Abnormal inflammatory mediator concentrations during SARS-CoV-2 infection may represent disease severity. We aimed to assess plasma inflammatory mediator concentrations in patients with SARS-CoV-2 in Addis Ababa, Ethiopia. In this study, 260 adults: 126 hospitalized patients with confirmed COVID-19 sorted into severity groups: severe (n=68) and mild or moderate (n=58), and 134 healthy controls were enrolled. We quantified 39 plasma inflammatory mediators using multiplex ELISA. Spearman rank correlation and Mann-Whitney U test were used to identify mechanistically coupled inflammatory mediators and compare disease severity. Compared to healthy controls, patients with COVID-19 had significantly higher levels of interleukins 1α, 2, 6, 7, 8, 10 and 15, C-reactive protein (CRP), serum amyloid A (SAA), intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion protein 1 (VCAM-1), IFN-γ-inducible protein-10 (IP-10, CXCL10), macrophage inflammatory protein-1 alpha (MIP-1α, CCL3), eotaxin-3 (CCL26), interferon-gamma (IFN-γ), tumor necrosis factor-α (TNF-α), basic fibroblast growth factor (bFGF), placental growth factor (PlGF), and fms-like tyrosine kinase 1 (Flt-1). Patients with severe COVID-19 had higher IL-10 and lower macrophage-derived chemokine (MDC, CCL22) compared to the mild or moderate group (P<0.05). In the receiver operating characteristic curve, SAA, IL-6 and CRP showed strong sensitivity and specificity in predicting the severity and prognosis of COVID-19. Greater age and higher CRP had a significant association with disease severity (P<0.05). Our findings reveal that CRP, SAA, VCAM-1, CXCL10, CCL22 and IL-10 levels are promising biomarkers for COVID-19 disease severity, suggesting that plasma inflammatory mediators could be used as warning indicators of COVID-19 severity, aid in COVID-19 prognosis and treatment.

In hospitalized COVID-19, neutrophil-to-lymphocyte ratio (NLR) and serum creatinine is sometimes measured under assumption they predict disease severity and mortality. We determined the potential value of NLR and serum creatinine as predictors of disease severity and mortality in COVID-19. Prospective cohort study of COVID-19 patients admitted to premier COVID-19 treatment hospitals in Ethiopia. Predictive capability of biomarkers in progression and prognosis of COVID-19 was analyzed using receiver operating characteristics. Survival of COVID-19 patients with different biomarker levels was computed. Logistic regression assessed associations between disease severity and mortality on NLR and serum creatinine adjusted for odds ratio (AOR). The study enrolled 126 adults with severe (n = 68) or mild/moderate (n = 58) COVID-19, with median age 50 [interquartile range (IQR 20–86)]; 57.1% males. The NLR value was significantly higher in severe cases [6.68 (IQR 3.03–12.21)] compared to the mild/moderate [3.23 (IQR 2.09–5.39)], with the NLR value markedly associated with disease severity (p<0.001). Mortality was higher in severe cases [13 (19.1%)] compared to mild/moderate cases [2 (3.4%)] (p = 0.007). The NLR value was significantly higher in non-survivors [15.17 (IQR 5.13–22.5)] compared to survivors [4.26 (IQR 2.40–7.90)] (p = 0.002). Serum creatinine was significantly elevated in severe cases [34 (50%)] compared with mild/moderate [11 (19%)] (p<0.001). Disease severity [AOR 6.58, 95%CI (1.29–33.56), p = 0.023] and NLR [AOR 1.07, 95%CI (1.02–1.12), p = 0.004)] might be associated with death. NLR had a sensitivity and specificity of 69.1% and 60.3% as predictor of disease severity (cut-off >4.08), and 86.7% and 55.9% as prognostic marker of mortality (cut-off >4.63). In COVID-19, NLR is a biomarker with only modest accuracy for predicting disease severity and mortality. Still, patients with NLR >4.63 are more likely to die. Monitoring of this biomarker at the earliest stage of the disease may predict outcome. Additionally, high creatinine seems related to disease severity and mortality.

