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Channeled spectropolarimetry enables real-time measurement of the polarimetric spectral information of the target. A crucial aspect of this technology is the accurate reconstruction of Stokes parameters spectra from the modulated spectra obtained through snapshot measurements. In this paper, a learnable sparse dictionary compressed sensing method is proposed for channeled spectropolarimeter (CSP) spectral reconstruction. Grounded in the compressive sensing framework, this method defines a variable sparse dictionary. It can learn prior knowledge from the measured modulated spectra, continuously optimizing its own structure and parameters iteratively by removing redundant basis functions and refining the matched basis functions. The learned sparse dictionary, post-training, can provide a more accurate sparse representation of the Stokes parameters spectra, enabling the proposed method to achieve more precise reconstruction results. To assess the efficacy of the proposed method, simulations and experiments were conducted, both of which consistently demonstrated the superior performance of the proposed approach. The suggested method is well-positioned to enhance the efficiency and accuracy of polarimetric spectral information retrieval in CSP applications.
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Achieving highly efficient broadband absorption is an important research area in nanophotonics. In this paper, a novel method is proposed to design broadband near-perfect absorbers, consisting of a four-layer hemispherical concentric nanoshell array. The proposed nanostructure supports absorptivity exceeding 95% in the entire visible region, and the absorption bandwidth is determined by the interaction or 'hybridization' of the plasmons of the inner and outer metal-based nanoshells. Moreover, the designed absorber has wide-angle capability and is insensitive to polarization. The simple structure, as well as the stable absorption properties, suggests that such core-shell nanostructures can serve as a potential candidate for many applications such as solar energy harvesting, photo-detection, and emissivity control.
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The prevalence of diabetic kidney disease (DKD) is increasing annually. Damage to and loss of podocytes occur early in DKD. tRNA-derived fragments (tRFs), originating from tRNA precursors or mature tRNAs, are associated with various illnesses. In this study, tRFs were identified, and their roles in podocyte injury induced by high-glucose (HG) treatment were explored. High-throughput sequencing of podocytes treated with HG was performed to identify differentially expressed tRFs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The expression levels of nephrin, podocin, and desmin were measured in podocytes after overexpression of tRF-1:24-Glu-CTC-1-M2 (tRF-1:24) and concomitant HG treatment. A total of 647 tRFs were identified, and 89 differentially expressed tRFs (|log2FC| ≥ 0.585; p ≤ .05) were identified in the HG group, of which 53 tRFs were downregulated and 36 tRFs were upregulated. The 10 tRFs with the highest differential expression were detected by real-time quantitative polymerase chain reaction (RT-qPCR), and these results were consistent with the sequencing results. GO analysis revealed that the biological process, cellular component, and molecular function terms in which the tRFs were the most enriched were cellular processes, cellular anatomical entities, and binding. KEGG pathway analysis revealed that tRFs may be involved in signaling pathways related to growth hormones, phospholipase D, the regulation of stem cell pluripotency, and T-/B-cell receptors. Overexpression of tRF-1:24, one of the most differentially expressed tRFs, attenuated podocyte injury induced by HG. Thus, tRFs might be potential biomarkers for podocyte injury in DKD.
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Glucose , Podócitos , Glucose/efeitos adversos , Glucose/farmacologia , Podócitos/metabolismo , RNA de Transferência/química , RNA de Transferência/genética , RNA de Transferência/metabolismo , Transdução de Sinais , Nefropatias Diabéticas/epidemiologiaRESUMO
A reconstruction method incorporates the complete physical model into a traditional deep neural network (DNN) is proposed for channeled spectropolarimeter (CSP). Unlike traditional DNN-based methods that need to employ training datasets, the method starts from randomly initialized parameters which are constrained by the CSP physical model. It iterates through the gradient descent algorithm to obtain the estimation of the DNN parameters and then to obtain the mapping relationship. As a result, it eliminates the need for thousands of sets of ground truth data, while also leveraging the physical model to achieve high-precision reconstruction. As seen, the physical model participates in the optimization process of DNN parameters, thus achieving physical guidance for the DNN output results. Based on the characteristic of the network, we designate this method as the physics-guided neural network (PGNN). Both simulations and experiments demonstrate the superior performance of the proposed method. Our approach will further promote the practical application of CSP in a wider range of fields.
