Search Results (3,880)

The development of sustainable coatings that combine reprocessability with active functionalities remains a central challenge for the composites sector. In this work, a healable, electrically conductive coating was formulated using epoxidized castor oil (ECO) as a bio-based matrix, dibutyl phosphate (DBP) as a transesterification catalyst, and short recycled carbon fibres (RCFs, 2 mm in length) as a conductive filler at loadings of 10 and 20 phr. Formulations were UV-cured via cationic photopolymerization and characterized across the full liquid-to-solid processing chain. FT-IR and photo-DSC showed that increasing RCF content progressively reduced curing rate and conversion, an effect attributed to light scattering/absorption by the fibres and restricted chain mobility, although gel content remained above 98% in all cases. DMTA showed that RCF did significantly affect the glass transition temperature but markedly increased the rubbery storage modulus and apparent crosslink density, consistent with a physical reinforcement mechanism. Stress relaxation tests confirmed the dynamic bond exchange behaviour in all formulations, with the apparent activation energy decreasing from 112 kJ/mol for the neat resin to 33–34 kJ/mol upon RCF incorporation. This significant reduction suggests that the presence of RCF facilitates the bond-exchange process, potentially through interfacial interactions between the polymer network and the fibre surface. However, the specific molecular mechanism responsible for this effect cannot be established from the present data. Electrical conductivity peaked at 10 phr RCF (3.6 × 10⁻³ S/m), enabling measurable Joule heating, while the 20 phr formulation showed reduced conductivity linked to voids and lower conversion. Thermally triggered healing at 120 °C for 6 h restored mechanical integrity, which is higher than reference values, demonstrating the coating’s capacity for repeated repair through its dynamic covalent network. Full article

Introduction: Chemotherapy-induced peripheral neuropathy (CIPN) is a common and dose-limiting toxicity in child, adolescent, and young adult (CAYA) oncology populations. Despite its clinical impact, objective biomarkers for early detection and monitoring remain limited. Neurofilament light chain (NfL), a marker of axonal injury, has emerged as a potential circulating biomarker of CIPN in adults and potentially for CAYAs. This pilot study evaluates the association between NfL and patient-reported CIPN severity in CAYAs. Methods: We conducted a prospective pilot study of 26 patients with acute lymphoblastic leukemia or lymphoma. CIPN was assessed using FACT-GOG/NTx scores. Linear mixed-effects models evaluated associations between NfL and neuropathy over time, adjusting for age and time from baseline. Logistic mixed models assessed the relationship between NfL and clinically significant neuropathy (FACT-GOG/NTx ≤ 40). Results: NfL was significantly associated with worsening neuropathy. A 50-unit increase in NfL corresponded to a 1.1-point decrease in FACT-GOG/NTx score (p < 0.001). Each doubling of NfL was associated with a 0.61-point decrease in FACT-GOG/NTx (p < 0.001). Higher NfL levels increased odds of neuropathy (OR 4.62, p < 0.001). Associations were strongest in leukemia patients and not observed in Hodgkin lymphoma when separately analyzed. Conclusions: This pilot study demonstrates that circulating NfL correlates with patient-reported neuropathy severity, supporting its role as a potential biomarker for CIPN in CAYAs. Differences between leukemia and lymphoma cohorts may reflect treatment-specific neurotoxicity patterns and should be validated in larger prospective studies. Limitations include small sample size, heterogeneity, and limited power for subgroup analyses. If validated, NfL could be incorporated into routine toxicity monitoring to identify patients at highest risk for progressive CIPN, enabling earlier supportive care interventions, referral to rehabilitation services, or enrollment in biomarker-guided prevention and treatment trials before irreversible nerve injury occurs. Full article

