Introduction

Inflammatory Bowel Disease (IBD)^1,2 requires close monitoring to detect flare ups early and guide treatment. While endoscopy is the gold standard, it is invasive, costly, and uncomfortable^1,2. Intestinal Ultrasound (IUS) is a non-invasive alternative with strong correlation to endoscopic findings—especially bowel wall thickness (BWT), a marker of disease activity³. Nevertheless, IUS remains limited due to operator dependence and a steep learning curve⁴.
AI has improved consistency in other domains, e.g. endoscopic evaluation, but its application to IUS in IBD remains underexplored. Prior models lack interpretability and require manual image cropping, or are trained on ideal, selected data, limiting clinical use^5,6.

Aims & Methods

We aim to develop a deep-learning model that automatically identifies and paints the bowel wall and measures BWT directly from raw clinical IUS images.
A training dataset of 570 images from 144 IUS videos and a testing dataset of 55 images from 55 separate exams were created. All images were extracted from previously performed IUS examinations reflecting real-world variation, including e.g. unclear boundaries and artefacts.
All images were annotated by International Bowel Ultrasound Group (IBUS) certified experts, including outline-paintings of the inner and outer bowel wall and two BWT measurements.
The AI consists of a combination of Convolutional neural networks and other image processing algorithms.
Evaluation included BWT error against the expert mean, classification accuracy using the standard IBUS 3 mm threshold³, and a leave-one-out comparison with individual doctors.

Results

The model produced predictions on 54 of 55 test images.
The model deviated from the gold standard mean by 0.98 mm (SD 1.1 mm) per image on the regression task. The average distance to expert-defined bounds was 0.44 mm (SD 0.89 mm), with 59% of predictions inside this range.
For classification (using a 3 mm threshold), the model reached an accuracy of 0.77, sensitivity of 0.69, specificity of 0.94, and Cohen’s Kappa of 0.56.
In the leave-one-out analysis, expert performance ranged from 0.89–0.93 accuracy and 0.79–0.83 Kappa. Depending on which expert was excluded from the gold standard, the model achieved 0.74–0.80 accuracy and 0.49–0.60 Kappa. Experts stayed within expert-defined bounds in 72–81% of cases, while the model did so in 46–55%.

Conclusion

Clinically, the model performed well. An error of 0.5–1 mm is negligible in practice and matches typical variation in manual measurements. Many real-world test images had BWT values near the 3 mm threshold, so small deviations led to misclassifications. In practice, a 2.5 mm reading could still raise concerns based on symptoms³.
While the system alone cannot provide expert-level BWT measurements, it could provide assistance to experts as well as non-expert and junior doctors, especially in locating the bowel, which is an essential part of IUS.
The model works on unprocessed clinical data, with the only selection criteria being that there is an identifiable bowel segment, measurable by an IBUS-certified doctor. Allowing the images to reflect realistic conditions
In summary, we developed an AI model that identifies the bowel and measures BWT with acceptable accuracy. We have already started the processes of collecting video data, to extend the AI’s functionality to a fully clinical setting.

References

1. Torres J, Mehandru S, Colombel JF, Peyrin-Biroulet L. Crohn’s disease. The Lancet. 2017;389(10080):1741-1755. doi:10.1016/S0140-6736(16)31711-1
2. Ungaro R, Mehandru S, Allen PB, Peyrin-Biroulet L, Colombel JF. Ulcerative colitis. Lancet. 2017;389(10080):1756-1770. doi:10.1016/S0140-6736(16)32126-2
3. Novak KL, Group I, Nylund K, et al. Expert Consensus on Optimal Acquisition and Development of the International Bowel Ultrasound Segmental Activity Score [IBUS-SAS]: A Reliability and Inter-rater Variability Study on Intestinal Ultrasonography in Crohn’s Disease. J Crohns Colitis. 2021;15(4):609-616. doi:10.1093/ECCO-JCC/JJAA216
4 Bove L, Meyer J, Collins M, Frampas E, Bourreille A, Le Berre C. Understanding the learning curve of intestinal ultrasound in inflammatory bowel disease: A comparative study between novice, regular, and expert. Clin Res Hepatol Gastroenterol. 2025;49(3):102548. doi:10.1016/J.CLINRE.2025.102548
5. Kumaralingam L, Le May K, Dang VB, Alavi J, Huynh HQ, Le LH. Artificial intelligence-assisted approach to assessing bowel wall thickness in pediatric inflammatory bowel disease using intestinal ultrasound images. J Crohns Colitis. 2025;19(4). doi:10.1093/ECCO-JCC/JJAF037
6. Carter D, Albshesh A, Shimon C, et al. Automatized Detection of Crohn’s Disease in Intestinal Ultrasound Using Convolutional Neural Network. Inflamm Bowel Dis. February 2023:1-6. doi:10.1093/IBD/IZAD014

