Discovery of Novel Peptide Antagonists Targeting GPR55 for Liver Inflammation and Fibrosis.

Liver fibrosis is a condition characterized by aberrant proliferation of connective tissue in the liver resulting from diverse etiological factors. G protein-coupled receptor GPR55 has recently been identified as a regulator of liver diseases. Herein, we report the discovery of a cyclic peptide P1-1 that antagonizes GPR55 and suppresses collagen secretion in hepatic stellate cells. The alanine scanning and docking study was carried out to predict the binding mode and allowed for further structural optimization of peptide antagonists for GPR55. The subsequent in vivo study demonstrated that P1-1 ameliorates CCl4-induce and MCD-diet-induce acute liver inflammation and fibrosis. Further study indicates that P1-1 reduces reactive oxygen species (ROS) production, attenuates ER stress, and inhibits mitochondria-associated hepatocyte apoptosis. In this work, we provided the first successful example of antagonizing GPR55 for liver inflammation and fibrosis, which validates GPR55 as a promising target for the treatment of liver fibrosis and affords a high-potent GPR55 antagonist P1-1 as a potential therapeutic candidate.

Ferroptosis-Related Gene Signatures in Epilepsy: Diagnostic and Immune Insights.

Epilepsy is characterized by a multifaceted aetiology. Ferroptosis has recently been implicated in seizure pathophysiology, although its mechanistic role in epilepsy remains obscure. We examined the roles of ferroptosis-related genes (FRGs) in epilepsy cohorts from the GSE143272 dataset. We investigated the associations between gene expression and the immune response by performing CIBERSORT and MCP-counter analyses. By employing unsupervised consensus clustering and weighted gene coexpression network analysis (WGCNA), we delineated robust gene clusters across cohorts. Single-cell RNA sequencing data from the GSE201048 dataset provided insights into the interactions between pivotal ferroptosis-related genes and immune cells. Additionally, we employed qRT‒PCR technology to measure the levels of these central genes in the tissues of epileptic patients and mice. Our findings revealed seven pivotal genes (TFRC, POR, PTGS2, RELA, PGD, TRIM21, and QSOX1) at the forefront in epilepsy specimens. A diagnostic model harnessing these genes exhibited substantial efficacy (AUC = 0.913). Similarly, the qRT‒PCR analysis of samples from epileptic patients and mouse epileptic brain tissues substantiated these findings. Stratification of 91 patients with epilepsy via WGCNA, based on gene expression, revealed distinct immunological profiles. The scRNA-seq data further indicated increased expression of central genes in macrophages and microglia. Notably, these cells and those with elevated ferroptosis scores were significantly enriched in inflammation-related pathways. These findings support the strong involvement of FRGs in the pathogenesis of epilepsy, particularly neuroinflammation. These central genes hold promise as novel diagnostic biomarkers for epilepsy.

Glutamate acts on acid-sensing ion channels to worsen ischaemic brain injury.

Glutamate is traditionally viewed as the first messenger to activate NMDAR (N-methyl-D-aspartate receptor)-dependent cell death pathways in stroke1,2, but unsuccessful clinical trials with NMDAR antagonists implicate the engagement of other mechanisms3-7. Here we show that glutamate and its structural analogues, including NMDAR antagonist L-AP5 (also known as APV), robustly potentiate currents mediated by acid-sensing ion channels (ASICs) associated with acidosis-induced neurotoxicity in stroke4. Glutamate increases the affinity of ASICs for protons and their open probability, aggravating ischaemic neurotoxicity in both in vitro and in vivo models. Site-directed mutagenesis, structure-based modelling and functional assays reveal a bona fide glutamate-binding cavity in the extracellular domain of ASIC1a. Computational drug screening identified a small molecule, LK-2, that binds to this cavity and abolishes glutamate-dependent potentiation of ASIC currents but spares NMDARs. LK-2 reduces the infarct volume and improves sensorimotor recovery in a mouse model of ischaemic stroke, reminiscent of that seen in mice with Asic1a knockout or knockout of other cation channels4-7. We conclude that glutamate functions as a positive allosteric modulator for ASICs to exacerbate neurotoxicity, and preferential targeting of the glutamate-binding site on ASICs over that on NMDARs may be strategized for developing stroke therapeutics lacking the psychotic side effects of NMDAR antagonists.

