Coupling bootstrap with synergy self-organizing map-based orthogonal partial least squares discriminant analysis: Stable metabolic biomarker selection for inherited metabolic diseases.

Biomarker selection has played an increasingly important part in modern medicine with advances of omics techniques. Kohonen self-organizing map is a well-established variable reduction algorithm in identifying significant biomarkers based on variable clustering. However, high dimensionality but small sample size of omics data makes self-organizing map-based model problematic in terms of selection stability and reproducibility. A novel feature screening system is presented in this study by coupling bootstrap with synergy self-organizing map-based orthogonal partial least squares discriminant analysis for stable and biologically meaningful metabolic biomarker selection. In the proposed feature screening system, particle swarm optimization algorithm is utilized to configure synergy self-organizing map-based orthogonal partial least squares discriminant analysis to perform the combination of clusters in a heuristic learning manner, enabling flexible selection of more informative features cost-effectively. Based on the paradigm of ensemble feature selection, bootstrap is adopted to explore significant variables consistently identified across multiple feature selectors rather than a single one. The feasibility of the novel feature screening system is evaluated by two most common inherited metabolic diseases, methylmalonic academia and propionic academia, using urinary metabolomics data. With the desirable classification performance, the proposed feature screening system outperforms simpler techniques in the identification of more features closely correlated with the metabolic mechanisms and the stability of selected candidate biomarkers against sample variations. Besides, the novel feature screening system greatly degrades the sensitivity of identified candidate biomarkers to the network size of self-organizing map, benefiting the identification of a suitable and stable final candidate biomarker list.

[Bacterial Community Shifts and Nitrogen Removal Characteristics for a SNAD Process Treating Anaerobic Digester Liquor of Swine Wastewater (ADLSW) in a Continuous-Flow Biofilm Reactor (CFBR)].

To realize a simultaneous partial nitrification, ANAMMOX (anaerobic ammonium oxidation), and denitrification (SNAD) process treating anaerobic digester liquor of swine wastewater (ADLSW) in a continuous-flow biofilm reactor (CFBR), we first gradually increased the influent ammonium (NH4+-N) concentration, and then enhanced the ADLSW ratio in the influent during operation; dissolved oxygen (DO) was controlled at (0.4±0.1) mg·L-1 by adjusting the air flow rate, and the temperature was kept at (30±1)℃. Meanwhile, high-throughput sequencing and quantitative PCR (polymerase chain reaction) techniques were used to analyze the bacterial community shifts and the amount of dominant nitrogen removal bacteria. The results demonstrated that a successful start-up of the SNAD process was accomplished in 150 d, and replacement of the actual biogas slurry was completed in 298 d. The effluent (NO3--N+NO2--N)/ΔNH4+-N value was less than 0.11, and the average removal rates of NH4+-N and TN (total nitrogen) increased to 63.26% and 55.71%, respectively. Moreover, high-throughput sequencing results demonstrated that the dominant microbial populations at phylum level were Chloroflexi (with a relative abundance of 50.78%), Proteobacteria (13.34%), and Planctomycetes (9.26%). The relative abundance of Nitrosomonas increased from 1.55% to 1.98%. In addition, the relative abundance of Candidatus_Brocadia and Candidatus_Kuenenia increased from 0.01% and (<0.01%) to 4.66% and 4.18%, respectively, and the relative abundance of Denitratisoma increased from (<0.01%) to 2.06%. Meanwhile, qPCR analysis showed that the amounts of ammonia-oxidizing bacteria, ANAMMOX, and denitrifying bacteria increased significantly compared with the inoculated sludge. An efficient and stable nitrogen removal rate can be achieved, and the follow-up processing cost can be reduced, by application of the SNAD treatment process for ADLSW.

Intermolecular copigmentation between five common 3-O-monoglucosidic anthocyanins and three phenolics in red wine model solutions: The influence of substituent pattern of anthocyanin B ring.

In this study, intermolecular copigmentation between five primary wine monoglucosidic anthocyanins (cyanidin-3-O-glucoside, peonidin-3-O-glucoside, delphinidin-3-O-glucoside, petunidin-3-O-glucoside, and malvidin-3-O-glucoside) and three common wine phenolics (gallic acid, (-)-epicatechin, and quercetin-3-O-glucoside) were investigated through experimental and theoretical methods, and the influence of substituent pattern of anthocyanin B ring was studied emphatically. Chromatic and thermodynamic analysis showed there were great differences among these different pigment-copigment systems. Spatial conformations of the 15 copigmentation complexes were obtained through theoretical calculation, and diverse π-π stacking modes were observed. These results indicated that the substituent pattern of anthocyanin B ring had significant impact on its affinity to copigments, and more, the structures of pigments and copigments determined the color expression and stability of copigmentation together.