Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases.

Gray matter (GM) atrophies were observed in multiple sclerosis, neuromyelitis optica spectrum disorders (both anti-aquaporin-4 antibody-positive [AQP4+], and -negative [AQP4-] subtypes NMOSD), and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicenter cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD, and 2,169 healthy controls (HCs). First, interregional GM atrophy profiles across the cortical and subcortical regions were determined by Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD, MOGAD and HCs. Then, the GM atrophy profiles were spatially correlated with the gene expressions extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical feature relevant GM atrophy by subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden, and cognitive function. Multiple sclerosis showed severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed obvious widespread GM atrophy pattern, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes, and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD had spatial correlations with GM atrophy profiles were observed, while no atrophy profile related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature relevant GM atrophy mainly pointed to the shared neuronal and endothelial cells among the four neuroinflammatory diseases. The unique underlying virtual histology patterns were microglia, astrocytes, and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings might help their differential diagnosis and optimal therapeutic strategies.

Joint Exposure to Ambient Air Pollutants, Genetic Risk, and Ischemic Stroke: A Prospective Analysis in UK Biobank.

BACKGROUND: Our primary objective was to assess the association between joint exposure to various air pollutants and the risk of ischemic stroke (IS) and the modification of the genetic susceptibility. METHODS: This observational cohort study included 307 304 British participants from the United Kingdom Biobank, who were stroke-free and possessed comprehensive baseline data on genetics, air pollutant exposure, alcohol consumption, and dietary habits. All participants were initially enrolled between 2006 and 2010 and were followed up until 2022. An air pollution score was calculated to assess joint exposure to 5 ambient air pollutants, namely particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, as well as nitrogen oxide and nitrogen dioxide. To evaluate individual genetic risk, a polygenic risk score for IS was calculated for each participant. We adjusted for demographic, social, economic, and health covariates. Cox regression models were utilized to estimate the associations between air pollution exposure, polygenic risk score, and the incidence of IS. RESULTS: Over a median follow-up duration of 13.67 years, a total of 2476 initial IS events were detected. The hazard ratios (95% CI) of IS for per 10 µg/m3 increase in particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, nitrogen dioxide, and nitrogen oxide were 1.73 (1.33-2.14), 1.24 (0.88-1.70), 1.13 (0.89-1.33), 1.03 (0.98-1.08), and 1.04 (1.02-1.07), respectively. Furthermore, individuals in the highest quintile of the air pollution score exhibited a 29% to 66% higher risk of IS compared with those in the lowest quintile. Notably, participants with both high polygenic risk score and air pollution score had a 131% (95% CI, 85%-189%) greater risk of IS than participants with low polygenic risk score and air pollution score. CONCLUSIONS: Our findings suggested that prolonged joint exposure to air pollutants may contribute to an increased risk of IS, particularly among individuals with elevated genetic susceptibility to IS.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles.

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network.

BACKGROUND: Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression. PURPOSE: To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs). STUDY TYPE: Prospective. POPULATION: A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium. FIELD STRENGTH/SEQUENCE: A 3.0 T/resting-state functional MRI using the gradient echo sequence. ASSESSMENT: A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores. STATISTICAL TESTS: Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant. RESULTS: The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r = 0.640) and anxiety (r = 0.616) in MDD. DATA CONCLUSION: Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

COPD Assessment Test as a Screening Tool for Anxiety and Depression in Stable COPD Patients: A Feasibility Study.

Anxiety and depression are common comorbidities in chronic obstructive pulmonary disease (COPD) patients but are often under-diagnosed. We aimed to assess the suitability of the COPD Assessment Test (CAT) in screening anxiety and depression in patients with COPD. Stable COPD patients from a cross-sectional observational study were assessed by CAT. Anxiety and depression were identified using the Generalized Anxiety Disorder questionnaire (GAD-7) and Patient Health Questionnaire (PHQ-9), respectively. Logistic regression analysis and receiver operating characteristic curve analysis were used to identify factors associated with anxiety or depression and to calculate the predictive values. A total of 530 stable COPD patients were enrolled and of those, the proportions of anxiety and depression were 17.0% and 21.5%, respectively. The adjusted odds ratios of the CAT for the presence of anxiety and depression were 1.094 (95%CI: 1.057-1.131) and 1.143 (95%CI: 1.104-1.183), respectively. The CAT score had a significant predictive value for the presence of anxiety (AUC = 0.709) and depression (AUC = 0.791) with an optimum cutoff score of 15. However, the psychometric properties of CAT were undesirable, presenting high negative predictive value (NPV) but low positive predictive value (PPV). Among CAT items, analysis further showed that non-respiratory CAT components were superior to respiratory components in identifying both anxiety and depression. Our results indicated that CAT is more useful to exclude anxiety and depression rather than detect them.

