Biogas purification via water scrubbing produces effluent containing dissolved CH4, H2S, and CO2, which should be removed to reduce greenhouse gas emissions and increase its potential for water regeneration. In this study, a reactor built with air supplies at the top and bottom was utilized for the treatment of biogas purification effluent through biological oxidation and physical stripping processes. Up to 98% of CH4 was removed through biological treatment at a hydraulic retention time of 2 hr and an upper airflow rate of 2.02 L/day. Additionally, a minimum CH4 concentration of 0.04% with no trace of H2S gas was detected in the off gas. Meanwhile, a white precipitate was captured on the carrier showing the formation of sulfur. According to the developed mathematical model, an upper airflow rate of greater than 2.02 L/day showed a small deterioration in CH4 removal performance after reaching the maximum value, whereas a 50 L/day bottom airflow rate was required to strip the CO2 efficiently and raise the effluent pH from 5.64 to 7.3. Microbiological analysis confirmed the presence of type 1 methanotroph communities dominated by Methylobacter and Methylocaldum. However, bacterial communities promoting sulfide oxidation were dominated by Hyphomicrobium.
Per- and polyfluoroalkyl substances (PFAS), one of the main categories of emerging contaminants, are a family of fluorinated organic compounds of anthropogenic origin. PFAS can endanger the environment and human health because of their wide application in industries, long-term persistence, unique properties, and bioaccumulation potential. This study sought to explain the accumulation of different PFAS in water bodies. In aquatic environments, PFAS concentrations range extensively from <0.03 (groundwater; Melbourne, Australia) to 51,000 ng/L (Groundwater, Sweden). Additionally, bioaccumulation of PFAS in fish and water biota has been stated to range from 0.2 (Burbot, Lake Vättern, Sweden) to 13,900 ng/g (Bluegill samples, U.S.). Recently, studies have focused on PFAS removal from aqueous solutions; one promising technique is advanced oxidation processes (AOPs), including microwaves, ultrasound, ozonation, photocatalysis, UV, electrochemical oxidation, the Fenton process, and hydrogen peroxide-based and sulfate radical-based systems. The removal efficiency of PFAS ranges from 3% (for MW) to 100% for UV/sulfate radical as a hybrid reactor. Therefore, a hybrid reactor can be used to efficiently degrade and remove PFAS. Developing novel, efficient, cost-effective, and sustainable AOPs for PFAS degradation in water treatment systems is a critical area of research.
White matter (WM) fiber bundles change dynamically with age. These changes could be driven by alterations in axonal diameter, axonal density, and myelin content. In this study, we applied a novel fixel-based analysis (FBA) framework to examine these changes throughout the adult lifespan. Using diffusion-weighted images from a cohort of 293 healthy volunteers (89 males/204 females) from ages 21 to 86 years old, we performed FBA to analyze age-related changes in microscopic fiber density (FD) and macroscopic fiber morphology (fiber cross section [FC]). Our results showed significant and widespread age-related alterations in FD and FC across the whole brain. Interestingly, some fiber bundles such as the anterior thalamic radiation, corpus callosum, and superior longitudinal fasciculus only showed significant negative relationship with age in FD values, but not in FC. On the other hand, some segments of the cerebello-thalamo-cortical pathway only showed significant negative relationship with age in FC, but not in FD. Analysis at the tract-level also showed that major fiber tract groups predominantly distributed in the frontal lobe (cingulum, forceps minor) exhibited greater vulnerability to the aging process than the others. Differences in FC and the combined measure of FD and cross section values observed between sexes were mostly driven by differences in brain sizes although male participants tended to exhibit steeper negative linear relationship with age in FD as compared to female participants. Overall, these findings provide further insights into the structural changes the brain's WM undergoes due to the aging process.
Autism spectrum disorder (ASD) is caused by combined genetic and environmental factors. Genetic heritability in ASD is estimated as 60-90%, and genetic investigations have revealed many monogenic factors. We analyzed 405 patients with ASD using family-based exome sequencing to detect disease-causing single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variations (CNVs) for molecular diagnoses. All candidate variants were validated by Sanger sequencing or quantitative polymerase chain reaction and were evaluated using the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines for molecular diagnosis. We identified 55 disease-causing SNVs/indels in 53 affected individuals and 13 disease-causing CNVs in 13 affected individuals, achieving a molecular diagnosis in 66 of 405 affected individuals (16.3%). Among the 55 disease-causing SNVs/indels, 51 occurred de novo, 2 were compound heterozygous (in one patient), and 2 were X-linked hemizygous variants inherited from unaffected mothers. The molecular diagnosis rate in females was significantly higher than that in males. We analyzed affected sibling cases of 24 quads and 2 quintets, but only one pair of siblings shared an identical pathogenic variant. Notably, there was a higher molecular diagnostic rate in simplex cases than in multiplex families. Our simulation indicated that the diagnostic yield is increasing by 0.63% (range 0-2.5%) per year. Based on our simple simulation, diagnostic yield is improving over time. Thus, periodical reevaluation of ES data should be strongly encouraged in undiagnosed ASD patients.
Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.