Mitochondrial Proteome Defined Molecular Pathological Characteristics of Oncocytic Thyroid Tumors.

Oncocytic thyroid tumors are characterized by an elevated mitochondrial density within the cells, distinguishing them from other thyroid tumors, exhibit distinct clinical behaviors, including increased invasiveness and iodine therapy resistance. However, the proteomic alterations in oncocytic thyroid tumors remain inadequately characterized. In this study, we analyzed 156 Asian patients with oncocytic thyroid adenomas (OA) and carcinomas (OCA) to explore their clinical, genetic, and proteomic features. Genetic testing of 73 samples revealed frequent mutations in TERT, NRAS, EIF1AX, EZH1, and HRAS, with TERT promoter mutations being exclusive to OCAs. Proteomic analysis identified 66 mitochondrial-specific proteins significantly highly expressed in oncocytic tumors than in non-oncocytic tumors. This led to the development of a thyroid oncocytic score (TOS) to quantify oncocytic characteristics. Among these proteins, isocitrate dehydrogenase 2 (IDH2) was substantially overexpressed in oncocytic tumors and further confirmed by immunohistochemistry in oncocytic tumor slides (n = 41) and non-oncocytic tumor slides (n = 40). Moreover, IDH2 is significantly overexpressed in OCA compared to OA highlighting its potential as a biomarker for differential diagnosis of oncocytic tumors and malignancy. These findings improve the understanding of oncocytic thyroid tumors molecular pathology and suggest IDH2 as a valuable marker for clinical management.

Study of Rates and Factors Associated to Psychosomatic Syndromes Assessed Using the Diagnostic Criteria for Psychosomatic Research across Different Clinical Settings.

INTRODUCTION: Diagnostic Criteria for Psychosomatic Research (DCPR) serve as an instrument for identifying and classifying specific psychosomatic syndromes that are not adequately encompassed in standard nosography. The present study aimed at measuring the prevalence of DCPR syndromes in different clinical settings and exploring factors associated to such diagnoses. METHODS: A cross-sectional and nationwide study recruited 6,647 patients in different clinical settings: 306 were diagnosed with fibromyalgia (FM), 333 with irritable bowel syndrome, 1,109 with migraine, 2,550 with coronary heart disease (CHD), and 2,349 with type 2 diabetes (T2D). Participants underwent DCPR diagnostic interview and were assessed for depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder 7-Item Scale), and subjective well-being (World Health Organization-5 Well-Being Index). The PsychoSocial Index was used to evaluate global well-being, stress, and abnormal illness behavior. The prevalence of DCPR diagnoses was calculated, and factors associated to such diagnoses were analyzed by logistic regression. RESULTS: Alexithymia (64.47%), irritable mood (20.55%), and demoralization (15.60%) were the most prevalent psychosomatic syndromes, with demoralization being most common in FM (49.02%). The factors associated to DCPR diagnoses encompassed high anxiety or abnormal illness behavior, and poor well-being. Notably, stress was found to be associated specifically to FM and T2D, with OR of 1.24 (95% CI: 1.06-1.46) and 1.26 (95% CI: 1.18-1.36), respectively. CONCLUSION: DCPR is a clinically helpful complementary assessment tool in need of being widely implemented in clinical settings in order to have a comprehensive picture of the patients.

SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data.

Spatial barcoding-based transcriptomic (ST) data require deconvolution for cellular-level downstream analysis. Here we present SDePER, a hybrid machine learning and regression method to deconvolve ST data using reference single-cell RNA sequencing (scRNA-seq) data. SDePER tackles platform effects between ST and scRNA-seq data, ensuring a linear relationship between them while addressing sparsity and spatial correlations in cell types across capture spots. SDePER estimates cell-type proportions, enabling enhanced resolution tissue mapping by imputing cell-type compositions and gene expressions at unmeasured locations. Applications to simulated data and four real datasets showed SDePER's superior accuracy and robustness over existing methods.

