Search Results (190)

Complex diseases often involve distributed interactions among biological regions, physiological systems, imaging phenotypes, and clinical variables that are not fully captured by anatomical proximity, isolated biomarkers, or conventional feature-based representations. In oncology, neuroimaging, critical care, and systems medicine, distant or apparently separate biomedical sectors may show strong statistical or functional coupling associated with multimodal imaging signatures, inflammatory responses, metabolic constraints, treatment-induced changes, or shared disease-state organization. In this work, we introduce a proof-of-concept relational graph framework for representing such candidate hidden connectivity in terms of correlation-induced accessibility bridges. The novelty of the framework is that it does not treat biomedical correlation, graph distance, and network connectivity as separate descriptors but explicitly couples non-factorizable inter-sector correlation to localized accessibility compression in an emergent disease-state geometry. The proposed framework represents a biomedical system as a weighted relational graph in which nodes correspond to clinically relevant entities, such as tissue regions, imaging-derived features, biomarker modules, physiological variables, or disease states, while weighted edges encode constraints on functional, statistical, or pathological accessibility. Within this structure, coarse-grained biomedical sectors are defined as organized subsystems, and non-factorizable coupling between sectors is quantified using mutual-information-type measures. Candidate biomedical bridges are then defined operationally as localized, high-gain reductions in effective inter-sector accessibility distance. We introduce explicit coupling rules linking sector-level correlation to bridge-specific accessibility compression, including an effective distance-compression model and an ensemble-based formulation. Numerical proof-of-concept simulations on randomized modular graph ensembles show that increasing correlation strength systematically reduces effective inter-sector distance and increases bridge gain. The strongest compression occurs when correlation modulates a designated bridge architecture, exceeding the effects observed under random non-bridge or generic inter-sector modulation. These simulations are not intended to validate a disease-specific biological mechanism but to test whether the proposed correlation–compression rule produces bridge-specific effects distinguishable from null graph perturbations. The resulting structures should not be interpreted as physical anatomical tunnels or direct causal pathways unless supported by additional biological evidence. Rather, they represent correlation-induced accessibility bridges: localized, high-gain routes in a patient- or disease-specific relational geometry. The framework may therefore provide a theoretical and computational basis for prioritizing candidate hidden connectivity patterns in radiomics, multimodal prognosis, physiological deterioration, recurrence modeling, and systems-level disease networks. Full article

Biomass-derived porous carbons are promising supercapacitor electrodes, but their electrochemical performance is often limited by the trade-off between activation-induced pore formation and heteroatom retention. In this work, algae biomass was used as an intrinsic N/O/S-containing precursor to prepare self-nitrogen-doped hierarchical porous carbon by pre-carbonization followed by controlled KOH activation. A temperature-, dosage- and time-dependent sample library was constructed to correlate activation conditions with textural properties, nitrogen configuration, wettability, charge-transfer resistance and electrochemical behavior. The optimized AHPC-850 sample exhibits a BET surface area of 1486 m² g⁻¹, a total pore volume of $0.96$ cm³ g⁻¹, a retained surface nitrogen content of 2.91 at.%, and a charge-transfer resistance of $0.41$$\Omega$. In a three-electrode configuration, AHPC-850 delivers 386 F g⁻¹ at 1 A g⁻¹ and retains 62.4% of its capacitance at 20 A g⁻¹. During 10,000 cycles at 10 A g⁻¹, the electrode maintains 96.3% capacitance retention with a stable coulombic efficiency above 98.8%. A symmetric aqueous device based on AHPC-850 achieves an energy density of $24.8$ Wh kg⁻¹ at 250 W kg⁻¹. These results indicate that algae-derived carbon can be improved by balancing pore accessibility, nitrogen retention and transport resistance rather than by maximizing surface area alone. Full article

