Search Results (10,589)

Background: Triple-negative breast cancer (TNBC) is a highly aggressive subtype with limited therapeutic options due to the lack of estrogen, progesterone, and HER2 receptors. This study investigated the synergistic anticancer effects of recombinant human apurinic/apyrimidinic endonuclease 1/redox factor-1 (rhAPE1/Ref-1) and acetylsalicylic acid (ASA), a combination that has not been previously tested in vivo. Methods: We treated MDA-MB-231 TNBC cells with rhAPE1/Ref-1, ASA, or their combination to assess cell viability and apoptosis in vitro. In vivo, a murine xenograft model was established to evaluate the efficacy of the combination treatment on tumor growth, tumor-specific biomarkers, and key apoptotic proteins. The safety profile of the combination therapy was also assessed by monitoring hematological parameters. Results: While monotherapy with either rhAPE1/Ref-1 or ASA had minimal effects, their combination significantly reduced cell viability and enhanced apoptosis in vitro by increasing DNA fragmentation. These synergistic cytotoxic effects were significantly inhibited by the receptor for advanced glycation end-products (RAGE) siRNA, suggesting that RAGE acts as an important mediator. In the xenograft model, the combination treatment suppressed tumor growth by approximately 70%, an effect comparable to paclitaxel (PTX). This was confirmed by a significant reduction in the plasma levels of TNBC biomarkers (CEA, CA27-29, and CA15-3) and increased tumor apoptosis via the upregulation of p53 and Bax and downregulation of Bcl-2. Notably, ASA, alone or combined with rhAPE1/Ref-1, induced the expression of RAGE in MDA-MB-231 tumors. In contrast to PTX, the combination of rhAPE1/Ref-1 and ASA did not cause hematological toxicity, such as anemia or thrombocytopenia. Conclusions: The combination of rhAPE1/Ref-1 and ASA represents a promising new therapeutic strategy for TNBC by enhancing apoptosis and significantly inhibiting tumor progression in a mouse xenograft model. Full article

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality globally, driven by marked molecular and cellular heterogeneity that complicates diagnosis and treatment. Despite advances in targeted therapies and immunotherapies, treatment resistance frequently emerges, and clinical benefits remain limited to specific molecular subtypes. To improve early detection and dynamic monitoring, novel diagnostic strategies—including liquid biopsy, low-dose computed tomography scans (CT) with radiomic analysis, and AI-integrated multi-modal platforms—are under active investigation. Non-invasive sampling of exhaled breath, saliva, and sputum, and high-throughput profiling of peripheral T-cell receptors and immune signatures offer promising, patient-friendly biomarker sources. In parallel, multi-omic technologies such as single-cell sequencing, spatial transcriptomics, and proteomics are providing granular insights into tumor evolution and immune interactions. The integration of these data with real-world clinical evidence and machine learning is refining predictive models and enabling more adaptive treatment strategies. Emerging therapeutic modalities—including antibody–drug conjugates, bispecific antibodies, and cancer vaccines—further expand the therapeutic landscape. This review synthesizes recent advances in NSCLC diagnostics and treatment, outlines key challenges, and highlights future directions to improve long-term outcomes. These advancements collectively improve personalized and effective management of NSCLC, offering hope for better-quality survival. Continued research and integration of cutting-edge technologies will be crucial to overcoming current challenges and achieving long-term clinical success. Full article

Background: Pseudomonas aeruginosa infection is a major driver of morbidity and mortality in cystic fibrosis (CF), yet disease severity varies widely among people with CF (pwCF). This clinical heterogeneity suggests the involvement of host genetic modifiers beyond CFTR. We previously identified sphingosine 1-phosphate receptor 1 (S1PR1) as a candidate gene associated with susceptibility to P. aeruginosa. Here, we investigated its role in modulating airway epithelial responses to infection. Methods: Using CRISPR/Cas9, we generated S1PR1-knockout bronchial epithelial cells with (IB3-1) and without (C38) CFTR mutations. We assessed cell viability, cytotoxicity, and interleukin-8 secretion following exposure to P. aeruginosa exoproducts. S1PR1 protein expression was evaluated in lung tissue from pwCF and non-CF individuals using immunohistochemistry. Results: S1PR1-mutant cells produced truncated, non-functional peptides. In CFTR-mutant cells, S1PR1 loss reduced viability, increased cytotoxicity, and significantly enhanced interleukin-8 production in response to P. aeruginosa exoproducts. These effects were not observed in CFTR-competent cells. Notably, S1PR1 protein levels were markedly lower in lung tissue from pwCF compared to non-CF individuals. Conclusions: S1PR1 deficiency exacerbates epithelial damage and inflammatory responses to P. aeruginosa in CF models. These findings highlight S1PR1 as a potential contributor to infection severity and a promising target for therapeutic strategies in pwCF. Full article

