Static and dynamic heterogeneities in a model for irreversible gelation

We study the structure and the dynamics in the formation of irreversible gels by means of molecular dynamics simulation of a model system where the gelation transition is due to the random percolation of permanent bonds between neighboring particles. We analyze the heterogeneities of the dynamics in terms of the fluctuations of the intermediate scattering functions: In the sol phase close to the percolation threshold, we find that this dynamical susceptibility increases with the time until it reaches a plateau. At the gelation threshold this plateau scales as a function of the wave vector $k$ as $k^{\eta -2}$, with $\eta$ being related to the decay of the percolation pair connectedness function. At the lowest wave vector, approaching the gelation threshold it diverges with the same exponent $\gamma$ as the mean cluster size. These findings suggest an alternative way of measuring critical exponents in a system undergoing chemical gelation.Comment: 4 pages, 4 figure

Static and dynamic heterogeneities in irreversible gels and colloidal gelation

We compare the slow dynamics of irreversible gels, colloidal gels, glasses and spin glasses by analyzing the behavior of the so called non-linear dynamical susceptibility, a quantity usually introduced to quantitatively characterize the dynamical heterogeneities. In glasses this quantity typically grows with the time, reaches a maximum and then decreases at large time, due to the transient nature of dynamical heterogeneities and to the absence of a diverging static correlation length. We have recently shown that in irreversible gels the dynamical susceptibility is instead an increasing function of the time, as in the case of spin glasses, and tends asymptotically to the mean cluster size. On the basis of molecular dynamics simulations, we here show that in colloidal gelation where clusters are not permanent, at very low temperature and volume fractions, i.e. when the lifetime of the bonds is much larger than the structural relaxation time, the non-linear susceptibility has a behavior similar to the one of the irreversible gel, followed, at higher volume fractions, by a crossover towards the behavior of glass forming liquids.Comment: 9 pages, 3 figure

Kinetics of bond formation in crosslinked gelatin gels

In chemical crosslinking of gelatin solutions, two different time scales affect the kinetics of the gel formation in the experiments. We complement the experimental study with Monte Carlo numerical simulations of a lattice model. This approach shows that the two characteristic time scales are related to the formation of single bonds crosslinker-chain and of bridges between chains. In particular their ratio turns out to control the kinetics of the gel formation. We discuss the effect of the concentration of chains. Finally our results suggest that, by varying the probability of forming bridges as an independent parameter, one can finely tune the kinetics of the gelation via the ratio of the two characteristic times.Comment: 8 pages, 9 figures, revised versio

Reentrant phase diagram and pH effects in cross-linked gelatin gels

Experimental results have shown that the kinetics of bond formation in chemical crosslinking of gelatin solutions is strongly affected not only by gelatin and reactant concentrations but also by the solution pH. We present an extended numerical investigation of the phase diagram and of the kinetics of bond formation as a function of the pH, via Monte Carlo simulations of a lattice model for gelatin chains and reactant agent in solution. We find a reentrant phase diagram, namely gelation can be hindered either by loop formation, at low reactant concentrations, or by saturation of active sites of the chains via formation of single bonds with crosslinkers, at high reactant concentrations. The ratio of the characteristic times for the formation of the first and of the second bond between the crosslinker and an active site of a chain is found to depend on the reactant reactivity, in good agreement with experimental data.Comment: 8 pages, 8 figure

Évaluation de l’impact du rejet des déchets phosphates dans la mer sur la biodiversité marine dans trois localités côtières au Togo à partir des biomarqueurs du stress oxydatif chez Sphyraena barracuda (HECKEL, 1843)

La pollution due aux rejets des déchets phosphatés à Kpémé par la Société Nouvelle des Phosphates du Togo (SNPT), concerne aussi les zones environnantes. Nous avons voulu dans ce travail déterminer l’impact de cette pollution dans ces zones sur la biodiversité marine. Les teneurs en métaux lourds toxiques (Cd et Pb) dans les organes de poissons à Gbodjomé (zone de référence), Agbodrafo, Goumoukopé et Aného sont déterminées par spectrophotométrie d’absorption atomique à la flamme ; de même que certains biomarqueurs du stress oxydatif. Dans l’ensemble, les résultats ont montré une altération des enzymes antioxydantes, du système de la glutathion et une induction de la peroxydation lipidique due à la présence du Cd et du Pb qui provoquent un stress oxydatif chez les poissons, et donc chez les espèces de la biodiversité marine de la côte togolaise des zones concernées. Les résultats de la présente étude indiquent que les zones environnantes sont touchées par le rejet des déchets à Kpémé et les impacts sur la biodiversité marine diminuent au fur et à mesure qu’on s’éloigne des sites de rejets vers l’aval à cause du sens d’écoulement de la mer. Aussi, peut-on déduire que les biomarqueurs du stress oxydatif sont des indicateurs de la pollution aquatique.Mots clés: Déchets phosphatés, pollution, Cd, Pb, bioaccumulatio

Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Family 7 glycoside hydrolases (GH7) are among the principal enzymes for cellulose degradation in nature and industrially. These enzymes are often bimodular, including a catalytic domain and carbohydrate-binding module (CBM) attached via a flexible linker, and exhibit an active site that binds cello-oligomers of up to ten glucosyl moieties. GH7 cellulases consist of two major subtypes: cellobiohydrolases (CBH) and endoglucanases (EG). Despite the critical importance of GH7 enzymes, there remain gaps in our understanding of how GH7 sequence and structure relate to function. Here, we employed machine learning to gain data-driven insights into relation-ships between sequence, structure, and function across the GH7 family. Machine-learning models, trained only on the number of residues in the active-site loops as features, were able to discriminate GH7 CBHs and EGs with up to 99% ac-curacy, demonstrating that the lengths of loops A4, B2, B3, and B4 strongly correlate with functional subtype across the GH7 family. Classification rules were derived such that specific residues at 42 different sequence positions each predicted the functional subtype with accuracies surpassing 87%. A random forest model trained on residues at 19 positions in the catalytic domain predicted the presence of a CBM with 89.5% accuracy. Our machine learning results recapitulate, as top-performing features, a substantial number of the sequence positions determined by previous experimental studies to play vital roles in GH7 activity. We surmise that the yet-to-be-explored sequence positions among the top-performing features also contribute to GH7 functional variation and may be exploited to understand and manipulate function

EFFECT OF BIOLOGICAL TREATMENTS OF GREEN CORN STOVER AND STALKS ON DIGESTIBILITY COEFFICIENTS, RUMEN FERMENTATION AND SOME BLOOD PARAMETERS IN SHEEP

This study aimed to investigate the effect of a mixture of  (ZAD) and (Lacto bacillus plantarum) on chemical composition of green corn stover and corn stalks and the effect of  these treatments in a metabolism trial on digestibility coefficients , rumen fermentation and some blood parameters. One ton of either green corn stover or corn stalks was chopped into (2-3 cm) and  its mixed with 0. 5 cubic metre of water or one cubic metre of water, respectively. They were then mixed with 3%w/w molasses and 1.5%w/w urea and incubated for six weeks. The experiment included six treatments, three of them were on green corn stover and the rest were on corn stalks. The treatments on green corn stover were as follows: (T1) Untreated green corn stover (control). (T2) corn stover + lactobacillus palantarum + ZAD (2litres of ZAD + 1 liter of lactobacillus palantarum / 1ton). (T3) corn stover + ZAD ( 2 liters of ZAD/ 1 ton). The treatments on corn stalks were as follows: (T4) Untreated corn stalks (control). (T5) corn stalks + lactobacillus palantarum+ ZAD (2litres of ZAD +1 liter of lactobacillus palantarum /1ton) (T6) corn stalks + ZAD (2 liters of ZAD/ 1 ton). Eighteen Ossimi male lambs were divided to six group rations for 15 days in metabolism trials. Results indicated that biological treatment on T2 and T3 treatments  on green  stover and T5 and T6 on  dry corn stalks decreased CF and NDF, ADF, ADL contents and increased CP content compared to the control.   Feeding lambs on treated green corn stover or treated dry corn stalks significantly (P<0.05) improved all of nutrients digestibility compared with those fed on control. The nutritive values as TDN,  DCP and N balance for lambs fed treated green stover or treated dry corn stalks showed significant(P<0.05) higher than those fed untreated and it had the same trend of nutrient digestibility . Adding lactobacillus palantarum + ZAD improved digestion coefficients of nutrients and TDN values compared with control. Results of blood parameter indicated that T2 of green corn stover and T5 of corn stalks had a significant (P<0.05) effect on (Tp, Alb, Glb, A/G) compared to the control and T3 of corn stover and T6 of corn stalks. All values of plasma ALT and AST for all treatments were in normal rang where all treatments had no effect on ALT. However, T2 of green corn stover and T5 of corn stalks had a significant (P<0.05) effect on AST compared to the control and T3 of corn stover and T6 of corn stalks. All values of plasma creatinine and urea for biological treatments appeared to significant(P<0.05) higher values. However, these values were in normal range.   Results of rumen parameters indicated that all treatments had no effect on pH and NH3-N. On the other hand T2 of  green corn stover and T5 of corn stalks significantly (P<0.05) increased TVF'S. Generally, Adding enzyme with or without lactobacillus  to green corn stover or dry corn stalks tended to improved nutrient components , digestibility coefficients, feeding values and nitrogen balance with no adverse effect of animal health

Correlated rigidity percolation and colloidal gels

Rigidity percolation (RP) occurs when mechanical stability emerges in disordered networks as constraints or components are added. Here we discuss RP with structural correlations, an effect ignored in classical theories albeit relevant to many liquid-to-amorphous-solid transitions, such as colloidal gelation, which are due to attractive interactions and aggregation. Using a lattice model, we show that structural correlations shift RP to lower volume fractions. Through molecular dynamics simulations, we show that increasing attraction in colloidal gelation increases structural correlation and thus lowers the RP transition, agreeing with experiments. Hence colloidal gelation can be understood as a RP transition, but occurs at volume fractions far below values predicted by the classical RP, due to attractive interactions which induce structural correlation

Dynamical heterogeneity in a model for permanent gels: Different behavior of dynamical susceptibilities

We present a systematic study of dynamical heterogeneity in a model for permanent gels, upon approaching the gelation threshold. We find that the fluctuations of the self intermediate scattering function are increasing functions of time, reaching a plateau whose value, at large length scales, coincides with the mean cluster size and diverges at the percolation threshold. Another measure of dynamical heterogeneities, i.e. the fluctuations of the self-overlap, displays instead a peak and decays to zero at long times. The peak, however, also scales as the mean cluster size. Arguments are given for this difference in the long time behavior. We also find that non-Gaussian parameter reaches a plateau in the long time limit. The value of the plateau of the non-Gaussian parameter, which is connected to the fluctuations of diffusivity of clusters, increases with the volume fraction and remains finite at percolation threshold.Comment: 11 pages, 14 figure