No sex difference in maturation of brain morphology during the perinatal period.

Accumulating evidence have documented sex differences in brain anatomy from early childhood to late adulthood. However, whether sex difference of brain structure emerges in the neonatal brain and how sex modulates the development of cortical morphology during the perinatal stage remains unclear. Here, we utilized T2-weighted MRI from the Developing Human Connectome Project (dHCP) database, consisting of 41 male and 40 female neonates born between 35 and 43 postmenstrual weeks (PMW). Neonates of each sex were arranged in a continuous ascending order of age to capture the progressive changes in cortical thickness and curvature throughout the developmental continuum. The maturational covariance network (MCN) was defined as the coupled developmental fluctuations of morphology measures between cortical regions. We constructed MCNs based on the two features, respectively, to illustrate their developmental interdependencies, and then compared the network topology between sexes. Our results showed that cortical structural development exhibited a localized pattern in both males and females, with no significant sex differences in the developmental trajectory of cortical morphology, overall organization, nodal importance, and modular structure of the MCN. Furthermore, by merging male and female neonates into a unified cohort, we identified evident dependencies influences in structural development between different brain modules using the Granger causality analysis (GCA), emanating from high-order regions toward primary cortices. Our findings demonstrate that the maturational pattern of cortical morphology may not differ between sexes during the perinatal period, and provide evidence for the developmental causality among cortical structures in perinatal brains.

Enhancing photoluminescence of WSe2 in vapor grown WSe2/VOCl bilayer heterojunctions via surface passivation.

Monolayer tungsten selenide (WSe2) has attracted attention due to its direct bandgap-generated strong light emission and light-matter interaction. Herein, vertical WSe2/VOCl bilayer heterojunctions with enhanced PL of WSe2 were synthesized by the vapor growth method. The morphology, crystal structure, and chemical composition of the WSe2/VOCl heterojunctions were systematically investigated, which confirmed the successful formation of the heterojunctions. The PL emission intensity of WSe2 obtained from the WSe2/VOCl heterojunction was about 2.4 times higher than that of the WSe2 monolayer, demonstrating the high optical quality of the WSe2/VOCl heterojunction, which was further confirmed by time-resolved PL measurements. The insulator top VOCl, which was deposited on the surface of the semiconductor bottom WSe2 as a surface passivation material, reducing the impurities and resulting in an atomically clean surface, successfully enhanced the PL emission of the bottom WSe2. This vertical WSe2/VOCl bilayer heterojunction with PL enhancement could provide a promising platform for optical devices.

Clinical application of targeted next-generation sequencing in severe pneumonia: a retrospective review.

BACKGROUND: The precise identification of the underlying causes of infectious diseases, such as severe pneumonia, is essential, and the development of next-generation sequencing (NGS) has enhanced the effectiveness of pathogen detection. However, there is limited information on the systematic assessment of the clinical use of targeted next-generation sequencing (tNGS) in cases of severe pneumonia. METHODS: A retrospective analysis was conducted on 130 patients with severe pneumonia treated in the ICU from June 2022 to June 2023. The consistency of the results of tNGS, metagenomics next-generation sequencing (mNGS), and culture with the clinical diagnosis was evaluated. Additionally, the results for pathogens detected by tNGS were compared with those of culture, mNGS, and quantitative reverse transcription PCR (RT-qPCR). To evaluate the efficacy of monitoring severe pneumonia, five patients with complicated infections were selected for tNGS microbiological surveillance. The tNGS and culture drug sensitisation results were then compared. RESULTS: The tNGS results for the analysis of the 130 patients showed a concordance rate of over 70% with clinical diagnostic results. The detection of pathogenic microorganisms using tNGS was in agreement with the results of culture, mNGS, and RT-qPCR. Furthermore, the tNGS results for pathogens in the five patients monitored for complicated infections of severe pneumonia were consistent with the culture and imaging test results during treatment. The tNGS drug resistance results were in line with the drug sensitivity results in approximately 65% of the cases. CONCLUSIONS: The application of tNGS highlights its promise and significance in assessing the effectiveness of clinical interventions and providing guidance for anti-infection therapies for severe pneumonia.

