Search Results (241)

Colitis-associated colorectal cancer (CAC) is a type of colorectal cancer (CRC) that develops as a result of chronic inflammation, particularly in patients with inflammatory bowel diseases such as ulcerative colitis and Crohn’s disease. Persistent intestinal inflammation and dysbiosis of gut microbiota under these conditions are major contributors to CRC progression. Doenjang, a traditional Korean fermented soybean paste, contains probiotics that influence intestinal microbiota composition, as well as biogenic amines (BAs), harmful compounds generated during fermentation. We analyzed the bacterial composition and BA content of Doenjang and evaluated its effects on CAC in a mouse model of AOM/DSS-induced CAC. Results revealed that Doenjang contains diverse beneficial probiotics alongside BAs. Doenjang significantly reduced tumor formation and attenuated CAC progression by modulating inflammatory and apoptotic pathways and suppressed the expression of pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) by inhibiting the NF-κB pathway. Additionally, Doenjang restored intestinal epithelial barrier integrity by increasing the expression of mucin-related genes (MUC-2, MUC-3) and protective factors like TFF-3. Gut microbiota analysis revealed that Doenjang promoted a healthier gut environment by increasing microbial diversity and reducing inflammation-related bacterial populations. These findings suggest that Doenjang helps prevent and manage CAC by modulating inflammatory responses and gut microbiota composition. Full article

Alpinetin, a distinctive plant-derived dihydroflavonoid from cardamom seeds, represents an under-explored chemical scaffold compared to common flavonoids like quercetin or kaempferol. While many flavonoids have shown general cardioprotective potential, the structural specificity of alpinetin may confer unique pharmacological advantages. Inspired by its historical use in traditional Chinese medicine for cardiac discomfort, this study systematically investigated its efficacy against acute myocardial infarction (AMI). In a rat AMI model, alpinetin demonstrated superior infarct size reduction and functional recovery relative to other tested flavonoids. It significantly attenuated key AMI pathologies—including inflammatory infiltration, CD68+ macrophage activation, IL-6/TNF-α release, collagen deposition, and cardiomyocyte apoptosis—more effectively than common flavonoid benchmarks. Mechanistically, alpinetin selectively targeted the TLR4/MyD88/NF-κB signaling axis with notable potency, a pathway not robustly modulated by other flavonoids in the screening. These findings not only validate the traditional wisdom of cardamom but also establish alpinetin as a structurally and mechanistically distinct flavonoid with high translational promise, offering a new candidate for the targeted treatment of ischemic heart disease. Full article

Chronic kidney disease (CKD) causes a variety of health problems including renal dysfunction and cardiovascular disease. This study aimed to investigate whether the probiotic strain Lactiplantibacillus plantarum HY7718 (HY7718) can protect against CKD using HK2 cells and a CKD mouse model, generated by feeding mice a diet containing 0.15% adenine. In vitro tests showed that HY7718 was anti-inflammatory in H₂O₂-treated HK2 cells and reduced apoptosis of tumor necrosis factor-α/cycloheximide-induced HK2 cells. In the adenine-induced CKD model, markers of renal dysfunction (blood urea nitrogen (BUN) and creatinine (Crea)) and inorganic calcium and phosphorus were markedly increased. However, oral administration of HY7718 (10⁸ colony-forming units/kg/day) significantly attenuated these increases. HY7718 also reduced the kidney histopathological score, including tubular necrosis, cast formation, and tubular dilatation, as well as the mononuclear cell infiltration score in kidney tissue, suggesting that it could reverse the progression of CKD. Additionally, HY7718 downregulated the renal expression of pro-inflammatory cytokine genes and members of the TLR/NF-κB signaling pathway. Furthermore, HY7718 reduced tubule apoptotic cells and expression of apoptosis-related genes, indicating that it is potentially renoprotective. These results demonstrate that supplementation with the probiotic HY7718 can ameliorate CKD symptoms by improving renal function and reducing kidney injury. Full article

