Search Results (2,599)

Head and neck cancer (HNC) comprises a heterogeneous group of tumours, most often of squamous cell origin, characterized by both high morbidity and mortality rates. It is the seventh most common form of cancer diagnosed in humans, accounting for approximately 4.7% of all cancers. Among HNCs, neck squamous cell carcinoma (HNSCC) is predicted to become the most common form of human cancer. Some sources include oesophagus (ESCC) in this group due to their similar histology, being described as upper aerodigestive tract cancers (UADT). Unfortunately, 60–70% of cases are diagnosed late, i.e., at clinical stages III-IV. As a result, despite modern surgical techniques and oncological treatments, the survival rate remains below 40–60% due to frequent lymph node metastases and local tumour recurrence. There is a growing concern that diet and inflammatory dietary components may influence the initiation and development of HNSCC. The inflammatory potential of diets can be quantified by the Dietary Inflammatory Index (DII). The DII was derived from an analysis of 45 dietary constituents that either increase or decrease inflammation. Several recent clinical studies have noted a significant relationship between DII score and many inflammation-associated chronic diseases, such as obesity, cardiovascular and neurodegenerative disorders, and diabetes, and the incidence of various human cancers, i.e., prostate, ovarian, breast, colorectal cancer, and HNC. However, few studies have investigated the relationship between DII and HNSCC, with most being limited to observational, case-control, and cross-sectional studies. Therefore, the aim of this narrative review is to present the substantial oncological aspects of DII, discuss the use of DII and its modification, the Energy-Adjusted Dietary Inflammatory Index (E-DII), as indicators of HNSCC risk. It also introduces key diet-induced pro- and anti-inflammatory mechanisms and the cellular molecular signalling pathways determining the carcinogenesis of HNSCC. It provides a comprehensive overview of the current literature, including key opinion-forming systematic reviews, as well as molecular, observational, cross-sectional and case-control studies, all of which are accessible via scholarly databases such as PubMed/EMBASE/Web of Science. Thus, the work serves as a compendium of up-to-date knowledge on the relationship between DII/ED-II score and HNSCC etiopathogenesis and the influence of a diet-induced persistent inflammatory microenvironment. Full article

Urban rocky desertification areas are characterized by shallow soils, rock–soil mosaics, and strong human disturbance, so infiltration processes may differ from those in homogeneous soils. However, interactions among multiple controlling factors remain insufficiently quantified. This study compared soil infiltration under artificially restored vegetation (planted grassland (PG) and planted woodland (PW)), and natural secondary vegetation (secondary grassland (SG) and secondary woodland (SW)). Saturated hydraulic conductivity (Ks) and falling-head duration (T) were measured using falling-head tests on undisturbed soil columns. Soil physical properties were then integrated with partial least squares structural equation modeling (PLS-SEM) to assess the effects of rocky desertification, soil aggregates, and porosity. Soil bulk density was significantly lower under artificially restored vegetation, whereas capillary porosity, non-capillary porosity, and water-holding capacity were significantly higher (p < 0.05). Infiltration performance followed PW > PG > SW > SG. PLS-SEM indicated that rocky desertification (−0.78), porosity (0.51), and aggregates (−0.03) jointly regulated infiltration, with non-capillary porosity as the dominant positive factor. Higher infiltration in artificially restored plots was mainly associated with improved pore structure. These findings support vegetation configuration and soil–water management in urban rocky desertification areas. Full article