Large carrier frequency offsets (CFOs) can severely distort the correlation response of the Physical Random Access Channel (PRACH), generating multiple significant peaks even for a single transmitting user equipment (UE), such that CFO-induced pseudo-peaks may exceed the detection threshold and be erroneously identified as valid peaks. This work addresses the problem of peak disambiguation under such conditions by formulating peak selection as a model-consistency validation problem under mismatch. A generalized likelihood ratio test (GLRT) is first formulated to provide a principled statistical validation of each detected candidate peak based on the estimated timing advance (TA) and CFO parameters. While theoretically grounded, this approach is shown to be insufficient under realistic large-CFO conditions, where CFO-induced peak ambiguity is further complicated by multipath-induced model mismatch. To address this limitation, a complementary residual-energy-based criterion is introduced, along with a weighted combination of both metrics, interpreted as a penalized consistency criterion for robust peak selection under model mismatch. The proposed framework enables the selection of a single reliable TA/CFO pair among multiple candidates, improving receiver robustness and reducing spurious updates. Performance is evaluated using precision, recall, and F1-score for both short and long PRACH formats under 3GPP-aligned channel models, including high-CFO and high-Doppler scenarios. Results demonstrate that the proposed weighted strategy generally provides a more robust trade-off than the individual GLRT-only and residual-only criteria. Full article

Cold stress is a critical abiotic factor that severely limits plant growth and agricultural productivity in subtropical regions. Poncirus trifoliata exhibits exceptional cold hardiness and is widely used as a rootstock in Citrus. However, the key genes and mechanisms conferring this resilience remain largely unexplored. Here, we characterized PtCOR8, a cold-induced gene isolated from P. trifoliata. Phylogenetic and subcellular localization analyses confirmed that PtCOR8 encodes a plasma membrane-localized protein belonging to the WCOR413 family. Functional validation revealed that heterologous overexpression of PtCOR8 in tomato significantly enhanced cold tolerance, concomitant with reduced malondialdehyde (MDA) content, elevated peroxidase (POD) activity, and upregulation of cold-responsive genes (e.g., CIN8). Notably, expression profiling of COR8 in 16 citrus accessions under natural overwintering conditions indicated a strong positive correlation between its expression level and cold tolerance of different genotypes. Transgenic tomato plants with PtCOR8 driven by its native promoter also presented enhanced cold tolerance, confirming that the native promoter is sufficient to drive functional expression under cold stress in the tomato system. Through promoter deletion and β-glucuronidase (GUS) staining experiments, the ATCT motif was further identified as a cis-acting element capable of mediating cold-induced promoter activity. Our findings uncover a dual-layered mechanism in which the PtCOR8 protein alleviates membrane lipid peroxidation and oxidative damage, while its transcription level is precisely modulated by a novel promoter regulatory mechanism, thereby improving freezing tolerance. This study provides important genetic insights and a valuable gene resource for cold-resistant citrus breeding. Full article

Background/Objectives: Transradial access (TRA) is the preferred route for coronary catheterization, yet its consequences for radial artery vasoreactivity and hemodynamic parameters remain incompletely characterized. We prospectively quantified TRA-induced functional impairment, its clinical determinants, and the association of baseline parameters with post-procedural outcomes. Methods: Ninety-four consecutive patients undergoing elective TRA were assessed at baseline, 24 h, and one month using high-resolution Doppler ultrasound. Nine vascular parameters were measured: flow-mediated dilation (FMD), nitroglycerin-mediated dilation (NMD), peak systolic velocity (PSV), resistive index (RI), pulsatility index (PI), resting and hyperemic velocity-time integral, hyperemic blood flow volume, and lumen diameter. Non-parametric methods were applied throughout. Results: FMD declined at 24 h (−31.2%; p < 0.001) and showed no significant recovery at one month (p = 0.08 vs. 24 h). NMD showed a greater acute decline (−36.6%; p < 0.001) with partial but statistically significant recovery at one month (p < 0.001). PSV recovered fully by one month; RI fell below baseline, consistent with compensatory microvascular vasodilation. Radial artery lumen diameter remained significantly below baseline at one month. Radial artery occlusion occurred in 4 patients (4.3%), all with spontaneous recanalization. Female sex was selectively associated with greater NMD reduction (ΔNMD −8.3% vs. −5.8%; p = 0.005) without a statistically significant FMD difference (p = 0.40). Older age correlated with impaired FMD recovery at one month (ρ = −0.62; p < 0.001) but not with NMD outcomes. Baseline PSV demonstrated the highest discriminatory performance for significant FMD decline (AUC = 0.73). Conclusions: TRA causes multidomain, persistent radial artery functional impairment at one month, with distinct recovery trajectories for endothelial and smooth muscle function. Female sex and advanced age are selective determinants of injury and recovery, respectively. A pre-procedural phenotype comprising baseline diameter, PSV, RI, and age is associated with post-procedural outcomes and supports further investigation of pre-procedural phenotyping as a candidate framework for risk stratification. Full article

