The Use of a Mixed Chlorella Cyanobacteria Culture as a Protein Source for Aquaculture

The increase in the global demand for fish feed in the last decades has resulted in the over exploitation of natural resources to produce more fishmeal supplies for aquaculture industry. The supply issues and high prices of fishmeal products have raised the incentives to seek for suitable alternatives to replace fishmeal protein. As a by-product of biofuel production process, residual microalgal biomass may be a low cost feed ingredient to the aquaculture diet. The potential of the use of a post lipid extraction Chlorella vulgaris/Leptolyngbya sp. Co-Culture (Louisiana co-culture) as a protein source in aquaculture feeds could help offset fishmeal. The objective of this research was to (1) Determine the effect of nutritional and environmental conditions on the Louisiana Co-Culture biochemical composition (2) determine whether the Louisiana co-culture contains the quality and quantity of amino acid profile to be used for aquaculture feed (3) determine the change in the protein content and amino acid profile of the Louisiana co-culture due to the system dilution rate and lipid extraction process (4) determine the cost savings as the residual microalgal biomass incorporates in the aquatic animal diets. The optimum growth condition for the Louisiana co-culture to obtain the highest lipid and protein contents was found at 25°C when the cultures were supplied with 40 mg N L-1 and 530 mg C L-1. The protein and lipid content of the Louisiana co-culture were determined at 26.5±4.39 and 37.3±0.60 percent, respectively on a dry mass basis. The quality of the protein (amino acid profile) of the Louisiana co-culture was not found a function of the lipid extraction process (Chloroform: methanol, 2:1 v/v) although the protein content was affected significantly. The protein content was lower in the residual microalgal biomass. From the theoretical stand point, the Louisiana co-culture can replace up to 41, 6.5, 51, and 7.4 percent of fishmeal protein in the diets of channel catfish (Ictalurus punctatus), chinook salmon (Oncorhynchus tshawytscha), hybrid striped sea bass (Morone chrysops× Morone saxatilis), and tiger prawn (Penaeus monodon), respectively which will result in a decrease of up to 16, 8.9,37, and 4.5 percent of the costs of their dietary proteins

Effects of folic acid supplementation on liver enzymes, lipid profile, and insulin resistance in patients with non-alcoholic fatty liver disease: A randomized controlled trial

Background: Previous evidence revealed an association between folate deficiency and non-alcoholic fatty liver disease (NAFLD). This study is the first one investigating the effects of folic acid on hepatic steatosis grade, liver enzymes, insulin resistance, and lipid profile in NAFLD cases. Materials and Methods: Sixty-six participants with NAFLD were allocated randomly to take either a placebo or one oral tablet of folic acid (1 mg) on a daily basis within eight weeks. Serum folate, homocysteine, glucose, aminotransferases, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), and lipids were assessed. Ultrasonography was used for assessing the liver steatosis grade. Results: The serum alanine transaminase, grade of hepatic steatosis, and aspartate transaminase significantly were decreased within both study groups; however, the between-group comparison was not statistically significant. Of note, the decrease in ALT was more pronounced in folic acid compared with the placebo group (-5.45 ± 7.45 vs. -2.19 ± 8.6 IU/L). The serum homocysteine was decreased after receiving folic acid compared to the placebo (-0.58 ± 3.41 vs. +0.4 ± 3.56 μmol/L; adjusted P = 0.054). Other outcomes did not significantly change. Conclusion: Supplementation with folic acid (1 mg/d) for eight weeks among cases with NAFLD did not change significantly the serum levels of liver enzymes, the hepatic steatosis grade, insulin resistance and lipid profile. However, it was able to prevent the increase in homocysteine in comparison with the placebo. Conducting further research is suggested with the longer duration and different doses of folic acid, adjusted to the genotypes of methylenetetrahydrofolate reductase polymorphism, among NAFLD patients

Hybridized neural fuzzy ensembles for dust source modeling and prediction

© 2020 Dust storms are believed to play an essential role in many climatological, geochemical, and environmental processes. This atmospheric phenomenon can have a significant negative impact on public health and significantly disturb natural ecosystems. Identifying dust-source areas is thus a fundamental task to control the effects of this hazard. This study is the first attempt to identify dust source areas using hybridized machine-learning algorithms. Each hybridized model, designed as an intelligent system, consists of an adaptive neuro-fuzzy inference system (ANFIS), integrated with a combination of metaheuristic optimization algorithms: the bat algorithm (BA), cultural algorithm (CA), and differential evolution (DE). The data acquired from two key sources – the Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue and the Ozone Monitoring Instrument (OMI) – are incorporated into the hybridized model, along with relevant data from field surveys and dust samples. Goodness-of-fit analyses are performed to evaluate the predictive capability of the hybridized models using different statistical criteria, including the true skill statistic (TSS) and the area under the receiver operating characteristic curve (AUC). The results demonstrate that the hybridized ANFIS-DE model (with AUC = 84.1%, TSS = 0.73) outperforms the other comparative hybridized models tailored for dust-storm prediction. The results provide evidence that the hybridized ANFIS-DE model should be explored as a promising, cost-effective method for efficiently identifying the dust-source areas, with benefits for both public health and natural environments where excessive dust presents significant challenges

Chitosan-based nanoscale delivery systems in hepatocellular carcinoma: Versatile bio-platform with theranostic application

The field of nanomedicine has provided a fresh approach to cancer treatment by addressing the limitations of current therapies and offering new perspectives on enhancing patients' prognoses and chances of survival. Chitosan (CS) is isolated from chitin that has been extensively utilized for surface modification and coating of nanocarriers to improve their biocompatibility, cytotoxicity against tumor cells, and stability. HCC is a prevalent kind of liver tumor that cannot be adequately treated with surgical resection in its advanced stages. Furthermore, the development of resistance to chemotherapy and radiotherapy has caused treatment failure. The targeted delivery of drugs and genes can be mediated by nanostructures in treatment of HCC. The current review focuses on the function of CS-based nanostructures in HCC therapy and discusses the newest advances of nanoparticle-mediated treatment of HCC. Nanostructures based on CS have the capacity to escalate the pharmacokinetic profile of both natural and synthetic drugs, thus improving the effectiveness of HCC therapy. Some experiments have displayed that CS nanoparticles can be deployed to co-deliver drugs to disrupt tumorigenesis in a synergistic way. Moreover, the cationic nature of CS makes it a favorable nanocarrier for delivery of genes and plasmids. The use of CS-based nanostructures can be harnessed for phototherapy. Additionally, the incur poration of ligands including arginylglycylaspartic acid (RGD) into CS can elevate the targeted delivery of drugs to HCC cells. Interestingly, smart CS-based nanostructures, including ROS- and pH-sensitive nanoparticles, have been designed to provide cargo release at the tumor site and enhance the potential for HCC suppression