Future traffic scenarios will involve autonomous vehicles (AVs) interacting with other road users, including cyclists. For this interaction to be safe and socially acceptable, there is a need for development and testing environments that enable scenarios between AVs and cyclists including ethical, logistical, and safety constraints. While human-in-the-loop transport simulation offers an alternative, achieving high behavioral validity requires maximizing user presence and control. This study evaluates a modular, multi-sensory cycling simulator built on the CARLA autonomous driving engine. Through a fully randomized and counterbalanced within-subjects design with 31 participants, we analyzed four simulator configurations incorporating combinations of stereoscopic visualization, speed-dependent haptic eolic feedback, first-person visual self-embodiment, and 3D spatialized audio. Non-parametric statistical evaluations revealed significant differences across the groups (${\chi }^2\left(3\right)=60.47$, $p<0.001$, $W=0.650$). Post-hoc pairwise comparisons indicated that, while head-mounted displays (HMDs) provide a level of spatial orientation, the concurrent integration of visual self-embodiment and speed-dependent airflow acts as a unifying sensory cue, significantly increasing system coherence. Conversely, the addition of 3D spatialised audio yielded no statistically significant improvement ($Z=-0.06$, $p=1.000$), suggesting a sensory saturation effect. Cross-dimensional analysis confirmed a positive correlation between perceived presence and interface control ($\rho =0.693$, $p<0.001$). These findings suggest that a combination of visual feedback, haptic airflow, and self-embodiment may be enough to provide a realistic environment for cyclist–AV interaction studies including multiple agents. Full article

Background: Human papillomavirus (HPV)-unrelated oropharyngeal squamous cell carcinoma (OPSCC) is a clinically aggressive disease characterized by poor outcomes and limited prognostic biomarkers. The Hippo–YAP pathway has emerged as a key regulator of tumorigenesis in epithelial cancers, although its role in OPSCC remains incompletely defined. Methods: We conducted a retrospective study including 215 patients with HPV-negative OPSCC treated surgically with curative intent. Tissue microarrays were constructed, and immunohistochemical analysis of YAP1 and TAZ expression was performed. Associations with clinicopathological variables, disease-free survival (DFS) and disease-specific survival (DSS) were assessed using univariable and multivariable analyses. Results: Nuclear and cytoplasmic YAP1 expression were detected in 53% and 85.6% of tumors, respectively. Both nuclear and cytoplasmic YAP1 expression were significantly associated with reduced DFS (p = 0.019 and p = 0.004, respectively) and DSS (p = 0.01 and p = 0.006, respectively). Multivariable analysis identified nodal involvement (HR = 1.64, p = 0.023) and nuclear YAP1 expression (HR = 1.65, p = 0.004) as independent predictors of DFS, and advanced tumor stage (HR = 1.57, p = 0.038), nodal involvement (HR = 2.34, p < 0.001), and nuclear YAP1 expression (HR = 1.78, p = 0.002) as independent predictors of DSS. In contrast, nuclear TAZ expression was observed at a lower frequency (14.5%) and showed no significant association with clinical parameters or survival outcomes. Conclusions: YAP1 expression, particularly its nuclear activated form, emerges as an independent poor prognostic factor in HPV-negative OPSCC, whereas nuclear TAZ expression was rather infrequent and showed no clinical relevance. These findings highlight the importance of Hippo pathway dysregulation in this tumor subtype and suggest the potential of YAP1 as both a prognostic biomarker and a therapeutic target. Full article

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) is an aggressive cancer of the oral cavity, pharynx, larynx and upper airway. HNSCC is subdivided into distinct clinical entities based on the presence or absence of high-risk human papillomavirus (HPV) infection. While HPV-positive HNSCC patients respond better to conventional and targeted therapies than HPV-negative cases, recurrence is more frequent in HPV-negative cases with limited treatment options. Ferroptosis is a form of iron-based programmed cell death caused by excessive lipid peroxide accumulation. Biomarkers of ferroptosis have proven useful for identifying and triggering ferroptosis in models of treatment-resistant cancers. Identifying and understanding ferroptosis biomarker function in HPV-negative HNSCC allows the possibility for more effective treatment strategies. Methods: Literature searches combined with the public online ferroptosis database FerrDB V3 were utilized for the objective identification and classification of established and non-established ferroptosis biomarkers in HPV-negative HNSCC. Additional novel biomarkers were identified based on known roles in HNSCC oncogenesis. Results: A total of 30 ferroptosis biomarkers were identified associated with HPV-negative disease. Biomarkers were grouped according to shared biological functions, with each marker summarized for prognostic and mechanistic roles in HNSCC ferroptosis. Conclusions: The described biomarkers present a means for stratifying tumors for ferroptotic induction, with several offering potential novel methods for overcoming refractory HPV-negative disease. These biomarkers may warrant further investigation into devising future patient-tolerant strategies that selectively activate ferroptosis in HPV-negative HNSCC. Full article

