Search Results (1,840)

Background: Urban planning documents at metropolitan scale typically demand large, cloud-hosted language models that limit their adoption in Global South contexts. This study deploys Moondream, a 1.7-billion-parameter vision-language model (VLM) runnable locally via Ollama, for extracting geographic knowledge from Planes Reguladores Comunales (PRCs) across 29 processed Gran Santiago municipalities. The pipeline combines native PDF text extraction, keyword-based multi-label classification across six thematic axes, and VLM-based optical character recognition and cartographic interpretation. Results: The pipeline processes 2289 PRC articles in 4.3 min at an estimated energy cost of 0.000866 kWh and zero marginal monetary cost. Zoning (53.3%) and land use (43.1%) dominate PRC content, while social housing provisions appear in only 4.0% of articles; normative gap analysis identifies five municipalities where social housing is entirely absent from regulatory text. A comparative evaluation of Moondream against keyword baseline on an 88-article validation sample yields macro-F1 = 0.355 and mean Cohen’s κ = 0.004, confirming that generalist VLMs require domain fine-tuning for specialized legal text. It is argued that the cost asymmetry between industrial-scale and small-model approaches constitutes an epistemic asymmetry with direct consequences for the geographic distribution of urban data infrastructure. Full article

Background and Objectives: Corneal collagen cross-linking (CXL) halts keratoconus progression, yet potential differences between conventional and accelerated protocols at one year remain uncertain. We analyzed the completed 12-month follow-up of a previously reported 6-month cohort to compare conventional (3 mW/cm² × 30 min; CXL 30) versus accelerated (9 mW/cm² × 10 min; CXL 10) CXL, interpreting outcomes within the ABCD framework alongside Kmax and curvature radii. Materials and Methods: In this single-center retrospective longitudinal analysis of prospectively collected routine clinical data, 22 eyes were included, with assessments performed at baseline and at 1, 3, 6, and 12 months of follow-up. Evaluated outcomes comprised ABCD stages (A–D), anterior and posterior radius of curvature (ARC and PRC), Kmax, pachymetric and elevation indices, as well as UDVA and BCVA. Within-group change used Friedman with Wilcoxon post hoc; between-group differences used Mann–Whitney (α = 0.05). Results: Both protocols resulted in significant visual improvement and Kmax reduction at 12 months (overall time effect: CXL 30 p < 0.001; CXL 10 p = 0.026). Median Kmax decreased 56.5 → 52.3 D (CXL 30) and 59.3 → 58.3 D (CXL 10). UDVA improved 0.2 → 0.6 (CXL 30) and 0.2 → 0.3 (CXL 10); BCVA 0.4 → 0.8 (CXL 30) and 0.2 → 0.5 (CXL 10). Tomographic analysis showed predominantly anterior changes, with a significant decrease in A stage in the CXL 30 group and an increase in ARC in both groups, more pronounced in CXL 30. In the late 6 → 12-month window, posterior metrics (PRC and posterior elevation) were largely stable; raw PRC change did not reach significance. Conclusions: Conventional and accelerated CXL both stabilized keratoconus at one year with meaningful functional gains. Beyond 6 months, remodeling was predominantly anterior; within-group findings suggested a more pronounced anterior tomographic response in the CXL 30 group. The 12-month visit may be useful for reassessing stability after CXL, although this study was not designed to determine optimal retreatment timing or optical rehabilitation strategy. Longer-term studies with standardized biomechanical and densitometric endpoints are warranted to assess durability and refine protocol selection. Full article

High levels of low-density lipoprotein cholesterol (LDL-c) have been recognized as the main causal factor of atherosclerotic cardiovascular disease (ASCVD) and are influenced by both genetic and environmental factors. Among genetic determinants, Familial Hypercholesterolemia (FH) is the most common monogenic disorder, caused by rare high-impact variants in genes involved in LDL uptake. Other monogenic causes of hypercholesterolemia include sitosterolemia, cerebrotendinous xanthomatosis and lysosomal acid lipase deficiency (LALD). However, monogenic disorders only account for a small proportion of inherited hypercholesterolemia. In many individuals, increased LDL-c levels are caused by the contemporary presence of different single-nucleotide polymorphisms (SNPs) with a moderate/low impact. These SNPs could be summarized through polygenic risk scores (PRS) that attribute relative weight to each of these. Another genetic determinant of hypercholesterolemic phenotypes is high levels of lipoprotein(a)—Lp(a). Lp(a) is an LDL particle modified by the binding of apolipoprotein(a)—apo(a)—which represents an independent risk factor for ASCVD. Lp(a) levels are mainly genetically determined by variation in the number of kringle IV type 2 (K-IV₂) repeats, as well as by several SNPs, and remain stable throughout life. The aim of this narrative review is to report an updated overview of the genetic mechanisms underlying hypercholesterolemia, including monogenic disorders, PRS and Lp(a), focusing on their potential repercussion in clinical practice by the integration into cardiovascular risk stratification beyond traditional clinical assessment. This integration could lead to a more comprehensive and individualized approach to cardiovascular prevention, with emerging perspectives including the possible use of artificial intelligence (AI). Full article

