Characterization of urethral fibrosis in a rabbit model: Potential roles of Wnt-ß catenin pathway and epithelial to mesenchymal transition.

AIM: To elucidate the precise cellular and molecular mechanisms that underlie urethral fibrogenesis. METHODS: Endoluminal electrocautery injury (using Karl Storz 10 Fr. Pediatric urethroscope) was employed in male rabbits (n = 6) to create mucosal injury. Retrograde urethrogram (RUG) and endoluminal ultrasound techniques were used to assess severity and changes in luminal cross-sectional area. Six control rabbits were subjected to sham injury, in which the electrocautery was inserted but not powered. Urethral tissues were harvested 30 days postinjury and subjected to RNA sequencing and quantitative polymerase chain reaction (qPCR) to determine changes in gene expression. Histological, immunostaining, and Western blot studies were used to determine changes in protein expression of known markers of fibrosis (eg, collagen, Integrinαv, GIV/Girdin, transforming growth factor-ß (TGF-ß), and pSMAD1,2,3). RESULTS: Trichrome staining confirmed increased connective tissue in urethral scar tissues. Immunostaining revealed a potential role for epithelial to mesenchymal cell transition (EMT) and positive labeling for all fibrotic markers (eg, collagen-1, Integrin αv, GIV/Girdin, transforming growth factor-ß (TGF-ß), and SMAD1,2,3). Western blot analysis confirmed increased protein levels of these fibrotic markers. CONCLUSION: Our RNA sequencing and qPCR studies, in conjunction with our protein data, suggest that urethral mucosal fibrogenesis may be mediated by novel fibrogenic signaling pathways involving Wnt-ß catenin, TGF-ß, GIV/Girdin, and EMT which lead to increased collagen deposition. Therapeutic strategies targeting these pathways may be beneficial in attenuating fibrogenesis and stricture progression.

Direct Characterization of Near-Field Coupling in Gap Plasmon-Based Metasurfaces.

Metasurfaces based on gap surface-plasmon resonators allow one to arbitrarily control the phase, amplitude, and polarization of reflected light with high efficiency. However, the performance of densely packed metasurfaces is reduced, often quite significantly, in comparison with simple analytical predictions. We argue that this reduction is mainly because of the near-field coupling between metasurface elements, which results in response from each element being different from the one anticipated by design simulations, which are commonly conducted for each individual element being placed in an artificial periodic arrangement. In order to study the influence of near-field coupling, we fabricate meta-elements of varying sizes arranged in quasi-periodic arrays so that the immediate environment of same size elements is different for those located in the middle and at the border of the arrays. We study the near-field using a phase-resolved scattering-type scanning near-field optical microscopy (s-SNOM) and conducting numerical simulations. By comparing the near-field maps from elements of the same size but different placements we evaluate the near-field coupling strength, which is found to be significant for large and densely packed elements. This technique is quite generic and can be used practically for any metasurface type in order to precisely measure the near-field response from each individual element and identify malfunctioning ones, providing feedback to their design and fabrication, thereby allowing one to improve the efficiency of the whole metasurface.

Establishment of an in ovo chick embryo yolk sac membrane (YSM) assay for pilot screening of potential angiogenic and anti-angiogenic agents.

Angiogenesis, the process of new blood vessel formation from pre-existing vessels, is essential for growth and development. Development of drugs that can accelerate or decelerate angiogenesis in the context of various diseases requires appropriate preclinical screening. As angiogenesis involves complex cellular and molecular processes, in vivo studies are superior to in vitro investigations. Conventional in vitro, in vivo, and ex ovo models of angiogenesis are time consuming and tedious, and require sophisticated infrastructure for embryo culture. In the present study, we established an in ovo chick embryo yolk sac membrane (YSM) assay for angiogenesis and tested the angiogenic potential of arginine, conditioned medium (CM) from human adipose tissue and placenta-derived mesenchymal stem cells (ADMSCs-CM and PDMSCs-CM), avastin and vitamin C. The obtained results were confirmed with the routinely employed chick embryo Chorioallantoic Membrane (CAM) assay. Both assays revealed the pro-angiogenic nature of arginine, ADMSCs-CM, and PDMSCs-CM, and the anti-angiogenic effect of avastin and vitamin C. This novel in ovo YSM model is simple, reproducible, and highly economic in terms of the time frame and cost incurred. The proposed model is thus a suitable substitute to the CAM model for pilot screening of potential angiogenic and anti-angiogenic agents.

