Artificial intelligence approaches to enable early detection of CKD
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GluN2B-mediated regulation of silent synapses for receptor specification and addiction memory
Psychostimulants, including cocaine, elicit stereotyped, addictive behaviors. The reemergence of silent synapses containing only NMDA-type glutamate receptors is a critical mediator of addiction memory and seeking behaviors. Despite the predominant abundance of GluN2B-containing NMDA-type glutamate receptors in silent synapses, their operational mechanisms are not fully understood. Here, using conditional depletion/deletion of GluN2B in D1-expressing accumbal medium spiny neurons, we examined the synaptic and behavioral actions that silent synapses incur after repeated exposure to cocaine. GluN2B ablation reduces the proportion of silent synapses, but some of them can persist by substitution with GluN2C, which drives the aberrantly facilitated synaptic incorporation of calcium-impermeable AMPA-type glutamate receptors (AMPARs). The resulting precocious maturation of silent synapses impairs addiction memory but increases locomotor activity, both of which can be normalized by the blockade of calcium-impermeable AMPAR trafficking. Collectively, GluN2B supports the competence of cocaine-induced silent synapses to specify the subunit composition of AMPARs and thereby the expression of addiction memory and related behaviors.
Myosteatosis is associated with adiposity, metabolic derangements and mortality in patients with chronic kidney disease
Myosteatosis has been associated with sarcopenia, and increased mortality risk in patients on hemodialysis. We aimed to explore the associations between myosteatosis, as assessed by computed tomography (CT), with demographic parameters, body composition metrics, muscle strength, metabolic parameters and mortality in patients with chronic kidney disease (CKD).
An artificial market model for the forex market
As financial markets have transitioned toward electronic trading, there has been a corresponding increase in the number of algorithmic strategies and degree of transaction frequency. This move to high-frequency trading at the millisecond level, propelled by algorithmic strategies, has brought to the forefront short-term market reactions, like market impact, which were previously negligible in low-frequency trading scenarios. Such evolution necessitates a new framework for analyzing and developing algorithmic strategies in these rapidly evolving markets. Employing artificial markets stands out as a solution to this problem. This study aims to construct an artificial foreign exchange market referencing market microstructure theory, without relying on the assumption of information or technical traders. Furthermore, it endeavors to validate the model by replicating stylized facts, such as fat tails, which exhibit a higher degree of kurtosis in the return distribution than that predicted by normal distribution models. The validated artificial market model will be used to simulate market dynamics and algorithm strategies; its generated rates could also be applied to pricing and risk management for currency options and other foreign exchange derivatives. Moreover, this work explores the importance of order flow and the underlying factors of stylized facts within the artificial market model.
Thermoregulatory integration in hand prostheses and humanoid robots through blood vessel simulation
In this paper, we introduce an innovative approach for generating robotic faces with a thermal signature similar to that of humans and equipping prosthetic or robotic hands with a lifelike temperature distribution. This approach enhances their detection via infrared cameras and promotes more natural interactions between humans and robots. This method integrates a temperature regulation system into artificial skin, drawing inspiration from the human body’s natural temperature control via blood flow. Central to this technique is a fiber network simulating blood vessels within the artificial skin. Water flows through these fibers under specific temperature and flow conditions, forming a controlled heat release system. The heat emission can be adjusted by changing the dilation of these fibers, primarily by modulating the frequency of circulation. Our findings indicate that this approach can replicate the varied thermal characteristics of different human faces and hand areas. Consequently, the robotic faces appear more human-like in infrared images, aiding their identification by infrared cameras. At the same time, the prosthetic hands achieve a more natural temperature, reducing the discomfort typically felt in direct contact with synthetic limbs. The aim of this study was to address the challenges faced by the users of prosthetic hands. The results from this study show a promising direction in humanoid robotics, fostering improved tactile interactions and redefining human–robot relationships. This innovative technique facilitates further advancements, blurring the lines between artificial aids and natural biological systems.
Responsive DNA artificial cells for contact and behavior regulation of mammalian cells
Artificial cells have emerged as synthetic entities designed to mimic the functionalities of natural cells, but their interactive ability with mammalian cells remains challenging. Herein, we develop a generalizable and modular strategy to engineer DNA-empowered stimulable artificial cells designated to regulate mammalian cells (STARM) via synthetic contact-dependent communication. Constructed through temperature-controlled DNA self-assembly involving liquid-liquid phase separation (LLPS), STARMs feature organized all-DNA cytoplasm-mimic and membrane-mimic compartments. These compartments can integrate functional nucleic acid (FNA) modules and light-responsive gold nanorods (AuNRs) to establish a programmable sense-and-respond mechanism to specific stimuli, such as light or ions, orchestrating diverse biological functions, including tissue formation and cellular signaling. By combining two designer STARMs into a dual-channel system, we achieve orthogonally regulated cellular signaling in multicellular communities. Ultimately, the in vivo therapeutic efficacy of STARM in light-guided muscle regeneration in living animals demonstrates the promising potential of smart artificial cells in regenerative medicine.
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