Egocentric multi-view image analysis refers to the processing of utilizing synchronized video streams captured from multiple wearable cameras worn on the head or body, providing complementary first-person perspectives of dynamic, real-world interactions. Unlike single-view egocentric vision, which may suffer from severe occlusions, motion blur, and limited field-of-view or traditional fixed-camera multi-view setups (assuming static geometry and controlled environments), egocentric multi-view systems leverage body-worn rigs to enable a more robust and flexible 3D understanding in open-world, mobile scenarios. In this work, we present a systematic survey of advancements in cross-view feature fusion, geometric consistency enforcement, open-world detection, human–object interaction (HOI) modeling, action segmentation, 3D reconstruction, and novel-view synthesis specifically tailored to wearable multi-camera platforms. Key datasets released between 2024 and 2026—including HOT3D (833 min of synchronized multi-view hand/object interactions from Project Aria and Quest 3), MultiEgo (first multi-egocentric dataset for 4D social scene reconstruction), and Ego-1K (large-scale 12-camera rig for dynamic 3D video synthesis) are thoroughly examined alongside an analysis of integrations with large language models (LLMs) and vision–language models that drive performance gains, typically in the 15–30% range over single-view baselines in hand tracking, HOI recognition, and reconstruction fidelity, although we show through a consolidated meta-analysis that this gain is task-dependent: larger for geometry-bottlenecked tasks such as in-hand object lifting, and smaller, method-dependent, or occasionally negative for semantic-recognition tasks such as keystep recognition under naive view fusion. These methods cover work in multi-view stereo, cross-view learning, and novel-view synthesis while addressing several real-time wearable constraints. Practical applications such as immersive Augmented Reality/Virtual Reality (AR/VR), assistive robotics, and healthcare monitoring are also discussed together with the challenges in motion calibration, benchmark diversity, and edge deployment ability. Thus, in this review, we attempt to fill a critical gap by focusing exclusively on wearable multi-view systems in an open-world setting, synthesizing the latest literature to chart future directions toward more embodied and continual learning agents. Full article

Migratory birds are potential carriers for the cross-regional spread of zoonotic diseases due to their high mobility and extensive geographical activity range. Blastocystis, a ubiquitous parasitic protist, can infect a broad spectrum of animal hosts including humans, constituting a potential public health hazard. Currently, data on Blastocystis infection in black-headed gulls (Chroicocephalus ridibundus) remain scarce. This study aimed to investigate the fecal sample positivity rate, epidemiological characteristics, and subtype distribution of Blastocystis in wintering black-headed gulls in Kunming, China. A total of 245 fresh fecal samples were collected from black-headed gulls in Kunming, Yunnan Province, during December 2025 and January 2026. Fecal DNA was extracted and subjected to PCR amplification targeting the small subunit ribosomal RNA (SSU rRNA) gene of Blastocystis. Results showed a 3.27% (8/245) overall Blastocystis fecal sample positivity rate in wintering black-headed gulls, with two subtypes detected: dominant zoonotic pathogenic ST7 (87.5%, 7/8) and ruminant-adapted ST26 (12.5%, 1/8). This study represents the first report of Blastocystis in black-headed gulls in China, providing data supporting the understanding of genetic subtype diversity of Blastocystis in avian hosts. Full article

