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The textile industry generates highly contaminated wastewater. It severely threatens local ecosystems without proper treatment, significantly diminishing biodiversity near the discharge point. With rapid growth rates, microalgae offer an effective solution to mitigate the environmental impact of textile wastewater, and the generated biomass can be valorised. This study sets out to achieve two primary objectives: (i) to assess the removal of pollutants by Chlorella vulgaris from two distinct real textile wastewaters (without dilution) and (ii) to evaluate microalgal biomass composition for further valorisation (in a circular economy approach). Microalgae grew successfully with growth rates ranging from 0.234 ± 0.005 to 0.290 ± 0.003 d−1 and average productivities ranging from 78 ± 3 to 112.39 ± 0.07 mgDW L−1 d−1. All cultures demonstrated a significant reduction in nutrient concentrations for values below the legal limits for discharge, except for COD in effluent 2. Furthermore, the pigment concentration in the culture increased during textile effluent treatment, presenting a distinct advantage over conventional ones due to the economic value of produced biomass and pigments. This study underscores the promise of microalgae in textile wastewater treatment and provides valuable insights into their role in addressing the environmental challenges the textile industry poses.

Carbon dioxide (CO2) emissions to the atmosphere have drastically increased in recent decades, with the energy and transport sectors representing major fractions of total greenhouse gas (GHG) emissions [...]

Microalgae have been intensively studied for CO2 capture, nutrient removal from wastewater, and biofuel production applications [...]

Study Question: Can additional genetic variants for circulating anti-Müllerian hormone (AMH) levels be identified through a genome-wide association study (GWAS) meta-analysis including a large sample of premenopausal women?Summary Answer: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7.What Is Known Already: AMH is expressed by antral stage ovarian follicles in women, and variation in age-specific circulating AMH levels has been associated with disease outcomes. However, the physiological mechanisms underlying these AMH-disease associations are largely unknown.Study Design, Size, Duration: We performed a GWAS meta-analysis in which we combined summary statistics of a previous AMH GWAS with GWAS data from 3705 additional women from three different cohorts.Participants/materials, Setting, Methods: In total, we included data from 7049 premenopausal female participants of European ancestry. The median age of study participants ranged from 15.3 to 48 years across cohorts. Circulating AMH levels were measured in either serum or plasma samples using different ELISA assays. Study-specific analyses were adjusted for age at blood collection and population stratification, and summary statistics were meta-analysed using a standard error-weighted approach. Subsequently, we functionally annotated GWAS variants that reached genome-wide significance (P < 5 × 10-8). We also performed a gene-based GWAS, pathway analysis and linkage disequilibrium score regression and Mendelian randomization (MR) analyses.Main Results and the Role Of Chance: We identified four loci associated with AMH levels at P < 5 × 10-8: the previously reported MCM8 locus and three novel signals in or near AMH, TEX41 and CDCA7. The strongest signal was a missense variant in the AMH gene (rs10417628). Most prioritized genes at the other three identified loci were involved in cell cycle regulation. Genetic correlation analyses indicated a strong positive correlation among single nucleotide polymorphisms for AMH levels and for age at menopause (rg = 0.82, FDR = 0.003). Exploratory two-sample MR analyses did not support causal effects of AMH on breast cancer or polycystic ovary syndrome risk, but should be interpreted with caution as they may be underpowered and the validity of genetic instruments could not be extensively explored.Large Scale Data: The full AMH GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/).Limitations, Reasons For Caution: Whilst this study doubled the sample size of the most recent GWAS, the statistical power is still relatively low. As a result, we may still lack power to identify more genetic variants for AMH and to determine causal effects of AMH on, for example, breast cancer. Also, follow-up studies are needed to investigate whether the signal for the AMH gene is caused by reduced AMH detection by certain assays instead of actual lower circulating AMH levels.Wider Implications Of the Findings: Genes mapped to the MCM8, TEX41 and CDCA7 loci are involved in the cell cycle and processes such as DNA replication and apoptosis. The mechanism underlying their associations with AMH may affect the size of the ovarian follicle pool. Altogether, our results provide more insight into the biology of AMH and, accordingly, the biological processes involved in ovarian ageing.Study Funding/competing Interest(s): Nurses' Health Study and Nurses' Health Study II were supported by research grants from the National Institutes of Health (CA172726, CA186107, CA50385, CA87969, CA49449, CA67262, CA178949). The UK Medical Research Council and Wellcome (217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. This publication is the work of the listed authors, who will serve as guarantors for the contents of this article. A comprehensive list of grants funding is available on the ALSPAC website (http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf). Funding for the collection of genotype and phenotype data used here was provided by the British Heart Foundation (SP/07/008/24066), Wellcome (WT092830M and WT08806) and UK Medical Research Council (G1001357). M.C.B., A.L.G.S. and D.A.L. work in a unit that is funded by the University of Bristol and UK Medical Research Council (MC_UU_00011/6). M.C.B.'s contribution to this work was funded by a UK Medical Research Council Skills Development Fellowship (MR/P014054/1) and D.A.L. is a National Institute of Health Research Senior Investigator (NF-0616-10102). A.L.G.S. was supported by the study of Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739). The Doetinchem Cohort Study was financially supported by the Ministry of Health, Welfare and Sports of the Netherlands. The funder had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Ansh Labs performed the AMH measurements for the Doetinchem Cohort Study free of charge. Ansh Labs was not involved in the data analysis, interpretation or reporting, nor was it financially involved in any aspect of the study. R.M.G.V. was funded by the Honours Track of MSc Epidemiology, University Medical Center Utrecht with a grant from the Netherlands Organization for Scientific Research (NWO) (022.005.021). The Study of Women's Health Across the Nation (SWAN) has grant support from the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR) and the NIH Office of Research on Women's Health (ORWH) (U01NR004061; U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495). The SWAN Genomic Analyses and SWAN Legacy have grant support from the NIA (U01AG017719). The Generations Study was funded by Breast Cancer Now and the Institute of Cancer Research (ICR). The ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent official views of the funders. The Sister Study was funded by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z01-ES044005 to D.P.S.); the AMH assays were supported by the Avon Foundation (02-2012-065 to H.B. Nichols and D.P.S.). The breast cancer genome-wide association analyses were supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the 'Ministère de l'Économie, de la Science et de l'Innovation du Québec' through Genome Québec and grant PSR-SIIRI-701, The National Institutes of Health (U19 CA148065, X01HG007492), Cancer Research UK (C1287/A10118, C1287/A16563, C1287/A10710) and The European Union (HEALTH-F2-2009-223175 and H2020 633784 and 634935). All studies and funders are listed in Michailidou et al. (Nature, 2017). F.J.M.B. has received fees and grant support from Merck Serono and Ferring BV. D.A.L. has received financial support from several national and international government and charitable funders as well as from Medtronic Ltd and Roche Diagnostics for research that is unrelated to this study. N.S. is scientific consultant for Ansh Laboratories. The other authors declare no competing interests. [ABSTRACT FROM AUTHOR]