PTENα is responsible for protection of brain against oxidative stress during aging.

Neural cells are continuously subjected to oxidative stress arising from electrochemical activity, and cellular protection systems can turn on the oxidative stress response to detect and alleviate adverse conditions. However, the function and mechanism of the protective systems are complicated and remain largely elusive. We report that PTENα, an isoform of the PTEN family, mediates defense signaling in response to oxidative stress during brain aging. We show that genetic ablation of Ptenα in mice increases oxidative stress and results in neuronal cell death, culminating in accelerated decline of cognition and motor coordination as age increases. PTENα maintains COX activity and promotes energy metabolism through abrogating NEDD4L-mediated degradation of COX4 in response to oxidative stress. In the presence of Parkinson's disease-associated mutation, PTENα loses the capability to protect COX4 and ameliorate defects caused by Ptenα deletion. Our study reveals an important role of PTENα in response to oxidative stress. We propose that dysregulation of PTENα signaling may accelerate the rate of brain aging and promote the development of neurodegenerative disorders.

PPP2R1B is modulated by ubiquitination and is essential for spermatogenesis.

The serine-threonine protein phosphatase 2A (PP2A) is a heterotrimeric enzyme complex that regulates many fundamental cellular processes. PP2A is involved in tumorigenesis because mutations in the scaffold subunit, PPP2R1B, were found in several types of cancers. However, the biological function of PPP2R1B remains largely unknown. We report here that homozygous deletion of Ppp2r1b in Mus musculus impairs meiotic recombination and causes meiotic arrest in spermatocytes. Consistently, male mice lacking Ppp2r1b are characterized with infertility. Furthermore, heterozygous missense mutations in the Homo sapiens PPP2R1B gene, which encodes PPP2R1B, are identified in azoospermia patients with meiotic arrest. We found that PPP2R1B mutants are susceptible to degradation by an E3 ligase CRL4ADCAF6 , and resistant to de-polyubiquitylation by ubiquitin-specific protease 5 (USP5). In addition, heterozygous mutations in PPP2R1B reduce stability of the wild-type PPP2R1B. Our results demonstrate an essential role of PPP2R1B in spermatogenesis and identify upstream regulators of PPP2R1B.

PTENα promotes neutrophil chemotaxis through regulation of cell deformability.

Neutrophils are a major component of immune defense and are recruited through neutrophil chemotaxis in response to invading pathogens. However, the molecular mechanism that controls neutrophil chemotaxis remains unclear. Here, we report that PTENα, the first isoform identified in the PTEN family, regulates neutrophil deformability and promotes chemotaxis of neutrophils. A high level of PTENα is detected in neutrophils and lymphoreticular tissues. Homozygous deletion of PTENα impairs chemoattractant-induced migration of neutrophils. We show that PTENα physically interacts with cell membrane cross-linker moesin through its FERM domain and dephosphorylates moesin at Thr558, which disrupts the association of filamentous actin with the plasma membrane and subsequently induces morphologic changes in neutrophil pseudopodia. These results demonstrate that PTENα acts as a phosphatase of moesin and modulates neutrophil-mediated host immune defense. We propose that PTENα signaling is a potential target for the treatment of infections and immune diseases.

Intelligent Cubic-Designed Piezoelectric Node (iCUPE) with Simultaneous Sensing and Energy Harvesting Ability toward Self-Sustained Artificial Intelligence of Things (AIoT).