Polycystic ovary syndrome (PCOS) is a complex disorder characterized by reproductive abnormalities such as hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology, and is frequently accompanied by metabolic disturbances such as insulin resistance, obesity and dyslipidemia. Genome-wide association studies (GWASs) have identified several susceptibility loci, yet little is known about their functional implications. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) has emerged as a powerful gene editing tool in bridging this gap by allowing researchers to directly target candidate genes in ovarian and metabolic pathways. For instance, experimental models have highlighted the role of CYP17A1 and DENND1A.V2 in androgen excess, anti-Müllerian hormone (AMH) in follicular arrest, and insulin receptor substrate 1 (IRS1) and PPARγ in insulin signaling and adipogenesis. To highlight the multifactorial nature of PCOS, animal models, including zebrafish and rodents, have been used to reveal interactions between reproductive and metabolic phenotypes. Nevertheless, most studies remain restricted to single-gene models, and dual-gene models or combined gene editing and hormonal induction models remain underexplored. Future research integrating precision editing, multi-omic platforms, and patient-derived organoids may provide more accurate disease models and novel therapeutic strategies. Full article

The biophysical characteristics of cellular membranes, particularly their electrical properties in the $\alpha$-dispersion frequency domain, offer valuable insights into cellular states and are increasingly important for cancer diagnostics through epidermal growth factor receptor (EGFR) expression analysis. However, a critical limitation in these electrical measurements is the confounding effect of morphological changes that inevitably occur during prolonged observation periods. These shape alterations significantly impact measured capacitance values, potentially masking true biological responses to epidermal growth factor (EGF) stimulation that are essential for cancer detection. In this study, we attempted to address this fundamental challenge by developing a deep learning method that establishes a direct computational relationship between cellular morphology and electrical properties. We combined optical trapping technology and capacitance measurements to generate a comprehensive dataset of HeLa cells under two different experimental conditions: (i) DPBS treatment and (ii) EGF stimulation. Our convolutional neural network (CNN) architecture accurately predicts 401-point capacitance spectra (0.1–2 kHz) from binary morphological images at low frequencies (0.1–0.8 kHz, < 10% error rate). This capability allows for the identification and subtraction of morphology-dependent components from measured capacitance changes, effectively isolating true biological responses from morphological artefacts. The model demonstrates remarkable prediction performance across diverse cell morphologies in both experimental conditions, validating the robust relationship between cellular shape and electrical characteristics. Our method significantly improves the precision and reliability of EGFR-based cancer diagnostics by providing a computational framework for a morphology-induced measurement error correction. Full article

Standardized, one-size-fits-all COVID-19 booster schedules may be suboptimal due to individual variation in immune backgrounds, particularly prior infection, which induces robust hybrid immunity. This study estimated optimal booster timing by modeling antibody decay in relation to surrogate correlates of protection (CoP). In a prospective cohort of 177 Japanese healthcare workers, we longitudinally monitored anti-spike receptor-binding domain (S-RBD) antibody titers following BNT162b2 vaccination. Participants were stratified into SARS-CoV-2-naïve and previously infected groups. Mixed-effects models were developed to predict when antibody titers would decline below predefined CoP thresholds. The model estimated optimal booster timing after a two-dose primary series to be 3–5 months for naïve individuals and approximately one year for those with prior infection. Following a third dose, the estimated interval extended to 8–12 months for the naïve group and 1.5–2 years for the previously infected group. These substantial differences underscore the limitations of uniform booster schedules. Our findings provide a quantitative framework for personalized vaccination strategies based on individual antibody profiles and immune status, thereby optimizing protection. Full article