Prostate cancer (PrC) is one of the most common malignancies among men worldwide. However, the contribution of genetic variation in microRNA (miRNA) biogenesis pathway genes to PrC susceptibility remains poorly characterized in many ethnically diverse populations. We conducted a case–control study involving 532 PrC patients and 550 controls from the Volga-Ural region of Eurasia to evaluate the association of twenty-one single nucleotide polymorphisms (SNPs) with PrC risk using single-variant and polygenic approaches. Association analyses identified rs595055 in the AGO1 gene as significantly associated with PrC risk after correction for multiple testing. To evaluate the cumulative effect of genetic variation, weighted and unweighted polygenic risk scores (PRSs) were constructed. The weighted PRS was significantly associated with PrC risk (odds ratio per standard deviation increase = 1.63, 95% CI [1.43–1.85], P = 1.37 × 10⁻¹³), and demonstrated moderate discriminatory performance (AUC = 63.1%), outperforming the unweighted model. Individuals in the highest PRS quartile had approximately threefold higher odds of PrC than those in the lowest quartile. Combining the weighted PRS with prostate-specific antigen improved discrimination (AUC = 68.1%). These findings support the contribution of miRNA biogenesis pathway genes to PrC susceptibility and highlight the potential value of pathway-based polygenic risk stratification in understudied populations. Full article

Temperature-dependent luminescence of Pr³⁺-doped materials was investigated using both conventional luminescence intensity ratio (LIR) and principal component analysis (PCA)-based thermometry. Three host matrices with distinct structural properties, LiLaP₄O₁₂, YNbO₄, and Y₂O₃, were selected to evaluate the influence of crystal structure on thermometric performance. Temperature-resolved emission spectra recorded over the 103–523 K (−170 to 250 °C) range were analyzed using both approaches, with the first principal component (PC₁) serving as a thermometric parameter in the PCA. The results show that crystal symmetry and site multiplicity strongly influence the temperature-dependent spectral evolution and, consequently, the thermometric response. LiLaP₄O₁₂ exhibits stable and well-defined spectral evolution, resulting in balanced thermometric accuracy and resolution. YNbO₄ shows enhanced sensitivity to temperature variations due to increased spectral complexity and stronger crystal-field effects, leading to improved resolution but increased calibration uncertainty. In contrast, Y₂O₃ exhibits reduced thermometric performance due to overlapping emissions from multiple crystallographically inequivalent sites with distinct thermal responses. Compared to LIR, PCA provides improved thermometric figures of merit, particularly in systems with complex and strongly overlapping emission bands, demonstrating the potential of full-spectrum analysis in luminescence thermometry. Full article

The rate control algorithm is designed for natural video by default in video-coding standards. However, computer-generated screen content video (SCV) is very different from natural video captured by a camera, with many different statistical characteristics, such as sharp edges, thin lines, and flat area. This will lead to a difference in the focus of the human visual system (HVS) when viewing on-screen content video. Especially in various sensor data visualization applications such as intelligent display terminals, industrial monitoring and human–computer interaction interfaces, screen content video carries key information collected and reconstructed by image sensors, vision sensors and multimodal sensors. Its edge structures and local details directly affect the interpretation accuracy and application reliability of sensor information. Therefore, it is crucial to investigate perceptual rate control methods that integrate both video content characteristics and human visual perception properties, which possesses substantial theoretical and practical significance. In this paper, we propose a perceptual rate control algorithm for screen content video based on just-noticeable distortion (JND) which is established on the edge profile reconstruction with tolerable variations. First of all, target bit rate allocation for the frame level and CTU level is based on a perceptual weight which is calculated on the JND factor and reconstruction edge character. Secondly, under the constraint of the JND model, an intra rate-distortion (RD) model is established under the constraint of the JND model. The similarity between reference frames and reconstructed frames is taken as feedback in this model. Finally, the proposed rate control algorithm (JND–perceptual rate control (PRC)) is integrated to the existing rate control framework in High-Efficiency Video Coding–Screen Content Coding (HEVC-SCC) for improving the coding efficiency. The experimental results show that the proposed algorithm achieves better bit control precision than the platform, as well as improves the R-D performance of screen content video. In particular, compared with the HEVC-SCC reference software, the coding performance is improved by 3.09 dB on average, the bit rate is saved by 26.51% on average, and the average bit rate mismatch is within 1.159%. Full article

