Structural insights into TRPV2 modulation by probenecid
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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.
The role of inhibitory and excitatory neurometabolites in age-related differences in action selection
Aging is accompanied by changes in the level of neurometabolites. However, their role in vital behavioral functions is still unclear. We aimed to explore the impact of aging on the neurochemical mechanisms underlying action selection. Young (YA) (n = 25) and older adults (OA) (n = 26) performed a simple (SRT) and a choice (CRT) reaction time tasks. Magnetic resonance spectroscopy was utilized to track task-induced modulations in GABA and glutamate in the sensorimotor cortex (SM1) and dorsolateral prefrontal cortex (dlPFC). Results showed that (i) SM1 Glx levels were higher during the SRT in the full sample, (ii) Glx modulation in the dlPFC predicted better behavioral performance in the SRT only in YA, and iii) a task-induced increase in GABA and Glx in the dlPFC was related to action selection learning in the full sample. Our findings highlight an important role of neurometabolic modulation during action selection and learning.
Incommensurable matter-wave jets in quasi-1D geometry
Bose-Einstein condensates subjected to modulation of the interaction between atoms exhibit the emergence of density waves and matter-wave jets with a velocity proportional to the square root of the modulation frequency. Matter-wave jets have been studied in two- and one-dimensional systems showing that for sufficiently strong modulation additional higher harmonic matter-wave jets emerge. Here we report the experimental observation of incommensurable “golden” (frac{1+sqrt{5}}{2}) matter-wave jets in a Bose-Einstein condensate exposed to a single frequency interaction modulation. We study the formation of higher-order jets in quasi-one-dimensional geometry with numerical one dimensional (1D) Gross-Pitaevskii equation simulation. We explore the process of jet formation experimentally and theoretically for a wide range of modulation amplitudes and frequencies and establish a phase diagram delineating different regimes of jet formation. The observation of incommensurate jets provides a new route to an aperiodic density modulation of the condensate without employing an external potential.
Modulating neuroplasticity for chronic pain relief: noninvasive neuromodulation as a promising approach
Chronic neuropathic pain is a debilitating neuroplastic disorder that notably impacts the quality of life of millions of people worldwide. This complex condition, encompassing various manifestations, such as sciatica, diabetic neuropathy and postherpetic neuralgia, arises from nerve damage or malfunctions in pain processing pathways and involves various biological, physiological and psychological processes. Maladaptive neuroplasticity, known as central sensitization, plays a critical role in the persistence of chronic neuropathic pain. Current treatments for neuropathic pain include pharmacological interventions (for example, antidepressants and anticonvulsants), invasive procedures (for example, deep brain stimulation) and physical therapies. However, these approaches often have limitations and potential side effects. In light of these challenges, interest in noninvasive neuromodulation techniques as alternatives or complementary treatments for neuropathic pain is increasing. These methods aim to induce analgesia while reversing maladaptive plastic changes, offering potential advantages over conventional pharmacological practices and invasive methods. Recent technological advancements have spurred the exploration of noninvasive neuromodulation therapies, such as repetitive transcranial magnetic stimulation, transcranial direct current stimulation and transcranial ultrasound stimulation, as well as innovative transformations of invasive techniques into noninvasive methods at both the preclinical and clinical levels. Here this review aims to critically examine the mechanisms of maladaptive neuroplasticity in chronic neuropathic pain and evaluate the efficacy of noninvasive neuromodulation techniques in pain relief. By focusing on optimizing these techniques, we can better assess their short-term and long-term effects, refine treatment variables and ultimately improve the quality of neuropathic pain management.
T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity
T-cell receptor (TCR) structures are currently under-utilised in early-stage drug discovery and repertoire-scale informatics. Here, we leverage a large dataset of solved TCR structures from Immunocore to evaluate the current state-of-the-art for TCR structure prediction, and identify which regions of the TCR remain challenging to model. Through clustering analyses and the training of a TCR-specific model capable of large-scale structure prediction, we find that the alpha chain VJ-recombined loop (CDR3α) is as structurally diverse and correspondingly difficult to predict as the beta chain VDJ-recombined loop (CDR3β). This differentiates TCR variable domain loops from the genetically analogous antibody loops and supports the conjecture that both TCR alpha and beta chains are deterministic of antigen specificity. We hypothesise that the larger number of alpha chain joining genes compared to beta chain joining genes compensates for the lack of a diversity gene segment. We also provide over 1.5M predicted TCR structures to enable repertoire structural analysis and elucidate strategies towards improving the accuracy of future TCR structure predictors. Our observations reinforce the importance of paired TCR sequence information and capture the current state-of-the-art for TCR structure prediction, while our model and 1.5M structure predictions enable the use of structural TCR information at an unprecedented scale.
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