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Coherent coupling of optical modes with a high Q-factor underpins realization of efficient light-matter interaction with multi-channels in resonant nanostructures. Here we theoretically studied the strong longitudinal coupling of three topological photonic states (TPSs) in a one-dimensional topological photonic crystal heterostructure embedded with a graphene monolayer in the visible frequencies. It is found that the three TPSs can strongly interplay with one another in the longitudinal direction, enabling a large Rabi splitting (â¼ 48 meV) in spectral response. The triple-band perfect absorption and selective longitudinal field confinement have been demonstrated, where the linewidth of hybrid modes can reach 0.2â nm with Q-factor up to 2.6 × 103. Mode hybridization of dual- and triple-TPSs were investigated by calculation of the field profiles and Hopfield coefficients of the hybrid modes. Moreover, simulation results further show that resonant frequencies of the three hybrid TPSs can be actively controlled by simply changing the incident angle or structural parameters, which are nearly polarization independent in this strong coupling system. With the multichannel, narrow-band light trapping and selectively strong field localization in this simple multilayer regime, one can envision new possibilities for developing the practical topological photonic devices for on-chip optical detection, sensing, filtering, and light-emitting.
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Diabetes mellitus is a complicated metabolic disease that has become one of the fastest-growing health crises in modern society. Diabetic patients may suffer from various complications, and diabetic foot is one of them. It can lead to increased rates of lower-extremity amputation and mortality, even seriously threatening the life and health of patients. Because its healing process is affected by various factors, its management and treatment are very challenging. To address these problems, smart biomaterials have been developed to expedite diabetic wound closure and improve treatment outcomes. This review begins with a discussion of the basic mechanisms of wound recovery and the limitations of current dressings used for diabetic wound healing. Then, the categories and characteristics of the smart biomaterial scaffolds, which can be utilized as a delivery system for drugs with anti-inflammatory activity, bioactive agency, and antibacterial nanoparticles for diabetic wound treatment were described. In addition, it can act as a responsive system to the stimulus of the pH, reactive oxygen species, and glucose concentration from the wound microenvironment. These results show that smart biomaterials have an enormous perspective for the treatment of diabetic wounds in all stages of healing. Finally, the advantages of the construction of smart biomaterials are summarized, and possible new strategies for the clinical management of diabetic wounds are proposed.
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Diabetes Mellitus , Pé Diabético , Humanos , Materiais Biocompatíveis/uso terapêutico , Pé Diabético/tratamento farmacológico , Cicatrização , Antibacterianos/farmacologia , Antibacterianos/uso terapêutico , Bandagens , Diabetes Mellitus/terapiaRESUMO
Channeled spectropolarimetry is a snapshot technique for measuring the spectra of Stokes parameters of light by demodulating the measured spectrum. As an indispensable part of the channeled spectropolarimeter, the spectrometer module is far from being perfect to reflect the real modulation spectrum, which further reduces the polarimetric reconstruction accuracy of the channeled spectropolarimeter. Since the modulation spectrum is composed of many continuous narrow-band spectra with high frequency, it is a challenging work to reconstruct it effectively by existing methods. To alleviate this issue, a convolutional neural network (CNN)-based spectral reconstruction solver is proposed for channeled spectropolarimeter. The key idea of the proposed method is to first preprocess the measured spectra using existing traditional methods, so that the preprocessed spectra contain more spectral features of the real spectra, and then these spectral features are employed to train a CNN to learn a map from the preprocessed spectra to the real spectra, so as to further improve the reconstruction quality of the preprocessed spectra. A series of simulation experiments and real experiments were carried out to verify the effect of the proposed method. In simulation experiments, we investigated the spectral reconstruction accuracy and robustness of the proposed method on three synthetic datasets and evaluate the effect of the proposed method on the demodulation results obtained by the Fourier reconstruction method. In real experiments, system matrices are constructed by using measured spectra and reconstructed spectra respectively, and the spectra of Stokes parameters of incident light are estimated by the linear operator method. Several other advanced demodulation methods are also used to demodulate the measured spectrum in both simulation and real experiments. The results show that compared with other methods, the accuracy of the demodulation results can be much more improved by employing the CNN-based solver to reconstruct the measured spectrum.