Causal Brain Network in Clinically-Annotated Epileptogenic Zone Predicts Surgical Outcomes of Drug-Resistant Epilepsy.

OBJECTIVE: Patients with drug-resistant epilepsy (DRE) are commonly treated using neurosurgery, while its success rate is limited with approximately 50%. Predicting surgical outcomes is currently a prominent topic. The DRE is recognized as a network disorder involving a seizure triggering mechanism within epileptogenic zone (EZ); however, a systematic exploration of the EZ causal network remains lacking. METHODS: This paper will advance DRE study by: (1) developing a novel causal coupling algorithm, "full convergent cross mapping (FCCM)" to improve the quantization performance; (2) characterizing the DRE's multi-frequency epileptogenic network by FCCM calculation of ictal iEEG; (3) predicting surgical outcomes using network features and machine learning. Numerical validations demonstrate the FCCM's superior quantization in terms of nonlinearity, accuracy, and stability. A multicenter cohort containing 22 DRE patients with 81 seizures is included. RESULT: Based on the Mann-Whitney-U-test, coupling strength of the epileptogenic network in successful surgeries is significantly higher than that of the failed group, with the most significant difference observed in α -iEEG network (p = 1.52e - 07 ) Other clinical covariates are also considered and all th α -iEEG networks demonstrate consistent differences comparing successful and failed groups, with p = 0.014 and 9.23e - 06 for lesional and non-lesional DRE, p = 2.32e - 05, 0.0074 and 0.0030 for three clinical centers CHFU, JHU and NIH. Using FCCM features and 10-fold cross validation, the SVM achieves the highest accuracy of 87.65% in predicting surgical outcomes. CONCLUSION: The epileptogenic causal network is a reliable biomarker for estimating DRE's surgical outcomes. SIGNIFICANCE: The proposed approach is promising to facilitate DRE precision medicine.

Design Strategies of Hydrogen Evolution Reaction Nano Electrocatalysts for High Current Density Water Splitting.

Hydrogen is now recognized as the primary alternative to fossil fuels due to its renewable, safe, high-energy density and environmentally friendly properties. Efficient hydrogen production through water splitting has laid the foundation for sustainable energy technologies. However, when hydrogen production is scaled up to industrial levels, operating at high current densities introduces unique challenges. It is necessary to design advanced electrocatalysts for hydrogen evolution reactions (HERs) under high current densities. This review will briefly introduce the challenges posed by high current densities on electrocatalysts, including catalytic activity, mass diffusion, and catalyst stability. In an attempt to address these issues, various electrocatalyst design strategies are summarized in detail. In the end, our insights into future challenges for efficient large-scale industrial hydrogen production from water splitting are presented. This review is expected to guide the rational design of efficient high-current density water electrolysis electrocatalysts and promote the research progress of sustainable energy.

Causal Brain Network Predicts Surgical Outcomes in Patients With Drug-Resistant Epilepsy: A Retrospective Comparative Study.

Network neuroscience, especially causal brain network, has facilitated drug-resistant epilepsy (DRE) studies, while surgical success rate in patients with DRE is still limited, varying from 30%  âˆ¼  70 %. Predicting surgical outcomes can provide additional guidance to adjust treatment plans in time for poorly predicted curative effects. In this retrospective study, we aim to systematically explore biomarkers for surgical outcomes by causal brain network methods and multicenter datasets. Electrocorticogram (ECoG) recordings from 17 DRE patients with 58 seizures were included. Ictal ECoG within clinically annotated epileptogenic zone (EZ) and non-epileptogenic zone (NEZ) were separately computed using six different algorithms to construct causal brain networks. All the brain network results were divided into two groups, successful and failed surgeries. Statistical results based on the Mann-Whitney-U-test show that: causal connectivity of α -frequency band ( 8  âˆ¼  13 Hz) in EZ calculated by convergent cross mapping (CCM) gains the most significant differences between the surgical success and failure groups, with a P value of 7.85e-08 and Cohen's d effect size of 0.77. CCM-defined EZ brain network can also distinguish the successful and failed surgeries considering clinical covariates (clinical centers, DRE types) with [Formula: see text]. Based on the brain network features, machine learning models were developed to predict the surgical outcomes. Among them, the SVM classifier with Gaussian kernel function and Bayesian optimization demonstrates the highest average accuracy of 84.48% by 5-fold cross-validation, further indicating that the CCM-defined EZ brain network is a reliable biomarker for predicting DRE surgical outcomes.

