Temporal regulation of MDA5 inactivation by Caspase-3 dependent cleavage of 14-3-3η.

The kinetics of type I interferon (IFN) induction versus the virus replication compete, and the result of the competition determines the outcome of the infection. Chaperone proteins that involved in promoting the activation kinetics of PRRs rapidly trigger antiviral innate immunity. We have previously shown that prior to the interaction with MAVS to induce type I IFN, 14-3-3η facilitates the oligomerization and intracellular redistribution of activated MDA5. Here we report that the cleavage of 14-3-3η upon MDA5 activation, and we identified Caspase-3 activated by MDA5-dependent signaling was essential to produce sub-14-3-3η lacking the C-terminal helix (αI) and tail. The cleaved form of 14-3-3η (sub-14-3-3η) could strongly interact with MDA5 but could not support MDA5-dependent type I IFN induction, indicating the opposite functions between the full-length 14-3-3η and sub-14-3-3η. During human coronavirus or enterovirus infections, the accumulation of sub-14-3-3η was observed along with the activation of Caspase-3, suggesting that RNA viruses may antagonize 14-3-3η by promoting the formation of sub-14-3-3η to impair antiviral innate immunity. In conclusion, sub-14-3-3η, which could not promote MDA5 activation, may serve as a negative feedback to return to homeostasis to prevent excessive type I IFN production and unnecessary inflammation.

Detection of individual brain tau deposition in Alzheimer's disease based on latent feature-enhanced generative adversarial network.

OBJECTIVE: The conventional methods for interpreting tau PET imaging in Alzheimer's disease (AD), including visual assessment and semi-quantitative analysis of fixed hallmark regions, are insensitive to detect individual small lesions because of the spatiotemporal neuropathology's heterogeneity. In this study, we proposed a latent feature-enhanced generative adversarial network model for the automatic extraction of individual brain tau deposition regions. METHODS: The latent feature-enhanced generative adversarial network we propose can learn the distribution characteristics of tau PET images of cognitively normal individuals and output the abnormal distribution regions of patients. This model was trained and validated using 1131 tau PET images from multiple centres (with distinct races, i.e., Caucasian and Mongoloid) with different tau PET ligands. The overall quality of synthetic imaging was evaluated using structural similarity (SSIM), peak signal to noise ratio (PSNR), and mean square error (MSE). The model was compared to the fixed templates method for diagnosing and predicting AD. RESULTS: The reconstructed images archived good quality, with SSIM = 0.967 ± 0.008, PSNR = 31.377 ± 3.633, and MSE = 0.0011 ± 0.0007 in the independent test set. The model showed higher classification accuracy (AUC = 0.843, 95 % CI = 0.796-0.890) and stronger correlation with clinical scales (r = 0.508, P < 0.0001). The model also achieved superior predictive performance in the survival analysis of cognitive decline, with a higher hazard ratio: 3.662, P < 0.001. INTERPRETATION: The LFGAN4Tau model presents a promising new approach for more accurate detection of individualized tau deposition. Its robustness across tracers and races makes it a potentially reliable diagnostic tool for AD in practice.

Characterization of tau propagation pattern and cascading hypometabolism from functional connectivity in Alzheimer's disease.

Tau pathology and its spatial propagation in Alzheimer's disease (AD) play crucial roles in the neurodegenerative cascade leading to dementia. However, the underlying mechanisms linking tau spreading to glucose metabolism remain elusive. To address this, we aimed to examine the association between pathologic tau aggregation, functional connectivity, and cascading glucose metabolism and further explore the underlying interplay mechanisms. In this prospective cohort study, we enrolled 79 participants with 18F-Florzolotau positron emission tomography (PET), 18F-fluorodeoxyglucose PET, resting-state functional, and anatomical magnetic resonance imaging (MRI) images in the hospital-based Shanghai Memory Study. We employed generalized linear regression and correlation analyses to assess the associations between Florzolotau accumulation, functional connectivity, and glucose metabolism in whole-brain and network-specific manners. Causal mediation analysis was used to evaluate whether functional connectivity mediates the association between pathologic tau and cascading glucose metabolism. We examined 22 normal controls and 57 patients with AD. In the AD group, functional connectivity was associated with Florzolotau covariance (ß = .837, r = 0.472, p < .001) and glucose covariance (ß = 1.01, r = 0.499, p < .001). Brain regions with higher tau accumulation tend to be connected to other regions with high tau accumulation through functional connectivity or metabolic connectivity. Mediation analyses further suggest that functional connectivity partially modulates the influence of tau accumulation on downstream glucose metabolism (mediation proportion: 49.9%). Pathologic tau may affect functionally connected neurons directly, triggering downstream glucose metabolism changes. This study sheds light on the intricate relationship between tau pathology, functional connectivity, and downstream glucose metabolism, providing critical insights into AD pathophysiology and potential therapeutic targets.

