Neuropeptide Y [NPY; encoded by the NPY gene] is a widely expressed 36-amino-acid neuropeptide that regulates neuronal function, vascular regulation, and immune regulation; its role in glioblastoma [GBM] remains incompletely characterized. We performed an integrative in silico multi-scale transcriptomic analysis combining bulk RNA-sequencing of IDH-wildtype GBM [n = 169] and lower-grade glioma [n = 510] surgical resections from TCGA, normal cortical tissue from GTEx [n = 207], and four independent GEO validation cohorts of surgical GBM and non-tumor brain specimens [GSE4290, GSE50161, GSE131928 scRNA-seq of ~20,426 cells from 28 patients, and GSE194329 10X Visium spatial transcriptomics from five patients], along with survival modeling, pathway enrichment, single-cell RNA sequencing, spatial transcriptomics, and cell-cell communication analysis. NPY and its principal receptor, NPY1R, were significantly downregulated in GBM, while genes associated with hypoxia, angiogenesis, invasion, and immune suppression were upregulated. Single-cell analysis showed that NPY-axis transcript expression was elevated in neural progenitor-like populations. In contrast, hypoxia and metabolic programs were concentrated in mesenchymal tumors and stromal compartments, indicating distinct cellular contexts. Spatial analysis revealed a weak and heterogeneous relationship between NPY and hypoxia signatures, with substantial inter-patient variability and no significant global spatial cross-correlation. These findings indicate that loss of NPY signaling is a consistent feature of GBM and is associated with hypoxia-driven tumor states, while the spatial relationship between NPY and hypoxia appears weak, heterogeneous, and patient-specific.

BACKGROUND:Cardiovascular disease (CVD) is the leading cause of global mortality, necessitating its early detection. Carotid intima-media thickness (CIMT) is a validated biomarker of CVD. In Saudi Arabia (SA), population-specific CIMT data for young adults are lacking. This pilot study aimed to generate single-institution preliminary CIMT data using the Butterfly iQ+ handheld ultrasound device (HHUD) and identify CVD risks. METHODS:A cross-sectional observational study was conducted on 63 medical students. CIMT was measured bilaterally on common carotid artery (CCA), using the Butterfly iQ+ HHUD. Data on sex, age, ethnicity, BMI, mean arterial pressure (MAP), family history, and dietary habits were collected and analysed using t-tests, one-way ANOVA, Chi-square tests, Spearman's rho (ρ) correlation, and stepwise multiple linear regression. RESULTS:Mean age was 19.19 ± 1.89 years, and mean BMI was 24.93 ± 4.72 kg/m2. Mean CIMT was 0.053 ± 0.006 cm. Males demonstrated thicker right CIMT (0.055 cm; 95% CI: 0.053-0.058 cm) than females (0.051 cm; 95% CI: 0.048-0.053 cm; mean difference: 0.005 cm, 95% CI: 0.001-0.008 cm; p = 0.012) and higher mean CIMT (0.0548 vs. 0.0513 cm; mean difference: 0.004 cm, 95% CI: 0.000-0.007 cm; p = 0.031). Height (ρ = 0.266; p = 0.035) and weight (ρ = 0.320; p = 0.011) correlated with right CIMT. Stepwise regression identified sex as the sole independent predictor (R2 = 0.105; F = 6.541; p = 0.013). CONCLUSIONS:This pilot study establishes preliminary single-institution CIMT data for young healthy medical students at a single university in Riyadh, Saudi Arabia. Sex, height, and body weight are key early determinants of carotid wall thickness. The Butterfly iQ+ HHUD is a feasible point-of-care tool for CIMT measurement, supporting community-based CVD screening in the region.

Gliomas, and particularly glioblastoma (GBM), remain among the most lethal primary brain tumors, with outcomes constrained by extensive intra tumor heterogeneity, a profoundly immunosuppressive tumor microenvironment (TME), and the restrictive nature of the blood–brain barrier (BBB). Although immunotherapies, including immune checkpoint inhibitors, chimeric antigen receptor (CAR) T and NK cells, and oncolytic virotherapy, have redefined treatment paradigms in other malignancies, their efficacy in gliomas has been modest, limited by low tumor mutational burden, antigenic plasticity, metabolic suppression, and therapy-associated immunosuppression. Recent advances in multi-antigen targeting, metabolic reprogramming, and innovative delivery strategies have enhanced preclinical efficacy, while the integration of emerging biomarkers such as ADAMTSL4, ACSS3, and radiomics-derived immune signatures offers opportunities for precision patient stratification. Converging developments in real-time molecular monitoring, spatial immunoprofiling, and rationally designed combination regimens hold the potential to recalibrate the glioma immune landscape, paving the way toward clinically impactful and durable immunotherapeutic responses.

