Spatial and temporal pattern of structure-function coupling of human brain connectome with development.

Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7-21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.

Disrupted cerebellar structural connectome in spinocerebellar ataxia type 3 and its association with transcriptional profiles.

Spinocerebellar ataxia type 3 (SCA3) is primarily characterized by progressive cerebellar degeneration, including gray matter atrophy and disrupted anatomical and functional connectivity. The alterations of cerebellar white matter structural network in SCA3 and the underlying neurobiological mechanism remain unknown. Using a cohort of 20 patients with SCA3 and 20 healthy controls, we constructed cerebellar structural networks from diffusion MRI and investigated alterations of topological organization. Then, we mapped the alterations with transcriptome data from the Allen Human Brain Atlas to identify possible biological mechanisms for regional selective vulnerability to white matter damage. Compared with healthy controls, SCA3 patients exhibited reduced global and nodal efficiency, along with a widespread decrease in edge strength, particularly affecting edges connected to hub regions. The strength of inter-module connections was lower in SCA3 group and negatively correlated with the Scale for the Assessment and Rating of Ataxia score, International Cooperative Ataxia Rating Scale score, and cytosine-adenine-guanine repeat number. Moreover, the transcriptome-connectome association study identified the expression of genes involved in synapse-related and metabolic biological processes. These findings suggest a mechanism of white matter vulnerability and a potential image biomarker for the disease severity, providing insights into neurodegeneration and pathogenesis in this disease.

Facile and efficient transformation of thiols to disulfides via a radical pathway with N-anomeric amide.

Radical coupling of thiols is an attractive route for the synthesis of disulfides, but this approach should be promoted by strong oxidants and/or metal salts in combination with additives, which limits its substrate scope and application. In this work, the N-anomeric amide was first found to be able to realize the conversion of thiols to sulfur radicals with high efficiency in the absence of an oxidant or any additives for the synthesis of symmetrical disulfides. The protocol features mild reaction conditions, good functional group tolerance, and moderate to excellent yields.

Right thalamic volume mediates impact of the dopamine beta-hydroxylase gene on the endowment effect.

The endowment effect is a tendency that individuals overvalue items belonging to them relative to those items that do not. Previous studies showed a strong relation between the dopamine beta-hydroxylase (DBH) gene and the endowment effect (EE), and a link between EE and task-based functional MRI activation in multiple brain regions. However, the role of brain structure on EE remains unclear. In this study, we have explored whether regional brain volume mediate the effect of the DBH gene on EE. Results showed that rs1611115, single-nucleotide polymorphisms (SNPs) at DBH loci, were significantly associated with right thalamus volume and the endowment effect in males but not in female participants. Specifically, male DBH rs1611115 T-carriers had larger right thalamus volume compared to carriers of CC genotype and exhibited a greater endowment effect. Importantly, we found that right thalamus volume mediated the effect of rs1611115 on the endowment effect in male participants. This study demonstrated how thalamic volume plays an important mediating role between genetics and decision-making in humans.

Degradation of Complex Carbon Sources in Organic Fertilizers Facilitates Nitrogen Fixation.

Biological nitrogen fixation is crucial for agriculture and improving fertilizer efficiency, but organic fertilizers in enhancing this process remain debated. Here, we investigate the impact of organic fertilizers on biological nitrogen fixation through experiments and propose a new model where bacterial interactions with complex carbon sources enhance nitrogen fixation. Field experiments showed that adding organic fertilizers increased the nitrogenase activity by 57.85%. Subculture experiments revealed that organic fertilizer addition enriched genes corresponding to complex carbon and energy metabolism, as well as nifJ involved in electron transfer for nitrogenase. It also enhanced bacterial interactions and enhanced connectors associated with complex carbon degradation. Validation experiments demonstrated that combinations increased nitrogenase activity by 2.98 times compared to the single. Our findings suggest that organic fertilizers promoted nitrogen fixation by enhancing microbial cooperation, improved the degradation of complex carbon sources, and thereby provided utilizable carbon sources, energy, and electrons to N-fixers, thus increasing nitrogenase activity and nitrogen fixation.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Dual isotopic evidence of δ15N and δ18O for priority control of vehicle emissions in a megacity of East China: Insight from measurements in summer and winter.