Background and objectives: Large language models (LLMs) show promise in automating open-ended evaluation tasks, yet their reliability in rubric-based assessment remains uncertain. Variability in scoring, feedback, and rubric adherence raises concerns about transparency and pedagogical validity in educational contexts. This study introduces CourseEvalAI, a framework designed to enhance consistency and fidelity in rubric-guided evaluation by fine-tuning a general-purpose LLM with authentic university-level instructional content. Methods: The framework employs supervised fine-tuning with Low-Rank Adaptation (LoRA) on rubric-annotated answers and explanations drawn from undergraduate computer science exams. Responses generated by both the base and fine-tuned models were independently evaluated by two human raters and two LLM judges, applying dual-layer rubrics for answers (technical or argumentative) and explanations. Inter-rater reliability was reported as intraclass correlation coefficient (ICC(2,1)), Krippendorff’s α, and quadratic-weighted Cohen’s κ (QWK), and statistical analyses included Welch’s t tests with Holm–Bonferroni correction, Hedges’ g with bootstrap confidence intervals, and Levene’s tests. All responses, scores, feedback, and metadata were stored in a Neo4j graph database for structured exploration. Results: The fine-tuned model consistently outperformed the base version across all rubric dimensions, achieving higher scores for both answers and explanations. After multiple-testing correction, only the Generative Pre-trained Transformer (GPT-4)—judged Technical Answer contrast remains statistically significant; other contrasts show positive trends without passing the adjusted threshold, and no additional significance is claimed for explanation-level results. Variance in scoring decreased, inter-model agreement increased, and evaluator feedback for fine-tuned outputs contained fewer vague or critical remarks, indicating stronger rubric alignment and greater pedagogical coherence. Inter-rater reliability analyses indicated moderate human–human agreement and weaker alignment of LLM judges to the human mean. Originality: CourseEvalAI integrates rubric-guided fine-tuning, dual-layer evaluation, and graph-based storage into a unified framework. This combination provides a replicable and interpretable methodology that enhances the consistency, transparency, and pedagogical value of LLM-based evaluators in higher education and beyond. Full article

Background: Lumbar disk herniation is a common cause of low back pain and radiculopathy, significantly impacting patients’ life quality and functional capacity. Magnetic Resonance Imaging (MRI) remains the gold standard for its assessment due to its superior soft tissue contrast and multiplanar imaging capabilities. However, recent advances in spectral computed tomography (CT), particularly dual-energy CT (DECT), have introduced new diagnostic opportunities, offering improved soft tissue characterization. Objective: To evaluate the diagnostic performance of DECT in detecting and grading lumbar disk herniations using dedicated color-coded fat maps. Materials and Methods: A total of 205 intervertebral levels from 41 consecutive patients with lumbar symptoms were prospectively analyzed. All patients underwent both DECT and MRI within 3 days. Three radiologists with varying years of experience independently assessed DECT images using color-coded reconstructions. A five-point grading score was attributed to each lumbar level: 1 = normal disk, 2 = bulging/protrusion, 3 = focal herniation, 4 = extruded herniation, and 5 = migrated fragment. The statistical analysis included Pearson’s correlation for score consistency, Cohen’s Kappa for interobserver agreement, generalized estimating equations for a cluster-robust analysis, and an ROC curve analysis. The DECT diagnostic accuracy was assessed in a dichotomized model (grades 1–2 = no herniation; 3–5 = herniation), using MRI as reference. Results: A strong correlation was observed between DECT and MRI scores across all readers (mean Pearson’s r = 0.826, p < 0.001). The average exact agreement between DECT and MRI was 79.4%, with the highest concordance at L1–L2 (86.7%) and L5–S1 (80.4%). The interobserver agreement was substantial (mean Cohen’s κ = 0.765), with a near-perfect agreement between the two most experienced readers (κ = 0.822). The intraclass correlation coefficient was 0.906 (95% CI: 0.893–0.918). The ROC analysis showed excellent performance (AUC range: 0.953–0.986). In the dichotomous model, DECT demonstrated a markedly higher sensitivity than conventional CT (95.1% vs. 57.2%), with a comparable specificity (DECT: 99.0%; CT: 96.5%) and improved overall accuracy (98.4% vs. 90.0%). Subgroup analyses by age and disk location revealed no statistically significant differences. Conclusions: The use of DECT dedicated color-coded fat map reconstructions showed high diagnostic performance in the assessment of lumbar disk herniations compared to MRI. These findings support the development of dedicated post-processing tools, facilitating the broader clinical adoption of spectral CT, especially in cases where MRI is contraindicated or less accessible. Full article