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An advanced optical design for a low f-number, high resolution, astigmatism-free, and broadband Czerny-Turner spectrometer is proposed. A hemispherical lens is added between the entrance slit and collimating mirror, which can correct astigmatism and increase numerical aperture at the same time. The theory and method for the aberration correction are analyzed in detail. An example of a design with the f-number as 3 working in 350-750 nm has been presented by the optimized theory. The comparison of the improved Czerny-Turner spectrometer with the conventional Czerny-Turner spectrometer is also thoroughly described in the paper. The ray-tracing results show that the RMS spot radius of the improved Czerny-Turner spectrometer decreases from over 200 µm to less than 18 µm compared with the traditional Czerny-Turner spectrometer.
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An advanced Dyson imaging spectrometer in the near ultraviolet-visible-near infrared region was designed, fabricated, and evaluated. A lens with reflective coating on the back surface is applying to replace the traditional lens-reflecting grating combination. The design concept and fabrication and alignment methods as well as the results of evaluations of the proposed spectrometer are described in detail. The advanced imaging spectrometer achieves high resolution in both spectral and spatial direction and low stray light at a high numerical aperture in the working waveband. The performance of this modified porotype is analyzed and evaluated. Results show the spectrometer is well suited for the remote sensing of the ocean color as well as for various agriculture and vegetation-related applications.
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Based on the statistical study of meteorological balloons equipped with thermosondes, a new model that estimates the profile of the refractive index structure constant (Cn2) is proposed. Utilizing temperature, pressure, and wind shear as inputs, this new approach can estimate vertical profiles of Cn2 with 100 m vertical resolution. We used four outer scale models (Thorpe, HMNSP99, Dewan, and our proposed model) on data acquired from Rongcheng (Shandong Peninsula) and Maoming (Guangdong Province) to estimate the Cn2 profiles and compared the results with the measured Cn2 profile. The proposed method outperformed the other three models, yielding an estimation profile that matched well with the measured median Cn2 profiles, with an average relative error generally less than 3.5% and a mean correlation coefficient larger than 0.72 in Maoming, an average relative error generally less than 3.4% and a mean correlation coefficient larger than 0.84 in Rongcheng. The proposed outer scale model also shows good performance in estimating integrated atmospheric parameters.
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A novel, to the best of our knowledge, configuration of a Littrow-Offner spectrometer that is off-axis in both the meridian and sagittal planes is proposed. Through theoretical analysis, the relationship between the distance of each element and the aperture is obtained, and the theoretical basis of the sagittal plane off-axis is given. Extra aberrations are corrected by a spherical lens with a convex grating. An example of design has been presented with an f-number of 4 working in 300-500 nm, according to the theory. Its spectral resolution achieves a 0.1 nm at central wavelength, and its volume decreases by 14.5% compared with the traditional Offner spectrometer.
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Spectral bandwidth correction is an effective way to obtain the original spectrum. However, the correct selection of optimal parameters used to recover the distortion spectrum in bandwidth correction algorithms has always been an important problem. To overcome the shortcomings of traditional parameter selection methods and obtain the optimal parameter, we propose a new optimal parameter selection method based on deep learning (DL). First, the database and neural network were constructed, and then the optimal parameters of corresponding algorithms were obtained through the training of the neural network. In order to verify the superiority of the optimal parameter selection method based on DL, the Levenberg-Marquardt (L-M) and Richardson-Lucy (R-L) algorithms with corresponding optimal parameters were compared with the traditional L-M and R-L algorithms to recover the distortion white light-emitting diode, Raman spectrum, and compact fluorescent lamp spectrum. The type A uncertainty and root mean square error values of the different cases were calculated. The results proved that, compared with the traditional methods for obtaining the optimal parameters, the neural network was capable of obtaining parameters that can make the bandwidth correction algorithm more efficient at recovering the distorted spectrum.