The source apportionment and main formation pathway of nitrate aerosols in China are not yet fully understood. In this study, PM2.5 samples were collected in Shanghai in the summer and winter of 2019. Water-soluble inorganic ions and isotopic signatures of stable nitrogen (δ15N-NO3-) and stable oxygen (δ18O-NO3-) in PM2.5 were determined. The results showed that NO3- was less important in summer (NO3-/SO42- = 0.4 ± 0.8), while it became the dominant species in winter (52.1 %). The average values of δ15N-NO3- and δ18O-NO3- in summer were + 2.0 ± 6.1 ‰ and 63.3 ± 9.4 ‰ respectively, which were significantly lower than those in winter (+7.2 ± 3.4 ‰ and 88.3 ± 12.1 ‰), indicating discrepancies between NOx sources and nitrate formation pathways. Both δ15N-NO3- and δ18O-NO3- were elevated at night, demonstrating that N2O5 hydrolysis contributed to the nocturnal nitrate increase even in summer. The contribution of the OH oxidation pathway to nitrate aerosols averaged at 70.5 ± 17.0 % in summer and N2O5 hydrolysis dominated the nitrate production in winter (approximately 80 %). On average, vehicle exhaust, coal combustion, natural gas burning, and soil emission contributed 50.7 %, 21.5 %, 15.9 %, and 11.9 %, respectively, to nitrate aerosols in summer, and contributed 56.8 %, 23.9 %, 13.6 %, and 5.7 %, respectively, to nitrate production in winter. Notably, natural gas burning is a non-negligible source of nitrate aerosols in Shanghai. In contrast to an inverse correlation between δ15N-NO3- and PM2.5, the value of δ18O-NO3- was positively correlated with nitrate concentration and aerosol liquid water content (ALWC) in winter, suggesting that explosive growth of nitrate was driven by continuous accumulation of N-depleted NOx and rapid N2O5 hydrolysis under calm and humid conditions. To continuously improve air quality, priority control should be given to vehicle emissions as the dominant source of NOx and volatile organic compounds (VOCs) in Shanghai.

Spatial and temporal pattern of structure-function coupling of human brain connectome with development.

Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7 to 21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.

Airborne environmentally persistent free radicals (EPFRs) in PM2.5 from combustion sources: Abundance, cytotoxicity and potential exposure risks.

As an emerging atmospheric pollutant, airborne environmentally persistent free radicals (EPFRs) are formed during many combustion processes and pose various adverse health effects. In health-oriented air pollution control, it is vital to evaluate the health effects of atmospheric fine particulate matter (PM2.5) from different emission sources. In this study, various types of combustion-derived PM2.5 were collected on filters in a partial-flow dilution tunnel sampling system from three typical emission sources: coal combustion, biomass burning, and automobile exhaust. Substantial concentrations of EPFRs were determined in PM2.5 samples and associated with significant potential exposure risks. Results from in vitro cytotoxicity and oxidative potential assays suggest that EPFRs may cause substantial generation of reactive oxygen species (ROS) upon inhalation exposure to PM2.5 from anthropogenic combustion sources, especially from automobile exhaust. This study provides important evidence for the source- and concentration-dependent health effects of EPFRs in PM2.5 and motivates further assessments to advance public health-oriented PM2.5 emission control.

Microbial mechanisms of C/N/S geochemical cycling during low-water-level sediment remediation in urban rivers.

Low-water-level regulation has been effectively implemented in the restoration of urban river sediments in Guangzhou City, China. Further investigation is needed to understand the microbial mechanisms involved in pollutant degradation in low-water-level environments. This study examined sediment samples from nine rivers, including low-water-level rivers (LW), tidal waterways (TW), and enclosed rivers (ER). Metagenomic high-throughput sequencing and the Diting pipeline were utilized to investigate the microbial mechanisms involved in sediment C/N/S geochemical cycling during low-water-level regulation. The results reveal that the degree of pollution in LW sediment is lower compared to TW and ER sediment. LW sediment exhibits a higher capacity for pollutant degradation and elimination of black, odorous substances due to its stronger microbial methane oxidation, nitrification, denitrification, anammox, and oxidation of sulfide, sulfite, and thiosulfate. Conversely, TW and ER sediment showcase greater microbial methanogenesis, anaerobic fermentation, and sulfide generation abilities, leading to the persistence of black, odorous substances. Factors such as grit and silt content, nitrate, and ammonia concentrations impacted microbial metabolic pathways. Low-water-level regulation improved the micro-environment for functional microbes, facilitating pollutant removal and preventing black odorous substance accumulation. These findings provide insights into the microbial mechanisms underlying low-water-level regulation technology for sediment restoration in urban rivers.

Associations of quantitative susceptibility mapping with cortical atrophy and brain connectome in Alzheimer's disease: A multi-parametric study.

