Search Results (3,474)

Multiple myeloma (MM) is a genetically and clinically heterogeneous plasma cell malignancy characterised by clonal expansion of differentiated B cells within the bone marrow (BM). Patients start with monoclonal gammopathy of undetermined significance (MGUS) and progress to an intermediate stage called smouldering multiple myeloma (SMM), characterised by several genetic alterations that represent the genomic backbone of the malignant clone. Immune checkpoint pathways play a central role in shaping an immunosuppressive BM niche, contributing to T-cell dysfunction, immune evasion, and therapeutic resistance. Key inhibitory receptors such as PD-1, CTLA-4, TIM-3, LAG-3, and CD47 are frequently dysregulated, promoting T-cell exhaustion, anergy, and senescence. Emerging evidence highlights extracellular vesicles (EVs) as critical mediators of intercellular communication in MM. MM-derived EVs carry bioactive cargo, including proteins and miRNAs, that reprogram immune and stromal cells, enhancing tumour progression and immune escape. Notably, EV-associated immune checkpoint molecules contribute to the establishment of a permissive microenvironment. This review provides an integrated overview of immune checkpoint dysregulation and EV-mediated immunomodulation in MM, emphasising their role in disease pathogenesis and progression. Furthermore, we discuss the therapeutic potential of targeting immune checkpoints and exploiting EVs as novel biomarkers and drug delivery systems, highlighting their promise for improving precision medicine approaches in MM. Full article

Astragalus membranaceus is an important medicinal plant with considerable pharmacological and economic value; however, its growth and productivity are frequently threatened by drought stress. Basic leucine zipper (bZIP) transcription factors play crucial roles in plant growth, development, and abiotic stress responses, yet a comprehensive investigation of the bZIP gene family in A. membranaceus remains unavailable. In this study, 74 bZIP genes (AmbZIPs) were identified in the A. membranaceus genome and classified into 12 subfamilies based on phylogenetic relationships with Arabidopsis thaliana. Analyses of gene structure, conserved motifs, chromosomal distribution, and duplication events revealed high conservation within subfamilies and indicated that segmental duplication was the major driver of AmbZIP family expansion. Codon usage analysis showed that AmbZIP genes exhibited relatively weak codon usage bias, with codon preference predominantly shaped by natural selection rather than mutation pressure. A total of 23 optimal codons were identified, of which 91.3% were A/T-ending codons. Codon adaptability analysis further demonstrated that tobacco possessed the highest codon compatibility among five tested hosts, whereas Escherichia coli exhibited the lowest adaptability, suggesting that plant expression systems may be more suitable for functional studies of AmbZIP genes. Promoter analysis identified numerous cis-acting elements associated with phytohormone signaling and abiotic stress responses, particularly those related to abscisic acid, methyl jasmonate, salicylic acid, and drought responsiveness. Transcriptome analysis and quantitative real-time polymerase chain reaction (qRT-PCR) validation revealed that several AmbZIP genes were significantly induced under drought stress. Among them, AmbZIP46 displayed strong drought-responsive expression, transcriptional activation activity, and exclusive nuclear localization. These findings provide the first comprehensive characterization of the bZIP gene family in A. membranaceus and establish a valuable foundation for elucidating drought-tolerance mechanisms and facilitating molecular breeding in this medicinal plant. Full article

The mammalian gut microbiome functions as a metabolically active immunological organ and has co-evolved with its host to maintain systemic homeostasis. This review integrates current evidence on the molecular mechanisms governing bidirectional microbiota–immune communication, emphasizing evolutionary conservation, receptor-mediated signaling, and translational implications. Microbial structural ligands and metabolites—including short-chain fatty acids, bile-acid derivatives, and tryptophan catabolites—engage host receptors such as G-protein-coupled receptors, FXR/TGR5, and the aryl hydrocarbon receptor (AhR), thereby regulating epithelial barrier integrity, regulatory T-cell differentiation, Th17 polarization, mucosal IgA production, and systemic immune tone. Riboflavin-derived metabolites presented via major histocompatibility complex class-I-related molecule (MR1) further shape mucosal-associated invariant T-cell development (MAIT), illustrating metabolite-driven immune system programming. Dysbiosis induced by antibiotics, dietary perturbation, or aging disrupts these molecular networks, promoting chronic inflammatory, metabolic, autoimmune, and neuroimmune disorders. Comparative analyses across mammalian systems underscore conserved pathways of host–microbe coadaptation and immune education. Therapeutically, microbiota-modulating strategies—including probiotics, prebiotics, synbiotics, fecal microbiota transplantation (FMT), postbiotics, and IgY-based passive immunotherapy—aim to restore immunometabolic signaling. Emerging in vitro and in silico platforms further provide mechanistic precision while supporting ethically aligned translational research. Collectively, these insights position microbiota-derived molecular signaling as a central determinant of adaptive immune architecture and a targetable axis in precision immunotherapy. Full article

