Transformation of dissolved organic matter in a constructed wetland: A molecular-level composition analysis using pyrolysis-gas chromatography mass spectrometry

This study investigated the transformation of dissolved organic matter (DOM) in a free-water surface flow constructed wetland. Pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) coupled with preparative high-performance liquid chromatography (prep-HPLC) was used to analyze the compositions of biopolymers (polysaccharides, amino sugars, proteins, polyhydroxy aromatics, lipids and lignin) in DOM according to the molecular size at three sampling points of the water flow: inflow, midflow, and outflow. The prep-HPLC results verified the decomposition of DOM through the decrease in the number of peaks from three to one in the chromatograms of the sampling points. The Py-GC/MS results for the degradable peaks indicated that biopolymers relating to polysaccharides and proteins gradually biodegraded with the water flow. On the other hand, the recalcitrant organic fraction (the remaining peak) in the outflow showed a relatively high concentration of aromatic compounds. Therefore, the ecological processes in the constructed wetland caused DOM to become more aromatic and homogeneous. This indicated that the constructed wetland can be an effective buffer area for releasing biochemically stable DOM, which has less influence on biological water quality indicators, e.g., biochemical oxygen demand, into an aquatic ecosyste

Organic Matter Composition of Manure and Its Potential Impact on Plant Growth

Since the advent of flush toilet systems, the aquatic environment has received a massive contaminant flow. Furthermore, the perception of human feces has changed from a useful nutrient source for agriculture to a harmful contaminant. In this study, we compared the nutritional quality of five samples: (1) human manure (HM), (2) human manure from a family mainly eating organic food (HMO), (3) cow manure (CM), (4) poultry manure (PM), and (5) commercial nursery media (CNM). Samples were analyzed in terms of organic and inorganic nutrient contents, molecular composition, seed germination, and chlorophyll concentration. Pyrolysis gas chromatography/mass spectrometry (GC/MS) was used to describe the differences in molecular composition. Three-dimensional excitation and emission matrix fluorescence spectroscopy characterized the organic composition of water extracts. From the results, CNM, PM, and HMO showed humic- and fluvic-like substance peaks, the highest values of potassium and sulfate ions, and of C/N ratios, indicating greater plant growth potential. This was confirmed by their higher chlorophyll concentrations and germination index values. These results contribute knowledge about the positive effects of manure, changing the negative perception of human excreta from waste to resource. This work provides a reference for reducing the wastewater loading rate in society

The different contributions of the eight prefrontal cortex subregions to reactive responses after unpredictable slip perturbations and vibrotactile cueing

IntroductionRecent advancements in functional near-infrared spectroscopy technology have offered a portable, wireless, wearable solution to measure the activity of the prefrontal cortex (PFC) in the human neuroscience field. This study is the first to validate the different contributions made by the PFC's eight subregions in healthy young adults to the reactive recovery responses following treadmill-induced unpredictable slip perturbations and vibrotactile cueing (i.e., precues).MethodsOur fall-inducing technology platform equipped with a split-belt treadmill provided unpredictable slip perturbations to healthy young adults while walking at their self-selected walking speed. A portable, wireless, wearable, and multi-channel (48 channels) functional near-infrared spectroscopy system evaluated the activity of PFC's eight subregions [i.e., right and left dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), frontopolar prefrontal cortex (FPFC), and orbitofrontal cortex (OFC)] as quantified by oxyhemoglobin and deoxyhemoglobin concentrations. A motion capture system and two force plates beneath the split-belt treadmill were used to quantify participants' kinematic and kinetic behavior. All participants completed 6 trials: 2 consecutive trials without vibrotactile cueing and with a slip perturbation (control trials); 3 trials with vibrotactile cueing [2 trials with the slip perturbation (cueing trial) and 1 trial without the slip perturbation (catch trial)], and 1 trial without vibrotactile cueing and with a slip perturbation (post-control trial). The PFC subregions' activity and kinematic behavior were assessed during the three periods (i.e., standing, walking, and recovery periods).ResultsCompared to the walkers' standing and walking periods, recovery periods showed significantly higher and lower levels of oxyhemoglobin and deoxyhemoglobin concentrations, respectively, in the right and left DLPFC, VLPFC, and FPFC, regardless of the presence of vibrotactile cueing. However, there was no significant difference in the right and left OFC between the three periods. Kinematic analyses confirmed that vibrotactile cueing significantly improved reactive recovery responses without requiring more involvement by the PFC subregions, which suggests that the sum of attentional resources is similar in cued and non-cued motor responses.DiscussionThe results could inform the design of wearable technologies that alert their users to the risks of falling and assist with the development of new gait perturbation paradigms that prompt reactive responses

Efficacy of smartphone application-based multi-domain cognitive training in older adults without dementia