Diabetes mellitus is primarily caused by the loss or malfunction of insulin-producing β-cells, and although current therapies improve glycemic control, they do not restore physiologic insulin secretion. Advances in stem cell biology and organoid engineering have led to the development of pancreatic organoids and induced pluripotent stem cell (iPSC)-derived β-cells as promising platforms for disease modeling, drug testing, and regenerative medicine. Pancreatic organoids generated from ductal, acinar, or progenitor populations can recapitulate key anatomical and functional features of native pancreatic tissue, enabling studies of development, injury, and regeneration. In parallel, improvements in iPSC differentiation protocols have produced β-like cells capable of insulin secretion in response to glucose, although achieving full functional maturity remains a challenge. Bioengineering strategies, including biomaterial scaffolds, microfluidic platforms, endothelial co-culture systems, three-dimensional bioprinting, and CRISPR-based genome editing, have enhanced the stability, vascular compatibility, and functional performance of both organoid and iPSC-derived systems. Despite these advances, variability in differentiation efficiency, limited β-cell maturity, and poor long-term survival continue to hinder clinical translation. Together, pancreatic organoids and iPSC-derived β-cells represent complementary platforms that advance fundamental research and support the development of β-cell replacement therapies, with ongoing integration of bioengineering approaches expected to accelerate progress toward reproducible, scalable, and clinically relevant β-cell regeneration.

Regulatory T cells (Tregs) are key mediators of immune tolerance and play a critical role in limiting excessive immune activation in conditions such as autoimmunity, transplantation, and graft-versus-host disease. Tregs are broadly classified into thymic-derived Tregs (tTregs) and peripherally induced Tregs (pTregs), which differ in lineage stability, epigenetic regulation, and functional plasticity. The suppressive function of tTregs is supported by stable expression of the transcription factor FOXP3, reinforced by demethylation of the Treg-specific demethylated region (TSDR). In contrast, pTregs are more susceptible to inflammatory cytokine signaling, which can destabilize FOXP3 expression and compromise suppressive function. Tregs employ multiple mechanisms of immune regulation, including CTLA-4-mediated inhibition of co-stimulatory signaling, cytokine modulation, metabolic interference, and, in certain contexts, granzyme-dependent cytotoxicity. Advances in cellular engineering have enabled the development of next-generation Treg therapies, including ex vivo expanded polyclonal Tregs, antigen-specific Tregs, and chimeric antigen receptor (CAR)-modified Tregs. Early-stage clinical and preclinical studies indicate that these approaches are feasible and exhibit favorable safety profiles in transplantation and immune-mediated diseases. This review summarizes current understanding of Treg biology, mechanisms governing lineage stability, and emerging strategies to enhance Treg specificity, persistence, and suppressive capacity, while highlighting remaining translational challenges.

BackgroundBiobanks play a significant role in the storage of biological samples for medical research, disease diagnosis at an early stage, treatment, and drug development. The research paper evaluates how medical students at Alfaisal University perceive and understand biobanking, as well as their level of ethical awareness. The study is a gap filler in the current literature base, as it reveals information about what Saudi medical students know and believe regarding biobanking.MethodsThe research employed a cross-sectional method where a survey was administered to medical students and interns at Alfaisal University, Saudi Arabia. A self-administered online questionnaire was used to collect the responses. The questionnaire included 30 questions divided into three subgroups: demographic, knowledge of the principle of biobanking, and perception and attitude towards biobanking. The validity of the questionnaire was evaluated in two directions, i.e., an expert review and a pilot test. The latter sample excluded those who were involved in the pilot stage. The sample size consisted of 457 students, with 72.2% being women and 40% being interns.ResultsThe mean of the knowledge scores was 3.93 (SD = 1.63), indicating an average knowledge level. 82.7% of the participants stated that biospecimen donation was a noble activity for society and medical research. 77.7% of the participants advocated for increased resource allocation to biobanking. The dangers of abuse, privacy invasion, and discrimination were brought up, with 81.8% expressing the need for restrictive regulation in medical research. 69.2% of the participants think that a researcher can ensure the interest of the participants, and 4.2% do not believe it is possible. A large proportion of the respondents reported that they would be concerned by the possibility of misuse of the sample (65.2%), confidentiality (64.8%), and discriminatory use (46.2%). Moderate knowledge concerning biobanking (mean = 3.93, SD = 1.63) was observed in the participants, but no significant correlation existed between the knowledge and the desire to contribute biospecimens.ConclusionMedical students at Alfaisal University are moderately informed about biobanking and are generally altruistic, although they also express serious ethical concerns about the utilization and safety of their information. Factual knowledge does not necessarily impact the decision to donate, and ethics, trust and positive attitudes should play a significant role in the encouragement of participation in biobanks. These findings highlight the importance of prioritizing open communication and strong ethical safeguards in biobanking ventures, as well as the integration of specialized biobanking education into medical education. This two-pronged approach is necessary to build trust and equip future medical practitioners with the opportunities to facilitate biobanking efforts in Saudi Arabia.