Cardiomyocyte-specific overexpression of FPN1 diminishes cardiac hypertrophy induced by chronic intermittent hypoxia.

The significance of iron in myocardial mitochondria function cannot be underestimated, because deviations in iron levels within cardiomyocytes may have profound detrimental effects on cardiac function. In this study, we investigated the effects of ferroportin 1 (FPN1) on cardiac iron levels and pathological alterations in mice subjected to chronic intermittent hypoxia (CIH). The cTNT-FPN1 plasmid was administered via tail vein injection to induce the mouse with FPN1 overexpression in the cardiomyocytes. CIH was established by exposing the mice to cycles of 21%-5% FiO2 for 3 min, 8 h per day. Subsequently, the introduction of hepcidin resulted in a reduction in FPN1 expression, and H9C2 cells were used to establish an IH model to further elucidate the role of FPN1. First, FPN1 overexpression ameliorated CIH-induced cardiac dysfunction, myocardial hypertrophy, mitochondrial damage and apoptosis. Second, FPN1 overexpression attenuated ROS levels during CIH. In addition, FPN1 overexpression mitigated CIH-induced cardiac iron accumulation. Moreover, the administration of hepcidin resulted in a reduction in FPN1 levels, further accelerating the CIH-induced levels of ROS, LIP and apoptosis in H9C2 cells. These findings indicate that the overexpression of FPN1 in cardiomyocytes inhibits CIH-induced cardiac iron accumulation, subsequently reducing ROS levels and mitigating mitochondrial damage. Conversely, the administration of hepcidin suppressed FPN1 expression and worsened cardiomyocyte iron toxicity injury.

Comprehensive analysis of clinical data and radiomic features from contrast enhanced CT for differentiating benign and malignant pancreatic intraductal papillary mucinous neoplasms.

The primary aim of this investigation was to leverage radiomics features derived from contrast-enhanced abdominal computed tomography (CT) scans to devise a predictive model to discern the benign and malignant nature of intraductal papillary mucinous neoplasms (IPMNs). Radiomic signatures were meticulously crafted to delineate benign from malignant IPMNs by extracting pertinent features from contrast-enhanced CT images within a designated training cohort (n = 84). Subsequent validation was conducted with data from an independent test cohort (n = 37). The discriminative ability of the model was quantitatively evaluated through receiver operating characteristic (ROC) curve analysis, with the integration of carefully selected clinical features to improve the comparative analysis. Arterial-phase images were utilized to construct a model comprising 8 features for distinguishing between benign and malignant cases. The model achieved an accuracy of 0.891 [95% confidence interval (95% CI), 0.816-0.996] in the cross-validation set and 0.553 (95% CI 0.360-0.745) in the test set. Conversely, employing 9 features from the venous-phase resulted in a model with a cross-validation accuracy of 0.862 (95%CI 0.777-0.946) and a test set accuracy of 0.801 (95% CI 0.653-0.950).Integrating the identified clinical features with imaging features yielded a model with a cross-validation accuracy of 0.934 (95% CI 0.879-0.990) and a test set accuracy of 0.904 (95% CI 0.808-0.999), thereby further improving its discriminatory ability. Our findings distinctly illustrate that venous-phase radiomics features eclipse arterial-phase radiomic features in terms of predictive accuracy regarding the nature of IPMNs. Furthermore, the synthesis and meticulous screening of clinical features with radiomic data significantly increased the diagnostic efficacy of our model, underscoring the pivotal importance of a comprehensive and integrated approach for accurate risk stratification in IPMN management.

Adenosine kinase protects against acetaminophen-induced acute liver injury by activating autophagy in hepatocytes.