Pollution of polycyclic aromatic hydrocarbons (PAHs) in drinking water of China: Composition, distribution and influencing factors.

Polycyclic aromatic hydrocarbons (PAHs) are a kind of persistent toxic substances, which have been frequently detected in environmental media. However, studies on their occurrences and distributions in drinking water are insufficient and their composition profiles in drinking water are still not clear. In this study, we investigated 16 priority polycyclic aromatic hydrocarbons (PAHs) in drinking water from different administrative level cities throughout mainland China, analyzed the influences of anthropogenic activities on PAHs, and assessed the health risk of the PAHs in drinking water. On the national scale, the sum concentration of the 16 priority-controlled PAHs (∑16PAHs) designated by the U.S. Environmental Protection Agency (USEPA) was in a range of 3.89-231.39 (mean 56.25) ng L-1. With the decline of ∑16PAHs, the concentration of 3-ring PAHs decreased, while its proportion increased, indicating 3-ring PAHs might be more difficult to remove than other PAHs in drinking water. The geographical distribution of PAHs in drinking water of China was in a descending order of West (69.81 ng L-1) > South (61.95 ng L-1) > North (58.63 ng L-1) > East (39.21 ng L-1) > Northeast China (37.93 ng L-1). ∑16PAHs in drinking water of Prefecture-level City was the greatest (71.49 ng L-1) followed by Provincial Capital (52.12 ng L-1), County-level City (50.98 ng L-1) and Municipality (33.92 ng L-1). ∑16PAHs was significantly negatively correlated with the per capita GDP of sampling city (P < 0.01, n = 78), implying that waterworks is an effective way to control and reduce PAH pollution in drinking water. The carcinogenic risk of the 16 PAHs in drinking water of China was much greater than the non-carcinogenic risk.

Phosphate-Based Ultrahigh Molecular Weight Polyethylene Fibers for Efficient Removal of Uranium from Carbonate Solution Containing Fluoride Ions.

This work provides a cost-effective approach for preparing functional polymeric fibers used for removing uranium (U(VI)) from carbonate solution containing NaF. Phosphate-based ultrahigh molecular weight polyethylene (UHMWPE-g-PO4) fibers were developed by grafting of glycidyl methacrylate, and ring-opening reaction using phosphoric acid. Uranium (U(VI)) adsorption capacity of UHMWPE-g-PO4 fibers was dependent on the density of phosphate groups (DPO, mmol∙g−1). UHMWPE-g-PO4 fibers with a DPO of 2.01 mmol∙g−1 removed 99.5% of U(VI) from a Na2CO3 solution without the presence of NaF. In addition, when NaF concentration was 3 g∙L−1, 150 times larger than that of U(VI), the U(VI) removal ratio was still able to reach 92%. The adsorption process was proved to follow pseudo-second-order kinetics and Langmuir isotherm model. The experimental maximum U(VI) adsorption capacity (Qmax) of UHMWPE-g-PO4 fibers reached 110.7 mg∙g−1, which is close to the calculated Qmax (117.1 mg∙g−1) by Langmuir equation. Compared to F−, Cl−, NO3−, and SO4²− did not influence U(VI) removal ratio, but, H2PO4− and CO3²− significantly reduced U(VI) removal ratio in the order of F− > H2PO4− > CO3²−. Cyclic U(VI) sorption-desorption tests suggested that UHMWPE-g-PO4 fibers were reusable. These results support that UHMWPE-g-PO4 fibers can efficiently remove U(VI) from carbonate solutions containing NaF.