Introduction

Spasmolytic polypeptide expressing metaplasia (SPEM) is a cell repair lineage and is a very important phenotype of gastric mucosal injury and precancerous lesion.
Previously, parietal cells loss is considered as the first step and followed with chief cells transdiffernation to induce SPEM. But whether chief cells initial loss cause SPEM
needs to be further investigation. Acidic mammalian chitinase (CHIA) belongs to the 18 glycosidase family and is highly expressed in the chief cells. Our previous study showed that CHIA deficiency in the chief cells is the key event to induce SPME to progress to gastric cancer (Liu et al., DDW 2023 and 2024). However, the molecular role of CHIA in the development of SPEM is need further investigated.

Aims & Methods

Electron microscopy, qRT-PCR and single-cell sequencing (scRNA-seq) technology, as well as histopathological and immunofluorescence (IF) stainning with specific markers were performed in chief cells specific CHIA knockout mouse model (CHIA^rox/rox-GIF-Dre) and wild-type mice(CHIA^rox/rox), and in CHIA over - expression mice (CHIA ^rox/rox - GIF - Dre + rAAv - CHIA) and the control group (CHIA ^rox/rox - GIF - Dre + rAAv - control).

Results

Compared with CHIA^rox/rox mice, histological analysis and scRNA-seq technology data showed that loss of chief cells with increased M2 macrophage infiltration and final SPEM formation, but remaining of parietal cells in CHIA^rox/rox-GIF-Dre mice. Electron microscopy showed CHIA deficiency in mice resulted in endoplasmic reticulum was dilated and swollen, as well as the mitochondrial membrane was discontinuous of chief cells, followed with the accumulation of endoplasmic reticulum stress marker, including PERK, XBP-1, eIF2α/P-eIF2α, and GRP78, together with upregulation of pyroptosis-related marker, including NLRP3, ACS, GSDMD, NEK7, Caspase1, Caspase11, IL-1β, and IL-18, which was detected by qRT-PCR. These data indicating that target CHIA deletion caused chief cells pyroptosis. Furthermore, qRT-PCR analysis showed that CHIA deficiency caused the activation of IL33/IL-13 circuit in the mucosa of mice. Moreover, double immunofluorescence staining confirmed that upregulation and colocalization of IL-33 induced M2 macrophage polarization markers, including F4/80 and CD163⁺ with NLRP3 in the base of gastric mucosal of CHIA^rox/rox-GIF-Dre mice when compared with CHIA^rox/rox mice.Notably, CHIA ^rox/rox - GIF - Dre + rAvv - CHIA mice reversed the above process compared with controls.

Conclusion

Chief cells specific CHIA deficiency resulted in endoplasmic reticulum stress mediate NLRP3 inflammasome activation to induce chief cells proptosis.
Chief cells initial loss is sufficient and the key step to activate IL-33/ST2-M2 macrophage polarization axis to induce SPEM, which is independent of parietal cells loss.

Introduction

Colorectal cancer is one of the most prevalent cancers with an estimated 1.8 million newly developed cases and 0.9 million cancer-related deaths in 2020.Resection of adenomatous polyps decreases the incidence and mortality of colorectal cancer. Narrow-band imaging (NBI) and linked color imaging (LCI) are the most predominantly conducted image-enhanced endoscopy using short-wavelength light but their usefulness in screening and surveillance colonoscopy remains controversial.

Aims & Methods

Our aim in this study was to investigate the superiority of LCI over NBI for ADR.
This is an open-label, two-arm, parallel, 1:1, multicenter, randomized, controlled, right-sided colonoscopy study and included patients who underwent colonoscopy at six endoscopy centers in Japan from November 2020 through November 2023. The patients were randomly assigned to undergo a proximal-sided colonoscopy (cecum and ascending colon) with LCI or 2G-NBI followed by WLI. The primary outcome included the ADR and secondary outcomes involved polyp detection rate (PDR), polyp miss rate, and adenoma miss rate. This study was registered on November 4, 2020, in the Japan Registry of Clinical Trials (jRCT1012200007).