BackgroundAs the population ages and the prevalence of dementia increases, there is a growing emphasis on the importance of cognitive training to prevent dementia. A smartphone application-based cognitive training software program, BeauBrain Trainer (BBT), has been developed to provide better access to cognitive training for older adults. Numerous studies have revealed the effectiveness of cognitive training using a cognitive assessment tool. However, relatively few studies have evaluated brain activation using brain imaging as a result of improved cognitive function.MethodsAll participants were required to download the BBT, an Android-based application for cognitive training, onto their own smartphone or tablet computer and to engage in cognitive training at home. Older adults without dementia were enrolled in this study, including 51 participants in the intervention group and 50 participants in the control group. The BBT comprised a set of 12 cognitive tasks, including two tasks in each of the following six cognitive domains: attention, language, calculation, visuospatial function, memory, and frontal/executive function. Each cognitive task was divided into four blocks based on its level of difficulty. A 16-week cognitive training was designed to carry out cognitive tasks using a total of 48 blocks (12 tasks × 4 levels) for at least 1.5 h per day, 5 days per week. All participants in the intervention group were given BBT tasks that gradually increased in difficulty level, which they submitted through a smartphone application daily for 16 weeks. The researchers monitored the participants’ task performance records on the website and encouraged participants to engage in cognitive training through regular contact. This study was conducted to investigate the improvement in cognitive function and the activation pattern of the frontal cortex in older adults participating in smartphone application-based cognitive training. The cognitive assessment tool was the BeauBrain cognitive screening test (CST), a tablet-based computerized cognitive screening test. The activation pattern of the frontal cortex was measured using functional near-infrared spectroscopy (fNIRS). Additionally, this study aimed to determine the positive effects of cognitive training on everyday functioning and psychological states using a questionnaire.ResultsOf 101 participants, 85 older adults without dementia (84.1%) who completed the study protocol were included in the statistical analysis. There were 41 participants (80.3%) in the intervention group and 44 participants (88.0%) in the control group. A two-way repeated-measures analysis of variance (ANOVA) was used to compare the cognitive scores over a 16-week period between the intervention and control groups. According to the CST results, the intervention group exhibited a statistically significant increase in the language subtest scores, specifically the phonemic word fluency test, compared to those of the control group. The fNIRS results revealed greater activation in the dorsolateral prefrontal cortex during the STROOP incongruent task in the intervention group than did the control group. However, the effectiveness of cognitive training was not observed across a variety of rating scales, including everyday functioning, depression, self-efficacy, attention, and subjective memory complaints.ConclusionThis study revealed that a smartphone-based cognitive training application led to improvements in phonemic generative naming ability and activation of the prefrontal cortex in older adults without dementia. This study is meaningful because it confirmed that cognitive training is partially effective in enhancing frontal lobe function. It also provided information on the brain mechanisms related to the effects of cognitive training using fNIRS

Roles of the prefrontal cortex in learning to time the onset of pre-existing motor programs.

The prefrontal cortex (PFC) is involved in cognitive control of motor activities and timing of future intensions. This study investigated the cognitive control of balance recovery in response to unpredictable gait perturbations and the role of PFC subregions in learning by repetition. Bilateral dorsolateral (DLPFC), ventrolateral (VLPFC), frontopolar (FPFC) and orbitofrontal (OFC) cortex hemodynamic changes induced by unpredictable slips were analyzed as a function of successive trials in ten healthy young adults. Slips were induced by the acceleration of one belt as the participant walked on a split-belt treadmill. A portable functional near-infrared spectroscope monitored PFC activities quantified by oxyhemoglobin (ΔO2Hb) and deoxyhemoglobin (ΔHbR) during the consecutive trial phases: standing, walking, slip-recovery. During the first 3 trials, the average oxyhemoglobin (ΔO2Hbavg) in the DLPFC, VLPFC, FPFC, and OFC cortex was significantly higher during slip-recovery than unperturbed walking or the standing baseline. Then, ΔO2Hbavg decreased progressively from trial-to-trial in the DLPFC, VLPFC, and FPFC, but increased and then remained constant in the OFC. The average deoxyhemoglobin (ΔHbRavg) presented mirror patterns. These changes after the third trial were paralleled by the progressive improvement of recovery revealed by kinematic variables. The results corroborate our previous hypothesis that only timing of the onset of a "good enough recovery motor program" is learned with practice. They also strongly support the assumption that the PFC contributes to the recall of pre-existing motor programs whose onset timing is adjusted by the OFC. Hence, learning is clearly divided into two steps delineated by the switch in activity of the OFC. Additionally, motor processes appear to share the working memory as well as decisional and predictive resources of the cognitive system

Anthropogenic Occurrence of Phthalate Esters in Beach Seawater in the Southeast Coast Region, South Korea

