A trailing ribosome speeds up RNA polymerase at the expense of transcript fidelity via force and allostery.

In prokaryotes, translation can occur on mRNA that is being transcribed in a process called coupling. How the ribosome affects the RNA polymerase (RNAP) during coupling is not well understood. Here, we reconstituted the E. coli coupling system and demonstrated that the ribosome can prevent pausing and termination of RNAP and double the overall transcription rate at the expense of fidelity. Moreover, we monitored single RNAPs coupled to ribosomes and show that coupling increases the pause-free velocity of the polymerase and that a mechanical assisting force is sufficient to explain the majority of the effects of coupling. Also, by cryo-EM, we observed that RNAPs with a terminal mismatch adopt a backtracked conformation, while a coupled ribosome allosterically induces these polymerases toward a catalytically active anti-swiveled state. Finally, we demonstrate that prolonged RNAP pausing is detrimental to cell viability, which could be prevented by polymerase reactivation through a coupled ribosome.

Argonaute divides its RNA guide into domains with distinct functions and RNA-binding properties.

MicroRNAs (miRNAs) and small interfering RNAs (siRNAs) guide Argonaute proteins to silence mRNA expression. Argonaute binding alters the properties of an RNA guide, creating functional domains. We show that the domains established by Argonaute-the anchor, seed, central, 3' supplementary, and tail regions-have distinct biochemical properties that explain the differences between how animal miRNAs and siRNAs bind their targets. Extensive complementarity between an siRNA and its target slows the rate at which fly Argonaute2 (Ago2) binds to and dissociates from the target. Highlighting its role in antiviral defense, fly Ago2 dissociates so slowly from extensively complementary target RNAs that essentially every fully paired target is cleaved. Conversely, mouse AGO2, which mainly mediates miRNA-directed repression, dissociates rapidly and with similar rates for fully paired and seed-matched targets. Our data narrow the range of biochemically reasonable models for how Argonaute-bound siRNAs and miRNAs find, bind, and regulate their targets.

Atomic Evolution Mechanism and Suppression of Edge Threading Dislocations in Nitride Remote Heteroepitaxy.

The majority of dislocations in nitride epilayers are edge threading dislocations (TDs), which diminish the performance of nitride devices. However, it is extremely difficult to reduce the edge TDs due to the lack of available slip systems. Here, we systematically investigate the formation mechanism of edge TDs and find that besides originating at the coalescence boundaries, these dislocations are also closely related to geometrical misfit dislocations at the interface. Based on this understanding, we propose a novel strategy to reduce the edge TD density of the GaN epilayer by nearly 1 order of magnitude via graphene-assisted remote heteroepitaxy. The first-principles calculations confirm that the insertion of graphene dramatically reduces the energy barrier required for interfacial sliding, which promotes a new strain release channel. This work provides a unique approach to directly suppress the formation of edge TDs at the source, thereby facilitating the enhanced performance of photoelectronic and electronic devices.

Pulvinar Response Profiles and Connectivity Patterns to Object Domains.

Distributed cortical regions show differential responses to visual objects belonging to different domains varying by animacy (e.g., animals vs tools), yet it remains unclear whether this is an organization principle also applying to the subcortical structures. Combining multiple fMRI activation experiments (two main experiments and six validation datasets; 12 females and 9 males in the main Experiment 1; 10 females and 10 males in the main Experiment 2), resting-state functional connectivity, and task-based dynamic causal modeling analysis in human subjects, we found that visual processing of images of animals and tools elicited different patterns of response in the pulvinar, with robust left lateralization for tools, and distinct, bilateral (with rightward tendency) clusters for animals. Such domain-preferring activity distribution in the pulvinar was associated with the magnitude with which the voxels were intrinsically connected with the corresponding domain-preferring regions in the cortex. The pulvinar-to-right-amygdala path showed a one-way shortcut supporting the perception of animals, and the modulation connection from pulvinar to parietal showed an advantage to the perception of tools. These results incorporate the subcortical regions into the object processing network and highlight that domain organization appears to be an overarching principle across various processing stages in the brain.SIGNIFICANCE STATEMENT Viewing objects belonging to different domains elicited different cortical regions, but whether the domain organization applied to the subcortical structures (e.g., pulvinar) was unknown. Multiple fMRI activation experiments revealed that object pictures belonging to different domains elicited differential patterns of response in the pulvinar, with robust left lateralization for tool pictures, and distinct, bilateral (with rightward tendency) clusters for animals. Combining the resting-state functional connectivity and dynamic causal modeling analysis on task-based fMRI data, we found domain-preferring activity distribution in the pulvinar aligned with that in cortical regions. These results highlight the need for coherent visual theories that explain the mechanisms underlying the domain organization across various processing stages.

Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies.

The human brain is organized as a complex, hierarchical network. However, the structural covariance patterns among brain regions and the underlying biological substrates of such covariance networks remain to be clarified. The present study proposed a novel individualized structural covariance network termed voxel-based texture similarity networks (vTSNs) based on 76 refined voxel-based textural features derived from structural magnetic resonance images. Validated in three independent longitudinal healthy cohorts (40, 23, and 60 healthy participants, respectively) with two common brain atlases, we found that the vTSN could robustly resolve inter-subject variability with high test-retest reliability. In contrast to the regional-based texture similarity networks (rTSNs) that calculate radiomic features based on region-of-interest information, vTSNs had higher inter- and intra-subject variability ratios and test-retest reliability in connectivity strength and network topological properties. Moreover, the Spearman correlation indicated a stronger association of the gene expression similarity network (GESN) with vTSNs than with rTSNs (vTSN: r = 0.600, rTSN: r = 0.433, z = 39.784, P < 0.001). Hierarchical clustering identified 3 vTSN subnets with differential association patterns with 13 coexpression modules, 16 neurotransmitters, 7 electrophysiology, 4 metabolism, and 2 large-scale structural and 4 functional organization maps. Moreover, these subnets had unique biological hierarchical organization from the subcortex-limbic system to the ventral neocortex and then to the dorsal neocortex. Based on 424 unrelated, qualified healthy subjects from the Human Connectome Project, we found that vTSNs could sensitively represent sex differences, especially for connections in the subcortex-limbic system and between the subcortex-limbic system and the ventral neocortex. Moreover, a multivariate variance component model revealed that vTSNs could explain a significant proportion of inter-subject behavioral variance in cognition (80.0 %) and motor functions (63.4 %). Finally, using 494 healthy adults (aged 19-80 years old) from the Southwest University Adult Lifespan Dataset, the Spearman correlation identified a significant association between aging and vTSN strength, especially within the subcortex-limbic system and between the subcortex-limbic system and the dorsal neocortex. In summary, our proposed vTSN is robust in uncovering individual variability and neurobiological brain processes, which can serve as biologically plausible measures for linking biological processes and human behavior.

Pain-Discriminating Information Decoded From Spatiotemporal Patterns of Hemodynamic Responses Measured by fMRI in the Human Brain.

Functional magnetic resonance imaging (fMRI) has been widely used in studying the neural mechanisms of pain in the human brain, primarily focusing on where in the brain pain-elicited neural activities occur (i.e., the spatial distribution of pain-related brain activities). However, the temporal dynamics of pain-elicited hemodynamic responses (HDRs) measured by fMRI may also contain information specific to pain processing but have been largely neglected. Using high temporal resolution fMRI (TR = 0.8 s) data acquired from 62 healthy participants, in the present study we aimed to test whether pain-distinguishing information could be decoded from the spatial pattern of the temporal dynamics (i.e., the spatiotemporal pattern) of HDRs elicited by painful stimuli. Specifically, the peak latency and the response duration were used to characterize the temporal dynamics of HDRs to painful laser stimuli and non-painful electric stimuli, and then were compared between the two conditions (i.e., pain and no-pain) using a voxel-wise univariate analysis and a multivariate pattern analysis. Furthermore, we also tested whether the two temporal characteristics of pain-elicited HDRs and their spatial patterns were associated with pain-related behaviors. We found that the spatial patterns of HDR peak latency and response duration could successfully discriminate pain from no-pain. Interestingly, we also observed that the Pain Vigilance and Awareness Questionnaire (PVAQ) scores were correlated with the average response duration in bilateral insula and secondary somatosensory cortex (S2) and could also be predicted from the across-voxel spatial patterns of response durations in the middle cingulate cortex and middle frontal gyrus only during painful condition but not during non-painful condition. These findings indicate that the spatiotemporal pattern of pain-elicited HDRs may contain pain-specific information and highlight the importance of studying the neural mechanisms of pain by taking advantage of the high sensitivity of fMRI to both spatial and temporal information of brain responses.