We introduce a minimal relational network model in which superconducting-like behavior emerges as a collective phase of constrained connectivity and phase coherence, without assuming microscopic electrons, phonons, or material-specific interactions. The model is formulated as a concrete instantiation of a previously introduced axiomatic relational–informational framework for emergent geometry and effective spacetime, in which geometry and effective forces arise from constrained information flow rather than from a background manifold. Mathematically, this construction is realized on a finite weighted graph with binary edge-activation variables and compact vertex phase variables, sampled through a Gibbs ensemble generated by an additive informational action. The system is represented as a finite weighted graph with weighted edges encoding transport or informational costs, augmented by dynamically activated low-cost channels and compact phase degrees of freedom defined at vertices. The effective edge costs induce a weighted shortest-path metric, providing an operational notion of emergent relational geometry. Using Monte Carlo simulations on two-dimensional periodic lattices, we show that the same informational action supports three distinct emergent regimes: a normal resistive phase, a fragile low-temperature-like superconducting phase characterized by noise-sensitive coherence, and a noise-robust high-temperature-like superconducting phase in which global phase coherence persists under substantial fluctuations. These regimes are identified using purely relational observables with direct graph-theoretic and statistical-mechanical interpretation, including percolation of low-cost channels, phase correlation functions, an operational phase stiffness (helicity modulus), and a geometric diagnostic based on relational ball growth. In particular, we extract an effective geometric dimension from the scaling of low-cost accessibility balls, using a ball-growth relation of the form $⟨B\left(r\right)⟩ ~ r^{d_{eff}}$, revealing a clear monotonic hierarchy between normal, fragile superconducting, and noise-robust superconducting—like regimes. This demonstrates that superconducting-like behaviour in the present framework corresponds not only to percolation and phase alignment, but also to a qualitative reorganization of relational geometry. Robustness is tested via finite-size comparison between 8 × 8, 12 × 12 and 16 × 16 lattice realizations. Within this framework, normal and superconducting-like behavior arise from the same underlying relational mechanism and differ only in the structural stability of connectivity, coherence, and geometric accessibility under fluctuations. The aim of this work is structural rather than material-specific: we do not reproduce detailed experimental phase diagrams or microscopic pairing mechanisms, but identify minimal relational conditions under which low-dissipation, phase-coherent transport can emerge as a generic organizational regime of constrained relational systems. Full article

Polyhydroxyalkanoates (PHAs) emerge as promising biodegradable polymers for sustainable applications, yet predicting their biodegradation behavior under different environmental conditions remains challenging. In this study, we propose a novel data-driven computational framework for predicting biodegradation-induced weight/mass loss in PHA-based materials. A comprehensive database of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV)-based formulations was manually curated by systematically collecting and harmonizing material descriptors, environmental parameters, and experimental biodegradation outcomes from laboratory- and large-scale studies conducted in soil, marine, freshwater, and compost environments. Multiple regression-based quantitative structure–activity relationship (QSAR) models were developed and rigorously validated, demonstrating high predictive performance and strong correlations between polymer structure, environmental conditions and degradation behavior. “Exposure time”, “degradation environment” and “hydroxybutyrate (HB) ratio” were identified as the most important features for weight loss. Finally, the predictive model was integrated into the Jaqpot computational platform, enabling open access and facilitating data-driven assessment and design of biodegradable polymer systems. Full article