Barriers to fruit and vegetable consumption among farmers' market incentive programme users in Illinois, USA.

OBJECTIVE: Previous research indicates that low-income individuals often struggle to consume the recommended amount of fruits and vegetables (F&V). LINK Up Illinois is a farmers' market incentive programme that aims to increase F&V consumption among Supplemental Nutrition Assistance Program (SNAP) recipients by improving access to and affordability of locally grown foods. The present research aimed to identify barriers to F&V consumption that exist among users of the LINK Up Illinois programme. DESIGN: Cross-sectional. SETTING: Farmers' markets in Chicago, Springfield, Northbrook, Woodstock, Aurora and Urbana, IL. SUBJECTS: In 2016, a volunteer sample of 140 LINK Up Illinois users (mean age 42·5 years; 81·7 % female; 28·7 % African American; 44·0 % obese) completed a survey at participating farmers' markets across the state. Information on demographics, food shopping behaviours, programme satisfaction, barriers to F&V consumption and frequency of F&V consumption was collected and examined. RESULTS: Approximately 23 % of survey participants reported consuming F&V ≥3 times/d. The barriers to F&V consumption most often reported by survey participants were the cost of F&V (29·5 %), spoilage (18·6 %), knowing how to cook F&V (8·7 %) and not thinking about F&V when hungry (8·6 %). Results from multivariable-adjusted logistic regression models suggested that reporting one or more barriers was associated with reduced odds of consuming vegetables ≥3 times/d, but not fruits. CONCLUSIONS: Cost, spoilage and knowledge of cooking are key barriers to F&V consumption that exist among LINK Up Illinois users. Strategies are needed to mitigate these barriers and increase F&V consumption in this population.

Real-time imaging as an emerging process analytical technology tool for monitoring of fluid bed coating process.

A direct imaging system (EyeconTM) was used as a Process Analytical Technology (PAT) tool to monitor fluid bed coating process. EyeconTM generated real-time onscreen images, particle size and shape information of two identically manufactured laboratory-scale batches. EyeconTM has accuracy of measuring the particle size increase of ±1 µm on particles in the size range of 50-3000 µm. EyeconTM captured data every 2 s during the entire process. The moving average of D90 particle size values recorded by EyeconTM were calculated for every 30 min to calculate the radial coating thickness of coated particles. After the completion of coating process, the radial coating thickness was found to be 11.3 and 9.11 µm, with a standard deviation of ±0.68 and 1.8 µm for Batch 1 and Batch 2, respectively. The coating thickness was also correlated with percent weight build-up by gel permeation chromatography (GPC) and dissolution. GPC indicated weight build-up of 10.6% and 9.27% for Batch 1 and Batch 2, respectively. In conclusion, weight build-up of 10% can also be correlated with 10 ± 2 µm increase in the coating thickness of pellets, indicating the potential applicability of real-time imaging as an endpoint determination tool for fluid bed coating process.

Third-order gap plasmon based metasurfaces for visible light.

Efficient control and manipulation of light using metasurfaces requires high fabrication accuracy that becomes progressively demanding when decreasing the operation wavelength. Considering gap surface plasmon (GSP) based metasurfaces, we demonstrate that the metasurfaces, which utilize the third-order GSP resonance and thereby involve relatively large nanobricks, can successfully be used for efficient polarization-controlled steering of visible light. The reflection amplitude and phase maps for a 450 nm period array of 50 nm thick nanobricks placed atop a 40 nm thick silica layer supported by an optically thick gold film are calculated for the operation wavelength of 633 nm. Exploiting the occurrence of the third-order GSP resonance for nanobricks having their lengths close to 300 nm, we design the phase-gradient metasurface, representing an array of (450 x 2250 nm2) supercells made of 5 nanobricks with different dimensions, to operate as a polarization beam splitter for linearly polarized light. The fabricated polarization beam splitter is characterized using a supercontinuum light source at the normal light incidence and found to exhibit a polarization contrast ratio of up to 40 dB near the design wavelength of 633 nm while showing better than 20 dB contrast in the range of 550 - 650 nm for both polarizations. The diffraction efficiency experimentally measured at normal incidence exceeds 10% (20% in simulations) at the design wavelength of 633 nm, with the performance for the TE polarization (electric field perpendicular to the plane of diffraction) being significantly better (experimentally > 20% and theoretically > 40%) than for the TM polarization. This difference becomes even more pronounced for the light incidence deviating from normal. Finally, we discuss possible improvements of the performance of polarization beam splitters based on third-order GSP resonance as well as other potential applications of the suggested approach.