Acute liver injury (ALI) is a common life-threatening condition with a high mortality rate due to liver disease-related death. However, current therapeutic interventions for ALI remain ineffective, and the development of effective novel therapies is urgently needed. Liver samples from patients with drug-induced ALI were collected to detect adenosine kinase (ADK) expression. Male C57BL/6 J mice, hepatocyte-specific ADK knockout (ADKHKO) mice, and their controls (ADKf/f) were exposed to acetaminophen (APAP) and other treatments to investigate the mechanisms of APAP-related ALI. ADK expression was significantly decreased in APAP-injured livers. Hepatocyte-specific ADK deficiency exacerbated APAP-induced ALI, while a gain-of-function approach delivering AAV-ADK, markedly alleviated APAP-induced ALI, as indicated by changes in alanine aminotransferases (ALT) levels, aspartate aminotransferase (AST) levels, neutrophil infiltration and hepatocyte death. This study showed that ADK played a critical role in ALI by activating autophagy through two signaling pathways, the adenosine monophosphate-activated protein kinase (AMPK)-mTOR pathway and the adenosine receptor A1 (ADORA1)-Akt-mTOR pathway. Furthermore, we found that metformin upregulated ADK expression in hepatocytes and protected against APAP-induced ALI. These results demonstrate that ADK is critical in protecting against APAP-induced ALI and that developing therapeutics targeting ADK-adenosine-ADORA1 is a new approach for ALI treatment. Metformin is a potential candidate for preventing ALI by upregulating ADK.

Photoredox-Neutral Radical-Radical Cross-Coupling of Isatins and Benzyl Carboxylic Acids.

A photoredox-neutral radical-radical cross-coupling is described for the synthesis of 3-hydroxy-3-alkyloxindoles using isatins and benzyl carboxylic acids as substrates and 2,4,5,6-tetra(9H-carbazol-9-yl)isophthalonitrile (4CzIPN) as the photocatalyst. The method features a broad substrate scope and good functional group tolerance, providing 30 sterically hindered alcohols with moderate to excellent yields. This approach utilizes inexpensive and commercially available starting materials, avoiding the use of transition metals, extra oxidants/reductants, and harsh reaction conditions, showcasing significant applicability and environmental friendliness.

Liver and bile duct organoids and tumoroids.

Organoids refer to 3D cultures established to recapitulate histology, pathology, architecture, and genetic traits of various organs and tissues in the body, thereby replacing 2D cell cultures, xenograft, and animal models. Organoids form a 3D in vitro mimic of original tissues like the liver and are derived from embryonic or adult tissue stem cells. Liver and bile duct tumor organoids, also called, tumoroids capture genetic diversity, cellular, and pathophysiological properties of original tumors. Moreover, co-culture techniques along with genetic modulation of organoids allow for using tumoroids in liver and bile duct cancer research and drug screening/testing. Therefore, tumoroids are promising platforms for studying liver and bile duct cancer, which paves the way for the new era of personalized therapies. In the current review, we aimed to discuss liver and bile duct organoids with special emphasis on tumoroids and their applications, advantages, and shortcomings.

PLA plastic particles disrupt bile acid metabolism leading to hepatic inflammatory injury in male mice.

Microplastics, such as polylactic acid (PLA), are ubiquitous environmental pollutants with unclear implications for health impact. This study aims to elucidate the mechanisms of PLA-induced inflammatory liver injury, focusing on disturbance of bile acid metabolism. The in vitro PLA exposure experiment was conducted using HepG2 cells to assess cell viability, cytokine secretion, and effects on bile acid metabolism. In vivo, male C57BL/6 J mice were exposed to PLA for ten days continuously, liver function and histopathological assessment were evaluated after the mice sacrificed. Molecular analyses including quantitative reverse transcription polymerase chain reaction (RT-qPCR) and Western blotting, were applied to evaluate the expression of bile acid metabolizing enzymes and transporters. PLA exposure resulted in decreased cell viability in HepG2 cells, increased inflammation and altered bile acid metabolism. In mice, PLA exposure resulted in decreased body weight and food intake, impaired liver function, increased hepatic inflammation, altered bile acid profiles, and dysregulated expression of bile acid metabolic pathways. PLA exposure disrupts bile acid metabolism through inhibition of the CYP7A1 enzyme and activation of the FGF-JNK/ERK signaling pathway, contributing to liver injury. These findings highlight the potential hepatotoxic effects of environmentally friendly plastics PLA and underscore the need for further research on their biological impact.