Therapeutic innovation in cardiovascular medicine is rapidly overcoming the limitations of conventional strategies, providing more targeted, durable, and multidimensional solutions. Key advances include next-generation lipid-lowering agents such as PCSK9 inhibitors, inclisiran, and bempedoic acid, as well as metabolic drugs like SGLT2 inhibitors, GLP-1 receptor agonists, and dual GIP/GLP-1 agonists, which offer cardiovascular and renal benefits beyond glucose control. At the same time, gene therapies, RNA-based interventions, genome editing tools, and nanocarriers are paving the way for precision medicine tailored to individual patient profiles. In parallel, digital innovations, including artificial intelligence, remote monitoring, and telehealth platforms, are transforming care delivery by enhancing adherence, enabling earlier intervention, and refining risk stratification. Collectively, these developments signify a paradigm shift toward a more personalized, proactive, and systems-based model of cardiovascular care. Full article

Background/Objectives: Triple-negative breast cancer (TNBC) is among the most aggressive subtypes, lacking estrogen, progesterone, and HER2 receptors, which limits the efficacy of targeted therapies. Standard treatments often fail due to rapid drug resistance and poor long-term outcomes. Repurposing approved drugs with anticancer potential offers a promising alternative. Disulfiram (DSF), an FDA-approved alcohol-aversion drug, forms a copper complex [Cu(DDC)₂] with potent anticancer activity, but its clinical translation is hindered by poor solubility, limited stability, and inefficient delivery. Methods: Here, we present an amphiphilic dendrimer-stabilized [Cu(DDC)₂] nanoparticle (NP) platform synthesized via the stabilized metal ion ligand complex (SMILE) method. Results: The optimized nanocarrier achieved high encapsulation efficiency, enhanced serum stability, and potent cytotoxicity against TNBC cells. It induced immunogenic cell death (ICD) characterized by calreticulin exposure and ATP release, while modulating the tumor microenvironment by downregulating MMP-3, MMP-9, VEGF, and vimentin, and restoring epithelial markers. In a 4T1 TNBC mouse model, systemic [Cu(DDC)₂] NP treatment significantly inhibited tumor growth without combinational chemo- or radiotherapy. Conclusions: This DSF-based metal–organic NP integrates drug repurposing, immune activation, and tumor microenvironment remodeling into a single platform, offering strong translational potential for treating aggressive breast cancers. Full article

The spotted-leaf mutant, characterized by spontaneous lesion formation resembling pathogen-induced hypersensitive cell death, serves as an ideal model for studying the molecular mechanisms behind rice (Oryza sativa) disease resistance and programmed cell death, as these plants display hypersensitive responses that mimic those triggered by pathogen infection. In this study, we generated a knockout line using CRISPR/Cas9 technology in homologous mutant HM113-induced calli. LOC_Os07g30510 encodes a cysteine-rich receptor kinase with a DUF26 domain, consisting of 688 amino acids. HM113 was localized to the cytosol and expressed in most rice tissues at various growth stages. A single nucleotide substitution from A to T was observed at the 847th base of LOC_Os07g30510, causing an amino acid change from serine to cysteine. Our results demonstrated that the A847T mutation was responsible for the spotted-leaf phenotype in the HM113 mutant through gene editing technology, as new frameshift mutations were introduced upstream of the A847T site in the HM113 gene. The mutation phenotype of HM113 was eliminated and resistance to bacterial blight was also lost, indicating that it is a gain-of-function gene. Full article

Background/Objectives: Breast cancer remains the most prevalent malignancy among women worldwide, with letrozole (LZ) serving as a critical aromatase inhibitor for hormone receptor–positive cases. However, long-term oral administration of LZ is often associated with systemic adverse effects and poor patient compliance. To overcome these limitations, new non-aqueous nanoemulgels (NEMGs) were developed for transdermal delivery of LZ. Methods: The NEMGs were formulated using glyceryl monooleate (GMO), Sepineo P600^®, Transcutol, propylene glycol, and penetration enhancers propylene glycol laurate (PGL), propylene glycol monocaprylate (PGMC), and Captex^®. Physicochemical characterization, solubility, stability, and in vitro permeation studies were conducted using Strat-M^® membranes, while in vivo pharmacokinetics were evaluated in rat models. Results: The optimized GMO/PGMC-based NEMG demonstrated significantly enhanced drug flux, higher permeability coefficients, and shorter lag times compared with other NEMGs and suspension emulgels. In vivo, transdermal application of the GMO/PGMC-based NEMG over an area of 2.55 cm² produced dual plasma absorption peaks, with 57% of the LZ dose absorbed relative to oral administration over 12 days. Shelf-life and accelerated stability assessments confirmed excellent physicochemical stability with negligible crystallization. Conclusions: The developed LZ NEMG formulations offer a stable, effective, and patient-friendly transdermal drug delivery platform for breast cancer therapy. This system demonstrates potential to improve patient compliance and reduce systemic toxicity compared to conventional oral administration. Full article