The evolution of artificial intelligence of things (AIoT) drastically facilitates the development of a smart city via comprehensive perception and seamless communication. As a foundation, various AIoT nodes are experiencing low integration and poor sustainability issues. Herein, a cubic-designed intelligent piezoelectric AIoT node iCUPE is presented, which integrates a high-performance energy harvesting and self-powered sensing module via a micromachined lead zirconate titanate (PZT) thick-film-based high-frequency (HF)-piezoelectric generator (PEG) and poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) nanofiber thin-film-based low-frequency (LF)-PEGs, respectively. The LF-PEG and HF-PEG with specific frequency up-conversion (FUC) mechanism ensures continuous power supply over a wide range of 10-46 Hz, with a record high power density of 17 mW/cm3 at 1 g acceleration. The cubic design allows for orthogonal placement of the three FUC-PEGs to ensure a wide range of response to vibrational energy sources from different directions. The self-powered triaxial piezoelectric sensor (TPS) combined with machine learning (ML) assisted three orthogonal piezoelectric sensing units by using three LF-PEGs to achieve high-precision multifunctional vibration recognition with resolutions of 0.01 g, 0.01 Hz, and 2° for acceleration, frequency, and tilting angle, respectively, providing a high recognition accuracy of 98%-100%. This work proves the feasibility of developing a ML-based intelligent sensor for accelerometer and gyroscope functions at resonant frequencies. The proposed sustainable iCUPE is highly scalable to explore multifunctional sensing and energy harvesting capabilities under diverse environments, which is essential for AIoT implementation.

Soft Modular Glove with Multimodal Sensing and Augmented Haptic Feedback Enabled by Materials' Multifunctionalities.

Immersive communications rely on smart perception based on diversified and augmented sensing and feedback technologies. However, the increasing of functional components also raises the issue of increased system complexity. Here, we propose a modular soft glove with multimodal sensing and feedback functions by exploring and utilizing the multiple properties of glove materials. With a single design of basic structure, the main functional unit possesses triboelectric-based sensing of static and dynamic contact, vibration, strain, and pneumatic actuation. Additionally, the same unit is also capable of offering pneumatic tactile haptic feedback and electroresistive thermal haptic feedback. Together with a machine learning algorithm, the proposed glove not only performs real-time detection of dexterous hand motion and direct feedback but also realizes intelligent object recognition and augmented feedback, which significantly enhance the communication and perception of more comprehensive information. In general, this glove utilizes a facile designed sensing and feedback device to achieve dual-way and multimodal communication among humans, machines, and the virtual world via smart perceptions.

Augmented tactile-perception and haptic-feedback rings as human-machine interfaces aiming for immersive interactions.

Advancements of virtual reality technology pave the way for developing wearable devices to enable somatosensory sensation, which can bring more comprehensive perception and feedback in the metaverse-based virtual society. Here, we propose augmented tactile-perception and haptic-feedback rings with multimodal sensing and feedback capabilities. This highly integrated ring consists of triboelectric and pyroelectric sensors for tactile and temperature perception, and vibrators and nichrome heaters for vibro- and thermo-haptic feedback. All these components integrated on the ring can be directly driven by a custom wireless platform of low power consumption for wearable/portable scenarios. With voltage integration processing, high-resolution continuous finger motion tracking is achieved via the triboelectric tactile sensor, which also contributes to superior performance in gesture/object recognition with artificial intelligence analysis. By fusing the multimodal sensing and feedback functions, an interactive metaverse platform with cross-space perception capability is successfully achieved, giving people a face-to-face like immersive virtual social experience.

Analysis of Sequential Micromixing Driven by Sinusoidally Shaped Induced-Charge Electroosmotic Flow.

Multi-fluid micromixing, which has rarely been explored, typically represents a highly sought-after technique in on-chip biochemical and biomedical assays. Herein, we propose a novel micromixing approach utilizing induced-charge electroosmosis (ICEO) to implement multicomplex mixing between parallel streams. The variations of ICEO microvortices above a sinusoidally shaped floating electrode (SSFE) are first investigated to better understand the microvortex development and the resultant mixing process within a confined channel. On this basis, a mathematical model of the vortex index is newly developed to predict the mixing degree along the microchannel. The negative exponential distribution obtained between the vortex index and mixing index demonstrates an efficient model to describe the mixing performance without solving the coupled diffusion and momentum equations. Specifically, sufficient mixing with a mixing index higher than 0.9 can be achieved when the vortex index exceeds 51, and the mixing efficiency reaches a plateau at an AC frequency close to 100 Hz. Further, a rectangle floating electrode (RFE) is deposited before SSFE to enhance the controlled sequence for three-fluid mixing. One side fluid can fully mix with the middle fluid with a mixing index of 0.623 above RFE in the first mixing stage and achieve entire-channel mixing with a mixing index of 0.983 above SSFE in the second mixing stage, thereby enabling on-demand sequential mixing. As a proof of concept, this work can provide a robust alternative technique for multi-objective issues and structural design related to mixers.