The investigation of the enrichment behavior of identified PFAS and unknown PFAA-precursors in water and suspended particulate matter of the surface microlayer: A case study in Tianjin (China).

The surface microlayer (SML) is an important air water interface layer, known as the skin of the ocean, which has chemical enrichment properties. Chemical enrichment in the SML can affect the occurrence of pollutants in the underlying water and air samples. Although the enrichment of per- and polyfluorinated substances (PFAS), a class of persistent organic pollutants of high concern, has been reported in the SML, information on the behavior of unknown PFAA-precursors in SML is lacked, and it is not clear whether there is a similar PFAS enrichment in suspended particulate matter (SPM) in the SML. Therefore, to investigate these questions, we conducted a systematic survey of 24 PFAS in 11 paired water and SPM samples from the SML and underlying water (U50cm and U2m) from the Duliujian River, which flows to the Bohai sea in Tianjin, China. The ∑PFAS mean concentrations in the water and SPM samples were 38.2 ng/L and 64.6 ng/g dw, respectively. The PFAS concentrations of PFAS in the SML were higher than those in the underlying water, and the enrichment factors (EFs) were greater in the SPM than that in the water. The long-chain PFAS EFs were greater than those for short-chain PFAS, indicating that the EFs were positively correlated with the hydrophobicity. Moreover, by applying the total oxidizable precursor (TOP) assay, the unknown PFAA-precursors (C5-C12) in the water and SPM contributed 11.4∼86.4 mol% and 7.1∼88.0 mol% to total PFAS, respectively. The ecological risk of the targeted PFAS in the SML was relatively higher than that in the underlying water, indicating that PFAS in the SML require more attention. Preliminary estimates indicate that the PFAS-enriched SML is an important exposure route that poses a potential risk to wildlife in rivers and oceans.

Exploring the dynamics of antibiotic resistome on plastic debris traveling from the river to the sea along a representative estuary based on field sequential transfer incubations.

The environmental risks arising from ubiquitous microplastics or plastic debris (PD) acting as carriers of antibiotic resistance genes (ARGs) have attracted widespread attention. Enormous amounts of plastic waste are transported by rivers and traverse estuaries into the sea every year. However, changes in the antibiotic resistome within the plastisphere (the biofilms formed on PD) as PD travels through estuaries are largely unknown. In this study, we performed sequential migration incubations for PD along Haihe Estuary to simulate the natural process of PD floating from rivers to the ocean. Metagenomic sequencing and analysis techniques were used to track microbial communities and antibiotic resistome on migrating PD and in seawater representing the marine environment. The total relative gene copies of ARGs on traveling PD remained stable. As migration between greatly varied waters, additional ARG subtypes were recruited to the plastisphere. Above 80 % ARG subtypes identified in the plastisphere were persistent throughout the migration, and over 30 % of these persistent ARGs were undetected in seawater. The bacterial hosts composition of ARGs on PD progressively altered as transported downstream. Human pathogenic bacteria carrying ARGs (HPBs-ARG) exhibited decreasing trends in abundance and species number during transfer. Individual HPBs-ARG persisted on transferred PD and were absent in seawater samples, comprising Enterobacter cloacae, Klebsiella pneumoniae, Mycobacterium tuberculosis, and Vibrio parahaemolyticus. Based on all detected ARGs and HPBs-ARG, the Projection Pursuit model was applied to synthetically evaluate the potential risks of antibiotic resistance on migrating PD. Diminished risks on PD were observed upon the river-to-sea journey but consistently remained significantly higher than in seawater. The potential risks posed to marine environments by drifting PD as dispersal vectors for antibiotic resistance deserve greater attention. Our results provide initial insights into the dynamics or stability of antibiotic resistome on PD crossing distinct aquatic systems in field estuaries.

Association between household size and risk of incident dementia in the UK Biobank study.

Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02-1.09), vascular dementia (HR, 1.08; 95% CI 1.01-1.15), and non-Alzheimer's disease non-vascular dementia (HR, 1.09; 95% CI 1.03-1.14). No significant association was observed for Alzheimer's disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia.

Spinal cord and brain atrophy patterns in neuromyelitis optica spectrum disorder and multiple sclerosis.