Relay Annulation of Ammonium Ylides with Oxindole-Derived α,ß-Unsaturated Ketimines: Catalytic Construction of Spiro-polycyclic Oxindoles.

An ammonium ylide-based relay annulation was disclosed, which uses DABCO as the catalyst and oxindole-derived α,ß-unsaturated ketimines and γ-bromo-crotonates as the starting materials. This method enables the rapid assembly of a series of structurally novel spiro-polycyclic oxindoles containing a bicyclo[4.1.0]heptane moiety through simultaneous generation of three new bonds and two rings in one step under mild reaction conditions.

An Attention-Based Hemispheric Relation Inference Network for Perinatal Brain Age Prediction.

Brain anatomical age is an effective feature to assess the status of the brain, such as atypical development and aging. Although some deep learning models have been developed for estimating infant brain age, the performance of these models was unsatisfactory because few of them considered the developmental characteristics of brain anatomy during the perinatal period-the most rapid and complex developmental stage across the lifespan. The present study proposed an attention-based hemispheric relation inference network (HRINet) that takes advantage of the nature of brain structural lateralization during early development. This model captures the inter-hemispheric relationship using a graph attention mechanism and transmits lateralization information as features to describe the interactive development between bilateral hemispheres. The HRINet was used to estimate the brain age of 531 preterm and full-term neonates from the Developing Human Connectome Project (dHCP) database based on two metrics (mean curvature and sulcal depth) characterizing the folding morphology of the cortex. Our results showed that the HRINet outperformed other benchmark models in fitting the perinatal brain age, with mean absolute error of 0.53 and determination coefficient of 0.89. We also verified the generalizability of the HRINet on an extra independent dataset collected from the Gansu Provincial Maternity and Child-care Hospital. Furthermore, by applying the best-performing model to an independent dataset consisting of 47 scans of preterm infants at term-equivalent age, we showed that the predicted age was significantly lower than the chronological age, suggesting a delayed development of premature brains. Our results demonstrate the effectiveness and generalizability of the HRINet in estimating infant brain age, providing promising clinical applications for assessing neonatal brain maturity.

Disrupted dynamic brain functional connectivity in male cocaine use disorder: Hyperconnectivity, strongly-connected state tendency, and links to impulsivity and borderline traits.

Cocaine use is a major public health problem with serious negative consequences at both the individual and societal levels. Cocaine use disorder (CUD) is associated with cognitive and emotional impairments, often manifesting as alterations in brain functional connectivity (FC). This study employed resting-state functional magnetic resonance imaging (rs-fMRI) to examine dynamic FC in 38 male participants with CUD and 31 matched healthy controls. Using group spatial independent component analysis (group ICA) combined with sliding window approach, we identified two recurring distinct connectivity states: the strongly-connected state (state 1) and weakly-connected state (state 2). CUD patients exhibited significant increased mean dwell and fraction time in state 1, and increased transitions from state 2 to state 1, demonstrated significant strongly-connected state tendency. Our analysis revealed abnormal FC patterns that are state-dependent and state-shared in CUD patients. This study observed hyperconnectivity within the default mode network (DMN) and between DMN and other networks, which varied depending on the state. Furthermore, after adjustment for multiple comparisons, we found significant correlations between these altered dynamic FCs and clinical measures of impulsivity and borderline personality disorder. The disrupted FC and repetitive effects of precuneus and angular gyrus across correlations suggested that they might be the important hub of neural circuits related behaviorally and mentally in CUD. In summary, our study highlighted the potential of these disrupted FC as neuroimaging biomarkers and therapeutic targets, and provided new insights into the understanding of the neurophysiologic mechanisms of CUD.

