Experimental Biology and Medicine最新文献

N6-methyladenosine (m6A) RNA methylation regulators have been implicated in colorectal cancer (CRC) progression. However, systematic evaluation using multiple machine learning approaches for prognostic prediction remains limited. This study aimed to develop and validate machine learning models for CRC prognosis based on m6A regulators and assess their potential for immunotherapy response prediction. We analyzed 1,047 CRC patients from TCGA and GEO databases (70% training, 30% validation). Twenty machine learning algorithms were systematically evaluated, with LASSO regression selecting optimal features from 27 m6A regulators. SHAP analysis provided model interpretability. Immune microenvironment characterization and immunotherapy response prediction were performed using established computational methods. LASSO regression selected eight m6A regulators (IGF2BP2, METTL3, HNRNPA2B1, METTL14, YTHDF2, VIRMA, FTO, ALKBH5) for model construction. Among 20 algorithms tested, Random Forest achieved optimal performance (training AUC = 0.895, validation AUC = 0.847). SHAP analysis identified IGF2BP2 (mean |SHAP| = 0.42) and METTL3 (mean |SHAP| = 0.36) as primary contributors to risk prediction. Risk stratification showed significant survival differences (HR = 2.41, 95% CI: 1.73-3.36, p < 0.001). Low-risk patients demonstrated enhanced immune infiltration with higher CD8⁺ T cells (17.8% vs. 10.2%, p < 0.001) and better predicted immunotherapy response rates (36.5% vs. 20.3%, p = 0.006). Our systematic machine learning analysis demonstrates that m6A regulators can effectively predict CRC prognosis and immunotherapy response. The eight-gene signature provides a practical tool for clinical risk assessment and treatment decision-making.

Even with the development of the Pfizer-BioNTech BNT162b2 vaccine, which provides protection against COVID-19 and demonstrates high efficacy in generating immune responses, the complexities of the dynamics linking pro- and anti-inflammatory cytokine profiles with anti-spike IgG production remain unclear. The study aims to elucidate these immune dynamics after vaccination. This prospective cohort research was done at the University of Diyala from January 2022 to January 2023, evaluating the immunological response to the Pfizer-BNT162b2 mRNA vaccine in 180 healthy students. Pro- and anti-inflammatory cytokines and anti-spike IgG antibodies were measured before vaccination, 1 month after the second dose, and 4 months after the second dose. Biomarkers were analyzed via ELISA and CRP assays. The study involved 180 healthy participants (80 males, 100 females; median age, 21 years; BMI, 25.7 kg/m²). After the first Pfizer-BNT162b2 vaccine dose, the level of anti-spike IgG increased by 330-fold, and the levels of pro- and anti-inflammatory markers, such as IL-1β, IL-10, and CRP, increased significantly. Four months after the second dose, anti-spike IgG levels were 136-fold above baseline. Significant correlations emerged between cytokine and IgG levels, with anti-spike IgG/IL-10 ratios elevated and sustained over the long term. Pfizer-BNT162b2 vaccine elicits a significant immune response associated with changes in pro-inflammatory cytokines, and the interaction between these cytokines and anti-spike IgG suggests a potential role for immune regulation in enhancing humoral immunity. Based on these findings, the IgG/IL-17 ratio may serve as a viable exploratory biomarker for assessing short- and medium-term vaccination efficacy.

Although multiple studies have confirmed the importance of chronic low-grade inflammation in the development of osteoarthritis (OA), the association between complete blood count (CBC)-derived inflammatory indicators and osteoarthritis prevalence remains unclear. The present study aims to explore the association between CBC-derived inflammatory indicators and OA prevalence. We used NHANES data from 2007 to 2020 for a cross-sectional analysis. Multivariate logistic regression models were used to evaluate the association between CBC-derived inflammatory indicators and OA prevalence. Restricted cubic spline function (RCS) and threshold analysis were used to assess potential nonlinear associations. In addition, subgroup and sensitivity analyses were performed to assess the stability of the results. Finally, we used LASSO regression to identify the variables most associated with OA outcomes to construct a prediction model, and the model's validity was verified. Among the 24,112 patients in this study, 3,195 were diagnosed with OA. In the adjusted model, multivariate logistic regression analysis showed that 5 inflammatory indicators (SII, SIRI, MLR, NMLR, NLR) were positively associated with OA prevalence. RCS and threshold analysis showed nonlinear associations between (SII, NMLR, NLR) and OA prevalence. After variable screening, we established an OA risk prediction model with an area under the curve (AUC) of 0.735 (95% CI: 0.726-0.744). Both the decision and calibration curve showed that the model had good clinical significance. The Present study suggests that CBC-derived inflammatory indicators are statistically associated with OA prevalence. Furthermore, MLR and NMLR could be valuable predictors of OA and offer novel perspectives on its assessment and treatment.

