Modeling and Control of COVID-19 Transmission from a Perspective of Polymerization Reaction Dynamics.

Due to the serious economic losses and deaths caused by COVID-19, the modeling and control of such a pandemic has become a hot research topic. This paper finds an analogy between a polymerization reaction and COVID-19 transmission dynamics, which will provide a novel perspective to optimal control measures. Susceptible individuals, exposed people, infected cases, recovered population, and the dead can be assumed to be specific molecules in the polymerization system. In this paper, a hypothetical polymerization reactor is constructed to describe the transmission of an epidemic, and its kinetic parameters are regressed by the least-squares method. The intensity of social distancing u is considered to the mixing degree of the reaction system, and contact tracing and isolation ρ can be regarded as an external circulation in the main reactor to reduce the concentration of active species. Through these analogies, this model can predict the peak infection, deaths, and end time of the epidemic under different control measures to support the decision-making process. Without any measures (u = 1.0 and ρ = 0), more than 90% of the population would be infected. It takes several years to complete herd immunity by nonpharmacological intervention when the proportion of deaths is limited to less than 5%. However, vaccination can reduce the time to tens to hundreds of days, which is related to the maximum number of vaccines per day.

[Measurement of properties of polypropylene copolymers by Raman spectrum].

Fourier-transform (FT) Raman spectra were measured for 7 kinds of different polypropylene copolymers and the assignments of all Raman bands were made through a detailed analysis. Ultimately, by choosing 2 700-3 100 cm(-1) as the characteristic spectral, partial least squares (PLS) regression models were set up for xylene solubles content, ethylene content and ethylene content of xylene solubles in polypropylene copolymers. The values of correlation coefficient (r) between predicted results and actual values were all greater than 0.94, and the values of average relative error (ARE) were all less than 5%. The second PLS factor was also analyzed in this paper, and it was concluded that the original information of the sample was accurately extracted by using PLS regression. This paper offered a kind of possibility for on-line measurement of xylene solubles content, ethylene content and ethylene content of xylene solubles in polypropylene copolymers.

[Quantitative determination of PVC concentration by Raman spectrum].

Quantitative determination of polyvinyl chloride (PVC) concentration by Raman spectrum was studied in the present work. According to partial least squares (PLS) analysis, it was found that scores of PLS factor 1 were proportional to the concentrations of the sample solutions. Meanwhile, the loadings of factor 1 could reflect the contents of PVC and cyclohexanone simultaneously. The PLS regression model for PVC concentration prediction was built. The values of r and root mean square error (RMSE) between predictive results and actual values were 0.9963 and 2.775, respectively. The Raman characteristic peaks of PVC and cyclohexanone were found, including the C-Cl bond for PVC (620 and 695 cm(-1)) and the alicyclic ketone for cyclohexanone (1709 cm(-1)). By using internal standard method, another model for PVC concentration prediction was established, and the values of r and RMSE were 0.9941 and 3.151, respectively. The results indicated that it is feasible to use Raman spectrum to detect the PVC concentration, which is of significant importance to PVC recycling.

[Measurement of ethylene content in polypropylene by Raman spectrum].

Ethylene content in polypropylene was studied by Raman spectrum, combined with partial least squares (PLS) method. The comparison between Raman spectra for polyethylene and polypropylene was carried out, and the spectra between 50 and 600, 600 and 1600, and 2700 and 3100 cm(-1) were analyzed respectively. The models for ethylene content prediction were built, while the model based on 50-3600 cm(-1) spectra gave the best performance. The experiment indicated that Raman spectrum gave the similar predictive results as the near infrared (NIR) spectrum; the values of correlation coefficient (r), relative average deviation (RAD) and root mean square error (RMSE) between predictive results and actual values were 0.995, 2.65% and 0.319, respectively. According to PLS analysis, the loadings of factor 1 could reflect the relationship between the composition of polypropylene molecular chain and ethylene content, and ethylene content had a positive correlation with CH2 content, but a negative correlation with content of CH3, C-H, and C-C. The results indicated that it was feasible to detect the ethylene content in polypropylene by Raman spectrum.