EMOST: A dual-branch hybrid network for medical image fusion via efficient model module and sparse transformer.

Multimodal medical image fusion fuses images with different modalities and provides more comprehensive and integrated diagnostic information. However, current multimodal image fusion methods cannot effectively model non-local contextual feature relationships, and due to direct aggregation of the extracted features, they introduce unnecessary implicit noise into the fused images. To solve the above problems, this paper proposes a novel dual-branch hybrid fusion network called EMOST for medical image fusion that combines a convolutional neural network (CNN) and a transformer. First, to extract more comprehensive feature information, an effective feature extraction module is proposed, which consists of an efficient dense block (EDB), an attention module (AM), a multiscale convolution block (MCB), and three sparse transformer blocks (STB). Meanwhile, a lightweight efficient model (EMO) is used in the feature extraction module to exploit the efficiency of the CNN with the dynamic modeling capability of the transformer. Additionally, the STB is incorporated to adaptively maintain the most useful self-attention values and remove as much redundant noise as possible by developing the top-k selection operator. Moreover, a novel feature fusion rule is designed to efficiently integrate the features. Experiments are conducted on four types of multimodal medical images. The proposed method shows higher performance than the art-of-the-state methods in terms of quantitative and qualitative evaluations. The code of the proposed method is available at https://github.com/XUTauto/EMOST.

Carrier-free immobilized enzymatic reactor based on CipA-fused carbonyl reductase for efficient synthesis of chiral alcohol with cofactor self-sufficiency.

In this study, based on the self-assembly strategy, we fused CipA with carbonyl reductase LXCARS154Y derived from Leifsonia xyli by gene coding, and successfully performed the carrier-free immobilization of LXCARS154Y. The immobilized enzyme was then characterized using scanning electron microscope (SEM), dynamic light scattering (DLS) and fourier transform infrared spectroscopy (FTIR). Compared with the free enzyme, the immobilized LXCARS154Y exhibited a 2.3-fold improvement in the catalytic efficiency kcat/km for the synthesis of a chiral pharmaceutical intermediate (R)-3,5-bis(trifluoromethyl)phenyl ethanol ((R)-BTPE) by reducing 3,5-bis(trifluoromethyl)acetophenone (BTAP). Moreover, the immobilized enzyme showed the enhanced stability while maintaining over 61 % relative activity after 18 cycles of batch reaction. Further, when CipA-fused carbonyl reductase was employed for (R)-BTPE production in a continuous flow reaction, almost complete yield (97.0 %) was achieved within 7 h at 2 M (512.3 g/L) of BTAP concentration, with a space-time yield of 1717.1 g·L-1·d-1. Notably, we observed the retention of cofactor NADH by CipA-based enzyme aggregates, resulting in a higher total turnover number (TTN) of 4815 to facilitate this bioreductive process. This research developed a concise strategy for efficient preparation of chiral intermediate with cofactor self-sufficiency via continuous flow biocatalysis, and the relevant mechanism was also explored.

MDC-RHT: Multi-Modal Medical Image Fusion via Multi-Dimensional Dynamic Convolution and Residual Hybrid Transformer.

