Chromatic pupillometry isolation and evaluation of intrinsically photosensitive retinal ganglion cell-driven pupillary light response in patients with retinitis pigmentosa

PurposeThe pupil light response (PLR) is driven by rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs). We aimed to isolate ipRGC-driven pupil responses using chromatic pupillometry and to determine the effect of advanced retinitis pigmentosa (RP) on ipRGC function.MethodsA total of 100 eyes from 67 patients with advanced RP and 18 healthy controls (HCs) were included. Patients were divided into groups according to severity of visual impairment: no light perception (NLP, 9 eyes), light perception (LP, 19 eyes), faint form perception (FFP, 34 eyes), or form perception (FP, 38 eyes). Pupil responses to rod-weighted (487 nm, −1 log cd/m2, 1 s), cone-weighted (630 nm, 2 log cd/m2, 1 s), and ipRGC-weighted (487 nm, 2 log cd/m2, 1 s) stimuli were recorded. ipRGC function was evaluated by the postillumination pupil response (PIPR) and three metrics of pupil kinetics: maximal contraction velocity (MCV), contraction duration, and maximum dilation velocity (MDV).ResultsWe found a slow, sustained PLR response to the ipRGC-weighted stimulus in most patients with NLP (8/9), but these patients had no detectable rod- or cone-driven PLR. The ipRGC-driven PLR had an MCV of 0.269 ± 0.150%/s and contraction duration of 2.562 ± 0.902 s, both of which were significantly lower than those of the rod and cone responses. The PIPRs of the RP groups did not decrease compared with those of the HCs group and were even enhanced in the LP group. At advanced stages, ipRGC responses gradually became the main component of the PLR.ConclusionChromatic pupillometry successfully isolated an ipRGC-driven PLR in patients with advanced RP. This PLR remained stable and gradually became the main driver of pupil contraction in more advanced cases of RP. Here, we present baseline data on ipRGC function; we expect these findings to contribute to evaluating and screening candidates for novel therapies

Homeostatic Plasticity Mediated by Rod-Cone Gap Junction Coupling in Retinal Degenerative Dystrophic RCS Rats

Rod-cone gap junctions open at night to allow rod signals to pass to cones and activate the cone-bipolar pathway. This enhances the ability to detect large, dim objects at night. This electrical synaptic switch is governed by the circadian clock and represents a novel form of homeostatic plasticity that regulates retinal excitability according to network activity. We used tracer labeling and ERG recording in the retinae of control and retinal degenerative dystrophic RCS rats. We found that in the control animals, rod-cone gap junction coupling was regulated by the circadian clock via the modulation of the phosphorylation of the melatonin synthetic enzyme arylalkylamine N-acetyltransferase (AANAT). However, in dystrophic RCS rats, AANAT was constitutively phosphorylated, causing rod-cone gap junctions to remain open. A further b/a-wave ratio analysis revealed that dystrophic RCS rats had stronger synaptic strength between photoreceptors and bipolar cells, possibly because rod-cone gap junctions remained open. This was despite the fact that a decrease was observed in the amplitude of both a- and b-waves as a result of the progressive loss of rods during early degenerative stages. These results suggest that electric synaptic strength is increased during the day to allow cone signals to pass to the remaining rods and to be propagated to rod bipolar cells, thereby partially compensating for the weak visual input caused by the loss of rods

Intelligent deep reinforcement learning-based scheduling in relay-based HetNets

Abstract We consider a fundamental file dissemination problem in a two-hop relay-based heterogeneous network consisting of a macro base station, a half-duplex relay station, and multiple users. To minimize the dissemination delay, rateless code is employed at the base station. Our goal is to find an efficient channel-aware scheduling policy at the half-duplex relay station, i.e., either fetch a packet from the base station or broadcast a packet to the users at each time slot, such that the file dissemination delay is minimized. We formulate the scheduling problem as a Markov decision process and propose an intelligent deep reinforcement learning-based scheduling algorithm. We also extend the proposed algorithm to adapt to dynamic network conditions. Simulation results demonstrate that the proposed algorithm performs very close to a lower bound on the dissemination delay and significantly outperforms baseline schemes

Table_1_Chromatic pupillometry isolation and evaluation of intrinsically photosensitive retinal ganglion cell-driven pupillary light response in patients with retinitis pigmentosa.DOCX

