Multiple-pathway arsenic oxidation and removal from wastewater by a novel manganese-oxidizing aerobic granular sludge

Aerobic granular sludge (AGS) is a powerful biotechnology to remove various heavy metal(loid)s from wastewater, but not including arsenic (As). In this study, a novel manganese-oxidizing aerobic granular sludge (Mn-AGS) was developed to remove As from organic wastewater. Eight sequencing batch reactors (SBRs) were operated in duplicate to investigate the feasibility of As removal by Mn-AGS. The immobilized As in the granular sludge was characterized by sequencing extraction, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS), and Raman spectroscopy. Oxidation pathways for As and their contributions in Mn-AGS were evaluated by seven batch experiments under different conditions. The results indicated that As removal efficiency was much higher by Mn-AGS than by AGS. In Mn-AGS, As(III) was efficiently oxidized into As(V) (74.6%-82.6%) and then mostly bound on amorphous ferrihydrite and biogenic Mn oxides (bio-MnO_x) (56.2%-65.0%), while metal arsenates, such as ferric arsenate, were not detected. Importantly, As removal was greatly improved by a small addition of Fe(II) in Mn-AGS. This might be primarily caused by Fenton reactions, because this improvement was removed when H₂O₂, self-generated in Mn-AGS, was scavenged by exogenous catalase (CAT). This study provided a novel extension of the traditional AGS technology to treat As in organic wastewater with an acceptable degree of efficiency.

Moringa Oleifera Alleviates Homocysteine-Induced Alzheimer's Disease-Like Pathology and Cognitive Impairments

Alzheimer’s disease (AD) is multifactorial with unclear etiopathology. Due to the complexity of AD, many attempted single therapy treatments, like Aβ immunization, have generally failed. Therefore, there is a need for drugs with multiple benefits. Naturally occurring phytochemicals with neuroprotective, anti-amyloidogenic, antioxidative, and anti-inflammatory properties could be a possible way out. In this study, the effect of Moringa oleifera (MO), a naturally occurring plant with high antioxidative, anti-inflammatory, and neuroprotective effects, was evaluated on hyperhomocysteinemia (HHcy) induced AD-like pathology in rats. Homocysteine (Hcy) injection for 14 days was used to induce AD-like pathology. Simultaneous MO extract gavage followed the injection as a preventive treatment or, after injection completion, MO gavage was performed for another 14 days as a curative treatment. MO was found to not only prevent but also rescue the oxidative stress and cognitive impairments induced by Hcy treatment. Moreover, MO recovered the decreased synaptic proteins PSD93, PSD95, Synapsin 1 and Synaptophysin, and improved neurodegeneration. Interestingly, MO decreased the Hyc-induced tau hyperphosphorylation at different sites including S-199, T-231, S-396, and S-404, and at the same time decreased Aβ production through downregulation of BACE1. These effects in HHcy rats were accompanied by a decrease in calpain activity under MO treatment, supporting that calpain activation might be involved in AD pathogenesis in HHcy rats. Taken together, our data, for the first time, provided evidence that MO alleviates tau hyperphosphorylation and Aβ pathology in a HHcy AD rat model. This and previous other studies support MO as a good candidate for, and could provide new insights into, the treatment of AD and other tauopathies.

Application of a Tabu search-based Bayesian network in identifying factors related to hypertension

The study aimed to study the related factors of hypertension using multivariate logistic regression analysis and tabu search-based Bayesian Networks (BNs). A cluster random sampling method was adopted to obtain samples of the general population aged 15 years or above. Multivariate logistic regression analysis indicated that gender, age, cultural level, body mass index (BMI), central obesity, drinking, diabetes mellitus, Myocardial infarction, Coronary heart disease, Stroke are associated with hypertension. While BNs found connections between those related factors and hypertension were established by complex network structure, age, smoking, occupation, cultural level, BMI, central obesity, drinking, diabetes mellitus, myocardial infarction, coronary heart disease, nephropathy, stroke were direct connection with hypertension, gender was indirectly linked to hypertension through drinking. The results showed that BNs can not only find out the correlative factors of hypertension but also analyze how these factors affect hypertension and their interrelationships, which is consistent with practical theory better than logistic regression and has a better application prospects.