Objectives: AC02, a novel synthetic peptide derived from ACTH, is being developed as a potential therapeutic alternative to porcine ACTH_1-39 for use in infantile spasms. Methods: The study comprised single-ascending dose cohorts (0.02, 0.04, 0.08, 0.16 mg/kg AC02) and multiple-ascending dose cohorts (0.04, 0.08 mg/kg AC02 daily for 5 days). A separate positive-control arm received porcine ACTH_1-39 (25 U/day for 5 days). PD effects (free and total cortisol) were compared head-to-head with the positive control. Plasma concentrations of AC02, porcine ACTH_1-39, free and total cortisol were quantified by validated LC-MS/MS methods, and anti-drug antibody responses were measured using a validated electrochemiluminescence bridging immunoassay. Population PK/PD modeling characterized the concentration–response relationships for free cortisol. Results: Across the 0.02–0.16 mg/kg dose range, AC02 exhibited approximately dose-proportional pharmacokinetics and no accumulation after multiple doses. At 0.04 and 0.08 mg/kg, the baseline-corrected effects on free cortisol were generally consistent with those of porcine ACTH_1-39. Dynamic monitoring of the free cortisol fraction revealed a biphasic pattern across all groups: an early peak followed by a later rise. Total cortisol, by contrast, showed only a monophasic decline, indicating the limitations of total cortisol as a sole PD biomarker. No unexpected safety signals were observed. At 0.04 mg/kg, AC02 demonstrated pharmacodynamic responses comparable to those of marketed ACTH product based on the biologically active component of free cortisol, with favorable safety and pharmacokinetic profiles. Conclusions: This first-in-human study demonstrates that AC02 has favorable pharmacokinetic properties, and an acceptable safety profile. Full article

This study extended a previously established intraoral scanning (IOS) and optical coherence tomography (OCT) dual-modality monitoring workflow for computer-aided design/computer-aided manufacturing (CAD/CAM) restorations to three additional crown material classes alongside a resin composite (RECO) reference. Four material classes were investigated ($n=8$ each): RECO, polymer-infiltrated ceramic network (PICN), lithium disilicate ceramic (LDSC), and zirconia-reinforced lithium silicate ceramic (ZLSC). Monolithic crowns were adhesively luted to standardized human molar abutment teeth and aged by cyclic loading (50500$\mathrm{N}$, 2$\mathrm{Hz}$, 37 2${}^{\circ }\mathrm{C}$, up to 1250000 cycles) in a mouth-motion simulator. IOS and handheld OCT were performed at baseline and after every 250000 cycles under phantom-head conditions; correspondence was assessed using Spearman’s rank correlation coefficient (exploratory, uncorrected for multiple comparisons). OCT consistently showed higher defect extents than IOS across all material classes and timepoints. While no significant IOS-OCT associations were found for RECO and the PICN, OCT detected full-thickness vertical subsurface damage propagation from the earliest timepoint in LDSC and ZLSC, with IOS-derived surface wear remaining markedly lower. Surface-based monitoring alone did not reliably reflect subsurface damage propagation, a dissociation most pronounced in the vertical dimension and silicate-based materials. Intraoral OCT may provide complementary, non-invasive subsurface information to support individualized recall scheduling and minimally invasive repair decisions. Full article

Finite element (FE) modeling is widely used in biomechanical research, enabling computational investigations of anatomical structures. To develop accurate FE models, high-resolution medical imaging such as computed tomography (CT) is essential. However, CT exposes patients to ionizing radiation. Recently, radiation-free three-dimensional zero-echo-time magnetic resonance imaging (3D ZTE MRI) has shown promising results for bone visualization. Therefore, this feasibility study investigated whether 3D ZTE MRI is reliable for creating subject-specific FE models. Human femora from four female subjects were imaged using 3D ZTE MRI. Static FE analyses of the femora were performed in Abaqus/CAE, assuming a biphasic homogenous linear-elastic material. A sensitivity analysis was conducted to evaluate varying bone material properties. After loading with 2000 N, the mean displacement of the femoral head amounted to −1.30 ± 0.26 mm (vertical) and −9.03 ± 2.21 mm (horizontal), while the femoral neck exhibited compressive (inferior: −1366.03 ± 182.70 µm/m) and tensile (superior: 1038.69 ± 135.82 µm/m) strains. Overall, the results demonstrate displacement and strain predictions similar to previous experimental and computational studies based on CT data. Therefore, despite several simplifications, these findings confirm the feasibility of radiation-free 3D ZTE MRI for subject-specific FE modeling, enabling future simultaneous assessment of bone morphology and surrounding soft tissues. Full article

