The majority of tissue-specific environmental quality standards (EQSs) considering metal tolerance are prior to the chemical-specific EQSs in aquatic organisms. However, metal baseline levels in ...marine organisms were very scarce. We explored the correlation between Hg, Cd, Pb, Cu, and Zn concentrations in water or sediments and those metal concentrations in marine organisms (crustacean, mollusc, and fish) by generalized additive models (GAMs) and executed a meta-analysis of Hg, Cd, Pb, Cu, and Zn contents in those three organisms by implementing cumulative frequency distribution analysis of individual metal distribution in a heavy metal-contaminated semi-enclosed Bay, China. Results showed that the average contents of Hg, Cd, Pb, Cu, and Zn were 0.042±0.01, 0.38±0.22, 1.72±0.65, 3.61±1.01, and 16.08±6.33 μg/L in water; 0.064±0.02, 0.42±0.04, 20.54±7.76, 28.97±3.90, and 96.74±35.11 μg/g dw in sediment; and 0.0049±0.0028, 0.52±0.28, 0.24±0.15, 11.05±6.95, and 21.12±4.47 μg/g dw in crustacean, 0.015±0.0087, 0.24±0.17, 0.08±0.02, 0.37±0.35, and 10.62±6.79 μg/g dw in mollusc; and 0.0038±0.0028, 0.065±0.05, 0.32±0.19, 2.01±0.59, and 16.04±4.97 μg/g dw in fish. The mercury content in mollusc presented a negative correlation with mercury content in sediment, while the content of other metals (Cd, Pb, Cu, and Zn) in organisms showed positive correlations with the content of those metals in water or sediment. We further obtained tissue-baseline-C5% in crustacean, mollusc, and fish which were 1.191, 3.341, and 0.014 μg/g dw for Cu; 0.013, 0.072, and 0.033 μg/g dw for Cd, 0.015, 0.027, and 0.052 μg/g dw for Pb; 9.515, 14.422, and 0.056 μg/g dw for Zn; and 0.0009, 0.004, and 0.0035 μg/g dw for Hg, respectively. However, there were no obvious relationships of the 4d-NOEC in laboratory toxicity tests with C5%, as well as C50% and 4d-LC50 or tolerance index
a
for Cu, Cd, Pb, Zn, and Hg in organisms. Our results pointed out the controversy of laboratory sensitive species toxicity results for deriving chemical-specific EQSs with field studies. We advocated to set up the metal concentration baselines in aquatic organisms and further served the tissue-specific EQSs, which are essential basis for geochemical recordings, bio-monitoring, and semi-enclosed bay management in the world.
Graphical abstract
Risk-taking differs between humans, and is associated with the personality measures of impulsivity and sensation-seeking. To analyse the brain systems involved, self-report risk-taking, resting state ...functional connectivity, and related behavioral measures were analyzed in 18,740 participants of both sexes from the UK Biobank. Functional connectivities of the medial orbitofrontal cortex, ventromedial prefrontal cortex (VMPFC), and the parahippocampal areas were significantly higher in the risk-taking group (p < 0.001, FDR corrected). The risk-taking measure was validated in that it was significantly associated with alcohol drinking amount (r = 0.08, p = 5.1×10−28), cannabis use (r = 0.12, p = 6.0×10−66), and anxious feelings (r = -0.12, p = 7.6×−98). The functional connectivity findings were cross-validated in two independent datasets. The higher functional connectivity of the medial orbitofrontal cortex and VMPFC included higher connectivity with the anterior cingulate cortex, which provides a route for these reward-related regions to have a greater influence on action in risk-taking individuals. In conclusion, the medial orbitofrontal cortex, which is involved in reward value and pleasure, was found to be related to risk-taking, which is associated with impulsivity. An implication is that risk-taking is driven by specific orbitofrontal cortex reward systems, and is different for different rewards which are represented differently in the brains of different individuals. This is an advance in understanding the bases and mechanisms of risk-taking in humans, given that the orbitofrontal cortex, VMPFC and anterior cingulate cortex are highly developed in humans, and that risk-taking can be reported in humans.
