Poor bioavailability and a short half-life limit the therapeutic efficacy of ibuprofen. This study developed floating nanoballoons to enhance ibuprofen’s bioavailability and sustain its anti-inflammatory effects through improved gastric retention.

Ibuprofen-loaded nanoballoons were synthesized using solvent evaporation with ethyl cellulose as the polymer matrix. The formulation was characterized for morphology, buoyancy, drug loading, and release kinetics. In vivo studies assessed the anti-inflammatory efficacy in acute and chronic inflammation models using male Sprague-Dawley rats.

The nanoballoons exhibited optimal characteristics, including 96% buoyancy and a drug loading efficiency of 96.54 ± 1.32%. Scanning Electron Microscopy revealed a spherical morphology with a porous structure. Drug release followed a biphasic pattern: an initial release of 35.23 ± 2.13% over 2 h, followed by sustained release reaching 97.54 ± 1.30% at 12 h. In acute inflammation studies, the nanoballoon formulation showed superior edema inhibition (68.12%) compared to pure ibuprofen (51.67%). Chronic inflammation studies demonstrated significant improvements in inflammatory markers: reduced TNF-α (19.12 ± 0.48 vs. 31.11 ± 1.23 pg/mL), hs-CRP (201.7 ± 11.02 vs. 232.12 ± 11.33 ng/mL), and IL-6 (100.01 ± 18.40 vs. 135 ± 11.22 pg/mL), with increased anti-inflammatory IL-10 (507.18 ± 10.11 vs. 276.11 ± 19.16 pg/mL).

The developed floating nanoballoon system significantly enhanced ibuprofen’s bioavailability and anti-inflammatory efficacy, presenting a promising gastro-retentive delivery platform for poorly water-soluble drugs.

Tumors are complex systems characterized by variations across genetic, transcriptomic, phenotypic, and microenvironmental levels. This study introduced a novel framework for quantifying cancer cell heterogeneity using single-cell RNA sequencing data. The framework comprised several scores aimed at uncovering the complexities of key cancer traits, such as metastasis, tumor progression, and recurrence.

This study leveraged publicly available single-cell transcriptomic data from three human breast cancer subtypes: estrogen receptor-positive, human epidermal growth factor receptor 2-positive, and triple-negative. We employed a quantitative approach, analyzing copy number alterations (CNAs), entropy, transcriptomic heterogeneity, and diverse protein-protein interaction networks (PPINs) to explore critical concepts in cancer biology.

We found that entropy and PPIN activity related to the cell cycle could distinguish cell clusters with elevated mitotic activity, particularly in aggressive breast cancer subtypes. Additionally, CNA distributions varied across cancer subtypes. We also identified positive correlations between the CNA score, entropy, and the activities of PPINs associated with the cell cycle, as well as those linked to basal and mesenchymal cell lines.

This study addresses a gap in the current understanding of breast cancer heterogeneity by presenting a novel quantitative approach that offers deeper insights into tumor biology, surpassing traditional marker-based methods.

Liquid biopsy (LB) represents a promising strategy for the early diagnosis and treatment of lung cancer. However, relying solely on single-biomarker immunohistochemistry for predictive purposes has shown limited efficacy, often leading to suboptimal responses in certain patients. LB provides a complementary or alternative approach to immunohistochemistry by aiding in the identification of patients better suited for immunotherapy, thereby improving treatment precision. This review highlights key LB targets, including circulating tumor cells, exosomes, and small protein molecules, and explores the predictive and prognostic value of LB in immunotherapy for lung cancer and other tumors. These biomarkers play complex and multifaceted roles in liquid biopsies. Consequently, researchers have developed numerous targeted detection methods to study and identify key factors among multiple biomarkers in lung cancer and other tumor diseases. In addition, the limitations and future directions of LB are examined, aiming to advance its clinical application and support the development of personalized and precise immunotherapy. The integration of LB with artificial intelligence holds significant clinical potential for guiding immunotherapy and advancing precision medicine in lung cancer and other tumors.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, highlighting the urgent need for innovative diagnostic and prognostic approaches to address their complex pathophysiology. Recent advances in molecular cardiology have unveiled immune-derived microRNAs (miRNAs), or immuno-miRs, as pivotal regulators in the interplay between immune responses and cardiovascular pathology. Secreted by immune cells such as T lymphocytes, macrophages, and neutrophils, these small non-coding RNAs modulate critical signaling pathways by regulating gene expression. Immuno-miRs influence essential processes, including inflammation, endothelial dysfunction, and fibrotic remodeling—core mechanisms underlying conditions such as atherosclerosis, myocardial infarction, and heart failure. Moreover, their presence in systemic circulation within extracellular vesicles underscores their role in intercellular communication, impacting both immune and non-immune cardiovascular cells, such as cardiomyocytes and endothelial cells. This dual functionality renders immuno-miRs promising candidates as diagnostic biomarkers for early disease detection and as prognostic tools for assessing disease progression and therapeutic efficacy. Furthermore, emerging miRNA-based interventions—such as miRNA mimics and inhibitors—show considerable promise in modulating immune dysregulation in CVDs, although clinical translation remains a significant challenge. In this review, we comprehensively examine the regulatory roles of immuno-miRs in both innate and adaptive immune responses and explore recent advancements in miRNA-based therapies. By consolidating current knowledge and identifying existing gaps, we provide a comprehensive overview of the transformative potential of immuno-miRs in CVD management. Integrating these molecules into personalized medicine may pave the way for more effective, targeted, and minimally invasive strategies to combat one of the world’s most pressing health challenges.