Atomic-scale simulations confirm that soluble beta-sheet-rich peptide self-assemblies provide amyloid mimics presenting similar conformational properties.

The peptide self-assembly mimic (PSAM) from the outer surface protein A (OspA) can form highly stable but soluble beta-rich self-assembly-like structures similar to those formed by native amyloid-forming peptides. However, unlike amyloids that predominantly form insoluble aggregates, PSAMs are highly water-soluble. Here, we characterize the conformations of these soluble beta-sheet-rich assemblies. We simulate PSAMs with different-sized beta-sheets in the presence and absence of end-capping proteins using all-atom explicit-solvent molecular dynamics, comparing the structural stability, conformational dynamics, and association force. Structural and free-energy comparisons among beta-sheets with different numbers of layers and sequences indicate that in similarity to amyloids, the intersheet side chain-side chain interactions and hydrogen bonds combined with intrasheet salt bridges are the major driving forces in stabilizing the overall structural organization. A detailed structural analysis shows that in similarity to amyloid fibrils, all wild-type and mutated PSAM structures display twisted and bent beta-sheets to some extent, implying that a twisted and bent beta-sheet is a general motif of beta-rich assemblies. Thus, our studies indicate that soluble beta-sheet-rich peptide self-assemblies can provide good amyloid mimics, and as such confirm on the atomic scale that they are excellent systems for amyloid studies. These results provide further insight into the usefulness of such mimics for nanostructure design.

Molecular modeling of two distinct triangular oligomers in amyloid beta-protein.

Amyloid-beta (Abeta) peptides exhibit many distinct structural morphology at the early aggregate stage, some of which are biological relevant to the pathogenesis of Alzheimer's disease (AD). Atomic-resolution structures of the early Abeta aggregates and their conformational changes in amyloid aggregation remain elusive. Here, we perform all-atom molecular modeling and dynamics simulations to obtain two stable triangular-like Abeta structures with the lowest packing energy, one corresponding to the Tycko's model (Paravastu, A.; Leapman, R.; Yau, W.; Tycko, R. Proc. Nat. Acad. Soc. U.S.A. 2008, 105, 18349-18354) (referred to C-WT model) and the other corresponding to computational model (N-WT model). Both models have the same 3-fold symmetry but distinct beta-sheet organizations in which three Abeta hexamers pack together via either C-terminal beta-strand residues or N-terminal beta-strand residues forming distinct hydrophobic cross section. Structural and energetic comparisons of two 3-fold Abeta oligomers, coupled with structural changes upon the mutations occurring at the interacting interfaces, reveal that although hydrophobic interactions are still dominant forces, electrostatic interactions are more favorable in the N-WT model due to the formation of more and stable intersheet salt bridges, while solvation energy is more favorable in the C-WT model due to more exposed hydrophilic residues to solvent. Both models display many common features similar to other amyloid oligomers and therefore are likely to be biologically relevant.

Comparative molecular dynamics study of Abeta adsorption on the self-assembled monolayers.

The adsorption and aggregation of the amyloid-beta (Abeta) peptides on the cell membrane plays a causal role in the pathogenesis of Alzheimer's disease. Here, we report all-atom molecular dynamics (MD) simulations to study the interactions of Abeta oligomer with self-assembled monolayers (SAMs) terminated with hydrophobic CH(3) and hydrophilic OH functional groups, with particular interests in how surface chemistry and Abeta orientation affect the adsorption behavior of Abeta. Simulation results show that the CH(3)-SAM has a stronger binding affinity to Abeta than the OH-SAM does, although both surfaces can induce Abeta adsorption. Regardless of the characteristics of the surface, the hydrophobic C-terminal region is more likely to be adsorbed on the SAMs, indicating a preferential orientation and interface for Abeta adsorption. Structural and energetic comparison among six Abeta-SAM systems further reveals that Abeta orientation, SAM surface hydrophobicity, and interfacial waters all determine Abeta adsorption behavior on the surface, highlighting the importance of hydrophobic interactions at the interface. This work may provide parallel insights into the interactions of Abeta with lipid bilayers.