Radiation-induced lung inflammation (RILI) is a major complication of thoracic radiotherapy, characterized by excessive inflammation and subsequent fibrosis that compromise pulmonary function and treatment outcomes. This study explores the pharmacological properties of a newly synthesized Lipoxin A4 analogue (CYNC-2) to mitigate RILI by modulating the AMP-activated protein kinase (AMPK)/NOD-like receptor family pyrin domain containing 3(NLRP3) inflammasome pathway. A murine RILI model was established in mice by delivering a single high-dose (ablative) X-ray irradiation to the left lung. Mice in the treatment group received CYNC-2 via tail-vein injection three times per week for 2 weeks. The effects of CYNC-2 on RILI were evaluated histological, immunohistochemical analysis of lung tissues, cytokine profiling, lung function testing using a FlexiVent system, and micro-computed tomography (micro-CT) imaging of lung damage. In parallel, two human lung cell lines—L132 (normal bronchial epithelial cells) and A549 (lung carcinoma cells)—were irradiated with 6 Gy X-rays and treated with CYNC-2 to assess cell viability and changes in AMPK/NLRP3 pathway markers via qPCR and immunofluorescence. Lung tissue sample from patients who underwent thoracic radiotherapy were also examined to validate key findings. CYNC-2 activated AMPK and inhibited mTOR signaling, which suppressed NLRP3 inflammasome activation and led to reduced secretion of pro-inflammatory cytokines (IL-1β, IL-6, and TGF-β1). In vitro, CYNC-2 mitigated radiation-induced inflammatory responses and preserved cellular viability. Overall, CYNC-2 effectively dampened acute pulmonary in the RILI model. These findings suggest that targeting the AMPK/NLRP3 inflammasome pathway via a stable LXA4 analogue such as CYNC-2 is a promising therapeutic strategy to improve clinical outcomes for patients receiving thoracic radiation therapy. Full article

Background/Objectives: T cell bispecific antibodies (TCBs) result in the activation of T cell receptor signaling upon binding to tumor antigens providing signal 1 to T cells. To enhance and sustain their activity, a co-stimulatory signal 2 is required. Here CEACAM5-targeted 4-1BBL antibody fusion proteins for combination with CEA-TCB (cibisatamab, RG7802) are described in an investigation of the relationship between the CEACAM5 epitope and T cell activity. Methods: CEACAM5-targeted bispecific 4-1BBL antibody fusion proteins (CEA-4-1BBLs) were generated based on different CEACAM5 antibodies and characterized in vitro in Jurkat-4-1BB reporter and PBMC cell assays. The impact of shed CEA on in vitro activity and cynomolgus cross-reactivity was studied. In vivo efficacy was assessed in human stem cell humanized NSG mice xenograft models bearing MKN-45 and HPAFII tumors. Results: MFE23-4-1BBL and Sm9b-4-1BBL showed superior functional activity in Jurkat-4-1BB reporter and primary T cell assays when combined with the CD3 antibody V9, whereas T84.66-LCHA-4-1BBL and A5B7-4-1BBL performed better when combined with CEA-TCB. In humanized NSG mice MKN-45 and HPAFII xenograft models, T84.66-LCHA-4-1BBL mediated the best anti-tumor efficacy. Conclusions: For the assessment of the combination of CEA-TCB with CEA-4-1BBL, co-stimulatory antibody fusion protein in vitro assays are not sufficient to fully capture the complex relationships affecting efficacy. Thus, screening with different cell assays and in vivo efficacy studies in combination with CEA-TCB are essential to select the best candidate. Based on the totality of data on the T84.66-LCHA-4-1BBL antibody fusion protein comprising the CEACAM5 antibody, T84.66-LCHA was selected as the optimal combination partner for CEA-TCB. Full article

