IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models.

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich vision-language correlation from image-text pairs, like BLIP-2 and GPT-4, have been intensively investigated. However, despite these developments, the application of LLMs and VLMs in image quality assessment (IQA), particularly in medical imaging, remains unexplored. This is valuable for objective performance evaluation and potential supplement or even replacement of radiologists' opinions. To this end, this study introduces IQAGPT, an innovative computed tomography (CT) IQA system that integrates image-quality captioning VLM with ChatGPT to generate quality scores and textual reports. First, a CT-IQA dataset comprising 1,000 CT slices with diverse quality levels is professionally annotated and compiled for training and evaluation. To better leverage the capabilities of LLMs, the annotated quality scores are converted into semantically rich text descriptions using a prompt template. Second, the image-quality captioning VLM is fine-tuned on the CT-IQA dataset to generate quality descriptions. The captioning model fuses image and text features through cross-modal attention. Third, based on the quality descriptions, users verbally request ChatGPT to rate image-quality scores or produce radiological quality reports. Results demonstrate the feasibility of assessing image quality using LLMs. The proposed IQAGPT outperformed GPT-4 and CLIP-IQA, as well as multitask classification and regression models that solely rely on images.

LncRNA H19 Promotes Gastric Cancer Metastasis via miR-148-3p/SOX-12 Axis.

Background: Gastric cancer (GC) is the most common malignant tumor and ranks third in the world. LncRNA H19 (H19), one of the members of lncRNA, is overexpressed in various tumors. However, many undetermined molecular mechanisms by which H19 promotes GC progression still need to be further investigated. Methodology. A series of experiments was used to confirm the undetermined molecular mechanism including wound healing and transwell assays. Key Results. In this study, a significant upregulation of H19 expression was detected in GC cells and tissues. The poor overall survival was observed in GC patient with high H19 expression. Overexpression of H19 promoted the migration of GC cells, while knockdown of H19 significantly inhibited cell migration. Moreover, miR-148a-3p had a certain negative correlation with H19. Luciferase reporter assay confirmed that H19 could directly bind to miR-148a-3p. As expected, miR-148a mimics inhibited cell migration and invasion induced by H19 overexpression. The above findings proved that H19 functions as a miRNA sponge and verified that miR-148a-3p is the H19-associated miRNA in GC. We also confirmed that SOX-12 expression was upregulated in GC patient's samples. SOX-12 expression was positively correlated with expression of H19 and was able to directly bind to miR-148a-3p. Importantly, in vitro wound healing assay showed that knockout of SOX-12 could reverse the promoting effect of H19 overexpression on cell migration. Conclusion: In conclusion, H19 has certain application value in the diagnosis and prognosis of GC. Specifically, H19 accelerates GCs to migration and metastasis by miR-138a-3p/SOX-12 axis.

Association Between Nonalcoholic Fatty Liver Disease and the Risk of Cardiovascular Disease in the Middle-Age and Elderly Population of Northern China: A Cross-Sectional Study.

Background: Nonalcoholic fatty liver disease (NAFLD) has become a major global health burden, which increases the risk of extra-hepatic complications such as type 2 diabetes mellitus (T2DM), dyslipidemia, metabolic syndrome (MetS), and cardiovascular disease (CVD). However, NAFLD remains underappreciated and underdiagnosed. Our study aimed to explore the prevalence of NAFLD and the association between NAFLD and CVD events among adults aged 40 and older in Northern China. Methods: This study was conducted in the Shijingshan district of Beijing, China from November 2011 to August 2012. A total of 18891 subjects were recruited in the study. The information including demographical information, lifestyle, previous history of diabetes, hypertension, dyslipidemia, CVD, and liver disease were gathered. Data on physical examination, blood lipid profile, fasting blood glucose, and 2-hour blood glucose were recorded. Determination of MetS was according to T2DM guideline of Chinese Diabetes Society (2020 edition). The association between CVD and NAFLD was evaluated by multivariate logistic regression. Results: The prevalence of NAFLD was 15.2%. After adjustment for age, smoking status, alcohol intake, WC, hypertension, dyslipidemia and hyperglycemia, the odds ratios (ORs) of CVD in men were 1.622 (95%CI: 1.345-1.957) and 1.990 (95%CI: 1.709-2.316) in women with NAFLD, compared with the subjects without NAFLD. Conclusions: NAFLD is independently associated with increased risk of CVD development.