Background: Chatbots are becoming increasingly valuable in clinical settings, offering rapid access to medical information, aiding documentation, and improving perioperative patient education. Their adaptability makes them promising tools for personalized perioperative risk stratification (PRS) and anesthesia planning, but their definitive role remains uncertain. We aimed to evaluate chatbot performance in PRS compared to standard clinical judgment and to assess the certainty of the evidence supporting their use. Methods: This systematic review (PROSPERO ID: CRD42025642357) followed PRISMA extended and PRISMA-S guidelines. The population was defined according to the PICO framework: we included adult surgical patients undergoing anesthesia assessment (P), evaluated with LLM-based chatbots for perioperative risk stratification and anesthesia planning (I), compared with traditional clinician assessment (C), and extracted performance metrics (O). Comprehensive searches of PubMed, MEDLINE, Scopus, Embase, Google Scholar, Open Gray, ClinicalTrials.gov, WHO ICTRP, and Cochrane Library Central were conducted through January 2026. Risk of bias and study quality were assessed using PROBAST-AI, RoB-2, and ROBINS-I. Certainty of the evidence was assessed using GRADE system. A random-effects meta-analysis of pooled chatbot accuracy was performed, with subgroup analyses by ASA status and perioperative risk stratification. A sensitivity analysis was performed with a leave-one-out exclusion test. Results: Eleven studies published between 2023 and January 2026 were included (N = 227,059 patients). Five prospective cohorts, two large retrospective cohorts, one randomized non-inferiority trial, and three non-clinical or mixed-methods studies were found. Meta-analysis showed that the pooled accuracy of LLM-based chatbots for AI–clinician concordance in perioperative risk stratification and ASA classification was 0.90 [95% CI: 0.42–0.99; 95% prediction interval 0.03–1.00]. Subgroup analyses indicated that the ASA status prediction subgroup reached a pooled accuracy of 0.91 (95% CI: 0.46 to 0.99), whereas the exploratory perioperative risk stratification subgroup showed an accuracy of 0.73 (95% CI: 0.10 to 0.98). Performance decreased with increasing patient complexity. Evidence is limited by small sample sizes, extreme sample size skew toward a single center, geographic bias, inconsistent outcome definitions and performance metrics, and incomplete reporting of adverse events. Most studies lacked prospective trial registration or robust control for confounding, and publication bias cannot be excluded. Conclusions: LLM-based chatbots show promising performance in routine perioperative risk stratification but remain unreliable in complex cases, with potential safety concerns. Given the overall very low GRADE certainty of evidence, these tools should be used as clinician-supervised decision support aids for routine ASA assessment, and should not be relied upon for autonomous use in complex cases or for general perioperative risk stratification. Other: This research received no external funding. PROSPERO ID: CRD42025642357. Full article