Aberrant susceptibility due to iron level abnormality and brain network disconnections are observed in Alzheimer's disease (AD), with disrupted iron homeostasis hypothesized to be linked to AD pathology and neuronal loss. However, whether associations exist between abnormal quantitative susceptibility mapping (QSM), brain atrophy, and altered brain connectome in AD remains unclear. Based on multi-parametric brain imaging data from 30 AD patients and 26 healthy controls enrolled at the China-Japan Friendship Hospital, we investigated the abnormality of the QSM signal and volumetric measure across 246 brain regions in AD patients. The structural and functional connectomes were constructed based on diffusion MRI tractography and functional connectivity, respectively. The network topology was quantified using graph theory analyses. We identified seven brain regions with both reduced cortical thickness and abnormal QSM (p < 0.05) in AD, including the right superior frontal gyrus, left superior temporal gyrus, right fusiform gyrus, left superior parietal lobule, right superior parietal lobule, left inferior parietal lobule, and left precuneus. Correlations between cortical thickness and network topology computed across patients in the AD group resulted in statistically significant correlations in five of these regions, with higher correlations in functional compared to structural topology. We computed the correlation between network topological metrics, QSM value and cortical thickness across regions at both individual and group-averaged levels, resulting in a measure we call spatial correlations. We found a decrease in the spatial correlation of QSM and the global efficiency of the structural network in AD patients at the individual level. These findings may provide insights into the complex relationships among QSM, brain atrophy, and brain connectome in AD.

Phytoplasma: A plant pathogen that cannot be ignored in agricultural production-Research progress and outlook.

Phytoplasmas are phloem-restricted plant-pathogenic bacteria transmitted by insects. They cause diseases in a wide range of host plants, resulting in significant economic and ecological losses worldwide. Research on phytoplasmas has a long history, with significant progress being made in the past 30 years. Notably, with the rapid development of phytoplasma research, scientists have identified the primary agents involved in phytoplasma transmission, established classification and detection systems for phytoplasmas, and 243 genomes have been sequenced and assembled completely or to draft quality. Multiple possible phytoplasma effectors have been investigated, elucidating the molecular mechanisms by which phytoplasmas manipulate their hosts. This review summarizes recent advances in phytoplasma research, including identification techniques, host range studies, whole- or draft-genome sequencing, effector pathogenesis and disease control methods. Additionally, future research directions in the field of phytoplasma research are discussed.

DCP: A pipeline toolbox for diffusion connectome.

The brain structural network derived from diffusion magnetic resonance imaging (dMRI) reflects the white matter connections between brain regions, which can quantitatively describe the anatomical connection pattern of the entire brain. The development of structural brain connectome leads to the emergence of a large number of dMRI processing packages and network analysis toolboxes. However, the fully automated network analysis based on dMRI data remains challenging. In this study, we developed a cross-platform MATLAB toolbox named "Diffusion Connectome Pipeline" (DCP) for automatically constructing brain structural networks and calculating topological attributes of the networks. The toolbox integrates a few developed packages, including FSL, Diffusion Toolkit, SPM, Camino, MRtrix3, and MRIcron. It can process raw dMRI data collected from any number of participants, and it is also compatible with preprocessed files from public datasets such as HCP and UK Biobank. Moreover, a friendly graphical user interface allows users to configure their processing pipeline without any programming. To prove the capacity and validity of the DCP, two tests were conducted with using DCP. The results showed that DCP can reproduce the findings in our previous studies. However, there are some limitations of DCP, such as relying on MATLAB and being unable to fixel-based metrics weighted network. Despite these limitations, overall, the DCP software provides a standardized, fully automated computational workflow for white matter network construction and analysis, which is beneficial for advancing future human brain connectomics application research.

Mn2+/CpG Oligodeoxynucleotides Codecorated Black Phosphorus Nanosheet Platform for Enhanced Antitumor Potency in Multimodal Therapy.

