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Background Alzheimer’s Disease (AD) is a progressive, age-related neurodegenerative disorder, with visual deficit and retinal abnormality in the early stage. Extracts of wolfberry protected retinal neuronal degenerations in both acute and chronic animal models. Aim To explore whether extract of wolfberry (lycium barbarum extract, LBE) may protect retinal function in a mouse model of AD. Methods 5xFAD mouse model of AD was orally fed with LBE (20 g/kg body weight) or vehicle control for 1 month from 3-month-old till 4-month-old every day. Then electroretinogram recording was performed under dark and light adaptation, then the amplitudes of a-wave, b-wave and photopic negative response were measured to check the retinal light responses of 5xFAD mice. Results LBE enhanced the a- and b-wave amplitudes under dark adaptation, but hardly affect the ERG responses under light adaptation. Conclusion Extract of wolfberry enhances rod-driven retinal light responses in 5xFAD mouse model of AD.

VoIP-based emergency communication is a promising approach to improving the safety of citizens worldwide. The transition required in this scope includes substituting the legacy PSTN/SS7 based emergency call system by Next Generation IP based components for call establishment and control. Thereby, SIP is used as a session control protocol and RTP as the means to transfer emergency data between the caller and the corresponding Public Safety Access Point (PSAP). The emergency data is not only restricted to voice communication but can cover a rich variety of data, which can be acquired by different means (including the end-user devices) and transmitted over IP. This includes video, geo-positioning data, voice, Real-Time Text, and sensor data in line with emerging IoT architectures and approaches. A vital aspect in this scope is given by the performance of the underlying network, including its capability to establish calls in emergencies and to transfer the data required for serving the situation. Therefore, in this paper, we evaluate the computational performance of the most recent VoIP emergency system implementation, which was developed by the H2020-EMYNOS project as a realisation of the EENA NG112 Long Term Definition (LTD) vision. We perform a series of trials and evaluate the performance of the EMYNOS system in a multi-party lab environment established during the project. We evaluate the time needed to perform basic emergency call operations over IP, whilst in parallel generating Internet type of background traffic. Correspondingly, we worked out a methodology and implemented it in our testbed, both of which are presented in the current paper. The obtained numerical results lea to the conclusion that SIP-based emergency services stand a good chance to replace legacy systems when it comes to their performance. Additionally, we also provide a perspective on how the blockchain technology could potentially be put to use to enhance the quality of the next-generation emergency services. We propose the utilisation of blockchain technology for tracking emergency calls and enabling efficient recognition of fraud calls, which is a critical aspect for PSAP providers concerning the potential denial of service attacks. In this context, we provide evaluations and numerical results based on a private Ethereum based blockchain playground running at the premises of Fraunhofer FOKUS.

VoIP emergency communications is a promising approach to improving the safety of citizens worldwide. The transition required in this scope includes substituting the legacy PSTN/SS7 based emergency call system by Next Generation IP based components for call establishment and control. Thereby, SIP is used as a session control protocol and RTP as the means to transfer emergency data between the caller and the corresponding Public Safety Access Point (PSAP). The emergency data is not only restricted to voice communication but can cover a rich variety of data, which can be acquired by different means (including the end user devices) and transmitted over IP. This includes video, geo-positioning data, voice, Real Time Text, and sensor data in line with emerging IoT architectures and approaches. A vital aspect in this scope is given by the performance of the underlying network, including its capability to establish calls in emergency situations and to transfer the data required for serving the situation. Therefore, in this paper we evaluate the computational performance of the most recent VoIP emergency system implementation, which was developed by the H2020-EMYNOS project as a realization of the EENA NG112 Long Term Definition (LTD) vision. We perform a series of trials and evaluate the performance of the EMYNOS system in a multi-party lab environment established during the project. We evaluate the time needed to perform basic emergency call operations over IP, whilst in parallel generating Internet type of background traffic. Correspondingly, we worked out a methodology and implemented it in our testbed, which are both presented in the current paper. The obtained numerical results lead to the conclusion that SIP based emergency services stand a good chance to replace legacy systems when it comes to their performance.