Breast cancer is the most common malignancy in women worldwide and is increasingly recognized as a biologically diverse disease shaped by both molecular and ancestral context. Women from the Middle East and North Africa (MENA) populations, including Saudi Arabia, often present at a younger age and with more aggressive subtypes such as HER2-positive and triple-negative breast cancer (TNBC) compared with Western cohorts. These clinical patterns reflect a distinctive genomic background marked by high consanguinity, founder mutations in key susceptibility genes, and population-specific somatic alterations that are not fully captured in global reference datasets. This review brings together current evidence on somatic, germline, transcriptomic, and epigenomic diversity in breast cancer across Western and MENA populations, with a focus on Saudi cohorts. Drawing on a previously published systematic review of more than 2,500 MENA breast cancer cases, TP53 accounted for approximately 24% and PIK3CA for roughly 10% of curated somatic mutation records pooled across 44 studies (proportions of mutation calls, not per-patient prevalence); in a separate single-center Saudi cohort, only 3.7% of patients underwent BRCA testing, and 37.5% of this clinically selected, testing-referred subgroup carried a pathogenic variant, a figure that should not be read as general-population BRCA prevalence. Variants of uncertain significance exceeded 20% across several regional genomic studies. We summarize conserved driver events, such as recurrent TP53 and PIK3CA mutations, while highlighting regional features, including unique stop-gain and loss-of-function variants, a high copy-number burden, and early-onset disease linked to ancestral architecture. We also discuss emerging data on MENA-specific regulatory signatures, including immune-enriched and basal-myo transcriptomic clusters, CIMP-like methylation patterns, and non-coding RNA networks; these associations are numerically suggestive in available cohorts but have not reached statistical significance in existing studies and warrant validation in larger, dedicated MENA/Saudi cohorts before being considered established determinants of treatment response and resistance. Finally, we examine the clinical implications of this diversity for biomarker development, pharmacogenomics, and access to targeted therapies, and outline practical steps toward ancestry-aware precision oncology in the region.

Nonalcoholic steatohepatitis (NASH) or metabolic dysfunction-associated steatohepatitis (MASH) is a long-term chronic liver disease condition that stems from nonalcoholic fatty liver disease (NAFLD) and results from multiple factors, including lifestyle, metabolic dysfunction, and genetic predisposition. The increasing prevalence of NAFLD in the global population is expected to reach over 35% by 2030. It thus has become a significant public health concern because of its association with metabolic syndrome, cardiovascular diseases, diabetes mellitus, and hepatocellular carcinoma. Therefore, early diagnosis is crucial to avoid further liver disease complications and to provide early and effective patient care. Though there are diagnostic measures available for NASH/MASH detection, like biopsy and serological assays, these are mostly invasive and do not provide the complete picture of the liver condition. Point-of-care diagnostics like biosensors can help overcome these limitations by allowing for a rapid, inexpensive, and more straightforward diagnostic method that also aligns with the present global health needs. Moreover, integrating artificial intelligence and machine learning approaches for automated analysis alongside real-time cloud-based reporting and telehealth interfaces can potentially aid in expanding the utility of these systems into integrated diagnostic systems. Through this review, we aim to address the interplay of technological innovation, public health significance, and implementation barriers in advancing biosensor diagnostics for effective and reliable detection of NASH/MASH for better liver health.