PAT-Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets.

Current endeavor was aimed towards monitoring percent weight build-up during functional coating process on drug-layered pellets. Near-infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15-Kg cellulosic coating material during Wurster coating process of drug-loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm-1, 7515.24 to 7108.33 cm-1, and 5257.00 to 5098.87 cm-1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm-1was found to be specific to drug. The final model gave superb correlation co-efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at-line prediction of functional coat value and can be used for monitoring the Wurster coating process.

Assessing the Capacity of a Denoising Diffusion Probabilistic Model to Reproduce Spatial Context.

Diffusion models have emerged as a popular family of deep generative models (DGMs). In the literature, it has been claimed that one class of diffusion models-denoising diffusion probabilistic models (DDPMs)-demonstrate superior image synthesis performance as compared to generative adversarial networks (GANs). To date, these claims have been evaluated using either ensemble-based methods designed for natural images, or conventional measures of image quality such as structural similarity. However, there remains an important need to understand the extent to which DDPMs can reliably learn medical imaging domain-relevant information, which is referred to as 'spatial context' in this work. To address this, a systematic assessment of the ability of DDPMs to learn spatial context relevant to medical imaging applications is reported for the first time. A key aspect of the studies is the use of stochastic context models (SCMs) to produce training data. In this way, the ability of the DDPMs to reliably reproduce spatial context can be quantitatively assessed by use of post-hoc image analyses. Error-rates in DDPM-generated ensembles are reported, and compared to those corresponding to other modern DGMs. The studies reveal new and important insights regarding the capacity of DDPMs to learn spatial context. Notably, the results demonstrate that DDPMs hold significant capacity for generating contextually correct images that are 'interpolated' between training samples, which may benefit data-augmentation tasks in ways that GANs cannot.

Understanding the light induced hydrophilicity of metal-oxide thin films.

Photocatalytic effects resulting in water splitting, reduction of carbon dioxide to fuels using solar energy, decomposition of organic compounds, and light-induced hydrophilicity observed on surfaces of various metal oxides (MOx), all rely on the same basic physical mechanisms, and have attracted considerable interest over the past decades. TiO2 and ZnO, two natively n-type doped wide bandgap semiconductors exhibit the effects mentioned above. In this study we propose a model for the photo-induced hydrophilicity in MOx films, and we test the model for TiO2/Si and ZnO/Si heterojunctions. Experimentally, we employ a wet exposure technique whereby the MOx surface is exposed to UV light while a water droplet is sitting on the surface, which allows for a continuous recording of contact angles during illumination. The proposed model and the experimental techniques allow a determination of minority carrier diffusion lengths by contact angle measurements and suggest design rules for materials exhibiting photocatalytic hydrophilicity. We expect that this methodology can be extended to improve our physical understanding of other photocatalytic surface effects.

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics.

BACKGROUND: The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. PURPOSE: The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain-relevant assessments via the analysis of relevant image statistics. METHODS: As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512  × $\times$  512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM-generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. RESULTS: Fifty-eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top-ranked submission employed a conditional latent diffusion model, whereas the joint runners-up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID-based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. CONCLUSIONS: This Grand Challenge highlighted the need for domain-specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics.

Background: The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose: The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain-relevant assessments via the analysis of relevant image statistics. Methods: As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108,000 images of size 512×512. For the evaluation of submissions to the Challenge, an ensemble of 10,000 DGM-generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance (FID)) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results: Fifty-eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top-ranked submission employed a conditional latent diffusion model, whereas the joint runners-up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID-based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions: This Grand Challenge highlighted the need for domain-specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions.