1,5-Hydrogen atom transfer of α-iminyl radical cations: a new platform for relay annulation for pyridine derivatives and axially chiral heterobiaryls.

The exploitation of new reactive species and novel transformation modes for their synthetic applications have significantly promoted the development of synthetic organic methodology, drug discovery, and advanced functional materials. α-Iminyl radical cations, a class of distonic ions, exhibit great synthetic potential for the synthesis of valuable molecules. For their generation, radical conjugate addition to α,ß-unsaturated iminium ions represents a concise yet highly challenging route, because the in situ generated species are short-lived and highly reactive and they have a high tendency to cause radical elimination (ß-scission) to regenerate the more stable iminium ions. Herein, we report a new transformation mode of the α-iminyl radical cation, that is to say, 1,5-hydrogen atom transfer (1,5-HAT). Such a strategy can generate a species bearing multiple reactive sites, which serves as a platform to realize (asymmetric) relay annulations. The present iron/secondary amine synergistic catalysis causes a modular assembly of a broad spectrum of new structurally fused pyridines including axially chiral heterobiaryls, and exhibits good functional group tolerance. A series of mechanistic experiments support the α-iminyl radical cation-induced 1,5-HAT, and the formation of several radical species in the relay annulations. Various synthetic transformations of the reaction products demonstrate the usefulness of this relay annulation protocol for the synthesis of significant molecules.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation.

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

Mycobacterium tuberculosis resides in lysosome-poor monocyte-derived lung cells during chronic infection.

Mycobacterium tuberculosis (Mtb) infects lung myeloid cells, but the specific Mtb-permissive cells and host mechanisms supporting Mtb persistence during chronic infection are incompletely characterized. We report that after the development of T cell responses, CD11clo monocyte-derived cells harbor more live Mtb than alveolar macrophages (AM), neutrophils, and CD11chi monocyte-derived cells. Transcriptomic and functional studies revealed that the lysosome pathway is underexpressed in this highly permissive subset, characterized by less lysosome content, acidification, and proteolytic activity than AM, along with less nuclear TFEB, a regulator of lysosome biogenesis. Mtb infection does not drive lysosome deficiency in CD11clo monocyte-derived cells but promotes recruitment of monocytes that develop into permissive lung cells, mediated by the Mtb ESX-1 secretion system. The c-Abl tyrosine kinase inhibitor nilotinib activates TFEB and enhances lysosome functions of macrophages in vitro and in vivo, improving control of Mtb infection. Our results suggest that Mtb exploits lysosome-poor lung cells for persistence and targeting lysosome biogenesis is a potential host-directed therapy for tuberculosis.

How Mycobacterium tuberculosis builds a home: Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs.

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

Development of an indirect ELISA against Orf virus using two recombinant antigens, partial B2L and F1L.

Orf is a highly contagious viral disease affecting goats and sheep. It is caused by Orf virus (ORFV) and has caused severe economic losses to the global goat industry, including in China. In this study, an indirect ELISA method for recombinant proteins based on truncated dominant antigenic epitopes of B2L and F1L genes of ORFV was established. A series of conditions and its performance were comprehensively evaluated. The optimized ELISA reaction conditions were: the optimal coating amount of antigen was 0.25 µg/mL, 5% skim milk powder was closed for 1 h, the optimal dilution of serum was 1:200, the optimal incubation time of the rabbit anti-goat IgG was 1:8000, the optimal color development time of TMB was 15 mins, and the threshold value of negative-positive was 0.358. The method specifically detects anti-ORFV antibodies and does not cross-react with positive sera for other common goat pathogenic bacteria antiserum. ORFV-positive sera were still positive after 1:512 dilution, with intra-batch coefficient of variation (CV) between 7.1% and 9.5% and inter-batch CV between 5.0% and 7.6%; 51% (92/180) of immunized goat serum samples were tested positive and 14.44% (14/63) of non-immunized goat serum samples were positive. The results show that the indirect ELISA antibody assay established in this study has good specificity, sensitivity and reproducibility, and provides a technical tool for clinical ORFV serum antibody detection and epidemiological investigation.