The serum neurofilament light chain (NfL) is a promising circulating biomarker for canine cognitive dysfunction syndrome (CCDS). This cross-sectional study evaluated serum NfL (sNfL) as a surrogate for cerebrospinal fluid NfL (cNfL) and assessed the effects of physiological factors on its clinical utility. Biofluid NfL was analyzed using the single-molecule array (Simoa) across 126 clinical samples, comprising 44 cNfL and 25 paired cNfL/sNfL samples in geriatric dogs (>8 years) and 16 paired samples from a younger cohort (≤8 years). A moderate monotonic correlation was observed between cNfL and sNfL in geriatric dogs, but this association was not maintained in the younger cohort after adjusting for body weight. In the geriatric cohort, raw sNfL levels differentiated cerebral atrophy from controls but not from other intracranial pathologies. Notably, the ability of cNfL to discriminate structural, atrophic, and mixed brain pathologies from controls significantly improved after adjustment for confounding effects of age and body weight. A similar optimization strategy may be applicable to sNfL. Systematically controlling for these physiological covariates in larger cohorts could potentially further improve the diagnostic precision of blood-based NfL screening in primary veterinary practice. Full article

Cross-domain data flows are commonplace in regulated inter-organizational environments, where durable audit evidence must be retained without publicly exposing sensitive flow metadata. This paper presents a privacy-preserving on-chain attestation framework for recorded cross-domain data transfers in a permissioned setting. Its core data structure, termed GBFPlus, extends the Garbled Bloom Filter (GBF) with explicit occupancy indicators, constrained payloads that encode a consistency prefix and an adjacent-domain identifier, and distinct pairing-derived positions. Each domain administrator records observed inbound and outbound transfers in directional GBFPlus instances and periodically commits signed filter attestations to an append-only ledger. An authorized regulator can reconstruct candidate transfer edges from available bilateral attestations, while light clients verify ledger inclusion through Merkle proofs. A traceable anonymous attestation signature conceals the uploader’s cryptographic identity from ordinary ledger observers while retaining regulator-assisted accountability. The security analysis establishes integrity, conditional anonymity, traceability, and metadata-privacy properties for committed attestations under the stated trust assumptions, and the prototype evaluation reports the measured costs of GBFPlus and the signature operations. Full article

Neurodegenerative diseases represent a major cause of disability and death, but early diagnosis, prognosis, and therapeutic monitoring are challenging due to biological heterogeneity and the absence of disease-specific biomarkers. Neurofilament light chain (NfL) is a highly sensitive fluid biomarker of neuroaxonal injury with well-established clinical utility in selected neurological disorders, especially in disease monitoring and prognostic evaluation. However, since NfL is not disease-specific, the interpretation has to be integrated with complementary molecular, imaging, and clinical biomarkers. Recent advances in genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and neuroimaging provide complementary information about the molecular and biological processes underlying neurodegeneration. Artificial intelligence (AI) and machine-learning approaches also allow the integration of these heterogeneous datasets for multimodal biomarker modeling. This review examines the biological and clinical relevance of NfL across major neurodegenerative diseases and critically discusses its combination with multi-omics, neuroimaging, and AI-based approaches. Special emphasis is placed on disease monitoring, prognosis, patient stratification, and therapeutic-response modeling, distinguishing established clinical applications from emerging research directions. The present review also addresses ongoing methodological challenges, including assay standardization, data harmonization, model interpretability, multicenter validation, and clinical translation. Finally, future potential is discussed for NfL-based multimodal biomarker frameworks in precision neurology. Full article

Cholangiocarcinoma (CCA) is an aggressive malignancy with limited treatment options and poor clinical outcomes. Kinesin light chain 1 (KLC1), a component of the kinesin-1 motor complex involved in intracellular transport, has been implicated in cancer biology; however, its role in CCA remains unclear. This study investigated the functional role and molecular alterations associated with KLC1 silencing in CCA. Analysis of publicly available datasets showed that KLC1 mRNA expression was significantly elevated in CCA tissues, and immunohistochemical images from the Human Protein Atlas demonstrated stronger KLC1 protein expression in tumor tissues. siRNA-mediated KLC1 knockdown markedly suppressed cell proliferation, migration, and invasion in KKU-213A and KKU-055 cells and altered the expression of epithelial–mesenchymal transition-associated proteins. Transcriptomic profiling identified 2074 differentially expressed genes following KLC1 knockdown. Functional enrichment analyses revealed significant alterations in cytoskeleton-associated processes and mitogen-activated protein kinase (MAPK) signaling. Protein–protein interaction network analysis identified interconnected gene networks associated with these pathways. Selected differentially expressed genes were validated by RT–qPCR, supporting the transcriptomic findings. Collectively, these results suggest that KLC1 contributes to aggressive phenotypes in CCA cells and is associated with transcriptomic alterations involving cytoskeletal regulation and MAPK signaling, highlighting KLC1 as a potential contributor to CCA progression and warranting further investigation. Full article

