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Plants are sessile organisms and therefore they must adapt their growth and architecture to a changing environment. Understanding how hormones and genes interact to coordinate plant growth in a changing environment is a major challenge in developmental biology. Although a localized auxin concentration maximum in the root tip is important for root development, auxin concentration cannot change independently of multiple interacting hormones and genes. In this review, we discuss the experimental evidence showing that the POLARIS peptide of Arabidopsis plays an important role in hormonal crosstalk and root growth, and review the crosstalk between auxin and other hormones for root growth with and without osmotic stress. Moreover, we discuss that experimental evidence showing that, in root development, hormones and the associated regulatory and target genes form a network, in which relevant genes regulate hormone activities and hormones regulate gene expression. We further discuss how it is increasingly evident that mathematical modeling is a valuable tool for studying hormonal crosstalk. Therefore, a combined experimental and modeling study on hormonal crosstalk is important for elucidating the complexity of root development.

Lactiplantibacillus plantarum is a Gram-positive bacterium that belongs to the lactic acid bacteria (LAB) group commonly used in the food industry. To use this microorganism, high biomass concentration is necessary, and models need to be established for predicting and improving its behavior along fermentation. However, current models for L. plantarum are applicable to only one substrate. The growth of a newly isolated strain L. plantarum 60-1 in a co-substrate (glucose and lactose) and lactic acid production in the batch process, were modeled in this work. Biomass growth was well described bydouble Monod kinetics. Substrate consumptions were modeled using two balance equations. Lactic acid was described with the Luedeking–Piret equation. No product inhibition was observed. Both glucose and lactose were metabolized in a concomitant way. This is the first report (as we know it) of a model includes dynamics of a dual limitation substrate glucoseand lactose in multiplicative effects on the growth of L. plantarum 60-1

Humic acids (HA) are promising green materials for water and wastewater treatment. They show a strong ability to sorb cationic and hydrophobic organic pollutants. Cationic compounds interact mainly by electrostatic interaction with the deprotonated carboxylic groups of HA. Other functional groups of HA such as quinones, may form covalent bonds with aromatic ammines or similar organic compounds. Computational and experimental works show that the interaction of HA with hydrophobic organics is mainly due to π–π interactions, hydrophobic effect and hydrogen bonding. Several works report that sorbing efficiency is related to the hydrophobicity of the sorbate. Papers about the interaction between organic pollutants and humic acids dissolved in solution, in the solid state and adsorbed onto solid particles, like aluminosilicates and magnetic materials, are reviewed and discussed. A short discussion of the thermodynamics and kinetics of the sorption process, with indication of the main mistakes reported in literature, is also given.

An enzyme membrane reactor is an attractive tool for producing oligosaccharides from biomass-based polysaccharides. However, kinetic modeling and reactor design based on the rate equations have rarely been reported for enzyme membrane reactors because of the difficulty in tracing the depolymerization process. In this study, a simplified reaction model based on Michaelis–Menten-type kinetics has been built to simulate the enzyme membrane reactor. Ramping various species into reactant, target, and byproduct worked well for discussing reactor performance. The use of a membrane with a molecular weight cut-off (MWCO) of 10 kDa with continuous feeding of the reactant was suggested for the efficient production of chitosan hexamer and pentamer by enzymatic hydrolysis of chitosan.

Plants have evolved strategies to tightly regulate metabolism during acclimation to a changing environment. Low temperature significantly constrains distribution, growth and yield of many temperate plant species. Exposing plants to low but non-freezing temperature induces a multigenic processes termed cold acclimation, which eventually results in an increased freezing tolerance. Cold acclimation comprises reprogramming of the transcriptome, proteome and metabolome and affects communication and signaling between subcellular organelles. Carbohydrates play a central role in this metabolic reprogramming. This review summarizes current knowledge about the role of carbohydrate metabolism in plant cold acclimation with a focus on subcellular metabolic reprogramming, its thermodynamic constraints under low temperature and mathematical modelling of metabolism.

Natural product waste treatment and the removal of harmful dyes from water by adsorption are two of the crucial environmental issues at present. Traditional adsorbents are often not capable in removing detrimental dyes from wastewater due to their hydrophilic nature and because they form strong bonds with water molecules, and therefore they remain in the dissolved state in water. Consequently, new and effective sorbents are required to reduce the cost of wastewater treatment as well as to mitigate the health problems caused by water pollution contaminants. In this study, the adsorption behaviour of methyl orange, MO, dye on chitosan bead-like materials was investigated as a function of shaking time, contact time, adsorbent dosage, initial MO concentration, temperature and solution pH. The structural and chemical properties of chitosan bead-like materials were studied using several techniques including SEM, BET, XRD and FTIR. The adsorption process of methyl orange by chitosan bead materials was well described by the Langmuir isotherm model for the uptake capacity and followed by the pseudo-second-order kinetic model to describe the rate processes. Under the optimal conditions, the maximum removal rate (98.9%) and adsorption capacity (12.46 mg/g) of chitosan bead-like materials were higher than those of other previous reports; their removal rate for methyl orange was still up to 87.2% after three regenerative cycles. Hence, this chitosan bead-like materials are very promising materials for wastewater treatment.