In modern times, humans have contributed to the occurrence of phthalate esters (PEs) in various environmental matrices by consuming plastics that generally contain PEs, which are essential synthetic organic chemicals for fabrication of various consumer products. Five beaches in Ulsan and Busan, South Korea, were investigated for the anthropogenic occurrence of four PEs (dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DnBP), and bis(2-ethylhexyl) phthalate (DEHP)) in beach seawater. Using stir-bar sorptive extraction-thermal desorption-gas chromatography/mass spectrometry, DnBP and DEHP were determined as generally dominant. At Ilsan Beach, both the northern and southern ends showed higher DnBP and DEHP concentrations than the middle of the beach, while DMP and DEP showed similar concentrations at all points. The differences in the DnBP and DEHP concentrations may be related to the fishery industry and domestic sewage inflow to the beach. In addition, a comparison among Ilsan, Imnang, and Songjeong beaches suggested the effects of neighboring industrial areas on the DnBP and DEHP ratio. This study provides information on the effects of seasons, weather events, the proximity of rivers, industrial behavior, and domestic sewage to PE concentrations in beach seawater

The Effects of Virtual Reality Treatment on Prefrontal Cortex Activity in Patients With Social Anxiety Disorder: Participatory and Interactive Virtual Reality Treatment Study

Background: Attempts to use virtual reality (VR) as a treatment for various psychiatric disorders have been made recently, and many researchers have identified the effects of VR in psychiatric disorders. Studies have reported that VR therapy is effective in social anxiety disorder (SAD). However, there is no prior study on the neural correlates of VR therapy in patients with SAD. Objective: The aim of this study is to find the neural correlates of VR therapy by evaluating the treatment effectiveness of VR in patients with SAD using portable functional near-infrared spectroscopy (fNIRS). Methods: Patients with SAD (n=28) were provided with 6 sessions of VR treatment that was developed for exposure to social situations with a recording system of each participant's self-introduction in VR. After each VR treatment session, the first-person view (video 1) and third-person view (video 2) clips of the participant's self-introduction were automatically generated. The functional activities of prefrontal regions were measured by fNIRS while watching videos 1 and 2 with a cognitive task, before and after whole VR treatment sessions, and after the first session of VR treatment. We compared the data of fNIRS between patients with SAD and healthy controls (HCs; n=27). Results: We found that reduction in activities of the right frontopolar prefrontal cortex (FPPFC) in HCs was greater than in the SAD group at baseline (t=-2.01, P=.049). Comparing the frontal cortex activation before and after VR treatment sessions in the SAD group showed significant differences in activities of the FPPFC (right: t=-2.93, P<.001; left: t=-2.25, P=.03) and the orbitofrontal cortex (OFC) (right: t=-2.10, P=.045; left: t=-2.21, P=.04) while watching video 2. Conclusions: Activities of the FPPFC and OFC were associated with symptom reduction after VR treatment for SAD. Our study findings might provide a clue to understanding the mechanisms underlying VR treatment for SAD

Replacing the internal standard to estimate micropollutants using deep and machine learning

Similar to the worldwide proliferation of urbanization, micropollutants have been involved in aquatic and ecological environmental systems. These pollutants have the propensity to wreak havoc on human health and the ecological system; hence, it is important to persistently monitor micropollutants in the environment. Micropollutants are commonly quantified via target analysis using high resolution mass spectrometry and the stable isotope labeled (SIL) standard. However, the cost-intensiveness of this standard presents a major obstacle in measuring micropollutants. This study resolved this problem by developing data-driven models, including deep learning (DL) and machine learning (ML), to estimate the concentration of micropollutants without resorting to the SIL standard. Our study hypothesized that natural organic matter (NOM) could replace internal standards if there was a specific mass spectrum (MS) subset, including NOM information, which correlated with an SIL standard peak. Therefore, we analyzed the MS to find the specific MS subsets for replacing the SIL standard peak. Thirty-five alternative MS subsets were determined for applying DL and ML as input data. Thereafter, we trained four different DL models, namely, ResNet101, GoogLeNet, VGG16, and Inception v3, as well as three different ML models, i.e., random forest (RF), support vector machine (SVM), and artificial neural network (ANN). A total of 680 MS data were used for the model training to estimate five different micropollutants, namely Sulpiride, Metformin, and Benzotriazole. Among the DL models, ResNet 101 exhibited the highest model performance, showing that the average validation R 2 and MSE were 0.84 and 0.26 ng/L, respectively, while RF was the best in the ML models, manifesting R 2 and MSE values of 0.69 and 0.58 ng/L. The trained models showed accurate training and validation results for the estimation of the five micropollutant concentrations. Therefore, this study demonstrates that the suggested analysis has a potential for alternative micropollutant measurement that has rapid and economic vantages. (C) 2020 Elsevier Ltd. All rights reserved

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