Henna plant biomass enhanced azo dye removal: Operating performance, microbial community and machine learning modeling.

The bio-reduction of azo dyes is significantly dependent on the availability of electron donors and external redox mediators. In this study, the natural henna plant biomass was supplemented to promote the biological reduction of an azo dye of Acid Orange 7 (AO7). Besides, the machine learning (ML) approach was applied to decipher the intricate process of henna-assisted azo dye removal. The experimental results indicated that the hydrolysis and fermentation of henna plant biomass provided both electron donors such as volatile fatty acid (VFA) and redox mediator of lawsone to drive the bio-reduction of AO7 to sulfanilic acid (SA). The high henna dosage selectively enriched certain bacteria, such as Firmicutes phylum, Levilinea and Paludibacter genera, functioning in both the henna fermentation and AO7 reduction processes simultaneously. Among the three tested ML algorithms, eXtreme Gradient Boosting (XGBoost) presented exceptional accuracy and generalization ability in predicting the effluent AO7 concentrations with pH, oxidation-reduction potential (ORP), soluble chemical oxygen demand (SCOD), VFA, lawsone, henna dosage, and cumulative henna as input variables. The validating experiments with tailored optimal operating conditions and henna dosage (pH 7.5, henna dosage of 2 g/L, and cumulative henna of 14 g/L) confirmed that XGBoost was an effective ML model to predict the efficient AO7 removal (91.6%), with a negligible calculating error of 3.95%. Overall, henna plant biomass addition was a cost-effective and robust method to improve the bio-reduction of AO7, which had been demonstrated by long-term operation, ML modeling, and experimental validation.

Coupled process of in-situ sludge fermentation and riboflavin-mediated nitrogen removal for low carbon wastewater treatment.

Volatile fatty acid recovery from waste activated sludge (WAS) was highly suggested to supplement carbon source for nitrogen removal. However, it was not easy to separate them from the metabolites under the ex-situ fermentation. In this study, in-situ WAS fermentation combined in the denitrification system was established to treat low carbon wastewater (COD/TN = 4), and riboflavin was employed as a redox mediator. This coupled process could simultaneously enhance the WAS fermentation and nitrogen removal, and riboflavin could significantly enrich the fermentative bacteria (Firmicutes phylum), denitrifying bacteria (Denitratisoma genus) and related functional genes (narGHJI, napABC, nirKS, nosZ, norBC), generating more available carbon sources for efficient nitrogen removal. This resulted in the effluent TN (<15 mg/L) satisfying the required discharge standard in China. This study provided new insights into the efficient nitrogen removal from low carbon wastewater, realizing the carbon-neutral operation of new concept wastewater treatment plant in China.

Identifying compositional and structural changes in the nucleus pulposus from patients with lumbar disc herniation using Raman spectroscopy.

Lower back pain (LBP) is one of the most common musculoskeletal complaints worldwide. Intervertebral disc degeneration (IDD) is considered to be a significant contributor to LBP; however, the mechanisms underlying IDD remain to be fully elucidated. One of the major features of IDD is the decreased content of type II collagen and proteoglycans in the nucleus pulposus (NP). The present study aimed to investigate the biochemical mechanisms of IDD at the microscopic level using Raman spectroscopy. Raman spectroscopy, based on inelastic scattering of light, is an emerging optical technique that may measure the chemical composition of complex biological samples, including biofluids, cells and tissues. In the present study, 30 NP tissue samples from 30 patients who were diagnosed with lumbar disc herniation and received spinal fusion surgery to relieve LBP were obtained and analyzed. Routine pre-operative 3.0T, T2-weighed MRI was used to classify the cases according to Pfirrmann grades and the T2 signal intensity value of the NP was measured. Subsequently, all NP samples were scanned and analyzed using a Laser MicroRaman Spectrometer at room temperature. The Raman spectral results demonstrated that the relative content of proteoglycans, expressed as the relative intensity ratio of two peaks (I1064/I1004), was significantly inversely correlated with the Pfirrmann grade (ρ=-0.6462; P<0.0001), whereas the content of collagen (amide I) was significantly positively correlated with the Pfirrmann grade (ρ=0.5141; P<0.01). In conclusion, the higher relative intensity of the ratio of two peaks (I1670/I1640; Amide I) represented a higher fractional content of disordered collagen, which suggested that the defective collagen structure may lead to NP abnormalities.