Search Results (16,372)

Post-conflict reconstruction research has examined façade materiality and symbolism, yet the process conditions under which aesthetic specifications are systematically overridden during construction remain neglected. This study investigates why designed architectural aesthetics fail to survive implementation in post-2017 Mosul, Iraq. A mixed-methods design combined formal visual analysis of 12 recently completed residential façades with a structured survey of 45 practicing architects. Survey data reveal that designers are excluded from construction supervision in 76% of projects and that clients intervene in material and color selection in 70% of cases. Visual analysis identifies a sophisticated design language—orthogonal massing articulated through contrasting materials—that is rarely realized in built form. Where designers retain supervisory authority, projects most consistently achieve material–form coherence. The study advances the concept of an aesthetics of interruption (the systematic degradation of designed form–material relationships through the fragmentation of professional authority during construction). Exclusion produces four distinct pathologies: material substitution, execution degradation, language override, and ornamental hollowing. The findings demonstrate that aesthetic degradation in post-conflict reconstruction stems not from design incapacity but from broken process structures. Safeguarding architectural quality requires contractual frameworks mandating designer supervision and material-substitution protocols that protect design intent. Full article

Non-small cell lung cancer (NSCLC) exhibits genomic heterogeneity that affects tumor immunogenicity and PD-L1 expression. Patient clustering based on shared mutational profiles using social network analysis (SNA) has been narrowly explored. The study aimed to identify subgroups of NSCLC patients with similar somatic mutation profiles using network-based modularity clustering, and to compare these groups with respect to PD-L1 expression, Tumor mutation burden (TMB), and clinical variables. Data of patients with stage 4 (metastatic) NSCLC, whose tumor tissue samples were collected between 2022 and 2024, were analyzed. This retrospective study included NSCLC patients harboring actionable driver mutations in genes such as EGFR, KRAS, ALK, BRAF, MET. A social network of 129 patients was constructed. Two distinct genomic clusters were identified. Cluster 2 (n = 55) showed a higher prevalence of KRAS, TP53, BRAF, STK11 and additional mutations, while cluster 1 (n = 74) displayed a limited number of driver mutations. Cluster 2 had significantly higher PD-L1 expression (29.8% vs. 13.7%, p = 0.001) and higher TMB (7.8 vs. 5.8, p = 0.021). In multivariate logistic regression, both PD-L1 and TMB were associated with cluster assignment (p < 0.05). Mutation-based SNA clustering delineated two biologically distinct subgroups of NSCLC patients. The highly mutated cluster displayed higher PD-L1 expression and TMB, a profile consistent with a more immunogenic phenotype. This method offers a novel integrative approach that requires prospective validation before clinical implementation. Full article

Background/Objectives: To investigate the immediate regulatory effects of magnetic stimulation with different parameters on the excitability of glutamatergic neurons and GABAergic neurons in the mouse hippocampal dentate gyrus (DG), and to analyze the underlying mechanisms using the Hodgkin–Huxley (HH) model. Methods: Whole-cell patch-clamp recordings were performed on acute brain slices to measure changes in resting membrane potential (RMP), the number of action potentials (APs) evoked by 500-ms long-duration stimulation, as well as AP threshold, peak, half-width, maximum rising slope, and maximum falling slope under magnetic stimulation at various frequencies (1, 10, 20 Hz) and intensities (50, 75 mT). An improved HH model was established based on experimental data to analyze the dynamic changes in gating variables under magnetic stimulation. Results: High-frequency magnetic stimulation (10–20 Hz) significantly increased the number of APs in both neuron types. In glutamatergic neurons, the number of APs increased from 10.12 ± 0.52 in the control group to 15.62 ± 0.84 in the 20 Hz-75 mT group; in GABAergic neurons, it increased from 7.88 ± 0.40 to 12.62 ± 0.53. Magnetic stimulation also depolarized RMP and significantly altered multiple AP waveform parameters in both neuron types. Glutamatergic neurons showed a more distinct frequency dependence, whereas GABAergic neurons were more sensitive to changes in both frequency and intensity in terms of RMP and multiple waveform parameters. Simulation results showed that the 1 Hz conditions produced negligible changes in AP firing, gating-variable dynamics, and steady-state ion-channel parameters compared with the Control condition. In contrast, high-frequency stimulation enhanced the dynamic changes of sodium and potassium channel gating variables and altered their voltage-dependent steady-state properties. Specifically, sodium channel activation shifted toward more negative potentials, whereas sodium channel inactivation and potassium channel activation shifted toward more depolarized potentials. Conclusions: Under the experimental conditions of this study, magnetic stimulation immediately enhanced the excitability of glutamatergic and GABAergic neurons in the hippocampal dentate gyrus of male mice in a frequency-dependent manner. The modified HH model reproduced both the weak effects under low-frequency stimulation and the enhanced excitability under high-frequency stimulation, suggesting that these immediate effects may be related to frequency-dependent changes in the gating kinetics and voltage-dependent properties of sodium and potassium channels. Full article

