M cells are involved in pathogenesis of human contact lens-associated giant papillary conjunctivitis

INTRODUCTION: The objective was to study the pathogenesis of contact lens-associated giant papillary conjunctivitis (CL-GPC). MATERIALS AND METHODS: Twenty-one biopsies of conjunctival giant papillae were obtained from soft contact lens wearers. The tissues were fixed in 4% paraformaldehyde and embedded in paraffin. Sections of 5 µm thickness were used for studies of histology and immunohistochemistry of pan-B and pan-T cell distributions. RESULTS: Conjunctival epitheliums on the top of conjunctiva-associated lymphoid tissue typically lacked goblet cells. Lymphocytes from underlying lymphoid follicle were pressed into intra-epithelial “pockets” formed through epithelial invagination. Under the follicle-associated epithelium, pan-B cells were mostly gathered in the central folliclar area and intraepithelial pockets, while CD3-positive T cells were predominantly distributed in parafolliclar region, but only a few in the intraepithelial pockets. CONCLUSIONS: Membranous epithelial cells (M cells) play a key role in the pathogenesis of CL-GPC for the binding and translocation of antigen and pathogen

One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation

Semantic communication in the 6G era has been deemed a promising communication paradigm to break through the bottleneck of traditional communications. However, its applications for the multi-user scenario, especially the broadcasting case, remain under-explored. To effectively exploit the benefits enabled by semantic communication, in this paper, we propose a one-to-many semantic communication system. Specifically, we propose a deep neural network (DNN) enabled semantic communication system called MR\_DeepSC. By leveraging semantic features for different users, a semantic recognizer based on the pre-trained model, i.e., DistilBERT, is built to distinguish different users. Furthermore, the transfer learning is adopted to speed up the training of new receiver networks. Simulation results demonstrate that the proposed MR\_DeepSC can achieve the best performance in terms of BLEU score than the other benchmarks under different channel conditions, especially in the low signal-to-noise ratio (SNR) regime.Comment: 5 pages, 6 figures, published to C

Biodegradable double-network GelMA-ACNM hydrogel microneedles for transdermal drug delivery

As a minimally invasive drug delivery platform, microneedles (MNs) overcome many drawbacks of the conventional transdermal drug delivery systems, therefore are favorable in biomedical applications. Microneedles with a combined burst and sustained release profile and maintained therapeutic molecular bioactivity could further broaden its applications as therapeutics. Here, we developed a double-network microneedles (DN MNs) based on gelatin methacrylate and acellular neural matrix (GelMA-ACNM). ACNM could function as an early drug release matrix, whereas the addition of GelMA facilitates sustained drug release. In particular, the double-network microneedles comprising GelMA-ACNM hydrogel has distinctive biological features in maintaining drug activity to meet the needs of application in treating different diseases. In this study, we prepared the double-network microneedles and evaluated its morphology, mechanical properties, drug release properties and biocompatibility, which shows great potential for delivery of therapeutic molecules that needs different release profiles in transdermal treatment

Likelihood-Based Panel Unit Root Tests for Factor Models

The thesis consists of four papers that address likelihood-based unit root tests for panel data with cross-sectional dependence arising from common factors. In the first three papers, we derive Lagrange multiplier (LM)-type tests for common and idiosyncratic unit roots in the exact factor models based on the likelihood function of the differenced data. Also derived are the asymptotic distributions of these test statistics. The finite sample properties of these tests are compared by simulation with other commonly used unit root tests. The results show that our LM-type tests have better size and local power properties. In the fourth paper, we estimate the spaces spanned by the common factors and the spaces spanned by the idiosyncratic components of the static factor model by using the quasi-maximum likelihood (ML) method and compare it with the widely used method of principal components (PC). Next, by simulation, we compare the size and power properties of established tests for idiosyncratic unit roots, using both the ML and PC methods. Simulation results show that the idiosyncratic unit root tests based on the likelihood-based residuals generally have better size and higher size-adjusted power, especially when the cross-sectional dimension is small and the time series dimension is large

Likelihood-Based Panel Unit Root Tests for Factor Models

The thesis consists of four papers that address likelihood-based unit root tests for panel data with cross-sectional dependence arising from common factors. In the first three papers, we derive Lagrange multiplier (LM)-type tests for common and idiosyncratic unit roots in the exact factor models based on the likelihood function of the differenced data. Also derived are the asymptotic distributions of these test statistics. The finite sample properties of these tests are compared by simulation with other commonly used unit root tests. The results show that our LM-type tests have better size and local power properties. In the fourth paper, we estimate the spaces spanned by the common factors and the spaces spanned by the idiosyncratic components of the static factor model by using the quasi-maximum likelihood (ML) method and compare it with the widely used method of principal components (PC). Next, by simulation, we compare the size and power properties of established tests for idiosyncratic unit roots, using both the ML and PC methods. Simulation results show that the idiosyncratic unit root tests based on the likelihood-based residuals generally have better size and higher size-adjusted power, especially when the cross-sectional dimension is small and the time series dimension is large

Biodegradable Beta-cyclodextrin Conjugated Gelatin Methacryloyl Microneedle for Delivery of Water-insoluble Drug

Transdermal delivery of water-insoluble drugs via hydrogel-based microneedle (MN) arrays is crucial for improving their therapeutic efficacies. However, direct loading water-insoluble drug into hydrophilic matrices remains challenging. Here we report a biodegradable MN arrays patch that is fabricated from naturally derived polymer conjugates of gelatin methacryloyl and (beta) -cyclodextrin (GelMA--CD). When curcumin, an unstable and water-insoluble anticancer drug, is loaded as a model drug, its stability and solubility are improved due to the formation of inclusion complex. The polymer-drug complex GelMA--CD/CUR) can be formulated into MN arrays with sufficient mechanical strength for skin penetration and tunable drug release profile. Anticancer efficacy of released curcumin is observed in three-dimensional (3D) B16F10 melanoma models. The GelMA--CD/CUR MN exhibits relatively higher therapeutic efficacy through more localized and deeper penetrated manner compared with a control non-transdermal patch. In vivo studies also verify biocompatibility and degradability of the GelMA--CD MN arrays patch

Biodegradable Beta-cyclodextrin Conjugated Gelatin Methacryloyl Microneedle for Delivery of Water-insoluble Drug

Transdermal delivery of water-insoluble drugs via hydrogel-based microneedle (MN) arrays is crucial for improving their therapeutic efficacies. However, direct loading water-insoluble drug into hydrophilic matrices remains challenging. Here we report a biodegradable MN arrays patch that is fabricated from naturally derived polymer conjugates of gelatin methacryloyl and (beta) -cyclodextrin (GelMA--CD). When curcumin, an unstable and water-insoluble anticancer drug, is loaded as a model drug, its stability and solubility are improved due to the formation of inclusion complex. The polymer-drug complex GelMA--CD/CUR) can be formulated into MN arrays with sufficient mechanical strength for skin penetration and tunable drug release profile. Anticancer efficacy of released curcumin is observed in three-dimensional (3D) B16F10 melanoma models. The GelMA--CD/CUR MN exhibits relatively higher therapeutic efficacy through more localized and deeper penetrated manner compared with a control non-transdermal patch. In vivo studies also verify biocompatibility and degradability of the GelMA--CD MN arrays patch