Search Results (103)

This study explores the use of machine learning to predict high-cycle fatigue (HCF) behavior and fatigue crack growth rate (FCGR) in Co-Cr-Mo alloys manufactured through laser powder bed fusion. Two machine learning (ML) models: extreme gradient boosting (XGB) and deep neural networks (DNN), are implemented to estimate HCF and FCGR across three distinct scanning strategies. The raw datasets for HCF and FCGR are taken from previously performed experiments. The HCF dataset is augmented using a Gaussian Mixture Model, while the FCGR dataset is used in its raw form. Following hyperparameter optimization, both models exhibited quite similar accuracy on validation datasets. Their performance is assessed during testing using mean squared error (MSE) and R² scores. The DNN model demonstrated higher accuracy in HCF predictions by achieving higher R² scores. The DNN performs better because it can handle more complex patterns effectively due to its multiple neurons and deeper multilayer architecture. In contrast, the XGB model performed better in FCGR predictions and yielded higher R² scores compared to XGB. The good agreement with the experimental dataset shows that these two ML techniques are effective in predicting HCF and FCGR behavior. Full article

It has been demonstrated that infants and young children exhibit immune tolerance as a consequence of immature immune systems, which are characterized by a natural Th2 bias. RSV infection has been reported to result in acute lower respiratory infection (ALRI), while formalin-inactivated vaccination has been observed to exacerbate Th2 responses, consequently leading to enhanced respiratory disease (ERD). Transcriptomic data from three independent cohorts of RSV-infected infants were analyzed (GSE246622 served as the discovery and train set; GSE105450 and GSE188427 were used as validation sets). Immune infiltration analysis revealed immunological characteristics, which were then used to perform unsupervised clustering using feature-related genes. WGCNA was used to identify co-expressed gene modules, while Mfuzz and TCseq were employed to analyze temporal expression patterns. Machine learning models were developed using a refined panel of candidate genes. Severe symptoms of RSV infection exhibited a strong correlation with age, with younger infants demonstrating more intense inflammatory responses from neutrophils, macrophages, mast cells and dendritic cells. A predictive model was constructed using ten co-expressed genes: The following genes were identified: MCEMP1, FCGR1B, ANXA3, FAM20A, CYSTM1, GYG1, ARG1, SLPI, BMX and SMPDL3A. It was observed that infants of a younger demographic demonstrated a heightened degree of immunosuppression and pronounced innate immune activation in patients of severe symptoms with RSV infection. However, eosinophils exhibited minimal involvement in these processes. These gene models pertaining to the neutrophil, macrophage or mast cell was found to be a relatively effective predictor in patients of severe symptoms. Full article

Background: Regulatory T cells (FOXP3⁺), checkpoint signaling (PD-1), and inhibitory B-cell signaling (CD32B/FCGR2B) may shape recurrence risk after resection of lung adenocarcinoma, but small, stage-heterogeneous cohorts complicate inference. Methods: We profiled 21 resected lung adenocarcinomas by immunohistochemistry (IHC) for CD3, CD8, FOXP3, PD-1, CD19, and CD32B. Five systematically sampled 200× fields per stain were quantified in ImageJ to derive continuous percentages and prespecified ratios: FOXP3/CD8 and CD32B/CD19 (primary), and PD-1/CD8 (exploratory). Analyses emphasized effect sizes with exact non-parametric tests for clinicopathologic associations and Cox time-to-event models for disease-free survival (DFS). Kaplan–Meier plots used median splits for visualization only. Results: Higher immunosuppressive balance associated with adverse features and shorter DFS. Patients with higher FOXP3/CD8 and CD32B/CD19 had markedly shorter DFS on K-M displays (FOXP3/CD8: 18.9 vs. 45.6 months; CD32B/CD19: 25.0 vs. 72.8 months). In Cox models, each ratio was associated with increased hazard of recurrence (FOXP3+PD-1/CD8, HR 2.03, 95% CI 1.26–3.29; CD32B/CD19, HR 1.98, 95% CI 1.16–3.37). Conclusions: In this hypothesis-generating pilot, an immunosuppressive tumor microenvironment, indexed by higher FOXP3 (relative to CD8) and higher CD32B (relative to CD19), portends earlier recurrence after surgery. These results support external validation in larger, stage-balanced cohorts and motivate incorporation of quantitative IHC ratios into postoperative risk stratification. Full article

