Search Results (11,513)

Acid mine drainage (AMD) pollution from closed coal mines in karst regions represents a major environmental challenge in the global mining industry. The complexity of hydrogeological conditions in such regions leads to significant challenges in both predictability and controllability of pollution. Taking the Yudong River Basin in Guizhou Province, Southwest China, as the study area, and based on six years (2017–2023) of systematic remediation practices and monitoring data, this study systematically evaluates the effectiveness and applicable conditions of three types of treatment technologies: centralized treatment stations, source control combined with end-of-pipe treatment, and water-sealing ecological plugging. On this basis, governance models applicable to karst regions are distilled. The results show that after six years of remediation, the number of pollution points in the Yudong River Basin decreased from 27 to 12. At the outflow section, the total Fe reduction rate reached 88.3%, the total Mn reduction rate reached 62.3%, and the proportion of contaminated river length was reduced by 78.5%. Each of the three technologies has its own applicable conditions. Centralized treatment stations, characterized by mature technology but high operational costs, are suitable for emergency transition periods. Source control combined with end-of-pipe treatment addresses both symptoms and root causes, making it applicable to complex pollution points. Water-sealing ecological plugging, although cost-controllable, carries a risk of secondary pollution in karst-developed areas. The failure of water-sealing ecological plugging technology is mainly attributed to two mechanisms: bypass flow through karst conduits and overflow induced by water level rise. Based on the six-year remediation practice, this study proposes a source control model for karst conduits centered on the core concepts of “filling, isolating, plugging, intercepting, draining, and controlling”. The implementation process consists of four stages: detailed investigation, graded optimization, stepwise implementation, and long-term monitoring. The core innovation lies in the cross-disciplinary application of coal mine water control techniques to environmental remediation, achieving a shift from passive end-of-pipe treatment to active source control. This model can provide theoretical reference and practical guidance for karst mining areas in Southwest China and other regions with similar geological conditions. Full article

The Probability Hypothesis Density (PHD) filter based on the Track-Before-Detect (TBD) approach is a key technique for detecting weak targets whose numbers are unknown and time-varying. To overcome the limitations of existing algorithms, such as high computational cost, poor real-time performance, and low tracking efficiency in dense clutter, this paper proposes a fast non-sequential particle PHD filter for TBD. Specifically, an adaptive particle generation method based on differential localization is introduced in the prediction stage, allowing newly generated particles to quickly concentrate around potential target locations. In the update stage, particles are divided into three groups to simplify weight calculation and improve efficiency. Furthermore, a parallel resampling strategy is adopted to further enhance real-time performance. Numerical experiments demonstrate that the proposed method maintains tracking accuracy with only a small number of particles, thereby significantly reducing computational complexity and improving real-time capability. This work offers a practical reference for the engineering deployment of TBD algorithms. Full article

Vibrio tubiashii infection has led to several Babylonia areolata pandemics on the southeast coast of China, yet the immune response of the ivory shell against V. tubiashii and the specific pathogen–host interaction remain unclear. This dynamic study aimed to characterize the response of B. areolata to V. tubiashii infection with the use of pathology, transcriptomics, an enzymatic assay, and inflammatory cytokines. Hepatopancreatic cells showed marked vacuolar degeneration with intact cell membrane and extensive cytoplasmic vacuolization after infection. The dynamic transcriptome of the hepatopancreatic tissue was analyzed by RNA-seq after V. tubiashii infection, and a total of 2733 (3 h), 5610 (24 h), 3323 (48 h), and 418 (72 h) differentially expressed genes (DEGs) were identified during infection. The GO and KEGG analyses showed that the DEGs were enriched in metabolic regulation, lysosome, and multiple immune-related pathways such as the MAPK signaling pathway. The immune response of B. areolata was distinct, where the early stage of immune response (3 h) showed binding, focal adhesion, and apoptosis, as well as an activated antioxidant system. Here, expression of TNF-α, IL-1, and IL-8 was significantly increased in the hepatopancreas, whereas expression of IL-6 and IL-17 increased afterward. During the middle stage (24 h and 48 h), a large number of DEGs were suppressed, especially those associated with metabolism and lysosomes, although their expression returned to normal during prolonged infection (72 h). The PPI network showed that ppp2, atp6, and sos1 were the top immune-related DEGs during infection. Key infection-related and time-course-related genes were analyzed by WGCNA. This study illustrates that oxidative stress, inflammation, and apoptosis are strategies of the hepatopancreatic immune response in B. areolata against V. tubiashii infection and enlightens conservation and production by furthering our understanding of gastropod immunity. Full article