Against the backdrop of the continuing “museum boom” and increasingly diversified cultural demands, many small and medium-sized museums in China face rigid constraints, including insufficient funding, limited collections, and a shortage of professional personnel. Under such conditions, traditional exhibition models often suffer from weak narratives and limited public appeal. Focusing on the Ancient Ferry Site Museum affiliated with Xianyang Museum as the core case, this study adopts a case-study approach supplemented by comparative analysis. Drawing on exhibition texts, social education activities, visitor statistics, and operational data from recent years, it explores the narrative transformation pathways of resource-constrained museums. The findings show that the museum has gradually transformed from object-centered display to cultural storytelling, and from one-way presentation to two-way interaction, through strategies such as highlighting regional culture, refining a core narrative IP, integrating accessible technologies to create immersive experiences, expanding social education functions, and improving management systems. Based on the case analysis, this paper further proposes a “four-dimensional driving” model for narrative innovation in small and medium-sized museums, emphasizing the synergy among narrative positioning, technological experience, social connection, and management innovation. The core purpose of this model is to transform resource limitations into opportunities for distinctive development through in-depth local cultural narratives and creative transformation. Studies indicate that small and medium-sized museums can develop distinctive development models amid resource constraints via localized cultural narration, resource integration and differentiated positioning, thereby expanding their functions of cultural communication and public service. On this basis, this study argues that limited resources do not necessarily hinder museum development; rather, differentiated development can be achieved through local storytelling and resource integration. The research provides theoretical reference and practical implications for the narrative transformation of resource-constrained museums and the enhancement of public cultural services. Full article

Background: Routine full blood count (FBC) testing is part of the haematological workup in diabetes management. There is limited information regarding the contributions of individual haematological parameters to regression models for glycated haemoglobin (HbA1c), estimated whole-blood viscosity (eWBV) and the resulting blood viscosity complications. Importantly, because association and prediction represent distinct concepts, this study extends previous work with a focus on comparative and exploratory relationships. The objective was to compare FBC parameters between higher and lower HbA1c and eWBV groups and identify variables contributing to the Akaike Information Criterion (AIC)-based regression model among diabetics. Methods: This laboratory-based mixed quantitative study involved cross-sectional and regression analyses. Fifteen parameters were evaluated, including the following: red blood cell count (RBC) and indices (MCV, MCH, MCHC); platelet count and derived ratios (PRR, PWR, RPR); and white blood cell count (WBC) with lymphocyte ratios (MLR, NLR, PLR). HbA1c and eWBV data were used to create dichotomous subgroups for univariate comparison, followed by exploratory AIC-based model identification of variables. Results: HbA1c, RDW, MCV, and RPR, differed significantly between HbA1c groups (p < 0.1). Regression analysis identified RDW, MCV, RPR, MCH and RBC as contributors to the HbA1c model. For eWBV, five out of seven parameters (HCT, HB, RBC, WBC, and MLR) showed a significant association. Conclusions: These findings highlight haematological parameters with potential values for future predictive model development. Overall, the study supports the usefulness of selected FBC variables as adjuncts in diabetes monitoring with potential utility in understanding glycaemia control and blood viscosity-related complications. Full article

