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OBJECTIVES: This study aims to evaluate the safety of a new inactivated poliomyelitis vaccine (Sabin strains) (sIPV) for large-scale use in primary and booster immunizations, whether simultaneously administered with other vaccines or not and to explore the persistence of all vaccines at approximately six months after vaccination. METHOD: A total of 3200 infants were recruited into this study, including 2000 infants aged 2-3 months randomly assigned (1:1) into the "sIPV basic" or the "sIPV+DTaP" group for primary immunization of sIPV. Another 1200 children aged 18 months old and above were randomly assigned (2:2:1:1) into the "sIPV booster," "sIPV+HepA-I," "sIPV+MMR", or "sIPV+HepA-L" group for booster immunization of sIPV. Adverse events within 30 days of each vaccination dose in all participants were self-reported by guardians using a WeChat mini-program. Approximately 200 blood samples were collected at 5-7 months after the final vaccination to test for antibodies against poliovirus and other viruses. RESULTS: 3198 participants in total were included in the safety study, including 1999 infants aged 2-3 months old and 1199 children aged 18-26 months old. For primary immunization, the incidence of adverse reactions in the "sIPV basic" and the "sIPV+DTaP" group were 3.19 and 6.21% (P = 0.001), respectively. For booster immunization, the incidences of adverse reaction for the "sIPV booster" group were 2.25%, while the incidence for the "sIPV +others" group in total was 2.50% (P = 0.788). Most adverse reactions were mild. Fever was the most common symptom in all groups. No vaccine-related serious adverse events (SAEs) were observed in this study. The seropositivity rates of antibodies in the "sIPV basic" and the "sIPV+DTaP" group were 92.31 and 100% against type 1 poliovirus (P = 0.031); 96.15% and 98.57% against type 2 poliovirus (P = 0.575); 98.08% and 91.43% against type 3 poliovirus (P = 0.237), respectively. Regarding booster vaccination with sIPV, whether co-administered with other vaccines or not, the seropositivity rates of antibodies against the three types of polioviruses were all 100%. Seropositivity rates of antibodies against hepatitis A, measles, mumps, and rubella were all no <77%, except for pertussis, which was <30%. CONCLUSION: sIPV demonstrated good safety and immune persistence for primary and booster vaccinations, whether administered singly or simultaneously. Antibodies against hepatitis A, measles, mumps and rubella were not disrupted by the co-vaccination. However, the seropositivity rates and geometric mean concentrations (GMCs) of antibodies against pertussis indicate the necessity for a booster dose.
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Anticuerpos Antivirales , Inmunización Secundaria , Poliomielitis , Vacuna Antipolio de Virus Inactivados , Humanos , Vacuna Antipolio de Virus Inactivados/inmunología , Vacuna Antipolio de Virus Inactivados/administración & dosificación , Vacuna Antipolio de Virus Inactivados/efectos adversos , Lactante , Inmunización Secundaria/métodos , Masculino , China , Femenino , Anticuerpos Antivirales/sangre , Poliomielitis/prevención & control , Poliomielitis/inmunología , Poliovirus/inmunología , Esquemas de Inmunización , Vacunación/métodos , Vacunas Combinadas/inmunología , Vacunas Combinadas/administración & dosificación , Vacunas Combinadas/efectos adversosAsunto(s)
Biomarcadores de Tumor , Neoplasias de la Mama , Neoplasias de los Genitales Femeninos , Inmunoterapia , Humanos , Femenino , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/terapia , Inmunoterapia/métodos , Neoplasias de los Genitales Femeninos/inmunología , Neoplasias de los Genitales Femeninos/terapia , Neoplasias de los Genitales Femeninos/diagnóstico , PronósticoRESUMEN
Rheumatoid arthritis (RA) is an autoimmune disease causing progressive joint damage. Early diagnosis and treatment is critical, but remains challenging due to RA complexity and heterogeneity. Machine learning (ML) techniques may enhance RA management by identifying patterns within multidimensional biomedical data to improve classification, diagnosis, and treatment predictions. In this review, we summarize the applications of ML for RA management. Emerging studies or applications have developed diagnostic and predictive models for RA that utilize a variety of data modalities, including electronic health records, imaging, and multi-omics data. High-performance supervised learning models have demonstrated an Area Under the Curve (AUC) exceeding 0.85, which is used for identifying RA patients and predicting treatment responses. Unsupervised learning has revealed potential RA subtypes. Ongoing research is integrating multimodal data with deep learning to further improve performance. However, key challenges remain regarding model overfitting, generalizability, validation in clinical settings, and interpretability. Small sample sizes and lack of diverse population testing risks overestimating model performance. Prospective studies evaluating real-world clinical utility are lacking. Enhancing model interpretability is critical for clinician acceptance. In summary, while ML shows promise for transforming RA management through earlier diagnosis and optimized treatment, larger scale multisite data, prospective clinical validation of interpretable models, and testing across diverse populations is still needed. As these gaps are addressed, ML may pave the way towards precision medicine in RA.