Environmental neuroscience linking exposome to brain structure and function underlying cognition and behavior.

Individual differences in human brain structure, function, and behavior can be attributed to genetic variations, environmental exposures, and their interactions. Although genome-wide association studies have identified many genetic variants associated with brain imaging phenotypes, environmental exposures associated with these phenotypes remain largely unknown. Here, we propose that environmental neuroscience should pay more attention on exploring the associations between lifetime environmental exposures (exposome) and brain imaging phenotypes and identifying both cumulative environmental effects and their vulnerable age windows during the life course. Exposome-neuroimaging association studies face several challenges including the accurate measurement of the totality of environmental exposures varied in space and time, the highly correlated structure of the exposome, and the lack of standardized approaches for exposome-wide association studies. By agnostically scanning the effects of environmental exposures on brain imaging phenotypes and their interactions with genomic variations, exposome-neuroimaging association analyses will improve our understanding of causal factors associated with individual differences in brain structure and function as well as their relations with cognitive abilities and neuropsychiatric disorders.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Preoperative prediction of disease-free survival in pancreatic ductal adenocarcinoma patients after R0 resection using contrast-enhanced CT and CA19-9.

OBJECTIVES: To investigate the efficiency of a combination of preoperative contrast-enhanced computed tomography (CECT) and carbohydrate antigen 19-9 (CA19-9) in predicting disease-free survival (DFS) after R0 resection of pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 138 PDAC patients who underwent curative R0 resection were retrospectively enrolled and allocated chronologically to training (n = 91, January 2014-July 2019) and validation cohorts (n = 47, August 2019-December 2020). Using univariable and multivariable Cox regression analyses, we constructed a preoperative clinicoradiographic model based on the combination of CECT features and serum CA19-9 concentrations, and validated it in the validation cohort. The prognostic performance was evaluated and compared with that of postoperative clinicopathological and tumor-node-metastasis (TNM) models. Kaplan-Meier analysis was conducted to verify the preoperative prognostic stratification performance of the proposed model. RESULTS: The preoperative clinicoradiographic model included five independent prognostic factors (tumor diameter on CECT > 4 cm, extrapancreatic organ infiltration, CECT-reported lymph node metastasis, peripheral enhancement, and preoperative CA19-9 levels > 180 U/mL). It better predicted DFS than did the postoperative clinicopathological (C-index, 0.802 vs. 0.787; p < 0.05) and TNM (C-index, 0.802 vs. 0.711; p < 0.001) models in the validation cohort. Low-risk patients had significantly better DFS than patients at the high-risk, defined by the model preoperatively (p < 0.001, training cohort; p < 0.01, validation cohort). CONCLUSIONS: The clinicoradiographic model, integrating preoperative CECT features and serum CA19-9 levels, helped preoperatively predict postsurgical DFS for PDAC and could facilitate clinical decision-making. CLINICAL RELEVANCE STATEMENT: We constructed a simple model integrating clinical and radiological features for the prediction of disease-free survival after curative R0 resection in patients with pancreatic ductal adenocarcinoma; this novel model may facilitate preoperative identification of patients at high risk of recurrence and metastasis that may benefit from neoadjuvant treatments. KEY POINTS: • Existing clinicopathological predictors for prognosis in pancreatic ductal adenocarcinoma (PDAC) patients who underwent R0 resection can only be ascertained postoperatively and do not allow preoperative prediction. • We constructed a clinicoradiographic model, using preoperative contrast-enhanced computed tomography (CECT) features and preoperative carbohydrate antigen 19-9 (CA19-9) levels, and presented it as a nomogram. • The presented model can predict disease-free survival (DFS) in patients with PDAC better than can postoperative clinicopathological or tumor-node-metastasis (TNM) models.

TMSCl-Promoted Sulfonylation of Propargylic Alcohols with Sodium Sulfinates for the Construction of (E)-1,3-Disulfonylpropenes and (E)-1-Sulfonylpropenols.