Objective.Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneous and structurally complicated objects is challenging under laboratory conditions due to partial spatial coherence and polychromaticity. A deep learning-based method (DLBM) provides a nonlinear approach to this problem while not being constrained by restrictive assumptions about object properties and beam coherence. The objective of this work is to assess a DLBM for its applicability under practical scenarios by evaluating its robustness and generalizability under typical experimental variations.Approach.Towards this end, an end-to-end DLBM was employed for QPR under laboratory conditions and its robustness was investigated across various system and object conditions. The robustness of the method was tested via varying propagation distances and its generalizability with respect to object structure and experimental data was also tested.Main results.Although the end-to-end DLBM was stable under the studied variations, its successful deployment was found to be affected by choices pertaining to data pre-processing, network training considerations and system modeling.Significance.To our knowledge, we demonstrated for the first time, the potential applicability of an end-to-end learning-based QPR method, trained on simulated data, to experimental propagation-based x-ray phase contrast measurements acquired under laboratory conditions with a commercial x-ray source and a conventional detector. We considered conditions of polychromaticity, partial spatial coherence, and high noise levels, typical to laboratory conditions. This work further explored the robustness of this method to practical variations in propagation distances and object structure with the goal of assessing its potential for experimental use. Such an exploration of any DLBM (irrespective of its network architecture) before practical deployment provides an understanding of its potential behavior under experimental settings.

Silk Fibroin Microparticle Scaffold for Use in Bone Void Filling: Safety and Efficacy Studies.

Silk fibroin (SF) is a natural biocompatible protein polymer extracted from cocoons of silkworm Bombyx mori. SF can be processed into a variety of different forms and shapes that can be used as scaffolds to support bone regeneration. Three-dimensional (3D) SF scaffolds have shown promise in bone-void-filling applications. In in vitro studies, it has been demonstrated that a microparticle-based SF (M-RSF) scaffold promotes the differentiation of stem cells into an osteoblastic lineage. The expression of differentiation markers was also significantly higher for M-RSF scaffolds as compared to other SF scaffolds and commercial ceramic scaffolds. In this work, we have evaluated the in vitro and in vivo biocompatibility of M-RSF scaffolds as per the ISO 10993 guidelines in a Good Laboratory Practice (GLP)-certified facility. The cytotoxicity, immunogenicity, genotoxicity, systemic toxicity, and implantation studies confirmed that the M-RSF scaffold is biocompatible. Further, the performance of the M-RSF scaffold to support bone formation was evaluated in in vivo bone implantation studies in a rabbit model. Calcium sulfate (CaSO4) scaffolds were chosen as reference material for this study as they are one of the preferred materials for bone-void-filling applications. M-RSF scaffold implantation sites showed a higher number of osteoblast and osteoclast cells as compared to CaSO4 implantation sites indicating active bone remodeling. The number density of osteocytes was double for M-RSF scaffold implantation sites, and these M-RSF scaffold implantation sites were characterized by enhanced collagen deposition, pointing toward a finer quality of the new bone formed. Moreover, the M-RSF scaffold implantation sites had a negligible incidence of secondary fractures as compared to the CaSO4 implantation sites (∼50% sites with secondary fracture), implying a reduction in postsurgical complications. Thus, the study demonstrates that the M-RSF scaffold is nontoxic for bone-void-filling applications and facilitates superior healing of fracture defects as compared to commercial calcium-based bone void fillers.

Silk fibroin and ceramic scaffolds: Comparative in vitro studies for bone regeneration.

Synthetic bone void fillers based on calcium ceramics are used to fill cavities in the bone and promote bone regeneration. More recently, silk fibroin (SF), a protein polymer obtained from Bombyx mori silkworm, has emerged as a promising material in bone void filling. In this work, we have compared the safety and efficacy of two types of silk fibroin-based bone void fillers with currently used and commercially available ceramic bone void fillers (based on calcium sulphate, beta tricalcium phosphate, and beta tricalcium phosphate with hydroxyapatite). Further, we have also evaluated these two types of SF scaffolds, which have strikingly different structural attributes. The biocompatibility of these scaffolds was comparable as assessed by cytotoxicity assay, cellular adhesion assay, and immunogenic assay. Ability of the scaffolds to support differentiation of human mesenchymal stem cells (hMSCs) into an osteoblastic lineage was also evaluated in an in vitro differentiation experiment using reverse transcriptase polymerase chain reaction analysis. These results revealed that cells cultured on SF scaffolds exhibit higher expression of early to late markers such as Runx2, BMPs, collagen, osterix, osteopontin, and osteocalcin as compared with ceramic-based scaffolds. This observation was further validated by studying the expression of alkaline phosphatase and calcium deposition. We also show that scaffolds made from same material of SF, but characterized by very different pore architectures, have diverse outcome in stem cell differentiation.