An automated CFD-based workflow for the design, evaluation, and comparative optimization of 2D tidal-stream turbine blade sections is presented for early-stage design exploration. The workflow is intended to efficiently derive an improved section using a consistent and higher fidelity evaluation approach, which is particularly relevant for floating tidal concepts where the effective angle of attack can vary. HEEDS is used to manage a SHERPA optimization loop, while candidate geometries are regenerated in Rhino Grasshopper through a control point parameterization with thickness bounds and smooth interpolation. STAR-CCM+ simulations are executed in an automated manner and the resulting lift and drag responses are returned to HEEDS to evaluate performance over four representative angles of attack, 0, 3, 6, and 9 deg. A total of 1000 design evaluations are conducted for a baseline NACA 63–815 section at Reynolds number 1 × 10⁷, using a two metric formulation that targets high mean lift to drag ratio while limiting the maximum drag coefficient within the same angle set. The optimization history shows rapid early improvement followed by a plateau and identifies a final best design at Design 746. Compared with the original section, the optimized section increases lift and improves the lift-to-drag ratio across the operating range, while keeping the peak drag constrained. Cavitation inception characteristics also improve, with the optimized section delaying inception at the same lift criterion and sustaining a cavitation free state at higher lift for the same cavitation number. Pressure coefficient distributions indicate that these changes are primarily associated with altered suction side loading in the front to mid chord region and modified pressure recovery behavior. A preliminary full 3D RANS CFD rotor comparison under a prescribed rotor geometry further shows that the optimized section can improve rotor power performance in the main operating TSR range, although the benefit becomes limited at high TSR. Full article

Pancreatic ductal adenocarcinoma (PDAC) is molecularly characterized by near-universal KRAS mutations and recurrent alterations in TP53, CDKN2A, and SMAD4. Gene fusions are exceptionally rare and have not been established as canonical drivers of PDAC. We report a case of metastatic PDAC harboring an EIF3E::RSPO2 gene fusion in the absence of detectable KRAS or other common driver mutations. A 48-year-old female was diagnosed with stage IV PDAC via endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA). Comprehensive molecular profiling using the Oncomine Precision Assay GX5 revealed no pathogenic single-nucleotide variants, indels, or copy number variations. However, an EIF3E::RSPO2 fusion, predicted to be a gain-of-function alteration, was identified as the sole genomic alteration. Immunohistochemistry showed retained mismatch repair protein expression and preserved SMAD4. Although RSPO2 fusions have been described in preclinical colorectal cancer models and are well-established activators of the Wnt signaling pathway in this setting, their clinical occurrence in PDAC remains poorly documented. This finding indicates a KRAS wild-type tumor with a potential KRAS-independent oncogenic mechanism that may involve aberrant Wnt/β-catenin signaling and raises the possibility of a rare, biologically distinct PDAC subset. Comprehensive genomic profiling in advanced PDAC may uncover actionable non-canonical drivers with therapeutic implications. Full article

Compared with hardware-dependent methods, light field (LF) reconstruction algorithms enable a more economical and convenient acquisition of densely sampled LF (DSLF). Existing learning-based LF reconstruction methods suffer from limited flexibility, as they rely on fixed sampling patterns and predefined angular resolutions. In this paper, we propose a flexible deep learning framework, which can reconstruct DSLF with arbitrary angular resolution from randomly distributed sparse input views of an arbitrary quantity. The proposed framework consists of two core stages, namely the SAI Synthesis and the LF Refinement. The SAI Synthesis adopts Plane Sweep Volume (PSV) to cope with randomly sampled input views, and leverages the Multi-Scale Attention (MSA) module to compute per-view weights for adaptive feature fusion and support arbitrary numbers of input views. The LF Refinement stage integrates intermediate results and fully exploits LF parallax structures to further improve reconstruction quality. Experimental results demonstrate that our method achieves superior flexibility and reconstruction quality, and outperforms most state-of-the-art LF reconstruction methods. Full article