Sensation-seeking is a multifaceted personality trait with components that include experience-seeking, thrill and adventure seeking, disinhibition, and susceptibility to boredom, and is an aspect of ...impulsiveness. We analysed brain regions involved in sensation-seeking in a large-scale study with 414 participants and showed that the sensation-seeking score could be optimally predicted from the functional connectivity with typically (in different participants) 18 links between brain areas (measured in the resting state with fMRI) with correlation r = 0.34 (p = 7.3 × 10−13) between the predicted and actual sensation-seeking score across all participants. Interestingly, 8 of the 11 links that were common for all participants were between the medial orbitofrontal cortex and the anterior cingulate cortex and yielded a prediction accuracy r = 0.30 (p = 4.8 × 10−10). We propose that this important aspect of personality, sensation-seeking, reflects a strong effect of reward (in which the medial orbitofrontal cortex is implicated) on promoting actions to obtain rewards (in which the anterior cingulate cortex is implicated). Risk-taking was found to have a moderate correlation with sensation-seeking (r = 0.49, p = 3.9 × 10−26), and three of these functional connectivities were significantly correlated (p < 0.05) with the overall risk-taking score. This discovery helps to show how the medial orbitofrontal and anterior cingulate cortices influence behaviour and personality, and indicate that sensation-seeking can involve in part the medial orbitofrontal cortex reward system, which can thereby become associated with risk-taking and a type of impulsiveness.
•Sensation-seeking can be predicted from the functional connectivity between.•The medial orbitofrontal cortex and anterior cingulate cortex.•This was shown with resting state analysis in 414 participants.•Sensation seeking is a type of impulsivity driven by reward systems in the medial.•Orbitofrontal cortex connecting to action systems in the anterior cingulate cortex.
Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of ...first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis.
Exposure routes are important for health risk assessment of chemical risks. The application of physiologically based toxicokinetic (PBTK) models to predict concentrations in vivo can determine the ...effects of harmful substances and tissue accumulation on the premise of saving experimental costs. In this study, Tri(2-chloroethyl) phosphate (TCEP), an organophosphate ester (OPE), was used as an example to study the PBTK model of mice exposed to different exposure doses by multiple routes. Different routes of exposure (gavage and intradermal injection) can cause differences in the concentration of chemicals in the organs. TCEP that enters the body through the mouth is mainly concentrated in the gastrointestinal tract and liver. However, the concentrations of chemicals that enter the skin into the mice are higher in skin, rest of body, and blood. In addition, TCEP was absorbed and accumulated very rapidly in mice, within half an hour after a single exposure. We have successfully established a mouse PBTK model of the TCEP accounting for multiple exposure Routes and obtained a series of kinetic parameters. The model includes blood, liver, kidney, stomach, intestine, skin, and rest of body compartments. Oral and dermal exposure route was considered for PBTK model. The PBTK model established in this study has a good predictive ability. More than 70% of the predicted values deviated from the measured values by less than 5-fold. In addition, we extrapolated the model to humans. A human PBTK model is built. We performed a health risk assessment for world populations based on human PBTK model. The risk of TCEP in dust is greater through mouth than through skin. The risk of TCEP in food of Chinese population is greater than dust.
•The concentrations of TCEP in various organs of mice were measured.•A PBTK model of mice exposed to TCEP in multiple routes was established.•Human health risks based on two exposure routes were evaluated.
•The predicted age difference (PAD) of brain MRI images correlates with aging and brain diseases.•Systematic bias still exists in the corrected PAD after sample-level correction.•PAD is not a ...reliable phenotype without further bias correction.•An age-level bias correction method works in numerical experiments.
The predicted age difference (PAD) between an individual’s predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases. However, the systematic bias appears in the PAD achieved using machine learning methods. Recent studies have designed diverse bias correction methods to eliminate it for further downstream studies. Strikingly, here we demonstrate that bias still exists in the PAD of samples with the same age even after kind of correction. Therefore, current PAD may not be taken as a reliable phenotype and more investigations are needed to solve this fundamental defect. To this end, we propose an age-level bias correction method and demonstrate its efficacy in numerical experiments.
Multimorbidities greatly increase the global health burdens, but the landscapes of their genetic risks have not been systematically investigated.
We used the hospital inpatient data of 385,335 ...patients in the UK Biobank to investigate the multimorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify multimorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for the networks of genetically interpretable multimorbidities to detect the hub diseases and the involved molecules and functions in each module.
In total, 11,285 multimorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture levels. Multimorbidities affecting the same and different physiological systems displayed different patterns of the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by multimorbidities converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable multimorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the multimorbidity modules could help provide useful insights for the genetic contributors of multimorbidities.
Our results provide a systematic resource for understanding the genetic predispositions of multimorbidities and indicate that hub diseases and converged molecules and functions may be the key for treating multimorbidities. We have created an online database that facilitates researchers and physicians to browse, search, or download these multimorbidities ( https://multimorbidity.comp-sysbio.org ).
