BackgroundAutonomic neuropathy is a common and serious complication of diabetes. Early detection is essential to enable appropriate interventional therapy and management. Dynamic pupillometry has been proposed as a simpler and more sensitive tool to detect subclinical autonomic dysfunction. The aim of this study was to investigate pupil responsiveness in diabetic subjects with and without cardiovascular autonomic neuropathy (CAN) using dynamic pupillometry in two sets of experiments.MethodsDuring the first experiment, one flash was administered and the pupil response was recorded for 3 s. In the second experiment, 25 flashes at 1-s interval were administered and the pupil response was recorded for 30 s. Several time and pupil-iris radius-related parameters were computed from the acquired data. A total of 24 diabetic subjects (16 without and 8 with CAN) and 16 healthy volunteers took part in the study.ResultsOur results show that diabetic subjects with and without CAN have sympathetic and parasympathetic dysfunction, evidenced by diminished amplitude reflexes and significant smaller pupil radius. It suggests that pupillary autonomic dysfunction occurs before a more generalized involvement of the autonomic nervous system, and this could be used to detect early autonomic dysfunction.ConclusionsDynamic pupillometry provides a simple, inexpensive, and noninvasive tool to screen high-risk diabetic patients for diabetic autonomic neuropathy.
Blue organic light-emitting diodes require high triplet interlayer materials, which induce large energetic barriers at the interfaces resulting in high device voltages and reduced efficiencies. Here, we alleviate this issue by designing a low triplet energy hole transporting interlayer with high mobility, combined with an interface exciplex that confines excitons at the emissive layer/electron transporting material interface. As a result, blue thermally activated delay fluorescent organic light-emitting diodes with a below-bandgap turn-on voltage of 2.5 V and an external quantum efficiency (EQE) of 41.2% were successfully fabricated. These devices also showed suppressed efficiency roll-off maintaining an EQE of 34.8% at 1000 cd m−2. Our approach paves the way for further progress through exploring alternative device engineering approaches instead of only focusing on the demanding synthesis of organic compounds with complex structures.
Autonomic neuropathy (AN) is a common and serious complication of diabetes. Early detection is essential to enable appropriate interventional therapy. It has long been recognized that subjects with diabetic peripheral neuropathy (DPN) are at much greater risk of developing AN, but there is currently no simple screening tool to assess them. The aim of this study was to investigate pupil responsiveness in diabetic subjects with and without DPN using dynamic pupillometry. During the first test, one flash was administered and the pupil response recorded for 3 seconds. In the second test, twenty-five flashes at one-second intervals were administered and the pupil response recorded for 30 seconds. Several time related parameters were computed from the results. A total of 29 diabetic subjects (17 no DPN, 12 DPN) and 25 healthy volunteers took part in the study. In the first test, pupil-iris ratios in darkness, large deviation and plateau were significantly different between groups. Latency time from flash exposure to the start of constriction was significantly longer in diabetic subjects with DPN compared to healthy volunteers. There was no difference in latency times of largest deviation, plateau or duration of constriction between groups. In the second test, the pupil-iris ratios evaluated in the frame preceding the tenth and the twenty-fifth light flash were significantly greater in healthy volunteers than diabetic subjects with DPN. Latency time from the tenth and twenty-fifth flash exposure to the start of constriction was significantly shorter in healthy volunteers than in diabetic subjects with DPN.
Application-specific ICs have been traditionally used to support the high computational and data rate requirements in medical ultrasound systems, particularly in receive beamforming. Utilizing the previously developed efficient front-end algorithms, in this paper, we present a simple programmable computing architecture, consisting of a field-programmable gate array (FPGA) and a digital signal processor (DSP), to support core ultrasound signal processing. It was found that 97.3% and 51.8% of the FPGA and DSP resources are, respectively, needed to support all the front-end and back-end processing for B-mode imaging with 64 channels and 120 scanlines per frame at 30 frames/s. These results indicate that this programmable architecture can meet the requirements of low- and medium-level ultrasound machines while providing a flexible platform for supporting the development and deployment of new algorithms and emerging clinical applications.
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