The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation Detection.

A National Institutes of Health (NIH) and U.S. Department of Energy (DOE) Office of Science virtual workshop on shared general topics was held in July of 2021 and reported on in this publication in January of 2023. Following the inaugural 2021 joint meeting representatives from the DOE Office of Science and NIH met to discuss organizing a second joint workshop that would concentrate on radiation detection to bring together teams from both agencies and their grantee populations to stimulate collaboration and efficiency. To meet this scientific mission within the NIH and DOE radiation detection space, the organizers assembled workshop sessions covering the state-of-the-art in cameras, detectors, and sensors for radiation external and internal (diagnostic and therapeutic) to human, data acquisition and electronics, image reconstruction and processing, and the application of artificial intelligence. NIH and DOE are committed to continuing the process of convening a joint workshop every 12-24 months. This Special Report recaps the findings of this second workshop. Beyond showing only the innovations and areas of success, important gaps in our knowledge were defined and presented. We summarize by defining four areas of greatest opportunity and need that emerged from the unique, dynamic dialogue the in-person workshop provided the attendees.

Unraveling Cross-Organ Impacts of Airborne Pollutants: A Multiomics Study on Respiratory Exposure and Gastrointestinal Health.

Poor air quality is increasingly linked to gastrointestinal diseases, suggesting a potential correlation with human intestine health. However, this relationship remains largely unexplored due to limited research. This study used a controlled mouse model exposed to cooking oil fumes (COFs) and metagenomics, transcriptomics, and metabolomics to elucidate interactions between intestine microbiota and host metabolism under environmental stress. Our findings reveal that short-term COF inhalation induces pulmonary inflammation within 3 days and leads to gastrointestinal disturbances, elucidating a pathway connecting respiratory exposure to intestinal dysfunction. The exposure intensity significantly correlates with changes in intestinal tissue integrity, microbial composition, and metabolic function. Extended exposure of 7 days disrupts intestine microbiota and alters tryptophan metabolism, with further changes observed after 14 days, highlighting an adaptive response. These results highlight the vulnerability of intestinal health to airborne pollutants and suggest a pathway through which inhaled pollutants may affect distant organ systems.

Water-soluble biodegradable polyesters with pH and ionic responsivity.

The synthesis of novel water-soluble polymers with biodegradability is an effective way to mitigate their negative environmental impacts. In this study, semi-aromatic copolyester poly(butylene succinate-co-butylene terephthalate) (PBST) with exceptional biodegradability is used as the resin matrix. Anionic sodium 1-3-isophthalate-5-sulfonate (SIPA) is introduced as a fourth monomer to prepare random poly(butylene succinate-co-butylene terephthalate-co-butylene 5-sodiosulfoisophthalate) (PBSTS) copolyesters by melt copolymerization. The incorporation of ionic groups enhances the hydrophilicity and water absorption of the copolyesters, resulting in water-soluble materials that exhibit ionic and temperature responsivity. Furthermore, the ionized biodegradable copolyesters demonstrate distinct pH-dependent degradation, which is accelerated at pH = 5.5 and 8.5 but inhibited at pH = 7.2. Degradation assessments in simulated body fluids reveal that the PBSTS copolyesters exhibit significant degradation in gastric fluids at pH = 1.5 with minimal degradation in intestinal fluids at pH = 6.8 and in body fluids at pH = 7.0. This unique degradation performance highlights the potential of these materials for addressing the challenges associated with selective drug delivery and localized controlled release in the human body.

Chinese verbal fluency deficiency in temporal lobe epilepsy with and without hippocampal sclerosis: a multiscale study.