BACKGROUND: Spinal cord and brain atrophy are common in neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (RRMS) but harbor distinct patterns accounting for disability and cognitive impairment. METHODS: This study included 209 NMOSD and 304 RRMS patients and 436 healthy controls. Non-negative matrix factorization was used to parse differences in spinal cord and brain atrophy at subject level into distinct patterns based on structural MRI. The weights of patterns were obtained using a linear regression model and associated with Expanded Disability Status Scale (EDSS) and cognitive scores. Additionally, patients were divided into cognitive impairment (CI) and cognitive preservation (CP) groups. RESULTS: Three patterns were observed in NMOSD: (1) Spinal Cord-Deep Grey Matter (SC-DGM) pattern was associated with high EDSS scores and decline of visuospatial memory function; (2) Frontal-Temporal pattern was associated with decline of language learning function; and (3) Cerebellum-Brainstem pattern had no observed association. Patients with CI had higher weights of SC-DGM pattern than CP group. Three patterns were observed in RRMS: (1) DGM pattern was associated with high EDSS scores, decreased information processing speed, and decreased language learning and visuospatial memory functions; (2) Frontal-Temporal pattern was associated with overall cognitive decline; and (3) Occipital pattern had no observed association. Patients with CI trended to have higher weights of DGM and Frontal-Temporal patterns than CP group. CONCLUSION: This study estimated the heterogeneity of spinal cord and brain atrophy patterns in NMOSD and RRMS patients at individual level, and evaluated the clinical relevance of these patterns, which may contribute to stratifying participants for targeted therapy.

The convergence of 2,6-dichloro-1,4-benzoquinone in the whole process of lignin phenol precursor chlorination.

The formation and decomposition of 2,6-dichloro-1,4-benzoquinone, an emerging disinfection byproduct (DBP), was studied in the chlorination of lignin phenol precursors. The results show that DCBQ and the related hydroxyl DCBQ (DCBQ-OH) acts as the intermediate products of the chlorination process of the three typical lignin phenol precursors (p-hydroxybenzoic acid, protocatechuic acid, and gallic acid). The contributions of lignin phenol precursors to the overall formation of the targeted DBPs were determined based on the observed abundances of individual lignin phenols and their DBP yields. DCBQ and DCBQ-OH were generated within 2-6 h, the relative abundance of the yields of mol carbon atoms in DCBQ corresponding to the mol carbon atoms in the three model precursors (DCBQ-C) was about 0.01%-14.37% under different pH conditions. With the chlorination reaction time increased (after two or four h), the concentrations of DCBQ and DCBQ-OH entirely decreased, and the decomposition of DCBQ do not follow a pseudo-first-order kinetics during chlorination. Conversely, the decomposition of DCBQ generated from p-hydroxybenzoic acid followed a pseudo-second-order kinetics. Moreover, the formation of trichloromethane (TCM), dichloroacetic acid (DCAA), and trichloroacetic acid (TCAA) was also detected during the chlorination. The contribution of the decomposed DCBQ was mainly to TCAA and the unknown DBPs within 2-12 h, and DCBQ decomposition pathway was affected by pH. Moreover, except for DCBQ/DCBQ-OH and TCM/HAAs, there were still 73.6%-92.41% unknown products (including non-halogenated aromatic DBPs and chlorine-substituted DBPs) needing to identify during the chlorination process for lignin phenols. Overall, revealing the formation and decomposition of DCBQ during the chlorination of lignin phenol precursors would contribute to the effective development of drinking water treatment processes for the removal of highly toxic intermediates generated during disinfection.

Metagenomic insights into the potential risks of representative bio/non-degradable plastic and non-plastic debris in the upper and lower reaches of Haihe Estuary, China.

As vectors for microorganisms and genetic elements, vast amounts of solid wastes, including plastics and non-plastics, enter oceans through estuaries globally. The heterogeneity of microbiomes developed on different types of plastic and non-plastic matrices and their potential environmental risks in field estuarine regions have not been fully explored. Here, microbial communities, antibiotic resistance genes (ARGs), virulence factors (VFs), and mobile genetic elements (MGEs) on substrate debris (SD) covering non-biodegradable plastics, biodegradable plastics, and non-plastics were first comprehensively characterized based on metagenomic analyzes (substrate identity). These selected substrates were field-exposed at both ends of the Haihe Estuary, China (geographic location). For substrate identity: conspicuously diverse functional gene profiles on different substrates were obtained; the relative gene copies of ARGs, VFs, and MGEs on non-biodegradable plastics were highest at both locations; non-biodegradable plastic matrices recruited the most abundant unique ARGs from ambient waters; the relative abundance of potential bacterial hosts carrying multiple ARGs and VFs (BH-AV) was much higher on non-biodegradable plastic surfaces than on the other two substrates, especially in the coastal water environment. For geographic locations: more abundant specific ARGs, VFs, and MGEs were significantly enriched on SD from the upper estuary; the average relative abundance of identified BH-AV on SD from the upper estuary was 1.99-7.14 folds from the lower estuary. Finally, the results of the Projection Pursuit Regression model verified the higher comprehensive potential risks arising from non-biodegradable plastics (substrate identity) and SD from the upstream of the estuary (geographic location). Based on comparative analysis, our results alert us to pay particular attention to ecological risks triggered by conventional non-biodegradable plastics in rivers and coastal environments and highlight the microbiological risk from terrestrial solid waste to the downstream marine environment.

Pollution characteristics, distribution, and source analysis of carbazole and polyhalogenated carbazoles in coastal areas of Bohai Bay, China.

Polyhalogenated carbazoles (PHCZs) are a class of emerging environmental contaminants formed by the substitution of hydrogen on carbazole (CZ) benzene rings with halogens (Cl, Br, I) with potential dioxin-like toxicity, and they have been frequently detected in various environmental media and organisms recently. Nevertheless, co-research of CZ/PHCZs with PAHs is very limited. In addition, I-PHCZs, which are believed to be much more toxic than CZ, Cl-PHCZs and Br-PHCZs, have a few data in sediments previously. The concentration and distribution of CZ/PHCZs and PAHs were analyzed in 18 surface sediments of Bohai Bay, China. There is a significant correlation (R = 0.64, P＜0.05) between PHCZs and PAHs, and principal component analysis (PCA) also indicating that they may have a certain similarity in origin. Additionally, total CZ and PHCZs was up to 230.57 ng/g dw in the studied samples, which was approximately 1-2 orders of magnitude lower than PAHs and other common persistent organic pollutants (POPs). The compositions of the CZ/PHCZs in our study were dominated by CZ (2.74-18.28, median 2.92 ng/g dw), 3,6-dichlorocarbazole (n.d-6.78, median 0.97 ng/g dw) and 3,6-iodocarbazole (n.d-12.68, median 1.65 ng/g dw). Results of this study discovered the varying origins of CZ and PHCZs and/or a complexity of anthropogenic influences and natural sources processes, and revealed a wide distribution of CZ/PHCZs across the studied. Moreover, more attention should be paid by comparing CZ/PHCZs with other widely distributed POPs.

Application and evaluation of nine-grid thinking model in biochemistry teaching.

Biochemistry is an important professional course to undergraduates majoring in rehabilitation therapy in medical colleges and universities. To deepen students' understanding of the taught content, enhance their application ability and cultivate their high-level thinking ability, we investigated the effect of integration of the nine-grid thinking model into the teaching process. With the inline and divergence of relevant knowledge as the guiding ideology, students' understanding of knowledge points was deepened through thinking visualization. According to the questionnaire survey, 75% of the students believed that the application of the nine-grid thinking model was an effective teaching method for improving the efficiency of teaching and enhancing the teaching effect. In addition, a team of four students from the investigated class were granted by the 2021 Shanxi University Student Innovation and Entrepreneurship Training Program and awarded RMB 6000 as a research fund (20210563). According to them, the application of the nine-grid thinking model in teaching is of great significance for cultivating students' higher-order thinking ability. The findings of this study might provide a new, effective approach to college course teaching.

Partitioning behavior and mechanism of polyhalogenated carbazoles in water and suspended particulate matter.

Polyhalogenated carbazoles (PHCZs), known as new dioxin-like compounds, are a new class of emerging environmental contaminants that have received increasing attention in recent years due to their wide distribution and dioxin-like toxicity. This study investigated the partition characteristics and adsorption mechanisms of eight PHCZs in the aqueous phase and suspended particulate matter (SPM). The competitive impact of humic acid (HA) on the adsorption of PHCZs was revealed when the effects of various environmental conditions (HA, temperature, perturbation disturbance, and pH) behavior were explored. The key finding of this study is that SPM, which is its effective vector, could adsorb 70.7 % of ΣPHCZs. The equilibrium adsorption amount is ranked as 3,6-ICZ > 3,6-BCZ > 2,7-BCZ > 3,6-CCZ > 1,3,6,8-BCZ > 3-BCZ > 2-BCZ > CZ. The halogen species, the degree of halogenation, and the substitution position of the PHCZs influence the amount of adsorption, where the log Kow values, the steric effect (Es), and the density contribute the most to the amount of adsorption, and the specific adsorption mechanisms are van der Waals force, π-π, hydrogen bonding, and nonspecific hydrophobic interactions. The adsorption reaction of PHCZs by SPM is endothermic, and the amount of adsorption increases with increasing temperature, oscillation velocity, and decrease in pH. HA may reduce the adsorption sites of hydroxyl, carbonyl, amide groups, and π-π bonds on SPM for PHCZs, while the SPM@HA conjugates can provide new sites for the adsorption of PHCZs. According to the experimental findings of this study, SPM plays a significant role in contaminant transport. As a result, when conducting environmental investigations of PHCZs and even other hydrophobic contaminants, we must fully consider the level of contaminants present in SPM to reveal the ecological risks accurately.

Composition, distribution, health risks, and drivers of phthalates in typical red paddy soils.

The accelerated accumulation of phthalate esters (PAEs) in paddy soils poses a serious threat to human health. However, related studies mainly focus on facility vegetable fields, drylands, and orchards, and little is known about paddy soils. In this study, 125 samples were collected from typical red paddy fields to investigate the pollution characteristics, sources, health risks, and main drivers of PAEs. Soil physicochemical properties, enzyme activity, and bacterial community composition were also measured simultaneously. The results showed that eight PAE congeners were detected ranging from 0.17 to 1.97 mg kg-1. Di-n-butyl phthalate (DBP), di-(2-ethylhexyl) phthalate (DEHP), and di-isobutyl phthalate (DIBP) were the most abundant PAE congeners, accounting for 81% of the total PAEs. DEHP exhibited a potential carcinogenic risk to humans through the intake route. The main PAEs were positively correlated with soil organic matter (SOM) and soil water content (SWC) contents. Low levels of PAEs increased bacterial abundance. Furthermore, most PAE congeners were positively correlated with hydrolase activity. Soil acidity and nutrient dynamics played a dominant role in the bacterial community composition, with PAE congeners playing a secondary role. These findings suggest that there may be a threshold response between PAEs and organic matter and nutrient transformation in red paddy soils, and that microbial community should be the key driver. Overall, this study deepens the understanding of ecological risks and microbial mechanisms of PAEs in red paddy soils.

Copper and cadmium co-contamination affects soil bacterial taxonomic and functional attributes in paddy soils.

Microorganisms inhabiting heavy metal-contaminated soils have evolved specific metabolic capabilities to survive, which has the potential for effective bioremediation. However, the ecological consequence of copper (Cu) and cadmium (Cd) on bacterial taxonomic and functional attributes of rice field remains unclear. Here, we selected paddy soils along a polluted river in southern China to evaluate the role of Cu and Cd contaminant fractions in regulating bacterial co-occurrence patterns. We also assessed the effects of these heavy metal fractions on the relative abundance of functional genes using shotgun metagenomic analysis. Soil Cu and Cd concentrations in paddy soils gradually decreased from upstream to downstream of the river, and had a greater impact on bacterial communities and metabolic potentials than soil general properties. Soil Cu and Cd contamination led to drastic changes in the cumulative relative abundance of ecological modules in bacterial co-occurrence networks. Bacteria associated with AD3, HSB_OF53-F07 (both belonging to Chloroflexi), Rokubacteriales, and Nitrospira were identified as tolerant to Cu and Cd contamination. The Cu and Cd contaminant fractions were positively correlated with the genes involved in metal resistance, carbon (C) fixation, nitrification, and denitrification, but negatively correlated with the genes related to nitrogen (N) fixation. These results indicated that soil Cu and Cd pollution not only enriched metal resistant genes, but also affected genes related to microbial C and N cycling. This is critical for facilitating microbiome bioremediation of metal-contaminated paddy soils.