Deep eutectic solvent (DES) extraction is a green and efficient technology. As a substitute for organic reagents, DESs are widely used to extract active ingredients from traditional Chinese medicine. This study established an environmentally friendly and efficient method for extracting astaxanthin (AST) from Phaffia rhodozyma (PR) using ultrasound-assisted deep eutectic solvents (DESs-UAE). The astaxanthin content was determined by high-performance liquid chromatography (HPLC). Six types of deep eutectic solvents composed of DL-menthol and selected hydrogen bond donors were prepared and evaluated, among which the DL-menthol–acetic acid system showed superior extraction performance. Response surface methodology (RSM) was employed to optimize extraction parameters (ultrasonic power, time, and temperature), and the optimal conditions were determined as follows: ultrasonic power 420 W, ultrasonic time 20 min, and ultrasonic temperature 60 °C, achieving an AST extraction rate of 62% (2.49 mg/g). Compared with conventional organic solvent extraction, DESs exhibited a significantly higher AST extraction rate from PR, except for dimethyl sulfoxide (DMSO). Scanning electron microscopy (SEM) analysis demonstrated that DES-UAE treatment disrupted the cellular structure of PR, resulting in numerous surface pores; this facilitated the release of intracellular bioactive components and significantly improved AST extraction efficiency. The PR extract showed no significant cytotoxicity and could effectively promote L929 cell proliferation. It concentration-dependently increased superoxide dismutase (SOD) activity and decreased malondialdehyde (MDA) content in H₂O₂-induced oxidative stress L929 cells, thereby alleviating oxidative damage. Additionally, it concentration-dependently upregulated type I collagen expression in these cells, ameliorated the decline in collagen synthesis function, and exerted a protective effect against cellular oxidative damage. This study provides a green alternative to toxic solvents and offers important theoretical and chemical support for the extraction of natural products and the high-value utilization of Phaffia rhodozyma (PR). Deep eutectic solvents have emerged as promising green alternatives to hazardous organic solvents, yet hydrophobic DESs tailored for lipophilic astaxanthin extraction from Phaffia rhodozyma and the linkage between extraction performance and anti-aging bioactivity remain insufficiently explored. Here, an ultrasound-assisted hydrophobic deep eutectic solvent extraction strategy was constructed to acquire astaxanthin, aiming to overcome low efficiency and environmental risks of conventional organic extraction techniques. Six DL-menthol-based DESs were prepared and screened, and DL-menthol–acetic acid possessed the optimal extraction capacity. Key extraction parameters were optimized via response surface methodology, and the maximum astaxanthin extraction recovery reached 62% (2.49 mg/g) under 420 W ultrasonic power, 20 min treatment and 60 °C. This yield was markedly higher than that of most common organic solvents; though comparable extraction effect was obtained with DMSO, the adopted DES possessed outstanding low-toxic and biodegradable superiorities that DMSO cannot match. SEM characterization verified that the combined treatment destroyed yeast cell structure and formed porous morphology, which accelerated intracellular astaxanthin release and accounted for improved extraction efficiency. Biological assays proved the extract possessed good biosafety and proliferation-promoting effect on L929 cells. It effectively relieved cellular oxidative injury by elevating the SOD level and reducing MDA accumulation in oxidative damaged cells, and upregulated type I collagen expression to mitigate aging-related collagen loss. This work develops an eco-friendly and high-efficiency extraction route for lipophilic active substance, confirms the practical value of hydrophobic DES, and provides experimental basis for high-value utilization of Phaffia rhodozyma resources. Full article

Hepatoblastoma (HB), the most common pediatric liver cancer, exhibits marked variability in therapeutic response despite minimal genetic heterogeneity, implicating epigenetic regulation as a key driver of tumor behavior. Among these, polycomb repressor complexes (PRC) remain poorly explored as therapeutic targets. Integrative analysis of samples from patients with HB and public datasets identified BMI1, a core component of PRC1, as significantly upregulated, with high expression strongly associated with aggressive disease and poor survival. Functional screening of epigenetic inhibitors across 15 HB cell lines revealed BMI1 inhibition as the most effective therapeutic strategy, with strong concordance between in vitro predictions and in vivo responses in patient-derived xenograft (PDX) models. The BMI1 inhibitor PTC596 demonstrated the highest potency, consistently suppressing tumor growth across models. Mechanistically, PTC596 induced BMI1 degradation, reduced histone H2A ubiquitination, impaired microtubule dynamics, and restored intrinsic apoptosis by shifting the BCL2–BAX balance, leading to caspase-3/7 activation. Transcriptomic profiling confirmed apoptosis as the most significantly enriched pathway. In vivo, PTC596 markedly reduced tumor burden and proliferation while inducing pro-apoptotic signaling, without detectable toxicity. Together, these findings establish BMI1 as a critical oncogenic dependency in HB, demonstrate the value of robust preclinical tumor modeling for therapeutic validation, and identify PTC596 as a promising, mechanism-based treatment strategy. Full article