Comparison of plantar loads among runners with different strike patterns

This study aimed to explore the plantar loading variables between habitual rearfoot strike (RFS) and non-rearfoot strike (NRFS) during running. 78 healthy males participated in this study (41 RFS, 37 NRFS). In-shoe pressure sensors were used to measure plantar loading while the participants were running on a 15 m indoor runway with their preferred foot strike pattern (FSP) at 12.0 ± 5% km/h. Results indicate that force and pressure parameters were much higher in the rearfoot and midfoot regions during RFS running and relatively greater in forefoot region during NRFS running. However, compared with NRFS running, the contact area, maximum force and force-time-integrals during RFS running on total foot were 21.44% (P < 0.001, ES = 2.29), 13.99% (P = 0.006, ES = 0.64) and 21.27% (P < 0.001, ES = 0.85) higher, respectively. Total foot peak pressure and pressure-time-integral between two FSPs were similar. Higher loads in the rearfoot region may transmit to the knee joint and result in patellofemoral joint injuries. NRFS runners' higher loads in forefoot seem to be ralated to metatarsal stress fractures and compensatory damage to the Achilles tendon. Therefore, runners should choose proper FSPs according to their unique physical conditions.

Characterization of Thiamine Diphosphate-Dependent 4-Hydroxybenzoylformate Decarboxylase Enzymes from Rhodococcus jostii RHA1 and Pseudomonas fluorescens Pf-5 Involved in Degradation of Aryl C2 Lignin Degradation Fragments

A thiamine diphosphate-dependent enzyme annotated as a benzoylformate decarboxylase is encoded by gene cluster ro02984-ro02986 in Rhodococcus jostii RHA1 previously shown to generate vanillin and 4-hydroxybenzaldehyde from lignin oxidation, and a closely related gene cluster is also found in the genome of Pseudomonas fluorescens Pf-5. Two hypotheses for possible pathways involving a thiamine diphosphate-dependent cleavage, either C-C cleavage of a ketol or diketone aryl C₃ substrate or decarboxylation of an aryl C₂ substrate, were investigated by expression and purification of the recombinant enzymes and expression of dehydrogenase and oxidase enzymes also found in the gene clusters. The ThDP-dependent enzymes showed no activity for cleavage of aryl C₃ ketol or diketone substrates but showed activity for decarboxylation of benzoylformate and 4-hydroxybenzoylformate. A flavin-dependent oxidase encoded by gene ro02984 was found to oxidize either mandelic acid or phenylglyoxal. The crystal structure of the P. fluorescens decarboxylase enzyme was determined at 1.69 Å resolution, showing similarity to structures of known benzoylformate decarboxylase enzymes. The P. fluorescens decarboxylase enzyme showed enhanced carboligase activity between vanillin and acetaldehyde, rationalized by the presence of alanine versus serine at residue 73 in the enzyme active site, which was investigated further by site-directed mutagenesis of this residue. A hypothesis for a pathway for degradation of aryl C₂ fragments arising from oxidative cleavage of phenylcoumaran and diarylpropane structures in lignin is proposed.

m6Acomet: large-scale functional prediction of individual m6A RNA methylation sites from an RNA co-methylation network

Background

Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methylation, especially N6-methyladenosine, has become one of the most researched topics in epigenetics.

Results

To date, the study of epitranscriptome layer gene regulation is mostly focused on the function of mediator proteins of RNA methylation, i.e., the readers, writers and erasers. There is limited investigation of the functional relevance of individual m⁶A RNA methylation site. To address this, we annotated human m⁶A sites in large-scale based on the guilt-by-association principle from an RNA co-methylation network. It is constructed based on public human MeRIP-Seq datasets profiling the m⁶A epitranscriptome under 32 independent experimental conditions. By systematically examining the network characteristics obtained from the RNA methylation profiles, a total of 339,158 putative gene ontology functions associated with 1446 human m⁶A sites were identified. These are biological functions that may be regulated at epitranscriptome layer via reversible m⁶A RNA methylation. The results were further validated on a soft benchmark by comparing to a random predictor.