PurposeThe pupil light response (PLR) is driven by rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs). We aimed to isolate ipRGC-driven pupil responses using chromatic pupillometry and to determine the effect of advanced retinitis pigmentosa (RP) on ipRGC function.MethodsA total of 100 eyes from 67 patients with advanced RP and 18 healthy controls (HCs) were included. Patients were divided into groups according to severity of visual impairment: no light perception (NLP, 9 eyes), light perception (LP, 19 eyes), faint form perception (FFP, 34 eyes), or form perception (FP, 38 eyes). Pupil responses to rod-weighted (487 nm, −1 log cd/m2, 1 s), cone-weighted (630 nm, 2 log cd/m2, 1 s), and ipRGC-weighted (487 nm, 2 log cd/m2, 1 s) stimuli were recorded. ipRGC function was evaluated by the postillumination pupil response (PIPR) and three metrics of pupil kinetics: maximal contraction velocity (MCV), contraction duration, and maximum dilation velocity (MDV).ResultsWe found a slow, sustained PLR response to the ipRGC-weighted stimulus in most patients with NLP (8/9), but these patients had no detectable rod- or cone-driven PLR. The ipRGC-driven PLR had an MCV of 0.269 ± 0.150%/s and contraction duration of 2.562 ± 0.902 s, both of which were significantly lower than those of the rod and cone responses. The PIPRs of the RP groups did not decrease compared with those of the HCs group and were even enhanced in the LP group. At advanced stages, ipRGC responses gradually became the main component of the PLR.ConclusionChromatic pupillometry successfully isolated an ipRGC-driven PLR in patients with advanced RP. This PLR remained stable and gradually became the main driver of pupil contraction in more advanced cases of RP. Here, we present baseline data on ipRGC function; we expect these findings to contribute to evaluating and screening candidates for novel therapies.</p

Comprehensive Evaluation of Appreciation of <i>Rhododendron</i> Based on Analytic Hierarchy Process

Qinting Lake Park has effectively imported Rhododendron varieties from Zhejiang Province. The analytic hierarchy process was employed to devise an evaluation framework to evaluate the ornamental and adaptive features of these species. Subsequently, we conducted a standardized evaluation of 24 species for their ornamental and adaptive traits under controlled cultivation conditions. The findings indicated that the percentage of ornamental flowers in the first-level index was significantly greater than the other two factors, indicating that the ornamental value of flowers was the most important in the evaluation of Rhododendron ornamental value. Among the secondary indicators, the proportion of flower color and flower weight was significantly higher than that of other factors, which had the greatest impact on the evaluation results. The 24 Rhododendron species were classified into two grades based on their ornamental value, as determined by index weights and scoring standards. Rhododendron ‘Xueqing’, Rhododendron ‘Big Qinglian’, and Rhododendron ‘Jinyang No. 9’ exhibited superior ornamental value and demonstrated more favorable suitability for garden applications

Towards H-SDN Traffic Analytic Through Visual Analytics and Machine Learning

With new networking paradigm emerged through Software-Defined Networking (SDN) offering various networking advantages over the traditional paradigm, organizations are attracted to migration their legacy networks to SDN networks. However, it is both challenging and impractical for organizations to migrate from traditional network architecture to full SDN architecture overnight. Therefore, the migration plan is performed in stages, resulting in a new type of network termed hybrid SDN (H-SDN). Effective migration and traffic scheduling in H-SDN environment are the two areas of challenges organizations face. Various solutions have been proposed in the literatures to address these two challenges. Differing from the approaches taken in the literatures, this work utilizes visual analytic and machine learning to address the two challenges. In both full SDN and H-SDN environment, literatures showed that data analytics applications have been successfully developed for various purposes as network security, traffic monitoring and traffic engineering. The success of data analytic applications is highly dependent on prior data analysis from both automated processing and human analysis. However, with the increasing volume of traffic data and the complex networking environment in both SDN and H-SDN networks, the need for both visual analytic and machine learning in inevitable for effective data analysis of network problems. Hence, the objectives of this article are three-folds: Firstly, to identify the limitations of the existing migration plan and traffic scheduling in H-SDN, followed by highlighting the challenges of the existing research works on SDN analytics in various network applications, and lastly, to propose the future research directions of SDN migration and H-SDN traffic scheduling through visual analytics and machine learning. Finally, this article presents the proposed framework termed VA-hSDN, a framework that utilizes visual analytics with machine learning to meet the challenges in SDN migration and traffic scheduling