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The neurophysiological mechanism underlying sedation, especially in school-aged children, remains largely unknown. The recently emerged resting-state functional magnetic resonance imaging (rsfMRI) technique, capable of delineating brain's functional interaction pattern among distributed brain areas, proves to be a unique and powerful tool to study sedation-induced brain reorganization. Based on a relatively large school-aged children population (n=28, 10.3±2.6 years, range 7-15 years) and leveraging rsfMRI and graph theoretical analysis, this study aims to delineate sedation-induced changes in brain's information transferring property from a whole brain system perspective. Our results show a global deterioration in brain's efficiency properties (p=0.0085 and 0.0018, for global and local efficiency, respectively) with a locally graded distribution featuring significant disruptions of key consciousness-related regions. Moreover, our results also indicate a redistribution of brain's information-processing hubs characterized by a right and posterior shift as consistent with the reduced level of consciousness during sedation. Overall, our findings inform a sedation-induced functional reorganization pattern in school-aged children that greatly improve our understanding of sedation's effect in children and may potentially serve as reference for future sedation-related experimental studies and clinical applications.

Background No study has assessed normal magnetic resonance imaging (MRI) findings to predict potential brain injury in neonates with hypoxic–ischemic encephalopathy (HIE). Objective We aimed to evaluate the efficacy of MRI-based radiomics models of the basal ganglia, thalami and deep medullary veins to differentiate between HIE and the absence of MRI abnormalities in neonates. Materials and methods In this study, we included 38  full-term neonates with HIE and normal MRI findings and 89 normal neonates. Radiomics features were extracted from T1-weighted images, T2-weighted images, diffusion-weighted imaging and susceptibility-weighted imaging (SWI). The different models were evaluated using receiver operating characteristic curve analysis. Clinical utility was evaluated using decision curve analysis. Results The SWI model exhibited the best performance among the seven single-sequence models. For the training and validation cohorts, the area under the curves (AUCs) of the SWI model were 1.00 and 0.98, respectively. The combined nomogram model incorporating SWI Rad-scores and independent predictors of clinical characteristics was not able to distinguish HIE in patients without MRI abnormalities from the control group (AUC, 1.00). A high degree of fitting and favorable clinical utility was detected using the calibration curve with the Hosmer−Lemeshow test. Decision curve analysis was used for the SWI, clinical and combined nomogram models. The decision curve showed that the SWI and combined nomogram models had better predictive performance than the clinical model. Conclusions HIE can be detected in patients without MRI abnormalities using an MRI-based radiomics model. The SWI model performed better than the other models. Graphical Abstract

The migration characteristics of iron ions in laterite in water can reflected by change characteristics of iron ion concentration in water solution. Its migration ability depends on itself features of laterite and the effect of external environment. The results show that, the migration ability of iron ion in laterite were weakened with increasing of compaction energy and extending of immersion times, were strengthed with increasing of moisture content and temperature. The effect of compaction energy is least, the effect of temperature is maximum, the effect of moisture content is between them. Its migration process is that iron ion of adsorption in laterite particles surface were dissolved and migrated into process of the water solution. Its migration mechanism can explained from water environmental balance and temperature balance and ion concentration balance. The results changed the migration characteristics of iron ion in laterite at different influencing factors.

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s. The microstructure characteristic of compacted laterite with acid contamination was researched by means of electronic microscope scanning and microstructures image analysis in which the hydrochloric acid was used as pollutant and the acid concentration and curing history of samples were taken into account. It shows that acid pollution significantly influences the microstructure of laterite in which with more acid concentration and longer pollution times, the microstructure images behave lower compaction, blur particle edges, dissolution cement among particles, gluing coatings parceling particles, pores among particles and darker gray color. The corresponding parameters of the microstructure behave different properties in which with longer pollution times of samples, there is a maximum of porosity, girths of particles increase, number of particles decreases, the circularity of particles is not obvious, the directionality and the fractal dimension vary with magnification of the images and with more acid concentration, the girths and porosity increase, the circularity and fractal dimension decrease, the particle number and the directionality vary with the magnification of images. The result shows that the mechanism of the effect of acid contamination on laterites micro structures is that the acid erodes its particles and the cement among particles.

BackgroundStructural magnetic resonance imaging (sMRI) reveals abnormalities in patients with autism spectrum syndrome (ASD). Previous connectome studies of ASD have failed to identify the individual neuroanatomical details in preschool-age individuals. This paper aims to establish an individual morphological connectome method to characterize the connectivity patterns and topological alterations of the individual-level brain connectome and their diagnostic value in patients with ASD.MethodsBrain sMRI data from 24 patients with ASD and 17 normal controls (NCs) were collected; participants in both groups were aged 24–47 months. By using the Jensen–Shannon Divergence Similarity Estimation (JSSE) method, all participants’s morphological brain network were ascertained. Student’s t-tests were used to extract the most significant features in morphological connection values, global graph measurement, and node graph measurement.ResultsThe results of global metrics’ analysis showed no statistical significance in the difference between two groups. Brain regions with meaningful properties for consensus connections and nodal metric features are mostly distributed in are predominantly distributed in the basal ganglia, thalamus, and cortical regions spanning the frontal, temporal, and parietal lobes. Consensus connectivity results showed an increase in most of the consensus connections in the frontal, parietal, and thalamic regions of patients with ASD, while there was a decrease in consensus connectivity in the occipital, prefrontal lobe, temporal lobe, and pale regions. The model that combined morphological connectivity, global metrics, and node metric features had optimal performance in identifying patients with ASD, with an accuracy rate of 94.59%.ConclusionThe individual brain network indicator based on the JSSE method is an effective indicator for identifying individual-level brain network abnormalities in patients with ASD. The proposed classification method can contribute to the early clinical diagnosis of ASD.

The stability of the soil slopes can be judged according to the critical moisture content and the actual moisture content when the soil slopes be in the limit equilibrium state. From the perspective of earth pressure, the critical moisture content is the moisture content when the soil slopes be in the active limit equilibrium state, at this time, the active earth pressure is 0. The critical moisture content can be determined and the stability of the slopes can be judged according to the relationship of the soil parameters and the moisture content and the active earth pressure being 0. The critical moisture content of the upright or declining cohesionless slopes can be determined according to the relationship of the internal friction angle and the moisture content. The critical moisture content of the upright cohesive slopes can be determined by solving the equation of the critical moisture content. For the declining cohesive slopes, first, the cohesive soil having the cohesion and internal friction angle is replaced by only having the equivalent internal friction angle of the cohesionless soil according to the principle of the equal strength, then, the critical moisture content can be determined according to the relationship of the equivalent internal friction angle and the moisture content of the declining cohesionless.