RPA1 controls chromatin architecture and maintains lipid metabolic homeostasis.

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease, with a prevalence of 25% worldwide. However, the underlying molecular mechanism involved in the development and progression of the NAFLD spectrum remains unclear. Single-stranded DNA-binding protein replication protein A1 (RPA1) participates in DNA replication, recombination, and damage repair. Here, we show that Rpa1+/- mice develop fatty liver disease during aging and in response to a high-fat diet. Liver-specific deletion of Rpa1 results in downregulation of genes related to fatty acid oxidation and impaired fatty acid oxidation, which leads to hepatic steatosis and hepatocellular carcinoma. Mechanistically, RPA1 binds gene regulatory regions, chromatin-remodeling factors, and HNF4A and remodels chromatin architecture, through which RPA1 promotes HNF4A transcriptional activity and fatty acid ß oxidation. Collectively, our data demonstrate that RPA1 is an important regulator of NAFLD through controlling chromatin accessibility.

FAM69C, a kinase critical for synaptic function and memory, is defective in neurodegenerative dementia.

Synapse loss and memory decline are the primary features of neurodegenerative dementia. However, the molecular underpinnings that drive memory loss remain largely unknown. Here, we report that FAM69C is a kinase critically involved in neurodegenerative dementia. Biochemical analyses uncover that FAM69C is a serine/threonine kinase. We generate the Fam69c knockout mice and show by single-cell RNA sequencing that FAM69C deficiency drives cell-type-specific transcriptional changes relevant to synapse dysfunction. Electrophysiological, morphological, and behavioral experiments demonstrate impairments in synaptic plasticity, dendritic spine density, and memory in Fam69c knockout mice, as well as stress-induced neuronal death. Phosphoproteomic characterizations reveal that FAM69C substrates are involved in synaptic structure and function. Finally, reduced levels of FAM69C are found in postmortem brains of Alzheimer's disease patients. Our study demonstrates that FAM69C is a protective regulator of memory and suggests FAM69C as a potential therapeutic target for memory loss in neurodegenerative dementia.

Deubiquitinase OTUD3 regulates metabolism homeostasis in response to nutritional stresses.

The ovarian-tumor-domain-containing deubiquitinases (OTUDs) block ubiquitin-dependent protein degradation and are involved in diverse signaling pathways. We discovered a rare OTUD3 c.863G>A mutation in a family with an early age of onset of diabetes. This mutation reduces the stability and catalytic activity of OTUD3. We next constructed an experiment with Otud3-/- mice and found that they developed worse obesity, dyslipidemia, and insulin resistance than wild-type mice when challenged with a high-fat diet (HFD). We further found that glucose and fatty acids stimulate CREB-binding-protein-dependent OTUD3 acetylation, promoting its nuclear translocation, where OTUD3 regulates various genes involved in glucose and lipid metabolism and oxidative phosphorylation by stabilizing peroxisome-proliferator-activated receptor delta (PPARδ). Moreover, targeting PPARδ using a specific agonist can partially rescue the phenotype of HFD-fed Otud3-/- mice. We propose that OTUD3 is an important regulator of energy metabolism and that the OTUD3 c.863G>A is associated with obesity and a higher risk of diabetes.

Low cost exoskeleton manipulator using bidirectional triboelectric sensors enhanced multiple degree of freedom sensory system.