Open-heart surgery with cardiopulmonary bypass (CPB) is a high-risk procedure with significant morbidity and mortality. CPB, tissue injury, blood loss, endotoxemia and ischemia–reperfusion injury induce a pronounced systemic inflammatory response, leading to endothelial glycocalyx (EG) damage and vascular endothelial dysfunction. Consequently, immune cells, reactive oxygen species, and enzymes gain free access to vascular endothelial cells, resulting in their dysfunction and enhancing inflammation, vascular permeability, and microvascular impairment. EG degradation is most commonly assessed by measuring the circulating levels of its degradation products. Additionally, CPB triggers an early inflammatory response that is characterized by the secretion of interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor alpha, and IL-18, which play roles in initiating the process of EG injury. EG damage is further propagated by the sustained release of cytokines, inhibiting the regeneration of the glycocalyx layer. Heparanase and matrix metalloproteinases are enzymatic pathways involved in cytokine-mediated EG degradation after cardiac surgery, and the balance between the pro- and anti-inflammatory cytokines determines the magnitude and duration of the inflammatory response and EG impairment, which correlates with adverse clinical outcomes, including myocardial dysfunction, acute lung and kidney injury, neurological complications, and prolonged need for intensive care. Thus, identifying patients with an exaggerated cytokine response could potentially provide more personalized therapy based on the circulating biomarkers of EG shedding, and cytokine-directed preservation of EG represents a promising therapeutic strategy in vascular dysfunction prevention during and after open-heart surgery. In this review, we summarize the current knowledge on cytokine-mediated EG impairment following open-heart surgery with CPB. Full article

Background: Inducible macrolide–lincosamide–streptogramin B (iMLSB) resistance is well defined in Gram-positive aerobes but remains poorly characterized in anaerobes, where standardized detection strategies are lacking. Following withdrawal of EUCAST guidance to infer clindamycin resistance from erythromycin resistance in Peptostreptococcus and Bacteroides spp. because of inconsistent species-specific performance, a diagnostic gap persists. Methods: We therefore assessed the accuracy of the D-test for detecting iMLSB resistance in anaerobes by correlating phenotypic results with whole-genome sequencing data. Fifty clinical anaerobic isolates, including Finegoldia magna, Peptostreptococcus anaerobius, and Bacteroides spp., were included in the analysis. Antimicrobial susceptibility testing was performed using gradient diffusion to determine minimum inhibitory concentrations of erythromycin and clindamycin, complemented by D-test analysis for phenotypic detection of inducible resistance. Whole-genome sequencing was undertaken to identify erm genes encoding ribosomal methyltransferases associated with the iMLSB phenotype. Results: Among the 50 isolates, erm genes were detected in 16 strains (32.0%). The prevalence of erm positivity was highest among Gram-positive cocci (50%), followed by Gram-positive rods (35.3%) and Gram-negative rods (11.8%). Five erm-positive isolates exhibited a characteristic D-shaped growth pattern, with high erythromycin MICs (>256 mg/L) and low clindamycin MICs (≤2 mg/L), consistent with an inducible iMLSB phenotype, whereas the remaining eleven demonstrated constitutive resistance. Conclusions: The D-test accurately identified inducible iMLSB resistance among Gram-positive anaerobic cocci and, if confirmed in larger studies, could form the basis of an accessible and pragmatic screening strategy for this subgroup. Integration of molecular analyses seems essential for the evidence-based refinement of diagnostic algorithms, particularly in the absence of robust, species-specific guidance. Full article

Background: The EXTREME regimen (cetuximab with cisplatin/carboplatin and 5-fluorouracil) has long been a standard first-line treatment for recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC), particularly in patients ineligible for immunotherapy. However, real-world evidence remains limited, especially in regions with delayed access to novel therapies. Methods: We conducted a retrospective, multicenter study of 217 patients with R/M HNSCC treated with cetuximab-based chemotherapy at six Croatian oncology centers between 2016 and 2022, prior to reimbursement of pembrolizumab. The primary endpoint was overall survival (OS); secondary endpoints included progression-free survival (PFS), response rates, and safety. Results: The majority (91%) received the EXTREME regimen. Median OS was 14 months (95% CI, 12–17), and median PFS was 6.2 months (95% CI, 6.0–7.2). Objective response rate was 21%, and disease control rate was 63%. Cetuximab-induced rash correlated with longer PFS. Grade ≥ 3 toxicity occurred in 18.9% of patients. No treatment-related deaths were observed. Conclusion: In routine clinical practice, cetuximab combined with platinum-based chemotherapy remains an effective and well-tolerated first-line treatment for R/M HNSCC, particularly in patients who are ineligible for immunotherapy or with PD-L1–negative tumors. These findings support its continued use in appropriately selected patients. Full article