The integration of AI-generated content into higher education has intensified interest in how students form and calibrate trust toward algorithmic outputs and whether pedagogical relationships can serve as conduits for that trust. Grounded in Trust Transfer Theory, this between-subjects randomized experimental study (N = 320) investigated whether teacher endorsement shapes students’ perceptions of AI-generated educational content across four dimensions: Perceived AI Competence, Academic Integrity, Perceived Human-Mediated Reliability, and Behavioral Intention to adopt. Participants from Saudi Arabian universities were randomly assigned to an endorsed or non-endorsed vignette condition and responded to a validated 13-item Trust and Acceptance Scale. Independent-samples t-tests confirmed statistically significant differences across all four dimensions in favor of the endorsed condition, with effect sizes ranging from small to large, and findings remained robust after controlling for gender via ANCOVA. Within-condition regression analyses further established Perceived Human-Mediated Reliability as a structurally stable positive predictor of trust outcomes in both conditions, with predictive power consistently amplified under endorsement. Postgraduate students placed greater emphasis on human oversight, while no disciplinary differences emerged, confirming the cross-disciplinary universality of the trust transfer mechanism. These findings are consistent with positioning the teacher as a trust guarantor in AI-mediated learning environments and carry direct implications for pedagogical design and institutional AI governance. Full article

The Upper Minjiang River Basin is a critical ecological barrier in the upper Yangtze River, where forest ecosystems play a vital role in carbon sequestration, water conservation, and soil retention. Given that different forest types exhibit significant variations in community structure, species composition, and ecological processes, their ecosystem service (ES) supplies and trade-off/synergy relationships are also expected to show distinct heterogeneity. However, systematic research on the trade-offs and synergies of ESs across different forest types remains limited, constraining the development of precision forest management and differentiated management strategies. To deal with this, we used the InVEST model and calculated five key services across the basin: carbon stock (CS), water yield (WY), soil conservation (SC), habitat quality (HQ), and forest stock volume (FSV). We then applied Spearman’s correlation, root mean square deviation (RMSD), and the GeoDetector model to analyze trade-offs and uncover driving mechanisms. Finally, we used spatially constrained K-means clustering to map different management zones. The results indicate that the Upper Minjiang River Basin stored 1.78 × 10⁸ t of carbon, retained 2.98 × 10⁸ t of soil, produced 6.48 × 10⁹ m³ of water yield, maintained a mean habitat quality of 0.78, and supported a forest stock volume of 1.20 × 10⁸ m³. Coniferous forests exhibited the highest CS (181.07 t ha⁻¹) and FSV (176.37 m³ ha⁻¹), whereas shrublands contributed the largest share (52.17%) of regional water yield. At the regional scale, CS and FSV showed the strongest synergy (r = 0.71, p < 0.01), while WY displayed significant trade-offs with most other services. GeoDetector analysis revealed that forest type acts as the primary driver shaping the relationships among services, while elevation and precipitation play supporting roles. Based on the ES bundles identified via spatially constrained K-means clustering, the Upper Minjiang River Basin was divided into four distinct management zones: a carbon sequestration core zone, an ecological balance zone, an ecologically fragile zone, and a multifunctional conservation zone. Therefore, findings from the Upper Minjiang River Basin may provide insights applicable to other mountain forest ecosystems facing similar environmental and management challenges. Full article