To test a Chinese character version of phonemic verbal fluency task in patients with temporal lobe epilepsy (TLE), and assess the verbal fluency deficiency pattern in TLE with and without hippocampal sclerosis. Thirty patients with TLE and hippocampal sclerosis (TLE-HS), 28 patients with TLE and without hippocampal sclerosis (TLE-NHS), and 29 demographically matched healthy controls (HC) participated in this cross-sectional study. Both sexes were enrolled. Participants finished a Chinese character verbal fluency (VFC) task during functional MRI. The activation/deactivation maps, functional connectivity, degree centrality, and community features of left frontal and temporal regions were compared. Neural network classification model was applied to differentiate TLE-HS and TLE-NHS using functional statistics. The VFC scores were correlated with semantic fluency in HC while correlated with phonemic fluency in TLE-NHS. Activation and deactivation deficiency was observed in TLE-HS and TLE-NHS (p < 0.001, k ≥ 10). Functional connectivity, degree centrality, and community features of anterior inferior temporal gyri were impaired in TLE-HS and retained or even enhanced in TLE-NHS (p < 0.05, FDR-corrected). The functional connectivity was correlated with phonemic fluency (p < 0.05, FDR-corrected). The neural network classification reached an area under curve = 0.90 in diagnosing hippocampal sclerosis. The VFC task is a Chinese phonemic verbal fluency task suitable for clinical application in TLE. During the VFC task, functional connectivity of phonemic circuits was impaired in TLE-HS and was enhanced in TLE-NHS, representing a compensative phonemic searching strategy applied by patients with TLE-NHS.Significance Statement Verbal fluency tasks are essential assessment for patients with epilepsy. However, the testing and applying of Chinese phonemic verbal fluency is at an initial stage. We tested a Chinses character verbal fluency task in Chinese with temporal lobe epilepsy, and depicted the functional alteration patterns in them. Our work provided a Chinese verbal fluency task suitable for clinical application. Our results highlighted the importance of left anterior inferior frontal gyrus in Chinese, and might have impact on the surgical protocol of Chinese patients with left TLE and promote further development of rehabilitative and therapeutic approaches for verbal fluency decline.

Fine Structure and Electrochemical Performance Investigations of Spherical LiMn0.6Fe0.4PO4/C Cathode Material Synthesized via a Spray-Drying Route at Various Calcination Temperatures.

LiMnxFe1-xPO4/C is characterized by excellent multiplicative performance and high operating voltage, and as a type of cathode material, it has a high electronic conductivity and thus has received much attention. In this paper, carbon-coated LiMn0.6Fe0.4PO4/C was synthesized using glucose + PEG2000 as the carbon source by wet sanding and spray-drying. The experimental results show that the use of sanding and the spray-drying method can make the particle size distribution of LiMn0.6Fe0.4PO4/C powder more uniform. The initial discharge specific capacity of the LiMn0.6Fe0.4PO4/C battery was 144.3 mA h g-1, and after 100 cycles at 1 C current, the discharge specific capacity of the battery remained at 128.2 mA h g-1 with a cycling efficiency of 94.3%. At the same time, the oxidation states and coordination environments of the elements Fe and Mn were elucidated by X-ray absorption fine structure spectroscopy. And the ex-Fe-MS was tested under different charging and discharging conditions. The sample optimized by the orthogonal test has good cycle stability and multiplication performance.

Enhanced treatment of breast cancer brain metastases with oncolytic virus expressing anti-CD47 antibody and temozolomide.