Extracellular matrix (ECM) detachment is crucial for metastasis in cancer cells. During tumorigenesis, a programmed cell death occurs to clear off the ECM detached cancer cells in the circulatory system; this phenomenon is referred to as anoikis. Metastatic cancer cells can evade anoikis by regulating mechanisms such as cell adhesion, cell growth, oxidative stress, cancer stemness, hypoxia and metabolic reprogramming. Studies have shown that RNA modifications regulate multiple cancer mechanisms; however, the role of RNA modifications in anoikis resistant is not established yet. Therefore, in this study, we assessed the role of N6-methyladenosine (m6A) modification of mRNAs in anoikis resistant conditions. First, we cultured cancer cells in low adhesive plates for six (6) days followed by quantitative real-time PCR (qRT-PCR) of major m6A regulators and quantification of the global m6A levels in detached versus attached cancer cells. We also assessed cell proliferation in detached cancer cells using STM2457, a potent and specific METTL3 inhibitor. Our results showed a significant (p < 0.05) increase in METTL3 expression and activity in anoikis resistant cancer cells. Furthermore, we observed an elevation in global m6A levels on mRNAs. Treatment of anoikis resistant cancer cells with STM2457 caused reduction in spheroid size, induction of apoptosis, and cell cycle arrest which were correlated with a decrease in global m6A levels. Conclusively, our findings reveal that METTL3-dependent m6A methylation sustains the survival and proliferation of anoikis-resistant cancer cells, highlighting an epitranscriptomic mechanism underlying metastatic fitness.

BACKGROUND:Gliomas are characterized by a high degree of molecular heterogeneity, which impairs the reproducibility of predictive biomarkers derived from bulk-based molecular profiling due to immune/stromal contamination of tumors and the high prevalence of the IDH mutation signature. METHODS:In this study, we used MOFA+ to derive intrinsic molecular signatures from transcriptional, methylation, and genomic profiles of a cohort of 667 diffuse gliomas in the Cancer Genome Atlas database. Thereafter, factor scores were derived for two separate Chinese Glioma Genome Atlas batches (Batch 1, n = 325; Batch 2, n = 693) without any retraining on the model. The prognostic independence of identified molecular signatures was assessed using multivariable Cox regression adjusted for IDH mutation status and tumor purity; purity-residualized survival analyses; IDH-stratified Cox regression in each cohort; validation by concordance index against established molecular signatures; and survival extreme profiling. To characterize the biological significance of factor signatures, we projected gene set signatures corresponding to each factor signature onto a single-cell RNA-seq dataset of GBM (GSE131928). RESULTS:MOFA+ identified 12 latent factors, of which a vascular-extracellular matrix (ECM) remodeling axis (Factor 1) explained the highest multi-omics variance (24.9%) and was the strongest independent prognostic factor. In multivariable Cox regression adjusting for IDH status and tumor purity, Factor 1 remained independently prognostic (HR = 1.67, 95% CI 1.27-2.20, p = 0.0002); in a fully-adjusted model additionally including age, WHO grade, MGMT methylation, and 1p/19q codeletion (plus radiotherapy and chemotherapy status in the CGGA cohorts), Factor 1 remained prognostic in both CGGA cohorts (CGGA1: HR = 1.50, p = 3.8 × 10-5; CGGA2: HR = 1.18, p = 0.003) but lost significance in TCGA (HR = 1.04, p = 0.83), consistent with the cohort-dependent magnitude reported in the IDH-stratified and meta-regression analyses below. Purity-residualized survival analysis showed negligible attenuation of the Factor 1 signal (raw HR = 3.57 vs. residualized HR = 3.72; concordance 96.5%). Within IDH-wildtype gliomas, Factor 1 was significant in both external validation cohorts (CGGA1: HR = 1.64, FDR = 4.6 × 10-6; CGGA2: HR = 1.20, FDR = 0.02), though the TCGA IDH-wildtype subgroup showed a trend that did not survive FDR correction (FDR = 0.060). All validation was performed without model retraining. Within IDH-mutant gliomas, Factor 1 was strongly prognostic in both CGGA cohorts but was not significant in TCGA (HR = 1.17, FDR = 0.33). These findings should therefore be interpreted as consistent in directionality across cohorts but not uniformly replicated at the FDR-adjusted significance threshold in the TCGA discovery dataset. Concordance index benchmarking on a matched subset (n = 503) showed Factor 1 achieved discrimination comparable to the Mesenchymal signature (C = 0.797 vs. 0.801; ΔC = -0.004) while outperforming four other established classifiers. Factor 1 consistently separated patients with extreme survival phenotypes (OS < 6 vs. >15 months) across all three cohorts (all log-rank p < 0.001). Projection onto a single-cell GBM atlas (GSE131928), supported by inferCNV-based malignant-cell classification, localized the Vascular-ECM program to malignant cells and the Immune-ECM axis to myeloid compartments. CONCLUSIONS:The Vascular-ECM axis is a consistent, prognostic program robust to purity adjustment for diffuse gliomas that remains relevant across IDH-defined subgroups in three independent datasets comprising 1685 patients. The Vascular-ECM axis is a reproducible, purity-robust prognostic program in diffuse glioma, with directionally consistent adverse effects across TCGA, CGGA Batch 1, and CGGA Batch 2 (pooled n = 1685). Given the strong co-loading of endothelial, ECM, and myeloid genes observed in the single-cell projection, Factor 1 is best interpreted as a vascular/ECM-associated tumor-microenvironment ecosystem program rather than a malignant-cell-autonomous signature. Its FDR-adjusted significance within IDH-stratified subgroups is cohort-dependent and robust in both CGGA cohorts but attenuated in the TCGA IDH-wildtype (FDR = 0.060) and TCGA IDH-mutant (FDR = 0.33) strata. The pooled signal should therefore be interpreted as evidence of a generalizable biological program rather than a uniformly replicated subgroup-specific biomarker. It is possible to calculate factor scores based on RNA sequencing alone using fixed loadings (Z = XWᵀ), which may have implications for future translational applications. All findings are correlative; a causal role for the Vascular-ECM program in glioma progression, invasion, or therapy resistance remains to be established through functional perturbation experiments.