Head and neck cancer (HNC) is highly heterogeneous and difficult to treat, underscoring the need for rapid, patient-specific models. Standard three-dimensional (3D) cultures often lose stromal partners that influence therapy response. We developed a patient-derived system maintaining tumor cells, cancer-associated fibroblasts (CAFs), and cells undergoing partial epithelial–mesenchymal transition (pEMT) for drug sensitivity testing. Biopsies from four HNC patients were enzymatically dissociated. CAFs were directly cultured, and their conditioned medium (CAF-CM) was collected. Cryopreserved primary tumor cell suspensions were later revived, screened in five different growth media under 2D conditions, and the most heterogeneous cultures were re-embedded in 3D hydrogels with varied gel mixtures, media, and seeding geometries. Tumoroid morphology was quantified using a perimeter-based complexity index. Viability after treatment with cisplatin or Notch modulators (RIN-1, recombination signal-binding protein for immunoglobulin κ J region (RBPJ) inhibitor; FLI-06, inhibitor) was assessed by live imaging and the water-soluble tetrazolium-8 (WST-8) assay. Endothelial Cell Growth Medium 2 (ECM-2) medium alone produced compact CAF-free spheroids, whereas ECM-2 supplemented with CAF-CM generated invasive aggregates that deposited endogenous matrix. Matrigel with this medium and single-point seeding gave the highest complexity scores. Two of the three patient tumoroids were cisplatin-sensitive, and all showed significant growth inhibition with the FLI-06 Notch inhibitor, while the RBPJ inhibitor RIN-1 induced minimal change. The optimized scaffold retains tumor–stroma crosstalk and provides patient-specific drug response data within days after operation, supporting personalized treatment selection in HNC. Full article

This work presents a closed-form approximation to the symbol error probability (SEP) for cross-quadrature amplitude modulation (cross-QAM) schemes over $\mathit{\kappa }$–$\mathit{\mu }$ fading channels. The proposed formulation enables accurate performance evaluation while avoiding computationally expensive numerical integration. The analysis covers millimeter-wave (mmWave) frequencies at 55, 60, and 65 GHz, under both line-of-sight (LoS) and non-line-of-sight (nLoS) conditions, and for multiple transmitter–receiver polarization configurations. A key contribution of this work is the experimental validation of the theoretical expression with real channel-measurement data, which confirms the applicability of the $\mathit{\kappa }$–$\mathit{\mu }$ model in realistic mmWave scenarios. Furthermore, we perform a detailed parametric study to quantify the influence of $\mathit{\kappa }$ and $\mathit{\mu }$ on adaptive modulation performance, providing practical insights for 5G and future 6G systems. The proposed framework bridges theoretical analysis and experimental validation, offering a computationally efficient and robust tool for the design and evaluation of advanced modulation schemes in generalized fading environments. Full article

Colorectal cancer (CRC) remains a major contributor to global cancer-related mortality, with rising incidence observed in several regions, including Saudi Arabia. This review compiles and critically analyzes recent preclinical research from Saudi-based institutions that investigates the anti-CRC potential of natural and synthetic compounds. Numerous natural products such as Nigella sativa, Moringa oleifera, Curcuma longa, and marine-derived metabolites have demonstrated cytotoxic effects through pathways involving apoptosis induction, reactive oxygen species (ROS) generation, and inhibition of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and cyclooxygenase-2 (COX-2). In parallel, synthetic and semi-synthetic agents, including C4–G4 (semi-synthetic hybrids designed from flavonoids and benzoxazole scaffolds that act as dual epidermal growth factor receptor (EGFR)/COX-2 inhibitors)), oxazole derivatives, and camptothecin-based nanocarriers, exhibit promising anti-tumor activity via molecular targeting of cyclin-dependent kinase 8 (CDK8), phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), and β-catenin pathways. Selected in vivo studies primarily utilizing xenograft and chemically induced rodent models have shown reductions in tumor volume and modulation of apoptotic and inflammatory biomarkers. Additionally, green-synthesized metallic nanoparticles (NPs) and polyethylene glycol (PEG)-modified carriers have been investigated to improve bioavailability and tumor targeting of lead compounds. While these findings are encouraging, the majority remain in preclinical phases. Limitations such as poor solubility, lack of pharmacokinetic data, and absence of clinical trials impede translational progress. This review highlights the need for standardized evaluation protocols, mechanistic validation, and region-specific clinical studies to assess efficacy and safety. Given Saudi Arabia’s rich biodiversity and growing research capacity under national strategies like Vision 2030, the country is well-positioned to contribute meaningfully to CRC drug discovery. By integrating bioactive natural products, rationally designed synthetics, and advanced delivery platforms, a pipeline of innovative CRC therapeutics tailored to local and global contexts may be realized. Full article