Background: The management of diabetic foot disease and knee osteoarthritis (OA) with smart orthotics holds significant importance during the early stages of these conditions, given their potential consequences, including functional impairment, chronic pain, and economic burden. Real-time monitoring of plantar foot pressure enables early detection of abnormal force distribution and gait biomechanics, allowing for the redirection of forces away from affected ulcers or arthritic joints. This is the first systematic review to synthesise clinical evidence for smart orthotics technology with real-time plantar pressure sensor biofeedback across both diabetic foot ulcer prevention and knee osteoarthritis management simultaneously. A search of the PROSPERO register confirmed no existing registration covers this specific combination. Objectives: To examine the clinical evidence for the use of standard and smart orthotics in the prevention and management of diabetic foot ulcers (DFUs) and knee OA, and to evaluate their impact on plantar pressure redistribution, ulcer recurrence, pain, biomechanics, and economic burden. Eligibility criteria: Studies published in English involving human adult participants (≥18 years) with a clinical diagnosis of diabetes mellitus (at risk of DFU or with peripheral neuropathy) or knee OA, where the intervention involved any orthotic device or smart/intelligent insole with clinical outcomes reported, were included. Studies on healthy individuals only, those not reporting participant age, and non-weight-bearing protocols not differentiated from weight-bearing were excluded. Information sources: Five databases were searched: CINAHL (EBSCO Information Services, Ipswich, MA, USA), PubMed Advanced (National Library of Medicine, Bethesda, MD, USA), Wiley Online Library (John Wiley & Sons, Hoboken, NJ, USA), Cochrane Library (Cochrane Collaboration, London, UK), and Google Scholar (Google LLC, Mountain View, CA, USA). Searches were completed in May 2026. Methods: We conducted a comprehensive literature review. This review was structured and reported with reference to the PRISMA 2020 statement (Preferred Reporting Items for Systematic Reviews and Meta-Analysis; University of Ottawa, Ottawa, ON, Canada) to guide transparency of reporting. It does not constitute a full Cochrane-style systematic review; risk of bias assessment was applied to key included studies and GRADE (Grading of Recommendations Assessment, Development and Evaluation; McMaster University, Hamilton, ON, Canada) certainty ratings were applied informally and narratively rather than as formal per-outcome evidence profiles. Five databases were searched yielding 92,637 records. After removal of 398 duplicates by Rayyan, 92,239 records remained. A subsequent automated keyword-based relevance filter applied within Rayyan (Rayyan AI, Doha, Qatar), prior to human screening, excluded 84,572 records that did not contain any terms related to orthotics, diabetic foot, or knee osteoarthritis, yielding 7667 records for human title/abstract screening. A narrative synthesis approach was adopted owing to the heterogeneity of study designs and outcome measures across included studies, which precluded meta-analysis. This review was not prospectively registered. A complete list of all 78 included studies, including those not individually discussed in the results and discussion. Results: The available clinical studies report promising findings for orthotics and smart orthotics in pain reduction, ulcer prevention, and potential reduction in economic burden, though conclusions are limited by small sample sizes, heterogeneity, and predominantly open-label designs. Recent research found that orthotics can be used to alter the gait pattern that influences knee OA by reducing excessive force on the affected joint. A randomised controlled trial demonstrated an 80% relative risk reduction in DFU recurrence (RR = 0.20; 95% CI: 0.06–0.79; p = 0.022), with absolute event rates of 6.3% in the intervention group versus 30.8% in controls (ARR = 24.5%); a second trial reported a 71% reduction in ulcer incidence over 18 months; and a third randomised controlled trial demonstrated statistically significant plantar pressure reduction (p < 0.01) in patients with diabetic neuropathy. Conclusions: The available evidence suggests that orthotics may be associated with improved pressure redistribution, reduced ulcer incidence, and benefit in the management of knee OA. Although the number of studies directly comparing smart orthotics with standard orthotics remains limited, the limited comparative studies suggested that smart orthotics showed promising results in reducing ulcer incidence, providing the patient with real-time feedback to offload via their electronic devices. These findings, while preliminary, highlight the potential of smart orthotic technology as an adjunct to standard orthotic care in reducing the overall burden of diabetic foot disease and knee osteoarthritis. Limitations: The primary methodological limitation of this review is the open-label design of all included smart orthotic trials, which precludes participant blinding and introduces performance bias. However, this limitation is structural and inherent to the wearable technology field—analogous to surgical trials—and is substantially mitigated by the use of objective primary outcome measures (plantar pressure and ulcer recurrence) across the three included RCTs, the consistency of effect direction across independent RCTs conducted in different countries, and a narrative sensitivity analysis confirming robustness of findings (Risk of Bias Across Studies Section). Formal per-outcome GRADE evidence profiles were not produced; overall certainty of evidence was assessed narratively with reference to GRADE domains and is judged to be low to moderate for smart orthotics in DFU prevention and low for knee OA management, consistent with the Level 2–3 evidence base and open-label study designs. Future adequately powered, multi-site RCTs with standardised outcome reporting, minimum 24-month follow-up, and integrated health economic modelling are the highest priority to extend these preliminary findings. Registration: This review was not prospectively registered. Full article

