Activation mechanism of PINK1.

Mutations in the protein kinase PINK1 lead to defects in mitophagy and cause autosomal recessive early onset Parkinson's disease1,2. PINK1 has many unique features that enable it to phosphorylate ubiquitin and the ubiquitin-like domain of Parkin3-9. Structural analysis of PINK1 from diverse insect species10-12 with and without ubiquitin provided snapshots of distinct structural states yet did not explain how PINK1 is activated. Here we elucidate the activation mechanism of PINK1 using crystallography and cryo-electron microscopy (cryo-EM). A crystal structure of unphosphorylated Pediculus humanus corporis (Ph; human body louse) PINK1 resolves an N-terminal helix, revealing the orientation of unphosphorylated yet active PINK1 on the mitochondria. We further provide a cryo-EM structure of a symmetric PhPINK1 dimer trapped during the process of trans-autophosphorylation, as well as a cryo-EM structure of phosphorylated PhPINK1 undergoing a conformational change to an active ubiquitin kinase state. Structures and phosphorylation studies further identify a role for regulatory PINK1 oxidation. Together, our research delineates the complete activation mechanism of PINK1, illuminates how PINK1 interacts with the mitochondrial outer membrane and reveals how PINK1 activity may be modulated by mitochondrial reactive oxygen species.

Interpretable modeling of time-resolved single-cell gene-protein expression with CrossmodalNet.

Cell-surface proteins play a critical role in cell function and are primary targets for therapeutics. CITE-seq is a single-cell technique that enables simultaneous measurement of gene and surface protein expression. It is powerful but costly and technically challenging. Computational methods have been developed to predict surface protein expression using gene expression information such as from single-cell RNA sequencing (scRNA-seq) data. Existing methods however are computationally demanding and lack the interpretability to reveal underlying biological processes. We propose CrossmodalNet, an interpretable machine learning model, to predict surface protein expression from scRNA-seq data. Our model with a customized adaptive loss accurately predicts surface protein abundances. When samples from multiple time points are given, our model encodes temporal information into an easy-to-interpret time embedding to make prediction in a time-point-specific manner, and is able to uncover noise-free causal gene-protein relationships. Using three publicly available time-resolved CITE-seq data sets, we validate the performance of our model by comparing it with benchmarking methods and evaluate its interpretability. Together, we show that our method accurately and interpretably profiles surface protein expression using scRNA-seq data, thereby expanding the capacity of CITE-seq experiments for investigating molecular mechanisms involving surface proteins.

Controlled Noise: Evidence of epigenetic regulation of Single-Cell expression variability.

MOTIVATION: Understanding single-cell expression variability (scEV) or gene expression noise among cells of the same type and state is crucial for delineating population-level cellular function. While epigenetic mechanisms are widely implicated in gene expression regulation, a definitive link between chromatin accessibility and scEV remains elusive. Recent advances in single-cell techniques enable the study of single-cell multiomics data that include the simultaneous measurement of scATAC-seq and scRNA-seq within individual cells, presenting an unprecedented opportunity to address this gap. RESULTS: This paper introduces an innovative testing pipeline to investigate the association between chromatin accessibility and scEV. With single-cell multiomics data of scATAC-seq and scRNA-seq, the pipeline hinges on comparing the prediction performance of scATAC-seq data on gene expression levels between highly variable genes (HVGs) and non-highly variable genes (non-HVGs). Applying this pipeline to paired scATAC-seq and scRNA-seq data from human hematopoietic stem and progenitor cells, we observed a significantly superior prediction performance of scATAC-seq data for HVGs compared to non-HVGs. Notably, there was substantial overlap between well-predicted genes and HVGs. The gene pathways enriched from well-predicted genes are highly pertinent to cell type-specific functions. Our findings support the notion that scEV largely stems from cell-to-cell variability in chromatin accessibility, providing compelling evidence for the epigenetic regulation of scEV and offering promising avenues for investigating gene regulation mechanisms at the single-cell level. AVAILABILITY: The source code and data used in this paper can be found at https://github.com/SiweiCui/EpigeneticControlOfSingle-CellExpressionVariability. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

P75NTR+CD64+ neutrophils promote sepsis-induced acute lung injury.

