SEPARATION OF HEMICELLULOSES FROM AN INDUSTRIAL STREAM BY NANOFILTRATION AND ULTRAFILTRATION PROCESSES

The performance of nanofiltration (NF) and ultrafiltration (UF) membranes was studied for separating hemicelluloses from a highly alkaline industrial stream, containing 17-18 wt% sodium hydroxide, resulting from the viscose process. Initially, screening experiments were performed to select suitable membranes, which were then investigated on a pilot scale spiral module. Screening experiments showed that the UF membrane, with a nominal molecular weight cut-off (MWCO) value of 3 kDa, and the NF one, with a nominal MWCO value of 0.5 kDa, showed a similar range of filtration performance and a flux of 4.2 L/m2.h. Further, a retention efficiency of 50% was observed for the 5 kDa and the 10 kDa membranes, indicating absence of any significant proportion of hemicelluloses in this range of molecular weights. The effects of process conditions were studied to understand their correlation with membrane performance with respect to hemicelluloses retention and permeate flux. UF membranes were found to be more prone to performance deterioration over time and with the number of cycles of usage during the pilot scale study, whereas the NF membrane showed consistent performance. It was seen that feed dilution can improve the membrane performance with respect to sodium hydroxide recovery. Significant reduction in feed viscosity with dilution resulted in a 50% increase in flux after normalizing for concentration.

Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment

Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods.

Development, Characterization, Optimization, and In Vivo Evaluation of Methacrylic Acid–Ethyl Acrylate Copolymer Nanoparticles Loaded with Glibenclamide in Diabetic Rats for Oral Administration

The methacrylic acid–ethyl acrylate copolymer nanoparticles were prepared using the solvent displacement method. The independent variables were the drug/polymer ratio, surfactant concentration, Polioxyl 40 hydrogenated castor oil, the added water volume, time, and stirring speed, while size, PDI, zeta potential, and encapsulation efficiency were the response variables analyzed. A design of screening experiments was carried out to subsequently perform the optimization of the nanoparticle preparation process. The optimal formulation was characterized through the dependent variables size, PDI, zeta potential, encapsulation efficiency and drug release profiles. In vivo tests were performed in Wistar rats previously induced with diabetes by administration of streptozotocin. Once hyperglycemia was determined in rats, a suspension of nanoparticles loaded with glibenclamide was administered to them while the other group was administered with tablets of glibenclamide. The optimal nanoparticle formulation obtained a size of 18.98 +/− 9.14 nm with a PDI of 0.37085 +/− 0.014 and a zeta potential of −13.7125 +/− 1.82 mV; the encapsulation efficiency was of 44.5%. The in vivo model demonstrated a significant effect (p < 0.05) between the group administered with nanoparticles loaded with glibenclamide and the group administered with tablets compared to the group of untreated individuals.

Cost optimization of two-stage helical gearboxes with second stage double gear-sets

In practice, the cost of a gearbox plays a very important role in the trade. Therefore, reducing the cost of gearboxes is an important task not only when manufacturing the gearboxes but also when designing them. In order to reduce the cost of a gearbox, there are many solutions in which determining the optimal partial gear ratios of a gearbox is an effective measure. This is because it not only the size, the mass but also the cost of a gearbox depends greatly on the partial gear ratios. This work presents a method for calculating the cost function of two-stage helical gearboxes with second-stage double gear-sets based on the mass of the components that construct the gearbox. The cost objective function is minimized to achieve the optimal transmission ratios. Furthermore, screening experiments are carried out with nine important input parameters that have significant effects on the optimum transmission ratio of the second stage. These parameters are the total gearbox ratio, the coefficient of wheel face width of the first stage, coefficient of wheel face width of the second stage, the allowable contact stress of the first stage, the allowable contact stress of the second stage, the output torque, the cost of gearbox housing, the cost of gears, and the shaft cost. The experimental results of were analysed by using the Analysis of Variance (ANOVA) method with the help of Minitab 19 software. The results demonstrate that the effective weight of the input parameters and their interactions on the output response was investigated. Also, a regression model for computing the optimal transmission ratio of the second stage was proposed. This brings significance not only in the design process but also in manufacturing since the gearbox cost can decrease

A Novel 3D Co-culture Platform for Integrating Tissue Interfaces for Tumor Growth, Migration and Therapeutic Sensitivity: PP-3D-S

Metastatic cancers can be highly heterogeneous, show large patient variability, and are typically hard to treat due to chemoresistance. Personalized therapies are therefore needed to suppress tumor growth and enhance patient's quality of life. Identifying appropriate patient-specific therapies remains a challenge though, due mainly to non-physiological in vitro culture systems. Therefore, more complex and physiological in vitro human cancer microenvironment tools could drastically aid in the development of new therapies. We developed a plasma-modified, electro-spun 3D scaffold (PP-3D-S) that can mimic the human cancer microenvironment for customized-cancer therapeutic screening. The PP-3D-S were characterized for optimal plasma-modifying treatment and scaffolds morphology including fiber diameter and pore size. PP-3D-S was then seeded with human fibroblasts to mimic a stromal tissue layer; cell adhesion on plasma-modified poly (lactic acid), PLA, electrospun mats vastly exceeded that on untreated controls. The cell-seeded scaffolds were then overlaid with alginate/gelatin-based hydrogel embedded with MDA-MB231 human breast cancer cells, representing a tumor-tissue interface. Among three different plasma treatments, we found that NH3 plasma promoted the most tumor cell migration to the scaffold surfaces after 7 days of culture. For all treated and non-treated mats, we observed a significant difference in tumor cell migration between small-sized and either medium- or large-sized scaffolds. In addition, we found that the PP-3D-S was highly comparable to the standard Matrigel migration assays in two different sets of doxorubicin screening experiments, where a 75% reduction in migration was achieved with 0.5 uM doxorubicin for both systems. Taken together, our data indicate that PP-3D-S is an effective, low-cost, and easy-to-use alternate 3D tumor migration model which may be suitable as a physiological drug screening tool for personalized medicine against metastatic cancers.