Results

During the study period, 1,655 patients were randomly assigned to the LCI group (828 patients, primary LCI followed by secondary WLI) and the 2G-NBI group (827 patients, primary 2G-NBI followed by secondary WLI), and 776 patients in the LCI group and 752 patients in the 2G-NBI groups were finally analyzed. The ADRs were 26.7% and 23.4% and the PDRs were 32.6% and 28.9% in primary LCI and 2G-NBI, respectively, with no statistically significant differences in ADR and PDR between groups (P = 0.14 and P = 0.12). However, multivariate regression analysis revealed primary LCI observation as an independent predictor for reducing PDR in the secondary WLI (Odds ratio [OR]: 0.72, 95% confidence interval [CI]: 0.53−0.97, P = 0.029). Moreover, polyp analysis demonstrated that miss rates of adenomas and polyps were significantly lower in the LCI group than in the NBI group (OR: 0.54, 95% CI: 0.39−0.76 in adenoma; OR: 0.59, 95% CI: 0.44−0.78 in polyp).

Conclusion

LCI is not superior to 2G-NBI in ADR and PDR in a clinical right-sided colonoscopy setting. However, LCI significantly reduced miss rates of adenomas and polyps.

Disclosure

Naohisa Yoshida has received lecture and/or consulting fees from Fujifilm and Olympus; Shoko Ono has received lecture and/or consulting fees from Fujifilm and Olympus; Momoko Tsuda has received lecture and/or consulting fees from Fujifilm; Nobuaki Yagi have received lecture and/or consulting fees from Fujifilm and Olympus; Mototsugu Kato has received lecture and/or consulting fees from Fujifilm. The remaining authors disclose no conflicts.

Introduction

Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely related to the metabolic syndrome of chronic liver disease and its pathogenesis involves a variety of cell types of metabolic disorders and inflammatory response, however, treatment is limited. Mas is a G protein-coupled receptor highly expressed by myeloid cells. It may play a key role in regulating myeloid-associated inflammation and metabolic homeostasis in the process of MASLD. However, its specific mechanism of action in MASLD remains unclear.

Aims & Methods

This study aims to explore the regulatory mechanism of MAS in myeloid cells in the occurrence and development of MASLD. In this study, liver tissues of patients with MASLD and animal models of MASLD induced by high-fat diet (HFD) were analyzed. In this study, myeloid-specific Mas1 knockout (Lysm^creMas1^f/f) mice were constructed. Single-cell RNA sequencing and multi-omics analysis were used to explore the role and mechanism of myeloid Mas in HFD-induced MASLD mice.

Results

The study found that the expression of MAS protein on myeloid cells in the livers of MASLD patients and MASLD animal models was significantly increased. Mononuclear phagocyte system（MPs）undergo metabolic disorders in the MASLD model, with elevated glycolysis levels, increased lactic acid production, and at the same time, the expression of cellular senescence markers (such as p16 and p21) is upregulated, and the secretion of inflammatory factors is increased. Single-cell multi-omics analysis revealed that myeloid MAS1 knockout activated the FN1⁺CCR2⁺monocytes first. Pseudo-temporal analysis showed that the FN1⁺CCR2⁺ monocytes had spatiotemporal metabolic responses with the macrophages, significantly involving the activation of glycolysis and inflammatory senescence by myeloid MAS. Non-target metabolomics of MASLD patients also revealed elevated glycolytic metabolism and increased lactic acid secretion. Mass spectrometry revealed that Mas specifically bound to the key glycolytic protein pyruvate kinase M2 (PKM2) and activated the lactylation of transcription factor Spi1-K208 site mediated by PKM2. The lactylation of Spi1-K208 promoted the transcription of senescence-associated secretory phenotype (SASP) -related proteins. Myeloid Mas1 knockout inhibited the nuclear translocation of PKM2 and blocked the lactylation of Spi1, inhibiting the transcriptional initiation of SASP. Screening of over 100,000 small molecule compounds through a virtual drug library revealed that Theaflavin 3,3'-digallate (TFDG) might reduce the protein expression of Mas and PKM2, and block the binding of the MAS-PKM2 complex. We synthesized macrophage membrane to encapsulat PLGA nanoparticles loaded with TFDG (MM@NP-TFDG) and found that MM@NP-TFDG effectively reduced the expression level of Mas-PKM2 complex protein expression in the MASLD mouse model, inhibited the glycolytic - inflammatory senescence axis of FN1⁺CCR2⁺ monocytes and macrophages, and alleviated liver inflammation and tissue damage. While the lipid deposition in the liver is reduced and the fatty acid oxidation is enhanced.