Patients suffering from sepsis-induced acute lung injury (ALI) exhibit a high mortality rate, and their prognosis is closely associated with infiltration of neutrophils into the lungs. In this study, we found a significant elevation of CD64+ neutrophils, which highly expressed p75 neurotrophin receptor (p75NTR) in peripheral blood of mice and patients with sepsis-induced ALI. p75NTR+CD64+ neutrophils were also abundantly expressed in the lung of ALI mice induced by lipopolysaccharide. Conditional knock-out of the myeloid lineage's p75NTR gene improved the survival rates, attenuated lung tissue inflammation, reduced neutrophil infiltration and enhanced the phagocytic functions of CD64+ neutrophils. In vitro, p75NTR+CD64+ neutrophils exhibited an upregulation and compromised phagocytic activity in blood samples of ALI patients. Blocking p75NTR activity by soluble p75NTR extracellular domain peptide (p75ECD-Fc) boosted CD64+ neutrophils phagocytic activity and reduced inflammatory cytokine production via regulation of the NF-κB activity. The findings strongly indicate that p75NTR+CD64+ neutrophils are a novel pathogenic neutrophil subpopulation promoting sepsis-induced ALI.

Mechanism and inhibition of the papain-like protease, PLpro, of SARS-CoV-2.

The SARS-CoV-2 coronavirus encodes an essential papain-like protease domain as part of its non-structural protein (nsp)-3, namely SARS2 PLpro, that cleaves the viral polyprotein, but also removes ubiquitin-like ISG15 protein modifications as well as, with lower activity, Lys48-linked polyubiquitin. Structures of PLpro bound to ubiquitin and ISG15 reveal that the S1 ubiquitin-binding site is responsible for high ISG15 activity, while the S2 binding site provides Lys48 chain specificity and cleavage efficiency. To identify PLpro inhibitors in a repurposing approach, screening of 3,727 unique approved drugs and clinical compounds against SARS2 PLpro identified no compounds that inhibited PLpro consistently or that could be validated in counterscreens. More promisingly, non-covalent small molecule SARS PLpro inhibitors also target SARS2 PLpro, prevent self-processing of nsp3 in cells and display high potency and excellent antiviral activity in a SARS-CoV-2 infection model.

A New Theranostic Platform Against Gram-Positive Bacteria Based on Near-Infrared-Emissive Aggregation-Induced Emission Nanoparticles.

Infections induced by Gram-positive bacteria pose a great threat to public health. Antibiotic therapy, as the first chosen strategy against Gram-positive bacteria, is inevitably associated with antibiotic resistance selection. Novel therapeutic strategies for the discrimination and inactivation of Gram-positive bacteria are thus needed. Here, a specific type of aggregation-induced emission luminogen (AIEgen) with near-infrared fluorescence emission as a novel antibiotic-free therapeutic strategy against Gram-positive bacteria is proposed. With the combination of a positively charged group into a highly twisted architecture, self-assembled AIEgens (AIE nanoparticles (NPs)) at a relatively low concentration (5 µm) exhibited specific binding and photothermal effect against living Gram-positive bacteria both in vitro and in vivo. Moreover, toxicity assays demonstrated excellent biocompatibility of AIE NPs at this concentration. All these properties make the AIE NPs as a novel generation of theranostic platform for combating Gram-positive bacteria and highlight their promising potential for in vivo tracing of such bacteria.

Extracorporeal photopheresis reduces inflammation and joint damage in a rheumatoid arthritis murine model.

BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune disease characterized by inflammatory reactions and tissue damage in the joints. Long-term drug use in clinical practice is often accompanied by adverse reactions. Extracorporeal photopheresis (ECP) is an immunomodulatory therapy with few side effects, offering a potential and safe therapeutic alternative for RA through the induction of immune tolerance. This study aimed to investigate the therapeutic effects of ECP on RA using a collagen-induced arthritis (CIA) murine model, as well as to explore its immunomodulatory effects in vivo. Additionally, particular attention was given to the significant role of monocytes during the ECP process. METHODS: A murine model of rheumatoid arthritis was established by administering two injections of bovine type II collagen to DBA/1J mice. ECP, ECP-MD (mononuclear cells were depleted during the ECP), MTX, and PBS treatment were applied to the CIA mice. During the treatment process, clinical scores and body weight changes of CIA mice were closely monitored. After six treatment sessions, micro-CT images of the hind paws from live mice were captured. Ankle joints and paws of the mice were collected and processed for histological evaluation. Spleen samples were collected to measure the Th17/Treg cells ratio, and serum samples were collected to assess cytokine and anti-type II collagen IgG levels. Monocytes and dendritic cells populations before and after ECP in vitro were detected by flow cytometry. RESULT: ECP therapy significantly attenuated the progression of CIA, alleviated the severity of clinical symptoms in CIA mice and effectively suppressed synovial hyperplasia, inflammation, and cartilage damage. There was an expansion in the percentage of CD3 + CD4 + CD25 + FoxP3 + Tregs and a decrease in CD3 + CD4 + IL17A + Th17 cells in vivo. Furthermore, ECP reduced the serum levels of pro-inflammatory cytokines IL-6 (53.47 ± 7.074 pg/mL vs 5.142 ± 1.779 pg/mL, P < 0.05) and IL-17A (3.077 ± 0.401 pg/mL vs 0.238 ± 0.082 pg/mlL, P < 0.0001) compared with PBS. Interestingly, the depletion of monocytes during the ECP process did not lead to any improvement in clinical symptoms or histological scores in CIA mice. Moreover, the imbalance in the Th17/Treg cells ratio became even more pronounced, accompanied by an augmented secretion of pro-inflammatory cytokines IL-6 and IL-17A. In vitro, compared with cells without ECP treatment, the proportion of CD11b + cells were significantly reduced (P < 0.01), the proportion of CD11c + cells were significantly elevated (P < 0.001) 24 h after ECP treatment. Additionally, the expression of MHC II (P < 0.0001), CD80 (P < 0.01), and CD86 (P < 0.001) was downregulated in CD11c + cells 24 h after ECP treatment. CONCLUSION: Our study demonstrates that ECP exhibits a therapeutic effect comparable to conventional therapy in CIA mice, and the protective mechanisms of ECP against RA involve Th17/Treg cells ratio, which result in decreased IL-6 and IL-17A. Notably, monocytes derived from CIA mice are an indispensable part to the efficacy of ECP treatment, and the proportion of monocytes decreased and the proportion of tolerogenic dendritic cells increased after ECP treatment in vitro.

Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood. METHODS: To address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue. RESULTS: Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs. CONCLUSIONS: This study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.

Effect of the configuration mixing on the polarization and angular distribution of x-ray line emissions following electron-impact excitation of Ne-like ions.

We present a systematic theoretical study on the angular distribution and linear polarization of x-ray line emissions of neon-like ions following the electron-impact excitation from the ground state to the excited levels [(2p5)1/23d3/2]J=1, [(2p5)3/23d5/2]J=1, [(2p5)3/23d3/2]J=1, and [(2p5)1/23s]J=1. The cross sections are calculated by using the flexible atomic code under configuration-interaction plus many-body perturbation theory method. The angular distribution and linear polarization are obtained based on density matrix theory. Emphasis has been placed on the effect of the configuration mixing on the angular distribution and polarization. It has been proved that the strong mixing of configuration [(2p5)3/23d3/2]J=1 with configuration [(2p5)1/23s]J=1 can result in the abrupt change of Z-dependence of angular distribution and polarization. It indicates that angular distribution and polarization can be expected to serve as a tool for investigation of configuration mixing effect.

Human embryonic stem cell-derived mesenchymal stromal cells suppress inflammation in mouse models of rheumatoid arthritis and lung fibrosis by regulating T-cell function.