A direct and novel transformation of propargylic alcohols with sodium sulfinates for the regio- and stereoselective synthesis of (E)-1,3-disulfonylpropenes and (E)-1-sulfonylpropenols was successfully developed in the presence of TMSCl under mild conditions. The preliminary mechanistic experiments demonstrated that the reaction underwent an unprecedented dual nucleophilic substitution/radical addition process, in which sodium sulfinates were used not only as nucleophiles but also as a sulfonyl radical source.

TFA-Promoted Cascade Sulfonylation/Rearrangement/Cyclization of 1,5-Diynols and Sodium Sulfinates to Construct Sulfonylated Benzo[b]fluorenes.

A novel conversion of 1,5-diynols into sulfonylated benzo[b]fluorenes is reported by a TFA-promoted cascade cyclization with sodium sulfinates under mild conditions. This strategy provides an efficient and practical approach for accessing various sulfonated benzo[b]fluorenes in moderate to excellent yields under metal-free conditions. On the basis of the control experimental results and density functional theory calculations, a possible cascade transformation mechanism consisting of the dehydration of propargylic alcohols, sulfonylation, allenylation, and Schmittel-type cyclization is proposed. It is worth noting that TFA played an important role in this cascade cyclization, which promoted C-SO2R bond cleavage in a propargylic sulfone intermediate to form allenyl sulfones, followed by Schmittel-type cyclization to give the target product.

Mapping cerebral atrophic trajectory from amnestic mild cognitive impairment to Alzheimer's disease.

Alzheimer's disease (AD) patients suffer progressive cerebral atrophy before dementia onset. However, the region-specific atrophic processes and the influences of age and apolipoprotein E (APOE) on atrophic trajectory are still unclear. By mapping the region-specific nonlinear atrophic trajectory of whole cerebrum from amnestic mild cognitive impairment (aMCI) to AD based on longitudinal structural magnetic resonance imaging data from Alzheimer's disease Neuroimaging Initiative (ADNI) database, we unraveled a quadratic accelerated atrophic trajectory of 68 cerebral regions from aMCI to AD, especially in the superior temporal pole, caudate, and hippocampus. Besides, interaction analyses demonstrated that APOE ε4 carriers had faster atrophic rates than noncarriers in 8 regions, including the caudate, hippocampus, insula, etc.; younger patients progressed faster than older patients in 32 regions, especially for the superior temporal pole, hippocampus, and superior temporal gyrus; and 15 regions demonstrated complex interaction among age, APOE, and disease progression, including the caudate, hippocampus, etc. (P < 0.05/68, Bonferroni correction). Finally, Cox proportional hazards regression model based on the identified region-specific biomarkers could effectively predict the time to AD conversion within 10 years. In summary, cerebral atrophic trajectory mapping could help a comprehensive understanding of AD development and offer potential biomarkers for predicting AD conversion.

A novel entity of HIPK2::YAP1 pulmonary fibromatosis.

BACKGROUND: Pulmonary fibromatosis (PF) is a specific variant of fibromatosis, which is rarely reported occurring in the lung. PF with HIPK2-YAP1 fusion was a novel entity. CASE PRESENTATION: In this report, a 66-year-old male with PF had been smoking over 40 years. Multiple cords and small nodules in both lungs had been detected in a health examination two years earlier at our hospital. But approximately twofold enlarged in the lingual segment of the upper lobe in the left lung were disclosed in this year. Immunohistochemical analysis demonstrated that the vimentin and ß-Catenin were positive in the largest nodule. After underwent a DNA/RNA panel next-generation sequencing (NGS), missense mutations and HIPK2-YAP1 fusion were found in this sample. Ultimately, the case diagnosis as PF with HIPK2-YAP1 fusion after multidisciplinary treatment. Currently, the patient is doing well and recurrence-free at 14 months post-surgery. CONCLUSIONS: It's difficult for patients with complex morphology to make accurate diagnosis solely based on morphology and immunohistochemistry. But molecular detection is an effective method for further determining pathological subtypes.

An equivalent source method for acoustic problems with thermoviscous effects.