The transfer of molecular cargo in exosomes plays a crucial role in cancer progression, influencing metabolic processes, angiogenesis, immune interactions, and invasive capabilities. This review synthesizes current evidence on how exosomes modulate tumor metabolism and drive drug resistance, and outlines therapeutic opportunities. We searched PubMed, Scopus, Web of Science, and Google Scholar for English-language studies using terms related to exosomes/extracellular vesicles, glycolysis, oxidative phosphorylation (OXPHOS), lipid metabolism, and drug resistance/chemoresistance, and integrated the literature qualitatively. Evidence indicates that exosomes reprogram tumor and stromal metabolism by delivering enzymes and non-coding RNAs that boost glycolysis and dampen OXPHOS, activate cancer-associated fibroblasts and extracellular matrix (ECM) remodeling, and modulate ferroptosis. They stimulate angiogenesis (e.g., via vascular endothelial growth factor (VEGF)/Wnt pathways) and promote immune escape through programmed death-ligand 1 (PD-L1), transforming growth factor beta (TGF-β), and macrophage reprogramming. Exosomal integrins and proteases contribute to epithelial–mesenchymal transition (EMT), organotropism, and pre-metastatic niche formation. Critically, exosomes propagate chemoresistance by exporting drugs and spreading determinants—including P-gp/BCRP/MRP-1, anti-apoptotic proteins, and regulatory RNAs—to previously sensitive cells; adipose-derived vesicles and lipid cargos further reinforce metabolic plasticity and therapy resistance. Given their stability, nanoscale dimensions, and ability to cross the blood–brain barrier, exosomes are promising vectors for targeted delivery; engineered vesicles can enhance chemotherapy responsiveness and counteract resistance, particularly alongside immunotherapy. In summary, interventions that disrupt exosome biogenesis, cargo loading, or uptake—paired with engineered exosomes for precision delivery—could mitigate drug resistance, metastasis, and immune evasion and advance more effective cancer treatment.

Cancer immunotherapy has transformed oncology by enabling targeted activation of antitumor immune responses in patients with relapsed or refractory malignancies. Among adoptive cell transfer (ACT) strategies, chimeric antigen receptor T-cell (CAR-T) therapy has emerged as a pivotal therapeutic advancement, genetically redirecting T lymphocytes to recognize tumor-associated antigens independently of major histocompatibility complex (MHC) presentation. This review provides a comprehensive overview of the biological principles, design evolution, manufacturing platforms, clinical applications, resistance mechanisms, toxicities, and future directions of CAR-T cell therapy within cancer immunotherapy. Specifically, we examine the evolution of CAR architecture, spanning from first-generation constructs to advanced armored and fifth-generation platforms. Furthermore, we compare viral and non-viral gene delivery systems and discuss emerging approaches such as in vivo CAR engineering, allogeneic "off-the-shelf" products, logic-gated receptors, safety switches, and alternative immune-cell platforms, including natural killer (NK) cells and macrophages. CAR-T cell therapy has achieved its most profound clinical success in hematological malignancies, particularly in cluster of differentiation 19 (CD19)-positive B-cell acute lymphoblastic leukemia and B-cell non-Hodgkin lymphoma, reporting durable remission rates of approximately 60–90% in specific clinical contexts. However, broader clinical translation, particularly in solid tumors, remains constrained by challenges such as cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), antigen escape, tumor heterogeneity, poor trafficking, limited persistence, high manufacturing costs, and the immunosuppressive tumor microenvironment (TME). While next-generation strategies—including clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated editing, lipid nanoparticle (LNP)-based messenger ribonucleic acid (mRNA) delivery, bispecific CARs, and inducible suicide switches—hold promise for improving safety, specificity, scalability, and accessibility, a significant number remain in preclinical or early-phase clinical development. Overall, CAR-T cell therapy represents a transformative "living drug" platform in oncology; however, its broader clinical utility is contingent upon improving durability, reducing toxicity, overcoming solid-tumor barriers, and validating next-generation technologies through robust, long-term clinical studies.