High-speed live cell interferometry for screening bioprinted organoids

There is increasing interest in leveraging tumor organoids for high-throughput drug screenings to investigate tumor biology and identify therapeutic leads. However, functional precision medicine platforms are limited by the difficulties of creating, scaling, and analyzing physiological disease models. Most systems use manually seeded organoids and take advantage of destructive endpoint assays to rapidly characterize response to treatment. These approaches fail to capture transitory changes and intra-sample heterogeneity that underlies much of the clinically observed resistance to therapy. We therefore developed bioprinted tumor organoids linked to real-time growth pattern quantitation via high-speed live cell interferometry (HSLCI). We demonstrate that bioprinting gives rise to 3D organoid structures that preserve histology and gene expression. These are suitable for imaging with HSLCI, enabling accurate parallel mass measurements for thousands of bioprinted organoids. In drug screening experiments, HSLCI rapidly identifies organoids transiently or persistently sensitive or resistant to specific therapies. We show that our approach can provide detailed, actionable information to guide rapid therapy selection.

Designing a Robust Surfactant Based SP Formulation in High Clay Containing Low Permeability Indonesian Field

Indonesian oil and gas reserves have been depleting since 2000 with no major addition of new oil reserves. Therefore, it is imperative to increase national oil production by optimizing the mature fields through the implementation of successful EOR technology. Out of this approach, a comprehensive study has been carried out on the targeted field by exploring the potential of surfactant-polymer (SP) flooding. This article describes the formulation design, optimization, and lessons learned leading up to a successful and robust chemical EOR formulation designing for a low permeability and high clay (&gt;20% clay) containing Indonesian oil field. The detailed workflow consists of analysis of fluid and rock characterization, tailor-made SP formulation designing, optimization and coreflood validation as presented in previous papers (Bazin, 2010). A series of surfactant formulation were designed and screened synthetically through a validated High Throughput Screening (HTS) methodology using a robotic platform combined with microfluidic tools for ultra-low interfacial tension (IFT), solubility, compatibility with brine and polymer. Rock mineralogy has played an important role due to heterogeneity and very high (&gt;20%) clay content. Surfactants retention through adsorption on reservoir rocks was the main constraint to achieve high performance and economical chemical EOR for the targeted field. Specific strategies by optimizing the surfactant formulation and by injecting adsorption inhibitor thus needed to be deployed to mitigate high surfactant retention. The detailed laboratory screening experiments conclude that the designed robust SP formulation is able to induce ultra-low IFT, excellent solubility and compatibility at the injection water salinity. The dynamic coreflood experiment using reservoir rock shows high incremental oil recovery (&gt;60% ROIP) in short SP slug injection. As expected from the nature of rock, adsorption was the main challenge encountered during the course of this study, which resulted in a very promising oil recovery in economically realistic conditions.

Flexible Fitting of PROTAC Concentration–Response Curves with Changepoint Gaussian Processes

A proteolysis-targeting chimera (PROTAC) is a new technology that marks proteins for degradation in a highly specific manner. During screening, PROTAC compounds are tested in concentration–response (CR) assays to determine their potency, and parameters such as the half-maximal degradation concentration (DC50) are estimated from the fitted CR curves. These parameters are used to rank compounds, with lower DC50 values indicating greater potency. However, PROTAC data often exhibit biphasic and polyphasic relationships, making standard sigmoidal CR models inappropriate. A common solution includes manual omitting of points (the so-called masking step), allowing standard models to be used on the reduced data sets. Due to its manual and subjective nature, masking becomes a costly and nonreproducible procedure. We therefore used a Bayesian changepoint Gaussian processes model that can flexibly fit both nonsigmoidal and sigmoidal CR curves without user input. Parameters such as the DC50, maximum effect Dmax, and point of departure (PoD) are estimated from the fitted curves. We then rank compounds based on one or more parameters and propagate the parameter uncertainty into the rankings, enabling us to confidently state if one compound is better than another. Hence, we used a flexible and automated procedure for PROTAC screening experiments. By minimizing subjective decisions, our approach reduces time and cost and ensures reproducibility of the compound-ranking procedure. The code and data are provided on GitHub ( https://github.com/elizavetasemenova/gp_concentration_response ).

Probiotics and Postbiotics from Food to Health: Antimicrobial Experimental Confirmation

The field of probiotics is up-and-coming, especially in management of microbial pathogens. Probiotics confer nutritional benefits, reduce inflammation and infection. Probiotics have also shown to be helpful in the management of microbial pathogens, which include bacteria, fungi, and viruses. To ernes this potential maximumly, there is a need for an elaborate screening system for new isolates. This entails; rigorous screening methods and thorough confirmatory systems. There is need also to come up with standard methods used to evaluate the probiotics mechanism of action both in vivo and in vitro. In summary, there is a need for a standard screening process for probiotic microorganisms that is reproducible. The aim is to ensure that, the candidate microbial cultures are not written off without proper investigations. This will also fasten the screening process and save time and resources wasted in pre-screening experiments.