Background One of the key goals of fruit biology is to understand the factors that influence fruit growth and quality, ultimately with a view to manipulating them for improvement of fruit traits. Scope Primary metabolism, which is not only essential for growth but is also a major component of fruit quality, is an obvious target for improvement. However, metabolism is a moving target that undergoes marked changes throughout fruit growth and ripening. Conclusions Agricultural practice and breeding have successfully improved fruit metabolic traits, but both face the complexity of the interplay between development, metabolism and the environment. Thus, more fundamental knowledge is needed to identify further strategies for the manipulation of fruit metabolism. Nearly two decades of post-genomics approaches involving transcriptomics, proteomics and/or metabolomics have generated a lot of information about the behaviour of fruit metabolic networks. Today, the emergence of modelling tools is providing the opportunity to turn this information into a mechanistic understanding of fruits, and ultimately to design better fruits. Since high-quality data are a key requirement in modelling, a range of must-have parameters and variables is proposed.

Biomass pyrolysis has been the focus of study by several researchers as a viable means of producing biofuels and other useful products. This paper gives a comprehensive, elaborate and updated review of pyrolysis technology as an efficient thermochemical route for biomass conversion. Pyrolysis products include pyrolytic gas, bio-oil, and solid biochar. Depending on the operating conditions, pyrolysis is usually classified as slow, intermediate, fast, and flash pyrolysis. The utilization of special catalysts can help facilitate pyrolytic gas production, while specific pretreatment processes can help facilitate bio-oil production. The efficiency of the pyrolysis process is affected by a number of factors such as temperature, heating rate, residence time, particle size, biomass type, and biomass pretreatment method. In this review, thermogravimetric analysis and kinetic modelling of biomass pyrolysis were also emphasized while the various constraints encountered during biomass pyrolysis have been highlighted and suggestions made to address them. More recently, more advanced experimental methods have been developed for biomass pyrolysis research, and these include Py-GC–MS/FID, TG-MS/TG-FTIR, in situ spectroscopy for reaction progress analysis, isotopic labelling, and intermediate product analysis techniques that enable the monitoring of the biomass devolatilization process as well as identification of the functional groups of the volatiles and monitoring of the changes in the functional groups on the surface of biomass in the course of pyrolysis. No doubt, biomass pyrolysis will continue to provide several benefits and serve as a sustainable means of producing biofuels, biochemicals, and other valuable products with far-reaching areas of applications.

There is evidence that subtle breakdown of the blood–brain barrier (BBB) is a pathophysiological component of several diseases, including cerebral small vessel disease and some dementias. Dynamic contrast-enhanced MRI (DCE-MRI) combined with tracer kinetic modelling is widely used for assessing permeability and perfusion in brain tumours and body tissues where contrast agents readily accumulate in the extracellular space. However, in diseases where leakage is subtle, the optimal approach for measuring BBB integrity is likely to differ since the magnitude and rate of enhancement caused by leakage are extremely low; several methods have been reported in the literature, yielding a wide range of parameters even in healthy subjects. We hypothesised that the Patlak model is a suitable approach for measuring low-level BBB permeability with low temporal resolution and high spatial resolution and brain coverage, and that normal levels of scanner instability would influence permeability measurements. DCE-MRI was performed in a cohort of mild stroke patients (n=201) with a range of cerebral small vessel disease severity. We fitted these data to a set of nested tracer kinetic models, ranking their performance according to the Akaike information criterion. To assess the influence of scanner drift, we scanned 15 healthy volunteers that underwent a “sham” DCE-MRI procedure without administration of contrast agent. Numerical simulations were performed to investigate model validity and the effect of scanner drift. The Patlak model was found to be most appropriate for fitting low-permeability data, and the simulations showed vp and KTrans estimates to be reasonably robust to the model assumptions. However, signal drift (measured at approximately 0.1% per minute and comparable to literature reports in other settings) led to systematic errors in calculated tracer kinetic parameters, particularly at low permeabilities. Our findings justify the growing use of the Patlak model in low-permeability states, which has the potential to provide valuable information regarding BBB integrity in a range of diseases. However, absolute values of the resulting tracer kinetic parameters should be interpreted with extreme caution, and the size and influence of signal drift should be measured where possible. •We performed DCE-MRI in 201 patients with a range of small vessel disease severity.•We tested tracer kinetic model performance via simulations and statistical analysis.•The Patlak model was optimal for assessing leakage in normal tissues and lesions.•Scanner drift leads to substantial errors in measured tracer kinetic parameters.•DCE-MRI measurements of subtle leakage should be interpreted with caution.

We posited that the grain size dependence of the tensile necking stress, as determined by the Considère criterion for plastic instability, is a more meaningful characteristic of the Hall–Petch (H–P) effect than that of the yield stress or the 0.2% proof stress. An inverse square-root dependence of the necking stress on the grain size was derived from a dislocation dynamics-based constitutive model. In this model, the grain size effect enters the stress indirectly via the evolution of the dislocation density. Model predictions were confirmed by the experimental data for nickel and titanium.