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Artritis Reumatoide , Aprendizaje Automático , Medicina de Precisión , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/terapia , Humanos , Medicina de Precisión/métodos , Reumatología/métodos , Manejo de la EnfermedadRESUMEN
Osteoarthritis (OA) is a common joint disorder characterized by the degeneration of cartilage and inflammation, affecting millions worldwide. The disease's complex pathogenesis involves various cell types, such as chondrocytes, synovial cells, osteoblasts, and immune cells, contributing to the intricate interplay of factors leading to tissue degradation and pain. RNA interference (RNAi) therapy, particularly through the use of small interfering RNA (siRNA), emerges as a promising avenue for OA treatment due to its capacity for specific gene silencing. siRNA molecules can modulate post-transcriptional gene expression, targeting key pathways involved in cellular proliferation, apoptosis, senescence, autophagy, biomolecule secretion, inflammation, and bone remodeling. This review delves into the mechanisms by which siRNA targets various cell populations within the OA milieu, offering a comprehensive overview of the potential therapeutic benefits and challenges in clinical application. By summarizing the current advancements in siRNA delivery systems and therapeutic targets, we provide a solid theoretical foundation for the future development of novel siRNA-based strategies for OA diagnosis and treatment, paving the way for innovative and more effective approaches to managing this debilitating disease.
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Osteoartritis , ARN Interferente Pequeño , Humanos , Osteoartritis/terapia , Osteoartritis/genética , ARN Interferente Pequeño/uso terapéutico , ARN Interferente Pequeño/genética , Animales , Interferencia de ARN , Condrocitos/metabolismo , Transducción de SeñalRESUMEN
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. Macrophages are key effector cells that play a central role in RA pathogenesis through their ability to polarize into distinct functional phenotypes. An imbalance favoring pro-inflammatory M1 macrophages over anti-inflammatory M2 macrophages disrupts immune homeostasis and exacerbates joint inflammation. Multiple signaling pathways, including Notch, JAK/STAT, NF-κb, and MAPK, regulate macrophage polarization towards the M1 phenotype in RA. Metabolic reprogramming also contributes to this process, with M1 macrophages prioritizing glycolysis while M2 macrophages utilize oxidative phosphorylation. Redressing this imbalance by modulating macrophage polarization and metabolic state represents a promising therapeutic strategy. Furthermore, complex bidirectional interactions exist between synovial macrophages and fibroblast-like synoviocytes (FLS), forming a self-perpetuating inflammatory loop. Macrophage-derived factors promote aggressive phenotypes in FLS, while FLS-secreted mediators contribute to aberrant macrophage activation. Elucidating the signaling networks governing macrophage polarization, metabolic adaptations, and crosstalk with FLS is crucial to developing targeted therapies that can restore immune homeostasis and mitigate joint pathology in RA.