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BACKGROUND: Chronic pain adversely affects health and daily life in the elderly. Gaining insight into chronic pain that affects the community-dwelling elderly is crucial for pain management in China, which possesses the largest elderly population in the world. METHODS: This is a cross-sectional design study that followed the STROBE Guideline. A randomized cluster sampling method was used to recruit participants in the Sichuan Province from Dec 2018 to May 2019. In addition, face-to-face interviews were conducted to collect socio-demographic data, characteristics and health-seeking behaviors of chronic pain through a self-designed questionnaire. RESULTS: A total of 1381 older adults participated in this study. Among these participants, 791 (57.3%) had chronic pain. Here, prevalence and pain intensity were both found to increase from the 60-69 group to the 70-79 group, which then decreased in the ≥80 group with no significant differences in sex (p > 0.05). The most common pain locations were observed in the legs/feet (53.5%), head (23.6) and abdomen/pelvis (21.1%). Among the elderly suffering from chronic pain, 29.4% sought medical help, 59.2% received medication and 59.7% adopted non-drug therapy. CONCLUSION: Chronic pain is a common health concern in the Chinese community-dwelling elderly, which possesses different characteristics than other countries' populations. Therefore, easier access to medication assistance and provision of scientific guidance for non-drug therapy may serve as satisfactory approaches in improving pain management.
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Dor Crônica , Vida Independente , Idoso , China/epidemiologia , Dor Crônica/diagnóstico , Dor Crônica/epidemiologia , Dor Crônica/terapia , Estudos Transversais , Humanos , PrevalênciaRESUMO
During the training phase of the supervised learning, it is not feasible to collect all the datasets of labelled data in an outdoor environment for the localization problem. The semi-supervised transfer learning is consequently used to pre-train a small number of labelled data from the source domain to generate a kernel knowledge for the target domain. The kernel knowledge is transferred to a target domain to transfer some unlabelled data into the virtual labelled data. In this paper, we have proposed a new outdoor localization scheme using a semi-supervised transfer learning for LoRaWANs. In the proposed localization algorithm, a grid segmentation concept is proposed so as to generate a number of virtual labelled data through learning by constructing the relationship of labelled and unlabelled data. The labelled-unlabelled data relationship is repeatedly fine-tuned by correctly adding some more virtual labelled data. Basically, the more the virtual labelled data are added, the higher the location accuracy will be obtained. In the real implementation, three types of signal features, RSSI, SNR, and timestamps, are used for training to improve the location accuracy. The experimental results illustrate that the proposed scheme can improve the location accuracy and reduce the localization error as opposed to the existing outdoor localization schemes.
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PURPOSE: To measure and compare the area of inhibition around a bioglass-containing adhesive and resin-based composite following an in vitro artificial caries model in human extracted teeth. METHODS: Preparations were made at the CEJ of extracted human molars (40, n=10/material) and restored with combinations of a bioglass-containing adhesive (BA, Regen), a reference adhesive which served as a negative control (RA), a bioglass-containing composite (BC, Regen), and a reference composite which served as a negative control (RC): BABC, RABC, BARC, RARC. All materials were light-cured and then finished with a polishing disc. Teeth were incubated (37°C) for 24 hours in water. A demineralization solution composed of 0.1 M lactic acid, 3 mM Ca3(PO4)2, 0.1% thymol, and NaOH (to adjust pH= 4.5) and a remineralization solution composed of 1.5 mM Ca, 0.9 mM P, and 20 mM Tris(hydroxymethil)-aminomethane (pH= 7.0) were prepared. Specimens were placed in the demineralization solution for 4 hours followed by a remineralization solution for 20 hours and cycled daily for 30 days. The specimens were embedded, sectioned into 100 µm sections, and the interface between the adhesive/composite and root dentin margin was viewed with polarized light. A line was drawn parallel with the zone of demineralization for each tooth. The area of "inhibition" (defined as the area external to the line) or "wall lesion" (defined as the area internal to the line) was traced with internal image evaluation software and measured. Areas of inhibition were measured as positive values and areas of wall lesions were measured as negative values. RESULTS: A one-way ANOVA found significant differences between materials for "inhibition/wall lesion" areas in root dentin (P< 0.001). Tukey post-hoc analysis ranked materials (µm2, mean± SD): BABC (3590± 2847)a RABC (1903± 1025)a, BARC (-792± 850)b, RARC (-2544± 1760)b. CLINICAL SIGNIFICANCE: The use of bioglass-containing resin-based composite with or without a bioglass-containing adhesive demonstrated inhibition of demineralization at the restoration margin.