Spatial proteomics of single cells and organelles on tissue slides using filter-aided expansion proteomics.

Hydrogel-based tissue expansion combined with mass spectrometry (MS) offers an emerging spatial proteomics approach. Here, we present a filter-aided expansion proteomics (FAXP) strategy for spatial proteomics analysis of archived formalin-fixed paraffin-embedded (FFPE) specimens. Compared to our previous ProteomEx method, FAXP employed a customized tip device to enhance both the stability and throughput of sample preparation, thus guaranteeing the reproducibility and robustness of the workflow. FAXP achieved a 14.5-fold increase in volumetric resolution. It generated over 8 times higher peptide yield and a 255% rise in protein identifications while reducing sample preparation time by 50%. We also demonstrated the applicability of FAXP using human colorectal FFPE tissue samples. Furthermore, for the first time, we achieved bona fide single-subcellular proteomics under image guidance by integrating FAXP with laser capture microdissection.

Comparative Review for Enhancing CO2 Capture Efficiency with Mixed Amine Systems and Catalysts.

This study investigates methods to enhance the efficiency of CO2 capture using organic amine absorption and compares the performance of traditional and novel amine solvents. It reviews various single-component and mixed amine absorbents, as well as catalysts used in these methods, highlighting the superiority of mixed amine absorbents over single-component amine absorbents in CO2 absorption and desorption. Additionally, the study explores the catalytic mechanisms and effects of catalysts in the CO2 absorption/desorption process with amine solvents and provides an outlook on future research directions. The aim is to promote the widespread adoption of organic amine absorption technology in industrial applications and to contribute to the development of more sustainable and efficient CO2 capture technologies.

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Probability graph complementation contrastive learning.

Graph Neural Network (GNN) has achieved remarkable progress in the field of graph representation learning. The most prominent characteristic, propagating features along the edges, degrades its performance in most heterophilic graphs. Certain researches make attempts to construct KNN graph to improve the graph homophily. However, there is no prior knowledge to choose proper K and they may suffer from the problem of Inconsistent Similarity Distribution (ISD). To accommodate this issue, we propose Probability Graph Complementation Contrastive Learning (PGCCL) which adaptively constructs the complementation graph. We employ Beta Mixture Model (BMM) to distinguish intra-class similarity and inter-class similarity. Based on the posterior probability, we construct Probability Complementation Graphs to form contrastive views. The contrastive learning prompts the model to preserve complementary information for each node from different views. By combining original graph embedding and complementary graph embedding, the final embedding is able to capture rich semantics in the finetuning stage. At last, comprehensive experimental results on 20 datasets including homophilic and heterophilic graphs firmly verify the effectiveness of our algorithm as well as the quality of probability complementation graph compared with other state-of-the-art methods.

Epilepsy lesion localization method based on brain function network.

Objective: In the past, the localization of seizure onset zone (SOZ) primarily relied on traditional EEG signal analysis methods. However, due to their limited spatial and temporal resolution, accurately pinpointing neural activity was challenging, thereby restricting their clinical applicability. Compared with traditional EEG signals, SEEG signals have superior spatial and temporal resolution, and can more accurately record neural activity near epileptic foci, making them better suited for studying SOZ. In addition, the traditional EEG signal analysis methods still have limitations, mainly focusing on the analysis of local signal features, while ignoring the complexity and interconnection of the overall brain network. How to more accurately locate SOZ is still not well resolved. The purpose of this study is to develop an effective positioning method for more accurate positioning. Method: To overcome these limitations, this study proposed a model integrating brain functional network analysis with nonlinear dynamics. We utilized weighted phase lag index (WPLI) to construct brain functional network, epilepic network connectivity strength (ENCS) as the feature, and introduced persistence entropy (PE) for feature fusion, subsequently employing support vector machine (SVM) classification. Results: The proposed method was verified on the HUP-iEEG dataset, our solution identified the SOZ with 0.9440 accuracy, 0.9848 precision, 0.8974 recall rate, 0.9340 F1 score and 0.9697 area under the ROC curve across patients, which outperforms the existing approaches. It exhibits a 2.30 percentage point enhancement in localisation accuracy along with a 2.97 percentage points in AUC compared to others. Conclusion: Our method consider the interactions between nodes in brain network connections, as well as the inherent nonlinear and non-stationary properties of neural signals, to be more robust.