Modular Assembly of 2-Aminoaniline Derivatives by Merging Hydroxylamine-Passerini and Hetero-Cope Rearrangement.

A metal-free three-component protocol that combines a hydroxylamine-Passerini reaction and hetero-Cope rearrangement was realized, which enables the modular assembly of a wide range of structurally new and interesting 2-aminoanilines bearing an α-hydroxyamide substructure.

Rich Club Reorganization in Nurses Before and After the Onset of Occupational Burnout: A Longitudinal MRI Study.

BACKGROUND: Studies on potential disruptions in rich club structure in nursing staff with occupational burnout are lacking. Moreover, existing studies on nurses with burnout are limited by their cross-sectional design. PURPOSE: To investigate rich club reorganization in nursing staff before and after the onset of burnout and the underlying impact of anatomical distance on such reconfiguration. STUDY TYPE: Prospective, longitudinal. POPULATION: Thirty-nine hospital nurses ( 23.67 ± 1.03 $$ 23.67\pm 1.03 $$ years old at baseline, 24.67 ± 1.03 $$ 24.67\pm 1.03 $$ years old at a follow-up within 1.5 years, 38 female). FIELD STRENGTH/SEQUENCE: Magnetization-prepared rapid gradient-echo and gradient-echo echo-planar imaging sequences at 3.0 T. ASSESSMENT: The Maslach Burnout Inventory and Symptom Check-List 90 testing were acquired at each MRI scan. Rich club structure was assessed at baseline and follow-up to determine whether longitudinal changes were related to burnout and to changes in connectivities with different anatomical distances (short-, mid-, and long range). STATISTICAL TESTS: Chi-square, paired-samples t, two-sample t, Mann-Whitney U tests, network-based statistic, Spearman correlation analysis, and partial least squares regression analysis. Significance level: Bonferroni-corrected P < 0.05 $$ P<0.05 $$ . RESULTS: In nurses who developed burnout: 1) Strengths of rich club, feeder, local, short-, mid-, and long-range connectivities were significantly decreased at follow-up compared with baseline. 2) At follow-up, strengths of above connectivities and that between A5m.R and dlPu.L were significantly correlated with emotional exhaustion (r ranges from -0.57 to -0.73) and anxiety scores (r = -0.56), respectively. 3) Longitudinal change (follow-up minus baseline) in connectivity strength between A5m.R and dlPu.L reflected change in emotional exhaustion score (r = 0.87). Longitudinal changes in strength of connectivities mainly involving parietal lobe were significantly decreased in nurses who developed burnout compared with those who did not. DATA CONCLUSION: In nurses after the onset of burnout, rich club reorganization corresponded to significant reductions in strength of connectivities with different anatomical distances. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder. / é‡åº¦æŠ‘éƒéšœç¢æ‚£è€ ä¸˜è„‘çš®å±‚çŽ¯è·¯çš„åŠ¨æ€åŠŸèƒ½è¿žæŽ¥å¼‚å¸¸.

Thalamocortical circuitry has a substantial impact on emotion and cognition. Previous studies have demonstrated alterations in thalamocortical functional connectivity (FC), characterized by region-dependent hypo- or hyper-connectivity, among individuals with major depressive disorder (MDD). However, the dynamical reconfiguration of the thalamocortical system over time and potential abnormalities in dynamic thalamocortical connectivity associated with MDD remain unclear. Hence, we analyzed dynamic FC (dFC) between ten thalamic subregions and seven cortical subnetworks from resting-state functional magnetic resonance images of 48 patients with MDD and 57 healthy controls (HCs) to investigate time-varying changes in thalamocortical FC in patients with MDD. Moreover, dynamic laterality analysis was conducted to examine the changes in functional lateralization of the thalamocortical system over time. Correlations between the dynamic measures of thalamocortical FC and clinical assessment were also calculated. We identified four dynamic states of thalamocortical circuitry wherein patients with MDD exhibited decreased fractional time and reduced transitions within a negative connectivity state that showed strong correlations with primary cortical networks, compared with the HCs. In addition, MDD patients also exhibited increased fluctuations in functional laterality in the thalamocortical system across the scan duration. The thalamo-subnetwork analysis unveiled abnormal dFC variability involving higher-order cortical networks in the MDD cohort. Significant correlations were found between increased dFC variability with dorsal attention and default mode networks and the severity of symptoms. Our study comprehensively investigated the pattern of alteration of the thalamocortical dFC in MDD patients. The heterogeneous alterations of dFC between the thalamus and both primary and higher-order cortical networks may help characterize the deficits of sensory and cognitive processing in MDD.

Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN.

Currently, significant progress has been made in predicting brain age from structural Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However, despite the valuable structural information they contain, the traditional engineering features known as anatomical features have been largely overlooked in this context. To address this issue, we propose an attention-based network design that integrates anatomical and deep convolutional features, leveraging an anatomical feature attention (AFA) module to effectively capture salient anatomical features. In addition, we introduce a fully convolutional network, which simplifies the extraction of deep convolutional features and overcomes the high computational memory requirements associated with deep learning. Our approach outperforms several widely-used models on eight publicly available datasets (n = 2501), with a mean absolute error (MAE) of 2.20 years in predicting brain age. Comparisons with deep learning models lacking the AFA module demonstrate that our fusion model effectively improves overall performance. These findings provide a promising approach for combining anatomical and deep convolutional features from sMRI data to predict brain age, with potential applications in clinical diagnosis and treatment, particularly for populations with age-related cognitive decline or neurological disorders.

Fine-grained features characterize hippocampal and amygdaloid change pattern in Parkinson's disease and discriminate cognitive-deficit subtype.

AIMS: To extract vertex-wise features of the hippocampus and amygdala in Parkinson's disease (PD) with mild cognitive impairment (MCI) and normal cognition (NC) and further evaluate their discriminatory efficacy. METHODS: High-resolution 3D-T1 data were collected from 68 PD-MCI, 211 PD-NC, and 100 matched healthy controls (HC). Surface geometric features were captured using surface conformal representation, and surfaces were registered to a common template using fluid registration. The statistical tests were performed to detect differences between groups. The disease-discriminatory ability of features was also tested in the ensemble classifiers. RESULTS: The amygdala, not the hippocampus, showed significant overall differences among the groups. Compared with PD-NC, the right amygdala in MCI patients showed expansion (anterior cortical, anterior amygdaloid, and accessory basal areas) and atrophy (basolateral ventromedial area) subregions. There was notable atrophy in the right CA1 and hippocampal subiculum of PD-MCI. The accuracy of classifiers with multivariate morphometry statistics as features exceeded 85%. CONCLUSION: PD-MCI is associated with multiscale morphological changes in the amygdala, as well as subtle atrophy in the hippocampus. These novel metrics demonstrated the potential to serve as biomarkers for PD-MCI diagnosis. Overall, these findings from this study help understand the role of subcortical structures in the neuropathological mechanisms of PD cognitive impairment.

Defect Engineering of 2D Semiconductors for Dual Control of Emission and Carrier Polarity.

2D transition metal dichalcogenides (TMDCs) are considered as promising materials in post-Moore technology. However, the low photoluminescence quantum yields (PLQY) and single carrier polarity due to the inevitable defects during material preparation are great obstacles to their practical applications. Here, an extraordinary defect engineering strategy is reported based on first-principles calculations and realize it experimentally on WS2 monolayers by doping with IIIA atoms. The doped samples with large sizes possess both giant PLQY enhancement and effective carrier polarity modulation. Surprisingly, the high PL emission maintained even after one year under ambient environment. Moreover, the constructed p-n homojunctions shows high rectification ratio (≈2200), ultrafast response times and excellent stability. Meanwhile, the doping strategy is universally applicable to other TMDCs and dopants. This smart defect engineering strategy not only provides a general scheme to eliminate the negative influence of defects, but also utilize them to achieve desired optoelectronic properties for multifunctional applications.