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Restauração Dentária Permanente , Desmineralização do Dente , Cerâmica , Resinas Compostas , Cimentos Dentários , Humanos , Desmineralização do Dente/prevenção & controleRESUMO
OBJECTIVES: To understand the influence of medical insurance policy reforms in Guangxi on the hospitalization expenses of breast cancer patients by analyzing the composition and changing trend in breast cancer diagnosis and treatment expenses in the Guangxi Medical University Cancer Hospital, and to provide the evidence for the improvement of medical insurance policy reform. METHODS: A total of 3 950 breast cancer patients were collected from 2014 to 2017 and analyzed. Kruskal-Wallis test and multiple linear regression model were used to discuss the breast cancer related epidemiology and analyze the composition of hospitalization expenses and its influential factors. RESULTS: The median hospitalization cost of breast cancer patients in our hospital from 2014 to 2017 was 29 266.94 Chinese Yuan. Single factor analysis showed that the impact of year, hospitalization days, age, payment method, tumor stage, and treatment method on hospitalization cost was significant (all P<0.01). Multiple linear regression analysis showed that the power of influential factors of hospitalization costs arranged descending from 2014 to 2017 as follows: hospitalization days, treatment methods, payment method, tumor staging, and age. CONCLUSIONS: Reasonably controlling hospitalization days and actively promoting the integration of urban and rural medical insurance can effectively reduce the economic burden for breast cancer patients.
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Neoplasias da Mama , Institutos de Câncer , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/terapia , China/epidemiologia , Feminino , Gastos em Saúde , Hospitalização , Humanos , Políticas , UniversidadesRESUMO
The directional polarimetric camera (DPC), developed by Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, is a satellite sensor used to observe the polarization and directionality of the earth's reflectance. It acquires the two-dimensional image of the earth with a large field of view (118.74°) and a high spatial resolution (3.3 km) in 8 spectral bands. The first DPC was successfully launched onboard the GaoFen-5 satellite in May 2018, subject to the Chinese high-resolution earth observation program. In this paper, a set of systematic and complete pre-flight calibrations of the DPC are proposed to ensure the effective characterization for in-flight calibration, so as to ensure the accuracy of DPC measured radiation polarization data and the reliability of inversion results. Since the geometric calibration method of the DPC has been presented in an early companion paper [Appl. Opt. 59 226 (2020)], this paper will not introduce it in detail. Instead, the geometric calibration results of each spectral band together with a discussion on the origin of differences between spectral bands are analyzed, and the error analysis of the method is conducted. The results of the DPC geometric calibration is that the residuals of all spectral bands are less than 0.1 pixel. For radiometric calibration, the radiometric models of non-polarized bands and polarized bands are derived in detail, respectively, and the specific calibration methods with error analysis, equipment, and main results with their related accuracies for each parameter of the radiometric models are described. To verify the accuracy of calibration parameters, a series of polarization detection accuracy verification experiments based on a non-polarized radiation source, a polarizing system, and a natural scene were carried out. The experimental results show that the maximum deviation of degree of polarization between the set values of the polarizing system and measured values of the DPC at the corresponding positions of four field of view angles of 0, 15, 30, and 45 degrees of each polarized spectral band is 0.009, 0.004, and 0.003, respectively. The average error in measuring the degree of polarization of a non-polarized light source by all pixels in the three polarized bands is 0.0043, 0.0046, and 0.0037, respectively. And the relative deviations of each field of view are within 0.020 when the DPC and CE318N simultaneously measure the DoLP of sky. All of these prove the effectiveness of the pre-flight calibration.