Keratoconus is a corneal ectasia whose pathophysiological mechanisms, including biomolecular alterations and genetic influences, remain poorly understood. Recent studies have shown altered cytokine levels, increased proteinase activity, and other potential mediators in the tear film and corneal tissue, highlighting a possible involvement of inflammatory pathways in the pathophysiology of keratoconus. This observational study aims to characterize the tear proteome of keratoconus patients and compare it to a control group, reporting potential disease biomarkers in the tear film. 23 keratoconus patients were selected at the Cornea and External Diseases Outpatient Clinic of the Clinics Hospital of UNICAMP. The control group consisted of 17 age- and sex-matched participants. All study subjects underwent corneal tomography (Pentacam). Tear film samples were collected and sent for proteomic evaluation by mass spectrometry at the National Biosciences Laboratory (LNBio). After quantification, univariate and multivariate statistical analyses were performed. A total of 353 proteins were identified and quantified, of which 25 showed statistical differences in the univariate analysis (t-test), and 19 were selected in the multivariate analysis (PLS-DA). There was an overlap of 7 proteins identified in both uni- and multivariate analyses: chitinase-3-like protein 2, prosaposin, zymogen granule protein 16 homolog B, procollagen-lysine,2-oxoglutarate 5-dioxygenase 1, secretoglobin family 1D member 1, albumin, and Ig kappa chain V-I region. Thirty-seven proteins showed statistically significant variation between the keratoconus and control groups. Proteomic analysis revealed differentially expressed proteins in the tear film of keratoconus patients. We report the identified proteomic profile, which includes potential biomarkers that may help elucidate the disease's pathophysiology.

Abdominal aortic aneurysm (AAA) is a life-threatening condition with no effective pharmacological treatments, underscoring the critical need to identify novel therapeutic targets. Emerging translational and clinical evidence implicates neutrophil extracellular traps (NETs) as potential drivers of AAA pathogenesis. This review systematically delineates the mechanisms by which NETs contribute to aortic wall degradation, focusing on their direct cytotoxicity to vascular smooth muscle cells (VSMCs), induction of VSMC phenotypic switching and ferroptosis, amplification of inflammatory cascades, and propagation of thromboinflammation. Key mediators include PAD4, IL-1β, PI3Kγ, neutrophil elastase, myeloperoxidase, and mitochondrial DNA. NET components (citrullinated histone H3, cell-free DNA, neutrophil elastase) serve as promising diagnostic and prognostic biomarkers. Preclinical studies highlight the efficacy of NET-targeting strategies, including inhibiting NET formation, degrading existing NETs, neutralizing cytotoxic components, and modulating downstream pathways (e.g., with ferroptosis inhibitors). Nanotechnology platforms enhance site-specific delivery of these agents. By integrating the research background with its practical implications, we conclude that targeting NETs represents a promising paradigm shift. Despite translational challenges, this approach offers a rational framework for developing the first pharmacotherapies aimed at stabilizing AAA and addressing a major unmet clinical need.

Acute lung injury (ALI) is a disease with an excessive inflammatory response triggered by activating the NF-κB signaling pathway. Our study aims to investigate the role of the long non-coding RNA HOTAIR in ALI-associated hyperinflammation, providing evidence for HOTAIR as a potential therapeutic target for ALI. Here, we examined the contribution of HOTAIR to LPS-induced lung injury using both A549 cell and murine models. LPS stimulation markedly increased HOTAIR expression in A549 cells, accompanied by reduced cell viability and elevated secretion of pro-inflammatory cytokines, including IL-1β, IL-6, and TNF-α. Overexpression of HOTAIR further amplified NF-κB signaling, as indicated by increased phosphorylation of IκBα and p65 and enhanced nuclear translocation of p65, whereas silencing HOTAIR effectively reversed these effects. In vivo, knockdown of HOTAIR significantly mitigated LPS-induced lung injury, reduced inflammatory cytokine production, and suppressed NF-κB activation in mice. Our findings reveal the contribution of HOTAIR to NF-κB-driven inflammatory injury in ALI, offering insight into its regulatory role and informing future exploration of targeted therapeutic approaches.

Natural killer (NK) cells represent a fundamental component of the innate immune system, endowed with the ability to identify and eradicate virus-infected and malignant cells. The advent of chimeric antigen receptor (CAR) technology has introduced innovative strategies for augmenting the antitumor potential of natural killer (NK) cells. Chimeric antigen receptor natural killer (CAR-NK) cells exert dual cytotoxic effects against tumor cells through CAR-mediated antigen-specific recognition in concert with the nonspecific cytolytic activity mediated by intrinsic NK receptors. This review critically evaluates the clinical progression of CAR-NK cells specifically against solid tumors, focusing on mechanisms to overcome the immunosuppressive tumor microenvironment (TME), the complexity of allogeneic manufacturing, and the latest engineering strategies for enhanced homing and persistence. Specifically, we emphasize the urgent need for robust Phase II/III clinical data and standardized Good Manufacturing Practice (GMP) protocols to realize the full potential of off-the-shelf allogeneic CAR-NK therapies. Additionally, we examine technological advancements and emerging directions addressing persistent challenges in this domain to offer theoretical underpinnings and research perspectives for the clinical deployment of CAR-NK cell therapy in solid tumor management.