Mastitis is a common mammary gland disease in mammals that severely impairs lactation function, with Staphylococcus aureus (S. aureus) being the primary pathogenic bacterium. However, the molecular mechanisms underlying S. aureus-induced mastitis in sheep remain incompletely elucidated. This study employed RNA sequencing (RNA-SEq) technology to systematically analyze the dynamic transcriptomic characteristics of mammary tissue in small-tailed sheep (SHT) after S. aureus infection, aiming to clarify the molecular regulatory mechanism of the host immune response and its relationship with the occurrence of mastitis. Twelve lactating STH were selected to establish an S. aureus-induced mastitis model. Blood, milk, and tissue samples were collected at 0, 24, 48, and 72 h post-infection (hpi). The infected sheep exhibited typical mastitis symptoms, including exacerbated breast swelling, reduced milk yield, elevated udder temperature, and darker, more viscous milk. Hematoxylin–eosin (HE) staining revealed significant pathological changes over time, such as stromal hyperplasia, extensive inflammatory cell infiltration, severe necrosis and sloughing of mammary epithelial cells, and compromised tissue integrity. RNA-Seq analysis identified 1299 differentially expressed genes (DEGs), among which 75 core genes maintained stable expression throughout the infection time (24 hpi, 48 hpi, and 72 hpi). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these DEGs were associated with metabolic processes, protein binding, Toll-like receptor signaling, and the NF-κB pathway. The PPI network analysis identified core hub genes including PTK2B, STAT3, and JAK1/3, providing critical evidence for therapeutic target screening. Furthermore, qPCR verification indicated that the expressions of innate immune receptors TLR2, TLR4, TLR7, and TLR10, as well as pro-inflammatory factors IL-1β, IL-16, TNF-α, type I interferon (IFN-α), and nuclear transcription factor NF-κB were significantly upregulated in a time-dependent manner (p < 0.05). In conclusion, this study delineated the dynamic response of ovine mammary tissue to S. aureus infection, systematically elucidated temporal gene expression patterns, and revealed the molecular mechanisms underlying the tissue’s initial defense against inflammatory challenges. Full article

Thymic stromal lymphopoietin (TSLP) works synergistically with Th2 cytokines to regulate infection, inflammation, and metabolic homeostasis. However, their aberrant activities lead to the onset and sustaining of many types of allergic inflammatory diseases. While biologics drug molecules blocking either TSLP or IL-4/IL-13 show clinical efficacies, the broader effect of simultaneously targeting these cytokines remains to be explored. We generated a bispecific antibody (BsAb) targeting both TSLP and IL-4Rα, which effectively blocked the signaling cascades driven by TSLP, IL-4, and IL-13. The BsAb also neutralized TSLP-driven CD4⁺ T cell proliferation as well as IL-4 and IL-13-driven TF-1 cell proliferation. The BsAb reduced CCL17 release from CD14⁺ monocytes activated by LPS, TSLP, and IL-4 and reduced allergen-induced CCL26 and IL-5 release from co-cultures of PBMC, MRC-5, and A549 cells. In a TSLP/OVA-induced asthma model with transgenic human TSLP, TSLP receptor, IL-4, and IL-4Rα mice, the BsAb reduced every single allergic/inflammatory hallmark, while the single target blockade antibody failed to have such comprehensive effects. Our data suggested that simultaneous blocking of TSLP, IL-4, and IL-13 could offer broader control of allergic inflammation, which could translate to a more effective treatment of related disorders. Full article

There exists an urgent need to improve colorectal cancer (CRC) diagnosis due to limitations in current diagnostic approaches. Systematic characterization of the human T cell receptor (TCR) repertoire, coupled with advanced computational methods, provides a promising opportunity to develop more accurate and less invasive diagnostic strategies for this major malignancy. The main objective of this work is to establish a TCR repertoire-based diagnostic model for CRC using machine learning algorithms and to identify the most significant features contributing to accurate diagnosis. Through comprehensive comparative analysis of several machine learning algorithms, our results demonstrated that the Transformer model exhibited superior performance capabilities. The trained model achieved an area under the receiver operating characteristic curve (AUC) of 0.973 in predicting disease status in the internal test set. Furthermore, TCR repertoire analysis from the independent test set demonstrated robust predictions with an AUC of 0.814. Notably, we identified a panel of 50 TCR repertoire features that showed a diagnostic AUC of 0.869 using these 50 TCR CDR3 sequences. Together, this TCR repertoire-based disease model demonstrates significant potential for clinical applications in CRC diagnosis and treatment response monitoring. Furthermore, similar diagnostic models could be established for other immune-related diseases based on disease-specific TCR repertoire data. Full article