International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

PURPOSE: Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging. METHOD: A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting. CONCLUSION: This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.

Visual reading for [18F]Florzolotau Tau PET scans in progressive supranuclear palsy.

PURPOSE: The identification of tau accumulation within living brains holds significant potential in facilitating accurate diagnosis of progressive supranuclear palsy (PSP). While visual assessment is frequently employed, standardized methods for tau positron emission tomography (PET) specifically in PSP are absent. We aimed to develop a visual reading algorithm dedicated to the evaluation of [18F]Florzolotau PET in PSP. METHODS: 148 PSP and 30 healthy volunteers were divided into a development set (for the establishment of the reading rules; n = 89) and a testing set (for the validation of the reading rules; n = 89). For differential diagnosis, 55 α-synucleinopathies were additionally included into the testing set. The visual reading method was established by an experienced assessor (Reader 0) and was then validated by Reader 0 and two additional readers on regional and overall binary manners. A positive binding in both midbrain and globus pallidus/putamen regions was characterized as a PSP-like pattern, whereas any other pattern was classified as non-PSP-like. RESULTS: Reader 1 (94.4%) and Reader 2 (93.8%) showed excellent agreement for the overall binary determination against Reader 0. The regional binary determinations of midbrain and globus pallidus/putamen showed excellent agreement among readers (kappa > 0.80). The overall binary evaluation demonstrated reproducibility of 86.1%, 94.4% and 77.8% for three readers. The visual reading algorithm showed high agreement with regional standardized uptake value ratios and clinical diagnoses. CONCLUSION: Through the application of the suggested visual reading algorithm, [18F]Florzorotau PET imaging demonstrated a robust performance for the imaging diagnosis of PSP.

Effects of brain radiotherapy strategies on survival in the era of MRI for patients with limited stage small cell lung cancer.

BACKGROUND AND PURPOSE: In the context of the widespread availability of magnetic resonance imaging (MRI) and aggressive salvage irradiation techniques, there has been controversy surrounding the use of prophylactic cranial irradiation (PCI) for small-cell lung cancer (SCLC) patients. This study aimed to explore whether regular brain MRI plus salvage brain irradiation (SBI) is not inferior to PCI in patients with limited-stage SCLC (LS-SCLC). METHODS: This real-world multicenter study, which was conducted between January 2014 and September 2020 at three general hospitals, involved patients with LS-SCLC who had a good response to initial chemoradiotherapy and no brain metastasis confirmed by MRI. Overall survival (OS) was compared between patients who did not receive PCI for various reasons but chose regular MRI surveillance and followed salvage brain irradiation (SBI) when brain metastasis was detected and patients who received PCI. RESULTS: 120 patients met the inclusion criteria. 55 patients received regular brain MRI plus SBI (SBI group) and 65 patients received PCI (PCI group). There was no statistically significant difference in median OS between the two groups (27.14 versus 33.00 months; P = 0.18). In the SBI group, 32 patients underwent whole brain radiotherapy and 23 patients underwent whole brain radiotherapy + simultaneous integrated boost. On multivariate analysis, only extracranial metastasis was independently associated with poor OS in the SBI group. CONCLUSION: The results of this real-world study showed that MRI surveillance plus SBI is not inferior to PCI in OS for LS-SCLC patients who had a good response to initial chemoradiotherapy.

Using interpretable deep learning radiomics model to diagnose and predict progression of early AD disease spectrum: a preliminary [18F]FDG PET study.

