Morphological and Thermochemical Changes upon Autohydrolysis and Microemulsion Treatments of Coir and Empty Fruit Bunch Residual Biomass to Isolate Lignin-Rich Micro- and Nanofibrillar Cellulose

Autohydrolysis and microemulsion treatments followed by microfluidization are employed to isolate micro- and nanofibrillar cellulose (MNFC) from coir fibers and palm tree empty fruit bunches (EFB) with residual lignin content of ∼24 and ∼31 wt %, respectively. The fibers and associated MNFC are characterized in each treatment for their chemical, structural, and thermal properties. The most significant findings include the fact that two MNFC populations are produced, with distinctive structural differences and characteristic lateral dimensions of 20–70 nm and 1–3 μm. The lignin distribution after possible recondensation occurred in the form of nanodroplets. Finally, a correlation between thermal degradation of MNFC with spatial arrangement of lignin is hypothesized and a defibrillation mechanism is proposed. The detailed structural and thermochemical analyses presented here are expected to facilitate further interest in the development of new materials from MNFC isolated from coir and EFB, two abundant bioresources that are most suitable for their valorization

Interactions between Cellulolytic Enzymes with Native, Autohydrolysis, and Technical Lignins and the Effect of a Polysorbate Amphiphile in Reducing Nonproductive Binding

Understanding enzyme–substrate interactions is critical in designing strategies for bioconversion of lignocellulosic biomass. In this study we monitored molecular events, in situ and in real time, including the adsorption and desorption of cellulolytic enzymes on lignins and cellulose, by using quartz crystal microgravimetry and surface plasmon resonance. The effect of a nonionic surface active molecule was also elucidated. Three lignin substrates relevant to the sugar platform in biorefinery efforts were considered, namely, hardwood autohydrolysis cellulolytic (HWAH), hardwood native cellulolytic (MPCEL), and nonwood native cellulolytic (WSCEL) lignin. In addition, Kraft lignins derived from softwoods (SWK) and hardwoods (HWK) were used as references. The results indicated a high affinity between the lignins with both, monocomponent and multicomponent enzymes. More importantly, the addition of nonionic surfactants at concentrations above their critical micelle concentration reduced remarkably (by over 90%) the nonproductive interactions between the cellulolytic enzymes and the lignins. This effect was hypothesized to be a consequence of the balance of hydrophobic and hydrogen bonding interactions. Moreover, the reduction of surface roughness and increased wettability of lignin surfaces upon surfactant treatment contributed to a lower affinity with the enzymes. Conformational changes of cellulases were observed upon their adsorption on lignin carrying preadsorbed surfactant. Weak electrostatic interactions were determined in aqueous media at pH between 4.8 and 5.5 for the native cellulolytic lignins (MPCEL and WSCEL), whereby a ∼20% reduction in the enzyme affinity was observed. This was mainly explained by electrostatic interactions (osmotic pressure effects) between charged lignins and cellulases. Noteworthy, adsorption of nonionic surfactants onto cellulose, in the form cellulose nanofibrils, did not affect its hydrolytic conversion. Overall, our results highlight the benefit of nonionic surfactant pretreatment to reduce nonproductive enzyme binding while maintaining the reactivity of the cellulosic substrate

Cellular and tissue properties of the atrial model.

<p>a) Action potentials produced by each cell model in 0D (top) and the atrial regions to which each model has been assigned labelled by colour (bottom); b) Longitudinal (coloured) and transversal (grey) tissue conduction velocities in 3D (top) and the corresponding atrial regions colour coded (bottom). Each region has different longitudinal tissue conductivity.</p

P-waves registered on the torso precordial (V3 and V6) and standard (D3) leads.

<p>a) and c) represent the P-wave produced by the whole atria depolarization (black line), the contribution from the RA structures (continuous red line) and the contribution from the structures in LA (dotted red line). b) and d) show only those individual regions with maximum amplitude of at least the 30% of the maximum P-wave amplitude registered at the frontal and rear sides.</p

Torso model including the most relevant organs segmented from an MR stack.

<p>Included organs are: ventricle (light blue,), ii) bones (orange), iii) liver (green), iv) lungs (purple), v) blood (red) and v) chest (transparent white).</p

Spatial information from the potential root means square (B-RMS).

<p>a) B-RMS (mV_RMS) at the frontal torso view; b) B-RMS (mV_RMS) at the rear torso view. Geometric forms in each quadrant represent the torso area where the displayed P-waves are registered (units: mV <i>vs</i> ms).</p

Contribution to the ECG from individual atrial regions.

<p>a) Location of the maximum value of potential RMS produced from each atrial structure; b) B-RMS patterns (mV_RMS) from the individual atrial structures with the highest contributions. Also displayed the P-waves (mV <i>vs</i> ms) registered at the point with maximum potential RMS value (red line) compared with the total P-wave registered at the same point (black line).</p

Atrial action potential (AP) morphology and duration.

<p>a) APD₉₀ (ms) measured in each node of the atria at the tenth beat; b) mean and standard deviation of the APD₉₀ (ms) for each region; AP (mV) registered at one random node from c) each structure of RA, and d) each structure of LA.</p

Properties of the 3D atrial model.

<p>Row (1) show in colours the division in 21 atrial regions; Row (2) shows preferential conduction bundles; Row (3) shows principal fibre direction; Columns correspond to a) Frontal view; b) rear view; c) inferior view; and d) right lateral view.</p

Contribution of the most influential individual atrial regions to the total RMS distribution.

<p>a) Joint contribution of the signals of the 9 regions jointly responsible for the 89% of the total contribution (RAA, RLW, TV, RAS, LAA, LPW, IB, LAS and LPV); b) Joint contribution from the remaining twelve regions responsible for the 11% of the total contribution.</p