Adsorption mechanism and effectiveness of phenol and tannic acid removal by biochar produced from oil palm frond using steam pyrolysis.

In order to meet the growing demand for adsorbents to treat wastewater effectively, there has been increased interest in using sustainable biomass feedstocks. In this present study, the dermal tissue of oil palm frond was pyrolyzed with superheated steam at 500 °C to produce nanoporous biochar as bioadsorbent. The effect of operating conditions was investigated to understand the adsorption mechanism and to enhance the adsorption of phenol and tannic acid. The biochar had a microporous structure with a Brunauer-Emmett-Teller surface area of 422 m2/g containing low polar groups. The adsorption capacity of 62.89 mg/g for phenol and 67.41 mg/g for tannic acid were obtained using 3 g/L biochar dosage after 8 h of treatment at solution pH of 6.5 and temperature of 45 °C. The Freundlich model had the best fit to the isotherm data of phenol (R2 of 0.9863), while the Langmuir model best elucidated the isotherm data of tannic acid (R2 of 0.9632). These indicated that the biochar-phenol interface was associated with a heterogeneous multilayer sorption mechanism, while the biochar-tannic acid interface had a nonspecific monolayer sorption mechanism. The residual concentration of 26.3 mg/L phenol and 23.1 mg/L tannic acid was achieved when treated from 260 mg/L three times consecutively with 1 g/L biochar dosage, compared to a reduction to 72.3 mg/L phenol and 69.9 mg/L tannic acid using 3 g/L biochar dosage in a single treatment. The biochar exhibited effective adsorption of phenol and tannic acid, making it possible to treat effluents that contain varieties of phenolic compounds.

Blood co-expression modules identify potential modifier genes of diabetes and lung function in cystic fibrosis.

Cystic fibrosis (CF) is a rare genetic disease that affects the respiratory and digestive systems. Lung disease is variable among CF patients and associated with the development of comorbidities and chronic infections. The rate of lung function deterioration depends not only on the type of mutations in CFTR, the disease-causing gene, but also on modifier genes. In the present study, we aimed to identify genes and pathways that (i) contribute to the pathogenesis of cystic fibrosis and (ii) modulate the associated comorbidities. We profiled blood samples in CF patients and healthy controls and analyzed RNA-seq data with Weighted Gene Correlation Network Analysis (WGCNA). Interestingly, lung function, body mass index, the presence of diabetes, and chronic P. aeruginosa infections correlated with four modules of co-expressed genes. Detailed inspection of networks and hub genes pointed to cell adhesion, leukocyte trafficking and production of reactive oxygen species as central mechanisms in lung function decline and cystic fibrosis-related diabetes. Of note, we showed that blood is an informative surrogate tissue to study the contribution of inflammation to lung disease and diabetes in CF patients. Finally, we provided evidence that WGCNA is useful to analyze-omic datasets in rare genetic diseases as patient cohorts are inevitably small.