Climatic variation is inherently linked with tree phenology; however, phenological triggers depend on species and habitat. We analyzed key climatic factors for the onset of secondary growth for Scots pine (Pinus sylvestris L.) at the southern limit of its distribution in Siberia. From direct observations of developing tree rings, seasonal curves of the number of cells in the cambial zone, in the cell-expansion zone, and the total number of xylem tracheids were developed over seven years with a wide variety in the phenological dates. We found that later and shorter intervals of these stages of xylogenesis were compensated by higher maximums of kinetics curves, probably due to higher temperatures and daylengths during the respective phenophases. Air temperature and soil temperature at a depth of 20 cm converged to values (mean ± SE) 6.6 ± 0.9 °C (air) and 3.7 ± 0.4 °C (soil) for a 15-day interval prior to cambial activity onset. Date of Tsoil ≥ 3.5 °C was most closely related to cambial activity onset (r = 0.99) and preceded it by 9.6 ± 1.1 days. Cumulative temperature sums were less reliable. Apparently, both air and soil temperature thresholds have to be reached for cambial division to start in this species-habitat combination. Late abundant snowfall can yield divergence between air and soil temperatures and delay the onset of xylogenesis. Full article

To protect human health and the environment, it is necessary to reduce the number of solid particles and harmful gases in the air or to minimize such pollution. Filtration and separation devices are intended for various industrial operations to capture pollutants from various technological processes. In the introduction, this article points out the use of cyclone filters in individual operations, names the most frequently occurring elements of pollution, and suggests the most suitable method of separation. In paint shops, grinding shops, welding workplaces, machining lines, and when handling powder materials, particles with very different properties are created. An important advantage of using cyclone filters is not only their simple construction but also their usability at high temperatures and pressures. Furthermore, this article highlights that cyclones are easy to maintain, typically contain no moving parts, are simple to manufacture, and are cost-effective, particularly as pre-filtration devices. Their efficiency generally ranges from 50% to 99% and is strongly influenced by design and operating parameters, especially cyclone geometry, which affects pressure drop, flow structure, cut diameter, and fractional collection efficiency. The article also summarizes that various modifications of the inlet, vortex finder, outlet pipe, and cyclone body have been proposed to enhance separation performance, particularly for smaller particles. Nevertheless, due to the centrifugal and inertial nature of cyclone separation, fine and submicrometric particulate matter remains difficult to remove using cyclones alone. Fabric filters are also analyzed as a possible solution, but high loading by coarse particles may cause clogging, increased pressure drop, and higher maintenance costs. In the end, the combination of a cyclone with an electrostatic precipitator is presented as a staged separation approach, enabling efficient removal of both coarse particles and fine particulate matter from the gas stream. Full article

The bearded dragon (Pogona vitticeps) is the most commonly kept pet lizard and a promising model organism for studies of sex determination and gonadal development. Despite its potential, the morphological basis of gonadogenesis in this species remains poorly characterized. Here, we provide a comprehensive histological characterization of gonad development in P. vitticeps using serial paraffin and semi-thin sections, supplemented by morphometric analyses. Gonadal ridges first appeared at stage S28 as bilateral thickenings of the coelomic epithelium, coinciding with primordial germ cell colonization; by S28/29, a recognizable cortex and medulla were already present. The first morphological differences between male and female gonads appeared at S29/30. In differentiating testes, well-defined testis cords with a central lumen formed rapidly, while the cortex became thin and retained only scattered germ cells. Testicular development was characterized by rapid lumen formation within the testis cords, resulting in their early transformation into seminiferous tubules, followed by elongation and coiling of the tubules, maintenance of a stable tubule diameter, and a transient mitotic arrest of germ cells, with proliferation resuming at stage S36. In differentiating ovaries, the cortex remained thick and multilayered, with a progressive increase in germ cell number reflecting active oogonial proliferation. The ovarian medulla expanded substantially, and from S36 onward, lacunae developed within the medullary cords. No meiotic cells were observed at any examined stage. These results provide an essential morphological framework for future molecular and experimental studies of sex determination and gonadal differentiation in this species and in squamates more broadly. Full article