Insula-Medial Prefrontal Cortex Functional Connectivity Modulated by Transcutaneous Auricular Vagus Nerve Stimulation: An fMRI Study.

Transcutaneous auricular vagus nerve stimulation (taVNS) is an emerging neuromodulation technology that has been reported to be beneficial in the treatment of diseases by several studies, but its exact mechanism of action is still unclear. It has been demonstrated that taVNS can influence interoceptive signals. Notably, the processing of interoceptive signals is directly related to many diseases, such as depression, anxiety, and insomnia. The insula and the medial prefrontal cortex (MPFC) communicate during the bottom-up transmission of taVNS-induced signals, and both play a role in interoceptive signal processing. By focusing on the insula and MPFC, our research pioneers detail the potential interactions between interoceptive signal processing and the neuromodulation effects of taVNS, providing novel insights into the neurobiological mechanisms of taVNS. Two functional connectivity (FC) analyses (region of interest-based and seed-based) were used in this study. We observed that negative connectivity between the insula and the MPFC was significantly weakened following taVNS, while there were no statistical changes in the sham group. Our findings elucidate potential mechanisms linking vagal activity with intrinsic FC among specific brain regions and networks. Specifically, our results indicate that taVNS may enhance the ability to flexibly balance interoceptive awareness and cognitive experiences by modulating the FC between the insula and MPFC. The modulation effects may impact body-brain interactions, suggesting the mechanism of taVNS in therapeutic applications.

Abnormal Insula Network Characteristics in Panic Disorder.

BACKGROUND: Panic disorder (PD) is a common disabling condition characterized by recurrent panic attacks. Emotional and behavioral impairments are associated with functional connectivity (FC) and network abnormalities. We used the whole brain FC, modular networks, and graph-theory analysis to investigate extensive network profiles in PD. METHOD: The functional MRI data from 82 PD and 97 controls were included. Intrinsic FC between each pair of 160 regions, 6 intra-networks, and 15 inter-networks were analyzed. The topological properties were explored. RESULTS: PD patients showed altered FCs within the right insula, between frontal cortex-posterior cingulate cortex (PCC), frontal cortex-cerebellum, and PCC-occipital cortex (corrected P values < 0.001). Lower connections within the Sensorimotor Network (SMN) and SMN-Occipital Network (OCN) were detected (P values < 0.05). Various decreased global and local network features were found in PD (P values < 0.05). In addition, significant correlations were found between PD symptoms and nodal efficiency (Ne) in the insula (r = -0.273, P = 0.016), and the FC of the intra-insula (r = -0.226, P = 0.041). CONCLUSIONS: PD patients present with abnormal functional brain networks, especially the decreased FC and Ne within insula, suggesting that dysfunction of information integration plays an important role in PD.

Dixon MRI-based quantitative parameters of extraocular muscles, intraorbital fat, and lacrimal glands for staging thyroid-associated ophthalmopathy.