Age-related macular degeneration (AMD) progresses to vision-threatening dry and wet forms, with no effective dry AMD treatments available. The sulfated polysaccharide (GNP, 25.8 kDa) derived from Gelidium crinale exhibits diverse biological activities and represents a potential source of novel therapeutic agents. This study employed a hydrogen peroxide (H₂O₂)-induced oxidative stress and epithelial–mesenchymal transition (EMT) model in retinal pigment epithelial (RPE) cells to investigate GNP’s protective mechanisms against both oxidative damage and EMT. The results demonstrated that GNP effectively suppressed oxidative stress, with the 600 μg/mL dose significantly inhibiting excessive reactive oxygen species (ROS) generation to levels comparable to untreated controls. Concurrently, at concentrations of 200–600 μg/mL, GNP inhibited NF-κB signaling and increased the Bax/Bcl-2 ratio, effectively counteracting H₂O₂-induced oxidative damage and cell apoptosis. Furthermore, in H₂O₂-treated ARPE-19 cells, 600 μg/mL GNP significantly reduced the secretion of N-cadherin (N-cad), Vimentin (Vim), and α-smooth muscle actin (α-SMA), while increasing E-cadherin (E-cad) expression, consequently inhibiting cell migration. Mechanistically, GNP activated the Nrf2/HO-1 pathway, thereby mitigating oxidative stress. These findings suggest that GNP may serve as a potential therapeutic agent for dry AMD. Full article

Digital contact-tracing (CT) systems differ in how they process risk and expose data, and the centralized–decentralized dichotomy obscures these choices. We propose a modular six-model classification and evaluate 18 platforms across 12 countries (July 2020–April 2021) using a 24-indicator rubric spanning privacy, security, functionality, and governance. Methods include double-coding with Cohen’s $\mathsf{\kappa }$ for inter-rater agreement and a 1000-draw weight-sensitivity check; assumptions and adversaries are stated in a concise threat model. Results: No single model dominates; Bulletin Board and Custodian consistently form the top tier on privacy goals, while Fully Centralized eases verification/notification workflows. Timelines show rapid GAEN uptake and near-contemporaneous open-source releases, with one late outlier. Contributions: (i) A practical, generalizable classification that makes compute-locus and data addressability explicit; (ii) a transparent indicator rubric with an evidence index enabling traceable scoring; and (iii) empirically grounded guidance aligning deployments with goals G1–G3 (PII secrecy, notification authenticity, unlinkability). Limitations include reliance on public documentation and architecture-level (not mechanized) verification; future work targets formal proofs and expanded double-coding. The framework and findings generalize beyond COVID-19 to privacy-preserving digital-health workflows. Full article

Background/Objectives: In many low- and middle-income countries (LMICs), including Bosnia and Herzegovina, oncology services are constrained by a limited number of specialists and uneven access to evidence-based care. Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT, may provide clinical decision support to help standardize treatment and assist clinicians where oncology expertise is scarce. This study aimed to evaluate the concordance, safety, and clinical appropriateness of ChatGPT-generated treatment recommendations compared to decisions made by a multidisciplinary team (MDT) in the management of newly diagnosed breast cancer patients. Methods: This retrospective study included 91 patients with newly diagnosed, treatment-naïve breast cancer, presented to an MDT in Bosnia and Herzegovina in 2023. Patient data were entered into ChatGPT-4.0 to generate treatment recommendations. Four board-certified oncologists, two internal and two external, evaluated ChatGPT’s suggestions against MDT decisions using a 4-point Likert scale. Agreement was analyzed using descriptive statistics, Cronbach’s alpha, and Fleiss’ kappa. Results: The mean agreement score between ChatGPT and MDT decisions was 3.31 (SD = 0.10), with high consistency across oncologist ratings (Cronbach’s alpha = 0.86). Fleiss’ kappa indicated moderate inter-rater reliability (κ = 0.31, p < 0.001). Higher agreement was observed in patients with hormone receptor-negative tumors and those treated with standard chemotherapy regimens. Lower agreement occurred in cases requiring individualized decisions, such as low-grade tumors or uncertain indications for surgery or endocrine therapy. Conclusions: ChatGPT showed high concordance with MDT treatment plans, especially in standardized clinical scenarios. In resource-limited settings, AI tools may support oncology decision-making and help bridge gaps in clinical expertise. However, careful validation and expert oversight remain essential for safe and effective use in practice. Full article

