Osteoarthritis versus psoriasis arthritis: Physiopathology, cellular signaling, and therapeutic strategies

Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018

Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly among individuals over the age of 45. This condition causes joint pain and dysfunction, significantly disrupting daily life. The objective of this study is to develop an optimal machine learning model for predicting the risk of osteoarthritis in individuals aged 45 and older. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018, which included a total of 2980 individuals. The dataset was randomly divided into a training set (n = 2235) and a validation set (n = 745). Five machine learning algorithms were employed to develop the predictive model for osteoarthritis. The SHapley Additive exPlanation (SHAP) method was used to interpret the machine learning algorithms and identify the most significant features for predicting outcomes. The study involved 2980 participants and focused on predicting the probability of osteoarthritis occurrence using machine learning algorithms. Five algorithms were employed, analyzing 24 features from an average 60-year-old cohort, with 605 osteoarthritis diagnoses. After performing Recursive Feature Elimination (RFE) to select 20 features, the CatBoost model achieved an AUC of 0.8109 and an accuracy rate of 0.7315, making it the most efficient model. The most influential factors in the predictions were Gender, Age, BMI, Waist Circumference, and Race. This study demonstrates that the CatBoost model with 20 features can effectively predict the occurrence of osteoarthritis. This accurate prediction model can help inform early interventions and patient management strategies, potentially improving patient prognosis. Further research will focus on enhancing the model performance, such as incorporating additional relevant features or refining existing ones. Additionally, validating the model in more diverse patient populations, and investigating its potential for real-time implementation in clinical settings would further increase the study's impact and facilitate its translation into clinical practice.

The interleukin gene landscape: understanding its influence on inflammatory mechanisms in apical periodontitis

Apical periodontitis is a common inflammatory illness caused by microbial infections in the root canal system, which destroys the periapical tissue. This disease's course and severity are highly regulated by a complex interaction of host immunological responses and genetic variables, particularly interleukin (IL) gene polymorphisms. These genetic variants influence cytokine production, the inflammatory cascade, and the ability to resolve infections. Polymorphisms in important cytokines (e.g., IL-1β, IL-6, IL-10, TNF-α, and IL-17) have been linked to worsening or reducing inflammation, affecting the clinical presentation and chronicity of apical periodontitis. A thorough examination of the molecular and clinical consequences of interleukin polymorphisms in apical periodontitis is given in this article. It emphasizes their function in regulating bone resorption, tissue degradation, and immune cell signaling. Their value in enhancing diagnostic precision, forecasting disease susceptibility, and directing treatment approaches is demonstrated by the incorporation of genetic insights into clinical practice. Targeted therapies, like immunomodulatory drugs and cytokine inhibitors, have great potential to reduce inflammation and encourage periapical healing. Future studies should focus on population-based research to examine genetic variability across ethnic groups, functional investigations to clarify the mechanisms behind polymorphism-driven cytokine regulation, and longitudinal studies to evaluate illness trajectories. Furthermore, developments in precision medicine and bioinformatics could completely transform patient-specific strategies by providing customized treatments and diagnostics. This review highlights the necessity of a multidisciplinary strategy that integrates immunology, genetics, and clinical practice to maximize apical periodontitis therapy and enhance dental health outcomes worldwide.

Notch signaling pathway in osteogenesis, bone development, metabolism, and diseases

The skeletal system provides vital importance to support organ development and functions. The Notch signaling pathway possesses well-established functions in organ development and cellular homeostasis. The Notch signaling pathway comprises five typical ligands (JAG1, JAG2, DLL1, DLL3, and DLL4), four receptors (Notch1-4), and four intracellular domains (NICD1-4). Each component of the Notch signaling pathway has been demonstrated to be fundamental in osteoblast differentiation and bone formation. The dysregulation in the Notch signaling pathway is highly linked with skeletal disorders or diseases at the developmental and postnatal stages. Recent studies have highlighted the importance of the elements of the Notch signaling pathway in the skeletal system, as well as its interaction with signaling, such as Wnt/β-catenin, BMP, TGF-β, FGF, autophagy, and hedgehog (Hh) to construct a potential gene regulatory network to orchestrate osteogenesis and ossification. Our review has provided a comprehensive summary of the Notch signaling pathway in the skeletal system, as well as the insights targeting Notch signaling for innovative potential drug discovery targets or therapeutic interventions to treat bone disorders, such as osteoporosis and osteoarthritis. An in-depth molecular mechanistic strategy to modulate the Notch signaling pathway and its associated signaling pathway will be encouraged for consideration to trigger enhanced therapeutic approaches for bone disorders by defining Notch-regulating drugs for clinical use.

Cbfβ: A key regulator in skeletal stem cell differentiation, bone development, and disease

The skeletal system comprises closely related yet functionally distinct bone and cartilage tissues, regulated by a complex network of transcriptional factors and signaling molecules. Among these, core-binding factor subunit beta (Cbfβ) emerges as a critical co-transcriptional factor that stabilizes Runx proteins, playing indispensable roles in skeletal development and homeostasis. Emerging evidence from genetic mouse models has highlighted the essential role of Cbfβ in directing the lineage commitment of mesenchymal stem cells (MSCs) and their differentiation into osteoblasts and chondrocytes. Notably, Cbfβ deficiency is strongly associated with severe skeletal dysplasia, affecting both endochondral and intramembranous ossification during embryonic and postnatal development. In this review, we synthesize recent advancements in understanding the structural and molecular functions of Cbfβ, with a particular focus on its interactions with key signaling pathways, including BMP/TGF-β, Wnt/β-catenin, Hippo/YAP, and IHH/PTHrP. These pathways converge on the Cbfβ/RUNX2 complex, which orchestrates a gene expression program essential for osteogenesis, bone formation, and cartilage development. The integration of these signaling networks ensures the precise regulation of skeletal development, remodeling, and repair. Furthermore, the successful local delivery of Cbfβ to address bone abnormalities underscores its potential as a novel therapeutic target for skeletal disorders such as cleidocranial dysplasia, osteoarthritis, and bone metastases. By elucidating the molecular mechanisms underlying Cbfβ function and its interactions with key signaling pathways, these insights not only advance our understanding of skeletal biology but also offer promising avenues for clinical intervention, ultimately improving outcomes for patients with skeletal disorders.

Advanced whole transcriptome sequencing and artificial intelligence/machine learning (AI/ML) in imiquimod-induced psoriasis-like inflammation of human keratinocytes

Introduction

Although the HaCaT keratinocyte model has been used in previous research to study the effects of antipsoriatic agents, there is still a lack of comprehensive understanding of the mechanism of imiquimod (IMQ)-induced proliferation and signal transduction in psoriasis-like keratinocytes.

Objectives

This study aimed to investigate the molecular mechanisms and pathways associated with psoriasis-like inflammation caused by IMQ in human keratinocytes.

Materials and methods

HaCaT cells were exposed to different concentrations of IMQ to induce inflammation similar to that observed in psoriasis. Cell viability was evaluated using the MTT assay and cell morphology was examined using phase-contrast microscopy. Gene expression profiles were analyzed through whole transcriptome sequencing, followed by bio-informatics network analysis using IPA software. The GSEA was conducted with the aim of identifying enriched pathways. The expression of key cytokines IL-6 and TNF-α was confirmed by QPCR. Artificial intelligence/machine learning (AI/ML) algorithms were used to predict potential diseases and phenotypes associated with the observed gene profiles.

Results

IMQ treatment demonstrated a substantial positive impact on cell survival without any detectable alterations in the morphology of HaCaT cells. A comprehensive analysis of the entire set of transcribed genes identified 513 genes that exhibited differential expression. Bioinformatics analysis revealed key pathways associated with immune response, cellular proliferation, and cytokine signaling. GSEA identified significant enrichment in the IFN-γ response and JAK-STAT signaling pathways. QPCR analysis confirmed the increased mRNA expression levels of IL-6 and TNF-α in cells treated with IMQ. AI/ML algorithms have identified potential correlations with diseases, such as multiple sclerosis, lympho-proliferative malignancy, and autoimmune disorders.

Conclusion

Our results highlight the importance of specific genes and pathways, particularly those associated with IFN-γ pathway and IL-6/JAK-STAT signaling. AI/ML predictions indicate potential associations with various diseases and provide valuable insights for the development of novel therapeutic approaches for psoriasis and related disorders.

A systematic review and meta-analysis of the efficacy and safety of iguratimod in the treatment of inflammatory arthritis and degenerative arthritis

Objective

To assess the efficacy and safety of iguratimod (IGU) in the treatment of inflammatory arthritis and degenerative arthritis.

Methods

Initially, randomized controlled trials (RCTs) on using IGU in treating inflammatory arthritis and degenerative arthritis were systematically gathered from various databases up to February 2024. Subsequently, two researchers independently screened the literature, extracted data, assessed the risk of bias in included studies, and conducted a meta-analysis using RevMan 5.4 software.

Results

Fifty-four RCTs involving three inflammatory arthritis were included, including ankylosing spondylitis (AS), osteoarthritis (OA), and rheumatoid arthritis (RA). For AS, the meta-analysis results showed that IGU may decrease BASDAI (SMD -1.68 [-2.32, -1.03], P < 0.00001) and BASFI (WMD -1.29 [-1.47, -1.11], P < 0.00001); IGU may also decrease inflammatory factor [ESR: (WMD -10.33 [-14.96, -5.70], P < 0.0001); CRP: (WMD -10.11 [-14.55, -5.66], P < 0.00001); TNF-α: (WMD -6.22 [-7.97, -4.47], P < 0.00001)]. For OA, the meta-analysis results showed that IGU may decrease VAS (WMD -2.20 [-2.38, -2.01], P < 0.00001) and WOMAC (WMD -7.27 [-12.31, -2.24], P = 0.005); IGU may also decrease IL-6 (WMD -8.72 [-10.00, -7.45], P < 0.00001). For RA, the meta-analysis results showed that IGU may improve RA remission rate [ACR20: (RR 1.18 [1.02, 1.35], P = 0.02); ACR50: (RR 1.32 [1.05, 1.64], P = 0.02); ACR70: (RR 1.44 [1.02, 2.04], P = 0.04)] and decrease DAS28 (WMD -0.92 [-1.20, -0.63], P < 0.00001); IGU may also decrease inflammatory factors [CRP: (SMD -1.36 [-1.75, -0.96], P < 0.00001); ESR: (WMD -9.09 [-11.80, -6.38], P < 0.00001); RF: (SMD -1.21 [-1.69, -0.73], P < 0.00001)]. Regarding safety, adding IGU will not increase the incidence of adverse events.

Conclusion

IGU might emerge as a promising and secure therapeutic modality for addressing AS, OA, and RA.

Systematic Review Registration

Identifier PROSPERO: CRD42021289249.

IGF signaling pathway in bone and cartilage development, homeostasis, and disease

The skeleton plays a fundamental role in the maintenance of organ function and daily activities. The insulin-like growth factor (IGF) family is a group of polypeptide substances with a pronounced role in osteoblast differentiation, bone development, and metabolism. Disturbance of the IGFs and the IGF signaling pathway is inextricably linked with assorted developmental defects, growth irregularities, and jeopardized skeletal structure. Recent findings have illustrated the significance of the action of the IGF signaling pathway via growth factors and receptors and its interactions with dissimilar signaling pathways (Wnt/β-catenin, BMP, TGF-β, and Hh/PTH signaling pathways) in promoting the growth, survival, and differentiation of osteoblasts. IGF signaling also exhibits profound influences on cartilage and bone development and skeletal homeostasis via versatile cell-cell interactions in an autocrine, paracrine, and endocrine manner systemically and locally. Our review summarizes the role and regulatory function as well as a potentially integrated gene network of the IGF signaling pathway with other signaling pathways in bone and cartilage development and skeletal homeostasis, which in turn provides an enlightening insight into visualizing bright molecular targets to be eligible for designing effective drugs to handle bone diseases and maladies, such as osteoporosis, osteoarthritis, and dwarfism.

Exploring the causal relationship between psoriasis and osteoarthritis through a 2-sample Mendelian randomization study

Previous research has demonstrated a robust association between osteoarthritis (OA) and psoriasis. Notably, a significant proportion of psoriasis patients exhibit symptoms of arthritis, particularly psoriatic arthritis. However, a definitive causal relationship between psoriasis, psoriatic arthritis and OA remains to be established. This study aimed to elucidate the causal relationship between psoriasis, psoriatic arthritis, and osteoarthritis using a 2-sample Mendelian randomization approach. The causal relationship between psoriasis, psoriatic arthritis and OA was rigorously investigated using a 2-sample Mendelian Randomization (MR) approach. Instrumental variables pertinent to psoriasis, psoriatic arthritis and 4 distinct types of OA (knee osteoarthritis (KOA), hand osteoarthritis (HOA), total knee replacement (TKR), and total hip replacement (THR)) were sourced from extensive, published genome-wide association studies (GWAS). To estimate the causal effects, methodologies such as inverse variance weighting (IVW), MR-Egger, and weighted median estimation (WM) were employed. Mendelian Randomization analysis suggested a potential causal effect of psoriasis on osteoarthritis (OA). For hand OA (HOA), the P value was .381 (OR = 0.28); for knee OA (KOA), the P value was .725 (OR = 1.46); for TKR, the P value was .488 (OR = 0.274); and for THR, the P value was .454 (OR = 0.216). Furthermore, we explored the causality of psoriatic arthritis on OA. For HOA, the P value was .478 (OR = 0.0095); for KOA, the P value was .835 (OR = 0.345); for THR, the P value was .807 (OR = 0.120); and for TKR, the P value was .860 (OR = 0.190). Our findings indicate that there is no evidence of a causal connection between psoriasis or psoriatic arthritis and OA, suggesting that while psoriasis may contribute to arthritis, it does not influence OA development.

Genome Sequencing Analysis of a Rare Case of Blood Infection Caused by Flavonifractor plautii

BACKGROUND Flavonifractor plautii belongs to the clostridium family, which can lead to local infections as well as the bloodstream infections. Flavonifractor plautii caused infection is rarely few in the clinic. To understand better Flavonifractor plautii, we investigated the drug sensitivity and perform genome sequencing of Flavonifractor plautii isolated from blood samples in China and explored the drug resistance and pathogenic mechanism of the bacteria. CASE REPORT The Epsilometer test method was used to detect the sensitivity of flavonoid bacteria to antimicrobial agents. PacBio sequencing technology was employed to sequence the whole genome of Flavonifractor plautii, and gene prediction and functional annotation were also analyzed. Flavonifractor plautii displayed sensitivity to most drugs but resistance to fluoroquinolones and tetracycline, potentially mediated by tet (W/N/W). The total genome size of Flavonifractor plautii was 4,573,303 bp, and the GC content was 59.78%. Genome prediction identified 4,506 open reading frames, including 9 ribosomal RNAs and 66 transfer RNAs. It was detected that the main virulence factor-coding genes of the bacteria were the capsule, polar flagella and FbpABC, which may be associated with bacterial movement, adhesion, and biofilm formation. CONCLUSIONS The results of whole-genome sequencing could provide relevant information about the drug resistance mechanism and pathogenic mechanism of bacteria and offer a basis for clinical diagnosis and treatment.

