Multidisciplinary Digital Publishing Institute (Switzerland)
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Transmissive Multilayer Geometric Phase Gratings Using Water-Soluble Alignment Material
No full textMultilayer liquid crystal devices can offer enhanced optical functionalities for augmented reality and photonic applications, but fabrication remains severely limited by solvent incompatibility between photoalignment materials and underlying polymerized layers. Conventional photoalignment agents use aggressive solvents like N,N-dimethylformamide that damage polymerized substrates, necessitating protective interlayers. This study demonstrates a water-soluble photoalignment approach using AbA-2522 that eliminates these fabrication barriers. The water-soluble alignment material enables direct multilayer processing without layer damage while maintaining alignment quality equivalent to conventional materials. We successfully fabricate compact transmissive devices integrating liquid crystal polarization gratings with quarter-wave plates, achieving a first-order diffraction efficiency of 65.4% for 9 μm period gratings for linearly polarized incident light (λ = 457 nm). The multilayer structure exhibits highly selective polarization-dependent diffraction with efficiency ratios exceeding 10:1 between preferred and suppressed orders, eliminating external polarization control elements. Polarized optical microscopy confirms excellent alignment uniformity, while the fabrication process offers environmental benefits and reduced complexity. This approach establishes a practical pathway for advanced multilayer photonic devices critical for next-generation augmented reality systems and photonic integration, addressing fundamental challenges that have limited multilayer liquid crystal device development
EEG Microstate Comparative Model for Improving the Assessment of Prolonged Disorders of Consciousness: A Pilot Study
No full textBackground: Accurate assessment of prolonged disorders of consciousness (pDOC) is a critical clinical challenge. Misdiagnosis in pDOC can occur in up to 40% of cases, highlighting the need for more objective and reproducible biomarkers to support neurophysiological scales, thereby improving diagnosis and guiding therapeutic and prognostic decisions. Electroencephalography (EEG) microstate analysis is a promising, non-invasive method for tracking large-scale brain dynamics, but research in pDOC has predominantly relied on a canonical 4-class model. This methodological constraint may limit the ability to capture the full complexity of neural alterations present in these patients. Objective: This pilot study aimed to offer an objective method for assessing consciousness, complementing and enhancing the existing approaches established in the literature. The classical 4-class and an extended 7-class microstate model were compared to determine which more accurately characterizes the complexity of resting-state brain dynamics across different levels of consciousness in pDOC patients and healthy controls (HCs). Methods: Retrospective resting-state EEG (rsEEG) data from a cohort of pDOC patients and HC subjects were analyzed. Microstate analysis was performed using both 4-class and 7-class templates. The models were evaluated and compared based on three criteria: spatial correspondence with canonical maps (shared variance), the number of significant intra-group correlations between temporal features (Spearman test), and their ability to discriminate between the pDOC and HC groups (Wilcoxon test). Results: The 7-class microstate model provided a more accurate description of brain activity for most participants, with a greater number of microstate classes exceeding the 50% shared variance threshold compared to the 4-class model. In the pDOC group, both the 4-class and 7-class models showed a mean shared variance <50% in class D, which is associated with executive functioning across both templates. For the HC group, a prevalence of classes B and D emerged in both models, indicating higher engagement of executive functions. Furthermore, the 7-class model allowed for a group-specific analysis, which demonstrated that microstates A and F were consistently shared among 86% of pDOC patients. This suggests the potential preservation of specific intrinsic brain networks, particularly the sensory and default networks, even in the presence of severely impaired consciousness. Moreover, the 7-class model yielded a higher number of significant correlations within both groups and identified a broader set of temporal features that were significantly different between pDOC patients and HCs. These results highlight the enhanced sensitivity of the 7-class model in distinguishing subtle brain dynamics and improving the diagnostic capability for pDOC. Conclusions: The 7-class microstate model provides a more fine-grained and sensitive characterization of brain activity in both pDOC patients and healthy individuals. It demonstrated better performance in capturing individual brain dynamics, identifying shared network patterns, and discriminating between clinical populations. These findings suggest that the extended 7-class model holds greater potential for clinical utility and could lead to the development of more robust biomarkers for assessing consciousness