Limited therapeutic options are available for patients with breast cancer brain metastases (BCBM), and thus there is an urgent need for novel treatment approaches. We previously engineered an effective oncolytic herpes simplex virus 1 (oHSV) expressing a full-length anti-CD47 monoclonal antibody (mAb) with a human IgG1 scaffold (OV-αCD47-G1) that was used to treat both ovarian cancer and glioblastoma. Here, we demonstrate that the combination of OV-αCD47-G1 and temozolomide (TMZ) improve outcomes in preclinical models of BCBM. The combination of TMZ with OV-αCD47-G1 synergistically increased macrophage phagocytosis against breast tumor cells and led to greater activation of NK cell cytotoxicity. In addition, the combination of OV-αCD47-G1 with TMZ significantly prolonged the survival of tumor-bearing mice when compared with TMZ or OV-αCD47-G1 alone. Combination treatment with the mouse counterpart of OV-αCD47-G1, termed OV-A4-IgG2b, also enhanced mouse macrophage phagocytosis, NK cell cytotoxicity, and survival in an immunocompetent model of mice bearing BCBM compared with TMZ or OV-A4-IgG2b alone. Collectively, these results suggest that OV-αCD47-G1 combined with TMZ should be explored in patients with BCBM.

Dynamic memristor for physical reservoir computing.

Reservoir computing (RC) has attracted considerable attention for its efficient handling of temporal signals and lower training costs. As a nonlinear dynamic system, RC can map low-dimensional inputs into high-dimensional spaces and implement classification using a simple linear readout layer. The memristor exhibits complex dynamic characteristics due to its internal physical processes, which renders them an ideal choice for the implementation of physical reservoir computing (PRC) systems. This review focuses on PRC systems based on memristors, explaining the resistive switching mechanism at the device level and emphasizing the tunability of their dynamic behavior. The development of memristor-based reservoir computing systems is highlighted, along with discussions on the challenges faced by this field and potential future research directions.

A denoising diffusion probabilistic model for metal artifact reduction in CT.

The presence of metal objects leads to corrupted CT projection measurements, resulting in metal artifacts in the reconstructed CT images. AI promises to offer improved solutions to estimate missing sinogram data for metal artifact reduction (MAR), as previously shown with convolutional neural networks (CNNs) and generative adversarial networks (GANs). Recently, denoising diffusion probabilistic models (DDPM) have shown great promise in image generation tasks, potentially outperforming GANs. In this study, a DDPM-based approach is proposed for inpainting of missing sinogram data for improved MAR. The proposed model is unconditionally trained, free from information on metal objects, which can potentially enhance its generalization capabilities across different types of metal implants compared to conditionally trained approaches. The performance of the proposed technique was evaluated and compared to the state-of-the-art normalized MAR (NMAR) approach as well as to CNN-based and GAN-based MAR approaches. The DDPM-based approach provided significantly higher SSIM and PSNR, as compared to NMAR (SSIM: p < 10-26; PSNR: p < 10-21), the CNN (SSIM: p < 10-25; PSNR: p < 10-9) and the GAN (SSIM: p < 10-6; PSNR: p < 0.05) methods. The DDPM-MAR technique was further evaluated based on clinically relevant image quality metrics on clinical CT images with virtually introduced metal objects and metal artifacts, demonstrating superior quality relative to the other three models. In general, the AI-based techniques showed improved MAR performance compared to the non-AI-based NMAR approach. The proposed methodology shows promise in enhancing the effectiveness of MAR, and therefore improving the diagnostic accuracy of CT.

Unbiasing Fairness Evaluation of Radiology AI Model.

Fairness of artificial intelligence and machine learning models, often caused by imbalanced datasets, has long been a concern. While many efforts aim to minimize model bias, this study suggests that traditional fairness evaluation methods may be biased, highlighting the need for a proper evaluation scheme with multiple evaluation metrics due to varying results under different criteria. Moreover, the limited data size of minority groups introduces significant data uncertainty, which can undermine the judgement of fairness. This paper introduces an innovative evaluation approach that estimates data uncertainty in minority groups through bootstrapping from majority groups for a more objective statistical assessment. Extensive experiments reveal that traditional evaluation methods might have drawn inaccurate conclusions about model fairness. The proposed method delivers an unbiased fairness assessment by adeptly addressing the inherent complications of model evaluation on imbalanced datasets. The results show that such comprehensive evaluation can provide more confidence when adopting those models.