The fusion of multi-modal medical images has great significance for comprehensive diagnosis and treatment. However, the large differences between the various modalities of medical images make multi-modal medical image fusion a great challenge. This paper proposes a novel multi-scale fusion network based on multi-dimensional dynamic convolution and residual hybrid transformer, which has better capability for feature extraction and context modeling and improves the fusion performance. Specifically, the proposed network exploits multi-dimensional dynamic convolution that introduces four attention mechanisms corresponding to four different dimensions of the convolutional kernel to extract more detailed information. Meanwhile, a residual hybrid transformer is designed, which activates more pixels to participate in the fusion process by channel attention, window attention, and overlapping cross attention, thereby strengthening the long-range dependence between different modes and enhancing the connection of global context information. A loss function, including perceptual loss and structural similarity loss, is designed, where the former enhances the visual reality and perceptual details of the fused image, and the latter enables the model to learn structural textures. The whole network adopts a multi-scale architecture and uses an unsupervised end-to-end method to realize multi-modal image fusion. Finally, our method is tested qualitatively and quantitatively on mainstream datasets. The fusion results indicate that our method achieves high scores in most quantitative indicators and satisfactory performance in visual qualitative analysis.

Regulation of post-translational modification of PD-L1 and associated opportunities for novel small-molecule therapeutics.

PD-L1 is overexpressed on the surface of tumor cells and binds to PD-1, resulting in tumor immune escape. Therapeutic strategies to target the PD-1/PD-L1 pathway involve blocking the binding. Immune checkpoint inhibitors have limited efficacy against tumors because PD-L1 is also present in the cytoplasm. PD-L1 of post-translational modifications (PTMs) have uncovered numerous mechanisms contributing to carcinogenesis and have identified potential therapeutic targets. Therefore, small molecule inhibitors can block crucial carcinogenic signaling pathways, making them a potential therapeutic option. To better develop small molecule inhibitors, we have summarized the PTMs of PD-L1. This review discusses the regulatory mechanisms of small molecule inhibitors in carcinogenesis and explore their potential applications, proposing a novel approach for tumor immunotherapy based on PD-L1 PTM.

[Box: see text].

Clickable tryptophan modification for late-stage diversification of native peptides.

As the least abundant residue in proteins, tryptophan widely exists in peptide drugs and bioactive natural products and contributes to drug-target interactions in multiple ways. We report here a clickable tryptophan modification for late-stage diversification of native peptides, via catalyst-free C2-sulfenylation with 8-quinoline thiosulfonate reagents in trifluoroacetic acid (TFA). A wide range of groups including trifluoromethylthio (SCF3), difluoromethylthio (SCF2H), (ethoxycarbonyl)difluoromethylthio (SCF2CO2Et), alkylthio, and arylthio were readily incorporated. The rapid reaction kinetics of Trp modification and full tolerance with other 19 proteinogenic amino acids, as well as the super dissolving capability of TFA, render this method suitable for all kinds of Trp-containing peptides without limitations from sequences, hydrophobicity, and aggregation propensity. The late-stage modification of 15 therapeutic peptides (1.0 to 7.6 kilodaltons) and the improved bioactivity and serum stability of SCF3- and SCF2H-modified melittin analogs illustrated the effectiveness of this method and its potential in pharmacokinetic property improvement.

[Two new glycosides from Hypericum elatoides].

The column chromatography with silica gel, reversed-phase C_(18), and Sephadex LH-20 was employed to separate the methanol extract of the aerial parts of Hypericum elatoides. The compounds were identified by the comprehensive analysis of IR, NMR, and MS data as methyl 8-O-ß-D-glucopyranosyl-(Z)-5-octenoate(1), methyl 3-O-ß-D-glucopyranosyl-4-methylhexanoate(2), byzantionoside B(3), 9-epi-blumenol C glucoside(4), corchoionoside C(5),(6S,9R)-roseoside(6), cis-p-coumaric acid 4-O-ß-D-glucopyranoside(7), trans-p-coumaric acid 4-O-ß-D-glucopyranoside(8), methyl 3-(4-hydroxyphenyl)propanoate(9),(E)-chlorogenic acid methyl ester(10), quercetin-3-O-ß-D-glucopyranoside(11), ß-sitosterol(12), stigmasterol(13), stigmast-4-en-3-one(14), ß-amyrin(15), daucosterol(16), sitoindoside Ⅰ(17), oleic acid(18), methyl α-linolenate(19), trilinolein(20), and cassipourol(21). Among them, compounds 1 and 2 were identified as new glycosides and named hyperelatosides G and H. Compounds 3-5, 7-9, 17, and 20-21 were isolated from the genus Hypericum for the first time. The remaining compounds were isolated from H. elatoides for the first time. The results of biological assays revealed that compound 11 exhibited significant anti-neuroinflammatory activity, and compounds 1, 3, and 19 displayed certain neuroprotective effects.