Diffusion-based image super-resolution (SR) has recently achieved impressive perceptual quality by progressively generating plausible high-resolution details. However, its restoration performance still depends strongly on the reliability of the conditioning signal derived from degraded low-resolution inputs. Under severe or complex degradations, LR-derived conditions may become incomplete or ambiguous, leading the denoising trajectory toward visually plausible but input-inconsistent reconstructions. This work focuses on a central question: how to construct reliable multimodal prior guidance for a diffusion backbone that commonly adopts a hierarchical U-shaped architecture. To this end, we propose STMP-DiT, a stage-aware text-aligned multimodal prior-guided Diffusion Transformer for image super-resolution. From a multimodal data mining perspective, STMP-DiT aims to discover, align, and organize complementary semantic and structural priors from heterogeneous foundation-model representations. To improve the reliability of semantic guidance, STMP-DiT first aligns LLaVA-derived LR prompts with the frozen CLIP HR-image embedding space, producing visually grounded textual priors for restoration. These aligned textual priors are complemented by hierarchical DINO features, where deep features guide coarse semantic layout, intermediate features support structural recovery, and shallow features refine local edges and textures in the U-shaped DiT backbone. Rather than treating textual and visual priors as a single homogeneous condition, STMP-DiT assigns hierarchical DINO priors to different restoration stages according to their representational granularity. The fused condition is then injected through bounded feature modulation, enabling controlled stage-aware guidance while reducing redundant conditioning and improving the parameter efficiency of the conditioning modules. Experimental results on widely used SR benchmarks indicate promising improvements in perceptual quality and distributional realism with a compact trainable parameter scale, suggesting the value of reliable, stage-aware, and parameter-efficient multimodal prior integration for diffusion-based image super-resolution. Full article

Firefighters operate in high-risk, rapidly evolving environments where exposure to extreme heat, toxic gases, and physiological stress significantly increases the likelihood of injury and fatality. This study systematically maps the emerging research landscape of real-time artificial intelligence (AI)-driven digital twins for environmental and physiological risk prediction in firefighting contexts. A combined bibliometric and qualitative content analysis was conducted using peer-reviewed literature retrieved from the Web of Science database (2010–2025). Bibliometric techniques were used to identify publication trends and thematic clusters, while content analysis examined the integration of sensing technologies, AI models, and digital twin architectures. The results reveal four dominant technological domains shaping the field: AI-enabled fire risk modeling, sensor data acquisition systems, IoT-based digital infrastructures, and predictive analytics for disaster simulation. Sensing technologies such as temperature, gas, particulate matter, thermal imaging, heart rate, and blood oxygen monitoring form the foundational data layer, while machine learning and deep learning models enable real-time hazard prediction and situational awareness. Digital twin architectures serve as the integration layer, fusing multi-source data and supporting simulation-based decision-making. Despite rapid advancements, key gaps persist, including limited integration of environmental and physiological data, insufficient predictive capabilities, a lack of standardized architectures, and minimal development of human-centered decision-support systems. This study provides a structured synthesis of current technologies and identifies future research directions toward integrated, explainable, and real-time digital twin systems to enhance firefighter safety and operational resilience. Full article

Background/Objectives: Celiac disease (CD) is an immune-mediated enteropathy with gastrointestinal and extraintestinal manifestations. In primary care, recognition can be delayed when psychiatric symptoms, arthralgia, thyroid dysfunction, alcohol exposure, and liver-test abnormalities coexist. This case report describes a confounder-aware diagnostic approach to histologically confirmed CD in a patient with a multifactorial primary-care presentation. Methods: We report a single-patient, de-identified reflective case from routine family medicine practice, organized according to CARE case-report principles. Results: A woman in her early sixties with hypothyroidism and glaucoma presented with new low mood, anhedonia, somnolence, generalized anxiety, increased alcohol intake, poor appetite, weight loss, abdominal bloating, diarrhea, flatulence, and polyarthralgia. Initial investigations, including celiac serology obtained before gluten-free diet advice, showed mild anemia, marked hyperferritinemia, severe cholestatic and hepatocellular liver-test abnormalities, uncontrolled hypothyroidism, and strongly positive tissue transglutaminase IgA (>250 kIU/L; reference 0.0–14.9). Radiographs showed mild osteoarthritis and osteopenia without erosive arthropathy. Computed tomography excluded malignancy but showed severe diffuse hepatic steatosis and mild pancreatic atrophy. Mirtazapine was started at the index visit; after the initial laboratory results, gluten-free diet advice, alcohol-reduction counseling, and levothyroxine adjustment were undertaken. During the diagnostic episode, small-bowel biopsy demonstrated moderate-to-severe crypt hyperplastic villous atrophy with increased intraepithelial lymphocytes, and gastric biopsies showed no significant pathology; the histology was consistent with CD. Symptoms improved substantially. Longer-term objective follow-up showed persistent but improved celiac serology (tTG-IgA 49.4 kIU/L), normalization of thyroid-stimulating hormone, partial improvement in gamma-glutamyl transferase, which remained elevated, and a later iron-deficiency pattern with persistent anemia. Conclusions: This case supports targeted CD testing when anxiety or depressive symptoms occur alongside gastrointestinal symptoms, weight loss, arthralgia, hypothyroidism or documented thyroid autoimmunity, anemia, osteopenia, or liver-test abnormalities. Histology and repeat serology confirmed the diagnosis, but the psychiatric and hepatic manifestations still require cautious interpretation because hypothyroidism, alcohol exposure, steatotic liver disease, and simultaneous treatments also shaped the clinical course. Full article

