Chronic wounds in older adults are a growing concern due to impaired immunity, delayed epithelialization, and prolonged inflammation. These wounds lead to significant morbidity, increased healthcare costs, and reduced quality of life. Immunotherapies and adjunctive interventions show promise but remain insufficiently validated in geriatric populations. This study aimed to synthesize and map current evidence on immune-based strategies and supportive approaches for chronic wound management in the elderly, focusing on mechanisms, outcomes, and delivery challenges. A scoping review was conducted following the Arksey and O’Malley framework and PRISMA-ScR guidelines. Searches in PubMed, Scopus, and Web of Science, complemented by manual screening, identified eligible studies using the PCC (Population–Concept–Context) framework. Data extracted included therapeutic class, mechanism, wound type, and outcomes. Of 1,142 records, 89 met inclusion. Key immunotherapies included NLRP3 inflammasome inhibitors, regulatory T-cell modulators, and mTOR-targeted agents, which improved re-epithelialization and reduced cytokines in preclinical models. However, evidence in elderly human cohorts was scarce. Adjunctive strategies—such as protein supplementation, senescence-targeted agents, and engineered biomaterials—enhanced immunotherapy effects. Major barriers were the lack of wound-specific formulations, limited geriatric trial representation, and underdeveloped topical delivery systems. While immunotherapy shows mechanistic potential to correct immune dysregulation in chronic wounds, most data remain preclinical. Multi-modal strategies integrating immunotherapy, nutrition, and bioengineered scaffolds, tailored to aging physiology, are needed to improve outcomes and require rigorous clinical validation.

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Asthma and allergies both cause similar signs and symptoms and often occur together. Evidence for the effectiveness of immunotherapy has rapidly increased in recent years. Several well-designed studies have demonstrated that allergen immunotherapy may prevent the development of asthma in people with allergic rhinitis. The present study aimed to assess the effect of subcutaneous immunotherapy with specific allergens on clinical symptoms, immunological factors, and cytokines in patients with allergic rhinitis and allergic asthma from the Kyrgyz Republic. This retrospective cohort study was conducted on patients with a slight to moderate level of persistent asthma and moderate to severe allergic rhinitis who had been referred to Osh State Clinic in Osh city, Kyrgyz Republic, from March 2000 to February 2025. About 160 atopic patients with allergic rhinitis and asthma were included in the study; confirmed by history, physical examination, and SPT, irrespective of gender. In patients with allergic asthma, 23 (58.97%) patients showed complete symptom improvement, 11 (28.2%) patients showed complete improvement, and 5 (12.82%) patients showed no response to treatment. Compared to previous treatment in the allergic rhinitis group, the cytokine TGFβ was significantly increased (p < 0.001), while the levels of IFN-γ (p = 0.047) and FOXP3 (p = 0.013) were also insignificantly decreased after immunotherapy. This study examined the impact of standard subcutaneous immunotherapy on patients with allergic respiratory diseases.  The study also shows that immunotherapy stands as the most effective treatment for asthma and nasal allergies in patients who meet selection criteria, especially when medications do not work.

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The majority of people today would suffer and pass away from the hepatitis C virus (HCV); there is little knowledge of the illness in the world. Although many individuals have HCV characteristics and are affected, several individuals do not genuinely believe that this is a major issue. They are simply visiting the hospital to get short-term relief from symptoms like fatigue, nausea, jaundice; in long-term situations, they may experience fluid accumulation in the belly and easily bruise. Later on, it will develop into a chronic illness that causes liver cancer, liver failure, and scarring of the liver (cirrhosis). Since HCV continues to be a major cause of death among the populations, we established a compartmental framework for the nationwide outbreak in the current research, classifying those infected into two sections with the most effective control. To get the fundamental reproduction number, first, we employed the Next-Generation Matrix method to identify the model's endemic and disease-free equilibrium point. Using infected and disease-free equilibrium points with reproduction number coordination, as well as MATLAB software to simulate the model's numerical equations, the local and global stability were analysed.

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Cancer immunotherapy has emerged as a breakthrough treatment, but access to this therapy is heavily influenced by social, geographic, and economic factors, potentially widening healthcare disparities. This study aimed to analyse global trends in scientific publications related to cancer immunotherapy within the context of social justice, service access, and social determinants of health through a bibliometric approach. Data were collected from the Scopus database (2017–2025) using a defined Boolean search query, and analysis was performed using VOSviewer, Publish or Perish, and Microsoft Excel. The results show a gradual increase in publications, with a significant spike in 2021 and a peak in 2024. The United States was the primary hub for knowledge production, followed by European countries, while developing regions such as Africa, Southeast Asia, and Latin America had minimal representation. International collaboration patterns revealed the dominance of North–North partnerships, with limited involvement from developing countries. Keyword analysis highlighted the importance of interdisciplinary approaches, addressing social determinants, healthcare access, and financing issues, but also revealed underexplored areas such as cultural contexts and social support. The findings emphasise the urgent need for more inclusive research agendas and international collaborations involving low- and middle-income countries. Strengthening capacity building, integrating regional and non-English databases, and prioritising social and cultural dimensions in future research are recommended strategies to ensure that advances in cancer immunotherapy contribute to reducing, rather than exacerbating, global health inequities.