The histamine receptor H1 acts as an alternative receptor for SARS-CoV-2.

Numerous host factors, in addition to human angiotensin-converting enzyme 2 (hACE2), have been identified as coreceptors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), demonstrating broad viral tropism and diversified druggable potential. We and others have found that antihistamine drugs, particularly histamine receptor H1 (HRH1) antagonists, potently inhibit SARS-CoV-2 infection. In this study, we provided compelling evidence that HRH1 acts as an alternative receptor for SARS-CoV-2 by directly binding to the viral spike protein. HRH1 also synergistically enhanced hACE2-dependent viral entry by interacting with hACE2. Antihistamine drugs effectively prevent viral infection by competitively binding to HRH1, thereby disrupting the interaction between the spike protein and its receptor. Multiple inhibition assays revealed that antihistamine drugs broadly inhibited the infection of various SARS-CoV-2 mutants with an average IC50 of 2.4 µM. The prophylactic function of these drugs was further confirmed by authentic SARS-CoV-2 infection assays and humanized mouse challenge experiments, demonstrating the therapeutic potential of antihistamine drugs for combating coronavirus disease 19.IMPORTANCEIn addition to human angiotensin-converting enzyme 2, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can utilize alternative cofactors to facilitate viral entry. In this study, we discovered that histamine receptor H1 (HRH1) not only functions as an independent receptor for SARS-CoV-2 but also synergistically enhances ACE2-dependent viral entry by directly interacting with ACE2. Further studies have demonstrated that HRH1 facilitates the entry of SARS-CoV-2 by directly binding to the N-terminal domain of the spike protein. Conversely, antihistamine drugs, primarily HRH1 antagonists, can competitively bind to HRH1 and thereby prevent viral entry. These findings revealed that the administration of repurposable antihistamine drugs could be a therapeutic intervention to combat coronavirus disease 19.

A Solid Electrolyte RHE for Electrode Diagnosis of Proton Exchange Membrane Water Electrolyzers.

Reference electrode is the foundation of electrochemical study; thus, most electrode materials are tested in a three-electrode mode to acquire potential-dependent kinetics. However, it is difficult to directly use conventional reference electrodes to detect potential information in solid electrolyte devices due to their compact assembly structure. Therefore, the kinetic study of an electrochemical device faces challenges in precise identification of specific problems originating from the anode or cathode. Here, focusing on proton exchange membrane water electrolysis, we design a solid electrolyte reversible hydrogen electrode (SE-RHE), which can be used for electrode diagnosis under various operating conditions. Compared to the reference electrodes reported in the literature, which are mainly based on liquid electrolyte, the SE-RHE is highly sensitive and compatible, as well as easy to assemble. The potential deviation is less than ±0.5 mV, and the cell voltage derived from the electrode potential well reproduces the value that was directly measured with a deviation less than 0.2%. The reference electrode developed in this work enables the kinetic study of a specific electrode rather than the entire cell. For instance, an interesting observation is that the cathode shows distinct stability under stable and fluctuating operations. Differing from the high stability under stable operation, the cathode degrades significantly under fluctuating operations.

Bi-parental graph strategy to represent and analyze hybrid plant genomes.