The Yellow River Delta is a representative coastal saline–alkaline ecosystem in China, where high salinity and complex soil properties create a distinct habitat that significantly shapes microbial community structure and function. In this study, we analyzed 34 saline–alkaline soil samples from four regions within the delta. We characterized soil physicochemical properties (salt content, electrical conductivity, and pH) and systematically assessed fungal diversity, potential ecological functions, and their relationships with environmental variables using both internal transcribed spacer high-throughput sequencing and culture-based isolation. Sequencing generated 1,137,196 sequences that clustered into 13,574 operational taxonomic units (OTUs), with Good’s coverage values ranging from 0.96 to 1.00, indicating sufficient sequencing depth. The soils were generally alkaline and exhibited pronounced spatial heterogeneity in salinity and electrical conductivity. Sequencing analyses revealed Ascomycota and Basidiomycota as the dominant fungal phyla. Alpha diversity tended to decline with increasing salt content and electrical conductivity; however, substantial within-group variability indicated strong microenvironmental influences. Beta diversity analyses revealed distinct clustering patterns in community structure among regions based on PCoA ordinations. Redundancy analysis revealed that soil pH had the only significant unique contribution to fungal community variation. However, all three measured edaphic factors together explained only 17% of the total community variation. Functional inference using the FUNGuild database identified diverse fungal trophic modes and several plant-associated taxa in several samples. Culture-based approaches yielded 347 isolates representing 52 genera. Among the isolates, the vast majority (>95%) belonged to Ascomycota, with Basidiomycota represented by only a few isolates, which is consistent with the dominance of Ascomycota observed in the high-throughput sequencing data. Comparisons between sequencing and cultivation results demonstrated complementary diversity profiles and highlighted a substantial reservoir of nonculturable fungi in these soils. Overall, this study clarifies spatial patterns and key environmental drivers of fungal diversity in the Yellow River Delta and establishes a foundational culture collection for future ecological restoration efforts. Full article

Background: Serum 25-hydroxyvitamin D [25(OH)D] interpretation requires clear distinction between epidemiological thresholds, routine-data distributions, and clinical decision limits. This study evaluated vitamin D status and clinically pre-filtered routine laboratory data-derived 25(OH)D distributional benchmarks among adults from Şanlıurfa, southeastern Türkiye, according to sex, age, and season. Methods: This retrospective single-center routine laboratory database study included adults aged 18–65 years tested between 1 January and 31 December 2025, at the Medical Biochemistry Laboratory of Şanlıurfa Mehmet Akif İnan Training and Research Hospital. After eligibility screening, duplicate removal, analytical screening, and predefined clinical pre-filtering, 48,826 participant-level records were analyzed. Serum 25(OH)D was measured using the Elecsys Vitamin D total III electrochemiluminescence immunoassay on a cobas e 801 analyzer/module. The primary distributional estimate was the nonparametric 2.5th–97.5th percentile range. Results: Median age was 38 [28–49] years, and 35,043 records were from female participants (71.8%). Median serum 25(OH)D was 12.74 [8.28–19.00] ng/mL. Vitamin D deficiency, severe deficiency, insufficiency, and sufficiency were observed in 38,072 (78.0%), 17,163 (35.2%), 8235 (16.9%), and 2519 (5.2%) records, respectively. Lower 25(OH)D concentrations and higher deficiency prevalence were observed among females, younger adults, and winter/spring samples, with small-to-modest effect magnitudes. The clinically pre-filtered routine-data 2.5th–97.5th percentile range was 3.46–35.50 ng/mL. Conclusions: Low 25(OH)D status was widespread among routinely tested adults in Şanlıurfa. The derived range should be interpreted only as a local routine-data distributional benchmark for the tested population, not as a healthy-volunteer reference interval, clinical sufficiency threshold, treatment threshold, or clinical decision limit. Full article

Heart failure (HF) in the setting of diabetes represents a distinct cardiometabolic phenotype characterized by profound disturbances in myocardial glucose metabolism, mitochondrial function, and energetic efficiency. Growing evidence indicates that sirtuins, a family of nicotinamide adenine dinucleotide (NAD⁺)-dependent deacylases, play a central role in coordinating glucose utilization, oxidative metabolism, and stress responses in the heart. Findings from genetically modified animal models and cardiomyocyte studies demonstrate that sirtuin impairment, often driven by NAD⁺ depletion and redox imbalance, further suppresses metabolic activity and promotes metabolic inflexibility, whereas restoration of NAD⁺ availability or sirtuin activity improves mitochondrial efficiency and metabolic coordination. Human studies, including analyses of myocardial tissue and circulating biomarkers, provide supportive but largely associative evidence, highlighting a substantial translational gap. In this review, we synthesize experimental and clinical data linking sirtuin signaling to the metabolic remodeling observed in diabetic HF, with particular emphasis on glycolysis–oxidation uncoupling, pyruvate dehydrogenase regulation, and mitochondrial dysfunction. We critically discuss context-dependent effects, apparent contradictions, and current limitations of the field, emphasizing differences between diabetic and non-diabetic HF, as well as phenotype- and stage-specific considerations. Finally, we explore therapeutic implications and outstanding questions, positioning the NAD⁺–sirtuin axis as a unifying mechanistic framework that links systemic metabolic disease to cardiac energetic failure and underscores the potential for metabolism-informed, precision strategies in diabetic HF. Full article