OBJECTIVE: To investigate the value of Dixon magnetic resonance imaging (MRI)-based quantitative parameters of extraocular muscles (EOMs), intraorbital fat (IF), and lacrimal glands (LGs) in staging patients with thyroid-associated ophthalmopathy (TAO). METHODS: Two hundred patients with TAO (211 active and 189 inactive eyes) who underwent Dixon MRI for pretreatment evaluation were retrospectively enrolled and divided into training (169 active and 151 inactive eyes) and validation (42 active and 38 inactive eyes) cohorts. The maximum, mean, and minimum values of the signal intensity ratio (SIR), fat fraction (FF), and water fraction (WF) of EOMs, IF, and LGs were measured and compared between the active and inactive groups in the training cohort. Binary logistic regression analysis, receiver operating characteristic curve analysis, and the Delong test were used for further statistical analyses, as appropriate. RESULTS: Compared with inactive TAOs, active TAOs demonstrated significantly greater EOM-SIRmax, EOM-SIRmean, EOM-SIRmin, IF-SIRmax, IF-SIRmean, LG-SIRmax, LG-SIRmean, EOM-WFmean, EOM-WFmin, IF-WFmax, IF-WFmean, and LG-WFmean and lower EOM-FFmax, EOM-FFmean, IF-FFmean, IF-FFmin, and LG-FFmean values (all p < 0.05). The EOM-SIRmean, LG-SIRmean, and LG-FFmean values were independently associated with active TAO (all p < 0.05). The combination of the EOM-SIRmean, LG-SIRmean, and LG-FFmean values showed better performance than the EOM-SIRmean value alone in staging TAO in both the training (AUC, 0.820 vs 0.793; p = 0.016) and validation (AUC, 0.751 vs 0.733, p = 0.341) cohorts. CONCLUSION: Dixon MRI-based parameters of EOMs, LGs, and IF are useful for differentiating active from inactive TAO. The integration of multiple parameters can further improve staging performance. CRITICAL RELEVANCE STATEMENT: In this study, the authors explored the combined value of quantitative parameters of EOMs, IF, and LGs derived from Dixon MRI in staging TAO patients, which can support the establishment of a proper therapeutic plan. KEY POINTS: The quantitative parameters of EOMs, LGs, and IF are useful for staging TAO. The EOM-SIRmean, LG-SIRmean, and LG-FFmean values were found to independently correlate with active TAO. Joint evaluation of orbital tissue improved the ability to assess TAO activity.

Traditional Meiyu-Baiu has been suspended by global warming.

More than 1000 years, the Meiyu-Baiu have shaped the uniqueness of natural resources, civilization and culture in the Yangtze River Basin of China and the main islands of Japan. In recent decades, frequent rainstorms and droughts have seemingly diminished the misty features of traditional Meiyu-Baiu rainfall. However, there is still no consensus on whether their traditional nature is suspended. In this study, we quantitatively demonstrate that the Meiyu-Baiu almost completely lost their traditional features during 1961-2023, ∼80% of which can be attributed to anthropogenic warming. Furthermore, in a warmer future, the traditional Meiyu-Baiu will be more unlikely to appear. This study underscores the urgency in adapting to climate shift because destructive extremes are measurably taking the place of mild and maternal rains.

Versatile filter membrane for effective sampling and real-time quantitative detection of airborne pathogens.

Construction of air filter membranes bearing prominent collecting and transferring capability is highly desirable for detecting airborne pathogens but remains challenging. Here, a hyaluronic acid air filter membrane (HAFM) with tunable heterogeneous micro-nano porous structures is straightforwardly constructed through the ethanol-induced phase separation strategy. Airborne pathogens can be trapped and collected by HAFM with high performance due to the ideal trade-off between removal efficiency and pressure drop. By exempting the sample elution and extraction processes, the HAFM after filtration sampling can not only directly disperse on the agar plate for colony culture but also turn to an aqueous solution for centrifugal enrichment, which significantly reduces the damage and losses of the captured microorganisms. The following combination with ATP bioluminescence endows the HAFM with a real-time quantitative detection function for the captured airborne pathogens. Benefiting from high-efficiency sampling and non-traumatic transfer of airborne pathogens, the real-world bioaerosol concentration can be facilely evaluated by the HAFM-based ATP assay. This work thus not only provides a feasible strategy to fabricate air filter membranes for efficient microbial collection and enrichment but also sheds light on designing advanced protocols for real-time detection of bioaerosols in the field.