Therapeutic strategies targeting “tumor-educated platelets” (TEPs) and platelet–tumor interactions by key signaling pathways (ITAM, P2Y12) may reduce metastasis and cancer. Using a TEP gene expression dataset originally created to study swarm intelligence-enhanced detection of lung cancer cells (GSE89843), we did perform extensive transcriptome analysis to integrate these data with directed protein–protein interactions and build a TEP-specific signaling network. We analyze network topology and controllability and identify critical and indispensable nodes, as well as high-weight, usually high-score nodes. We reconstruct (pharmacological) controllable subnetworks of TEP signaling, which we then explore for drugs targets. We found 111 upregulated and 108 downregulated genes compared to control platelets, enriched in pathways related to extracellular matrix interactions, cytoskeleton organization, immune signaling, and platelet activation. Ribosomal function, apoptosis, and immune signaling were among the downregulated processes, highlighting unique TEP profiles in non-small-cell lung cancer (NSCLC). Our integrative analysis of TEPs in NSCLC reveals key transcriptional and network-based alterations harmful for the cancer patient. Using four complementary strategies, we identified five high-confidence genes (Gene symbols always given throughout the paper), ITGA2B, FLNA, GRB2, FCGR2A, and APP, as central to TEP signaling. These can be targeted by FDA-approved drugs. Fostamatinib, an SYK inhibitor, emerged as the top candidate drug to disrupt ITAM-mediated platelet activation selectively; metastasis-promoting metalloprotease and cytoskeletal targets influencing adhesion were also identified. A low-dose combination therapy of fostamatinib, Aducanumab, and acetylsalicylic acid (aspirin) may control TEP effects. In conclusion, our preclinical in silico approach revealed FDA-approved drugs that allow therapeutic targeting of metastasis-promoting TEPs and target NSCLC at the same time. Full article

Background: Celiac disease (CD) is a gluten-sensitive immune-related enteropathy of the small intestine characterized by villus atrophy, crypt hyperplasia, and increased intraepithelial lymphocytes (IELs). Objectives: To characterize the phenotype of IELs and immune cells of the lamina propria of small intestine control using immuno-oncology and immune-phenotype markers and test the most relevant marker, an immune checkpoint co-inhibitory receptor, leukocyte-associated immunoglobulin-like receptor 1 (LAIR1), in CD. Methods: Immunohistochemical analysis of CD3 (CD3E), CD4, CD8, CD103 (ITGAE), Granzyme B (GZMB), TCR beta (β), TCR delta (δ), CD56 (NCAM), CD16 (FCGR3A), LAIR1 (CD305), PD-L1 (CD274), PD1 (CD279), BTLA (CD272), TOX2, HVEM (TNFRSF14), CD163, HLA-DP-DQ-DR, IL4I1, and FOXP3 was performed using histological analysis. Gene expression analysis was performed using an independent dataset to expand and confirm the findings. Results: IELs exhibited a cytotoxic T-cell phenotype and were CD3+, CD8+, CD103+, TCR beta+, and LAIR1+. The lamina propria (LP) was abundant in CD163+, HLA-DP-DQ-DR+, BTLA+, PD-L1+, CD103+, CD56+, and LAIR1+ cells corresponding to macrophages and T- and B-lymphocytes. In CD, IELs and part of the inflammatory cells of the lamina propria cells were LAIR1+. CD was characterized by higher quantity of LAIR1+ IELs and LP immune cells than the small intestine control (p = 0.004). Higher intestinal lesions evaluated by Marsh scoring were correlated with higher LAIR1 (p < 0.001). Gene expression analysis confirmed the overexpression of the LAIR1 pathway in CD and highlighted BTLA. At the protein level, BTLA overexpression was confirmed in CD. Finally, as a proof-of-concept AI analysis, a convolutional neural network classified LAIR1-stained image patches between the three diagnoses of small intestine control, CD, and reactive tonsils with high accuracy (99.6%). Conclusions: IELs exhibit a cytotoxic T-cell phenotype and were found to be CD3+, CD8+, CD103+, TCR beta+, and LAIR1+ in the small intestine control. Increased numbers of LAIR1+ IELs and lamina propria immune cells characterize CD. Full article