Apheresis CD8+CCR7+CD45RA− T-Cells as a Novel Biomarker Associated with CAR T-Cell Kinetics and Clinical Outcome
No full textChimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of relapsed or refractory (r/r) diffuse large B-cell lymphoma (DLBCL); however, a significant proportion of patients fail to achieve a durable response, underscoring the need for reliable predictive biomarkers. We characterize T-lymphocyte subpopulations in apheresis samples from 23 r/r large B-cell lymphoma (LBCL) patients who received axicabtagene ciloleucel (axi-cel) to identify pre-treatment cell biomarkers associated with CAR T-cell kinetics and clinical outcomes. Immunophenotyping of T-cells within fresh apheresis samples and monitoring of circulating CAR T-cells were performed by multiparametric flow cytometry. The median peak CAR T-cell count was 45.2 CAR T-cells/mL. Strong CAR-T expanders (≥45.2 CAR T-cells/mL) exhibited higher values of both CD4+ (p = 0.011) and CD8+ (p = 0.023) central memory T-cells (TCM; CCR7+CD45RA−), as well as lower proportions of CD8+CD38+ T-cells in apheresis samples. In apheresis, a cut-off value of >4.3% of CD8+ TCM predicted strong CAR-T expansion (AUC: 0.80; p = 0.023) and superior progression-free survival (p = 0.04) compared with patients who had CD8+ TCM below the cut-off. Our data suggest that high frequencies of CD8+ TCM cells in apheresis samples may represent a promising pre-treatment biomarker associated with strong CAR-T expansion and superior clinical outcome in r/r LBCL patients following axi-cel
Data Factor Flow and the Reduction of Inter-Enterprise Total Factor Production Gaps: Mechanisms and Pathways
No full textThe mobility of data factors and the adoption of a collaborative innovation framework are key drivers influencing the gaps in total factor productivity (TFP) among enterprises in the digital economy. Using panel data from Chinese A-share listed companies between 2006 and 2022, this study empirically demonstrates how data factor flow reduces TFP gaps. The findings reveal that data factor flow enhances TFP convergence by facilitating knowledge diffusion, improving information transmission, and boosting innovation efficiency. However, the heterogeneity in enterprise RD efforts limits this convergence effect, highlighting the importance of collaborative innovation. The study further shows that the impact of data factor flow is more significant in smaller, privately owned enterprises in the eastern regions and in industries with low to high technology intensity and high market concentration. Key insights include (1) a positive synergy between government data openness policies and enterprise data flow, which reinforces the narrowing of TFP gaps; (2) a nonlinear relationship between data flow and TFP gaps, suggesting an optimal range for its maximum impact. The study concludes that an integrated framework optimizing both data governance and collaborative innovation ecosystems can foster innovation diffusion and support productivity-based competition. These findings provide valuable insights for innovation policy formulation and strategic decision-making in the digital economy
Consumption of Ultra-Processed Foods and Biochemical Markers Predictive of Type 2 Diabetes Mellitus in a Self-Selected Pilot Sample of Muslim Adolescents in Melilla
No full textThe consumption of ultra-processed foods (UPFs) in adolescence is high due to their widespread availability and accessibility and has been linked to increased cardiometabolic risk. In the Autonomous City of Melilla, an environment with particular cultural and religious characteristics, it is relevant to analyze the relationship of UPFs with metabolic markers of type 2 diabetes mellitus. This is a cross-sectional pilot study on 31 Muslim adolescents aged 15 to 17 years. The NOVA food classification was used to identify UPFs. The final sample comprised Muslim adolescents because written consent for venous blood sampling was obtained only from Muslim families/legal guardians. Separate multiple linear regression models adjusted for sex were fitted to examine the associations between UPF intake (%E/day) and each cardiometabolic and inflammatory marker. Higher UPF intake was positively associated with BMI, body fat percentage, waist circumference, waist-to-height indicator (ICA), and fasting glucose after controlling for the false discovery rate (q < 0.05). Regarding the inflammatory component, Muslim girls had elevated levels of IL-7, IL-10, and IL-13, and Muslim boys had higher levels of MIP-1β. In addition, IL-8 correlated positively with waist circumference, BMI, and the HDL/LDL ratio, while MCP-1 was negatively associated with Apo A1, total cholesterol, and HDL. In this exploratory pilot study, higher intake of UPF appears to be associated with greater central adiposity and higher fasting glucose; these hypothesis-generating findings warrant confirmation in larger, representative samples and may inform culturally adapted nutritional screening in Melilla
