Imbalance of APOB Lipoproteins and Large HDL in Type 1 Diabetes Drives Atherosclerosis.

BACKGROUND: Individuals with type 1 diabetes (T1D) generally have normal or even higher HDL (high-density lipoprotein)-cholesterol levels than people without diabetes yet are at increased risk for atherosclerotic cardiovascular disease (CVD). Human HDL is a complex mixture of particles that can vary in cholesterol content by >2-fold. To investigate if specific HDL subspecies contribute to the increased atherosclerosis associated with T1D, we created mouse models of T1D that exhibit human-like HDL subspecies. We also measured HDL subspecies and their association with incident CVD in a cohort of people with T1D. METHODS: We generated LDL receptor-deficient (Ldlr-/-) mouse models of T1D expressing human APOA1 (apolipoprotein A1). Ldlr-/-APOA1Tg mice exhibited the main human HDL subspecies. We also generated Ldlr-/-APOA1Tg T1D mice expressing CETP (cholesteryl ester transfer protein), which had lower concentrations of large HDL subspecies versus mice not expressing CETP. HDL particle concentrations and sizes and proteins involved in lipoprotein metabolism were measured by calibrated differential ion mobility analysis and targeted mass spectrometry in the mouse models of T1D and in a cohort of individuals with T1D. Endothelial transcytosis was analyzed by total internal reflection fluorescence microscopy. RESULTS: Diabetic Ldlr-/-APOA1Tg mice were severely hyperglycemic and hyperlipidemic and had markedly elevated plasma APOB levels versus nondiabetic littermates but were protected from the proatherogenic effects of diabetes. Diabetic Ldlr-/-APOA1Tg mice expressing CETP lost the atheroprotective effect and had increased lesion necrotic core areas and APOB accumulation, despite having lower plasma APOB levels. The detrimental effects of low concentrations of larger HDL particles in diabetic mice expressing CETP were not explained by reduced cholesterol efflux. Instead, large HDL was more effective than small HDL in preventing endothelial transcytosis of LDL mediated by scavenger receptor class B type 1. Finally, in humans with T1D, increased concentrations of larger HDLs relative to APOB100 negatively predicted incident CVD independently of HDL-cholesterol levels. CONCLUSIONS: Our results suggest that the balance between APOB lipoproteins and the larger HDL subspecies contributes to atherosclerosis progression and incident CVD in the setting of T1D and that larger HDLs exert atheroprotective effects on endothelial cells rather than by promoting macrophage cholesterol efflux.

How Do People with Limited Movement Personalize Upper-Body Gestures? Considerations for the Design of Personalized and Accessible Gesture Interfaces.

Always-on, upper-body input from sensors like accelerometers, infrared cameras, and electromyography hold promise to enable accessible gesture input for people with upper-body motor impairments. When these sensors are distributed across the person's body, they can enable the use of varied body parts and gestures for device interaction. Personalized upper-body gestures that enable input from diverse body parts including the head, neck, shoulders, arms, hands and fingers and match the abilities of each user, could be useful for ensuring that gesture systems are accessible. In this work, we characterize the personalized gesture sets designed by 25 participants with upper-body motor impairments and develop design recommendations for upper-body personalized gesture interfaces. We found that the personalized gesture sets that participants designed were highly ability-specific. Even within a specific type of disability, there were significant differences in what muscles participants used to perform upper-body gestures, with some pre-dominantly using shoulder and upper-arm muscles, and others solely using their finger muscles. Eight percent of gestures that participants designed were with their head, neck, and shoulders, rather than their hands and fingers, demonstrating the importance of tracking the whole upper-body. To combat fatigue, participants performed 51% of gestures with their hands resting on or barely coming off of their armrest, highlighting the importance of using sensing mechanisms that are agnostic to the location and orientation of the body. Lastly, participants activated their muscles but did not visibly move during 10% of the gestures, demonstrating the need for using sensors that can sense muscle activations without movement. Both inertial measurement unit (IMU) and electromyography (EMG) wearable sensors proved to be promising sensors to differentiate between personalized gestures. Personalized upper-body gesture interfaces that take advantage of each person's abilities are critical for enabling accessible upper-body gestures for people with upper-body motor impairments.

Enabling devices, empowering people: the design and evaluation of Trackball EdgeWrite.

PURPOSE: To describe the research and development that led to Trackball EdgeWrite, a gestural text entry method that improves desktop input for some people with motor impairments. To compare the character-level version of this technique with a new word-level version. Further, to compare the technique with competitor techniques that use on-screen keyboards. METHOD: A rapid and iterative design-and-test approach was used to generate working prototypes and elicit quantitative and qualitative feedback from a veteran trackball user. In addition, theoretical modelling based on the Steering law was used to compare competing designs. RESULTS: One result is a refined software artifact, Trackball EdgeWrite, which represents the outcome of this investigation. A theoretical result shows the speed benefit of word-level stroking compared to character-level stroking, which resulted in a 45.0% improvement. Empirical results of a trackball user with a spinal cord injury indicate a peak performance of 8.25 wpm with the character-level version of Trackball EdgeWrite and 12.09 wpm with the word-level version, a 46.5% improvement. Log file analysis of extended real-world text entry shows stroke savings of 43.9% with the word-level version. Both versions of Trackball EdgeWrite were better than on-screen keyboards, particularly regarding user preferences. Follow-up correspondence shows that the veteran trackball user with a spinal cord injury still uses Trackball EdgeWrite on a daily basis 2 years after his initial exposure to the software. CONCLUSIONS: Trackball EdgeWrite is a successful new method for desktop text entry and may have further implications for able-bodied users of mobile technologies. Theoretical modelling is useful in combination with empirical testing to explore design alternatives. Single-user lab and field studies can be useful for driving a rapid iterative cycle of innovation and development.