Background/Objectives: Only substantial quantities of xeno-free human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs) (hiPSC-CMs) with stable quality and structural and functional maturity can meet the demand for cardiac cell therapy. The use of xeno-free microcarriers can significantly increase cell yield. Co-culturing with hematopoietic stem cells (HSCs) simulates the environment in vivo and has a necessary impact on the development of CMs. However, no microcarrier-based protocol for xeno-free hiPSC-CM culture has yet been established, and the effects of HSCs on CM development and their underlying mechanisms remain unclear. Therefore, this study aims to investigate these issues. Methods: We used a xeno-free microcarrier (plastic) culture system coated by a defined xeno-free matrix (MatriClone) to expand hiPSCs and hiPSC-CMs with human hematopoietic stem cells (hHSCs). Using RNA sequencing (RNA-seq), cytokine assay, and various cellular molecular techniques, we investigated the role of hHSCs in cardiac differentiation and maturation, and underlying mechanisms. Results: hiPSCs were evenly distributed on the surface of plastic coated with 1 μg/cm² MatriClone (MatriClone-Plastic), increasing and sustaining pluripotency marker levels. Directed differentiation of hiPSCs on 1 μg/cm² MatriClone-Plastic induced a larger number of CMs, and the level of cardiac differentiation was also significantly improved. When hHSCs were co-cultured with cells at the cardiac progenitor cell stage, results from electron microscopy, electrophysiology, and qPCR showed that hiPSC-CMs significantly promoted cardiac structural and functional maturation. The co-cultured hHSCs released multiple cytokines that were changed dynamically at different time points, and that were highly likely to activate the epidermal growth factor receptor (EGFR)/mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling pathway to promote cardiac development and maturation. Conclusions: hHSCs can efficiently promote differentiation and maturation of xeno-free hiPSC-CMs on MatriClone-Plastic via the EGFR/MAPK/ERK signaling pathway. Full article

Background/Objectives: Periodontitis is a highly prevalent chronic disease requiring accurate diagnosis for effective treatment planning. Artificial intelligence (AI) has emerged as a potential tool to support clinical decision-making. This study aimed to compare the diagnostic performance and classification error patterns of a large language model (LLM) and a neural network (NN) in periodontitis classification according to the current staging and grading system. Methods: This retrospective study included 110 patients with periodontal disease. Clinical and demographic variables (age, sex, smoking status, number of teeth, API, BOP, PPD, and CAL) were analyzed. Reference diagnoses were established by two experts. Cases were evaluated using an LLM and a neural network. Model performance was assessed using accuracy, confusion matrices, and Cohen’s kappa coefficient, along with error analysis. Results: The LLM achieved 62% accuracy for stage and 63% for grade classification (κ = 0.48). The neural network showed higher performance, with 85% accuracy for stage and 79% for grade (κ = 0.79 and κ = 0.67, respectively). The LLM more often underestimated disease severity, whereas the neural network tended to overestimate progression. Differences between models were statistically significant (p < 0.0001). Conclusions: In this dataset and classification task, the task-specific neural network demonstrated higher diagnostic performance than the evaluated large language model. However, the findings should be interpreted in light of the fundamentally different training paradigms and intended applications of these AI systems. Further research is required to optimize and validate AI-based approaches for clinical use. Full article

Early flowering-related factors play pivotal roles in coordinating plant growth and reproductive development. In this study, we investigated the biological function of early flowering gene (ELF) in Arabidopsis thaliana using CRISPR/Cas9-mediated genome editing and construction of overexpression approaches. Two independent ELF overexpression (OE-ELF) and genome-edited (ge-elf) lines were generated and systemically analyzed. ELF overexpression significantly enhanced early seedling performance, increasing germination rate and seedling fresh weight by up to 8.7%, while genome-edited lines exhibited a marked reduction. Root growth was strongly promoted in OE-ELF plants, with root length increase of 85% and 75%, whereas ge-elf lines showed a reduction of up to 48%. At later developmental stages, OE-ELF plants displayed enhanced vegetative growth, including increased leaf length (32%), leaf area (91%), and accelerated flowering (21% earlier than wild type). In contrast, ge-elf delayed flowering by up to 25% and resulted in compact plant architecture. Reproductive development was severely compromised in ge-elf plants, which exhibited malformed inflorescences, reduced pollen germination, shortened silique (45%), and a drastic decrease in seed number per silique (70%). Conversely, OE-ELF plants showed increased silique number and seed per silique. Molecular analysis revealed that ELF positively regulates key flowering-related genes, including FLC, SOC1, AP1, and LFY, which correlated strongly with growth and reproductive traits. Our results demonstrate that ELF functions as a central regulator integrating vegetative growth, floral development, male fertility, and seed production in Arabidopsis thaliana. Full article