Emerging evidence highlights the critical role of phagocytosis-related genes in CRC progression, underscoring the need for novel phagocytosis-based prognostic models to predict clinical outcomes. In this study, a four-gene (SPHK1, VSIG4, FCGR2B and FPR2) signature associated with CRC prognosis was developed using single-sample gene set enrichment analysis (ssGSEA), least absolute shrinkage and selection operator (LASSO) regression, and univariate Cox analysis. Pathway enrichment analysis was conducted on the prognostic genes, along with evaluations of the tumor microenvironment and sensitivity to immunotherapy and chemotherapy across the high- and low-risk groups. Prognostic gene validation was performed via quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) using CRC cDNA and tissue microarrays. High-risk patients showed enhanced responsiveness to immunotherapy, while chemotherapy sensitivity varied across risk subgroups. qRT-PCR results revealed upregulation of SPHK1 and FPR2 in cancer tissues, whereas FCGR2B and VSIG4 were downregulated. IHC assays confirmed increased SPHK1 and FPR2 expression in cancer samples. Single-cell RNA sequencing analysis demonstrated a decrease in SPHK1 and FCGR2B, while VSIG4 and FPR2 progressively increased during macrophage differentiation. These findings provide a potential framework for targeted therapy. Full article

Natural killer (NK) cells are promising candidates for adoptive immunotherapy, but their clinical application requires standardized expansion protocols that yield functional cells in sufficient numbers. This study examined how initial seeding density and donor-intrinsic variability affect NK cell proliferation and receptor phenotype during in vitro expansion in a G-Rex^® 24-well plate under IL-2 stimulation. NK cells from healthy donors were analyzed longitudinally by flow cytometry, and targeted SNP sequencing of selected receptor genes (IL2RA, IL2RB, FCGR3A, NCR1, KLRK1, and ICAM-1) was performed to assess potential genetic contributions. A seeding density of 2.0 × 10⁶ cells/cm² promoted high expansion rates and favorable expression of activating receptors including CD16a, NKp46, and NKG2D. Nonetheless, marked inter-donor differences were observed. Some donors exhibited impaired proliferation and aberrant receptor expression, possibly associated with high-priority SNPs and distinct haplotype structures. Others showed robust proliferation despite the absence of identifiable genetic drivers, suggesting the involvement of variants in other genes or non-genetic mechanisms such as epigenetic priming or adaptive NK-cell differentiation. These results highlight the influence of both culture conditions and donor-intrinsic factors on NK-cell expansion outcomes. Integrating phenotypic and genetic analyses may improve the reproducibility and personalization of NK-cell-based manufacturing protocols for therapeutic use. Full article

Fc gamma receptors (FcγRs) control humoral and cellular immune responses and maintain the immune system balance. Functional polymorphisms of FcγRs, whose prevalence was dependent on ethnic origin, were found to be associated with systemic lupus erythematosus (SLE) or kidney injuries in several ethnic groups. We aimed at investigating the association between the functional single-nucleotide polymorphisms (SNPs) of FcγRIIa-H131R (rs1801274), FcγRIIb-I232T (rs1050501), FcγRIIIa-V158F (rs396991) and FcγRIIIb variants (NA1 and NA2) and lupus erythematosus systemic in an indigenous African Caribbean population. We compared the frequencies of the functional SNPs of FCGR2A (FcγRIIa-H131R, rs1801274), FCGR2B (FcγRIIb-I232T, rs1050501), FCGR3A (FcγRIIIa-V158F, rs396991) and FCGR3B variants (FcγRIIIb NA1 and NA2) between lupus and healthy controls in an indigenous African Caribbean population. We highlighted an association between the FCGR3B-NA1/NA1 and FCGR3A-158F alleles and systemic lupus erythematosus, in addition to an association between FCGR2A-131R and lupus nephritis. Furthermore, an increase in the 131R-158V haplotype in lupus nephritis (30.4%) vs. lupus non-nephritis (15.8%) was noticed. Surprisingly, in spite of the high frequency of the FCGR2B-232T allele in our population, our study did not highlight any association of this allele either with SLE or lupus nephritis (a severe and frequent form of SLE). CD72-Hap1, which has been shown to confer resistance to SLE against T232 allele, was not enhanced in the control group. Our results emphasize an association between FCGR2A-131R and lupus nephritis with a distinctive FCGR polymorphism distribution in an indigenous African Caribbean population, confirming the important variation in the FCGR locus depending on ethnic origin. Full article

In Arctic regions, ship structures face low temperatures, overloads, thickness effects, and fluctuating stress ratios, which significantly influence the fatigue crack growth (FCG) behavior of marine steels. This study investigates the FCG behaviors of DH36 steel by a series of experiments under the combined effects of low temperatures, overload ratios R_ol, specimen thickness B, and stress ratios R. Experiment results show that the yield strength, ultimate tensile strength, and elastic modulus of DH36 steel exhibit negative correlations with temperature varying within the Arctic temperature range. A reduction in fatigue crack growth rate (FCGR) is observed under the combined effects of low temperature and overload, and the magnitude of decrease shows a positive correlation with R_ol. Notably, low temperatures weaken the FCG retardation effect induced by overload, and this attenuation becomes more pronounced as temperature decreases. Under low temperatures, while maintaining constant peak load, increasing R significantly reduces both initial and terminal stress intensity factor ranges ΔK₀ and ΔK_e, resulting in diminished effective crack driving force and thereby substantially extending FCG life. Although increased B enhances FCGR at low temperatures, thinner plates demonstrate shorter FCG life due to their higher ΔK₀ values. Full article

