In service economy, scholars and practitioners focus on the development and the appliance of innovative services. The importance of service innovation is rising in many sectors and among different organizations. Several disciplines (e.g. marketing, management, operations research, etc.) focus on this innovation, a concept widely used, but with different definitions. In this paper, service innovation has been analyzed according to SD Logic and a service ecosystem perspective. Literature still call for a deeper understanding of how new or renewed resources’ combination affect the shaping of service ecosystems. To contribute to fill this gap, the study explores the practices that different actors, internal and external to a healthcare service ecosystem, enact to co-create value in novel ways that is service innovation. The paper is structured as follows. In the next section, the main academic contributions on service research have been reviewed, focusing on healthcare service innovation. Follows, the research method and the discussion of research findings. Finally, theoretical and managerial implications have been detailed and an agenda for future research suggested. The paper offers interesting insights to develop new or renewed practices that foster the reshaping and maintaining of a healthcare service ecosystem. Some recommendations are included to support managers in the development of service innovation strategies.

ABC-OCT, Affordable B-scan Camera-based Optical Coherence Tomography, implements Fourier-Domain Optical Coherence Tomography with real-time display using cross-platform C++ and the OpenCV framework. The software can be compiled using current versions of GCC for *nix/Mac and Microsoft^® Visual Studio for Windows. Full functionality of ABC-OCT needs the camera SDK from QHYCCD and a QHYCCD camera to be connected; but the code can be easily modified to support other camera drivers, as is shown by an included demo version which can use any installed webcam. The code is made available under the MIT license. The software is available from GitHub (https://github.com/hn-88/FDOCT).

Gas electron multipliers (GEMs) with wire (WGEMs) or metal electrodes (MGEMs), which don’t use any plastic insulators between electrodes are created. The chambers containing MGEMs (WGEMs) with pin-anodes are proposed as detectors for searching of spin-dependent interactions between Dark Matter (DM) particles and gases with nonzero-spin nuclei (H2, D2, 3He, 21Ne, CF4, CH4, etc.). In this paper, we present a review of such chambers. For investigation of the gas mixtures Ne+10%H2, H2 (D2) +3ppmTMAE, the chamber containing WGEM with pin-anode detection system was constructed. In this paper we present the results of an experimental study of these gaseous mixtures exited by an α - source. Mixture of Ar + 40 ppm C2H4 and mixture 50% Xe + 50%CF4 have been investigated. The spatial distributions of photoelectron clouds produced by primary scintillations on α- and β-particle tracks, as well as the distributions of photoelectron clouds due to photons from avalanches at the pin-anode, have been measured for the first time. In our experiments as another filling of the chambers for search of low-mas WIMP (<10 GeV/c2), solar neutrino and solar axions with spin-dependent interaction we propose to use the mixtures: D2 + 3ppmTMAE, 3He + 3%CH4, 21Ne + 10%H2, at pressure 10-17 bar. And in our experiment with liquid gases is used the mixtures with 19F (LAr + CF4, LXe + CF4) and mixture LCH4 + 40ppm TMAE. The time projection chamber (TPC) with the mixture D2 + 3ppmTMAE filling allow to search of spin-dependent interactions of solar axions and deuterium. As well as we present the detecting systems for search of narrow pp-resonances (quarks) in accelerators experiments.

We studied short- and long-term effects of intravitreal injection of N-methyl-D-aspartate (NMDA) on melanopsin-containing (m⁺) and non-melanopsin-containing (Brn3a⁺) retinal ganglion cells (RGCs). In adult SD-rats, the left eye received a single intravitreal injection of 5µL of 100nM NMDA. At 3 and 15 months, retinal thickness was measured in vivo using SD-OCT. Ex vivo analyses were done at 3, 7, 14 days or 15 months after damage. Whole-mounted retinas were immunolabelled for Brn3a and melanopsin, the total number of Brn3a⁺RGCs and m⁺RGCs were quantified and their topography represented. In control retinas, the mean total numbers of Brn3a⁺RGCs and m⁺RGCs were 78,903±3,572 and 2,358±144 (mean ± SD; n=10), respectively. In the NMDA injected retinas, Brn3a⁺RGCs numbers diminished to 50% and 25%, at 3 and 14 days, respectively, but there was no further loss up to 15 months. The number of immunoidentified m⁺RGCs decreased significantly at 3 days, recovered between 3-7 days and was back to normal thereafter. OCT measurements revealed a significant thinning of the left retinas at 3 and 15 months. Intravitreal injections of NMDA induce a rapid loss of 75% of Brn3a⁺RGCs, a transient downregulation of melanopsin expression but not m⁺RGC death, and a thinning of the inner retinal layers.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

To evaluate whether autologous mesenchymal cells, adipose derived stem cells and platelet-rich plasma, grafted into the supracoroideal space by surgical treatment according to Limoli retinal restoration technique (LRRT), can produce growth factors in order to exert a beneficial effect in retinitis pigmentosa (RP) patients. Twenty-one eyes underwent surgery and divided based on retinal foveal thickness ≤ 190 or >190 µm into group A and group B, respectively. The specific LRRT triad was grafted in a deep scleral pocket above the choroid of each eye. At 6-month follow-up, group B showed an improvement in residual close-up visus and sensitivity at microperimetry compared to group A. After an in-depth review of molecular biology studies concerning degenerative phenomena underlying the etiopathogenesis of RP, it can be confirmed that further research is needed on tapeto-retinal degenerations both from a clinical and molecular point of view to obtain better functional results. In particular, it is necessary to increase the number of patients, extend observation times, and treat subjects in the presence of still trophic retinal tissue to allow adequate biochemical and functional catering.