Proteomic, single-cell and bulk transcriptomic analysis of plasma and tumor tissues unveil core proteins in response to anti-PD-L1 immunotherapy in triple negative breast cancer.

BACKGROUND: Anti-PD-1/PD-L1 treatment has achieved durable responses in TNBC patients, whereas a fraction of them showed non-sensitivity to the treatment and the mechanism is still unclear. METHODS: Pre- and post-treatment plasma samples from triple negative breast cancer (TNBC) patients treated with immunotherapy were measured by tandem mass tag (TMT) mass spectrometry. Public proteome data of lung cancer and melanoma treated with immunotherapy were employed to validate the findings. Blood and tissue single-cell RNA sequencing (scRNA-seq) data of TNBC patients treated with or without immunotherapy were analyzed to identify the derivations of plasma proteins. RNA-seq data from IMvigor210 and other cancer types were used to validate plasma proteins in predicting response to immunotherapy. RESULTS: A random forest model constructed by FAP, LRG1, LBP and COMP could well predict the response to immunotherapy. The activation of complement cascade was observed in responders, whereas FAP and COMP showed a higher abundance in non-responders and negative correlated with the activation of complements. scRNA-seq and bulk RNA-seq analysis suggested that FAP, COMP and complements were derived from fibroblasts of tumor tissues. CONCLUSIONS: We constructe an effective plasma proteomic model in predicting response to immunotherapy, and find that FAP+ and COMP+ fibroblasts are potential targets for reversing immunotherapy resistance.

Current State of Consultation-Liaison Psychiatry in China and Future Directions.

This article provides an overview of the history and current status of consultation-liaison psychiatry (CLP) in China and its development within the Chinese Society of Psychosomatic Medicine. Over the past decade, various CLP practice models have been developed to meet the diverse needs of different regions in China. Notably, the Chinese Multidisciplinary Integrated Centers of Psychosomatic Medicine have been established as regional hubs throughout the country. Additionally, this article delves into the role of Chinese traditional medicine in the practice of CLP in China. Finally, several projects involving CLP-based multidisciplinary collaboration are highlighted. We hope this article offers a bird's-eye view of CLP in China and opens a window for future collaboration with CLP initiatives in other countries.

Cryoprotectant-Mediated Cold Stress Mitigation in Litchi Flower Development: Transcriptomic and Metabolomic Perspectives.

Temperature is vital in plant growth and agricultural fruit production. Litchi chinensis Sonn, commonly known as litchi, is appreciated for its delicious fruit and fragrant blossoms and is susceptible to stress when exposed to low temperatures. This study investigates the effect of two cryoprotectants that counteract cold stress during litchi flowering, identifies the genes that generate the cold resistance induced by the treatments, and hypothesizes the roles of these genes in cold resistance. Whole plants were treated with Bihu and Liangli cryoprotectant solutions to protect inflorescences below 10 °C. The soluble protein, sugar, fructose, sucrose, glucose, and proline contents were measured during inflorescence. Sucrose synthetase, sucrose phosphate synthetase, antioxidant enzymes (SOD, POD, CAT), and MDA were also monitored throughout the flowering stage. Differentially expressed genes (DEGs), gene ontology, and associated KEGG pathways in the transcriptomics study were investigated. There were 1243 DEGs expressed after Bihu treatment and 1340 in the control samples. Signal transduction pathways were associated with 39 genes in the control group and 43 genes in the Bihu treatment group. The discovery of these genes may contribute to further research on cold resistance mechanisms in litchi. The Bihu treatment was related to 422 low-temperature-sensitive differentially accumulated metabolites (DAMs), as opposed to 408 DAMs in the control, mostly associated with lipid metabolism, organic oxidants, and alcohols. Among them, the most significant differentially accumulated metabolites were involved in pathways such as ß-alanine metabolism, polycyclic aromatic hydrocarbon biosynthesis, linoleic acid metabolism, and histidine metabolism. These results showed that Bihu treatment could potentially promote these favorable traits and increase fruit productivity compared to the Liangli and control treatments. More genomic research into cold stress is needed to support the findings of this study.