This study examines the effect of various prompting strategies on ChatGPT's ability to interpret histological images across different tissue types and varying question complexities. GPT-4o's performance was assessed using three distinct prompting techniques: P1 (zero-shot), P2 (few-shot with examples), and P3 (chain-of-thought with reasoning explanations) across 120 histological images of four tissue types (epithelial, connective, muscular, and neural). Three standardized questions assessed tissue recognition, structural identification, and functional assessment. GPT-4o demonstrated a noticeable variation in performance across tissue types (p < 0.001, η2 = 0.042). Question complexity significantly affected performance (p < 0.001, η2 = 0.022), revealing a hierarchical pattern in which structural identification proved most challenging across all conditions. Error dependency analysis revealed that 98% of functional assessment errors co-occurred with structural identification errors, indicating strong cascading effects. Inter-rater reliability remained consistently high across all conditions (ICC = 0.95-0.96). Across prompting approaches, answer accuracy ranged from 58.9% (P1) to 63.6% (P3), with modest or nonsignificant effects of prompt type (p = 0.116, η2 = 0.004). This study demonstrates that GPT-4o's performance in histological image interpretation varies significantly across tissue types and question complexity. Tissue-specific approaches and a focus on structural identification accuracy are essential for effective educational integration, whereas prompt engineering alone yields limited performance gains.

Objectives: Breast cancer (BC) subtypes such as HR+, HER2+, and triple-negative (TNBC) show distinct molecular features, treatment responses, and outcomes. DNA methylation is a key, targetable epigenetic regulator in BC. This study examined whether the DNA methyltransferase inhibitor decitabine (DAC) produces subtype-specific epigenomic and transcriptional effects in breast cancer cell lines representing distinct molecular subtypes. Methods: Gene expression and DNA methylation data from DAC-treated and untreated T-47D (Luminal-A) and JIMT-1 (HER2-amplified, trastuzumab-resistant with a TNBC-like phenotype) breast cancer cell lines were obtained from a published dataset. Differential expressions were assessed using limma , and methylation changes were defined using β-value thresholds. Integrated epigenomic–transcriptional analysis, functional enrichment, Horvath clock CpG evaluation, and survival analysis were performed in the METABRIC and TCGA cohorts. Results: In JIMT-1, DAC caused hypomethylation at 1195 CpG sites and upregulation of 187 genes, including TFAP2E , an age-associated locus selectively hypomethylated after DAC. In T-47D, DAC induced hypomethylation at 1937 CpGs and upregulated 248 genes. Amongst these, KRT20 was upregulated despite promoter hypermethylation, indicating a subtype-specific regulatory architecture. DAC-responsive genes in JIMT-1 were enriched for cytokine signaling and piRNA-mediated epigenetic silencing, whereas T-47D showed enrichment for extracellular matrix organization, collagen dynamics, and piRNA processing pathways. Horvath clock CpG analysis showed selective perturbation of age-associated sites. Survival analysis identified 114 DAC-responsive genes associated with overall survival in ER/PR-positive BC and 8 in the JIMT-1-derived gene set. Conclusion: DAC induces subtype-dependent epigenomic and transcriptional remodeling, selectively disrupts age-associated regulatory programs, and underscores the need for subtype-stratified evaluation of epigenetic therapies in breast cancer.