DATA-DRIVEN IMAGING GEOMETRIC RECOVERY OF ULTRAHIGH RESOLUTION ROBOTIC MICRO-CT FOR IN-VIVO AND OTHER APPLICATIONS.

We introduce an ultrahigh-resolution (50µm) robotic micro-CT design for localized imaging of carotid plaques using robotic arms, cutting-edge detector, and machine learning technologies. To combat geometric error-induced artifacts in interior CT scans, we propose a data-driven geometry estimation method that maximizes the consistency between projection data and the reprojection counterparts of a reconstructed volume. Particularly, we use a normalized cross correlation metric to overcome the projection truncation effect. Our approach is validated on a robotic CT scan of a sacrificed mouse and a micro-CT phantom scan, both producing sharper images with finer details than that prior correction.

Toward a nomenclature consensus for diverse intelligent systems: Call for collaboration.

Disagreements about language use are common both between and within fields. Where interests require multidisciplinary collaboration or the field of research has the potential to impact society at large, it becomes critical to minimize these disagreements where possible. The development of diverse intelligent systems, regardless of the substrate (e.g., silicon vs. biology), is a case where both conditions are met. Significant advancements have occurred in the development of technology progressing toward these diverse intelligence systems. Whether progress is silicon based, such as the use of large language models, or through synthetic biology methods, such as the development of organoids, a clear need for a community-based approach to seeking consensus on nomenclature is now vital. Here, we welcome collaboration from the wider scientific community, proposing a pathway forward to achieving this intention, highlighting key terms and fields of relevance, and suggesting potential consensus-making methods to be applied.

Effects of nasal allergens and environmental particulate matter on brainstem metabolites and the consequence of brain-spleen axis in allergic rhinitis.

BACKGROUND: The growing consensus links exposure to fine particulate matter (PM2.5) with an increased risk of respiratory diseases. However, little is known about the additional effects of particulate matter on brainstem function in allergic rhinitis (AR). Furthermore, it is unknown to what extent the PM2.5-induced effects in the brainstem affect the inflammatory response in AR. This study aimed to determine the effects, mechanisms and consequences of brainstem neural activity altered by allergenic stimulation and PM2.5 exposure. METHODS: Using an AR model of ovalbumin (OVA) elicitation and whole-body PM2.5 exposure, the metabolic profile of the brainstem post-allergen stimulation was characterized through in vivo proton magnetic resonance imaging (1H-MRS). Then, the transient receptor potential vanilloid-1 (TRPV1) neuronal expression and sensitivity in the trigeminal nerve in AR were investigated. The link between TRPV1 expression and brainstem differential metabolites was also determined. Finally, we evaluated the mediating effects of brainstem metabolites and the consequences in the brain-spleen axis in the inflammatory response of AR. RESULTS: Exposure to allergens and PM2.5 led to changes in the metabolic profiles of the brainstem, particularly affecting levels of glutamine (Gln) and glutamate (Glu). This exposure also increased the expression and sensitivity of TRPV1+ neurons in the trigeminal nerve, with the levels of TRPV1 expression closely linked to the brainstem metabolism of Glu and Gln. Moreover, allergens increased the activity of p38, while PM2.5 led to the phosphorylation of p38 and ERK, resulting in the upregulation of TRPV1 expression. The brainstem metabolites Glu and Gln were found to partially mediate the impact of TRPV1 on AR inflammation, which was supported by the presence of pro-inflammatory changes in the brain-spleen axis. CONCLUSION: Brainstem metabolites are altered under allergen stimulation and additional PM2.5 exposure in AR via sensitization of the trigeminal nerve, which exacerbates the inflammatory response via the brain-splenic axis.

Reconfigurable Origami/Kirigami Metamaterial Absorbers Developed by Fast Inverse Design and Low-Concentration MXene Inks.