Glioma is the most common primary malignant intracranial tumor with limited treatment options and a dismal prognosis. This study aimed to develop a robust gene expression-based prognostic signature for GBM using the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Using WGCNA and LASSO algorithms, we identified four MHC-related genes (TNFSF14, MXRA5, FCGR2B, and TNFRSF9) as prognostic biomarkers for glioma. A risk model based on these genes effectively stratified patients into high- and low-risk groups with distinct survival outcomes across TCGA and CGGA cohorts. This signature correlated with immune pathways and glioma progression mechanisms, showing strong associations with immune function and tumor microenvironment infiltration patterns. The risk score reflected tumor microenvironment remodeling, suggesting its prognostic relevance. We further propose I-BET-762 and Enzastaurin as potential therapeutic candidates for glioma. In conclusion, the four-gene signature we identified and the corresponding risk score model constructed from it provide valuable tools for the prognosis prediction of glioblastoma multiforme (GBM) and may guide personalized treatment strategies. The least absolute shrinkage and selection operator (LASSO) risk score has demonstrated significant prognostic evaluation utility in clinical GBM patients, bringing potential implications for patient stratification and the optimization of treatment regimens. Full article

The Institute of Plasma Physics Chinese Academy of Sciences (ASIPP) is currently engaged in the design of a compact fusion device with a fusion power gain (Q) exceeding one. Due to space limitation for the device, the conductor jacket of the central solenoid (CS) magnet experiences significant electromagnetic stress. Therefore, a higher strength stainless steel known as modified N50 (CHSN01) is utilized for manufacturing the jacket. To effectively heat the plasma, the CS magnet within the device requires operation with alternating current. It is crucial to monitor fatigue crack growth caused by stress cycles in the CS jacket and assess its severity in order to ensure the safety and reliability of the fusion device. In this study, a finite element method is applied to establish a functional relationship between the stress intensity factor range ∆K and the jacket defect depth a precisely based on actual cyclic loads experienced by CS magnet operation. Experimental investigations are conducted to determine fatigue crack growth rates (FCGRs) at 4.2 Kelvin (K) for the CHSN01 jacket. The maximum likelihood estimation method is employed to calculate the probability equations of FCGRs with a random variable description. Consequently, it is possible to determine the maximum allowable initial defect size for a jacket to withstand 60,000 plasma pulses, which will serve as an input parameter for non-destructive testing of jackets. Full article

Background: Spinal cord injury (SCI) remains a profound medical challenge, with limited therapeutic options available. Studies focusing on individual molecular markers have limitations in addressing the complex disease process. Methods: This study utilizes RNA-sequencing (RNA-seq) to investigate the differentially expressed genes (DEGs) in spinal cord tissue from a rat SCI model at 1 and 21 days post-injury (dpi). After data processing and analysis, a series of biological pathway enrichment analyses were performed using online tools DAVID and GSEA. Interactions among the enriched genes were studied using Cytoscape software to visualize protein–protein interaction networks. Results: Our analysis identified 595 DEGs, with 399 genes significantly upregulated and 196 significantly downregulated at both time points. CD68 was the most upregulated gene at 21 dpi, with a significant fold change at 1 dpi. Conversely, MPZ was the most downregulated gene. Key immune response processes, including tumor necrosis factor (TNF) production, phagocytosis, and complement cascades, as well as systemic lupus erythematosus (SLE)-associated pathways, were enriched in the upregulated group. The enriched pathways in the downregulated group were related to the myelin sheath and neuronal synapse. Genes of interest from the most significantly downregulated DEGs were SCD, DHCR24, PRX, HHIP, and ZDHHC22. Upregulation of Fc-γ receptor genes, including FCGR2B and FCGR2A, points to potential autoimmune mechanisms. Conclusions: Our findings highlight complex immune and autoimmune responses that contribute to ongoing inflammation and tissue damage post-SCI, underscoring new avenues for therapeutic interventions targeting these molecular processes. Full article