Most active pharmaceutical ingredients (APIs) reach their target by passive systemic distribution, so the dose required for efficacy at the lesion is set by what healthy tissue can tolerate; conventional dosage forms consequently produce pharmacokinetic profiles that oscillate between toxic peaks and sub-therapeutic troughs. Nanoparticulate carriers (liposomes, lipid nanoparticles, polymeric and inorganic systems, and biomimetic carriers) and hydrogels (natural, synthetic, supramolecular, and microgel-assembled) have emerged as the dominant strategies to address this, increasingly combined as hybrid nanoparticle–hydrogel constructs in which the gel provides locoregional retention and the nanoparticles provide cargo protection, intracellular delivery and stimuli responsiveness. Stimuli-responsive chemistries (pH, redox, enzyme, ROS, hypoxia, temperature, light, magnetic, ultrasound, glucose, and multi-stimuli logic) translate the molecular signatures of a disease into spatiotemporally controlled cargo release. This narrative review consolidates the state of the art (prioritizing 2022–2026) and departs from the conventional carrier-type survey in one respect: the literature is read along an explicit chain—disease cue, sensing chemistry, carrier architecture, release mechanism and kinetics, administration route, and clinical readiness—which exposes a variable that classification by carrier type conceals. Across all three material classes, what governs release behavior is not primarily the carrier chemistry but the identity of the released species (dissolved drug, drug from an embedded nanoparticle, an intact nanoparticle, and a matrix fragment) and the transport step that limits it. This is why power-law exponent analysis developed for dissolved drug fits particulate release poorly, why statistical goodness-of-fit cannot by itself establish a release mechanism, and why carrier class predicts clinical readiness less well than administration route and regulatory product type. Translational hurdles—CMC complexity, regulatory fragmentation, anti-PEG immunogenicity, and the structural mismatch between preclinical promise and clinical efficacy—are critically appraised in light of previously reported <1% delivery efficiency analysis. This review identifies converging strategies that could move stimuli-responsive controlled release from an aspirational outcome to a routine clinical reality. Full article

Hyaluronic acid (HA)-based hydrogels are widely used as wound-healing materials and topical delivery systems because of their excellent biocompatibility, water retention capacity, and ability to promote cell migration. However, HA is prone to oxidative chain scission, which reduces molecular weight and compromises formulation stability and functional performance. This study evaluated the feasibility of ergothioneine (EGT) as a candidate antioxidant stabilizing excipient in a model HA-based wound-healing material. CCK-8 assays assessed the biocompatibility of EGT in L929 mouse fibroblasts after 24 h of exposure, and a stress-screening framework including Fenton oxidation, high-temperature/high-humidity treatment, light exposure, and quiescent storage at 4 °C was established. The results showed that Fenton oxidation markedly induced HA degradation, whereas EGT incorporation effectively protected HA structural integrity under oxidative stress. Cell scratch assays further demonstrated that EGT did not interfere with the ability of HA to promote cell migration. EGT may serve as a candidate antioxidant stabilizing excipient for HA-based wound-healing materials, improving HA structural and material stability under oxidative challenge while preserving HA-associated cell-migration function. Full article

Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy caused by extracellular deposition of misfolded proteins, most commonly immunoglobulin light chains (AL) or transthyretin (ATTR). Once considered a rare disease, CA is increasingly recognised due to improved diagnostic strategies and the availability of disease-modifying therapies. Early diagnosis is crucial, as treatment efficacy and clinical outcomes are strongly influenced by the stage of cardiac involvement. Multimodality cardiac imaging plays a central role in the diagnostic pathway, risk stratification, and evaluation of therapeutic response in CA. Echocardiography represents the first-line imaging modality and is essential for raising clinical suspicion through the identification of characteristic structural and functional abnormalities, including ventricular wall thickening, diastolic dysfunction, and distinctive strain patterns. Bone scintigraphy has revolutionised the non-invasive diagnosis of ATTR-CA, allowing accurate identification of transthyretin-related disease in the absence of monoclonal gammopathy, which needs to be excluded via serum and urinary immunofixation. Cardiovascular magnetic resonance provides advanced tissue characterisation through late gadolinium enhancement and quantitative mapping techniques, enabling detection of early myocardial involvement and robust prognostic stratification. Emerging imaging modalities, including dual-energy (spectral) computed tomography and positron emission tomography tracers, show promise in myocardial amyloid quantification and subtype differentiation, although their role is still evolving. Integration of imaging findings with clinical and laboratory parameters allows comprehensive disease assessment, facilitating early diagnosis, guiding therapeutic decisions, and improving risk stratification. This review summarises the current role of multimodality imaging in CA, highlighting its contribution from early detection to prognostic evaluation and monitoring of treatment efficacy, with particular emphasis on the emerging role of quantitative imaging in monitoring treatment response. Full article

Cross-border trade security risks are often embedded in inconsistencies among trade documents, logistics trajectories, hardware sensor states, and financial settlement activities. Existing methods primarily rely on structured declaration fields, making it difficult to verify digital declarations against actual physical processes or to generate complete evidence suitable for regulatory review. To address these challenges, TradeSense-EQA is proposed as a cross-border trade security anomaly detection and evidence-grounded English question-answering framework. Multisource sensing information, including trade documents, GPS/AIS trajectories, RFID records, electronic seal events, port weighing data, temperature and humidity measurements, vibration signals, container door states, and visual images, is jointly modeled within the framework. The reliability-aware representation module dynamically adjusts sensing-channel weights according to data missingness, sampling intervals, device health states, and communication quality. The trade-process-constrained module identifies anomalies across declaration, packing, transportation, transshipment, arrival, and customs clearance stages and generates process-consistent evidence chains. The evidence-grounded question-answering module answers English trade risk questions on the basis of verified documentary fields and sensor records, while confidence estimation and abstention mechanisms are incorporated to reduce factual hallucinations. Experimental results demonstrate that TradeSense-EQA achieved an Accuracy of $0.918$, a Precision of $0.909$, a Recall of $0.897$, a Macro-F1 of $0.903$, and a ROC-AUC of $0.958$ on the cross-border trade anomaly detection task, outperforming baseline methods including XGBoost, LightGBM, TCN, Transformer, BERT, CLIP, and VisualBERT. On the English trade risk question-answering task, Exact Match, Token-level F1, BLEU, ROUGE-L, and BERTScore reached $0.782$, $0.851$, $0.668$, $0.801$, and $0.934$, respectively. Ablation results further confirmed the effectiveness of hardware sensing input, reliability-aware weighting, declaration–fact alignment, process-graph reasoning, and evidence-constrained generation. The proposed framework provides a reliable, interpretable, and auditable artificial intelligence-driven sensing solution for customs supervision, port security, international logistics review, and trade-background investigation. Full article

