Nanodiamonds and natural deep eutectic solvents as potential carriers for lipase.

This study investigates the use of nanodiamonds (ND) as a promising carrier for enzyme immobilization and compares the effectiveness of immobilized and native enzymes. Three different enzyme types were tested, of which Rhizopus niveus lipase (RNL) exhibited the highest relative activity, up to 350 %. Under optimized conditions (1 h, pH 7.0, 40 °C), the immobilized ND-RNL showed a maximum specific activity of 0.765 U mg-1, significantly higher than native RNL (0.505 U mg-1). This study highlights a notable enhancement in immobilized lipase; furthermore, the enzyme can be recycled in the presence of a natural deep eutectic solvent (NADES), retaining 76 % of its initial activity. This aids in preserving the native conformation of the protein throughout the reusability process. A test on brine shrimp revealed that even at low concentrations, ND-RNL had minimal toxicity, indicating its low cytotoxicity. The in silico molecular dynamics simulations performed in this study offer valuable insights into the mechanism of interactions between RNL and ND, demonstrating that RNL immobilization onto NDs enhances its efficiency and stability. All told, these findings highlight the immense potential of ND-immobilized RNL as an excellent candidate for biological applications and showcase the promise of further research in this field.

Stability and Activity of Rhodium Promoted Nickel-Based Catalysts in Dry Reforming of Methane.

The rhodium oxide (Rh2O3) doping effect on the activity and stability of nickel catalysts supported over yttria-stabilized zirconia was examined in dry reforming of methane (DRM) by using a tubular reactor, operated at 800 °C. The catalysts were characterized by using several techniques including nitrogen physisorption, X-ray diffraction, transmission electron microscopy, H2-temperature programmed reduction, CO2-temperature programmed Desorption, and temperature gravimetric analysis (TGA). The morphology of Ni-YZr was not affected by the addition of Rh2O3. However, it facilitated the activation of the catalysts and reduced the catalyst's surface basicity. The addition of 4.0 wt.% Rh2O3 gave the optimum conversions of CH4 and CO2 of ~89% and ~92%, respectively. Furthermore, the incorporation of Rh2O3, in the range of 0.0-4.0 wt.% loading, enhanced DRM and decreased the impact of reverse water gas shift, as inferred by the thermodynamics analysis. TGA revealed that the addition of Rh2O3 diminished the carbon formation on the spent catalysts, and hence, boosted the stability, owing to the potential of rhodium for carbon oxidation through gasification reactions. The 4.0 wt.% Rh2O3 loading gave a 12.5% weight loss of carbon. The TEM images displayed filamentous carbon, confirming the TGA results.

Energy Level Prediction of Organic Semiconductors for Photodetectors and Mining of a Photovoltaic Database to Search for New Building Units.

Due to the large versatility in organic semiconductors, selecting a suitable (organic semiconductor) material for photodetectors is a challenging task. Integrating computer science and artificial intelligence with conventional methods in optimization and material synthesis can guide experimental researchers to develop, design, predict and discover high-performance materials for photodetectors. To find high-performance organic semiconductor materials for photodetectors, it is crucial to establish a relationship between photovoltaic properties and chemical structures before performing synthetic procedures in laboratories. Moreover, the fast prediction of energy levels is desirable for designing better organic semiconductor photodetectors. Herein, we first collected large sets of data containing photovoltaic properties of organic semiconductor photodetectors reported in the literature. In addition, molecular descriptors that make it easy and fast to predict the required properties were used to train machine learning models. Power conversion efficiency and energy levels were also predicted. Multiple models were trained using experimental data. The light gradient boosting machine (LGBM) regression model and Hist gradient booting regression model are the best models. The best models were further tuned to achieve better prediction ability. The reliability of our designed approach was further verified by mining the photovoltaic database to search for new building units. The results revealed that good consistency is obtained between experimental outcomes and model predictions, indicating that machine learning is a powerful approach to predict the properties of photodetectors, which can facilitate their rapid development in various fields.

Palm Raceme as a Promising Biomass Precursor for Activated Carbon to Promote Lipase Activity with the Aid of Eutectic Solvents.

This study concerns the role of activated carbon (AC) from palm raceme as a support material for the enhancement of lipase-catalyzed reactions in an aqueous solution, with deep eutectic solvent (DES) as a co-solvent. The effects of carbonization temperature, impregnation ratio, and carbonization time on lipase activity were studied. The activities of Amano lipase from Burkholderia cepacia (AML) and lipase from the porcine pancreas (PPL) were used to investigate the optimum conditions for AC preparation. The results showed that AC has more interaction with PPL and effectively provides greater enzymatic activity compared with AML. The optimum treatment conditions of AC samples that yield the highest enzymatic activity were 0.5 (NaOH (g)/palm raceme (g)), 150 min, and a carbonization temperature of 400 °C. DES was prepared from alanine/sodium hydroxide and used with AC for the further enhancement of enzymatic activity. Kinetic studies demonstrated that the activity of PPL was enhanced with the immobilization of AC in a DES medium.

Enhancement of brackish water desalination using hybrid membrane distillation and reverse osmosis systems.

Desalination of geothermal brackish water by membrane distillation (MD) provides a low recovery rate, but integrating MD with reverse osmosis (RO) can maximize the production rate. In this study, different design configurations of a hybrid system involving brine recycling and cascading are studied via simulations, and the performance improvement due to the process integration is substantiated via the increased recovery rate and reduced specific energy consumption. Brine recycling is also found to improve the recovery rate considerably to 40% at an energy cost of 0.9 $/m3. However, this achievement is only valid when the final brine is recycled to the RO feed: when the final brine is recycled to the MD feed, the overall performance degrades because the recycled brine cools the feed and causes a serious reduction in the driving force and the consequent production rate. Configuring the hybrid system in multiple stages connected in series increases the recovery rate to 90% and reduces the specific energy consumption to 0.9 MJ/kg. Although the specific energy cost increases dramatically because external inter-stage heating is implemented, using a free energy source (such as a geothermal or waste-energy source) for inter-stage heating could provide the optimum configuration.

[EFFECT OF YOUNG AGE ON CLINICAL, PATHOLOGICAL FEATURES AND SURVIVAL OF PATIENTS WITH COLORECTAL CANCER].

BACKGROUND: Colorectal cancer is one of the most common malignancies in the Western World and in Israel. Most patients with colon cancer are older than 50 years of age. There is no consensus in the literature regarding the behavior of this disease in young patients. AIM: The aim of the present study is to compare clinical and ic pathological features of colon cancer between young and sold patients. METHODS: All clinical and pathological characteristics of 200 patients with colon cancer treated at our center during the period 2001-2006 were retrospectively reviewed. RESULTS: Twenty five patients (12.5%) were <50 years age (young patients) at diagnosis (mean age 41 years) and 175 were >50 years (mean age 68 years). Males were 56% of the young group and 60.1% of the old one. Arab patients were 52% of the young group, although their total number was 35 of the 200 patients. No significant difference was found in the stage of tumor at diagnosis between the two groups. Histopathological grade 3 tumors were found in 33.3% of young versus 7.7% in old patients. Surgery and chemotherapy were performed in 96% and 88% versus 95.4% and 69.7% in the two groups respectively. In a median follow-up period of 96 months, 35% of young patients died of their disease compared to 33.1% of the old patients. CONCLUSIONS: Other than histological grade, no difference was found in colon cancer features and survival of young compared to old patients. Further studies with higher numbers of patients are suggested to clarify our findings.