Background/Objectives: Glioblastoma (GBM) is the most lethal primary brain malignancy in adults, with a median overall survival of approximately 15 months. Temozolomide (TMZ) resistance develops in virtually all patients, and no second-line regimen has improved outcomes over the past two decades. The DNA methyltransferase inhibitor decitabine (DAC) has attracted interest as a chemosensitizer, but whether it directly reverses the TMZ-resistance transcriptome or operates through distinct, complementary mechanisms has not been tested at multi-omics resolution. Methods: We performed an integrative six-layer multi-omics analysis across five public GEO datasets (bulk RNA-seq, EPIC 850K methylation, and 21,676 single cells) re-purposed from studies conducted for unrelated aims, formally tested DAC-mediated reversal of the TMZ-resistance transcriptome across 11,707 genes, mapped pharmacogenomic targets with DGIdb v5, and built an exploratory, hypothesis-generating 11-gene prognostic model internally validated in TCGA-GBM (n = 166) and externally tested in the independent CPTAC-GBM cohort (n = 96). Results: DAC reprogrammed transcription across 1114-1882 differentially expressed genes per cohort and reactivated 146 direct epigenetic targets, identifying INPP5D/SHIP1 as the top-ranked direct epigenetic-reactivation target. Genome-wide reversal analysis across 11,707 co-detected genes showed a negligible effect (Spearman ρ = 0.073), but single-cell analysis revealed significant per-cell attenuation of MES-like and stem-like programs (Δ = -0.071 and -0.135, respectively; both p < 0.001). The 11-gene risk model achieved a Harrell's C-index of 0.706 (apparent); after correcting for the two-stage gene selection with a full-pipeline bootstrap, the optimism-corrected C-index was 0.63, and external validation in an independent cohort (CPTAC-GBM, n = 96) showed only near-chance discrimination (C-index 0.55), indicating that the signature does not generalize and is exploratory. Pharmacogenomic mapping yielded 734 unique therapeutic agents (230 FDA-approved) across 69 druggable targets after excluding AR. Most of these agents are not GBM-directed, so this catalog-level mapping is hypothesis-generating rather than a set of therapeutic recommendations. Conclusions: DAC does not broadly reverse the TMZ-resistant transcriptome but acts through three complementary mechanisms: epigenetic reactivation of INPP5D/SHIP1, cancer-testis-antigen and type I interferon induction, and per-cell attenuation of mesenchymal-stem-like transcriptional intensity, supporting hypotheses for rationally designed DAC-based combination therapy in TMZ-resistant GBM.

Exosomes are small, nanoscale extracellular vesicles that facilitate intercellular communication through the transport of proteins, lipids, and nucleic acids. Recent advances in utilizing exosomes as promising vehicles for targeted delivery have opened up numerous opportunities for establishing next-generation exosome-based nanocarriers and therapeutics for multiple biomedical domains. Their inherent biocompatibility, low immunogenicity, nanoscale size and ability to naturally cross biological barriers make them promising alternatives to traditional synthetic drug-delivery systems such as liposomes and polymeric nanoparticles. In this review, we analyzed existing literature and provided an overview of biogenesis, molecular composition, and functional diversity of exosomes followed by a review of recent reports on their application in regenerative therapies and immunomodulation. First, we outlined the role of exosomes in angiogenesis, tissue repair, and immunomodulation. Next, we critically evaluated existing engineering solutions, including isolation techniques, cargo-loading approaches, genetic programming of donor cells, and surface functionalization strategies. Furthermore, we provided a comprehensive overview of recent research on engineered systems that enable controlled release, stability, and multifunctional design of therapeutics, such as exosome–biomaterial hybrids, synthetic exosome mimics, and exosome–nanoparticle platforms. Finally, we highlighted the significant barriers, such as vesicle heterogeneity, optimized production and standardization, and other regulatory challenges in translating exosomal therapeutics from basic research to clinical practice.