Environmental pollutants such as heavy metals, endocrine-disrupting chemicals, microplastics, and airborne particulates are increasingly recognized for their potential to influence immune function through epigenetic mechanisms. This review examines conserved pollutant-associated pathways at interfaces of immunity and epigenetics, with particular attention to Toll-like receptor–NF-κB signalling, NLRP3 inflammasome activity, and reactive oxygen species-driven cascades. Evidence from cellular, animal, and epidemiological studies indicates that these pathways may converge on chromatin regulators such as DNA methyltransferases, histone deacetylases, and EZH2, leading to DNA methylation shifts, histone modifications, and altered chromatin accessibility. Pollutants are also reported to modulate non-coding RNAs, including miR-21, miR-155, and several lncRNAs, which can act as intermediaries between cytokine signalling and epigenetic remodelling. Findings from transgenerational models suggest that pollutant-linked immune–epigenetic alterations might persist across generations, raising the possibility of long-term consequences for immune and neurodevelopmental health. Comparative analyses further indicate convergence across diverse pollutant classes, pointing to a shared mechanistic axis of immune–epigenetic disruption. Overall, these insights suggest that pollutant-induced immune–epigenetic signatures may contribute to inflammation, altered immune responses, and heritable disease risks, and their clarification could inform biomarker discovery and future precision approaches in immunotoxicology. Full article

Background: Zebrafish-based drug discovery systems provide significant advantages over mammalian models for high-throughput in vivo screening. Among these, the NF-κB eGFP reporter system significantly enhances drug discovery in zebrafish by enabling real-time, high-resolution monitoring of pathway activity in live organisms, thereby streamlining mechanistic studies and high-throughput screening. Methods: We developed a novel AI (Quantifish and Orange software)-based zebrafish precision individualized 96-well ZF plates (0–7 dpf) and individualized MT tanks (8 dpf–4 mpf) protocol for the transposon-mediated transgenesis of the NFκB eGFP reporter system. Results: One-cell stage embryos were administered NFκB reporter construct and Tol2 transposase mRNA via microinjection and transferred to separate wells of a 96-well ZF plate. Bright-field and fluorescence images of each well were captured at 5 dpf in the F0, F1, and F2 generations using the automated confocal high-content imager CQ1. The Quantifish software was used for the automated detection and segmentation of zebrafish larval fluorescence intensity in specific regions of interest. Quantitative data on the fluorescence intensity and distribution patterns were measured in Quantifish, and advanced statistical and machine learning methods were applied using Orange. Imaging data with eGFP expression results were assessed to evaluate the efficiency of the transgenic protocol. Discussion: This AI-enhanced precision protocol allows for high-throughput screening and quantitative analysis of NFκB reporter transgenesis in zebrafish, enabling the efficient identification and characterization of stable transgenic lines that exhibit tissue-specific expression of the NF-κB reporter, such as lines with induced expression restricted to the retina following LPS stimulation. This approach streamlines the evaluation of regulatory elements, enhances data consistency, and reduces animal use, making it a valuable tool for zebrafish drug discovery. Full article