Rapid developments of robotics and virtual reality technology are raising the requirements of more advanced human-machine interfaces for achieving efficient parallel control. Exoskeleton as an assistive wearable device, usually requires a huge cost and complex data processing to track the multi-dimensional human motions. Alternatively, we propose a triboelectric bi-directional sensor as a universal and cost-effective solution to a customized exoskeleton for monitoring all of the movable joints of the human upper limbs with low power consumption. The corresponding movements, including two DOF rotations of the shoulder, twisting of the wrist, and the bending motions, are detected and utilized for controlling the virtual character and the robotic arm in real-time. Owing to the structural consistency between the exoskeleton and the human body, further kinetic analysis offers additional physical parameters without introducing other types of sensors. This exoskeleton sensory system shows a great potential of being an economic and advanced human-machine interface for supporting the manipulation in both real and virtual worlds, including robotic automation, healthcare, and training applications.

All in One, Self-Powered Bionic Artificial Nerve Based on a Triboelectric Nanogenerator.

Sensory and nerve systems play important role in mediating the interactions with the world. The pursuit of neuromorphic computing has inspired innovations in artificial sensory and nervous systems. Here, an all-in-one, tailorable artificial perception, and transmission nerve (APTN) was developed for mimicking the biological sensory and nervous ability to detect and transmit the location information of mechanical stimulation. The APTN shows excellent reliability with a single triboelectric electrode for the detection of multiple pixels, by employing a gradient thickness dielectric layer and a grid surface structure. The sliding mode is used on the APTN to eliminate the amplitude influence of output signal, such as force, interlayer distance. By tailoring the geometry, an L-shaped APTN is demonstrated for the application of single-electrode bionic artificial nerve for 2D detection. In addition, an APTN based prosthetic arm is also fabricated to biomimetically identify and transmit the stimuli location signal to pattern the feedback. With features of low-cost, easy installation, and good flexibility, the APTN renders as a promising artificial sensory and nervous system for artificial intelligence, human-machine interface, and robotics applications.

Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self-Powered Sensor Enhanced Soft Robotic Manipulator.

Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital-twin-based remote interactive system for advanced robotic-enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction and user experience. To realize such a system, a smart soft robotic manipulator is presented that consists of a triboelectric nanogenerator tactile (T-TENG) and length (L-TENG) sensor, as well as a poly(vinylidene fluoride) (PVDF) pyroelectric temperature sensor. With the aid of machine learning (ML) for data processing, the fusion of the T-TENG and L-TENG sensors can realize the automatic recognition of the grasped objects with the accuracy of 97.143% for 28 different shapes of objects, while the temperature distribution can also be obtained through the pyroelectric sensor. By leveraging the IoT and artificial intelligence (AI) analytics, a digital-twin-based virtual shop is successfully implemented to provide the users with real-time feedback about the details of the product. In general, by offering a more immersive experience in human-machine interactions, the proposed remote interactive system shows the great potential of being the advanced human-machine interface for the applications of the unmanned working space.

An epidermal sEMG tattoo-like patch as a new human-machine interface for patients with loss of voice.

Throat cancer treatment involves surgical removal of the tumor, leaving patients with facial disfigurement as well as temporary or permanent loss of voice. Surface electromyography (sEMG) generated from the jaw contains lots of voice information. However, it is difficult to record because of not only the weakness of the signals but also the steep skin curvature. This paper demonstrates the design of an imperceptible, flexible epidermal sEMG tattoo-like patch with the thickness of less than 10 µm and peeling strength of larger than 1 N cm-1 that exhibits large adhesiveness to complex biological surfaces and is thus capable of sEMG recording for silent speech recognition. When a tester speaks silently, the patch shows excellent performance in recording the sEMG signals from three muscle channels and recognizing those frequently used instructions with high accuracy by using the wavelet decomposition and pattern recognization. The average accuracy of action instructions can reach up to 89.04%, and the average accuracy of emotion instructions is as high as 92.33%. To demonstrate the functionality of tattoo-like patches as a new human-machine interface (HMI) for patients with loss of voice, the intelligent silent speech recognition, voice synthesis, and virtual interaction have been implemented, which are of great importance in helping these patients communicate with people and make life more enjoyable.

Haptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applications.

Human-machine interfaces (HMIs) experience increasing requirements for intuitive and effective manipulation. Current commercialized solutions of glove-based HMI are limited by either detectable motions or the huge cost on fabrication, energy, and computing power. We propose the haptic-feedback smart glove with triboelectric-based finger bending sensors, palm sliding sensor, and piezoelectric mechanical stimulators. The detection of multidirectional bending and sliding events is demonstrated in virtual space using the self-generated triboelectric signals for various degrees of freedom on human hand. We also perform haptic mechanical stimulation via piezoelectric chips to realize the augmented HMI. The smart glove achieves object recognition using machine learning technique, with an accuracy of 96%. Through the integrated demonstration of multidimensional manipulation, haptic feedback, and AI-based object recognition, our glove reveals its potential as a promising solution for low-cost and advanced human-machine interaction, which can benefit diversified areas, including entertainment, home healthcare, sports training, and medical industry.

Machine Learning Glove Using Self-Powered Conductive Superhydrophobic Triboelectric Textile for Gesture Recognition in VR/AR Applications.

The rapid progress of Internet of things (IoT) technology raises an imperative demand on human machine interfaces (HMIs) which provide a critical linkage between human and machines. Using a glove as an intuitive and low-cost HMI can expediently track the motions of human fingers, resulting in a straightforward communication media of human-machine interactions. When combining several triboelectric textile sensors and proper machine learning technique, it has great potential to realize complex gesture recognition with the minimalist-designed glove for the comprehensive control in both real and virtual space. However, humidity or sweat may negatively affect the triboelectric output as well as the textile itself. Hence, in this work, a facile carbon nanotubes/thermoplastic elastomer (CNTs/TPE) coating approach is investigated in detail to achieve superhydrophobicity of the triboelectric textile for performance improvement. With great energy harvesting and human motion sensing capabilities, the glove using the superhydrophobic textile realizes a low-cost and self-powered interface for gesture recognition. By leveraging machine learning technology, various gesture recognition tasks are done in real time by using gestures to achieve highly accurate virtual reality/augmented reality (VR/AR) controls including gun shooting, baseball pitching, and flower arrangement, with minimized effect from sweat during operation.

Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications.

Designing efficient sensors for soft robotics aiming at human machine interaction remains a challenge. Here, we report a smart soft-robotic gripper system based on triboelectric nanogenerator sensors to capture the continuous motion and tactile information for soft gripper. With the special distributed electrodes, the tactile sensor can perceive the contact position and area of external stimuli. The gear-based length sensor with a stretchable strip allows the continuous detection of elongation via the sequential contact of each tooth. The triboelectric sensory information collected during the operation of soft gripper is further trained by support vector machine algorithm to identify diverse objects with an accuracy of 98.1%. Demonstration of digital twin applications, which show the object identification and duplicate robotic manipulation in virtual environment according to the real-time operation of the soft-robotic gripper system, is successfully created for virtual assembly lines and unmanned warehouse applications.

Self-Powered and Self-Functional Cotton Sock Using Piezoelectric and Triboelectric Hybrid Mechanism for Healthcare and Sports Monitoring.