Antibody-drug conjugates (ADCs) have transitioned from clinically marginal agents into a defining therapeutic class for solid tumor oncology. In DESTINY-Breast03, trastuzumab deruxtecan achieved a four-fold progression-free survival advantage over trastuzumab emtansine, attributable not to antibody engineering but to the linker-payload axis: a cleavable peptide linker and a topoisomerase I payload with bystander activity. Sacituzumab govitecan extends the same logic to Trop-2-positive disease via extracellular payload release, and the framework now spans breast, urothelial, gynecologic, lung, gastric, and colorectal cancers, with enfortumab vedotin plus pembrolizumab displacing platinum chemotherapy as first-line therapy for urothelial cancer in EV-302 (median overall survival 31.5 versus 16.1 months). This review synthesizes ADC biology along three analytical axes. The mechanistic axis links each linker-payload-DAR configuration to a specific tumor-biology barrier: vascular limitation, which delivers approximately 0.1% of the administered dose to tumor tissue; the binding-site barrier, which concentrates exposure at the perivascular margin; and antigen mosaicism, which defeats internalization-dependent killing. The translational axis examines resistance as a coordinated failure across antigen modulation, trafficking, efflux, apoptotic execution, and lysosomal processing. The clinical axis traces the platform’s migration toward earlier-line and curative-intent settings. We close by examining whether the ADC delivery architecture translates to precision immunosuppression in autoimmune disease, where the glucocorticoid receptor modulator ADC ABBV-154 met placebo-controlled efficacy endpoints in rheumatoid arthritis but was discontinued because its benefit-risk profile did not differentiate it from existing biologic therapies.

Visual identification of anatomical structures is a foundational skill in gross anatomy education. Whether multimodal large language models (LLMs) can reliably perform this task, and whether prompt engineering can meaningfully improve their accuracy, remains insufficiently investigated This cross-sectional comparative study evaluated four leading multimodal LLMs (GPT-5.2, Claude Sonnet 4.6, Gemini 3, and Grok 4) on their ability to identify anatomical structures across cadaveric dissection images. A total of 75 expert-validated anatomical structures spanning five body regions (abdomen, head and neck, lower limb, thorax, and upper limb) were evaluated using three prompt strategies: zero-shot (P0), few-shot (PF), and chain-of-thought (PCoT). Each prompt strategy was administered across three independent sessions conducted in April-May 2026, yielding 675 binary-scored responses per model (2700 total responses). Gemini 3 achieved the highest overall accuracy (67.3%), followed by GPT-5.2 (41.9%), Claude Sonnet 4.6 (27.3%), and Grok 4 (23.0%)-an ordering that inverts the hierarchy typically observed in text-based anatomy assessments, where GPT-4o has generally led, and Gemini has ranked lower. Gemini 3 significantly outperformed all other models (all Bonferroni-corrected p < 0.001). Prompt strategy had a statistically significant effect for Gemini 3 (PCoT > PF, p = 0.015) and Grok 4 (PCoT > P0, p = 0.023); no significant prompt effect was observed for GPT-5.2 or Claude Sonnet 4.6. Performance varied substantially by anatomical region: the abdomen consistently yielded the highest accuracy across all models, while the lower limb yielded the lowest. Inter-trial consistency was high (70.7%-89.3%) but dissociated from accuracy, as some models produced reproducibly incorrect responses. Current multimodal LLMs, accessed via consumer interfaces, are insufficient for reliable standalone identification of cadaveric anatomical structures. Gemini 3, when used with chain-of-thought prompting, may serve as a supplementary aid in select anatomical regions; however, critical educator supervision and verification against authoritative anatomical resources remain essential before any clinical or educational deployment.

Background: Gene expression and cellular identity are regulated by epigenetics that occurs through chromatin modifications, RNA changes, chromatin accessibility, and three-dimensional genome organization. Although DNA methylation has been the focus of most epigenetics studies in the past, other non-methyl epigenetic processes, including histone post-translational modifications (PTMs), epitranscriptomic marks, and chromatin remodeling, are dynamic, reversible, and context-dependent, and thus are difficult to accurately interrogate using endpoint sequencing-based assays, especially in heterogeneous tissues, developing systems, and therapeutic response environments. Scope and Approach: The present review discusses epigenetic modifications other than DNA methylation regarding sensor-based technologies that can measure live, dynamic, and spatially resolved measurements. Epigenetic sensors include any genetically encoded sensors (GECs) based on resonance energy transfer, CRISPR/dCas-derived sensors, or aptamer-based sensors, and hybrid biochemical/imaging sensors that can be used in live or semi-live settings. It lays emphasis on the technologies, which have been developed recently, that allow real-time kinetic measurements, working in three-dimensional and organoid models, and being applied to disease-relevant perturbations. On these platforms, performance properties such as specificity, sensitivity, spatial and temporal resolution, ability to perform dynamic versus locus-specific interrogation, and perturbed endogenous chromatin states are compared. Key Conclusions and Outlook: Together, these sensing strategies are complementary to the traditional methods of measuring epigenomics in that they show epigenetic dynamics unobservable with static measurements. We list the important technical issues, including specificity, quantitation, multiplexing, and chromatin perturbation, and report the barriers and solutions in development and design. Lastly, we provide a conceptual map of how live epigenetic sensing and multi-omics and translational models can be integrated, and how the two methodologies can be used to develop functional epigenetics and guide disease modeling and drug development.

