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The reductions of Pt(iv) anticancer prodrugs [Pt(dach)Cl4] (ormaplatin/tetraplatin), cis-[Pt(NH3)2Cl4], and cis,cis,trans-[Pt(NH3)2Cl2Br2] by the several dominant reductants in human plasma have been characterized kinetically in this work, including l-ascorbic acid (Asc), l-glutathione (GSH), l-cysteine (Cys), dl-homocysteine (Hcy), and a dipeptide Gly-Cys. All the reductions follow an overall second-order kinetics, being first-order each in [Pt(iv)] and in the [reductant]. A general reactivity trend of Asc < Hcy < Cys-Gly < GSH < Cys is clearly revealed for the reductions of [Pt(dach)Cl4] and [Pt(NH3)2Cl4] at 37.0 °C and pH 7.40. Analysis of the observed second-order rate constants k' implies that these Pt(iv) prodrugs have a very short lifetime (less than a minute) in human plasma and can hardly enter into cells before reduction and that Asc might not play a dominant role in the reduction process among the reductants. The reductions of [Pt(dach)Cl4] and [Pt(NH3)2Cl4] by Asc have been studied in a wide pH range, and a reaction mechanism has been proposed involving parallel reductions of the Pt(iv) complexes by the Asc protolytic species. Moreover, a halide-bridged (inner-sphere) electron transfer mode for the rate-determining steps is discussed in detail; several lines of evidence strongly bolster this type of electron transfer. Furthermore, the observed activation parameters corresponding to k' have been measured around pH 7.40. Analysis of the established k'-pH profiles indicates that k' is a composite of at least three parameters in the pH range of 5.74-7.40 and the measured activation parameters in this range do not correspond to a single rate-determining step. Consequently, the isokinetic relationship reported previously using the measured ΔH(‡) and ΔS(‡) in the above pH range might be an artifact since the relationship is not justified anymore when our new data are added.

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In this work, mesh-embedded polysulfone (PSU)/sulfonated polysulfone (sPSU) supported thin film composite (TFC) membranes were developed for forward osmosis (FO). The robust mesh integrated in PSU/sPSU sublayer imparts impressive mechanical durability. The blending of hydrophilic sPSU in PSU sublayer affects the hydrophilicity, porosity, pore structure, and pore size of mesh-embedded PSU/sPSU substrates, and the total thickness, cross-linking degree, and roughness of the corresponding TFC-FO membrane active layers. An appropriate incorporation of sPSU not only significantly decreases the structural parameter, S of the mesh-embedded substrate to 220 μm, which is the lowest reported value for fabric backed FO membrane, but also optimizes the permselectivity of the formed active layer. Regarding the osmosis performance, TFC membranes with sPSU modified substrates gain a higher water flux (J) while keeping the specific reverse salt flux (J/J) low. The optimal TFC-FO membrane has a J of 31.76 LMH with J/J of 0.19 g/L in FO mode when using deionized water feed and 1 M NaCl draw solution. This paper is practical for developing TFC-FO membrane on hydrophilic support membrane materials.

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BackgroundIturin A is a potential lipopeptide antibiotic produced by Bacillus subtilis. Optimization of iturin A yield by adding various concentrations of asparagine (Asn), glutamic acid (Glu) and proline (Pro) during the fed-batch fermentation process was studied using an artificial neural network-genetic algorithm (ANN-GA) and uniform design (UD). Here, ANN-GA based on the UD data was used for the first time to analyze the fed-batch fermentation process. The ANN-GA and UD methodologies were compared based on their fitting ability, prediction and generalization capacity and sensitivity analysis.ResultsThe ANN model based on the UD data performed well on minimal statistical designed experimental number and the optimum iturin A yield was 13364.5 ± 271.3 U/mL compared with a yield of 9929.0 ± 280.9 U/mL for the control (batch fermentation without adding the amino acids). The root-mean-square-error for the ANN model with the training set and test set was 4.84 and 273.58 respectively, which was more than two times better than that for the UD model (32.21 and 483.12). The correlation coefficient for the ANN model with training and test sets was 100% and 92.62%, respectively (compared with 99.86% and 78.58% for UD). The error% for ANN with the training and test sets was 0.093 and 2.19 respectively (compared with 0.26 and 4.15 for UD). The sensitivity analysis of both methods showed the comparable results. The predictive error of the optimal iturin A yield for ANN-GA and UD was 0.8% and 2.17%, respectively.ConclusionsThe satisfactory fitting and predicting accuracy of ANN indicated that ANN worked well with the UD data. Through ANN-GA, the iturin A yield was significantly increased by 34.6%. The fitness, prediction, and generalization capacities of the ANN model were better than those of the UD model. Further, although UD could get the insight information between variables directly, ANN was also demonstrated to be efficient in the sensitivity analysis. The results of these comparisons indicated that ANN could be a better alternative way for fermentation optimization with limited number of experiments.

their energy consumption is much lower than that of thermal approaches. [3] Therefore, membrane technologies are regarded as cost-effective candidates and play an increasingly important role in the treatment of natural waters and wastewaters. [4] Membrane processes for water purification and desalination can be generally classified into microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), reverse osmosis (RO), and emerging forward osmosis (FO) according to the pore size of the membrane and the respective rejection mechanism. The materials used to fabricate the membranes cover a wide range of polymers and inorganic materials. By far, polymeric membranes are the most widespread type due to their high processability, high flexibility, and low cost. [5][6][7] Traditional asymmetric membranes that contain only one type of polymer are mainly used for UF and a few NF applications. These membranes exhibit an asymmetric porous structure that consists of a thin nano porous active layer and a microporous underlying layer. MF membranes, however, possess a relatively symmetric micro porous structure. These porous membranes are mainly fabricated by phase inversion. For RO, FO, and most NF membranes that reject nanoscale solutes, an individual nonporous, dense, and thin polyamide (PA) active layer is normally required and is deposited onto a porous support layer to ensure a high selectivity. The active layer is prepared via interfacial polymerization (IP), while the support layer can be fabricated by phase inversion. These membranes are known as thin film composite (TFC) membranes, and the layers are comprised of different polymers. TFC membranes possess superior permeability over that of first-generation cellulose acetate membranes. [8,9] Although polymeric membranes have been widely reported in scientific studies and utilized for industrial applications, they are restricted by the inherent limitations of the material, such as a permeability/selectivity trade-off and a low fouling resistance. The current ability to control the membrane structure in both molecular-level design and fabrication process is not satisfactory. [10] In the last decade, the incorporation of nanomaterials into polymeric membranes has gained considerable attention owing to the potential of the resulting materials for overcoming the above limitations. [11,12] These advanced composite membranes have shown enhanced performance with a low loading of nanoparticles (NPs), including zeolites, [13][14][15] silica, [16][17][18][19][20][21][22] Membrane technologies for water treatment and desalination are increasingly developed and utilized to address the global challenges of water security and supply. Membrane-based separations can produce water with desirable qualities from a wide range of water sources, such as groundwater, seawater, brackish water, and wastewater. However, the membranes, which are typically made from polymers, are still restricted by their inherent limitations, including a permeability/selectivity trade-off and a high fouling prop...