Background/Objectives: Primary thyroid lymphoma accounts for approximately 0.2–2% of thyroid malignancies. Plasmablastic lymphoma (PBL), an aggressive large B-cell neoplasm with plasma-cell differentiation and frequent loss of conventional B-cell markers, is a rare thyroid presentation. We report a thyroid PBL presenting as an acute surgical airway emergency in an immunocompetent patient and highlight the diagnostic and management pitfalls that distinguish this from anaplastic thyroid carcinoma. Case Presentation: A 75-year-old man without any significant past medical history presented with rapidly progressive right-sided neck swelling, dysphagia, inspiratory stridor, and respiratory failure. Imaging demonstrated a large, thyroid-centered mass with tracheal involvement, initially raising concern for anaplastic thyroid carcinoma. Histopathology revealed a diffuse infiltrate of large, atypical cells with immunoblastic and plasmablastic morphology. The neoplastic cells were CD20- and CD138-negative but strongly MUM1-positive, with lambda light-chain restriction, bright CD38 by flow cytometry, a Ki-67 proliferation index exceeding 95%, aberrant cytoplasmic CD3 expression, and a MYC::IGH rearrangement, supporting a diagnosis of PBL. Staging identified extranodal perinephric disease and mesenteric lymphadenopathy, consistent with disseminated extranodal Ann Arbor stage IV disease. The patient underwent systemic treatment and initially had an excellent response; however, one month after the last treatment cycle they presented to the hospital with a mass consistent with recurrence. Discussion: Rapid growth, fixation, and tracheal invasion strongly suggest anaplastic thyroid carcinoma in routine clinical practice. However, plasmablastic lymphomas can present similarly and require fundamentally different treatment. In this case, loss of conventional B-cell markers, CD138 negativity, and aberrant cytoplasmic CD3 expression created substantial diagnostic challenges. Light-chain restriction, plasma-cell-associated markers, flow cytometry, and MYC cytogenetics were vitally important. Conclusions: Thyroid-presenting PBL is exceptionally rare and may closely mimic anaplastic thyroid carcinoma, including presentation with life-threatening airway compromise and tracheal involvement. This case highlights several diagnostic pitfalls: CD138 negativity despite plasma-cell differentiation, and aberrant cytoplasmic CD3 expression. Prompt airway stabilization, adequate tissue acquisition, broad immunophenotyping, light-chain assessment, flow cytometry, EBV/HHV8/ALK testing, and MYC cytogenetics are essential for accurate diagnosis and lymphoma-directed treatment. Full article

Cross-chain bridges represent one of the most damaging attack surfaces in decentralized finance, with major exploits (e.g., Ronin, Wormhole, Nomad, Multichain) arising not from broken signature schemes but from failures in proof verification, replay protection, and signer-set management, gaps that conventional threshold-signature multisignature wallets do not address. This study presents an incident-aware multisignature architecture combining three on-chain predicates—block-height freshness windows, epoch-bound signer sets, and Merkle inclusion-proof verification—with a non-authoritative off-chain LightGBM classifier that generates SHAP-attributed risk explanations to support governance actions such as pausing, vetoing, or rotating signers, without directly blocking or approving execution. The framework was evaluated on a simulated benchmark of 78,600 Ethereum testnet transactions containing six injected anomaly classes (gas spikes, nonce jitter, malformed call data, stale intents, proof-delivery delays, and epoch-rotation replays). The LightGBM advisor achieved ROC-AUC 0.92 (95% CI [0.906, 0.926]) and F1 0.73 ([0.712, 0.749]), outperforming five baselines—logistic regression, Random Forest, XGBoost, isolation forest, and a rule-based detector—with the highest F1 (0.731) and PR-AUC (0.799), while the rule-based detector, which by construction covers only the anomaly classes addressed by the deterministic predicates, attained F1 0.282. Differences were statistically significant except for the LightGBM–XGBoost PR-AUC comparison. The deterministic layer itself is verified through 28 property-level contract tests covering all seven modeled attack objectives, with measured per-function gas costs (execute_Intent: 118,756 gas, of which 28,432 gas is Merkle-proof verification). Within this controlled setting, the results indicate that a machine learning advisor can extend anomaly-prioritization coverage beyond the scope of the deterministic predicates while leaving execution control fully deterministic. This work is presented as a controlled proof of concept: the reported metrics quantify recovery of scripted injection patterns, and validation against real-world exploit traces remains future work. Full article

Poly(methyl methacrylate) (PMMA), as a widely used transparent polymer material, is highly stable because of its all-carbon backbone, which makes its chain cleavage under mild conditions challenging. In this work, we report a photo-initiated solution reaction that induces main-chain scission of PMMA at room temperature, leading mainly to molecular-weight reduction and oligomer formation. This method requires no catalysts and does not need pre-introduction of specific groups. The degradation mechanism proposed according to DFT calculations involves the photolysis of trichloromethane to produce phosgene, which then reacts with ester groups on the side chains of PMMA to form acyl chloride groups. These acyl chloride groups further cleave under light or heat, generating radicals that trigger β-scission of the PMMA main chain through a side-chain-initiated pathway. The degradation mechanism was demonstrated experimentally, and the extent of chain scission can be regulated by temperature, O₂ and an alcohol stabilizer. Full article