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The directional polarimetric camera (DPC) is a remote-sensing instrument for the characterization of atmospheric aerosols and clouds by simultaneously conducting spectral, angular, and polarimetric measurements. Polarization measurement accuracy is an important index to evaluate the performance of the DPC and mainly related to the calibration accuracy of instrumental parameters. In this paper, firstly, the relationship between the polarization measurement accuracy of DPC and the parameter calibration errors caused by the nonideality of the components of DPC are analyzed, and the maximum polarization measurement error of DPC in the central field of view and edge field of view after initial calibration is evaluated respectively. Secondly, on the basis of the radiometric calibration of the DPC onboard the GaoFen-5 satellite in an early companion paper [Opt. Express2813187 (2020)10.1364/OE.391078], a series of simple and practical methods are proposed to improve the calibration accuracy of the parameters-the diattenuation of the optics, absolute azimuth angle, and relative transmission corresponding to each pixel, thereby improving the polarization measurement accuracy of DPC. The calibration results show that, compared with the original methods, the accuracy of the diattenuation of the optics, relative azimuth angle, and relative transmission of three polarized channels obtained with the improved methods are improved from ±1%, 0.1 degree and ±2% to ±0.4%, 0.05 degree and ±0.2%, respectively. Finally, two verification experiments based on a non-polarized radiation source and a polarizing system were carried out in the laboratory respectively to verify the improvement of the parameters modified by the proposed methods on the polarization measurement accuracy of the DPC to be boarding the GaoFen-5 (02) satellite. The experimental results show that when the corrected parameters were employed, the average error in measuring the degree of linear polarization of non-polarized light source for all pixels in the three polarized bands and the maximum deviation of the degree of linear polarization between the values set by the polarizing system and the values measured by the DPC at several different field of view angles for each polarized spectral band are obviously reduced. Both the mean absolute errors and the root mean square errors of the degree of linear polarization obtained with the corrected parameters are much lower than those obtained with the original parameters. All of these prove the effectiveness of the proposed methods.
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The directional polarimetric camera (DPC) is a polarization sensor with ultra-wide-angle and low-distortion imaging characteristics. Geometric calibration is usually the first essential step before remote sensing satellites are launched. In this paper, a geometric calibration method based on a two-dimensional turntable and a rotation matrix with high precision, simple operation, and wide application range is proposed for the directional polarimetric camera. Instead of precisely adjusting the position of the sensor on the turntable, the method effectively eliminates the errors caused by the mechanical axis of the turntable and the optical axis of the sensor not being adjusted to the same direction through the rotation transformation of the coordinate system. The geometric calibration experiments of the directional polarimetric camera were carried out with the method of Chen et al. [Optik121, 486 (2010)10.1016/j.ijleo.2008.08.004OTIKAJ0030-4026] and the proposed method. The experimental results showed the calibration residual of the proposed method was less than 0.1 pixel while Chen's method was 0.3 pixel. The mean reprojection error and root mean square error of the proposed method were reduced to 0.06352 pixel and 0.06961 pixel, respectively. The geometric calibration parameters obtained by the proposed method were used for geometric correction of the in-orbit images of the DPC, and the results also prove the effectiveness and superiority of the proposed method.
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OBJECTIVES: To compare the ability of resin-modified glass ionomer (RMGI) and bioactive cements to prevent root dentin demineralization. MATERIALS AND METHODS: Fifty molars were prepared at the cementum-enamel junction (n = 10) and restored with three bioactive cements (Activa Bioactive Cement, ACT; Ceramir Crown and Bridge, CER; and Theracem, THE), a self-adhesive resin cement (Rely X Unicem 2, UNI), and a RMGI cement (Rely X Luting Plus, LUT). Specimens were cycled for 30 days between a demineralization solution (pH = 4) composed of 0.1 M lactic acid and 3 mM Ca3 (PO4 )2 for 4 hours and a remineralization solution (pH = 7.0) composed of 1.5 mM Ca, 0.9 mM P, and 20 mM Tris(hydroxymethyl)-aminomethane for 20 hours. Specimens were sectioned to 100 µm and evaluated with polarized light microscopy. A line was drawn parallel with the zone of demineralization for each tooth. The areas of "inhibition" (external to the line) were measured as positive values and "wall lesions" (pulpal to the line) were measured as negative areas. RESULTS: Significant differences were found between materials for "inhibition/wall lesion" areas in root dentin (P < .001) and ranked as (µm2 , mean ± SD): LUT (7700 ± 2500) > CER (3800 ± 1900), THE (2100 ± 2600), and ACT (1400 ± 700) > UNI (-2000 ± 1700). CONCLUSIONS: Bioactive cements showed net areas of demineralization inhibition albeit at a lower level than a reference RMGI cement. CLINICAL SIGNIFICANCE: RMGI or bioactive cements may be indicated for patients at risk of secondary caries around crown margins.