OBJECTIVES: In this study, we propose an interpretable deep learning radiomics (IDLR) model based on [18F]FDG PET images to diagnose the clinical spectrum of Alzheimer's disease (AD) and predict the progression from mild cognitive impairment (MCI) to AD. METHODS: This multicentre study included 1962 subjects from two ethnically diverse, independent cohorts (a Caucasian cohort from ADNI and an Asian cohort merged from two hospitals in China). The IDLR model involved feature extraction, feature selection, and classification/prediction. We evaluated the IDLR model's ability to distinguish between subjects with different cognitive statuses and MCI trajectories (sMCI and pMCI) and compared results with radiomic and deep learning (DL) models. A Cox model tested the IDLR signature's predictive capability for MCI to AD progression. Correlation analyses identified critical IDLR features and verified their clinical diagnostic value. RESULTS: The IDLR model achieved the best classification results for subjects with different cognitive statuses as well as in those with MCI with distinct trajectories, with an accuracy of 76.51% [72.88%, 79.60%], (95% confidence interval, CI) while those of radiomic and DL models were 69.13% [66.28%, 73.12%] and 73.89% [68.99%, 77.89%], respectively. According to the Cox model, the hazard ratio (HR) of the IDLR model was 1.465 (95% CI: 1.236-1.737, p < 0.001). Moreover, three crucial IDLR features were significantly different across cognitive stages and were significantly correlated with cognitive scale scores (p < 0.01). CONCLUSIONS: Preliminary results demonstrated that the IDLR model based on [18F]FDG PET images enhanced accuracy in diagnosing the clinical spectrum of AD. KEY POINTS: Question The study addresses the lack of interpretability in existing DL classification models for diagnosing the AD spectrum. Findings The proposed interpretable DL radiomics model, using radiomics-supervised DL features, enhances interpretability from traditional DL models and improves classification accuracy. Clinical relevance The IDLR model interprets DL features through radiomics supervision, potentially advancing the application of DL in clinical classification tasks.

Diagnostic and prognostic nomograms for laryngeal carcinoma patients with lung metastasis: a SEER-based study.

PURPOSE: To establish two nomograms to quantify the risk of lung metastasis (LM) in laryngeal carcinoma (LC) and predict the overall survival of LC patients with LM. METHODS: Totally 9515 LC patients diagnosed histologically from 2000 to 2019 were collected from the Surveillance, Epidemiology, and End Results database. The independent diagnostic factors for LM in LC patients and prognostic factors for LC patients with LM were identified by logistic and Cox regression analysis, respectively. Nomograms were established based on regression coefficients and evaluated by receiver operating characteristic curve, calibration curves, and decision curve analysis. RESULTS: Patients with supraglottis, higher pathological grade, higher N stage, and distant metastasis (bone, brain, or liver) were more likely to have LM (P < 0.05). Chemotherapy, surgery and radiotherapy were independent factors of the overall survival of LC patients with LM (P < 0.05). The area under curve of diagnostic nomogram were 0.834 and 0.816 in the training and validation cohort respectively. For the prognostic nomogram, the area under curves of 1-, 2-, and 3-years were 0.735, 0.734, and 0.709 in the training cohort and 0.705, 0.803, and 0.809 in the validation cohort. The calibration curves and decision curve analysis indicated good performance of the nomograms. CONCLUSION: Distant metastasis (bone, brain, or liver) and N stage should be considered for prediction of LM in LC patients. Chemotherapy is the most significant influencing prognostic factor improving the survival of LC patients with LM. Two nomograms may benefit for providing better precautionary measures and treatment decision.

Pilot implementation of the revised criteria for staging of Alzheimer's disease by the Alzheimer's Association Workgroup in a tertiary memory clinic.