Nimotuzumab is a humanized anti-EGFR monoclonal antibody with a unique pharmacodynamic profile characterized by intermediate affinity and bivalent binding dependence, enabling density-selective tumor targeting while sparing normal tissues from the severe skin rash and other toxicities common to EGFR inhibitors. Since its first approval in 2002, nimotuzumab has been registered for eight cancer indications. Unlike conventional fixed-dose schedules, emerging evidence supports prolonged administration beyond initial combination therapy. This review summarizes clinical data from pancreatic cancer, esophageal cancer, high-grade glioma, pediatric diffuse intrinsic pontine glioma, head and neck squamous cell carcinoma, nasopharyngeal cancer and other solid tumors, showing that extended nimotuzumab exposure, often as maintenance monotherapy, may prolong overall survival, progression-free survival, and disease control compared to limited cycles. Despite heterogeneity in tumor types and treatment regimens, maintenance nimotuzumab was consistently associated with better results, particularly in terms of overall survival. Notably, significant survival benefits were observed in locally advanced SCCHN (24.9 vs. 12.5 months) and esophageal cancer (15.9 vs. 8.1 months) across independent clinical trials. Mechanistically, nimotuzumab exerts direct cytostatic effects via G1 arrest, potent anti-angiogenic activity through VEGF downregulation, indirect pro-apoptotic effects, and broad immunomodulation including ADCC, NK-DC cross-talk, EGFR-specific CD8+ T cell priming, upregulation of HLA class I, and favorable regulation of regulatory T cells. Its density-selective binding reduces selective pressure for acquired resistance. Future research priorities should include prospective randomized trials specifically evaluating maintenance strategies, biomarker-driven patient selection, the molecular characterization of resistance mechanisms, integration with immunotherapy and modern combination regimens, and the development of next-generation platforms, including antibody–drug conjugates and multi-specific constructs. Full article

Background and Objectives: Mild traumatic brain injury (mTBI) is a common cause of emergency department visits worldwide. Optimal decisions are essential for optimizing patient outcomes while minimizing unnecessary imaging. The present study explores the potential utility of ChatGPT-5.1 for predicting intracranial injury and determining CT necessity in mTBI. Methods: We evaluated adult patients with mild traumatic brain injury who met Canadian CT Head Rule (CCHR) criteria and underwent CT imaging during a two-year period. ChatGPT-5.1 was prompted under two frameworks: ER physician simulation and rule (literature)-based. Additionally, a probabilistic multi-variable logistic regression model was developed. ChatGPT-5.1’s performance was compared with that of human controls (consultants and residents) and the CCHR. Pairwise comparisons were conducted using McNemar’s test. Results: A total of 127 patients were included. ChatGPT-5.1’s recommendation for CT showed comparable performance to CCHR. For predicting CT findings, the probabilistic model achieved the highest performance (accuracy 74.0%), followed by consultants (accuracy 69.3%) and residents (66.9%). The rule (literature)-based model displayed the highest sensitivity (91.8%) but exhibited low specificity (22.2%), indicating a high rate of false positives despite its potential utility as a screening or decision-supporting tool. The ER physician simulation model demonstrated the lowest overall performance (accuracy 54.3%). Statistically significant differences were observed between the probabilistic model and both the ER physician and rule-based models (p < 0.05). Consultants outperformed the ER simulation model (p = 0.01), while their performance was similar to that of the probabilistic model (p = 0.44). Conclusions: ChatGPT-5.1 demonstrated performance comparable to the Canadian CT Head Rule in predicting the need for head CT imaging but showed lower accuracy in identifying intracranial injury. While the literature-based rule model achieved high sensitivity, its low specificity emphasizes that it acts primarily as a conservative screening aid rather than a definitive diagnostic tool in CCHR-positive mTBI patients. Full article