BACKGROUND AIMS: Rheumatoid arthritis (RA) is characterized by an overactive immune system, with limited treatment options beyond immunosuppressive drugs or biological response modifiers. Human embryonic stem cell-derived mesenchymal stromal cells (hESC-MSCs) represent a novel alternative, possessing diverse immunomodulatory effects. In this study, we aimed to elucidate the therapeutic effects and underlying mechanisms of hESC-MSCs in treating RA. METHODS: MSC-like cells were differentiated from hESC (hESC-MSCs) and cultured in vitro. Cell proliferation was assessed using Cell Counting Kit-8 assay and Ki-67 staining. Flow cytometry was used to analyze cell surface markers, T-cell proliferation and immune cell infiltration. The collagen-induced arthritis (CIA) mouse model and bleomycin-induced model of lung fibrosis (BLE) were established and treated with hESC-MSCs intravenously for in vivo assessment. Pathological analyses, reverse transcription-quantitative polymerase chain reaction and Western blotting were conducted to evaluate the efficacy of hESC-MSCs treatment. RESULTS: Intravenous transplantation of hESC-MSCs effectively reduced inflammation in CIA mice in this study. Furthermore, hESC-MSC administration enhanced regulatory T cell infiltration and activation. Additional findings suggest that hESC-MSCs may reduce lung fibrosis in BLE mouse models, indicating their potential to mitigate complications associated with RA progression. In vitro experiments revealed a significant inhibition of T-cell activation and proliferation during co-culture with hESC-MSCs. In addition, hESC-MSCs demonstrated enhanced proliferative capacity compared with traditional primary MSCs. CONCLUSIONS: Transplantation of hESC-MSCs represents a promising therapeutic strategy for RA, potentially regulating T-cell proliferation and differentiation.

[18F]FDG PET for mapping the cerebral glucose metabolic characteristics of drug-sensitive and drug-resistant epilepsy in pediatric patients.

OBJECTIVE: This study aimed to investigate [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET) mapping for cerebral glucose metabolism in drug-sensitive and drug-resistant pediatric epilepsy patients. METHODS: This retrospective study enrolled 40 patients and 25 controls. Patients were categorized into drug-sensitive epilepsy (n = 22) and drug-resistant epilepsy (n = 18) according to the seizure frequency at follow-up. All patients underwent two [18F]FDG PET scans separated by a minimum of one year. Absolute asymmetry index (|AI|) was calculated for assessing metabolic differences and changes in epileptic foci. Statistical Parametric Mapping (SPM) was utilized to reveal voxel-wise metabolic characteristics and alterations throughout the brain. Network analysis based on graph theory was used to investigate network-level differences between the two patient groups. RESULTS: The drug-sensitive group showed a lower |AI| at both baseline (P = 0.038) and follow-up (P = 0.003) PET scans than the drug-resistant group. |AI| decreased in the drug-sensitive group and increased in the drug-resistant group across scans, but these trends were not statistically significant (P = 0.240 and P = 0.450, respectively). Both groups exhibited hypometabolism at baseline. The drug-sensitive group showed less hypometabolic brain regions than the drug-resistant group. The drug-sensitive maintained stable level of hypometabolism between the two scans, whereas the drug-resistant group showed an increasing hypometabolism. Network analysis demonstrated that the drug-sensitive group had a higher global efficiency, average degree, and clustering, along with a shorter characteristic path length compared to the drug-resistant group. CONCLUSIONS: For the first time, this study revealed in vivo cerebral glucose metabolic pattern of nonsurgical pediatric epilepsy patients treated by antiepileptic drugs. Especially, drug-resistant epilepsy patients represented significantly extensive and progressive hypometabolism with inefficient brain network connectivity compared with drug-sensitive epilepsy. [18F]FDG PET imaging may be a potential visual approach for theranostics of epilepsy patients.

In vivo cerebral metabolic and dopaminergic characteristics in multiple system atrophy with orthostatic hypotension.