INTRODUCTION: We aimed to evaluate the feasibility of the 2024 Alzheimer's Association Workgroup's integrated clinical-biological staging scheme in outpatient settings within a tertiary memory clinic. METHODS: The 2018 syndromal cognitive staging system, coupled with a binary biomarker classification, was implemented for 236 outpatients with cognitive concerns. The 2024 numeric clinical staging framework, incorporating biomarker staging, was specifically applied to 154 individuals within the Alzheimer's disease (AD) continuum. RESULTS: The 2024 staging scheme accurately classified 95.5% AD. Among these, 56.5% exhibited concordant clinical and biological stages (canonical), 34.7% demonstrated more advanced clinical stages than biologically expected (susceptible), and 8.8% displayed the inverse pattern (resilient). The susceptible group was characterized by a higher burden of neurodegeneration and inflammation than anticipated from tau, whereas the resilient group showed the opposite. DISCUSSION: The 2024 staging scheme is generally feasible. A discrepancy between clinical and biological stages is relatively frequent among symptomatic patients with AD. HIGHLIGHTS: The 2024 AA staging scheme is generally feasible in a tertiary memory clinic. A discrepancy between clinical and biological stages is relatively frequent in AD. The mismatch may be influenced by a non-specific pathological process involved in AD. Individual profiles like aging and lifestyles may contribute to such a mismatch. Matched and mismatched cases converge toward similar clinical outcomes.

Gasdermin E mediates photoreceptor damage by all-trans-retinal in the mouse retina.

The breakdown of all-trans-retinal (atRAL) clearance is closely associated with photoreceptor cell death in dry age-related macular degeneration (AMD) and autosomal recessive Stargardt's disease (STGD1), but its mechanisms remain elusive. Here, we demonstrate that activation of gasdermin E (GSDME) but not gasdermin D promotes atRAL-induced photoreceptor damage by activating pyroptosis and aggravating apoptosis through a mitochondria-mediated caspase-3-dependent signaling pathway. Activation of c-Jun N-terminal kinase was identified as one of the major causes of mitochondrial membrane rupture in atRAL-loaded photoreceptor cells, resulting in the release of cytochrome c from mitochondria to the cytosol, where it stimulated caspase-3 activation required for cleavage of GSDME. Aggregation of the N-terminal fragment of GSDME in the mitochondria revealed that GSDME was likely to penetrate mitochondrial membranes in photoreceptor cells after atRAL exposure. ABC (subfamily A, member 4) and all-trans-retinol dehydrogenase 8 are two key proteins responsible for clearing atRAL in the retina. Abca4-/-Rdh8-/- mice exhibit serious defects in atRAL clearance upon light exposure and serve as an acute model for dry AMD and STGD1. We found that N-terminal fragment of GSDME was distinctly localized in the photoreceptor outer nuclear layer of light-exposed Abca4-/-Rdh8-/- mice. Of note, degeneration and caspase-3 activation in photoreceptors were significantly alleviated in Abca4-/-Rdh8-/-Gsdme-/- mice after exposure to light. The results of this study indicate that GSDME is a common causative factor of photoreceptor pyroptosis and apoptosis arising from atRAL overload, suggesting that repressing GSDME may represent a potential treatment of photoreceptor atrophy in dry AMD and STGD1.

18F-Florzolotau PET imaging captures the distribution patterns and regional vulnerability of tau pathology in progressive supranuclear palsy.

PURPOSE: Human post mortem studies have described the topographical patterns of tau pathology in progressive supranuclear palsy (PSP). Recent advances in tau PET tracers are expected to herald the next era of PSP investigation for early detection of tau pathology in living brains. This study aimed to investigate whether 18F-Florzolotau PET imaging may capture the distribution patterns and regional vulnerability of tau pathology in PSP, and to devise a novel image-based staging system. METHODS: The study cohort consisted of 148 consecutive patients with PSP who had undergone 18F-Florzolotau PET imaging. The PSP rating scale (PSPrs) was used to measure disease severity. Similarities and differences of tau deposition among different clinical phenotypes were examined at the regional and voxel levels. An 18F-Florzolotau pathological staging system was devised according to the scheme originally developed for post mortem data. In light of conditional probabilities for the sequence of events, an 18F-Florzolotau modified staging system by integrating clusters at the regional level was further developed. The ability of 18F-Florzolotau staging systems to reflect disease severity in terms of PSPrs score was assessed by analysis of variance. RESULTS: The distribution patterns of 18F-Florzolotau accumulation in living brains of PSP showed a remarkable similarity to those reported in post mortem studies, with the binding intensity being markedly higher in Richardson's syndrome. Moreover, 18F-Florzolotau PET imaging allowed detecting regional vulnerability and tracking tau accumulation in an earlier fashion compared with post mortem immunostaining. The 18F-Florzolotau staging systems were positively correlated with clinical severity as reflected by PSPrs scores. CONCLUSIONS: 18F-Florzolotau PET imaging can effectively capture the distribution patterns and regional vulnerability of tau pathology in PSP. The 18F-Florzolotau modified staging system holds promise for early tracking of tau deposition in living brains.