Manganese ions (Mn2+)-coordinated nanoparticles have emerged as a promising class of antitumor nanotherapeutics, capable of simultaneously disrupting the immunosuppressive tumor microenvironment (TME) and triggering the stimulator of interferon genes (STING) pathway-dependent antitumor immunity. However, the activation of STING signaling by Mn2+-based monotherapies is suboptimal for comprehensive stimulation of antigen presenting cells and reversal of immunosuppression in the TME. Here, we report the design of a Mn2+/CpG oligodeoxynucleotides (ODNs) codecorated black phosphorus nanosheet (BPNS@Mn2+/CpG) platform based on the Mn2+ modification of BPNS and subsequent adsorption of synthetic CpG ODNs. The coordination of Mn2+ significantly improved the stability of BPNS and the adsorption of CpG ODNs. The acidic TME and endosomal compartments can disrupt the Mn2+ coordination, triggering pH-responsive release of CpG ODNs and Mn2+ to effectively activate the Toll-like receptor 9 and STING pathways. As a result, M2-type macrophages and immature dendritic cells were strongly stimulated in the TME, thereby increasing T lymphocyte infiltration and reversing the immunosuppression within the TME. Phototherapy and chemodynamic therapy, utilizing the BPNS@Mn2+/CpG platform, have demonstrated efficacy in inducing immunogenic cell death upon 808 nm laser irradiation. Importantly, the treatment of BPNS@Mn2+/CpG with laser irradiation exhibited significant therapeutic efficacy against the irradiated primary tumor and effectively suppressed the growth of nonirradiated distant tumor. Moreover, it induced a robust immune memory, providing long-lasting protection against tumor recurrence. This study demonstrated the enhanced antitumor potency of BPNS@Mn2+/CpG in multimodal therapy, and its proof-of-concept application as a metal ion-modified BPNS material for effective DNA/drug delivery and immunotherapy.

Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum.

Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0-T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including ß-amyloid (Aß), phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 × 10-24 ; quadratic trend: t = 7.708, p = 2.25 × 10-13 ; adjusted R2 = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 × 10-10 ; quadratic trend: t = 3.896, p = 1.22 × 10-4 ; adjusted R2 = 0.330), p-tau181 (linear trend: t = 8.452, p = 1.61 × 10-15 ; quadratic trend: t = 6.316, p = 1.05 × 10-9 ; adjusted R2 = 0.346) and Aß42/Aß40 (linear trend: t = -3.257, p = 1.27 × 10-3 ; quadratic trend: t = -1.662, p = 9.76 × 10-2 ; adjusted R2 = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = -0.61, p = 6.3 × 10-7 ), NfL (R = -0.57, p = 6.4 × 10-6 ), and p-tau181 (R = -0.48, p = 2.0 × 10-4 ). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = -0.224, 95% confidence interval [CI] = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA) or NfL (ab = -0.224, 95% CI = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network-plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.

Protein interaction mapping reveals widespread targeting of development-related host transcription factors by phytoplasma effectors.

Phytoplasmas are pathogenic bacteria that reprogram plant host development for their own benefit. Previous studies have characterized a few different phytoplasma effector proteins that destabilize specific plant transcription factors. However, these are only a small fraction of the potential effectors used by phytoplasmas; therefore, the molecular mechanisms through which phytoplasmas modulate their hosts require further investigation. To obtain further insights into the phytoplasma infection mechanisms, we generated a protein-protein interaction network between a broad set of phytoplasma effectors and a large, unbiased collection of Arabidopsis thaliana transcription factors and transcriptional regulators. We found widespread, but specific, interactions between phytoplasma effectors and host transcription factors, especially those related to host developmental processes. In particular, many unrelated effectors target specific sets of TCP transcription factors, which regulate plant development and immunity. Comparison with other host-pathogen protein interaction networks shows that phytoplasma effectors have unusual targets, indicating that phytoplasmas have evolved a unique and unusual infection strategy. This study contributes a rich and solid data source that guides further investigations of the functions of individual effectors, as demonstrated for some herein. Moreover, the dataset provides insights into the underlying molecular mechanisms of phytoplasma infection.

Bimodular architecture of bacterial effector SAP05 that drives ubiquitin-independent targeted protein degradation.

In eukaryotes, targeted protein degradation (TPD) typically depends on a series of interactions among ubiquitin ligases that transfer ubiquitin molecules to substrates leading to degradation by the 26S proteasome. We previously identified that the bacterial effector protein SAP05 mediates ubiquitin-independent TPD. SAP05 forms a ternary complex via interactions with the von Willebrand Factor Type A (vWA) domain of the proteasomal ubiquitin receptor Rpn10 and the zinc-finger (ZnF) domains of the SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) and GATA BINDING FACTOR (GATA) transcription factors (TFs). This leads to direct TPD of the TFs by the 26S proteasome. Here, we report the crystal structures of the SAP05-Rpn10vWA complex at 2.17 Å resolution and of the SAP05-SPL5ZnF complex at 2.20 Å resolution. Structural analyses revealed that SAP05 displays a remarkable bimodular architecture with two distinct nonoverlapping surfaces, a "loop surface" with three protruding loops that form electrostatic interactions with ZnF, and a "sheet surface" featuring two ß-sheets, loops, and α-helices that establish polar interactions with vWA. SAP05 binding to ZnF TFs involves single amino acids responsible for multiple contacts, while SAP05 binding to vWA is more stable due to the necessity of multiple mutations to break the interaction. In addition, positioning of the SAP05 complex on the 26S proteasome points to a mechanism of protein degradation. Collectively, our findings demonstrate how a small bacterial bimodular protein can bypass the canonical ubiquitin-proteasome proteolysis pathway, enabling ubiquitin-independent TPD in eukaryotic cells. This knowledge holds significant potential for the creation of TPD technologies.

