DataSheet_1_Artificial intelligence unveils key interactions between soil properties and climate factors on Boletus edulis and B. reticulatus mycelium in chestnut orchards of different ages.docx

The main objective of this study was to determine the possible interaction of two important abiotic factors (soil and climate) on the mycelial concentration and frequency of the ectomycorrhizal fungi Boletus edulis and B. reticulatus, using traditional statistics and artificial neural network tools. The frequency and concentration of Boletus mycelium were determined over three months (September, October, and November), and two years (2018 and 2020), in three hybrid chestnuts (Castanea × coudercii) orchards of 40-, 10-, and 3- years-old, using real-time qPCR. Statistical analysis revealed a significant effect of the year on B. edulis mycelium concentration and of the sampling plot (different tree ages) on B. reticulatus frequency. The combination of artificial intelligence networks (ANN) with fuzzy logic, named neurofuzzy logic (NF), allowed the construction of two robust models. In the first, using year, month, and sampling plot as inputs, NF identified hidden interactions between year and month on B. edulis mycelium concentration and between sampling plot and sampling month on B. reticulatus mycelium frequency, thus improving the information obtained from the statistical analysis. In the second model, those three factors were disaggregated into 44 inputs, including 20 soil properties and 24 climatic factors, being NF able to select only 8 as critical factors to explain the variability found in both ectomycorrhizal Boletus species regarding mycelial frequency and concentration. Specifically, NF selected two chemical soil properties (cation exchange capacity and total carbon) and three physical properties (macroaggregates, total porosity, and soil moisture at field capacity), as well as their interactions with three climatic elements (cumulative difference between precipitation and potential evapotranspiration (P-PET-1-2) and water deficit (WD-1-2) in the previous two months and excess water (WE-1) in the month prior to sampling. These results provide a much deeper understanding and new insights into the ecology and the role of abiotic factors which explain the different mycelial development patterns of ectomycorrhizal fungi such as B. edulis and B. reticulatus in chestnut agroecosystems.</p

DataSheet_1_Neurofuzzy logic predicts a fine-tuning metabolic reprogramming on elicited Bryophyllum PCSCs guided by salicylic acid.docx

Novel approaches to the characterization of medicinal plants as biofactories have lately increased in the field of biotechnology. In this work, a multifaceted approach based on plant tissue culture, metabolomics, and machine learning was applied to decipher and further characterize the biosynthesis of phenolic compounds by eliciting cell suspension cultures from medicinal plants belonging to the Bryophyllum subgenus. The application of untargeted metabolomics provided a total of 460 phenolic compounds. The biosynthesis of 164 of them was significantly modulated by elicitation. The application of neurofuzzy logic as a machine learning tool allowed for deciphering the critical factors involved in the response to elicitation, predicting their influence and interactions on plant cell growth and the biosynthesis of several polyphenols subfamilies. The results indicate that salicylic acid plays a definitive genotype-dependent role in the elicitation of Bryophyllum cell cultures, while methyl jasmonate was revealed as a secondary factor. The knowledge provided by this approach opens a wide perspective on the research of medicinal plants and facilitates their biotechnological exploitation as biofactories in the food, cosmetic and pharmaceutical fields.</p

DataSheet_2_Neurofuzzy logic predicts a fine-tuning metabolic reprogramming on elicited Bryophyllum PCSCs guided by salicylic acid.xlsx

Novel approaches to the characterization of medicinal plants as biofactories have lately increased in the field of biotechnology. In this work, a multifaceted approach based on plant tissue culture, metabolomics, and machine learning was applied to decipher and further characterize the biosynthesis of phenolic compounds by eliciting cell suspension cultures from medicinal plants belonging to the Bryophyllum subgenus. The application of untargeted metabolomics provided a total of 460 phenolic compounds. The biosynthesis of 164 of them was significantly modulated by elicitation. The application of neurofuzzy logic as a machine learning tool allowed for deciphering the critical factors involved in the response to elicitation, predicting their influence and interactions on plant cell growth and the biosynthesis of several polyphenols subfamilies. The results indicate that salicylic acid plays a definitive genotype-dependent role in the elicitation of Bryophyllum cell cultures, while methyl jasmonate was revealed as a secondary factor. The knowledge provided by this approach opens a wide perspective on the research of medicinal plants and facilitates their biotechnological exploitation as biofactories in the food, cosmetic and pharmaceutical fields.</p

