Synthesis and Characterization of Aminoamidine-Based Polyacrylonitrile Fibers for Lipase Immobilization with Effective Reusability and Storage Stability.

Lipases are extensively utilized industrial biocatalysts that play an important role in various industrial and biotechnological applications. Herein, polyacrylonitrile (PAN) was treated with hexamethylene diamine (HMDA) and activated by glutaraldehyde, then utilized as a carrier support for Candida rugosa lipase. In this regard, the morphological structure of modified PAN before and after the immobilization process was evaluated using FTIR and SEM analyses. The immobilized lipase exhibited the highest activity at pH 8.0, with an immobilization yield of 81% and an activity of 91%. The optimal pH and temperature for free lipase were 7.5 and 40 °C, while the immobilized lipase exhibited its optimal activity at a pH of 8.0 and a temperature of 50 °C. After recycling 10 times, the immobilized lipase maintained 76% of its activity and, after 15 reuses, it preserved 61% of its activity. The lipase stability was significantly improved after immobilization, as it maintained 76% of its initial activity after 60 days of storage. The calculated Km values were 4.07 and 6.16 mM for free and immobilized lipase, and the Vmax values were 74 and 77 µmol/mL/min, respectively. These results demonstrated that synthetically modified PAN is appropriate for immobilizing enzymes and has the potential for commercial applications.

Acrylic fabric and nanomaterials to enhance α-amylase-based biocatalytic immobilized systems for industrial food applications.

An innovative approach for immobilizing α-amylase was used in this investigation. The acrylic fabric was first treated with hexamethylene diamine (HMDA) and then coated with copper ions that were later reduced to copper nanoparticles (CuNPs). The corresponding materials obtained, Cu(II)@HMDA-TA and CuNPs@HMDA-TA, were employed as carriers for α-amylase, respectively. The structural and morphological characteristics of the produced support matrices before and after immobilization were assessed using various techniques, including FTIR, SEM, EDX, TG/DTG, DSC, and zeta potential. The immobilized α-amylase exhibited the highest level of activity at pH 7.0, with immobilization yields observed for CuNPs@HMDA-TA (81.7 %) (60 unit/g support) followed by Cu(II)@HMDA-TA (71.7 %) (49 unit/g support) and 75 % and 61 % of activity yields, and 91.7 % and 85 % of immobilization efficiency, respectively. Meanwhile, biochemical characterizations of the activity of the soluble and immobilized enzymes were carried out and compared. Optimal temperature, pH, kinetics, storage stability, and reusability parameters were optimized for immobilized enzyme activity. The optimal pH and temperature were recorded as 6.0 and 50 °C for soluble α-amylase while the two forms of immobilized α-amylase exhibit a broad pH of 6.0-7.0 and optimal temperature at 60 °C. After recycling 15 times, the immobilized α-amylase on CuNPs@HMDA-TA and Cu(II)@HMDA-TA preserved 63 % and 52 % of their activities, respectively. The two forms of immobilized α-amylase displayed high stability when stored for 6 weeks and preserved 85 % and 76 % of their activities, respectively. Km values were calculated as 1.22, 1.39, and 1.84 mg/mL for soluble, immobilized enzymes on CuNPs@HMDA-TA, and Cu(II)@HMDA-TA, and Vmax values were calculated as 36.25, 29.68, and 21.57 µmol/mL/min, respectively. The total phenolic contents of maize kernels improved 1.4 ± 0.01 fold after treatment by two immobilized α-amylases.

Novel and Facile Colorimetric Detection of Reducing Sugars in Foods via In Situ Formed Gelatin-Capped Silver Nanoparticles.

The evolution of green technology for the simple and ecological formation of silver nanoparticles (AgNPs) inspired the present work for simple and efficient detection of reducing sugars (RS) in foods. The proposed method relies on gelatin as the capping and stabilizing agent and the analyte (RS) as the reducing agent. This work may attract significant attention, especially in the industry, for testing the sugar content using gelatin-capped silver nanoparticles as it not only detects the sugar in food, but also determines the content (%), which could be an alternative technique to the conventionally used DNS colorimetric method. For this purpose, a certain amount of maltose was mixed with a gelatin-silver nitrate. Different conditions that may affect the color changes at 434 nm owing to the in situ formed AgNPs, such as gelatin-silver nitrate ratio, PH, time, and temperature, have been investigated. The 1:3 mg/mg ratio of gelatin-silver nitrate dissolved in 10 mL distilled water was most effective in color formation. The development of AgNPs color increases within 8-10 min at PH 8.5 as the selected optimum value and at the optimum temperature of 90 °C for the evolution of the gelatin-silver reagent's redox reaction. The gelatin-silver reagent showed a fast response (less than 10 min) with a detection limit for maltose at 46.67 µM. In addition, the selectivity of maltose was checked in the presence of starch and after its hydrolysis with α-amylase. Compared with the conventionally used dinitrosalicylic acid (DNS) colorimetric method, the proposed method could be applied to commercial fresh apple juice, watermelon, and honey to prove its viability for detecting RS in fruits; the total reducing sugar content was 287, 165, and 751 mg/g, respectively.