This paper presents an equivalent source method (ESM) for analyzing sound propagation in small-scale acoustic structures with thermoviscous effects. The formulations that describe the thermal, viscous, and acoustic modes for thermoviscous acoustic problems are introduced. The concept of ESM is then applied to solve these formulations, resulting in an efficient numerical computation and implementation procedure. Based on two different strategies, the obtained ESM formulations are coupled at the boundary using the isothermal, non-slip, and null-divergence conditions. The coupling based on the first strategy is efficient for solving thermoviscous acoustic problems with few matrices required. However, this procedure faces the evaluation of the tangential derivatives of the boundary velocity. Coupling the ESM formulations directly for each component of the total particle velocity at the boundary has no such problem, which leads to the second strategy. However, it entails a larger memory usage compared to the former. Additionally, the coupled finite element method (FEM)-ESM formulations based on the above strategies are developed for acoustic-structural interaction. The validity of the presented ESM formulations is demonstrated through benchmark examples, and that of the coupled FEM-ESM formulation is illustrated by the numerical analysis of a simplified microphone.

Analytical method for studying acoustic fields radiated by general spherical sound sources in thermoviscous fluids.

The study of acoustic radiation from spherical sound sources plays a crucial role in understanding the thermoviscous effects in practical acoustic problems. However, finding a general solution of acoustic radiation from spherical sound sources in thermoviscous fluids remains a formidable challenge. To advance this issue, an analytical method is developed in this paper to calculate the acoustic field radiated by spherical sound sources with the isothermal boundary condition and arbitrary velocity boundary condition. The developed method is utilized to present the solutions of the acoustic field generated by an oscillating sphere and a general spherical sound source, and the accuracy and validity of these solutions are verified through analytical and numerical methods.

Systematic investigation of cerebellar functional alterations and their association with surgical outcomes in patients with degenerative cervical myelopathy: a resting-state fMRI study.

OBJECTIVE: The aim of this study was to systematically investigate the changes in cerebellar neural activity and cerebellar-cortical functional connectivity (FC) in patients with degenerative cervical myelopathy (DCM) using resting-state functional magnetic resonance imaging (fMRI). METHODS: In this study, we collected clinical data and resting-state fMRI data from 54 DCM patients and 50 healthy controls (HCs). We analyzed voxel-wise regional fMRI metrics, including amplitude of low frequency fluctuation (ALFF), fractional ALFF, regional homogeneity, functional connectivity density, and voxel-mirrored homotopic connectivity. In analysis 1, we examined the differences in regional fMRI metrics within the cerebellum between the DCM patient group and the healthy control group, as well as their correlation with preoperative neurological status and prognosis. In analysis 2, we investigated cerebellar-cortical functional connectivity differences between the two groups and their correlation with preoperative neurological status and prognosis. Lastly, in analysis 3, we explored the internetwork connectivity between the 'cerebellar-SMN' (sensorimotor network) system, examined the between-group differences, and investigated its correlation with preoperative neurological status and prognosis. RESULTS: (1) Relative to HCs, DCM patients exhibited functional alterations in wide-spread cerebellar regions; (2) DCM patients exhibited altered cerebellar-cortical FC which was associated with the preoperative neurological status and prognosis; (3) DCM patients exhibited altered internetwork connectivity between 'cerebellar-SMN' system which was associated with duration of symptom. CONCLUSION: Wide-spread cerebellar functional alterations occur in DCM pathogenesis and the deficits in cerebellar-SMN functional connectivity may be beneficial in future studies for predicting surgical outcomes in patients with DCM.

Analysis of the potential profile and influencing factors for oral frailty in olderly patients with dental implants.

OBJECTIVE: To investigate the current state of oral frailty in oldely patients with require dental implants, analyze influencing factors in the characteristics of oral frailty across different patient categories, and provide a reference for clinical staff to identify high-risk groups and develop proactive management strategies. METHODS: Between January 2024 and March 2024, 654 patients with dental implants were selected using convenience sampling from six secondary and tertiary stomatological hospitals in Jiangsu and Zhejiang provinces. Data were collected via a general information questionnaire and the Oral Frailty Index-8. The latent profiles of oral frailty were examined, and univariate and Logistic regression analyses were conducted to determine the impact of various factors on these profiles. RESULTS: In this cross-sectional study, 605 valid questionnaires were returned, yielding an effective rate of 92.58%. The mean oral frailty score was 6.64 ± 1.21, with the sample comprising 223 males and 382 females, averaging 72.54 ± 6.33 years old. Oral frailty was categorized into three latent profiles: high (20.50%), moderate (53.72%), and low (25.78%) frailty groups. Factor analysis indicated that age, gender, education level, family income, number of implants, and dyslipidemia significantly predicted the classification of these profiles (P < 0.05). CONCLUSION: Oral frailty in oldely patients with dental implants exhibits heterogeneity and is influenced by age, sex, education level, family income, number of implants, and dyslipidemia. Clinical staff should recognize the characteristics of different patient categories and implement proactive measures for those at high risk of oral frailty to enhance their quality of life.