Bumetanide has been reported to alter synaptic excitation-inhibition (E-I) balance by potentiating the action of γ-aminobutyric acid (GABA), thereby attenuating the severity of autism spectrum ...disorder (ASD) in animal models. However, clinical evidence of its efficacy in young patients with ASD is limited. This was investigated in the present clinical trial of 83 patients, randomised to the bumetanide group (bumetanide treatment, 0.5 mg twice daily) or the control group (no bumetanide treatment). Primary Children Autism Rating Scale (CARS), secondary Clinical Global Impressions (CGI), and exploratory inhibitory (γ-aminobutyric acid, GABA) and excitatory (glutamate, Glx) neurotransmitter concentrations measured in the insular cortex (IC) and visual cortex (VC) by magnetic resonance spectroscopy (MRS) outcome measures were evaluated at baseline and at the 3-month follow-up. Side effects were monitored throughout the treatment course. Compared with the control group, the bumetanide group showed significant reduction in symptom severity, as indicated by both total CARS score and number of items assigned a score ≥ 3. The improvement in clinical symptoms was confirmed by CGI. GABA/Glx ratio in both the IC and VC decreased more rapidly over the 3-month period in the bumetanide group than that in the control group. This decrease in the IC was associated with the symptom improvement in the bumetanide group. Our study confirmed the clinical efficacy of bumetanide on alleviating the core symptoms of ASD in young children and it is the first demonstration that the improvement is associated with reduction in GABA/Glx ratios. This study suggests that the GABA/Glx ratio measured by MRS may provide a neuroimaging biomarker for assessing treatment efficacy for bumetanide.
Hemispheric lateralization constitutes a core architectural principle of human brain organization underlying cognition, often argued to represent a stable, trait-like feature. However, emerging ...evidence underlines the inherently dynamic nature of brain networks, in which time-resolved alterations in functional lateralization remain uncharted. Integrating dynamic network approaches with the concept of hemispheric laterality, we map the spatiotemporal architecture of whole-brain lateralization in a large sample of high-quality resting-state fMRI data (N = 991, Human Connectome Project). We reveal distinct laterality dynamics across lower-order sensorimotor systems and higher-order associative networks. Specifically, we expose 2 aspects of the laterality dynamics: laterality fluctuations (LF), defined as the standard deviation of laterality time series, and laterality reversal (LR), referring to the number of zero crossings in laterality time series. These 2 measures are associated with moderate and extreme changes in laterality over time, respectively. While LF depict positive association with language function and cognitive flexibility, LR shows a negative association with the same cognitive abilities. These opposing interactions indicate a dynamic balance between intra and interhemispheric communication, i.e., segregation and integration of information across hemispheres. Furthermore, in their time-resolved laterality index, the default mode and language networks correlate negatively with visual/sensorimotor and attention networks, which are linked to better cognitive abilities. Finally, the laterality dynamics are associated with functional connectivity changes of higher-order brain networks and correlate with regional metabolism and structural connectivity. Our results provide insights into the adaptive nature of the lateralized brain and new perspectives for future studies of human cognition, genetics, and brain disorders.
Close friendships are important for mental health and cognition in late childhood. However, whether the more close friends the better, and the underlying neurobiological mechanisms are unknown. Using ...the Adolescent Brain Cognitive Developmental study, we identified nonlinear associations between the number of close friends, mental health, cognition, and brain structure. Although few close friends were associated with poor mental health, low cognitive functions, and small areas of the social brain (e.g., the orbitofrontal cortex, the anterior cingulate cortex, the anterior insula, and the temporoparietal junction), increasing the number of close friends beyond a level (around 5) was no longer associated with better mental health and larger cortical areas, and was even related to lower cognition. In children having no more than five close friends, the cortical areas related to the number of close friends revealed correlations with the density of μ-opioid receptors and the expression of OPRM1 and OPRK1 genes, and could partly mediate the association between the number of close friends, attention-deficit/hyperactivity disorder (ADHD) symptoms, and crystalized intelligence. Longitudinal analyses showed that both too few and too many close friends at baseline were associated with more ADHD symptoms and lower crystalized intelligence 2 y later. Additionally, we found that friendship network size was nonlinearly associated with well-being and academic performance in an independent social network dataset of middle-school students. These findings challenge the traditional idea of 'the more, the better,' and provide insights into potential brain and molecular mechanisms.
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