18 F-Florzolotau Positron Emission Tomography Imaging of Tau Pathology in the Living Brains of Patients with Corticobasal Syndrome.

BACKGROUND: Recent development in tau-sensitive tracers has sparkled significant interest in tracking tauopathies using positron emission tomography (PET) biomarkers. However, the ability of 18 F-florzolotau PET imaging to topographically characterize tau pathology in corticobasal syndrome (CBS) remains unclear. Further, the question as to whether disease-level differences exist with other neurodegenerative tauopathies is still unanswered. OBJECTIVE: To analyze the topographical patterns of tau pathology in the living brains of patients with CBS using 18 F-florzolotau PET imaging and to examine whether differences with other tauopathies exist. METHODS: 18 F-florzolotau PET imaging was performed in 20 consecutive patients with CBS, 20 cognitively healthy controls (HCs), 20 patients with Alzheimer's disease (AD), and 16 patients with progressive supranuclear palsy-Richardson's syndrome (PSP-RS). Cerebrospinal fluid (CSF) levels of ß-amyloid biomarkers were quantified in all patients with CBS. 18 F-florzolotau uptake was quantitatively assessed using standardized uptake value ratios. RESULTS: Of the 20 patients with CBS, 19 (95%) were negative for CSF biomarkers of amyloid pathology; of them, three had negative 18 F-florzolotau PET findings. Compared with HCs, patients with CBS showed increased 18 F-florzolotau signals in both cortical and subcortical regions. In addition, patients with CBS were characterized by higher tracer retentions in subcortical regions compared with those with AD and showed a trend toward higher signals in cortical areas compared with PSP-RS. An asymmetric pattern of 18 F-florzolotau uptake was associated with an asymmetry of motor severity in patients with CBS. CONCLUSIONS: In vivo 18 F-florzolotau PET imaging holds promise for distinguishing CBS in the spectrum of neurodegenerative tauopathies. © 2023 International Parkinson and Movement Disorder Society.

Feasibility of 18F-florzolotau quantification in patients with Alzheimer's disease based on an MRI-free tau PET template.

OBJECTIVES: Quantification of tau accumulation using positron emission tomography (PET) is critical for the diagnosis of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of 18F-florzolotau quantification in patients with AD using a magnetic resonance imaging (MRI)-free tau PET template, since individual high-resolution MRI is costly and not always available in practice. METHODS: 18F-florzolotau PET and MRI scans were obtained in a discovery cohort including (1) patients within the AD continuum (n = 87), (2) cognitively impaired patients with non-AD (n = 32), and (3) cognitively unimpaired subjects (n = 26). The validation cohort comprised 24 patients with AD. Following MRI-dependent spatial normalization (standard approach) in randomly selected subjects (n = 40) to cover the entire spectrum of cognitive function, selected PET images were averaged to create the 18F-florzolotau-specific template. Standardized uptake value ratios (SUVRs) were calculated in five predefined regions of interest (ROIs). MRI-free and MRI-dependent methods were compared in terms of continuous and dichotomous agreement, diagnostic performances, and associations with specific cognitive domains. RESULTS: MRI-free SUVRs had a high continuous and dichotomous agreement with MRI-dependent measures for all ROIs (intraclass correlation coefficient ≥ 0.980; agreement ≥ 94.5%). Similar findings were observed for AD-related effect sizes, diagnostic performances with respect to categorization across the cognitive spectrum, and associations with cognitive domains. The robustness of the MRI-free approach was confirmed in the validation cohort. CONCLUSIONS: The use of an 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer. KEY POINTS: • Regional 18F-florzolotau SUVRs reflecting tau accumulation in the living brains are reliable biomarkers for the diagnosis, differential diagnosis, and assessment of disease severity in patients with AD. • The 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer.