Spermidine Cross-Linked Hydrogels as a Controlled Release Biomimetic Approach for Cloxacillin

The intrinsic ability of albumin to bind active substances in the physiological fluids has been explored to endow hydrogels with improved capability to regulate drug release. To develop such biomimetic-functional hydrogels, it is critical that albumin conformation is not altered and that the protein remains retained inside the hydrogel keeping its conformational freedom, i.e., it should be not chemically cross-linked. Thus, the hydrogels were prepared with various proportions of albumin by physical cross-linking of anionic polysaccharides (gellan gum and chondroitin sulfate) with the cationic endogen polyamine spermidine under mild conditions in order to prevent albumin denaturation. Texture and swelling properties of hydrogels with various compositions were recorded, and the effect of the preparation variables was evaluated applying neurofuzzy logic tools for hydrogels prepared with and without albumin and associating the antibiotic cloxacillin. Developed hydrogel systems were extensively analyzed by means of nuclear magnetic resonance (NMR) to determine weak-to-medium and strong binding modes and the equilibrium constants of the albumin–cloxacillin association. NMR techniques were also employed to demonstrate the successful modulation of the cloxacillin release from the albumin-containing hydrogels. <i>In vitro</i> microbiological tests carried out with <i>Staphylococcus aureus</i> and <i>Staphylococcus epidermidis</i> confirmed the interest of the albumin-containing hydrogels as efficient platforms for cloxacillin release in its bioactive form

Effect of Polymer Composition on Rheological and Degradation Properties of Temperature-Responsive Gelling Systems Composed of Acyl-Capped PCLA-PEG-PCLA

In this study, the ability to modulate the rheological and degradation properties of temperature-responsive gelling systems composed of acyl-capped poly­(ε-caprolactone-<i>co</i>-lactide)-<i>b</i>-poly­(ethylene glycol)-<i>b</i>-poly­(ε-caprolactone-<i>co</i>-lactide) (PCLA-PEG-PCLA) triblock copolymers was investigated. Eight polymers with varying molecular weight of PCLA, caproyl/lactoyl ratio (CL/LA) and capped with either acetyl- or propionyl-groups were synthesized by ring-opening polymerization of l-lactide and ε-caprolactone in toluene using PEG as initiator and tin­(II) 2-ethylhexanoate as catalyst, and subsequently reacted in solution with an excess of acyl chloride to yield fully acyl-capped PCLA-PEG-PCLA. The microstructure of the polymers was determined by ¹H NMR, and the thermal properties and crystallinity of the polymers in dry state and in 25 wt % aqueous systems were studied by differential scanning calorimetry and X-ray diffraction. Rheological and degradation/dissolution properties of aqueous systems composed of the polymers in 25 wt % aqueous systems were studied. ¹H NMR analysis revealed that the monomer sequence in the PCLA blocks was not fully random, resulting in relatively long CL sequences, even though transesterification was demonstrated by the enrichment with lactoyl units and the presence of PEG–OH end groups. Except the most hydrophilic polymer composed of acetyl-capped PCLA₁₄₀₀-PEG₁₅₀₀-PCLA₁₄₀₀ having a CL/LA molar ratio of 2.5, the polymers at 25 wt % in buffer were sols below room temperature and transformed into gels between room temperature and 37 °C, which makes them suitable as temperature-responsive gelling systems for drug delivery. Over a period of weeks at 37 °C, the systems containing polymers with long CL sequences (∼8 CL) and propionyl end-groups became semicrystalline as shown by X-ray diffraction analysis. Degradation of the gels by dissolution at 37 °C took 100–150 days for the amorphous gels and 250–300 days for the semicrystalline gels. In conclusion, this study shows that changes in the polymer composition allow an easy but significant modulation of rheological and degradation properties