. That is, on average, the folded core of the nucleus is found to be relatively diffuse. We also study the growth of the folding nucleus and interface along the folding route in terms of the density or packing fraction. The evolution of the folded core and interface regions can be classified into three patterns of growth depending on how the growth of the folded core is balanced by changes in density of the interface. Finally, we quantify the diffuse versus polarized structure of the critical nucleus through direct calculation of the packing fraction of the folded core and interface regions. Our results support the general picture of describing protein folding as the capillarity-like growth of folding nuclei.

Excluded volume, local structural cooperativity, and the polymer physics of protein folding rates.

A coarse-grained variational model is used to investigate the polymer dynamics of barrier crossing for a diverse set of two-state folding proteins. The model gives reliable folding rate predictions provided excluded volume terms that induce minor structural cooperativity are included in the interaction potential. In general, the cooperative folding routes have sharper interfaces between folded and unfolded regions of the folding nucleus and higher free energy barriers. The calculated free energy barriers are strongly correlated with native topology as characterized by contact order. Increasing the rigidity of the folding nucleus changes the local structure of the transition state ensemble nonuniformly across the set of proteins studied. Nevertheless, the calculated prefactors k(0) are found to be relatively uniform across the protein set, with variation in 1/k(0) less than a factor of 5. This direct calculation justifies the common assumption that the prefactor is roughly the same for all small two-state folding proteins. Using the barrier heights obtained from the model and the best-fit monomer relaxation time 30 ns, we find that 1/k(0) approximately 1-5 mus (with average 1/k(0) approximately 4 micros). This model can be extended to study subtle aspects of folding such as the variation of the folding rate with stability or solvent viscosity and the onset of downhill folding.