Background/Objectives: Epigenetic factors are increasingly recognized to contribute to the pathogenesis of intestinal diseases, yet the precise mechanisms through which these factors influence ulcerative colitis (UC) remain poorly understood. Methods: Transcriptome profiles pertaining to UC and genes associated with epigenetic factors (EFRGs) were retrieved from publicly accessible datasets. Candidate genes were ascertained through the intersection of differentially expressed genes (DEGs) and EFRGs. Key genes were screened through machine learning algorithms and validated via the Artificial Neural Network (ANN) model. Enrichment analysis and immune infiltration assays were conducted to elucidate the underlying mechanisms of these genes. The hub gene, CBX4 (Chromobox homolog 4), was validated through immunohistochemical analysis of both healthy controls and patients with UC, and the correlation was evaluated using UC-related clinical parameters. Additionally, CBX4 expression was knocked down in dextran sulphate sodium (DSS)-treated mice to examine its regulatory function. Unlike conventional broad-spectrum biomarker screens, this study specifically integrated epigenetic factor-related genes (EFRGs) with machine learning and experimental validation using both clinical samples and animal models. Results: SMARCB1, JAK2, CBX4, and PPARGC1A were identified as key genes, with SMARCB1, JAK2, and CBX4 being upregulated in the UC group, while PPARGC1A was significantly downregulated. The ANN model exhibited excellent diagnostic performance. Enrichment analysis revealed that the key genes were associated with pathways such as the “chemokine signaling pathway”. Immune cell infiltration analysis results revealed marked differences in the abundances of 13 immune cell types between the UC and control groups, and there were notable associations between immune cell infiltration and key genes. Notably, CBX4 expression was elevated in both DSS-treated mice and patients with UC, showing positive correlations with clinical indicators of UC. Further in vivo experiments revealed that silencing CBX4 alleviated DSS-induced colon damage and inflammation. Conclusions: This study identifies four EFRG-related key genes (SMARCB1, JAK2, CBX4, PPARGC1A) in UC, suggesting that CBX4 may play a significant role as an epigenetic regulator. CBX4 is upregulated in UC intestinal tissues, and its knockdown mitigates DSS-induced colitis. These findings provide critical theoretical support for developing targeted therapies for UC. Full article

Background and Objectives: Reliable tools for evaluating tumor biology and forecasting clinical outcomes in recurrent hepatocellular carcinoma (HCC) remain scarce, and molecular characterization through genetic profiling is equally limited in this setting. This investigation explores whether serum tumor marker expression patterns correlate with genomic mutation profiles, and whether such correlations may facilitate more accurate prediction of tumor biology and patient prognosis in recurrent HCC. Materials and Methods: We analyzed a cohort of 20 patients who underwent curative-intent resection for both primary and recurrent HCC. Tumor specimens collected at the time of each operation were subjected to targeted next-generation sequencing for mutation profiling. Based on pre-operative serum levels of AFP (alpha-fetoprotein) and PIVKA-II (Protein Induced by Vitamin K Absence or Antagonist-II) measured before each surgery, patients were stratified into four biomarker subgroups. Those who maintained the same biomarker subgroup at both operations were designated the ‘serum concordant group’, whereas those who transitioned between subgroups were classified as the ‘serum discordant group’. Clinical characteristics and mutation data were subsequently compared between these two classifications. Results: The interval from primary surgery to disease recurrence was significantly shorter in the serum concordant group relative to the serum discordant group (mean 11.16 ± 1.86 vs. 44.8 ± 9.45 months, p < 0.001). Additionally, disease-free survival following reoperation was significantly inferior in the concordant group compared with the discordant group (p = 0.039). Regarding mutational patterns, the concordant group demonstrated shared gene mutations between primary and recurrent lesions, while the discordant group exhibited divergent mutational landscapes across both timepoints. Conclusions: The concordance or discordance of serum tumor marker profiles between primary and recurrent HCC lesions may serve as a clinically accessible surrogate for underlying tumor biology and prognostic stratification. These results are preliminary and hypothesis-generating. Further studies in larger, independent cohorts are warranted to confirm the observed associations. Full article

