Photothermally Activated Artificial Neuromorphic Synapses.

Biological nervous systems rely on the coordination of billions of neurons with complex, dynamic connectivity to enable the ability to process information and form memories. In turn, artificial intelligence and neuromorphic computing platforms have sought to mimic biological cognition through software-based neural networks and hardware demonstrations utilizing memristive circuitry with fixed dynamics. To incorporate the advantages of tunable dynamic software implementations of neural networks into hardware, we develop a proof-of-concept artificial synapse with adaptable resistivity. This synapse leverages the photothermally induced local phase transition of VO2 thin films by temporally modulated laser pulses. Such a process quickly modifies the conductivity of the film site-selectively by a factor of 500 to "activate" these neurons and store "memory" by applying varying bias voltages to induce self-sustained Joule heating between electrodes after activation with a laser. These synapses are demonstrated to undergo a complete heating and cooling cycle in less than 120 ns.

Light-narrowed parametric resonance magnetometer with the fundamental sensitivity beyond the spin-exchange limit.

In the field of biomagnetic measurements, one of the most important recent challenges is to perform measurements in a magnetically unshielded environment. This first requires that atomic magnetometers can operate in a finite magnetic field, and have enough high sensitivity. To meet these requirements, we develop a light-narrowed parametric resonance (LPR) magnetometer. By adding a modulation magnetic field to the large longitudinal magnetic field, our LPR magnetometer can measure small transverse magnetic fields with an intrinsic sensitivity of 3.5 fT/Hz1/2 in a longitudinal magnetic field of µT range. Moreover, we have also demonstrated that in contrast to the previous light-narrowed scalar magnetometers, our LPR magnetometer has the potential to achieve higher sensitivity. Because in our case spin-exchange relaxation suppression by using light narrowing can lead to an improvement of fundamental sensitivity limit regardless of which quantum noise is dominant, and hence the fundamental sensitivity is no longer limited by spin-exchange, and approaches the fundamental limit set by the spin-exchange and spin-destruction cross sections.

Stabilization of the angiotensin-(1-7) receptor Mas through interaction with PSD95.

The functions and signalling mechanisms of the Ang-(1-7) [angiotensin-(1-7)] receptor Mas have been studied extensively. However, less attention has been paid to the intracellular regulation of Mas protein. In the present study, PSD95 (postsynaptic density 95), a novel binding protein of Mas receptor, was identified, and their association was characterized further. Mas specifically interacts with PDZ1-2, but not the PDZ3, domain of PSD95 via Mas-CT (Mas C-terminus), and the last four amino acids [ETVV (Glu-Thr-Val-Val)] of Mas-CT were determined to be essential for this interaction, as shown by GST pull-down, co-immunoprecipitation and confocal co-localization experiments. Gain-of-function and loss-of-function studies indicated that PSD95 enhanced Mas protein expression by increasing the stabilization of the receptor. Mas degradation was robustly inhibited by the proteasome inhibitor MG132 in time- and dose-dependent manners, and the expression of PSD95 impaired Mas ubiquitination, indicating that the PSD95-Mas association inhibits Mas receptor degradation via the ubiquitin-proteasome proteolytic pathway. These findings reveal a novel mechanism of Mas receptor regulation by which its expression is modulated at the post-translational level by ubiquitination, and clarify the role of PSD95, which binds directly to Mas, blocking the ubiquitination and subsequent degradation of the receptor via the ubiquitin-proteasome proteolytic pathway.

A user-friendly visual brain-computer interface based on high-frequency steady-state visual evoked fields recorded by OPM-MEG.

Objective. Magnetoencephalography (MEG) shares a comparable time resolution with electroencephalography. However, MEG excels in spatial resolution, enabling it to capture even the subtlest and weakest brain signals for brain-computer interfaces (BCIs). Leveraging MEG's capabilities, specifically with optically pumped magnetometers (OPM-MEG), proves to be a promising avenue for advancing MEG-BCIs, owing to its exceptional sensitivity and portability. This study harnesses the power of high-frequency steady-state visual evoked fields (SSVEFs) to build an MEG-BCI system that is flickering-imperceptible, user-friendly, and highly accurate.Approach.We have constructed a nine-command BCI that operates on high-frequency SSVEF (58-62 Hz with a 0.5 Hz interval) stimulation. We achieved this by placing the light source inside and outside the magnetic shielding room, ensuring compliance with non-magnetic and visual stimulus presentation requirements. Five participants took part in offline experiments, during which we collected six-channel multi-dimensional MEG signals along both the vertical (Z-axis) and tangential (Y-axis) components. Our approach leveraged the ensemble task-related component analysis algorithm for SSVEF identification and system performance evaluation.Main Results.The offline average accuracy of our proposed system reached an impressive 92.98% when considering multi-dimensional conjoint analysis using data from both theZandYaxes. Our method achieved a theoretical average information transfer rate (ITR) of 58.36 bits min-1with a data length of 0.7 s, and the highest individual ITR reached an impressive 63.75 bits min-1.Significance.This study marks the first exploration of high-frequency SSVEF-BCI based on OPM-MEG. These results underscore the potential and feasibility of MEG in detecting subtle brain signals, offering both theoretical insights and practical value in advancing the development and application of MEG in BCI systems.