Distinguishing bipolar depression, bipolar mania, and major depressive disorder by gut microbial characteristics.

BACKGROUND: Gut microbial disturbance has been widely confirmed in mood disorders. However, little is known about whether gut microbial characteristics can distinguish major depressive disorder (MDD), bipolar depression (BP-D), and bipolar mania (BP-M). METHODS: This was a prospective case-control study. The composition of gut microbiota was profiled using 16S ribosomal RNA (rRNA) gene sequencing of fecal samples and compared between healthy controls (HC; n = 46), MDD (n = 51), BP-D (n = 44), and patients with BP-M (n = 45). RESULTS: Gut microbial compositions were remarkably changed in the patients with MDD, BP-D, and BP-M. Compared to HC, distinct gut microbiome signatures were found in MDD, BP-D, and BP-M, and some gut microbial changes were overlapping between the three mood disorders. Furthermore, we identified a signature of 7 operational taxonomic units (OUT; Prevotellaceae-related OUT22, Prevotellaceae-related OUT31, Prevotellaceae-related OTU770, Ruminococcaceae-related OUT70, Bacteroidaceae-related OTU1536, Propionibacteriaceae-related OTU97, Acidaminococcaceae-related OTU34) that can distinguish patients with MDD from those with BP-D, BP-M, or HC, with area under the curve (AUC) values ranging from 0.910 to 0.996. CONCLUSION: Our results provide the clinical rationale for the discriminative diagnosis of MDD, BP-D, and BP-M by characteristic gut microbial features.

Sorafenib inhibits ossification of the posterior longitudinal ligament by blocking LOXL2-mediated vascularization.

Ossification of the Posterior Longitudinal Ligament (OPLL) is a degenerative hyperostosis disease characterized by the transformation of the soft and elastic vertebral ligament into bone, resulting in limited spinal mobility and nerve compression. Employing both bulk and single-cell RNA sequencing, we elucidate the molecular characteristics, cellular components, and their evolution during the OPLL process at a single-cell resolution, and validate these findings in clinical samples. This study also uncovers the capability of ligament stem cells to exhibit endothelial cell-like phenotypes in vitro and in vivo. Notably, our study identifies LOXL2 as a key regulator in this process. Through gain-and loss-of-function studies, we elucidate the role of LOXL2 in the endothelial-like differentiation of ligament cells. It acts via the HIF1A pathway, promoting the secretion of downstream VEGFA and PDGF-BB. This function is not related to the enzymatic activity of LOXL2. Furthermore, we identify sorafenib, a broad-spectrum tyrosine kinase inhibitor, as an effective suppressor of LOXL2-mediated vascular morphogenesis. By disrupting the coupling between vascularization and osteogenesis, sorafenib demonstrates significant inhibition of OPLL progression in both BMP-induced and enpp1 deficiency-induced animal models while having no discernible effect on normal bone mass. These findings underscore the potential of sorafenib as a therapeutic intervention for OPLL.

Synthesis and Evaluation of [18F]AlF-NOTA-c-DVAP: A Novel PET Probe for Imaging GRP78 in Cancer.