Background and purpose: Vulvovaginal candidiasis (VVC), caused by Candida albicans (C. albicans), is exacerbated by oxidative stress and uncontrolled inflammation. Pathogens like C. albicans generate reactive oxygen species (ROS) to enhance virulence, while host immune responses further amplify oxidative damage. This study investigates the antioxidant and antifungal properties of Hyssopus cuspidatus Boriss volatile extract (SXC), a traditional Uyghur medicinal herb, against fluconazole-resistant VVC. We hypothesize that SXC’s bioactive volatiles counteract pathogen-induced oxidative stress while inhibiting fungal growth and inflammation. Methods: GC-MS identified SXC’s major bioactive components, while broth microdilution assays determined minimum inhibitory concentrations (MICs) against bacterial/fungal pathogens, and synergistic interactions with amphotericin B (AmB) or fluconazole (FLC) were assessed via time–kill kinetics. Anti-biofilm activity was quantified using crystal violet/XTT assays, and in vitro studies evaluated SXC’s effects on C. albicans-induced cytotoxicity (LDH release in A431 cells) and inflammatory responses (cytokine production in LPS-stimulated RAW264.7 macrophages). A murine VVC model, employing estrogen-mediated pathogenesis and intravaginal C. albicans challenge, confirmed SXC’s in vivo effects. Immune modulation was assessed using ELISA and RT-qPCR targeting inflammatory and antioxidative stress mediators, while UPLC-MS was employed to profile metabolic perturbations in C. albicans. Results: Gas chromatography-mass spectrometry identified 10 key volatile components contributing to SXC’s activity. SXC exhibited broad-spectrum antimicrobial activity with MIC values ranging from 0.125–16 μL/mL against bacterial and fungal pathogens, including fluconazole-resistant Candida strains. Time–kill assays revealed that combinations of AmB-SXC and FLC-SXC achieved sustained synergistic bactericidal activity across all tested strains. Mechanistic studies revealed SXC’s dual antifungal actions: inhibition of C. albicans hyphal development and biofilm formation through downregulation of the Ras1-cAMP-Efg1 signaling pathway, and attenuation of riboflavin-mediated energy metabolism crucial for fungal proliferation. In the VVC model, SXC reduced vaginal fungal burden, alleviated clinical symptoms, and preserved vaginal epithelial integrity. Mechanistically, SXC modulated host immune responses by suppressing oxidative stress and pyroptosis through TLR4/NF-κB/NLRP3 pathway inhibition, evidenced by reduced caspase-1 activation and decreased pro-inflammatory cytokines (IL-1β, IL-6, TNF-α). Conclusions: SXC shows promise as a broad-spectrum natural antimicrobial against fungal pathogens. It inhibited C. albicans hyphal growth, adhesion, biofilm formation, and invasion in vitro, while reducing oxidative and preserving vaginal mucosal integrity in vivo. By disrupting fungal metabolic pathways and modulating host immune responses, SXC offers a novel approach to treating recurrent, drug-resistant VVC. Full article

Background: Large language models (LLMs) such as ChatGPT, Google Gemini, and Microsoft Copilot are increasingly used by patients seeking medical information online. While these tools provide accessible and conversational explanations, their accuracy and safety in emotionally sensitive scenarios—such as an incidental cancer diagnosis—remain uncertain. Objective: To evaluate the quality, completeness, readability, and safety of responses generated by three state-of-the-art LLMs to common patient questions following the incidental discovery of a kidney tumor. Methods: A standardized use-case scenario was developed: a patient learns of a suspicious renal mass following a computed tomography (CT) scan for back pain. Ten plain-language prompts reflecting typical patient concerns were submitted to ChatGPT-4o, Microsoft Copilot, and Google Gemini 2.5 Pro without additional context. Responses were independently assessed by five board-certified urologists using a validated six-domain rubric (accuracy, completeness, clarity, currency, risk of harm, hallucinations), scored on a 1–5 Likert scale. Two statistical approaches were applied to calculate descriptive scores and inter-rater reliability (Fleiss’ Kappa). Readability was analyzed using the Flesch Reading Ease (FRE) and Flesch–Kincaid Grade Level (FKGL) metrics. Results: Google Gemini 2.5 Pro achieved the highest mean ratings across most domains, notably in accuracy (4.3), completeness (4.3), and low hallucination rate (4.6). Microsoft Copilot was noted for empathetic language and consistent disclaimers but showed slightly lower clarity and currency scores. ChatGPT-4o demonstrated strengths in conversational flow but displayed more variability in clinical precision. Overall, 14% of responses were flagged as potentially misleading or incomplete. Inter-rater agreement was substantial across all domains (κ = 0.68). Readability varied between models: ChatGPT responses were easiest to understand (FRE = 48.5; FKGL = 11.94), while Gemini’s were the most complex (FRE = 29.9; FKGL = 13.3). Conclusions: LLMs show promise in patient-facing communication but currently fall short of providing consistently accurate, complete, and guideline-conform information in high-stakes contexts such as incidental cancer diagnoses. While their tone and structure may support patient engagement, they should not be used autonomously for counseling. Further fine-tuning, clinical validation, and supervision are essential for safe integration into patient care. Full article