Chemotherapy-induced neurotoxicity is a major dose-limiting complication of systemic anticancer therapy that adversely affects neurological function, treatment continuity, and long-term quality of life among cancer survivors. Chemotherapy-induced peripheral neuropathy (CIPN) is the most common manifestation, whereas chemotherapy-related cognitive impairment (CRCI) and selected immune-mediated neurological toxicities increasingly contribute to survivorship-related morbidity. Although these immune-mediated syndromes are distinct from conventional chemotherapy-induced neurotoxicity, they are included because they share several downstream pathogenic mechanisms relevant to biomarker discovery and neuroprotective strategies. This structured narrative review critically synthesizes current evidence on the molecular mechanisms, clinical manifestations, biomarkers, and emerging neuroprotective strategies underlying chemotherapy-induced neurotoxicity. A comprehensive PubMed/MEDLINE search was performed, with emphasis on studies published between 2014 and 2026. Evidence from systematic reviews, meta-analyses, clinical guidelines, randomized controlled trials, prospective clinical studies, and high-quality translational research was critically evaluated. Current evidence indicates that chemotherapy-induced neurotoxicity arises through interconnected mechanisms involving oxidative stress, mitochondrial dysfunction, neuroinflammation, calcium dysregulation, blood–brain barrier disruption, and SARM1-mediated programmed axonal degeneration. Among emerging biomarkers, neurofilament light chain (NfL) demonstrates the greatest translational potential for early detection and monitoring, while inflammatory cytokines, circulating microRNAs, pharmacogenomic markers, cerebrospinal fluid biomarkers, and advanced neuroimaging may improve individualized risk stratification. Although duloxetine remains the only guideline-recommended pharmacological treatment for established painful CIPN, mechanism-based therapies targeting mitochondrial dysfunction, neuroinflammation, oxidative stress, and SARM1 signaling, together with structured exercise and biomarker-guided precision medicine, represent promising translational approaches. However, clinical implementation remains limited by incomplete biomarker validation, heterogeneous study methodologies, and the absence of effective disease-modifying neuroprotective therapies, underscoring the need for large biomarker-guided multicenter clinical trials. Full article

Background/Objectives: Lecanemab, a humanized anti-amyloid-β protofibril antibody, achieves substantial amyloid clearance and modest slowing of clinical decline in early Alzheimer’s disease (AD). Amyloid-related imaging abnormalities (ARIA) represent the most clinically important safety concern, yet no fluid biomarker has been prospectively validated for ARIA prediction in lecanemab-treated patients. This review critically synthesizes current evidence on fluid and imaging biomarkers for ARIA risk stratification and treatment-response monitoring, with emphasis on distinguishing clinically actionable markers from those that remain investigational, and on the interpretive challenge of differentiating pseudo-atrophy from true neurodegeneration. Methods: A narrative literature review was conducted across PubMed, Google Scholar, Scopus, Web of Science, Embase, and the Cochrane Library, covering English-language publications from January 2020 to April 2026, supplemented by landmark earlier studies, regulatory documents, and appropriate-use recommendations. Evidence was synthesized narratively and classified into four tiers: Established, Emerging, Exploratory, and Hypothesis-generating. Results: APOE ε4 genotype and baseline MRI markers of cerebral amyloid angiopathy are the only established, clinically actionable ARIA risk stratifiers. In CLARITY-AD, ARIA-E and ARIA-H occurred across all APOE genotype groups. Plasma p-tau217 demonstrates the strongest evidence for downstream biological response monitoring, while neurofilament light chain (NfL) dynamics help distinguish pseudo-atrophy from ongoing neurodegeneration. GFAP is exploratory, while sTREM2, endothelial markers, and endogenous anti-Aβ antibodies remain hypothesis-generating, with no prospective validation in lecanemab-treated cohorts. Assay-platform variability substantially limits cross-study comparability for all quantitative fluid biomarkers. Conclusions: Current ARIA monitoring remains anchored in APOE genotyping, baseline MRI assessment, and serial MRI surveillance. Plasma p-tau217 and NfL provide complementary biological context for treatment-response interpretation but cannot replace established imaging protocols. Future studies should prioritize prospective multicenter validation of multimodal ARIA prediction models integrating fluid biomarkers, APOE genotype, baseline cerebrovascular imaging, and standardized assay platforms. Full article