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A MEMS grating modulator with a tunable sinusoidal grating for large-scale extendable apertures
Microelectromechanical system (MEMS) grating modulators enable versatile beam steering functions through the electrostatic actuation of movable ribbons. These modulators operate at ultrahigh frequencies in the hundred kHz range, and their micromirror-free configuration simplifies the fabrication process and reduces costs compared to micromirror-based modulators. However, these modulators are limited in their optical efficiency and aperture. Here, we present a MEMS grating modulator with a notably extendable aperture and a high optical efficiency that benefits from the adoption of a tunable sinusoidal grating. Instead of end-constrained movable ribbons, we constrain the MEMS grating modulator through broadside-constrained continuous ribbons. The end-free grating enables improved scalability along the ribbons, and the continuous sinusoidal surface of the grating allows an increased fill factor. As an example, we experimentally demonstrate a MEMS grating modulator with a large-scale aperture of 30 × 30 mm and an optical efficiency of up to 90%. The modulation depth enables intensity modulation across a broad wavelength range from 635 to 1700 nm. The experimental results demonstrate that the reported modulator has a mechanical settling time of 1.1 μs and an extinction ratio of over 20 dB. Furthermore, it offers a dynamic modulation contrast of over 95% within a 250 kHz operating frequency and achieves full modulation within a field of view (FOV) of ±30°. The reported MEMS grating modulator holds promise for application in high-speed light attenuation and modulating retroreflector free-space optical (MRR-FSO) communication systems. Our device also paves new ways for future high-speed, energy-efficient, and cost-effective communication networks.
Smartwatch- and smartphone-based remote assessment of brain health and detection of mild cognitive impairment
Consumer-grade mobile devices are used by billions worldwide. Their ubiquity provides opportunities to robustly capture everyday cognition. ‘Intuition’ was a remote observational study that enrolled 23,004 US adults, collecting 24 months of longitudinal multimodal data via their iPhones and Apple Watches using a custom research application that captured routine device use, self-reported health information and cognitive assessments. The study objectives were to classify mild cognitive impairment (MCI), characterize cognitive trajectories and develop tools to detect and track cognitive health at scale. The study addresses sources of bias in current cognitive health research, including limited representativeness (for example, racial/ethnic, geographic) and accuracy of cognitive measurement tools. We describe study design and provide baseline cohort characteristics. Next, we present foundational proof-of-concept MCI classification modeling results using interactive cognitive assessment data. Initial findings support the reliability and validity of remote MCI detection and the usefulness of such data in describing at-risk cognitive health trajectories in demographically diverse aging populations. ClinicalTrials.gov identifier: NCT05058950.
Boredom signals deviation from a cognitive homeostatic set point
Boredom is the feeling of wanting but failing to engage the mind and can be conceived as one among many signals of suboptimal utilization of cognitive and neural resources. Using homeostasis as an analogy, this perspective argues that boredom represents a signal indicating deviation from optimal engagement—that is, deviation from a cognitive homeostatic set point. Within this model, allostasis accounts for chronic boredom (i.e., trait boredom proneness), according to which faulty internal models are responsible for why the highly boredom prone may set unrealistic expectations for engagement. In other words, the model characterizes boredom as a dynamic response to both internal and external exigencies, leading to testable hypotheses for both the nature of the state and the trait disposition. Furthermore, this perspective presents the broader notion that humans strive to optimally engage with their environs to maintain a kind of cognitive homeostatic set-point.
A tumor-secreted protein utilizes glucagon release to cause host wasting
Tumor‒host interaction plays a critical role in malignant tumor-induced organ wasting across multiple species. Despite known regulation of regional wasting of individual peripheral organs by tumors, whether and how tumors utilize critical host catabolic hormone(s) to simultaneously induce systemic host wasting, is largely unknown. Using the conserved yki3SA-tumor model in Drosophila, we discovered that tumors increase the production of adipokinetic hormone (Akh), a glucagon-like catabolic hormone, to cause systemic host wasting, including muscle dysfunction, lipid loss, hyperglycemia, and ovary atrophy. We next integrated RNAi screening and Gal4-LexA dual expression system to show that yki3SA-gut tumors secrete Pvf1 to remotely activate its receptor Pvr in Akh-producing cells (APCs), ultimately promoting Akh production. The underlying molecular mechanisms involved the Pvf1-Pvr axis that triggers Mmp2-dependent ECM remodeling of APCs and enhances innervation from the excitatory cholinergic neurons. Interestingly, we also confirmed the similar mechanisms governing tumor-induced glucagon release and organ wasting in mammals. Blockade of either glucagon or PDGFR (homolog of Pvr) action efficiently ameliorated organ wasting in the presence of malignant tumors. Therefore, our results demonstrate that tumors remotely promote neural-associated Akh/glucagon production via Pvf1-Pvr axis to cause systemic host wasting.
Cognitive reserve is associated with education, social determinants, and cognitive outcomes among older American Indians in the Strong Heart Study
Cognitive reserve, a component of resilience, may be conceptualized as the ability to overcome accumulating neuropathology and maintain healthy aging and function. However, research measuring and evaluating it in American Indians is needed. We recruited American Indians from 3 regional centers for longitudinal examinations (2010-13, n = 818; 2017-19, n = 403) including MRI, cognitive, clinical, and questionnaire data. We defined cognitive reserve by measuring the residual from individual regressions of cognitive tests over imaged brain volumes, adjusted for age and sex. Analyses examined three different metrics of cognitive reserve against sociodemographic, clinical, and longitudinal cognitive data in causal mediation models. Better cognitive reserve was significantly associated with more education, higher income, lower prevalence of depression, lower prevalence of diabetes, and lower prevalence of kidney disease, but we found no statistically significant evidence for an association with plasma biomarkers for Alzheimer’s disease and related dementias, APOE e4 carrier status, alcohol use, body mass, or hypertension. Better cognitive reserve was associated with better cognitive function over mean 6.7 years follow-up (range 4-9 years); and the association for education with cognition over time was mediated in part (15-24%) by cognitive reserve. Cognitive reserve, although challenging to measure, appears important for understanding the range of cognitive aging in American Indians.
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