Background: Head and neck squamous cell carcinomas (HNSCCs) are highly immunosuppressive, and tumor-associated macrophages constitute a major component of HNSCC tumor microenvironments. Here, we investigate the effects of circulating small extracellular vesicles (sEVs) from HNSCC patients on primary macrophages, to elucidate systemic sEV-mediated immune regulation in HNSCC patients. Methods: sEVs were isolated from plasma by size-exclusion chromatography. Internalization of PKH26-labeled sEVs was demonstrated, and mass spectrometry analysis was performed on HNSCC sEVs and sEV-treated macrophages. NF-κB activation was investigated by Western blot and p65 translocation assay. Downstream, mRNA and protein levels of cytokines and chemotaxis of T cells were investigated. Results: Proteomic analysis revealed time-dependent modulation of the macrophage proteome and NF-κB signaling pathway, which was confirmed by Western blot and p65 translocation assay. sEVs from HNSCC patients negative for human papillomavirus type 16 (HPV) differentially modulated NF-κB signaling and sEV uptake mechanisms compared with sEVs from HPV-positive patients and healthy donors. Conclusions: Circulating sEVs derived from HNSCC patient plasma modulate macrophage proteomic profiles and NF-κB signaling. HPV16 status was associated with differential sEV-mediated macrophage regulation, suggesting a potential role of sEVs in systemic immune modulation in HNSCC. Full article

Wearable electroencephalography (EEG) is rapidly evolving toward lightweight, user-friendly systems that enable brain monitoring in naturalistic settings. Traditional multi-channel, gel-based systems provide broad scalp coverage and high signal fidelity but are impractical for unsupervised or long-term use. This review focuses on the emerging generation of smart wearable EEG devices that are easy to wear, require minimal setup, and typically integrate additional physiological sensors such as photoplethysmography (PPG), temperature, or motion sensors. We review wearable EEG systems across four main form factors: head-worn EEG devices, smart EEG patches and tattoos, in-ear and headphone-based EEG, and glasses-integrated EEG. Head-worn systems offer broader signal coverage and support more complex applications such as sleep staging, human–machine interaction, and epilepsy monitoring. Patch-based systems are well suited to comfortable long-term monitoring, particularly in sleep-related applications. Ear-center systems provide high user comfort and stable signal acquisition from non-traditional electrode locations. Glasses-integrated devices represent an emerging option for unobtrusive daytime neurophysiology. Each category is examined in terms of sensor fusion, technical parameters, and embedded algorithms, with particular emphasis on automated signal analysis. We conclude with a discussion on current limitations, regulatory and usability challenges, and future directions toward unobtrusive, AI-powered neurotechnology for home and clinical use. Full article

Accurate change detection in high-resolution remote sensing imagery is essential for urban planning, land-use monitoring, and disaster response. This study introduces CTA-Net, a Cross-Temporal Attention Network for binary change detection in bi-temporal optical imagery, designed to improve robustness against pseudo-changes caused by illumination variation, seasonal effects, and sensor noise. The proposed method employs a shared Siamese encoder with multi-scale Cross-Temporal Attention modules that derive spatial and channel attention from L2 feature differences, along with a lightweight confidence estimation head for per-pixel uncertainty modelling. A hybrid loss function combining confidence-weighted binary cross-entropy and focal loss is used to address class imbalance. Experiments on the LEVIR-CD dataset demonstrate that CTA-Net achieves an overall accuracy of 98.99%, an F1-score of 87.68%, an Intersection over Union of 78.06%, a Cohen’s kappa of 0.8715, and a Matthews Correlation Coefficient of 0.8721, with stable convergence and minimal overfitting. Qualitative and calibration analyses further indicate that the model produces interpretable attention maps and reliable probabilistic outputs. To evaluate cross-domain generalization, we conduct a transfer learning case study on multispectral Sentinel-2 agricultural imagery. The model is adapted to 11-channel input and fine-tuned on automatically generated change masks derived from NDVI-delta thresholding. Under this supervision protocol, CTA-Net achieves an F1-score of 95.18% and an IoU of 90.81% on a held-out test region, with balanced precision and recall. While these results demonstrate effective adaptation across sensor modality, spatial resolution, and semantic domain, the evaluation reflects agreement with the mask generation procedure rather than independently annotated ground truth. While CTA-Net shows strong performance and reasonable interpretability, its cross-domain evaluation is limited by the use of automatically generated labels. As a result, the reported transferability should be interpreted cautiously until validated on human-annotated datasets. Full article