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Artritis Reumatoide , Fibroblastos , Activación de Macrófagos , Macrófagos , Transducción de Señal , Membrana Sinovial , Humanos , Artritis Reumatoide/metabolismo , Artritis Reumatoide/inmunología , Artritis Reumatoide/patología , Macrófagos/inmunología , Macrófagos/metabolismo , Membrana Sinovial/metabolismo , Membrana Sinovial/inmunología , Membrana Sinovial/patología , Fibroblastos/metabolismo , Fibroblastos/inmunología , Animales , Activación de Macrófagos/inmunología , Comunicación Celular/inmunología , Reprogramación MetabólicaRESUMEN
Psoriasis is a chronic inflammatory skin disease characterized by the excessive proliferation of keratinocytes and heightened immune activation. Targeting pathogenic genes through small interfering RNA (siRNA) therapy represents a promising strategy for the treatment of psoriasis. This mini-review provides a comprehensive summary of siRNA research targeting the pathogenesis of psoriasis, covering aspects such as keratinocyte function, inflammatory cell roles, preclinical animal studies, and siRNA delivery mechanisms. It details recent advancements in RNA interference that modulate key factors including keratinocyte proliferation (Fibroblast Growth Factor Receptor 2, FGFR2), apoptosis (Interferon Alpha Inducible Protein 6, G1P3), differentiation (Grainyhead Like Transcription Factor 2, GRHL2), and angiogenesis (Vascular Endothelial Growth Factor, VEGF); immune cell infiltration and inflammation (Tumor Necrosis Factor-Alpha, TNF-α; Interleukin-17, IL-17); and signaling pathways (JAK-STAT, Nuclear Factor Kappa B, NF-κB) that govern immunopathology. Despite significant advances in siRNA-targeted treatments for psoriasis, several challenges persist. Continued scientific developments promise the creation of more effective and safer siRNA medications, potentially enhancing the quality of life for psoriasis patients and revolutionizing treatments for other diseases. This article focuses on the most recent research advancements in targeting the pathogenesis of psoriasis with siRNA and explores its future therapeutic prospects.
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BACKGROUND: Thyroid cancer represents the most prevalent malignant endocrine tumour, with rising incidence worldwide and high mortality rates among patients exhibiting dedifferentiation and metastasis. Effective biomarkers and therapeutic interventions are warranted in aggressive thyroid malignancies. The transcription factor 19 (TCF19) gene has been implicated in conferring a malignant phenotype in cancers. However, its contribution to thyroid neoplasms remains unclear. RESULTS: In this study, we performed genome-wide and phenome-wide association studies to identify a potential causal relationship between TCF19 and thyroid cancer. Our analyses revealed significant associations between TCF19 and various autoimmune diseases and human cancers, including cervical cancer and autoimmune thyroiditis, with a particularly robust signal for the deleterious missense variation rs2073724 that is associated with thyroid function, hypothyroidism, and autoimmunity. Furthermore, functional assays and transcriptional profiling in thyroid cancer cells demonstrated that TCF19 regulates important biological processes, especially inflammatory and immune responses. We demonstrated that TCF19 could promote the progression of thyroid cancer in vitro and in vivo and the C>T variant of rs2073724 disrupted TCF19 protein binding to target gene promoters and their expression, thus reversing the effect of TCF19 protein. CONCLUSIONS: Taken together, these findings implicate TCF19 as a promising therapeutic target in aggressive thyroid malignancies and designate rs2073724 as a causal biomarker warranting further investigation in thyroid cancer.
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Polimorfismo de Nucleótido Simple , Neoplasias de la Tiroides , Animales , Humanos , Ratones , Línea Celular Tumoral , Regulación Neoplásica de la Expresión Génica , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Neoplasias de la Tiroides/genética , Neoplasias de la Tiroides/patología , Tiroiditis/genéticaRESUMEN
Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.
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Metilación de ADN , Pueblos del Este de Asia , Sitios de Carácter Cuantitativo , Femenino , Humanos , Masculino , Pueblos del Este de Asia/genética , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo/métodos , Herencia Multifactorial , Polimorfismo de Nucleótido SimpleRESUMEN
OBJECTIVES: Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples. METHODS: The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient. RESULTS: The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94. CONCLUSIONS: This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.
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Artritis Reumatoide , Neoplasias , Osteoartritis , Femenino , Humanos , Metilación de ADN , Teorema de Bayes , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/genética , Osteoartritis/diagnóstico , Osteoartritis/genética , Biomarcadores , ADN , Neoplasias/genética , Antígenos de Neoplasias , Antígenos CDRESUMEN
Background: The single nucleotide polymorphism (SNP) of Gastrokine-1 (GKN1) is associated with lung cancer but its association with prognosis is not clear. Methods: Genomic DNA was extracted from the blood samples of 888 patients with lung cancer. The association between GKN1 polymorphism rs4254535 and prognostic was analyzed by the Kaplan-Meier (KM) method, Log-rank test, and Cox proportional hazards model. Results: In females and patients diagnosed with late-stage lung cancer, the CC genotype (CC vs TT, adjusted odds ratio [HR] = 0.57, 95% Confidence Interval [CI]: 0.33-0.99, P = 0.045; HR = 0.66, 95% CI: 0.48-0.92, P = 0.014) and recessive CC genotype (CC vs TT + TC, HR = 0.55, 95% CI: 0.32-0.94, P = 0.028; HR = 0.64, 95% CI: 0.47-0.89, P = 0.006) of rs4254535 conferred a better prognosis, compared with the TT and TT + TC genotype. Rs4254535 dominate TC + CC genotype, recessive CC genotype, and C allele who were adenocarcinoma patients had a significantly better prognosis. The recessive CC genotype of non-smoking patients has a better prognosis, compared to the TT + TC genotype. Additionally, in the dominant TT + TC genotype and C allele, no family history patients had a significantly better prognosis, compared to the TT genotype. Conclusion: For lung cancer patients, GKN1 polymorphism rs4254535 may be a protective genetic marker and predicts the prognosis of lung cancer patients.