Conclusions

An online web server m6Acomet was constructed to support direct query for the predicted biological functions of m⁶A sites as well as the sites exhibiting co-methylated patterns at the epitranscriptome layer. The m6Acomet web server is freely available at: www.xjtlu.edu.cn/biologicalsciences/m6acomet.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2840-3) contains supplementary material, which is available to authorized users.

WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach

N 6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotes, and plays a pivotal role in various biological processes, such as splicing, RNA degradation and RNA-protein interaction. We report here a prediction framework WHISTLE for transcriptome-wide m6A RNA-methylation site prediction. When tested on six independent datasets, our approach, which integrated 35 additional genomic features besides the conventional sequence features, achieved a major improvement in the accuracy of m6A site prediction (average AUC: 0.948 and 0.880 under the full transcript or mature messenger RNA models, respectively) compared to the state-of-the-art computational approaches MethyRNA (AUC: 0.790 and 0.732) and SRAMP (AUC: 0.761 and 0.706). It also out-performed the existing epitranscriptome databases MeT-DB (AUC: 0.798 and 0.744) and RMBase (AUC: 0.786 and 0.736), which were built upon hundreds of epitranscriptome high-throughput sequencing samples. To probe the putative biological processes impacted by changes in an individual m6A site, a network-based approach was implemented according to the 'guilt-by-association' principle by integrating RNA methylation profiles, gene expression profiles and protein-protein interaction data. Finally, the WHISTLE web server was built to facilitate the query of our high-accuracy map of the human m6A epitranscriptome, and the server is freely available at: www.xjtlu.edu.cn/biologicalsciences/whistle and http://whistle-epitranscriptome.com.

Imbalance in obesity and mental health among "little emperors" in China

INTRODUCTION

Previous research has indicated that only children (i.e., those living with no siblings) have higher odds of obesity during childhood and young adulthood, compared with those living with siblings. However, little is known about whether the developing difference in overweight/obesity is accompanied by a difference in mental health (i.e., internalizing symptoms of depression and anxiety).

METHODS

The subjects for this prospective study were a randomly generated cohort of 1348 high-school students in Guangzhou, China. Participants completed assessments of anthropometric indices, lipid profiles, family-based factors, lifestyle, and internalization of symptoms (including those of depression and anxiety).

RESULTS

Compared to their peers with siblings, only children (adjusted odds ratio [aOR] = 1.68, 95% confidence interval [CI] [1.06, 2.65]) had significantly higher risk for obesity. However, only children with overweight/obesity had lower OR for depression at follow-up (aOR = 0.19, 95% CI [0.34, 0.86]), compared to individuals who were overweight/obese with siblings. This relationship was not significant for non-overweight individuals. No significant relationship between the number of siblings and anxiety at follow-up was observed, regardless of body mass index (BMI).

CONCLUSIONS

Although being an only child was significantly associated with overweight and obesity among adolescents in China, participants with history of overweight/obesity are less likely to experience symptoms of depression associated with being an only child.

Accurate Facial Image Parsing at Real-Time Speed

In this paper, we propose a design scheme for deep learning networks in face parsing task with promising accuracy and real-time inference speed. By analyzing the differences between general image parsing task and face parsing task, we first revisit the structure of traditional FCN and make improvements to adapt to the unique properties of face parsing task. Especially, the concept of Normalized Receptive Field is proposed to give more insights on designing the network. Then a novel loss function called Statistical Contextual Loss is introduced, which integrates richer contextual information and regularizes features during training. For further model acceleration, we propose a semi-supervised distillation scheme that effectively transfers the learned knowledge to a lighter network. Extensive experiments on LFW and Helen dataset demonstrate the significant superiority of the new design scheme on both efficacy and efficiency.