Colorectal cancer (CRC) exhibits a highly heterogeneous tumor immune microenvironment (TME), ranging from “immune-inflamed” to “immune-desert” or “immune-excluded” phenotypes. Understanding how immune cell composition, cytolytic activity (CYT) and genomic alternations shape tumor-immune interactions is critical for improving immunotherapy outcomes. We analyzed TCGA-COAD and TCGA-READ datasets to evaluate immune competency, CYT, immune subtypes, microsatellite instability (MSI), and genomic instability, including somatic mutations, copy number aberrations (CNAs), and chromothriptic events. Immune cell infiltration was correlated with CYT levels, immune checkpoint expression, and immune-related gene signatures. Immune-competent (IC) tumors were predominantly CYT-high, enriched in stromal and immune scores, and exhibited distinct TME characteristics compared with immune-deficient (ID) tumors. IC/CYT-high tumors expressed higher levels of immune checkpoints (PD-1, PD-L1, CTLA-4, IDO1/2, LAG-3) and cytokines/chemokines (C1QA/B/C, CXCL9/10/11, CXCL13). Differences in immune infiltration were observed across tumors with significant mutations and copy number alterations. No prognostic difference was observed between CYT-high and CYT-low patients, indicating that CYT reflects immune activation rather than clinical outcome. Functionally, stimulated CD8⁺ T cells exhibited cytotoxicity activity against MSI-high (HCT-116) and microsatellite-stable (HT-29) CRC cells, with MSI-H cells showing higher sensitivity. Dynamic 3D co-culture demonstrated tumor-guided T cell infiltration and retention of CD8 expression, and co-culture was associated with moderate upregulation of cytotoxicity-related genes GZMA and PRF1 within the system. Cytotoxic activity decreased at lower effector-to-target ratios, highlighting the importance of effector dose. Overall, these findings link CYT, immune competency, MSI status, and genomic instability to T cell cytotoxic responses, providing insights into tumor-immune interactions, and suggest potential associations relevant for immunotherapy research in CRC. Full article

Spectral line shapes are used to diagnose parameters of white dwarfs and neutron stars in particular. In magnetized plasmas, the motion of the radiating atom in the plasma needs to be considered in the collision process as the electronic structure of the atom depends on its center-of-mass translational momentum. More broadly, collision models do not explicitly or fully account for the motion of the nucleus, accounting for deflection through conservation of momentum. Traditionally, the correlation between electronic and nuclear motion has been captured through mass-polarization terms involving momenta scalar products between different electrons. We reformulate the collision problem accounting for the motion of the nucleus, taking advantage of unitary transformations. In this new formulation, Coulomb interactions between the atom and projectile/plasma particle become displaced Coulomb interactions, and exchange interactions include corrections of order $1/M_A$. We demonstrate the resulting impact on the elastic scattering T-matrices of the $1s$ state of hydrogen, where the lowest-energy electrons increase the real part by 20–30% while leaving the imaginary part practically unaltered. Lastly, we present a formulation so that the atomic motion can be explicitly included in the collision problem for magnetic-field applications. Full article