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Neoplasias Pulmonares , Hormonas Peptídicas , Femenino , Humanos , Pronóstico , Neoplasias Pulmonares/genética , Genotipo , Polimorfismo de Nucleótido Simple/genética , ChinaRESUMEN
Objective: To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Methods: Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and HLA genes. We performed a protein-protein interaction network analysis and identified hub genes based on STRING and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the DGIdb database were used to mine hub genes' interactions with drugs. Results: There were 26 differentially expressed Anoikis-related genes (FDR = 0.05, log2FC = 1) and HLA genes exhibited differential expression (P < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between PIM2 and RAC2 was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls (P < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and HLA gene expression (P < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Conclusion: Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.
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Rheumatoid arthritis (RA) is a chronic, autoimmune pathology characterized by persistent synovial inflammation and gradually advancing bone destruction. Matrix metalloproteinases (MMPs), as a family of zinc-containing enzymes, have been found to play an important role in degradation and remodeling of extracellular matrix (ECM). MMPs participate in processes of cell proliferation, migration, inflammation, and cell metabolism. A growing number of persons have paid attention to their function in inflammatory and immune diseases. In this review, the details of regulation of MMPs expression and its expression in RA are summarized. The role of MMPs in ECM remodeling, angiogenesis, oxidative and nitrosative stress, cell migration and invasion, cytokine and chemokine production, PANoptosis and bone destruction in RA disease are discussed. Additionally, the review summarizes clinical trials targeting MMPs in inflammatory disease and discusses the potential of MMP inhibition in the therapeutic context of RA. MMPs may serve as biomarkers for drug response, pathology stratification, and precision medicine to improve clinical management of rheumatoid arthritis.
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Background: Czech dysplasia is a rare skeletal disorder with symptomatology including platyspondyly, brachydactyly of the third and fourth toes, and early-onset progressive pseudorheumatoid arthritis. The disorder segregates in an autosomal dominant fashion. A specific missense mutation (R275C, c.823C > T) in exon 13 of the COL2A1 gene has been identified in German and Japanese families. Case summary: We present the case of a Chinese woman diagnosed with Czech dysplasia (proband) who carried a variant in the COL2A1 gene. Whole-exome sequencing (WES) identified the COL2A1 missense mutation (R275C, c.823C > T) in close relatives of the proband who also exhibited the same disorder. Conclusion: This study is a thorough clinical and physiological description of Czech dysplasia in a Chinese patient.
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Large-scale longitudinal biobank data can be leveraged to identify genetic variation contributing to human diseases progression and traits trajectories. While methods for genome-wide association studies (GWAS) of multiple correlated traits have been proposed, an efficient multiple-trait approach to model longitudinal phenotypes is not currently available. We developed GAMUT, a genome-wide association approach for multiple longitudinal traits. GAMUT employs a mixed-effects model to fit longitudinal outcomes where a fast algorithm for inversion by recursive partitioning of the random effects submatrix is introduced. To evaluate performance of the algorithms introduced and assess their statistical power and type I error, stochastic simulation was conducted. Consistent with our expectation, power was greater for cross-sectional (CS) than longitudinal (LT) effects, particularly with a diminishing LT/CS ratio. With a minimum minor allele count of 3 within genotype by time categories, observed type I error was roughly equal to theoretical genome-wide significance. Additionally, 28 blood-based biomarkers measured at 2 time points on participants of the UK Biobank were used to compare GAMUT against single-trait standard and longitudinal GWAS (including rate of change). Across all biomarkers, we observed 539 (CS) and 248 (LT) significant independent variants for the GAMUT method, and 513 (CS) and 30 (LT) for single-trait longitudinal GWAS, respectively. Only 37 variants were identified by modeling rates of change using standard GWAS.