PURPOSE: Multiple system atrophy (MSA) is a rare neurodegenerative disease, often presented with orthostatic hypotension (OH), which is a disabling symptom but has not been very explored. Here, we investigated MSA patients with OH by using positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) and 11C-N-2-carbomethoxy-3-(4-fluorophenyl)-tropane (11C-CFT) for in vivo evaluation of the glucose metabolism and dopaminergic function of the brain. METHODS: Totally, 51 patients with MSA and 20 healthy controls (HC) who underwent 18F-FDG PET/CT were retrospectively enrolled, among which 24 patients also underwent 11C-CFT PET/CT. All patients were divided into MSA-OH(+) and MSA-OH(-) groups. Then, statistical parametric mapping (SPM) method was used to reveal the regional metabolic and dopaminergic characteristics of MSA-OH(+) compared with MSA-OH(-). Moreover, the metabolic networks of MSA-OH(+), MSA-OH(-) and HC groups were also constructed and analyzed based on graph theory to find possible network-level changes in MSA patients with OH. RESULTS: The SPM results showed significant hypometabolism in the pons and right cerebellar tonsil, as well as hypermetabolism in the left parahippocampal gyrus and left superior temporal gyrus in MSA-OH(+) compared with MSA-OH(-). A reduced 11C-CFT uptake in the left caudate was also shown in MSA-OH(+) compared with MSA-OH(-). In the network analysis, significantly reduced local efficiency and clustering coefficient were shown in MSA-OH(+) compared with HC, and decreased nodal centrality in the frontal gyrus was found in MSA-OH(+) compared with MSA-OH(-). CONCLUSION: In this study, the changes in glucose metabolism in the pons, right cerebellar tonsil, left parahippocampal gyrus and left superior temporal gyrus were found closely related to OH in MSA patients. And the decreased presynaptic dopaminergic function in the left caudate may contribute to OH in MSA. Taken together, this study provided in vivo pathophysiologic information on MSA with OH from neuroimaging approach, which is essential for a better understanding of MSA with OH.

PET imaging of synaptic vesicle glycoprotein 2 subtype A for neurological recovery in ischemic stroke.

PURPOSE: [18F]SynVesT-1 is a novel radiopharmaceutical for assessing synaptic density in vivo. This study aims to investigate the potential of [18F]SynVesT-1 positron emission tomography (PET) in evaluating neurological recovery in the rat model of ischemic stroke, and to compare its performance with [18F]FDG PET. METHODS: Sprague-Dawley rats were subjected to photothrombotic cerebral infarction, and safinamide was administered intraperitoneally from day 3 to day 14 post-stroke to alleviate neurological deficits. Cylinder test and forelimb placing test were performed to assess the neurological function. MRI, [18F]SynVesT-1 PET/CT and [18F]FDG PET/CT imaging were used to evaluate infarct volume, synaptic density, and cerebral glucose metabolism pre- and post-treatment. [18F]SynVesT-1 and [18F]FDG PET images were compared using Statistical Parametric Mapping (SPM) and region of interest (ROI)-based analysis. Post-mortem histological analysis was performed to validate PET images. RESULTS: Safinamide treatment improved behavioral outcomes in stroke-damaged rats. Both [18F]SynVesT-1 and [18F]FDG PET detected stroke-induced injury, with the injured region being significantly larger in [18F]FDG PET than in [18F]SynVesT-1 PET. Compared with the saline group, radiotracer uptake in the injured area significantly increased in [18F]SynVesT-1 PET after safinamide treatment, whereas no notable change was observed in [18F]FDG PET. Additionally, [18F]SynVesT-1 PET imaging showed a better correlation with neurological function recovery than [18F]FDG PET. Post-mortem analysis revealed increased neuronal numbers, synaptic density, and synaptic neuroplasticity, as well as decreased glia activation in the stroke-injured area after treatment. CONCLUSION: [18F]SynVesT-1 PET effectively quantified spatiotemporal dynamics of synaptic density in the rat model of stroke, and showed different capabilities in detecting stroke injury and neurological recovery compared with [18F]FDG PET. The utilization of [18F]SynVesT-1 PET holds promise as a potential non-invasive biomarker for evaluating ischemic stroke in conjunction with [18F]FDG PET.

Spatial-temporal dynamic evolution of lewy body dementia by metabolic PET imaging.