Oxidative stress is a critical factor in the development of cardiometabolic diseases. The Oxidative Balance Score (OBS), integrating dietary and lifestyle factors, has been proposed as a measure of the balance between pro-oxidants and antioxidants. This study aims to explore the relationship between OBS and prevalent cardiometabolic multimorbidity (CMM), and to evaluate whether adding OBS into clinical practice is associated with better CMM identification in the general population. A total of 26,191 participants were selected from the National Health and Nutrition Examination Survey. CMM was defined as having a history of two or more conditions: diabetes mellitus, stroke, or coronary heart disease. The prevalence of CMM was 2.95%. After adjusting for demographic, anthropometric, laboratory, and medical history data, each standard deviation increase in OBS was associated with a 26.1% reduction in the risk of prevalent CMM. Participants in the highest quartile of OBS had a 0.530-fold risk of prevalent CMM compared to those in the lowest quartile. Smooth curve fitting indicated a proportional reduction in CMM risk with increasing OBS. Sensitivity analysis confirmed significant associations between both dietary and lifestyle OBS with prevalent CMM. ROC analysis revealed that incorporating OBS into conventional cardiometabolic risk factors was associated with a slight improvement in CMM identification (AUC: 0.912 vs. 0.916, P = 0.001). Reclassification analysis further indicated the incremental value of OBS. This study revealed a negative, linear, and robust association between OBS and prevalent CMM in the general population. However, reverse causation cannot be ruled out. Future studies should use longitudinal or Mendelian randomization approaches to establish causality.

Messenger RNA (mRNA) therapeutics have significantly transformed contemporary medicine, particularly through their role as the active component in the SARS-CoV-2 vaccine. This remarkable achievement is the culmination of extensive research conducted over many years by scientists. The widespread administration of the COVID-19 vaccine has further accelerated research into the precise therapeutic potential of mRNA technologies. Since mRNA doesn't integrate with the host genome, the safety and versatility of mRNA-based therapeutics make them an iconic candidate in targeted therapies. Due to a surge in innovation efforts, biomodification of the molecular signatures of mRNAs like the 5'cap, untranslated regions (UTRs), and the poly(A) tail are being developed to increase translation efficacy. Recent advancements in chemical modifications, codon optimization techniques, and targeted delivery methods have significantly enhanced the stability of synthetic mRNAs while concurrently reducing their immunogenicity. Various mRNA manufacturing and synthesizing methods are investigated in this review, focusing on their scalability and limitations. mRNA therapeutic strategies can be divided into protein replacement, immune modulation, and cellular modulation. This review explores mRNA's molecular landscape and comprehensive utility, including applications in both clinical trials and commercial sectors.

Berberine, known as an antioxidant agent, can improve glycemic indices in animal models of diabetes; however, it is clinically limited by poor bioavailability. Nanoparticles show the desirable capacity as delivery platforms for improving the bioavailability of medicinal agents. Here, we aimed to enhance the bioavailability and therapeutic impacts of berberine in streptozotocin (STZ)-induced gestational diabetes mellitus (GDM) rats by its encapsulation into the chitosan-coated solid lipid nanoparticles (SLNs) formulation. Berberine-loaded chitosan/SLN nanoparticles were formulated by the solvent-injection approach followed by a homogenization operation. The particle size, surface charge, and polydispersity index, as well as encapsulation efficiency percent (EE%), in vitro stability and berberine release, and in vivo pharmacokinetics were studied. Glycemic indices, such as fasting glucose and insulin, oral glucose tolerance, insulin tolerance, and homeostasis model of insulin resistance (HOMA-IR) scores, as well as the activity level of liver antioxidant and pro-oxidant enzymes, were evaluated in STZ-induced GDM rats. The particle size of berberine-loaded chitosan/SLN formulation was detected in the nano-range with high stability and high EE% as well as a sustained-release profile. Berberine nanoparticle treatment could provide a significantly higher oral bioavailability of berberine in experimental rats. Berberine nanoparticles remarkably reversed the altered glycemic indices, body weight, and pro-oxidant/antioxidant balance in STZ-induced GDM rats, with significantly higher effects than free berberine. In conclusion, chitosan-coated SLN nanoparticles firmly enhanced the therapeutic impacts of berberine on STZ-induced GDM, suggesting chitosan-coated SLN nanoparticles as an efficient oral delivery system for enhancing the bioavailability of berberine and, thus, improving its pharmacological impacts.