Serum albumin (SA) is a highly water-soluble plasma protein essential for maintaining physiological homeostasis. It plays a crucial role in supporting liver and kidney function and regulating plasma osmolality. Reduced SA levels are frequently linked to liver failure and chronic hepatitis, emphasizing the urgent need for low-cost, accurate, and rapid methods for SA analysis. In this study, we have developed a fluorescent probe, triphenylamine derivative substituted with rhodanine-3-acetic acid (mRA),that exhibits a robust fluorescence response upon binding to bovine serum albumin (BSA). mRA is a bifunctional molecule containing both electron-rich and electron-deficient moieties, enabling strong intramolecular charge transfer (ICT)-mediated emission characteristics. mRA displays negligible fluorescence in aqueous solution. While it bind to BSA binding pocket, it restricts the intramolecular rotation, resulting in a significant increase in fluorescence intensity. A BSA concentration-dependent fluorescence enhancement was observed in the range of 0.01 to 300 μg/mL, with a detection limit as low as 8 ng/mL. This proof-of-concept was validated using BSA-spiked samples. Additionally, demonstrate that mRA can monitor BSA consumption/degradation in cell culture. The observed fluorescence recovery supports the effectiveness of this detection strategy as a viable alternative to conventional techniques. Moreover, this approach holds strong potential for the development of point-of-care diagnostic tools for detecting liver diseases.

Background/Objectives: Gliomas arise from distinct subgroups driven by different genetic alterations. Gain-of-function mutations in isocitrate dehydrogenase 1/2 (IDH1/2) are frequent in a subset of gliomas and are associated with improved survival compared with wild-type tumors. IDH-mutant gliomas can be classified as having the CpG island methylator phenotype (G-CIMP), which is characterized by widespread epigenetic changes associated with IDH1 mutations. G-CIMP-based stratification provides an added improvement in glioma classification when considered alongside grade and histology. Despite the success of G-CIMP-based stratification in predicting outcome in some patients, it does not fully account for non-responders, largely due to heterogeneity within G-CIMP gliomas. Methods: Using a The Cancer Genome Atlas (TCGA) glioblastoma, IDH-wildtype discovery cohort, we identified gene-level DNA methylation and expression patterns associated with clinical outcomes, including epigenetically regulated genes such as TUBB2A and TM4SF1. Results: In an independent TCGA diffuse glioma validation cohort enriched for IDH-mutant tumors, canonical IDH-defined G-CIMP classification was applied, and promoter methylation of TUBB2A and TM4SF1 showed significant associations with overall survival. Conclusions: These findings highlight molecular heterogeneity within IDH-defined G-CIMP gliomas and demonstrate that gene-specific methylation events can refine prognostic stratification beyond IDH status alone.

Organ: and organoid-on-a-chip (OoC) platforms provide microengineered human tissue models that reproduce key physiological features such as perfusion, mechanical cues, and multicellular interfaces while remaining compatible with established gene expression profiling (GEP) techniques. This review examines how conventional transcriptomic methods, including qPCR, microarrays, and bulk and single-cell RNA sequencing, are integrated with OoC systems and how microphysiological control reshapes the interpretation of gene expression data beyond static culture conditions. Representative applications across major organ systems are synthesized to illustrate how chip design parameters (cell source, architecture, flow, mechanical stimulation, and exposure route) influence transcriptional programs associated with disease phenotypes and drug responses. Rather than presenting OoC-derived gene signatures as stand-alone predictors, we emphasize their value as mechanistic endpoints that link controlled environmental perturbations to pathway-level biological responses. The analysis highlights both advantages, such as time-resolved sampling, improved contextual relevance, and reduced reliance on animal models, and persistent challenges, including device-to-device variability, low-input RNA handling, limited interlaboratory reproducibility, and incomplete standardization. Finally, emerging directions are discussed, including multi-organ integration, patient-specific iPSC-derived models, AI-assisted data analysis, and growing regulatory interest in New Approach Methodologies (NAMs) for safety and efficacy decision support. Together, these developments position OoC-coupled GEP as a promising but still maturing approach for translational research and personalized medicine.