PURPOSE: Lewy body dementia (LBD) is a neurodegenerative disease with high heterogeneity and complex pathogenesis. Our study aimed to use disease progression modeling to uncover spatial-temporal dynamic evolution of LBD in vivo, and to explore differential profiles of clinical features, glucose metabolism, and dopaminergic function among different evolution-related subtypes. METHODS: A total of 123 participants (31 healthy controls and 92 LBD patients) who underwent 18F-FDG PET scans were retrospectively enrolled. 18F-FDG PET-based Subtype and Stage Inference (SuStaIn) model was established to illustrate spatial-temporal evolutionary patterns and categorize relevant subtypes. Then subtypes and stages were further related to clinical features, glucose metabolism, and dopaminergic function of LBD patients. RESULTS: This 18F-FDG PET imaging-based approach illustrated two distinct patterns of neurodegenerative evolution originating from the neocortex and basal ganglia in LBD and defined them as subtype 1 and subtype 2, respectively. There were obvious differences between subtypes. Compared with subtype 1, subtype 2 exhibited a greater proportion of male patients (P = 0.045) and positive symptoms such as visual hallucinations (P = 0.033) and fluctuating cognitions (P = 0.033). Cognitive impairment, metabolic abnormalities, dopaminergic dysfunction and progression were all more severe in subtype 2 (all P < 0.05). In addition, a strong association was observed between SuStaIn subtypes and two clinical phenotypes (Parkinson's disease dementia and dementia with Lewy bodies) (P = 0.005). CONCLUSIONS: Our findings based on 18F-FDG PET and data-driven model illustrated spatial-temporal dynamic evolution of LBD and categorized novel subtypes with different evolutionary patterns, clinical and imaging features in vivo. The evolution-related subtypes are associated with LBD clinical phenotypes, which supports the perspective of existence of distinct entities in LBD spectrum.

Identification of metabolic progression and subtypes in progressive supranuclear palsy by PET molecular imaging.

INTRODUCTION: Progressive supranuclear palsy (PSP) is a neurodegenerative disorder with diverse clinical presentations that are linked to tau pathology. Recently, Subtype and Stage Inference (SuStaIn) algorithm, an innovative data-driven method, has been developed to model both the spatial-temporal progression and subtypes of disease. This study explores PSP progression using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging and the SuStaIn algorithm to identify PSP metabolic progression subtypes and understand disease mechanisms. METHODS: The study included 72 PSP patients and 70 controls, with an additional 24 PSP patients enrolled as a test set, undergoing FDG-PET, dopamine transporter (DAT) PET, and neuropsychological assessments. The SuStaIn algorithm was employed to analyze the FDG-PET data, identifying progression subtypes and sequences. RESULTS: Two PSP subtypes were identified: the cortical subtype with early prefrontal hypometabolism and the brainstem subtype with initial midbrain alterations. The cortical subtype displayed greater cognitive impairment and DAT reduction than the brainstem subtype. The test set demonstrates the robustness and reproducibility of the findings. Pathway analysis indicated that disruptions in dopaminergic cortico-basal ganglia pathways are crucial for elucidating the mechanisms of cognitive and behavioral impairment in PSP, leading to the two metabolic progression subtypes. CONCLUSION: This study identified two spatiotemporal progression subtypes of PSP based on FDG-PET imaging, revealing significant differences in metabolic patterns, striatal dopaminergic uptake, and clinical profiles, particularly cognitive impairments. The findings highlight the crucial role of dopaminergic cortico-basal ganglia pathways in PSP pathophysiology, especially in the cortical subtype, providing insights into PSP heterogeneity and potential avenues for personalized treatments.

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.

IAIH-PG consensus for histological criteria of AIH: Multicentre validation with focus on chronic liver diseases in China.