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Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Humanos , Estudios Transversales , Fenotipo , Genotipo , BiomarcadoresRESUMEN
Rheumatic and autoimmune diseases are a group of immune system-related disorders wherein the immune system mistakenly attacks and damages the body's tissues and organs. This excessive immune response leads to inflammation, tissue damage, and functional impairment. Therapeutic approaches typically involve medications that regulate immune responses, reduce inflammation, alleviate symptoms, and target specific damaged organs. Tripterygium wilfordii Hook. f., a traditional Chinese medicinal plant, has been widely studied in recent years for its application in the treatment of autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis. Numerous studies have shown that preparations of Tripterygium wilfordii have anti-inflammatory, immunomodulatory, and immunosuppressive effects, which effectively improve the symptoms and quality of life of patients with autoimmune diseases, whereas the active metabolites of T. wilfordii have been demonstrated to inhibit immune cell activation, regulate the production of inflammatory factors, and modulate the immune system. However, although these effects contribute to reductions in inflammatory responses and the suppression of autoimmune reactions, as well as minimize tissue and organ damage, the underlying mechanisms of action require further investigation. Moreover, despite the efficacy of T. wilfordii in the treatment of autoimmune diseases, its toxicity and side effects, including its potential hepatotoxicity and nephrotoxicity, warrant a thorough assessment. Furthermore, to maximize the therapeutic benefits of this plant in the treatment of autoimmune diseases and enable more patients to utilize these benefits, efforts should be made to strengthen the regulation and standardized use of T. wilfordii.
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Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and joint damage. The signaling lymphocytic activation molecule (SLAMF) family of receptors are expressed on various hematopoietic and non-hematopoietic cells and can regulate both immune cell activation and cytokine production. Altered expression of certain SLAMF receptors contributes to aberrant immune responses in RA. In RA, SLAMF1 is upregulated on T cells and may promote inflammation by participating in immune cell-mediated responses. SLAMF2 and SLAMF4 are involved in regulating monocyte tumor necrosis factor production and promoting inflammation. SLAMF7 activates multiple inflammatory pathways in macrophages to drive inflammatory gene expression. SLAMF8 inhibition can reduce inflammation in RA by blocking ERK/MMPs signaling. Of note, there are differences in SLAMF receptor (SFR) expression between normal and arthritic joint tissues, suggesting a role as potential diagnostic biomarkers. This review summarizes recent advances on the roles of SLAMF receptors 1, 2, 4, 7, and 8 in RA pathogenesis. However, further research is needed to elucidate the mechanisms of SLAMF regulation of immune cells in RA. Understanding interactions between SLAMF receptors and immune cells will help identify selective strategies for targeting SLAMF signaling without compromising normal immunity. Overall, the SLAMF gene family holds promise as a target for precision medicine in RA, but additional investigation of the underlying immunological mechanisms is needed. Targeting SLAMF receptors presents opportunities for new diagnostic and therapeutic approaches to dampen damaging immune-mediated inflammation in RA.
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Recent research has shown that visual-text pretrained models perform well in traditional vision tasks. CLIP, as the most influential work, has garnered significant attention from researchers. Thanks to its excellent visual representation capabilities, many recent studies have used CLIP for pixel-level tasks. We explore the potential abilities of CLIP in the field of few-shot segmentation. The current mainstream approach is to utilize support and query features to generate class prototypes and then use the prototype features to match image features. We propose a new method that utilizes CLIP to extract text features for a specific class. These text features are then used as training samples to participate in the model's training process. The addition of text features enables model to extract features that contain richer semantic information, thus making it easier to capture potential class information. To better match the query image features, we also propose a new prototype generation method that incorporates multi-modal fusion features of text and images in the prototype generation process. Adaptive query prototypes were generated by combining foreground and background information from the images with the multi-modal support prototype, thereby allowing for a better matching of image features and improved segmentation accuracy. We provide a new perspective to the task of few-shot segmentation in multi-modal scenarios. Experiments demonstrate that our proposed method achieves excellent results on two common datasets, PASCAL-5i and COCO-20i.