Observational evidence for detrimental impact of inhaled ozone on human respiratory system.

The detrimental influence of inhaled ozone on human respiratory system is ambiguous due to the complexity of dose response relationship between ozone and human respiratory system. This study collects inhaled ozone concentration and respiratory disease data from Shenzhen City to reveal the impact of ozone on respiratory diseases using the Generalized Additive Models (GAM) and Convergent Cross Mapping (CCM) method at the 95% confidence level. The result of GAM exhibits a partially significant lag effect on acute respiratory diseases in cumulative mode. Since the traditional correlation analysis is incapable of capturing causality, the CCM method is applied to examine whether the inhaled ozone affects human respiratory system. The results demonstrate that the inhaled ozone has a significant causative impact on hospitalization rates of both upper and lower respiratory diseases. Furthermore, the harmful causative effects of ozone to the human health are varied with gender and age. Females are more susceptible to inhaled ozone than males, probably because of the estrogen levels and the differential regulation of lung immune response. Adults are more sensitive to ozone exposure than children, potentially due to the fact that children need longer time to react to ozone stress than adults, and the elderly are more tolerant than adults and children, which may be related to pulmonary hypofunction of the elderly while has little correlation with ozone exposure.

Research progress of proanthocyanidins and anthocyanidins.

Proanthocyanidins (PA) are polyphenol compounds that are widely distributed in the bark, fruit core, skin, or seeds of various plants. Anthocyanidins are water-soluble natural pigments widely found in plants. They are all flavonoids, a major coloring substance in plants and fruits. In recent years, research into PA and anthocyanins has become increasingly popular because of their excellent anti-oxidation, scavenging of reactive oxygen free radicals and other physical and chemical activities, and their anti-cancer, vision protection, aging prevention, skin beauty pharmacological, and nutraceutical effects. Especially, recent systematic reviews and meta-analyses indicate their value, safety, and efficacy in the prevention, adjuvant therapy, and management of cardiometabolic disease. Here, we summarize their research progress from the aspects of chemical structure, biosynthetic pathways, distribution, extraction and separation, coloration, efficacy, and potential. The comparison between them might provide a reference for their development and efficient utilization. However, more large-sample-size randomized controlled trials and high-quality studies are needed to firmly establish their clinical efficacy.

Weakly Supervised Concept Map Generation through Task-Guided Graph Translation.

Recent years have witnessed the rapid development of concept map generation techniques due to their advantages in providing well-structured summarization of knowledge from free texts. Traditional unsupervised methods do not generate task-oriented concept maps, whereas deep generative models require large amounts of training data. In this work, we present GT-D2G (Graph Translation-based Document To Graph), an automatic concept map generation framework that leverages generalized NLP pipelines to derive semantic-rich initial graphs, and translates them into more concise structures under the weak supervision of downstream task labels. The concept maps generated by GT-D2G can provide interpretable summarization of structured knowledge for the input texts, which are demonstrated through human evaluation and case studies on three real-world corpora. Further experiments on the downstream task of document classification show that GT-D2G beats other concept map generation methods. Moreover, we specifically validate the labeling efficiency of GT-D2G in the label-efficient learning setting and the flexibility of generated graph sizes in controlled hyper-parameter studies.

Enterovirus A71 Induces Neurological Diseases and Dynamic Variants in Oral Infection of Human SCARB2-Transgenic Weaned Mice.

