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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The influence of bromide and iodide ions on the sulfamethoxazole (SMX) halogenation during chlorination.

Disinfection by-products (DBPs) were produced during the chlorination process, posing a threat to drinking water safety and human health. In the presence of bromide and iodide ions, brominated and iodinated DBPs will be generated, which might be more toxic than the parent compound. However, there are few studies on brominated and iodinated DBPs of antibiotics. Therefore, in this study, the fates of sulfamethoxazole (SMX) during chlorination in different systems (Blank; SMX + NaClO; SMX+ NaClO+ Br-; SMX+ NaClO+I-; SMX+ NaClO+ Br- + I-) were investigated. In different systems, all the reaction followed a pseudo-first-order kinetics, while the reaction rates of NaClO with SMX were different, the reaction rates were in order of SMX + NaClO + Br- + I- > SMX + NaClO + Br- > SMX + NaClO + I- > SMX + NaClO. When Br- and I- existed simultaneously, the reaction rate was the fastest. Iodide played an important role in oxidation and promoted the chlorination of SMX. SMX mainly underwent S-C cleavage, S-N hydrolysis, desulfonation, and substitution reactions. Nine disinfection by-products, including three reported for the first time, were identified using a non-targeted approach, and degradation pathways were proposed. Furthermore, EPI Suite software was applied to predict the environmental accumulation potential and environmental persistence of the degradation products. The results indicated that SMX and degradation products had little environmental accumulative potential and environmental persistence.

Altered dynamic amplitude of low-frequency fluctuations in patients with postpartum depression.

BACKGROUND: Postpartum depression (PPD) is a common mood disorder with increasing incidence year by year. However, the dynamic changes in local neural activity of patients with PPD remain unclear. In this study, we utilized the dynamic amplitude of low-frequency fluctuation (dALFF) method to investigate the abnormal temporal variability of local neural activity and its potential correlation with clinical severity in PPD. METHODS: Twenty-four patients with PPD and nineteen healthy primiparous mothers controls (HCs) matched for age, education level and body mass index were examined by resting-state functional magnetic resonance imaging (rs-fMRI). A sliding-window method was used to assess the dALFF, and a k-means clustering method was used to identify dALFF states. Two-sample t-test was used to compare the differences of dALFF variability and state metrics between PPD and HCs. Pearson correlation analysis was used to analyze the relationship between dALFF variability, states metrics and clinical severity. RESULTS: (1) Patients with PPD had lower variance of dALFF than HCs in the cognitive control network, cerebellar network and sensorimotor network. (2) Four dALFF states were identified, and patients with PPD spent more time on state 2 than the other three states. The number of transitions between the four dALFF states increased in the patients compared with that in HCs. (3) Multiple dALFF states were found to be correlated with the severity of depression. The variance of dALFF in the right middle frontal gyrus was negatively correlated with the Edinburgh postnatal depression scale score. CONCLUSION: This study provides new insights into the brain dysfunction of PPD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding the neurophysiological mechanisms of PPD.

Responses of soil fungal taxonomic attributes and enzyme activities to copper and cadmium co-contamination in paddy soils.

Excess heavy metals, especially copper (Cu) and cadmium (Cd), are common in paddy soils in the red soil hilly areas of southern China. Microorganisms are regulators of soil organic matter accumulation and pollutant transformation. Clarifying the effects of Cu and Cd accumulation on microbial community composition and function is a prerequisite for bioremediation of paddy soil contamination. However, it remains unclear how Cu and Cd contamination affects soil fungal taxonomic attributes and microbial-mediated biogeochemical processes in paddy soils. Here, soil heavy metals, fungal community composition, and soil enzyme activities were determined in paddy fields downstream of a typical mining area in southern China, and the effects of Cu and Cd co-contamination on fungal community diversity and co-occurrence networks, as well as the associations between them were assessed. The concentrations of Cu and Cd in paddy soils decreased from upstream to downstream of the river, and were positively correlated with the Shannon index of fungal communities. Soil Cu and Cd concentrations exhibited a greater impact on the structure and assembly of fungal communities than soil general properties. Increases in soil Cu and Cd concentrations were correlated with drastic changes in the cumulative relative abundance of ecological clusters in fungal co-occurrence networks. Soil Cu and Cd concentrations were positively correlated with the relative abundances of Eurotiomycetes, Pezizomycetes, Ustilaginomycetes, and Kickxellomycetes, respectively, whereas negatively correlated with hydrolase activities related to carbon, nitrogen, and phosphorus cycles. These results confirmed in the field that long-term Cu and Cd enrichment significantly altered the structure and diversity of fungal communities in the subtropical paddy soils, thereby affecting soil nutrient transformation and organic matter accumulation. This can also provide a basis for the bioremediation of heavy metal pollution in paddy soils.

Pregnancy leads to changes in the brain functional network: a connectome analysis.

Pregnancy leads to long-lasting changes in human brain structure; however, little is known regarding alterations in the topological organization of functional networks. In this study, we investigated the effect of pregnancy on human brain function networks. Resting-state fMRI data was collected from eighteen primiparous mothers and twenty-four nulliparous control women of similar age, education level and body mass index (BMI). The functional brain network and topological properties were calculated by using GRETNA toolbox. The demographic data differences between two groups were computed by the independent two sample t-test. We tested group differences in network metrics' area under curve (AUC) using non-parametric permutation test of 1,000 permutations and corrected for false discovery rate (FDR). Differences in regional networks between groups were evaluated using non-parametric permutation tests by network-based statistical analysis (NBS). Compared with the nulliparous control women, a hub node changed from left inferior temporal gyrus to right precentral gyrus in primiparous mothers, while primiparous mothers showed enhanced network global efficiency (p = 0.247), enhanced local efficiency (p = 0.410), larger clustering coefficient (p = 0.410), but shorter characteristic path length (p = 0.247), smaller normalized clustering coefficient (p = 0.111), and shorter normalized characteristic path length (p = 0.705). Although both groups of functional networks have small-world property (σ > 1), the σ values of primiparous mothers were decreased significantly. NBS evaluation showed the majority of altered connected sub-network in the primiparous mothers occurred in the bilateral frontal lobe gyrus (p < 0.05). Altered functional network metrics and an abnormal sub-network were found in primiparous mothers, suggested that pregnancy may lead to changes in the brain functional network.