The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems worldwide, placing healthcare workers (HCWs) at severe infection risk through direct patient contact. Epidemiological data confirm that HCWs were approximately seven times more likely to develop severe COVID-19 than other occupations, with over 7000 HCW deaths recorded globally by mid-2020. This paper presents the design and laboratory proof-of-concept validation of an IoT-based remote patient-monitoring system prototype—the IoT-Based Isolation Ward Monitoring System Prototype—designed to eliminate unnecessary patient-to-HCW physical contact while maintaining continuous, real-time physiological surveillance. The system integrates multi-sensor hardware comprising an AD8232 ECG module, a MAX30100 pulse oximeter, an NTC thermistor, and an MQ-135 ${\mathrm{C}\mathrm{O}}_2$ sensor. These sensors interface with an Arduino UNO for data acquisition, while localized edge computing is executed on a Raspberry Pi 3B. A convolutional neural network (CNN) trained on the MIT-BIH Arrhythmia Database classifies heartbeats into five distinct categories. By utilizing SMOTE resampling on 109,446 samples, the network achieves an on-device inference latency of under 200 ms. The sensor data are transmitted to a Firebase Realtime Database via an authenticated REST API, which synchronizes data across dual front-end interfaces: a LabVIEW desktop dashboard for clinical oversight and a cross-platform Flutter mobile application for mobile monitoring. End-to-end technical validation under controlled laboratory conditions confirmed round-trip cloud latencies between 300 and 800 ms, error-free threshold alert generation, and sub-second latency for the integrated chat utility. The proposed system uniquely combines hardware sensing, ML-based ECG classification, cloud storage, a LabVIEW physician dashboard, and bidirectional doctor–patient mobile communication into a single unified, low-cost platform. Full article

Objective: This study aims to explore the differences in chemical composition among Tibetan medicinal Rhododendron species and their potential correlation with anti-complement activity, with the goal of identifying promising medicinal resources. In Tibetan medicinal practice, the two groups of large-leaved Rhododendron (Tibetan: Dama) and small-leaved Rhododendron (Tibetan: Tali) are often used interchangeably despite unclear chemical and taxonomic bases. By comparing chemical profiles and evaluating anti-complement effects, this investigation seeks to provide preliminary scientific evidence for clarifying medicinal origins and facilitating the targeted development of high-quality resources. Methods: Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was employed to analyze seven Rhododendron samples. Separation was achieved on a Waters CORTECS UPLC C18 column (2.1 × 100 mm, 1.6 μm) using a gradient mobile phase system consisting of acetonitrile and 0.1% formic acid in water, at a flow rate of 0.3 mL/min and a column temperature of 30 °C. Data were acquired in both positive and negative electrospray ionization (ESI) modes. Compound identification was performed using Peakview 1.2 software by comparison with databases and literature. Grey relational analysis and partial least squares (PLS) regression, combined with 5000 bootstrap resampling iterations, were applied to establish spectrum–effect relationships and to screen for characteristic peaks potentially associated with anti-complement activity. Results: A total of 52 compounds were tentatively identified, including flavonoids (e.g., hyperin, isoquercitrin, taxifolin-3-O-arabinoside), terpenoids (e.g., grayanotoxin I/III), and chromanes (e.g., anthopogochromane series). The CH₅₀ values of the ethanol extracts ranged from 179.29 to 579.47 μg/mL, with Rhododendron principis showing the strongest activity (179.29 ± 11.86 μg/mL), followed by Rhododendron vellereum (198.61 ± 7.93 μg/mL). Spectrum–effect analysis revealed that four unidentified peaks (F5315, F5822, F5368, F5991) exhibited negative regression coefficients and VIP means close to or above 0.8, suggesting a possible positive correlation with anti-complement activity. Among these, F5315 (VIP = 0.909), F5822 (VIP = 0.877), and F5368 (VIP = 0.834) showed relatively higher values and were considered preliminary candidate peaks warranting further investigation. Conclusions: This study tentatively identifies 52 compounds from the ethanol extracts of seven Tibetan medicinal Rhododendron species and reports their anti-complement activities. The findings reveal chemical distinctions between the large-leaved (Dama) and small-leaved (Tali) groups, offering a potential chemical basis for species differentiation and quality evaluation. Furthermore, four unknown peaks were preliminarily screened through spectrum–effect analysis as potential anti-complement candidates, which may serve as a foundation for future activity-guided isolation and quality marker studies. Full article