Dual-Band Metasurfaces Using Multiple Gap-Surface Plasmon Resonances.

Metasurfaces operating at multiple spectral ranges with integrated diversified functionalities while retaining the flexible design strategy are highly desired within the area of modern flat optics. Here, we propose and demonstrate the use of multiple gap-surface plasmon (GSP) resonances for the realization of dual-band multifunctional metasurfaces by designing GSP meta-atoms that would resonate at two different wavelengths. By tailoring nanobrick dimensions of a simple GSP meta-atom so as to enable both the first-order resonance at 1450 nm and the third-order one at 633 nm, we design phase-gradient GSP metasurfaces for polarization-independent beam steering and polarization-splitting, simultaneously, at telecom (1350-1550 nm) and visible (575-675 nm) wavelengths. The fabricated metasurfaces show good performance with >65% diffraction efficiency at the first-order resonant wavelength of 1450 nm and over 50% efficiency within the telecom range of 1350-1550 nm, while at the third-order resonant wavelength of 633 nm, the diffraction efficiency is 20 and >10% within the visible range of 575-675 nm. Our findings, therefore, demonstrate a flexible and robust approach for the realization of efficient dual-band GSP metasurfaces that can readily be combined with complex integrated designs to implement multiple functionalities highly sought after for diverse applications.

Metasurface-enabled broadband beam splitters integrated with quarter-wave plate functionality.

Conventional beam splitters and wave plates, while being essential components in diverse optical systems, require considerable space, especially when used in combination. Here, we designed and experimentally demonstrated metasurface-enabled efficient broadband beam splitters integrated with quarter-wave plate (QWP) functionality for simultaneous power splitting and circular-to-linear polarization conversion in the near-infrared range. By utilizing two different gap-plasmon meta-atoms, which function as QWPs performing efficient circular-to-linear polarization conversion and provide the phase difference of π between reflected linearly polarized beams, we designed a metasurface that completely suppress the specular reflection (zero-order diffraction) and second-order diffraction, while ensuring efficient and equal beam splitting of a circularly polarized wave into two reflected beams with predesigned directions and well-defined linear-polarization states in the wavelength range of 750-950 nm. The fabricated metasurface exhibits excellent performance of circular-to-linear conversion and power splitting, with efficient suppression of specular reflection (<1%) and splitting efficiencies above 50% for both right and left circularly polarized excitation at the design wavelength of λ = 850 nm. By enabling the combined functionalities of a conventional beam splitter and a QWP, our approach opens up new prospects for advanced research and applications targeting photonics integration and miniaturization.

Characterization of gap-plasmon based metasurfaces using scanning differential heterodyne microscopy.

Optical phase-gradient metasurfaces, whose unique capabilities are based on the possibility to arbitrarily control the phase of reflected/transmitted light at the subwavelength scale, are seldom characterized with direct measurements of phase gradients. Using numerical simulations and experimental measurements, we exploit the technique of scanning differential heterodyne microscopy (SDHM) for direct phase and amplitude characterization of gap-plasmon based optical metasurfaces. Two metasurface configurations utilizing the third-order gap surface plasmon (GSP) resonance, representing a binary grating and linear phase gradient, are experimentally characterized with the SDHM operating at the light wavelength of 633 nm. Comparing the experimental performances of these GSP metasurfaces with those expected from the phase and amplitude profiles reconstructed from the SDHM measurements, we verify the efficiency and accuracy of the developed SDHM characterization approach for direct inspection of GSP reflective metasurfaces.

Bifunctional gap-plasmon metasurfaces for visible light: polarization-controlled unidirectional surface plasmon excitation and beam steering at normal incidence.