Ion diffusion retarded by diverging chemical susceptibility.

For first-order phase transitions, the second derivatives of Gibbs free energy (specific heat and compressibility) diverge at the transition point, resulting in an effect known as super-elasticity along the pressure axis, or super-thermicity along the temperature axis. Here we report a chemical analogy of these singularity effects along the atomic doping axis, where the second derivative of Gibbs free energy (chemical susceptibility) diverges at the transition point, leading to an anomalously high energy barrier for dopant diffusion in co-existing phases, an effect we coin as super-susceptibility. The effect is realized in hydrogen diffusion in vanadium dioxide (VO2) with a metal-insulator transition (MIT). We show that hydrogen faces three times higher energy barrier and over one order of magnitude lower diffusivity when it diffuses across a metal-insulator domain wall in VO2. The additional energy barrier is attributed to a volumetric energy penalty that the diffusers need to pay for the reduction of latent heat. The super-susceptibility and resultant retarded atomic diffusion are expected to exist universally in all phase transformations where the transformation temperature is coupled to chemical composition, and inspires new ways to engineer dopant diffusion in phase-coexisting material systems.

Machine learning-based predictive and risk analysis using real-world data with blood biomarkers for hepatitis B patients in the malignant progression of hepatocellular carcinoma.

Hepatitis B Virus (HBV) infection may lead to various liver diseases such as cirrhosis, end-stage liver complications, and Hepatocellular carcinoma (HCC). Patients with existing cirrhosis or severe fibrosis have an increased chance of developing HCC. Consequently, lifetime observation is currently advised. This study gathered real-world electronic health record (EHR) data from the China Registry of Hepatitis B (CR-HepB) database. A collection of 396 patients with HBV infection at different stages were obtained, including 1) patients with a sustained virological response (SVR), 2) patients with HBV chronic infection and without further development, 3) patients with cirrhosis, and 4) patients with HCC. Each patient has been monitored periodically, yielding multiple visit records, each is described using forty blood biomarkers. These records can be utilized to train predictive models. Specifically, we develop three machine learning (ML)-based models for three learning tasks, including 1) an SVR risk model for HBV patients via a survival analysis model, 2) a risk model to encode the progression from HBV, cirrhosis and HCC using dimension reduction and clustering techniques, and 3) a classifier to detect HCC using the visit records with high accuracy (over 95%). Our study shows the potential of offering a comprehensive understanding of HBV progression via predictive analysis and identifies the most indicative blood biomarkers, which may serve as biomarkers that can be used for immunotherapy.

PF-PLC micelles ameliorate cholestatic liver injury via regulating TLR4/MyD88/NF-κB and PXR/CAR/UGT1A1 signaling pathways in EE-induced rats.

Paeoniflorin (PF) has a certain therapeutic effect on cholestasis liver injury. To further improve the bioavailability of PF and play its pharmacological role in liver protection, PF-phospholipid complex micelles (PF-PLC micelles) were prepared based on our previous research on PF-PLC. The protective effects of PF and PF-PLC micelles on cholestasis liver injury induced by 17α-ethynylestradiol (EE) were compared, and the possible mechanisms were further explored. Herein, we showed that PF-PLC micelles effectively improved liver function, alleviated liver pathological damage, and localized infiltration of inflammatory cells. Mechanism studies indicated that PF-PLC micelles treatment could suppress the TLR4/MyD88/NF-κB pathway, and further reduce the levels of pro-inflammatory factors. Meanwhile, our experimental results demonstrated that the beneficial effect of PF-PLC micelles on EE-induced cholestasis may be achieved by the upregulation of nuclear receptors and metabolic enzymes (PXR/CAR/UGT1A1). All these results indicate that PF-PLC micelles have great potential in the treatment of cholestatic liver disease.

Anchoring Pt Single Atoms on Te Nanowires for Plasmon-Enhanced Dehydrogenation of Formic Acid at Room Temperature.

Formic acid (HCOOH), as a promising hydrogen carrier, is renewable, safe, and nontoxic. However, the catalytic dehydrogenation of HCOOH is typically conducted at elevated temperature. Here, HCOOH decomposition is successfully achieved for hydrogen production on the developed Pt single atoms modified Te nanowires with the Pt mass loading of 1.1% (1.1%Pt/Te) at room temperature via a plasmon-enhanced catalytic process. Impressively, 1.1%Pt/Te delivers 100% selectivity for hydrogen and the highest turnover frequency number of 3070 h-1 at 25 °C, which is significantly higher than that of Pt single atoms and Pt nanoclusters coloaded Te nanowires, Pt nanocrystals decorated Te nanowires, and commercial Pt/C. A plasmonic hot-electron driven mechanism rather than photothermal effect domains the enhancement of catalytic activity for 1.1%Pt/Te under light. The transformation of HCOO* to CO2 δ -* on Pt atoms is proved to be the rate-determining step by further mechanistic studies. 1.1%Pt/Te exhibits tremendous catalytic activity toward the decomposition of HCOOH owing to its plasmonic hot-electron driven mechanism, which efficiently stimulates the rate-determining step. In addition, hot electrons generated by the Te atoms nearby Pt single atoms are regarded to directly inject into the reactants adsorbed and activated on Pt single atoms.