RÉSUMÉ
Optical Fourier surfaces (OFSs), characterized by sinusoidally profiled diffractive optical elements, can outperform traditional binary-type counterparts by minimizing optical noise through selectively driving diffraction at desired frequencies. While scanning probe lithography (SPL), gray-scale electron beam lithography (EBL), and holographic inscriptions are effective for fabricating OFSs, achieving full-color diffractions at fundamental efficiency limits is challenging. Here, an integrated manufacturing process is presented, validated theoretically and experimentally, for fully transparent OFSs reaching the fundamental limit of diffraction efficiency. Leveraging holographic inscriptions and soft nanoimprinting, this approach effectively addresses challenges in conventional OFS manufacturing, enabling scalable production of noise-free and maximally efficient OFSs with record-high throughput (1010-1012 µm2 h-1), surpassing SPL and EBL by 1010 times. Toward this end, a wafer-scale OFSs array is demonstrated consisting of full-color diffractive gratings, color graphics, and microlenses by the one-step nanoimprinting, which is readily compatible with rapid prototyping of OFSs even on curved panels, demanding for transformative optical devices such as augmented and virtual reality displays.
RÉSUMÉ
To facilitate rapid monitoring of airborne viruses, they must be collected with high efficiency and concentrated in a small volume of a liquid sample. In addition, the development of low-cost miniaturized samplers is essential for multipoint monitoring. Thus, in an attempt to fulfill these requirements, this study developed a microfluidic condensation bioaerosol sampler (MCBS). The developed sampler comprised two parts: a virus growth section and a virus droplet-to-liquid sample conversion section, each of which was fabricated on a chip using microfluidic technology. The condensation nucleus growth technique used in the virus growth section grew nanometer-sized airborne viruses into micro-sized droplets, making it possible to collection of viruses easier and with high efficiency. In addition, the virus droplet-to-liquid sample conversion section controlled the transport of droplets based on electrowetting technology. This enabled the collected airborne viruses to be concentrated in tens of microliters of the liquid sample. To evaluate the performance of both the sections, the virus dropletization, virus collection efficiency, and virus droplet-to-liquid sample conversion efficiency were evaluated through quantitative experiments. H1N1 and HCOV-229E viruses were used to conduct quantitative experiments on MCBS. We could obtain virus liquid samples with at 72.8- and 89.9-times higher concentration through 1:1 evaluation with a commercial sampler. Thus, the developed sampler facilitated efficient collection and concentration of airborne viruses in a compact, cost-effective manner. This is expected to facilitate rapid and accurate multipoint monitoring of viral aerosols.
RÉSUMÉ
Background and Objective: Rheumatoid arthritis (RA) is an autoimmune disease in which joints are gradually destroyed. Early diagnosis and treatment before joint deformation or destruction is important. The detection of novel RA biomarkers in saliva may facilitate early detection of RA before disease onset. This study aimed to evaluate salivary concentration of α1-antitrypsin (A1AT) in healthy patients and those with RA, and to assess the diagnostic value of salivary A1AT. Materials and Methods: In total, 80 participants were included: 20 healthy participants, and 60 patients with RA. Saliva and serum samples were obtained from all the patients. Levels of A1AT and cytokines, including interleukin-1 beta (IL-1ß), IL-6, and IL-10 in saliva and serum, were evaluated using an enzyme-linked immunosorbent assay kit and Luminex assay. Data were analyzed using SPSS for Windows. Results: There was a higher level of A1AT in the saliva of patients with RA (median: 2388.66 ng/mL) than that in healthy controls (1579.06 ng/mL). There was a positive mild-to-moderate accuracy (area under the curve: 0.57-0.85) of A1AT in saliva to diagnose RA. The cut-off level (ng/mL) of A1AT in saliva for detecting RA was 1689.0. Conclusions: The obtained data can promote the application of the measurements of A1AT in saliva to diagnose RA.
Sujet(s)
Polyarthrite rhumatoïde , Salive , alpha-1-Antitrypsine , Femelle , Humains , Mâle , alpha-1-Antitrypsine/analyse , alpha-1-Antitrypsine/sang , Polyarthrite rhumatoïde/diagnostic , Polyarthrite rhumatoïde/sang , Marqueurs biologiques/analyse , Marqueurs biologiques/sang , Test ELISA/méthodes , Interleukine-1 bêta/analyse , Interleukine-1 bêta/sang , Projets pilotes , Salive/composition chimiqueRÉSUMÉ
Rheumatoid arthritis (RA) and osteoarthritis (OA) are two different types of arthritis. Within RA, the subsets between seronegative RA (snRA) and seropositive RA (spRA) represent distinct disease entities; however, identifying clear distinguishing markers between them remains a challenge. This study investigated and compared the oral health conditions in patients with RA and OA to clarify the differences from healthy controls. In addition, we investigated the serological characteristics of the patients, the factors that distinguished patients with RA from those with OA, and the main factors that differentiated between snRA and spRA patients. A total of 161 participants (mean age: 52.52 ± 14.57 years, 32 males and 129 females) were enrolled in this study and categorized as: normal (n = 33), OA (n = 31), and RA (n = 97). Patients with RA were divided into the following two subtypes: snRA (n = 18) and spRA (n = 79). Demographics, oral health, and serological characteristics of these patients were compared. The prevalence of periodontal diseases was significantly higher in patients with OA (100%) and RA (92.8%) than in healthy controls (0.0%). However, the presence of periodontal diseases was not utilized as a distinguishing factor between OA and RA. Xerostomia occurred more frequently in patients with RA (84.5%) than in patients with OA (3.2%) and healthy controls (0.0%) (all p < 0.001). ROC analysis revealed that periodontal disease was a very strong predictor in the diagnosis of OA compared to healthy controls, with an AUC value of 1.00 (p < 0.001). Additionally, halitosis (AUC = 0.746, 95% CI 0.621-0.871, p < 0.001) and female sex (AUC = 0.663, 95% CI 0.529-0.797, p < 0.05) were also significant predictors of OA. The strongest predictors of RA diagnosis compared to healthy controls were periodontal diseases (AUC = 0.964), followed by xerostomia (AUC = 0.923), age (AUC = 0.923), female sex (AUC = 0.660), and halitosis (AUC = 0.615) (all p < 0.05). Significant serological predictors of RA were anti-CCP Ab (AUC = 0.808), and RF (AUC = 0.746) (all p < 0.05). In multiple logistic regression analysis, xerostomia (odds ratio, OR: 8124.88, 95% CI 10.37-6368261.97, p-value = 0.008) and Anti-CCP Ab (OR: 671.33, 95% CI 2.18-207,074.02, p = 0.026) were significant predictors for RA compared to OA. When diagnosing spRA compared to snRA, anti-CCP Ab (AUC = 1.000, p < 0.001) and RF (AUC = 0.910, 95%CI 0.854-0.967, p < 0.001) had outstanding predictive performances. Therefore, clinicians and researchers should thoroughly evaluate the oral status of both OA and RA patients, alongside serological factors, and consider these elements as potential predictors.