Reconfigurable metamaterial absorbers (MAs), consisting of tunable elements or deformable structures, are able to transform their absorbing bandwidth and amplitude in response to environmental changes. Among the options for building reconfigurable MAs, origami/kirigami structures show great potential because of their ability to combine excellent mechanical and electromagnetic (EM) properties. However, neither the trial-and-error-based design method nor the complex fabrication process can meet the requirement of developing high-performance MAs. Accordingly, this work introduces a deep-learning-based algorithm to realize the fast inverse design of origami MAs. Then, an accordion-origami coding MA is generated with reconfigurable EM responses that can be smoothly transformed between ultrabroadband absorption (5.5-20 GHz, folding angle α = 82°) and high reflection (2-20 GHz, RL > -1.5 dB, α = 0°) under y-polarized waves. However, the asymmetric coding pattern and accordion-origami deformation lead to typical polarization-sensitive absorbing performance (2-20 GHz, RL > -4 dB, α < 90°) under x-polarized waves. For the first time, a kirigami polarization rotation surface with switchable operation band is adapted to balance the absorbing performance of accordion-origami MA under orthogonal polarized waves. As a result, the stacked origami-kirigami MA maintains polarization-insensitive ultrabroadband absorption (4.4-20 GHz) at ß = 0° and could be transformed into a narrowband absorber through deformation. Besides, the adapted origami/kirigami structures possess excellent mechanical properties such as low relative density, negative Poisson's ratio, and tunable specific energy absorption. Moreover, by modulating the PEDOT:PSS conductive bridges among MXene nanosheets, a series of low-concentration MXene-PEDOT:PSS inks (∼46 mg·mL-1) with adjustable square resistance (5-32.5 Ω/sq) are developed to fabricate the metamaterials via screen printing. Owing to the universal design scheme, this work supplies a promising paradigm for developing low-cost and high-performance reconfigurable EM absorbers.

Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction.

Early diagnosis and accurate prognosis of colorectal cancer is critical for determining optimal treatment plans and maximizing patient outcomes, especially as the disease progresses into liver metastases. Computed tomography (CT) is a frontline tool for this task; however, the preservation of predictive radiomic features is highly dependent on the scanning protocol and reconstruction algorithm. We hypothesized that image reconstruction with a high-frequency kernel could result in a better characterization of liver metastases features via deep neural networks. This kernel produces images that appear noisier but preserve more sinogram information. A simulation pipeline was developed to study the effects of imaging parameters on the ability to characterize the features of liver metastases. This pipeline utilizes a fractal approach to generate a diverse population of shapes representing virtual metastases, and then it superimposes them on a realistic CT liver region to perform a virtual CT scan using CatSim. Datasets of 10,000 liver metastases were generated, scanned, and reconstructed using either standard or high-frequency kernels. These data were used to train and validate deep neural networks to recover crafted metastases characteristics, such as internal heterogeneity, edge sharpness, and edge fractal dimension. In the absence of noise, models scored, on average, 12.2% ( α = 0.012 ) and 7.5% ( α = 0.049 ) lower squared error for characterizing edge sharpness and fractal dimension, respectively, when using high-frequency reconstructions compared to standard. However, the differences in performance were statistically insignificant when a typical level of CT noise was simulated in the clinical scan. Our results suggest that high-frequency reconstruction kernels can better preserve information for downstream artificial intelligence-based radiomic characterization, provided that noise is limited. Future work should investigate the information-preserving kernels in datasets with clinical labels.

FvUVI4 inhibits cell division and cell expansion to modulate fruit development in Fragaria vesca.