The fractal characteristics of coal pore–fracture networks and their evolution under compression are essential for predicting rock mass failure and fluid transport. This study combines micro-CT scanning with fractal theory and seepage mechanics to investigate the structural evolution of coal under uniaxial compression and its impact on fluid transport. CT scans were performed at four characteristic stages (initial, elastic, plastic, and failure) to reconstruct three-dimensional fracture networks. Quantitative analysis reveals that fracture porosity increases sequentially from 0.44% to 5.01%, with the failure stage reaching 11.4 times the initial value. Fracture length and aperture distributions follow power-law scaling, and their fractal dimensions exhibit distinct evolution patterns: length dimension increases from 2.43 to a peak of 2.56 in the plastic stage and then drops to 2.47 at failure, while aperture dimension decreases from 2.29 to a trough of 2.12 before rebounding to 2.26. These patterns reflect a dynamic adjustment of network complexity, transitioning from primary fractures to micro-fracture dominance and finally to main fracture coalescence. Based on the Knudsen number, three diffusion regimes of Fick, transition and Knudsen are identified. A fractal permeability model is developed by idealizing the pore space as tortuous capillaries, showing that permeability scales with the fourth power of the maximum pore diameter and is positively influenced by the fractal dimension and the number of large pores. Furthermore, a coupled seepage–stress model is derived, incorporating pressure transmission, shear transmission, and crack opening coefficients. The damage variable is expressed as a function of stress level and fractal dimension. These findings provide theoretical support for predicting gas transport and failure behavior in coal under coupled hydro-mechanical conditions. Full article

Immunotherapy has transformed cancer treatment; however, clinical benefit remains limited to a subset of patients, underscoring the need for robust biomarkers that capture tumor-immune interactions across cancer types. In this study, we performed a comprehensive pan-cancer, multi-omics characterization of the immune checkpoint–related molecules CD70, CD80, and TIGIT to evaluate their diagnostic, prognostic, and immunological relevance. Using integrative analyses of transcriptomic, epigenomic, genomic, pharmacogenomic, and single-cell RNA-sequencing data from The Cancer Genome Atlas and complementary resources, we assessed expression patterns, DNA methylation, somatic mutations, copy number alterations, immune infiltration, tumor stemness, and drug sensitivity. CD70, CD80, and TIGIT were broadly dysregulated across multiple malignancies, with coordinated overexpression particularly evident in kidney renal clear-cell carcinoma. Elevated expression of these immune checkpoints was associated with advanced tumor stage, aggressive molecular subtypes, and unfavorable survival outcomes in selected cancers, including uveal melanoma and renal malignancies. Functional analyses revealed significant associations between checkpoint expression and key oncogenic pathways, including epithelial–mesenchymal transition, apoptosis, and hormone receptor signaling, suggesting links with tumor progression and immune activation states. Immune deconvolution analyses indicated that TIGIT expression is associated with a T-cell–inflamed microenvironment and reduced neutrophil infiltration, while CD80 exhibited methylation-dependent associations with immune cell composition. Genomic and epigenetic alterations were found to correlate with checkpoint expression patterns and immune phenotypes across tumor types. Pharmacogenomic profiling identified associations between checkpoint expression and sensitivity to multiple anticancer agents; however, these findings are based on cell line datasets and should be considered predictive. Single-cell transcriptomic analyses further resolved cell-type–specific expression patterns, distinguishing tumor-intrinsic from immune-restricted expression profiles. Collectively, our findings establish CD70, CD80, and TIGIT as integrative biomarkers of tumor progression, immune contexture, and therapeutic response, providing a rationale for their clinical exploitation in precision immuno-oncology. Full article