Real-time monitoring of lithium-ion capacitors (LICs) is crucial for ensuring reliability and predictive maintenance in dynamic applications such as electric transportation. However, traditional electrochemical impedance spectroscopy (EIS) techniques are complex and costly for onboard diagnostics due to their reliance on external excitation signals and dedicated hardware. Therefore, this paper presents an innovative framework for online state of health (SOH) estimation that bypasses these limitations by utilizing fast Fourier transform (FFT)-based passive impedance extraction directly from operational current and voltage signals. From experimental data, the equivalent circuit model (ECM) is developed, as well as its parameters, such as ohmic resistance, charge-transfer resistance, and Warburg diffusion. These parameters are identified through the extraction of impedance points in the low frequency region through FFT and the series resistance point using ohmic measurement, then performing a periodic curve fitting to these points. These curve fittings provide extracted ECM parameters. These parameters are used with a trained model to estimate the SOH of the monitored cell and are updated online. The proposed method was experimentally validated on five LIC cells aged under various C-rates (1C, 4C, 7C) and temperatures (35 °C, 40 °C, 50 °C), showing consistent impedance evolution with capacity fade. Validation of the utilized machine learning models, such as Polynomial Regression (PR), principal components analysis (PCA), and random forest (RF) regression, achieved SOH prediction errors as low as 2.23% compared to experimental results. The developed framework is particularly suitable for applications such as flash-charged electric buses but is broadly applicable across other energy storage systems as well. This advanced method enables real-time diagnostics without hardware modification, offering significant potential for integration into existing battery management systems (BMSs). Full article

The accumulation of intermediate products, particularly volatile fatty acids (VFAs) like propionic acid (HPr) or its dissociated form, can inhibit biogas production during anaerobic digestion (AD) at low concentrations. Knowledge about the response of microorganisms to VFA inhibition can help control the digesters. In this study, we aimed to determine how sodium propionate (NaPr) inhibits the AD of municipal sewage sludge by identifying shifts in the microbial community. Four 5 L reactors were operated in semi-continuous mode using sewage sludge and then loaded with different levels of NaPr. The reactors operated at 37 °C with two hydraulic retention times. The results show that there was no apparent inhibition of biogas production at NaPr loading up to 20.3 mmol·L⁻¹. However, moderate inhibition was observed at 81 mmol·L⁻¹, corresponding to an approximate 10% decrease in methane production, while a ≈40% decrease in methane production was observed at 135.3 mmol·L⁻¹. Sequencing analysis revealed that the community composition was dominated by Bacillota, Bacteroidota, Proteobacteria, Chloroflexi, and Cloacimonadota, with Halobacterota and Euryarchaeota as the main archaeal groups. PERMANOVA revealed incubation time as the primary driver of community structure, followed by NaPr concentration. Elevated NaPr levels resulted in a decline in Methanothrix and Methanobrevibacter and promoted distinct syntrophic propionate-oxidizing bacteria (SPOB). Full article

This study investigated the optoelectronic synaptic properties of amorphous gallium oxide (GaO_x) thin films for low-power physical reservoir computing (PRC) applications. The fabricated devices were irradiated with time series UV-C light to characterize the paired pulse facilitation (PPF) index, a fundamental synaptic property governed by transient photocurrent dynamics. Furthermore, the short-term memory (STM) capacity and parity check (PC) nonlinearity were quantitatively evaluated as essential PRC performance metrics, alongside a practical demonstration using a handwritten digit recognition task. The experimental results revealed a high PPF index when the width and interval of the input light pulses were comparable to or shorter than the inherent photocurrent time constants of the device. Although the evaluated nonlinearity was lower than that of conventional optoelectronic artificial synapses based on other semiconductor materials, the GaO_x device exhibited a comparable short-term memory capacity. Consequently, the reservoir layer achieved a high classification accuracy of approximately 90% in the handwritten digit recognition task. As these performance metrics were higher than those of the annealed sample, the device without annealing proved to be more suitable for PRC applications. These findings indicate that the amorphous GaO_x thin film device holds significant potential to serve as a robust, UV-C-responsive edge artificial intelligence (AI) sensor in harsh environments, such as outer space. Full article