Septic Arthritis of the Temporomandibular Joint (SATMJ) in Adults: A Systematic Review of Case Reports and Case Series, Part I: Etiology and Epidemiology
No full textBackground/Objectives: Septic temporomandibular joint disease (STMJ) is a rare condition with a potentially dangerous course. Its etiology includes bacterial and fungal infections, systemic factors (e.g., diabetes, immunodeficiencies), and molecular mechanisms. Methods: Reports of SATMJ in adults, clinically and microbiologically confirmed, published up to the time of protocol registration (PROSPERO CRD42024613462), were included. ACM, BASE, CENTRAL, PubMed, ClinicalTrials.gov, Embase, Scopus, Google Scholar, and reference lists were searched. The search included strategies using the terms “temporomandibular joint septic arthritis” and related phrases. Two independent reviewers studied a selection of articles and extracted data (demographics, microbiology, risk factors, molecular mechanisms). Risk of bias was assessed using JBI tools, and the certainty of evidence was assessed using the GRADE tool. Results: The analysis included 59 cases of SATMJ. Anaerobic infections were found in 77%, Gram-positive infections in 72%, and fungal infections in only 7%. Diabetes and immunoincompetence were associated with SATMJ. Conclusions: The results highlight the predominance of Gram-positive and anaerobic infections. Systemic factors, such as diabetes, increase the risk of SATMJ. Limitations result from the heterogeneity and retrospective nature of the analyzed cases and possible publication biases
Emissivity-Driven Directional Biases in Geostationary Satellite Land Surface Temperature: Integrated Comparison and Parametric Analysis Across Complex Terrain in Hunan, China
No full textLand surface temperature (LST) is fundamental for monitoring surface energy balance and environmental dynamics, with remote sensing providing the primary means of acquisition. However, directional anisotropy (DA) introduces systematic bias in satellite-derived LST products, particularly over complex landscapes. This study examines the impact of angular effects on LST retrievals from three leading East Asian geostationary satellites (FengYun 4A, FengYun 4B, and Himawari 9) across Hunan Province, China, using integrated comparison with in situ measurements and reanalysis data. Results show that all products exhibit a systematic cold bias, with FY4B achieving the highest accuracy. Diurnal retrieval precision increases with higher solar zenith angles (SZA), while no consistent relationship is observed between viewing zenith angle (VZA) and retrieval accuracy. Notably, the retrieval bias of the FY4 series increases significantly when the sun and sensor are aligned in azimuth, particularly when the relative azimuth angle (RAA) is less than or equal to 30°. Parametric modeling reveals that emissivity kernel-induced anisotropy is the principal driver of significant LST deviations in central Hunan, while solar kernel effects result in LST overestimation in mountainous regions and underestimation in plains. Increases in elevation or vegetation density reduce emissivity-induced errors but amplify errors caused by shadowing and sunlit effects. Emissivity anisotropy is thus identified as the primary source of LST DA. These findings deepen the understanding of LST DA in remote sensing and provide essential guidance for refining retrieval algorithms and improving the applicability of LST products in complex terrains
Asymmetric Tear Secretion: Can This Disorder Help in Suspecting Gastroesophageal Reflux Disease and in Managing Sjögren’s Disease? A Pilot Study
No full textBackground and Objectives: Patients with Sjögren’s disease (SjD) do not experience any improvement in gastroesophageal reflux disease (GERD) symptoms after SjD treatment, and in some patients, reflux even worsens. It is important to note that GERD manifests itself through typical and atypical symptoms, the latter of which may include eye damage, as evidenced by a growing body of research. When SjD patients were prescribed medication to treat GERD, their condition improved at the same time. Therefore, we aim to investigate whether there is a link between ocular dryness and gastroesophageal reflux disease (GERD) in patients with Sjögren’s disease (SjD). Materials and Methods: Our study included 27 patients with SjD according to the 2016 American College of Rheumatology and the European League Against Rheumatism (ACR/EULAR) Sjögren’s syndrome Classification Criteria, and 28 patients with non-autoimmune sicca syndrome due to GERD (nonautoimmSicca). Results: The study involved 55 participants, 48 (87.3%) women and 7 (12.7%) men. The median age was 54 years (IQR 49–64). A total of 41 subjects (74.5%) had GERD, and 20 subjects (36.4%) tested positive for Helicobacter pylori: 13 (48.1%) and 1 (3.7%) in the SjD group, and 28 (100.0%) and 19 (67.9%) in the nonautoimmSicca group, respectively. A significant difference in asymmetric tear secretion (p < 0.001) was found between the nonautoimmSicca and SjD patients, with values of 5 (3–10) mm/5 min and 1 (0–2) mm/5 min, respectively. A low correlation was detected between sialometry results and tear secretion asymmetry (r = 0.48, p < 0.001). An increase of 1 mm/5 min in the tear secretion asymmetry between the eyes was associated with a 2.04-fold increase in the odds ratio for having GERD (95% CI 1.25–3.32, p = 0.004), and was associated with a 1.9-fold increase in the odds ratio for having GERD (95% CI 1.04–3.49, p = 0.038) in patients with SjD. The presence of Helicobacter pylori is associated with asymmetric tear secretion [95% CI 1.22 (1.05–1.41, p = 0.010)]. Conclusions: Asymmetric tear secretion between the eyes is associated with the odds of having GERD. Patients with non-autoimmune sicca syndrome due to GERD have significantly greater asymmetry in tear secretion compared to those diagnosed with Sjögren’s disease
Gas–Liquid Coalescing Filter with Wettability-Modified Gradient Pore Structure: Achieving Low Resistance, High Efficiency and Long Service Life
No full textWidely used in treating oil mist aerosols generated from metalworking processes, conventional gas–liquid coalescing filters face drawbacks such as increased energy consumption, performance limitations, and shortened service life due to high steady-state pressure drop. To address these issues, this study proposes an innovative design for a filter based on wettability-regulated gradient pore structure. Using glass fiber filter media with different pore size parameters as the substrate and incorporating an intermediate mesh layer, a three-layer filtration structure of “large-pore filtration layer—mesh layer—small-pore filtration layer” was constructed. The surface wettability of each layer was regulated by a self-developed surface modifier, producing gradient pore structure filters with different wettability configurations. The variations in key performance parameters, including steady-state pressure drop, filtration efficiency, saturation, and service life, were systematically evaluated for these configurations. Experimental results demonstrated that the configuration with an “oleophobic large-pore filtration layer—mesh layer—oleophilic small-pore filtration layer” yielded the best overall performance. Analysis based on the “jump-channel” model indicated that the gradient pore structure achieves progressive droplet filtration and optimizes droplet coalescence and capture through wettability differences. Consequently, while maintaining exceptional filtration efficiency (>99%), this configuration significantly reduces the steady-state pressure drop by over 34% and effectively extends the service life by more than 66%. This wettability-regulated gradient pore structure provides a novel technical pathway for addressing the challenges of balancing pressure drop and filtration efficiency, as well as extending the service life, in gas–liquid coalescing filters
Multicellular Model Reveals the Mechanism of AEE Alleviating Vascular Endothelial Cell Injury via Anti-Inflammatory and Antioxidant Effects
No full textVascular endothelial injury is a key pathological characteristic of multiple diseases, such as atherosclerosis, stroke, and mastitis. Aspirin eugenol ester (AEE) has been confirmed to exert a significant protective effect on vascular endothelial injury. However, the universal action patterns and underlying mechanisms of AEE across different pathological scenarios have not been systematically elucidated. This study aimed to investigate the effect and mechanism of AEE in alleviating multiple vascular endothelial injury models. Nine vascular endothelial injury models were established by treating bovine aortic endothelial cells (BAECs), mouse aortic endothelial cells (MAECs), and human umbilical vein endothelial cells (Huvecs) with ethanol (EtOH), hydrogen peroxide (H2O2), and copper sulfate (CuSO4), respectively. The protective effects of AEE were systematically evaluated via morphological observation, detection of inflammatory responses, and oxidative stress markers. Furthermore, metabolomics was employed to identify and analyze differentially expressed metabolites between the nine model groups and AEE groups. AEE exerted protective effects on all nine vascular endothelial injury models, inhibiting inflammation and oxidative stress induced by all inducers. Metabolomic analysis revealed that the differentially expressed metabolites modulated by AEE in most models were primarily enriched in lipid metabolism, amino acid metabolism, coenzyme biosynthesis, and other related pathways. AEE could improve vascular endothelial injury by upregulating antioxidant substance which included eicosapentaenoic acid (EPA), choline, coenzyme A (CoA), glutathione (GSH), catalase (CAT) and superoxide dismutase (SOD), as well as downregulating substances that cause endothelial oxidative damage, including phytosphingosine (PS), palmitic acid (PA), and arachidonic acid (AA)