Background and Objectives: Chronic spontaneous urticaria (CSU) significantly affects patients’ quality of life (QoL) and remains challenging to manage, particularly in under-researched regions. This study aimed to assess the clinical burden, disease control, and quality of life among patients with CSU in Kazakhstan and to identify predictors of severe disease activity. Materials and Methods: We conducted a cross-sectional study of 350 patients with CSU attending the Republican Allergy Center in Almaty between December 2024 and June 2025. Patients were classified based on the presence of co-existing chronic inducible urticaria (CIndU), angioedema, or both. Disease activity, control, and QoL were assessed using the Urticaria Activity Score over 7 days (UAS7), Urticaria Control Test (UCT), and Dermatology Life Quality Index (DLQI), respectively. Multivariable logistic regression and correlation analyses were used to identify predictors of severe disease and interrelationships among clinical measures. Results: Among 350 patients (mean age 43.5 ± 14.7 years; 78% female), 46.3% had CSU alone, while 53.7% had associated phenotypes. Severe urticaria (UAS7 ≥ 28) affected 30% of patients. Suboptimal disease control (UCT ≤ 11) was reported in 30%, and 30% experienced strong or very strong QoL impairment (DLQI > 10). Older disease onset (≥60 years; OR = 1.98; 95% CI: 1.02–3.81) and nighttime symptoms (OR = 1.67; 95% CI: 1.02–2.73) were independently associated with severe disease. A strong inverse correlation was observed between UAS7 and UCT (ρ = −0.71), and a positive correlation between UAS7 and DLQI (ρ = 0.66), highlighting the impact of disease activity on control and QoL. Conclusions: CSU imposes a substantial clinical and psychosocial burden in Kazakhstan. One-third of patients experience severe symptoms and impaired QoL despite ongoing treatment. Older age at disease onset and nighttime symptoms may serve as practical indicators of disease severity. These findings highlight the need for improved access to advanced therapies, systematic monitoring using validated tools, and multidisciplinary care strategies in resource-constrained settings. Full article

Tumor Mutational Burden (TMB) is a critical biomarker used to determine patient eligibility for immunotherapy with immune checkpoint inhibitors. However, its gold-standard assessment via whole exome sequencing is limited by high costs, technical complexity, and lengthy processing times. To address these challenges, we investigated whether Ultra-High-Frequency (UHF) electromagnetic wave sensing could serve as an alternative method for evaluating TMB. We analyzed the dielectrophoresis crossover frequency spectrum and corresponding electromagnetic signature (EMS) of cancer cells using a lab-on-a-chip biosensor that integrates microfluidics with dielectrophoresis-based electro-manipulation. Across seven solid tumor cell lines exhibiting diverse TMB levels, EMS exhibited an upward shift correlated with higher TMB, suggesting a relationship between mutational load and electromagnetic behavior. To further explore this connection, we artificially increased the somatic variant burden by exposing cells to the mutagen N-ethyl-N-nitrosourea (ENU). EMS measurements reliably detected the induced increase in variant load in ENU-treated cells. Overall, these findings demonstrate that EMS can detect both intrinsic TMB differences and experimentally induced increases in mutational burden, enabling refined categorization of cancer cells. Although further validation is required, this work lays the foundation for developing complementary, rapid, and accessible tools to support cancer cell stratification and guide immunotherapy decision-making. Full article

Drought stress induces pronounced metabolic and transcriptional reprogramming of glucosinolate (GLS) biosynthesis in Brassica oleracea. An integrative approach combining HPLC-based quantification of individual GLSs, quantitative real-time PCR of core biosynthetic and regulatory genes, correlation-based network analysis, and in silico promoter characterization was applied to evaluate drought responses across genetically diverse accessions. Drought triggered strong, accession-specific shifts in GLS composition, with sinigrin content increasing from 35.9% to 55.1% in BR1 and glucoerucin reaching up to 80.2% in CCP1, while indolic GLSs such as glucobrassicin and neoglucobrassicin accounted for >75% of total GLSs in CV2 and CCP3. Hierarchical clustering separated accessions into four distinct drought response clusters independent of morphotype. Correlation analysis revealed drought-induced rewiring of GLS interdependencies, characterized by strengthened positive associations among aliphatic GLSs (r > 0.75). Gene expression profiling identified conserved MYB-centered regulatory modules (MYB28, MYB29, MYB34, MYB122) alongside strong accession-specific induction of CYP79F1 (up to 6.3-fold), FMOGS-OX5 (up to 4.8-fold), and ST5a (up to 5.1-fold). Promoter analysis revealed enrichment of ABA- and stress-responsive cis-regulatory elements. These findings delineate a genotype-dependent regulatory framework underlying GLS plasticity and identify quantitative metabolic and transcriptional markers relevant for breeding drought-resilient Brassica cultivars. Full article