Wearable devices rely on hybrid mechanisms that possess the advantages of establishing a smarter system for healthcare, sports monitoring, and smart home applications. Socks with sensing capabilities can reveal more direct sensory information on the body for longer duration in daily life. However, the limitation of suitable materials for smart textile makes the development of multifunctional socks a major challenge. In this paper, we have developed a self-powered and self-functional sock (S2-sock) to realize diversified functions including energy harvesting and sensing various physiological signals, i.e., gait, contact force, sweat level, etc., by hybrid integrating poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS)-coated fabric triboelectric nanogenerator (TENG) and lead zirconate titanate (PZT) piezoelectric chips. An output power of 1.71 mW is collected from a PEDOT:PSS-coated sock with mild jumping at 2 Hz and load resistance of 59.7 MΩ. The study shows that cotton socks worn daily can potentially be a power source for enabling self-sustained socks comprising wireless transmission modules and integrated circuits in the future. We also investigate the influences of environmental humidity, temperature, and weight variations and verify that our S2-sock can successfully achieve walking pattern recognition and motion tracking for smart home applications. On the basis of the sensor fusion concept, the outputs from TENG and PZT sensors under exercise activities are effectively merged together for quick detection of the sweat level. By leveraging the hybrid S2-sock, we can achieve more functionality in the applications of foot-based energy harvesting and monitoring the diversified physiological signals for healthcare, smart homes, etc.

Triboelectric Self-Powered Wearable Flexible Patch as 3D Motion Control Interface for Robotic Manipulator.

Triboelectric nanogenerators and sensors can be applied as human-machine interfaces to the next generation of intelligent and interactive products, where flexible tactile sensors exhibit great advantages for diversified applications such as robotic control. In this paper, we present a self-powered, flexible, triboelectric sensor (SFTS) patch for finger trajectory sensing and further apply the collected information for robotic control. This innovative sensor consists of flexible and environmentally friendly materials, i. e., starch-based hydrogel, polydimethylsiloxane (PDMS), and silicone rubber. The sensor patch can be divided into a two-dimensional (2D) SFTS for in-plane robotic movement control and a one-dimensional (1D) SFTS for out-of-plane robotic movement control. The 2D-SFTS is designed with a grid structure on top of the sensing surface to track the continuous sliding information on the fingertip, e. g., trajectory, velocity, and acceleration, with four circumjacent starch-based hydrogel PDMS elastomer electrodes. Combining the 2D-SFTS with the 1D-SFTS, three-dimensional (3D) spatial information can be generated and applied to control the 3D motion of a robotic manipulator, and the real-time demonstration is successfully realized. With the facile design and very low-cost materials, the proposed SFTS shows great potential for applications in robotics control, touch screens, and electronic skins.

PTENα regulates mitophagy and maintains mitochondrial quality control.

PTEN plays an important role in tumor suppression, and PTEN family members are involved in multiple biological processes in various subcellular locations. Here we report that PTENα, the first identified PTEN isoform, regulates mitophagy through promotion of PARK2 recruitment to damaged mitochondria. We show that PTENα-deficient mice exhibit accumulation of cardiac mitochondria with structural and functional abnormalities, and PTENα-deficient mouse hearts are more susceptible to injury induced by isoprenaline and ischemia-reperfusion. Mitochondrial clearance by mitophagy is also impaired in PTENα-deficient cardiomyocytes. In addition, we found PTENα physically interacts with the E3 ubiquitin ligase PRKN, which is an important mediator of mitophagy. PTENα binds PRKN through the membrane binding helix in its N-terminus, and promotes PRKN mitochondrial translocation through enhancing PRKN self-association in a phosphatase-independent manner. Loss of PTENα compromises mitochondrial translocation of PRKN and resultant mitophagy following mitochondrial depolarization. We propose that PTENα functions as a mitochondrial quality controller that maintains mitochondrial function and cardiac homeostasis. ABBREVIATIONS: BECN1 beclin 1; CCCP carbonyl cyanide m-chlorophenylhydrazone; FBXO7 F-box protein 7; FS fraction shortening; HSPA1L heat shock protein family A (Hsp70) member 1 like; HW: BW heart weight:body weight ratio; I-R ischemia-reperfusion; ISO isoprenaline; MAP1LC3/LC3 microtubule associated protein 1 light chain 3; MBH membrane binding helix; MFN1 mitofusin 1; MFN2 mitofusin 2; Nam nicotinamide; TMRM tetramethylrhodamine ethyl ester; WGA wheat germ agglutinin.