Genetic risks of Alzheimer's by APOE and MAPT on cortical morphology in young healthy adults.

Genetic risk factors such as APOE ε4 and MAPT (rs242557) A allele are associated with amyloid and tau pathways and grey matter changes at both early and established stages of Alzheimer's disease, but their effects on cortical morphology in young healthy adults remain unclear. A total of 144 participants aged from 18 to 24 underwent 3T MRI and genotyping for APOE and MAPT to investigate unique impacts of these genetic risk factors in a cohort without significant comorbid conditions such as metabolic and cardiovascular diseases. We segmented the cerebral cortex into 68 regions and calculated the cortical area, thickness, curvature and folding index for each region. Then, we trained machine learning models to classify APOE and MAPT genotypes using these morphological features. In addition, we applied a growing hierarchical self-organizing maps algorithm, which clustered the 68 regions into 4 subgroups representing different morphological patterns. Then, we performed general linear model analyses to estimate the interaction between APOE and MAPT on cortical patterns. We found that the classifiers using all cortical features could accurately classify individuals carrying genetic risks of dementia outperforming each individual feature alone. APOE ε4 carriers had a more convoluted and thinner cortex across the cerebral cortex. A similar pattern was found in MAPT A allele carriers only in the regions that are vulnerable for early tau pathology. With the clustering analysis, we found a synergetic effect between APOE ε4 and MAPT A allele, i.e. carriers of both risk factors showed the most deviation of cortical pattern from the typical pattern of that cluster. Genetic risk factors of dementia by APOE ε4 and MAPT (rs242557) A allele were associated with variations of cortical morphology, which can be observed in young healthy adults more than 30 years before Alzheimer's pathology is likely to occur and 50 years before dementia symptoms may begin.

Granger Causal Inference Based on Dual Laplacian Distribution and Its Application to MI-BCI Classification.

Granger causality-based effective brain connectivity provides a powerful tool to probe the neural mechanism for information processing and the potential features for brain computer interfaces. However, in real applications, traditional Granger causality is prone to the influence of outliers, such as inevitable ocular artifacts, resulting in unreasonable brain linkages and the failure to decipher inherent cognition states. In this work, motivated by constructing the sparse causality brain networks under the strong physiological outlier noise conditions, we proposed a dual Laplacian Granger causality analysis (DLap-GCA) by imposing Laplacian distributions on both model parameters and residuals. In essence, the first Laplacian assumption on residuals will resist the influence of outliers in electroencephalogram (EEG) on causality inference, and the second Laplacian assumption on model parameters will sparsely characterize the intrinsic interactions among multiple brain regions. Through simulation study, we quantitatively verified its effectiveness in suppressing the influence of complex outliers, the stable capacity for model estimation, and sparse network inference. The application to motor-imagery (MI) EEG further reveals that our method can effectively capture the inherent hemispheric lateralization of MI tasks with sparse patterns even under strong noise conditions. The MI classification based on the network features derived from the proposed approach shows higher accuracy than other existing traditional approaches, which is attributed to the discriminative network structures being captured in a timely manner by DLap-GCA even under the single-trial online condition. Basically, these results consistently show its robustness to the influence of complex outliers and the capability of characterizing representative brain networks for cognition information processing, which has the potential to offer reliable network structures for both cognitive studies and future brain-computer interface (BCI) realization.

Exact results for the residual entropy of ice hexagonal monolayer.

Since the problem of the residual entropy of square ice was exactly solved, exact solutions for two-dimensional realistic ice models have been of interest. In this work, we study the exact residual entropy of ice hexagonal monolayer in two cases. In the case that the external electric field along the z-axis exists, we map the hydrogen configurations into the spin configurations of the Ising model on the kagome lattice. By taking the low temperature limit of the Ising model, we derive the exact residual entropy, which agrees with the result determined previously from the dimer model on the honeycomb lattice. In another case that the ice hexagonal monolayer is under the periodic boundary conditions in the cubic ice lattice, the residual entropy has not been studied exactly. For this case, we employ the six-vertex model on the square lattice to represent the hydrogen configurations obeying the ice rules. The exact residual entropy is obtained from the solution of the equivalent six-vertex model. Our work provides more examples of the exactly soluble two-dimensional statistical models.