Abnormal cytokine and chemokine concentrations during SARS-CoV-2 infection may represent disease severity. We aimed to assess plasma cytokine and chemokine concentrations in patients with SARS-CoV-2 in Addis Ababa, Ethiopia. In this study, 260 adults: 126 hospitalized patients with confirmed COVID-19 sorted into severity groups: severe (n=68) and mild or moderate (n=58), and 134 healthy controls were enrolled. We quantified 39 plasma cytokines and chemokines using multiplex ELISA. Spearman rank correlation and Mann-Whitney U test were used to identify mechanistically coupled cytokines/chemokines and compare disease severity. Compared to healthy controls, patients with COVID-19 had significantly higher levels of interleukins 1α, 2, 6, 7, 8, 10 and 15, C-reactive protein (CRP), serum amyloid A (SAA), intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion protein 1 (VCAM-1), IFN-γ-inducible protein-10 (IP-10), macrophage inflammatory protein-1 alpha (MIP-1α), eotaxin-3, interferon-gamma (IFN-ϒ), tumor necrosis factor-α (TNF-α), basic fibroblast growth factor (bFGF), placental growth factor (PlGF), and fms-like tyrosine kinase 1 (Flt-1). Patients with severe COVID-19 had higher IL-10 and lower macrophage-derived chemokine (MDC) compared to the mild or moderate group ( P<0.05 ). In the receiver operating characteristic curve, SAA, IL-6 and CRP showed strong sensitivity and specificity predicting the severity and prognosis of COVID-19. Greater age and higher CRP had a significant association with disease severity ( P<0.05 ). Our findings reveal that CRP, SAA, VCAM-1, IP-10, MDC and IL-10 levels are promising biomarkers for COVID-19 disease severity, suggesting that plasma cytokines/chemokines could be used as warning indicators of COVID-19 severity, aid in COVID-19 prognosis and treatment. IMPORTANCE: SARS-CoV-2 triggers inflammatory reaction resulting in respiratory discomfort and in critical case may result in death. Cytokines and chemokines are inflammatory biomarkers that regulate and determine the nature of immune responses. Measuring cytokine and chemokine levels is useful in stratification, management and treatment of COVID-19 patients as well as guide resource allocations and therapeutic options. Here, we examined ctytokine and chemokine profiles in COVID-19 patients. Understanding how distinct cytokines and chemokines change over time as COVID-19 disease progresses might aid clinicians in detecting severe illness earlier and thereby improve patient prognosis.

Introduction: Patients with Diabetes are at increased risk of severe COVID-19 and death, thus, it is imperative to provide them with vaccination. Ad26.COV2. S vaccine has proven its efficacy. However, the immunological response of the patients with diabetes in Ethiopia has not been well studied.Methods: This prospective cohort study assessed immune responses after vaccination with a single dose of the Ad26.COV2.S. The subjects were enrolled diabetic patients who were 18 years old and above and attended a diabetes clinic at Adama Hospital Medical College. A sufficient blood sample was collected from each participant, following established standard protocols. We evaluated correlations among selected immunological parameters (IgG, IgM, CRP, IL6, IFN-Y) and employed statistical techniques such as chi-square tests, independent t-tests, and Generalized Estimating Equations (GEE) to analyze differences between given vaccinated and non-vaccinated cohorts. Generalized Estimating Equations (GEE) are a statistical method for modeling longitudinal or clustered data, particularly useful when dealing with non-normal data like binary or count data, by estimating parameters of a generalized linear model while accounting for potential correlations between observations.Results: It was found that vaccinated subjects showed significant alterations in the immune response with IgM elevation and a temporary increase of inflammatory biomarkers CRP and IL-6. Younger age and females were associated with lower inflammatory markers, and no significant effects of lifestyle factors (alcohol, chat, smoking) on immunological outcomes were observed. This vaccine elicited significant immunological responses in diabetic patients, characterized by initial increases in inflammatory markers and subsequent stabilization, and with implications for the healthcare policies to design tailored approaches for diabetic groups.