Fruit development is mainly regulated by cell division and expansion. As a negative regulator of the anaphase-promoting complex/cyclosome, UVI4 plays important roles in plant growth and development via coordinating cell cycle. However, currently there is no report on UVI4's functions in regulating fruit development in strawberry. Here, Fragaria vesca homolog FvUVI4 is identified and localizes in the nucleus. FvUVI4 has high gene expression in roots, leaves, flower, buds and green fruits, and low expression in petiole, stem, white and yellow fruit. Fruit development of F. vesca 'Hawaii4' is regulated by endoreduplication, and the expression of FvUVI4 is negatively correlated with fruit cell size. Overexpression of FvUVI4 inhibits endoreduplication of leaves, flowers and fruits in both Arabidopsis and F. vesca 'Hawaii4', thereby limiting cell expansion and decreasing cell area. Overexpression of FvUVI4 also inhibits mitotic cell cycle leading to decreased cell number, and ultimately affects the growth of leaves, petals and seeds or fruits. Arabidopsis uvi4 mutants obtained via CRISPR-Cas9 technology display opposite growth phenotypes to Arabidopsis and F. vesca 'Hawaii4' overexpression lines, which can be restored by overexpression of FvUVI4 in Arabidopsis uvi4 mutants. In conclusion, our study indicates that FvUVI4 inhibits cell expansion and cell division to modulate receptacle development in woodland strawberry.

The circular RNA hsa_circ_0045800 serves as a favorable biomarker in pathogenesis of sjögren's syndrome.

BACKGROUND: Circular RNAs (circRNAs) play various roles in the development of many autoimmune diseases. However, their expression profiles and specific function in Sjögren's Syndrome remains largely unknown. OBJECTIVES: We aimed to investigate circRNAs potential diagnostic value in primary Sjögren's syndrome (pSS) and contribution to the pathogenesis of pSS. METHODS: This study included 102 subjects, 51 pSS patients and 51 healthy controls. The concentration of hsa_circ_0045800 was analyzed in peripheral blood mononuclear cells obtained from 51 pSS patients and 51 healthy controls by qRT-PCR. We established a receiver operating characteristic curve (ROC) to assess the biological diagnostic value of hsa_circ_0045800 for pSS. In addition, we analyzed the correlation between hsa_circ_0045800 and disease activity in Sjogren's syndrome. A differential analysis was also conducted on the concentration of hsa_circ_0045800 in patients in pSS patients before and after treatment. We studied the downstream mechanism of hsa_circ_0045800 through bioinformatics analysis and confirmed it using luciferase reporter gene assay. RESULTS: We confirmed that the concentration of hsa_circ_0045800 was elevated 10.4-fold in peripheral blood mononuclear cells of pSS patients than in healthy controls (p = 0.00). In the pSS active disease group, the concentration of hsa_circ_0045800 is 2.5-fold higher compared to the pSS non-active disease group (p = 0.04). The concentration of hsa_circ_0045800 after treatment was decreased by 80% compared with that before treatment (p = 0.037), suggesting its utility as a potential marker for monitoring treatment efficacy. ROC curve analysis showed that the diagnostic value of hsa_circ_0045800 in pSS patients was significantly higher than that in healthy controls, with an area under the curve of 0.865, a sensitivity of 74%, and a specificity of 92%. The concentration of hsa_circ_0045800 is correlated with various clinical factors: the concentration of hsa_circ_0045800 is positively associated with age (r = 0.328, P = 0.019), oral dryness (r = 0.331, P = 0.017), while it is negatively correlated with HGB (r = -0.435, P = 0.001) and and hypothyroidism (r = -0.318, P = 0.023). Bioinformatics predictions and luciferase assays indicated that hsa_circ_0045800 acts as a molecular sponge for miR-1247-5p, with SMAD2 being a target gene of miR-1247-5p. CONCLUSION: Our study results show that hsa_circ_0045800 potentially contributes to the development and progression of pSS via the miR-1247-5p/SMAD2 pathway. Peripheral blood mononuclear cells are directly involved in the pathogenesis of pSS, and the discovery of hsa_circ_0045800 in peripheral blood mononuclear cells highlights its potential as a novel biomarker for disease activity and diagnosis in patients with pSS. Key Points • The concentration of hsa_circ_0045800 was higher in peripheral blood mononuclear cells of pSS patients. • Hsa_circ_0045800 promoted pSS progression through miR-1247-5p-SMAD2 axis. • Hsa_circ_0045800 is a potential biomarker for pSS.