Quantifying the spatial distribution of immune cells within intact skin tissue is essential for understanding diseases such as vitiligo, in which CD8⁺ T cells selectively destroy epidermal melanocytes within the discrete, parallelogram-shaped epidermal compartments of mouse tail skin, which we term scales. Existing workflows rely on manual region drawing, which is labor-intensive and operator-dependent. Here we present ScaleNet, a three-stage deep-learning pipeline for automated per-scale quantification of whole-mount immunofluorescent images, implemented as an Imaris XTension to enable seamless integration with existing 3D imaging workflows. ScaleNet (i) encodes a 3D confocal volume as a pseudo-RGB projection that preserves height information lost by standard maximum-intensity projection, (ii) applies two independently trained Detectron2 Mask R-CNN models—one for epidermal scales and one for hair follicles—with sliced inference (SAHI) to segment whole-mount images at full resolution, and (iii) maps the resulting 2D mask back into the Imaris 3D coordinate system to quantify user-defined Spot objects per scale. Applied to vitiligo mice imaging, ScaleNet produced per-scale counts of CD8⁺ T cells and DCT⁺ melanocytes, enabling unbiased spatial statistics in the tail epidermis, demonstrating that ScaleNet can provide the quantitative spatial resolution needed to dissect the micro-anatomical dynamics of autoimmune depigmentation. Full article

Faults in high-permeability fault-block reservoirs may act as sealing boundaries, partial flow baffles, or hydraulically communicating interfaces. In this study, a field-constrained pressure-transient workflow is developed for diagnosing fault-related flow baffling in long-horizontal-well reservoir systems. Finite cross-fault transmissibility is represented by a leakage coefficient, $L_f$, and numerical models are used to examine the evolution of middle- and late-time pressure-derivative responses. The model is benchmarked against KAPPA Saphir and reproduces the principal derivative-shape evolution, anomaly timing, and peak attenuation, with average errors of 9.66% for the pressure derivative and 10.36% for pressure drawdown over the comparison interval. As $L_f$ increases, the response evolves from sustained late-time uplift to finite humps, broadened transitions, weak platform distortion, and connected-like behavior. For finite anomalies, the relative intensity $I_h$, occurrence time $t_h$, and transition width $W_h$ describe anomaly magnitude, timing, and broadness; sustained-uplift and connected-like responses are interpreted qualitatively. The workflow is applied to three anonymized long horizontal wells: Well A shows strong boundary control, Well B shows a broadened transitional anomaly with $I_h^{*}=0.61$ and $t_h=27.17$h, and Well C shows a smooth, connected-like response. The results indicate that fault diagnosis is inherently non-unique and should combine derivative characteristics with well–fault geometry, test quality, reservoir properties, production dynamics, and geological constraints. The framework provides a practical dynamic complement to static fault-seal interpretation. Full article

Biliary tract cancers (BTCs), including cholangiocarcinoma and gallbladder cancers, are characterized by their rarity, poor prognosis, limited treatment options, and significant psychosocial burden among affected individuals. Hope and loneliness are known to play significant roles in shaping cancer-related experiences and outcomes; however, their trajectories in the context of rare cancers remain unexplored. The Canadian Cholangiocarcinoma Collaborative (C3) was founded to enhance access to treatment, research, and support for individuals affected by BTC in Canada. This mixed-methods study aimed to measure hope and loneliness among patients and caregivers over time and to gain a deeper understanding of their experiences. A total of 92 patients and 44 informal caregivers, self-, peer-, or physician-referred, consented to participate in this study. Participants completed electronic self-reported measures of hope (Hope Herth Index (HHI), 12 items) and loneliness (UCLA Loneliness scale, 20 items) upon joining C3 (baseline, T0), following the first informational session with a C3 research navigator (T1), and after two to three months (T2). A subsample (n = 14) also participated in two online focus groups. At baseline, participants reported relatively high levels of hope (patients: M = 39.8, SD = 4.9; caregivers: M = 38.9, SD = 4.68), with the HHI ranging from 12 to 48, where higher scores indicate higher hope. They also reported low-to-moderate levels of loneliness (patients: M = 32.13, SD = 9.63; caregivers: M = 36.69, SD = 12.37), with the scale ranging from 20 to 80, where low loneliness: 20–34; moderate: 35–49; moderately high: 50–64; and high: 65–80. At T1, a significant decrease in hope (mean difference [MD] = −1.38, 95% CI [−2.64, −0.11], p = 0.029) and a significant increase in loneliness (MD = 1.75, 95% CI [0.27, 3.23], p = 0.016) were found among patients, with no further significant changes from T1 to T2. Among caregivers, no significant changes were observed from baseline to T1; however, at T2, there was a significant decrease in hope (MD = −2.01, 95% CI [−3.61, −0.40], p = 0.010) and a significant increase in loneliness (MD = 4.54, 95% CI [1.31, 7.77], p = 0.004). No significant differences in hope or loneliness were found between participants who engaged in C3 activities and those who did not. Dyadic analysis revealed significant correlations between patients’ and caregivers’ hope and loneliness at baseline and at T2. Despite the significant changes, findings indicate consistently high levels of hope and low-to-moderate levels of loneliness over time. Focus group analyses further contextualize quantitative findings by highlighting patients’ and caregivers’ experiences in greater depth. The results serve to inform current and future initiatives aimed at providing timely, personalized psychosocial support to patients and caregivers affected by BTC. Full article