Hybrid plants are found extensively in the wild, and they often demonstrate superior performance of complex traits over their parents and other selfing plants. This phenomenon, known as heterosis, has been extensively applied in plant breeding for decades. However, the process of decoding hybrid plant genomes has seriously lagged due to the challenges associated with genome assembly and the lack of appropriate methodologies for their subsequent representation and analysis. Here, we present the assembly and analysis of two hybrids, an intraspecific hybrid between two maize (Zea may ssp. mays) inbred lines and an interspecific hybrid between maize and its wild relative teosinte (Zea may ssp. parviglumis), utilizing a combination of PacBio High Fidelity (HiFi) sequencing and chromatin conformation capture sequencing data. The haplotypic assemblies are well-phased at chromosomal scale, successfully resolving the complex loci with extensive parental structural variations (SVs). By integrating into a bi-parental genome graph, the haplotypic assemblies can facilitate downstream short-reads-based SV calling and allele-specific gene expression analysis, demonstrating outstanding advantages over a single linear genome. Our work offers a comprehensive workflow that aims to facilitate the decoding of numerous hybrid plant genomes, particularly those with unknown or inaccessible parentage, thereby enhancing our understanding of genome evolution and heterosis.

Mucin phenotype and microvessels in early gastic cancer: Magnifying endoscopy with narrow band imaging.

Backgrounds: In order to detect early gastric cancer (EGC), this research sought to assess the diagnostic utility of magnifying endoscopy (ME) as well as the significance of mucin phenotype and microvessel features. Methods: 402 individuals with an EGC diagnosis underwent endoscopic submucosal dissection (ESD) at the Department of ME between 2012 and 2020. After adjusting for image distortion, high-magnification endoscopic pictures were taken and examined to find microvessels in the area of interest. The microvessel density was measured as counts per square millimeter (counts/mm2) after segmentation, and the vascular bed's size was computed as a percentage of the area of interest. To identify certain properties of the microvessels, such as end-points, crossing points, branching sites, and connection points, further processing was done using skeletonized pixels. Results: According to the research, undifferentiated tumors often lacked the MS pattern and showed an oval and tubular microsurface (MS) pattern, but differentiated EGC tumors usually lacked the MS pattern and presented a corkscrew MV pattern. Submucosal invasion was shown to be more strongly associated with the destructive MS pattern in differentiated tumors as opposed to undifferentiated tumors. While lesions with a corkscrew MV pattern and an antrum or body MS pattern revealed greater MUC5AC expression, lesions with a loop MV pattern indicated higher MUC2 expression. Furthermore, CD10 expression was higher in lesions with a papillary pattern and an antrum or body MS pattern. Conclusion: These results imply that evaluating mucin phenotype and microvessel features in conjunction with magnifying endoscopy (ME) may be a useful diagnostic strategy for early gastric cancer (EGC) detection. Nevertheless, further investigation is required to confirm these findings and identify the best course of action for EGC diagnosis.

ODNet: A High Real-Time Network Using Orthogonal Decomposition for Few-Shot Strip Steel Surface Defect Classification.

Strip steel plays a crucial role in modern industrial production, where enhancing the accuracy and real-time capabilities of surface defect classification is essential. However, acquiring and annotating defect samples for training deep learning models are challenging, further complicated by the presence of redundant information in these samples. These issues hinder the classification of strip steel surface defects. To address these challenges, this paper introduces a high real-time network, ODNet (Orthogonal Decomposition Network), designed for few-shot strip steel surface defect classification. ODNet utilizes ResNet as its backbone and incorporates orthogonal decomposition technology to reduce the feature redundancies. Furthermore, it integrates skip connection to preserve essential correlation information in the samples, preventing excessive elimination. The model optimizes the parameter efficiency by employing Euclidean distance as the classifier. The orthogonal decomposition not only helps reduce redundant image information but also ensures compatibility with the Euclidean distance requirement for orthogonal input. Extensive experiments conducted on the FSC-20 benchmark demonstrate that ODNet achieves superior real-time performance, accuracy, and generalization compared to alternative methods, effectively addressing the challenges of few-shot strip steel surface defect classification.