GRP78, a member of the HSP70 superfamily, is an endoplasmic reticulum chaperone protein overexpressed in various cancers, making it a promising target for cancer imaging and therapy. Positron emission tomography (PET) imaging offers unique advantages in real time, noninvasive tumor imaging, rendering it a suitable tool for targeting GRP78 in tumor imaging to guide targeted therapy. Several studies have reported successful tumor imaging using PET probes targeting GRP78. However, existing PET probes face challenges such as low tumor uptake, inadequate in vivo distribution, and high abdominal background signal. Therefore, this study introduces a novel peptide PET probe, [18F]AlF-NOTA-c-DVAP, for targeted tumor imaging of GRP78. [18F]AlF-NOTA-c-DVAP was radiolabeled with fluoride-18 using the aluminum-[18F]fluoride ([18F]AlF) method. The study assessed the partition coefficients, stability in vitro, and metabolic stability of [18F]AlF-NOTA-c-DVAP. Micro-PET imaging, pharmacokinetic analysis, and biodistribution studies were carried out in tumor-bearing mice to evaluate the probe's performance. Docking studies and pharmacokinetic analyses of [18F]AlF-NOTA-c-DVAP were also performed. Immunohistochemical and immunofluorescence analyses were conducted to confirm GRP78 expression in tumor tissues. The probe's binding affinity to GRP78 was analyzed by molecular docking simulation. [18F]AlF-NOTA-c-DVAP was radiolabeled in just 25 min with a high yield of 51 ± 16%, a radiochemical purity of 99%, and molar activity within the range of 20-50 GBq/µmol. [18F]AlF-NOTA-c-DVAP demonstrated high stability in vitro and in vivo, with a logD value of -3.41 ± 0.03. Dynamic PET imaging of [18F]AlF-NOTA-c-DVAP in tumors showed rapid uptake and sustained retention, with minimal background uptake. Biodistribution studies revealed rapid blood clearance and excretion through the kidneys following a single-compartment reversible metabolic model. In PET imaging, the T/M ratios for A549 tumors (high GRP78 expression), MDA-MB-231 tumors (medium expression), and HepG2 tumors (low expression) at 60 min postintravenous injection were 10.48 ± 1.39, 6.25 ± 0.47, and 3.15 ± 1.15% ID/g, respectively, indicating a positive correlation with GRP78 expression. This study demonstrates the feasibility of using [18F]AlF-NOTA-c-DVAP as a PET tracer for imaging GRP78 in tumors. The probe shows promising results in terms of stability, specificity, and tumor targeting. Further research may explore the clinical utility and potential therapeutic applications of this PET tracer for cancer diagnosis.

Altered Static and Dynamic Brain Functional Topological Organization in Patients With Dysthyroid Optic Neuropathy.

CONTEXT: Dysthyroid optic neuropathy (DON) is a serious vision-threatening complication of thyroid-associated ophthalmopathy (TAO). Exploration of the underlying mechanisms of DON is critical for its timely clinical diagnosis. OBJECTIVE: We hypothesized that TAO patients with DON may have altered brain functional networks. We aimed to explore the alterations of static and dynamic functional connectomes in patients with and without DON using resting-state functional magnetic resonance imaging with the graph theory method. METHODS: A cross-sectional study was conducted at a grade A tertiary hospital with 66 TAO patients (28 DON and 38 non-DON) and 30 healthy controls (HCs). Main outcome measures included topological properties of functional networks. RESULTS: For static properties, DON patients exhibited lower global efficiency (Eg), local efficiency, normalized clustering coefficient, small-worldness (σ), and higher characteristic path length (Lp) than HCs. DON and non-DON patients both exhibited varying degrees of abnormalities in nodal properties. Meanwhile, compared with non-DON, DON patients exhibited abnormalities in nodal properties in the orbitofrontal cortex and visual network (VN). For dynamic properties, the DON group exhibited higher variance in Eg and Lp than non-DON and HC groups. A strengthened subnetwork with VN as the core was identified in the DON cohort. Significant correlations were found between network properties and clinical variables. For distinguishing DON, the combination of static and dynamic network properties exhibited optimal diagnostic performance. CONCLUSION: Functional network alterations were observed both in DON and non-DON patients, providing novel insights into the underlying neural mechanisms of disease. Functional network properties may be potential biomarkers for reflecting the progression of TAO from non-DON to DON.