Conclusion

This study reveals that myeloid MAS1 protein participates in the occurrence and development of MASLD by regulating PKM2-mediated Spi1 lactylation and reprogramming the metabolic-inflammatory senescence axis of MPs during the process of MASLD. This discovery provides new potential targets for the treatment of MASLD patients and is expected to offer new clinical treatment strategies for MASLD patients.

Disclosure

The authors declare no conflict of interest.

Introduction

Hepatocellular carcinoma (HCC) is the sixth most common malignancy and the third leading cause of cancer-related deaths globally, with increasing incidence and mortality rates. Most patients are diagnosed at advanced stages, missing the opportunity for radical treatment. Sorafenib, a tyrosine kinase inhibitor, is the first-line treatment for advanced HCC; however, drug resistance typically develops within 6 months. Therefore, elucidating the mechanisms of sorafenib resistance and identifying new therapeutic targets are of significant importance. Our study focuses on the role and mechanism of Ribonucleotide Reductase M2 (RRM2) in sorafenib resistance in HCC.

Aims & Methods

The primary objective of this study is to investigate the role of RRM2 in sorafenib resistance in HCC and explore its underlying mechanisms. We aim to clarify whether RRM2 regulates aerobic glycolysis via the HIF-1α/HK2 pathway, thereby affecting sorafenib sensitivity. Our methods include:

• Analyzing RRM2 expression in HCC tissues and its correlation with clinical outcomes, such as disease-free survival (DFS) and overall survival (OS).
• Establishing sorafenib-resistant HCC cell lines (LM3-SR and SMMC7721-SR) and manipulating RRM2 expression using lentiviral vectors for knockdown and overexpression.
• Conducting in vitro experiments to assess the effects of RRM2 on cell proliferation, apoptosis, glycolysis, and sorafenib sensitivity using assays such as CCK8, flow cytometry, and Seahorse analysis.
• Performing in vivo studies using a nude mouse xenograft model to evaluate the impact of RRM2 knockdown on tumor growth and sorafenib efficacy.
• Utilizing RNA-seq, Western blot, PCR, and other techniques to investigate the molecular mechanisms, including the potential regulation of HIF-1α and HK2 by RRM2.

Results

• Clinical Correlation: RRM2 expression was significantly higher in HCC tissues compared to adjacent normal tissues. Higher RRM2 levels were associated with shorter DFS and OS in HCC patients.
• In Vitro Findings: RRM2 knockdown in sorafenib-resistant HCC cells (LM3-SR and SMMC7721-SR) increased sensitivity to sorafenib, as evidenced by reduced cell viability and increased apoptosis. Additionally, RRM2 knockdown decreased glycolysis, as indicated by reduced lactate production and glucose uptake. Conversely, RRM2 overexpression in HCC cells promoted resistance to sorafenib and enhanced glycolysis.
• Molecular Mechanisms: RRM2 regulated the expression of glycolytic enzymes, particularly HK2, through the HIF-1α pathway. Knockdown of RRM2 reduced HIF-1α and HK2 expression, while overexpression of HIF-1α or HK2 could reverse the effects of RRM2 knockdown on glycolysis and sorafenib sensitivity.
• In Vivo Validation: In a nude mouse xenograft model, RRM2 knockdown enhanced the inhibitory effects of sorafenib on tumor growth, as demonstrated by reduced tumor volume and increased apoptosis.

Conclusion

Our study demonstrates that RRM2 plays a crucial role in sorafenib resistance in HCC by regulating aerobic glycolysis via the HIF-1α/HK2 pathway. Targeting RRM2 or its downstream pathways may represent a promising strategy to overcome sorafenib resistance and improve therapeutic outcomes in HCC patients. Future work will focus on further elucidating the molecular mechanisms and exploring the potential clinical applications of RRM2 as a therapeutic target.

Disclosure

The authors declare that they have no conflict of interest.