Glioblastoma is the most common primary tumor of the central nervous system, characterized by an infiltrative growth pattern, which results in the most unfavorable prognosis. The average survival time of patients after diagnosis of this tumor is typically several months, with complete recovery from glioma being very rare. In recent years, significant involvement of exosomes in the development of cancer, including malignant brain tumors, has been discovered. Exosomes are extracellular vesicles that carry signaling molecules and participate in communication between cells. They influence cell survival, proliferation, migration, and increased neoangiogenesis, all of which significantly contribute to tumor recurrence. Molecules carried by exosomes are considered potential diagnostic markers, enabling early diagnosis of cancer and prompt implementation of appropriate treatment. Of particular diagnostic importance are microRNA molecules, which promote increased cell proliferation and inhibition of apoptosis. Equally important exosomal transmitters include proteins such as PSMD2 and EGFR, which enhance tumor invasiveness and resistance to chemotherapeutic agents. Recent studies suggest the possibility of using exosomes as carriers for new anticancer drugs, potentially improving the therapeutic treatment of cancers resistant to standard treatment methods. This review aimed to provide a comprehensive analysis of recent research on glioblastoma, the role of exosomes in its progression, the potential of exosomes as diagnostic biomarkers, and their use as therapeutic targets for patients who have not responded to conventional treatments.

Therapy-related B-lymphoblastic leukemia (B-ALL) following treatment for multiple myeloma is a rare occurrence. Despite its rarity and the lack of recognition by the World Health Organization as a distinct disease entity, previous publications indicate its possible emergence following myeloma treatment.

The patient is a 65-year-old gentleman with a history of IgG kappa multiple myeloma, status post multiple lines of therapy. The patient presented with a fever, and a complete blood count showed cytopenia. Bone marrow morphologic evaluation revealed numerous blasts. Immunophenotypic analysis demonstrated that these blasts were B lymphoblasts, despite MYC and unusual surface kappa light chain expression. A diagnosis of B-ALL with surface kappa light chain expression post-myeloma treatment was made. Ancillary studies indicated that the B-ALL and the previous myeloma were clonally unrelated. Next-generation gene sequencing revealed pathogenic mutations in KDM6A and KRAS.

This case highlights the potential for therapy-related B-ALL following myeloma treatment, a phenomenon deserving further investigation. The expression of surface light chain in blasts can present a diagnostic pitfall.

Incomplete immune reconstitution is characterized by chronic immune activation and systemic inflammation, which are not fully reversed by antiretroviral therapy. Dihydroartemisinin (DHA) has demonstrated anti-inflammatory and immunosuppressive properties, which may benefit individuals with incomplete immune reconstitution. This study aimed to investigate the biological mechanisms underlying incomplete immune reconstitution and evaluate the therapeutic potential of DHA in modulating immune activation in immunological non-responders (INRs). This study aimed to investigate the biological mechanisms underlying incomplete immune reconstitution and evaluate the therapeutic potential of DHA in modulating immune activation in immunological non-responders (INRs).

RNA sequencing data (GSE106792) was retrieved from the Gene Expression Omnibus database. R software and Bioconductor packages were used to identify differentially expressed genes (DEGs) among INRs, immune responders (IRs), and healthy controls (HCs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, along with protein-protein interaction (PPI) network construction, were performed. Potential DHA-binding proteins were predicted using the STITCH server and molecular docking studies. Validation experiments were conducted on peripheral blood mononuclear cells from 18 INRs. Cells were treated with varying concentrations of DHA, and CD4+ and CD8+ T cell activation markers (CD38 and HLA-DR) were measured via flow cytometry.

Enrichment and PPI network analysis identified 119, 56, and 189 DEGs in the INR vs. HC, INR vs. IR, and IR vs. HC comparisons, respectively. Enrichment and PPI analyses showed that DEGs were mainly involved in immune response pathways. DHA was predicted to interact with multiple target proteins, indicating anti-inflammatory effects. In vitro, DHA significantly reduced the frequency of CD38− HLA-DR+ CD4+ T cells and CD38+ HLA-DR+ CD8+ T cells at 1,000 µM and 500 µM compared to the control.

This study provides insights into the biological mechanisms underlying incomplete immune reconstitution and supports DHA’s potential as a therapeutic agent. DHA effectively inhibits T cell activation in INRs, presenting a novel and promising treatment strategy.

Intrahepatic cholangiocarcinoma (iCCA) is the second most prevalent primary liver cancer, characterized by insidious onset and high malignancy. Many patients are diagnosed at an inoperable stage, and the effectiveness of chemotherapy and radiotherapy remains limited. This study aimed to provide a comprehensive review of the histological classification, genetic alterations, molecular subtypes, and corresponding imaging signatures of iCCA, highlighting its heterogeneity and offering insights into targeted therapy and personalized treatment. The heterogeneity of iCCA poses significant challenges to both targeted therapy and immunotherapy, necessitating in-depth exploration at the molecular and subtyping levels. Investigating genetic variations, signaling pathway alterations, and molecular subtypes can aid in patient stratification. Stratifying iCCA patients allows for more precise treatment selection, ultimately improving survival outcomes. Imaging, as a non-invasive tool, holds substantial potential for predicting subtypes and molecular profiles. It is possible to infer histological and molecular features from imaging, or to interpret imaging signatures in light of known histological and molecular data. This integrative approach, combining external imaging with internal molecular insights, fosters a comprehensive understanding of iCCA’s characteristics and enhances clinical management.