DRUM: Inference of Disease-Associated m6A RNA Methylation Sites From a Multi-Layer Heterogeneous Network

Recent studies have revealed that the RNA N 6-methyladenosine (m6A) modification plays a critical role in a variety of biological processes and associated with multiple diseases including cancers. Till this day, transcriptome-wide m6A RNA methylation sites have been identified by high-throughput sequencing technique combined with computational methods, and the information is publicly available in a few bioinformatics databases; however, the association between individual m6A sites and various diseases are still largely unknown. There are yet computational approaches developed for investigating potential association between individual m6A sites and diseases, which represents a major challenge in the epitranscriptome analysis. Thus, to infer the disease-related m6A sites, we implemented a novel multi-layer heterogeneous network-based approach, which incorporates the associations among diseases, genes and m6A RNA methylation sites from gene expression, RNA methylation and disease similarities data with the Random Walk with Restart (RWR) algorithm. To evaluate the performance of the proposed approach, a ten-fold cross validation is performed, in which our approach achieved a reasonable good performance (overall AUC: 0.827, average AUC 0.867), higher than a hypergeometric test-based approach (overall AUC: 0.7333 and average AUC: 0.723) and a random predictor (overall AUC: 0.550 and average AUC: 0.486). Additionally, we show that a number of predicted cancer-associated m6A sites are supported by existing literatures, suggesting that the proposed approach can effectively uncover the underlying epitranscriptome circuits of disease mechanisms. An online database DRUM, which stands for disease-associated ribonucleic acid methylation, was built to support the query of disease-associated RNA m6A methylation sites, and is freely available at: www.xjtlu.edu.cn/biologicalsciences/drum.

Simultaneous remediation of As(III) and dibutyl phthalate (DBP) in soil by a manganese-oxidizing bacterium and its mechanisms

Soils are experiencing increasing pollution with arsenic (As) and phthalate esters (PAEs), which is threatening human health. In this study, the feasibility of simultaneous remediation of soil As(III) and a PAE, dibutyl phthalate (DBP), by a manganese-oxidizing bacterium (MnOB) was evaluated. As immobilization and DBP degradation were simultaneously enhanced by MnOB addition. The effects of initial concentrations of As(III), DBP, and Mn(II), and moisture content on the removal of As(III) and DBP were investigated. The results indicated that there was a competitive interaction between As(III) and DBP removal, and 40 mg/kg of Mn(II) dosage and 20%-30% soil moisture content were recommended for optimal and simultaneous removal of As(III) and DBP. Microbial community analysis revealed that community structure and diversity were not changed significantly by MnOB addition. Taken together, the findings from this study indicated that DBP was degraded primarily by microorganisms, whereas As(III) was removed largely by biogenic Mn oxides and immobilized by adsorption onto Mg/Fe oxides and/or formation of metal arsenate precipitates/co-precipitates. This study offers a novel and high-efficiency strategy to remediate the combined contamination of As and PAEs in soils.

Graphene oxide-film-coated splitting ratio-adjustable Mach-Zehnder interferometer for relative humidity sensing

In this paper, a splitting ratio-adjustable Mach-Zehnder interferometer (MZI) for the measurement of relative humidity (RH) is proposed and experimentally demonstrated. The sensing head contains three sections of single mode fiber (SMF) and two sections of multimode fiber (MMF), in which the two MMFs are spliced among the three SMFs. The MMFs are corroded with hydrofluoric acid and act as mode couplers to split and recombine light owing to the core diameter mismatch with the SMF. A layer of graphene oxide (GO) is coated on the MMFs by dip-coating and natural evaporation. The effective refractive index of the GO will vary when it absorbs the water molecules. As a result, the intensity of the transmission light in the core and cladding of the single mode fiber can be adjusted. Thus, the intensity of the resonant dip will vary when the relative humidity changes. The experimental results show that a humidity sensitivity of 0.263 dB/RH% with a linear correlation coefficient of 99% can be achieved in a relative humidity range of 35% to 85%.