Classification of major depression disorder via using minimum spanning tree of individual high-order morphological brain network.

BACKGROUND: Major depressive disorder (MDD) is an overbroad and heterogeneous diagnosis with no reliable or quantifiable markers. We aim to combine machine-learning techniques with the individual minimum spanning tree of the morphological brain network (MST-MBN) to determine whether the network properties can provide neuroimaging biomarkers to identify patients with MDD. METHOD: Eight morphometric features of each region of interest (ROI) were extracted from 3D T1 structural images of 106 patients with MDD and 97 healthy controls. Six feature distances of the eight morphometric features were calculated to generate a feature distance matrix, which was defined as low-order MBN. Further linear correlations of feature distances between ROIs were calculated on the basis of low-order MBN to generate individual high-order MBN. The Kruskal's algorithm was used to generate the MST to obtain the core framework of individual low-order and high-order MBN. The regional and global properties of the individual MSTs were defined as the feature. The support vector machine and back-propagation neural network was used to diagnose MDD and assess its severity, respectively. RESULT: The low-order and high-order MST-MBN constructed by cityblock distance had the excellent classification performance. The high-order MST-MBN significantly improved almost 20 % diagnostic accuracy compared with the low-order MST-MBN, and had a maximum R2 value of 0.939 between the predictive and true Hamilton Depression Scale score. The different group-level connectivity strength mainly involves the central executive network and default mode network (no statistical significance after FDR correction). CONCLUSION: We proposed an innovative individual high-order MST-MBN to capture the cortical high-order morphological correlation and make an excellent performance for individualized diagnosis and assessment of MDD.

Occurrence of legacy and emerging poly- and perfluoroalkyl substances in water: A case study in Tianjin (China).

Due to the water solubility and environmentally persistent properties of poly- and perfluoroalkyl substances (PFAS), the contamination of PFAS in drinking water is raising widespread concerns for their potential adverse health risks. In the present study, the behavior of PFAS from source waters to effluent water was analyzed by taking samples from three drinking water sources (Yuqiao Reservoir, Beidagang Reservoir, and Yangtze River) and effluent of several treatment processes used in one drinking water treatment plant (DWTP) of Tianjin (China), including pre-chlorination, coagulation, sand filtration, and chlorination. The range of total concentration of PFAS (∑21PFAS) in three source water was 6.64-19.80 ng/L (Yuqiao Reservoir), 80.00-119.86 ng/L (Beidagang Reservoir), and 15.87 ng/L (Yangtze River), respectively. As for individual PFAS, PFBA (perfluorobutanoic acid) was the most abundant PFAS, followed by PFOA (perfluorooctanoic acid), PFBS (perfluorobutane sulfonate), and PFOS (perfluorooctane sulfonate), especially, 6:2 Cl-PFESA (6:2 Cl-polyflurinated ether sulfonate) was detected in all samples. During treatment, the removal rate of ∑21PFAS was 11%, and the removal rate of long-chain PFAS such as PFNA (perfluorononanoic acid), PFOS, and PFDS (perfluorodecane sulfonate) were relatively higher than short-chain PFAS due to their hydrophobic characteristic. Besides, the influence of seasonal factor (precipitation) on the occurrence and composition characteristics of PFAS in the aquatic environment was also investigated, and the results demonstrated that precipitation affected the total concentrations of PFAS in the aquatic environment, but barely on the composition characteristics of PFAS. Furthermore, the ecological risks could be negligible based on the concentration of PFAS measured in surface water. In the meanwhile, the health risks were also assessed based on the concentration of PFAS detected in drinking water, the result indicated that the concentrations of PFAS were less than the suggested drinking water advisories. In addition, more attention should be paid to the risk caused by the frequently detected emerging PFAS such as 6:2 Cl-PFESA and HFPO-DA (hexafluoropropylene oxide-dimer acid).