Understanding how brain activity varies across neurological and neurodevelopmental disorders requires tools capable of revealing patterns hidden in complex electroencephalographic (EEG) data. Conditions such as epilepsy, Alzheimer’s disease, dementia, and autism exhibit distinct alterations in neural oscillations and connectivity, which remain difficult to interpret in real time; therefore, this study proposes an interactive interface for intuitive exploration and analysis of disease-specific EEG dynamics. The system integrates classical signal processing techniques and computational modeling to extract spectral features, inter-electrode coherence, and spatial activation patterns, which are visualized through spectrograms, topographic maps, and connectivity graphs that update continuously. In addition, a web-based platform is incorporated to enable clinicians and technicians to store and manage patient information, including diagnosis, severity level, number of recordings, sampling frequency, recording duration, and acquisition dates, supporting structured data organization and longitudinal monitoring. The results demonstrate that the interface captures meaningful differences between disorders, with epileptic patterns showing strong synchronization and burst activity, while neurodegenerative conditions exhibit spectral slowing and reduced connectivity. Overall, the proposed framework provides an effective and accessible tool for EEG visualization, combining interactive analysis with clinical data management to support research, education, and potential clinical applications. Full article

Ionization potentials and electron affinities provide the energetic basis for several conceptual density functional theory descriptors, but their use in donor–acceptor maps requires careful distinction between physically bound anions, weak or borderline electron-affinity cases, and formally computed diagnostic states. In this work, a periodic donor–acceptor descriptor map was constructed for main-group atoms from H to Kr using a $\Delta$SCF-DFT framework. Neutral atoms, monocations, and formally defined monoanionic states were evaluated to obtain ionization potentials, electron affinities, and global reactivity descriptors, including electronegativity, chemical hardness, chemical potential, electrophilicity, electrodonating power, and electroaccepting power. The production dataset was calculated at the $\omega$B97X-D4/def2-QZVPPD level and benchmarked against reference atomic data. This protocol reproduced ionization potentials with a mean absolute error of 0.134 eV and electron affinities with a mean absolute error of 0.116 eV for the reference EA set, including the weak calcium case. A functional and basis-set sensitivity analysis using $\omega$B97X-D4/def2-TZVPPD, PBE0/def2-QZVPPD, and PBE0/def2-TZVPPD showed that ionization potentials are comparatively robust, whereas electron affinities are strongly affected by the quality of the diffuse basis set. The normalized donor–acceptor map reproduces chemically intuitive periodic trends, with alkali metals occupying the strong-donor region and halogens defining the strong-acceptor region. The analysis explicitly separates core validation atoms from weak or borderline electron-affinity cases and diagnostic finite-basis anionic states, emphasizing that formally computed negative electron affinities for unbound anions should not be interpreted as physical bound states. The resulting nonrelativistic dataset provides a reproducible atomic descriptor reference for interpreting donor–acceptor behavior in atoms, clusters, superatoms, doped materials, and charge-transfer systems. Full article

This study applies a synoptic seasonal climatological framework, extended vertically through the troposphere, to investigate the South Asian monsoon using daily mean data (1948–2024) from the NCEP–NCAR Reanalysis. A seasonal synoptic circulation framework was developed using self-organizing maps (SOMs) to classify four distinct seasons—winter, pre-monsoon, monsoon, and post-monsoon—and their transitional phases. Diagnostics including temperature and moisture advection and vertically integrated moisture transport (VIMT) were incorporated to examine circulation–environment interactions. The results highlight the pre-monsoon-to-monsoon transition as the most critical seasonal shift, marked by rapid land heating, steep pressure gradients, and northward ITCZ migration that initiates southwesterly monsoon winds. Classical land–sea thermal contrasts initiate the low-level monsoon wind reversal, while vertical circulation assessment suggests that mid- to upper-tropospheric thermal gradients, supported by latent heating and Hadley-type overturning, help organize and sustain monsoon circulation strength. Additionally, South Asian monsoon circulation is shifting from well-defined seasonal regimes toward more transitional states. The results reveal widespread warming, weakened VIMT during major monsoon-related phases, and uneven moisture redistribution, suggesting that climate change is reshaping the monsoon seasonal cycle through both thermodynamic and circulation-driven processes. Taken together, the findings demonstrate that monsoon dynamics arise not from a single mechanism but from interconnected processes operating across atmospheric layers. This vertically integrated synoptic circulation approach thus provides a more comprehensive framework for understanding monsoon processes. Full article