Background: Oropouche virus (OROV), part of the Peribunyaviridae family, is an emerging pathogen causing Oropouche fever, a febrile illness endemic in South and Central America. Transmitted primarily through midge bites (Culicoides paraensis), OROV has no specific antiviral treatment or vaccine. This study aims to identify host-targeted therapeutics against OROV using computational approaches, offering a potential strategy for sustainable antiviral drug discovery. Methods: Virus-associated host targets were identified using the OMIM and GeneCards databases. The Enrichr and DSigDB platforms were used for drug prediction, filtering compounds based on Lipinski’s rule for drug likeness. A protein–protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape 3.10.3 software. Four key host targets—IL10, FASLG, PTPRC, and FCGR3A—were prioritized based on their roles in immune modulation and OROV pathogenesis. Molecular docking simulations were performed using the PyRx software to evaluate the binding affinities of selected small-molecule inhibitors—Acetohexamide, Deptropine, Methotrexate, Retinoic Acid, and 3-Azido-3-deoxythymidine—against the identified targets. Results: The PPI network analysis highlighted immune-mediated pathways such as Fc-gamma receptor signaling, cytokine control, and T-cell receptor signaling as critical intervention points. Molecular docking revealed strong binding affinities between the selected compounds and the prioritized targets, suggesting their potential efficacy as host-targeting antiviral candidates. Acetohexamide and Deptropine showed strong binding to multiple targets, indicating broad-spectrum antiviral potential. Further in vitro and in vivo validations are needed to confirm these findings and translate them into clinically relevant treatments. Conclusions: This study highlights the potential of using computational approaches to identify host-targeted therapeutics for Oropouche virus (OROV). By targeting key host proteins involved in immune modulation—IL10, FASLG, PTPRC, and FCGR3A—the selected compounds, Acetohexamide and Deptropine, demonstrate strong binding affinities, suggesting their potential as broad-spectrum antiviral candidates. Further experimental validation is needed to confirm their efficacy and potential for clinical application, offering a promising strategy for sustainable antiviral drug discovery. Full article

Adhesive joints in real-world conditions often experience variable or step loading rather than constant-amplitude fatigue. This study addresses this gap by examining the influence of load sequence and block loading on fatigue damage in adhesive joints of fiber-reinforced polymer (FRP) composites. A novel bilinear traction-separation law based on the Fatigue Crack Growth Rate (FCGR) rule is introduced to predict fatigue failure under step/variable loads, accounting for load history, sequence, and interaction effects. This model was validated using a double-lap joint model under step/variable loading across four experimental scenarios. The proposed model outperformed existing fatigue damage-accumulation models, significantly reducing the Relative Error of Prediction ($REP$). Notably, the proposed model significantly reduced the Relative Error of Prediction ($REP$), achieving reductions from 81.10% to as low as 0.013% in certain cases. The proposed bilinear law exhibited an accelerated damage accumulation rate per cycle for low-to-high loading situations and a decelerated rate for high-to-low loading scenarios, aligning more closely with experimental observations. The proposed model offers practical benefits by improving fatigue life predictions, enabling optimized FRP composite designs, and minimizing overengineering. These advancements are particularly relevant in industries such as aerospace, automotive, and wind energy, where structural durability and safety are paramount. This research represents a significant step forward in the fatigue analysis of composite adhesive joints, paving the way for more reliable engineering solutions. Full article

Receptors for the immunoglobulin G constant fraction (FcγRs) are widely expressed in cells of the immune system. Complement-independent phagocytosis prompted FcγR research to show that the engagement of IgG immune complexes with FcγRs triggers a variety of cell host immune responses, such as phagocytosis, antibody-dependent cell cytotoxicity, and NETosis, among others. However, variants of these receptors have been implicated in the development of and susceptibility to autoimmune diseases such as systemic lupus erythematosus. Currently, the knowledge of FcγR variants is a required field of antibody therapeutics, which includes the engineering of recombinant soluble human Fc gamma receptors, enhancing the inhibitory and blocking the activating FcγRs function, vaccines, and organ transplantation. Importantly, recent interest in FcγRs is the antibody-dependent enhancement (ADE), a mechanism by which the pathogenesis of certain viral infections is enhanced. ADEs may be responsible for the severity of the SARS-CoV-2 infection. Therefore, FcγRs have become a current research topic. Therefore, this review briefly describes some of the historical knowledge about the FcγR type I family in humans, including the structure, affinity, and mechanism of ligand binding, FcγRs in diseases such as systemic lupus erythematosus (SLE), and the potential therapeutic approaches related to these receptors in SLE. Full article