This study aims understand microplastics from personal care and cosmetic products in Malaysia via quantification and characterization of microplastics together with emission estimation to marine environment. A total of 214 respondents from all over Malaysia were surveyed with identification of top ten personal care and cosmetic products usage. Particles found in facial cleaner/scrub and toothpaste were colored and colorless with majority of granular shapes. Particles in toothpaste were found between 3 and 145 μm while particles in facial cleaner/scrub were found to be between 10 and 178 μm, stipulating the presence of microplastics. Plastic polymers (LDPE and polypropylene) were found in all facial cleaner/scrub samples while only plastic polymers (LDPE) were present in toothpaste sample G. A total of 0.199 trillion microplastics are expected to be released annually to marine environment in Malaysia. Personal care and cosmetic products are seen as one of the microplastics sources for Malaysia and worldwide.
A novel coupling process using an aerobic bacterial reactor with nitrification and sulfur-oxidization functions followed by a microalgal reactor was proposed for simultaneous biogas desulfurization and anaerobic digestion effluent (ADE) treatment. ADE nitrified by bacteria has a potential to be directly used as a culture medium for microalgae because ammonium nitrogen, including inhibitory free ammonia (NH3), has been converted to harmless NO3-. To demonstrate this hypothesis, Chlorella sorokiniana NIES-2173, which has ordinary NH3 tolerance; that is, 1.6 mM of EC50 compared with other species, was cultivated using untreated/treated ADE. Compared with the use of a synthetic medium, when using ADE with 1-10-fold dilutions, the specific growth rate and growth yield maximally decreased by 44% and 88%, respectively. In contrast, the algal growth using undiluted ADE treated by nitrification-desulfurization was almost the same as with using synthetic medium. It was also revealed that 50% of PO43- and most metal concentrations of ADE decreased following nitrification-desulfurization treatment. Moreover, upon NaOH addition for pH adjustment, the salinity increased to 0.66%. The decrease in metals mitigates the bioconcentration of toxic heavy metals from wastewater in microalgal biomass. Meanwhile, salt stress in microalgae and limiting nutrient supplementation, particularly for continuous cultivation, should be of concern.
Sulfide inhibition to nitrifying bacteria has prevented the integration of digestate nitrification and biogas desulfurization to simplify anaerobic digestion systems. In this study, liquid digestate with NaHS solution was treated using nitrifying sludge in a sequential-batch reactor with a long fill period, with an ammonium loading rate of 293 mg-N L-1 d-1 and a stepwise increase in the sulfide loading rate from 0 to 32, 64, 128, and 256 mg-S L-1 d-1. Batch bioassays and microbial community analysis were also conducted with reactor sludge under each sulfide loading rate to quantify the microbial acclimatization to sulfide. In the reactor, sulfide was completely removed. Complete nitrification was maintained up to a sulfide load of 128 mg-S L-1 d-1, which is higher than that in previous reports and sufficient for biogas treatment. In the batch bioassays, the sulfide tolerance of NH4+ oxidizing activity (the 50% inhibitory sulfide concentration) increased fourfold over time with the compositional shift of nitrifying bacteria to Nitrosomonas nitrosa and Nitrobacter spp. However, the sulfur removal rate of the sludge slightly decreased, although the abundance of the sulfur-oxidizing bacteria Hyphomicrobium increased by 30%. Therefore, nitrifying sludge was probably acclimatized to sulfide not by the increasing sulfide removal rate but rather by the increasing nitrifying bacteria, which have high sulfide tolerance. Successful simultaneous nitrification and desulfurization were achieved using a sequential-batch reactor with a long fill period, which was effective in facilitating the present acclimatization.
Human leukocyte antigen (HLA) is a key genetic factor conferring risk of systemic lupus erythematosus (SLE), but precise independent localization of HLA effects is extremely challenging. As a result, the contribution of specific HLA alleles and amino-acid residues to the overall risk of SLE and to risk of specific autoantibodies are far from completely understood. Here, we dissected (a) overall SLE association signals across HLA, (b) HLA-peptide interaction, and (c) residue-autoantibody association. Classical alleles, SNPs, and amino-acid residues of eight HLA genes were imputed across 4,915 SLE cases and 13,513 controls from Eastern Asia. We performed association followed by conditional analysis across HLA, assessing both overall SLE risk and risk of autoantibody production. DR15 alleles HLA-DRB1*15:01 (P = 1.4x10-27, odds ratio (OR) = 1.57) and HLA-DQB1*06:02 (P = 7.4x10-23, OR = 1.55) formed the most significant haplotype (OR = 2.33). Conditioned protein-residue signals were stronger than allele signals and mapped predominantly to HLA-DRB1 residue 13 (P = 2.2x10-75) and its proxy position 11 (P = 1.1x10-67), followed by HLA-DRB1-37 (P = 4.5x10-24). After conditioning on HLA-DRB1, novel associations at HLA-A-70 (P = 1.4x10-8), HLA-DPB1-35 (P = 9.0x10-16), HLA-DQB1-37 (P = 2.7x10-14), and HLA-B-9 (P = 6.5x10-15) emerged. Together, these seven residues increased the proportion of explained heritability due to HLA to 2.6%. Risk residues for both overall disease and hallmark autoantibodies (i.e., nRNP: DRB1-11, P = 2.0x10-14; DRB1-13, P = 2.9x10-13; DRB1-30, P = 3.9x10-14) localized to the peptide-binding groove of HLA-DRB1. Enrichment for specific amino-acid characteristics in the peptide-binding groove correlated with overall SLE risk and with autoantibody presence. Risk residues were in primarily negatively charged side-chains, in contrast with rheumatoid arthritis. We identified novel SLE signals in HLA Class I loci (HLA-A, HLA-B), and localized primary Class II signals to five residues in HLA-DRB1, HLA-DPB1, and HLA-DQB1. These findings provide insights about the mechanisms by which the risk residues interact with each other to produce autoantibodies and are involved in SLE pathophysiology.