This study presents (i) a hybrid experimental strategy combining a large-scale wave flume and harbor basin for broad-period buoy hydrodynamic characterization, with internal consistency assessment across the facility transition, (ii) a comprehensive, uncertainty-quantified dataset for a shallow-draft disk-shaped buoy (D/T ≈ 10) including RAOs with repeatability statistics, extreme sea-state responses, and environmental load coefficients with uncertainty bounds, and (iii) new physical insights into the roll damping mechanism of such geometries without appendages. A hybrid experimental strategy was employed, integrating a large-scale wave flume (for long-period waves and currents) with a harbor basin (for short-period waves and wind), aiming to mitigate the scale effects inherent in Froude-scaled models, particularly with regard to drag force measurements. The test matrix included free decay in calm water, RAOs under regular waves, motion and mooring line tension under irregular waves, and measurements of wind and current drag coefficients. Key results indicate a natural roll period of approximately 3.0 s (prototype) with a notably high dimensionless damping ratio (ζ ≈ 0.14–0.15), which is conducive to rapid motion attenuation. A pronounced resonance peak in the roll RAO (26.6°/m) was observed near the 3.0 s. Under an extreme sea state (prototype: H_s = 13.8 m, T_p = 16.1 s), the maximum roll angle and dynamic mooring line tension reached 21.30° and 61.56 kN, respectively, the latter being about 3.0 times the static pretension. The mean wind drag coefficient and current drag coefficient were determined as 0.76 and 0.44. This research provides a comprehensive dataset with quantified uncertainty and critical insights for the design, mooring system optimization, and operational safety assessment of such disk-shaped buoys. The hybrid testing approach demonstrated qualitative consistency across the two facilities, pending quantitative cross-validation through dedicated overlapping tests, and the measured roll damping (ζ = 0.14–0.15, expanded uncertainty ±0.01–0.011) is favorable for motion stability within the tested Reynolds-number range. Full-scale validation is recommended to confirm these findings under prototype conditions. Wind, wave, and current effects were tested separately and then comprehensively assessed. Full article

Background: Cervical dumbbell-shaped neurogenic tumors occurring at two noncontiguous levels are rare, and postoperative cerebrospinal fluid (CSF) collection causing cord compression is an uncommon but serious complication after intradural tumor resection. Case Presentation: A 30-year-old man presented with a 3-month history of progressive gait disturbance. Neurological examination revealed grade 3 paraparesis with upper motor neuron signs. Magnetic resonance imaging (MRI) demonstrated two discrete dumbbell-shaped neurogenic tumors located at the C1-2 and C7-T1 levels. The lesions were simultaneously resected. Complete removal of the C1-2 tumor required total sacrifice of the left C2 nerve root, while the C7-T1 lesion was excised through a T-shaped dural incision. The dura was closed primarily with watertight sutures reinforced with dural sealant, and no CSF leakage was observed during intraoperative Valsalva testing. Two months postoperatively, the patient developed worsening upper back and trapezial pain with severe scapular swelling. MRI revealed a large CSF collection extending from C6 to T5, causing moderate cord compression. Urgent revision surgery was performed. Controlled drainage was attempted to prevent intracranial hypotension, but significant CSF egress occurred. The dural defect was repaired using an autologous muscle plug reinforced with fibrin glue. The patient recovered uneventfully after revision surgery and was discharged without recurrence or complications. Conclusions: This case highlights that delayed, extensive postoperative CSF collection can occur despite apparently watertight primary closure and negative intraoperative Valsalva testing. Clinical vigilance for this complication is essential when patients present with new axial pain or localized swelling following cervical intradural surgery, even in the absence of classic low-pressure headaches. Full article