Enterovirus A71 (EV-A71) and many members of the Picornaviridae family are neurotropic pathogens of global concern. These viruses are primarily transmitted through the fecal-oral route, and thus suitable animal models of oral infection are needed to investigate viral pathogenesis. An animal model of oral infection was developed using transgenic mice expressing human SCARB2 (hSCARB2 Tg), murine-adapted EV-A71/MP4 virus, and EV-A71/MP4 virus with an engineered nanoluciferase gene that allows imaging of viral replication and spread in infected mice. Next-generation sequencing of EV-A71 genomes in the tissues and organs of infected mice was also performed. Oral inoculation of EV-A71/MP4 or nanoluciferase-carrying MP4 virus stably induced neurological symptoms and death in infected 21-day-old weaned mice. In vivo bioluminescence imaging of infected mice and tissue immunostaining of viral antigens indicated that orally inoculated virus can spread to the central nervous system (CNS) and other tissues. Next-generating sequencing further identified diverse mutations in viral genomes that can potentially contribute to viral pathogenesis. This study presents an EV-A71 oral infection murine model that efficiently infects weaned mice and allows tracking of viral spread, features that can facilitate research into viral pathogenesis and neuroinvasion via the natural route of infection. IMPORTANCE Enterovirus A71 (EV-A71), a positive-strand RNA virus of the Picornaviridae, poses a persistent global public health problem. EV-A71 is primarily transmitted through the fecal-oral route, and thus suitable animal models of oral infection are needed to investigate viral pathogenesis. We present an animal model of EV-A71 infection that enables the natural route of oral infection in weaned and nonimmunocompromised 21-day-old hSCARB2 transgenic mice. Our results demonstrate that severe disease and death could be stably induced, and viral invasion of the CNS could be replicated in this model, similar to severe real-world EV-A71 infections. We also developed a nanoluciferase-containing EV-A71 virus that can be used with this animal model to track viral spread after oral infection in real time. Such a model offers several advantages over existing animal models and can facilitate future research into viral spread, tissue tropism, and viral pathogenesis, all pressing issues that remain unaddressed for EV-A71 infections.

Plasma Aß42/Aß40 and p-tau181 Predict Long-Term Clinical Progression in a Cohort with Amnestic Mild Cognitive Impairment.

BACKGROUND: Previous studies reported the value of blood-based biomarkers in predicting Alzheimer disease (AD) progression among individuals with different disease stages. However, evidence regarding the value of these markers in those with amnestic mild cognitive impairment (aMCI) is insufficient. METHODS: A cohort with 251 aMCI individuals were followed for up to 8 years. Baseline blood biomarkers were measured on a single-molecule array platform. Multipoint clinical diagnosis and domain-specific cognitive functions were assessed to investigate the longitudinal relationship between blood biomarkers and clinical AD progression. RESULTS: Individuals with low Aß42/Aß40 and high p-tau181 at baseline demonstrated the highest AD risk (hazard ratio = 4.83, 95% CI 2.37-9.86), and the most dramatic decline across cognitive domains. Aß42/Aß40 and p-tau181, combined with basic characteristics performed the best in predicting AD conversion (AUC = 0.825, 95% CI 0.771-0.878). CONCLUSIONS: Combining Aß42/Aß40 and p-tau181 may be a feasible indicator for AD progression in clinical practice, and a potential composite marker in clinical trials.

Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET.

PURPOSE: Alzheimer's disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE). METHODS: A total of 1080 [18F]Flortaucipir brain positron emission tomography (PET) images were collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. VAE was built to compress the hidden features from tau images in latent space. Hierarchical agglomerative clustering and minimum spanning tree (MST) were applied to organize the features and calibrate them to the tau progression, thus deriving pseudo-time. The image-level tau trajectory was inferred by continuously sampling across the calibrated latent features. We assessed the pseudo-time with regard to tau standardized uptake value ratio (SUVr) in AD-vulnerable regions, amyloid deposit, glucose metabolism, cognitive scores, and clinical diagnosis. RESULTS: We identified four clusters that plausibly capture certain stages of AD and organized the clusters in the latent space. The inferred tau trajectory agreed with the Braak staging. According to the derived pseudo-time, tau first deposits in the parahippocampal and amygdala, and then spreads to the fusiform, inferior temporal lobe, and posterior cingulate. Prior to the regional tau deposition, amyloid accumulates first. CONCLUSION: The spatiotemporal trajectory of tau progression inferred in this study was consistent with Braak staging. The profile of other biomarkers in disease progression agreed well with previous findings. We addressed that this approach additionally has the potential to quantify tau progression as a continuous variable by taking a whole-brain tau image into account.

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS: This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS: The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION: This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis.