Search Results (141)

Meniscal degradation is considered a driver of osteoarthritis (OA) progression, but the underlying mechanisms leading to age-related meniscus degeneration remain unknown. This study aimed to identify key genes and pathways involved in meniscal degradation through a computational analysis. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differential expression gene (DEG) analysis was performed using DESeq2 accompanied by functional enrichment analysis, protein–protein interaction (PPI) and clustering analysis. Additionally, gene set enrichment analysis (GSEA) was performed. A total of 85 mRNAs (DEMs) and 8 long non-coding RNAs (DE LncRNAs) were found to be differentially expressed in OA meniscus tissues. Among 85 DEMs, 12 genes were found to be known OA-related genes, whereas 15 genes acted as transcription regulators, including RUNX2 and TBX4, which were identified as effector genes for OA. Enrichment analysis revealed the implication of DEMs in cartilage-degradation-related processes, including inflammatory pathways, lipid metabolism, extracellular matrix organization and superoxide/nitric oxide metabolic processes. Target genes of DE lncRNAs were found to be involved in chondrocyte differentiation and pathways related to cartilage degradation. A comparative analysis of meniscus, synovium and cartilage datasets identified three genes (GJB2, PAQR5 and CLEC12A) as being differentially expressed across all three OA-affected tissues, which were implicated in inflammatory and cholesterol metabolism processes. Our results support that shared mechanisms lead to meniscal and cartilage degradation during OA progression, providing further insights into the processes underlying OA pathogenesis and potential therapeutic targets for knee OA. Full article

Staphylococcus aureus is a significant bacterial pathogen responsible for a wide range of diseases in both humans and animals. This study aimed to investigate nucleotide sequence variations, gene expression patterns, and serum biomarkers, including acute phase proteins (APPs), hormonal fluctuations, and iron profile parameters in sheep affected by pneumonia. Additionally, the study focused on the isolation and characterization of S. aureus from pneumonic sheep, with particular emphasis on the prevalence of methicillin-resistant S. aureus (MRSA) strains. Blood samples were collected from both healthy and pneumonic sheep for gene expression and biochemical analyses, while nasal swabs from pneumonic sheep were used for bacterial isolation and identification. Out of 100 nasal swabs analyzed, 44% tested positive for Staphylococcus spp., and 61.4% of these were confirmed as S. aureus by PCR. The mecA gene, a key marker of methicillin resistance, was identified in 17 isolates (38.6% of the S. aureus-positive samples). MRSA isolates showed complete resistance to amoxicillin, cloxacillin, and erythromycin, and high resistance to penicillin, amoxicillin, and tetracycline; however, all MRSA strains remained fully susceptible to vancomycin. Gene expression analysis revealed that TLR2, CLEC4E, PTX3, CXCL8, and IL15RA were significantly upregulated (p < 0.05) in pneumonic ewes, while SOCS3 expression was markedly downregulated. Sequence analysis of immune-related genes revealed notable nucleotide differences between healthy and affected animals. Furthermore, the pneumonic group exhibited significantly elevated levels of APPs, cortisol, and growth hormone, along with reduced levels of insulin, T3, and T4. These findings underscore the zoonotic risk posed by MRSA and emphasize the need for robust surveillance and antibiotic stewardship to control its spread. The study also highlights the importance of molecular diagnostics in accurately identifying MRSA and elucidating resistance mechanisms, thereby facilitating targeted treatment and informed management strategies. Full article

Currently, there are two major theories regarding the pathogenesis of sepsis: hyperimmune and hypoimmune. The hyperimmune theory suggests that a cytokine storm causes the symptoms of sepsis. On the contrary, the hypoimmune theory suggests that immunosuppression causes the manifestations of sepsis. By conducting a microarray analysis on peripheral leukocytes from patients with sepsis, this study found that hyperactivity of TH17 immunity was noted in sepsis patients. Innate immunity-related genes are significantly upregulated, including CD14, TLR1,2,4,5,8, HSP70, CEBP proteins, AP1 (JUNB and FOSL2), TGFB1, IL6, TGFA, CSF2 receptor, TNFRSF1A, S100A binding proteins, CCR2, FPR2, amyloid proteins, pentraxin, defensins, CLEC5A, whole complement machinery, CPD, NCF, MMP, neutrophil elastase, caspases, IgG and IgA Fc receptors (CD64, CD32), ALOX5, PTGS, LTB4R, LTA4H, and ICAM1. The majority of adaptive immunity genes were downregulated, including MHC-related genes, TCR genes, granzymes/perforin, CD40, CD8, CD3, TCR signaling, BCR signaling, T and B cell-specific transcription factors, NK killer receptors, and TH17 helper-specific transcription factors (STAT3, RORA, and REL), as well as Treg-related genes, including TGFB1, IL15, STAT5B, SMAD2/4, CD36, and thrombospondin. The findings of this study show that Th17 with Treg over-presentation play an important role in the pathophysiology of sepsis. Full article

Accurate early-season crop classification is critical for food security, agricultural applications and policymaking. However, when classification is performed earlier, the available time-series data gradually become scarce. Existing methods mainly focus on enhancing the model’s ability to extract features from limited data to address this challenge, but the extracted critical phenological information remains insufficient. This study proposes a Cascade Learning Early Classification (CLEC) framework, which consists of two components: data preprocessing and a cascade learning model. Data preprocessing generates high-quality time-series data from the optical, radar and thermodynamic data in the early stages of crop growth. The cascade learning model integrates a prediction task and a classification task, which are interconnected through the cascade learning mechanism. First, the prediction task is performed to supplement more time-series data of the growing stage. Then, crop classification is carried out. Meanwhile, the cascade learning mechanism is used to iteratively optimize the prediction and classification results. To validate the effectiveness of CLEC, we conducted early-season classification experiments on soybean, corn and rice in Northeast China. The experimental results show that CLEC significantly improves crop classification accuracy compared to the five state-of-the-art models in the early stages of crop growth. Furthermore, under the premise of obtaining reliable results, CLEC advances the earliest identifiable timing, moving from the flowing to the third true leaf stage for soybean and from the flooding to the sowing stage for rice. Although the earliest identifiable timing for corn remains unchanged, its classification accuracy improved. Overall, CLEC offers new ideas for solving early-season classification challenges. Full article

Alzheimer’s disease (AD) pathogenesis involves progressive synaptic degeneration, a process potentially driven by maladaptive microglial pruning activity. While synaptic loss is a hallmark of AD, the molecular signals triggering pathological microglia-mediated synaptic engulfment remain elusive. Clec7a—a key marker of disease-associated microglia (DAM)—is known to activate spleen tyrosine kinase (SYK) signaling, enhancing Aβ phagocytosis and neuroprotective functions in 5×FAD models. However, its role in regulating synapse–microglia interactions under tauopathic conditions remains undefined. Our analysis revealed a progressive activation of the Clec7a–SYK signaling axis in the hippocampus of PS19 tauopathy mice, correlating with disease progression. Spatial mapping demonstrated a significant co-localization of Clec7a with hippocampal microglia, suggesting cell-autonomous signaling. The pharmacological inhibition of Clec7a achieved multimodal therapeutic effects by attenuating microglial hyperreactivity, suppressing neuroinflammatory cytokine release, and restoring physiological synaptic turnover. Mechanistically, we identified MD2 as a synaptic “eat-me” signal on tauopathy-related synapses, recruiting Clec7a+ microglia to drive aberrant synaptic elimination in PS19 mice. Strikingly, Clec7a blockade rescued hippocampal-dependent memory deficits in behavioral tests. These findings position Clec7a as a context-dependent therapeutic target, with inhibition strategies showing particular promise for tauopathy-related synaptic degeneration. Full article

(1) Background: The C-type lectin domain family 4 member M (CLEC4M, also known as L-SIGN) is a crucial pathogen-recognition receptor for the dengue virus (DENV). Our previous study has exhibited a polymorphism in its extracellular neck region, specifically within the long tandem repeats of exon 4, which correlates with DHF in DENV infection and causes liver damage. (2) Methods: Using monocyte-derived dendritic cells (MDDCs) and SK-HEP1 liver endothelial cell lines to compare viral replication relative to L-SIGN expression. (3) Results: Results indicated that SK-HEP1 cells were more susceptible to DENV infection than MDDCs, and L-SIGN transfection significantly increased viral replication in SK-HEP1 cell lines. The study also found that L-SIGN-enhanced DENV infection is mediated by the decrease in monocyte chemoattractant protein-1 (MCP-1) but not interferon gamma inducible protein-10 (IP-10). These findings reveal that L-SIGN-induced DENV infection leads to reduced MCP-1 levels, which, in turn, enhances DENV replication velocity. (4) Conclusions: This study offers insights into the molecular mechanisms of DENV replication and identifies potential therapeutic targets involving MCP-1 and L-SIGN pathways. Full article

Background/Objectives: Biomaterials are an essential part of healthcare for both diagnostic and therapeutic procedures. Although some biomaterials possess antimicrobial properties, introducing biomaterial into the body may lead to infections due to bacterial adhesion on their surfaces and still poses a major clinical problem. Peptides derived from the human cartilage-specific C-type lectin domain family 3 member A (CLEC3A) show a potent antimicrobial effect. In addition, coating titanium, a commonly used prosthetic material, with the CLEC3A-derived AMPs HT-47 and WRK-30 greatly reduces the number of adherent bacteria in vitro. The aim of this study was to evaluate the effectiveness of CLEC3A-derived peptides HT-47 and WRK-30 in reducing bacterial adhesion and mitigating infection in vivo in a murine biomaterial-associated infection model. Methods: To do so, an in vivo mouse infection model was used, where titanium plates—either uncoated or coated with chimeric CLEC3A-derived peptides TiBP-HT-47 and TiBP-WRK-30—were implanted subcutaneously into mice. This was followed by the introduction of Staphylococcus aureus bacterial cultures to induce a biomaterial-associated infection. After 24 h, the titanium plates, surrounding tissue, and mice blood samples were investigated. Results: CLEC3A-coated titanium plates lead to a significantly lower bacterial count than uncoated ones. Additionally, they prevent the infection from spreading to the surrounding tissue. Moreover, mice with CLEC3A-coated implants display lower IL-6 serum levels and therefore decreased systemic inflammation. Conclusions: In conclusion, in this biomaterial-associated infection mouse-model, CLEC3A-derived peptides show in vivo antimicrobial activity by reducing bacterial burden on biomaterial and wound tissue and decreasing systemic inflammation, making them promising candidates for clinical applications. Full article

Background: Tumor mutation burden (TMB), a genomic biomarker, has proven to be a strong predictor of immunotherapy response but is not widely adopted. This study investigates the association between TMB and immune checkpoint inhibitors (ICIs) response in TNBC patients. Methods: From the TCGA database, patients were stratified into two levels based on TMB and validated using survival analysis. Then, four machine learning models were trained to classify TNBC patients based on histological features into high and low TMB. To further validate our approach, we compared the genomic landscapes of both groups, identified differentially expressed genes (DEGs), and performed pathway enrichment analysis. Results: Our findings revealed a significant association between TMB and ICI response in TNBC. Random forest model effectively classified TNBC patients based on the representative histological features and clinical data with an accuracy of 0.82 on the validation set. The genomic analysis revealed that FAT3, TTN, and DYNC2H1 had a significantly high mutation rate in the TMB groups. Genes impacting cancer progression and immunogenicity were identified in the DEG analysis as IGF2, CLEC3A, and CASC9. Conclusions: This study constructs a model to identify suitable TNBC patients for immunotherapy and highlights the potential role of TMB associated with genomic alterations in predicting immune response in TNBC. Full article

The genetic landscape of multiple sclerosis (MS) has been extensively mapped, yielding significant insights into the molecular mechanisms of the disorder. Early studies highlighted key genes associated with the immune system, particularly T cells, as critical for MS susceptibility. Subsequent large-scale genome-wide association studies (GWASs) identified over 200 genetic variants linked to MS, revealing a complex interplay between MS risk and genes involved in various processes within adaptive and innate immune cells, as well as brain-resident microglia. Recently, a groundbreaking GWAS pinpointed the first gene variant associated with MS disease progression, distinguishing the mechanisms driving disease onset from those influencing progression. The C-type lectin domain family 16, member A (CLEC16A) gene within the 16p13 region has consistently been shown to be associated with increased risk of developing both MS and other autoimmune disorders. Notably, several autoimmune-associated genetic variants in CLEC16A introns act as expression quantitative trait loci for the dexamethasone-induced protein (DEXI gene, adding DEXI to the growing list of MS susceptibility genes. This review explores the molecular and functional characterization of DEXI with a particular focus on recent advances in understanding its role in autoimmunity, specifically in the context of multiple sclerosis. We underscore the importance of continued molecular investigation of susceptibility loci for MS identified in genetic studies, with the goal of translating this knowledge into clinical applications. Full article

Background and Objectives: Immunoglobulin G4-related disease (IgG4-RD) is an immune-mediated, fibroinflammatory, multiorgan disease with an obscure pathogenesis. Findings indicating excessive platelet activation have been reported in systemic sclerosis, which is another autoimmune, multisystemic fibrotic disorder. The immune-mediated, inflammatory, and fibrosing intersections of IgG4-RD and systemic sclerosis raised a question about platelets’ role in IgG4-RD. Materials and Methods: By borrowing transcriptomic data from Nakajima et al. (GEO repository, GSE66465) we sought a platelet contribution to the pathogenesis of IgG4-RD. GEO2R and BRB-ArrayTools were used for class comparisons, and WebGestalt for functional enrichment analysis. During the selection of differentially expressed genes (DEGs), the translationally active but significantly low amount of platelet mRNA was specifically considered. The platelet-specific gene signature derived was used for cluster analysis of patient and control groups. Results: When IgG4-RD patients were compared with controls, 268 DEGs (204 with increased and 64 with decreased expression) were detected. Among these, a molecular signature of 22 platelet-specific genes harbored genes important for leukocyte–platelet aggregate formation (i.e., CLEC1B, GP1BA, ITGA2B, ITGB3, SELP, and TREML1) and extracellular matrix synthesis (i.e., CLU, PF4, PPBP, SPARC, and THBS1). Functional enrichment analysis documented significantly enriched terms related to platelets, including but not limited to “platelet reactivity”, “platelet degranulation”, “platelet aggregation”, and “platelet activation”. During clustering, the 22 gene signatures successfully discriminated IgG4-RD and the control and the IgG4-RD before and after treatment groups. Conclusions: Patients with IgG4-RD apparently display an activated platelet phenotype with a potential contribution to disease immunopathogenesis. If the platelets’ role is validated through further carefully designed research, the therapeutic potentials of selected conventional and/or novel antiplatelet agents remain to be evaluated in patients with IgG4-RD. Transcriptomics and/or proteomics research with platelets should take into account the relatively low amounts of platelet mRNA, miRNA, and protein. Secondary analysis of omics data sets has great potential to reveal new and valuable information. Full article

Systemic lupus erythematosus (SLE) is a complex autoimmune disorder characterized by widespread inflammation and autoantibody production. Its development and progression involve genetic, epigenetic, and environmental factors. Although genome-wide association studies (GWAS) have repeatedly identified a susceptibility signal at 16p13, its fine-scale source and its functional and mechanistic role in SLE remain unclear. We used bioinformatics to prioritize likely functional variants and validated the top candidate through various experimental techniques, including clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing in B cells. To assess the functional impact of the proposed causal variant in C-type lectin domain family 16, member A (CLEC16A), we compared autophagy levels between wild-type (WT) and knock-out (KO) cells. Systematic bioinformatics analysis identified the highly conserved non-coding intronic variant rs17673553, with the risk allele apparently affecting enhancer function and regulating several target genes, including CLEC16A itself. Luciferase reporter assays followed by chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR) validated this enhancer activity, demonstrating that the risk allele increases the binding of enhancer histone marks (H3K27ac and H3K4me1), the CTCF-binding factor, and key immune transcription factors (GATA3 and STAT3). Knock-down of GATA3 and STAT3 via siRNA led to a significant decrease in CLEC16A expression. These regulatory effects on the target gene were further confirmed using CRISPR-based genome editing and CRISPR-dCas9-based epigenetic activation/silencing. Functionally, WT cells exhibited higher levels of starvation-induced autophagy compared to KO cells, highlighting the role of CLEC16A and the rs17673553 locus in autophagy regulation. These findings suggest that the rs17673553 locus—particularly the risk allele—drives significant allele-specific chromatin modifications and binding of multiple transcription factors, thereby mechanistically regulating the expression of target autophagy-associated genes, including CLEC16A itself. This mechanism could potentially explain the association between rs17673553 and SLE, and could underlie the signal at 16p13. Full article

Membrane proteins, especially extracellular domains, are key therapeutic targets due to their role in cell communication and associations. Yet, their functions and interactions often remain unclear. This study presents a general method to discover interactions of membrane proteins with immune cells and subsequently to deorphanize their respective receptors. We developed a comprehensive recombinant protein library of extracellular domains of human transmembrane proteins and proteins found in the ER-Golgi-lysosomal systems. Using this library, we conducted a flow-cytometric screen that identified several cell surface binding events, including an interaction between carbonic anhydrase 9 (CAH9/CA9/CAIX) and CD14^high cells. Further analysis revealed this interaction was indirect and mediated via platelets bound to the monocytes. CA9, best known for its diverse roles in cancer, is a promising therapeutic target. We utilized our library to develop an AlphaLISA high-throughput screening assay, identifying CLEC2 as one robust CA9 binding partner. A five-amino-acid sequence (EDLPT) in CA9, identical to a CLEC2 binding domain in Podoplanin (PDPN), was found to be essential for this interaction. Like PDPN, CA9-induced CLEC2 signaling is mediated via Syk. A Hodgkin’s lymphoma cell line (HDLM-2) endogenously expressing CA9 can activate Syk-dependent CLEC2 signaling, providing enticing evidence for a novel function of CA9 in hematological cancers. In conclusion, we identified numerous interactions with monocytes and platelets and validated one, CA9, as an endogenous CLEC2 ligand. We provide a new list of other putative CA9 interaction partners and uncovered CA9-induced CLEC2 activation, providing new insights for CA9-based therapeutic strategies. Full article

Thyroid cancer (TC), due to its heterogeneous nature, remains a clinical challenge. Many factors can initiate the carcinogenesis process of various types of TC, which complicates diagnosis and treatment. The presented review gathers current information on specific types of TC, taking into account the effects of the COVID-19 pandemic. It is likely that COVID-19 has influenced and continues to influence the function of the thyroid gland. A high percentage of patients with COVID-19 showing simultaneous pathological changes in the thyroid suggests that SARS-CoV-2 may disrupt the function of this gland and initiate pro-oxidative mechanisms, inflammatory states, and autoimmune diseases, thereby promoting the formation of neoplastic changes. Furthermore, changes in the expression of the ACE2, TMPRSS2, CLEC4M and DPP4 genes, observed in TC, also occur in COVID-19. Therefore, it is probable that the interaction of SARS-CoV-2 with thyroid cell receptors may initiate carcinogenesis in this gland. Additionally, some drugs used in TC therapy (e.g., levothyroxine) may increase the affinity of SARS-CoV-2 for cells, which could contribute to a more severe course of COVID-19 and the emergence of long-term symptoms (post-COVID-19). Moreover, the consequences of sanitary restrictions (limited access to medical services, reduction in endocrinological and oncological procedures) that took place in many countries during the COVID-19 pandemic may lead in the future to an increased number of missed diagnoses and the emergence of aggressive cancers. Full article

Glioblastoma multiforme (GBM) is a malignant primary brain tumor categorized as a Grade 4 astrocytic glioma by the World Health Organization (WHO). Some of the established risk factors of GBM include inherited genetic syndromes, body mass index, alcohol consumption, use of non-steroidal anti-inflammatory drugs (NSAIDs), and therapeutic ionizing radiation. Vascular anomalies, including local and peripheral thrombosis, are common features of GBM. Podoplanin (PDPN), a ligand of the C-type lectin receptor (CLEC-2), promotes platelet activation, aggregation, venous thromboembolism (VTE), lymphatic vessel formation, and tumor metastasis in GBM patients. It is regulated by Prox1 and is expressed in developing and adult mammalian brains. It was initially identified on lymphatic endothelial cells (LECs) as the E11 antigen and on fibroblastic reticular cells (FRCs) of lymphoid organs and thymic epithelial cells as gp38. In recent research studies, its expression has been linked with prognosis in GBM. PDPN-expressing cancer cells are highly pernicious, with a mutant aptitude to form stem cells. Such cells, on colocalization to the surrounding tissues, transition from epithelial to mesenchymal cells, contributing to the malignant carcinogenesis of GBM. PDPN can be used as an independent prognostic factor in GBM, and this review provides strong preclinical and clinical evidence supporting these claims. Full article

Cultivated land ecological compensation (CLEC) is an important way to solve regional development imbalance and cultivated land problems, and the scientific quantification of the ecological value of cultivated land is the key to CLEC. This study quantified the total amount and urgency of CLEC in China’s main grain-producing region using the cropland ecological footprint (EF) and ecosystem service value (ESV) methods. Furthermore, this study analyzed the comprehensive zoning of CLEC considering natural and economic development. The results showed that the spatial distribution of EFs and the ecological carrying capacity of cultivated land in Henan Province are similar, presenting the spatial characteristics of being high in the southeast and low in the northwest; the cultivated land in most of the counties and districts is in a state of ecological surplus, and the cultivated land resources are sufficient to support their own consumption needs. Henan Province as a whole is an ecologically compensated region, with a compensation amount of CNY 1.39 billion, and the total amount of compensation is in a positive value of 94.94%. The Southwest Yu and North Yu economic zone of Henan are the areas of high and low values of cultivated land compensation. The priority compensation region is the most extensive and widely distributed type in the five regions of Henan Province, accounting for 55% of the counties and districts. The degree of compensation is most urgent in the Huanghuai, Southwest Yu, and North Yu economic zones. This study’s findings provide new ideas for the development of differentiated ecological compensation policies, and provide references for the participation of multiple market participants and the diversification of compensation forms. Full article