Both fine-grained and coarse-grained spatial patterns of neural activity measured by functional MRI show preferential encoding of pain in the human brain.

How pain emerges from human brain remains an unresolved question in pain neuroscience. Neuroimaging studies have suggested that all brain areas activated by painful stimuli were also activated by tactile stimuli, and vice versa. Nonetheless, pain-preferential spatial patterns of voxel-level activation in the brain have been observed when distinguishing painful and tactile brain activations using multivariate pattern analysis (MVPA). According to two hypotheses, the neural activity pattern preferentially encoding pain could exist at a global, coarse-grained, regional level, corresponding to the "pain connectome" hypothesis proposing that pain-preferential information may be encoded by the synchronized activity across multiple distant brain regions, and/or exist at a local, fine-grained, voxel level, corresponding to the "intermingled specialized/preferential neurons" hypothesis proposing that neurons responding specially or preferentially to pain could be present and intermingled with non-pain neurons within a voxel. Here, we systematically investigated the spatial scales of pain-distinguishing information in the human brain measured by fMRI using machine learning techniques, and found that pain-distinguishing information could be detected at both coarse-grained spatial scales across widely distributed brain regions and fine-grained spatial scales within many local areas. Importantly, the spatial distribution of pain-distinguishing information in the brain varies across individuals and such inter-individual variations may be related to a person's trait about pain perception, particularly the pain vigilance and awareness. These results provide new insights into the longstanding question of how pain is represented in the human brain and help the identification of characteristic neuroimaging measurements of pain.

MRAß: A multimodal MRI-derived amyloid-ß biomarker for Alzheimer's disease.

Florbetapir 18 F (AV45), a highly sensitive and specific positron emission tomographic (PET) molecular biomarker binding to the amyloid-ß of Alzheimer's disease (AD), is constrained by radiation and cost. We sought to combat it by combining multimodal magnetic resonance imaging (MRI) images and a collaborative generative adversarial networks model (CollaGAN) to develop a multimodal MRI-derived Amyloid-ß (MRAß) biomarker. We collected multimodal MRI and PET AV45 data of 380 qualified participants from the ADNI dataset and 64 subjects from OASIS3 dataset. A five-fold cross-validation CollaGAN were applied to generate MRAß. In the ADNI dataset, we found MRAß could characterize the subject-level AV45 spatial variations in both AD and mild cognitive impairment (MCI). Voxel-wise two-sample t-tests demonstrated amyloid-ß depositions identified by MRAß in AD and MCI were significantly higher than healthy controls (HCs) in widespread cortices (p < .05, corrected) and were much similar to those by AV45 (r > .92, p < .001). Moreover, a 3D ResNet classifier demonstrated that MRAß was comparable to AV45 in discriminating AD from HC in both the ADNI and OASIS3 datasets, and in discriminate MCI from HC in ADNI. Finally, we found MRAß could mimic cortical hyper-AV45 in HCs who later converted to MCI (r = .79, p < .001) and was comparable to AV45 in discriminating them from stable HC (p > .05). In summary, our work illustrates that MRAß synthesized by multimodal MRI could mimic the cerebral amyloid-ß depositions like AV45 and lends credence to the feasibility of advancing MRI toward molecular-explainable biomarkers.

Unraveling schizophrenia replicable functional connectivity disruption patterns across sites.

Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal-based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site-effect correction methods in removing the site-related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site-related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo-connectivity within sensory areas (Net1), hypo-connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper-connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet-specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out-of-sample public data set (Z = -1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet-specific composite FC measures might be replicable neuroimaging markers for schizophrenia.