Applying Eye Tracking to Identify Autism Spectrum Disorder in Children

Eye tracking (ET) holds potential for the early detection of autism spectrum disorder (ASD). To overcome the difficulties of working with young children, developing a short and informative paradigm is crucial for ET. We investigated the fixation times of 37 ASD and 37 typically developing (TD) children ages 4-6 watching a 10-second video of a female speaking. ASD children showed significant reductions in fixation time at six areas of interest. Furthermore, discriminant analysis revealed fixation times at the mouth and body could significantly discriminate ASD from TD with a classification accuracy of 85.1%, sensitivity of 86.5%, and specificity of 83.8%. Our study suggests that a short video clip may provide enough information to distinguish ASD from TD children.

Publisher Correction: Deacetylation of serine hydroxymethyl-transferase 2 by SIRT3 promotes colorectal carcinogenesis

The original version of this Article contained an error in the Data Availability Statement. The accession code indicated '53V' and should have read '5X3V'. This has been corrected in both PDF and HTML versions of the Article.

Optimization of methane-dependent oxygenic denitrification in sequencing batch reactors by insights into the microbial interactions

Methane-dependent oxygenic denitrification (O2DN) is a promising technology used for reducing greenhouse gas emissions of nitrous oxide (N₂O) during wastewater treatment. Heterotrophic bacteria are associated with methane-dependent O2DN bacteria, and it has been proposed that metabolic cross-feeding occurs between the two populations above. In this study, a mathematical model was developed to describe the microbial processes and interactions between methane-dependent O2DN bacteria and associated heterotrophic bacteria in a sequencing batch reactor (SBR). A growth factor-dependent decoupling of metabolism and growth of methane-dependent O2DN bacteria was introduced into the model. Effects of influent substrates, operating parameters, and initial biomass on microbial community and reactor performance were then investigated, and the above parameters were optimized using the model. Results surprisingly show that organic matter in the influent greatly stimulated the growth of methane-dependent O2DN bacteria but slightly limited the increase of heterotrophic bacteria. This effect could be explained by the increased excretion of growth factors by heterotrophic bacteria and the intensified competition for nitrite when methane-dependent O2DN bacteria increased. These results will assist in providing a new understanding of microbial interactions in methane-dependent O2DN systems and offer a new and efficient strategy for operating methane-dependent O2DN reactors.

An advanced three-way factor analysis model (SDABB model) for size-resolved PM source apportionment constrained by size distribution of chemical species in source profiles

Source samples including crustal dust, cement dust, coal combustion were sampled and ambient samples of PM_2.5 and PM₁₀ were synchronously collected in Hefei from April to December 2014. The size distributions of the markers in the measured source profiles were incorporated into ME-2 solution to develop a new method, called the SDABB model (an advanced ABB three-way factor analysis model incorporating size distribution information). The performance of this model was investigated using three-way synthetic and ambient dataset. For the synthetic tests, the size distributions of markers estimated by the SDABB model were more consistent with true condition. The AAEs between estimated and observed contributions of the SDABB ranged from 15.2% to 29.0% for PM₁₀ and 19.9%-31.6% for PM_2.5, which is lower than those of PMF2. For the ambient PM, six source categories were identified by SDABB for both sizes, although the profiles were different. The source contributions were sulphate (33.33% and 24.53%), nitrate and SOC (22.33% and 18.16%), coal combustion (19.01% and 18.23%), vehicular exhaust (12.99% and 12.07%), crustal dust (10.69% and 19.40%) and cement dust (1.65% and 5.39%) for PM_2.5 and PM₁₀ respectively. In addition, the estimated ratios of Al, Si, Ti and Fe in CRD were 0.76, 0.84, 1.10 and 0.85; those of Al and Si in CC were 0.42 and 0.66; Ca and Si in CD were 0.95 and 1.10; NO₃^- and NH₄⁺ in nitrate were 1.11 and 1.01; and SO₄^2- and NH₄⁺ in sulphate were 0.96 and 1.16. These modeled ratios were consistent with the measured ratios. The size distribution of contributions also came close to reality. Thus, the advanced SDABB three-way model can better capture the characteristics of sources between sizes by effectively incorporating the size distributions of the markers as physical constraints.