Restaurants combine long opening hours, catering demand, kitchen ventilation, DHW, and mixed-fuel cooking loads, making their decarbonisation different from generic commercial retrofit. For small- and medium-sized enterprise (SME) hospitality premises, this makes the transition to net-zero operation a distinct sustainability challenge because a large, process-driven share of demand lies outside conventional building-fabric and building-services retrofit. This single-case study develops a whole-building utility-calibrated OpenStudio/EnergyPlus model for Beit El Zaytoun, a 655.82 m² restaurant in Park Royal, London. Monthly electricity and gas data for June 2024–May 2025 were used to calibrate the baseline at whole-building level. Standalone and cumulative scenarios tested insulation, low-emissivity double glazing, LED lighting and controls, ASHP service scenarios, and an 11 kWp PV array. Baseline demand was 413,895 kWh/yr, equivalent to 631.1 kWh/m²·yr and 75,020 kgCO₂e/yr. The lowest-net-energy analytical package reduced net imported energy to 314,734 kWh/yr and operational carbon to 56,700 kgCO₂e/yr, a retained 24.0% reduction on the source reporting basis; this package is treated as an analytical bound rather than as a final design recommendation because it excludes cooling. The model-derived residual process load, kitchen and catering gas plus kitchen, and back-of-house electricity remained 233,920 kWh/yr across building-focused scenarios. The Residual-Load Index (RLI) rose from 0.57 to 0.74; with ±15% process-load allocation uncertainty, the optimised RLI range was 0.63–0.85, so the post-retrofit balance remained process-load dominated. The case demonstrates a practical decarbonisation ceiling likely to recur in similar high-process-load hospitality premises: fabric, lighting, heat electrification, and PV are necessary but insufficient without catering-equipment, cooking-fuel, kitchen-ventilation, refrigeration-control, sub-metering, and demand-response strategies. The paper contributes whole-building utility-calibrated quantitative evidence and a transferable RLI metric for sub-sector-specific sustainable retrofit policy, and the net-zero transition of SME food-service premises. Full article

Background/Objectives: The objective of this study was to investigate the effects of local zoledronate treatment during periapical lesion development on inflammatory and bone remodeling responses in two immunologically distinct inbred rat strains, Dark Agouti (DA) and Albino Oxford (AO). Methods: Periapical lesions were induced in the mandibular first molars of AO and DA rats (n = 44) by pulp exposure. Animals were assigned to four groups: DA + zoledronate, DA + saline, AO + zoledronate, and AO + saline. Zoledronate (0.15 mg/kg) or saline was locally administered on days 0, 7, 14, and 21 during lesion development. Animals were sacrificed on day 28. Mandibles were analyzed radiographically and histologically for lesion size, while osteogenic activity was assessed by osteocalcin immunohistochemistry. Gene expression was evaluated by qRT-PCR, and systemic oxidative stress parameters were analyzed spectrophotometrically. Statistical analysis included parametric or non-parametric tests according to data distribution, with significance set at p < 0.05. Results: Zoledronate -treated AO rats exhibited smaller periapical lesions and higher radiographic grayscale density than DA rats (p < 0.05). Histological analysis confirmed the radiographic findings and demonstrated smaller lesion areas in AO rats. Osteocalcin expression was significantly higher in AO rats (p < 0.05), indicating increased osteogenic activity. At the molecular level, DA rats showed higher expression of TNF-α and IL-1β, whereas AO rats exhibited higher expression of IL-10 and IL-4 (p < 0.05). In addition, expression of osteoclastogenic factor RANKL was significantly lower in AO rats than in DA rats (p < 0.05), while OPG expression showed a non-significant tendency toward higher levels in AO rats. Systemic redox analysis demonstrated lower NO₂⁻ and O₂⁻ levels in zoledronate-treated AO rats, whereas no significant differences were observed in the remaining oxidative stress parameters. Conclusions: Following local zoledronate treatment during lesion development, Th2-dominant AO rats exhibited reduced inflammatory responses and increased osteogenic activity compared with Th1-dominant DA rats. In contrast, DA rats primarily demonstrated attenuation of osteoclastogenic signaling without comparable osteogenic responses. These findings indicate that the biological effects of local zoledronate treatment in developing periapical lesions are influenced by the host immune phenotype. Full article