BACKGROUND AND AIMS: The International AIH Pathology Group (IAIH-PG) put forward the new histological criteria of autoimmune hepatitis (AIH) in 2022, which have not undergone adequate verification. In this study, we verified the applicability of the new histological criteria in the population of Chinese patients with chronic liver disease, comparing it with the simplified criteria. METHODS: The gold standard for diagnosis in all patients was based on histological findings, combined with clinical manifestations and laboratory tests and determined after a follow-up period of at least 3 years. A total of 640 patients with various chronic liver diseases from multiple centres underwent scoring using the new histological criteria and the simplified criteria, comparing their diagnostic performance. RESULTS: In this study, the new histological criteria showed a sensitivity of 73.6% and 100% for likely and possible AIH, with specificities of 100% and 69.0% respectively. The coincidence rates of possible AIH for the new histological criteria, simplified histological criteria and simplified score were 81.7%, 72.8% and 69.7% respectively. For likely AIH, the rates were 89.2%, 75.9% and 65.6% respectively. Based on the new histological criteria, all patients with AIH were correctly diagnosed. Specifically, 73.6% were diagnosed with likely AIH and 26.4% were possible AIH. Additionally, the simplified histological criteria achieved a diagnosis rate of 98.6% for AIH, while the simplified score could only diagnose 53.8% of AIH. CONCLUSIONS: Compared with the simplified score and simplified histological criteria, the sensitivity and specificity of the new histological criteria for AIH were significantly improved. The results indicate that the new histological criteria exhibit high sensitivity and specificity for diagnosing AIH in China.

Reduced-rank clustered coefficient regression for addressing multicollinearity in heterogeneous coefficient estimation.

Clustered coefficient regression (CCR) extends the classical regression model by allowing regression coefficients varying across observations and forming clusters of observations. It has become an increasingly useful tool for modeling the heterogeneous relationship between the predictor and response variables. A typical issue of existing CCR methods is that the estimation and clustering results can be unstable in the presence of multicollinearity. To address the instability issue, this paper introduces a low-rank structure of the CCR coefficient matrix and proposes a penalized non-convex optimization problem with an adaptive group fusion-type penalty tailor-made for this structure. An iterative algorithm is developed to solve this non-convex optimization problem with guaranteed convergence. An upper bound for the coefficient estimation error is also obtained to show the statistical property of the estimator. Empirical studies on both simulated datasets and a COVID-19 mortality rate dataset demonstrate the superiority of the proposed method to existing methods.

Chelativorans salis sp. nov., a slightly halophilic bacterium isolated from an enrichment system with saline lake sediment.

A Gram-stain-negative, non-motile, and slightly halophilic alphaproteobacterium, designated strain EGI FJ00035T, was isolated from enrichment sediment samples of a saline lake in Xinjiang Uygur Autonomous Region, PR China. The taxonomic position of the isolate was determined using the polyphasic taxonomic and phylogenomic analyses. Phylogenetic analysis based on the 16S rRNA gene sequences indicated that strain EGI FJ00035T formed a distinct clade with 'Chelativorans alearense' UJN715 and 'Chelativorans xinjiangense' lm93 with sequence similarities of 98.44 and 98.22 %, respectively, while sharing less than 96.7 % with other valid type strains. The novel isolate could be distinguished from other species of the genus Chelativorans by its distinct phenotypic, physiological, and genotypic characteristics. Optimal growth of strain EGI FJ00035T occurred on marine agar 2216 at pH 7.0 and 30 °C. The major respiratory quinone was Q-10, while the major fatty acids (>5 %) were C19 : 0 cyclo ω8c, summed feature 8 (C17 : 1 ω6c and/or C17 : 1 ω7c), C16 : 0, C18 : 0, and iso-C17 : 0. The detected polar lipids included diphosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, unidentified aminophospholipids, unidentified glycolipids, and an unidentified lipid. Based on its genome sequence, the G+C content of strain EGI FJ00035T was 63.2 mol%. The average nucleotide identity, average amino acid identity, and digital DNA-DNA hybridization values of strain EGI FJ00035T against related members of the genus Chelativorans were below the thresholds for delineation of a novel species. According our polyphasic taxonomic data, strain EGI FJ00035T represents a new species of the genus Chelativorans, for which the name Chelativorans salis sp. nov. is proposed. The type strain of the proposed novel isolate is EGI FJ00035T (=KCTC 92251T=CGMCC 1.19480T).