Integration of multiple diversified functionalities into a single, planar and ultra-compact device has become an emerging research area with fascinating possibilities for realization of very dense integration and miniaturization in photonics that requires addressing formidable challenges, particularly for operation in the visible range. Here we design, fabricate and experimentally demonstrate bifunctional gap-plasmon metasurfaces for visible light, allowing for simultaneous polarization-controlled unidirectional surface plasmon polariton (SPP) excitation and beam steering at normal incidence. The designed bifunctional metasurfaces, consisting of anisotropic gap-plasmon resonator arrays, produce two different linear phase gradients along the same direction for respective linear polarizations of incident light, resulting in distinctly different functionalities realized by the same metasurface. The proof-of-concept fabricated metasurfaces exhibit efficient (>25% on average) unidirectional (extinction ratio >20 dB) SPP excitation within the wavelength range of 600-650 nm when illuminated with normally incident light polarized in the direction of the phase gradient. At the same time, broadband (580-700 nm) beam steering (30.6°-37.9°) is realized when normally incident light is polarized perpendicularly to the phase gradient direction. The bifunctional metasurfaces developed in this study can enable advanced research and applications related to other distinct functionalities for photonics integration.

Curcumin reverses diabetes-induced endothelial progenitor cell dysfunction by enhancing MnSOD expression and activity in vitro and in vivo.

Diabetes mellitus (DM) causes dysfunction of endothelial progenitor cells (EPCs), resulting in impaired wound healing. EPC therapy is a potential substitute to the current treatments of chronic wounds. Because EPCs isolated from diabetic patients are dysfunctional and therefore pose an obstacle in their efficacious employment in autologous cell therapy, a strategy to rescue them prior to transplantation would be expected to improve the efficacy of autologous cell therapy multifold. Compromised reactive oxygen species scavenging ability being the main cause of EPC dysfunction (EPCD), reactive oxygen species scavengers are likely to reverse or rescue EPCD. Therefore, in this study, we evaluated the potential of curcumin in reversing DM-induced EPCD. We found that in vitro treatment of bone marrow EPCs from diabetic mice (D-EPC) with curcumin restored their functionality, as judged by colony formation, tubule formation, and migration assays. Most importantly, autologous transplantation of curcumin-treated D-EPCs onto diabetic wounds also resulted in accelerated wound healing. Furthermore, curcumin-treated diabetic mice exhibited improved wound healing, as compared with their vehicle-treated diabetic counterparts, underscoring the efficacy of curcumin in vivo as well. The levels and activity of manganese superoxide dismutase (MnSOD) in D-EPCs treated in vitro with curcumin or those isolated from curcumin-treated diabetic mice were comparable with those in non-diabetic EPCs. Addition of methyl mercury chloride to inhibit MnSOD activity during curcumin treatment abolished the salutary effects of curcumin. Our data demonstrate that curcumin reverses DM-induced EPCD by boosting MnSOD expression and activity and emphasizes its potential for use in autologous cell therapy for diabetic wound management.

Matrix-entrapped cellular secretome rescues diabetes-induced EPC dysfunction and accelerates wound healing in diabetic mice.

Cellular secretory products have infinite potential, which is only recently explored for research and therapeutic applications. The present study elaborated on the formation of a unique matrix-entrapped cellular secretome (MCS), a hydrogel-like secretome produced by bone marrow-derived mononuclear cells when cultured on a three-dimensional electrospun nanofiber matrix under specific conditions. These culture conditions support the growth of a mixed population predominantly comprising of endothelial precursor cells (EPCs), along with mesenchymal stromal cells and pericytes. Interestingly, such secretome is not formed in a pure culture of EPCs on the similarly formulated matrix, suggesting that a heterotypic cell-cell interaction is essential for the formation of MCS. In addition, the specific composition of the matrix was found to be a critical necessity for the formation of MCS. Furthermore, the application of the MCS as a substrate promotes the growth of EPCs in culture. It also rescues the diabetes-induced EPC dysfunction as assessed based on the parameters, such as viability, proliferation, colony formation, cellular adhesion, chemotactic migration, and tubule formation. MCS augments the levels of eNOS-specific mRNA (Nos3) and also promotes the restoration of the SDF1/CXCR4 axis in diabetic EPCs. Notably, a topical application of MCS on diabetic wounds leads to an accelerated wound closure. Thus, the current data showed that MCS forms an excellent cell-free biomaterial in the treatment of diabetic wounds and non-healing ulcers.