Integration of lead zirconate titanate (PZT) films on metallic substrates is important for flexible piezoelectric devices, but achieving highly textured crystallinity without detrimental interfacial diffusion or oxidation remains challenging. In this work, PZT thick films (~1.3 μm) were deposited on titanium substrates using radio-frequency magnetron sputtering at 400 °C followed by rapid thermal processing at 640 °C for 2.5 min. A conductive LaNiO₃ buffer layer was introduced to promote the nucleation of the perovskite phase and suppress interfacial degradation. The resulting PZT films on the LNO/Pt/Ti substrates exhibit a strong (001) preferred orientation and a dense microstructure. The films show a large remnant polarization P_r of ~61 μC cm⁻² and a low coercive field E_c of ~56 kV cm⁻¹ at 60 V, together with a dielectric constant ε_r of ~1350–1612 and a dielectric loss tanδ ≤ 0.06 in the frequency range of 1 kHz to 1 MHz. Patterned Pt/PZT/LNO/Pt/Ti cantilevers yield a transverse piezoelectric coefficient e_31,f of ~−6.7 C/m², significantly outperforming reported piezoelectric films deposited on Ti. These results demonstrate that controlled nucleation and rapid thermal crystallization enable highly textured PZT films on reactive metallic substrates, providing a viable route for flexible piezoelectric MEMS devices. Full article

Total Electron Content (TEC) is a key parameter for characterizing the state of the ionosphere, and its spatiotemporal variations can significantly affect satellite navigation, radio communication, and space weather monitoring. To address the pronounced diurnal periodicity in global TEC map forecasting and the commonly neglected continuity at longitudinal boundaries, this study proposes an encoder–decoder ConvLSTM model that integrates periodic-matched residual prediction with longitude-circular boundary-aware convolution, namely the Longitude-Circular Periodic-Residual ED-ConvLSTM (LC-PR-EDConvLSTM). In the proposed model, the TEC map at the same temporal phase on the previous day is used as a periodic background field, enabling the network to focus on learning the residual variation in future TEC relative to this background. Meanwhile, longitude-circular padding is introduced into the convolution operations to preserve the spatial continuity of global TEC maps across the −180° and 180° meridians. Experiments were conducted using CODE global ionospheric map products from 2009 to 2019, with 12 TEC maps from the previous day used as inputs to predict 12 TEC maps for the following day. The results show that LC-PR-EDConvLSTM achieves RMSE values of 3.68 TECU and 1.37 TECU on the 2015 high-solar-activity test set and the 2019 low-solar-activity test set, respectively, outperforming the C1pg, ED-ConvGRU, and ED-ConvLSTM benchmark models. Ablation experiments further verify the effectiveness of the periodic-matched residual prediction strategy and the longitude-circular boundary-aware convolution. Analyses of typical space weather events and latitudinal regions demonstrate that the proposed model provides stable forecasting performance under complex space weather conditions and across most latitude regions. Full article

Background/Objectives. Breast cancer is the most frequently diagnosed cancer worldwide, with approximately 15% classified as Triple-Negative Breast Cancer (TNBC). TNBC is characterized by the absence of estrogen receptor (ER) and progesterone receptor (PR), and the lack of HER2 overexpression, limiting use of targeted therapies. Current TNBC treatment relies heavily on chemotherapy, most commonly taxanes including paclitaxel that stabilize microtubules, disrupt chromosome separation and induce apoptosis. TNBCs frequently develop chemoresistance after multiple treatment cycles, highlighting a critical unmet need for novel therapeutic strategies. This study addresses this challenge by targeting salt-inducible kinase 2 (SIK2), which is overexpressed in 85% of TNBCs compared to normal breast tissue. Methodes. In collaboration with Arrien Pharmaceuticals and Greenfire Biologics, we developed ARN-3261/GRN-300, a novel orally bioavailable SIK2 inhibitor and evaluated its ability to sensitize TNBC cells to paclitaxel in vitro and in vivo. Results. GRN-300 demonstrated strong synergy with paclitaxel in all eight TNBC cell lines tested, as indicated by favorable combination indices. In xenograft models, the combination therapy significantly enhanced tumor growth inhibition and prolonged survival compared to either agent alone. Mechanistic studies showed that GRN-300 disrupts the anaphase-promoting complex/cyclosome (APC/C) pathway by downregulating key mitotic regulators, including CDC27, CDK1, and PLK1, thereby potentiating G2/M cell cycle arrest and apoptosis. Conclusions. Together, these findings establish GRN-300 as a promising therapeutic agent that enhances paclitaxel efficacy through complementary disruption of mitotic regulatory pathways, providing strong preclinical rationale for clinical development in TNBC. Full article