Diagnostic Efficiency of ACR-TIRADS Score for Differentiating Benign and Malignant Thyroid Nodules of Various Pathological Types

BACKGROUND Thyroid nodule prevalence reaches 65% in the general population. Hence, appropriate ultrasonic examination is key in disease monitoring and management. We investigated the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) score for diagnosis of benign and malignant thyroid nodules and pathological types. MATERIAL AND METHODS A retrospective study was conducted. According to ultrasound images, ultrasonic characteristics of benign and malignant thyroid nodules and different pathological types were analyzed using ACR-TIRADS score, and diagnostic value was determined. AUCs were compared for tumor diagnosis and differentiation. RESULTS Overall, 1675 thyroid nodules from 1614 patients were included. AUC value of papillary thyroid carcinoma (PTC) diagnosed with ACR-TIRADS was highest (0.955 [95% CI=0.946-0.965]), while that of follicular thyroid carcinoma (FTC) was lowest (0.877 [95% CI=0.843-0.912]). FTC had the highest sensitivity (95.1%) and lowest specificity (64.8%). When the cut-off value was 5.5 points, accuracy of diagnosing PTC and anaplastic thyroid carcinoma (ATC) was highest, 80.5% and 78.7% respectively. Comparison of the multi-index prediction model constructed by multivariable logistic regression analysis and prediction model constructed by ACR-TIRADS score showed, when evaluating PTC and ATC, the multi-index model was better: AUCs of PTC were 0.966 vs 0.955, and AUCs of ATC were 0.982 vs 0.952, respectively, (P<0.05). CONCLUSIONS ACR-TIRADS score-based ultrasound examination of thyroid nodules aids diagnosis of benign and malignant thyroid nodules. TIRADS criteria favor diagnosis of PTC (and ATC) over FTC. ACR-TIRADS score can help clinicians diagnose thyroid nodules quickly and earlier, exhibits good clinical value, and can prevent missed diagnoses.

Potential therapeutic strategies for osteoarthritis via CRISPR/Cas9 mediated gene editing

Osteoarthritis (OA) is an incapacitating and one of the most common physically degenerative conditions with an assorted etiology and a highly complicated molecular mechanism that to date lacks an efficient treatment. The capacity to design biological networks and accurately modify existing genomic sites holds an apt potential for applications across medical and biotechnological sciences. One of these highly specific genomes editing technologies is the CRISPR/Cas9 mechanism, referred to as the clustered regularly interspaced short palindromic repeats, which is a defense mechanism constituted by CRISPR associated protein 9 (Cas9) directed by small non-coding RNAs (sncRNA) that bind to target DNA through Watson-Crick base pairing rules where subsequent repair of the target DNA is initiated. Up-to-date research has established the effectiveness of the CRISPR/Cas9 mechanism in targeting the genetic and epigenetic alterations in OA by suppressing or deleting gene expressions and eventually distributing distinctive anti-arthritic properties in both in vitro and in vivo osteoarthritic models. This review aims to epitomize the role of this high-throughput and multiplexed gene editing method as an analogous therapeutic strategy that could greatly facilitate the clinical development of OA-related treatments since it's reportedly an easy, minimally invasive technique, and a comparatively less painful method for osteoarthritic patients.

Mechanistic role of quercetin as inhibitor for adenosine deaminase enzyme in rheumatoid arthritis: systematic review

Rheumatoid arthritis (RA) is an autoimmune disease involving T and B lymphocytes. Autoantibodies contribute to joint deterioration and worsening symptoms. Adenosine deaminase (ADA), an enzyme in purine metabolism, influences adenosine levels and joint inflammation. Inhibiting ADA could impact RA progression. Intracellular ATP breakdown generates adenosine, which increases in hypoxic and inflammatory conditions. Lymphocytes with ADA play a role in RA. Inhibiting lymphocytic ADA activity has an immune-regulatory effect. Synovial fluid levels of ADA are closely associated with the disease's systemic activity, making it a useful parameter for evaluating joint inflammation. Flavonoids, such as quercetin (QUE), are natural substances that can inhibit ADA activity. QUE demonstrates immune-regulatory effects and restores T-cell homeostasis, making it a promising candidate for RA therapy. In this review, we will explore the impact of QUE in suppressing ADA and reducing produced the inflammation in RA, including preclinical investigations and clinical trials.