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In this susceptible population, respiratory syncytial virus (RSV) can cause severe lower respiratory tract illness (LRTI), which can result in substantial morbidity and mortality. Adults who have RSV infection face a substantial burden. In this study, a Phase III, randomized, double-blind, placebo-controlled trial evaluated the effectiveness of a liposome-encapsulated perfusion F protein nanoparticle-based RSV vaccine (Nano-RSV) in preventing RSV infection. Adults who were enrolled and 60 years of age or older were given either Nano-RSV or a placebo. The incidence of laboratory-confirmed RSV LRTI exhibiting three or more symptoms (cough, fever, and shortness of breath) was the main outcome. Severity of symptoms and hospitalization rates for RSV LRTI were secondary endpoints. When compared to a placebo, the Nano-RSV vaccine dramatically lowered the risk of RSV LRTI (vaccine efficacy: 82.6%, 95% CI: 74.1–90.2%). RSV LRTI-related hospitalization rates were likewise markedly lower in the immunization group. The safety profile of the Nano-RSV vaccine was comparable to that of a placebo, and it was well-tolerated. These results imply that Nano-RSV may prove to be a secure and reliable prophylactic against RSV infection and its sequelae in the elderly.

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Nipah virus (NiV) is a highly virulent zoonotic pathogen associated with significant mortality rates and limited treatment options, posing a significant public health threat. This review explores the epidemiology, molecular structure, and vaccine development efforts targeting glycoprotein G, a critical component of the virus's entry mechanism. Advances in structural biology and immunogenetics have highlighted the potential of glycoprotein G-based vaccines in preventing NiV infections. Despite promising preclinical results, challenges such as immune evasion, safety concerns, and limited clinical trials persist. Additionally, we examine the benefits of glycoprotein G-based vaccines in enhancing immune responses and preventing viral entry, as well as the limitations posed by genetic diversity and cross-reactivity. This review highlights the critical need for ongoing research to overcome existing challenges and guide future vaccine development efforts against NiV. It further underscores the necessity of innovative approaches in vaccine design to reduce the global burden of NiV infections. Glycoprotein G-based vaccines represent a promising avenue for combating NiV infections. Advances in structural biology, immune system targeting, and delivery system technology are paving the way for more effective vaccines. However, overcoming challenges such as cross-reactivity and safety concerns will require continued innovation and collaboration.

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In the immunotherapy process, a machine vision algorithm exhibits an efficient next-generation model for navigating the complex tumor microenvironment with CAR-T cells. With the integration of image-based analysis into the real-time processing algorithm, the system is able to compute spatial guidance for the immune cell, enabling it to detect, eliminate, and infiltrate cells. The variation between computational vision and cellular therapy needs to overcome the issues in the physical and biological barriers of tumors. Hence, in this paper, an effective Fejer Kernel Entropy Masked R-Convolutional Neural Network (FEM-R-CNN) was constructed. The proposed FEM-R-CNN model performs pre-processing of the CAR-T cell using the Fejer Kernel, and segmentation is performed with the entropy model. With the estimated segmentation, the Single Shot Detector (SSD) is employed for the CAR-T cell, and classification is computed using the masked R-CNN for the immunotherapy. Experimental results demonstrate that FEM-R-CNN achieves a cancer cell detection accuracy of 96.2%, a segmentation Intersection over Union (IoU) of 0.86, and a classification accuracy of 94.8%, outperforming traditional models such as U-Net and standard Mask R-CNN by over 5% across key metrics. The model improves signal-to-noise ratio by 46.4% and reduces false positive rates by 53.3%, enabling more precise CAR-T cell navigation. Immune response analysis revealed a CAR-T cell density of up to 150 cells/mm², with a 50% proliferation rate and 72% tumor cell apoptosis, indicating effective immune activity monitoring. The inference time remains competitive at approximately 70 ms per image, supporting near real-time applications.

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The tumor microenvironment (TME) is an environment that affects the growth, progression, and resistance of the tumor. AI is already transformational in the process of comprehending and attacking the TME. Using datasets with many more variables and different aspects, AI models can predict tumor behavior with greater precision than conventional techniques. In this work, the polyethylene glycol-poly (lactic-co-glycolic acid) (PEG-PLGA) nanoparticles coated with magnesium fluoride (MgF₂) and loaded with L-arginine have been developed to modulate the immunity in tumors using nitric oxide (NO). Designed to be released near the TME, PLGA-MgF₂ regulates the release of NO, producing an improvement in immune responses against cancer cells. Plasma-polymer coating of PLGA-MgF₂ nanoparticles showed an average size of 150 nm with MgF₂ shell thicknesses of 12–14 nm and L-arginine loads of 72–75%. The concentrations of NO did not change under the acidic tumor-like conditions, and the concentration was between 25 and 30 µM in the first 48 hours. Transmission electron microscopy (TEM) showed 75–120 particles per square micrometer in the tumor, and the immune cell infiltration increased by 35–45%, and the hypoxia in the tumor decreased by 30–36%. The deep neural networks and support vector machines reached 85–95% accuracy in tumor response classification using AI. The therapy led to 60% augmentation of T-cell activation, 85% tumor growth retardation, 4-fold elevation of the M1/M2 ratio, and 45% longer survival.

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